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The goal of this work is to further improve our knowledge of the nonlinear radiative second-grade nano fluid flow boundary layer phenomena which is associated with an Arrhenius activation energy, a sinusoidal magnetic field, and a stretched peripheral with a heat source. The unsteady governing equations are transformed into a proper dimensionless arrangement, and then the explicit finite difference (EFD) method is applied to numerically calculate the equations. However, precise stability and convergence criteria have been developed to make the solution convergent. Along with the typical profile of other flow fields, the oscillatory forms of the velocity are shown. Tabular research has even demonstrated a relationship between the Nusselt number and other parameters, and graphical depiction has been used for regression and data prediction. The novel conclusions drawn from this research indicate that, in comparison to linear patterns, nonlinear radiative heat flux significantly raises (30.35 %) flow profiles with second-grade characteristics. Moreover, the heat transfer rates of second-grade Nano fluids are seen to be significantly influenced (35.14 %) by the sinusoidal magnetic component. When considering nonlinear thermal radiation, activation energy principles cause a major change (34.19 % more) in mass transmission, as high-temperature processes become an essential part of chemical reactions.

The computing education research community now has at least 40 years of published research on teaching ethics in higher education. To examine the state of our field, we present a systematic literature review of papers in the "Association for Computing Machinery" computing education venues that describe teaching ethics in higher-education computing courses. Our review spans all papers published to SIGCSE, ICER, ITiCSE, CompEd, Koli Calling, and TOCE venues through 2022, with 100 papers fulfilling our inclusion criteria. Overall, we found a wide variety in content, teaching strategies, challenges, and recommendations. The majority of the papers did not articulate a conception of "ethics," and those that did used many different conceptions, from broadly applicable ethical theories to social impact to specific computing application areas (e.g., data privacy and hacking). Instructors used many different pedagogical strategies (e.g., discussions, lectures, assignments) and formats (e.g., stand-alone courses, incorporated within a technical course). Many papers identified measuring student knowledge as a particular challenge, and 59% of papers included mention of assessments or grading. Of the 69% of papers that evaluated their ethics instruction, most used student self-report surveys, course evaluations, and instructor reflections. While many papers included calls for more ethics content in computing, specific recommendations were rarely broadly applicable, preventing a synthesis of guidelines. To continue building on the last 40 years of research and move toward a set of best practices for teaching ethics in computing, our community should delineate our varied conceptions of ethics, examine which teaching strategies are best suited for each, and explore how to measure student learning.

KEY POINTS: The authors leverage the unique benefits of panoptic segmentation to perform the largest ever quantitation of reference kidney morphometry. Kidney features vary with age and sex; and glomeruli size may intricately link to creatinine, defying prior notions. BACKGROUND: Reference histomorphometric data of healthy human kidneys are largely lacking because of laborious quantitation requirements. Correlating histomorphometric features with clinical parameters through machine learning approaches can provide valuable information about natural population variance. To this end, we leveraged deep learning (DL), computational image analysis, and feature analysis to associate the relationship of histomorphometry with patient age, sex, serum creatinine (SCr), and eGFR in a multinational set of reference kidney tissue sections. METHODS: A panoptic segmentation neural network was developed and used to segment viable and sclerotic glomeruli, cortical and medullary interstitia, tubules, and arteries/arterioles in the digitized images of 79 periodic acid–Schiff-stained human nephrectomy sections showing minimal pathologic changes. Simple morphometrics (e.g., area, radius, density) were quantified from the segmented classes. Regression analysis aided in determining the association of histomorphometric parameters with age, sex, SCr, and eGFR. RESULTS: Our DL model achieved high segmentation performance for all test compartments. The size and density of glomeruli, tubules, and arteries/arterioles varied significantly among healthy humans, with potentially large differences between geographically diverse patients. Glomerular size was significantly correlated with SCr and eGFR. Slight, albeit significant, differences in renal vasculature were observed between sexes. Glomerulosclerosis percentage increased, and cortical density of arteries/arterioles decreased, as a function of increasing age. CONCLUSIONS: Using DL, we automated precise measurements of kidney histomorphometric features. In the reference kidney tissue, several histomorphometric features demonstrated significant correlation to patient demographics, SCr, and eGFR. DL tools can increase the efficiency and rigor of histomorphometric analysis.

