The operational measure (OM) of the Second-Generation Intact Stability Criteria (SGISC) is the initial step toward the design of a performance-based dynamic stability assessment of the ship by considering both the vessel’s operation, loading condition and weather parameters. The SGISC recommends the standard wave scatter table (WST) for the environmental data, an indefinite requirement for a simplified assessment pathway, which provides the probability of wave occurrence. The existing standard WST was developed based on the North Atlantic Ocean. This study aims to identify the discrepancy in the probability of wave occurrence in the IMO-recommended WST when compared with developed hindcast WST for smaller regions of the North Atlantic Ocean for the application of SGISC. The significant difference in the existing standard WST is identified when compared with hindcast data, especially across different seasons. A case study of OM on the C11 class post-Panamax container ship for excessive acceleration is provided to better represent the study. The identified limitation limits the use of standard WST in ship stability assessment. The study recommends using hindcast-based WST for SGISC applications that are region and season based. This recommendation is beneficial in improving the safety assessment by OM, given the data is reliable and available for the season and region-specific, and hence the accuracy of the ship stability can be improved while using for the SGISC OM assessment. Further, it makes the WST adhere to the actual framework of the SGISC, i.e., using existing environmental data for design assessment and improving the simplified stability analysis.

Background: Although Tuberculosis (TB) is one of the oldest diseases known to mankind, many practitioners are still unaware of various aspects of management of TB including drug resistant TB. To be able to make an impact on the disease burden we need to understand the knowledge, attitude and practices (KAP) of practitioners, both in government and private sector, towards TB case management. Methodology: A random cross-sectional survey of 99 respondents to assess the KAP towards TB case management using a digital semi-structured questionnaire which was pre-tested and administered to allopathic practitioners from across States in North and Central India. Results: 77% responders were government doctors and 23% were private practitioners. Chest physicians accounted for 61% of the responders. 26% of government and 78% of private doctors relied on sources which are difficult to validate for their knowledge on drug resistant TB management. There were large variations seen in knowledge on modes of transmission, standard precautions, extent of drug resistant TB, diagnostics as well as treatment regimen for drug resistant TB. Conclusion: The knowledge of both sector doctors especially amongst private practitioners with respect to the awareness of extent, diagnosis, and treatment and infection control measures for drug resistant TB is suboptimal which translates to poor diagnostic, therapeutic and infection control choices amongst private practitioners. If India has to achieve the targets for TB Elimination by 2025, serious work needs to be done to upgrade the knowledge of the private sector doctors on drug resistant tuberculosis. The Ministry of Health and Family Welfare, GoI needs to have regular educational programs for the private practitioners coupled with awareness campaigns and frequent surveys to assess the knowledge, attitude and practices being followed in the private sector for TB management including drug resistant TB.

Leishmaniasis is considered one of the different neglected tropical diseases by the World Health Organization. Over the past few decades to tackle leishmaniasis, effective and novel drugs have progressed. But few are expensive some other medication shows poor effects and few drugs with long treatment lead to cause resistance. But it is very important to start a better medication against leishmania so researchers came to the front of the utilization of natural products which are considered a better option. Finding active compounds in medicinal plants is another alternative to currently accessible medications. Materials and methods: This study examined and reported the far more potential natural products used to treat disease caused by Leishmania spp. Leishmaniasis, plant metabolites, in vivo, in vitro, and treatment against leishmaniasis have been used as search terms in the Google Scholar, PubMed, and Science Direct databases, and only papers published between 2015 and 2021 have been chosen for further analysis. Results: The use of novel natural compounds with leishmanicidal action as well as the leishmanicidal activity of natural compounds against promastigote, axenic, and intracellular amastigote forms were included in roughly 20 research papers that were reviewed.Conclusion: Due to their capacity to selectively target parasites without harming host cell viability, herbal plants are a possible source of new anti-leishmanial medication. Future leishmaniasis treatments will draw on the isolated compounds as a source, completing those already offered in clinics.

Integrating advanced air mobility (AAM) into the logistics of high-value electronic commodities can enhance efficiency and promote sustainability. The objective of this study is to optimize the logistics network for high-value electronics by integrating AAM solutions, specifically using heavy-lift cargo drones for middle-mile transport and using the mostly rural and small urban U.S. state of North Dakota as a case study. The analysis utilized geographic information system (GIS) and spatial optimization models to strategically assign underutilized airports as multimodal freight hubs to facilitate the shift from long-haul trucks to middle-mile air transport. Key findings demonstrate that electronics, because of their high value-to-weight ratio, are ideally suited for air transport. Comparative analysis shows that transport by drones can reduce the average cost per ton by up to 60% compared to traditional trucking. Optimization results indicate that a small number of strategically placed logistical hubs can reduce average travel distances by more than 13% for last-mile deliveries. Cost analyses demonstrate the viability of drones for middle-mile transport, especially on lower-volume rural routes, highlighting their efficiency and flexibility. The study emphasizes the importance of utilizing existing infrastructure to optimize the logistics network. By replacing truck traffic with drones, AAM can mitigate road congestion, reduce emissions, and extend infrastructure lifespan. These insights have critical implications for supply chain managers, shippers, urban planners, and policymakers, providing a decision support system and a roadmap for integrating AAM into logistics strategies.

This primer provides an overview of the rapidly evolving field of generative artificial intelligence, specifically focusing on large language models like ChatGPT (OpenAI) and Bard (Google). Large language models have demonstrated unprecedented capabilities in responding to natural language prompts. The aim of this primer is to demystify the underlying theory and architecture of large language models, providing intuitive explanations for a broader audience. Learners seeking to gain insight into the technical underpinnings of large language models must sift through rapidly growing and fragmented literature on the topic. This primer brings all the main concepts into a single digestible document. Topics covered include text tokenization, vocabulary construction, token embedding, context embedding with attention mechanisms, artificial neural networks, and objective functions in model training. The primer also explores state-of-the-art methods in training large language models to generalize on specific applications and to align with human intentions. Finally, an introduction to the concept of prompt engineering highlights the importance of effective human-machine interaction through natural language in harnessing the full potential of artificial intelligence chatbots. This comprehensive yet accessible primer will benefit students and researchers seeking foundational knowledge and a deeper understanding of the inner workings of existing and emerging artificial intelligence models. The author hopes that the primer will encourage further responsible innovation and informed discussions about these increasingly powerful tools.

The condition of surface transportation infrastructure directly affects the economic health of a nation. However, it is difficult to justify the large sums of money needed to extend current methods to monitor all the multimodal infrastructure. The convergence of connected vehicle and cloud computing technologies presents an opportunity to automate the collection of ride quality and imagery data to continuously assess the condition of all roadways and railways. This paper presents several perspectives to help policy and standardization initiatives promote adoption.

Human exposure to antimicrobial resistance (AMR) through food is now very imperfectly understood, creating a significant gap in the design of interventions. The interchange of AMR genes and the transfer of AMR bacteria from animals to humans through the food chain necessitate comprehensive methods to risk reduction. With a focus on AMR in bacterial species isolated from food products, foods (of both animal and non-animal origin), and ambient samples, the current meta-analysis gathered up-to-date information on the epidemiology of AMR in animal-source food chain. As a result, the combined prevalence of AMR across the various food sources was calculated. From the 18,784 food samples obtained as a result of selected publications, 7,676 (40.9%) samples were contaminated, including 4343 (56.6%) and 3363 (43.4%) samples from Taiwan and India, respectively. Meat (chicken, pork, and beef), fish and milk all have moderate to medium potential for AMR exposure to both Gram-positive and Gram-negative foodborne pathogens such S. aureus, Clostridium, E. coli, Salmonella, etc. Antibiotic resistance to β-lactam, fluoroquinolone, carbapenem etc, is present in the majority of food samples. The results of this study emphasize the persistent danger of antimicrobial residue in animal-derived foods in Taiwan, India, and other nations with comparable customs.

Measuring the impact of land use regulation on the land market involves identifying and classifying relevant impact factors related to the land market. The objective of this study was to identify land market impact factors in the context of the introduction of land use regulation in Nepal. A desktop review was carried out to identify preliminary set of impact factors, which were reclassified through intuitive analysis based on the degree of thematic closeness. Perspective-based impact factors were identified through the qualitative analysis of primary data collected through semi-structured interviews with the Nepalese land market stakeholders. These independently derived impact factors were compared with the desktop literature review impact factors resulting in fourteen land market impact factors across four dimensions, including transaction cost, valuation, mortgage availability, taxation, and compensation across the economic dimension; lot size, subdivision restrictions, and coordination across the institutional dimension; awareness, expectation and proximity across the social dimension; and risk reduction, quality of residential land, and suitability of zoning classification across the environmental dimension. There was significant overlap and commonality across factors identified from both the literature review and semi-structured interviews. The land market impact factors determined in the study may be adapted and generalized across other countries and could be utilized to better understand the impacts of land policy decisions on urban planning and development. Further research is recommended on the process to operationalize the use of these factors to quantify the impact of land use regulation on different land markets.

Antimicrobial resistance (AMR) is a growing public health concern worldwide, and it poses a significant threat to human, animal, and environmental health. The overuse and misuse of antibiotics have contributed significantly to the emergence and spread of antimicrobial resistance, which may lead to significant economic consequences like reduced productivity and increased healthcare costs. Nanotechnology offers a promising platform for addressing this challenge. Nanoparticles have unique properties that make them highly effective in combating bacterial infections by inhibiting the growth and survival of multidrug-resistant bacteria in three areas of health: human, animal, and environmental. To conduct an economic evaluation of surveillance in this context, it is crucial to have a comprehension of the connections to be addressed by several nations by implementing national action policies based on the One Health strategy. This review provides an overview of the progress made thus far and presents potential future directions to optimize the impact of nanobiotics on AMR.

Breast cancer (BC) is one of the most common types of cancer in women. Triple-negative breast cancer (TNBC), characterized by the absence of estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2), exhibits a highly aggressive phenotype with increased metastasis and resistance to conventional treatments. Nanocarrier technology is consistently employed to overcome limitations associated with traditional breast cancer therapy. The targeted drug delivery approach using nanocarriers enhances bioavailability, prolongs circulation, and facilitates effective drug accumulation at the tumor site through active or passive targeting. Currently, the FDA has approved a few nanocarrier systems, and numerous nano formulations are undergoing preclinical and clinical development for breast cancer targeting. Common nanocarrier types include polymeric micelles, microemulsions, magnetic microemulsions, liposomes, dendrimers, carbon nanotubes, and magnetic nanoparticles (NPs). This review extensively explores the targeting potential of nanocarriers in breast cancer. This study will provide a concise summary of current advances in treatment of breast cancer and diagnostics.

Poultry eggs are a critical source of protein, vitamins, and minerals for people worldwide; facing the current global egg shortage is a significant concern. The shortage results from various factors, including avian flu outbreaks, changes in consumer demand, and supply chain disruptions caused by the COVID-19 pandemic. The economic crisis caused by the pandemic has also impacted the availability and affordability of eggs, particularly in low-income countries. The global egg shortage has implications for public health, particularly for vulnerable populations who rely on eggs for essential nutrients. One Health, an approach that recognizes the interconnectedness of human, animal, and environmental health, provides a useful framework for understanding and addressing the egg shortage. One Health approaches to the egg shortage involve collaboration between agriculture and environmental sectors to address the root causes of the lack and ensure the sustainable production and distribution of eggs. Addressing the global egg shortage requires a multifaceted approach considering the complex social, economic, and environmental factors. One Health perspectives offer a way to understand and address the interconnected factors contributing to the shortage to ensure access to affordable, nutritious eggs for all in a healthy way

Ethiopian Airlines is a leading airline in the world. Its supply chain management is one of the most critical aspects in achieving its sustainability objectives. The present study aims to assess the sustainability practices and strategies of Ethiopian Airways in its supply chain, identifying areas for improvement and recommending strategies for enhancing sustainability. The study concentrates on pertinent sustainability concerns within the aviation sector while examining antecedent research on the sustainability of Ethiopian Airlines’ supply chain management strategies. The findings of the study reveal that there are several areas in need of improvement, including the implementation of waste reduction measures, the establishment of a recycling program, and the reduction of single-use plastic usage. It is suggested that promoting responsible tourism embodying sustainable practices is imperative, particularly within the airline context.

Electrifying aircraft, a crucial advancement in the aviation industry, aims to cut pollutive emissions and boost energy efficiency. Traditional aircraft depend on fossil fuels, which contribute significantly to greenhouse gas emissions and environmental pollution. Despite progress in electric propulsion and energy storage technologies, challenges such as low energy density and integration issues persist. This paper provides a comprehensive thematic and bibliometric analysis to map the research landscape in aircraft electrification, identifying key research themes, influential contributors, and emerging trends. The study applies natural language processing to unstructured bibliographic data and cross-sectional statistical methods to analyze publications, citations, and keyword distributions across various categories related to aircraft electrification. The findings reveal significant growth in research output, particularly in energy management and multidisciplinary design analysis. Collaborative networks highlight key international partnerships, with the United States and China being key research hubs, while citation metrics highlight the impact of leading researchers and institutions in these countries. This study provides valuable insights for researchers, policymakers, and industry stakeholders, guiding future research directions and collaborations.

