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.

Attempts to use computers to aid in the detection of breast malignancies date back more than 20 years. Despite significant interest and investment, this has historically led to minimal or no significant improvement in performance and outcomes with traditional computer aided detection. However, recent advances in artificial intelligence and machine learning are now starting to deliver on the promise of improved performance. There are at present more than 20 FDA approved AI applications for breast imaging, but adoption and utilization are widely variable and overall low. Breast imaging is unique and has aspects that create both opportunities and challenges for AI development and implementation. Breast cancer screening programs worldwide rely on screening mammography to reduce the morbidity and mortality of breast cancer and many of the most exciting research and available AI applications focus on cancer detection for mammography. There are however multiple additional potential applications for AI in breast imaging including decision support, risk assessment, breast density quantitation, workflow and triage, quality evaluation, response to neoadjuvant chemotherapy assessment, and image enhancement. In this review the current status, availability, and future directions of investigation of these applications are discussed, as well as the opportunities and barriers to more widespread utilization.

Background: Throughout the COVID-19 pandemic, hospital medical staff (HMS) have faced significant personal, workplace, and financial disruption. Many have experienced psychosocial burden, exceeding already concerning baseline levels. This study examines the types and predictors of coping strategies and help-seeking behaviours utilised by Australian junior and senior HMS during the first year of the pandemic. Methods: A cross-sectional online survey of Australian frontline healthcare workers was conducted between 27th August and 23rd October 2020. Data collected included demographics, personal and workplace disruptions, self-reported and validated mental health symptoms, coping strategies, and help-seeking. Results: The 9518 participants included 1966 hospital medical staff (62.1% senior, 37.9% junior). Both groups experienced a high burden of anxiety, depression, post-traumatic stress disorder, and burnout. Coping strategies varied by seniority, with maintaining exercise the most common strategy for both groups. Adverse mental health was associated with increased alcohol consumption. Engagement with professional support, although more frequent among junior staff, was uncommon in both groups. Conclusions: Junior and senior staff utilised different coping and help-seeking behaviours. Despite recognition of symptoms, very few HMS engaged formal support. The varied predictors of coping and help-seeking identified may inform targeted interventions to support these cohorts in current and future crises.

Alcohol abuse can result in detrimental multisystem effects. Chronic alcohol abuse is known to be associated with pathophysiological changes in multiple organs often resulting in life threatening clinical outcomes e.g. breast and colon cancer, pancreatic disease, cirrhosis of the liver, diabetes, osteoporosis, arthritis, kidney disease, immune system dysfunction, hypertension, coronary artery disease, alcohol-induced cardiomyopathy and heart failure as well as central nervous system disorders. In this review article, we will discuss the multisystemic effects of alcohol abuse and explore in greater detail alcohol’s impact on two main systems that result in pathophysiological changes i.e. the cardiovascular and central nervous systems.

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.

Dynamic systems which underly controlled systems are expected to increase in complexity as robots, devices, and connected networks become more intelligent. While classical stable systems converge to a stable point (a sink), another type of stability is to consider a stable path rather than a single point. Such stable paths can be made of saddles which draw in trajectories from certain regions, and then push the trajectory toward the next saddle point. These are chains of saddles are called stable heteroclinic channels (SHCs), and can be used in robotic control to represent time sequences. While we have previously shown that each saddle is visualizable as a trajectory waypoint in phase space, how to increase the fidelity of the trajectory was unclear. In this paper, we hypothesized that the waypoints can be individually modified to locally vary fidelity. Specifically, we expected that increasing the saddle value (ratio of saddle eigenvalues) causes the trajectory to slow to more closely approach a particular saddle. Combined with other parameters that control speed and magnitude, a system expressed with an SHC can be modified locally, point by point, without disrupting the rest of the path, supporting their use in motion primitives. However, even more complex trajectory shape modifications are possible. While some combinations can enable a trajectory to better reach into corners, other combinations can rotate, distort and round the trajectory in the region of a corner. In our example, modifying select saddle values produced a 32% decrease in the trajectory error of a complex trajectory produced using this system. This is an effect not visible in previous 1D studies, that can lead to different learnable and tunable representations of dynamic systems.

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..

Leaders are essential in encouraging and facilitating creative thinking among members of a group or organization. A leader must also monitor the group's initiatives to encourage innovation and fresh thinking. In this article, we take a look at the circumstances under which there is a link between leadership and original problem-solving. Thirty separate studies served as the basis for this sample. Many of these analyses see leadership independently from the concept of innovation. Both moderating and mediating factors were discussed, and two additional factors were identified for which no firm conclusions could be drawn. This investigation reveals three new potential mediators or moderators of the connection between leadership and inventiveness.

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.

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.

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.

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

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.

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.

There is increasing evidence that rising temperatures and heatwaves in the United Kingdom are associated with an increase in heat-related mortality. This study aims to retrospectively quantify the impact of heatwaves on mortality during the 2019 summer period using daily death occurrences. Second, it compares excess mortality during the 2019 heatwaves to excess mortality during the 2018 and 2017 heatwave periods. Lastly, it compares the excess mortality in the 2017-2019 heatwaves to the estimated excess deaths for the same period in the Public Health England (PHE) Heatwave mortality monitoring Reports. The cumulative number of excess deaths during the summer 2019 heatwaves were minimal and were substantially lower than during the summer 2018 heatwaves (1,700 deaths) and summer 2017 heatwaves (1,489 deaths). All findings were at variance with the PHE Heatwave mortality monitoring reports which estimated cumulative excess deaths to be 892, 863 and 778 during the summer period of 2019, 2018 and 2017 respectively using provisional death registrations. Issues have been identified in the use of provisional death registrations for mortality monitoring and the reduced reliability of the ONS daily death occurrence database before 2019. These findings may identify more reliable ways to monitor heat mortality during heatwaves in the future.

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.

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.

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.

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

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.

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.

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.

Spironucleosis is considered one of the most significant enteric infectious diseases in young and growing game birds. Despite its importance diagnosing spironucleosis in game birds remains a continuing problem as no 'gold standard' test exists and there is no consensus for the use of the available methods for the diagnosis of spironucleosis in game birds. In this study we describe veterinarians’ perceptions of the adoption of existing methods for the diagnosis of spironucleosis in game birds and identify implications for the development of diagnostic guidelines. A questionnaire was used to evaluate participants’ familiarity with and use of existing diagnostic methods for spironucleosis, and to assess their perceptions of the adoption of these methods in their geographic regions. We surveyed veterinarians in practices in East Anglia (EA) and Northern Ireland (NI), UK with expertise or involvement in the treatment and/or diagnosis of spironucleosis in game birds. Of the 261 participants surveyed, 15 EA and 13 NI veterinarians (10.7%) responded to the questions on existing diagnostic methods. The study results indicate an overall insufficient knowledge and skills in the diagnosis and treatment of spironucleosis among veterinarians surveyed. These findings highlight the need for improved training of veterinarians in the diagnosis of spironucleosis.

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 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.

Background: Sudden changes in clinical practice and the altered ability to care for patients due to the COVID-19 pandemic have been associated with moral distress and mental health concerns in healthcare workers internationally. This study aimed to investigate the severity, prevalence, and predictors of moral distress experienced by Australian healthcare workers during the COVID-19 pandemic. Methods: A nationwide, voluntary, anonymous, single time-point, online survey of self-identified frontline healthcare workers was conducted between 27th August and 23rd October 2020. Participants were recruited through health organisations, professional associations or colleges, universities, government contacts, and national media. Results: 7846 complete responses were received from nurses (39.4%), doctors (31.1%), allied health staff (16.7%) or other roles (6.7%). Many participants reported moral distress related to resource scarcity (58.3%), wearing PPE (31.7%) limiting their ability to care for patients, exclusion of family going against their values (60.2%), and fear of letting co-workers down if they were infected (55.0%). Many personal and workplace predictors of moral distress were identified, with those working in certain frontline areas, metropolitan locations, and with prior mental health diagnoses at particular risk of distress. Moral distress was associated with an increased risk of adverse mental health outcomes. Feeling appreciated by the community mitigated this risk in healthcare workers. Conclusions: Safeguarding healthcare workforces during crises is important for both patient safety and workforce longevity. Targeted interventions are required to prevent or minimise moral distress and associated mental health concerns in healthcare workers during COVID-19 and other crises.

