Neural electrode insertion trauma impedes the recording and stimulation capabilities of numerous diagnostic and treatment avenues. Implantation leads to the activation of inflammatory markers and cell types, which is detrimental to neural tissue health and recording capabilities. Oxidative stress and inflammation at the implant site have been shown to decrease with chronic administration of antioxidant melatonin at week 16, but its effects on the acute landscape have not been studied. To assess the effect of melatonin administration in the acute phase, specifically the first week post-implantation, we utilized histological and q-PCR methods to quantify cellular and molecular indicators of inflammation and oxidative stress as well as two-photon microscopy to track the microglial responses in real-time. Histological results indicate that melatonin effectively maintained neuron density surrounding the electrode, inhibited accumulation and activation of microglia, astrocytes, and reduced oxidative tissue damage. The expression of the pro-inflammatory cytokines, TNF-α and IL-6, were significantly reduced in melatonin-treated animals. Additionally, microglia encapsulation of the implant surface was inhibited by melatonin as compared to control animals following implantation. Our results combined with previous research suggest that melatonin is a particularly suitable drug for modulating inflammatory activity around neural electrode implants both acutely and chronically, translating to more stable and reliable interfaces.

Iron oxide nanozymes are a form of nanomaterial with both superparamagnetic and enzyme-mimicking properties. Given the multifunctional nature of iron oxide nanozymes, it is attractive for creating iron oxide hybrid nanozymes through biomolecular modifications to imbue with auxillary properties. Such iron oxide hybrid nanozymes can be useful for rapid and cost-effective analysis of circulating tumor nucleic acids (ctNAs) in patient liquid biopsies during minimal residual disease (MRD) monitoring of cancer recurrence. Herein, the use of streptavidin-modified iron oxide hybrid nanozymes is reported for magnetic enrichment and bioelectrocatalytic sensing of three prostate cancer (PCa) ctRNA biomarkers with high detection specificity and sensitivity (10 copies) over an ultrabroad dynamic range (five orders of magnitude). Furthermore, the feasibility of ctRNA analysis for pre- and post-cancer treatment MRD monitoring is demonstrated using PCa urinary liquid biopsy samples.

Titania is one of the most comprehensively studied nanostructures due to its widespread applications in production of catalytic, gas- sensing and corrosion- resistance materials [1]. M-polynomial of nanotubes has been vastly investigated as it produces many degree-based topological indices which are numerical parameters capturing structural and chemical properties. These indices are used in the development of quantitative structure-activity relationships (QSARs) in which the biological activity and other properties of molecules are correlated with their structure like boiling point, stability, strain energy etc of chemical compounds. In this paper, we determine M-polynomials of single-walled titanium (SW TiO2) nanotubes and recover important topological degree based indices of them to theoretically judge these nanotubes. We also use Maple to plot surfaces associated to different types of single-walled titanium (SW TiO2) nanotubes.

In the U.S. 44% of low-income households struggle to pay their utility bills, affecting their ability to afford necessities such as food and health expenses. Several government and utility funded energy efficiency programs exist to assist those experiencing energy insecurity. In Salt Lake City, Utah, there is a high demand for, but low availability of, energy efficiency services in underserved neighborhoods creating an opportunity for creative community-based programs to fill this inherent gap. This pilot project, involving the exchanging of LED bulbs in Salt Lake City, highlights the development of a community-based energy efficiency program that aims to bring energy savings to a uniquely targeted portion of the city and determines its feasibility in addressing energy insecurity at a larger scale. Through the 8-month project duration, 1,432 bulbs were exchanged at 23 events reaching 181 households in low-income areas. Through a year of use, these bulbs are estimated to save residents approximately 18,219 USD in electricity bills and reduce CO2 emissions from power plants by 122.23 metric tons, in addition to a savings of 4,400 USD in social cost of carbon as defined by the U.S. Environmental Protection Agency. Since this pilot reached less than 1% of households, we extrapolated a reach of 2%, 5%, and 7.5% and found substantial potential decreases in power plant emissions and financial savings. As this project is ongoing and being expanded, we discuss relevant findings that will help shape future community-based models so that they are appropriately deployed and more effective in alleviating local energy insecurity.

This study investigates the emergence of ertapenem-resistant, meropenem-susceptible (ErMs) among non-carbapenemase producing (NCP) and carbapenemase producing (CP) Escherichia coli and Klebsiella pneumoniae. As mutations for ertapenem resistance establish the genetic background for non-carbapenemase meropenem resistance, there is a great need for antibiotic stewards and researchers to understand the determinants of a strain’s propensity to become resistant. Whole genome sequencing was conducted on clinical carbapenem-resistant E. coli (CREC) and K. pneumoniae (CRKP) across 5 hospitals in San Antonio, U.S. from 2012-2018. The majority of carbapenem resistant Enterobacterales (CRE) were NCP (54%; 41/76). The blaCTX-M was found to be most prevalent among NCP isolates (p = 0.02). LC-MS/MS analysis of carbapenem hydrolysis revealed that blaCTX-M-mediated carbapenem hydrolysis, indicating the need to reappraise the term, “non-carbapenemase (NCP)” for quantitatively uncharacterized CRE strains harboring blaCTX-M. Antimicrobial susceptibility results showed that 56% of all NCPE isolates had an ErMs phenotype (NCPE vs. CPE, p < 0.001), with E. coli driving the phenotype (E. coli vs. K. pneumoniae, p < 0.001). ErMs strains carrying blaCTX-M, had approximately 4-fold more copies of blaCTX-M than ceftriaxone-resistant but ertapenem and meropenem susceptible (EsMs) isolates (3.7 v. 0.9, p < 0.001). ErMs also carried more mobile genetic elements (MGEs), particularly IS26 composite transposons, than EsMs (37 vs. 0.2, p < 0.0001). Immunoblot analysis demonstrated the absence of OmpC expression in NCP-ErMs E. coli, with 92% of strains lacking full contig coverage of ompC. Overall, this work provides evidence of a collaborative effort between blaCTX-M and OmpC in NCP strains that confer resistance to ertapenem but not meropenem. To thwart potential mismanagement of CRE infected patients, future efforts should focus on understanding the mechanism(s) underlying OmpC loss, developing rapid methods to detect blaCTX-M copy number variants, and targeted antimicrobials for NCPE and ErMs strains.

Glaucoma poses a serious public health concern as it is the second leading cause of blindness after cataracts, while also being the leading cause of irreversible blindness worldwide. Glaucoma is more prevalent among Black, Latino, and Asian populations and it is essential to examine both racial and ethnic disparities that exist in treatment and prevention. As the number of people with glaucoma continues to grow, it is important to review aspects of this condition in order to better care for those affected. This article will review significant forms of glaucoma and what differentiates them in a diagnosis, treatment options, and recommendations on prevention and improving awareness

Abstract: As a low-input crop, Miscanthus offers numerous advantages that, in addition to agricultural applications, permits its exploitation for energy, fuel, and material production. Depending on the Miscanthus genotype, season, and harvest time as well as plant component (leaf versus stem), correlations between structure and properties of the corresponding isolated lignins differ. Here, a comparative study is presented between lignins isolated from M. x giganteus, M. sinensis, M. robustus and M. nagara using a catalyst-free organosolv pulping process. The lignins from different plant constituents are also compared regarding their similarities and differences regarding monolignol ratio and important linkages. Results showed that the plant genotype has the weakest influence on monolignol content and interunit linkages. In contrast, structural differences are more significant among lignins of different harvest time and/or season. Analyses were performed using fast and simple methods such as nuclear magnetic resonance (NMR) spectroscopy. Data was assigned to four different linkages (A: b-O-4 linkage, B: phenylcoumaran, C: resinol, D: b-unsaturated ester). In conclusion, A content is particularly high in leaf-derived lignins at just under 70 % and significantly lower in stem and mixture lignins at around 60 % and almost 65 %. The second most common linkage pattern is D in all isolated lignins, the proportion of which is also strongly dependent on the crop portion. Both stem and mixture lignins, have a relatively high share of approximately 20 % or more (maximum is M. sinensis Sin2 with over 30 %). In the leaf-derived lignins, the proportions are significantly lower on average. Stem samples should be chosen if the highest possible lignin content is desired, specifically from the M. x giganteus genotype, which revealed lignin contents up to 27 %. Due to the better frost resistance and higher stem stability, M. nagara offers some advantages compared to M. x giganteus. Miscanthus crops are shown to be very attractive lignocellulose feedstock (LCF) for second generation biorefineries and lignin generation in Europe.

A number of Unidentified Aerial Phenomena (UAP) encountered by military, commercial, and civilian aircraft have been reported to be structured craft that exhibit 'impossible' flight characteristics. We consider a handful of well-documented encounters, including the 2004 encounters with the Nimitz Carrier Group off the coast of California, and estimate lower bounds on the accelerations exhibited by the craft during the observed maneuvers. Estimated accelerations range from almost 100g to 1000s of g's with no observed air disturbance, no sonic booms, and no evidence of excessive heat commensurate with even the minimal estimated energies. In accordance with observations, the estimated parameters describing the behavior of these craft are both anomalous and surprising. The extreme estimated flight characteristics reveal that these observations are either fabricated or seriously in error, or that these craft exhibit technology far more advanced than any known craft on Earth. In many cases, the number and quality of witnesses, the variety of roles they played in the encounters, and the equipment used to track and record the craft favor the latter hypothesis that these are indeed technologically advanced craft. The observed flight characteristics of these craft are consistent with the flight characteristics required for interstellar travel. That is, if these observed accelerations were sustainable in space, then these craft could easily reach relativistic speeds within a matter of minutes to hours and cover interstellar distances in a matter of days to weeks, proper time.

The preparation of transition metal salt ammine complexes having oxidizing anions is a great challenge due to the reaction between the ammonia and oxidizing anions during the synthesis of these materials. However, they have an important role in the development of new oxidants in organic chemistry and especially as precursors in the preparation of mixed metal oxides and alloys in controlled temperature thermal decomposition reactions. Therefore, the synthetic procedures to prepare the complexes of transition metal permanganate, pertechnetate, and perrhenate (VIIB group tetraoxometallates) salts with ammonia as ligand or co-ligand have been comprehensively reviewed. The available data about the structure and spectroscopic properties of these compounds, including the hydrogen bonds that act as redox reaction centers under their thermal decomposition are given and evaluated. Their thermal decomposition processes and products have been summarized. The available pieces of information about their role in organic oxidation reactions like the oxidation of benzyl alcohols, and regeneration of oxo-compounds from oximes and phenylhydrazones including the kinetics of these processes have also been collected.

From a differential geometric perspective, information geometry (IG) aims to characterise the structure of statistical geodesic models. The research done for this paper offers a novel method for modelling the information geometry of a queuing system. From the perspective of IG, the manifold of the transient M/M/infinity queue is described in this context. The Fisher Information matrix (FIM) as well as the inverse of (FIM), (IFIM) of transient M/M/infinity QM are devised. In addition to that, new results that uncovered the significant impact of stability of QM on the existence of (IFIM) are obtained. Moreover, the Geodesic equations of motion of the coordinates of the underlying transient are obtained. Also, it is revealed that stable QM is developable (i.e., has a zero Gaussian curvature) and has a non-zero Ricci Curvature Tensor (RCT). Novel stability dynamics of transient M/M/iInfinity queue manifold is revealed by discovering the mutual dual impact between the behaviour of (RCT) and the stability(instability) phases of M/M/Infinity QM. Furthermore, a new discovery that presents the significant impact of stability of queue manifold and the continuity of the unique representation between M/G/1 queue manifold and Ricci Curvature Tensor (RCT). The information matrix exponential (IME) is devised. Also, it is shown that stability of the devised (IME) enforces the instability of M/M/ Infinity QM. More interestingly, novel relativistic info-geometric queueing theoretic links are revealed .

This study aims to examine the cytotoxicity mechanisms of synthetic cathinone (bath salts) on rat primary cultured neurons and primary astroglial cells, and to assess their neurobehavioral effects on mice. We administered methylenedioxypyrovalerone (MDPV) to both rat primary cultured neurons and primary astroglial cells to assess cell injury. We also analyzed the effects of MDPV on these cell cultures using immunocytochemistry. We utilized western blotting to assess the breakdown of αII-spectrin and glial fibrillary acidic protein (GFAP) induced by MDPV. The western blotting experiment also included calpain and caspase inhibitors (SNJ1945 and Z-D-DCB, respectively) and pro-apoptotic and pro-necrotic agents (Staurosporine and calcium ionophore A23187, respectively). Lastly, we assessed MDPV’s effects on behavioral effects using rotarod, locomotor activity, elevated plus maze, Morris water maze, forced swimming, and open field tests. MDPV caused a dose-dependent release of LDH in both cerebrocortical neuron-astroglia mixed cultures and primary astroglial cultures. MDPV also caused neurite breakages and astroglial process retraction on immunocytochemistry. Lastly, MDPV induced αII-spectrin breakdown in western blotting experiments. Co-administration of calpain and caspase inhibitors reduced the degradation of αII-spectrin and GFAP. MDPV administration also increased anxiety-like behavior and locomotor activity in the mice. Synthetic cathinones, which share structural similarities with methamphetamine, also induce significant neurotoxic effects and neurobehavioral effects on rodent models. These neurotoxic effects are likely mediated by calpain and caspase-induced apoptosis and necrosis, while astroglial death is likely only due to calpain activation. Therefore, further research may focus on pharmacological interventions targeting these pathways to mitigate the cytotoxic impact of cathinones in humans.