The immune system is a dynamic network of cells and cytokines are the major mediators of immune responses which combat pathogens. Based on the cytokine production, effector T cells differentiate into subsets known as Th1, Th2, Th17 or Treg (T regulatory). This system serves as a barrier to intracellular pathogens, bacterial infections and stimulates the production of reactive oxygen species (ROS), reactive nitrogen intermediates (RNI) and nitric oxide (NO), which diffuses across membranes and engulfs intracellular pathogens. Oxidative stress occurs when ROS, reactive nitrogen species (RNS) production and antioxidant defences become imbalanced. Oxidative stress generated by infected cells produces a substantial amount of free radicals which enables killing of intracellular pathogens. Intracellular pathogens are exposed to endogenous ROS as part of normal aerobic respiration, also aexogenous ROS and RNS are generated by the host immune system in response to infection. Nanoparticles which are designed for drug delivery are capable of trapping the desired drug in the particles which protects the drug from enzymatic degradation in a biological system. The small (subcellular) size of nanoparticles enables higher intracellular uptake of the drug which results in the reduction of the concentration of free drugs reducing their toxic effect. Research on the modulation of immune response and oxidative stress using nanoparticles used to encapsulate drugs has yet to be explored fully. In this review we illustrate the immune activation and generation of oxidative stress properties which are mediated by nanoparticle encapsulated drug delivery systems which can make the therapy more effective in case of diseases caused by intracellular pathogens.

Agriculture is the largest sector of Nepalese economy among the south-Asian developing countries that contributed 26.98 % share of Gross Domestic Product (GDP) in the year 2018/19. The capacity to derive maximum output by per unit of resource is resource use efficiency. Resource use efficiency of a producer explains the comparison between inputs and output value. Potato is staple vegetable in every parts of Nepal. Cobb-Douglas production function is used to predict the significance of inputs in income from cash crops. Due to lack of optimum utilization of available resources in cultivation of vegetable like lack of technical knowledge, low education level, and extensive service the productivity and production is low in Nepalese economy. It ensures vegetable security in Nepal. Though, there are extensive researches on the resource use efficiency and productivity issues on agriculture, very few papers explored in the case of Sudurpaschim province of Nepal OBJECTIVE: This study had the specific purposes: (1) To identify the factors affecting in resource use efficiency and productivity of potato production (2) to utilize the resource use efficiency and productivity in potato production and (3) to show the type of returns to scale in potato production. METHODS: Applying post-positivist paradigm and quantitative causal survey research design, it explored the resource use efficiency and productivity through the semi-structured questionnaire from 140 households by random sampling. Data analysis was carried out by multiple regression model using Cobb-Douglas production function. SPSS software was used to find quantitative results. From the analysis of data using mean, and SD, t-test, analysis of variance, Durbin-Waston test, Marginal Value Product and marginal Factor cost, findings of this research was emerged. RESULTS AND DISCUSSION: The major findings: education level, extension service, farm size and pesticide cost were significant variables in potato production; seed, hired labor, Family Yard Manure and pesticide cost were overused and needed to decrease their cost for optimum allocation and there was decreasing returns to scale in production. This study emphasized on increasing education level, extensive service and farm size for optimum utilization of resources and increasing returns to scale. SIGNIFICANCE: Barriers to Indian potatoes and increasing returns to scale are only possible through protection policy of government. For optimum use of resources and increasing returns to scale, government can introduce capital intensive technique. This study can be implied in policy making and improving existing situation of agriculture, and allocating budget.

The aim of this tutorial is to help students grasp the theory and applicability of support vector machines (SVMs). The contribution is an intuitive style tutorial that helped students gain insights into SVM from a unique perspective. An internet search will reveal many videos and articles on SVM, but many of them give simplified explanations that leave gaps in the derivations that beginning students cannot fill. Most free tutorials lack guidance on practical applications and considerations. The software wrappers in popular programming libraries such as Python and R hide many of the operational complexities. Free software tools often use default parameters that ignore domain knowledge or leave knowledge gaps about the important effects of SVM hyperparameters, resulting in misuse and subpar outcomes. The author uses this tutorial as a course reference for students studying artificial intelligence and machine learning. The tutorial derives the classic SVM classifier from first principles and then derives the practical form that a computer uses to train a classification model. An intuitive explanation about confusion matrices, F1 score, and the AUC metric extend insights into the inherent tradeoff between sensitivity and specificity. A discussion about cross-validation provides a basic understanding of hyperparameter tuning to maximize generalization by balancing underfitting and overfitting. Even seasoned self-learners with advanced statistical backgrounds have gained insights from this tutorial style of intuitive explanations, with all related considerations for tuning and performance evaluations in one place.

Analytical solutions for radiation dominated phase of Quasi Steady State Cosmology in Friedmann-Robertson-Walkar models are obtained. We find that matter density is positive in all the cases (k = 0,-1,1). The nature of Hubble parameter (H) in [0,2] is discussed. The deceleration parameter (q) is marginally less than zero indicating accelerating universe. The scale factor (S) is graphically shown with time. The model represents oscillating universe between the above mentioned limits. Because of bounce in QSSC, the maximum density phase is still matter dominated. The models represent singularity free model. We also find that the models have event horizon i.e. no observer beyond the proper distance rH can communicate each other in FRW mdels for radiation dominated phase in the frame work of QSSC. The FRW models are special classes of Bianchi type I, V, IX space-times with zero, negative and positive curvatures respectively. Initially i.e. at  = 0, the model represents steady model. We have tried to show how a good fit can be obtained to the observations in the framework of QSSC during radiation dominated phase.

Bianchi type III string cosmological models (massive and geometric) in presence of magnetic field with vacuum energy density following the techniques used by Letelier (1979) and Stachel (1980) are obtained. We find that the energy conditions (dominant as well as weak) given by Hawking and Ellis (1974) are satisfied for the models. Also the solutions obtained satisfy conservation equation for massive string with magnetic field and vacuum energy density. The models in general, represent anisotropic phase of space-time due to the presence of string. However, the models isotropize at late time and in special case. It has also been shown that the magnetic field is directly linked with the matter. For string dust model, the state finder parameters {r,s} are in excellent agreement with Planck results (Sahni et al. (2003)). The physical and geometrical aspects of the models with special cases are also discussed.

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.

Background: The COVID-19 among humans is spreading heavily and is largely impacting the mental health of the general population, students, and health care workers worldwide. Hence, this review aims to summarize the literatures addressing the impact of the COVID-19 pandemic on the mental health of the general population, students, and health care workers. Methods: Published articles concerning mental health of the general population, students, and health care workers related to the COVID-19 outbreak have been considered and reviewed. Results and Discussion: Mental health symptoms of stress, anxiety, and depression are common psychological reactions to the COVID-19 pandemic in the general population, students, and health care workers. This collectively influences daily behavior, economy, prevention strategies and decision making from policy makers and health organizations, weakening the strategies of COVID-19 control leading to more morbidity and mental health needs at the global level. Conclusion: There is a need for more evidence-based research from other affected countries, particularly in vulnerable populations such as children and adolescents, people of lower socioeconomic status, and those residing in rural areas, so that valid strategies can be developed and COVID-19 and outbreaks of similar types in the near future can be prevented.

This study examines the balancing between urban transportation security and supply chain efficiency amid global disruptions like the COVID-19 pandemic, attacks on maritime lanes, and geopolitical conflicts. The authors combine bibliometric network analysis and natural language processing (NLP) to review scholarly literature from 2017 to 2023. This approach identifies and visualizes evolving thematic trends. Findings reveal a shift towards integrating advanced technologies such as blockchain, AI, and IoT to enhance security without compromising efficiency. This study highlights the significance of integrating urban planning principles and sustainable practices to enhance transportation security and supply chain efficiency within urban environments. Actionable insights for policymakers and supply chain managers emphasize the adoption of integrated, technology-driven security solutions to foster resilient and sustainable supply chains. This research contributes to academic discourse by refining the understanding of evolving priorities in transportation security and supply chain management, offering both theoretical and practical implications for secure and efficient global supply chains.

This paper explores factors affecting Out-of-Pocket payments for healthcare expenditures in SAARC countries. The specific objectives of the paper were to compare healthcare expenditure patterns amongst the SAARC countries and explore the macroeconomic, demographic and social factors influencing OOP payments for healthcare these countries. The model selection tests suggest that the fixed effect model is the most appropriate for the data, though the random effect model also provides valuable insights. Fixed effect model result showed that a 1 per cent change in GDP per capita, consumer price index, population aged 65 years and above causes change in out-of-pocket payments for healthcare by 1.08 per cent (p< 0.01), 0.09 per cent (p< 0.05), 1.20 per cent (p

(1) Background: Artificial intelligence (AI) has existed in some form for decades, but recent rapid advances in a subset called machine learning (ML) — and more specifically deep learning (DL), a neural network-based approach — have made headlines for the potential to revolutionize and automate multiple large sectors of society, including scientific research and the healthcare field. Furthermore, large language models (LLMs) — which are built on DL — could lead to a more seamless, natural interaction between humans and computers. (2) Methods: We reviewed numerous publications on this subject from recent years. (3) Results: We found these studies collectively show that AI is positively disrupting both biomedical research and medical practice, such as optical imaging in surgery guidance. (4) Conclusions: However, we recommend caution in over-reliance on AI in the laboratory or the clinic due to anticipated risks and current limitations.

The concept of public financial accountability, often associated with account-rendering, lacks a clear and comprehensive definition in the realm of accounting literature. Disentanglement the true essence of a phenomenon is essential, as formal definitions can only provide a superficial understanding. This study seeks to delve into the core principles of public financial accountability and their implications for financial reporting in the public sector. Applying a qualitative approach, data was gathered through in-depth interviews with 25 Nigerian scholars, professionals, and public affairs experts. The analysis reveals that the essence of public financial accountability lies in upholding citisens' trust in public officials, ensuring the responsible management of public financial resources for the greater public good, and effectively communicating financial decisions, actions, and outcomes to the public through a transparent reporting mechanism. This study sheds light on the fundamental nature of financial accountability in the public sector, enhancing our understanding of its significance in governance and financial reporting.

Rapid draw-down in an earthfill dam has serious implications for dam safety regarding slope stability. The evaluation of reservoir draw-down impact on slope stability was carried out considering the case study of 8 hours of rapid draw-down of the Middle Marsyangdi Hydroelectric Power Project (MMHPP) rock-fill dam using the Limit Equilibrium Method (LEM) and stress-based Finite Element Method (FEM). The time-dependent factor of safety (FOS) was evaluated and found that the 8 hours of rapid draw-down undertaken in October 2012 for reservoir flushing was unsafe with a draw-down rate of 1.91m/h. The resulting FOS of 1.28 and 1.27 using LEM and FEM was classified as unsafe as per the US Army Corps of Engineers’ guideline, the minimum required factors of safety should be greater than 1.3. The minimum safe allowable draw-down rate of 0.76m/h for 20 hours was identified. Applying three layers of horizontal filter materials and increasing the upstream dam’s permeability provided adequate FOS results for all cases by increasing seepage discharge to reduce the destabilizing excess pore water pressure. Several gradual draw-down rates were also tested and found that FOS increases with decreased draw-down rates, as it reduces the excess pore water pressure controlled with stabilizing existing water load.

The concept of "Eco-authoritarianism", although appeared in the 1970s, through the writings of Robert Heilbroner, William Ophuls etc., but Eco-authoritarianism as a theory has emerged very recently [1]. In this era of global environmental degradation and rampant defacement of green space in the rapidly expanding cities of developing countries especially in India, historical sites of green belts, or eco-space developed by royal dynasties or colonial rulers are still preserved by eco-authoritarianism and cultural praxis. A lot of such heritage sites and built-up eco-spaces have faded out over time but at the same time, huge numbers are still present due to the imposition of restrictions by the state or national government or statutory organizations. Built up eco-space under Burdwan Raj Dynasty during the 18th and 19th centuries is still preserved almost in its original form due to the eco-authoritarianism outlook of the present stakeholder (The University authority mainly and the Forest Department). People of this urban unit not only feel proud of such built up eco-space; they also give credit to the university authority for maintaining the legacy of the Raj Dynasty. This investigation attempts to capture not only the role of authoritarian legacy for the preservation and conservation of eco-space in the urban context but also clarify the benefits of this eco-space regarding the cultural ecosystem services and outlook of urbanites towards nature. To portray this, both the qualitative and quantitative methods have been applied to glean the whole perspective.

Dam breaches have catastrophic consequences, causing severe property damage, life loss, and environmental impact. The Kulekhani reservoir rockfill dam break was studied to evaluate the downstream impact. The appropriate breaching parameter of MacDonald and Langridge (1984) regression equations was selected based on the sixteen observed dam failure cases and cross-sectional geometry of the existing dam of Kulekhani. The 2D Diffusion Wave and Full Dynamic Wave Equation were applied for downstream flood assessment, Full Dynamic Wave was able to capture the physical flow phenomena like river bend effects resulting in higher flow velocity at the outer bend, and formation of eddies considering losses. The application of a Full Dynamic Equation was found to be appropriate for rapidly varying unsteady flow considering steep slopes, and sudden changes in channel geometry. Flood mapping of water depth, flow velocity, flood intensity, and arrival time were carried out for flood hazard assessment classified by the American Society of Civil Engineers (ASCE). Flow depth and extension of the flow area were compared to identify the affected area, higher flow depth and larger extension were observed using a Full Dynamic Wave Equation as a result of less flow velocity considering the losses. Almost 17 minutes of the arrival time of peak difference at the Bagmati River confluence was evaluated between the models which plays an important role in decision-making for selection of the flood model. Flood mitigation with river diversion works through a hydraulic measure of Levee was suggested to protect the highly affected households of Ranche, Nagmar, Khanikhet, and Debaltar towns. Most of the household was found to be safe after the construction of the Levee except for eleven houses that lie along the river below flood elevation of 1269.6 m.a.s.l. This signifies the importance of room for the rivers and the human settlement near the river might be life-threatening.

