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.

The quality and shelf-life of NCS (Non-centrifugal sugar) mainly depend on the moisture content present in it. NCS formed by the current practice of open sun drying contains moisture substantially greater than the acceptable level of 3%. This paper presents the work taken up to design a tunnel dryer to attain require moisture content in granular NCS for various load conditions. Initially, an experimental investigation had been carried out on a laboratory scale dryer to achieve required moisture content (< 3%) for various load conditions. This experimental data was used for validating two drying models and found that one of the models is best suitable for designing an industrial-scale dryer. For various load conditions on each tray and dryer exit temperature, nine different cases were arrived at. The number of trucks, trays, drying time and energy requirements were computed using the suitable theoretical model. Tunnel dryer with a length of 18 m, a height of 1.2 m, a width of 1 m, number of trucks of 18 and 24 number of trays on each truck was found to be the suitable dryer to dry 1 tone of NCS based on the minimum energy requirement of 176.49 MJ, and a minimum drying time of 68 minutes.

TeamIndus’ Lunar Logistics vision includes multiple lunar missions over the coming years to meet requirements of science, commercial and efforts towards building readiness for crewed missions to Mars in the global exploration roadmap. TeamIndus is the only Indian team that participated in the Google Lunar X Prize. The challenge called for privately funded spaceflight teams to be the first to land a robotic spacecraft on the Moon, travel 500 meters, and transmit back high-definition video and images. The first mission is expected to have a net landed payload capacity of 50 kg. The prime objective is to demonstrate autonomous lunar landing, and operations for a Surface Exploration Rover - to collect data in the vicinity of the landing site. The rover is designed to execute the commands given by the operations manager autonomously. The rover software architecture relevant to the navigation and control is described in detail. The functional modes are defined to functionally distinguish the rover drive. Among the various operations performed by the rover are execution of simple drive steps through navigation and control algorithms. The kinematic model of the rover is studied in the hardware locomotion tests performed. The Kalman filter formulation to estimate the sensor bias and to get attitude estimate is discussed. The structural model and the frame definitions are described in a relevant section. A simple heading control algorithm is designed to control the heading direction of the rover according to the operations requirement. The path planning process and visual odometry processes are described. Finally the SIMULINK$^{\textregistered}$ model is tested on the prototype rover and the test experience results are discussed in the last section.

Natural language Processing (NLP) has significantly transformed in the last decade, especially in the field of Language Modeling. Large Language Models (LLMs) have achieved SOTA performances on Natural Language Understanding (NLU) and Natural Language Generation (NLG) tasks by learning language representation in self-supervised ways. This paper provides a comprehensive survey to capture the progression of advances in Language Models. In this paper, we examine the different aspects of Language Models, which started with a few million parameters but have reached the size of a trillion in a very short time. We also look at how these LLMs transitioned from task-specific to task-independent to task-and-language-independent architectures. This paper extensively discusses different pre-training objectives, benchmarks, and transfer learning methods used in LLMs. It also examines different fine-tuning and In-Context learning techniques used in downstream tasks. It also explores how LLMs can perform well across many domains and datasets if sufficiently trained on a large and diverse dataset. Next, it discusses how, over time, the availability of cheap computational power and large datasets have improved LLM’s capabilities and raised new challenges. As part of our study, we also inspect LLMs from the lens of scalability to see how their performance is affected by the model’s depth, width, and data size. Lastly, we provide an empirical comparison of existing trends and techniques and a comprehensive analysis of where the field of LLM currently stand.

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.

In this digital world, organisations are facing global competition as well as manpower pressures leading towards knowledge economy, which heavily impacts on their local and international businesses. The trend is to foster collaboration and knowledge sharing to cope with these problems. With the advancement of technologies and social engineering that can connect people in virtual world across time and distance, several organisations are embarking on knowledge management (KM) systems, implementing community of practice (CoP) approach. However, virtual communities are relatively new paradigms, and there are several challenges to their successful implementation from an organisation’s point of interest. There is lack of CoP implementation framework that can cater to today’s dynamic business and sustainability requirements. To fill the gap in literature, this paper develops a practical framework for a CoP implementation with a view to align KM strategy with business strategy of an organization. It explores the different steps of building, sharing and using tacit and explicit knowledge in CoPs by applying Wiig KM cycle. It proposes a practical CoP implementation framework that adopts the Benefits-Tools-Organisation-People-Process (BTOPP) model in addressing the key questions surrounding each of the BTOPP elements with a structured approach. Finally, it identifies key challenges such as organizational culture and performance measurements, and provides practical recommendations to overcome them for a successful CoP implementation.

Spider silks, renowned for their exceptional mechanical and biocompatible properties, offer significant potential as scaffolds in tissue engineering. This paper explores the feasibility of using spidroins, the primary proteins in spider silk, to develop scaffolds that closely mimic the extracellular matrix (ECM) essential for tissue regeneration. Spidroins (spider silk proteins) are particularly valuable due to their unique strength, elasticity, and biocompatibility, which support cellular growth and differentiation. The paper examines current methods for producing recombinant spider silk, including using unicellular hosts like E. coli and multicellular systems like transgenic plants and silkworms. It also examines current scaffolds that utilize spidroins and their shortcomings, such as immunogenicity and protein production, which must be urgently addressed for more practical and effective widespread biomedical applications. In addition, it stresses the need for further research to solve these challenges and fully realize the potential of spider silk in biomedical applications.

Increased smart devices in various industries is creating numerous sensors in each of the equipment prompting the need for methods and models for sensor data. Current research proposes a systematic approach to analyze the data generated from sensors attached to industrial equipment. The methodology involves data cleaning, preprocessing, basics statistics, outlier, and anomaly detection. Present study presents the prediction of RUL by using various Machine Learning models like Regression, Polynomial Regression, Random Forest, Decision Tree, XG Boost. Hyper Parameter Optimization is performed to find the optimal parameters for each variable. In each of the model for RUL prediction RMSE, MAE are compared. Outcome of the RUL prediction should be useful for decision maker to drive the business decision; hence Binary classification is performed, and business case analysis is performed. Business case analysis includes the cost of maintenance and cost of non-maintaining a particular asset. Current research is aimed at integrating the machine intelligence and business intelligence so that the industrial operations optimized both in resource and profit.

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.

In this paper, a thermodynamic investigation is done on a Kalina-flash cycle. This work is initially validated with the Kalina cycle power plant, Wich is commissioned in Husavic. Low-temperature Kalina-flash is considered for this study. This cycle is working with the ammonia-water mixture. The Kalina-flash cycle was optimized in the view of exergy and thermal efficiency. A multi-objective genetic algorithm is used to accomplish optimization. The optimum values of the objective functions are observed to be 40.20 and 11.70% respectively. At last, The influence of the separator inlet dryness fraction, basic ammonia mass fraction, temperature and flash pressure ratio on the first and second law efficiencies are analysed.

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.

The field of human microbiome and gut microbial diversity research has witnessed a profound transformation, driven by advances in omics technologies. These advancements have unveiled essential connections between microbiome alterations and severe conditions, spurring the development of new frameworks through epidemiological studies. Traditionally, each individual was thought to harbor unique microbial communities acquired early in life, but recent research challenges this belief. The neonatal microbiome's onset, influenced by factors like delivery mode and maternal health, remains a subject of intense debate, hinting at potential intrauterine microbial processes. In-depth research reveals associations between microbiome profiles and specific health outcomes, ranging from obesity to neurodevelopmental disorders. Understanding these diverse microbiome profiles is essential for unraveling the intricate relationships between the microbiome and health outcomes.

Amyotrophic lateral sclerosis (ALS) disease clusters are found in several countries worldwide. In the United States, ALS clusters are found in many states, largely within the northern United States. The cause of the increased rates of ALS in these areas remains indefinite. It is reported here that many ALS clusters are associated with sites of current or prior glacial lakes, or regions containing an abundance of silts and clay minerals. The potential significance of these findings in ALS is discussed.

