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ABSTRACT Considering the indispensability of environmental protection, the utilization of natural ingredients as sustainable and eco‐friendly alternatives to synthetic dyes in fabric dyeing is of great significance. Betacyanins are naturally sourced pigments of red‐violet color that have the propensity to be fixed to mordanted substrates with reasonable permanency. In this study, the betacyanins sourced from beetroot (Beta vulgaris) were used to dye pre‐mordanted silk fabrics employing ultrasonication. In addition, a comparative analysis of the effects of five different mordants such as orange‐peel extracts, lemon peel extracts, tannic acid, ferrous sulfate, and alum on the color strength and fastness of beetroot‐dyed silk fabrics was presented in this research. For the characterization of the extracted dye, undyed, dyed, and mordanted silk fabric, infrared spectroscopy was performed. To observe the interaction of extracted dye and silk fabric, scanning electron microscopy was also accomplished. The outcomes of the characterization validated the successful extraction of dyes from beetroot and dyeing silk fabric with it. The values of color intensity (K/S), CIE L* a* b*, and CIE L* c* h* were measured using a reflectance spectrophotometer. At the same time, dry and wet rubbing and lightfastness ratings of dyed silk fabrics were determined according to the ISO standards. When 5% (o.w.f.) ferrous sulfate was used in pre‐mordanting, the ratings of colorfastness to wash, rub, and light ranged from 4 to 4/5, and the K/S value of the final sample was 4.88, which is higher than the K/S values of any other dyed samples. In contrast, the performance of 5% (o.w.f.) lemon peel extracts as a mordant was remarkably higher than orange peel extracts and even better than alum and tannic acid to some extent. The beetroot‐dyed silk fabric pre‐mordanted with 5% lemon peel exhibited a K/S value of 4.32, and the overall colorfastness rating ranged from 3/4 to 4/5. In conclusion, beetroot extracts hold the promise of being utilized as a sustainable replacement for environmentally harmful synthetic dyestuff in silk dyeing. Furthermore, in silk dyeing with beetroot extract, lemon peel extract is a potent alternative to ferrous sulfate as a mordant. [ABSTRACT FROM AUTHOR]

Sonneratia apetala, a nutrient-rich mangrove fruit, presents an opportunity for innovative food product development, offering potential health benefits and economic value through the creation of jam, jelly, and pickle. This innovative invention reveals the nutritional content including vitamins and minerals of Sonneratia apetala jam, jelly, and pickles from Nijhum Dwip in Hatiya Upazila, Noakhali District. These products contain Na, Mg, K, Ca, Mn, Fe, Cu, and Zn, which are essential for human nutrition. The texture and sensory qualities of the products depend on their Total Soluble Solids (TSS), acidity, moisture, pH, and total sugar content, with each parameter receiving an average score of 7 to 8 out of 9 (hedonic scale). Trace amounts of Cd, Cr, Pb, and Hg were found to be significantly below the safe consumption limits. F-, Cl-, SO42-, soluble and total PO43- concentrations were also below safety thresholds. The moisture, ash, protein, fat, fiber, pectin, sugar, carbohydrate, and caloric values highlight the dietary benefits and energy content of these products. The products exhibited higher levels of vitamin C and minerals compared to other citrus fruits. All tested parameters met safe consumption standards, ensuring product safety. These products underwent testing for Heterotrophic Bacterial Count to guarantee their safety. A one-year shelf life is ensured by conducting quarterly storage data checks and organoleptic tests by a 10-member jury panel. The one-way ANOVA test for sensory analysis and shelf life detection indicates statistically significant results. These products help mitigate nutrient deficiencies and promote health by regulating the diet. Applying this technology in grassroots jam, jelly, and pickle production could potentially boost the local economy by approximately $10,000 annually through the creation of small industries among the coastal population. [ABSTRACT FROM AUTHOR]

AbstractReturned concrete, a waste product of ready-mixed concrete (RMC), is generally washed to reclaim coarse aggregates from the finer portion consisting of fine aggregate, hydration products of cement, and un-hydrated cement particles, if any. In searching for environmentally sustainable construction materials, this finer part, termed as washed fines (WF), may substitute natural sand in producing mortar and concrete. An extensive study was conducted to determine the feasibility of replacing sand with WF by testing mortar cubes (50 mm x 50 mm x 50 mm) and prisms (285 mm x 25 mm x 25 mm) at replacement levels of natural sand by WF at 5%, 10%, 15%, and 20% for compressive strength, sorptivity, and drying shrinkage. The specimens were made with different types of cement. The microstructure of hardened mortar around WF was also examined using scanning electron microscope (SEM). Field trials reusing WF in concrete were conducted at an RMC plant to validate the laboratory results. Findings indicate compressive strength of mortar increased up to 19% with partial sand replacement by WF. The incorporation of WF reduced shrinkage and sorptivity coefficient. SEM images revealed a dense microstructure around WF in hardened mortar. [ABSTRACT FROM AUTHOR]

Introduction: Maternal and child health, which is integral to public health, depends on maintaining a healthy diet during pregnancy and lactation to achieve optimal outcomes. This study aimed to investigate the prevalence and determinants of minimum dietary diversity (MDD) among pregnant and lactating women (PLW) in this particular context. Methods: A stratified cluster sampling approach was employed, encompassing intervention areas (Rangpur and Nilphamari in Bangladesh) as strata, with 30 clusters. The study included 631 pregnant and lactating women (PLW) aged 15 to 49 years, focusing on their consumption of a minimally diverse diet. The outcome variable was binary: MDD (1 = if they consumed ≥ 5 food items from a basket of 10 food groups, indicating they met the MDD; 0 = if they consumed < 5 items, indicating they did not meet the MDD), assessed based on ten food groups over a 24-hour period. The data were analyzed using a binary logistic regression model. Results: The study found that 51.19% of PLW met MDD criteria, indicating positive dietary practices. Those aged 21–49 years had significantly lower odds of meeting MDD than those aged 15–20 years. Education played a key role, with completion of primary (p = 0.029) and secondary incomplete education (p = 0.055) associated with higher odds of meeting MDD. Other identified predictors included climate-smart techniques for agriculture, women's empowerment, food security, producing legume, nut and seeds and negative impact on family expenditure due to increase in commodity prices, especially food prices. Employing climate-smart agriculture increased odds by 1.58 times (p = 0.028), empowered women had 2.31 times higher odds (p < 0.001), and food security played a crucial role (p = 0.006). Moreover, producing legumes, nuts, or seeds was significantly associated with higher odds of meeting MDD (OR = 1.55, p = 0.039), while experiencing negative economic impacts lowered the odds (OR = 0.63, p = 0.034). Conclusion: The study provides insights into factors influencing MDD among PLW in northern Bangladesh. Empowering women and promoting climate-smart techniques for agriculture emerged as pivotal determinants, alongside enhancing education levels, increasing food security, and addressing economic barriers. Implementing multifaceted interventions that consider socio-demographic diversity, economic disparities, and dietary preferences is crucial for enhancing dietary diversity and improving health outcomes in this vulnerable population. [ABSTRACT FROM AUTHOR]

Through the advancement of the contemporary web and the rapid adoption of social media platforms such as YouTube, Twitter, and Facebook, for example, life has become much easier when dealing with certain highly personal problems. The far-reaching consequences of online harassment require immediate preventative steps to safeguard psychological wellness and scholarly achievement via detection at an earlier stage. This piece of writing aims to eliminate online harassment and create a criticism-free online environment. In the paper, we have used a variety of attributes to evaluate a large number of Bengali comments. We communicate cleansed data utilizing machine learning (ML) methods and natural language processing techniques, which must be followed using term frequency and reverse document frequency (TF-IDF) with a count vectorizer. In addition, we used tokenization with padding to feed our deep learning (DL) models. Using mathematical visualization and natural language processing, online bullying could be detected quickly. Multi-layer Perceptron (MLP), K-Nearest Neighbors (K-NN), Extreme Gradient Boosting (XGBoost), Adaptive Boosting Classifier (AdaBoost), Logistic Regression Classifier (LR), Random Forest Classifier (RF), Bagging Classifier, Stochastic Gradient Descent (SGD), Voting Classifier, and Stacking are employed in the research we conducted. We expanded our investigation to include different DL frameworks. Deep Neural Networks (DNN), Convolutional Neural Networks (CNN), Convolutional-Long Short-Term Memory (C-LSTM), and Bidirectional Long Short-Term Memory (BiLSTM) are all implemented. A large amount of data is required to precisely recognize harassing behavior. To rapidly recognize internet harassment written material, we combined two sets of data, producing 94,000 Bengali comments from different points of view. After understanding the ML and DL models, we can see that a hybrid model (MLP+SGD+LR) performed more effectively when compared to other models, its evaluation accuracy is 99.34%, precision is 99.34%, recall rate is 99.33%, and F1 score is 99.34% on multi-label class. For the binary classification model, we got 99.41% of accuracy. [ABSTRACT FROM AUTHOR]