Probiotics are becoming more and more popular in the growing of fin and shellfish because these species are consumed worldwide and because different techniques are employed to maximize the productivity and efficiency of fin and shellfish. Probiotic Bacillus is one of the many types of probiotics that are used, but it stands out due to its superior qualities. For instance, because of its ability to sporulate, it can survive in harsh environments, produce antimicrobial substances, and is safe to feed to fish. The different species of Bacillus used in the farming of fin and shell fish were discussed in this review, along with the benefits of using Bacillus spp. as a good substitute in sustainable aquaculture to improve feed utilization, immune system response, stress adaptation, resistance to infectious diseases, tissue preservation integrity, and water quality. Additionally, we discussed the possible risks to safety that Bacillus poses when raising these significant species. For the purpose of future research and development regarding Bacillus application in aquaculture, a summary of the findings of recent studies about the advantages of applying Bacillus to enhance fin and shellfish aquatic animal culture has been provided.

In the context of developing machine learning models, until and unless we have the required data engineering and machine learning development competencies as well as the time to train and test different machine learning models and tune their hyperparameters, it is worth trying out the automatic machine learning features provided by several cloud-based and cloud-agnostic platforms. This paper explores the possibility of generating automatic machine learning models with low-code experience. We have developed criteria to compare different machine learning platforms for generating automatic machine learning models and presenting their results. Thereafter, lessons learned by developing automatic machine learning models from a sample dataset across four different machine learning platforms were elucidated. We have also interviewed machine learning experts to conceptualize their domain-specific problems that automatic machine learning platforms could address. Results showed that automatic machine learning platforms could provide a fast track for organizations seeking digitalization of their businesses. Automatic machine learning platforms help produce results, especially for time-constrained projects where resources are lacking. The contribution of this paper is in the form of a lab experiment in which we demonstrate how low-code platforms could provide a viable option to many business cases and henceforth provide a lane that is faster than the usual hiring and training of already scarce data scientists and to analytics projects that suffer from overruns.

Based on the insight gained from single jet analysis performed earlier [1], CFD analysis on turbulent jets impinging on one another at an angle was performed. Multiple impingement angles were considered for this study to gain better understanding of the parameters affecting resultant jet growth and velocity distribution. From the study of single jet, it was concluded that the SST k-ω turbulence model was the ideal turbulence model capable of accurately predicting the flow physics of the jets exiting a fully developed pipe at low Reynolds number. Hence, for the study of impinging jets, SST k-ω turbulence model was used to study the velocity and jet growth characteristics. It became evident that the mesh alignment with the velocity vector at exit of the pipe domain plays a crucial role in the accuracy of the results. The parameter used to evaluate this condition was identified as False Diffusion and was observed to affect the TKE parameter significantly. Methods to reduce false diffusion are also discussed in this article. Based on the mesh obtained from the grid sensitivity study, jets impinging at 30, 45 and 60 degrees at Reynolds number of 7500 were numerically analyzed. It was observed that the profile of the resultant jet closely matched with the prediction of elliptical profile predicted by past researchers, [2] and [3]. Also, it was seen that higher jet growth was predicted in case of jets impinging at a higher impingement angle.

Polymer nanocomposites are composed of polymer materials reinforced with nano fillers. In the present study the effective thermal conductivity of the composites filled with nanofillers has been investigated using commercially available finite element software ABAQUS 6.11. The nanofillers used were alumina particles and multi-walled carbon nanotubes (MWNTs) and the matrix was considered to be made of epoxy. For the analysis 2D and 3D Representative Volume Elements (RVEs) were generated using Random Sequential Adsorption (RSA) algorithm using MATLAB and Python scripts. Thermal conductivity was found out for 2D and 3D RVEs for different area and weight fractions respectively. Two different shapes of the alumina nanoparticles were considered: spherical (circular) and ellipsoidal (elliptical) for 3D (2D) analysis. It was found that the thermal conductivity was increased with the addition of nanofillers. The increase in thermal conductivity was approximately same for both types of inclusions at corresponding area or weight fractions in 2D or 3D analysis. The results showed that addition of MWNTs to the composites lead to a significant increase in thermal conductivity than spherical or ellipsoidal inclusions.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is pandemic. Prevention and control strategies require an improved understanding of SARS-CoV-2 dynamics. We did a rapid review of the literature on SARS-CoV-2 viral dynamics with a focus on infective dose. We sought comparisons of SARS-CoV-2 with other respiratory viruses including SARS-CoV-1 and MERS-CoV. We examined laboratory animal, and human studies. The literature on infective dose, transmission, and routes of exposure was limited specially in humans, and varying endpoints were used for measurement of infection. We propose the minimum infective dose of COVID-19 in humans, is higher than 100 particles, possibly slightly lower than the 700 particles estimated for H1N1 influenza. Despite variability in animal studies, there was some evidence that increased dose at exposure correlated with higher viral load clinically, and severer symptoms. Higher viral load measures did not reflect COVID-19 severity. Aerosol transmission seemed to raise the risk of more severe respiratory complications in animals. An accurate quantitative estimate of the infective dose of SARS-CoV-2 in humans is not currently feasible and needs further research. Further work is also required on the relationship between routes of transmission, infective dose, co-infection, and outcomes.

60\% of the global population is expected to be in cities by 2050. At the same time the climate is changing at an accelerated rate. In this short paper we discuss the conflation of these two phenomena and how it may change the cities of the future. We formulate this as an optimization problem that could help answer important questions such as where are they likely to be located? How are they to be powered? What would be their demand for mobility and how might this be met? How over or under ground might these cities be? This paper first looks at a historical paradigm of cities in the absence of the climate crisis and then proposes the new paradigm to look at cities of the future faced by the challenge of the climate change crisis.

Motivated by Autonomous vehicle idea and driving safety issues, driver assistance system such as Active braking, Cruise Control, Lane departure warning lane keeping and etc. has become a very active research area. However, this paper presents the performance and robustness analysis of a model predictive control and proportional integral derivative control for lane keeping maneuvers of an autonomous vehicle using computer vision simulation studies. A simulation study was carried out where a vehicle model based on single tracked bicycle model was developed in MATLAB/SIMULINK environment together with a vision dynamic system. Both PID controller and MPC were simulated to maintain the desired reference trajectory of the vehicle by controlling steering angle. Further performance and robustness analysis were carried out and the simulation results show that the proposed control system for the PID control achieved its objective even though it was less robust in maintaining its performance under various conditions like vehicle load change, different longitudinal speed and different cornering stiffness. While in the case of MPC the optimizer made sure that the predicted future trajectory of the vehicle output tracks the desired reference trajectory and was more robust in maintaining its performance under same conditions as in PID.

Clothing consumers mostly purchase, use, and dispose of clothing products in a linear business model. This approach pollutes the environment and causes economic and social crises in the ecosystems. This study evaluates the amount of generated postconsumer clothing waste (PCCW) and proposes recycling as a sustainable waste management approach. Data were collected to understand disposal behavior of consumers with 474 respondents selected from households in Bahir Dar city. The findings show that all the determinant factors on the PCCW generation level except religion were significant. The most frequently disposed type of clothing waste is jeans-trouser (51%). The CEBM was used to develop alternative products from a jeans-based clothing waste. The jean's fiber and fabric-reinforced composite materials were developed using unsaturated polyester resin as a sustainable way of PCCW management strategy. The shredded form fiber-reinforced composite was found to have a smoother surface than that of the chopped or cut fabric-reinforced composite. The product was characterized by physical and mechanical properties. The study can be further extended to the scope of the entire consumers in Ethiopia and alternative recyclable products can be studied.

In December 2019, outbreak of novel coronavirus (COVID-19) occurred in Wuhan, Hubei Province, China and exported across the world leading to thousands of deaths and millions of suspected cases. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV2) infection into the host undergoes a huge number of complex replicative machineries which still remains unclear. Understanding the mechanism (s) of replication and mode of infection of SARS-CoV2 to human cells will help us in the development of novel vaccines or drugs for the eradication and prevention of the disease. This review compiles the knowledge of SARS-CoV2 replicative machinery, mode of infection to the human cells and the development of drugs and vaccines which are currently under clinical trials.

As sustainability gains significance within Higher Education Institutions (HEIs) worldwide, the University of British Columbia (UBC) stands as one of the global champions of sustainability. In 2019, Times Higher Education ranked UBC as number one in the world for taking urgent action to combat climate change and its impacts and ranked one in Canada for making cities inclusive, safe, resilient, and sustainable. Over the years, UBC students have been instrumental to sustainability on the UBC campus by advocating for divestment, climate justice, and other sustainability commitments and projects in the university. Hence, this qualitative study examines students’ engagement with or their perception of the university’s sustainability programs and image. The study found that students acknowledged and commended the university’s sustainability efforts in teaching, research, providing sustainability-related opportunities for students, and in sustainability operations. However, students also addressed hesitation on the part of university administration in championing climate justice and bolder climate action. The conclusion is that continued support and engagement with students are critical for UBC to achieve its climate action plans and sustainability goals in general. The study contributes to the ongoing discourse on the influential role of young people and the youth climate movement in catalyzing ambitious global climate action at all levels.

Biochemical compositions of black carpenter ants (Camponotus pennsylvanicus) were analyzed using standard methods. The proximate composition (%) were as follows: crude protein (22.50), crude fibre (1.46), carbohydrate by difference (30.86) and energy (35.4Kcal). The predominant mineral was potassium and nickel was the least. The antinutritional properties (mgkg^-1) ranged as follows: Oxalate (1.35), phytate (62.79), and tannins (0.72). The results suggested that the ant may be a good source of nutrition.

In the year in which the world "stopped" due to the pandemic, many people didn't have that option and had to keep moving as the only alternative to survive. One of the main destinations in South America, during the quarantine measures established around the world, was Brazil, especially because of the crisis Venezuela went through in the second half of the 2010s. Throughout the research, we observed measures that were applied by the Brazilian government on the grounds of public health issues or cases of health risks related to COVID-19. An analysis of the first measures published by the Brazilian government reveals an effort to securitize borders, which at the same time restricted the government's responsibility to fulfil its role of protecting migrants in need.

Understanding of the molecular mechanisms of prostate cancer has led to development of therapeutic strategies targeting androgen receptor (AR). These androgen-receptor signaling inhibitors (ARSI) include androgen synthesis inhibitor- abiraterone and androgen receptor antagonists- enzalutamide, apalutamide, and darolutamide. Although these medications provide significant improvement in survival among men with prostate cancer, drug resistance develops in nearly all patients with time. This could be through androgen-dependent or androgen-independent mechanisms. Even weaker signals and non-canonical steroid ligands can activate AR in the presence of truncated AR-splice variants, AR overexpression, or activating mutations in AR. AR splice variant, AR-V7 is the most studied among these and is not targeted by available ARSIs. Non-androgen receptor dependent resistance mechanisms are mediated by activation of an alternative signaling pathway when AR is inhibited. DNA repair pathway, PI3K/AKT/mTOR pathway, BRAF-MAPK and Wnt signaling pathway and activation by glucocorticoid receptors can restore downstream signaling in prostate cancer by alternative proteins. Multiple clinical trials are underway exploring therapeutic strategies to overcome these resistance mechanisms.

For the past few decades, researchers have been intrigued with glassy polymers, which have applications ranging from gas separations to corrosion protection to drug delivery systems. The techniques employed to examine the sorption and diffusion of small molecules in glassy polymers are the subject of this review. Diffusion models in glassy polymers are regulated by Fickian and non-Fickian diffusion, with non-Fickian diffusion being more prevalent. The characteristics of glassy polymers are determined by sorption isotherms, and different models have been proposed in the literature to explain sorption in glassy polymers during the last few years. This review also includes the applications of glassy polymer. Despite having so many applications, current researchers still have difficulty in implementing coating challenges due to issues like as physical ageing, which is briefly discussed in the review.

In the quest to develop a more effective and representative electoral system that offers a higher global satisfaction while also resisting strategic voting, this paper introduces the Bipartisan/Range method. This electoral system operates in two separate rounds: a first round where voters rank candidates, and if no Condorcet winner emerges, a second round where voters score candidates within a small head set known as the bipartisan set. The proposed method takes inspiration from randomized Condorcet voting system, probably the most strategy-resistant Condorcet methods, but eliminates the non-determinism while improving efficiency in the case of paradoxes. By introducing an unpredictable second round spaced in time and prohibiting predictive surveys, voters face difficulties in anticipating paradoxes, and insincere votes carry inherent risks. Furthermore, the Bipartisan set's limited size mitigates the range voting problem of exaggerated votes. Thus, the method has the potential to be both efficient in reflecting voters' preferences and resistant to strategic voting, exceeding expectations from Arrow's theorem. The method's versatility allows for extensions to multiple candidates, enhancing its applicability across various electoral contexts. Additionally, we have developed BipartiVox, an online platform specifically designed to conduct elections using the Bipartisan/Range method, making it accessible to a wider audience. In conclusion, the Bipartisan/Range method represents a substantial contribution to the field of voting systems, providing a practical, strategy-resistant, and efficient alternative that aligns closely with genuine voter preferences.

