In this study, we evaluated the physicochemical and microbial qualities of source and stored household waters in some communities in Southwestern Nigeria using standard methods. Compared parameters include physicochemical constituents; Temperature (T), pH, Total Dissolved Solids (TDS), Total Hardness (TH), Biological Oxygen Demand (BOD), Magnesium ion (Mg²⁺) and Calcium ion (Ca²⁺) and microbiological parameters included Total Coliform Counts (TC), Faecal Coliform Counts (FC), Fungal Counts (Fung C), Heterotrophic Plate Counts (HPC). Comparing Stored and Source samples, the mean values of some physicochemical parameters of most of the stored water samples significantly (P<0.05) exceeded that of Sources and ranged in the following order: T (15.3±0.3^oC - 28.3±0.5^oC), pH (6.4±0.1 - 7.6±0.1), TDS (192.1±11.1 ppm - 473.7±27.9 ppm), TH (10.6±1.7 mg/L - 248.6±18.6 mg/L), BOD (0.5±0.0 mg/L - 3.2±0.3 mg/L), Mg²⁺ (6.5±2.4 mg/L - 29.1±3.2 mg/L) and Ca²⁺ (6.5±2.4 mg/L - 51.6±4.4 mg/L). The mean microbial counts obtained from microbial comparison of different points (Stored and Source) of collection showed that most of the stored water had counts significantly exceeding (P<0.05) those of the source water samples (cfu/100 mL) which ranged as follows: TC (3.1±1.5 - 156.8±42.9), FC (0.0±0.0 - 64.3±14.2) and HPC (47.8±12.1 - 266.1±12.2) across all sampled communities. Also, the predominant isolates recovered from the samples were identified as Escherichia coli, Klebsiella pneumonia, Pseudomonas aeruginosa, Enterobacter aerogenes, Aspergillus spp, Mucor spp, Rhizopus spp and Candida spp. The presence of these pathogenic and potentially pathogenic organisms in the waters and the high counts of the indicator organisms suggest the waters to be a threat to public health.

Two desirable functions of healthy soil are nutrient cycling and pest suppression. We review recent literature on the contributions of soil microarthropods to soil health through their intersecting roles in decomposition and nutrient cycling and direct and indirect suppression of plant pests. Microarthropods can impact soil and plant health directly by feeding on pest organisms or serving as alternate prey for larger predatory arthropods, and indirectly, by mediating the ability of crop plants to resist or tolerate insect pests and diseases through interactions with the decomposition food web in support of plant nutrition. Soil fauna, including microarthropods, are key regulators of decomposition at local scales but their role at larger scales is unresolved. Future research priorities include the incorporation of multi-channel omnivory into food web modeling and understanding the vulnerability of our soil carbon to increased global temperatures.

Both Stevens Johnson Syndrome (SJS) and toxic epidermal necrolysis (TEN) are main injurious cutaneous medication reactions that mostly affect the epidermis and mucus membranes. TEN and SJS affecting nearly 1 or 2/1,000,000 people per year, and can recognized as medical crises since they may be deadly. Mucocutaneous discomfort, hemorrhagic erosions, erythema, and more or less severe epidermal separation that appear as ulcer and patches of dermic loss are their defining characteristics. The sole difference between TEN and SJS at this time is the degree of skin detachment, making them two extremes of a spectrum of severe cutaneous adverse drug reactions (cADRs). In the majority of cases, drugs are considered as the principal reason of SJS/TEN, but herpes simplex virus and Mycoplasma pneumoniae infections are also recognized causes, along with lesser number of cases in which the cause is still unknown. Among the drugs with a "high" likelihood of producing TEN/SJS are carbamazepine (CBZ), trimethoprim-sulfamethoxazole, phenytoin, aminopenicillins, allopurinol, cephalosporins, other sulfonamide antibiotics, quinolones, phenobarbital, and NSAIDs of the oxicam variety. There is strong genetic evidence for SJS and TEN in Han Chinese due to the substantial association between the human leukocyte antigen (HLA-B*1502) and SJS brought on by CBZ. The diagnosis is made mostly based on clinical symptoms and the histological study of a dermal biopsy. Pemphigus vulgaris, bullous pemphigoid, linear IgA dermatosis, paraneoplastic pemphigus, disseminated fixed bullous drug eruption, acute generalized exanthematous pustulosis (AGEP), and staphylococcal scalded skin syndrome (SSSS) are among the differential diagnoses. The management of patients with SJS/TEN is complicated by the high risk of mortality, necessitating early diagnosis, estimation of the SCORTEN prognosis, identification and discontinuation of the causative drug, specialized supportive care, and high-dose injectable Ig therapeutic interventions. The reported fatality rates for SJS are 1-5% on average and 25-35% for TEN; it can be even higher in patients who are elderly or who have a significant amount of epidermal detachment on their skin. More than 50% of TEN patients who survive the disease experience long-term consequences.

Diffuse large B cell lymphoma (DLBCL) is curable with chemoimmunotherapy in ~65% of patients. One of the hallmarks of the pathogenesis and resistance to therapy in DLBCL is inhibition of apoptosis, which allows malignant cells to survive and acquire further alterations. Inhibition of apoptosis can be the result of genetic events inhibiting the intrinsic or extrinsic apoptotic pathways, as well as their modulators, such as the inhibitor of apoptosis proteins, P53, and components of the NF-kB pathway. Mechanisms of dysregulation include upregulation of anti-apoptotic proteins and downregulation of pro-apoptotic proteins via point mutations, amplifications, deletions, translocations, and influences of other proteins. Understanding the factors contributing to resistance to apoptosis in DLBCL is crucial in order to be able to develop targeted therapies that could improve outcomes by restoring apoptosis in malignant cells. This review describes the genetic events inhibiting apoptosis in DLBCL, provides a perspective of their interactions in lymphomagenesis, and discuss their implication for the future of DLBCL therapy.

Although fragility fractures, osteoporosis, sarcopenia and frailty are becoming more prevalent in our aging society the treatment options are limited and preventative strategies are needed. Despite magnesium being integral bone and muscle physiology the relationship between dietary magnesium and skeletal muscle and bone health has not been investigated concurrently before. We analysed cross-sectional associations between dietary magnesium and skeletal muscle mass (as fat free mass – FFM), grip strength and bone density (BMD) in 156,575 men and women aged 39-72 years from the UK Biobank cohort. FFM was measured with bioelectrical impedance and expressed as the percentage of body weight (FFM%) or divided by body mass index (FFM_BMI). Adjusted mean grip strength, FFM%, FFM_BMI, and BMD were calculated according quintiles of dietary magnesium, correcting for covariates. Significant inter-quintile differences across intakes of magnesium existed in men and women respectively of 1.1% and 2.4% for grip strength, 3.0% and 3.6% for FFM%, 5.1% and 5.5% for FFM_BMI, and 2.9% and 0.9% for BMD. These associations are as great or greater than annual measured losses of these musculoskeletal outcomes indicating potential clinical significance. Our study suggests that dietary magnesium may play a role in musculoskeletal health and have relevance for population prevention strategies for sarcopenia, osteoporosis and fractures.

Developing new antibiotics poses a significant challenge in the fight against antimicrobial resistance (AMR), a critical global health threat responsible for approximately 5 million deaths annually. Finding new classes of antibiotics that are safe, have acceptable pharmacokinetic properties, and are appropriately active against pathogens is a lengthy and expensive process. Therefore, high-throughput platforms are needed to screen large libraries of synthetic and natural compounds. In this review, we present bacterial cytological profiling (BCP) as a rapid, scalable, and cost-effective method for identifying the mechanisms of action of antibiotics, offering a promising tool for combating AMR and drug discovery. We present the application of BCP for different bacterial organisms and different classes of antibiotics and discuss BCP's advantages, limitations, and potential improvements. Furthermore, we highlight the studies that have utilized BCP to investigate pathogens listed in the Bacterial Priority Pathogens List 2024 and we identify the pathogens whose cytological profiles are missing. Lastly, we explore the most recent artificial intelligence and deep learning techniques that could enhance the analysis of data generated by BCP, potentially advancing our understanding of antibiotic resistance mechanisms and the discovery of novel druggable pathways.

Uterine fibroid (UF) is a tumour in some parts of the uterus, which introduces health challenges or death due to failed surgery among women globally. This study was designed to ascertain the involvement of micro-nutrients, inflammation, and antioxidant enzymes in the UF development to gain further insights and provide a strategy for managing the disease. One hundred ninety reproductive-aged women were recruited and classified equally into case and control subjects. The supernatant obtained from excised tissues from the fibroid and the normal samples from the adjacent myometrium were assessed for the selected biochemical parameters with standard methods. The levels of vitamin A and sodium between 26-35 years; vitamins D, E, zinc, and selenium between 46-55 years; and vitamin E at 56 years and above significantly decreased (p&lt;0.05). Interleukin-2 (IL-2) level significantly increased (P &lt; 0.05) among the case between 36-45 years. An increase in the activity of glutathione-s-transferase and the reduction in glutathione peroxidase activity and vitamin A level in the uterus between 26-45 years were the most pronounced significant findings (p&lt;0.05) recorded. Prolonged vitamin A deficiency coupled with excess sodium salts facilitating inflammation induced by IL-2 are critical factors for UF development.

In 2023, the Bureau of Land Management (BLM) estimated that there were 68,928 mustangs living on United States public lands in 10 western states. The agency uses Appropriate Management Levels to determine the number of mustangs who need to be removed from the land. Once removed and processed, mustangs are sent to adoptions or sales events or retained in short-or long-term holding facilities. Adoptions and sales are the leading avenues for rehoming mustangs; however, the number of horses the BLM can place fluctuates annually and never approaches the greater number removed from the range. To explore opportunities for increasing the number of mustang adoptions, we conducted in-depth interviews with 23 horse trainers located on the U.S. East Coast, asking about participants’ training programs, relationships with horses, perceptions of mustangs, and challenges that mustangs face in the dressage and eventing industries. Participants had varying experiences with mustangs; however, all were willing to work with a mustang in some capacity. Participants voiced the need for more satellite adoption locations on the East Coast to decrease barriers to acquiring a mustang, notably cost and time, and for expanding existing training programs to include eventing and dressage.

Lifelong learning has been integral to advancement of the nutrition and dietetics profession and its practitioners. Both the Commission on Dietetic Registration (CDR) and the Academy of Nutrition and Dietetics (Academy) advocate for continuous skill development and professional growth. Responding to evolving environmental trends and diverse practice perspectives, CDR joined the Joint Accreditation for Interprofessional Continuing Education organization in 2020 and CDR is transforming its own continuing professional education (CPE) requirements and prior approval program. This paper, a historical perspective and current state review, chronicles past and recent developments in nutrition and dietetics CPE, including opportunities for reflective learning and interprofessional continuing education (IPCE). Also explored are the establishment and expansion of the Joint Accreditation organization and its standards, as well as applicable case examples. Additionally, the paper outlines CDR’s and the Academy's strategies to advance inclusion, diversity, equity, and access (IDEA) within the profession and identifies how CPE advancements may facilitate accessible and equitable CPE for an increasingly diverse membership of practitioners. Nutrition and dietetics professionals stand to benefit from a more comprehensive understanding of CPE changes and the opportunities they may bring to the future of the profession.

Recent advancements in vascular organoid (VO) and vessel-on-chip (VoC) technologies have revolutionized our approach to studying cardiovascular diseases (CVDs), offering unprecedented insights through more physiologically relevant models. VOs generated from human pluripotent stem cells exhibit remarkable self-organization capabilities, forming complex three-dimensional structures that closely mimic human blood vessel architecture and function, while VoCs engineered with groundbreaking microfluidic systems that meticulously recreate the physical and functional attributes of blood vessels. These innovative constructs serve as powerful tools for investigating vascular development, disease progression, and therapeutic efficacy. By enabling the creation of patient-specific VOs and VoCs, they pave the way for personalized medicine approaches, allowing researchers to delve into genetic variations, intricate cellular interactions, and dynamic processes with exceptional resolution. The synergy between VOs and VoCs with cutting-edge technologies such as single-cell sequencing and high-resolution imaging has further amplified their potential, unveiling novel mechanisms underlying CVDs and identifying promising therapeutic targets. Herein, we summarize different types of VOs and VoCs and present an extensive overview on the generation and applications of VOs and VoCs in CVDs. We will also highlight clinical and translational challenges and future perspectives around VOs and VoCs.

In a world filled with uncertainties, Ebb&Flow emerged as a story of convergence, intertwining dementia research, caregiving, and artistic exploration into a tripartite creative knowledge exchange. This study delves into the complexities of uncertainty in dementia care and research through a collaborative project involving artists, researchers, carers, and individuals with lived experience of dementia. Initiated by the Trellis:Arbor program, Ebb&Flow sought to co-created a human space addressing the multifaceted nature of uncertainty. The sea, with its unpredictable nature, served as a guiding metaphor for the project, reflecting the unpredictability of dementia and life. Over three months, through paintings, writings, and digital mediums, participants documented the changing emotions, challenges, and discoveries they encountered daily. The project fostered an environment where uncertainties were openly discussed, building supportive and resilient communities through participatory co-creation and methodological exchange. Key activities included a digital logbook, allowing participants to document and share their experiences of uncertainty, and the creation of the Ebb&Flow card deck—a compilation of personal stories and insights that serve as a legacy of shared experiences. Each card facilitated dialogue, understanding, and connection, bridging gaps between those affected by dementia and the broader community. The project culminated in a final exhibition and sharing event, where participants, researchers, and the public celebrated the journey's outcomes through stories and artworks. Throughout this journey, we observed that embracing uncertainty and fostering empathy through creative collaboration profoundly impacted participants, enhancing empathy and resilience. This project underscores the transformative potential of integrating artistic practices with scientific research to address the emotional and psychological burdens of dementia and research environments. Ebb&Flow demonstrates that even in the face of the unknown, a united community can find strength, solace, and understanding, highlighting the power and beauty of unity in exploring and expressing the multifaceted experiences of dementia and life.

In 2011 over 1.7 million people were hospitalized because of a fragility fracture, and direct costs associated with osteoporosis treatment exceeded 70 billion dollars in the United States. Failure to reach and maintain optimal peak bone mass during adulthood is a critical factor in determining fragility fracture risk later in life. Physical activity is a widely accessible, low cost, and highly modifiable contributor to bone health. Here, we will review the evidence linking exercise and physical activity to bone health in women. Bone structure and quality will be discussed, especially in the context of clinical diagnosis of osteoporosis. We will review the mechanisms governing bone metabolism in the context of physical activity and exercise. Questions such as, when during life is exercise most effective, and what specific types of exercises improve bone health, will be addressed. Finally, we will discuss some emerging areas of research on this topic, and will summarize areas of need and opportunity.

In the realm of metal steel and iron manufacturing, there is a constant drive to optimize production efficiency and enhance the quality of the final products. This abstract explores a paradigm shift in this industry through the utilization of Computational Fluid Dynamics (CFD) as a powerful tool for achieving these goals .The study focuses on various critical aspects of the manufacturing process. Firstly, it delves into three-phase processes such as slag and gas entrainment in liquid steel, which have a significant impact on the overall product quality. Understanding and optimizing these processes is crucial to ensure the desired chemical composition and physical properties of the final metal.The abstract investigates the role of CFD in vacuum degassing, a process that plays a pivotal role in removing impurities, such as hydrogen and oxygen, from the liquid steel. By leveraging CFD to simulate and analyze the fluid flow patterns, researchers and engineers can design more efficient vacuum degassing systems, leading to improved product purity and reduced waste.Another crucial aspect explored in this abstract is the alloy melt and mixing process. By employing CFD simulations, researchers can gain insights into the movement of different alloy components and optimize their distribution within the melt. This aids in achieving the desired alloy composition, ensuring uniformity, and enhancing the mechanical properties of the final product.In addition, the study delves into the movement and flotation of inclusions, which are unwanted impurities present in the metal. CFD can be utilized to model and analyze the behavior of these inclusions, enabling engineers to design efficient strategies for their removal, thereby enhancing the purity and integrity of the final product.Moreover, the abstract considers the impact of melt temperature losses, which can occur during different stages of the manufacturing process. By employing CFD, it becomes possible to understand and mitigate these temperature losses, leading to improved energy efficiency and better control over the manufacturing parameters.Part 1 of this abstract critically evaluates the use of CFD in iron making, analyzing its benefits and limitations. It highlights how CFD can aid in process optimization, improving the understanding of complex phenomena involved in iron making, and ultimately leading to enhanced production efficiency.Part 2 focuses on the application of CFD in steel making and steel operation. It explores the fluid flow dynamics during different stages of steel production, including refining, casting, and rolling. By leveraging CFD, engineers can optimize these processes, leading to improved product quality, reduced defects, and increased productivity.This abstract demonstrates the transformative potential of Computational Fluid Dynamics in metal, steel, and iron manufacturing. By utilizing CFD as a tool to model and analyze complex fluid flow phenomena, researchers and engineers can revolutionize the production process, maximizing efficiency, and ensuring high-quality end products.