Intimate Partner Violence (IPV) during pregnancy poses a serious threat to maternal health, particularly in low- and lower-middle-income countries (LMICs). Despite these known risks, the role of spousal educational differences in IPV during pregnancy remains poorly understood. This study aimed to examine this influence, analyzing data from multiple countries across five continents. This study utilized data from Demographic and Health Surveys (DHS) focusing on lower and LMIC countries. DHS employs two-stage sampling to gather comprehensive health data. Thirty countries from five regions were selected. Covariates like husband’s age, residence, wealth, education, husband’s working status, husband’s education, and spousal educational gap were considered. Cross-sectional survey design was considered. Chi-square test was done to find the association between IPV and covariates. Binary logistic regression was used to assess whether the independent variable is related to spousal educational disparity and other covariates of IPV during pregnancy. Out of 152,643 (weighted) pregnant women from all five continents, 8357 (weighted) experienced IPV during pregnancy. IPV is most prevalent in Papua New Guinea (17.01%; 95% CI 15.76–18.38%)), while least prevalent in Cambodia (0.99%; 95% CI 0.88–1.10%)). Overall, the IPV prevalence was (5.47%; 95% CI 5.30–5.65%)). Educational disparity and socioeconomic factors play a significant role in encountering IPV during pregnancy. This study revealed complex, region-specific effects on violence likelihood, emphasizing implications for policymakers and practitioners addressing IPV. Education disparity emerged as a significant factor; lower-educated couples exhibit increased abusive behavior. [ABSTRACT FROM AUTHOR]

The study aims to investigate the clinicopathological significance of MRPL24 in human cancers, with a particular focus on breast cancer (BC). Comprehensive bioinformatics analyses were conducted using data from The Cancer Genome Atlas (TCGA) and various advanced database, including cBioPortal, UALCAN, TIMER, Prognoscan, TISIDB, KM Plotter, and The Human Protein Atlas, to provide a detailed evaluation of MRPL55's role in cancer. The findings were further validated through experimental studies. Pan-cancer analysis of TCGA/ICGC data revealed significant amplification of MRPL24 across multiple cancer types, with the highest amplification rate of 60% observed in metastatic breast cancer. MRPL24 was found to be overexpressed in primary breast tumors, metastatic, and various molecular subtypes of breast cancer. High MRPL24 expression was associated with poor prognosis and lower survival rates in breast cancer patients. RT-PCR and western blot confirmed MRPL24 depletion in breast cancer cells. Knockdown of MRPL24 was shown to suppress proliferation, and clonogenic potential in breast cancer cells and inhibit cell migration. Additionally, MRPL24 depletion sensitized breast cancer cells to PD0325901 and 5-FU treatment. Mechanistic studies revealed that MRPL24 knock-down downregulates mRNA levels of oncogenic genes, including c-MYC, BRD4, WNT3, and STAT3. Positive correlations were observed between MRPL24 and key genes involved in ferroptosis regulation, such as ERBB2, ERBB3, GRB2, PIK3CA, AKT1, MAPK3, and MAPK1. Finally, through virtual screening and molecular dynamics simulations, we have identified three FDA-approved drugs with strong binding affinities and interactions with MRPL24. These findings underscore MRPL24's oncogenic role in breast cancer and suggest potential therapeutic strategies targeting this protein. [ABSTRACT FROM AUTHOR]

Environmental pollution has been a significant concern for the last few years. The leather industry significantly contributes to the economy but is one of Bangladesh's most prominent polluting industries. It is also responsible for several severe diseases such as cancer, lung diseases, and heart diseases of leather workers because they use bleaching agents and chemicals, and these have numerous adverse effects on human health. The study was aimed at isolating, identifying, and molecularly characterizing bacteria that produce protease enzymes that are highly capable of dehairing goat hide. Several attempts were made to isolate and identify protease‐producing bacterial strains from different soil samples of tannery wastes. Initially, a total of four isolates were selected from tannery soil. After the different phenotypic and morphological characterization, one isolate (BS2) showed Gram‐positive, rod‐shaped, and spore‐forming characteristics and could produce novel hair‐degrading protease enzymes. The growth profile and protease activity of the bacteria at 37°C were observed; a basal level of extracellular protease increased with time. The enzyme's proteolytic activity was measured, and the unit of enzyme activity of the enzyme sample was 18.1. The ExPASy server (ProtParam) tool was used to estimate the physicochemical characteristics of the proteins and found molecular weight (MW) (7375.94 Da), aliphatic index (71.56), instability index (II, 80.63), Grand Average of Hydropathy (GRAVY) (−0.231), and isoelectric point (11.41). The protein–protein interactions (PPI) networks were generated using the Search Tool for the Retrieval of Interacting Genes (STRING) database and Cytoscape software. The PSIPRED v.4.0 and SAVES v.6.0 programs were used to determine the secondary and three‐dimensional assembly of the selected protein. They found alpha helix (16, 25.00%), extended strand (6, 9.38%), beta‐turn (5, 7.81%), and random coil (37, 57.81%). DNA isolation and purification were carried out, and the purity ratio was ~2.17 at 260 and 280 nm. Polymerase chain reaction (PCR) for amplifying the 16S rRNA gene was conducted, and the isolate was authentically recognized as Bacillus cereus (BS2) based on morphological, biochemical, and molecular analyses. The quantitative assessment has shown that 40 mL of culture centrifugation could dehair 2 × 1 cm of goat leather sample in 9 h. This potential bacterial strain can be used in the leather industry as an ecofriendly alternative to chemical dehairing, which can reduce environmental pollution and the risk of severe diseases among leather industry workers. [ABSTRACT FROM AUTHOR]

The recent advancements in synthesizing single‐crystalline 1D nanostructures of vanadium dioxide (VO2) in the form of nanowires (NWs) have sparked increased research interest for application in electrical and optical switching devices. In this study, the photocurrent response in VO2 is examined. This highly correlated material is well known for its significant metal‐insulator transition at around 340 K. This property makes VO2 potentially valuable for optoelectronic detection and switching applications, particularly for UV wavelengths. The investigation included the examination of individual and isolated VO2 NWs photocurrent response before and after gold nanoparticles (Au NPs) surface deposition via the dielectrophoresis (DEP) method. Carrier injection is controlled by manipulating the presence of AuNPs on the surface of a single‐crystal VO2 NWs. The VO2 NW device exhibits an enhanced photocurrent after AuNPs surface deposition. In this study, the significance of using AuNP deposition is demonstrated via the DEP process for the improved photocurrent response to analyze nanoscale crystals in studying highly correlated materials for thermoelectric and optical applications. [ABSTRACT FROM AUTHOR]

This article proposes an eye-shape enclosed split ring resonator (ESE-SRR) based metamaterial absorber for multi-band microwave applications with high absorption levels. Four-fold rotational symmetric eye-shaped electrical resonators form the structure of the proposed metamaterial absorber (MMA) to achieve polarisation-insensitive characteristics. Eight near-unity absorption peaks between S, C, X, Ku, and K-band are achieved, where peak absorptions are attained at 3.349 GHz, 5.06 GHz, 6.829 GHz, 9.178 GHz, 14.54 GHz, 17.96 GHz, 18.89 GHz, and 20.4 GHz with absorption levels of 99.8%, 99.7%, 92.9%, 99.1%, 96.4%, 93.3%, 91.3%, and 99.35%, respectively. The electrical dimension of the unit cell is 0.112λmin × 0.112λmin × 0.018λmin, making it a subwavelength compact structure for oblique incident angle stable absorption behaviour. The absorption characteristics are also investigated with metamaterial properties, surface current, and electromagnetic field distributions. The designed MMA is validated by prototype fabrication and measurement, which shows good agreement with simulation results. Finally, the proposed MMA shows an electrically compact structure with eight near-unity absorption peaks and polarisation insensitivity, which makes it an attractive candidate for absorption, sensing, radar cross-section reduction, etc. [ABSTRACT FROM AUTHOR]

Steganography is used to hide sensitive types of data including images, audio, text, and videos in an invisible way so that no one can detect it. Image-based steganography is a technique that uses images as a cover media for hiding and transmitting sensitive information over the internet. However, image-based steganography is a challenging task due to transparency, security, computational efficiency, tamper protection, payload, etc. Recently, different image steganography methods have been proposed but most of them have reliability issues. Therefore, to solve this issue, we propose an efficient technique based on the Least Significant Bit (LSB). The LSB substitution method minimizes the error rate in the embedding process and is used to achieve greater reliability. Our proposed image-based steganography algorithm incorporates LSB substitution with Magic Matrix, Multi-Level Encryption Algorithm (MLEA), Secret Key (SK), and transposition, flipping. We performed several experiments and the results show that our proposed technique is efficient and achieves efficient results. We tested a total of 165 different RGB images of various dimensions and sizes of hidden information, using various Quality Assessment Metrics (QAMs); A name of few are; Normalized Cross Correlation (NCC), Image Fidelity (IF), Peak Signal Noise Ratio (PSNR), Root Mean Square Error (RMSE), Quality Index (QI), Correlation Coefficient (CC), Structural Similarity Index (SSIM), Mean Square Error (MSE), Entropy, Contrast, and Homogeneity, Image Histogram (IH). We also conducted a comparative analysis with some existing methods as well as security analysis which showed better results. The achieved result demonstrates significant improvements over the current state-of-the-art methods. [ABSTRACT FROM AUTHOR]