Neurodegenerative diseases of protein misfolding affect humans and animals. In humans, these diseases include Alzheimer’s disease (AD), Parkinson’s disease (PD), amyotrophic lateral sclerosis (ALS), and Western Pacific amyotrophic lateral sclerosis and Parkinsonism-dementia complex (ALS/PDC). Mineral exposure may be important in the pathogenesis of protein misfolding cascades. The possible association of bentonite, montmorillonite, and mineral risk factors with Alzheimer’s disease, Parkinson’s disease, ALS, and Western Pacific ALS/PDC is analyzed and discussed.

Colonoscopy is used for colorectal cancer (CRC) screening. Extracting details of the colonoscopy findings from free text in electronic health records (EHRs) can be used to determine patient risk for CRC and colorectal screening strategies. In this study, we developed and evaluated the accuracy of a deep learning model framework to extract information for the clinical decision support system to analyze relevant free-text colonoscopy reports, including indications, pathology, and findings notes. The Bio-Bi-LSTM-CRF framework was developed using Bidirectional Long Short-term Memory (Bi-LSTM) and Conditional Random Fields (CRF) to extract several clinical features from these free-text reports, including indications for the colonoscopy, findings during the colonoscopy, and pathology of the resected material. We then trained the Bio-Bi-LSTM-CRF and existing Bi-LSTM-CRF models on 80% of 4,000 manually annotated notes obtained from the colonoscopy reports of 3,867 patients. The clinical notes were from a group of patients aged over 40 years old enrolled in four Veterans Affairs Medical Centers. A total of 10% of the remaining annotated notes were used to train hyperparameter, while the remaining 10% were used to evaluate the accuracy of our model (Bio-Bi-LSTM-CRF) and to compare the results with the outcomes obtained using Bi-LSTM-CRF. The results of our experiments showed that the bidirectional encoder representations by integrating dictionary function vector from Bio-Bi-LSTM-CRF and strategies character sequence embedding approach is an effective way to identify colonoscopy features from EHR-extracted clinical notes. Therefore, the Bio-Bi-LSTM-CRF model is concluded to be capable of creating new opportunities to identify patients at risk for colon cancer and to study their health outcomes.

It was found that patients with comorbidities of obesity and diabetes have a high risk of breast cancer occurrence and face worse breast cancer outcomes. Though several reports showed the reinforced link between obesity, diabetes, and prediabetes with breast cancer, the underlying molecular mechanism is still unknown. The present study aimed to investigate the underlying molecular link between increased risks of breast cancer due to coincident diabetes or obesity using a spontaneous obese rat model with impaired glucose tolerance (WNIN/GR-Ob rat). A single dose of solubilized DMBA suspension (40 mg/kg body weight) was orally administered to the animals at the age of 60 days to induce breast tumors. The tumor incidence, latency period, tumor frequency, and tumor volume were measured. Histology, immunohistochemistry, and immunoblotting were performed to evaluate the tumor morphology and expression levels of signal molecules. It was observed that the onset of breast tumor and latency period per tumor development were early in GR-Ob rats compared to respective lean rats. It was found that 62% of obese rats were bearing tumors, and in comparison, only 21% of the lean animals developed breast tumors. Overexpression of ER, PR, Ki67, and p53 markers was observed in tumor tissues of obese rats in comparison with lean rats. The levels of the hallmarks of cell proliferation and angiogenesis involved in IGF-1/PI3K/Akt/GSK3β/β-catenin signaling pathway molecules were upregulated in obese rat breast tumors compared to lean rats. Furthermore, obesity with prediabetes is associated with changes in IGF-1 signaling and acts on PI3K/Akt/GSK3β/β-catenin signaling, which results in quick cell proliferation and development of breast tumors in obese rats than the lean rats. These results indicate that the onset of the tumor and its development was faster in a spontaneous obese rat model with impaired glucose tolerance than their lean counterparts, with a higher percentage of tumor incidence.

The discovery of water ice on the moon has revolutionized our understanding of lunar science and has profound implications for future space exploration and habitation. Through a comprehensive analysis of remote sensing data, isotopic studies, and neutron detection experiments, this research elucidates the presence, distribution, and origins of lunar water ice. Radar observations from missions like Clementine and Chandrayaan-1 reveal distinct polar regions with elevated circular polarization ratios, indicative of volatile ice deposits. Spectral detections by instruments such as M3 and Diviner further confirm the presence of water ice in lunar-shadowed regions, with estimates suggesting reserves of up to 300 million tons at the poles. Neutron detection experiments on lunar orbiters like LRO provide additional evidence, detecting hydrogen signals consistent with water ice below the lunar surface. Isotopic analyses offer insights into the origin and evolution of lunar water ice, with comparisons to cometary and asteroidal sources. Proposed missions, such as Artemis-3 and Artemis-4, aim to collect samples from the lunar South Pole for detailed isotopic analysis, furthering our understanding of lunar water ice's composition and history. Scientific data, including the lunar bulk water content and estimated water ice reserves, underscore the significance of lunar water ice as a critical resource for future space exploration endeavors. Calculations estimating the total water-ice area and water abundance near specific lunar features provide valuable insights into the potential utilization of lunar water ice for sustained human presence on the Moon and beyond.

The space exploration landscape has transformed dramatically over the past several decades, with a significant rise in the number of annual launches. Key factors driving this increase include technological advancements, the miniaturization of satellites, and the surge in commercial satellite deployments for communication, Earth observation, and remote sensing. This paper examines the evolution of space activities from the launch of Sputnik 1 in 1957 to recent developments in commercial spaceflight and international collaborations. The paper discusses notable milestones in space exploration history, including early space missions, Apollo Moon landings, and the development of space stations like the International Space Station. It highlights the shift from state-led space programs to a more diverse landscape, characterized by private sector involvement and international partnerships. The "Space 4.0" phase, beginning around 2006, has seen the entry of commercial players like SpaceX, leading to a significant upsurge in orbital launches. Statistical data reveals an upward trend in launch activity, with over 200 launches in 2023 alone, driven by large satellite constellations like SpaceX's Starlink and the steady growth of China's space program. The increasing launch rate poses challenges such as space debris, emphasizing the need for mitigation strategies. Looking ahead, the paper projects a continued increase in launch activity, with over 150 launches expected annually by 2026 and 200-300 launches by 2040. Commercial space ventures, deep space exploration, lunar activities, and space tourism drive this growth. The paper concludes by emphasizing the importance of addressing space debris and promoting the long-term sustainability of space activities, which is crucial as humanity's presence in space continues to expand.

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.

Cancer researchers are fascinated by the chemistry of diverse natural products which show exciting potential as anticancer agents. In this study, we aimed to investigate the anticancer properties of watermelon rind extract (WRE) by examining its effects on cell proliferation, apoptosis, senescence, and global gene expression in human renal cell adenocarcinoma cells (HRAC-769-P) in vitro. Our metabolome data analysis of WRE exhibited untargeted phyto-constituents and targeted citrulline (22.29 µg/mg). HRAC-769-P cells were cultured in RPMI-1640 media and treated with 22.4, 44.8, 67.2, 88.6, 112, 134.4, and 156.8 mg mL-1 for 24, 48, and 72 hrs. At 24 hrs after treatment, (88.6 mg ml-1 of WRE) cell proliferation significantly reduced, more than 34% compared to the control. Cell viability decreased 48 and 72 hours after treatment to 45% and 37%, respectively. We also examined poly caspase, SA-beta-galactosidase (SA-beta-gal), and wound healing activities using WRE. All treatments induced an early poly caspase response and a significant reduction in cell migration. Further, we analyzed the transcript profile of the cells grown at 44.8 mg ml-1 of WRE after 6 hours using RNA sequencing (RNAseq) analysis. We identified 186 differentially expressed genes (DEGs), including 149 upregulated genes and 37 downregulated genes, in cells treated with WRE compared to the control. The differentially expressed genes were associated with NF-Kappa B signaling and TNF pathways. Crucial apoptosis-related genes such as BMF, NPTX1, NFKBIA, NFKBIE, and NFKBID might induce intrinsic and extrinsic apoptosis. Another possible mechanism is a high quantity of citrulline may lead to induction of apoptosis by the production of increased nitric oxide. Hence, our study suggests the potential anticancer properties of WRE and provides insights into its effects on cellular processes and gene expression in HRAC-769-P cells.