Driven by mounting environmental apprehensions stemming from the over dependence on fossil fuels in energy and transportation sectors, extensive exploration into alternative energy sources, particularly biomass, has stimulated profound research on harnessing the potential of computational and mathematical techniques. This comprehensive survey delves into optimal models and strategies, unveiling their pivotal role in the design of biomass gasification processes.of hydrogen through biomass gasification. In this study, we aim to provide a comprehensive overview of the computational and mathematical techniques employed in optimizing biomass gasification processes, with a specific focus on enhancing hydrogen yield. Through an extensive literature review, various models and strategies will be examined, including thermodynamic analysis, kinetic modeling, reactor design, and process optimization. By uncovering the power of these techniques, we aim to contribute to the advancement of sustainable and efficient biomass utilization for the hydrogen-based future economy.This paper aims to provide an updated and comprehensive coverage of the investigations conducted on the potential of producing hydrogen from biomass through gasification. To achieve this, we incorporate the latest works that have utilized numerical modeling, simulation, optimization techniques, process heat integration, and co-generation in their studies. By encompassing these aspects, we aim to offer a broader and more in-depth re-appraisal of the subject matter. This will ensure that readers gain a holistic understanding of the advances made in the field and the potential for sustainable hydrogen production of biomass gasification.Through a meticulous re-appraisal and analysis of each subject, we can identify their respective strengths and areas that require further research effort. By thoroughly examining numerical modeling, simulation, optimization techniques, process heat integration, and co-generation, we can assess their effectiveness and applicability in the context of biomass gasification for hydrogen production. This analysis shed light on the areas where these techniques excel, as well as pinpoint limitations or gaps in current understanding. By identifying these areas, we can highlight the need for further research and development, enabling us to make significant advancements in biomass gasification processes and pave the way for a sustainable and efficient hydrogen-based future economy..

Artificial Intelligence (AI) is revolutionizing head and neck cancer (HNC) care by providing innovative tools that enhance diagnostic accuracy and personalize treatment strategies. This review highlights the advancements in AI technologies, including deep learning and natural language processing, and their applications in HNC. The integration of AI with imaging techniques, genomics, and electronic health records is explored, emphasizing its role in early detection, biomarker discovery, and treatment planning. Despite noticeable progress, challenges such as data quality, algorithmic bias, and the need for interdisciplinary collaboration remain. Emerging innovations like explainable AI, AI-powered robotics, and real-time monitoring systems are poised to further advance the field. Addressing these challenges and fostering collaboration among AI experts, clinicians, and researchers is crucial for developing equitable and effective AI applications. The future of AI in HNC holds significant promise, offering potential breakthroughs in diagnostics, personalized therapies, and improved patient outcomes.

Summer annual species are the most widely grown crops in the Upper Midwest, but reliance on a summer annual system has led to excessive soil and nutrient loss when crops are not present. Integrating winter rye (Secale cereale L.), known for its hardiness and environmental benefits, into the rotation can address these issues. However, there's limited understanding of the phenotypic diversity in winter rye during key growth stages that overlap with the typical planting dates for corn (Zea mays L.), soybean [Glycine max (L.) Merr], and late-planted crops like dry bean (Phaseolus vulgaris L.). Thus, the objectives of this study were to evaluate changes in biomass accumulation and quality of winter rye and triticale (x Triticosecale Wittmack) cultivars at three growth stages. Twenty cultivars were assessed over the 2014-2015 and 2015-2016 growing seasons across three environments in Minnesota. Winter rye and triticale were harvested for biomass at the tillering, booting, and soft dough growth stages and rye biomass yield and quality [i.e., crude protein, neutral detergent fiber (NDF), and 48-hour digestibility (NDFD)] were determined following harvest. Overall, there was little variation in each parameter among the cultivars within a location and growth stage. NDFD had some variation at the soft dough stage where digestibility ranged from 273 to 324 g kg-1 at the Crookston site and 332 to 406 g kg-1 at the St. Paul site. The lack of difference between cultivars indicates a wide range of choice when selecting a winter rye cultivar.

The rising challenge of polyethylene terephthalate (PET) waste necessitates efficient collection methods to mitigate environmental impacts. The Analytic Hierarchy Process (AHP) is one of the Multi-Criteria Decision Analysis (MCDA) approaches utilized in this study. The Technique for Order of Preference by Similarity to the Ideal Solution (TOPSIS) was used to rank each alternative according to the objective weight that AHP had produced. Also, sensitivity analysis was performed to determine how robust the findings were when considering equal weights and entropy weights to maximize PET waste collection techniques. The alternative achieved the objective of obtaining the best collection method, Threshold Plastic Bottle Waste Collection (Tpbw), out of all the three alternatives considered. Another MCDA approach, VIseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR), was used to compare the results and validate the ranking result achieved by the TOPSIS method. The VIKOR technique's validation of the TOPSIS approach showed that the outcomes were highly consistent. Data for the study were gathered from the archives of waste management companies on possible practices of plastic waste collection addressing costs, environmental impacts, social acceptance, feasibility, and efficiency. The findings provide a prioritized framework for enhancing PET waste collection strategies, contributing to sustainable waste management. Many criteria are considered when deciding the best collecting method for PET waste recycling, making it challenging. By using criteria importance, multi-criteria decision analysis (MCDA) was applied in this study, and the objective weight of the criteria was determined using the analytic hierarchy process (AHP). The five criteria considered in this study are Initial investment cost, Operational cost, Transportation cost, Environmental risk, Employment potential, and the objective weights allocated to them. AHP results 0.4952, 0.1997, 0.1565, 0.0870, and 0.0616 are respectively determined.

This study explored differences in student-athletes’ symptoms of depression, anxiety, and stress pre- to post-COVID-19 pandemic. The WHO reported a 25% increase in depression and anxiety rates worldwide with young people disproportionately affected. Student-athletes face many stressors related to their sporting and academic feats but what is not known is how the COVID-19 pandemic affected their experiences of mental illness. A multiple cohort cross-sectional study design was employed, and data collected using physical and online surveys. Participants (M age = 19.98 years, SD = 1.50) were recruited from UK universities (N = 807; 427 pre-pandemic cohort, 380 post-pandemic cohort). Results revealed statistically significant differences in mean depression, anxiety, and stress scores between cohorts. Scores for the post-pandemic cohort were significantly higher than pre-pandemic, suggesting a worsening of symptom severity. Distributions of student-athletes across categories of symptom severity also worsened for depressive and anxiety symptoms post-pandemic and were skewed towards more severe categories. Symptoms of de-pression, anxiety, and stress were a concern pre-pandemic. Rates are higher in the post-pandemic cohort, suggesting a worsening of symptoms. This data adds to evidence on student-athletes’ symptoms of mental illness by exploring a UK sample and comparing scores pre- and post-pandemic.

Epidermal Growth Factor Receptor (EGFR) tyrosine kinase is a cell surface receptor whose overexpression has been associated with different types of cancers including brain cancer (glioblastoma multiforme). The ability of the extract of Scutellaria baicalensis to inhibit the proliferation of malignant glioma cells have been reported. Thus, in this study we report the identification of 307 bioactive constituents responsible for the anti-glioblastoma multiforme effect from S. baicalensis using in silico studies such as molecular docking, binding free energy calculations, pharmacophore modelling, induced-fit docking, gene enrichment analysis, molecular dynamic simulations and ADMET predictions. A total of 307 chemical constituents of S. baicalensis were screened and the top 10 scoring compounds indicated different binding affinities ranging from -9.010 to -6.427 kcal/mol towards the EGFR tyrosine kinase; Ganhuangenin, 5,7,2',5'-tetrahydroxyflavone, (2R)-2-(2,6-dihydroxyphenyl)-3,4-dihydro-2H-chromene-5,7-diol, and tenaxin I possess higher binding affinities (-9.010 to -8.649 kcal/mol) compared to the standard ligand, erlotinib having -8.539 kcal/mol. The compounds interacted with amino acids of clinical importance such as MET 769, GLU 738, THR 766 via H-bond. The structural features involved in the interaction with the target were mostly two aromatic rings, H-bond donors and acceptors and some hydrophobic interactions which varies between the ligands. Better docking scores in the induced-fit docking further validates the inhibitory potential of the compounds against the flexible protein. All the top-scoring ligands from S. baicalensis had zero Lipinski violation and also obeyed other drug-likeness rules by Ghose, Veber, Egan, and Muegge with the exception of breviscapine. Interestingly, all the compounds are not likely to be hepatotoxic, mutagenic, or cytogenic, making them potentially safe as anti-cancer agents.

Using a randomized, double-blinded, placebo-controlled, parallel group design, this investigation determined if the combination of 2-weeks flavonoid supplementation (329 mg/day, quercetin, anthocyanins, flavan-3-ols mixture) and a 45-minute walking bout (62.2±0.9% VO_2max) enhanced the translocation of gut-derived phenolics into circulation in a group of walkers (N = 77). The walkers (flavonoid, placebo groups) were randomized to either sit or walk briskly on treadmills for 45 minutes (thus four groups: placebo-sit, placebo-walk, flavonoid-sit, flavonoid-walk). A comparator group of runners (N = 19) ingested a double flavonoid dose for 2 weeks (658 mg/day) and ran for 2.5 h (69.2±1.2% VO_2max). Four blood samples were collected (pre- and post-supplementation, immediately-post- and 24-h post-exercise/rest). Of the 76 metabolites detected in this targeted analysis, 15 increased after the 2.5-h run, and when grouped were also elevated post-exercise (versus placebo-sit) for the placebo- and flavonoid-walking groups (P < 0.05). A secondary analysis showed that pre-study plasma concentrations of gut-derived phenolics in the runners were 40% higher compared to walkers (P = 0.031). These data indicate that acute exercise bouts (brisk walking, intensive running) are linked to an increased translocation of gut-derived phenolics into circulation, an effect that is amplified when combined with a 2-week period of increased flavonoid intake or chronic training as a runner.

Solids in the interstellar medium consist of an intimate mixture of silicate and carbonaceous grains. Because 99% of silicates in meteorites were reprocessed at high temperatures in the inner regions of the Solar Nebula, we propose that similar levels of heating of carbonaceous materials in the oxygen-rich Solar Nebula would have converted nearly all carbon in dust and grain coatings to CO. We discuss catalytic experiments on a variety of grain surfaces that not only produce gas-phase species such as CH4, C2H6, C6H6, C6H5OH or CH3CN, but also produce carbonaceous solids and fibers that would be much more readily incorporated into growing planetesimals. CO and other more volatile products of these surface mediated reactions were likely transported outwards along with chondrule fragments and small Calcium Aluminum Inclusions (CAIs) to enhance the organic content in the outer regions of the nebula where comets formed. Carbonaceous fibers formed on the surfaces of refractory oxides may have significantly improved the aggregation efficiency of chondrules and CAIs. Carbonaceous fibers incorporated into chondritic parent bodies might have served as the carbon source for the generation of more complex organic species during thermal or hydrous metamorphic processes on the evolving asteroid.

Fluorescence microscopy provides an unparalleled tool for imaging biological samples. However, producing high-quality volumetric images quickly and without excessive complexity remains a challenge. Here, we demonstrate a simple multi-camera structured illumination microscope (SIM) capable of simultaneously imaging multiple focal planes, allowing for the capture of 3D fluorescent images without any axial movement of the sample. This simple setup allows for the acquisition of many different 3D imaging modes, including 3D time lapses, high-axial-resolution 3D images, and large 3D mosaics.

Load transfer through orthopaedic joint implants is poorly understood. The longer-term outcomes of these implants are just starting to be studied, making it imperative to monitor contact loads across the entire joint implant interface to elucidate the force transmission and distribution mechanisms exhibited by these implants in service. This study proposes and demonstrates the design, implementation, and characterization of a 3D-printed smart polymer sensor array using conductive polyaniline (PANI) structures embedded within a polymeric parent phase. The piezoresistive characteristics of PANI were studied to characterize the sensing behaviours inherent to these embedded pressure sensor arrays. PANI's stable response to a continuous load, its stability throughout loading and unloading cycles, and its repeatable and linear response to incremental loading cycles together with the accuracy of these measurements were investigated. It is demonstrated that this specially developed multi-material additive manufacturing process for polyaniline is an attractive approach for the fabrication of implant components having embedded smart-polymer sensors for the measurement and analysis of joint loads in orthopaedic implants.

White adipose tissue (WAT) represents an endocrinologically and immunologically active tissue that’s primary role is energy storage and homeostasis. Breast WAT is involved in the secretion of hormones and proinflammatory molecules that are associated with breast cancer development and progression. The role of adiposity and systemic inflammation in immune responses and resistance to anti-cancer treatment in breast cancer (BC) patients is still not clear. This review aims to evaluate the emerging evidence on the crosstalk between adiposity and the immune-tumour microenvironment in BC, its progression and treatment resistance. Adiposity, and by extension subclinical inflammation, are associated with metabolic dysfunction and changes in the immune-tumour microenvironment in BC. In oestrogen receptor positive (ER+) breast tumours, it is proposed that these changes are mediated via a paracrine interaction between macrophages and preadipocytes leading to elevated aromatase expression and secretion of pro-inflammatory cytokines and adipokines in the breast tissue in patients who are obese or overweight. In HER2+ breast tumours, WAT inflammation has been shown to be associated with resistance to trastuzumab mediated via MAPK or PI3K pathways. Furthermore, adipose tissue in patients with obesity is associated with upregulation of immune checkpoints on T-cells that is partially mediated via immunomodulatory effects of leptin and has been paradoxically associated with improved responses to immunotherapy in several cancers. In conclusion, evidence suggests that body composition and metabolic status are associated with patient outcomes. To optimise patient stratification and personalisation of treatment, prospective studies are required to evaluate the role of body composition and metabolic parameters in metabolic immune reprogramming with and without immunotherapy in patients with BC.

Lymphangioleiomyomatosis (LAM) is a cystic pulmonary disorder that has been known to primarily affect women of childbearing age. The disorder can develop with mutations in the tuberous sclerosis (TSC) genes TSC1 & TSC2 but may arise by other irregular cases in the lack of these mutations. LAM can manifest in a wide variety of ways and generally compounded in symptoms of other lung disorders such as bronchitis, emphysema, & asthma. However, due to lack of effective diagnostic methods, biomarkers of LAM leading to a treatment for the disorder are currently unmet. Using integrative dating analytics and bioinformatics approaches; this study used publicly available microarray data to identify biomarkers in LAM. The results showed important differential expressed genes (DEGs) including: CDH2, CXCL6, ANXA10, MFAP5, RPS4Y1, DCBLD2, PAPPA, TFPI2, SERPINE1, LOX, MYH11, RGS1, SEPP1, TMOD1, ID1, SFTPB, CDH1, HTR2B, OGN, and IGLC1. Furthermore, gene – network and gene ontology (GO) analysis were conducted to show the importance of these genes from a molecular understanding. Taken together, the results revealed could serve as diagnostic and prognostic biomarkers with LAM patients.

Cerebral cavernous malformation (CCM) is a collection of irregular small blood vessels that may be present in the brain or spinal cord. These vessels contain slow – moving blood that commonly clot. These malformations are frequently caused by mutations in one of the CCM genes. The CCM1 (also known as KRIT1) gene is essential for vascular morphogenesis however, its interactions with transcriptional regulators are unknown. Inhibitor of DNA-Binding/Differentiation-3 (ID3) has been recognized to be involved in different vascular/blood vessel diseases such as peripheral arterial disease, stroke, arteriovenous malformations, and atherosclerosis. We show interactions between ID3 and additional key differential expressed genes (DEGs) in microarray data of overexpressed CCM1 in endothelial cells through bioinformatic and data analytic tools. Improved understanding of how ID3, CCM1, and DEGs interact will play an important role in adding to the increasing knowledge for creating therapeutic targets for cerebral cavernous malformations.