Background: Only few studies have studied the link between risk perception and sleep in the context of the COVID-19 pandemic. This study investigates the effect of two distinct risk appraisals—risk perception and perception of collective coordinated defense (PCCD) on Chinese adults’ sleep quality during the COVID-19 pandemic, and tested COVID-19-related fear and rumination as potential mediators of the relationships. Methods: Data were collected using a self-report online questionnaire from a sample of 224 Chinese adults during the fourth wave of the COVID-19 pandemic in Hong Kong. Results: COVID-19 risk perception and PCCD were related to poor sleep quality. Mediation analysis showed that both fear and rumination mediated the relationship between risk perception and sleep quality, whereas only fear mediated the relationship between PCCD and sleep quality. The model showed an excellent fit to the data and accounted for 44% of the variance in sleep quality in Chinese adults. Conclusions: This study demonstrates the distinct perceptual processes—risk appraisals in particular—contributed to poor sleep quality in Chinese adults during the COVID-19 public emergencies. These findings would be helpful for policy makers to address the sleep problems induced by psychological consequences of the pandemic.

A new set of basis functions is presented. The foundation in mathematics is established. To reconstruct a signal, it is compared to the Fourier basis functions. The M-basis functions' potential applications are also presented.

Many lifestyle and occupational habits negatively impact on physical and mental health, increasing the risk of cardiovascular and other diseases. While larger institutions fulfill occupational health requirements to ensure their employees’ wellbeing at work, smaller business workers and entrepreneurs may neglect initial signs of stress or physical decline, putting themselves at increased risk. Early detection of compromised cardiopulmonary health or fitness has the potential to flag up indications for early interventions and reduce the risk of disease onset and progression. This case study highlights the usefulness of respiratory muscle training (RMT) in improving pulmonary and cardiovascular parameters as an early countermeasure to cardiopulmonary decline. We suggest RMT as an easily accessible, cost- and time effective opportunity to support a healthy lifestyle.

The aim of this study was to evaluate the Hapo ms, a passive upper limbs exoskeleton developed to assist workers for tasks with arms in front of the body. Twelve participants had to perform a static task, a manual handling task and a load carrying task two times: with and without the exoskeleton. In all cases subjective (perceived effort in arm and back areas, comfort) and objective (muscular activity, postural balance) criteria were evaluated. Results have shown a decrease in anterior deltoid (-12 to -18% depending of the task) and in biceps brachii (-19% to -33% depending of the task) muscular activity. No significant difference was pointed out in back muscle and postural balance was not significantly perturbed due to the wear of the exoskeleton. Finally, perceived effort reduction was observed during the three tasks (except in back area for task 1). To conclude, the Hapo ms seems well adapted to assist upper arms during tasks with arms in front of the body.

Prior work has suggested that discrimination and immigration-related stress may impede mental health care seeking and utilization among Latinx populations. These effects may be more nuanced as both discrimination and immigration-related stress may increase symptomology, particularly posttraumatic stress disorder (PTSD) and depression. Both symptoms may in turn prompt attempts to seek care. The current study examined the direct effects of discrimination and immigration-related stress on care access, as well as potentially indirect effects with PTSD and depression symptoms as mediators. Interviews and online surveys were completed with 234 Latinx residents of the Midwest assessing everyday discrimination, discrimination in healthcare, PTSD symptoms, depression symptoms, current mental health utilization, and previous unsuccessful attempts to seek care. Direct effects of discrimination and immigration-related stress were largely unrelated to care access variables. Discrimination in healthcare settings predicted both unsuccessful attempts to seek care and current use, but this effect was positive. The indirect effect was largely supported, but only for PTSD symptoms and not depression. Results indicate further investigation is necessary to understand the direct effects of discrimination on care access. Further, discrimination and immigration-related stress may indirectly prompt attempts to seek mental health care.

We report on the occurrence of natural Magnesium Alumina Silicate Hydrate (M-(A)-S-H) cement at Feragen and Leka in eastern and western Trøndelag Norway, respectively. Both occurrences are located in the sub-arctic climate zone and form in glacial till and moraine material deposited on ultramafic rock during the Weichselian glaciation. Weathering of serpentinized peridotite dissolve brucite and result in a relative high pH alkaline fluid that subsequently reacts with the felsic minerals of the till (quartz, plagioclase, K-feldspar) to form a cement consisting of an amorphous material or a mixture of nanocrystalline Mg-rich phyllosilicates, including illite. The presence of plagioclase in the till results in the enrichment of alumina in the cement, i.e., forms M-A-S-H instead of the M-S-H cement. Dissolution of quartz results in numerous etch-pits and negative quartz crystals filled with M-A-S-H cement. Where the quartz dissolution is faster that the cement precipitation, a honeycomb-like texture is formed. Compositionally the cemented till (tillite) contains more MgO and has a higher loss of ignition than the till, suggesting that the cement is formed by a MgO fluid that previously reacted with the peridotite. The M-(A)-S-H cemented till represent a new type of duricrust, coined magsilcrete. The study of natural Mg-cement provides information on peridotites as a Mg-source for Mg-cement and as a feedstock for CO2 sequestration.

We find that the standard relative entropy and the Umegaki entropy are designed for the purpose of inferentially updating probability and density matrices respectively. From the same set of inferentially guided design criteria, both of the previously stated entropies are derived in parallel. This formulates a quantum maximum entropy method for the purpose of inferring density matrices in the absence of complete information.

The misuse of antibiotics during the last decades led to the emergence of multidrug resistant pathogenic bacteria. This phenomenon constitutes a major public health issue. Consequently, the discovery of new antibacterials in the short term is crucial. Colicins, due to their antibacterial properties, thus constitute good candidates. These toxin proteins, produced by E. coli to kill enteric relative competitors, exhibit cytotoxicity through ionophoric activity or essential macromolecule degradation. Among the 25-colicin types known to date, colicin M (ColM) is the only one colicin interfering with peptidoglycan biosynthesis. Accordingly, ColM develops its lethal activity in E. coli periplasm by hydrolyzing the last peptidoglycan precursor, lipid II, into two dead-end products, thereby leading to cell lysis. Since the discovery of its unusual mode of action, several ColM orthologs have also been identified based on sequence alignments; all of the characterized ColM-like proteins display the same enzymatic activity of lipid II degradation and narrow antibacterial spectra. This publication aims at being an exhaustive review about what is currently known on this new family of antibacterial enzymes as well as on their potential use of food preservatives or therapeutic agents.

Current therapeutic strategies targeting cancer cells within solid tumors have displayed limited success owing to the presence of non-cancer components referred to as the tumor stroma within the tumor microenvironment (TM). These stromal cells, extracellular matrix and blood vessels influence cancer cell response to therapy and play key roles in tumor relapse and resistance. Of the stromal cells present in the TM, a lot of attention has been given to cancer-associated fibroblasts (CAFs) as they are the most abundant and are important in cancer initiation, progression and therapy resistance. In this updated review I emphasize the role of CAFs in the regulation of tumor cell behaviour and reveal how CAF-derived factors and signaling influence tumor cell heterogeneity and development of novel strategies to combat cancer. To investigate the expression of CAF markers in tumor tissues versus normal tissues, transcriptomic data from The Cancer Genome Atlas (TCGA) and the Gene Expression Profiling Interactive Analysis (GEPIA) databases was used. Bioinformatic analysis reveals differential expression of CAF markers in several cancer types, underscoring the need for further multiomics and biochemical studies on CAFs, CAF subsets and markers. Differences in CAF markers’ expression could be due to different cellular origins as well as the effect of cancer-specific tumor microenvironmental effect on CAFs. Lastly, I present recent advances in therapeutic targeting of CAFs and the success of such endeavours or its lack thereof. It is recommended that for patients’ outcomes to improve, cancer treatment be combinatorial in nature, targeting both cancer cells and stromal cells and interactions.

: Extra- and intra-cellular activity occurs under the direction of numerous inter-molecular interactions, and in any tissue or cell, molecules are densely packed, thus promoting those molecular interactions. Galectins and chemokines, the focus of this review, are small, protein effector molecules that mediate various cellular functions, in particular cell adhesion and migration, as well as cell signaling/activation. In the past, researchers have reported that combinations of these (and other) effector molecules act separately, yet sometimes in concert, but nevertheless physically apart and via their individual cell receptors. This view that each effector molecule functions independently of the other limits our thinking about functional versatility and cooperation, and, in turn, ignores the prospect of physiologically important inter-molecular interactions, especially when both molecules are present or co-expressed in the same cellular environment. This review is focused on such protein-protein interactions with chemokines and galectins, their homo- and hetero-oligomeric structures that they can form, and the functional consequences of those paired interactions.

Many cellular functions important for tumor initiation and progression are mediated by members of the integrin family, a diverse family of cell adhesion receptors. With recent studies emphasising on the role of the tumor microenvironment (TME) in tumor initiation and progression, it is not surprising that a lot of attention is being given to integrins. Several integrins are under trial with many demonstrating appealing activity in patients with different cancers. A deeper knowledge of the functions of integrins within the tumor microenvironment is still required, and might lead to better inhibitors being discovered. Integrin expression is commonly dysregulated in many tumors with integrins playing key roles in signaling as well as promotion of tumor cell invasion and migration. This review report new data on the differential expression of integrins within solid tumors using two publicly available resources: The Cancer Genomic Atlas (TCGA) and Gene Expression Profiling Interactive Analysis (GEPIA). In this analysis, I investigated the expression of integrin alpha 2 (ITGα2), ITGα3, ITGβ4 and ITGβ6 in tumor tissues versus adjacent normal tissues. This analysis showed that integrins were differentially expressed in cervical squamous cell carcinoma (CESC), head and neck squamous cell carcinoma (HNSC), esophageal carcinoma (ESCA) and lung adenocarcinoma (LUAD). This analysis showed that ITGα2 and ITGβ6 expression are upregulated in CESC and ESCA, ITGα3 is upregulated in HNSC and ESCA whilst ITGβ4 is highly expressed in CESC, HNSC, ESCA and LUAD tumor tissues compared to adjacent normal tissues. Integrins also play a major role in adhesion of circulating tumor cells to new sites and the resulting formation of secondary tumors. Furthermore, integrins have demonstrated the ability to promoting stem cell-like properties in tumor cells as well as drug resistance. Anti-integrin therapies rely heavily on the doses or concentrations used as these determine whether the drugs act as antagonists or as integrin agonists. This review offers the latest synthesis in terms of current knowledge of integrins functions within the tumor microenvironment and potential targets for different cancers.

Early reports demonstrated the presence of cells with stem-like properties in bone marrow, with these cells having both hematopoietic and mesenchymal lineages. Over the years, various investigations have purified and characterized mesenchymal stromal/stem cells (MSCs) from different human tissues as cells with multi-lineage differentiation potential under the appropriate conditions. Due to their appealing characteristics and potential, MSCs are leveraged in many applications including medicine, oncology, bioprinting and as recent as treatment of COVID-19. To date, reports indicate mesenchymal stromal/stem cells have varied differentiation capabilities into different cell types and demonstrate immunomodulating and anti-inflammatory properties. Reports indicate that different MSCs microenvironments or niche and the resulting heterogeneity may influence their behavior and differentiation capacity. The potential clinical applications of mesenchymal stromal/stem cells have led to an avalanche of research reports on their properties and hundreds of clinical trials being undertaken. The future looks bright and promising for mesenchymal stem cell research with many clinical trials under way to prove their utility in many applications and in the clinic. This report provides an update on the potential broader use of mesenchymal stromal/stem cells, review early observations of the presence of these cells in the bone marrow and their magnificent differentiation capabilities and immunomodulation.

This paper defines the two main causes of global warming in the UK and seeks to cut climate change using green hydrogen made from renewable electricity sources. Combustion vehicles powered by fossil gasoline and diesel emit a third of UK climate-warming CO2 while buildings heated by natural gas provide a quarter. First, current UK grid problems are defined: Electricity grid, gas grid and petroleum grid. Then experiments on the private energy community of Keele University allow electrolysis demonstrations producing green hydrogen for buildings and vehicle refueling. Next, the model supply chain is planned and tested. Finally, experiments and calculations are outlined, analyzing the optimum system design criteria proposed. We conclude that economic green hydrogen can displace diesel and gasoline in vehicle transport, while also displacing natural gas for combined heat and power in buildings. In addition, the prospect in 2023 is that profits can now be made all along the green hydrogen supply chain, such that new businesses involved in clean communities can beat the National Grid monopoly and other large dominant fossil grid companies.