Hypsometric or area-altitude analysis unveils the geomorphic evolution of a river basin and its interactions with tectonics, lithology, and climate. The results of hypsometric analysis i.e., hypsometric curve (HC) along with the hypsometric parameters (HP) namely, hypsometric integral (HI), skewness (SK), kurtosis (KU), density skewness (DSK), and density kurtosis (DKU) can also be further analyzed to evaluate the geological erosional status of a river basin. However, the spatial scale’s significance in such analyses is often underestimated, assuming consistency across various resolutions of Digital Elevation Models (DEMs). To address this oversight, this study compares HP values obtained from DEMs of different sources and resolutions—Shuttle Radar Topographic Mission (30 m), Global Multi-resolution Terrain Elevation Data 2010 (225 m), and Global 30 Arc-Second Elevation Data Set (1000 m). A total of 108 sub-watersheds spanning four large Indian River basins (Mahanadi, Godavari, Krishna, and Cauvery) underwent analysis using both parametric and non-parametric statistical tests, namely Shapiro-Wilk, Kolmogorov-Smirnov, and Anderson-Darling tests, to assess the distribution of hypsometric parameters. Subsequently, the null hypothesis regarding the robustness of HP across varying DEM resolutions was tested using non-parametric statistical tests such as the Mann-Whitney U test, Kruskal-Wallis H test, and Friedman test. The study’s findings challenge the prevalent notion of robustness, revealing that DEM resolution significantly impacts the results of hypsometric analysis. The Friedman test, in particular, highlighted significant differences in the full distribution of hypsometric parameters across different DEM resolutions, suggesting that variations in DEM resolution can alter the shape and variability of these parameters, not just their central tendencies. Higher-resolution DEMs, such as SRTM (30 m), provided more accurate representations of landscape features, especially in capturing subtle variations that influence erosion rates, sediment transport, and geomorphic classification. [ABSTRACT FROM AUTHOR]

In order to plan and facilitate the culture of personalized / precision medicine in medical practices within any healthcare institution, it is requisite for healthcare professionals like clinicians to have a clear understanding and approach towards the practices of personalized genetic testing. This nationwide cross-sectional study aimed to measure the perceptions and knowledge of clinicians towards personalized genetic testing and assess their current practices of personalized genetic testing in clinical settings through an online self-administered questionnaire in Saudi Arabia. The results of the study revealed that almost two-fifths of participants were responsible for ordering genetic tests directly (39.0%). The main concerns of the participants were the lack of clinical practice guidelines on personalized genetic tests (50.0%) and the cost of these tests (50.9%). The participants revealed that the genetic tests had influenced the patients' treatment plans (50.0%) and helped them understand the risks of their patients' disorders (52.3%). The study revealed a gap in understanding and implementing personalized genetic testing in Saudi Arabia, with enthusiasm tempered by challenges like insufficient knowledge, lack of guidelines, and practical applications' barriers. Effective integration of genetic testing into clinical practice should focus on enhancing medical education, developing clinical guidelines, and improving patient awareness about genetic tests that can lead to an improved personalized healthcare approach. [ABSTRACT FROM AUTHOR]

The present study introduces a one-dimensional finite element (FE) model that utilizes third-order deformation kinematics to analyze the flexural vibration of two-layered composite beams with partial shear slip. The proposed model incorporates a three-node straight beam element, utilizing the field-consistent approach and full numerical integration of the stiffness matrix. This approach is adopted to effectively address stress oscillation and shear locking issues, ensuring accurate and reliable results. The analysis focuses on the third-order deformation kinematics of longitudinal displacement within the beam depth, examining each of the two layers individually. The interface between the two material layers is joined using deformable shear connectors, which are represented as dispersed shear springs over the length of the beam. This study focuses on conducting a flexural vibration analysis of two-layered composite beams. The analysis includes the examination of both free vibration and forced vibration responses while considering or omitting the influence of damping under various loading conditions. The validity of the proposed FE model is assessed by the utilization of a two-dimensional model developed within the ABAQUS software. Additionally, the suggested model is evaluated through the process of verification by comparing it with previously published results. [ABSTRACT FROM AUTHOR]

COVID-19 caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) had an adverse effect globally because it caused a global pandemic with several million deaths. This virus possesses spike protein that is cleaved or activated by Furin-like protease enzymes occurring by mammalian lung or respiratory cells to enter the mammalian body. The addition of the Furin cleavage site in SARS-CoV-2 makes it a more infectious and emerging virus than its ancestor's viruses. Phylogenetic relationships of coronavirus spike proteins have analyzed and mapped Furin recognition motif on the tree using bioinformatics tools such as GTEx, KEGG, GO, NCBI, PolyPhen-2, SNAP2, PANTHER, Hidden Markov Models (Fathmm), Phd-single-nucleotide polymorphism (SNP), I-TASSER, Modpred, Phobius, SIFT, iPTREE-STAB, and PROVEAN. During this study, it has been found that in certain regions, Furin SNPs have some relation with the susceptibility to SARS-CoV-2. Whereas in other regions, the effects are very negligible. Finally, our study demonstrates that Furin SNPs have a strong relationship with susceptibility to SARS-CoV-2. As it helps to cleave the spike protein of the virus, thus it can be targeted to inhibit at a particular site to prevent the SARS-CoV-2 from the entrance into the body. [ABSTRACT FROM AUTHOR]

Objective: We aimed to determine the prevalence and factors associated with loneliness among adolescent students in three South Asian countries.Methods: We used data from the latest Global School-Based Health Survey of Afghanistan, Bangladesh, and Pakistan. A two-stage cluster sampling design was used to collect the cross-sectional survey data. Data from 8 089 in-school adolescents were analysed using STATA 14.0.Results: Among all the participants, the prevalence of loneliness was 14.9%. The prevalence of loneliness was significantly higher in females (19.7%), Afghan adolescents (35.5%), participants having anxiety-induced sleep disturbance (51.4%), often experiencing bullying (28.9%), feeling hungry often or always (23.9%), suffering parental emotional neglect (21.2%), and spending ≥ 8 hours/day leisure time (35.8%), than their counterparts. The final adjusted model of multiple logistic regression showed that females (OR = 1.36, 95% CI: 1.02 –1.80), having no close friends (OR = 2.00, 95% CI: 1.30 – 3.10), having an anxiety-induced sleep disturbance (OR = 5.25, 95% CI: 3.75 – 7.34), being bullied 1 to 2 days in the past month (OR = 2.13, 95% CI: 1.60 – 2.84), being physically attacked 2 or more times in the past year (OR = 1.69, 95% CI: 1.26 – 2.26), suffering parental emotional neglect (OR = 1.67, 95% CI: 1.18–2.34), and current tobacco user (OR = 2.70, 95% CI: 1.39 – 5.25) had significantly higher odds of having loneliness.Conclusion: We found a higher prevalence of loneliness and identified several risk factors among in-school adolescents in three South Asian countries. To reduce loneliness among in-school adolescents, target-oriented interventions, such as peer, parental, and counselling support, are needed at schools. [ABSTRACT FROM AUTHOR]

In 2D materials, tungsten diselenide (WSe2) has great potential for optical and electronic devices. However, the quality of WSe2 crystals, determined by defects and grain boundaries, currently restricts its performance in controlling carrier‐transport properties. Consequently, the most significant issue achieves superior growth of WSe2 crystals and appropriate metal contacts. Herein, a doping‐free approach to manipulate the polarity of WSe2 transistors by utilizing distinct metal contacts is presented. WSe2 field‐effect transistors are examined employing low‐ and high‐work function metals. In these findings, a transition in polarity from n‐type for In and Cr to p‐type for Pd and Au is demonstrated, showcasing remarkably high on/off ratios (≈107) and mobilities (≈117 cm2 V−1 s−1) at room temperature. This straightforward polarity control technique can be further extended by utilizing contact architecture‐based research in other 2D materials for future nano‐electrical and optoelectronic devices. [ABSTRACT FROM AUTHOR]