In 2015, the World Health Organization substantially revised its guidance for vaccination coverage cluster surveys (revisions were finalized in 2018) and has since developed a set of accompanying resources, including definitions for standardized coverage indicators and software (named the Vaccination Coverage Quality Indicators - VCQI) to calculate them. The current WHO vaccination coverage survey manual was used to design and conduct two nationally representative vaccination coverage surveys in Nigeria – one to assess routine immunization and one to measure post-measles campaign coverage. The primary analysis for both surveys was conducted using VCQI. In this paper, we describe those surveys and highlight some of the analyses that are facilitated by the new resources. In addition to calculating coverage of each vaccine-dose by age group, VCQI analyses provide insight into several indicators of program quality such as crude coverage versus valid doses, vaccination timeliness, missed opportunities for simultaneous vaccination, and, where relevant, vaccination campaign coverage stratified by several parameters, including the number of previous doses received. The VCQI software furnishes several helpful ways to visualize survey results. We show that routine coverage of all vaccines is far below targets in Nigeria and especially low in northeast and northwest zones, which also have highest rates of dropout and missed opportunities for vaccination. Coverage in the 2017 measles campaign was higher and showed less geospatial variation than routine coverage. Nonetheless, substantial improvement in both routine program performance and campaign implementation will be needed to achieve disease control goals.

The material undergoes high temperature and high strain rate deformation process during cutting process, may induce the dynamic recrystallization behavior and result the evolution of dynamic mechanical properties of the material to be machined. In this paper, the modified Johnson-Cook(J-C) model for Nickel based powder metallurgy superalloy considering dynamic recrystallization behavior in high strain rate and temperature is proposed. The dynamic mechanical properties of the material under different strain rates and temperature conditions are obtained by quasi-static compression test and split Hopkinson pressure bar (SHPB) test. The coefficients of the modified J-C model are obtained by linear regression method. The modified model is verified by comparison with experimental and model prediction results. The results show that the modified J-C model proposed in this paper can accurately describe the mechanical properties of nickel-based powder metallurgy superalloys at high temperature and high strain rate. Which provides help for studying the cutting mechanism and finite element simulation of nickel-based powder metallurgy superalloy.

Computational Fluid Dynamics (CFD) is revolutionizing the oil and gas industry by offering powerful insights and innovative solutions. This paper explores the cutting-edge applications of CFD in enhancing and innovating within the sector. CFD simulations provide engineers with invaluable insights into fluid behavior, enabling optimized designs and informed decision-making. The software facilitates foresight by predicting system performance, optimizing drilling techniques, and maximizing reservoir management strategies. Moreover, CFD optimizes equipment design, increases operational efficiency, and reduces costs through virtual testing, eliminating the need for costly physical prototypes. The application of CFD aligns with the United Nations Sustainable Development Goals (SDGs), promoting energy efficiency, climate action, responsible production, and sustainable consumption. It addresses flow assurance challenges, enhances safety protocols, and mitigates environmental impacts. CFD is a powerful tool driving innovation, resilience, and sustainability within the oil and gas industry, ensuring a more efficient, safe, and environmentally conscious future. As advancements in CFD methodologies continue, the potential for further enhancements and breakthroughs within the sector becomes even more promising, driving the industry towards a sustainable and prosperous future.

This study investigates the compressive strength and workability of concrete incorporating coconut shells and bamboo strips as alternative aggregates. The research compares traditional concrete to concrete mixtures with varying percentages of coconut shells and bamboo strips. Specifically, the study examines the effects of adding 10% coconut shell, 10% bamboo strip, and a combination of 5% coconut shell and 5% bamboo strip by volume to the concrete mix, tested in both C20 and C30 grades. To prepare the materials, coconut shells and bamboo strips were first crushed and then sieved. The sieving process retained particles that passed through a 10mm sieve but were retained on a 4.7mm sieve. The primary focus of the experimental tests was on measuring the compressive strength of the resulting concrete mixtures. The findings indicate that concrete incorporating coconut shells showed moderate workability. In contrast, concrete with bamboo strips exhibited lower workability. Regarding compressive strength, the concrete mix containing a combination of 5% coconut shell and 5% bamboo strips demonstrated a reduction in strength compared to the control group of normal concrete. This research highlights the potential of using coconut shells and bamboo strips as sustainable alternatives in concrete construction. While the workability varies between the different materials, the results provide valuable insights into their suitability for specific applications. This encourages further exploration of eco-conscious building practices and the development of sustainable construction materials.

Enhancing the Efficiency of Natural Gas Liquid (NGL) Extraction and Fractionation Trains: An Integrated Approach of Simulation Analysis, Advanced Modifications, and Technological Advancements. Through comprehensive research, innovative solutions such as the heat pump aided distillation (HPAD) system and self-heat recuperation technology (SHRT) have been developed to significantly reduce the energy consumption associated with conventional distillation systems. To identify a practical system for NGL fractionation trains, this study extensively examined and compared various HPAD and SHRT options to retrofit a single column. The objective was to find the most suitable and efficient solution for the fractionation process of natural gas liquids (NGLs). The retrofit options analyzed in this study encompassed a range of techniques, including vapor compression (VC), mechanical vapor re-compression (MVR), thermal vapor re-compression (TVR), bottom flashing (BF), side heat exchanger (SHE), intermediate heating and cooling (IHC), self-heat recuperative (SHR), and modified self-heat recuperative (MSHR) distillation. These methods were carefully examined to determine their suitability and effectiveness in improving the performance of NGL fractionation trains.In this study, a depropanizer column, typically employed in conventional NGL plants, was selected as a case study. The simulation software Aspen HYSYS V7.3 was employed to model and analyze eight retrofit designs based on predefined criteria. The simulation data was carefully evaluated to identify the most efficient design for minimizing energy consumption. Among the retrofit options, the mechanical vapor re-compression (MVR) technique demonstrated the most significant energy cost reduction, with a remarkable 68.11 percent improvement compared to the base case conventional column. These findings highlight the potential of MVR as an effective solution for lowering energy costs in NGL fractionation trains.Following the MVR retrofit option, the study found that vapor compression (VC) achieved a considerable energy cost reduction of 66.65 percent, closely followed by modified self-heat recuperative (MSHR) at 64.02 percent, bottom flashing (BF) at 62.88 percent, self-heat recuperative (SHR) at 55.85 percent, side heat exchanger (SHE) at 54.23 percent, intermediate heating and cooling (IHC) at 39.54 percent, and thermal vapor re-compression (TVR) also at 39.54 percent. These findings highlight the significant potential for energy savings offered by these retrofit options, with VC being the most popular choice, closely followed by MSHR, BF, SHR, SHE, IHC, and TVR.

ABSTRACT Lubricants play a crucial role in reducing friction and wear between surfaces in relative motion. Engine oil, as a lubricant, is specifically designed to minimize friction and wear between the moving parts of different equipment and machinery. Engine oil blending serves the purpose of adjusting the variety of lubricants available to meet specific performance requirements. Through blending, it is possible to tailor the characteristics of the lubricating oil, such as viscosity, stability, and additive content, to optimize its effectiveness in reducing friction, protecting engine components, and enhancing overall equipment performance. By customizing lubricant formulations through blending, manufacturers can address the diverse lubrication needs of modern engines and machinery, ensuring smooth operation, longevity, and efficiency.To enhance the quality of the lubricant and achieve the desired high-performance multi-grade engine oil, a systematic approach was followed. The process began with testing the specific gravity of the oil using a hydrometer and thermometer to ensure accurate measurements. Subsequently, 5 liters of base oil were carefully measured and poured into a stainless steel reactor pot to serve as the blending vessel. Following this, 1 liter of paraffin oil (100N) was added to the base oil to introduce specific properties to the blend. To further optimize the formulation, 0.42 kg (7% of the total blend) of additives, including a selection of specific performance-enhancing compounds, was incorporated. These additives, such as Aspen, Tackifier, and other essential components like anti-wear, corrosion inhibitors, detergents, dispersants, and antioxidants, were meticulously measured and added to the mix. Through this precise blending process, the goal was to craft a high-quality multi-grade engine oil that meets the stringent performance requirements for various operating conditions and equipment types. After the melted Aspen and dissolved tackifier were added to the mixture, thorough stirring was carried out to ensure uniform distribution until a homogeneous blend was achieved. The mixture was then exposed to heat to facilitate the reaction between the base oil and additives, reaching a temperature of 70°C for optimal blending. Subsequently, 0.5 kg of viscosity index improver was introduced into the mixture and stirred continuously for a period of 5 minutes to ensure proper integration. Following this step, 5 grams of dye were carefully added to the mixture, and stirring was continued to evenly disperse the coloring agent throughout the blend. This meticulous process aimed to ensure that all components were effectively incorporated, facilitating the production of a high-quality, customized multi-grade engine oil with enhanced performance characteristics and optimal lubricating properties. After subjecting the mixture to a temperature of 70°C, the heat source was removed, allowing the product to gradually cool down to room temperature, which was estimated to be around 30°C. Following this cooling process, the product underwent a filtration step to remove any residual impurities present in the mixture. A sample of the purified product was then extracted for further analysis. Quality control tests were meticulously carried out on the sample to ensure that the product met the rigorous standards set by the Standard Organization of Nigeria (SON). The results obtained from the quality control tests were highly promising, indicating that the product indeed complied with the stringent specifications outlined by the regulatory body. This adherence to quality standards is essential in ensuring the product's reliability and performance in various applications. The successful outcome of the quality control test underscores the meticulous attention to detail and commitment to excellence in the production process. The rigorous quality control procedures implemented in the analysis of the product highlight the commitment to upholding high standards of quality and safety in the manufacturing process. By consistently meeting and exceeding industry regulations and standards, the product not only demonstrates its reliability but also reflects a dedication to customer satisfaction and product excellence. The adherence to the SON standards showcases a commitment to producing top-quality products that meet the needs and expectations of consumers and industry stakeholders alike.

Revolutionizing Lng Plant Construction and its Comprehensive Comparative Analysis And Evaluation Of Modular Design Development Versus Stick-Built Approach For Enhanced Efficiency And Cost-Effectiveness,.Although the utilization of modularization concepts in the LNG industry remains limited, this study focuses on exploring their potential. It is worth noting that modular units typically incur higher costs compared to field erected units due to the additional requirements of structural steel and robustness for transportation purposes.Nevertheless, the increased cost of modularization can often be balanced by conducting the work at the fabrication site instead of on-field construction. This approach reduces the overall project cost by minimizing field construction expenses and shortening the construction schedule. The objective of this paper is to assess and compare LNG modularization options for a newly established LNG facility in comparison to a conventional stick-built plant used as the base case.:The paper delves into various topics related to LNG plant construction, such as the development of modular units, a comprehensive comparison of different options, evaluation of construction schedules and manpower requirements, logistics considerations, and a recommended approach for design and construction. The cost estimates and engineering, procurement, and construction (EPC) schedules are meticulously compared for each option. Additionally, an inshore/near shore gravity base structure (GBS) option is included for further comparison. It is crucial to emphasize that establishing general costs is not possible as each project is distinct and requires individual study and analysis.:Each project has unique characteristics, resulting in varying shapes of cost curves and break-even points. The outcomes of the feasibility evaluation play a crucial role in determining the extent to which the modular approach to construction is advantageous for the specific project at hand. The evaluation takes into consideration multiple factors to determine the potential benefits of adopting a modular construction approach, allowing decision-makers to make informed choices regarding the project's construction methodology

The global energy landscape is undergoing a transformative shift, and the potential of LNG as a major energy source is a topic of intense debate. In order to meet the growing demand for sustainable energy supply, it is crucial to maximize the efficiency and environmental friendliness of the LNG supply chain. This research aims to leverage computational modeling and optimization techniques to enhance the production units involved in LNG production. By harnessing the power of advanced algorithms and simulations, we can identify and implement innovative strategies that minimize energy consumption, reduce greenhouse gas emissions, and enhance the overall sustainability of LNG. Through this study, we seek to uncover novel approaches to address the challenges faced by the LNG industry, including improving operational efficiency, optimizing liquefaction processes, and enhancing the utilization of natural resources. By integrating cutting-edge computational tools and considering environmental factors, we aspire to pave the way for a more sustainable and environmentally friendly future powered by LNG. By exploring the immense potential of computational modeling and optimization, we strive to contribute to the ongoing efforts in advancing energy sustainability and shaping the future of LNG as a crucial global energy source."In this paper, our focus is on simulating and optimizing the process of converting natural gas to LNG. Our goal is to achieve the minimum energy consumption per ton of LNG produced. Through our research, we have identified that utilizing a three-stage exchanger is the most effective approach for minimizing energy consumption in an LNG industrial production unit. Moreover, we have discovered that the outlet pressure from the compressor and the type of refrigerant in the cooling system play significant roles in determining the rate of energy conservation. By carefully considering these factors and optimizing their settings, we can further enhance the overall energy efficiency of the LNG production process. Our research aims to provide valuable insights and guidance to industry professionals and decision-makers in the LNG sector. By implementing the findings of this study, we can contribute to the sustainable development and utilization of LNG as a cleaner and more environmentally energy source. Friendly It's great to see the optimized parameters for the refrigerants and pressure settings in the liquefaction and subcooling cycles. With the mass fraction of 0.89 for methane and 0.14 for ethane in the liquefaction cycle, and 0.59 for methane and 0.3 for nitrogen in the composition for achieving energy efficiency in the LNG production subcooling cycle, The optimized outlet pressure of 650 kPa for the compressors in the liquefaction cycle and 1800 kPa for the subcooling cycle furtherr ccontribute to minimizing energy consumption. Based on your findings, the amount of consumed energy at 14.81 kW per ton of produced LNG highlights the success of the optimization efforts. Reducing the energy consumption per ton of LNG produced is a significant accomplishment towards achieving energy sustainability and environmental friendliness in the LNG industry. These results demonstrate the importance of computational modeling and optimization in identifying the best parameters for eenhancing energy efficiency in LNG production. By implementing these optimized settings, we can work towards a more sustainable future with reduced energy consumption and lower environmental impact

COVID-19 and long COVID-19 vulnerabilities may be caused indirectly by albumin binding deficiency (ABD) which can be corrected by the correct administration of human serum albumin (HSA). The liver is the primary site of nutrient regulation and fluid volume maintenance, control of both is by changes to albumin concentration. In healthy subjects the HSA lymphatic nutrient pump (HSALNP) ensures continual pumping of nutrients from the liver are appropriately distributed to organs. Nutrients are delivered to cells according to the availability of binding to HSA. The HSALNP therefore maintains the correct nutrients and colloidal pressure balance in all tissues independently. In unhealthy tissues, following COVID-19 infection, the passage of HSA/nutrients through the interstitial spaces and lymph will be impeded. Fluid therapy into the periphery leads to dilution of essential nutrients attached to the protein-carriers such as albumin. The levels of albumin being charged by the liver with nutrients is critical in maintaining immune stability by maintaining nutrient support and colloidal pressure of cellular structures. The site of HSA binding by the liver is of great importance and direct infusion of albumin into the Hepatic Portal Vein is the most appropriate method of maintaining colloid pressure and cellular nutrient levels.

There are four commercial pathways to make grill charcoal from wood. These have been modelled to calculate a carbon intensity (CI) for each. Results are presented along with discussion of the sensitivities: biogenic carbon; quality of the charcoal; classification of products, wastes and residues; and division of burden. Grill charcoal’s CI ranges greatly, depending on the pathway by which it is produced. Wood distillation, a commercial process that once was common but now is rare, has a CI 50+% lower than that of the next-lowest commercial process, Kilns. Earth mounds/pits and external-fuelled Retorts have CIs considerably higher still. The carbon efficiency (CE) of Wood distillation is more than twice that of the next-best, again Kilns. CE is defined as normalised, total carbon emitted. This is not the same as CI, it is not usually considered in studies such as this, yet it is important for climate impact. CE could be a useful measure in assessments (such as this) where biogenic carbon is significant.

This review article explores the convergence of virtual reality (VR) and architectural design from an inclusive lens. It underscores the crucial role of virtual reality (VR) in serving as a catalyst for the incorporation of social and cultural sustainability principles in architectural projects. The exploration is guided by inclusive design principles, which encompass several aspects such as accessibility, cultural sensitivity, diversity and inclusivity, user-centered design, and empathy. These concepts serve as the basis for further investigation into the potential of virtual reality (VR) technology to enhance and heighten these features within architectural design, therefore promoting the progress of social and cultural sustainability. The review article highlights the profound impact that virtual reality (VR) may have, going beyond mere visualisation to generate architectural experiences that are immersive, interactive, and empathetic. These experiences are designed to take into account diverse perspectives and needs.