Human-Computer Interaction, including technology-aided instruction, is beginning to focus on virtual reality (VR) technology due to its ability to support immersive learning, teaching through simulation, and gamification of learning. These systems can deliver high-level multisensory learning experiences that are important in the teaching of many subjects, especially those involving abstract concepts or requiring spatial skills, such as organic chemistry. Haptic experiences with VR, however, remain a challenge. In addition, development have focused on general entertainment/gaming; VR systems in chemistry implement simulations of the chemistry laboratory and other advanced systems whereas those that support safe, game-like, immersive and multisensory learning of organic chemistry with haptics at pre-university education levels are scarce. We developed the VR Multisensory Classroom (VRMC) as an immersive learning environment within a VR head-mounted display, where learners employ hand movements to build hydrocarbon molecules and experience haptic feedback through gloves with built-in sensors and hand-tracking with the Leap Motion system. We report here the evaluation of the first prototype by learners from diverse backgrounds who reported on the ability of the VRMC to support high engagement, motivation, interest and organic chemistry learning as well as diverse learning styles. The VRMC is a novel VR classroom that supports immersive learning in molecular organic chemistry with haptics for multisensory learning.

Colorectal cancer (CRC) is the third most commonly diagnosed cancer worldwide, and despite advances in treatment, survival rates are still low; therefore, the development of novel drugs is imperative. Acetylcorynoline (ACN) is derived from Corydalis ambigua. The effect of ACN on colon cancer is still unknown. Therefore, we investigated its potential effects. Our data showed that ACN inhibited cell viability and proliferation. Moreover, ACN induced apoptosis and cell cycle arrest by inhibiting cell growth. In the present study, we hypothesized that ACN regulates c-Myc through CNOT2 or MID1IP1. ACN reduced the protein expression of oncogenic genes, decreased c-Myc half-life, and rapidly inhibited the serum stimulation response. Moreover, knockdown of CNOT2 and MID1IP1 with ACN increased apoptosis and further reduced the expression of oncogenes. In addition, ACN exhibited a synergistic effect with low-dose of 5-fluorouracil (5-FU) and doxorubicin (Dox). Collectively, our data demonstrates that ACN inhibited c-Myc expression through CNOT2 and MID1IP1 and induced apoptosis. These findings indicate the potential of ACN as a therapeutic agent against colon cancer.

The World Health Organization(WHO) in 2016 considered mHealth as: “the use of mobile wireless technologies including smart devices such as smartphones and smartwatches for public health” as an important resource for health services delivery and public health given their ease of use, broad reach and acceptance. WHO emphasizes the potential of this technology to increase access to health information, services and skills as well as promoting positive changes in health behaviors and management of diseases. In this regard, the capability of smartphones and smartwatches for m-health monitoring as well as verification of the patient the signal has become an important component of mHealth system. Most of the smartwatches could extract more than one bioelectrical signal therefore, therefore they provide suitable platform for extracting health data for e-monitoring. The existing approaches have not considered the integrity of data obtained from these smart devices. Therefore, it is important that the integrity of the collected data be verified continuously through user authentication. This could be done using any of the bioelectrical signals extracted and transmitted for e-monitoring. In this article, a smartwatch is used for extracting bioelectrical signal before decomposing the signal into sub-bands of Detail and Approximation Coefficient for user authentication. To select suitable features using biorthogonal wavelet decomposition of signal from a non-intrusive extraction, a detailed experiment is conducted extracting suitable statistical features from the bioelectrical signal from 30 subjects using different biorthogonal wavelet family. Ten features are extracted using Biorthogonal wavelet to decompose the signal into three levels of sub-band Detail and Approximation Coefficient and features extracted from each level the decomposed Detail and Approximation Coefficients. Comparison analysis is done after the classification of the extracted features based on the Equal Error Rate (EER). Using Neural Network (NN) classifier, Biorthogonal Wavelet Detail Coefficient Sub-band level 3 of bior1.1 achieved the best result of EER 13.80% with the fusion of the best sub-band three levels of bior1.1 achieving a better result of 12.42% EER.

Extensive genome structure variation, such as copy number variations (CNVs) and presence/absence variations, is the basis for the remarkable maize genetic diversity; however, the effect of CNVs on maize herbivory defense remains largely underexplored. Here, we report that the naturally occurring duplication of the maize 9-lipoxygenase gene, ZmLOX5, leads to increased resistance of maize to herbivory by fall armyworms (FAW). Previously, we showed that ZmLOX5-derived oxylipins are required for defense against chewing insect herbivores and identified several inbred lines, including Yu796, that contained duplicated CNVs of ZmLOX5, referred to as Yu796-2×LOX5. To test whether introgression of the Yu796-2×LOX5 locus into the herbivore-susceptible B73 background that contains a single ZmLOX5 gene is a feasible approach to increase resistance, we generated a series of near-isogenic lines that contained either 2, 1 or 0 copies of the Yu796-2×LOX5 locus in the B73 background by six back crosses (BC6). Droplet digital PCR (ddPCR) confirmed the successful introgression of the Yu796-2×LOX5 locus in B73. The resulting B73-2×LOX5 inbred line displayed increased resistance against FAW associated with increased expression of ZmLOX5, increased wound-induced production of its primary oxylipin product, the α-ketol, 9-hydroxy-10-oxo-12(Z),15(Z)-octadecadienoic acid (9,10-KODA), and the downstream defense hormones regulated by this molecule, 12-oxo-phytodienoic acid (12-OPDA) and abscisic acid (ABA). Surprisingly, wound-induced JA-Ile production was not increased in B73-2×LOX5, resulting from the increased JA catabolism. Furthermore, B73-2×LOX5 displayed enhanced drought tolerance likely due to increased ABA and 12-OPDA content. Taken together, this study revealed that the duplicated CNV of ZmLOX5 quantitively contributes to maize antiherbivore defense and presents proof-of-concept evidence that the introgression of naturally occurring duplicated CNVs of a defensive gene into the productive, but susceptible, crop varieties is a feasible breeding approach for enhancing plant resistance to herbivory and tolerance to abiotic stress.

Let R be a commutative ring with identity and m, n be positive integers. In this paper, we introduce the class of (m,n)-prime ideals which lies properly between the classes of prime and (m,n)-closed ideals. A proper ideal I of R is called (m,n)-prime if for a,b∈R, a^{m}b∈I implies either aⁿ∈I or b∈I. Several characterizations of this new class with many examples are given. Analougus to primary decomposition, we define the (m,n)-decomposition of ideals and show that every ideal in an n-Noetherian ring has an (m,n)-decomposition. Furthermore, the (m,n)-prime avoidance theorem is proved.

We report on metastable defects introduced in n-type 4H-SiC material by epithermal and fast neutron irradiation. The epithermal and fast neutron irradiation defects in 4H-SiC are much less explored compared to electron or proton irradiation induced defects. In addition to silicon vacancy (Vsi) and carbon antisite-carbon vacancy (CAV) complex, the neutron irradiation has introduced four deep level defects, all arising from the metastable defect, the M-center. The metastable deep level defects were investigated by deep level transient spectroscopy (DLTS), high-resolution Laplace DLTS (L-DLTS) and isothermal DLTS. The existence of the fourth deep level M4, recently observed in ion implanted 4H-SiC, has been additionally confirmed in neutron irradiated samples. The isothermal DLTS technique has been proven as a useful tool for studying the metastable defects.

The current work reports the upper bound of the state variable of the of the Pointwise Steady Fluid Flow Approximation (PSFFA) model of non-stationary M/Ek/1 queueing system.

We examine the relation between environmental, social, and governance commitment levels (ESG) and firm dividend payer status. Given that larger and more profitable firms are positively associated with both payer status and ESG, it could be that ESG and dividends are complements. However, given that both dividends and ESG relate to firm spending decisions, it may be that the choice is “either/or” and that ESG and dividends are substitutes. We document a positive relation between ESG and dividend payer status in U.S. firms over the period 1991-2016. In particular we find that the proportion of dividend payers is roughly 13% higher for firms with positive ESG compared to those with negative ESG. Including ESG in the models used to predict payer status provides, on average, a nearly 26% improvement in relative forecast accuracy. Our results are robust to estimation techniques and the inclusion of variables known to be determinants of payer status.

Soil-borne Trichoderma spp. have been extensively studied for their biocontrol activities against pathogens and growth promotion ability with plants. However, the beneficial effect of Trichoderma on inducing resistance against insect herbivores has been considered only recently. Among diverse Trichoderma species, consistent with previous reports, we showed that root colonization by T. virens triggered induced systemic resistance (ISR) to leaf-infecting fungal pathogens. Whether T. virens induces ISR to insect pests has not been tested before. In this study, we investigated whether T. virens affects jasmonic acid (JA) biosynthesis and defense against fall armyworm (FAW) and western corn rootworm (WCR). Unexpectedly, the results showed that T. virens colonization of maize seedlings grown in autoclaved soil suppressed wound-induced production of JA, resulting in reduced resistance to FAW. Similarly, the bacterial endophyte Pseudomonas chlororaphis 30-84 suppressed systemic resistance to FAW due to reduced JA. Further comparative analyses of the systemic effects of these endophytes when applied into sterile or non-sterile field soil showed that both T. virens and P. chlororaphis 30-84 triggered ISR against hemibiotrophic fungal pathogen Colletotrichum graminicola in both soil conditions, but only suppressed resistance to FAW in sterile soil. In contrast to the effect on FAW defense, T. virens colonization of maize roots suppressed WCR larvae survival and weight gain. This is the first report suggesting the potential role of T. virens as a biocontrol agent against WCR.

The theories of quantum mechanics and relativity dramatically altered our understanding of the universe ushering in the era of modern physics. Quantum theory deals with objects probabilistically at small scales, whereas relativity deals classically with motion in space and time. We show here that the mathematical structures of quantum theory and of relativity follow together from pure thought, defined and uniquely constrained by the same elementary ``combining and sequencing'' symmetries that underlie standard arithmetic and probability. The key is uncertainty, which inevitably accompanies observation of quantity and imposes the use of pairs of numbers. The symmetries then lead directly to the use of complex \sqrt{-1} arithmetic, the standard calculus of quantum mechanics, and the Lorentz transformations of relativistic spacetime. One dimension of time and three dimensions of space are thus derived as the profound and inevitable framework of physics.

Manzamines are complex polycyclic marine-derived β-carboline alkaloids with reported anticancer, immunostimulatory, anti-inflammatory, antibacterial, antiviral, antimalarial, neuritogenic, hyperlipidemia and atherosclerosis suppression bioactivities, putatively associated with inhibition of glycogen synthase kinase-3, cyclin-dependent kinase 5, and vacuolar ATPases. We hypothesized that additional and yet undiscovered molecular targets might be associated with Manzamine A (MZA) reported pharmacological properties. We report herein for the first time to our knowledge that MZA inhibited a 90kDa ribosomal protein kinase S6 (RSK1) when screened against a panel of 30 protein kinases. Furthermore in vitro RSK kinase assays demonstrated a 10-fold selectivity in potency of MZA against RSK1 versus RSK2. MZA’s differential binding and selectivity toward the two isoforms is also supported by computational docking experiments. Specifically, the RSK1-MZA (N- and C-termini) complexes appear to have stronger interactions and preferable energetics contrary to the RSK2-MZA ones. In addition, our computational strategy suggests that MZA binds to the N-terminal kinase domain of RSK1 rather than the C-terminal domain. RSK is a vertebrate family of cytosolic serine-threonine kinases that act downstream of the ras-ERK1/2 (extracellular-signal-regulated kinase 1/2) pathway, which phosphorylates substrates shown to regulate several cellular processes including growth, survival and proliferation. Consequently, our findings have lead us to hypothesize that MZA and the 80 currently known manzamine-type alkaloids isolated from several sponge genera, may have novel pharmacological properties.

Pulmonary infections with Mycobacterium avium occur in susceptible individuals following exposure to the bacterium in the environment, where it often persists in biofilms. Many methods have been used to generate biofilms of M. avium, and it is unknown whether different approaches generate similar structures and cell phenotypes. To make a parallel comparison of in vitro biofilm ultrastructure, extracellular matrix (ECM) composition, and drug susceptibility of biofilm resident bacteria, we used two published methods to generate M. avium biofilms: four week incubation in M63 medium or 24 hour exposure to dithiothreitol (DTT). Scanning electron microscopy revealed differences in biofilm ultrastructure between the two methods, including variation in appearance of ECM materials and morphology of resident cells, while light microscopy and staining with calcofluor white indicated that both biofilms contained polysaccharides characteristic of cellulose. Measuring susceptibility of biofilms to degradation by enzymes suggested differences in structurally important ECM molecules, with DTT biofilms having important protein and, to a lesser extent, cellulose components, and M63 biofilms having moderate protein, cellulose, and DNA components. Both biofilms conferred resistance to the bactericidal effects of amikacin and clarithromycin, with resident cells being killed at >10-fold lower rates than planktonic cells at almost all concentrations. Though these comparisons indicate differences in biofilm responses by M. avium under differing conditions, they also suggest common features of biofilm formation including cellulose production and antimicrobial resistance.