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.

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.

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.

Low-cost particulate matter (PM) sensors offer an excellent opportunity to improve our knowledge about this type of pollution. Their size and their cost, which support multi-node network deployment, along with their temporal resolution, enable them to report fine spatio-temporal resolution for a given area. These sensors have known issues across performance metrics. Generally, the literature focuses on the PM mass concentration reported by these sensors but some models of sensors also report particle number concentrations (PNC) segregated into different PM size bins. In this study, 8 units of each Alphasense OPC-R1, Plantower PMS5003 and Sensirion SPS30 have been exposed, under controlled conditions, to short-lived peaks of PM generated using two different combustion sources of PM, exposing the sensors to different particle size distributions to quantify and better understand the low cost sensors performance across a range of relevant environmental ranges. The PNC reported by the sensors were analysed. This study showed that there is added value in directly using the PNC reported by the sensors instead of the mass concentrations, which could aid the efforts to calibrate these sensors to a known accuracy. It demonstrated that all sensors tested here could track the fine temporal variation of PNC, that the Alphasense OPC-R1 could closely follow the variations of size distribution between the two sources of PM, and it showed that particle size distribution and composition are more impactful on the sensors measurement than relative humidity.

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..

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 < 6.00K. Hispanic (>7.00K) and Asian (<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.

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.

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

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.

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.

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.

Speleothem oxygen isotope records from the Caribbean, Central, and North America reveal climatic controls that include orbital variation, deglacial forcing related to ocean circulation and ice sheet retreat, and the influence of local and remote sea surface temperature variations. Here, we review these records and the global climate teleconnections they suggest following the recent publication of the Speleothem Isotopes Synthesis and Analysis (SISAL) database. We find that low-latitude records generally reflect changes in precipitation, whereas higher latitude records are sensitive to temperature and moisture source variability. Tropical records suggest precipitation variability is forced by orbital precession and North Atlantic Ocean circulation driven changes in atmospheric convection on long timescales, and tropical sea surface temperature variations on short timescales. On millennial timescales, precipitation seasonality in southwestern North America is related to North Atlantic climate variability. Great Basin speleothem records are closely linked with changes in Northern Hemisphere summer insolation. Although speleothems have revealed these critical global climate teleconnections, the paucity of continuous records precludes our ability to investigate climate drivers from the whole of Central and North America for the Pleistocene through modern. This underscores the need to improve spatial and temporal coverage of speleothem records across this climatically variable region.

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.

Cyanobacteria produce a wide range of structurally diverse cyanotoxins and bioactive cyanopeptides in freshwater, marine, and terrestrial ecosystems. The health significance of these metabolites, which include genotoxic- and neurotoxic agents, is confirmed by continued associations between the occurrence of animal and human acute toxic events and, in the long term, by associations between cyanobacteria and neurodegenerative diseases. One of the implicated mechanisms includes a misincorporation of cyanobacterial non-proteogenic amino acids leading to mistranslation and protein misfolding. A better understanding of the interaction between the cyanopeptide metabolism and the nervous system will be crucial to target or to prevent pathogenic response.

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.

Mixed reality technology is being increasingly used in cultural heritage attractions to enhance visitors’ experience. However, how the characteristics of mixed reality affect satisfaction and brand loyalty has not been explored in previous research. The purpose of this study is to identify factors affecting satisfaction with mixed reality experiences at cultural and artistic visitor attractions and their influence on brand loyalty, which is connected with management performance. We propose a theoretical model based on brand equity theory in the context of mixed reality experience. Survey data were gathered from 251 respondents visiting a cultural and artistic visitor attraction in Seoul, Korea using a stratified sampling method. PLS-SEM was employed for the data analysis. The results suggest that the characteristics of mixed reality (interactivity, vividness) not only influence the affective aspects (perceived immersion, perceived enjoyment) of visitors’ experience, but also positively affect brand awareness, brand association, and brand loyalty.

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.

Global anaesthesia workforce limitations contribute to emigration of skilled anaesthesiologists from lower- to higher-income countries, jeopardizing workforce balance and patient outcomes in Pakistan. This study aims to explore challenges experienced by anaesthesiologists in Punjab, Pakistan’s most populous province, and necessary changes to encourage their retention. We conducted a qualitative study to examine perspectives of anaesthesiologists who chose to serve in Pakistan. We drew data from semi-structured interviews conducted with 25 purposively-sampled consultant anaesthesiologists. We analysed data thematically and distinguished the practice hurdles faced by anaesthesiologists in public and private hospitals of Punjab. The main reasons to work abroad could be broadly categorized under two inductive themes, i.e. practice hurdles in public and private sector. Both had distinct issues which compromised the number and quality of anaesthesia workforce in the country. The key outcomes were workplace security, promotion/incentive issues and gender inequalities in the government sector. The private sector had improper salaries and facilities, anaesthesiologist’s dependency on surgeons for getting work and lack of out-of-theatre practice which minimise the scope and earnings of anaesthesiologist within the country. There is a need to overcome surgeon dependency and hospital manipulation by fixing salary percentages for each surgical case and encouraging direct patient-anaesthesiologist relationships.

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.

Energy-related greenhouse gas emissions dominate the carbon footprints of most product systems, and petroleum is one of the main types of energy sources. This is consumed as a variety of refined products – most notably diesel, petrol (gasoline) and jet fuel (kerosene). Refined product carbon footprints are of great importance to regulators, policymakers and environmental decision-makers. For instance, they are at the heart of legislation such as the European Union’s Renewable Energy Directive or the United States’ Renewable Fuels Standard. This study identified 14 datasets that report footprints for the same system, European petroleum refining. For the main refined products – diesel, petrol and jet fuel – footprints vary by at least a factor of three. For minor products, the variation is even greater. Five different organs of the European Commission have estimated refining footprints: for main products these are relatively harmonic; for minor products much less so. The footprint variation is due mainly to differing approaches to refinery modelling, especially regarding the rationale and methods applied to assign shares of the total burden from the petroleum refinery operation to the individual products. Given the economic/social importance of refined products, a better harmony of their footprints would be valuable to their users.

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.

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.

"Hydrogen is an extremely promising energy carrier, poised to become a commercially viable product in the coming years. However, there are significant hurdles that need to be addressed. One such challenge is the high energy consumption during the electrolysis process, which is used to produce hydrogen. Furthermore, the co-production of CO and CO2 during steam hydrocarbon reforming adds to the complexity. Finding innovative solutions to these issues is crucial for the widespread adoption of hydrogen as a clean and efficient energy source." Simultaneously, various industries have the capability to generate hydrogen as a by-product, each with differing levels of purity. For instance, sodium and chlorine production plants have the potential to produce high-purity hydrogen. On the other hand, digester and sewage gas can yield low-purity hydrogen. In both instances, there is an economic incentive to utilize this hydrogen for energy production or to inject it into existing natural gas pipelines A brief estimation of the technical potential of utilizing hydrogen from various sources in Nigeria, specifically for fuel cell usage, has been conducted. Moreover, resource potential visualization maps have been generated to help visualize the availability and distribution of these hydrogen sources throughout the country.