The creation of protonated water nanoclusters from amorphous water-ice under laboratory conditions suggests the possible ejection of such nanoclusters from ubiquitous amorphous water-ice-covered cosmic dust to interstellar space. The quantum properties of these quintessential water entities introduce a tantalizing prospect that bridges the origins of dark matter, dark energy, and life in the universe. The quantum-entangled diffuse Rydberg electronic states inherent to cosmic water nanoclusters make them plausible candidates for baryonic dark matter. Moreover, they exhibit the capacity to absorb, through the microscopic dynamical Casimir effect, virtual photons originating from zero-point-energy vacuum fluctuations occurring above the water-nanocluster vibrational frequency cutoff. This selective interaction leaves only vacuum fluctuations below these frequencies with gravitational significance, cancelling the vacuum-energy catastrophe and yielding a shared genesis for dark matter and dark energy. Moreover, this theory extends its implications to the origins of life itself, proposing that RNA protocells on Earth and habitable exoplanets may have emerged from the interactions between cosmic water nanoclusters and prebiotic organic molecules, thus yielding an anthropic narrative. Collectively, these findings coalesce into a cosmological framework depicting a cyclic universe, with cosmic water nanoclusters constituting a quintessence scalar field, instead of adhering to the multiverse concept based on cosmic inflation theory. Recent observations of CMB birefringence support this quintessence.

Through the ACE2, a main enzyme of the renin-angiotensin system (RAS), the SARS-CoV2 gains access into the cell, resulting in different complications which may extend beyond the RAS and impact the Arachidonic Acid (ArA) pathway. The contribution of the RAS through ArA pathways metabolites in the pathogenesis of COVID-19 is unknown. We investigated whether RAS components and ArA metabolites can be considered biomarkers of COVID-19. We measured the plasma levels of RAS and ArA metabolites using an LC-MS/MS. Results indicate that Ang1-7 levels were significantly lower, whereas Ang II levels were higher in the COVID-19 patients than healthy control individuals. The ratio of Ang1-7/Ang II as an indicator of the RAS classical and protective arms balance was dramatically lower in COVID-19 patients. There was no significant increase in inflammatory 19-HETE and 20-HETE lev-els. The concentration of EETs was significantly increased in COVID-19 patients, whereas the DHETs concentration was repressed. Their plasma levels were correlated with Ang II concentration in COVID-19 patients. In conclusion, evaluating the RAS and ArA pathway biomarkers could provide helpful information for the early detection of high-risk groups, avoid delayed medical attention, facilitate resource allocation and improve patient clinical outcomes to prevent long COVID incidence.

The detrimental consequences of soil pollution caused by crude oil or petroleum products are immense, leading to land degradation, property damage, and rendering agricultural practices ineffective. Extensive research has been conducted in the field of soil remediation, but further studies are still required to explore additional details of the remedial process. As a result, this study focuses on evaluating the effectiveness of Vernonia Galamensis and Vernonia Amygdalina, commonly known as bitter leaf, in remediating hydrocarbon-contaminated soil. In the analysis of micro-organisms, it was found that the bitter leaf extracts contained three types of bacteria: Pseudomonas aeruginosa, Staphylococcus aureus, and Escherichia coli. The leaf extracts were prepared using different methods, including sun drying, room drying, and using them in their wet form, which were then blended into the contaminated soil. The study also took into consideration three different types of soil: sandy-loamy soil, clay soil, and swamp soil. These advanced techniques and considerations are relevant to the topic of revolutionizing soil remediation, as they explore the potential of bitter leaf extracts and different soil types in effectively mitigating the effects of hydrocarbon contamination.The findings revealed that the wet blended extracts of Vernonia performed exceptionally well in the remediation process, surpassing a 50% reduction in the initial contamination levels. The study involved utilizing a quantity of bitter leaf ranging from 10g to 40g, which was added to the contaminated soils and monitored for a duration of 40 days. Remarkably, this approach led to a significant decrease in the concentration of contaminants within the soil, indicating the effectiveness of the bitter leaf extracts in the remediation process. Towards the conclusion of the study, predictive models were constructed to forecast the impact of hydrocarbon content, as well as the levels of lead, zinc, and chromium in the soil. These variables served as the dependent variables in the models, while the mass of bitter leaf, the duration of treatment, and the pH of the soil were considered as independent variables. Significantly, the models achieved a level of significance of less than 0.05, indicating their statistical validity. Furthermore, the r2 value, which represents the goodness of fit, demonstrated an appreciable level of accuracy in predicting the remediation effects. These results highlight the potential of the developed models in assessing and predicting the remedial outcomes of hydrocarbon contamination using bitter leaf extract.

(S)-1-Methyl-2-oxoimidazolidine-4-carboxylic acid 1 is an analog of (S)-pyroglutamic acid, a key component of naturally occurring peptide hormones and synthetic pharmaceutical candidates. Reaction of (S)-2-amino-3-(methylamino)propionic acid with COCl2 and aqueous NaHCO3 followed by ion exchange afforded 1, which was recrystallized from acetonitrile and then characterized by IR, 1H NMR, 13C NMR, polarimetry, elemental microanalysis, high resolution mass spectrometry and single crystal X-ray diffraction. The acid 1 crystallized in the orthorhombic chiral space group P212121 with cell constants a = 6.2275(4) Å, b = 8.3963(5) Å, c = 24.9490(14) Å. The X-ray crystal structure reveals that two distinct conformers of 1 occur at alternating positions within helices which are supported by hydrogen-bonding. Each molecule of 1 is linked to its two neighbors in the helix by a total of three hydrogen bonds and four molecules of 1 are contained within each turn of the helix. The pattern of hydrogen bonds illustrates a preference for the carboxylic acid group to act as a hydrogen bond donor and for the urea unit to be a hydrogen bond acceptor.

1) Background. Stevens-Johnson syndrome (SJS) and toxic epidermal necrolysis (TEN) are severe mucocutaneous reactions, characterized by extensive necrosis and detachment of the epidermis. 2) Case presentation. We present a case of a 46-year-old patient with late-stage high-grade serous ovarian cancer who was primarily treated with neoadjuvant chemotherapy and interval debulking which was followed by adjuvant chemotherapy. At first recurrence, she was again treated with chemotherapy and due to severe abdominal pain, an elastomeric pump containing analgesics, anti-inflammatories and ondansetron was administered. In the same month, she was admitted to the hospital due to severe dysphagia and in the following days, she developed haemorrhagic vesiculobullous lesions on facial skin and trunk. Stevens-Johnson syndrome was confirmed and ondansetron as a leading cause was discontinued. Despite multimodal treatment, her condition deteriorated, and she died. 3) Discussion and conclusion. Although gynaecologists rarely encounter Stevens-Johnson syndrome, high mortality of the disease should ensure a low threshold for diagnosing and treating this disease.

The principal barrier to an HIV-1 cure is the persistence of infected cells harboring replication-competent proviruses despite antiretroviral therapy (ART). HIV-1 transcriptional suppression, referred to as viral latency, is foremost among persistence determinants, as it allows infected cells to evade the cytopathic effects of virion production and killing by cytotoxic T lymphocytes (CTL) and other immune factors. HIV-1 persistence is also governed by cellular proliferation, an innate and essential capacity of CD4+ T cells that both sustains cell populations over time and enables a robust directed response to immunological threats. Yet when HIV-1 infects CD4+ T cells, this capacity for proliferation can counterproductively enable surreptitious HIV-1 propagation without the deleterious effects of viral gene expression in latently infected cells. Over time on ART, the HIV1 reservoir is shaped by both persistence determinants, with selective forces most often favoring clonally expanded infected cell populations harboring transcriptionally quiescent proviruses. Moreover, if HIV latency is incomplete or sporadically reversed in clonal infected cell populations that are replenished faster than they are depleted, such populations could both persist indefinitely and contribute to low-level persistent viremia during ART and viremic rebound if treatment is withdrawn. In this review, select genetic, epigenetic, cellular, and immunological determinants of viral transcriptional suppression and clonal expansion of HIV-1 reservoir T cells, interdependencies among these determinants, and implications for HIV-1 persistence will be presented and discussed.

The existence of insecurity in a state necessitates immediate government attention and action as it poses a risk to human life and property and impedes socio-economic development. The study aims to evaluate insecurity and its impact on socio-economic development in Oyo state. It will also determine the major causes of insecurity problems and offer data that can help develop effective security strategies and policies. The study population consisted of residents who were randomly selected from the Ibarapa North Local Government Area of Oyo State, Nigeria. The descriptive survey method was adopted and analyzed with the Chi-square technique. According to this research, there is a negative correlation between insecurity and the state's socio-economic development. The study recommends good governance and inclusive government policies to curb insecurity and ensure the state's socio-economic development.

“Minas Frescal” cheese is a high moisture product, subject to the proliferation of several microorganisms. Essential oils are natural antimicrobial alternatives that can increase the quality of dairy products. This study aimed to analyze the antimicrobial action of oregano (Origanum vulgare) and rosemary (Rosmarinus officinalis) essential oils against Escherichia coli and Staphylococcus aureus. An antimicrobial test by diffusion and microdilution was performed to calculate the MIC (Minimum Inhibitory Concentration) and MBC (Minimum Bactericidal Concentration). The behavior of E. coli in “Minas Frescal” cheese added with oregano oil was evaluated. The MIC of oregano oil was 0.25% against E. coli and 1% against S. aureus. For rosemary essential oil, the MIC was 8% of against E. coli. There was no activity of rosemary oil against S. aureus. The MBC observed for oregano essential oil was 1% and 0.25% respectively for S. aureus and E. coli. Bacterial analysis during cheese storage with E. coli indicated inhibition of microorganisms by oregano essential oil at a concentration of 0.25%. No alterations were observed regards to physical-chemical attributes. The use of essential oil as an antimicrobial agent has potential for industrial use, and type of microorganism, oil and sensory reflexes in the product must be observed.

The GLUT members belong to a family of glucose transporter proteins that facilitate glucose transport across the cell membrane. The mammalian GLUT family consists of thirteen members (GLUTs 1-12 and HMIT). Humans have a recently duplicated GLUT member, GLUT14. Avians express the majority of GLUT members. The arrangement of multiple GLUTs across all somatic tissues signifies the important role of glucose across all organisms. Defects in glucose transport have been linked to metabolic disorders, insulin resistance and diabetes. Despite the essential importance of these transporters, our knowledge regarding GLUT members in avians is fragmented. It has been clear that there are no chicken orthologs of mammalian GLUT4 and GLUT7. Our examination of GLUT members in the chicken revealed that some chicken GLUT members do not have corresponding orthologs in mammals. We review the information regarding GLUT orthologs and their function and expression in mammals and birds, with emphasis on chickens and humans.

Plastics play a pivotal role in the principles of a circular economy, where their effective recycling post-utilization, leading to economic value generation and minimal environmental harm, is crucial for achieving sustainable management. Extensive research has delved into the incorporation of waste plastics in concrete, showcasing promising outcomes with a myriad of advantages..The escalating volume of plastic waste is becoming a pressing issue, contributing to environmental pollution, particularly in densely populated cities and towns in Nigeria such as Delta, Aba, Port Harcourt, Onitsha, Enugu, Benue, and Ogun. These urban centers experience high consumption of goods packaged or sealed in plastic materials. Tourist destinations are also affected as large quantities of plastic waste are improperly disposed of or incinerated, resulting in environmental contamination and air pollution. Efforts to address this growing concern are crucial to safeguarding the environment and public health in these regions.Therefore, it is imperative to find effective ways to utilize these waste plastics. By cleaning low-density polyethylene bags and combining them with sand at specific proportions, high-strength bricks can be produced. These bricks not only exhibit thermal and sound insulation properties but also help in pollution control and cost reduction in construction projects. This innovative approach not only addresses the issue of accumulating plastic waste, a non-biodegradable pollutant, but also offers a sustainable solution to manage plastic waste while contributing to the construction industry's efficiency and environmental protection., By incorporating waste plastic and nylon into brick production, we not only reduce the amount of sand extracted from our natural resources like rivers and seas but also utilize the surplus plastic waste that is currently discarded. This research focuses on creating eco-friendly bricks by incorporating molten plastic, nylon, and plastic bottles in varying percentages (0 to 15% by weight) along with 5kg of fly ash. The experimental results from this study will shed light on the feasibility and benefits of using these materials in brick manufacturing, highlighting the potential of sustainable construction practices that minimize environmental impact and resource depletion, The experimental process involved utilizing cement and sand to complete the brick composition, with curing conducted underwater for 29 days followed by baking at temperatures between 100°C to 120°C for 2 hours. The resulting eco-friendly bricks exhibited key characteristics such as being lightweight, porous, having low thermal conductivity, and displaying appreciable mechanical strength. Interestingly, the compressive strengths of these bricks, post the addition of waste plastic and nylon, were found to be comparable to that of conventional bricks. Additionally, these eco-friendly bricks showcased reduced water absorption capacity compared to regular bricks, offering a promising alternative for sustainable and efficient construction practices.The eco-friendly bricks made from A, B, C, and D using 0%, 5%, 10%, and 15% plastic/nylon waste showed comprehensive strengths of 19.5 ,19.46, 20.3, and 21.1 respectively, with corresponding water absorption percentages of 0.34, 0.25, 0.22, 0.20, and 0.085. The efflorescence values were lower than those of normal bricks. These bricks are likely to enhance energy efficiency in buildings and provide economic value to manufacturers, thereby promoting a sustainable ecosystem for plastic waste management with the involvement of all stakeholders.

Cyclic STAT3 decoy (CS3D) is a second-generation, double-stranded oligodeoxynucleotide (ODN) that mimics a genomic response element for signal transducer and activator of transcription 3 (STAT3), an oncogenic transcription factor. CS3D competitively inhibits STAT3 binding to target gene promoters, resulting in decreased expression of proteins that promote cellular proliferation and survival. Previous studies have demonstrated antitumor activity of CS3D in preclinical models of solid tumors. However, prior to entering human clinical trials, the efficiency of generating the CS3D molecule and its stability in biological fluids should be determined. CS3D is synthesized as a single-stranded ODN and must have its free ends ligated to generate the final cyclic form. In this study, we report a ligation efficiency of nearly 95 percent. The ligated CS3D demonstrated a half-life of 7.9 hours in human serum, indicating adequate stability for intravenous delivery. These results provide requisite biochemical characterization of CS3D that will inform upcoming clinical trials.

The present review explores the critical role of oxime and oxime ether moieties in enhancing the physicochemical and anticancer properties of structurally diverse molecular frameworks. Specific examples are carefully selected to illustrate the distinct contributions of these functional groups to general strategies for molecular design, modulation of biological activities, computational modeling, and structure-activity relationship studies. An extensive literature search was conducted across three databases, including Pub-Med, Google Scholar, and Scifinder, enabling us to create one of the most comprehensive overviews of how oximes and oxime ethers impact antitumor activities within a wide range of structural frameworks. This search focused on various combinations of keywords or their synonyms, related to the anticancer activity of oximes and oxime ethers, structure-activity relationships, mechanism of action, as well as molecular dynamics and docking studies. Each article was evaluated based on its scientific merit and the depth of the study, resulting in 268 cited references and more than 336 illustrative chemical structures carefully selected to support this analysis. As many previous reviews focus on one subclass of this extensive family of compounds, this report represents one of the rare and fully comprehensive assessments of the anti-cancer potential of this group of molecules across diverse molecular scaffolds.

We tested the hypothesis that obesity influences the pharmacodynamics of volatile general anesthetics (VGAs) by comparing effects of anesthetic exposure on mortality from traumatic brain injury (TBI) in lean and obese Drosophila melanogaster. We induced TBI with a High-Impact Trauma device. Starvation-selection over multiple generations resulted in an obese phenotype (SS flies). Fed flies served as lean controls (FC flies). Adult (1-7 day old) SS and FC flies were exposed to equianesthetic doses of isoflurane or sevoflurane either before or after TBI. The principal outcome was percent mortality 24 hours after injury, expressed as the Mortality Index at 24 hours (MI24). TBI resulted in lower MI24 in FC than in SS flies (21 (2.35) and 57.8 (2.14), respectively n= 12, p=0.0001). Preexposure to isoflurane or sevoflurane preconditioned FC flies to TBI reducing the risk of death to 0.53 [0.25 to 1.13] and 0.82 [0.43 to 1.58], respectively, but had no preconditioning effect in SS flies. Postexposure to isoflurane or sevoflurane increased the risk of death in SS flies. Only postexposure to isoflurane increased the risk in FC flies (1.39 [0.81 to 2.38]). Thus, obesity affects the pharmacodynamics of VGAs, thwarting the preconditioning effect of isoflurane and sevoflurane in TBI.