Understanding surface water evaporation in tropical catchments is pivotal for effective water management, but limited research exists on stable isotopic (δ2H and δ18O) assessment of water evaporation losses. Our study bridges that gap, examining stable isotopes in meteoric water and surface waters across tropical regions, both humid and semi-arid. Using the Craig-Gordon model, we calibrated evaporation-to-inflow (E/I) ratios, identifying distinct E/I variations between seasons and regions. Notably, the semi-arid region consistently exhibited higher E/I ratios due to climatic characteristics. By integrating the Hamiltonian Monte Carlo and the No-U-Turn Sampler, we were able to quantify uncertainties in isotopic and meteorological parameters, resulting in E/I estimates within 68% and 95% confidence intervals. Our Bayesian model insights are critical for freshwater resource optimization and hydrological modeling in tropical regions.

In this paper, we study the effect of parasitic channel on electrical characteristics and power consumptions of vertically stacked gate-all-around (GAA) silicon nanosheet (NS) MOSFETs of the bulk and silicon-on-insulator (SOI) substrates. Through deliberate control of the bottom parasitic channel coverage, we systematically assess its influence on DC, AC, and RF characteristics including power consumption. The observed findings highlight a significant differentiation among the bottom parasitic channels: GAA (i.e., control sample with 100% coverage), omega-shaped gate NS (70% and 80% coverages), and FinFET (60% coverage). Compared with the device with a 60% coverage channel, the device with a 100% coverage channel possesses 3520% and 8030% normalized leakage current improvement for both NFET and PFET under the bulk substrate, respectively. Compared with bulk-substrate devices, the SOI-substrate devices further significantly improve the leakage current. Due to enhanced off-state current leakages in the 100% covered bulk-substrate device, the static power demonstrates a notable improvement (about 98.1%), compared to 60% covered devices. Hence, the utilization of a 60% covered channel will result in a degradation of both device and circuit performance. The observation of GAA NS MOSFET indicates that an increase in the bottom parasitic channel coverage ratio leads to a positive impact on power consumption and leakage currents. The examination presented here is useful in the fabrication of stacked GAA NS MOSFETs.

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 utilization of medicinal herbs has been steadily increasing globally since the Pandemic. The use of these medicinal plants helps minimize side effects and adverse consequences. As technology evolves, insilico analysis, such as screening, is often employed to figure out the mechanism of action of these medicinal plants. This method takes into account the pharmacokinetics and screening of medicinal plants. The main emphasis is on the profile of Ocimum sanctum Linn using insilico techniques like Swiss ADME. The results of these studies can be utilized to future studies involving in vivo and in vitro studies for establishing the particular activity of medicinal plants.

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.

This review explores the critical difficulties confronting global agriculture in the face of changing climate patterns and limited resources, highlighting the importance of sustainable practices. With agriculture as the largest consumer of water worldwide, sustainable techniques are critical for long-term survival and ecological harmony. Even with advancements, rapid population increase and changing environment conditions demand immediate investment in cutting-edge technologies. Optimizing agricultural operations, increasing output, and reducing resource waste can be achieved through smart farming, which utilizes machine learning and Internet of Things tech-nologies. Particular difficulties like decreasing cultivator proportions and rising costs are empha-sized, with a focus on developing nations where agriculture plays a crucial role in the economy. Additionally, the anticipated rise in food demand highlights how urgent it is to find sustainable alternatives. But problems like inappropriate land and agricultural land fragmentation still exist, necessitating creative solutions. The paper explores how agriculture could be revolutionized by machine learning and IoT-based hydroponics, providing insights into how to improve resilience, productivity, and sustainability in the face of changing environmental and socioeconomic dy-namics. Through a thorough investigation, this paper advances the discussion on sustainable ag-riculture by demonstrating the important role that technology-driven strategies play in addressing concerns about environmental sustainability and global food security.

The arrival of new developments in the field of power electronics circuit’s applications in power systems builds new control strategy to improve voltage quality for power grid by overcome interruptions. Wind energy resources are unconventional resources and get advanced problems to power grid when it is connected. Uncertainty of load sharing, peak energy management, climatic conditions, wind velocity and wind energy injected into power grid leads many of power quality problems on power grid based on the existing guidelines specified in IEC-61400 standard. This system plans efficient operation of DFIG to eliminate the voltage collapse and mismatch frequency to power grid. The DFIG connected diode rectifier and rotor side converter wind generator works as an Efficient Static Synchronous Compensator (E-SATCOM) for supplying the demand of reactive power for power grid to mitigate PQ problems. The benefit of using a combined controller was verified by simulink/Matlab and its simulated results used Doubly Fed Induction Generator (DFIG), wind Turbine. This simulation results gives good quality transient and stable state response to manage and support reactive power for both symmetrical and unsymmetrical faults in connection of grid codes to provide continuous quality of power supply, multiple wind generators are required for 140 bus power grid.

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.

Clairton, Pennsylvania, is home to the largest coke works facility in the United States (US). On 24 December 2018, a large fire occurred at this facility and damaged pollution control equipment. Although repairs were not completed for several months, production continued at pre-fire capacity and daily emissions increased by 24 to 35 times, with multiple exceedances of monitored levels of outdoor air pollution (OAP). The aim of this study was to objectively evaluate the impact of this industrial incident and resultant OAP exceedances on asthma morbidity. We assessed pre-fire and post-fire rate ratios (RR) of outpatient and emergency department (ED) visits for asthma exacerbations among nearby adult residents. Pre-fire versus post-fire RRs increased for both visit types: RR = 1.82 (95% CI: 1.30, 2.53; p < 0.001) and 1.84 (95% CI: 1.05, 3.22; p = 0.032) for outpatient and ED visits, respectively. Additionally, total visit rates increased on days with OAP exceedances: RR = 2.47 (95% CI: 1.52, 4.01; p < 0.0001), 1.58 (95% CI: 1.00, 2.48; p = 0.048) and 1.79 (95% CI: 1.27, 2.54; p = 0.001) for PM_2.5, SO₂, and H₂S exceedance days, respectively. These results show a near doubling of acute visits for asthma exacerbations in nearby adult residents during this industrial incident and underscore the need for prompt remediation and public notification of OAP exceedances to prevent adverse health impacts.

The aim of this article is to discuss the transformative amalgamation of Internet of Things and Machine Learning technologies within the domain of vegetable hydroponic systems for nutrition management. Hydroponics, being an efficient cultivation method, benefits a great deal from the precision and adaptability that machine learning algorithms can offer, along with the real-time monitoring facilitated by the devices using the Internet of Things. This study summarizes the latest research and underlines how ML and IoT may work together, focusing on nutrient optimization, plant development, and resource efficiency. The use of ML algorithms, the function of IoT devices for real-time monitoring, communication protocols, scalability issues, and implementation are among some of the key subjects of the discussion. The research indicates benefits to crop output, efficiency in using resources, and sustainability based on the case studies and the analysis of results. However, ethical problems and some complications concerning data privacy do call for responsible adoptions. The conclusion of this paper provides directions for further research and calls for more investigation into state-of-the-art machine learning approaches and scalable solutions for the re-silient and sustainable future of hydroponic agriculture. The machine learning and deep learning models introduced in this research were evaluated against contemporary studies, revealing an accuracy enhancement ranging from 1.17% to 5.25%, depending on the dataset and algorithm employed. The present study conducts a comparative analysis involving machine learning algo-rithms, indicating that among all the models, the Decision Tree and Gradient Boosting Classifier achieved an accuracy of 99.42% in the dataset by making stage-wise decisions.