Human serum albumin (HSA) is the ultimate, homeostatic determinant of fluid volume (FV) in all compartments of the body. The ability to change the pressure and flow of nutrient medium to cellular structures selectively has clinical significance in almost all areas of clinical medicine. We have shown that present fluid therapy (FT) using either colloid or saline dilutes nutrients. HSA binds and delivers nutrients, a lack of HSA binding causes Albumin Binding Disease (ABD) changing both colloidal pressure and nutrients leading to symptoms of sepsis. A reduction in HSA binding can be through lack of HSA or external ligands taking up binding sites on HSA. Many diseases cause ABD when immunoglobulins, infectious particles and by products bind to HSA including COVID-19 and other bacterial diseases like streptococcus as well as metabolic and cardiac disease due to incorrect pressure and nutrients. To raise HSA binding potential and remove vulnerabilities to these diseases we propose raising HSA. We show how present methods of fluid therapy (FT) are inefficient in that control of both pressure and nutrients forms initial equilibrium in the liver. HSA production and binding to nutrients is maintained at a level by the pressure in hepatocytes with the pancreatic and adrenal hormones moderating. Glucose and Ke-tone production are critical in the management of HSA binding and control of blood, colloidal pressure, and health of cells. Ketones provide a distinct mechanism of liver to lungs-heart metabolism during hypoglycaemia and activity. This known chain of nutrition becomes critical during disease like acute respiratory distress syndrome (ARDS) when ketones may be overproduced. HSA must therefore be infused into the liver to raise HSA levels safely. We investigated the control of HSA as a product of the actions of pressure in hepatocytes and changes in pancreatic and adrenal hormones. We found that in addition to pressure during glucose abundancy HSA is re-leased with ketones on administration of insulin and consider that this mechanism retains HSA moderation. HSA can therefore be increased by increasing insulin in the presence of glucose in the correct amounts. We suggest a protocol to increase FV, blood, lymph volume by infusion of HSA, insulin, and glucose direct to the liver so that the level of HSA stabilises. We suggest this will raise all other nutrients in the new FV, blood, lymph culminating in the creation of new blood cells. We propose that in a clinical situation maintaining this protocol will alleviate the symptoms of ABD and decrease the likelihood of serious illness and death.

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.

Sea cucumbers (Holothuroidea; Echinodermata) are ecologically significant constituents of benthic marine habitats. We surveilled RNA viruses inhabiting 8 species (representing 4 families) of holothurian collected from four geographically distinct locations by viral metagenomics, including a single specimen of Apostichopus californicus affected by a hitherto undocumented wasting disease. The RNA virome comprised genome fragments of both single-stranded positive sense and double stranded RNA viruses, including those assigned to the Picornavirales, Ghabrivirales, and Amarillovirales. We discovered an unconventional flavivirus genome fragment which was most similar to a shark virus. Ghabivirales-like genome fragments were most similar to fungal totiviruses in both genome architecture and homology, and likely infected mycobiome constituents. Picornavirales, which are commonly retrieved in host-associated viral metagenomes, were similar to invertebrate transcriptome-derived picorna-like viruses. Sequence reads recruited from the grossly normal A. californicus metavirome to nearly all viral genome fragments recovered from the wasting-affected A. californicus. The greatest number of viral genome fragments was recovered from wasting A. californicus compared to any other surveyed holothurian, including the grossly normal A. californicus, which reflects a pattern observed in viral metagenomics study of sea star wasting. These results expand the known host range of flaviviruses, and suggest that fungi and their viruses may play roles in holothurian ecology.

Crystal structures of simple metals and binary alloy phases based on the face-centered cubic (fcc) structure are analyzed within the model of Fermi sphere – Brillouin zone interactions to understand the stability of original cubic structure and derivative structures with distortions, superlattices and vacancies. Examination of the Brillouin-Jones configuration in relation to the nearly-free electron Fermi sphere for several representative phases reveals significance of the electron energy contribution to the phase stability. Representation of complex structures in the reciprocal space clarifies their relationship to the basic cubic cell.

We describe the genomes of two Echovirus isolates from Nigeria as reference enterovirus species B genomes for the region. These Echovirus 7 and 19 genomes have 7,411nt and 7,426nt, and were recovered from sewage contaminated water (in 2010) and an acute flaccid paralysis case (in 2014), respectively.

Natural gas is an important energy source among various fossil fuels. However, natural gas typically contains a significant amount of water vapor, which can pose challenges in its usage. Therefore, the process of removing water vapor from natural gas, known as gas dehydration, is crucial in the gas industry. The presence of water vapor in the gas supply can lead to the formation of hydrates, which can cause issues such as blockages in pipelines. To tackle this problem effectively, gas dehydration makes use of Tri ethylene glycol (TEG) as a drying agent. TEG works by selectively absorbing water vapor from the natural gas flow, thereby significantly reducing its moisture content.In the gas dehydration process, wet gas is treated by using lean glycol in an absorber, where the water vapor is removed. The resulting rich glycol is then recovered and recycled for further use. In this study, we explore the possibility of replacing nitrogen with dry natural gas in the re-generator of the glycol dehydration system. The aim is to evaluate the feasibility and effectiveness of this alternative approach. To assess the performance of both techniques, we employed HYSYS modeling and simulation. Through this analysis, we compared the capital and utility expenses associated with each method while ensuring that the glycol purity requirements remained unchanged. By examining the results obtained from the simulations, we can gain insights into the economic viability and efficiency of utilizing dry natural gas in the re-generator stage of the glycol dehydration process.In addition to the primary purpose of removing water vapor, the wet gas obtained from the stripping mechanisms in the glycol dehydration process can serve additional functions. It can be utilized to power steam pumps and compressors, thereby maximizing energy efficiency within the system. Alternatively, the wet gas can be recycled back into the process for further treatment. To develop a comprehensive understanding of the entire mechanism, we constructed a model based on the actual flow diagram. This model takes into account the various components and processes involved in the glycol dehydration system, including the stripping mechanisms and their connection to other equipment. By analyzing the data and outcomes generated by this model, we can derive valuable insights. These findings can be utilized to optimize the heat and material balance within the plant, ensuring efficient operation and potentially leading to the design of an improved system in terms of energy consumption and overall performance

: Cybersecurity has become a critical area in the digital field in recent years. The expansion of networks has revolutionised the way network structures are organised and managed. However, with increased connectivity and the growing complexity of modern networks, the threat of cyber-attacks has become more intense. As technology continues to advance, it brings both opportunities and challenges. One of the major challenges is the need to secure networks and sensitive data from various malicious activities. Traditional networks have evolved to include Software Defined Network (SDN), which offers a more flexible and programmable framework. Researchers should focus on detecting attacks in SDN because SDN networks are becoming more popular and attractive targets for clients due to their programmability and dynamic nature. The centralised controller, known as the backbone of an SDN, becomes a single point of failure and a potential target for attackers if not properly secured. Researchers need to emphasise the detection of attacks in SDN in order to mitigate these risks. By understanding the potential vulnerabilities and attack methods specific to SDN, researchers can develop effective detection approaches and propose countermeasures. This methodology helps protect the network from potential threats and minimises the impact of successful attacks. Therefore, this survey paper provides a review of Intrusion Detection Systems (IDSs) in Software-Defined Networks (SDN) to provide a thorough understanding of SDN security issues.

Among other fossil fuels, natural gas is a major energy source. It is generally created saturated with water vapor. Dehydration of natural gas is vital in the gas business to remove water vapor from the gas supply, which may cause hydrate development in pipes. Gas dehydration employs Tri ethylene glycol (TEG) to remove water vapor from natural gas flow. The wet gas is dehydrated with lean glycol in an absorber, and the rich glycol is recovered and reused. This work investigates the use of dry natural gas instead of nitrogen in the glycol dehydration re-generator, and compares the results using HYSYS modeling and simulation. The two techniques were compared for capital and utility expenses, while maintaining the identical glycol purity criteria. The wet gas from the stripping mechanisms may also be utilized to run steam pumps and compressors or recycled. The model is based on the real mechanism flow diagram. Finally, the findings of this model might be used to design a new heat and material balance for the plant.