The topological index is a numerical quantity based on the characteristics of various invariants or molecular graph. For ease of discussion, these indices are classified according to their logical derivation from topological invariants rather than their temporal development. Degree based topological indices depends upon the degree of vertices. This paper computes degree based topological indices of Bismuth Tri-Iodide chains and sheets with the help of M-polynomial.

The extracellular matrix (ECM) is a ubiquitous member of the body and is key to the maintenance of tissues and organs integrity. Initially thought to be a by-stander in many cellular processes, the extracellular matrix has been shown to have diverse components that regulate and activate many cellular processes and ultimately influence cell phenotype. Importantly, the ECM composition, architecture, and stiffness/elasticity influence cellular phenotypes. Under normal conditions and during development, the synthesized ECM is constantly undergoing degradation and remodeling processes via the action of matrix proteases that maintain tissue homeostasis. In many pathological conditions including fibrosis and cancer, the ECM synthesis, remodeling, and degradation is dysregulated causing its integrity to be altered. Both physical and chemical cues from the ECM are sensed via receptors including integrins and play key roles in driving cellular proliferation and differentiation and in various disease progression such as cancers. Advances in ‘omics’ technologies have seen an increase in studies focussing on bi-directional cell-matrix interactions and here we highlight emerging knowledge on the role played by the ECM during normal development and in pathological conditions. This review summarizes current ECM-targeted-therapies that can modify tumor ECM to overcome drug resistance and better cancer treatment.

Soil and Water Assessment Tool (SWAT) was used to simulate five glacierized river basins that are global in coverage and vary in climate. The river basins included the Narayani (Nepal), Vakhsh (Central Asia), Rhone (Switzerland), Mendoza (Central Andes, Argentina), and Central Dry Andes (Chile) with a total area of 85,000 km2. A modified SWAT snow algorithm was applied in order to consider spatial variation of associated snow melt /accumulation by elevation band across each subbasin. In the previous studies, melt rates varied as a function of elevation resulting from an air temperature gradient while the snow parameters were constant throughout the entire basin. A major improvement of the new snow algorithm is separating the glaciers from seasonal snow based on their characteristics. Two SWAT snow algorithms were evaluated in simulation of monthly runoff from glaciered watershed: 1) the snow parameters are lumped (i.e. constant throughout the entire basin) and 2) the snow parameters are spatially variable based on elevation band-subbasin (i.e. modified snow algorithm). Applying the distributed SWAT snow algorithm improved the model performance in simulation of monthly runoff with snow-glacial regime, so that mean RSR decreased to 0.49 from 0.55 and NSE increased to 0.75 from 0.69. Improvement of model performance was negligible in simulation of monthly runoff from the basins with monsoon runoff regime.

More people around the world now have obesity than suffer from starvation thanks to our modern food system. Agriculture was transformed over the 20^th century by a variety of technological advancements that relied heavily on fossil fuels. In the United States of America, government policies and economic incentives led to surplus production of cheap inputs to processed food industries that produced a wide variety of heavily marketed, convenient, rewarding, timesaving, and relatively inexpensive ultra-processed foods. The energy available in the United States food supply increased much more than population needs, albeit with large inequities in food distribution and nutrition security. While most of the rise in per capita food availability during the late 20^th and early 21^st centuries in the United States resulted in increased food waste, a variety of mechanisms have been proposed by which changes in the increasingly ultra-processed food environment resulted in excess energy intake disproportionately in people genetically susceptible to obesity. As populations continue to grow, substantial investments in coordinated nutrition and agricultural research are needed to transform our current food system to one that relies less on fossil fuels, preserves biodiversity, ensures environmental health, and provides equitable access to affordable, safe, and nutritious food that reduces the prevalence of chronic diseases like obesity.

Based on its large surface area and covering the whole human body, the skin body’s largest organ and its main function is protection. Injuries and wound healing involving the skin offer valuable lessons shared with and of relevance to other organ systems and the diseases that impact them. Arguably the most complex human body process, wound healing is a multifaceted process that involves multiple cells and the extracellular matrix (ECM), with each component playing a specific role in the different stages of the healing process. Importantly, studies indicate that cells with stem cell-like properties are present within many of the human tissues and play key roles in case of tissue and cellular injury. Cell-to-cell and cell-to-ECM interactions are salient in wound healing subsequent to an injury. Microenvironment related factors and the variations therein including hypoxia or the abundance of oxygen, the presence/absence of growth factors and cytokines add to the complexity of the wound healing process and impact cell function and result in compromised or enhanced wound healing. This expert review critically examines the advances in biochemical and analytical tools that are enable the analysis of numerous cells and molecules within the wound microenvironment, revealing great cellular heterogeneity as well as novel molecular targets of importance to enhance wound healing. In a broader angle, we emphasize the ways in which wound healing is significant in the search for perfect skin after injury and in many common complex human diseases including cancer. In all, wound healing is a centrepiece of integrative biology research and applications in medicine as well as dermatology as discussed in this review.

Celecoxib as adjuvant therapy has been shown in a small randomized trial for Covid-19 to prevent clinical deterioration and rapidly improve thoracic computerized axial tomography (CT-chest)¹. Multiple descriptive trials of high dose famotidine (both inpatient and outpatient) have demonstrated clinical response^2,3,4. We describe the rapid clinical responses after increasing the celecoxib dosage to 400mg bid with high dose famotidine 80mg qid in both a critical inpatient who on baseline required 40 liters per minute high flow nasal insufflation and an outpatient who declined admission but had critical Covid-19 biomarkers.

The ability to detect the presence as well as classify the activities of individuals behind visually obscuring structures is of significant benefit to police, security and emergency services in many situations. This paper presents the analysis from a series of experimental results generated using a through-the-wall (TTW) Frequency Modulated Continuous Wave (FMCW) C-Band radar system named Soprano. The objective of this analysis was to classify whether an individual was carrying an item in both hands or not using micro-Doppler information from a FMCW sensor. The radar was deployed at a standoff distance, of approximately 0.5 m, outside a residential building and used to detect multiple people walking within a room. Through the application of digital filtering, it was shown that significant suppression of the primary wall reflection is possible, significantly enhancing the target signal to clutter ratio. Singular Value Decomposition (SVD) signal processing techniques were then applied to the micro-Doppler signatures from different individuals. Features from the SVD information have been used to classify whether the person was carrying an item or walking free handed. Excellent performance of the classifier was achieved in this challenging scenario with accuracies up to 94%, suggesting that future through wall radar sensors may have the ability to reliably recognize many different types of activities in TTW scenarios using these techniques.

Fractional differential equations have become a fundamental modelling approach for understanding and simulating the many aspects of nonlocality and spatial heterogeneity of complex materials and systems. Yet, while real-order fractional operators are nowadays widely adopted, little progress has been made in extending such operators to complex-order counterparts. In this work, we introduce new definitions for the complex-order fractional Laplacian, fully consistent with the theory of averaging of smooth functions over fractal sets, and present tailored spectral methods for their numerical treatment. The proposed complex-order operators exhibit a dual particle-wave behaviour, with solutions manifesting wave-like features depending on the magnitude of the imaginary part of the fractional order. Reaction-diffusion systems driven by the complex-order fractional Laplacian exhibit unique spatio-temporal dynamics, such as equilibrium of diffusion in random materials by interference of scattered waves, conduction block and highly fractionated propagation, or the generation of completely novel Turing patterns. Taken together, our results support that the proposed complex-order operators hold unparalleled capabilities to advance the description of multiscale transport phenomena in physical and biological processes highly influenced by the heterogeneity of complex media.

10% copper substituted (BiCUVOX/Bi₂V_0.9Cu_0.1O_5.5−δ) and 5% copper/titanium double-substituted bismuth vanadate (BiCUTIVOX/Bi₂V_0.9(Cu_0.05Ti_0.05)O_5.5−δ) platelets were formed by molten salt synthesis (MSS) using a eutectic KCl/NaCl salt mixture. The product was phase pure within the limits of X-ray diffraction. The size and form of the platelets could be controlled by changing the heating temperature and time. The crystallite growth rate at a synthesis temperature of 650 °C, and activation energy for grain growth were determined for BICUTIVOX, which experienced inhibited growth compared to BICUVOX. Quasi-equilibrium, multi-foil shapes consisting of lobes around the perimeter of the platelets were observed and explained in the context of relative two-dimensional nucleation and edge growth rates.

Climate warming is expected to have pronounced effects on Arctic and Subarctic ecosystems, especially regions underlain by discontinuous and relatively warm permafrost. The main goal of this research is to evaluate the vulnerability and dynamics of permafrost under climate warming across the various ecotypes in respect of ecosystem stability, socioeconomic impact, and for better understanding possible future environmental changes. We suggested the new version of the spatially distributed permafrost dynamics model (GIPL2-MPI), which is developed in the Geophysical Institute, University of Alaska Fairbanks. This model is based on the ecosystem approach to simulate the permafrost dynamics, which we are discussing in this paper. We combined ground-based observations and numerical freeze/thaw modeling using climate-ecosystem-permafrost interactions to understand the physical processes and mechanisms controlling permafrost physical state. We predict the changes in permafrost conditions using output from two GCMs (NCAR-CCSM4 and GFDL-CM3) and Five-Model Average Ensemble for the RCP-4.5 and RCP-8.5 scaled down to 1 by 1 km spatial resolution (https://uaf-snap.org/) across entire Alaska. Our result shows that by the end of the current century widespread near-surface permafrost degradation could begin everywhere in Alaska southward of the Brooks Range as well as across some spots at the North Slope Alaska.

The scope of this study was twofold: first, to introduce a new method in examining measurement invariance, especially with large-scale studies where a large number of group comparisons are involved: the alignment approach, where only configural invariance is necessary to achieve measurement invariance. Second, to evaluate the psychometric robustness of this approach using real-life data. Particularly, we applied this approach to examine whether the factor structure of a cognitive ability test (PGAT) exhibits measurement invariance across the 26 universities of the Kingdom of Saudi Arabia. The sample consisted of 9,849 graduate students from 26 universities around the Kingdom. The results indicated a robust configural model suggesting that the P-GAT subscales were invariant across the 26 universities. Finally, the aligned factor mean values were estimated, and factor mean comparisons of every group’s mean with all other group means were conducted for both cognitive domains (Verbal and Quantitative). In both domains, King Saud University had the highest mean score among all universities. Moreover, its mean factor score was significantly higher than any other university besides Dammam University. On the other hand, several universities allocated at the northern and Southern borders of the country exhibited the lowest factor mean scores.

‘‘Sustainable Supply Chain Management’’ (SSCM) has become a hot topic on which eminent researchers are working on every day. However, it is clear that we still observe in this field of research, an artistic vagueness on the fundamental differences between Sustainable Supply Chain Management and Green Supply Chain Management (GSCM) Moreover, it is regrettable to note that previous researchers haven't yet thought about having a specific theory which can be applied to SSCM, the use of macro theories still being observed. In addition, we observe a lack of research in the oil and gas industry especially in Developing Countries when we know that this industry is the most lucrative and polluting. Therefore, this paper’s purpose consists to make a Systematic Literature Review (SLR) of 38 papers published from 2005 to 2023 especially in oil and gas industry and in Developing Countries, in order to make a clear distinction between SSCM and GSCM while highlighting the practices related to them and at the same time, generating a united theory which will bring together the triple bottom line of the SSCM. As findings, the authors built a Conceptual Framework that applies the triple bottom line of the SSCM in oil and gas industry by demonstrating that GSCM which is more related to environmental issues and is a part of the SSCM. Therefore, in order to be more efficient and to have a great impact on their performances, Oil and gas companies should apply SSCM practices rather than GSCM practices which are very different from what is applied in Developed Countries because of certain barriers and pressures.

The seismic damage in reinforced concrete bridges is identified in this study using the "M and P" hybrid technique initially developed for planar frames. The proposed methodology involves a series of pushover and instantaneous modal analyses with a progressively increasing target deck displacement along the longitudinal direction of the bridge. From the results of these analyses, the diagram of the instantaneous eigenfrequency of the bridge, ranging from the health state to near collapse, is plotted against the inelastic seismic deck displacement. By pre-determining the eigen-frequency of an existing bridge along its longitudinal direction through "monitoring and frequency identification", the target deck displacement corresponding to the damage state can directly be found from this diagram. Subsequently, the damage can be identified by examining the results of the pushover analysis at the step where the target deck displacement is indicated. The effectiveness of this proposed technique is evaluated in the context of multiple span bridges with unequal pier heights, illustrated through an example of a four-span bridge. The findings demonstrate that the damage potential in bridge piers can be successfully identified by combining the results of a monitoring process and pushover analysis.