In the dynamic realm of agribusiness construction, firms are striving to bolster their operational efficiency and profitability amidst the global shift from traditional farming to commercial agriculture. This transition has intensified the demand for sophisticated infrastructure development, presenting new challenges for commercial managers. A critical hurdle is the accurate estimation of profitability for prospective contracts, a task often reliant on intuition rather than data-driven methods. To address this, we propose the development of a mathematical model utilising machine learning techniques to predict contract profitability and identify influential factors. This model aims to aid in bid decision-making, financial forecasting, and enhancing competitiveness in the marketplace. Furthermore, it would provide valuable insights into how altering specific contract attributes might affect predicted profitability. The implementation of such a system necessitates close collaboration between IT professionals and construction executives. This study delineates the development of this predictive model, outlining the data analysis process and the application of machine learning algorithms to tackle this complex commercial challenge. The ultimate goal is to bridge the gap between intuitive estimation and data-driven prediction, thereby enhancing the financial performance and strategic decision-making capabilities of firms in the agribusiness construction sector.

This paper provides an alternative Slope-Deflection equation for performing the static analysis of the indeterminate structures. While the conventional Slope-Deflection method introduced in undergraduate structural analysis course involves the use of fixed end moments in the Slope-Deflection equations, the proposed method employs the slope of a simply supported beam to obtain the unknown moments at the joints. Three numerical examples of continuous beams with different load configurations are chosen and the efficacy of the proposed equations is demonstrated. From the perspective of undergraduate structural analysis course in Civil Engineering education, the approach proposed in this paper offers two advantages: (1) prior knowledge of fixed beams is not required and (2) the concepts gained from determinate structural analysis are directly applicable.

We propose a pricing formula for a defaultable zero-coupon bond with imperfect information under a regime-switching model using a structural form of credit risk modelling. While the value of the firm’s equity is observed continuously, we assume that the total value of the firm is only observed at discrete times, such as the dates of the release of the firm’s annual reports, or quarterly reports. This uncertainty about the true value of the firm results in credit spreads that do not approach zero as the debt approaches maturity, which is a problem with many structural models. The firm’s value is typically defined as its equity and debt; however, we consider the asset-to-equity ratio, an accounting ratio used to examine a firm’s financial well-being. A dependent regime-switching process models the components of this ratio, and the Markov chain represents the states of the economy. The main contribution is to study this problem when the dynamics of a firm’s assets have different parameters with regime changes.

The basis for computation in the brain is the quantum threshold of the ‘soliton’ accompanying the ion changes of the action potential and the refractory membrane at convergences. We provide a logical explanation from the action potential to a neuronal model of the coding and computation of the retina and have explained how the visual cortex operates by quantum phase processing. In the small world network parallel frequencies collide into definable patterns of distinct objects. Elsewhere we have shown how many sensory cells are mean sampled to a single neuron and that convergences of neurons are common. We have also demonstrated, using the threshold and refractory period of a quantum phase pulse, that action potentials diffract across a neural network due to the annulment of parallel collisions in phase ternary computation (PTC). Thus, PTC applied to neuron convergences results in collective mean sampled frequency and is the only mathematical solution within the constraints of brain neural networks (BNN). In the retina and other sensory areas, we discuss how this information is coded and then understood in terms of network abstracts within the lateral geniculate nucleus (LGN) and visual cortex. First by defined neural patterning within a neural network, and then in terms of contextual networks, we demonstrate that the output of frequencies from the visual cortex contain information amounting to abstract representations of objects in increasing detail. We show that nerve tracts from the LGN provide time synchronisation to the neocortex (defined as the location of the combination of connections of the visual cortex, motor cortex, auditory cortex, etc). The full image is therefore combined in the neocortex with other sensory modalities so that it receives information about the object from the eye, and all abstracts that make up the object. Spatial patterns in the visual cortex are formed from individual patterns illuminating the retina and memory is encoded by reverberatory loops of computational actions potentials (CAPs). We demonstrate that a similar process of PTC may take place in the cochlea and associated ganglia, as well as ascending information from the spinal cord, and that this function should be considered universal where convergences of neurons occur.

The peptide hormone kisspeptin attenuates liver steatosis, metabolic dysfunction-associated stea-tohepatitis (MASH) and fibrosis in mouse models, by signaling via the kisspeptin 1 receptor (KISS1R). However, whether kisspeptin impacts fibrogenesis in the human liver is not known. We investigated the impact of a potent kisspeptin analog (KPA) on fibrogenesis using human precision cut liver slices (hPCLS) from fibrotic livers from male patients, in human hepatic stellate cells (HSCs), LX-2 and in primary mouse HSCs. In hPCLS, 48 h and 72 h of KPA (3 nM, 100 nM) treatment decreased collagen secretion, and lowered expression of fibrogenic and inflammatory markers. Immunohistochemical studies revealed that KISS1R is expressed and localized to HSCs in MASH/fibrotic livers. In HSCs, KPA treatment reduced transforming growth factor beta (TGFb)-induced expression of fibrogenic and inflammatory markers, in addition to decreasing TGFb induced collagen secretion, cell migration, proliferation and colony formation. Mechanistically, KISS1R signaling downregulated TGFb signaling by decreasing SMAD2/3 phosphorylation, via activation of protein-phosphatases PP2A, that dehosphorylates SMAD 2/3. This study revealed for the first time that kisspeptin reverses human hepatic fibrogenesis thus identifying it as a new therapeutic target to treat hepatic fibrosis.

The Universe is treated as an unbound thermodynamic system in which two forces of Nature compete: Attractive gravity loss and repulsive entropic gain. Entropic gain, although not presently considered a force of Nature, is otherwise well known and can be expressed with the gas laws. The Universe at the time of last scattering was all gas. Its instant gain is expressed as gas pressure. When the Gibbs equation is properly applied to this unbound gas, the resulting atomic Hubble parameter is found to be exclusively dependent on baryon density, giving a constant and perpetual two-to-one gain/loss ratio. Instant loss to gravity cannot offset gas pressure in this “thermal equation”. By contrast, the Friedmann equation, a ΛCDM foundation, treats baryon mass as accreted, having little if any entropic gain. These two equations are actually equivalent. Expanding accreted matter at its comoving critical density is herein shown to behave exactly like a freely expanding gas. However, neither equation includes all of today’s Universal kinetic energy, and cannot by themselves fully account for observed stellar movement. The present paper proposes the plausible existence of highly energetic or “suprathermal” free electrons which comprise about half of the intergalactic medium’s kinetic total. It is this suprathermal energy which Λ expresses. The fluid equation, another ΛCDM foundation, eliminates entropic gain from the Gibbs equation. Additionally, rest mass’s Einstein energy E=Mc² is treated as a thermal variable. These two assumptions, isoentropy and energy conflation, led astronomers to populate Λ as they followed the prior art.

This case study focuses on exploring the potential of biogas as a direct substitute for conventional fossil fuels in industrial applications. Instead of being limited to its common uses as a vehicle fuel or for power generation, this research aims to investigate how biogas can be integrated into industrial processes as an advanced and sustainable energy solution. By conducting a detailed analysis of the financial implications associated with the utilization of landfill gas and gas derived from biomass, a comprehensive understanding of their practical applications in the industrial sector can be obtained. This research goes beyond a superficial examination and delves into the intricate aspects of incorporating biogas as a viable alternative fuel source. When we say that utilizing biogas is technically feasible, it means that the necessary infrastructure and technologies are available to support its integration into industrial processes. This implies that there are existing methods and systems in place that can efficiently harness and utilize biogas for various industrial applications. These technologies ensure a seamless transition from conventional fossil fuels to renewable energy sources, leading to a more sustainable and environmentally friendly industrial landscape. Moreover, the statement that utilizing biogas is economically feasible emphasizes that the financial viability of employing biogas in industrial processes is advantageous. This research explores the potential cost savings and benefits associated with substituting conventional fuels with biogas. By carefully examining the economic aspects, such as initial investments, operational costs, and potential revenue streams, a comprehensive understanding of the financial impact of adopting biogas solutions in the industrial sector can be gained. By expanding and broadening the understanding of the technical and economic feasibility of biogas integration, this research aims to provide valuable insights into the potential of advanced biogas solutions for industrial applications. Indeed, to make biogas a viable and sustainable option as a raw material, it is necessary to establish farming subsidies and financial support specifically tailored for biogas production, similar to the existing support provided for food production. These subsidies and financial incentives play a crucial role in promoting and encouraging the growth of the biogas industry. By establishing such support systems, farmers and other stakeholders in the agricultural sector can be incentivized to participate in the production of biogas. This can involve the utilization of agricultural waste, organic residues, or dedicated energy crops for biogas generation. The financial assistance can help offset the initial investment costs, provide incentives for production, and ensure the economic viability of biogas projects. Moreover, when considering large-scale landfills or situations where industrial demands for energy are relatively low, landfill gas becomes a viable and practical option. Landfill gas, which is generated by the decomposition of organic waste in landfills, can be harnessed and utilized for various industrial purposes. This not only helps in managing waste but also provides a valuable source of renewable energy. In summary, while farming subsidies and financial support are crucial for promoting biogas production, landfill gas remains a viable option for large landfills or situations with minor industrial demands. The combination of these two approaches offers a comprehensive outlook on utilizing biogas as a renewable energy source for industrial applications.

With the global supply of LNG experiencing unprecedented growth, the industry is on the brink of a programmed glut, further exacerbated by the challenges posed by weaker energy pricing. In light of this, it is expected that marginal programs will be deferred temporarily, yet continuously assessed to enhance their economic potential in the future. Moreover, recent setbacks in LNG programs, such as cost overruns and delays, highlight the critical need for a unique conceptual design master plan. This plan will serve as a powerful tool to evaluate and optimize new programs, ensuring improved economic viability and boosting rates of return. By leveraging advanced analytical frameworks, innovative technologies, and comprehensive risk assessments, this study aims to develop a transformative approach that drives sustainable growth and profitability in the dynamic landscape of LNG program development." "This paper centers around the development of a comprehensive conceptual design master plan aimed at optimizing the total program economics across various areas, including sub-sea, offshore, and onshore advancements. The master plan serves as a crucial framework for identifying opportunities to reduce costs and enhance program definition, drawing insights from selective benchmarks derived from recent successful LNG programs. The ultimate objective is to boost the program rate of return while improving overall program definition, thereby mitigating the risks of cost overruns and schedule delays that have plagued the industry. By implementing this master plan, marginal programs stand a greater chance of becoming economically viable, fostering sustainable growth and enabling stakeholders to make informed decisions in the highly dynamic LNG landscape.

Besides the increase in global energy demand, access to clean energy, reduction in greenhouse gas emissions caused by conventional power generation sources, energy security, and availability of electricity in remote villages in emerging nations are some of the factors that foster the use of renewable energy sources (RESs) in generating electricity. One of the aims of initiating microgrids (MGs) is to maximize the benefits of RES and alleviate the associated grid integration issues. Microgrids are made up of RES connected to electrical loads within clearly delineated electrical limits that operate as individual controllable units on the electrical network. It can operate in-dependently as well as in connection with the grid. The paper presents an overview of microgrids and investigates the system's performance when connected to and disconnected from the grid. Furthermore, in both modes of operation, the functioning and behavior of system components such as the bidirectional DC-DC converter and energy storage system (ESS) were evaluated. The architecture of the proposed microgrid consists of a small hydropower plant, a wind farm, and a battery energy storage system (BESS). The microgrid under investigation is modeled and simu-lated using MATLAB and Simulink.

To elucidate mesenchymal stromal cells (MSC)-tumor intricate and ambiguous interactions, the reliable cell labeling and tracking techniques are imperative. Traditional methods of cell labelling have limitations mostly relevant to need for genetic modification what demands the exploration for alternative strategies. Here, we propose using fluorescent photoconvertible microcapsules containing Rhodamine B (RhB) to study mMSC migration in brain tumors. These 3 μm sized microcapsules are readily internalised by cells and undergo photoconversion under 561 nm laser exposure with fluorescence blue shift on demand. Optimal photoconversion was achieved with a laser irradiation duration of 0.4 ms, which provide a maximal brightness of photoconverted label without an excessive laser exposure on cells. Capsules modified with polyallylamine hydrochloride demonstrated the best potential for intracellular uptake without significantly affecting cell viability, motility, or proliferation. The optimal ratio of 20 capsules per mMSC was determined for labeling. Moreover, migration of individual mMSCs within 2D and 3D glioblastoma cell (EPNT-5) colonies over 2 days and in vivo tumor settings over 7 days was tracked. Our study unveils a robust platform for investigating MSC-tumor dynamics, offering insights into therapeutic strategies. Photoconvertible microcapsules could also become an indispensable tool for studying complex fundamental processes of cell-cell interactions for a wide range of problems in biology and medicine.

Transforming Small-Scale LNG Business, Enhancing Efficiency and Resilience in an Evolving Supply Chain In various industries, innovative systems have proven their value due to their efficiency and adaptability. A prime example of this lies in the rapid growth of the liquefied natural gas (LNG) market. LNG, a fuel derived from natural gas, has gained significant traction in recent years. In light of this, we aim to explore optimal strategies for small-scale LNG businesses, with a focus on revolutionizing their supply chain to ensure adaptability and sustainability. Our objective is to enhance efficiency and sturdiness in this evolving sector. By devising innovative methods and implementing cutting-edge technologies, we aim to revolutionize the small-scale LNG market, paving the way for a more optimized and resilient supply chain. Through this transformation, we strive to create a sustainable and adaptable framework that will drive the growth and success of a small-scale LNG businesses.LNG' ability to be transported and stored more cost-effectively in its reduced volume compared to natural gas in its original state is a significant advantage. The distribution network for LNG starts at numerous supply terminals and extends to a diverse range of consumption centers, each with varying tank capacities. In the broader economic context, the establishment of efficient routes for LNG Truck tank plays a critical role.To tackle the challenge of selecting a pickup location and determining optimal destinations with specific unloading volumes for liquefied natural gas (LNG), this research presents an innovative solution utilizing state-of-the-art machine learning techniques. The proposed approach combines the power of reinforcement learning, recurrent neural networks, online learning, and graph theory. By leveraging these cutting-edge techniques, we aim to develop an intelligent system that can effectively determine the most efficient pickup location and sequence of destinations for LNG delivery. This system will take into account various factors such as transportation costs tank capacity, and demand fluctuations. Through the integration of reinforcement learning, the system will continuously learn and improve its decision-making process in real-time. The recurrent neural networks will allow for the analysis of historical aim to model and optimize the complex network of pickup and delivery routes, considering factors such as distance, capacity constraints, and operational efficiencies. With this innovative approach, we strive to revolutionize the selection and planning process for LNG pickup and delivery, ultimately enhancing efficiency and reducing cost within the LNG supply chain.Improving the distribution network offers several financial benefits, including cost reduction, faster delivery times, more affordable distribution, and enhanced efficiency in the utilization of tanker trucks for LNG transportation. By optimizing the distribution network, transit costs associated with LNG transportation can be significantly lowered. This can be achieved through intelligent route planning, taking into account factors such as distance, traffic conditions, and fuel consumption. Minimizing transit costs contributes to overall savings for businesses operating in the LNG market. Faster delivery times are another advantage of an enhanced distribution network. By designing efficient routes and eliminating unnecessary detours or delays, the time taken for LNG to reach its intended destinations can be reduced. This not only improves customer satisfaction but also allows for more frequent deliveries and better coordination of supply and demand. Cheaper distribution is a direct outcome of an optimized distribution network. By strategically planning pickup locations, destinations, and intermediate stops, the costs associated with transferring LNG between terminals and consumption centres can be minimized. This leads to savings in transportation expenses, ultimately benefiting both businesses and end-users. Efficient utilization of tanker trucks is crucial for maximizing profitability in the LNG industry. An improved distribution network enables better allocation of resources, ensuring that tanker trucks are utilized optimally. This includes reducing empty or underutilized trips, maximizing load capacities, and minimizing idle time. Such efficiency improvements translate to cost savings and increased revenue for businesses involved in LNG transportation. Overall, the financial gains from improving the distribution network are substantial. Lower transit costs, faster delivery times, cheaper distribution, and more efficient use of tanker trucks contribute to increased profitability, competitiveness, and sustainability in the LNG market.

