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Abstract Preserving the quality of groundwater has become Bangladesh’s primary challenge in recent years. This study explores temporal trend variations in groundwater quality on a broader scale across 18 stations within the Dhaka division over 35 years. The data set encompasses an analysis of 15 distinct water quality parameters. Modified Mann-Kendal, Sens Slope and Mann-Kendal tests were performed to determine the trend’s variation and slope. In addition, the spatial–temporal changes in the quality of groundwater are studied through Geographic Information System (GIS) mapping and Piper diagram was applied to identify the unique hydrochemical properties. This is the first study conducted on this area using various trends analysis and no in-depth study is available highlighting the trends analysis of groundwater quality on a larger magnitude. In contrast, the correlation matrix reveals a high association between Mg2+ and SO4 2−, Na+ and Cl− that affects salinity and overall hardness at the majority of sites. The Piper diagram also demonstrates that the groundwater in Madaripur Sadar has major salinity issues. The analysis reveals a distinctive dominance of bicarbonate (HCO3 −) ions across all sampling stations, with (HCO3 −) equivalent fractions consistently ranging from 0.70 to 0.99 which can cause a significant impact on groundwater uses. This extensive analysis of long-term groundwater quality trends in the Dhaka Division enables researchers to comprehend the overall transition of groundwater quality for hardness related complications in future. Moreover, it can be a baseline study considering the valuable implications and future steps for sustainable water resource management in this region.

Abstract Textile coloration is a complex process involving the interaction of dye molecules with fibers in a dye bath. Synthetic dyes pose environmental hazards, leading to increased interest in natural dyes sourced from plants, animals, and minerals. However, natural dyes often require mordants for application to textiles. Despite their eco‐friendliness, natural dyes can exhibit poor wash fastness on fabrics, necessitating further research to enhance their performance. This study investigates the use of mahogany sawdust extract as a natural dye for cotton coloration, focusing on the enhancement of fastness properties through metallic mordants and associated environmental risks. Mahogany sawdust, rich in flavonoids and tannins, shows promise as a sustainable alternative to synthetic dyes. The dyeing process involves the extraction of natural dyes from sawmill bio‐waste and subsequent application onto cotton fabrics using various metallic mordants. Evaluation of colorfastness properties, color strength, color coordinates, tensile strength, FTIR, and SEM analysis provides insights into the dye‐fiber interactions and fabric properties. Environmental risk assessment considers metal exhaustion onto fabric surfaces, residual metal concentrations in mordant baths, and metal content in dyeing wastewater. Overall, this study contributes to the development of sustainable dyeing processes and highlights the importance of environmental considerations in textile coloration. Highlights Mahogany sawdust extract: potential natural dye for sustainable cotton coloration. Metallic mordants enhance colorfastness and fabric durability in dyeing processes. Comprehensive analysis reveals the intricate dynamics of dye‐fiber interactions. Environmental risk evaluation guides sustainable textile manufacturing practices. Research paves the way for greener, more sustainable textile industry practices globally.

The PHLDA (pleckstrin homology-like domain family) gene family is popularly known as a potential biomarker for cancer identification, and members of the PHLDA family have become considered potentially viable targets for cancer treatments. The PHLDA gene family consists of PHLDA1, PHLDA2, and PHLDA3. The predictive significance of PHLDA genes in cancer remains unclear. To determine the role of pleckstrin as a prognostic biomarker in human cancers, we conducted a systematic multiomics investigation. Through various survival analyses, pleckstrin expression was evaluated, and their predictive significance in human tumors was discovered using a variety of online platforms. By analyzing the protein–protein interactions, we also chose a collection of well-known functional protein partners for pleckstrin. Investigations were also carried out on the relationship between pleckstrins and other cancers regarding mutations and copy number alterations. The cumulative impact of pleckstrin and their associated genes on various cancers, Gene Ontology (GO), and pathway analyses were used for their evaluation. Thus, the expression profiles of PHLDA family members and their prognosis in various cancers may be revealed by this study. During this multiomics analysis, we found that among the PHLDA family, PHLDA1 may be a therapeutic target for several cancers, including kidney, colon, and brain cancer, while PHLDA2 can be a therapeutic target for cancers of the colon, esophagus, and pancreas. Additionally, PHLDA3 may be a useful therapeutic target for ovarian, renal, and gastric cancer.