One of the most used markers of cancer stem cells in several cancers, including colorectal cancer and breast cancer, is CD44. CD44 is a glycoprotein that traverses the cell membrane and binds to many ligands including hyaluronan resulting in activation of signaling cascades. Several reports have shown conflicting data on the expression of CD44 and that the expression depends on modes of investigations and subtypes of cancers. In addition, the correlation between CD44 expression and drug resistance, immune infiltration, EMT, metastasis and patients prognosis in several cancer types remains unclear. This study investigated CD44 expression in several cancers and explored its relationship with tumorigenesis using various publicly available databases, including The Cancer Genome Atlas, GEPIA, Oncomine, Genomics of Drug Sensitivity in Cancer and Tumor Immune Estimation Resource. Our analysis reveals that CD44 is differentially expressed in different cancers. CD44 expression is significantly associated with cancer patients’ survival in gastric, pancreatic and colorectal cancers. In addition, CD44 expression is closely linked with immune infiltration and immune suppressive features in pancreatic, colon adenocarcinoma and stomach cancer. High CD44 expression was significantly correlated with the expression of drug resistance-, EMT- and metastasis- linked genes. Tumors expressing high CD44 have higher mutation burden and afflict older patients than tumors expressing low CD44. Cell lines expressing high CD44 are more resistant to anti-cancer drugs compared to those expressing low CD44. Protein-protein interaction investigations and functional enrichment analysis showed that CD44 interacts with gene products related to cell-substrate adhesion, migration, platelet activation, and cellular response to stress. KEGG pathway analysis revealed that these genes play key roles in biological adhesion, cell component organization, locomotion, G-α-signaling and the response to stimulus. Overall, this investigation reveals that CD44 play significant roles in tumorigenesis, can be used as a prognostic biomarker in several cancers and can be therapeutically targeted in cancer therapy.

Let R be a commutative ring and m, n be positive integers. We define a proper submodule N of an R-module M to be (m,n)-closed if for r∈R and b∈M, r^{m}b∈N implies rⁿ∈(N:_{R}M) or b∈N. This class of submodules lies properly between the classes of prime and primary submodules. Many characterizations, properties and supporting examples concerning this class of submodules are provided. The notion of (m,n)-modules is introduced and characterized. Furhermore, the (m,n)-closed avoidance theorem is proved. Finally, the (m,n)-closed submodules in amalgamated modules are studied.

It has been more than a century since Erlang published his paper in 1909. The classical queueing system for the M/D/c queue has been investigated by many authors. The key is to find the roots of an equation using explicit or numerical methods. We present an alternate form of explicit solution(s) of this/these root(s) using the Lambert-W function in this paper. In addition, the unsaturated probabilities of the number of customers in the system is derived explicitly in terms of this/these root(s). Finally, the mean number of customers in the system and the mean queueing delay are obtained from these probabilities. The exact queueing delay formula for the M/D/c queue is expressed in closed-form in terms of the root(s). Numerical results show that they are in excellent agreement with the numerical results published by Seelen, Tijms and Van Hoorn.

Acid proteins capable of nucleating Ca2+ and displaying aggregation capacity play key roles in the formation of calcium carbonate biominerals. EF-hands are among the largest Ca2+-binding motif in proteins. Gad m 1, an Atlantic cod β-parvalbumin isoform, is a monomeric EF-hand protein that acts as a Ca2+ buffer in fish muscle and is able to form amyloids under acidic conditions. Since nucleating Ca2+ protein have a propensity to form extended β-strand structures, we wondered whether amyloid assemblies of a protein containing refolded EF-hand motifs were able to influence the in vitro calcium carbonate crystallization. Here we have used the Gad m 1 chain as model to generate monomeric and amyloid assemblies and analyze their effect on in vitro calcite formation. We found that only amyloid assemblies alter calcite morphology.

The current study characterizes the transient M/M/1 queue manifold info-geometrically, through devising Fisher Information matrix(FIM) and its inverse(IFIM). Additionally, the impact of stability on the existence of IFIM and explore the geodesic equations of motion has been revealed. More potentially, the paper discusses some info-geometric applications to Machine Learning are highlighted. Closing remarks with some challenging open problems combined with the next phase of research are given.

Cotton is the most ubiquitous and profitable fiber with diverse industrial and domestic applications. Grown in over 100 countries, it has a global market value of about $40 billion and employs over 350 million people from fields to textile mills, contributing about 7% of total labor-force recruitment in developing economies. Cotton has an indeterminate growth habit and an extensive tap root system affected by soil physicochemical and environmental conditions. There is a consensus among experts that conventional cotton cultivation still has a long way to attain sustainability, which is essential if cotton will maintain its competitive edge over other natural and synthetic fibers like hemp, polyesters, and rayon. Despite several efforts already committed to growing cotton sustainably, sustainability has eluded cotton cultivation globally because of the intense farm inputs (freshwater, pesticides, and heavy-duty equipment) needs, especially in developing economies. Some of the technological advancements towards achieving the goal of sustainable cotton cultivation include the development of new varieties, improved irrigation and mulching and precision agriculture techniques, application of remote sensing and Unmanned Aerial Systems (UAS) combined with image processing, and the introduction of autonomous and multi-purpose robotic platforms for growing and harvesting cotton. This review attempts to evaluate the successes already achieved by stakeholders in moving cotton towards sustainable production and identify areas where efforts are still needed to reach sustainable production and improved profitability goals for cotton with projections for future research directions.

We summarize structural instabilities exhibited by the one dimensional (1D) (arene)2X family of organic conductors in relation with their electronic and magnetic properties. With a charge transfer of one electron to each anion X these salts exhibit a quarter-filled (hole) conduction band located on the donor stacks. Compounds built with donors such as fluorenthene and perylene derivatives and anions X such PF6 or AsF6 exhibit a high temperature (TP~170K) conventional Peierls transition which is announced by a sizeable regime of 1D 2kF charge density wave fluctuations (kF is the Fermi wave vector of the 1D electron gas located on Per stacks). Surprisingly, and probably because of the presence of a multi-sheet warped Fermi surface, the Peierls transition is considerably reduced in the perylene series α-(Per)2[M(mnt)2] where X is the dithiolate molecule with M=Au, Cu, Co and Fe. A special attention is devoted in this paper to physical properties of α-(Per)2[M(mnt)2] salts which with M=Pt, Pd and Ni incorporate segregated S=1/2 1D antiferromagnetic (AF) dithiolate stacks with 1D metallic Per stacks. We analyse conjointly the structural and magnetic properties of these salts in relation with the 1D spin-Peierls (SP) instability located on the dithiolate stacks. We show that the SP instability of the Pd and Ni derivatives occurs in the classical (adiabatic limit) while the SP instability of the Pt derivative occurs in the quantum (anti-adiabatic limit). Furthermore we show that in the Pd and Ni derivatives frustrated 1st neighbour direct and 2nd neighbour indirect (through a fine tuning with the mediated 2kF RKKY coupling interaction on Per stacks) AF interactions add their contribution to the SP instability to open a singlet-triplet gap. Our analysis of the data show unambiguously that magnetic α-(Per)2[M(mnt)2] salts are a typical realization of the physics predicted for two chain 1D Kondo lattices.

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.

Clarifying the impact mechanism of digital transformation of enterprises on the M&A efficiency of listed companies can provide a factual basis for improving capital market regulatory policies. Taking the mergers and acquisitions of listed companies from 2007 to 2021 as a research sample, the influence mechanism of the digital transformation degree of companies on their M&A efficiency was studied. The research results show that the digital transformation of listed companies will improve their M&A efficiency. Digital transformation will reduce the degree of mispricing of stocks of M&A companies, curb conflicts between managers and agents of M&A companies, and improve their M&A efficiency. Further research finds that the promotion effect of digital transformation on M&A efficiency is more significant in non-state-owned companies, with a higher degree of financing constraint and high analyst attention. In the future, regulatory authorities should actively promote the digital transformation of listed companies, curb mispricing and management agency problems in the capital market with digital governance, and improve the efficiency of mergers and acquisitions in the capital market.

Purpose. Moraxella is an ocular bacterial pathogen isolated in cases of keratitis, conjunctivitis, and endophthalmitis. Gram-negative brick-shaped diplobacilli from ocular specimens, and slow growth in culture, are early indications of Moraxella ocular infection; however, identifying Moraxella to species can be complex and inconsistent. Methods. In this study, bacteria consistent with Moraxella were identified to species using: 1) DNA sequencing coupled with vancomycin susceptibility, 2) MALDI-TOF Mass Spectrometry, and 3) Biolog ID System. Study samples consisted of 9 ATCC Moraxella controls, 82 isolates from keratitis, 21 isolates from conjunctivitis, and 4 isolates from endophthalmitis. Results. The ATCC controls were correctly identified. For keratitis, 66 (80.5%) were identified as M. nonliquefaciens, 7 (9.0%) as M. lacunata, 5 (6%) as M. osloensis, 2 (2.5%) as Acinetobacter lwoffi, 1 (1.0%) as M. bovis/nonliquefaciens, and 1 (1.0%) as M. osloensis/nonliquefaciens. For conjunctivitis, 9 (43.0%) were identified as M. osloensis, 6 (29.0%) as M. nonliquefaciens, 3 (14.3%) as Roseomonas, 2 (9.5%) as Acinetobacter (parvus, junii), and 1 (4.5%) as M. catarrhalis/M. nonliquefaciens. From endophthalmitis, 3 of 4 of the isolates were M. nonliquefaciens. Overall, M. nonliquefaciens and M. osloensis were identified in 70% (75 of 107) and 13% (14 of 107) of cases, respectively, totaling 83% (89 of 107). Conclusions. M. nonliquefaciens and M. osloensis are important bacterial pathogens of the eye as determined by DNA sequencing, MALDI-TOF MS, and Biolog. Although Moraxella catarrhalis is a clinical pathogen, other species of Moraxella appear to have a prominent role in eye infections.

Graph theory plays a crucial role in modeling and designing of chemical structure or chemical network. Chemical Graph theory helps to understand the molecular structure of molecular graph. The molecular graph consists of atoms as vertices and bonds as edges. Topological indices capture symmetry of molecular structures and give it a mathematical language to predict properties such as boiling points, viscosity, the radius of gyrations etc. In this article, we study the chemical graph of carbon Crystal structure of graphite and cubic carbon and compute several degree-based topological indices. Firstly we compute M-Polynomials of these structures and then from these M-polynomials we recover nine degree-based topological indices.

The paper deals with the problem of choosing the best O&M strategy for wind power plants. Current maintenance theory considers just production opportunities and minimizes the maintenance costs, but with the liberalization of the electricity market also the electricity price has become an important variable to take into account in the O&M scheduling. Another important variables that is often neglected by the existing maintenance theory is the weather condition. This paper proposes a new strategy that takes into account the electricity price and weather conditions, improves the expected profit of the systems, and reduce the overall maintenance and logistic costs. The maintenance schedule is formalized as an optimization problem where the discounted cumulative profit of a wind generation portfolio in a fixed-time horizon (e.g. two years ahead), subject to the technologically-derived maintenance time constraints is optimized. Both the theoretical and computational aspects of the proposed O&M strategy are discussed. Results show that taking into account market and weather opportunities in the design of the maintenance strategy, it is possible to achieve a more complete scheduling for a given set of wind power plants.

In the present manuscript, we report new insights into the concept of (a)synchronicity in Diels-Alder (DA) reactions in the framework of the reaction force analysis, in conjunction with natural population calculations and atomic resolution of energy derivatives along the intrinsic reaction coordinate (IRC) path. Our findings suggest that the DA reaction transitions between a preferentially concerted mechanism to a stepwise one in a 0.10 Å window of synchronicity indices, ranging from 0.90 to 1.00 Å. We have also shown that the relative position of the global minimum of the reaction force constant with respect to the TS is an alternative and quantifiable indicator of the (a)synchronicity in DA reactions. Moreover, the atomic resolution of energy derivatives reveals that the mechanism of the DA reaction involves two inner elementary processes associated with the formation of each of the two C-C bonds. This resolution goes on to indicate that, in asynchronous reactions, the driving and retarding components of the reaction force are mostly due the fast and slow-forming C-C bonds (elementary process) respectively, while in synchronous ones both elementary processes retard and drive the process concomitantly and equivalently.

The Drosophila spermatogenesis has the renewal of germline stem cells, meiosis of spermatocytes, and morphological transformation of spermatids into mature sperm. We previously demonstrated that Ocnus (ocn) plays an essential role in spermatogenesis. ValRS-m (Valyl-tRNA synthetase, mito-chondrial) gene was downregulated in ocn RNAi testes. By hatchability testing, we found that ValRS-m-knockdown induced complete sterility of male flies. We also concluded that ValRS-m-knockdown inhibited the transition from spermatogonia to spermatocytes and caused accumulated spermatogonia in testes. To understand the intrinsic reason for this destruction, we further conducted transcriptome sequencing analysis in ValRS-m RNAi testes. A total of 7710 dif-ferentially expressed genes (DEGs) were identified to have at least a 2-fold change with a p-value of

In order to investigate the coordination chemistry of O-alkyl N-aryl thiocarbamate ligands, BiI3 has been reacted with two equivalents of MeOC(=S)N(H)Ph in MeCN solution to afford the dinuclear title compound complexes [{I2Bi(μ2-I)2BiI2}{1-MeOC(=S)N(H)Ph}4] 1. Compound 1 has been characterized by IR, UV and NMR spectroscopy, the dinuclear framework has be ascertained by a single-crystal X-ray diffraction study performed at 100 K.