Azoospermia, a severe form of male infertility characterized by the complete absence of sperm in the ejaculate, affects about 1% of the male population, with most cases attributed to nonobstructive azoospermia (NOA) caused by gametogenic failure. NOA has various genetic origins, including chromosomal abnormalities, Y chromosome microdeletions, and monogenic mutations. Although whole-exome sequencing (WES) has identified over thirty candidate genes associated with NOA, the genetic causes of most cases have yet to be elucidated. In our study, we selected seven consanguineous families diagnosed with azoospermia from a total of 21 male infertile families recruited from the rural area of Pakistan. Blood samples were collected from both patients and fertile controls for DNA extraction, followed by WES to identify potential causative recessive monogenic variants linked to male infertility. We successfully identified five deleterious variants among five of the seven families, including three missense biallelic substitutions in WWC2, RPL10L, and SOHLH1, a hemizygous deletion in ESX1, and a homozygous deletion in TXNDC2, which have potentially pathogenic relevance to the azoospermia of human male infertility. These novel findings enhance our understanding of the molecular mechanisms underlying the complex etiology of azoospermia, offering valuable insights for genetic counseling and diagnostics and paving the way for future therapeutic approaches. [ABSTRACT FROM AUTHOR]

Conventional index-based testing of asphalt mixtures cannot accurately capture local deformation in a sample, limiting the usage of standard test measurements. The non-contact-based measurements proved effective to capture local deformation fields. This study aimed to capture the fatigue and thermal cracking behaviour of fiber-reinforced asphalt mixture (FRAM) by utilising digital image correlation (DIC). One binder (PG76-22), a diabase aggregate and three fibers (polyolefin/ aramid fibers (PFA) at 0.05% dosage and Sasobit-coated aramid fibers at 0.01% and 0.02% dosage) were used to prepare a total of four mixtures (one control and three FRAM). All these mixtures were produced at a local batch plant following manufacturer-recommended mixing methods. DIC analysis was performed for three-point bending beam (3PB) and disk shape compact tension (DCT) tests at intermediate temperature (25°C) and low temperatures of −12°C and −18°C. Based on index values from DCT and 3PB, the thermal and fatigue cracking performance enhancement was not significant. However, DIC analysis showed that, regardless of testing temperature, the crack propagated in a random pattern for FRAM, whereas the crack followed a relatively straight path for the control mix. Finally, based on DIC strain contours, FRAM mixtures exhibit distributed strain over a larger area compared to the control mix. [ABSTRACT FROM AUTHOR]

A conventional flag is placed downstream of the inverted half cylinder to study pressure over the flag's surface due to fluid-flexible body interaction between the flag and the vortices generated by the half cylinder. An immersed boundary method provides a reliable and fast solution to the fluid-structure interaction problems, albeit with limitation. One such limitation is the accurate pressure profile over the Lagrangian grid, i.e., the structure boundary. A pressure prediction algorithm is proposed which couples with the improved immersed boundary method to predict pressure over flag's surface. The effect of flow patterns on flag's surface pressure is studied by varying flag's distance from the bluff body. The pressure results are analyzed as negative and positive pressure fluctuations from the assigned reference pressure in the far field. Results show high flag surface pressure at a smaller stream-wise distance. A subsequent decrease in flow pressure is observed, when the stream-wise distance is increased. Changing span-distance shows that the highest pressure occurs at Gy = 0.25 with a significant drop at span positions of 0 and 0.5. The average pressure over the flag's surface is also affected by the vibration modes and the vortex shedding from the surface of the flag. The deflected mode appears at a smaller stream-wise distance accompanied by additional vortex shedding from the flag surface resulting in a high average pressure. Whereas biased and conventional flapping modes appear as stream-wise distance is progressively decreased resulting in reduced average pressure. Hydrodynamic analysis shows that the vortices originating from the bluff body and their subsequent interaction with the flag serve as the primary source of pressure fluctuations resulting in a change in the pressure profile over the surface of the flag. [ABSTRACT FROM AUTHOR]

We report on the surface properties of aluminum-gallium-oxide [(AlxGa1−x)2O3] thin films grown on c-plane sapphire substrates, which form the building block of heterojunction semiconductor devices, by metal–organic chemical vapor deposition (MOCVD). The (AlxGa1−x)2O3 films with aluminum mole fraction (composition) ranging from x = 0 to x = 0.36 were analyzed using x-ray diffraction (XRD) and atomic force microscopy (AFM). The increase in the aluminum composition resulted in the shift in XRD peaks to larger 2θ angles due to the decrease in the lattice constants and broadening due to the degradation in crystallinity. By utilizing the AFM in scanning Kelvin probe microscopy (SKPM) configuration, we report the surface work function of (AlxGa1−x)2O3 decreased from 6.13 to 5.62 eV as aluminum composition increased from 0% to 36%. Direct measurements of epitaxial surface potential in (AlxGa1−x)2O3 thin films show downward band bending ranging from 1.19 to 0.65 eV. The SKPM measurements with trap filling under UV illumination suggest the presence of a relatively high density of donor surface states in (AlxGa1−x)2O3 samples. By modeling the surface states as a spatially localized and energetically discrete level in the bandgap, the density of surface states is found to be ∼2 × 1012 to ∼4 × 1013 cm−2. [ABSTRACT FROM AUTHOR]

Gait recognition is a behavioral biometric technique that identifies individuals based on their unique walking patterns, enabling long-distance identification. Traditional gait recognition methods rely on appearance-based approaches that utilize background-subtracted silhouette sequences to extract gait features. While effective and easy to compute, these methods are susceptible to variations in clothing, carried objects, and illumination changes, compromising the extraction of discriminative features in real-world applications. In contrast, model-based approaches using skeletal key points offer robustness against these covariates. Advances in human pose estimation (HPE) algorithms using convolutional neural networks (CNNs) have facilitated the extraction of skeletal key points, addressing some challenges of model-based approaches. However, the performance of skeleton-based methods still lags behind that of appearance-based approaches. This paper aims to bridge this performance gap by introducing a multi-biometric framework that extracts features from multiple HPE algorithms for gait recognition, employing feature-level fusion (FLF) and decision-level fusion (DLF) by leveraging a single-source multi-sample technique. We utilized state-of-the-art HPE algorithms, OpenPose, AlphaPose, and HRNet, to generate diverse skeleton data samples from a single source video. Subsequently, we employed a residual graph convolutional network (ResGCN) to extract features from the generated skeleton data. In the FLF approach, the features extracted from ResGCN and applied to the skeleton data samples generated by multiple HPE algorithms are aggregated point-wise for gait recognition, while in the DLF approach, the decisions of ResGCN applied to each skeleton data sample are integrated using majority voting for the final recognition. Our proposed method demonstrated state-of-the-art skeleton-based cross-view gait recognition performance on a popular dataset, CASIA-B. [ABSTRACT FROM AUTHOR]

Garment products are international trade items and essential consumption items. The readymade garment industry of Bangladesh is the second largest garment exporter in the world. The garment industry of Bangladesh consumes one-third of the country's total industrial energy. Such industry consumes significant energy and contributes greenhouse gas (GHG) emissions into the atmosphere. Assessment of energy consumption and GHG emission of garment products helps to understand the baseline status of the production and benchmarking the energy and emission leveling of the product. This paper aims to investigate the energy consumption and GHG emissions of readymade garment (T-shirt) production in Bangladesh. Gate-to-gate production stages have been considered for the investigation. The strategies for the energy and GHG emission-saving potential have been also analyzed. The result showed that the total energy consumption in terms of natural gas, oil, and electricity found are 15,105 m3, 49.93 kg, and 36,265 kWh respectively per day. The total CO2 emission found is 56.65 tons per day. The specific energy consumption found is 12 MJ/piece and the specific emissions of the CO2, CO, CH4, NOx, and SOx are 0.94 kg/piece, 1.69 gm/piece, 3.53 gm/piece, 4.1 gm/piece, and 0.89gm/piece, respectively. The proposed strategies could save energy in the machinery section in the range of 22–70%. The energy saving potential of 25% is possible in the steam generation sector by employing the proposed electric steam generator. The steam generation section gives the highest CO2 emission and the compressor section gives the lowest emission. The specific energy consumption and carbon footprint of Bangladesh-manufactured garments are in very close agreement with the literature studied. [ABSTRACT FROM AUTHOR]