The African continent has the highest prevalence of hypertension globally, with South Africa reporting the highest prevalence in Southern Africa. While the influence of genetic variability in the pathogenesis of hypertension is well described internationally, limited reports are available for African populations. This study aimed to assess the association of genetic variants and essential hypertension in a cohort of two ethnic South African population groups. Two hundred and seventy-seven hypertensive and one hundred and seventy-six normotensive individuals were genotyped for 79 variants. Genotyping was performed using the Illumina GoldenGate Assay and allele-specific polymerase chain reaction. The association of variants was assessed using the Fisher Exact test under the additive and allelic genetic models, while multivariate logistic regression was used to predict the development of hypertension. Five variants (CYP11B2 rs179998, AGT rs5051 and rs699, AGTR1 rs5186 and ACE rs4646994) were significantly associated with essential hypertension in the cohort under study. Furthermore, AGTR1 rs5186 and AGT rs699 were identified as risk factors for the development of hypertension in both ethnic groups. In two ethnic South African populations an association was observed between Renin-Angiotensin-Aldosterone System (RAAS) related genes and the development of hypertension.

Residential satisfaction with post-disaster housing is crucial for the success and sustainability of a resettlement project. However, little attention has been given to this aspect in the permanent houses developed after the 2015 Gorkha earthquake. To bridge this gap, the study examined factors affecting residential satisfaction among poor displaced households resettled in the Panipokhari Integrated Settlement of Nepal. Data were collected through a questionnaire survey, interviews, and field observation. Internal consistency and reliability were assessed using Cronbach's Alpha test, while satisfaction was measured by mean satisfaction scores. The relative importance index ranked the factors, and Spearman's rank correlation coefficient analyzed their relationship with overall residential satisfaction. The study identified several crucial fac-tors influencing residential satisfaction, including the design and layout of the house, space for modification, provision of a kitchen garden and cattle shed, thermal comfort, completeness of the house, provision of a hearth, and spaces for rituals and cultural events. These findings shed light on the resettlement decisions of affected populations and provide valuable insights for policymakers, implementers, and researchers aiming for successful and sustainable resettlement outcomes.

The Novel Coronavirus (COVID-19) is a positive-sense single-stranded RNA ((+)ssRNA) virus. The COVID-19 Main Proteases play very important role in the propagation of the Novel Coronavirus (COVID-19). It has already killed more than 8000 people around the world and thousands of people are getting infected every day. Therefore, it is very important to identify a potential inhibitor against COVID-19 Main Proteases to inhibit the propagation of the Novel Coronavirus (COVID-19). We have applied a drug repurposing approach of computational methodology, depending on the synergy of molecular docking and virtual screening techniques, aimed to identify possible potent inhibitors against Novel Coronavirus (COVID-19) from FDA approved antiviral compounds and from the library of active phytochemicals. On the basis of recently resolved COVID-19 Main Protease crystal structure (PDB:6LU7), the library of 100 FDA approved antiviral compounds and 1000 active components of Indian Medicinal Plants extracted for screening against COVID-19 Main Protease. The compounds were further screened using Pyrex virtual screening tool and then best inhibitors, top 19 compounds optimally docked to the COVID-19 Main Protease structure to understand the participation of specific amino acids with inhibitors at active sites. Total 19 best compounds were identified after screening based on their highest binding affinity with respect to the other screened compounds. Out of 19, 6 best compounds were further screened based on their binding affinity and best ADME properties. Nelfinavir exhibited highest binding energy -8.4 kcal/mol and strong stability with the TRP207, ILE281, LEU282, PHE3, PHE291, GLN127, ARG4, GLY283, GLU288, LYS5, LYS137, TYR126, GLY138, TYR126, SER139 and VAL135 amino acid residues of COVID-19 Main Protease participating in the interaction at the binding pocket. In addition to Nelfinavir (-8.4), Rhein (-8.1), Withanolide D (-7.8), Withaferin A (-7.7), Enoxacin (-7.4), and Aloe-emodin (-7.4) also showed good binding affinity and best ADME properties. Our findings suggest that these compounds can be used as potential inhibitors against COVID-19 Main Protease, which could be helpful in inhibiting the propagation of the Novel Coronavirus (COVID-19). Moreover, further in vitro and in vivo validation of these findings would be very helpful to bring these inhibitors to next level study.

This article reports the two-step synthesis of NiFeO_x nanomaterials, their characterisation and bifunctional electrocatalytic activity measurements in alkaline electrolyte for metal-air batteries. The samples were mostly in layered double hydroxide at the initial temperature, but upon heat treatment, they were converted to NiFe₂O₄ phases. The electrochemical behaviour of the different samples was studied by linear sweep voltammetry and cyclic voltammetry on the glassy carbon electrode. The OER catalyst activity was observed for low mass loadings (0.125 mg cm⁻²), whereas high catalyst loading exhibited the best performance on the ORR side. The sample heat treated at 250 °C delivered the highest bi-functional oxygen evolution and reduction reaction activity (OER/ORR) thanks to its thin-holey nanosheet like structure with higher nickel oxidation state at 250 °C. This work further helps to develop low-cost electrocatalyst development for metal-air batteries.

This study explores the intricacies of supplier relationships and inventory optimization within high-technology industries, offering a comprehensive analysis of the strategic imperatives and operational challenges faced by firms in these sectors. By adopting a qualitative research methodology involving semi-structured interviews with supply chain professionals and documentary analysis, the study provides in-depth insights into the evolving dynamics of supply chain management. Findings reveal a marked shift towards collaborative and strategic supplier relationships, characterized by trust, transparency, and joint innovation initiatives. These partnerships are essential for enhancing operational efficiency, driving product development, and navigating market uncertainties. Additionally, the research underscores the critical role of advanced technologies, such as artificial intelligence and the Internet of Things, in optimizing inventory levels and improving supply chain visibility. The integration of these technologies facilitates precise demand forecasting and proactive inventory management, thereby reducing costs and enhancing service levels. However, the study also highlights significant challenges, including geopolitical uncertainties, supply chain disruptions, and cultural barriers, which necessitate robust risk management strategies and adaptive supply chain practices. Strategic implications for organizational leaders and policymakers include the need to invest in supplier development, embrace digital transformation, and enhance risk management frameworks to build resilient and agile supply chains. This study contributes valuable insights into the complex interplay between supplier relationships, inventory optimization, and technological integration in high-technology industries, offering actionable recommendations for practitioners and researchers seeking to drive innovation and maintain competitiveness in a dynamic global marketplace.

This qualitative research explores the intricate relationship between cultural influences on supply chain practices and their implications for marketing strategies. Cultural dimensions such as individualism versus collectivism, uncertainty avoidance, and contextuality significantly shape decision-making processes, risk management strategies, and relationship dynamics within global supply chains. Through semi-structured interviews with supply chain managers, marketing executives, and cultural experts across diverse industries and regions, this study investigates how cultural values impact supply chain operations and consumer engagement strategies. Key findings highlight that collectivist cultures prioritize consensus-building and long-term relationships, fostering trust and collaboration among supply chain partners. In contrast, individualist cultures emphasize efficiency and accountability but may face challenges in relationship building. Risk management practices vary with cultural orientations towards uncertainty, influencing the adoption of structured versus flexible approaches to mitigate disruptions. In terms of marketing implications, the study underscores the importance of cultural sensitivity in crafting effective strategies. High-context cultures require marketing messages that resonate emotionally through implicit communication and cultural symbolism, while low-context cultures prefer clear, direct messaging focusing on product benefits. The study concludes by advocating for cultural competence as a strategic imperative for global businesses, enabling them to leverage cultural diversity for innovation and competitive advantage. It emphasizes the need for continuous adaptation to cultural nuances and market dynamics to foster inclusive collaboration and achieve sustainable growth in a globalized economy.

Plant pathogens utilize effectors to subvert host cell biology for facilitating infection. However certain effectors, called as the avirulence proteins, trigger immune responses in the host. AvrPi54 is an avirulence protein from fungus Magnaporthe oryzae which induces the defense reactions in rice cells that contain Pi54 resistance gene. The characterization of such proteins and elucidation of their function facilitate the understanding of the mechanism of disease establishment. In present study, physiochemical properties of AvrPi54 were analysed using computational methods. We found that mature AvrPi54 is a small, hydrophobic and secretary protein with 134 amino acids. It is rich in small amino acids with no significant homology with other proteins in databases. The gene ORF was cloned in pET28a(+) vector and expressed in E. coli BL21(DE3)pLysS. The protein was purified using affinity chromatography. Transient expression of the gene in epidermal cells of onion bulb is a powerful tool to predict the subcellular localization in plant cells. We fused AvrPi54 to eYFP and transformed epidermal cell layer of onion bulb. Fused protein localized to the plasma membrane and nucleus of plant cells. Therefore, AvrPi54 might be functioning in the host cell as transcription factor or chromatin remodelling factor to modify pathogenesis-related processes.

This qualitative study explores the implementation and conformation process of digital devices in teaching and learning before, during, and after the COVID-19 pandemic in Nepal. Using Rogers' Diffusion of Innovation Theory as a framework, the study examines the adoption and adaptation of digital devices by in-service secondary mathematics teachers (n=62) and their perceptions and preferences towards instructional modality. The findings suggest that despite the increased reliance on digital devices during the pandemic, there is a less likelihood of using them in face-to-face classrooms in developing countries like Nepal. The adoption of online learning has not yet reached the confirmation stage, even after the onset of the COVID-19 pandemic. Prior to the pandemic, online learning was not widely implemented or confirmed by teachers in developing countries societies. The study also provides important insights into the challenges and opportunities of using digital devices in post-COVID-19 classrooms, and its implications for policymakers and educators in Nepal.

Traumatic brain injury (TBI) is a leading cause of death and disability worldwide. Despite extensive research efforts, the majority of trialed monotherapies to date have failed to demonstrate significant benefit. It has been suggested that this is due to the complex pathophysiology of TBI, which may possibly be addressed by a combination of therapeutic interventions. In this article, we have reviewed combinations of different pharmacologic treatments, combinations of non-pharmacologic interventions, and combined pharmacologic and non-pharmacologic interventions for TBI. Both preclinical and clinical studies have been included. While promising results have been found in animal models, clinical trials of combination therapies have not yet shown clear benefit. This may possibly be due to their application without consideration of the evolving pathophysiology of TBI. Improvements of this paradigm may come from novel interventions guided by multimodal neuromonitoring and multimodal imaging techniques, as well as the application of multi-targeted non-pharmacologic and endogenous therapies. There also needs to be a greater representation of female subjects in preclinical and clinical studies.

Abstract: Remarkably, the p53 transcription factor, referred to as “the guardian of the genome”, is not essential for mammalian development. Moreover, efforts to identify p53‑dependent developmental events have produced contradictory conclusions. Given the importance of pluripotent stem cells as models of mammalian development, and their applications in regenerative medicine and disease, resolving these conflicts is essential. Here we attempt to reconcile disparate data into justifiable conclusions predicated on reports that p53‑dependent transcription is first detected in late mouse blastocysts, that p53 activity first becomes potentially lethal during gastrulation, and that apoptosis does not depend on p53. Furthermore, p53 does not regulate expression of genes required for pluripotency in embryonic stem cells (ESCs); it contributes to ESC genomic stability and differentiation. Depending on conditions, p53 accelerates initiation of apoptosis in ESCs in response to DNA damage, but cell cycle arrest as well as the rate and extent of apoptosis in ESCs are p53-independent. In embryonic fibroblasts, p53 induces cell cycle arrest to allow repair of DNA damage, and cell senescence to prevent proliferation of cells with extensive damage.

Along with the Coronavirus pandemic, another crisis has manifested itself in the form of mass fear and panic phenomena, fuelled by incomplete and often inaccurate information. There is therefore a tremendous need to address and better understand COVID-19's informational crisis and gauge public sentiment, so that appropriate messaging and policy decisions can be implemented. In this research article, we identify public sentiment associated with the pandemic using Coronavirus specific Tweets and R statistical software, along with its sentiment analysis packages. We demonstrate insights into the progress of fear-sentiment over time as COVID-19 approached peak levels in the United States, using descriptive textual analytics supported by necessary textual data visualizations. Furthermore, we provide a methodological overview of two essential machine learning classification methods, in the context of textual analytics, and compare their effectiveness in classifying Coronavirus Tweets of varying lengths. We observe a strong classification accuracy of 91% for short Tweets, with the Naive Bayes method. We also observe that the logistic regression classification method provides a reasonable accuracy of 74% with shorter Tweets, and both methods showed relatively weaker performance for longer Tweets. This research provides insights into Coronavirus fear sentiment progression, and outlines associated methods, implications, limitations and opportunities.