Developing a dependable gas and condensate value chain is vital for the ongoing prosperity of the oil and gas industries. To achieve this, NNPC is enhancing its production facilities by employing process modeling and simulation with the assistance of Symmetry iCON®. As a part of this initiative, a simulation model was created using the Symmetry iCON® pipe plexus solver to simulate the dynamic environment of the gas and condensate pipeline network in the Nigerian Southern region. To validate the model, data from a single month, specifically December 2022, was utilized. Furthermore, the algorithm was utilized to generate projections for the month of January 2023, providing valuable insights into its effectiveness. The study also highlighted the significance of accurately estimating the characteristics and properties of a pseudo component of C6+ in relation to thermodynamics and material properties, which was a particularly insightful finding. he assessment of this property has transitioned from being relatively unimportant to becoming critically important, primarily due to the lack of condensate data monitoring at specific terminals. However, it's worth noting that the model currently has an error margin of 4-6% when predicting the data. As more information becomes available in the future, the model can be easily fine-tuned to better align with the actual conditions, allowing for more accurate predictions.

The purpose of this study was to identify potential causes of violence and crime in informal settlements and residents’ strategies for response and prevention to these issues, as perceived by women living in Mathare informal settlement in Nairobi, Kenya. A total of 55 in-depth interviews were conducted with women living in the informal settlement in 2015-2016. A modified grounded theory approach was used to guide data collection and analysis. The most common contributor to violence and crime identified by women in Mathare informal settlement was idle youth, but leadership and government challenges, corruption and/or inadequacy of police, community barriers, tribalism, and lack of protective infrastructure also emerged as contributing factors. Despite facing many economic, environmental, and day-to-day challenges, women in Mathare identified violence and crime as predominant issues; thus, developing effective response and prevention strategies to these issues in informal settlements is paramount. Women suggest there are many strategies and initiatives to reduce and prevent violence and crime in informal settlements, but also identified barriers to implementing them. Findings suggest there is a need for trust-building between formal and informal organizations and institutions, systems of accountability, and long-term investment to foster sustainable and effective violence and crime response and interventions in these settlements.

Cannabis has long been used for its medicinal and psychoactive properties. With the relatively new adoption of formal medicinal cannabis regulations worldwide, the study of cannabinoids, both endogenous and exogenous, has similarly flourished in more recent decades. In particular, research investigating the role of cannabinoids in regeneration and neurodevelopment has yielded promising results in vertebrate models. However, regeneration-competent vertebrates are few, whereas a myriad of invertebrate species have been established as superb models for regeneration. As such, this review aims to provide a comprehensive summary of the endocannabinoid system, with a focus on current advances in the area of endocannabinoid system contributions to invertebrate neurodevelopment and regeneration.

Kratom (Mitragyna speciosa) is a Southeast Asian plant containing various alkaloids which induce pharmacological effects in humans. In Western countries, online vendors sell a variety of different kratom strains which are marketed to have distinct effect profiles. However, as of yet such marketing claims are unsubstantiated, and therefore the current study investigated whether differently colored kratom products can induce unique effects, as self-reported by users. 644 current kratom users were anonymously surveyed to compare the self-reported effects and motivations for using kratom products sold as red, green, and white strains. Most of the survey respondents were customers of the same kratom vendor, the products of which had been assessed for their alkaloid content by an independent laboratory. The survey respondents reported distinct subjective experiences for different kratom strains, in a manner congruent with common marketing descriptions. However, the product analyses revealed no significant cross-strain differences in alkaloid content, suggesting that the reported effect differences might be disproportionally influenced by marketing narratives and anecdotal reports. Future studies should engage a more diverse population and include kratom strains from various vendors. Controlled, blinded experiments could assess whether the reported effect differences stem from a placebo effect or from alternative factors, e.g. minor alkaloids and terpenes.

Fruit and vegetable (FV) consumption benefits the health of populations, particularly those in East and Southeast Asian countries, which have undergone an unprecedented change in their food environments in the last decade. This current systematic review is the first to study determinants—facilitators, barriers, and moderators—associated with FV consumption in East and Southeast Asia. In a search of the literature, we consulted five electronic academic databases of English peer-reviewed papers published between 2010 and 2020 and found 31 studies. Results of these studies show that individuals strongly perceive FVs as being higher quality and safe and trust in their benefits, and food businesses with modernized systems have significantly fostered the consumption of FVs. A main barrier to FV consumption, however, is financial concerns, exacerbated by food businesses with FV unavailability and urbanization-induced FV price inflation and dietary patterns. Further hindering FV consumption are demographics and shopping patterns. The fragmented and conditionalized findings of the 31 studies require standardized FV consumption measurements. Unlike the impact of FV consumption determinants and their interactions in Western countries, those in Asia, particularly countries other than China, have been substantially understudied. Therefore, as the research gaps in studies of food environments and FV consumption in East and Southeast Asia urgently demand scholarly attention, this paper proposes recommendations that favour the consumption of FVs.

The identification of floral visitation by pollinators provides an opportunity to improve our understanding of the fine-scale ecological interactions between plants and pollinators, contributing to biodiversity conservation and promoting ecosystem health. In this review we outline the various methods which can be used to identify floral visitation, providing a comparison between molecular and non-molecular methods. We review the literature covering the ways in which DNA metabarcoding has been used to answer ecological questions relating to plant use by pollinators and discuss the findings of this research. We present detailed methodological considerations for each step of the metabarcoding workflow, from sampling through to amplification and finally bioinformatic analysis. Detailed guidance is provided to researchers for utilization of these techniques, emphasizing the importance of standardization of methods and improving the reliability of results. Future opportunities and directions of using molecular methods to analyze plant-pollinator interactions are then discussed.

Despite providing some critical financial services to support the operation of Emissions Trading Systems (ETS), such as increasing market liquidity and price visibility and allowing operators to hedge against future fluctuations, there is growing concern about the potential threat of financial actors' speculation behaviour to the ETS's effectiveness. To confirm or alleviate the fear associated with such concern, we employ both ex-post and ex-ante approaches to determine the role of speculation in the emission reduction effect of the ETS and its forecasting power in predicting climate change. In addition to confirming carbon prices and the speculation behaviour of the emissions non-compliance actors in the ETS as accurate predictors of climate change, we also show that they both matter in the emission reduction effect of the ETS. We use several verifiable econometric approaches to select the Feasible Quasi Generalised Least Squares (FQGLS) as the best estimator for addressing some of the biases in climate change predictability. We demonstrate that a predictive model combining the complementing dynamics of the EST emissions compliance and emissions non-compliance features forecasts climate change more accurately. We demonstrate the robustness of our findings for both in-sample and out-of-sample forecasts and across different forecast horizons by using alternative approaches to evaluate forecast performance.

Gout is not only associated with obstructive sleep apnea (OSA), but the intermittent episodes of hypoxia that occur with OSA may also have a role in causing gout. Epidemiological studies have documented a higher incidence and prevalence of gout in individuals diagnosed with OSA than in individuals never diagnosed with OSA. The pathophysiology of OSA’s chronic episodes of hypoxia leading to hyperuricemia and gout involves boththe overproduction and underexcretion of uric acid. Treating OSA may be an additional way to control gout and its life-threatening comorbidities. Clinicians are urged to evaluate their patients with hyperuricemia/gout for OSA as it may lead to alternative ways to control gout with superior outcomes that simply pharmacologic treatment alone.