As the demand for fossil fuels continues to rise and their availability becomes increasingly limited, it is crucial to explore innovative approaches to optimize fuel combustion in existing systems. Among various engines, diesel engines are heavily reliant on fluid motion within the engine cylinder, which plays a critical role in fuel-air mixing. This abstract focuses on the potential of dynamic mathematical model simulation for multi-compartment rotor compressed combustion engines, aiming to revolutionize power generation by enhancing fuel burning efficiency. By leveraging advanced simulation techniques, this research seeks to unlock new insights into fluid dynamics and optimize fuel-air mixing, leading to more efficient and sustainable energy utilization. Through this exploration, we aim to pave the way for groundbreaking advancements in the field of combustion engines, ultimately contributing to a greener and more sustainable future. In the realm of internal combustion engines, the fluid dynamics within the engine cylinder greatly influence the combustion processes and heat transfer. For compression ignition (C.I) engines, both the bulk gas motion and turbulence characteristics play vital roles in engine performance. This study focuses on enhancing the combustibility of the fuel-air mixture in C.I engines by modifying the engine design to induce turbulence through squish and tumble flows. The modification involves creating multiple compartments on the rotor crown, comprising three small chambers spaced 120º apart. By implementing this design, the aim is to optimize the fuel-air mixing and improve the overall combustion efficiency. Through comprehensive analysis and experimentation, we seek to revolutionize C.I engine technology and pave the way for more efficient and environmentally-friendly power generation. In this study, the performance of a compression ignition (C.I) engine with a multiple compartment rotor has been analyzed under motoring conditions using computational fluid dynamics (CFD) simulations with FLUENT software. The obtained results have been compared with those of a base C.I engine. The analysis focused on the effects of the modified engine design on the tumble ratio and squish velocity, which are important parameters for fuel-air mixing and combustion efficiency. The results indicated a significant improvement with the modified engine, with a 35% increase in tumble ratio and a 31% increase in squish velocity compared to the base engine. These findings suggest that the modified engine design has the potential to enhance fuel-air mixing and combustion performance, leading to improved overall engine efficiency. This research presents promising insights into the optimization of C.I engine design and contributes to the development of more efficient and environmentally-friendly power generation technologies..

The Gestalt psychologists’ theory of insight problem-solving was based on a direct parallelism between perceptual experience and higher-order forms of cognition (e.g., problem-solving). Simi-larly to the sudden recognition of an ambiguous figure, they contended that problem-solving in-volves a restructuring of one's initial representation of the problem’s elements, leading to a sud-den leap of understanding phenomenologically indexed by the "Aha!" feeling. Over the last centu-ry, different scholars discussed the validity of the Gestalt psychologists’ perspective foremost us-ing the behavioral measures available at the time. However, in the last 2 decades, scientists gained a deeper understanding of insight problem-solving due to the advancements in cognitive neuroscience. This review aims to provide a retrospective reading of Gestalt theory based on the knowledge accrued by adopting novel paradigms and investigating their neurophysiological correlates. Among several key points that the Gestalt psychologists underscored, we focus specif-ically on the role of the visual system in marking a discrete switch of knowledge into awareness, as well as the perceptual experience and the holistic standpoints. While the main goal of this paper is to read the previous theory in light of new evidence, we also hope to initiate an academic dis-cussion and encourage further research about the points we raise.

The Universe at last scattering is locally treated as an unbound gas. The internal kinetic energy of the gas effectively constitutes a scalar energy field. The gas’s adiabatic expansion is entropic, giving repulsive entropic pressure. Gas kinetic energy is converted into entropic energy gain (63%) and isoentropic work against gravity (37%) at a constant 63:37 ratio. A three-term expression of the gas’s Hubble parameter is derived and found to be exclusively dependent on its mass density. At last scattering, this model gives a Hubble constant that is 125% of the value found from the ΛCDM model. After partition of Universal mass into the cosmic web of galaxies and the intergalactic medium (IGM), expansion came mostly from the IGM, presently comprising about 84% of total Universal mass and 90% of its volume. The onset of star formation within the cosmic web increased the IGM’s kinetic energy through the action of starlight, giving free electrons as an additional repository. Many of these free electrons are suprathermal. Suprathermal energy from both electrons and protons comprises about half of the IGM’s total kinetic energy and is expressed in the ΛCDM model as “dark energy” Λ. Entropic pressure derives from thermodynamic laws not found within general relativity.

The Heisenberg Lie algebra (HA) plays an important role in mathematics with Fourier transforms, as well as for the foundations of quantum theory where it expresses the operators of space-time, X, and their commutation rules with the momentum operators, D, that execute infinitesimal translations in X. Yet it is known that space-time is curved and thus the D operators must interfere thus giving “structure constants” that vary with location which suggests a mathematical generalization of the concept of a Lie algebra to allow for “structure constants” that are functions of X. We here investigate the mathematics of such a “generalized Heisenberg algebra” (GHA) which has “structure constants” that are functions of X and thus are in the enveloping algebra rather than constants. As expected, the Jacobi identity no longer holds globally but only in small regions of space-time where the [D, X] commutator can be considered locally constant and thus where one has a true Lie algebra. We show that one is able to reframe Riemannian geometry in this GHA. As an example, it is then shown that one can express the Einstein equations of general relativity as commutation rules. If one requires that the GHA commutator reduces to the HA of quantum theory in the limit of no curvature, then there are observable effects for quantum theory in this curved space time.

The microbiome gut brain (MGB) axis involves bidirectional routes of communication and has emerged as a potential therapeutic target for multiple medical specialities including psychiatry. Significant numbers of preclinical trials have taken place with some transitioning to clinical studies in more recent years. Some positive results have been reported secondary to probiotic administration in both healthy populations and specific patient groups. This review aims to summarise the current understanding of the MGB axis and the preclinical and clinical findings relevant to psychiatry. The link between the gut microbiome and irritable bowel syndrome (IBS) is well established. Significant differences have been identified between the microbiome of patients with a diagnosis of depressive disorder and healthy controls. Similar findings have occurred in patients diagnosed with bipolar affective disorder. A probiotic containing Lactobacillus acidophilus, Lactobacillus casei, and Bifidobacterium bifidum produced clinically measurable symptom improvement in patients with depressive disorder. To date some promising results have suggested that probiotics could play a role in the treatment of stress-related psychiatric disease. However, more well-controlled clinical trials are required to determine which clinical conditions are likely to benefit most significantly from this novel approach.

This research presents a maximum power point tracking of traditional single-ended primary converter (SEPIC) with the aid of fuzzy logic controller (FLC) for regulating the voltage and perturbation and observation(P&O) algorithms for regulating the reference voltage and reaching the maximum power point tracking. This is a promising technique for the conventional SEPIC converter to achieve maximum power point tracking with much less error. Moreover, the method is simple, reliable, and understandable for photovoltaic systems.

Influenza virus imprinting is now understood to significantly the influence immune responses and clinical outcome of influenza virus infections that occur later in life. Due to the yearly cycling of influenza viruses, humans are imprinted with the circulating virus of their birth year to subsequently build a complex influenza virus immune history but very little is known about how the imprinting strain influences vaccine responses. To investigate the imprinted host immune responses to split-virion vaccination, we imprinted ferrets with a sublethal dose of the historical seasonal H1N1 strain A/USSR/90/1977. After a +60 day recovery period was given to build immune memory, ferrets were immunized and the challenge at Day 123. Samples were collected throughout the time course and immunological assays were performed to investigate recall mechanisms. The preimmune-vaccinated ferrets did not experience significant disease during challenge while naïve-vaccinated ferrets had severe disease. Hemagglutination inhibition assays showed preimmune ferrets had a more robust antibody response post vaccination, increased virus neutralization activity. Virus specific immunoglobulins were of predominantly the IgG isotype suggesting B cell maturity and plasticity at vaccination. These results are important and should be considered for vaccine design.

A recent paper demonstrates the importance of the linker region joining the two SNARE motifs of the neuronal t-SNARE SNAP25 for maintaining rates of secretion with roles for distinct segments in speeding fusion pore expansion (Shaaban et al., 2019, Elife. 8). Remarkably, lipid perturbing agents rescue a palmitoylation-deficient phenotype that includes slow fusion pore expansion, suggesting that protein-protein interactions have a role not only in bringing together the granule or vesicle membrane with the plasma membrane but also in orchestrating protein-lipid interactions leading to the fusion reaction. Furthermore, biochemical investigations demonstrate the importance of the C-terminal domain of the linker in the formation of the plasma membrane t-SNARE acceptor complex for synaptobrevin2 (Jiang, et al., 2019, FASEB J. 33:7985-7994;Shaaban et al., 2019, Elife. 8). This insight, together with biophysical and optical studies from other laboratories (Wang, et al., 2008, Molecular Biology of the Cell. 19:3944-3955; Zhao, et al., 2013, Proc Natl Acad Sci U S A. 110:14249-14254) suggests that the plasma membrane SNARE acceptor complex between SNAP25 and syntaxin and the resulting trans SNARE complex with the v-SNARE synaptobrevin form just milliseconds before fusion.

Translation of basic animal research to find effective methods of diagnosing and treating human neurological disorders requires parallel analysis infrastructures. Small animals such as mice provide exploratory animal disease models. However, many interventions developed using small animal models fail to translate to human use due to physical or biological differences. Recently, large-animal minipigs have emerged in neuroscience due to both brain similarity and economic advantages. Medical image processing is a crucial part of research as it allows researchers to monitor their experiments and understand disease development. However, although many algorithms are created and optimized for MR analysis of human data, those tools are not directly applicable or sufficiently sensitive to measure minipig data. In this work, we propose PigSNIPE - a pipeline for the automated handling, processing, and analyzing of large-scale data sets of minipig MR images. The pipeline allows for image registration, AC-PC alignment, landmark detection, skull stripping, brainmasks and intracranial volume segmentation (DICE 0.98), tissue segmentation (DICE 0.82), and caudate-putamen brain segmentation (DICE 0.8) in under two minutes. To the best of our knowledge, this is the first automated pipeline tool aimed at large animal images.

The primary objective of this research was to assess the energy consumption of the gas treatment units at Bonny NLNG Refinery, the first Gas Refinery in Rivers State, Nigeria, while utilizing semi-lean amine. To achieve this goal, a simulation of the units was conducted using the advanced software package Aspen Hysys (V.8.3). The simulation was designed to accurately represent the dynamic behavior of the refinery's gas treatment units, allowing for a comprehensive analysis of their energy usage. The research aimed to quantify the energy consumption of the gas treatment units and identify opportunities for energy optimization. By utilizing semi-lean amine, which is known to improve energy efficiency, the study sought to evaluate the potential energy savings that could be achieved in the refinery's operations. The simulation model incorporated the specific design and operational parameters of the gas treatment units at Bonny NLNG Refinery, including the gas flow rate, lean amine concentration, absorber pressure, stripping temperature, amine circulation rate, and acid gas removal efficiency. By considering these parameters, the simulation accurately represented the dynamic behavior of the gas treatment units, enabling a detailed analysis of their energy consumption. Through the simulation, various scenarios and operational conditions were evaluated to determine the optimal set of parameters that minimized energy consumption. The research also examined the trade-offs between energy consumption, acid gas removal efficiency, and other performance indicators, such as amine circulation rate and regeneration efficiency. The findings of this research have significant implications for the energy efficiency and sustainability of gas treatment operations at Bonny NLNG Refinery. By identifying opportunities for energy optimization and providing recommendations for the utilization of semi-lean amine, the study contributes to the development of more efficient and environmentally friendly gas treatment processes. Overall, this research combines advanced simulation techniques with a comprehensive analysis of energy consumption to provide valuable insights into the energy efficiency of gas treatment units at Bonny NLNG Refinery, enabling informed decision-making and potential improvements in energy utilization. By utilizing the percentage-based unit simulation approach, a detailed examination of the energy consumption patterns was obtained. This analysis provides valuable insights into the operational efficiency and determination of potential energy-saving opportunities within the gas treatment units. This study specifically focuses on the integration of an absorption column split stream (stream flow) and a flash unit as a potential means to reduce the energy consumption of gas treatment devices. The integration of these units aims to optimize the overall energy efficiency of the gas treatment process by recovering and utilizing waste heat and reducing energy losses. The absorption column split stream allows for the diversion of a portion of the gas stream to a flash unit before entering the absorber. The flash unit operates at a lower pressure, which facilitates the release of entrained hydrocarbons and reduces the overall energy requirements for gas treatment. By separating and recovering the hydrocarbons in the flash unit, energy losses associated with their absorption and subsequent regeneration are minimized. Through the simulation, the study analyzes the energy consumption patterns of the gas treatment units with and without the integration of the absorption column split stream and flash unit. Comparative assessments are conducted to evaluate the energy savings and overall operational efficiency achieved through this integration. The findings of this research will provide valuable insights into the potential energy-saving opportunities offered by the integration of the absorption column split stream and flash unit in gas treatment devices. It will help refine the design and operation of gas treatment units, enabling more energy-efficient processes in the gas refining industry. By optimizing energy consumption in gas treatment units, the study contributes to the industry's goals of reducing greenhouse gas emissions and improving sustainability. The integration of the absorption column split stream and flash unit offers a promising approach to enhance energy efficiency, reduce operational costs, and minimize environmental impact. Overall, this research underscores the importance of exploring innovative solutions, such as the integration of different process units, to achieve energy savings in gas treatment operations. Through a comprehensive analysis of energy consumption patterns, this study aims to provide practical recommendations for optimizing energy efficiency in gas treatment units, fostering a more sustainable and efficient gas refining industry.The research specifically explores the impact of integrating the absorption column split stream and flash unit when dealing with sour gas streams containing carbon dioxide concentrations of less than mole ℅, while utilizing MDEA fluid as the solvent. Through comprehensive analysis and simulation using advanced software tools, the study demonstrates that by incorporating the absorption column split stream and flash unit, a significant reduction in device energy consumption of up to 10% can be achieved. The integration of the absorption column split stream and flash unit offers promising opportunities to enhance the energy efficiency of gas treatment devices. By diverting a portion of the gas stream to the flash unit, the separation of hydrocarbons and the subsequent release of entrained hydrocarbons at lower pressure significantly reduce the overall energy requirements for gas treatment. The comprehensive analysis and simulation conducted in the research provide concrete evidence of the energy-saving potential of this integration. By quantifying the energy consumption patterns and comparing scenarios with and without integration, the study establishes the effectiveness of the approach and its impact on operational efficiency. The findings of the research highlight the importance of considering the specific gas composition and utilizing appropriate solvents, such as MDEA, for optimizing energy efficiency. The integration of the absorption column split stream and flash unit not only reduces energy consumption but also offers the potential for cost savings and environmental benefits. Overall, the research demonstrates that by incorporating the absorption column split stream

A groundbreaking integrated predictive model, termed Cyber Forensics Behavioral Analysis (CFBA), has been developed in an environment characterized by rapidly evolving and increasingly sophisticated cyber threats. This model merges Cyber Behavioral Sciences with Digital Forensics to enhance the prediction accuracy and effectiveness of cyber threats originating from specific Autonomous System Numbers (ASNs). It has been observed that traditional cybersecurity strategies, predominantly focused on technical aspects, must be improved in addressing the complex landscape of cyber threats. Consequently, a novel approach has been proposed in this research, combining technical expertise with insights into the behavior of cybercriminals, thereby addressing a significant gap in existing methodologies. A mixed-methods approach has been employed in the study, integrating quantitative and qualitative research methods. This approach has created a comprehensive framework incorporating digital forensics, cybersecurity, computer science, forensic psychology, and the cyber behavioral sciences which incorporates disciplines scuch as cyberpsychology and forensic cyberpsychology. The study is anchored around four key concepts: (1) Forensic Cyberpsychology, which focuses on understanding psychological aspects of cybercriminal behavior; (2) Digital Forensics, involving the collection and analysis of digital evidence from cyber incidents; (3) Predictive Modeling, which utilizes historical data and patterns to anticipate potential cyber threats; and (4) the Cyber Behavioral Analysis Metric (CBAM) and Cyber Behavioral Score (CBS), tools designed for evaluating and scoring ASNs based on their behavior in terms of cybersecurity threat risks. Challenges encountered in the development of this integration have been significant. Initial setbacks included the misalignment of traditional cyber defense methods with the evolving nature of cyber threats and the absence of a holistic approach in pre-existing models. Through the narrative of these challenges and the subsequent development of the CFBA model, the research highlights the necessity for an interdisciplinary approach to cybersecurity. The outcomes of this study are not merely theoretical but provide practical, actionable tools and frameworks that markedly improve the precision of predicting cyber threats, especially from ASNs. The CFBA model represents a significant shift in cybersecurity strategies, highlighting the importance of integrating behavioral insights with technical knowledge. The study emphasizes the need for ongoing research and collaboration in cybersecurity, advocating for an approach that is as comprehensive and multifaceted as the cyber threats it seeks to mitigate. This research has been conducted to contribute significantly to cybersecurity, offering new perspectives and methodologies in a rapidly changing domain.