The integration of supply chain analytics and Customer Relationship Management (CRM) systems represents a critical strategy for organizations seeking to enhance operational efficiency and customer-centricity in today's competitive business environment. This qualitative study investigates the motivations, strategies, challenges, and outcomes associated with integrating supply chain analytics with CRM systems across diverse industries. Motivations for integration include gaining a unified view of customer data, improving decision-making capabilities, enhancing operational efficiency, and ensuring strategic alignment across organizational functions. Strategies employed by organizations include cross-functional collaboration, investment in scalable technology platforms, and leadership commitment to drive successful integration initiatives. Despite the potential benefits, the integration process presents challenges such as data integration complexities, technical interoperability issues, and organizational resistance to change. Addressing these challenges requires robust technological solutions, effective change management strategies, and a proactive approach to data governance and security. The study identifies significant outcomes from integration efforts, including improved operational efficiency through streamlined processes and optimized resource allocation, enhanced customer insights leading to personalized experiences, and strengthened strategic decision-making supported by real-time analytics.

Digital transformation is revolutionizing supply chain management, profoundly influencing marketing effectiveness across industries. This qualitative study explores the impact of digital transformation on supply chains and its implications for marketing strategies. Through in-depth interviews, case studies, and document analysis, the research elucidates how digital technologies such as IoT, blockchain, AI, and advanced analytics are reshaping supply chain dynamics. Key findings highlight enhanced supply chain visibility, improved decision-making capabilities, and strengthened collaboration among supply chain partners. These technological advancements empower organizations to optimize inventory management, anticipate market trends, and deliver personalized customer experiences, thereby enhancing operational efficiency and customer satisfaction. Furthermore, the study underscores the role of digital transformation in promoting sustainability and ethical practices within supply chains. Technologies like blockchain facilitate transparent and traceable supply chains, supporting initiatives for responsible sourcing and environmental stewardship. Despite the transformative benefits, the study identifies challenges including significant investment requirements, integration complexities, and data security concerns. Strategic approaches to technology adoption, robust cybersecurity measures, and employee training are essential for overcoming these challenges and maximizing the benefits of digital transformation. Overall, this study contributes to understanding how digital transformation drives innovation in supply chain management and enhances marketing effectiveness. By embracing digital technologies and aligning supply chain strategies with marketing objectives, organizations can navigate competitive landscapes, meet evolving consumer expectations, and achieve sustainable growth in the digital era.

This qualitative study explores consumer responses to sustainable supply chains and green marketing strategies, aiming to uncover insights into consumer behavior, perceptions, and attitudes towards sustainability in the marketplace. Through semi-structured interviews and focus group discussions with 30 participants, the study examines key factors influencing consumer trust in green marketing claims, barriers to adopting sustainable products, generational differences in attitudes towards sustainability, and the impact of social media on consumer perceptions. Findings reveal that consumers value transparency and credibility in green claims, preferring products certified by trusted third parties and companies that demonstrate transparent supply chain practices. Higher pricing, concerns about product effectiveness, and limited availability emerged as significant barriers to consumer adoption of sustainable products, highlighting the need for cost competitiveness and increased market accessibility. Generational cohorts, particularly Millennials and Generation Z, exhibit strong inclinations towards sustainability-driven behaviors, shaping market trends towards ethical consumption practices. Social media plays a pivotal role in influencing consumer perceptions, disseminating information about sustainability, and fostering engagement with environmental issues. The study underscores the importance of clear communication, consumer education, and supportive regulatory frameworks in promoting sustainable consumption behaviors. Practical implications include recommendations for businesses to enhance transparency, innovate sustainable products, align with consumer values, leverage social media platforms, and advocate for regulatory measures that uphold environmental standards. By addressing these insights, businesses and policymakers can effectively meet consumer expectations and contribute to sustainable development goals in the global marketplace.

This qualitative study explores consumer perceptions of supply chain sustainability and its impact on buying decisions. Through in-depth interviews and focus groups, the research investigates the multifaceted factors influencing consumer behaviors towards sustainable products. Findings reveal that environmental impact, social responsibility, transparency, economic considerations, and cultural influences are pivotal in shaping consumer attitudes. While consumers express strong motivations to support sustainability, practical barriers such as higher costs and limited availability often hinder consistent adoption of sustainable practices. Effective communication strategies, including transparency reports and sustainability certifications, emerge as crucial in bridging the gap between consumer intentions and actions. The study underscores the importance of aligning corporate sustainability initiatives with consumer expectations to build trust and foster sustainable consumption patterns. Insights suggest a need for targeted interventions and policy measures to address barriers and promote broader adoption of sustainable behaviors. By understanding and responding to consumer concerns, businesses can enhance their sustainability strategies and contribute to a more environmentally and socially responsible marketplace.

Cattle slurry is an important nitrogen source for maize on dairy farms. Slurry injection is an effective measure to reduce ammonia emissions after field application, but with higher risk of nitrous oxide emission than surface application. This study compared soil mineral nitrogen dynamics and nitrous oxide emissions with two ways of application. First, traditional injection at 25 cm spacing between rows followed by ploughing (called “non-placed slurry”), and second, injection using a new so-called goosefoot slurry injector that placed the slurry in ploughed soil as a c. 30 cm broad band at 10 cm depth below maize crop rows with 75 cm spacing (named “placed slurry”). Furthermore, the effect of treating slurry with the nitrification inhibitor 3,4-dimethylpyrazole phosphate (DMPP) in Vizura® was tested with both application methods. The field experiment was conducted on a sandy loam soil in a temperate climate. Both nitrous oxide emissions, and the dynamics of soil mineral nitrogen, were monitored for eight weeks after slurry application and seeding of maize using static chambers. The level of nitrous oxide emissions was higher with non-placed compared to placed slurry, mainly due to higher emissions during the first four weeks. That might be due to higher rates of nitrification rate and in turn stimulation of denitrification process. In both placed and non-placed slurry treatments, Vizura® caused higher soil ammonium concentrations and lower nitrate concentrations, particularly from 3 to 8 weeks after slurry application. The final level of soil nitrate was similar with and without the nitrification inhibitor, but higher with placed compared to non-placed slurry. Adding Vizura® to non-placed slurry reduced nitrous oxide emissions by 70 % when compared to placed slurry. Surprisingly, there was a non-significant trend towards higher cumulative emissions from placed slurry with the nitrification inhibitor compared to untreated slurry, which were due to higher emissions in the last part of the monitoring period (5-7 weeks after slurry application). Possibly degradation of the nitrification inhibitor, and nitrification activity inside the slurry band as the soil dried, promoted nitrous oxide emissions by this time. In summary, placement of untreated slurry in a broad band under maize seeds reduced nitrous oxide emissions compared to non-placed slurry with more soil contact. A comparable reduction was achieved by adding a nitrification inhibitor to non-placed slurry. The pattern of nitrous oxide emissions from placed slurry treated with the inhibitor was complex and requires more investigation.

This study explores the dynamic interplay between supply chain integration and marketing strategies in achieving customer satisfaction. Through a qualitative approach involving semi-structured interviews with supply chain and marketing professionals, the research delves into how these traditionally distinct functions can be aligned to enhance operational efficiency and deliver superior customer experiences. Findings reveal that strategic alignment between supply chain management (SCM) and marketing fosters better coordination of product availability and service delivery, thereby meeting customer expectations consistently and enhancing brand loyalty. Information sharing and technological integration emerge as critical enablers, facilitating real-time data exchange and collaborative decision-making. The study also identifies challenges such as organizational silos, cultural resistance, and technological constraints that impede seamless integration, highlighting the need for proactive strategies to foster cross-functional collaboration. Additionally, the evolving roles of sustainability and customer-centricity are emphasized as key drivers for differentiating brands and achieving competitive advantage. By integrating sustainable practices and adopting a customer-centric approach, organizations can build stronger customer relationships and enhance their market position. The research underscores the importance of leadership support, investment in technology, and a collaborative organizational culture in overcoming integration barriers. The study’s findings provide actionable insights for organizations aiming to optimize their SCM and marketing strategies, drive innovation, and sustain growth in an increasingly complex and competitive business environment. This research contributes to the growing body of knowledge on supply chain and marketing integration, offering practical recommendations for achieving customer satisfaction and long-term success.

Consumer trust in supply chain certifications plays a pivotal role in shaping contemporary consumer behavior and marketing effectiveness. This qualitative research investigates consumer perceptions of supply chain certifications and their impact on purchasing decisions and brand loyalty. Through semi-structured interviews and focus group discussions with 30 participants, the study explores themes such as credibility, transparency, perceived value, and the influence of certifications on consumer trust. Findings reveal that consumers value certifications that signal ethical sourcing practices and sustainability commitments, viewing them as assurances of product quality and social responsibility. Credibility and transparency in certification processes emerged as critical factors influencing consumer trust, while perceived benefits such as environmental sustainability and fair labor practices positively influenced purchase intentions. Moreover, certifications were found to enhance brand loyalty by aligning with consumers' ethical values and beliefs. However, the study identifies challenges including high certification costs, complexity in compliance, and consumer skepticism, which hinder broader adoption and effectiveness of certifications. The implications of these findings suggest that businesses can enhance consumer trust and market competitiveness by investing in rigorous certification standards, clear communication strategies, and sustainable practices. Addressing barriers through improved transparency and consumer education is crucial for maximizing the impact of certifications on ethical consumption. Future research directions include longitudinal studies on certification impacts and comparative analyses across industries and global markets to further enrich understanding of consumer behavior and certification influences.

People counting applications have been used in diverse applications. The ability and accuracy of thermal imaging over conventional image cameras has led to the implementation of thermal cameras in people counting applications. This paper present a thermal people counting smart glass windows. The people counting application would be remotely monitored from a single centralized PC station as it’s connected to a multiplex of mass monitoring of 20 thermal camera, all embedded into different glass windows. The thermal cameras would then be able to detect body temperatures of all individuals who pass through any of the camera range and also count the numbers of people who passed through the camera range. The data gotten can then be further utilized in various ways, example is in the control of air conditioning and lightening.

Aligning supply chain and marketing functions is crucial for high-tech startups aiming to successfully launch new products in competitive markets. This qualitative research explores the strategies, challenges, benefits, and best practices associated with supply chain and marketing alignment in high-tech startups. Through a detailed analysis of case studies and semi-structured interviews with industry professionals, the study identifies key insights into how startups can effectively integrate these functions to enhance operational efficiency, market responsiveness, customer satisfaction, and risk management. The findings reveal that successful alignment requires the formation of cross-functional teams, leveraging integrated technologies like CRM and ERP systems, establishing regular inter-departmental communication, and developing joint performance metrics. These strategies foster collaboration and ensure that supply chain and marketing efforts are coordinated towards shared goals. However, startups face challenges such as differing departmental objectives, resource constraints, communication barriers, and technological limitations, which hinder effective alignment. Benefits observed from effective alignment include improved operational efficiency through streamlined processes, enhanced market responsiveness to adapt quickly to changing demands, increased customer satisfaction by delivering products that meet market expectations, and better risk management through proactive identification and mitigation of supply chain and market risks. Best practices identified include fostering a culture of collaboration, investing in technology for data integration and transparency, aligning strategic objectives across functions, and continuously monitoring and adjusting alignment strategies. Integration of broader elements such as sustainability, entrepreneurship, emotional intelligence, marketing, and supplier relationship management further enriches the alignment framework. This study contributes to a deeper understanding of how high-tech startups can strategically align their supply chain and marketing functions to achieve competitive advantage and sustainable growth in dynamic market environments.

This qualitative research explores the influence of supply chain disruption management on brand resilience and consumer perception. Amidst increasingly complex global dynamics, effective strategies are crucial for organizations to mitigate risks, maintain operational continuity, and preserve consumer trust. The study employs semi-structured interviews with stakeholders across diverse industries, focusing on strategies employed, outcomes observed, and challenges faced in managing disruptions. Key findings underscore the significance of proactive measures such as risk assessment, contingency planning, diversification, technology integration, and collaboration in enhancing organizational resilience. These strategies not only enable businesses to navigate disruptions effectively but also contribute to sustaining competitive advantage and stakeholder confidence. Consumer perception during disruptions emerges as pivotal, shaped by brands' transparency, responsiveness, and ethical considerations in managing supply chain challenges. Transparent communication and reliable service delivery during disruptions enhance brand reputation and foster consumer loyalty. However, challenges including information gaps, resource constraints, coordination issues, and regulatory compliance complexities highlight the need for adaptive strategies and robust partnerships across the supply chain. Overall, the study provides insights into the interconnectedness of disruption management, brand resilience, and consumer perception, offering practical implications for organizations seeking to strengthen their resilience strategies and consumer relationships in dynamic market environments.

This qualitative study explores the transformative role of digital technologies in enhancing supply chain efficiency and marketing effectiveness across diverse industries. The integration of Internet of Things (IoT), artificial intelligence (AI), blockchain, and advanced analytics has reshaped organizational practices, enabling real-time data collection, analysis, and decision-making in supply chain management (SCM) and marketing. Through semi-structured interviews with 25 professionals, including supply chain managers, marketing executives, and IT specialists, insights were gathered into the adoption, integration, and impact of digital technologies within organizational contexts. Key findings highlight IoT's contribution to enhancing supply chain visibility, predictive maintenance, and operational efficiency through continuous monitoring and data-driven insights. AI technologies support demand forecasting, inventory optimization, and personalized marketing strategies, improving customer engagement and satisfaction. Blockchain enhances supply chain transparency, traceability, and security, reducing risks associated with fraud and ensuring compliance with regulatory standards. Advanced analytics provide organizations with actionable insights into consumer behavior and market trends, guiding strategic decision-making and optimizing marketing campaigns. Despite these benefits, organizations face challenges such as technological complexity, integration issues, data privacy concerns, and organizational resistance to change. Strategic planning, leadership support, and investment in digital infrastructure are essential for overcoming these challenges and maximizing the potential of digital technologies. Future research directions include exploring sustainability initiatives in digital SCM, advancing AI-driven analytics, and understanding digital transformation in emerging markets.