Deepfakes are manipulated or altered images, or video, that are created using deep learning models with high levels of photorealism. The two popular methods of producing a deepfake are based on either convolutional neural networks (CNN), or autoencoders. Deepfakes created using CNN comparatively show higher qualities of realism, yet oftentimes leave artifacts and distortions in the generated media that can be detected using machine learning and deep learning algorithms. In recent years, there has been an influx of periocular image and video data because of the increase usage of face masks. By wearing masks, much of what is used for facial recognition is hidden, leaving only the periocular region visible to an observer. This loss of vital information leads to easier misidentification of media, allowing deepfakes to less likely be identified as fake. In this work, feature extraction methods, such as Scale-Invariant Feature Transform (SIFT), Histogram of Oriented Gradients (HOG), and CNN, are used to train an ensemble deep learning model to detect deepfakes in videos on a frame-by-frame level based on the periocular region. Our proposed model is able to distinguish original and manipulated images with accuracies around 98.9 percent, which is an improvement to previous works by combining SIFT and HOG for deepfake detection in convolutional neural networks.

Lameness on dairy goat farms is a welfare concern and could negatively affect milk production. This study's objective was to evaluate the effects of clinical lameness on the daily milk production of dairy goats. Between July 2019 and June 2020, 11,847 test-day records were collected from 3,145 goats on three farms in New Zealand. Locomotion scoring of goats used a 5-point scoring system (0 to 4). The dataset was split into two groups by lactation type, where goats were classified as being in seasonal lactation (≤305 days in milk) or extended lactation (>305 days in milk). A linear mixed model was used to analyze datasets using milk characteristics as the dependent variables. Clinically lame goats (score 3 or 4) in seasonal and extended lactation produced 2.63% and 4.66% less milk than goats not lame, respectively. Severely lame goats (score 4) in seasonal and extended lactation produced 7.10% and 8.56% less milk than goats not lame, respectively. The estimated average daily milk income lost was between NZD 26 and 104 per goat. This study established the negative impact of lameness on milk production and annual income in dairy goats on three farms.

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.

"Chemical absorption is currently the most advanced technique for capturing carbon dioxide after combustion. A fascinating approach within amine-based technology for post-combustion carbon removal is the utilization of aqueous ammonia as a solvent, leading to a method called chilled ammonia capture. This study aims to enhance the performance of chilled ammonia capture through a thermodynamic assessment, focusing on crystalline configuration.""This study explores the development of an improved second generation chilled ammonia capture process, which involves the formation of solids to enhance capturing efficiency. The simulation software ASPEN is employed to model the expanded UNIQUAC Thermodynamics hypothesis. The modeling encompasses both the conventional carbon ammonia capture process and the more advanced carbon ammonia capture system powered by a crystallizerIn this study, the energy costs associated with implementing different technologies for carbon ammonia capture in typical ultra supercritical power plants are evaluated. The introduction of solid formation in the carbon ammonia capture system has yielded promising results. The findings indicate that the energy required for the carbon ammonia capture system, which utilizes a crystallizer, is approximately 10% lower compared to the overall cost associated with the conventional carbon ammonia capture system. These results highlight the potential for significant energy savings and improved efficiency in carbon capture processes

Mouthbrooding or oral incubation, the retention of early developmental stages inside of the mouth for an extended period of time, has evolved multiple times in bony fishes1,2. Though uncommon, this form of parental care has been documented and well-studied in several groups of freshwater fishes but is also known to occur in a small number of marine fishes, all inhabiting coastal waters1,2. A recent paper3, reported for the first time mouthbrooding in a deep-water fish species, the zeiform Parazen pacificus, which according to the authors “fills in a gap in the larval literature for this family of fishes and prompts further investigation into other novel reproductive modes of deep-sea fauna.”

Around one billion people live in informal settlements, globally, including over half of Nairobi, Kenya’s three million residents. The purpose of this study was to explore women’s fear of victimization within Mathare, an informal settlement in Nairobi, Kenya and how fear of victimization influences behavior. Fifty-five in-depth interviews were conducted with women in 2016. A modified grounded theory approach guided data collection and analysis. Findings suggest fear of victimization is a serious concern in informal settlements. Women have found ways to adopt their behaviors that allow them to continue to function and protect their children despite fearing victimization, but at a potential cost to their health and well-being. Thus, there is a critical need for more research focused on social, economic, structural, community, infrastructure, technological, and individual strategies to prevent violence, enhance residents’ sense of safety, and, subsequently, minimize women’s fear of victimization in informal settlements.

ABSTRACT"In the realm of the industrial complex, a pressing concern lies in optimizing resource utilization and enhancing energy efficiency. This critical issue finds strong support from a variety of government programs, strategies, and regulatory documents. To effectively tackle this challenge and revolutionize petrochemical production, it is imperative to establish and develop innovative mechanisms. One such mechanism involves harnessing the power of automation and advanced Industry 4.0 technologies to streamline production processes. By doing so, we can unlock the full potential of these systems, driving operational efficiency, conserving valuable reserves, and propelling innovation within the petrochemical industry."The article delves into an in-depth analysis of the prominent trends in the application of the "Industry 4.0" concept within the petrochemical industry. It sheds light on the various factors that impact the efficiency of organizing production systems. Additionally, the article identifies the primary avenues that drive the advancement and enhancement of production organization practices. Moreover, the article explores the fundamental tools employed for process improvements and highlights the significance of process automation in petrochemical plants. By examining these key aspects, it aims to provide valuable insights and recommendations for leveraging Industry 4.0 technologies to optimize production processes in the petrochemical industry..The study focuses on examining and evaluating various systems and technologies that contribute to the optimization of production processes within the petrochemical industry. Specifically, it delves into the implementation and benefits of the just-in-time system, the 5S system for workplace rationalization, as well as different information systems including ERP systems and CALS-technologies. By exploring these systems and technologies, the article aims to identify the advantages of automating production processes within the petrochemical complex. This analysis will unveil the potential benefits such as improved efficiency, reduced waste, enhanced productivity, streamlined operations, and increased overall competitiveness. Through this research, we aim to shed light on the value of these automation solutions and their impact on driving the petrochemical industry towards greater success.

In insects, Adipokinetic hormone is the primary hormone responsible for the mobilization of stored energy. While a growing body of evidence has solidified role of Adipokinetic hormone (AKH) in modulating the physiological and behavioral responses to metabolic stress, little is known about the upstream endocrine circuit that directly regulates AKH release. We evaluated the AKH-producing cell (APC) transcriptome to identify potential regulatory elements controlling APC activity, and found that a number of receptors show consistent expression levels, including all known dopamine receptors and the Pigment Dispersing Factor receptor (PDFR). We tested the consequences of targeted genetic knockdown and found that AKH expression of RNAi elements corresponding to each dopamine receptor caused a significant reduction in survival under starvation. In contrast, PDFR knockdown significantly extended lifespan under starvation whereas expression of a tethered PDF in APCs resulted in a significantly shorter lifespan. These manipulations caused various changes in locomotor activity under starvation. We used live-cell imaging to evaluate the acute effects of the ligands for these receptors on APC activation. Dopamine application led to a transient increase in intracellular calcium in a sugar-dependent manner. Furthermore, co-application of dopamine and ecdysone led to a complete loss of this response, suggesting that these two hormones act antagonistically. We also found that PDF application led to an increase in cAMP in APCs, and that this response was dependent on expression of the PDFR in APCs. Together these results suggest a complex circuit in which multiple hormones act on APCs to modulate metabolic state.