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.

Background In 2016, Global Polio Eradication Initiative (GPEI) recommended cessation of type 2 oral poliovirus vaccine (OPV) and OPV using countries switched from trivalent to bivalent OPV (bOPV) with addition of inactivated poliovirus vaccine (IPV) in the routine immunization schedule. The current GPEI strategy 2022-2026 includes bOPV cessation plan and switching to IPV standalone or the combination vaccine schedules in future. The focus of our study was to evaluate immunogenicity of monovalent OPV type 1 (mOPV1) with IPV and IPV only schedules. Methods This was a three-arm, multi-center randomized controlled trial conducted in 2016-2017 in India. Participants, at birth, were randomly assigned to bOPV-IPV (Arm A) or mOPV1-IPV (Arm B) or IPV (Arm C) schedules. Serum specimens collected at birth, 14-, 18- and 22- weeks age were analyzed with standard microneutralization assay for all three poliovirus serotypes. Results Results of 598 participants were analyzed. The type 1 cumulative seroconversion rates four weeks after completion of the schedule at 18 weeks were 99.5% (97.0-99.9), 100.0% (97.9-100.0) 96.0% (92.0-98.1) in Arms A (4bOPV+IPV), B (4mOPV1+IPV) and C (3IPV) respectively. Type 2 and type 3 seroconversion at 18 weeks were 80.0% (73.7-85.1), 76.9% (70.3-82.4), 93.2% (88.5-96.1) and 100.0% (98.0-100.0), 81.9% (75.6-86.8), 99.4% (96.9-99.9) respectively in the three arms. Conclusions This study shows high efficacy of different polio vaccines for serotype 1 in all three schedules. Type 1 seroconversion rate of mOPV1 is non-inferior to bOPV. All the vaccines provide high type specific immunogenicity. The program can adopt the use of different vaccines or schedules depending on epidemiology from time-to-time.

The disruption of brain energy metabolism, leading to alterations in synaptic signaling, neural circuitry, and neuroplasticity, has been implicated in severe mental illnesses such as schizophrenia, bipolar disorder, and major depressive disorder. The therapeutic potential of ketogenic interventions in these disorders suggests a link between metabolic disturbances and disease pathology; however, the precise mechanisms underlying these metabolic disturbances and the therapeutic effects of metabolic ketogenic therapy remain poorly understood. In this study, we conducted an in silico analysis of transcriptomic data to investigate perturbations in metabolic pathways in the brain across severe mental illnesses via gene expression profiling. We also examined dysregulation of the same pathways in rodent or cell culture models of ketosis, comparing these expression profiles to those observed in the disease states. Our analysis revealed significant perturbations across all metabolic pathways, with the greatest perturbations in glycolysis, the tricarboxylic acid (TCA) cycle, and the electron transport chain (ETC) across all three disorders. Additionally, we observed some discordant gene expression patterns between disease states and ketogenic intervention studies, suggesting a potential role for ketone bodies in modulating pathogenic metabolic changes. Our findings highlight the importance of understanding metabolic dysregulation in severe mental illnesses and the potential therapeutic benefits of ketogenic interventions in restoring metabolic homeostasis. This study provides insights into the complex relationship between metabolism and neuropsychiatric disorders and lays the foundation for further experimental investigations aimed at appreciating the implications of the present transcriptomic findings as well as developing targeted therapeutic strategies.

This paper explores the development of life support systems (LSS) for human space exploration, emphasizing the need for sustainable solutions to support long-term missions beyond Low Earth Orbit. As humanity seeks to explore and potentially colonize distant planets, maintaining a habitable environment in space poses significant challenges. Life support systems must manage air quality, water supply, temperature, humidity, and waste while ensuring crew safety in environments devoid of breathable air and exposed to harmful cosmic radiation. The International Space Station's (ISS) Environmental Control and Life Support System (ECLSS) represents a significant advancement, demonstrating that humans can live in space for extended periods with a combination of recycling and Earth-based resupply. However, future missions to the Moon, Mars, and beyond require more advanced, self-sustaining systems. This paper examines technological advancements such as closed-loop systems, bio-regenerative life support systems (BLSS), and In-Situ Resource Utilization (ISRU), focusing on their potential to reduce reliance on Earth-based resupply. Projects like NASA's Mars Oxygen In-Situ Resource Utilization Experiment (MOXIE) and ESA's MELiSSA initiative offer promising solutions for future deep space exploration. By enhancing recycling, integrating ISRU, and improving energy efficiency, future life support systems will support humanity's journey into the cosmos, paving the way for sustainable space exploration and eventual colonization.

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

In this empirical article, we argue that, while emergency remote teaching (ERT) may have achieved its goal of saving the academic years during the COVID-19 pandemic, it also constructed unintended pedagogical consequences that were possibly overlooked at the time of advocating it. The research question that the article attempted to answer is, what unintended pedagogical consequences did students and lecturers suffer because of the move to ERT at rural-based universities (RBUs) in South Africa? Drawing on students' and lecturers’ lived experiences of ERT, this article foregrounds unintended pedagogical consequences that arose at one RBU in South Africa during the transition from face-to-face teaching to ERT. Underpinned by the tenets of critical realism philosophy, as well as student integration theory, in-depth interviews with three lecturers and six students were conducted. The findings of the study indicate that home conditions, individual characteristics, pre-COVID-19 blended learning experiences, university training and support, and teaching, learning, and assessment practices and policies altogether contributed to the construction of unintended pedagogical consequences of ERT presented in this article. These consequences include (1) exclusion of low-income students in active teaching and learning, (2) equipping middle-class students with better chances of success than working-class students. (3) distressing female students and lecturers more than their male counterparts, and (4) unproductive assessment practices. This study may be beneficial to academics and policymakers from similar contexts in their plight to continue with remote teaching and assessment (RTA) beyond the pandemic.

(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.

PM-Gati-Shakti Initiative, integration of ministries, including railways, ports, waterways, logistic infrastructure, mass transport, airports, and roads. Aimed at enhancing connectivity and bolstering the competitiveness of Indian businesses, the initiative focuses on six pivotal pillars known as "Connectivity for Productivity": comprehensiveness, prioritization, optimization, synchronization, analytical, and dynamic. In this study, we explore the application of these pillars to address the problem of "Maximum Demand Forecasting in Delhi." Electricity forecasting plays a very significant role in the power grid as it is required to maintain a balance between supply and load demand at all times, to provide a quality electricity supply, for Financial planning, generation reserve, and many more. Forecasting helps not only in Production Planning but also in Scheduling like Import / Export which is very often in India and mostly required by the rural areas and North Eastern Regions of India. As Electrical Forecasting includes many factors which cannot be detected by the models out there, We use Classical Forecasting Techniques to extract the seasonal patterns from the daily data of Maximum Demand for the Union Territory Delhi. This research contributes to the power supply industry by helping to reduce the occurrence of disasters such as blackouts, power cuts, and increased tariffs imposed by regulatory commissions. The forecasting techniques can also help in reducing OD and UD of Power for different regions. We use the Data provided by a department from the Ministry of Power and use different forecast models including Seasonal forecasts for daily data.