The aim of the study was to identify existing livestock product supply chains and price disparities between producers and consumers. The study was conducted in three different locations at the producer level, usually livestock farmers and consumer level in an urban area of southwestern Bangladesh. Data were collected using a pre-tested questionnaire from 90 livestock and poultry farmers and 40 consumers through face-to-face interview method. The results showed that livestock farmers had limited access to their desired markets and in more than half of the cases (53.33%), local consumers were the primary buyers of livestock products and almost half of the farmers (45.56%) sold livestock products from farmers to consumers. Poor transport systems and a moderate farm-to-market distance of 11-20 km indicate poor market access for livestock products. Price discrepancies between producers and consumers indicated that significant differences were observed as consumers paid 21.86%, 39.25%, 29.24% and 21.35% more prices for eggs, milk, poultry meat and beef, respectively than the price received by producers. Several challenges have been identified in the livestock supply chain in Bangladesh including limited access to credit and finance, inadequate extension services and technical support, and the presence of middlemen. It can be concluded that weak supply chain exists in southwestern Bangladesh and the high price disparity between producers and consumers can be reduced by improving market access for livestock products by creating an enabling environment. Therefore, small farmers can contribute to the overall development of the livestock industry in a suitable market atmosphere.

Abstract HistoLens is an open-source graphical user interface developed using MATLAB AppDesigner for visual and quantitative analysis of histological datasets. HistoLens enables users to interrogate sets of digitally annotated whole slide images to efficiently characterize histological differences between disease and experimental groups. Users can dynamically visualize the distribution of 448 hand-engineered features quantifying color, texture, morphology, and distribution across microanatomic sub-compartments. Additionally, users can map differentially detected image features within the images by highlighting affected regions. We demonstrate the utility of HistoLens to identify hand-engineered features that correlate with pathognomonic renal glomerular characteristics distinguishing diabetic nephropathy and amyloid nephropathy from the histologically unremarkable glomeruli in minimal change disease. Additionally, we examine the use of HistoLens for glomerular feature discovery in the Tg26 mouse model of HIV-associated nephropathy. We identify numerous quantitative glomerular features distinguishing Tg26 transgenic mice from wild-type mice, corresponding to a progressive renal disease phenotype. Thus, we demonstrate an off-the-shelf and ready-to-use toolkit for quantitative renal pathology applications.

This project estimates the safety and mobility impact of changing speed limits on California highways. The safety impact is estimated using statistical models to predict the change in the frequency of all crashes and fatal-or-severe crashes that would result by varying the design speed (85th percentile speed). Statewide crash and traffic data (from the Statewide Integrated Traffic Records System, the Highway Safety Information System, and the Performance Measurement System) were combined to develop a balanced and sampled dataset for the statistical models. Three different increases in differential speed limits (DSLs; whereby trucks and cars have different speed limits) lead to increases in the frequency of all crashes, including fatal and severe crashes, for all of the classified segments (urban, rural, and different design speed segments). The operational condition (speed, travel time, delay) is tested using seven simulation segments with urban-rural classification. Four different DSL scenarios and four uniform speed limit (USL) scenarios are tested for each of the simulation segments. The results show a decrease of travel time but an increase of fuel consumption as the speed limits get higher. The safety cost of crashes and operational costs were also estimated based on the simulation models. In general, as the speed limits are increased, the safety costs increase with the predicted increases in crashes, particularly severe and fatal crashes. The operational costs, on the other hand, generally decrease as the speed limits are increased. However, the amount of operational cost decreases are subject to greater uncertainty than the safety cost estimates are, due to uncertainties in sampling and demand estimation and in negligence of construction costs of roadway and signage changes to accommodate the new speed limits. From the economic perspective in this study, raising speed limits on rural California highways could reduce monetary costs, as savings in operational costs would exceed losses from more crashes.

Sheep are small ruminants that require small amounts of feed and can graze on poor-quality pastures, including fallow lands, roadsides, dikes and playgrounds. Therefore, the experiment was conducted to evaluate the effect of the grazing length on growth performance of crossbred sheep in the southwestern region of Bangladesh. Sixteen crossbred female sheep were divided into four treatment groups and randomly allowed four different grazing periods. The experimental design was based on a randomized complete block design (RCBD). Lambs were initially weighed and grouped by keeping the average weight of the four treatment groups approximately the same. The grazing hours allocated to the four treatment groups were 6, 8, 10 and 12 hours, respectively. During this period, the sheep of particular treatment groups were housed when their allocated grazing period was completed. Empty body weight data were taken fortnightly in the morning before they were allowed to graze. The results revealed that body weight increased with increasing grazing length but the mean difference did not differ significantly (p>0.05). In most cases, the highest body weight was observed in sheep grazing for 12 hours per day. Average growth rates of grazing sheep varied significantly between the 6 to 8 hour and 10 to 12 hour grazing groups. But between the 6 to 8 hour grazing group and the 10 and 12 hour grazing group, the growth rate of crossbred sheep did not vary significantly (p>0.05). The growth rate (g day-1) of crossbred sheep ranged from 22.44±4.75 to 92.00±11.95, highest in 12 hour grazing group and lowest in 6 hour group. It can be concluded that the body weight and growth rate of crossbred sheep increased with an increase in grazing length. However, 10 hours of grazing meets the requirements for their maintenance and growth due to good pasture quality.