Magnetic Particle Imaging (MPI) is a new imaging modality that sensitively and specifically detects superparamagnetic iron oxide nanoparticles (SPIONs). Many labs have been developing cellular magnetic resonance imaging (MRI) tools using both SPIONs and fluorine-19 (19F)-based contrast agents for numerous important applications, including tracking of immune and stem cells used for cellular therapies. SPION-based MRI cell tracking has very high sensitivity, but low specificity. SPIONs produce negative contrast in MRI, or signal voids. SPIO is not directly detected by MRI, but indirectly through its relaxation effects on protons, therefore, it is not possible to reliably quantify the local tissue concentration of SPION particles and cell number cannot be determined. 19F based cell tracking uses perfluorocarbons (PFC) to label cells. The number of 19F atoms can be directly measured from 19F MR images and related to cell number. 19F MRI has high specificity, but low sensitivity. MPI cell tracking displays great potential for overcoming the challenges of MRI-based cell tracking allowing for both high cellular sensitivity and high specificity and quantification of SPIO labeled cell number. In this paper we describe nanoparticle and MPI system factors that influence MPI sensitivity and resolution, quantification methods and give our perspective on testing and applying MPI for cell tracking.

Environment approachable products such as fuels and lubricants are among the best choices in several countries that contain renewable products as alternatives. To protect human life, alternative methods of saving the environment and production balance is needed to reduce the effects of the crisis and the contamination of the Environment. This research concentrated on the Manufacturing and testing of bio- grease from sugar cane filter mud vegetable oil as a lubricant for friction reduction and determining the properties of both bio grease and Mineral oil grease with environmental problems. SC filter mud oil as an alternative use for bio-grease preparation in addition to mineral oil grease. The Testing was accepted to determine the quality of the eco-friendly grease produced. For the preparation of this bio- grease, the SC Filter cake sample is taken from different sugar factory which found in Ethiopia. The sample has a moisture content of 78%. Using this sample first oil is extracted by Soxhlet apparatus, n-hexane solvent and temperature for extraction from 42 -68℃. The maximum temperature and time for extraction of oil were 68 and 7hrs respectively. The extracted oil's physical properties include color, acid value, specific graphite, saponification value, iodine value, density, and viscosity. Finally, the friction behavior in function of time for both grease at identical load, the friction coefficient vs time for SC filter Cake Grease_ Na_ MoS2 and industrial mineral one (I_ Greasily _ MoS2), grease was determined.

Here we describe the genome of an Echovirus 7 isolate of South-East Asian ancestry recovered from a child with acute flaccid paralysis (AFP) in Nigeria. The genome has 7,295nt and an open reading frame with 2,195 amino acids.

The effects of carbon fiber hybridisation on the thermal properties of woven kenaf reinforced epoxy composites kenaf fibre were studied. Woven kenaf hybrid composites at the different weave designs of plain and satin, and fabric count of 5 × 5 and 6 × 6 were manually prepared by vacuum infusion technique. Thermal properties of pure carbon fibre and hybrid composites were conducted by using thermogravimetric analyser (TGA) and differential scanning calorimeter (DSC). It was found that at high kenaf fibre content showed better thermal stability while the highest thermally stable was found in pure carbon fibre composite. The TG and DTG results showed that the amount of residue decreased in plain-designed hybrid composite compared to satin-designed hybrid composite. The DSC data revealed that the presence of woven kenaf increase decomposition temperature.

Air pollution is a leading cause of death in the United States, and is associated with adverse health outcomes, including increased vulnerability to coronavirus disease 2019 (COVID-19). The AirBeam2 was used to measure particulate matter with a diameter of 2.5 micrometers or smaller (PM2.5), to investigate differences between indoor and ambient levels at seven private homes in New York during and after the COVID-19 lockdown. Measurements taken in 2020 winter, spring and fall and in fall 2022 showed that 90% of the time, indoor PM2.5 levels exceeded outdoor levels both during and after the COVID-19 lockdown, p = 0.03, and exceeded safety levels. Higher indoor PM2.5 levels attributed to little or no ventilation from cooking and smoke in the kitchen and basements, were significantly greater in fall than in winter. Higher ambient PM2.5 levels were attributed to vehicular traffic at a street-facing sampling site. PM2.5 sources identified in this study may help in devising control strategies to improve indoor air quality (IAQ), and consequently alleviate respiratory health effects. These findings may be used as a basis for in-house modifications including natural ventilation and use of air purifiers to reduce exposures, mitigate future risks, and prevent potential harm to vulnerable residents.

The associations between dietary sodium intake (DSI), dietary potassium intake (DPI), and kidney stone disease (KSD) are not clear. We examined The National Health and Nutrition Examination Survey 2011-2018 to determine the independent associations between daily DSI, DPI, DSI/DPI and prevalent KSD. 19,405 participants were included for analysis, of which 1,895 had KSD. Higher DSI was not associated with increased odds of KSD in regression analysis when DSI was modeled as a continuous variable (OR=0.99, 95% CI: 0.99-1.00, p=0.2), or when comparing highest quartile of DSI to lowest quartile (OR=0.84, 95% CI: 0.68–1.04, p=0.1). Unlike DSI, higher DPI associated strongly with reduced odds of KSD in regression analysis when DPI was modeled as a continuous variable (OR=0.99, 95% CI: 0.99-0.99, p=0.02), or when comparing highest quartile of DPI to lowest quartile (OR =0.75, 95% CI: 0.60–0.94, p=0.01). Lastly, higher DSI/DPI also associated strongly with increased odds of KSD in regression analysis when DSI/DPI was modeled as a continuous variable (OR=1.1, 95% CI: 1.01-1.20, p=0.03), or when comparing highest quartile of DPI to lowest quartile (OR =1.30, 95% CI: 1.10–1.70, p=0.008). All the observed relationships were independent of total calorie intake. In conclusion, both lower DPI and higher DSI/DPI associate with an increased risk of KSD. Future prospective studies are needed to clarify these causal relationships.

Neurodegenerative diseases, including Alzheimer's, Huntington's, Parkinson’s, and Amyotrophic Lateral Sclerosis, involve neuron degeneration linked to the misfolding of amyloidogenic proteins, resulting in β-sheet-enriched aggregates. This phenomenon disrupts the normal folding of proteins critical for cellular function. Genetic mutations, proteolytic cleavage, oxidative stress, and aging contribute to misfolding. Parkinson's disease (PD) is closely tied to alpha-synuclein (αS) misfolding, with A53T mutation and Lewy bodies (LB) in PD brains pivotal to understanding the disease mechanism. Other synuclein homologues (βS, γS) further contribute to synucleinopathies. Mutants (A30P, A53T, E46K, H50Q, and G51D) underscore αS's role in PD development. This concise review focuses on molecular and pathological aspects of neurodegenerative diseases, emphasizing αS in PD. The integration of genetic, structural, and mechanistic insights highlights the disorders. complexity, paving the way for future therapeutic strategies targeting protein misfolding and aggregation.

This study reports the first example of major erosion from hurricanes degrading a rocky coastline anywhere around the Gulf of California, although other sources of evidence are well known regarding the effect of inland erosion due to catastrophic rainfall in the Southern Cape Region of the Baja California peninsula and farther north. The uplifted, 12-meter terrace on the eastern shore of Isla del Carmen is the site of an unconsolidated coastal boulder deposit (CBD) consisting of large limestone blocks and boulders eroded from underlying Pliocene strata. The CBD stretches approximately 1.5 km in length, mostly set back 25 m from the lip of the terrace. The largest blocks of upturned limestone near the terrace edge are estimated to weigh between 5.8 and 28 metric tons. Waves impacting the rocky coast that peeled back slabs of horizontally layered limestone at this spot are calculated to have been between 11.5 and 14 m in height. Analysis of sampled boulders from the CBD set back from the terrace edge by 25 m suggest that the average wave height responsible for moving those boulders was on the order of 4.3 m. Additional localities with exposed limestone shores, as well as other more common rock types of igneous origin, have yet to be surveyed for this phenomenon elsewhere around the Gulf of California.