The main characteristic of polycystic kidney disease is the development of multiple fluid filled renal cysts. The discovery of mislocated Na,K-ATPase in the apical membrane of cyst lining epithelia alluded to a reversal of polarity as a possible explanation to the fluid secretion. The topic of apical Na,K-ATPase in cysts remains controversial. We investigated the localization of the Na,K-ATPase and assessed the apical-basolateral polarization of cyst lining epithelia by means of immunohistochemistry in kidney tissue from six polycystic kidney disease patients undergoing nephrectomy. The Na,K-ATPase α1 subunit was conventionally situated in the basolateral membrane of all immunoreactive cysts. Proteins of the Crumbs and partitioning defective (Par) complexes were localized to the apical membrane domain in cyst epithelial cells. The apical t-SNARE protein Syntaxin-3 also immunolocalized to the apical domain of cyst lining epithelial cells. Proteins of the basolateral Scribble complex immunolocalized to the basolateral domain of cysts. Furthermore, we confirmed that cysts can originate from virtually any tubular segment with preserved polarity. In conclusion, we find no evidence of a reversal in apical-basolateral polarity in cyst lining epithelia in polycystic kidney disease.

The Necessity of Human resources beyond perception of human understanding towards the Evaluation of video quality or Data screening methodology is conducted based on human perception level since it is concerned with how visual content is perceived by a observer based on observations with his/ her perception on a particular video sequence. Therefore, we considered that the subject has to grade the encoded video sequences under certain test environment conditions based on ITU-Recommendations. Since Human perception is considered as the true judgment and precise measurement of visual content, data screening has became quite essential and quite comfortable to general public due to introduction of User Experience(UX) concept by User Experience community. The translations of A recurrent neural network is based on certain principles, for instance we considered natural language processing which is certainly adaptable towards understanding sequential data and use patterns to predict the consistency within observers. In our research, we adapted principles based on Recurrent Neural Networks while assuming consistency within observers for predicting video quality within data screening environment towards subjective experiments. Moreover,this research work explores the trade offs between Human perception on visual content and consistency of observations within individual observer.

This qualitative study explores the relationship between supply chain responsiveness (SCR) and customer loyalty within the e-commerce sector. E-commerce has revolutionized global commerce, driven by technological advancements and shifting consumer behaviors. Central to e-commerce success is the ability to meet customer expectations swiftly and reliably, necessitating agile supply chain management (SCM) practices. SCR in e-commerce encompasses the capacity to adapt to dynamic market demands, minimize disruptions, and enhance customer satisfaction through efficient logistics, inventory management, and last-mile delivery. Through in-depth interviews with customers, e-commerce platform managers, and supply chain practitioners, this study investigates key themes, challenges, strategies, and impacts associated with SCR and customer loyalty. Findings reveal that customers prioritize fast order fulfillment, reliable service quality, personalized experiences, and trustworthy interactions, all of which significantly influence their loyalty and advocacy behaviors. Challenges identified include inventory management complexities, logistical hurdles in last-mile delivery, and the need for effective supplier communication. Strategic approaches to enhance SCR include leveraging data analytics for demand forecasting, adopting agile SCM practices, integrating customer feedback into service improvements, and fostering collaborative relationships with suppliers. These strategies not only optimize operational efficiency but also cultivate enduring customer relationships based on satisfaction, trust, and loyalty. The study concludes that improved SCR practices lead to increased customer satisfaction, repeat purchases, and positive word-of-mouth, thereby strengthening competitive advantage and sustainability in the e-commerce marketplace.

Background: Mental health is a growing concern worldwide. It is not well understood whether Nepali workers, including international labour migrants from Nepal, are at higher risk of developing mental health problems. The purpose of our study is to determine the prevalence of and examine the risks factors for depression among returnee migrants and non-migrant working male adults in Nepal. Methods: A cross-sectional survey of a probability-based sample of 725 participants was conducted in February 2020. The sample was comprised of two groups based on migration status: returning migrants and non-migrants. Logistic regression was applied to investigate factors associated with symptoms depression.Results: The overall prevalence of depression was 10.1%. However, the prevalence of depression was lower (7%) among returnee migrants compared to non-migrants (13.7%). Participants in the lower income group were more at risk of depression (OR=5.38, 95% CI: 1.96-14.78) than those in the higher income group. Similarly, Buddhists and Christians were more likely to be depressed (OR=2.17, 95% CI: 1.02-4.64) than Hindus. Interestingly, participants having more than two children had a higher prevalence of depression (OR=5.14, 95% CI: 1.22-21.63) compared with those having no children. Unmarried participants were more likely to be depressed (OR=4.05, 95%, CI:1.10-14.93) than those who were married. Conclusion: The working Nepali adult male population in Nepal, including returning migrants, is at risk of depression, but this risk is lower in those in the higher income group, returnee migrants, married, Hindus and those with no children. This study highlights the need to monitor and develop national policies to ensure the mental health of Nepali male adult population, including returnee migrants.

Introduction: Over decades, much have been said and done regarding under-five mortality in Ethiopia. The country has been following the lead of sustainable development goals and UNICEF with its transformation plan targets. However, unless the efforts supported by status assessing studies, it might be difficult for the country to progress. Thus, the current study was directed to identify the prevalence and associated factors of under-five mortality in 2019. Methods: According to the study criteria, we extract and cleaned data in STATA v. 15.0. The data then weighted as per the sampling weight, primary sampling unit, and strata before analyzing in STATA 15.0. Data management consisted of descriptive (mean, standard deviation, and proportion or percent) and association statistics. We deliberated binary logistic regression for this analysis and we checked each variable at 0.25 p-values to include in the model. The final p-value to declare association was p <0.05 and AOR with 95% CI was also applied to describe the results. The data source was the Ethiopian Mini Demographic Health Survey (EMDHS) 2019. EMDHS collected the data from 8,885 in a face-to-face manner with a 99% response rate. Results: From 5,527 numbers of weighted women with under-five analysed in this study, the proportion of under-five mortality was 277.23(5.02%). Factors like 2nd birth order 0.52(0.35, 0.79), 3rd-4th 0.49(0.28, 0.84), 1-2 ANC visits 0.24(0.12, 0.49, ANC visit three’ 0.14(0.07, 0.28), ANC visit four and above 0.22(0.14, 0.36), in marriage mother 0.43(0.19, 0.96), ‘1-2 under-five children 0.02(0.011, 0.03), and greater than three under-five children 0.007(0.0007, 0.004) were all negatively associated with under-five mortality rate. Conclusion: To obtain the exalted outcome out of this study, the government might need to increase antenatal care, women education, institutional delivery, and the modern contraceptive methods use through enhanced community mobilization, health education using community health workers, increasing access to essential cares of mothers and children, and the policy commitment for the issues related to family size, birth order, and birth interval.

Neurodegenerative diseases, including Alzheimer's, Huntington's, Parkinson’s, and Amyotrophic Lateral Sclerosis, involve neuron degeneration linked to the misfolding of amyloidogenic proteins, resulting in β-sheet-enriched aggregates. This phenomenon disrupts the normal folding of proteins critical for cellular function. Genetic mutations, proteolytic cleavage, oxidative stress, and aging contribute to misfolding. Parkinson's disease (PD) is closely tied to alpha-synuclein (αS) misfolding, with A53T mutation and Lewy bodies (LB) in PD brains pivotal to understanding the disease mechanism. Other synuclein homologues (βS, γS) further contribute to synucleinopathies. Mutants (A30P, A53T, E46K, H50Q, and G51D) underscore αS&#39;s role in PD development. This concise review focuses on molecular and pathological aspects of neurodegenerative diseases, emphasizing αS in PD. The integration of genetic, structural, and mechanistic insights highlights the disorders. complexity, paving the way for future therapeutic strategies targeting protein misfolding and aggregation.

This qualitative research investigates the role of collaborative planning in synchronizing supply chain and marketing activities among multinational companies (MNCs). Collaborative planning integrates traditionally separate functions to enhance operational efficiency, customer responsiveness, and strategic alignment. The study employs semi-structured interviews with key informants from diverse MNCs across industries and geographies to explore practices, challenges, and outcomes associated with collaborative planning initiatives. Findings highlight the pivotal role of cross-functional collaboration and advanced technologies, such as artificial intelligence and big data analytics, in improving demand forecasting accuracy, optimizing inventory management, and enabling personalized marketing strategies. Challenges include organizational resistance, cultural barriers, and the complexity of aligning global strategies. Strategic outcomes encompass improved operational efficiency, cost savings, enhanced customer satisfaction, and strengthened competitive advantage. Moreover, the integration of sustainability goals underscores the importance of environmental responsibility and regulatory compliance in collaborative planning frameworks. The study also identifies emerging trends in digital transformation and agile supply chains shaping future practices. Overall, collaborative planning emerges as a strategic imperative for MNCs to navigate complexities, capitalize on opportunities, and sustain growth in a globalized marketplace.

This qualitative research explores consumer perceptions of supply chain responsiveness and its impact on brand loyalty within the apparel industry. The study investigates how consumers perceive supply chain practices such as reliability, agility, and sustainability, and examines their influence on brand loyalty decisions. Thirty participants, representing diverse demographics and purchasing behaviors, were interviewed to gather insights into their awareness, expectations, and experiences related to supply chain responsiveness. Findings reveal that consumers prioritize supply chain reliability, expecting brands to consistently deliver high-quality products, accurate sizing, and timely responses to market trends. Sustainability practices also emerged as a significant factor, with consumers favoring brands that demonstrate ethical sourcing and environmental responsibility. Technology plays a crucial role in enhancing supply chain responsiveness, as consumers value real-time updates, personalized experiences, and seamless transactions. Moreover, the study underscores the impact of supply chain disruptions on brand trust and loyalty, highlighting the importance of resilience and contingency planning in supply chain management. Brands that effectively navigate disruptions through agile strategies can enhance consumer trust and loyalty, even in challenging circumstances. Overall, this research contributes to understanding the intricate relationship between supply chain dynamics, consumer perceptions, and brand loyalty in the apparel industry. It offers practical implications for apparel brands seeking to enhance consumer satisfaction, differentiate themselves in a competitive market, and foster sustainable growth through strategic supply chain management.

Brand communication and supply chain management are critical components of value co-creation in B2B markets, yet their interplay and implications remain underexplored in current literature. This qualitative study investigates how these elements synergistically contribute to mutual value creation among businesses. Through semi-structured interviews with senior executives and managers from diverse industries, key insights were gleaned regarding the strategic alignment of brand communication strategies with supply chain practices. Findings underscore the importance of authenticity, transparency, and consistency in brand messaging to build credibility and foster stakeholder trust. Supply chain management emerged as pivotal in supporting effective brand communication, facilitated by advancements in AI, blockchain, IoT, and cloud computing, enhancing operational efficiency and responsiveness across global networks. Entrepreneurship and emotional intelligence were identified as crucial drivers of innovation and collaboration within B2B contexts, augmenting organizational agility and resilience. Furthermore, the integration of sustainable practices within supply chain operations was found to enhance brand reputation and mitigate risks associated with environmental and ethical considerations. The study highlights actionable insights for practitioners, emphasizing the strategic integration of brand communication and SCM capabilities to navigate complexities, capitalize on emerging opportunities, and foster sustainable growth. This research contributes to a deeper understanding of the multifaceted dynamics shaping B2B interactions and provides a foundation for future research endeavors. By aligning brand communication strategies with SCM practices and leveraging technological advancements, businesses can enhance competitive advantage, cultivate enduring relationships with stakeholders, and achieve sustainable success in a dynamic global marketplace.

In today's volatile and competitive business landscape, achieving synergy between supply chain agility and marketing flexibility is imperative for organizations striving to enhance resilience and maintain competitiveness. This qualitative study explores the integration of these strategic elements and their impact on organizational performance in turbulent markets. Semi-structured interviews were conducted with key stakeholders from diverse industries to capture insights into adaptation strategies, challenges, and outcomes associated with aligning supply chain agility and marketing flexibility. Findings reveal that supply chain agility, characterized by rapid response capabilities to disruptions and fluctuating demands, is essential for optimizing operational efficiency and maintaining continuity in uncertain environments. Meanwhile, marketing flexibility enables organizations to adjust strategies swiftly based on real-time market insights, enhancing customer engagement and market responsiveness. The study identifies organizational silos, resistance to change, and technological limitations as primary barriers to achieving seamless integration. Benefits of synergy include improved customer satisfaction, accelerated time-to-market for new products, and enhanced competitive advantage through personalized marketing strategies and optimized resource allocation. Moreover, organizations that effectively integrate supply chain agility with marketing flexibility reported greater innovation, employee satisfaction, and sustainable growth.