Continuous blood pressure (BP) provides essential information for monitoring one's health condition. However, BP is currently monitored using uncomfortable cuff-based devices, which does not support continuous BP monitoring. This paper aims to introduce a blood pressure monitoring algorithm based on only photoplethysmography (PPG) signals using the deep neural network (DNN). The PPG signals are obtained from 125 unique subjects with 218 records and filtered using signal processing algorithms to reduce the effects of noise, such as baseline wandering, and motion artifacts. The proposed algorithm is based on pulse wave analysis of PPG signals, extracted various domain features from PPG signals, and mapped them to BP values. Four feature selection methods are applied and yielded four feature subsets. Therefore, an ensemble feature selection technique is proposed to obtain the optimal feature set based on major voting scores from four feature subsets. DNN models, along with the ensemble feature selection technique, outperformed in estimating the systolic blood pressure (SBP) and diastolic blood pressure (DBP) compared to previously reported approaches that rely only on the PPG signal. The coefficient of determination ( R 2 ) and mean absolute error (MAE) of the proposed algorithm are 0.962 and 2.480 mmHg, respectively, for SBP and 0.955 and 1.499 mmHg, respectively, for DBP. The proposed approach meets the Advancement of Medical Instrumentation standard for SBP and DBP estimations. Additionally, according to the British Hypertension Society standard, the results attained Grade A for both SBP and DBP estimations. It concludes that BP can be estimated more accurately using the optimal feature set and DNN models. The proposed algorithm has the potential ability to facilitate mobile healthcare devices to monitor continuous BP. [ABSTRACT FROM AUTHOR]

To optimize weather research and forecasting (WRF) model, a sensitivity analysis has been performed for test thunderstorm events to determine the best combination of cumulus physics (CU) and data source options to be used for simulating thunderstorms over Bangladesh. Six combinations for three cumulus physics options namely, Kain-Fritsch Scheme (KF) (CU-1), Betts-Miller-Janjic Scheme (BMJ) (CU-2) and Grell-Dévényi (GD) Ensemble Scheme (CU-3) and two different data sources namely, National Center for Environmental Prediction (NCEP) Final Analysis (FNL) and the Global Forecast System (GFS) data have been used for this purpose. WRF model has been run on a single domain of 9 km horizontal resolution utilizing the combinations of these cumulus physics and six hourly GFS/FNL datasets for 48 h; from 0000 UTC of 14 May 2017 to 0000 UTC of 16 May 2017 and from 0000 UTC of 29 March 2018 to 0000 UTC of 31 March 2018 as initial and lateral boundary conditions for test event-1 and test event-2 respectively. Model simulated output for rainfall, relative humidity; mean sea level pressure and temperature have been compared with the observed data of Bangladesh Meteorological Department (BMD). Then absolute error of each simulated parameter has been calculated. On the basis of root mean square error (RMSE) for each parameter, better cumulus physics and data source combination has been selected. It is found that, CU-1 and GFS dataset combination exhibits less RMS error in 4 sections out of 12 sections for event-1 and in 5 sections out of 12 sections for event-2. So, it may be expected that Cu_1 and GFS dataset combination may be used for simulating thunderstorm over Bangladesh. After finalizing model physics options and data sets, another test case of TS has been simulated and different parameters are analyzed for justification of WRF setup. It is found that WRF model captured MSLP, temperature and relative humidity very well. But in case of rainfall the simulated value is much smaller than the observed value. For more accuracy more case studies may be carried out including for fair weather days as well as severe TS days. [ABSTRACT FROM AUTHOR]

MicroRNAs (miRNAs) act as key gene expression regulators, influencing intracellular biological and pathological processes. They are of significant interest in animal genetics as potential biomarkers for animal selection and health. This study aimed to unravel the complex miRNA signature involved in mastitis in in vitro cell culture. For this purpose, we constructed a control and treatment model in ovarian mammary epithelial cells to analyze miRNA responses upon Staphylococcus aureus (S. aureus) stimulation. The high-throughput Illumina Small RNA protocol was employed, generating an average of 7.75 million single-end reads per sample, totaling 46.54 million reads. Standard bioinformatics analysis, including cleaning, filtering, miRNA quantification, and differential expression was performed using the miRbase database as a reference for ovine miRNAs. The results indicated differential expression of 63 miRNAs, including 33 up-regulated and 30 down-regulated compared to the control group. Notably, miR-10a, miR-10b, miR-21, and miR-99a displayed a significant differential expression (p ≤ 0.05) associated to signal transduction, transcriptional pathways, diseases of signal transduction by growth factor receptors and second messengers, MAPK signaling pathway, NF-κB pathway, TNFα, Toll Like Receptor 4 (TLR4) cascade, and breast cancer. This study contributes expanding miRNA databases, especially for sheep miRNAs, and identifies potential miRNA candidates for further study in biomarker identification for mastitis resistance and diagnosis. [ABSTRACT FROM AUTHOR]

The review focuses on application of chemometric modeling in raw material characterization and quantification of parameter in various steps of pulp and papermaking processes. These models are built by supervised or unsupervised machine-learning techniques. Chemometric models are predominantly developed with data from spectroscopic instruments like, Ultraviolet spectrophotometer (UV), Near Infrared spectrophotometer (NIR), Fourier Transform Infrared Spectrometer (FTIR), Raman Spectrometer etc. These spectroscopic data are large in size which are reduced by applying different dimension reduction techniques. Moreover, these data contain instrumental noise in most of the cases, and they are de-noised or smoothed by several preprocessing techniques for developing better performing models. Among the popular calibration techniques for classification, Soft Independent Modeling for Classification Algorithm (SIMCA), Discrimination Analysis (DA) are mentionable. Multiple Linear Regression (MLR), Principal Component Regression (PCR), Partial Least Square Regression (PLSR), Artificial Neural Network (ANN), Support Vector Machine (SVM) etc., are used for quantification of different physical, morphological and chemical properties of wood, pulp and paper properties. Based on chemometric models, sensors for online measurements of different parameters in pulping and papermaking processes are being developed in recent years. Through this review, better performing multivariate analysis based chemometric modeling techniques have been identified for determining different parameters by comparing the existing ones which could be used in different processes in pulp and papermaking industries. [ABSTRACT FROM AUTHOR]

The rapid expansion of varied network systems, including the Internet of Things (IoT) and the Industrial Internet of Things (IIoT), has led to an increasing range of cyber threats. Ensuring robust protection against these threats necessitates the implementation of an effective Intrusion Detection System (IDS). For more than a decade, researchers have delved into supervised machine learning techniques to develop IDS to classify normal and attack traffic. However, building effective IDS models using supervised learning requires a substantial number of benign and attack samples. To collect a sufficient number of attack samples from real-life scenarios is not possible since cyber attacks occur occasionally. Further, IDS trained and tested on known datasets fails in detecting zero-day or unknown attacks due to the swift evolution of attack patterns. To address this challenge, we put forth two strategies for semi-supervised learning-based IDS where training samples of attacks are not required: (1) training a supervised machine learning model using randomly and uniformly dispersed synthetic attack samples; (2) building a One Class Classification (OCC) model that is trained exclusively on benign network traffic. We have implemented both approaches and compared their performances using 10 recent benchmark IDS datasets. Our findings demonstrate that the OCC model based on the state-of-art anomaly detection technique called usfAD significantly outperforms conventional supervised classification and other OCC-based techniques when trained and tested considering real-life scenarios, particularly to detect previously unseen attacks. [ABSTRACT FROM AUTHOR]

Polymers synthesized with end-of-life consideration allow for recovery and reprocessing. "Living-anionic polymerization (LAP)" and hydrosilylation reaction were utilized to synthesize hair-end furan functionalized hairy nanoparticles (HNPs) with a hard polystyrene (PS) core and soft polydimethylsiloxane (PDMS) hairs via a one-pot approach. The synthesis was carried out by first preparing the living core through crosslinking styrene with divinylbenzene using sec-butyl lithium, followed by the addition of the hexamethylcyclotrisiloxane (D3) monomer to the living core. The living polymer was terminated by dimethylchlorosilane to obtain the HNPs with Si-H functional end groups. The furan functionalization was carried out by the hydrosilylation reaction between the Si-H of the functionalized HNP and 2-vinyl furan. Additionally, furan functionalized polystyrene (PS) and polydimethylsiloxane (PDMS) were also synthesized by LAP. 1H NMR and ATR-IR spectra confirmed the successful synthesis of the target polymers. Differential scanning calorimetry showed two glass transition temperatures indicative of a polydimethylsiloxane soft phase and a polystyrene hard phase, suggesting that the HNPs are microphase separated. The furan functionalized HNPs form thermo-reversible networks upon crosslinking with bismaleimide (BMI) via a Diels−Alder coupling reaction. The kinetics of the forward Diels–Alder reaction between the functionalized polymer and BMI were studied at three different temperatures: 50 °C, 60 °C, and 70 °C by UV–Vis spectroscopy. The activation energy for the furan functionalized HNPs reaction with the bismaleimide was lower compared to the furan functionalized polystyrene and polydimethylsiloxane linear polymers. The crosslinked polymer network formed from the Diels−Alder forward reaction dissociates at around 140–154 °C, and the HNPs are recovered. The recovered HNPs can be re-crosslinked at 50 °C. The results suggest that furan functionalized HNPs are promising building blocks for preparing thermo-reversible elastomeric networks. [ABSTRACT FROM AUTHOR]