Welcome to the world of bioethanol revolution, in response to the soaring global energy demand, the production of bioethanol has taken center stage, captivating the attention of governments, academia, and the private sector alike. Over the years, research in this field has witnessed exponential growth, paving the way for sustainable energy production. Ethanol, the front-runner in renewable energy, can be derived from a plethora of sources. In this abstract, we will explore the exciting advancements and emerging trends in the production of bioethanol, shedding light on the promising future of sustainable energy. Bioethanol production presents a cost-effective solution by utilizing the abundance of agricultural resources. These resources serve as the foundation for producing bioethanol from various biomass sources. In this context, we evaluate the raw materials used, including sucrose-based, starchy-based, and perennial grasses. By exploring these options, we can gain a comprehensive understanding of the diverse range of agricultural feedstocks that contribute to the production of bioethanol, this paper delves into the multiple processes involved in the production of bioethanol from agricultural base biomass, unveiling a range of possibilities for harnessing renewable energy. The key steps that were thoroughly examined include pretreatment, which encompasses both physical and chemical methods, hydrolysis, direct fermentation, and saccharification. These steps serve as crucial components in the overall bioethanol production process from agricultural base biomass. By understanding and optimizing each of these stages, we can unlock the full potential of sustainable energy generation. The paper goes beyond exploring the production processes and delves into the different generations of bioethanol, each with its unique components. Additionally, it provides a comprehensive overview of the composition of agricultural and forest residues, shedding light on their potential as valuable resources for bioethanol production. Moreover, it highlights the significance of the agricultural sector in Nigeria's economy, emphasizing the importance of energy for enhancing productivity and efficiency. The integration of bioethanol as an energy source has the potential to propel this sector forward, fostering sustainable development and contributing to the overall growth of the Nigerian economy. By harnessing the power of bioethanol, Nigeria can tap into its energy potential, promoting energy utilization and creating a positive impact on various industries.

Intercellular transport of auxin is driven by PIN-formed (PIN) proteins. PINs are localized at the plasma membrane (PM) and on constitutively recycling endomembrane vesicles. Therefore, PINs can mediate auxin transport either by direct translocation across the PM or by pumping it into secretory vesicles (SVs), leading to its secretory release upon fusion with the PM. Which of these two mechanisms dominates is a matter of debate. Here we addressed the issue with a mathematical modeling approach. We demonstrate that the efficiency of secretory transport depends on SV size, half-life of PINs on the PM, pH, exocytosis frequency and PIN density. 3D-SIM microscopy was used to determine PIN density on the PM. Combing this data with published values of the other parameters, we show that the transport activity of PINs in SVs would have to be at least 1000x greater than on the PM in order to produce a comparable macroscopic auxin transport. If both transport mechanisms operated simultaneously and PINs were equally active on SVs and PM, the contribution of secretion to the total auxin flux would be negligible. In conclusion, while secretory vesicle-mediated transport of auxin is intriguing and theoretically possible model, it unlikely to be a major mechanism of auxin transport in planta.

Background and Objectives: A 62-year-old patient presented with significant visual reduction in the last three months. Best corrected visual acuity (BCVA) of the right eye (RE) dropped from 20/20 on both eyes to 20/200 on the RE and counting fingers (CF) on the left eye (LE); respectfully. She was diagnosed with stage 4 ovarian cancer 1 month ago. Materials and Methods: Examination revealed significant progression of cataracts and subretinal fluid on the posterior pole with choroidal thickening. Multifocal, orange-pigmented elevated choroidal lesions were observed in the RE, while the view of the left eye fundus was obstructed by cataracts. OCT revealed bilateral choroidal thickening with overlying folds and subretinal fluid and ultrasound of the choroidal lesions showed moderate homogenous internal reflectivity. Results: The patient was diagnosed with BDUMP (bilateral diffuse uveal melanocytic proliferation), a paraneoplastic syndrome characterised by simultaneous, bilateral, painless vision loss and rapidly acquired bilateral cataracts with serous retinal detachments. Cataract extraction had not obtained the expected visual recovery (RE: CF; LE 2/200, respectfully). Plasmapheresis demonstrated some success by stabilizing vision loss obtained by serous retinal detachments. Conclusion: The focus of treating BDUMP is aimed at the underlying malignancy. Vision typically deteriorates to near blindness within a year from presentation. Overall prognosis is generally poor and mean survival is reported at 12-15.7 months from the time of ocular diagnosis.

The COVID-19 pandemic was associated with increases in some healthcare-associated infections. We investigated the impact of the pandemic on rates and molecular epidemiology of Clostridioides difficile infection (CDI) within one VA Hospital. We anticipated that the potential widespread use of antibiotics for pneumonia during the pandemic might increase CDI rates given that antibiotics are a major risk for CDI. Hospital data on patients with CDI and recurrent CDI (rCDI) were reviewed pre-COVID-19 pandemic (2015 to 2019) and during the pandemic (2020 - 2021). Restriction endonuclease analysis (REA) strain typing was performed on CD isolates recovered from stool samples collected from 10/2019 – 3/2022. CDI case numbers declined 43.2% in 2020 – 2021 compared to the annual mean over the previous 5 years. Stool test positivity rate was also lower during the COVID-19 pandemic (14.3% vs. 17.2%; P = 0.013). Although inpatient volume declined, rates of CDI among inpatients were reduced by 34.2% in 2020 – 2021. Mean monthly cases of rCDI also declined significantly after 2020 [3.38 (95% CI: 2.89 – 3.87) vs. 1.92 (95% CI: 1.27 – 2.56); P = <0.01]. Prior to the pandemic, REA group Y was the most prevalent CD strain among the major REA groups (27.3%). During the first wave of the pandemic from March 8, 2020, through June 30, 2020, there was an increase in the relative incidence of REA group BI (26.7% vs. 9.1%. After adjusting for CDI risk factors, a multivariable logistic regression model revealed that odds of developing an REA group BI CDI increased during the first pandemic wave (OR 6.41, 95% CI: 1.03 – 39.91) compared to the pre-pandemic period. In conclusion, the incidence of CDI and rCDI decreased significantly during the initial waves of the COVID-19 pandemic. In contrast, REA BI (Ribotype 027), a virulent, previously epidemic CD strain and frequently associated with hospital transmission and outbreaks, reappeared as a prevalent strain during the first wave of the pandemic.

The association between depressive symptomatology and cognitive decline has been examined using the Centre for Epidemiologic Studies-Depression Scale (CES-D), however, concerns have been raised about this self-report measure. Here, we examined how the CES-D total score from the 14- and 10-item versions compared to the 20-item version in predicting progression to cognitive decline from a cognitively unimpaired baseline. Data from 1,054 participants were analysed using ordinal logistic regression, alongside moderator and receiver-operating characteristics curve analyses. All baseline total scores significantly predicted progression to cognitive decline. The 14-item version was better than the 20-item version in predicting consensus diagnosis, as shown by their AICs, while also showing the highest accuracy when discriminating between participants by diagnosis at last visit. We did not find sex to moderate the relationship between CES-D score and cognitive decline. Current findings suggest the 10- and 14-item versions of the CES-D are comparable to the 20-item version, and that the 14-item version may be better at predicting longitudinal consensus diagnosis compared to the 20-item version.