Abstract Missions into Deep Space are planned this decade. Yet the health consequences of exposure to microgravity and galactic cosmic radiation (GCR) over years-long missions on indispensable visceral organs such as the kidney are largely unexplored. We performed biomolecular (epigenomic, transcriptomic, proteomic, epiproteomic, metabolomic, metagenomic), clinical chemistry (electrolytes, endocrinology, biochemistry) and morphometry (histology, 3D imaging, miRNA-ISH, tissue weights) analyses using samples and datasets available from 11 spaceflight-exposed mouse and 5 human, 1 simulated microgravity rat and 4 simulated GCR-exposed mouse missions. We found that spaceflight induces: 1) renal transporter dephosphorylation which may indicate astronauts’ increased risk of nephrolithiasis is in part a primary renal phenomenon rather than solely a secondary consequence of bone loss; 2) remodelling of the nephron that results in expansion of distal convoluted tubule size but loss of overall tubule density; 3) renal damage and dysfunction when exposed to a Mars roundtrip dose-equivalent of simulated GCR.

Abstract Canine distemper virus (CDV) is a highly contagious virus that affects domestic and wild animals, causing severe illness with high mortality rates. Rapid monitoring and sequencing can provide valuable information about circulating CDV strains, which may foster effective vaccination strategies and the successful integration of these into conservation programs. During two site visits in Bangladesh in 2023, we tested a mobile, deployable genomic surveillance setup to explore the genetic diversity and phylogenetic patterns of locally circulating CDV strains. We collected and analysed 355 oral swab samples from stray dogs in Rajshahi and Chattogram cities, Bangladesh. CDV-specific real-time RT-PCR was performed to screen the samples. Out of the 355 samples, 7.4% (10/135) from Rajshahi city and 0.9% (2/220) from Chattogram city tested positive for CDV. We applied a real-time RT-PCR assay and a pan-genotype CDV-specific amplicon-based Nanopore sequencing technology to obtain the near-completes. Five near-complete genome sequences were generated, with phylogenetic relation to the India-1/Asia-5 lineage previously identified in India. This is the first study to provide genomic data on CDV in Bangladesh and the first demonstration of a mobile laboratory setup as a powerful tool in rapid genomic surveillance and risk assessment for CDV in low resource regions.

Reference histomorphometric data of healthy human kidneys are lacking due to laborious quantitation requirements. We leveraged deep learning to investigate the relationship of histomorphometry with patient age, sex, and serum creatinine in a multinational set of reference kidney tissue sections. A panoptic segmentation neural network was developed and used to segment viable and sclerotic glomeruli, cortical and medullary interstitia, tubules, and arteries/arterioles in digitized images of 79 periodic acid-Schiff (PAS)-stained human nephrectomy sections showing minimal pathologic changes. Simple morphometrics (e.g., area, radius, density) were measured from the segmented classes. Regression analysis was used to determine the relationship of histomorphometric parameters with age, sex, and serum creatinine. The model achieved high segmentation performance for all test compartments. We found that the size and density of nephrons, arteries/arterioles, and the baseline level of interstitium vary significantly among healthy humans, with potentially large differences between subjects from different geographic locations. Nephron size in any region of the kidney was significantly dependent on patient creatinine. Slight differences in renal vasculature and interstitium were observed between sexes. Finally, glomerulosclerosis percentage increased and cortical density of arteries/arterioles decreased as a function of age. We show that precise measurements of kidney histomorphometric parameters can be automated. Even in reference kidney tissue sections with minimal pathologic changes, several histomorphometric parameters demonstrated significant correlation to patient demographics and serum creatinine. These robust tools support the feasibility of deep learning to increase efficiency and rigor in histomorphometric analysis and pave the way for future large-scale studies.

The Banff Digital Pathology Working Group (DPWG) was established with the goal to establish a digital pathology repository; develop, validate, and share models for image analysis; and foster collaborations using regular videoconferencing. During the calls, a variety of artificial intelligence (AI)-based support systems for transplantation pathology were presented. Potential collaborations in a competition/trial on AI applied to kidney transplant specimens, including the DIAGGRAFT challenge (staining of biopsies at multiple institutions, pathologists visual assessment, and development and validation of new and pre-existing Banff scoring algorithms), were also discussed. To determine the next steps, a survey was conducted, primarily focusing on the feasibility of establishing a digital pathology repository and identifying potential hosts. Sixteen of the 35 respondents (46%) had access to a server hosting a digital pathology repository, with 2 respondents that could serve as a potential host at no cost to the DPWG. The 16 digital pathology repositories collected specimens from various organs, with the largest constituent being kidney (n = 12,870 specimens). A DPWG pilot digital pathology repository was established, and there are plans for a competition/trial with the DIAGGRAFT project. Utilizing existing resources and previously established models, the Banff DPWG is establishing new resources for the Banff community.