Kidney cancer has emerged as a major medical problem in recent times. Multiple compounds are used to treat kidney cancer by triggering cancer-causing gene targets. For instance, isoquercitrin (quercetin-3-O-β-d-glucopyranoside) is frequently present in fruits, vegetables, medicinal herbs, and foods and drinks made from plants. Our previous study predicted using protein-protein interaction (PPI) and molecular docking analysis that the isoquercitrin compound can control kidney cancer and inflammation by triggering potential gene targets of IGF1R, PIK3CA, IL6, and PTGS2. So, the present study is about further in silico and in vitro validation. We performed molecular dynamic (MD) simulation, gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis, cytotoxicity assay, and RT-PCR and qRT-PCR validation. According to the MD simulation (250 ns), we found that IGF1R, PIK3CA, and PTGS2, except for IL6 gene targets, show stable binding energy with a stable complex with isoquercitrin. We also performed gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses of the final targets to determine their regulatory functions and signaling pathways. Furthermore, we checked the cytotoxicity effect of isoquercitrin (IQ) and found that 5 μg/mL and 10 μg/mL doses showed higher cell viability in a normal kidney cell line (HEK 293) and also inversely showed an inhibition of cell growth at 35% and 45%, respectively, in the kidney cancer cell line (A498). Lastly, the RT-PCR and qRT-PCR findings showed a significant decrease in PTGS2, PIK3CA, and IGF1R gene expression, except for IL6 expression, following dose-dependent treatments with IQ. Thus, we can conclude that isoquercitrin inhibits the expression of PTGS2, PIK3CA, and IGF1R gene targets, which in turn controls kidney cancer and inflammation.

Rare ginsenoside compound K (CK) is an intestinal microbial metabolite with a low natural abundance that is primarily produced by physicochemical processing, side chain modification, or metabolic transformation in the gut. Moreover, CK exhibits potent biological activity compared to primary ginsenosides, which has raised concerns in the field of ginseng research and development, as well as ginsenoside-related dietary supplements and natural products. Ginsenosides Rb1, Rb2, and Rc are generally used as a substrate to generate CK via several bioconversion processes. Current research shows that CK has a wide range of pharmacological actions, including boosting osteogenesis, lipid and glucose metabolism, lipid oxidation, insulin resistance, and anti-inflammatory and anti-apoptosis properties. Further research on the bioavailability and toxicology of CK can advance its medicinal application. The purpose of this review is to lay the groundwork for future clinical studies and the development of CK as a therapy for metabolic disorders. Furthermore, the toxicology and pharmacology of CK are investigated as well in this review. The findings indicate that CK primarily modulates signaling pathways associated with AMPK, SIRT1, PPARs, WNTs, and NF-kB. It also demonstrates a positive therapeutic effect of CK on non-alcoholic fatty liver disease (NAFLD), obesity, hyperlipidemia, diabetes, and its complications, as well as osteoporosis. Additionally, the analogues of CK showed more bioavailability, less toxicity, and more efficacy against disease states. Enhancing bioavailability and regulating hazardous variables are crucial for its use in clinical trials.