Healthcare professionals and resource planners can use healthcare delivery process mining to ensure the optimal utilisation of scarce healthcare resources when developing policies. Within hospitals, patients' Length of Stay (LOS) and volume of admitted patients, in terms of number and characteristics (age, gender, and social deter-minants), are significant factors determining daily resource requirements. In this study, we used Coxian phase-type Distribution (C-PHD) based Phase-Type Survival (PTS) trees for analysing how covariates such as admission date, gender, age, district, and admissions source influence the admission rate and LOS distribution. PTS trees. This study used a two-year data set (2011-2012) of patients admitted to the Emergency Department at Mater Dei Hospital to generate models and an independent one-year data set (2013) of patients admitted to the Emergency Department at Mater Dei Hospital to evaluate. The PTS tree effectively clusters patients based on their LOS, considering the prognostic significance of different covariates related to patients' characteristics. Charac-terising these covariates provided meaningful results about LOS. Similarly, the PTS tree was used to effectively cluster patients based on the admission rate, considering the prognostic significance of these covariates.

The natural variation in estrogen secretion throughout the female menstrual cycle impacts various organs, including estrogen receptor (ER)-expressed skeletal muscle. Many women commonly experience increased fatigue or reduced energy levels in the days leading up to and during menstruation when blood estrogen levels decline. Yet, it remains unclear whether endogenous 17β-estradiol, a major estrogen component, directly affects energy metabolism in skeletal muscle due to the intricate and fluctuating nature of female hormones. In this study, we employed 3D 31P FID-MRSI to investigate phosphoryl metabolites in the soleus muscle of a cohort of young females (average age: 28 ± 6 years, n = 7) during the early follicular (EF) and peri-ovulation (PO) phases when their blood 17β-estradiol levels differ significantly (EF: 28 ± 18 pg/mL vs. PO: 71 ± 30 pg/mL, p < 0.05), while the levels of other potentially interfering hormones remain relatively invariant. Our findings reveal a reduction in ATP-referenced phosphocreatine (PCr) levels in the EF phase compared to the PO phase for all participants (5.4 ± 4.3%). Furthermore, we observe a linear correlation between muscle PCr levels and blood 17β-estradiol concentrations (r = 0.64, p = 0.014). Conversely, inorganic phosphate Pi and phospholipid metabolite GPC levels remain independent of 17β-estradiol but display a high correlation between EF and PO phases (p = 0.015 for Pi and p = 0.0008 for GPC).The robust association we have identified between ATP-referenced PCr and 17β-estradiol suggests that 17β-estradiol plays a modulatory role in the energy metabolism of skeletal muscle.

The objective of this study is to determine the relationship between body condition score (BCS) and body carcass fat (BCF) of ewes at two key stages of the production cycle. Data were collected from 88 Coopworth ewes including BCS measurements manually evaluated by the farm manager, BCF measurements determined by computerized tomography (CT) and body parameter measurements automatically determined by an image processing application. Artificial neural network (ANN) statistical analysis method was used to develop a relationship between the body parameters and the BCF with an r2=0.96 and RMSE=1.01 using all top and side variables.

Objectives of this study were to investigate effects of repeated superstimulation on the success of ovum-pick up and in vitro production of embryos (OPU-IVP) and donor health and evaluate the efficiency of a modified SOF sequential medium in producing viable embryos. Over 1 y, six cross-bred beef heifers and three beef cows were subjected to superstimulations and OPU-IVP. Oocytes recovered were used for in vitro embryo production and the resulting embryos were transferred as fresh or frozen-thawed. Number of follicles, oocytes recovered, cleavage and blastocyst rates substantially varied among individuals. However, repeated trials did not significantly affect the efficiency of OPU-IVP. The pregnancy rates (PR) 22 to 30 d after embryo transfer for in vitro-derived fresh embryos was similar to that of fresh in vivo embryos, whereas transfer of in vitro-derived frozen embryos reduced PR compared to frozen-thawed in vivo embryos. All recipient heifers diagnosed pregnant delivered a viable calf, suggesting developmental competence of the embryos. Repeated OPU-IVP had no apparent deleterious effects, as all donors had viable calves after ET. We concluded that multiple OPU-IVP cycles can be effectively performed for a prolonged interval to maximize embryo production from elite donors without compromising their reproductive health.

Recent advancements in machine learning have ushered in innovative techniques for augmenting datasets, particularly through contrastive learning in the computer vision domain. This study pioneers the application of contrastive learning for sentiment analysis, introducing a novel approach termed EmoConLearn. By fine-tuning contrastive learning embeddings, EmoConLearn significantly surpasses BERT-based embeddings in sentiment analysis accuracy, as evidenced by our evaluations on the DynaSent dataset. This research further delves into the efficacy of EmoConLearn across various domain-specific datasets, highlighting its versatility. Additionally, we investigate upsampling strategies to mitigate class imbalance, further enhancing EmoConLearn's performance in sentiment analysis benchmarks.

Background: Increasing number of long-term gastrointestinal (GI) cancer survivors highlights the importance of understanding factors that contribute to their health-related quality of life (HRQoL). We investigated the risk factors of HRQoL, in-cluding demographics, clinical characteristics, and social and behavioral determinants of health (SBDH). Methods: Adult GI cancer survivors (n = 3,201) in the BRFSS surveys from 2014-2021 (except for 2015) were analyzed. Unadjusted/adjusted logistic regression was used. Results: The majority were female (54%) and White (78%), with a median age of 67. Survivors who were 65 years or older, diagnosed with colorectal cancer, or who had fewer comorbidities were more likely to report significantly better HRQoL. Significant social factors of poor HRQoL were being unmarried, racial and ethnic minorities, low socioeconomic status, and poor health care access. Significant behavioral factors of poor HRQoL were lack of physical activity, heavy alcohol consumption, and current smoking, with lack of physical activity being the most significant factor. Conclusions: The SBDH have a critical role in HRQoL. Future studies are warranted to develop a tailored survivorship intervention, such as physical rehabilitation and to ex-plore machine learning/artificial intelligence predictive models to identify cancer sur-vivors at a high risk of developing poor HRQoL.

The pulsatile flow rate (PFR) in the cerebral artery system and shunt ratios in bifurcated arteries are two patient-specific parameters which may affect the hemodynamic characteristics on the pathobiology of cerebral aneurysms (CAs). Accordingly, a systematic study was employed to investigate the effects of the two parameters on hemodynamic characteristics in two internal carotid artery sidewall aneurysms (i.e., ICASA-1 and ICASA-2) models. Numerical results indicate larger PFRs can cause higher WSS in some local regions of the aneurysmal dome that may increase the probability of small/secondary aneurysms generation than under smaller PFRs. The low WSS and relatively high oscillatory shear index (OSI) could appear under a smaller PFR, which has the potential to cause aneurysmal sac growth and rupture. However, the variances in PFRs and bifurcated shunt ratios have rare impacts on the time-average pressure distributions on the aneurysmal sac, although a higher PFR can contribute more to the pressure increase in ICASA-1 dome due to the relatively stronger impingement by the redirected blood stream than in ICASA-2. Simulation results also present the variances of shunt ratios have rare impacts on the hemodynamic characteristics in sacs, mainly because the bifurcated location is not close enough to the sac in present models. Furthermore, it has been found that the vortex location plays a major role in the temporal and spatial distribution of the WSS on the luminal wall, varying significantly with the cardiac period.

This paper aims to analyze the effects of Covid-19 on financial markets from the perspective of Complexity. The Covid-19 pandemic has caused turmoil in financial markets and is already one of the most important financial crises in history, causing a fall in several stock markets as well as great volatility. Unlike past crises, which in most cases were caused either by problems of fiscal deficits or in the financial system, this crisis has its origin in an epidemic disease, which occurred in Wuhan, China, and quickly spread across the globe affecting transport networks, commerce and finance, and will affect the public debt of many countries. This is a systemic situation in which there is a need to consider several interconnected systems, financial instability and high financial risk, something that econophysics and some complexity theorists already do. Therefore, this paper intends to show, theoretically, the systemic and complex character of the recent financial crisis caused by Covid-19.