Cyclin dependent kinase 1 (CDK1) has been primarily identified as a key cell cycle regulator in both mitosis and meiosis. Recently, an extramitotic function of CDK1 emerged when evidence was found that CDK1 is involved in many cellular events that are essential for cell proliferation and survival. In this review we summarize the involvement of active CDK1 in the initiation and elongation steps of protein synthesis in eukaryotes. During its activation CDK1 influences the initiation of protein synthesis, promotes the activity of specific translational initiation factors and affects the functioning of a subset of elongation factors. Our review provides insights into gene expression regulation during the transcriptionally silent cell cycle/M-phase and describes quantitative and qualitative translational changes based on the extramitotic role of the cell cycle master regulator CDK1, to optimize temporal synthesis of proteins to sustain division-related processes: mitosis and cytokinesis.

In virology, the term reverse genetics refers to a set of methodologies in which changes are introduced into the viral genome and their effects on the generation of infectious viral progeny and their phenotypic features are assessed. Reverse genetics emerged thanks to advances in recombinant DNA technology, which made the isolation, cloning, and modification of genes through mutagenesis possible. Most virus reverse genetics studies depend on our capacity to rescue an infectious wild-type virus progeny from cell cultures transfected with an “infectious clone”. This infectious clone generally consists of a circular DNA plasmid containing a functional copy of the full-length viral genome, under the control of an appropriate polymerase promoter. For most DNA viruses, reverse genetics systems are very straightforward, since DNA virus genomes are relatively easy to handle and modify and are also (with few notable exceptions) infectious per se. This is not true for RNA viruses, whose genomes need to be reverse transcribed into cDNA before any modification can be done. Establishing reverse genetics systems for members of the Caliciviridae has proven exceptionally challenging, due to the low number of members of this family that propagate in cell culture. Despite the early successful rescue of a calicivirus from a genome-length cDNA more than two decades ago, reverse genetics methods are not routine procedures that can be easily extrapolated to other members of the family. Reports of calicivirus reverse genetics systems have been few and far between. In this review, we discuss the main pitfalls, failures, and delays behind the generation of several successful calicivirus infectious clones.

We present a modified version of the Szilard Engine, demonstrating that an explicit measurement procedure is entirely unnecessary for its operation. By considering our modified engine, we are able to provide a new interpretation of Landauer’s original argument for the cost of erasure. From this view, we demonstrate that a reset operation is strictly impossible in a dynamical system with only conservative forces. Then, we prove that to approach a reset yields an unavoidable instability at the reset point. Finally, we present an original proof of Landauer’s principle that is completely independent from the Second Law of Thermodynamics.

Tumorigenesis is a complex and dynamic process involving cell-cell and cell-extracellular matrix (ECM) interactions that allow tumor cell growth, drug resistance and metastasis. This review provides an updated summary of the role played by the tumor microenvironment (TME) components and hypoxia in tumorigenesis and highlight various ways through which tumor cells reprogram normal cells including into phenotypes that are pro-tumorigenic including cancer associated- fibroblasts, -macrophages and -endothelial cells. Tumor cells secrete numerous factors leading to transformation of a previously anti-tumorigenic environment into a pro-tumorigenic environment. Once formed, solid tumors continue to interact with various stromal cells including local and infiltrating fibroblasts, macrophages, mesenchymal stem cells, endothelial cells, pericytes, and secreted factors and the ECM within the tumor microenvironment (TME). The TME is key to tumorigenesis, drug response and treatment outcome. Importantly, stromal cells and secreted factors can initially be anti-tumorigenic but over time promote tumorigenesis and induce therapy resistance. To counter hypoxia, increased angiogenesis leads to formation of new vascular networks in order to actively promote and sustain tumor growth via supply of oxygen and nutrients whilst removing metabolic waste. Angiogenic vascular network formation aid in tumor cell metastatic dissemination. Successful tumor treatment and novel drug development require the identification and therapeutic targeting of pro-tumorigenic components of the TME including cancer-associated- fibroblasts (CAFs) and -macrophages (CAMs), hypoxia, blocking ECM-receptor interactions, in addition to targeting of tumor cells. Re-programming of stromal cells and the immune response to be anti-tumorigenic is key to therapeutic success. Lastly, this review highlights potential TME- and hypoxia-centred therapies under investigations.

Critically ill patients treated in the intensive care unit (ICU) can present many abdominal conditions that need a prompt diagnosis and timely treatment because of their general frailty. Clinical evaluation and diagnostic tools like ultrasound or CT scan are not reliable or feasible in these patients. Bedside laparoscopy (BSL) is a minimally invasive procedure that allows surgeons to assess the abdominal cavity directly in the ICU, thus avoiding unnecessary exploratory laparotomy or incidence related to intra-hospital transfer. We conducted a review of the literature to summarize the state-of-the-art of BSL. Medline, The Cochrane Central Register of Controlled Trials (CENTRAL), and Scopus databases were utilized to identify all relevant publications. Indications, contraindications, technical aspects, and outcomes are discussed. The procedure is safe, feasible, and effective. When other diagnostic tools fail to diagnose or exclude an intra-abdominal condition in ICU patients, BSL should be preferred over exploratory laparotomy.

Text fields in electronic medical records (EMR) contain information on important factors that influence health outcomes, however, they are underutilized in clinical decision making due to their unstructured nature. We analyzed 6,497 inpatient surgical cases with 719,308 free text notes from Le Bonheur Children’s Hospital EMR. We used a text mining approach on preoperative notes to obtain the text-based risk score algorithm as predictive of death within 30 days of surgery. We studied the additional performance obtained by including text-based risk score as a predictor of death along with other structured data based clinical risk factors. The C-statistic of a logistic regression model with 5-fold cross-validation significantly improved from 0.76 to 0.92 when text-based risk scores were included in addition to structured data. We conclude that preoperative free text notes in EMR include significant information that can predict adverse surgery outcomes.

The application potential of cellulosic materials in natural composites and other fields needs to be explored to develop innovative, sustainable, lightweight, functional biomass materials that are also environmentally friendly. This study investigated Typha augostifolia (Typha sp.) as a potential new raw material for extracting cellulose nanocrystals (CNCs) for application in wastewater treatment composites. Alkaline treatments and bleaching were used to remove cellulose from the stem fibers. The CNCs were then isolated from the recovered cellulose using acid hydrolysis. The study showed a few distinct functional groups (O-H, -C-H, =C-H and C-O, and C-O-C) in the Fourier Transform Infrared (FTIR) spectra. Scanning electron microscope (SEM) revealed the smooth surface of CPC and CNCs that resulted from removing lignin and hemicellulose from powdered Typha augostifolia. Based on the crystalline index, the powdered Typha augostifolia, CPC, and CNCs were 42.86%, 66.94% and 77.41%. The loss of the amorphous section of the Typha sp. fiber resulted in a decrease in particle size. It may be inferred from the features of a Typha sp. CNC that CNCs may be employed as reinforcement in composites for wastewater treatment.

Consumer preference not only dictates what food is consumed but how that food is produced. Ingredients in livestock feed that are not antibiotics, not genetically modified, not of animal origin, and that are nutrient-like, tend to be more acceptable to consumers, retailers, and producers. Mono- and diglycerides (MDG) fit these criteria, are commonly used in food, and are generally recognized as safe. But beyond being emulsifiers and a source of energy, MDG are also known to have antimicrobial, immune and microbiome modulation, and angiogenic activity. MDG in broiler diets have been shown to impact a variety of immune-related functions such as regulation of circulating antibodies, as well as decreased gene expression or protein concentration of pro-inflammatory cytokines like TNF-α, IL-1β, IL-6, and IFN-γ. In addition, MDG can affect metabolic function and intestinal integrity. Results of this review show that MDG can serve as antimicrobial and growth-supporting alternatives for reducing poultry production losses, improving resource utilization, and meeting consumer demand for sustainably produced and safe animal protein.

Fractional calculus gained a lot of attention in the last couple of years. Researchers discovered that processes in various fields follow rather fractional dynamics than ordinary integer-ordered dynamics, meaning the corresponding differential equations feature non-integer valued derivatives. There are several arguments for why this is the case, one of them being that fractional derivatives’ inherit spatiotemporal memory and/or the ability to express complex naturally occurring phenomena. Another popular topic nowadays is machine learning, i.e., learning behavior and patterns from historical data. In our ever-changing world with ever-increasing amounts of data, machine learning is a powerful tool for data analysis, problem-solving, modeling, and prediction. It further provides many insights and discoveries in various scientific disciplines. As these two modern-day topics provide a lot of potential for combined approaches to describe complex dynamics, this article reviews combined approaches of fractional derivatives and machine learning from the past, puts them into context, and thus provides a list of possible combined approaches and the corresponding techniques. Note, however, that this article does not deal with neural networks, as there already is profound literature on neural networks and fractional calculus. We sorted past combined approaches from the literature into three categories, i.e., preprocessing, machine learning & fractional dynamics, and optimization. The contributions of fractional derivatives to machine learning are manifold as they provide powerful preprocessing and feature augmentation techniques, can improve physically informed machine learning, and are capable of improving hyperparameter optimization. Thus, this article serves to motivate researchers dealing with data-based problems, to be specific machine learning practitioners, to adopt new tools and enhance their existing approaches.

Cells respond to DNA double-strand breaks by initiating DSB repair and ensuing a cell cycle checkpoint. The primary responder to DSB repair is non-homologous end joining, an error prone repair pathway. However, when DSBs are generated after DNA replication in the G2 phase of the cell cycle, a second DSB repair pathway, homologous recombination, can come into action. Both ATM and ATR are important for DSB-induced DSB repair and checkpoint responses. One method of ATM and ATR working together is through the DNA end-resection of DSBs. As a readout and marker of DNA end-resection, RPA is phosphorylated at Ser4/Ser8 of the N-terminus of RPA32 in response to DSBs. Here, the significance of RPA32 Ser4/Ser8 phosphorylation in response to DNA damage, specifically in S phase to G2 phase of the cell cycle is examined. RPA32 Ser4/Ser8 phosphorylation in G2 synchronized cells is necessary for increases in TopBP1 and Rad9 accumulation on chromatin and full activation of the ATR-dependent G2 checkpoint. In addition, our data suggest RPA Ser4/Ser8 phosphorylation modulates ATM-dependent KAP-1 phosphorylation and Rad51 chromatin loading in G2 cells.

In present paper, spatial Minkowski Pythagorean Hodograph (MPH) curves are characterized with Rational Rotation Minimizing Frames (RRMFs). We define Euler-Rodrigues Frame (ERF) for MPH curves and by means of this concept, we reach the definition of MPH curves of type (n, m). Expressing the conditions provided by these curves in the form of Minkowski-Hopf map that we define, it is aimed to establish a connection with the Lorentz force which occurs during the process of Computer Numerical Control (CNC) type sinker Electronic Discharge Machines (EDMs). This approach is reinforced by split quaternion polynomials. Finally, we give conditons satisfied by MPH curves of low degree to be type (n, m) and construct illustrative examples.

In this work, we derive the spectral efficiency, secrecy outage probability, and bit error rate of a communication system assisted by a large intelligent surface (LIS). We consider a single-antenna user and an array of antennas at the transmitter side and the possibility of a direct link between transmitter and receiver. Additionally, there is a single-antenna eavesdropper with a direct link to the transmitter, which is modeled as a Nakagami-m distributed fading coefficient. The channels from transmitter to the LIS and from the LIS to the user may or may not have the line-of-sight (LoS) and are modeled by the Nakagami- m distribution. Moreover, we assume that the LIS elements perform non-ideal phase cancellation leading to a residual phase error that assumes a Von Mises distribution. We show that the resulting channel can be accurately approximated by a Gamma distribution whose parameters are analytically estimated using the moments of the equivalent signal-to-noise ratio. We also provide an upper bound for the error probability for M-QAM modulations. With the derived formulas, we analyze the effect of the strength of the LoS link by varying the Nakagami parameter, m.

The increasing spatial and spectral resolution of hyperspectral imagers yields detailed spectroscopy measurements from both space-based and airborne platforms. Machine learning algorithms have achieved state-of-the-art material classification performance on benchmark hyperspectral data sets; however, these techniques often do not consider varying atmospheric conditions experienced in a real-world detection scenario. To reduce the impact of atmospheric effects in the at-sensor signal, atmospheric compensation must be performed. Radiative Transfer (RT) modeling can generate high-fidelity atmospheric estimates at detailed spectral resolutions, but is often too time-consuming for real-time detection scenarios. This research utilizes machine learning methods to perform dimension reduction on the transmittance, upwelling radiance, and downwelling radiance (TUD) data to create high accuracy atmospheric estimates with lower computational cost than RT modeling. The utility of this approach is investigated using the instrument line shape for the Mako long-wave infrared hyperspectral sensor. This study employs physics-based metrics and loss functions to identify promising dimension reduction techniques. As a result, TUD vectors can be produced in real-time allowing for atmospheric compensation across diverse remote sensing scenarios.