This research explores the effectiveness of two hybrid composites, pattern-1 (K-M-G-K-M-G-G-M-K) and pattern-2 (K-M-G-K-M-G-K-M-G), in experimental and simulation tests to create a cost-efficient hybrid composite. The composite includes Mulberry (M) silk (Bombyx mori) fibers reinforcing an epoxy resin-matrix hybrid with Kevlar (K) and Glass fiber (G). Both pattern-1 and pattern-2 are evaluated through experimental tests, and simulation tests are conducted to validate the findings. ANSYS Workbench is used for simulation tests to determine the best stacking sequence for protective gears, aerospace components, automotive parts, sport equipment and marine applications. The structural morphology of the hybrid composites is examined using scanning electron microscope (SEM). The results show that pattern-1 performs better than pattern-2 in various experimental and simulation tests, with a wider plastic zone in the tensile test stress-strain curve, greater tensile strength (73 MPa and 67.923 MPa), higher load-bearing capacity, and enhanced ductility. Pattern-1 also demonstrates improved performance in flexural strength (45.35 MPa and 71.474 MPa) and impact strength (6 J and 5.4898 J). Simulation results confirm that pattern-1 is superior to pattern-2 in terms of energy absorption and resistance to bullet penetration.

Commercial microalgae cultivation is a dynamic field with ongoing efforts to improve efficiency, reduce costs, and explore new applications. We conducted a study to examine how different light exposure periods affect Chlorella vulgaris's growth. We employed a Phyto tank batch system of approximately 3.5 L with LED light control, controlled airflow, and sterilized bags, maintained at 22.0 ± 2.0 °C indoors. Various methods, including spectrophotometry, and cell counter were employed to monitor Chlorella vulgaris growth under different light exposure cycles. Additionally, quality analysis as feed source was employed by proximate, amino acid, beta-glucan, and microbial content analysis. The results revealed significant variations in C. vulgaris biomass production based on light exposure duration. Notably, the 16:8-h light-dark photoperiod exhibited the highest biomass concentration, reaching 6.48 × 107 ± 0.50 cells/mL with an optical density (OD) of 1.165 absorbance at 682 nm. The 12:12-h light-dark photoperiod produced the second-highest biomass concentration, with 2.305 × 106 ± 0.60 cells/mL at an OD of 0.489. Proximate analysis of dry algae powder revealed low lipid content (0.48 %), high protein content (37.61 %), variable ash concentration (average 10.75 %), and a significant carbohydrate fraction (51.16 %) during extended daylight and shorter dark periods. Amino acid analysis identified nine essential amino acids, with glutamic acid being the most abundant (17.7 %) and methionine the least (0.4 %). Furthermore, quality analysis and microbiological assays demonstrated that the C. vulgaris biomass is well-suited for fish and livestock use as a feed source and possibility as human nutraceuticals. These findings can be considered more environmentally friendly and ethically sound due to the absence of genetic modification.

The study aimed to develop fish powder as a promising dietary supplement to combat inadequate nutrition. To achieve this goal, the study assessed the nutritional aspects, including proximate composition, mineral content, amino acid profile, and fatty acid profile, as well as the microbiological quality and heavy metal contents, of six small indigenous fish species. The protein content ranged from 57.73 % to 65.26 %, with G. chapra exhibiting the highest protein content (p < 0.001). In all fish powders, the mineral composition was found in the following order: Na > P > Ca > K> Mg > Fe > Mn > Zn. The results revealed significantly elevated levels of total essential amino acids in A. mola (227.20 mg/g, p < 0.001). The PUFA/SFA ratio (> 0.45) and ω-6/ω-3 fatty acids ratio (< 4.00) were generally optimal. The quality and safety of the fish products for human consumption were confirmed, as both the total colony count and heavy metal concentrations remained below the recommended threshold. All ready-to-use fish products, except A. mola, meet over 20 % of the daily nutritional needs for PLW, infants, and adults. Hence, these findings advocate the utilization of the studied fish species as a dietary supplement to address malnutrition.