The allosteric SERCA (Sarcoplasmic/Endoplasmic Reticulum Ca2+-ATPase) activator CDN1163 has been recently added to the group of pharmacological tools for probing SERCA function. We chose to investigate the effects of the compound on T lymphocyte Ca2+ stores, using the well-described Jurkat T lymphocyte as a reliable cell system for Ca2+ signaling pathways. Our study identified the lowest concentrations of the SERCA inhibitors thapsigargin (TG) and 2,5-di-(tert butyl)-1,4-benzohydroquinone (tBHQ) capable of releasing Ca2+, permitting the differentiation of the TG-sensitive SERCA 2b Ca2+ store from the tBHQ-sensitive SERCA 3 Ca2+ store. We proceeded to test the effects of CDN1163 on Ca2+ stores, examining specific actions on the SERCA 2b and SERCA 3 Ca2+ pools using our low-dose SERCA blocker regimen. In contrast to previous work, we find CDN1163 exerts complex time-sensitive and SERCA isoform-specific actions on Ca2+ stores. Surprisingly, short-term exposure (0–30 min) to CDN1163 perturbs T cell Ca2+ stores by suppressing Ca2+ uptake with diminished Ca2+ release from the SERCA 2b-controlled store. Concomitantly, we find evidence for a SERCA-activating effect of CDN1163 on the SERCA-3 regulated store, given the observation of increased Ca2+ release inducible by low-dose tBHQ. Intriguingly, longer-term (>12 h) CDN1163 exposure reversed this pattern, with increased Ca2+ release from SERCA 2b-regulated pools yet decreased Ca2+ release responses from the tBHQ-sensitive SERCA 3 pool. Indeed, this remodeling of SERCA 2b Ca2+ stores with longer-term CDN1163 exposure also translated into the compound's ability to protect Jurkat T lymphocytes from TG but not tBHQ-induced growth suppression. [ABSTRACT FROM AUTHOR]

RNA modifications are pivotal in the development of newly synthesized structures, showcasing a vast array of alterations across various RNA classes. Among these, 5-hydroxymethylcytosine (5HMC) stands out, playing a crucial role in gene regulation and epigenetic changes, yet its detection through conventional methods proves cumbersome and costly. To address this, we propose Deep5HMC, a robust learning model leveraging machine learning algorithms and discriminative feature extraction techniques for accurate 5HMC sample identification. Our approach integrates seven feature extraction methods and various machine learning algorithms, including Random Forest, Naive Bayes, Decision Tree, and Support Vector Machine. Through K-fold cross-validation, our model achieved a notable 84.07% accuracy rate, surpassing previous models by 7.59%, signifying its potential in early cancer and cardiovascular disease diagnosis. This study underscores the promise of Deep5HMC in offering insights for improved medical assessment and treatment protocols, marking a significant advancement in RNA modification analysis. [ABSTRACT FROM AUTHOR]

This paper investigates energy and exergy analyses of 660 MW capacity supercritical coal power plant with single reheat and regenerative. The fuel utilized in the plant is a combination of sub‐bituminous and lignite coal. It is found that the turbine section of the system exhibits the highest energy efficiency (around 94.17%) and exergy efficiency (around 90.73%). Also, 82.07% of the total exergy destruction is found for the boiler, and the remaining 17.93% of the irreversibility is determined for the turbine, condenser, and other components. The overall cycle energy efficiency at maximum load is computed as 40.77%, while the overall cycle exergy efficiency at maximum load is found to be 39.69%. These findings provide valuable insights into the performance of the power plant and suggest the improvements needed in performance enhancement of the boiler. [ABSTRACT FROM AUTHOR]

One of the most popular topics in sustainable chemistry is the creation of new eco-friendly solvents. Deep eutectic solvents (DESs) have been established as accessible and affordable substitutes for ionic liquids. Herein, we studied the formation of a novel amino acid-based DES (AADES) considering L -threonine as a hydrogen bond acceptor and glycerol as a hydrogen bond donor. Owing to their complexity, a comprehensive understanding of DESs requires combined efforts that integrate experimental observations with computational approaches. The validation of the synthesized DES was initially performed through FTIR spectroscopy, where significant changes in bond-bending vibrations indicated strong non-covalent bond formation. In differential scanning calorimetry (DSC) analysis, the 1 : 3 Thr/Gly deep eutectic system displayed phase transitions marked by a pronounced peak at −22 °C, which was lower than the melting points of threonine (Thr) and glycerol (Gly). 1H-NMR studies also revealed hydrogen bonding intermolecular interactions between glycerol and threonine. Deshielded chemical shifts of proton signals of both glycerol and threonine are due to the local changes in electron density induced by the closeness of electronegative oxygens via the inductive effect, which supports the formation of the conformer (3 : 1 glycerol/threonine DES). Molecular dynamics (MD) simulation was employed to acquire a comprehensive understanding of how these solvents form and function at both the molecular and macroscopic levels. RDF and CDF analyses revealed the non-bonding sites (C–O⋯H and C＝O⋯H), interaction intensity (2–4.7), and predominant angles (135–180 and 0–30 degrees) governing the process by which hydrogen bonds originate in the DES. SDF uncovered the conformations of the liquid DES and highlighted its variability, particularly in terms of clusters. The bulk properties of DESs are of paramount significance because they are intricately linked to their diverse applications. Transport property values were obtained through specialized MD simulations, providing crucial insights into the behavior of the systems. Non-equilibrium molecular dynamics (NEMD) simulations were performed to assess the rheological properties of viscosity at three distinct temperatures (298 K, 313 K, and 328 K). The obtained viscosity, surface tension, and self-diffusion coefficient values appear practical and fall within a reasonable range when compared to those of other well-known DESs. [ABSTRACT FROM AUTHOR]

Water infrastructure affects the quantity, quality, and environment of water. During reservoir construction, only the social-economic benefits were considered and the health of the downstream river was neglected. Due to the severe downstream river system, the operators and managers faced the challenge of the downstream ecosystem. Many scholars are concerned with the reservoir’s optimum functioning, which considers social and economic advantages. Numerous significant opinions and research findings are being presented on ecological scheduling at the moment, both in China and overseas, which surely deepen the connotations of ecological scheduling and serve as the research basis and critical reference of this work. The influence of hydropower development on hydrological conditions, the categorization and calculation of environmental runoff, and the building and solution of ecological scheduling models are all discussed and researched in this work. The study examined how the ChiTan hydropower project influenced the Jinxi River’s flow. The total hydrologic alteration calculated using RVA is 50.53%. The component analysis is also utilized to eliminate the statistical redundancy in the hydrologic indicators. The indicators’ monthly flow for July and August’s mean minimum flow for 7 days are relevant indicators for the Jinxi River basin’s hydrologic modification regime. [ABSTRACT FROM AUTHOR]

Non-Newtonian fluid threads are common in many natural and synthetic processes. An appreciation of how such threads break into droplets has been a subject of study for a long time. In this paper, we investigate the absolute instability of a cylindrical thread, modeled as a power law fluid, falling under gravity surrounded by an inviscid medium. Particular attention is paid to investigating the effects of the gas-to-liquid density ratio and the Reynolds number as well as the influence of the flow index number on critical Weber numbers (which mark the transition between convective and absolute instability). Our results determine the convective to absolute instability boundary for a number of different parameter values. [ABSTRACT FROM AUTHOR]

This study assessed consumer preferences and consumption patterns for prawns in Bangladesh, underscoring the economic and nutritional significance of prawns in the local diet. A total of 120 respondents were interviewed following a random sampling technique from four districts. The data analysis employed descriptive statistics alongside mathematical and statistical methods. The findings indicate a strong preference for fresh and large-sized prawns among the consumers. Income level substantially influenced the prawn purchases, with the high-income consumers more likely to buy premium prawn products, while the low-income consumers showed sensitivity to price changes. The primary concerns that significantly influenced the consumers' purchasing decisions were found to be size, freshness, taste, price, market availability, and income. Additionally, the consumers' perceived value and willingness-to-pay for prawns were significantly driven by size, freshness, environmental sustainability, and income levels. Policy recommendations include promoting sustainable prawn farming and improving accessibility for low-income consumers to enhance both nutritional intake and economic resilience. This research offers valuable insights for stakeholders in the prawn industry, facilitating the development of targeted marketing strategies and informed policymaking for sustainable industry growth. [ABSTRACT FROM AUTHOR]

This study documented the lesser-known indigenous fruits and vegetables used in a montane area of high biocultural diversity in Bangladesh, the Chittagong Hill Tracts (CHTs), and analyzed the nutritional values of selected species. Over 125 species were noted, and based on their frequent uses, 10 plant species were selected for nutritional analysis. All of the analyzed fruits and vegetables contain significant amounts of nutrients. Adoption of these species as alternative sources of food in other parts of Bangladesh could play a key role in improving livelihood and well-being in marginal communities. [ABSTRACT FROM AUTHOR]