In the present scenario of increased industrialization and transportation in the world leads to increased consumption of fossil fuels which in turns leads to depletion of fossil fuels at a faster rate. Fossil fuels combustion is the dominant source for greenhouse gases and global warming. In view of energy crisis raised in 1970’s and environmental concern, many researches are directed towards search of alternative fuels which can replace consumption of fossil fuels as well as reduce pollution. In developing countries like India which is agriculture land the best alternative fuels are biodiesel and ethanol as they are produced from renewable feedstocks like sugarcane, corn etc. and they are also less hazardous to environment because of lower emission property. Ethanol blends results in significant reduction of emissions of hydrocarbon (HC), carbon monoxide (CO) and particulates matter but increase in nitrogen oxides (NOx). The main purpose of ethanol addition is to reduce the viscosity of biodiesel blends. This paper represents significance of Compression Ratio(CR) on performance, combustion and emission of single cylinder four stroke CI diesel engine by using various compression ratios such as 17.5:1, 18.5:1 and 19.5:1. Experimental research has been conducted with four types of ethanol blends, namely E10, E20, E30 and E40. Ethanol-biodiesel mixture mixed with 2% emulsifier 1% diethyl carbonate and 1% ethyl acetate to maintain similarity and to avoid phase separation. Ethanol subjected to high compression ratio has been used to increase brake thermal efficiency (BTE). The compression ratio has been increased to improve the combustion and performance of the diesel engine.

Kaposi sarcoma is the most common neoplasm associated with Human Immunodeficiency Virus (HIV) infection. Most patients with a confirmed diagnosis experienced limited disease progression. We describe the case of a 49-year-old African American male with a rare presentation of disseminated Kaposi sarcoma as determined by multi-organ work-up. The patient’s cutaneous manifestations involved several hyperpigmented skin lesions, but the worsening of his respiratory symptoms coupled with unexplained weight loss led providers to develop a high suspicion for disseminated disease progression. This case highlights the need to increase awareness of atypical Kaposi sarcoma presentation.

An Indo-French campaign was conducted during May 2014 at Gadanki (13.5^oN, 79.2^oE), India, for investigating gravity wave (GW) coupling between the lower and middle atmospheres using a suite of experimental techniques. In this paper we are presenting the sources for those GWs which are observed at airglow layer (~87 km) using (OH) Airglow Imager during the campaign. For this purpose we have developed a background model atmosphere by combining the ERA-Interim, MSIS E 90 model and HWM 07 model data sets. Uniqueness of the present study lies in using near-real time background atmosphere data from simultaneous radiosonde and SVU Meteor Radar covering both source and propagation/ dissipation regions of GWs. We have observed 17 wave events and used GROGRAT model for reverse tracing to locate the source(s). When we searched for the sources near the terminal points or along the ray path, deep convection is found to occur but no strong wind shear. This indicates that the source for the observed GWs is deep convection. We have also simulated small scale waves that can reach mesosphere during different seasons (background conditions). GWs with periods less than 100 minutes and horizontal wavelengths less than 200 km are mostly reaching the mesospheric altitudes. Interestingly, it is found that only few GWs that are generated in the troposphere reach the mesospheric altitudes during the monsoon season, though strong sources like convection and wind shear persist throughout this season. Thus, background wind plays significant role in deciding the propagation of GWs in to upper atmosphere.

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.

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.

The electrical signal of micro-transducers operating in electrically conductive fluids must be effectively isolated from the surrounding environment while remaining in contact for sensing purposes. A thermally actuated MEMS viscosity sensor uses a buried resistive heat element for actuating a thin silicon membrane whose movement is monitored with embedded piezoresistive elements since the frequency response and behavior of the membrane are used to correlate the viscosity of the fluid being tested. The post-processing materials, (1) Parylene-C, (2) flouroacrylate-based polymer, and (3) nitrocellulose-based polymer, were coated as thin layers of waterproofing materials on different sensors. All three coating materials provided adequate protection when they were used to waterproof the sensors when tested under normal operating conditions. Although the vibration response of the sensors was slightly modified, it did not affect their functionality in a significant way when measuring conductive fluids based on glycerol-water mixtures. All the treated sensors lasted over 1.2 million actuations without any decay in performance or failures. When the test bias conditions were increased by 5x to accelerate failures, the flouroacrylate-based polymer samples lasted 2x longer than the others. Visual analysis of the failures indicates that the edge of the diaphragm, which undergoes the most significant stress and strain values during actuation, was the location of the mechanical failure. This work guides post-processed waterproofing coatings for micro-scale actuators operating in harsh and damaging environments.

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.

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.

Inflammation is an underlying problem for many disease states and has been implicated in iron deficiency (ID). This study aimed to determine whether iron status is improved by epigallocate-chin-3-gallate (EGCG) through reducing inflammation. Thirty-two male Sprague-Dawley rats were randomly divided into four groups (n = 8 each): positive controls, negative controls, lipo-polysaccharide (LPS, 0.5 mg/kg body weight), and LPS + EGCG (LPS plus 600 mg EGCG/kg diet). Iron status, hepcidin, C - reactive protein (CRP), serum amyloid A (SAA), and interleukin-6 (IL-6) were measured. There were no differences in treatment groups compared with control in CRP, hepcidin, and liver iron concentrations. Serum iron concentrations were significantly lower in the LPS (p=0.02) and the LPS+EGCG (p=0.01) than in the positive control group. Compared to the positive control group, spleen iron concentrations were significantly lower in the negative con-trol (p<0.001) but not with both LPS groups. SAA concentrations were significantly lower in LPS + EGCG group compared to LPS alone group. IL-6 concentrations were significantly higher in LPS+EGCG (p= 0.004) than in any of the three groups. EGCG reduced SAA concentrations but did not affect hepcidin or improve serum iron concentration or other iron markers.

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.

Intestinal Parasitic infections are one of the most common infections in tropics. There is paucity of data on prevalence of intestinal parasite infections among migrant construction workers and their house holds so this study was taken up. A cross sectional study was conducted for eight months with an aim to determine the prevalence and assess the associated risk factors among the households of migrant construction workers at AIIMS Bhopal. A semi-structured interview questionnaire survey was conducted prior to collection of stool samples. Each stool sample was examined macroscopically followed by occult blood testing. Wet mount observation was followed by modified acid fast staining and formal ether sedimentation. Recruits with pathogenic parasites in any of the three samples were considered positive and treated as per the national guidelines for age, drug and dose by clinical consultation. 361 participants were recruited. 122/361 (33.8%) were between 21 to 30 years. 55.2% females, 47.4% had occupation of digging soil, 93.1% practiced open field defecation. 36.9% (133/361) was the prevalence of intestinal parasitic infection. 88.7% monoinfection, E.histolytica/dispar (41%) and H.nana( 10.2%) were most prevalent parasites. 26.7%) was commonest. 11.28%coinfection, G. intestinalis with A. duodenale (26.7%) was commonest. In our study only hand washing was independent predictor having Odds Ratio of 3.6 with confidence interval 1.00-13.00(those who don’t wash hands before meals are 3.6 times more likely to develop infection). Only few studies address migrant construction workers, their nomadic behaviour makes them vulnerable for intestinal parasitic infections and not benefitting from prevention programmes as deworming programme.

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.

One of the most frequent brain diseases, Alzheimer's is defined by poor cognitive function brought on by the build-up of Beta Amyloid plaques and the gradual death of neurons. Glucose metabolism and the development of amyloid plaques are being studied together. Under physiologically normal circumstances, glucose is the primary substrate for the adult human brain. The prodromal phases of AD are significantly influenced by glucose hypometabolism. Hypometabolism of glucose in the brain is a clear sign of mitochondrial dysfunction and bioenergetic system impairment. By regulating energy synthesis and cell death, mitochondria play a crucial role in the functioning of cells. Increased formation of reactive oxygen species (ROS) and oxidative stress are a result of mitochondrial dysfunction, which also accelerates the development of Alzheimer's disease. For the maintenance of balance, autophagy is crucial because it selectively destroys damaged mitochondria. AD affects this route for mitochondrial breakdown. Targeting specific mitochondrial ligands by interventions along this pathway might be a useful therapeutic approach. Due to a number of biological obstacles, this method has significant limitations. As a result, many nanocarriers have been created to improve drug delivery effectiveness. All potential nanotechnology-based treatments for AD have been examined in this study, with a particular emphasis on medication delivery to the mitochondria

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.