Agricultural soil contamination is increasing day-by-day and becoming a major problem over the globe. Trace elements accumulation in the bulk soil is frequently documented, however, there is no precise mechanism of their distribution in the different soil aggregates level. We collected twelve composite soil samples from banana fields, fallow land, rice cultivated with pond water (rice field-I), and rice cultivated with rain water (rice field-II). We separated soil samples into four different size of aggregates (4-2, 2–0.25, 0.25–0.053, 0.05). Moreover, macroaggregate acted as an accumulator for Fe, Mn, and As, while all the aggregate fractions acted as accumulators for Cu and Zn. Our study indicated that MWD, SOC, aggregate size and composition, and metal species were the controlling factors of trace elements accumulation and distribution in the various sizes of soil aggregates.

Swift identification of leaf diseases is crucial for sustainable rice farming, a staple grain consumed globally. The high costs and inefficiencies of manual identification underline the requirement of prompt disease detection. Traditional approaches for identifying leaf diseases in crops, particularly rice, are laborious, and and often ineffective. Given the significant impact of leaf diseases (such as Rice Blast, Brown Spot, and Rice Turgor) on rice quality and yield, computer-assisted detection can be an effective method of ensuring the long-term sustainability of rice production. This study utilizes advanced artificial intelligence (AI) as the optimized bidirectional encoder representations from the transformers for images(BEiT) model along with pre-trained CNNs (Convolutional Neural Networks), to build a comprehensive study for detecting rice leaf diseases. We train and validate two extensive datasets, featuring healthy and various types of unhealthy plant and rice leaf images respectively.Our optimized model demonstrates high accuracy, outperforming other deep learning and transformer-based models such as ViT, Xception, InceptionV3, DenseNet169, VGG16, and ResNet50. The proposed model achieves a precision of 0.97, a recall of 0.96, and an F1-score of 0.97.The explainability of our proposed model is achieved through the use of segmentation techniques in conjunction with the Local Interpretable Model-agnostic Explanations (LIME) method.

This study focused on the effects of alternating current (AC) and radio frequency (RF) power in the formation of plasma polymerized 3,4-ethylenedioxythiophene (PPEDOT) thin films onto glass substrates. Field emission scanning electron microscopy revealed that thin films produced both in AC and RF conditions exhibited a pristine surface morphology without any pinholes. Fourier transform infrared spectroscopy indicated that the chemical compositions of the PPEDOT films differed from that of the 3,4-ethylenedioxythiophene (EDOT) monomer due to structural rearrangements. The energy band gap values determined from the UV–Vis spectra were approximately 3.68 eV for the samples produced under AC power, while those for the samples produced under RF power were relatively higher, around 3.84 eV. Furthermore, the thin films synthesized using RF power and AC power exhibited significant differences in optical properties, including Urbach energy, extinction coefficient, steepness parameter, refractive index, optical conductivity, and skin depth. The EDOT monomer, PPEDOT and computed PEDOT via Density Functional Theory have been explicitly modeled with the intend to scrutinize the interplay between polymer formation and the modulation of molecular orbital energy levels, calculating band gaps, and molecular vibrations.

This study aims to enhance the comprehension of the fundamental fluid behavior by comparing Newtonian fluid with second-grade fluid under the influence of periodic magnetic fields, nonlinear radiative nanomaterial, and a porous stretched surface featuring a heat source. The governing equations' dimensionless forms are generated by applying the proper transformations, and the explicit finite difference (EFD) method is used to solve the numerically-derived solution while carefully maintaining stability and convergence standards. The results include velocity, heat, and mass transfer oscillation profiles; streamlines, and isothermal lines. Nusselt and Sherwood numbers are correlated with different factors according to tabular studies, and data prediction and regression are done using graphical representations. This study revealed that, in contrast to Newtonian fluid, second-grade fluid flow elevates velocity profiles with variations in chemical reaction parameters and mass Grashof numbers. Conversely, the thermal non-linear radiation and heat source in second-grade fluid particles effectively enhance the temperature field, although the temperature increase is more pronounced in Newtonian fluid compared to second-grade fluid. Also, second-grade fluid flow exhibits a lower mass transmission rate but higher stress sharing and heat transmission rates compared to Newtonian fluid flow. The implications of this research may impact prostate cancer treatment, as cancer patients have already benefited from the use of magnetic fields to regulate drug release from nanoparticles. Although the greater stress sharing and heat transmission rates may be used for targeted therapy, the lower mass transmission rate raises the possibility of benefits in controlled release scenarios.