The ability to obtain food security is essential to human existence. Secure food access can have a variety of positive effects, such as economic expansion, the creation of jobs, and the eradication of poverty. This study assessed the food security status of farm households and its determinants in the Dinajpur district of Bangladesh. Efforts were also made to assess and compare the socio-economic demographics and item-wise calorie intake among households receiving government and non-government agricultural extension services. One hundred twenty-five (125) farm households receiving government or non-government extension services were selected using a multi-stage random sampling procedure. The percentages, means, and standard deviations were employed to summarise the data gathered during the interviews. The inferential statistical investigation involved using the independent sample t-test, correlation analysis, and multiple regression analysis. The findings revealed that 68.8 percent of the families in the study area were food secure, while food insecurity was more prevalent for those receiving non-government extension services. In addition, significant differences existed between the selected characteristics of the two groups of farmers in terms of age, household head’s education, average family education, household size, farm size, farming experience, annual household income, annual household expenditure, knowledge on food and nutrition, and extension sources contact. There were also large discrepancies between the food item-wise calorie consumption between the two groups of farmers. The major determinants of household food security were dependency ratio, household size, training exposure, annual household income, knowledge on food and nutrition, and extension sources contact. It is recommended that both government and non-government agricultural extension organisations work together in an effective, transparent, and unbiased manner to reduce food insecurity.

Money laundering is the process by which criminals move large sums of illicit money to hidden locations and integrate them as legal funds through existing financial services. The United Nations (UN) estimates that 2 to 5% of global GDP, which is approximately 0.8 to 2.0 trillion dollars, is laundered globally every year. Therefore, accurately identifying such globally alarming activities is crucial for enforcing anti-money laundering (AML) measures. Numerous techniques have been proposed to detect money laundering from transaction graphs of money transfers between bank accounts by analysing the structural and behavioural dynamics of their corresponding dense subgraphs. However, these techniques often do not consider that money laundering usually involves high-volume flows of funds through chains of bank accounts. Moreover, most AML approaches either result in lower detection accuracy or incur higher computational costs, making them less reliable and suitable for real financial systems. Consequently, only a fraction of money laundering activities can be detected and prevented. In this paper, we propose an efficient approach to AML by employing semi-supervised graph learning techniques on a large-scale financial transactional graph in both pipeline settings (i.e., graph embedding models are first trained to generate node embeddings that are combined with additional topological graph features to train binary classifiers) and end-to-end settings (i.e., node classification is performed by training SkipGCN, FastGCN, and EvolveGCN without requiring separate classifiers) to identify nodes involved in potential money laundering activities. We evaluate our approach on four datasets: AMLSim, Elliptic, IBM AML, and SynthAML, with a view to scalability and practicality for real financial systems. Further, we provide local (e.g., how money is laundered between nodes) and global (e.g., what factors contribute to money laundering) explanations of the predictions by highlighting the predominant factors in money laundering cases and elucidating the mechanisms of illicit fund transfers between nodes to enhance the interpretability and transparency of the AML models. Experimental results suggest that our approach is scalable and effective at detecting money laundering from real and synthetic transaction graphs.

The growing demand for fiber-reinforced polymer (FRP) in industrial applications has prompted the exploration of natural fiber-based composites as a viable alternative to synthetic fibers. Using jute–rattan fiber-reinforced composite offers the potential for environmentally sustainable waste material decomposition and cost reduction compared to conventional fiber materials. This article focuses on the impact of different machining constraints on surface roughness and delamination during the drilling process of the jute–rattan FRP composite. Inspired by this unexplored research area, this article emphasizes the influence of various machining constraints on surface roughness and delamination in drilling jute–rattan FRP composite. Response surface methodology designs the experiment using drill bit material, spindle speed, and feed rate as input variables to measure surface roughness and delamination factors. The technique of order of preference by similarity to the ideal solution method is used to optimize the machining parameters, and for predicting surface roughness and delamination, two machine learning-based models named random forest (RF) and support vector machine (SVM) are utilized. To evaluate the accuracy of the predicted values, the correlation coefficient (R2), mean absolute percentage error, and mean squared error were used. RF performed better in comparison with SVM, with a higher value of R2 for both testing and training datasets, which is 0.997, 0.981, and 0.985 for surface roughness, entry delamination, and exit delamination, respectively. Hence, this study presents an innovative methodology for predicting surface roughness and delamination through machine learning techniques.