Background: The novel coronavirus (COVID-19) infection is primarily transmitted through respiratory droplets from an infected person and contact with tainted surfaces or items. Social distancing became the primary measure of preventing the spread of COVID-19, with the principal aim being to reduce the probability of contact with an already infected person. Social distancing can be distressing, as it is against the community's way of life. Saudi Arabia imposed a curfew and suspended all religious, entertainment, sporting, and mass congregations. The daily updates on COVID-19 infection and mortality are upsetting and further, aggravate depression and anxiety. With this background, this study was planned with the following objectives. To determine the sociodemographic profile of the study participants, to find the prevalence of psychological morbidity, and to measure the association between the sociodemographic details, COVID-19 associated factors, and psychological effects among Abha citizens during the COVID-19 pandemic. Methodology: A descriptive cross-sectional community-based study was conducted in the Abha city population from August 2021 to July 22. This study followed snowball sampling, the data was collected using an online Google form the link was shared in WhatsApp groups and through emails to contacts, asking friends to share it with their friends, until reaching the adequate sample size the responses were accepted. Results: A total of 530 participated, and their age ranged from 19 -70 years. Many of the participants (34.5%, n=183) belonged to 36-45 years old. Most of the responders were 69.8% married and Females (69.2%, n=367). Half of the participants had been quarantined (49.6%), and 51.5% were scared from fear of COVID-19. 64.8% of the participants had depression; 14.2%, 20.8%, 13.6%, and 16.2% had mild, moderate, severe, and extremely severe depression, respectively. Around 58.2% of participants suffered from anxiety; 5.8% experienced mild anxiety, 21.7% moderate anxiety, and 30.7% severe anxiety. The proportion of stress among the participants was 45.0%; 10.8% had mild stress, 9.4% had moderate stress, and 24.5% had severe to extremely severe stress. Conclusions: COVID-19 poses mental health problems among individuals and communities. There is a need to find the more susceptible individuals for mental health issues or other psychological disorders. Mental health and psychological problems can be resolved with health education, counseling, and appropriate interventions to curb the negative health impacts of COVID-19.

This paper aims to investigate the criteria of behaviour of certain type of third order neutral generalized difference equations with distributed delay. With the technique of generalized Riccati transformation and Philos-type method, some oscillation criteria are obtained to ensure convergence and oscillatory solution of suitable example is listed to illustrate the main result.

The authors intend to establish new oscillation criteria for a class of generalized third order functional difference equation of the form \begin{equation}{\label{eq01}} \Delta_{\ell}\left(a_2(n)\left[\Delta_{\ell}\left(a_1(n)\left[\Delta_{\ell}z(n)\right]^{\beta_1}\right)\right]^{\beta_2}\right)+q(n)f(x(g(n)))=0, ~~n\geq n_0, \end{equation} where $z(n)=x(n)+p(n)x(\tau(n))$. We also present sufficient conditions for the solutions to converges to zero. Suitable examples are presented to validate our main results.

The technologies influencing alternative ways of transportation are augmenting in recent years as the need for transportation is increasing rapidly due to urbanization and motorization. In this paper, a solar powered electric auto-rickshaw (SPEA) is designed and developed for Indian conditions. The developed vehicle is comprehensively analyzed techno-economically for its viability in the Indian market. The performance analysis of SPEA results in an optimal charging rate of 2 kWh per day with an average solar irradiance of 325 W/m2. The discharging characteristics are studied based on different loading conditions. The vehicle achieved a maximum speed of 21.69 km/h with battery discharge rate of 296W at 90kg load and also reached a maximum discharge rate of 540W at 390kg loading with a maximum speed of 12.11 km/h. The environmental analysis of SPEA displayed yearly CO2 emissions of 1,777 kg, 1,987 kg and 1,938 kg using Compressed Natural Gas, Liquefied Petroleum Gas and gasoline engines respectively can be mitigated using SPEA. The results of financial analysis of SPEA were welcoming as the investor gets 24.44% lesser payback duration compared to gasoline run vehicle. Socio-Economic analysis of SPEA discussed its significant advantages and showed 18.73% and 3.9% increase in yearly income over gasoline driven and battery driven vehicles.

Contamination of soil and crops with heavy metals (HMs) poses a significant environmental challenge in the United States. Hence, this study aimed to assess HM contamination levels from sampled Ohio and West Virginia soils using various pollution indicators analyses, including Enrichment Factor (EF), Geo-accumulation index (lgeo), Contamination Factor (CF), and Pollution Load Index (PLI) and identify the Translocation Factor (TF) of HMs in the edible part of the vegetables and further evaluate health risks associated with dietary exposure through estimations of Estimated Daily Intake (EDI), Hazard Index (HI), Target Hazard Quotient (THQ), Cancer Risk (CR) and Target Cancer Risk (TCR) on adults and children. In this study, Fe was the most predominant contaminant, ranging from 28.41 to 67.36 g/kg in the soil. Cancer risk assessment revealed that Ni poses significant risks. Therefore, regular monitoring of metal concentrations in soil and vegetables grown in these regions might mitigate potential health hazards in the future.

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.

Introduction: In the marginalised countries most neglected health issue is Newborn mortality. A study was undertaken to assess the influence of factors and newborn care practices influencing newborn health in the rural area of Bareilly district. Methodology: The Descriptive cross-sectional study was organized in the rural areas of Bareilly. Study participants were selected based on the mothers who gave birth to a baby during the last six months. The mothers who delivered in that area within six months were included, and using the semi-structured questionnaire, data was collected. Data analyzed using Microsoft Excel and SPSS 2021 version for windows. Results: Mothers initiating early breastfeeding were more commonly 78 (52.3%) observed in the younger mothers at 24-29 years, followed by 48(32.3%) at 30-35 years, the difference was statistically significant (p<0.05). Delayed bathing was observed in nearly 125 (70.1%) three fourth in the age of 24-29 years, followed by 29 (16.8%) in the age period 30-35 years. It was observed that unsafe cord care practices were observed more among 8(53.4%) nuclear families than 7(46.6%) joint families, and it was found to be statistically insignificant. Conclusion: The practice of essential newborn care still needs to improve in Bareilly; there is a need to create awareness to the mothers and family members on newborn and early neonatal care aspects, such as promoting exclusive and early initiation of breastfeeding and delayed bathing practices.

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.

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.

This study aims to assess using a smartphone app (DecibelX), as a noise measuring alternative to the more costly traditional use of measuring noise levels with a Sound Level Meter (SLM). The study compares the accuracy of the app to readings taken with a SLM and dosimeter, and also evaluates the app’s performance for pure tone and narrow band noise. And a usability study identifies strengths and weaknesses related to usability of the app.

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.

Alternative splicing (AS) is a gene regulatory mechanism modulating gene expression in multiple ways. AS is prevalent in all eukaryotes including plants. AS generates two or more mRNAs from the precursor mRNA (pre-mRNA) to regulate transcriptome complexity and proteome diversity. Advances in next-generation sequencing, omics technology and bioinformatics tools, and computational methods provide new opportunities to quantify and visualize AS-based quantitative trait variation associated with plant growth, development, reproduction, and stress tolerance. Domestication, polyploidization and environmental perturbation may evolve novel splicing variants associated with agronomically beneficial traits. To date, pre-mRNAs from many genes are spliced into multiple transcripts that cause phenotypic variation for complex traits, both in model plant Arabidopsis and field crops. Cataloguing and exploiting such variation may provide new paths to enhance climate resilience, resource-use efficiency, productivity, and nutritional quality of staple food crops. This review provides insights into AS variation alongside gene expression analysis to select for novel phenotypic diversity for use in breeding programs. AS contributes to heterosis, enhances plant symbiosis (mycorrhiza and rhizobium), and provides a mechanistic link between the core clock genes and diverse environmental clues.

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.

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.

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.

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.