HIV disease remains prevalent in the USA and chronic kidney disease remains a major cause of morbidity in HIV-1-positive patients. Host double-stranded RNA (dsRNA)-activated protein kinase (PKR) is a sensor for viral dsRNA, including HIV-1. We show that PKR inhibition by compound C16 ameliorates the HIV-associated nephropathy (HIVAN) kidney phenotype in the Tg26 transgenic mouse model, with reversal of mitochondrial dysfunction. Combined analysis of single-nucleus RNA-seq and bulk RNA-seq data revealed that oxidative phosphorylation was one of the most downregulated pathways and identified signal transducer and activator of transcription (STAT3) as a potential mediating factor. We identified in Tg26 mice a novel proximal tubular cell cluster enriched in mitochondrial transcripts. Podocytes showed high levels of HIV-1 gene expression and dysregulation of cytoskeleton-related genes, and these cells dedifferentiated. In injured proximal tubules, cell-cell interaction analysis indicated activation of the pro-fibrogenic PKR-STAT3-platelet-derived growth factor (PDGF)-D pathway. These findings suggest that PKR inhibition and mitochondrial rescue are potential novel therapeutic approaches for HIVAN.

Wheat is one of the most extensively cultivated crops worldwide that contributes significantly to global food caloric and protein production and is grown on millions of hectares yearly. However, diseases like brown rust, septoria, yellow rust, and other fungus diseases pose notable threats to wheat crops, impacting production and quality. Diagnosing these diseases is challenging, especially in areas with limited agricultural experts. Thus, creating computerized disease identification and decision-support technologies is crucial for safeguarding wheat leaf preservation and crop loss mitigation. The traditional approach to integrating data gathering and model training has substantial challenges in terms of data confidentiality, availability, and the costs related to data transmission. To address these challenges, federated learning (FL) is an appealing and effective option. Our study focuses on applying FL to classify agricultural diseases using image analysis. In our study, we conduct experiments on high-parameterized transfer learning (TL) models along with our proposed architecture based on the attention mechanism, introducing these models into a distributed learning strategy founded in FL. Our proposed architecture leverages the beneficial interactions of two cutting-edge vision transformer models including the advanced depthwise incorporating self-attention model referred to as CoAtNets, and the enhanced Swin Transformer V2, resulting in enhanced feature representation. Moreover, we introduce weight pruning into our model which is further classified by a reinforced linear attention mechanism (LA) to lower output dimensions. Our pruned lightweight (32M parameters) considerably decreases inference time with 624.249 ms and 644.899 on devices with low computational power, making it highly efficient in FL-based systems. The proposed model in our FL system significantly outperforms all other tested transfer learning models, including ConvNeXtBase, ConvNeXtLarge, EfficientNetV2L, InceptionResNetV2, ResNet152, and NASNetLarge, achieving accuracies up to 98% and 99%, precision up to 98%, recall up to 98%, and F-1 scores up to 95% across multiple input dimensions for wheat leaf disease classification.

Background: Antenatal care can play an important role in reducing the death of both mothers and children. This study was designed to find out the determinants of world health organization recommended antenatal care visits in six South Asian countries to achieve the targets for Sustainable Development Goal. Methods: This study used recent demographic and health survey data from six South Asian countries such as Afghanistan (2015), Bangladesh (2017-18), India (2015-16), Maldives (2016-17), Nepal (2016), and Pakistan (2047-18). Descriptive statistics were calculated for the distribution and prevalence of antenatal care visits. Bivariate and multivariable logistic regressions were used to investigate the influencing factors of antenatal care visits. Results: 71,862 women aged 15 to 49 years were included in this study, and 46.64% (95% Confidence Interval = 45.59 - 47.69%) had world health organization recommended antenatal care visits. In the pooled data, urban women (AOR ([Adjusted Odds Ratio]=1.48; 95% CI [Confidence Interval]=1.33-1.66), richest family (AOR=1.48; 95% CI=1.25-1.76), women’s higher education (AOR=3.76; 95% CI=3.33-4.25), women’s partner/husband’s higher education (AOR=1.69; 95% CI=1.50-1.92), 35–49 years (AOR=1.25, 95% CI=1.11-1.42), women’s age at first birth >25 years (AOR=1.51, 95% CI=1.36-1.68) and fully media exposure (AOR=2.11; 95% CI=1.74-2.56) were significantly positively associated with WHO recommended antenatal care visits. Whereas, working women (AOR=0.82; 95% CI=0.76-0.88), healthcare decision maker by their husband/others (AOR=0.71, 95% CI=0.60-0.84), ≥7 children (AOR=0.59; 95% CI=0.50-0.69), and ≥7 family members (AOR=0.82; 95% CI=0.73-0.93) had significant negative effect on antenatal care visits. In country specific analysis, overall, media exposure, secondary and above education of women, ≥25 of years age at first birth, and