Two new zoanthamine alkaloids, namely 3-acetoxynorzoanthamine (1) and 3-acetoxyzoanthamine (2), have been isolated from the zoantharian Zoanthus cf. pulchellus collected off the coast of the Peninsula of Santa Elena – Ecuador, together with three known alkaloids zoanthamine, norzoanthamine and 3-hydroxynorzoanthamine. The chemical structures of 1 and 2 were determined by interpretation of their 1D and 2D NMR data and comparison with literature data. This is the first report of zoanthamine-type alkaloids from Zoanthus cf. pulchellus collected in the Tropical Eastern Pacific. The neuroinflammatory activity of all the isolated compounds were evaluated in microglia BV-2 cells and high inhibitory effects were observed in ROS and NO generation.

Crowdsourced Data (CSD) generated by citizens is becoming more popular as its potential utilisation in many applications is increasing due to its currency and availability. However, the quality of CSD, including its relevance, is often questioned as the data is not generated by professionals nor follows standard data collection procedures. The quality of CSD can be assessed according to a range of attributes including its relevance. Information relevance has been explored through using in Geographic Information Retrieval (GIR) techniques to identify relevant information. This research tested a relevance assessment approach for CSD by adapting relevance assessment techniques available in the GIR domain. The thematic and geographic relevance were assessed using the Term Frequency-Inverse Document Frequency (TF-IDF), Vector Space Model (VSM) and Natural Language Processing (NLP) techniques. The thematic and geographic specificities of the queries were calculated as 0.44 and 0.67 respectively, which indicates the queries used were more geographically specific than thematically specific. The Spearman's rho value of 0.62 indicated that the final ranked relevance lists showed reasonable agreement with a manually classified list and confirmed the potential of the approach for CSD relevance assessment for other possible crowdsourced data analysis.

Cardiovascular disease (CVD) is the number one cause of death worldwide. This condition resulted in huge research on CVD increasing the need for animal models suitable for the in vivo research. Daphnia and Zebrafish are good animal models for cardiovascular research due to their relative body transparency and easy culture property. Several methods have been developed to conduct cardiac performance measurement in Daphnia and Zebrafish. However, most of the methods only able to obtain heartbeat rate. The other important cardiac endpoints like stroke volume, ejection fraction, fraction shortening, cardiac output and heartbeat regularity must use other programs for measurement. To overcome this limitation, in this study, we successfully developed a one-stop ImageJ-based method using kymograph macros language that able to obtain multiple cardiac performance endpoints simultaneously for the first time. To validate its utility, we incubate Daphnia magna at different ambient temperatures and exposed zebrafish with astemizole to detect the corresponding cardiac performance alterations. In summary, the kymograph method reported in this study provides a new, easy to use, and inexpensive one-stop method on obtaining multiple cardiac performance endpoints with high accuracy and convenience.

We provide quantitative results from GIS-based modelling of urban emission functions for a range of representative low- and mid-rise locations, ranging from individual streets to residential communities within cities as well as entire towns and city regions with the aim of whether lantern photometry or built environment has the dominant effect on light pollution. We demonstrate the scalability of our work by providing results for the largest urban area modelled to date, comprising the central 117 km2 area of Dublin City and containing nearly 42,000 public lights. Our results show a general similarity in the shape of the azimuthally-averaged emission function for all areas examined, with differences in total light output distribution depending primarily on the nature of the lighting and, to a smaller extent, on the obscuring environment including seasonal foliage effects. A comparison with global satellite observations shows that they are consistent with the deduced angular emission function for other low-rise areas worldwide. We further validate our approach by comparing results for a range of urban locations by the close agreement observed in a detailed comparison of with calibrated imagery from the International Space Station. To our knowledge, this is the first such detailed quantitative verification of light loss calculations.

This study delves into the intricate interplay of economic growth components, specifically focusing on Consumption and investment in Saudi Arabia from 2000 to 2022. Employing vector error correction models and cointegration techniques, we analyze the short- and long-term dynamics within the relationship of Consumption, investment, and economic growth. Granger causality analysis is also used to discern these pivotal variables' causal connections. Our empirical analysis reveals a persistent long-term cointegration relationship among the variables, underscoring the enduring nature of their interdependency. Furthermore, our findings highlight Consumption and investment's statistically significant positive impact on economic growth. Notably, the short-term analysis unveils a stable model characterized by an annual adjustment to equilibrium of 100%.Moreover, the Granger causality study demonstrates unidirectional causal linkages between Consumption, investment, and economic growth. These findings hold substantial implications for policy formulation in Saudi Arabia. Policymakers must grasp the ramifications of burgeoning prosperity and evolving private consumption patterns on future environmental outcomes. Achieving sustainable long-term results necessitates equal emphasis on bolstering private Consumption and fostering other facets of economic growth.

To solve large scale linear equations involved in the Fast Multipole Boundary Element Method (FM-BEM) efficiently, an iterative method named the generalized minimal residual method (GMRES)(m)algorithm with Variable Restart Parameter (VRP-GMRES(m) algorithm) is proposed. By properly changing a variable restart parameter for the GMRES(m) algorithm, the iteration stagnation problem resulting from improper selection of the parameter is resolved efficiently. Based on the framework of the VRP-GMRES(m) algorithm and the relevant properties of generalized inverse matrix, the projection of the error vector r_m+1 on r_m is deduced. The result proves that the proposed algorithm is not only rapidly convergent but also highly accurate. Numerical experiments further show that the new algorithm can significantly improve the computational efficiency and accuracy. Its superiorities will be much more remarkable when it is used to solve larger scale problems. Therefore, it has extensive prospects in the FM-BEM field and other scientific and engineering computing.

Dementia education and training for workforce development is becoming increasingly important in bridging knowledge gaps among health and social care practitioners in the UK and internationally. Dementia Education for Workforce Excellence (DEWE) was developed during the COVID-19 pandemic blending both synchronous and asynchronous instruction and delivered across three different contexts: care homes, home care, and nurse education within the UK and India. This study aimed to evaluate DEWE using mixed methods with online survey data analyzed descriptively and interview data analyzed thematically. Integration of survey and interview data aimed toward a comprehensive evaluation of this novel approach for dementia workforce development. Thirty-four social care practitioners and nurse educators completed the online survey demonstrating high-level learner satisfaction; learning gains; behavioral change, and motivation to share new knowledge. Four key themes developed from the analysis of interviews (n=9) around participants’ pursuit of new knowledge; delivery modes in DEWE; learning gains and impact of DEWE; and adaptations for future program implementation. Findings suggest DEWE is an innovative resource that promotes person- and relationship-centered dementia care across all stages of one’s dementia journey. Cultural adaptations are recommended for international delivery to ensure contextual alignment and maximum impact.

The terms 'open' and 'openness' are widely used across the current higher education environment particularly in the areas of repository services and scholarly communications. Open-access licensing and open-source licensing are two prevalent manifestations of open culture within higher education research environments. As theoretical ideals, open-licensing models aim at openness and academic freedom. But operating as they do within the context of global neoliberalism, to what extent are these models constructed by, sustained by, and co-opted by neoliberalism? In this paper, we interrogate the use of open-licensing within scholarly communications and within the larger societal context of neoliberalism. Through synthesis of various sources, we will examine how open access licensing models have been constrained by neoliberal or otherwise corporate agendas, how open access and open scholarship have been reframed within discourses of compliance, how open-source software models and software are co-opted by politico-economic forces, and how the language of 'openness' is widely misused in higher education and repository services circles to drive agendas that run counter to actually increasing openness. We will finish by suggesting ways to resist this trend and use open-licensing models to resist neoliberal agendas in open scholarship.

In the power plant industry, the turbine inlet temperature (TIT) plays a key role in the efficiency of the gas turbine and, therefore, the overall—in most cases combined—thermal power cycle efficiency. Gas turbine efficiency increases by increasing TIT. However, an increase of TIT would increase the turbine component temperature which can be critical (e.g., hot gas attack). Thermal barrier coatings (TBCs)—porous media coatings—can avoid this case and protect the surface of the turbine blade. This combination of TBC and film cooling produces a better cooling performance than conventional cooling processes. The effective thermal conductivity of this composite is highly important in design and other thermal/structural assessments. In this article, the effective thermal conductivity of a simplified model of TBC is evaluated. This work details a numerical study on the steady-state thermal response of two-phase porous media in two dimensions using personal finite element analysis (FEA) code. Specifically, the system response quantity (SRQ) under investigation is the dimensionless effective thermal conductivity of the domain. A thermally conductive matrix domain is modeled with a thermally conductive circular pore arranged in a uniform packing configuration. Both the pore size and the pore thermal conductivity are varied over a range of values to investigate the relative effects on the SRQ. In this investigation, an emphasis is placed on using code and solution verification techniques to evaluate the obtained results. The method of manufactured solutions (MMS) was used to perform code verification for the study, showing the FEA code to be second-order accurate. Solution verification was performed using the grid convergence index (GCI) approach with the global deviation uncertainty estimator on a series of five systematically refined meshes for each porosity and thermal conductivity model configuration. A comparison of the SRQs across all domain configurations is made, including uncertainty derived through the GCI analysis.

Objectives Asylum seekers in Germany represent a highly vulnerable group from a health perspective due to a variety of risk factors. At the same time their access to healthcare is restricted. While the introduction of the Electronic Health Insurance Card (EHIC) for asylum seekers instead of healthcare-vouchers is discussed controversially using politico-economic reasons, there is hardly any empirical evidence on its actual impact on the use of medical services Study design Thus, the aim of this study is to examine the influence of the possession of the EHIC on the use of medical services by asylum seekers as measured by their consultation rate of ambulant physicians (CR). For this purpose, a standardized survey was carried out to 260 asylum seekers in different municipalities of which some have introduced the EHIC for asylum seekers, while others have not. Methods Various CR were differentiated considering possible third variables as well as confounding factors. The period prevalence was compared between the groups "with EHIC" and "without EHIC" using a two-sided t-test. Multivariate analysis was done using a linear OLS regression model. Results Asylum seekers who are in possession of the EHIC are significantly more likely to seek ambulant medical care than those receiving healthcare-vouchers. Their CR, however, does not differ significantly from the age-corrected CR of the autochtonous population. Taking into account relevant covariables, the possession of the EHIC can be viewed as an independent influencing factor on the asylum seekers' use of medical care. Conclusions The results of this study suggest that having to ask for healthcare-vouchers at the social security office could be a relevant barrier for asylum seekers. Nevertheless, the ownership of the EHIC does not seem to lead to an overuse of medical services.

We prove an analog of the removable singularity theorem for bounded harmonic functions on stratified sets. The harmonic functions are understood in the sense of the soft Laplacian. The result can become one of the main technical components for extending the well-known Poincaré–Perron’s method of proving the solvability of the Dirichlet problem for the soft Laplacian.

Background: The practice of self-medication is common worldwide and is an important component of medical self-care. However, the practice can be dangerous and is linked to various risks for the patients and the entire community. This study aimed to estimate the prevalence and factors associated with self-medication among Bangladeshi adults. Methods: A cross-sectional survey was conducted between April and June 2021 among Bangladeshi adults (aged >19 years) using convenient sampling. A total of 1320 data were collected through face-to-face interviews using a standardized questionnaire. Multivariable logistic regression analysis was used to identify factors associated with self-medication practice (SMP). Results: Overall, 41% of adults in our survey reported SMP. The most common illnesses that prompted SMP were common cold/flu (66.4%), gastric problems (65%), and headache (64.4%). The most frequent reasons for SMP were to get better services (30.59%), perceive SMP without side effects (23.28%), and save time with effectiveness (14.56%). Potential risk factors included 10 years (AOR = 1.91; 95% CI: 1.04 - 3.50) and >12 years of schooling (AOR = 5.03; 95% CI: 2.27 - 11.15), being a businessman (AOR = 4.64; 95% CI: 1.74 - 12.37), having ≤6 family members (AOR = 2.13; 95% CI: 1.40 - 3.24), being a member of a social group (AOR = 1.53; 95% CI: 1.10 - 2.12), a health status check after every six months (AOR = 1.52; 95% CI: 1.08 - 2.13), and current ill-health (AOR = 1.41; 95% CI: 1.06 - 1.87). Protective factors identified included ≤30 years of age (AOR = 0.40; 95% CI: 0.17 - 0.93), and practice of modern (AOR = 0.39; 95% CI: 0.22- 0.69) and herbal (AOR = 0.45; 95% CI: 0.21- 0.97) healing types. Conclusion: More than one-third of the study participants reported practicing self-medication. Increasing the community’s awareness of the extreme consequences of SMP and not just the average experience might sway individuals away from SMP, and implementing strict jurisdiction could be a way to minimize the SMP.

In this study, we address the formidable challenge of solving large-scale Max-Cut problems (MCP). We introduce a rapid computational procedure utilizing a hybrid 1-flip/r-flip local search heuristic. This innovative strategy significantly reduces the computational time required for MCP problems while consistently generating solutions of exceptional quality. The paper presents substantial computational insights, showcasing the effectiveness of our approach on very-large-scale Max-Cut instances with varying densities. Our proposed heuristic is rigorously evaluated by comparing its performance against a quantum annealing solver, leveraging a multi-start Tabu Search framework. The results underscore the potency of this unique combination as an efficient and effective solution for large-scale QUBO problems. Notably, our hybrid heuristic consistently delivers high-quality solutions within the stringent CPU time limits of 600 seconds, demonstrating its efficacy across Max-Cut instances ranging from 10,000 to 40,000 variables. This research contributes to advancing the state-of-the-art in large-scale QUBO problem-solving, offering a powerful and time-efficient approach with broad applicability.