Coproporphyrins I and III (CP-I and CP-III) are established as substrates of hepatic sinusoidal organic anion transporting polypeptides (Oatps), multidrug resistance-associated protein 3 (Mrp3), and canalicular transporter Mrp2. We aimed to evaluate the potential of plasma CP-I and CP-III concentrations to indicate functional changes in hepatic transporters in nonalcoholic stea-tohepatitis (NASH) rodent models using modeling and simulation approach. Mechanistic copro-porphyrins (CP-I and CP-III) models in rats and mice were constructed based on metabolism, transport, and elimination pathways in rodents. To parameterize the rat mechanistic model, we measured CP concentrations in plasma, liver, bile, and urine in healthy control Sprague Dawley rats. The mouse mechanistic model was parameterized using published data. The rat and mouse CP models described the steady-state levels of CP-I and CP-III in plasma, liver, and bile. The model recapitulated the observed high plasma CP-III / CP-1 ratio (9- and 3-fold in rats and mice, respec-tively) and elimination pathways of CP-I (>90% via biliary secretion) and CP-III (equal via bile and urine). Rat CP model was further validated with the published rat fistula model. The simulated increased plasma CP-I concentrations (4-fold), resulted from decreased Oatp activity (0.6-fold) and increased Mrp3 activity (3-fold) were comparable to those observed in bile-duct ligated NASH model. Sensitivity analysis revealed that 90% inhibition of Oatp and Mrp2 leads to a 4-fold and 2.5-fold increase in plasma CP-I levels, respectively. Additionally, we demonstrated the utility of the mechanistic CP models in testing hypothesis and understanding the mechanisms of the ob-served plasma CPs disposition in the Oatp knockout (KO) mice, bile-duct ligation NASH mice, and Mrp2 deficient TR- rats. Collectively, using a mechanistic model, we conclude that CP-I is a robust and predictable marker for assessing change in the activity of Oatps and Mrps in animal models. Our analysis suggests that efflux transporters (Mrp2 and Mrp3) can play an important role in the disposition of CP-I along with Oatp transporters in rodents.

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.

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.

Toxins present in cigarette and e-cigarette smoke constitute a significant cause of illnesses and are known to have fatal health impacts. Specific mechanisms by which toxins present in smoke impair cell repair are still being researched and are of prime interest for developing more effective treatments. Current literature suggests toxins present in cigarette smoke and aerosolized e-vapor trigger abnormal intercellular responses, damage mitochondrial function, and consequently disrupt the homeostasis of the organelle’s biochemical processes by increasing reactive oxidative species. Increased oxidative stress sets off a cascade of molecular events, disrupting optimal mitochondrial morphology and homeostasis. Furthermore, smoking-induced oxidative stress may also amalgamate with other health factors to contribute to various pathophysiological processes. An increasing number of studies show that toxins may affect mitochondria even though exposure to secondhand or thirdhand smoke. This review assesses the impact of toxins present in tobacco smoke and e-vapor on mitochondrial health, networking, and critical structural processes including mitochondria fission, fusion, hyperfusion, fragmentation, and mitophagy. The efforts are focused on discussing current evidence linking toxins present in first, second, and thirdhand smoke to mitochondrial dysfunction

Background: MicroRNAs are short non-coding RNAs that have an essential role in controlling gene expression at the post-transcriptional level. Additionally, they can serve as biomarkers in the management of obesity. Circulating levels of miRNAs have been shown to fluctuate with exercise, exhibiting a variety of physiological and biological consequences on the biological systems, including structural and functional changes. Aim: The purpose of this study is to evaluate the profile of Ci-miRNAs 423-5p and 128-1 in young obese adolescents before and after aerobic exercise, as well as to analyse the relationship between those microRNAs and obesity-related parameters in response to aerobic exercise training. Methods: A total of 64 adolescent individuals (32 obese & 32 healthy individuals) were enrolled in the study to participate in 6-month aerobic exercise program. Anthropometric measurements, biochemical parameters and blood samples were collected from all the participants prior to exercise training and after 6-month exercise program. Gene expression analysis of the study participants was performed using quantitative real-time PCR. Results: Expression levels of circulating microRNAs 423-5p(p<0.01) & 128-1(p<0.01) were significantly differed before and after exercise in study population. Circulating miRNA 423-5p increased and correlated significantly with BMI while Circulating miRNA 128-1 decreased and correlated significantly with BMI after 6-month aerobic exercise program. Logistic regression statistics proves that the elevation in the expression of miRNAs genes has a strong significant association with elevation of the cytokines IL-6 & TNF-α (p<0.05). Conclusion: Obesity leads to alterations in Ci-miRNA 423-5p & Ci-miRNA 128-1 expressions and significant alterations associated with the aerobic exercise program shows that these miRNAs can be used as diagnostic and target predictive biomarkers in obesity.

Alzheimer’s disease (AD) is a neurodegenerative disorder characterized mainly by the gradual decay in neuronal function as a consequence of diverse degenerating events primarily including mitochondria dysfunction and cascades of neuro-immune reactions. Besides the acquired harmful reactive oxygen species (ROS), neurotoxins, and amyloid-beta (Aβ) and TAU pathologies in neurons, accumulating evidence with time underlined the roles of cytokines and growth factors in the AD pathogenesis. It may help us in evaluating the propensities and specific mechanism(s) of cytokines and factors impacting neuron upon apoptotic decline. Proinflammatory cytokines often induce inflammation in AD and AD-like pathogenesis in response to the apoptotic scenarios where some growth factors are involved in cytokinetic reactions to activate microglia and causing inflammation in AD. In this report, we comprehensively reviewed role of cytokines and chemokines in immune response to AD and neuropsychiatry. We provided insights into the neuroinflammation and the role of diverse factors including the pro-/anti-inflammatory cytokines, APP, TAU phosphorylation, glycation end products, complement system, and the role of glial cells. Also, we discussed the pathogenic and protective role of macrophage migration inhibitory factors, choroid plexus-, neurotrophic- and hematopoietic -related growth factors in AD. We further shed light on the availability and accessibility of the cytokines across the blood-brain barrier in AD pathophysiology. Taken together, the emerging role of these factors in AD pathology emphasized the importance of building novel strategies for an effective therapeutic/neuropsychiatric management of AD in clinics.

Recent developments in the field of room temperature ferromagnetic metal oxide semiconductors (RTFMOS) have shown promising potential for improved photocatalytic performance. This review focuses on the combined study of photocatalytic and ferromagnetic properties at room temperature, with a particular emphasis on metal oxides, such as TiO2, which have emerged as a key area of interest in the domains of magnetism and environmental remediation. Despite extensive research over the years, the precise mechanism behind the interplay of ferromagnetism and photocatalysis in these materials remains incompletely understood. Several critical factors contributing to magnetism have been hinted at, including oxygen vacancies and various metal doping. Numerous reports have demonstrated that these factors play a primary role in room temperature ferromagnetism and photocatalysis in wide-band-gap metal oxides. However, establishing a direct correlation between magnetism, oxygen vacancies, dopant concentration, and photocatalysis has proven challenging. This review aims to provide a comprehensive overview of the recent progress in understanding the magnetism and photocatalytic behaviour of metal oxides. By examining the latest findings, this study sheds light on the potential of RTFMOS as effective photocatalysts, thereby contributing to advancements in environmental remediation and related applications.

In this work we develop a new algorithm for efficient computation of the Voigt/complex error function. In particular, in this approach we propose a two-domain scheme where number of the grid-points is dependent on the input parameter $y$. The error analysis we performed shows that the MATLAB implementation meets the requirements for radiative transfer applications involving the HITRAN spectroscopic database. The run-time test shows that this MATLAB implementation provides rapid computation especially at smaller range of the parameter x.