Abstract Current study examined the magnetohydrodynamic (MHD) Prandtl nanofluid of a thermal double‐diffusive flow through an exponentially vertical surface in association with heat generation, and thermophoresis effect. The novelty of this study is due to the analysis of Prandtl nanofluid model with Soret mechanism and chemically responding fluids. This suggested model is beneficial since it can significantly advance the domains of thermal and industrial engineering. The fluid flow phenomenon is characterized by nonlinear coupled differential equations involving two or more independent variables. A suitable numerical technique is used to handle the set of governing equations along with a stability and convergence analysis. According to recent study, the fluid velocity increases since all the parameters are set to higher levels. For the various parametric values, isotherms and streamlines have been explored. This suggested model is beneficial since it can significantly advance the domains of thermal and industrial engineering. For instance, thermal radiation is crucial in designing sophisticated energy‐transformed systems that operate at high temperatures. On the other hand, the phenomenon of Soret is useful in separating isotopes in chemical engineering. An important findings of the current investigations can be treated as, radiative heat encourages fluid temperature distribution since it is the measure of the electromagnetic element radiates from the fluid particle that convert it into thermal radiation. These studies have several applications in the manufacturing and biomedical fields, petrochemical industries, automobiles, medical sciences, and various production processes in industries.

The largest bottleneck to the development of convolutional neural network (CNN) models in the computational pathology domain is the collection and curation of diverse training datasets. Training CNNs requires large cohorts of image data, and model generalizability is dependent on training data heterogeneity. Including data from multiple centers enhances the generalizability of CNN-based models, but this is hindered by the logistical challenges of sharing medical data. In this paper, we explore the feasibility of training our recently developed cloud-based segmentation tool (Histo-Cloud) using federated learning. Using a dataset of renal tissue biopsies we show that federated training to segment interstitial fibrosis and tubular atrophy (IFTA) using datasets from three institutions is not found to be different from a training by pooling the data on one server when tested on a fourth (holdout) institution's data. Further, training a model to segment glomeruli for a federated dataset (split by staining) demonstrates similar performance.

BackgroundImage-based machine learning tools hold great promise for clinical applications in pathology research. However, the ideal end-users of these computational tools (e.g., pathologists and biological scientists) often lack the programming experience required for the setup and use of these tools which often rely on the use of command line interfaces.MethodsWe have developed Histo-Cloud, a tool for segmentation of whole slide images (WSIs) that has an easy-to-use graphical user interface. This tool runs a state-of-the-art convolutional neural network (CNN) for segmentation of WSIs in the cloud and allows the extraction of features from segmented regions for further analysis.ResultsBy segmenting glomeruli, interstitial fibrosis and tubular atrophy, and vascular structures from renal and non-renal WSIs, we demonstrate the scalability, best practices for transfer learning, and effects of dataset variability. Finally, we demonstrate an application for animal model research, analyzing glomerular features in three murine models.ConclusionsHisto-Cloud is open source, accessible over the internet, and adaptable for segmentation of any histological structure regardless of stain.

Background Implementation of National Tobacco Control Laws (NTCLs) in university settings was found to be worse in Bangladesh.Objectives This study aimed to depict the compliance status of tobacco control laws (TCLs) and the associated factors following the university setting approach in Bangladesh.Methods This cross-sectional study was conducted with a mixed-method approach among the 385 students (quantitative method), 10 teachers and 10 administrative staff (qualitative method) of Northern University Bangladesh. Data were collected through mobile phone calling (quantitative) and in-depth interviews method (qualitative). Appropriate ethical issues were addressed. Logistic regression analysis was performed to find out the determinants. The study revealed non-satisfactory compliance with TCLs among 56.4% of study subjects which was strongly supported by the outcome of the qualitative approach. Predominant non-satisfactory compliance was found through the explorations of the conditions of buying and selling tobacco (78.4%), pasting no-smoking signage (3.2%), antitobacco advertisement within the university (34.8%) and specific university policy to implement NTCL. Non-satisfactory compliance was found significant among the younger aged (≤21 years: COR/p=2.74/0.01; 95% CI 1.27 to 5.92) from the first-year group (adjusted odds ratio (AOR)/p=2.28/0.02; 95% CI 1.15 to 4.49) who had moderate nicotine dependency (AOR/p=4.04/0.01; 95% CI 1.28 to 12.74), poor knowledge on TCLs (AOR/p=3.57/0.02; 95% CI 1.28 to 9.95) and the respondents who suggested family guidance (AOR/p=1.77/0.06; 95% CI 0.97 to 3.22) might be a sustainable way to minimise tobacco consumption in the university setting.Conclusions The study revealed some crucial factors for the non-satisfactory compliance status towards TCLs in the university setting. This empirical outcome and evaluation strategy can guide to plan of future large-scale studies, which may lead to implementing effective intervention programmes focusing on the development of a tobacco-free environment in the university setting.

This study offers an idea of investigating the temperature and humidity effect on salt crystallization in burned clay brick when it is subjected to a saline environment. It has been investigated that salt may be carried into masonry pores structures by moisture. As moisture production and movement are affected by temperature and humidity, the mechanism of salt crystallization is affected as well. Uniaxial Salt crystallization in burned clay bricks at different temperatures (20 °C, 30 °C, and 40 °C) and humidity (70%, 80%, and 90%) has been investigated, considering all other parameters to be constant. Analyzing the data derived from the experiment, two equations have been developed (one for temperature effect analysis and another for humidity effect analysis). Results indicate that the salt crystallization in burned clay bricks increases when the temperature of samples and sodium sulfate (Na2SO4) solution increases. However, the salt crystallization in burned clay bricks goes down when the relative humidity of the surrounding environment of samples decreases.