Background: Disability and caste are two different forms of oppression, however Dalits and people with disabilities commonly face similar types of marginalities. Dalit women with disabilities may experience double discrimination because of the intersectionality of disability and caste. This study examines whether the disability and caste identity of women together affects and compounds the utilization of maternal healthcare services. Methods: A cross-sectional survey was conducted using a semi-structured questionnaire among a total of 354 Dalit and non-Dalit women, with and without a disability aged between 15 – 49 years. Maternal healthcare service utilization was assessed by Ante-Natal Care (ANC), health facility (HF) delivery, and Post-Natal Care (PNC) during the last pregnancy. Logistic regression was performed to detect the predictors of service utilization and identify whether disability and caste were associated with service utilization. First, disability and caste were fitted separately in models. Secondly, the intersectionality of disability and caste was tested by the inclusion of disability*caste interaction term. Finally, the confounding effect of socio-demographic factors was investigated. Results: Out of surveyed women, 73% had 4+ ANC visits, 65% had HF delivery and 29% had a PNC visit during their last pregnancy. Women with a disability had lower odds of HF delivery (OR 0.50, CI 0.30 – 0.84) and PNC (OR 0.47, CI 0.25 – 0.88) than women without a disability. Adjustment for women’s age and household wealth explained associations in HF delivery by women with disabilities. There was no association between caste and service utilization. Disability overrode caste and there was no other evidence of effect modification by women’s caste status in the utilization. However, a weak interaction effect in the utilization of ANC services was found in the caste group by their education (OR 0.19, 95% CI 0.05 – 0.74). Conclusions: Disabled women – whether Dalit or non-Dalit - had lower rates of utilizing all maternal healthcare services than non-disabled women. However, Dalit women with disabilities were more likely to receive PNC than non-Dalit women with disabilities. Increasing equity in maternal healthcare service utilization requires that traditional approaches to service development and program intervention to be re-examined and more nuanced interventions considered to ensure improved access and outcome among all vulnerable groups.

Interest in organic foods is increasing at a moment when humanity is facing a range of health challenges including the concern that some conventionally produced foods may pose possible adverse effects on human and livestock health. With the increasing human population, intensive production is increasingly trending towards high-input systems that aim to close yield gaps, increase crop yields, and develop new crop varieties with higher yield potential and tolerance to biotic and abiotic stresses, all within the context of incorporating specific traits to satisfy consumer demand. Potato (Solanum tuberosum L.) is one of the most consumed foods under different cultural diets, however its production faces some challenges related to soilborne diseases, marketable yield and quality, sugars and dry matter content of the produced tubers, tuber content in terms of nitrate, minerals, vitamins, bioactive compounds and antioxidants, and consumer appreciation regarding the sensory characteristics of tubers and processed products. Different studies have been investigating some of these challenges, with sometimes straightforward and sometimes connflicting results. This variability in research results indicates the general non-transferability of the results from one location to another under the same management practices in addition to differences in plant material. This review compares some characteristics of raw or boiled potato and processed products from potato tubers grown organically and conventionally. Ideally, such information may be of benefit in decision making by consumers in their dietary choices, by potato growers in their selection of crop management practices, and by scientists looking at potential areas for future research on potatoes.

Transcription factors are diverse intracellular proteins facilitating cellular responses to inducing factors via gene expression. Regulatory signalling cascades from the membrane proteins (sensors) to transcription factors (effectors) are paramount to accurate phenotypic display against external factors. This review examines several transcription factors germane to Cryptococcus (C.) neoformans adaptation and survival for human infection. These opportunistic pathogenic single-cell yeasts (fungi) possess several gene duplications and peculiar membrane proteins due to adaptive phenotypes and morphological plasticity. Consequently, hundreds of responsible pleiotropic genes have been studied to understand how these genes are induced, regulated, and coordinated. However, these findings are sparsely converged and interlinked, making it cumbersome to relate one gene to the other or group them by their functions. We reviewed several wide-ranging transcriptional analysis works associated with C. neoformans into comparable phenotypic traits that necessitate adaptation, survival, and human infection. We present a robust work that addresses several transcription factors and their inducing factors. Lastly, we converge, link, and group several of these factors according to their multifunctional expression pattern. We also provide adequate information on certain genes critical to this fungus, which could be explored pharmaceutically in drug targeting for more effective antifungal management.

The frequent incidents of oil spills and other forms of pollution arising from crude oil exploration and exploitation (OEE) in the Niger Delta have caused several investigations on Polycyclic Aromatic Hydrocarbons (PAHs) pollution. This study aimed at developing a comprehensive report on PAH pollution and its human health risks recorded in the Niger Delta. Studies were extracted from Google Scholar, PubMed, and ResearchGate using a defined selection criterion. The quality of each study was assessed using the Newcastle – Ottawa Scale. Thirty-eight studies were selected with the majority reporting on PAH pollution in aquatic environments. Across all the selected studies, the total number of PAHs recorded ranged from 7 to 28 PAH congeners. Also, PAH potential sources reported in the studies were of pyrogenic and petrogenic sources. PAH concentrations recorded in water, sediment, aquatic organisms (fish and shrimp), soil, dust, and crop samples ranged from below detection limit (BDL) to 450 ± 117.9 mg/L, BDL to 1821.5 mg/kg, 0.005 to 1.098 mg/kg, ND to 4154 ± 3461 mg/kg, 165.1 to 1012 mg/kg, and 0.020 to 3.37 mg/kg, respectively. Majority of the selected studies reported PAH levels which were higher than the permissible limits. Incremental Lifetime Cancer Risk (ILCR) assessment of PAHs in samples ranged from low to high via ingestion and dermal routes of exposure to humans. It is recommended that the Federal Government of Nigeria promotes environmentally friendly operations of OEE. Future studies should focus on PAH pollution in farmlands, ambient air and the associated human and ecological health risks.

Despite the existence of pasteurization and its advocacy worldwide, most marketed milk in a developing country like Nigeria are sold raw by the locals. It costs hundreds of millions of Naira to set up a conventional pasteurizing plant in Nigeria. Boiled milk ends up curdling which results in to a loss of nutrients, so it is not beneficial to treat milk by this method. This paper hence presents the re-designing and fabrication of the contact area of a solar milk pasteurizer

Research topics surrounding the giraffe have been subject to recent disagreement, with work focusing on taxonomy over ecological phenomena such as behavioural thermoregulation. Much interest in taxonomy arises around the existence of distinct local populations of giraffes, often enclosed in small, fenced reserves, preventing natural gene flow. Targeted management of reserves may act as a buffer for declining populations, providing landscape that minimises requirements for thermoregulatory behaviours. Notable behaviours include shade-usage via trees and other giraffes, and positioning of the body towards the sun, employing an individual’s own neck as a shade source. Breeding programmes and translocation of individuals away from large communities on fenced reserves may increase giraffe population numbers across their range; however, the genetic diversity of large populations in enclosed spaces may be called into question. 55 of the 57 giraffes from the population on the Mogalakwena River Reserve (MRR) were observed over eight months, recording thermoregulatory behaviours such as body positioning in response to sun exposure, and shade usage; behaviours both noted in secondary works. These behaviours were compared across identities, such as sex and age, to assess how thermoregulation varies per individual. The population on the MRR spent more time facing the sun during high temperature days, with adults, sub-adults, males, and dark-coated individuals prioritising the behaviour beyond other individuals. Body positioning behaviours of individuals were also found to be more important in thermoregulation than shade-seeking, with shade usage decreasing on hotter days. Positional behaviour, disregarding identity, was also observed across wet and dry seasons, with a clear contrast; giraffes face the sun significantly more during the hotter wet season. The behaviours observed in this work provide an insight into the direction conservational strategies may take on closed reserves. However, further work is required on other reserves with varied population structures, to determine whether one strategy may be implemented across the giraffe's range, or whether specialised strategies are required in individual locations.

In this research a neccessary and sufficient condition for the proof of the Binary Goldbach conjecture is established. It is established that the square of all natural numbers greater or equal to 2 have an additive partition equal to the sum of the square of a natural number greater or equal to zero and a Goldbach partition semiprime. All Goldbach partition semiprimes are odd except 4. This finding is in itself proof all composite even numbers have at least Goldbach partition. The result of the proof of the Binary Goldbach conjecture is used to prove the Andrica and Legendre conjectures. The Riemann hypothesis is examined and sources of non trivial zeroes outside the critical strip are discussed. An example example of a non-trivial zero outside the critical strip is given

Social Anxiety Disorder (SAD) is a common mental health condition characterized by an intense fear of social situations, leading to significant impairments in daily functioning. Traditional exposure therapies, including Cognitive-Behavioral Therapy (CBT), have shown efficacy in treating SAD but are often limited by logistical challenges and patient reluctance. Virtual Reality Exposure Therapy (VRET) has emerged as a promising alternative, providing a controlled and immersive environment for exposure to anxiety-provoking scenarios. This paper explores the integration of Generative Adversarial Networks (GANs) into VRET to enhance the personalization, realism, and adaptability of therapeutic scenarios. GANs, which consist of a generator and a discriminator network, allow for the creation of highly realistic virtual environments tailored to the specific fears and triggers of individual patients. By offering real-time adjustments and personalized exposure scenarios, GAN-enhanced VRET addresses key limitations of traditional therapies, increasing patient engagement and treatment adherence. This review synthesizes findings from key studies on GAN-enhanced VRET, evaluating its efficacy in reducing anxiety symptoms and discussing the potential for broader application across various anxiety disorders. The results indicate that GAN-enhanced VRET offers a significant advancement in the treatment of SAD, providing a more accessible, engaging, and effective approach to exposure therapy. Future directions include expanding accessibility through cost reduction, integrating additional AI techniques, and exploring applications beyond SAD to improve mental health outcomes across diverse patient populations.

In this paper we aim to help topical probiotics research and development achieve its potential as an incredible future solution for skin problems by investigating whether the current products on the market satisfy criteria for safe and effective use on the skin microbiome. As previously defined, this includes whether they use microbes known to be part of a healthy skin microbiome and in healthy amounts. In addition, we evaluate whether they contain live microbes, and therefore can be classified as probiotics according to the WHO’s definition. Using recent market analysis at least 84% of products do not contain live microbes. Of the products that appeared to use live microbes, they contained those used in research and development of probiotics for the gut. Due to the varying composition of each person’s microbiome, there is not a one size fits all probiotic solution. Personalisation of probiotics products is essential to satisfy the criteria for safe and effective use, but none of the products on the market, understandably, offer this. Upsetting the delicate ecosystem balance of the skin microbiome could have damaging effects and regulation could help to stop a loss of trust between consumers and cosmetics industry. Future work will perform an in-depth evaluation of the topical probiotics on the market in the EU, USA, and Canada. We will also investigate how to move the topic closer to achieving its potential by updating the criteria, including by discussing how to measure the success of a probiotic solution.

The electron of spin −1/2 is a Dirac fermion of a complex four-component spinor field. Though it is effectively addressed by relativistic quantum field theory, an intuitive form of the fermion still remains lacking and it is often described by the so-called Dirac belt trick. In this novel undertaking, the electron is examined within the boundary posed by a recently proposed MP model of a hydrogen atom into 4D space-time. Its transformation to Dirac fermion appears consistent with Dirac belt trick, quantum mechanics and Lie group with gravity considered to be a classical force for an irreducible spinor field. These outcomes are compatible with Dirac field theory and its associated features like wave function collapse, quantized Hamiltonian, non-relativistic wave function, Weyl spinor, Lorentz transformation and Feynman diagrams. The model though speculative, it could become important towards defining the fundamental state of matter subject to further examinations.

This interdisciplinary work presents a novel patent pending method of inertial electrostatic confinement (IEC) fusion called the Nuclear Electromagnetic Shaping Accelerator Reactor (NESAR) that addresses all of the major failure problems with currently known methods of IEC fusion. A brief background of previous IEC methods that generate a negative potential well to accelerate ions for fusion will be reviewed and compared to the NESAR method of magnetic confinement. In addition, a direct comparison will be presented between the NESAR and the tokamak method of fusion. The NESAR method of fusion obtains the plasma oscillation and compression capabilities of a tokamak without producing the catastrophic magnetic reconnection disruptions that currently plague tokamaks. Since the NESAR can oscillate charged particles comparable to the tokamak, this work will briefly review the history of the tokamak, how sawtooth magnetic reconnection occurs, and how the NESAR precludes the occurrence of magnetic reconnection. This work will also review the beginnings of a novel unified field theory that has obtained interest from the Defense Advanced Research Projects Agency (DARPA). This unified field theory is based upon the trajectory of charged particle movements within the NESAR, which is the only concept of magnetic confinement in the world that may allow charge particles to collectively interact relatively to a solitary location. Due to this possible capability, the confined charged particles have the potential to experience curved trajectories; allowing for the effects of curvature deviation to be placed upon the charged particle within the magnetic confines of the NESAR. If charged particles can experience curvature deviation then deviated acceleration is generated; allowing the electromagnet field to be propelled to a higher spatial dimension that could influence spacetime. Finally, this work will review another theory that explains how magnetic pole reversals are observed by the National Aeronautics and Space Administration’s (NASA) coiled magnetic field detectors. This theory requires little to no postulations to be framed and it is purely based upon the trajectory of charged particles within the NESAR, Michael Faraday’s law of induction, and experimental observations of rotating plasmas.

In this work we derive a generalized series expansion of the acrtangent function by using the enhanced midpoint integration (EMI). Algorithmic implementation of the generalized series expansion utilizes a simple two-step iteration. This approach significantly improves the convergence and requires no surd numbers in computation of the arctangent function.