Abstract Background Depression is a common mental health problem all over the world including Bangladesh. World Health Organization included it in the Mental Health Gap Action Programme as one of its priority conditions. Research on this issue is scanty in Bangladesh. Therefore, we designed to a gender-based household study on associated factors of depression among married adults in Rajshahi City of Bangladesh. Methods We conducted this household cross-sectional study from August 01 to October 31, 2019. A total of 708 married adults currently living together in Rajshahi City were recruited for this study. We applied a multi-stage random sampling technique for selecting samples and used a semi-structured questionnaire to collect necessary information from them. The Patient Health Questionnaire-9 was used for measuring depression and frequency distribution and binary logistic regression model were used for data analysis. Results The prevalence of depression (moderate to severe) was 14.4% (95% CI: 11.9–16.9) among married adults, and females (21.2%, 95% CI: 17.2–25.4) suffered more than males (7.6%, 95% CI: 4.8–10.5). A multiple binary logistic regression model established four main factors of depression among married females: (i) multiple marriage [AOR = 19.982; 95% CI: 10.081–39.610; p

Application of appropriate doses of macro and micronutrients is pre-requisite for maximizing growth and yield of crops. The present study was conducted at the Horticulture Farm of Bangladesh Agricultural University, Mymensingh during the period from October 2022 to February 2023 to assess the effects of different doses of nitrogen (N) and zinc (Zn) on growth and yield of cabbage. The two-factor experiment was laid out in Randomized Complete Block Design (RCBD) with three replications. The first factor was nitrogen having four doses of N, such as N0 = 0 kg/ha, N1 = 100 kg/ha, N2 = 150 kg/ha and N3 = 200 kg/ha and the second factor was Zn having four doses, namely Zn0 = 0 kg/ha, Zn1= 1.5 kg/ha, Zn2 = 2.0 kg/ha, Zn3 = 2.5 kg/ha. Significant variations were noted due to the application of different doses of N and Zn fertilizers in respect of all growth and yield traits studied. Application of N at 200 kg/ha contributed the best outcomes on plant height (32.72 cm), number of leaves per plant (47.86), gross yield per hectare (69.99 tons), marketable yield per hectare (45.98 tons) and the lowest yield per hectare (64.52 tons), marketable yield per hectare (38.37 tons) produced from control treatment. The highest level of zinc Zn3 (2.5 kg/ha) produced the best results on plant height (32.30 cm), number of leaves (48.26) per plant, gross yield per hectare (78.02 tons), marketable yield per hectare (61.62 tons) and the lowest gross yield per hectare (59.17 tons), marketable yield per hectare (29.40 tons) produced from control treatment. The maximum doses of nitrogen and zinc (200 kg/ha and 2.5 kg/ha), respectively showed the best performance on plant height (33.32 cm), number of leaves (49.53) per plant, gross yield per hectare (81.15 tons), marketable yield per hectare (65.78 tons) and the lowest gross yield per hectare (55.41 tons) and marketable yield per hectare (27.28 tons) were obtained from the control treatment. The results of this investigation revealed that application of nitrogen (N) and zinc (Zn) enhanced the affects the growth and yield of cabbage. [Fundam Appl Agric 2023; 8(3.000): 590-601]

Metal nanoparticles made from biological source are currently catching a lot of attention to the researcher because of their versatile application in different fields. Realizing this fact, the present study describe the utilization of Amoora rohituka leaves to prepare silver nanoparticles (AgNPs) and make their characterization along with evaluating bioactivities using different techniques. In UV–Vis spectrum, the highest absorption peak at 446 nm confirmed the formation of AgNPs whereas the FTIR spectrum exposed the participation of phytoconstituents with different functional group that play as reducing and capping agents in AgNPs synthesis. The face centered cubic structure with crystalline nature was found for AgNPs in XRD analysis and SEM captured the spherical-shaped images of nanoparticles with diameter ranging 5.63–23.6 nm. In antioxidant assay, the synthesized AgNPs exhibited prominent free radical scavenging capability for DPPH (IC50: 35.34 μg/mL) and ABTS∙+ (IC50: 10.39 μg/mL) radicals. The antibacterial efficiency of AgNPs can be ranked as Shigella boydii > Staphylococcus aureus > Escherichia coli. Moreover, the AgNPs displayed cytotoxicity against EAC cells in a dose-dependent pattern (IC50: 15.84 ± 0.85 μg/mL). The overall findings help to conclude that this green manufactured AgNPs might be a promising candidate for many biomedical applications.