The Metaverse, distinguished by its capacity to integrate the physical and digital realms seamlessly, presents a dynamic virtual environment offering diverse opportunities for engagement across innovation, entertainment, socialization, and commercial endeavors. However, the Metaverse is poised for a transformative evolution through the convergence of contemporary technological advancements, including artificial intelligence (AI), Blockchain, Robotics, augmented reality, virtual reality, and mixed reality. This convergence is anticipated to revolutionize the global digital landscape, introducing novel social, economic, and operational paradigms for organizations and communities. To comprehensively elucidate the future potential of this technological fusion and its implications for digital innovation, this research endeavors to undertake a thorough analysis of scholarly discourse and research pertaining to the Metaverse, AI, Blockchain, and associated technologies. This survey delves into various critical facets of the Metaverse ecosystem, encompassing component analysis, exploration of digital currencies, assessment of AI utilization in virtual environments, and examination of Blockchain's role in enhancing digital content and data security. Leveraging articles retrieved from esteemed digital repositories including ScienceDirect, IEEE Xplore, Springer Nature, Google Scholar, and ACM, published between 2017 and 2023, this study adopts an analytical approach to engage with these materials. Through rigorous examination and discourse, this research aims to provide insights into the emerging trends, challenges, and future directions in the convergence of the Metaverse, Blockchain, and AI. This article is categorized under:Application Areas > Industry Specific Applications [ABSTRACT FROM AUTHOR]

Background: Fiber-matrix debonding is a precursor for transverse cracking and several other types of damage in fiber composites. However, to date, there are limited experiment-based reports that study the fundamental mechanisms of fiber-matrix debonding. Objective: This work aims to uncover the governing mechanisms of fiber-matrix interface debonding by full-field measurements supplemented by numerical simulations. In particular, the application of a dual-vision image-based characterization approach on single glass macro fiber samples is discussed and proven useful in understanding the in-plane and out-of-plane debonding characteristics at the fiber-matrix interface. Methods: Full-field strain and displacement measurements based on digital image correlation are performed on model single-fiber composites. The use of a dual-vision system allows strain measurements in the vicinity of the fiber-matrix interface, also allowing for the identification of critical strain and stress values corresponding to the initiation and propagation of debonding damage. The experimental data are used to calibrate an inverse identification approach that outputs the shape of the debonded interface along the fiber length. Results: Full-field measurements allow for establishing correlations between local and global strain fields. Observation of debonding propagation along the fiber axis seems to be representative of the crack tunneling during the early stages of the failure process, i.e., when the crack tip is subjected to opening mode only. Conclusions: Side view measurements are useful as a first-order approximation of the debonding propagation velocity along the fiber axis but fail to provide accurate measurements for the debonding shape, esp. in areas where the crack is under a dominantly shear stress state. This issue can be resolved by full-field measurements coupled with computational simulations. [ABSTRACT FROM AUTHOR]

The availability of fresh water is limited compared to its huge consumption. Conversely, certain industries like dyes, textiles, paper, and tanning not only consume vast quantities of fresh water, but also generate significant amounts of wastewater that poses severe threats to living organisms. The present investigation focuses on the degradation of Rhodamine-B (Rh–B) as a model pollutant by using the nanocomposite based on waste scrap tire-derived activated carbon (AC) and titanium dioxide (TiO 2). These nanostructures were fabricated using wet chemistry techniques. Analysis using scanning electron microscopy (SEM) revealed that the morphology of the structures remained largely unchanged even with a concentration of 6 mg of AC. X-ray diffraction (XRD) results confirmed the successful fabrication of rutile and anatase phases of TiO 2 @AC nanocomposite. The XPS results confirmed the presence of AC and TiO 2 in the composite. Furthermore, the optical band gap of the nanocomposites decreased up to 17.17 % and 34.57 % through direct and indirect methods respectively, owing to the varying quantity of AC used. The narrowing of optical band gap and the increased surface oxygen vacancies were caused by the successive addition of AC during the synthesis of nanocomposites. This resulted in the efficient degradation of Rhodamine-B (Rh–B) using adsorption and photocatalytic oxidation. The findings demonstrate a significant influence of AC on the TiO 2 catalyst in the removal of Rh–B dye. The maximum efficiency of dye removal, reaching up to 99.14 %, was achieved with the highest concentration of AC, thus demonstrating almost complete elimination of Rh–B dye. The findings suggest that the use of waste scrap tires can be effectively applied to design efficient photocatalysts for addressing the wastewater management issues. [ABSTRACT FROM AUTHOR]

AbstractMicroplastics (MPs) possess a strong capacity to adsorb and biodegrade slowly, resulting in substantial harm to the environment and potential health risks. In recent years, a flourishing study of MPs has led to valuable advancements. This review article presents a comprehensive bibliometric analysis of global microplastic pollution, providing a deep understanding of published data, current progress, research trends, and focal points. We conducted extensive searches in the Scopus and Web of Science Core Collection databases from 2012 to 2021, utilizing the widely used R software for analysis. Our findings demonstrate a significant increase in micro(nano)plastic publications, with a growth rate of 73.0% from 2012 to 2021. China emerges as the predominant contributor in this field. The journal Science of the Total Environment has published the highest proportion of relevant articles (16.1%) and received the most citations (9801). The analysis further emphasizes polymer products and MPs as key research areas in the past decade. This study serves as a fundamental basis for future investigations into micro(nano)plastic pollution’s impacts on terrestrial and aquatic ecosystems. [ABSTRACT FROM AUTHOR]

The prevalence of various kidney diseases has become a significant threat to global public health and one of the leading causes of severe morbidity and high mortality. Multiple extrinsic or intrinsic factors, including drug or chemotoxicity, aging biomarkers, and various aging-related disorders, may exacerbate multiple kidney diseases and subsequently lead to end-stage renal disease (ESRD). In addition, the complications of kidney pathologies further pose challenges to current clinical practices. However, amid the development of various novel therapeutic approaches against kidney diseases, the interest in natural products or nutraceutical-based treatments has been growing and active in research on renal disorders. Amongst these, luteolin-a flavone, has been shown to be potent in combatting kidney disorders by effectively preventing and ameliorating the progression of various kidney biomarkers and associated pathologies. Therefore, this systemic review assimilates the evidence of numerous in-vitro and in-vivo studies along with the progress in luteolin-based drug development to enlighten its pharmacological potency in treating kidney disorders. The existing reports strongly support the promising therapeutic benefits of luteolin and thus, the review suggests conducting clinical studies to establish it as a potent therapeutic agent against kidney diseases. [ABSTRACT FROM AUTHOR]

Rapid urbanization, industrialization, and population growth have led to significant changes in land use and land cover (LULC) across cities in developing countries, particularly in Bangladesh. This study investigates the LULC changes in Narayanganj District, one of the fastest-growing regions in Bangladesh, over a 20-year period (2000–2020). Using Google Earth Engine (GEE) and the Random Forest (RF) classifier, Landsat 7 Enhanced Thematic Mapper Plus (ETM+) images were analyzed to classify five major LULC types: urban, bare land, water bodies, vegetation, and cropland, with an overall accuracy of 97.8%, 100%, 95.8%, 97.8%, and 96.4% for the years 2000, 2005, 2010, 2015, and 2020, respectively. The study demonstrates a marked increase in urban areas, with an 88.06% rise, accompanied by a 70.77% reduction in bare land and a 36.72% decrease in water bodies. Vegetation showed a significant growth of 74.64%, possibly due to reforestation efforts, natural regrowth of abandoned lands, or conversion of lower-intensity agricultural land. Meanwhile, cropland experienced minor changes, maintaining its area over time. The results highlight the rapid pace of urbanization, driven by Narayanganj’s proximity to Dhaka and its role as an economic hub. This expansion poses environmental challenges, such as the loss of critical land resources and the reduction of water bodies, which could exacerbate urban heat island effects and water scarcity issues. The analysis of urban expansion and its encroachment on agricultural and natural landscapes stresses the urgent need for sustainable land-use planning to balance urban growth with environmental conservation. The study offers a novel approach by leveraging GEE’s cloud-computing capabilities for large-scale LULC monitoring, making it an efficient and scalable tool for analyzing land cover changes in rapidly urbanizing areas. These findings contribute valuable insights for policymakers and urban planners, ensuring sustainable development while addressing environmental and socio-economic concerns. This methodology can be extended to other regions, facilitating informed decision-making in land management and urban planning globally. [ABSTRACT FROM AUTHOR]