This short communication reports on the initial results of a much larger, ongoing project, the aim of which is to investigate the question: could the skin microbiome, just like the gut microbiome, play a role in sports recovery and performance – and if so, could this role be as significant a one as that played by the gut microbiome? 17 high performance college athletes addressed their skin microbiome by minimizing contact with synthetic chemicals and by using topical skin supplements, shown previously to significantly increase skin microbiome biodiversity, for two weeks after training. 76% said their skin softness improved, 35% said their muscle stiffness and recovery after sport improved, 12% said their sleep quality improved, and 100% said they would be likely to use skin supplements again. Future work will use hundreds of athletes.

Recent years have seen a massive increase in research on mindfulness as both a therapeutic practice as well as a protective health factor. While many associations have been made between mindfulness and clinical outcomes, understanding of the underlying mechanistic processes is still in its infancy. In this review, associations between mindfulness and other established frameworks in cognitive control are explored—in particular the dual modes of control framework in cognitive control theory. Studies in mindfulness providing evidence towards a dual-mode mindfulness model are reviewed and compared with the proactive and reactive modes of cognitive control to identify common underlying principles. Studies involving cognitive testing, advanced neuroimaging, and neurotransmitter levels and their associations with proactive and reactive control are reviewed in the context of the dual modes of mindfulness. While evidence supporting relationships between proactive and reactive modes of mindfulness and cognitive control are preliminary, existing literature on mindfulness already supports the notion of two components of mindfulness and is in line with the hypothesis that cognitive control and mindfulness are closely related. Since preliminary evidence suggests that proactive forms of mindfulness are more associated with improvement in clinical outcomes, mindfulness programs could be modified to target proactive mindfulness practices to maximize outcomes. The implications of proactive and reactive mindfulness on therapy, limitations of the framework, and necessity of studies providing direct evidence are further discussed.

Melanoma, a deadly form of skin cancer, has seen improved survival rates due to advances in diagnosis and treatment, yet the need for further improvement remains critical. Tumor-associated antigens, such as PRAME (Preferentially Expressed Antigen in Melanoma), offer promising avenues for enhanced diagnostic precision, prognostic assessment, and targeted immunotherapy. PRAME, a cancer-testis antigen, is selectively expressed in various cancers, including melanoma, and plays a key role in promoting tumorigenesis through inhibition of retinoic acid signaling, epithelial-to-mesenchymal transition, and immune evasion. This review explores the diagnostic utility of PRAME in distinguishing melanoma from benign nevi, its prognostic value in aggressive melanoma subtypes, and its potential as a therapeutic target in cancer vaccines and adoptive T-cell therapies. While PRAME-targeted therapies face challenges such as tumor heterogeneity and immune suppression, ongoing research aims to overcome these barriers, offering hope for more effective melanoma treatments.

The arrest of Pavel Durov, the CEO of Telegram, represents a critical moment in the ongoing discourse surrounding free speech and content moderation. This event exemplifies the tension between upholding individual liberties and addressing the potential societal harms caused by unregulated digital communication. This paper explores the implications of Durov’s arrest and Telegram’s stance on free speech through the lens of John Stuart Mill’s Harm Principle. The Harm Principle, as articulated in Mill’s seminal work On Liberty (1859), provides a valuable theoretical framework for examining the balance between individual freedom and societal protection. This paper argues that the application of the Harm Principle can offer a nuanced perspective on the ethical responsibilities of digital platforms like Telegram in the age of global communication.

The optimization of the energy grid is a critical task for ensuring a sustainable and efficient energy future. Deep machine learning techniques have the potential to improve energy grid optimization by predicting energy demands and supplies, optimizing energy production and distribution, and detecting and preventing fraud. However, there are also several challenges associated with the use of deep machine learning in energy grid optimization. These include the lack of standardized datasets and data quality issues, interpretability and explain-ability of machine learning models, ethical and social implications of using machine learning, and integration with existing energy infrastructure and regulatory frameworks. Having a clear understanding that continued research and developments in deep learning applications to energy field are crucial for achieving a sustainable and efficient energy future. This paper therefore reviewed existing literature for challenges and opportunities associated with deep machine learning in energy grid optimization; and highlights the importance of continued research and development in the field. The paper found out that opportunities for future research in deep machine learning for energy grid optimization include advancements in machine learning algorithms and techniques, development of new datasets and data collection methods, integration of machine learning with other emerging technologies. It also established needs for collaborative research and public-private partnerships.

In this review, we present several extracellular proteases, enzymes, membrane permeases, and transporters as essential accessories proteins for nutrient assimilation, conservation, and transportation as determined by nutrient repletion or depletion. As an obligate aerobic pathogen, it is crucial for invading Cryptococcus (C.) neoformans to negotiate its adaptation to human internal organs like the brain and spinal cord, where the oxygen level is low compared to peripheral organs. Besides, essential metals like copper and iron are important cofactors to functional proteins; however, these metals are not usually freely available to invading human pathogens. Again, the phagolysosome low pH with glucose paucity, internal temperature, immune response, and complex extracellular matrixes are challenging environments that must be circumvented by C. neoformans in the systemic tissues for survival, adaptation, and infection in humans. We review extensive works on several extracellular proteases, enzymes, membrane permeases and transporters orchestrated by different transcription factors and present these proteins as weapons needed to outwit systemic resistance to invading pathogens. Lastly, we examine the extracellular secretory vesicles of C. neoformans as “an exosomal virulence bag” that harbours urease, laccase, phosphatase, and capsular components as additional secretory weapons for tissue invasion and persistence.

We present an open-source Star Tracker (ST) for Attitude Determination. Our implementation makes use of open source software of common usage in astronomy running on a Raspberry Pi 2 platform. The developed platform is open and available for parties interested in further development. Evaluation of the system showed that the ST is suitable for Cubesats of 2U or larger. The ST platform is capable of solving the Lost-In-Space (LIS) problem. Currently, the average accuracy reached of the algorithm is close to 5 seconds of arc with an average processing time of 75 seconds. However, a average accuracy of about 3 minutes of arc can be reached with 35 seconds in average processing time. We also describe the evaluation procedure, the found conclusions of this procedure, in particular the section of the algorithm where most of the processing time is spent and other possible source of errors not included in this study.

Commercially cultivated Prunus species are commonly grown in adjacent or mixed orchards, and can be infected with unique or commonly shared viruses. Apple (Malus domestica), another member of the Rosacea and distantly related to Prunus, can share the same growing regions and common pathogens. Pollen can be a major route for virus transmission, and analysis of the pollen virome in tree fruit orchards can provide insights into these virus pathogen complexes from mixed production sites. Commercial honey bee (Apis mellifera) pollination is essential for improved fruit set and yield in tree fruit production systems. Here we describe the metagenomics-based detection of plant viruses through bee and pollen samples collected during the spring bloom period from a mixed Prunus and Malus orchard. Twenty-one unique viruses were detected in samples collected during apricot (Prunus armeniaca), sweet cherry (Prunus avium), peach (Prunus persica), and apple blooms. Ilarviruses prune dwarf virus (PDV) and prunus necrotic ringspot virus (PNRSV), Secoviridae family members tomato necrotic ringspot virus, tobacco necrotic ringspot virus, and prunus virus F, and Capillovirus cherry virus A (CVA) were detected in all time points, while other viruses were detected with restricted ranges. These results demonstrate the benefits of area-wide monitoring through bee pollination activities, and provide new insights into the diversity of viruses in tree fruit pollination ecosystems.

Microemulsions with excellent properties have shown significant potential for enhancing oil recovery from tight formations through spontaneous imbibition. This work present a high-temperature-tolerant lower-phase microemulsion (HTLP-ME) using a microemulsion dilution method. The properties and morphological characteristics of HTLP-ME were evaluated and proposed a enhanced spontaneous imbibition oil recovery mechanism using imbibition tests and CT scanning technology. The results show that the optimum concentration of HTLP-ME is 0.2wt% has a superior thermal stability, small particle size, lower IFT, good wettability alteration ability, and minimum adsorption loss. Imbibition and CT experiments showed that the longer the imbibition distance, the better is the effect on spontaneous imbibition oil recovery. Furthermore, the solubilization coefficient and self-driving force were defined and calculated to quantitatively analyze the imbibition mechanisms. The imbibition mechanisms demonstrate that the reduction of oil/solid adhesion is due to the synergistic effect of IFT reduction and wettability alteration, and the ability to increase the imbibition distance through a larger self-driving force.

Circulating tumor DNA (ctDNA), the tumor-derived cell-free DNA fragments in the bloodstream carrying tumor-specific genetic and epigenetic alterations, represents an emerging novel tool for minimal residual disease (MRD) assessment in patients with resected colorectal cancer (CRC). For many decades, precise risk-stratification following curative-intent colorectal surgery has remained an enduring challenge. The current risk stratification strategy relies on clinicopathologic characteristics of the tumors that lacks precision and results in over-and undertreatment in a significant proportion of patients. Consequently, a biomarker that can reliably identify patients harboring MRD would be of critical importance in refining patient selection for adjuvant therapy. Several prospective cohort studies have provided compelling data suggesting that ctDNA could be a robust biomarker for MRD that outperforms all existing clinicopathologic criteria. Numerous clinical trials are currently underway to validate the ctDNA-guided MRD assessment and adjuvant treatment strategies. Once validated, the ctDNA technology will likely transform the adjuvant therapy paradigm of colorectal cancer, supporting ctDNA-guided treatment escalation and de-escalation. The current article presents a comprehensive overview of the published studies supporting the utility of ctDNA for MRD assessment in patients with CRC. We also discuss ongoing ctDNA-guided adjuvant clinical trials that will likely shape future adjuvant therapy strategies for patients with CRC.

This study investigates the role of oxygen vacancy on Fe-doped CeO₂ catalyst activity for soot oxidation. The oxygen vacancy was assessed through Ce³⁺ content. The Fe content was varied between 0 and 30% for two catalyst preparation methods, co-precipitation (CP) and solution combustion synthesis (SCS). X-ray photoelectron spectroscopy indicates that ceria exists as both Ce₄₊ and Ce₃₊, while iron is present only as Fe₃₊. The catalyst’s activity was evaluated by ignition (T10) and combustion (T50) temperatures using thermogravimetric analysis. Optimum Fe contents yielding the highest activity were found to be 10% and 5% for CP and SCS catalysts, respectively. The surface area and morphology have shown moderate effect on catalyst activity, because catalytic soot oxidation involves solid-solid contact. More importantly, regardless of the fabrication method, it was found that Ce₃₊ content, which is closely related to oxygen vacancies, plays the most important role in affecting the catalyst activity.

Legal research is an indispensable skill for lawyers. Therefore, it is always necessary for lawyers to engage in legal research in due course of trying to alleviate various legal problems. Although the purpose and methodology of the research may vary from lawyer to lawyer, doing research is a common activity. As a result, the quest to assess the impacts of artificial intelligence (hereinafter ‘AI’) on legal research allows one to measure the influence of AI on the legal profession in general. Moreover, with the advent of Legal AI, it is now evident that the legal profession is not immune from disruption. According to the above, this article discusses the impacts of AI on research in the legal profession in general in accomplishing various lawyerly tasks by different legal professionals.

Tremendous progress has been witnessed in artificial intelligence within the domain of neural network backed deep learning systems and its applications. As we approach the post Moore’s Law era, the limit of semiconductor fabrication technology along with a rapid increase in data generation rates have lead to an impending growing challenge of tackling newer and more modern machine learning problems. In parallel, quantum computing has exhibited rapid development in recent years. Due to the potential of a quantum speedup, quantum based learning applications have become an area of significant interest, in hopes that we can leverage quantum systems to solve classical problems. In this work, we propose a quantum deep learning architecture; we demonstrate our quantum neural network architecture on tasks ranging from binary and multi-class classification to generative modelling. Powered by a modified quantum differentiation function along with a hybrid quantum-classic design, our architecture encodes the data with a reduced number of qubits and generates a quantum circuit, loading it onto a quantum platform where the model learns the optimal states iteratively. We conduct intensive experiments on both the local computing environment and IBM-Q quantum platform. The evaluation results demonstrate that our architecture is able to outperform Tensorflow-Quantum by up to 12.51% and 11.71% for a comparable classic deep neural network on the task of classification trained with the same network settings. Furthermore, our GAN architecture runs the discriminator and the generator purely on quantum hardware and utilizes the swap test on qubits to calculate the values of loss functions. In comparing our quantum GAN, we note our architecture is able to achieve similar performance with 98.5% reduction on the parameter set when compared to classical GANs. With the same number of parameters, additionally, QuGAN outperforms other quantum based GANs in the literature for up to 125.0% in terms of similarity between generated distributions and original data sets.

An article's tone and framing not only influence an audience's perception of a story but may also reveal attributes of author identity and bias. Building upon prior media, psychological, and machine learning research, this neural network-based system detects those writing characteristics in ten news agencies' reporting, discovering patterns that, intentional or not, may reveal an agency's topical perspectives or common contextualization patterns. Specifically, learning linguistic markers of different organizations through a newly released open database, this probabilistic classifier predicts an article's publishing agency with 74% hidden test set accuracy given only a short snippet of text. The resulting model demonstrates how unintentional 'filter bubbles' can emerge in machine learning systems and, by comparing agencies' patterns and highlighting outlets' prototypical articles through an open source exemplar search engine, this paper offers new insight into news media bias.