Previous studies have shown, in the United States (U.S.), that non-White communities are exposed to significantly higher temperatures in urban environments than complementary White populations. Studies highlighting this disparity have usually been cross-sectional and are therefore “snapshots” in time. Using surface urban heat island (SUHI) intensity data, U.S. Census 2020 population counts, and a measure of residential segregation, this study performs a comparative analysis between census tracts identified as prevalent for White, Black, Hispanic and Asian populations and their thermal exposure from 2003 – 2018. The analysis concentrates on the top 200 most populous U.S. cities. SUHI intensity is shown to be increasing through time for all examined tracts. However, the increase is only statistically significant for White and Black prevalent zones. There is a 1.25K to ~2.00K higher degree of thermal exposure on average for non-White relative to White prevalent areas. When examined on an inter-city basis, White and Black prevalent tracts had the largest disparity, as measured by SUHI intensity, in New Orleans, LA, USA by &lt; 6.00K. Hispanic (&gt;7.00K) and Asian (&lt;6.75K) prevalent tracts were greatest in intensity in San Jose, CA, USA. To further explore temporal patterns, two models were developed using a Bayesian hierarchical spatial temporal framework. One models the effect of varying the percentages of each population group relative to SUHI intensity within all examined tracts. Increases in percentages of Black, Hispanic, and Asian populations contributed to statistically significant increases in SUHI intensity. White increases in population percentage lowered SUHI temperature intensity. Throughout all modeled tracts, there is a statistically significant 0.01K per year average increase in SUHI intensity. A second model tests the effect of residential segregation on thermal inequity across all examined cities. Residential segregation, indeed, has a statistically significant positive association with SUHI intensity from this portion of the analysis. Similarly, there is a statistically significant 0.01K increase in average SUHI intensity per year for all cities. Results from this study can be used to guide and prioritize intervention strategies and furthers urgency related to social, climatic, and environmental justice concerns.

innate and adaptive immune responses lead to wound healing by regulating a complex series of events promoting cellular cross-talk. An inflammatory response is presented with its characteristic clinical symptoms: heat, pain, redness, and swelling. Some smart thermo-responsive polymers like chitosan can be used to create biocompatible and biodegradable scaffolds with 3D architectures similar to human structures, allowing their efficient and safe use as tissue engineering and drug delivery systems in chronic wounds. Locally heated tumors above polymer lower critical solution temperature can induce its conversion into a hydrophobic form, enhancing drug release until the thermal stimulus is gone, where a lower release is due to the swelling of the material. This paper integrates the relevant reported contributions of bioengineered scaffolds for thermo-responsive drug delivery in wound healing. Therefore, we present a comprehensive review that aims to demonstrate the capacity of these systems to provide spatially and temporally controlled release strategies for one or more drugs used in wound healing. In this sense, the novel manufacturing techniques of 3D-printing and electrospinning are explored for the tuning of their physicochemical properties to adjust therapies according to the patient’s convenience, as well as reduce drug toxicity and side effects.

While persons with schizophrenia find steady employment difficult to sustain, many of the women take on the most difficult task of all – motherhood. The aim of this paper is to review the challenges of motherhood in this population and the treatment strategies needed to keep mothers and children safe, protecting health and fostering growth. This is a narrative review reflecting the author’s life experience and a non-systematic search of the recent literature. Topics added are the stigma against motherhood in the context of schizophrenia, mothers’ painful choices, issues of contraception, abortion, and child custody, fostering and kin placement of children, the effects of antipsychotics, specific perinatal delusional syndromes, and parental supports. Recommendations are to work collaboratively with mothers who struggle with serious mental illness, take note of their strengths as well as their failings, offer a wide array of family services, monitor closely for safety, and appreciate the challenges these women daily face.

Severe mental illness such as schizophrenia is associated with factors such as unemployment, meagre per capita income, and residence in disadvantaged, poorly resourced neighbourhoods. This means difficult access to healthy food and is particularly problematic for pregnant women and mothers with children to feed. Eating problems are also linked to the necessity of taking antipsychotic drugs that often lead to serious cognitive, psychological, and behavioural sequelae. Psychosis makes it extremely difficult to maintain a healthy diet; nutritional deficiencies result, as do medical complications. The results of present literature review confirm the gravity of the problem and suggest a number of potentially useful interventions.

High-strength wastewaters from a variety of sources, including the food industry, domestic septage and landfill leachate, are often hauled to municipal wastewater treatment plants (WWTPs) for co-treatment. Due to their high organic loadings, these wastewaters can cause process upsets in both the WWTP’s liquid and solids treatment trains and consume organic treatment capacity, leaving less capacity available to service customers in the catchment area. A novel pre-treatment method, the Waste Activated Sludge-High Rate (WASHR) process, is proposed to optimize the co-treatment of high-strength wastewaters. The WASHR process combines the contact stabilization and sequencing batch reactor processes. It utilizes waste activated sludge from the municipal WWTP as its biomass source, allowing rapid start-up. Bench scale treatment trials of winery wastewater confirm the WASHR process can reduce loadings on the downstream WWTP’s liquid treatment and solids treatment trains. A case study approach is used to confirm the economic viability and environmental sustainability of the WASHR process compared to direct co-treatment using life cycle cost analyses and greenhouse gas emissions estimates.

The steep decline in the price of wind and solar photovoltaics provides a possibility to decarbonize electricity deeply and affordably. This study uses HOMER Pro energy modeling tool to model an optimized grid-connected renewable energy system for a community in southern Alberta, Canada. The study's goal is to identify the best renewable energy technology combinations that can provide electricity at the lowest levelized cost of energy (LCOE) and has lesser greenhouse gas emission as compared to the electricity produced by traditional fossil fuel. Gleichen, is a small town in southern Alberta and is near to numerous commercial wind and solar projects given the region’s high quality renewable resources. “Tri-brid” systems consisting of wind turbines, solar photovoltaics, and battery energy storage systems (BESS) are considered and compared based on electricity prices, net present cost, and greenhouse gas emissions savings. This tri-brid system is connected to the grid to sell excess electricity generated or buying electricity when there is less or no availability of solar and wind. The tri-brid energy system has an estimated LCOE of 0.0705 CAD/kWh which is competitive with the price of electricity generated by natural gas and coal which is 0.127 CAD/kWh.

Background: Process mining (PM) exploits event logs to obtain meaningful information about the processes that produced them. As the number of applications developed on cloud infrastructures is increasing, it becomes important to study and discover their underlying processes. However, many current PM technologies face challenges in dealing with complex and large event logs from cloud applications, especially when they have little structure (e.g., clickstreams). Methods: Using Design Science Research, this paper introduces a new method, called Cloud Pattern API – Process Mining (CPA-PM), that enables discovering and analyzing cloud-based application processes using PM in a way that addresses many of these challenges. CPA-PM exploits a new application programming interface (API), with an R implementation, for creating repeatable scripts that preprocess event logs collected from such applications. Results: Applying CPA-PM to a case with real and evolving event logs related to the trial process of a Software-as-a-Service cloud application led to useful analyses and insights, with reusable scripts. Conclusion: CPA-PM helps producing executable scripts for filtering event logs from clickstream and cloud-based applications, where the scripts can be used in pipelines while minimizing the need for error-prone and time-consuming manual filtering.

Excessive extracellular histones can damage cells despite their importance in DNA structure and gene regulation. We previously showed the harmful effect of histone 3.3 (H3.3) and its acetylated form (AcH3.3) in chronic obstructive pulmonary disease (COPD), but further research is needed to understand the in vivo underlying mechanisms. To investigate this, we administered a single dose of recombinant histones via intra-tracheal instillation in C57BL/6 mice and analyzed the outcomes after 48 hours. Both rH3.3 and rAcH3.3 effectively reached the bronchial and alveolar space. Lung histology revealed severe immune cell infiltration, rupture, damage, and thickening of many alveolar walls. Micro-CT scans showed macroscopic structure changes with a decreased tissue volume to total volume ratio. The administration of rH3.3 and rAcH3.3 induced lung apoptotic activity, as indicated by increased levels of cleavage caspase 3 and 9. Moreover, elevated plasma levels of pro-inflammatory cell mediators, including TNF-alpha, IL-6, MCP-3, and CXCL-1, were observed. The pathological changes and pro-inflammatory cytokine response were more pronounced in animals treated with rAcH3.3, which also exhibited leukocytosis and lymphocytosis. These findings emphasize the crucial role of extracellular H3.3 acetylation in inducing cytotoxicity and a robust, acute inflammatory response similar to what occurs in the lungs of COPD patients.

In the rapidly evolving field of sentiment analysis, the introduction of Transformer-based architectures, particularly the BERT model, has markedly improved accuracy levels, setting new standards in the analysis of textual sentiment. These advancements have been instrumental in enhancing the model's ability to grasp the nuances and complexities inherent in human language, thereby providing deeper insights into the sentiment expressed in various texts. However, the impressive performance of such deep learning models comes at the cost of increased computational demands and a lack of transparency in their decision-making processes. These challenges have reignited interest in rule-based sentiment analysis methods, which utilize sentiment lexicons for a more straightforward and computationally economical approach to determining text sentiment. Despite being overshadowed by the rise of machine learning models in recent years, these lexicon-based methods possess distinct advantages, including ease of interpretation and lower resource requirements, making them particularly appealing for certain applications. This paper seeks to re-evaluate the relevance and effectiveness of two prominent lexicon-based sentiment analysis methods, SO-CAL and SentiStrength, which have been specifically adapted for the language, in light of the advancements represented by Transformer-based models like SentBERT. Through a comprehensive comparative analysis, we examine the performance of these methodologies in contrast to SentBERT across an extensive collection of 16 text corpora, spanning a variety of genres and contexts. Our findings reveal a nuanced landscape of performance, where SentBERT's advanced capabilities typically afford it a significant advantage in accurately capturing sentiment. Nevertheless, in a surprising turn, the SO-CAL method exhibits exceptional performance on a substantial portion of the datasets, underscoring the continuing value and potential of lexicon-based approaches in sentiment analysis. This study not only highlights the strengths and weaknesses of both deep learning and lexicon-based methods but also opens the door for future hybrid approaches that could leverage the best of both worlds to achieve even greater accuracy and efficiency in sentiment analysis tasks.

Childhood obesity has become a global epidemic, with significant increases in prevalence over recent decades. While excessive calorie consumption and physical inactivity are known factors, emerging research highlights the role of Endocrine-Disrupting Chemicals (EDCs), particularly obesogens, in obesity's pathogenesis. This review explores the historical context of the environmental obesogens hypothesis, their sources, mechanism of action, impact on prenatal and postnatal development and epigenetics. Additionally, it discusses the long-term consequences of childhood obesity and proposes prevention strategies that will mitigate the negative health effects. Obesogens were found to disrupt hormonal balance and metabolic processes through various mechanisms such as altering gene expression, hormonal interference, and inflammation. Especially significant, was exposure during critical windows of development which correlates with increased risk of obesity in childhood or adolescence. Long-term effects of childhood obesity include chronic health conditions and psychosocial issues. A comprehensive approach is necessary to address childhood obesity, encompassing genetic, environmental, and lifestyle factors. Prevention strategies should focus on reducing obesogens exposure, promoting healthy lifestyles, and implementing regulatory policies. Future research should investigate obesogens-diet interactions, microbiome impacts, and combined obesogens effects. Long-term human studies are also crucial for validating findings from animal models and allow for inform decision-making to combat the obesity pandemic.

Bioprospecting native Australian plants offers potential discovery of latent and novel bioactive compounds. Promising cytotoxic and antibacterial activity of methanolic extracts of Pittosporum angustifolium and Terminalia ferdinandiana led to further fractionation and isolation using our laboratory’s bioassay guided fractionation protocol. Hence, the aim of this study was to further evaluate the bioactivity of the fractions and subfractions and characterize bioactive compounds using liquid chromatography mass spectroscopy (LC-MS/MS) and gas chromatography MS (GC-MS). Compounds tentatively identified in P. angustifolium Fraction 1 using LC-ESI-QTOF-MS/MS were chlorogenic acid and/or neochlorogenic acid, bergapten, berberine, 8’-epitanegool and rosmarinic acid. GC-MS analysis data showed the presence of around 100 compounds, mainly comprising of carboxylic acids, sugars, sugar alcohols, amino acids, and monoalkylglycerols. Furthermore, the fractions obtained from T. ferdinandiana flesh extracts showed no cytotoxicity, except against HT29 cell lines, and only Fraction 2 exhibited some antibacterial activity. The reduced bioactivity observed in the T. ferdinandiana fractions could be attributed to the potential loss of synergy as compounds become separated within the fractions. As a result, further fractionation, and separation of compounds in these samples were not pursued. However, additional dose-dependent studies are warranted to validate the bioactivity of T. ferdinandiana flesh fractions, particularly since this is an understudied species. Moreover, LC-MS/GC-MS studies confirm the presence of bioactive compounds in P. angustifolium Fraction 1/subfractions which helps to explain the significant acute anti-cancer activity of this plant. The screening process designed in this study has the potential to pave the way for developing scientifically validated phytochemical/bioactivity information on ethnomedicinal plants, thereby facilitating further bioprospecting efforts, and supporting the discovery of novel drugs in modern medicine.

In the rapidly evolving landscape of wireless communication, each successive generation of networks has achieved significant technological leaps, profoundly transforming the way we connect and interact. From the analog simplicity of 1G to the digital prowess of 5G, the journey of mobile networks has been marked by constant innovation and escalating demands for faster, more reliable, and more efficient communication systems. As 5G becomes a global reality, laying the foundation for an interconnected world, the quest for even more advanced networks leads us to the threshold of the sixth-generation (6G) era. This paper presents a hierarchical exploration of 6G networks, poised at the forefront of the next revolution in mobile wireless technology. This study delves into the technological advancements that underpin the need for 6G, examining its key features, benefits, and the key enabling technologies. We dissect the intricacies of cutting-edge innovations like terahertz communication, ultra-massive MIMO, artificial intelligence (AI), machine learning, quantum communication, and re-configurable intelligent surfaces. Through a meticulous analysis, we evaluate the strengths, weaknesses, and state-of-the-art research in these areas, offering a wider view of the current progress and potential applications of 6G networks. Central to our discussion is the transformative role of AI in shaping the future of 6G networks. By integrating AI and machine learning, 6G networks are expected to offer unprecedented capabilities, from enhanced mobile broadband to groundbreaking applications in areas like smart cities and autonomous systems. This integration heralds a new era of intelligent, self-optimizing networks that promise to redefine the parameters of connectivity and digital interaction. This paper also addresses critical challenges in the deployment of 6G, from technological hurdles to regulatory concerns, providing a holistic assessment of potential barriers. By highlighting the interplay between 6G and AI technologies, this study not only maps out the current landscape but also lights the path forward in this rapidly evolving domain. This paper aims to be a cornerstone resource, providing essential insights, addressing unresolved research questions, and stimulating further investigation into the multifaceted realm of 6G networks. By highlighting the synergy between 6G and AI(Artificial Intelligence) technologies, we aim to illuminate the path forward in this rapidly evolving field.

Mangoes have a unique nutrient profile (carotenoids, polyphenols, sugars, vitamins) that we hypothesized would mitigate post-exercise inflammation. This study examined the effects of mango ingestion in moderating exercise-induced inflammation in a randomized crossover trial with 22 cyclists. In random order with trials separated by a 2-week washout period, the cyclists ingested 330 g/day mangoes with 0.5 liters water or 0.5 liters water alone for 2 weeks, followed by a 2.25-h cycling bout challenge. Blood and urine samples were collected pre- and post-2 weeks supplementation, with additional blood samples collected immediately post-exercise, and then 1.5-h, 3-h, and 24-h post-exercise. Urine samples were analyzed for targeted mango-related metabolites. The blood samples were analyzed for 67 oxylipins that are upstream regulators of inflammation and other physiological processes. After 2-weeks mango ingestion, three targeted urine mango-related phenolic metabolites were significantly elevated compared to water alone (interaction effects, p≤0.003). Significant post-exercise increases were measured for 49 oxylipins, but various subgroup analyses showed no differences in the pattern of change between trials (all interaction effects, p&gt;0.150). The 2.25-h cycling bouts induced significant inflammation but no countermeasure effect was found after 2-weeks mango ingestion despite the elevation of mango gut-derived phenolic metabolites.