In the last two decades, the discovery of various pathways involved in renal cell carcinoma (RCC) have led to the development of biologically-driven targeted therapies. Hypoxia inducible factors (HIFs), angiogenic growth factors, von Hippel-Lindau (VHL) gene mutations and oncogenic miRNAs play essential roles in the pathogenesis and drug resistance of clear cell renal cell carcinoma. These insights have led to the development of VEGF inhibitors, mTOR inhibitors and immunotherapeutic agents which have significantly improved outcomes of patients with advanced RCC. HIF inhibitors will be a valuable asset in the growing therapeutic armamentarium of RCC. Various histone deacetylase (HDAC)inhibitors, including selenium and agents such as PT2385 and PT2977, are being explored in various clinical trials as potential HIF inhibitors to ameliorate the outcomes of RCC patients. In this article, we will review the current treatment options and highlight the potential role of selenium in the modulation of drug resistance biomarkers expressed in ccRCC tumors.

Background: Polycystic ovary syndrome (PCOS) is a common reproductive and endocrinological disease characterized by ovulatory dysfunction, polycystic ovaries, and hyperandrogenism. Adipokines are believed to contribute to developing PCOS and its accompanying metabolic complications such as dyslipidemia, insulin resistance, and cardiovascular diseases. Oncostatin M (OSM), a novel adipokine, plays a role in oogenesis, lipogenesis, and inflammation and may contribute to PCOS pathogenesis and its related metabolic problems. Methods: In this case-control study, the patients were grouped in a 1:1 ratio into either the PCOS (n = 32) or the control group (n = 32). Blood samples were obtained between the 3rd and 5th days of the menstrual cycle. Serum levels of fasting glucose, insulin, C-reactive protein (CRP), low-density lipoprotein, high-density lipoprotein, triglyceride, white blood cell count, thyroid-stimulating hormone, luteinizing hormone, follicle-stimulating hormone, total testosterone, prolactin estradiol, and OSM were analyzed. Results: OSM levels were significantly lower, but CRP levels were substantially higher in the PCOS group than in the control group (p = .002, p = .001, respectively). OSM was inversely correlated with total cholesterol, non-high-density lipoprotein cholesterol, fasting glucose, and the luteinizing hormone/follicle-stimulating hormone ratio (ρ = .329, p = .017; ρ = .386, p = .005; ρ = .440, p = .001; ρ = .316, p = .023, respectively). Conversely, there was no correlation between OSM and total testosterone level (ρ = .220; p = .118). In the context of inflammation and metabolic parameters, OSM was inversely correlated with CRP, Homeostatic Model Assessment for Insulin Resistance score (HOMA-IR), and low-density lipoprotein cholesterol (LDL) (ρ = .353, p = .019; ρ = .275, p = .048; ρ = .470, p < .001, respectively). The performance of Oncostatin M for diagnosing PCOS showed 50% sensitivity, 75% specificity, and 63% accuracy (p = .009) in ROC curve analysis. Conclusions: Plasma OSM levels were considerably lower in patients with PCOS than in the control group, and this was inversely correlated with the hormonal and metabolic parameters of PCOS. Thus, OSM may be a novel therapeutic target for PCOS and metabolic complications.

In this paper, chaos sequence is used to replace the traditional Spread Spectrum sequence. From the perspective of the communication partner, a new method of generating the initial value of chaotic sequence is proposed, which is more suitable for the multi-base Spread Spectrum System and easy to extract. In order to further improve the error performance of the system and ensure the integrity of the system, an improved suboptimal soft information extraction method based on log-likelihood ratio (LLR) is proposed in the channel coding module, which can further improve the error performance of the system. On this basis, we choose the synchronization mode of multiple transmission of one reference signal to solve the problem that chaotic sequence is difficult to obtain synchronization because of its aperiodic characteristics. Finally, the system is simulated in the channel with low SNR. The simulation results show that chaotic sequence as Spread Spectrum code can make the signal transmit accurately in the worse channel environment. The performance gain of applying soft information decoding decision in the M-ary Spread Spectrum System with chaotic sequence as Spread Spectrum code can reach 5.2dB compared with the traditional Direct Spread Spectrum System.

Imbalance of homeostasis between the microbial communities and the host system leads to dysbiosis in oral micro flora. DMTU (1,3-di-m-tolyl-urea), is a biocompatible compound that was shown to inhibit Streptococcus mutansbiofilms by inhibiting its communication system (quorum sensing). Here, we hypothesized that DMTU is able to inhibit multispecies biofilms. We developed a multispecies oral biofilm model comprising an early colonizer Streptococcus gordonii, a bridge colonizer Fusobacterium nucleatum, and late colonizers Porphyromonas gingivalis, Aggregatibacter actinomycetemcomitans. We performed comprehensive investigations to demonstrate the effect of DMTU on planktonic cells and biofilms. Our findings showed that DMTU inhibits and disrupts multispecies biofilms without bactericidal effects. Mechanistic studies revealed significant down regulation of biofilm and virulence related genes in P. gingivalis. Taken together, our study highlights the potential of DMTU to inhibit polymicrobial biofilm communities and their virulence.

In this article, we investigate the applicability of quantum machine learning for classification tasks using two quantum classifiers from the Qiskit Python environment: the Variational Quantum Classifier (VQC) and the Quantum Kernel Estimator (QKE). We evaluate the performance of these classifiers on six widely known and publicly available benchmark datasets and analyze how their performance varies with the number of samples on two artificially generated test classification datasets. As quantum machine learning is based on unitary transformations, this paper explores data structures and application fields that could be particularly suitable for quantum advantages. Hereby, we developed a data set based on concepts from quantum mechanics using the exponential map of a Lie algebra. This dataset will be made publicly available and contributes a novel contribution to the empirical evaluation of quantum supremacy. We further compared the performance of VQC and QKE on six widely applicable datasets to contextualize our results.\\ Our results demonstrate that the VQC and QKE perform better than basic machine learning algorithms such as advanced linear regression models (Ridge and Lasso). They do not match the accuracy and runtime performance of sophisticated modern boosting classifiers like XGBoost, LightGBM, or CatBoost. Therefore, we conclude that while quantum machine learning algorithms have the potential to surpass classical machine learning methods in the future, especially when physical quantum infrastructure becomes widely available, they currently lag behind classical approaches. Our investigations also show that classical machine learning approaches have superior performance classifying datasets based on group structures, compared to quantum approaches that particularly use unitary processes.\\ Furthermore, our findings highlight the significant impact of different quantum simulators, feature maps, and quantum circuits on the performance of the employed quantum estimators. This observation emphasizes the need for researchers to provide detailed explanations of their hyperparameter choices for quantum machine learning algorithms, as this aspect is currently overlooked in many studies within the field.\\ To facilitate further research in this area and ensure the transparency of our study, we have made the complete code available in a linked GitHub repository.

We developed a temporal population receptive field model to differentiate the functional and hemodynamic responses in the human LGN. The hemodynamic response of the human LGN is dominated by the richly vascularized hilum, a structure that serves as a point of entry for blood vessels entering the LGN and supplying the substrates of central vision. The location of the hilum along the ventral surface of the LGN and the resulting gradient in the amplitude of the hemodynamic response across the extent of the LGN has made it difficult to segment the human LGN into its more interesting magnocellular and parvocellular regions that represent two distinct visual processing streams. Here, we show that an intrinsic clustering of the LGN responses to a variety of visual input reveals the hilum, and further that this clustering is dominated by the amplitude of the hemodynamic response. We introduce a temporal population receptive field model that includes both a sustained and transient temporal impulse response. When we account for the hemodynamic amplitude, we demonstrate that this temporal response model is able to functionally segregate the residual responses according to their temporal properties.

This paper proposes an Integrated Fire Management (IFM) framework that can be used to support communities and resource managers in finding effective and efficient approaches to prevent damaging fires, as well as maintain desirable fire regimes in Kenya. Designing and implementing an IFM approach in Kenya calls for a systematic understanding of the various uses of fire and the underlying perceptions and traditional ecological knowledge of the local people. The here proposed IFM framework allows an evaluation of the risks posed by fires, while balancing them with their beneficial ecological and economic effects, and thus developing effective fire management approaches. A case study of the proposed IFM framework was conducted in Gathiuru Forest that is part of the larger Mt. Kenya Forest Ecosystem. Focus group discussions were held with key resource persons, primary and secondary data on socio-economic activities were studied, fire and weather records were analyzed and the current fire management plans were consulted. Questionnaires were used to assess how the IFM is implemented in the Gathiuru Forest Station. The results show that the proposed IFM framework is scalable and can be applied in places with fire-dependent ecosystems as well as in places with fire-sensitive ecosystems in Kenya. The effectiveness is dependent on the active participation, formulation and implementation of the IFM activities by the main stakeholder groups (Kenya Forest Service (KFS), Kenya Wildlife Service (KWS), and the Community Forest Associations (CFA)). The proposed IFM framework helps in implementing cost-effective approaches to prevent damaging fires and maintain desirable fire regimes in Kenya.

A total of 473 metabolites were identified from 4 sour cherry genotypes using UPLC-TOF-MS. Untargeted metabolomics revealed the dominant chemical groups present in sour cherries. PCA showed that the diversity in sour-cherry metabolites was due to the genotype differences indicating iditol, malic acid, chlorobenzene, 2-mercaptobenzothiazole, and pyroglutamic acid as the predominant contributors. The variable importance in the projection (VIP > 1.0) in partial least-squares–discriminant analysis described 20 biomarker metabolites, representing the cherry metabolome profiles. A heatmap of Pearson’s correlation analysis between the 20 biomarker metabolites and antioxidant activities identified seven antioxidant determinants that displayed the highest correlations with different types of antioxidant activities. This study of correlating metabolomics and antioxidant activities elucidated that the higher nutritional value and biological functions of select sour cherry genotypes can be useful for the development of nutraceutical and functional foods.

This study introduces SkinLiTE, a lightweight supervised contrastive learning model, tailored to enhance the detection and typification of skin lesions in dermoscopic images. The core of SkinLiTE lies in its unique integration of supervised and contrastive learning approaches, which leverages labeled data to learn generalizable representations. This approach is particularly adept at handling the complexities and imbalances inherent in skin lesions datasets. The methodology encompasses a two-phase learning process. In the first phase, SkinLiTE utilizes an encoder network and a projection head to transform and project dermoscopic images into a feature space where contrastive loss is applied, focusing on minimizing intra-class variations while maximizing inter-class differences. The second phase freezes the encoder's weights, leveraging the learned representations for classification through a series of dense and dropout layers. The model was evaluated using three datasets from Skin Cancer ISIC 2019-2020, covering a wide range of skin conditions. SkinLiTE demonstrated superior performance across various metrics—accuracy, AUC , and F1 score—particularly when compared with traditional supervised learning models. Notably, SkinLiTE achieved an accuracy of 0.9087 using AugMix augmentation for binary classification of skin lesions. It also showed comparable results with the state-of-the-art approaches of ISIC challenge without relying on external data, underscoring its efficacy and efficiency. The results highlight the potential of SkinLiTE as a significant step forward in the field of dermatological AI, offering a robust, efficient, and accurate tool for skin lesion detection and classification. Its lightweight architecture and ability to handle imbalanced datasets make it particularly suited for integration into Internet of Medical Things environments, paving the way for enhanced remote patient monitoring and diagnostic capabilities. This research contributes to the evolving landscape of AI in healthcare, demonstrating the impact of innovative learning methodologies in medical image analysis.

Concrete contributes 8% of all global carbon emissions making the need to find substitute critical for environmental sustainability. Research has indicated the potential for recycled plastics to be used as concrete substitutes. This study extends existing research by investigating the use of polycarbonate (PC) in plastic sand bricks as a mechanical equivalent to concrete. PC has high compressive strength, durability, impact strength, thermal resistivity, clarity, fatigue resistance, and UV resistance. This work provides a method and mold to produce a matrix of sand-plastic sample compositions with dimensions adhering to ASTM D695 standard for compressive properties of rigid-plastic. Compositions of 0% (control), 20%, 30%, 40%, and 50% sand by weight were tested. Samples were tested for compressive strength until yield and stress-strain behaviors plotted. The results for 100% PC demonstrated an average and maximum compressive strength of 71 MPa and 72 MPa, respectively. The 50% PC and 50% sand composition yielded an average and maximum compressive strength of 71 MPa and 73 MPa respectively with an increase in compressive stiffness, and transition to shear failure resembling cement. With a composite density of 1.86 g/cm3 against concrete’s average 2.4 g/cm3, and a compressive strength exceeding commercial concrete demands of 23.3 MPa to 30.2 MPa, this lightweight alternative meets the strength demands of concrete, reduces the need for new construction materials, and provides an additional recycling opportunity for nonbiodegradable waste plastic.