This work revealed the investigation of the Casson nanofluid flow's MHD (magneto-hydrodynamic) unstable boundary layer characteristics in the simultaneous transmission of thermoelectric and radiation on a stretched sheet. On MHD Newtonian and non-Newtonian (Casson) nanofluid flows, the cumulative impact of radiation and thermoelectricity has been addressed. Thermal radiation, Casson nanofluids, and MHD are pivotal in engineering and industry, transforming applications like heat exchangers, nuclear power plants, thermal energy storage, and advanced drug delivery systems. The problem-related partial differential equations have been formulated with boundary layer approximation. The boundary layer equations have been changed into dimensionless form with the help of appropriate dimensionless variables and parameters. Finite difference techniques have been employed to get the numerical solution via the FORTRAN 6.6a programming algorithm, and the numerical solutions have been illustrated graphically with the support of Tecplot-360 software. The consequences of the numerous parameters have been investigated using a variety of figures, with the amounts of the various parameters being revised. The simultaneous effects of thermoelectric and radiation on primary velocity, secondary velocity, and temperature profiles have been presented and discussed with critical physical properties such as skin friction in addition to Nusselt number. The combined effects of thermoelectric and radiation on streamlines and isotherms have been illustrated with line and contour flood views. The most significant finding is that the collective influence of thermoelectric and thermal radiation impacts promotes the physical phenomena of non-Newtonian (Casson) fluid flow comparatively more than Newtonian fluid flow. For the purpose of creating effective procedures, forecasting flow patterns, and guaranteeing product performance in a variety of industries, it is crucial to explain the Casson fluids. This model can also aid in blood flow simulation and risk assessment for thrombosis and other cardiovascular diseases.

The present research explores linear as well as nonlinear radiation patterns based on the MHD non-Newtonian (Maxwell) nanofluid flow having Arrhenius activation energy. This study's core focus is MHD properties in non-Newtonian fluid dynamics and boundary layer phenomena analysis. It initiates with time-dependent equations, employing boundary layer approximations. Extensive numerical computations, executed with custom Compact Visual Fortran code and the EFD method, provide profound insights into non-Newtonian fluid behavior, revealing intricate force interactions and fluid patterns. To check the stability of the solution, a convergence and stability analysis is performed. With the values of ΔY = 0.25, Δτ = 0.0005, and ΔX = 0.20; it is found that the model convergence occurs to the Lewis number, Le > 0.016 as well as the Prandtl number, Pr > 0.08. In this context, investigating non-dimensional results that depend on multiple physical factors. Explanation and visual representations of the effects of different physical characteristics and their resultant temperatures, concentrations, and velocity profiles are provided. As a result of the illustrations, the skin friction coefficient and Sherwood number, which are calculated, as well as Nusselt values, have all come up in discussion. Additionally, detailed representations of isothermal lines and streamlines are implemented, and it is pointed out that the development of these features occurs at the same time as Brownian motion. Furthermore, the temperature field for Maxwell fluid is modified due to the impression of chemical reaction as well as the Dufour number (Kr and Du). Our research demonstrates the superior performance of non-Newtonian solutions, notably in cases involving activation energy and nonlinear radiation. This paradigm shift carries significant implications. In another context, the interplay between Maxwell fluid and nonlinear radiation is notably affected by activation energy, offering promising applications in fields like medicine and industry, particularly in groundbreaking cancer treatment approaches.

Highway speed limits inherently represent a tradeoff between safety and mobility. While higher speed limits shorten travel times and foster economic benefits (especially for the trucking and logistics industries), they can also increase the likelihood and severity of crashes, as higher vehicle speeds require longer stopping distances and generate more energy during a collision. Highway speed limits are increasing nationwide. While there is no consensus on the optimal speed limit (Figure 1), research generally shows that lower speed limits reduce the frequency and severity of crashes. Likewise, there is mixed evidence on whether a universal speed limit (trucks and passenger vehicles subject to the same speed limit) or a differential speed limit (trucks subject to a lower speed limit than passenger vehicles) is safer. While some evidence indicates that setting lower speed limits for heavier trucks that are slow to stop has safety benefits, other research suggests that differential speed limits create bottlenecks that may actually cause more crashes as cars attempt to overtake slower trucks. California is one of only seven states that set differential speed limits.