The fine chemical and pharmaceutical sectors are starting to advocate the use of flow chemistry due to reasons such as EHS, environmental, efficiency, cost saving and regulatory compliance. The use of trickle bed or fixed bed system could replace a batch autoclave typically used for hydrogenation reactions. However, there are few studies which detail the process from laboratory proof of concept through design to commercial realization. This study, using the production of 1,3-cyclohexanedione from catalytic hydrogenation of resorcinol as a case study demonstrates how the laboratory-scale recycle trickle bed can be used for catalyst screening and selection. Further, design data are generated by operation over a range of design superficial velocities and operating pressure that are used to derive a design correlation that is then used to specify a single stream plant at a level of definition consistent with a Preliminary Design for capital cost estimation. Finally, the further actions required in terms of data generation to increase the level of definition and confidence to a Sanction Grade or Final Design are discussed.

This study explores the potential of yoga in developing crucial executive competencies within the context of transitional economies in Eastern Europe. As public sector enterprises face increasing competition, both domestically and internationally, there is a growing need for executives to acquire new skills. Through the lens of mindfulness, this research investigates the impact of yoga on the helping behavior and cultural intelligence of business leaders in a transitional economy. The findings reveal that yoga practices significantly enhanced participants' helping behavior and cultural intelligence. The study demonstrates that approximately two-thirds of the impact on helping behavior can be attributed to increased mindfulness, with the remaining one-third stemming directly from yoga practice. In terms of cultural intelligence, the results indicate that 88% of the improvement is due to heightened mindfulness, while 12% is directly attributable to yoga practices.

The Food and Drug Administration’s 2011 Process Validation Guidance and International Council for Harmonization Quality Guidelines recommend continued process verification (CPV) as a mandatory requirement for pharmaceutical, biopharmaceutical, and other regulated industries. As a part of product life cycle management, after process characterization in stage 1 and process qualification and validation in stage-2, CPV is performed as stage-3 validation during commercial manufacturing. CPV ensures that the process continues to remain within a validated state. CPV requires the collection and analysis of data related to critical quality attributes, critical material attributes, and critical process parameters on a minimum basis. Data is then used to elucidate process control regarding the capability to meet predefined specifications and stability via statistical process control tools. In statistical process control, control charts and Nelson rules are commonly used throughout the industry to monitor and trend data to ensure that a process remains in control. In the control chart, the mean value is taken as the center line, and 3σ limits are placed on either side of the center line. In CPV, manufactured lots are summarized, trended, and discussed at a cross-functional level at pre-defined intervals (either weekly, bi-weekly, or even monthly) based on the batch run rate. A cross-functional team assesses details regarding 1) violation frequency, 2) statistical strength of the signal, 3) violation magnitude and its impact on process or quality, and 4) any potential root causes for out-of-expectation or out-of-trend signals. The cross-functional team must analyze whether any signal identified by the control chart is reliable and must determine whether corrective action should be taken and justify the decision in the CPV meeting minutes based on statistical strength and reliability of the signal. However, basic control charts are susceptible to false alarms and nuisance alarms. Therefore, it is imperative to understand the assumptions behind control charts and the inherent false alarm rates for different Nelson rules. In this article, the authors have detailed the assumptions behind the usage of control charts, the rate of false alarms for different Nelson rules, the impact of skewness and kurtosis of a data distribution on the false alarm rate, and methods for optimizing control chart design by reducing false alarm rates and nuisance signals.

A good optical quality crystal of 2-aminopyridine (2AP) metal complex crystals was grown by slow evaporation technique at room temperature. The transparent and defect less bulk size of 2-aminopyridine potassium dihydrogen orthophosphate metal complex crystals have been grown by solution growth method. The molecular structure and morphology of grown crystals was drawn and planes are indexed using WINXMORPH software. A optical absorption spectrum, the UV cut-off wavelength, Band gap (Eg), Reflectance (R), Refractive Index (n), Extinction coefficient (K) and Electrical susceptibility (χc) are calculated for 2AP metal complex crystals.

Background: The efficacy of sunscreen is evaluated by SPF values, which are quantitatively determined in laboratories on the backs of human subjects according to a standardized procedure. However, SPF cannot be directly translated to sunburn protection under real-life situations because actual efficacy depends on various factors related to human behaviors and environmental conditions. This study clinically evaluated the efficacy of two sunscreen sprays (SPF 30 and SPF 70) under natural sunlight exposure on healthy subjects at the beach. Methods: Twenty subjects were divided into two cells for the two sunscreen sprays (SPF 70 and SPF 30) in a single-center, actual usage test. The primary endpoint of the study was sunburn protection on the dorsal arms and the secondary endpoint was protection on the face and neck. Subjects stayed at the beach for 4 h after application of the sunscreens with normal beach activities. Subjects’ behavior at the beach, the amounts of sunscreen applied and reapplied, and environmental conditions were all recorded. Results: There was no significant sunburn for a majority of the subjects in either cell. However, neither sunscreen completely blocked the sunburn, especially for the face/neck area. We found that the SPF 70 sunscreen was more effective than the SPF 30 sunscreen. Conclusion: Modern sunscreen sprays, applied liberally, are effective in providing sunburn protection for the body in a beach setting.

Chronic inflammation may have a detrimental impact on human health as it tends to result in cancer. In addition, it is often linked to different steps that participate in tumorigenesis, including cellular transformation, survival, promotion, invasion, proliferation, angiogenesis, and metastasis. Hence, inflammation predisposes cancer development and plays a vital role in promoting all tumorigenesis stages. Inflammation is caused by many factors, such as bacterial and viral infections, tobacco smoking, autoimmune diseases, obesity, asbestos exposure, and many others, increasing cancer risk. Moreover, cancer can be enhanced by mutations that proceed to cancer progression. Consequently, it leads to immunosuppression and provides a favorable background for tumor development. Although many studies address the question of relationships between inflammation and cancer development, little attention is paid to the link between inflammation and blood cancer. Therefore, the current study reviews the role of inflammation in cancer development, particularly in blood cancer. A meta-analysis research approach meets the research objective and answers the research question. The review results indicate that chronic inflammation directly relates to the development of many cancer types, blood cancer in particular.

Research into the neurobiological and psychosocial mechanisms involved in fibromyalgia (FM) has progressed remarkably in recent years. Despite this, currents accounts of FM fail to capture the complex, dynamic and mutual crosstalk between neurophysiological and psychosocial domains. We conducted a comprehensive review of the existing literature in order to synthesise current knowledge on FM, explore and highlight multi-level links and pathways among different systems and build bridges between existing approaches. An extensive panel of international experts in neurophysiology and psychosocial aspects of FM discussed the collected evidence and progressively refined and conceptualized its interpretation. Fibromyalgia is a complex condition resulting from the dynamic interplay between multiple systems and processes. We provided an updated overview of the most relevant observations in FM to date as well as the potential pathways by which they exert they are related and exert their mutual influence, to produce the manifestations commonly associated with FM. This review constituted the first step towards and supported the development of a much needed model capable of integrating the main factors implicated in FM into a single, unified model that may prove valuable in understanding and managing FM.

Succinate is proposed to be a mediator of muscle exercise-induced adaptations. We studied metabolic health and changes of muscle mass in 6-month-old male mice after 12 weeks of feeding regular diet (RD, 13.4 kcal% fat, 66.8 kcal% carbohydrate, 29.8 kcal% protein), high fat diet (HFD, 60 kcal% fat, 20 kcal% carbohydrates, 20 kcal% protein) and ketogenic diet (KD, 80 kcal% fat, &lt;1 kcal% carbohydrates, 20 kcal% protein) with or without 2% succinate supplements (SUS) in drinking water (n=8-12 per group). Functional overloading of the plantaris muscle (PL) was induced in a group of mice by denervation of the gastrocnemius and soleus muscles at week 6 of feeding different diets. HFD induced the greatest (p &lt; 0.001) increase in body and fat mass. HFD and KD lead to significant (p &lt; 0.01) impairment in glucose tolerance compared to RD. SUS blunted (p &lt; 0.01) initial surge in energy intake when mice were switched from RD to HFD, but did not influence any measures of metabolic health after 12 weeks of the study. Functional overloading lead to ~25% increase in PL mass which was not affected by diet or SUS. In conclusion, SUS does not have a long-term effect on metabolic health or muscle mass.

Background: The uptake of COVID-19 booster vaccines has been significantly low. Therefore, it is questionable whether combining the COVID-19 booster vaccines with Influenza vaccines can increase the population's interest in taking such vaccines and manage the health pandemic effectively. Methodology: In this systematic review and meta-analysis, a synthesis of the findings and summary of a total of 30 research articles based on the topic, ‘combining influenza and COVID-19 booster vaccination strategy’ was undertaken. The research articles were identified from three databases, namely, PubMed, Cochran Library, and Google Scholar using specific keywords and inclusion criteria. However, research articles that were not peer-reviewed and not published in English were excluded from the systematic review and meta-analysis. The average risk ratio of the included articles was 0.78% based on a 95% CI. On the other hand, the heterogeneity between such studies was I² = 35%, while the statistical significance of their findings occurred at p < 0.05. The average p-value of the included research studies was p = 0.62, implying that the null hypothesis was not rejected in almost all the studies. Results: A synthesis of the chosen research articles revealed that when influenza and COVID-19 booster vaccines are combined, there is potential for an increase in the uptake of the latter, mainly because many populations have already been accustomed to taking influenza vaccines on an annual basis. Conclusions: In this way, through such findings, medical health experts can make informed decisions to increase the population's willingness to receive the COVID-19 booster vaccines.

The COVID-19 pandemic halted progress in global vaccine coverage and disrupted routine childhood vaccination practices worldwide. While there is ample evidence of vaccination declines experienced during the pandemic, it is less clear how low-income countries were affected. We executed a systematic review to synthesize the current literature on impacts to routine childhood vaccinations in low-income countries from January 1, 2020 to February 8, 2023. We collected data using an extraction form on Covidence and assessed the quality of studies included in the review using the Risk of Bias in Non-Randomized Studies of Interventions (ROBINS-I) tool. Effect estimates for changes in vaccination during the pandemic were reported and summarized. Factors that influenced changes were grouped into descriptive themes. Thirteen studies, encompassing 18 low-income countries and evaluating 15 vaccines at varying doses, were included in the final review. We found that routine childhood vaccinations during the COVID-19 pandemic varied considerably by vaccine type, location, and phase of the pandemic. Nine different themes were identified as factors that influenced changes in vaccination. Documenting past experiences and lessons learned is crucial for informing preparedness efforts in anticipation of future public health emergencies. Failure to effectively address these things in the next public health emergency could result in a recurrence of declining routine childhood vaccinations.

(1) Background: The definition of value addition is based on the process or processes which are used to transform physically the initial raw material in the final food or non-food article. Diversification can enhance the possibility of increased gains. The aim of this work is to give a reliable description of value addition when speaking of coconut-based beverages among all possible derivatives; (2) Methods: a systematic review of main papers on the argument has been critically examined and discussed; (3) Results: Processing degree is a consequence of consumers’ requests. Three different drivers for value addition have been considered: packaging, durability, and size options; sensorial features; and sustainability. Results of this investigation have highlighted the added value of several products because of recyclable packaging materials, intermediate or long durability expectations, different available sizes, and good or excellent sensorial performances; (4) Conclusions: There are different value-added coconut-based beverages with interesting perspectives. On the other side, sustainability and eco-friendly policies may be a problem for those products which are produced similarly to non-coconut based beverages. The opportunity of certified organic and/or fair-trade products could help the industry of coconuts in the next future. More research is still needed in this ambit.

Background of the Study: We investigated the link between hypertension and cancer since it has been suggested that hypertension may raise the long-term risk of cancer. Previous large observational cohort studies found that greater blood pressure (BP) was related to a higher risk of cancer. Mendelian randomization (MR) was utilized to produce less confounded blood pressure estimates (BP) on overall and site-specific malignancies. The study aims to draw conclusions on the relationship between high blood pressure and cancer. Methods: Studies on high blood pressure and various malignancies are inconclusive, except for renal cell carcinoma. However, given that most meta-analyses only contained a limited number of trials, some relative risks had small to moderate magnitudes, and several may have been impacted by residual confounding, careful interpretation is necessary. The study was conducted using the meta-analysis technique. Cochran's Q test and I2 test were used to assess statistical heterogeneity between studies in the current investigation for research involving two or more cause and outcome combinations. Results: Positive correlations were also reported between high blood pressure and esophageal adenocarcinoma, squamous cell carcinoma, liver, and squamous cell carcinoma. However, most studies lacked multivariable adjustments. Physical and numerical risk of cardiovascular disease is linked to bowel cancer but no other cancers. According to a meta-analysis, hypertensive persons could also be at increased danger of gastrointestinal and breast cancer. Most meta-analyses comprised several trials with moderate or mild hazard ratios.ConclusionDifferent types of cancers have been noted to be directly caused by hypertension. In addition, some treatments have also been associated with the side effects of cancer treatments to cause hypertension. Women facing hypertension have an increased risk of getting breast cancer. Although some cancers showed a real relationship with hypertension, others had no connection at all.

forging a resilient path towards a low carbon future, this research delves deep into the intricate dynamics of the petroleum and petrochemical industries. By uncovering the challenges posed by transitioning to a low carbon economy, this study emphasizes their transformative potential as catalysts for growth. Through an in-depth analysis of the oil and natural gas sector, it not only sheds light on the carbon footprint of Nigeria's petroleum and petrochemical industries but also identifies the opportunities for sustainable transformation within these sectors. Ultimately, this research aims to pave the way for a greener future by unraveling the complexities and intricacies of building a low carbon economy."By incorporating the unique attributes of the petroleum and petrochemical industries and considering the evolving domestic and global context, this research investigates the challenges and prospects associated with the shift towards a low-carbon economy. It delves deep into the complexities of the sector, taking into consideration the distinct characteristics of petroleum and petrochemical production. Through a comprehensive analysis, this study aims to uncover the potential barriers and opportunities that arise from the pursuit of a sustainable and low-carbon future within the petroleum and petrochemical industries. In addition, this research thoroughly examines the current global and local conditions, shedding light on the opportunities for growth and transformation within the petroleum and petrochemical sectors. By presenting insightful perspectives and recommendations, the study aims to provide valuable guidance for fostering the development of a low-carbon economy within these industries. Ultimately, the research seeks to drive positive change by offering actionable insights and strategies to propel the transition towards a sustainable future.

A significant number of research studies have focused on determining whether BMI influences various types of cancer. The findings of these studies showed that people have to manage their BMIs to decrease their risk of developing various types of cancer, one of which is ovarian cancer. A PRISMA guideline for systematic review and meta-analysis was used to identify 20 research studies related to the topic to establish the truth or falsity of the findings. Later, their findings were synthesized. The synthesis of the findings of such research articles suggests that overweight and obesity increase an individual’s risk of developing ovarian cancer and experiencing severe symptoms of the disease. In such a manner, the current research study can conclude that effective management of BMI is necessary for decreasing the prevalence and mortality rates associated with ovarian cancer.

Grill-specific footprints for common fuels/grill types in the USA are estimated from public information and data from a major grill manufacturer. These are a function of both 1) a fuel’s footprint and 2) a grill’s efficiency of cooking. In 2022, grill-specific footprints vary by 9:1. A typical gas grill is highest at 3.6 lb CO2e/grill session, nine times that of a wood-pellet grill, lowest at 0.4 lb. Charcoal briquettes, electricity and super-efficient gas grills come in-between. Pellets are lowest, because they are made from waste wood and their production burden is modest. Electricity has the highest fuel footprint, yet the second-lowest grill-specific footprint, thanks to its high efficiency. Briquettes come in fourth, because their production involves fossil gas, and they contain some fossil coal. Grill efficiency is key for gas (natural gas or propane): a typical gas grill has twice the footprint of a super-efficient one. In 2027, with bio substitution, the super-efficient gas grill would move ahead of pellets. Electricity and charcoal could improve but would still place fifth and sixth. The range of grill-specific footprints could fall to 4.5:1, within a much-lower range, the highest footprint in 2027 almost 60% lower than 2022’s highest.