This study examines how corporate board features and auditor characteristics in Bangladesh influence the disclosure of key audit matters (KAM) in annual reports from 2018 to 2021. Using ordinary least squares (OLS) regressions, the study finds that factors such as chair gender, the presence of women on the board, audit committee (AC) size, auditor tenure, and client-auditor relationship significantly affect KAM disclosure. However, AC expertise, family CEO succession, and board political connections do not have significant effects. Notably, having a family member CEO with a long-tenured auditor has a negative association with KAM disclosure, while a politically connected family CEO has a positive association with such disclosures. Additionally, Big-4 auditors of important clients are negatively associated with KAM disclosure.

The synthesis of silver nanoparticles using plant extracts is a promising field of research due to the versatile biomedical application of metal nanoparticles. In the present study, silver nanoparticles (AgNPs) were synthesized using the aqueous extract of Mikania cordata leaves where extract act as both reducing and capping agents. Successful biosynthesis of AgNPs had been studied using UV Spectrophotometry that recorded the surface plasmonic resonance peak at around 451 nm. The structural properties and morphology of AgNPs were confirmed by scanning electron microscope with Energy dispersive X-ray (SEM/EDX), Fourier transform infrared (FT-IR) and X-ray diffraction (XRD) spectroscopic techniques. In antioxidant assays, AgNPs were found as strong free radical scavenger as ascorbic acid (standard) with the values of 10.06 (EC50, μg/mL) and 20.94 (EC50, μg/mL) for DPPH and ABTS radicals, respectively. In antimicrobial study, the effectiveness of synthesized AgNPs was observed as follows: Shigella boydii > Staphylococcus aureus > Shigella dysenteriae > Escherichia coli. Moreover, the results of cytotoxic assay indicated that AgNPs inhibited the growth of EAC cells in dose-dependent manner. Overall results of this study suggested that the synthesized AgNPs from Mikania cordata leaves have the merits to use in the field of nanomedicines.

Abstract Polymeric hydrogel with the incorporation of nano to submicro-meter sized materials forms an exhilarating new generation of composite hydrogels. Most of the applications of hydrogels are in aqueous environments in which they swell to a very high degree. This emanates from low density of the polymer chains, making them highly inferior in terms of physical strength and their prospective applications. In order to address the weak mechanical properties, hydrogels have successfully prepared with high tensile strength and toughness by reinforcing the acrylamide (AAm) network with 3-methacryloxypropyltrimethoxysilane (MPTS) modified silica particles (MSiO2) as chemical cross-linker. The MSiO2 cross-linkers are prepared from narrow-dispersed silica particles (SiO2) of 100 nm, 200 nm, and 300 nm diameters to investigate the effect of cross-linker sizes on the mechanical strengths of hydrogels. The presence of MSiO2 remarkably increases the stretching ability and toughness of hydrogels compared to conventional hydrogels. The tensile strength, toughness, and Young’s modulus of the hydrogel decrease from 30 to 11 kPa, 409 to 231 kJ/m3, and 0.16 to 0.11 kPa, respectively, while the SiO2 particle size increase from 100 to 300 nm and the concentration of AAm and MSiO2 (%) are kept constant. The compressive strength and toughness of the hydrogel decrease from 34 to 18 kPa and 6 to 4 kJ/m3, respectively, but the Young’s modulus increases from 0.11 to 0.19 kPa. This work is excellent proof of regulating mechanical strength of hydrogel by adjusting the particle size of MSiO2 cross-linkers.