Background: Type 2 diabetes is a major public health challenge. Indian Diabetes Risk Score (IDRS), a simple and cost-effective tool consisting of two modifiable (waist circumference, physical activity) and two non-modifiable risk factors (age, parental history) for diabetes, can be easily applied in mass screening programmes. Opportunistic screening for diabetes among individuals aged = 30 years is being done under the programme for Prevention and Control of Non-communicable Diseases. Objective: To assess the risk of type 2 diabetes mellitus using IDRS, coverage of screening services for diabetes through the primary health care delivery system and to identify their correlates. Methodology: : A descriptive, cross-sectional study was conducted in a block of Murshidabad district, West Bengal during September to November 2023 among permanent residents aged = 30 years on a calculated sample of 300 selected through multi-stage sampling. Required data were collected by interviewing the study subjects using pre-designed, pre-tested schedule including IDRS, reviewing medical records and measuring waist circumference. Analysis was done using SPSS-20. Results: Among 300 participants, 40.7% had high risk; 54% and 5.3% had moderate and low risk of diabetes respectively according to IDRS. In multivariable analysis, age =35 years (AOR 18.10, 95% CI 5.07-64.66), female gender (AOR 2.36, 95% CI 1.40-4.00) and being in joint family (AOR 3.53, 95% CI 1.77-7.04) were significant correlates for high-risk category according to IDRS. Only 67% were screened for diabetes within last six months, of which 89% were through primary health care delivery system. Screening status varied significantly by age group (OR 3.81, 95% CI 1.98-7.35) and IDRS risk categories (OR 1.72, 95% CI 1.06-2.80). Conclusion: Alarmingly substantial proportion of people in the area are at high/moderate risk of diabetes coupled with low opportunistic screening coverage, which highlights the need for intensive behaviour change communication and stronger service delivery.

Biosimilars are emerging class of medications that are very similar to biologics (in terms of safety and efficacy to the original reference product); but not the same as generic, originating, or reference drugs. The availability and use of biosimilars in oncology landscape are slowly picking, thereby combating financial burden to cancer patients. Breast cancer, with a staggering number of cases recently, has become the most common cancer in females. Human epidermal growth factor receptor-2 (HER2)-positive breast cancer involves the cell-surface protein that causes cell growth and proliferation and is more aggressive than typical breast cancer. The emergence of trastuzumab (first oncogene-targeted therapeutic agent for solid tumours to be clinically available under the brand name Herceptin) has improved the scope for patients suffering from this type of breast cancer. However, the associated cost remains to be a significant barrier for patients with breast cancer to access this treatment. Biosimilars, since their relatively recent advent, have reduced the cost of cancer treatment significantly, and will continue to play important cost-effective therapeutic roles for years to come. Notably, healthcare professionals still bear a somewhat negative/reluctant connotation to biosimilars. This article attempts to describe and analyse the studies that have been published in peer-reviewed literature on the use of trastuzumab biosimilars and their efficacy, safety, pharmacokinetic, and pharmacodynamic properties. It also covers on the chemistry and clinical advantages of using biosimilars for the ongoing and future treatment prospects for patients with breast cancer.

The purpose of the study was to utilise fish scale powder (FSP) of Labeo rohita (Rohu, R) and a combination of Labeo rohita and Labeo catla (Rohu and Catla, RC) fish scales as an alternative to the salt curing of goatskins. The preservation process's efficacy was assessed by periodically evaluating the parameters of the preserved goatskins. This reduced the chloride content (Cl−) and total dissolved solids (TDS) in discharged effluent to 92.78 and 87.67% in experiment 1 (15% Rohu FSP + 5% salt) and 97.19 and 86.54% in experiment 2 (15% Rohu & Catla FSP + 5% salt), respectively.

Abstract A magnetic field might interact with its surroundings, influencing chemical and physical processes in materials processing, heat exchangers, and other scientific study. Therefore, a computational study of non‐Newtonian (Casson) free convective MHD unsteady fluid flow has been highlighted in this article with mass and heat transit property through a vertical infinite porous plate. A sinusoidal boundary conditions as well as chemical reaction and thermal radiation have been considered. Using a collection of nondimensional variables, the flow related equations are also turned into nondimensional form. The EFDM algorithm is employed in order to arrive at a numerical solution via Compaq Visual Fortran. The reliability of the numerical solution has been confirmed using stability testing and convergence analysis. The whole system is convergent when the values of Prandtl number and Lewis number are greater than or equals to 0.075 and 0.025, respectively. A visual depiction of the impact of the pertinent factors on dimensionless velocity, temperature, and concentration profiles are displayed through graphical representation as well as with tabular representation. It has been inspected that when the magnetic component is regarded, it greatly affects the heat transfer factors of Casson nanofluid and the heat also rises when Eckert number, heat source and radiation parameter accelerate. It is also found that the Sherwood number is increased as the impact of chemical reaction parameter and the Lewis number, also the skin friction is decreased as the influence of porosity term got accelerated. The comparison of the current findings with the data that were previously published serves as the final stage in validating the present study.