Quality of Service (QoS) metrics deal with network quantities, e.g. latency and loss, whereas Quality of Experience (QoE) provides a proxy metric for end-user experience. Many papers in the literature have proposed mappings between various QoS metrics and QoE. This paper goes further in providing analysis for QoE versus bandwidth cost. We measure QoE using the widely accepted Mean Opinion Score (MOS) rating. Our results naturally show that increasing bandwidth increases MOS. However, we extend this understanding by providing analysis for internet access scenarios, using TCP, and varying the number of TCP sources multiplexed together. For these target scenarios our analysis indicates what MOS increase you get by further expenditure on bandwidth. We anticipate that this will be of considerable value to commercial organizations responsible for bandwidth purchase and allocation.

According to Copenhagen interpretation, a quantum particle can exist in a superposition of all possible states, out of which only one state is observed when it is measured. Interestingly, it has been observed that interaction with the quantum particle during measurement can also affect the outcome of the state. A scheme for interaction free measurement was proposed by Elitzur and Vaidman [Found. Phys. 23, 987 (1993)], where they used Mach Zehnder interferometer to detect whether a bomb is alive or dead. In 25 % of the cases they were able to detect that the bomb is alive without exploding it. Here, we demonstrate the above experiment using quantum computing, which can be realized in a quantum computer designing quantum circuits on it. We explicate all the cases, including whether the bomb is alive or dead by proposing new quantum circuits and executing those in QISKit as provided by IBM Quantum Experience platform and verify the obtained results.

The Thailand automotive industry grapples with complex challenges in service parts management, demanding a strategic approach for post-sales operations. This research unveils a tailored methodology, leveraging historical sales data, refined part classifications, and strategic decision rules. A high-level overview of the automotive supply chain emphasizes interconnected stakeholders. The systematic methodology delves into part categorization, decision rules, and data analysis. Decision rule outcomes, exceptions, and contingency solutions showcase efficacy. A cost impact assessment highlights substantial savings. Visualization tools offer nuanced perspectives. Optimized service parts classification, robust stocking decision rules, and cost-effective strategies emerge. Support Vector Regression excels in forecasting, with recommendations for dynamic stocking. Implications extend to the broader industry, offering efficiency and service quality blueprints. Acknowledging limitations and suggesting future research, this study contributes a valuable framework for Thai automotive service parts management.

Growing food autonomously on Mars is challenging due to the Martian soil's low nutrient content and high salinity. Understanding how plants adapt and evaluating their nutritional attributes are pivotal for sustained Mars missions. This research delved into the regeneration, stress tolerance, and dietary metrics of sweet potato (Ipomoea batatas) across different Mars Global Simulant (MGS-1) concentrations (0, 25, 50, and 75%). In our greenhouse experiment, 75% MGS-1 concentration most significantly inhibited sweet potato growth, storage root biomass, and chlorophyll content. This concentration also elevated plant tissues' H2O2, proline, and ascorbic acid levels. Higher MGS-1 exposures (50 and 75%) notably boosted vital amino acids and sugar groups in the plant's storage roots. Yet, increased MGS-1 concentrations notably diminished the total C: N ratio and elemental composition in both vines and storage roots. In summary, sweet potato exhibited optimal growth, antioxidant properties, yield, and nutrient profiles at 25% MGS-1 exposure, compared to higher concentrations. This study underscores the need for future interventions, like nutrient enhancement and controlled metal accessibility, to render it a suitable plant for space-based studies.

The heavy-metal-associated (HMA) proteins are a class of PB1-Type ATPases related to the intracellular transport and detoxification of metals. However, due to a lack of information regarding the HMA gene family in the Cucurbitaceae family, a comprehensive genome-wide analysis of the HMA family was performed in ten Cucurbitaceae species: Citrullus amarus, Citrullus colocynthis, Citrullus lanatus, Citrullus mucosospermus, Cucumis melo, Cucumis sativus, Cucurbita maxima, Cucurbita moschata, Cucurbita pepo, and Legenaria siceraria. We identified 103 Cucurbit HMA proteins with various members, ranging from 8 (Legenaria siceraria) to 14 (Cucurbita pepo) across species. The phylogenetic and structural analysis confirmed that the Cucurbitaceae HMA protein family could be further classified into two major clades: Zn/Co/Cd/Pb and Cu/Ag. GO annotation-based subcellular localization analysis predicted that all HMA gene family members were localized on membranes. Moreover, the analysis of conserved motifs and gene structure (intron/exon) revealed the functional divergence between clades. Interspecies microsynteny analysis demonstrated that maximum orthologous genes were found between species of the Citrullus genera. Finally, nine candidates HMA genes were selected, and their expression analysis was carried out via qRT-PCR in root, leaf, flower, and fruit tissues of C. pepo under arsenic stress. The expression pattern of the CpeHMA genes showed a distinct pattern of expression in root and shoot tissues, with a remarkable expression of CpeHMA6 and CpeHMA3 genes from the Cu/Ag clade. Overall, this study provides insights into the functional analysis of the HMA gene family in Cucurbitaceae species and lays down the basic knowledge to explore the role and mechanism of the HMA gene family to cope with arsenic stress conditions.

Introduction: Endoscopic biliary stenting is a widely utilized procedure in the realm of interventional gastroenterology, primarily employing plastic stents for short-term biliary drainage. This case series endeavours to investigate the occurrence and ensuing clinical ramifications of forgotten or retained biliary stents. Methods: Carried out over an 8-month duration at King George Hospital in Visakhapatnam, this case series encompasses 12 patients diagnosed with forgotten biliary stents. Diagnostic confirmation was established through a combination of X-ray, abdominal ultrasound, and magnetic resonance cholangiopancreatography (MRCP). Four patients experienced complications such as fractured distal pigtails and obstructed stents, thwarting retrieval efforts via endoscopic retrograde cholangiopancreatography (ERCP) and cholangioscopy. Results: This case series featured 12 patients with a median age of 48 years (range: 18-76), comprising 7 females (58.3%) and 5 males (41.7%). The primary indication for initial stent placement was choledocholithiasis in 10 instances (83.3%), while benign biliary strictures accounted for 3 cases (25%). On average, patients presented 31.3 months post-initial stenting, primarily manifesting cholangitis symptoms (83.3%). ERCP succeeded in stent removal in 8 cases (66.6%), while the remaining cases necessitated advanced procedures such as cholangioscopy, with two patients being referred for surgical intervention. It is noteworthy that there were no instances of mortality. Conclusion: This case series, conducted against the backdrop of the COVID-19 pandemic, highlights an increased prevalence of neglected plastic biliary stents. The principal complication encountered was cholangitis, often coexisting with common bile duct (CBD) stones. Standard ERCP techniques demonstrated reduced efficacy in instances characterized by fractured, obstructed, or displaced stents, necessitating the exploration of alternative strategies like cholangioscopy or surgical intervention. This compilation of cases underscores the pressing imperative for prompt stent retrieval and the enhancement of management protocols to proactively mitigate the potential for complications.

Marine seaweeds are nature’s largesse resource in human well-being. Seaweed’s contribution to the food industry is being widened for its rich source of essential vitamins, minerals, and PUFA. ‘Nori’ is a dried sheet of red seaweed Porphyra sp. used to make ‘sushi’ a renowned cuisine in Japan, and other Southeast Asian countries. In this present study, commercial-grade ‘Nori’ was extracted and fractionated with different solvents, and subjected to evaluate the cytotoxic activity on human ovarian tetracarcinoma cells (PA1). As a result, the ethyl acetate fraction was found effective in inhibiting the proliferation of human ovarian cancer cells with an IC50 value of 41.1 µg/mL. The main component responsible for anticancer activity was determined as a sesquiterpene lactone Tatridin B (3h-cyclodeca[b]furan-2-one, 4,9-dihydroxy-6-methyl-3,10-dimethylene-). Moreover, it was found effective in inhibiting NSD2, an important and recently proposed biomarker for several types of cancer. This is a hitherto report on the presence of this compound in ‘Nori’ showing potent anticancer activity on human ovarian tetracarcinoma (PA1).