This research paper inquires about different attributes of Computer-aided processes in garments production. This perspective Research was done by our courageous team from 2021 to 2022. It reveals adequate information on the Garments industry's Intension and criteria for choosing CAD/CAM software. For the sake of this Research, we visited more than 600 industries to gather raw data; Every Industry tried to attend this Research from a different region of Bangladesh willingly. After collecting all raw data from the garments industry. The data of the Garments industry was coordinated by Excel program. Consequently, the data was analyzed and implemented statistically to identify the Garments Industry attribute for satisfaction with CAD/CAM software. This process also detects many challenges and defines and advises a proper solution to the problems that the Garments industry is facing in the current situation. This research paper demonstrates adequate information about the Garment's criteria and demand in purchasing garments Computer-aided software.

Background Maternal and infant mortality is a major problem in a developing country like Bangladesh and these deaths are mostly related to incomplete antenatal care (ANC) visits. Adequate ANC visits for women are crucial in controlling maternal and infant mortality. Aims To investigate factors associated with ANC visits among women of reproductive age (15-49) in Bangladesh using the Bangladesh Demographic Health Survey 2017–2018 (BDHS) data. Methods This study included 5012 respondents, of whom 2414 women (48.2%) were complete ANC visits and 2598 women (51.8%) were incomplete ANC visits. Quantile regression was used for analysis indicating that the effects of different covariates functioned differently across the utilization of antenatal care visits. The results revealed the women's educational level, birth order number, sex of household head, and wealth index were highly significant on the lower, middle, and higher quantiles of the number of incomplete ANC visits. Besides, in the higher quantiles (for example, 75% quantile), the place of residence was highly significant. For division variables, Rajshahi, Rangpur, and Khulna were highly significant in lower and middle quantiles, while Dhaka, Khulna, Mymensingh, and Rajshahi were insignificant in higher quantiles. Conclusions This study observed that education, wealth index, birth order of children, and place of residence are associated with utilization of ANC visits and significantly influence maternal mortality. These determinations can help healthcare programmers and policymakers to take appropriate policies and programs for complete antennal care visits among pregnant women in Bangladesh. In order to increase the number of ANC visits among women, it is necessary to establish a mutually coordinated and trusting relationship between the government, non-governmental organizations and NGOs.

(1) Background: A large and diverse microbial population exists in the human intestinal tract, which supports gut homeostasis and the health of the host. Short-chain fatty acid (SCFA)-secreting microbes also generate several metabolites with favorable regulatory effects on various malignancies and immunological inflammations. The involvement of intestinal SCFAs in kidney diseases, such as various kidney malignancies and inflammations, has emerged as a fascinating area of study in recent years. However, the mechanisms of SCFAs and other metabolites produced by SCFA-producing bacteria against kidney cancer and inflammation have not yet been investigated. (2) Methods: We considered 177 different SCFA-producing microbial species and 114 metabolites from the gutMgene database. Further, we used different online-based database platforms to predict 1890 gene targets associated with metabolites. Moreover, DisGeNET, OMIM, and Genecard databases were used to consider 13,104 disease-related gene targets. We used a Venn diagram and various protein−protein interactions (PPIs), KEGG pathways, and GO analyses for the functional analysis of gene targets. Moreover, the subnetwork of protein−protein interactions (through string and cytoscape platforms) was used to select the top 20% of gene targets through degree centrality, betweenness centrality, and closeness centrality. To screen the possible candidate compounds, we performed an analysis of the ADMET (absorption, distribution, metabolism, excretion, and toxicity) properties of metabolites and then found the best binding affinity using molecular docking simulation. (3) Results: Finally, we found the key gene targets that interact with suitable compounds and function against kidney cancer and inflammation, such as MTOR (with glycocholic acid), PIK3CA (with 11-methoxycurvularin, glycocholic acid, and isoquercitrin), IL6 (with isoquercitrin), PTGS2 (with isoquercitrin), and IGF1R (with 2-amino-1-methyl-6-phenylimidazo[4,5-b] pyridine, isoquercitrin), showed a lower binding affinity. (4) Conclusions: This study provides evidence to support the positive effects of SCFA-producing microbial metabolites that function against kidney cancer and inflammation and makes integrative research proposals that may be used to guide future studies.