β-phase gallium oxide (Ga2O3) is an emerging ultrawide bandgap (UWBG) semiconductor with a bandgap energy of ∼ 4.8 eV and a predicted high critical electric field strength of ∼8 MV/cm, enabling promising applications in next generation high power electronics and deep ultraviolet optoelectronics. The advantages of Ga2O3 also stem from its availability of single crystal bulk native substrates synthesized from melt, and its well-controllable n-type doping from both bulk growth and thin film epitaxy. Among several thin film growth methods, metalorganic chemical vapor deposition (MOCVD) has been demonstrated as an enabling technology for developing high-quality epitaxy of Ga2O3 thin films, (AlxGa1−x)2O3 alloys, and heterostructures along various crystal orientations and with different phases. This tutorial summarizes the recent progresses in the epitaxial growth of β-Ga2O3 thin films via different growth methods, with a focus on the growth of Ga2O3 and its compositional alloys by MOCVD. The challenges for the epitaxial development of β-Ga2O3 are discussed, along with the opportunities of future works to enhance the state-of-the-art device performance based on this emerging UWBG semiconductor material system. [ABSTRACT FROM AUTHOR]

Iron homeostasis is vital for normal physiology, but in the majority of circumstances, like iron overload, this equilibrium is upset leading to free iron in the plasma. This condition with excess iron is known as hemochromatosis, which has been linked to many side effects, including cancer and liver cirrhosis. The current research aimed to investigate active molecules from Streptomyces sp. isolated from the extreme environment of Bahawalpur deserts. The strain was characterized using 16 S rRNA sequencing. Chemical analysis of the ethyl acetate cure extract revealed the presence of phenols, flavonoids, alkaloids, and tannins. Multiple ultraviolet (UV) active metabolites that were essential for the stated pharmacological activities were also demonstrated by thin layer chromatography (TLC) and high-performance liquid chromatography (HPLC). Additionally, Gas chromatography/mass spectrometry (GC-MS) analysis revealed the primary constituents of the extract to compose of phenol and ester compounds. The 2,2-diphenyl-1-picrylhydrazyl (DPPH) assay was used to assess the extract's antioxidant capacity, and the results showed a good half-maximal inhibitory concentration (IC50) value of 0.034 µg/mL in comparison to the positive control ascorbic acid's 0.12 µg/mL. In addition, iron chelation activity of extract showed significant chelation potential at 250 and 125 µg/mL, while 62.5 µg/mL showed only mild chelation of the ferrous ion using ethylene diamine tetra acetic acid (EDTA) as a positive control. Likewise, the extract's cytotoxicity was analyzed through 3-(4,5-Dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assay using varying concentrations of the extract and showed 51% cytotoxicity at 350 µg/mL and 65% inhibition of cell growth at 700 µg/mL, respectively. The bioactive compounds from Streptomyces sp. demonstrated strong antioxidant and iron chelating potentials and can prolong the cell survival in extreme environment. [ABSTRACT FROM AUTHOR]

Triple-negative breast cancer (TNBC), the most aggressive subtype, presents a critical challenge due to the absence of approved targeted therapies. Hence, there is an urgent need to identify effective therapeutic targets for this condition. While epidermal growth factor receptor (EGFR) is prominently expressed in TNBC and recognized as a therapeutic target, anti-EGFR therapies have yet to gain approval for breast cancer treatment due to their associated side effects and limited efficacy. Here, we discovered that intercellular adhesion molecule-1 (ICAM-1) exhibits elevated expression levels in metastatic breast cancer and serves as a pivotal binding adaptor for EGFR activation, playing a crucial role in malignant progression. The activation of EGFR by tumor-expressed ICAM-1 initiates biased signaling within the JAK1/STAT3 pathway, consequently driving epithelial-to-mesenchymal transition and facilitating heightened metastasis without influencing tumor growth. Remarkably, ICAM-1-neutralizing antibody treatment significantly suppressed cancer metastasis in a breast cancer orthotopic xenograft mouse model. In conclusion, our identification of ICAM-1 as a novel tumor intrinsic regulator of EGFR activation offers valuable insights for the development of TNBC-specific anti-EGFR therapies. [ABSTRACT FROM AUTHOR]

Despite its impressive economic growth, Bangladesh faces a persistent malnutrition challenge, costing over US$1 billion annually. The broiler industry plays a vital role in addressing nutritional needs by providing essential protein through meat and eggs. However, small and medium enterprises (SMEs) in this sector struggle with high feed prices, impacting their profitability and growth. Black Soldier Fly Larvae (BSFL) offers a sustainable and cost-effective alternative to conventional poultry feed, addressing both rising costs and environmental impacts. This study examined different aspects of BSFL, such as broiler feed, and farmers' perceptions of them in some selected areas of the Sylhet region of Bangladesh. A total of 60 respondents from three subdistricts in Sylhet district were selected using the purposive sampling technique. Data were analyzed through descriptive statistics, discriminative power value, binary logistic regression model, and profitability equation. Among the respondents, 70% (42) had a favorable attitude toward BSFL, and 30% (18) had a highly favorable attitude towards BSFL. Among eight socioeconomic attributes examined for the likeliness of adopting BSFL as broiler feed, the respondents' average income (p < 0.01), years of schooling (p < 0.05), and years of broiler farming experience (p < 0.01) were found to be significant. Further, farms using 50% BSFL and 50% traditional feed had a net return of BDT (Bangladeshi Taka) 35,045.67 (USD 419.71), higher than those using traditional feed, which had a net return of BDT 29670.67 (USD 355.38). Further, farms using 50% BSFL and 50% traditional feed had a benefit–cost ratio (BCR) of 1.16, compared to other farms with a BCR of 1.11. The study also found some problems causing slow growth in the adoption rate of BSFL in the study region, such as lack of training programs, extension campaigns, the uncertainty of input supply, and financial assistance. The study suggests making adequate measures to raise awareness about the profitability of BSFL as broiler feed, conducting training at the root level, and making inputs easily available to farmers. [ABSTRACT FROM AUTHOR]

In this research, the influences of quadratic Boussinesq approximation and quadratic thermal radiation on the heat transfer analysis of magnetized Sisko nanofluid flow with Cattaneo–Christov heat flux through stretching surfaces are studied. The formulated mathematical model is solved by the finite difference technique, and heat transfer rate and skin friction coefficients are computed for acting parameters, i.e., magnetic field, Eckert number, Forchheimer parameter, thermal relaxation parameter, radiation parameter, porosity parameter and Biot number. For sensitivity analysis, the response surface method (RSM) with a face-centered central composite design is utilized. The RSM is elucidated by applying nonlinear regression, analysis of variance and goodness of fit. The results indicate that the friction coefficient and Nusselt number have positive sensitivities for the Forchheimer parameter. The heat transfer rate decreases with an increase in magnetic field, Biot number and thermal relaxation parameter values for shear thickening (n > 1) and shear thinning (n < 1). Further for n < 1, a one unit increase in A1 leads to a 33% drop in SFC and 48% in LNN; and an increase of 8 units in Fr leads to a 67.18% rise in LNN. [ABSTRACT FROM AUTHOR]

Over the last few decades, governance systems across the world have prioritised citizen participation. Direct participation of the citizenry facilitates social accountability, which contributes to the advancement of good governance. In Bangladesh, following the success of donor-funded pathfinder projects, various social accountability mechanisms were legally mandated at the local level. This study examines the prescribed functioning of these mechanisms and compares this to actual practice. The study followed an explanatory, descriptive method for content analysis by reviewing relevant secondary literature. Key findings were: no practical guidelines exist in Bangladesh for managing social accountability mechanisms; citizens have limited access to information; local functionaries have insufficient understanding of their role; and social accountability has not been institutionalised. To ensure successful social accountability, it will be necessary to provide adequate guidelines, take financial and management factors into account, and make people aware of their rights. Government and NGO intervention on the demand side (local people) will be required to make this happen. [ABSTRACT FROM AUTHOR]

Conventional solid-state reaction method has been cautiously employed to prepare the Ba0.75Sr0.25Ti1−xMnxO3 ceramic where Sr was firmly doped at the Ba site and Mn was doped with different densities at the Ti site. Since the performance of materials varies with frequency, electric field, and temperature, we have elucidated the various features of the synthesized samples for the sake of scientific benefit in the fields of microelectronics, telecommunications, and spintronics. Structural and morphological features of the ready samples were examined by X-ray diffraction and scanning electron microscopy (SEM). The crystal's tetragonal behavior was verified by XRD analysis, and with the increment of Mn content, the volume of the unit cell is little changed. It is clear from the SEM images that the grain size of the prepared samples increases with Mn doping. The dielectric properties of Ba0.75Sr0.25Ti1−xMnxO3 were measured by dielectric constant and AC conductivity in a wide range of frequency from 1 kHz to 10 MHz. This result also explores that the dielectric constant rises with the concentration of Mn, most significantly for the 20% Mn substitution with Ti. We also found from the experimental result that the dielectric constant is high in the frequency range of 1–10 kHz. The magnetic permeability of the prepared sample increased with 10% and 20% of Mn replacement. Ferromagnetic features with a weak coercive field and the increased ferromagnetic order with rising Mn concentrations of the prepared samples were confirmed by VSM data analysis. The developed multiferroic materials can be employed in future spintronic devices like spin transistors, sensors, spin diodes, and memory devices. [ABSTRACT FROM AUTHOR]