Existing navigation applications such as Google Maps, Apple maps provide a core service to users to find the shortest path or the path that takes the least amount of time towards a user’s destination. The applications and other research efforts have been sought to include other features such as 3D maps, neighboring facilities, traffic information, and multi-modal alternate route suggestion based on user constraints. None of these, however, take into account an important factor: “user safety while commuting”. Although the common perception of street crime is that it is primarily a problem in the third-world countries, current popular hashtags or topics (e.g. “blacklifematters”) indicate that it is now prevalent in other parts of the world as well. Even existing multi-modal alternative route recommender systems are incapable of adapting to a dynamic set of safety features, are unable to provide new safe path updates in response to real-time commuter responses, and take little or no account of historical on-road events when designing the safe algorithm. In light of the above background, we begin by developing a generic framework, namely On-road Risk Minimization Problem (ORMP). We then introduce a dynamic population-based algorithm, that we call Safe Path for Everyone (SPaFE), that solves ORMP using multi-modal historical and crowdsourced data. Finally, our extensive empirical results demonstrate that SPaFE markedly outperforms the state-of-the-art.

In Natural Language Processing, Parts-of-Speech tagging is a vital component that significantly impacts applications like machine translation, spell-checker, information retrieval, and speech processing. In languages such as English and Dutch, POS tagging is considered a solved problem (accuracy: 97%). However, for low-resource languages like Bangla, challenges are still there. In this article, we have proposed a novel RNN-based network named BaNeP to determine parts of speech for Bangla words. The proposed network extracts structural features through a bidirectional LSTM-based sub-network, and intricate contextual relations among words of a sentence are identified through an elaborate weighted context extraction procedure. These features are then combinedly utilized to generate the final Parts-of-Speech prediction. Training the model requires only an annotated dataset vanishing the need for any hand-crafted features. Experimental results on the LDC2010T16 dataset show significant accuracy improvement compared to existing Bangla POS taggers.

Artificial intelligence (AI) systems are increasingly used in health and personalized care. However, the adoption of data-driven approaches in many clinical settings has been hampered due to their inability to perform in a reliable and safe manner to leverage accurate and trustworthy diagnoses. A critical and challenging usage scenario for AI is aiding the treatment of cancerous conditions. Providing accurate diagnosis for cancer is a challenging problem in precision oncology. Although machine learning (ML)-based approaches are very effective at cancer susceptibility prediction and subsequent treatment recommendations, ML models can be vulnerable to adversarial attacks. Since adversarially weak models can lead to wrong clinical recommendations, such vulnerabilities is critical – especially when AI-guided systems are used to aid medical doctors. Therefore, it is indispensable that healthcare professionals employ trustworthy AI tools for predicting and assessing disease risks and progression. In this paper, we propose an adversary-aware multimodal convolutional autoencoder (MCAE) model for cancer susceptibility prediction from multi-omics data consisting of copy number variations (CNVs), miRNA expression, and gene expression (GE). Based on different representational learning techniques, the MCAE model learns multimodal feature representations from multi-omics data, followed by classifying the patient cohorts into different cancer types on multimodal embedding space that exhibit similar characteristics in end-to-end setting. To make the MCAE model robust to adversaries and to provide consistent diagnosis, we formulate robustness as a property, such that predictions remain stable with regard to small variations in the input. We study different adversarial attacks scenarios and take both proactive and reactive measures (e.g., adversarial retraining and identification of adversarial inputs). Experiment results show that the MCAE model based on latent representation concatenation (LRC) exhibits high confidence at predicting cancer types, giving an average precision and Matthews correlation coefficient (MCC) scores of 0.9625 and 0.8453, respectively and shows higher robustness when compared with state-of-the-art approaches against different attack scenarios w.r.t. ERM and CLEVER scores. Overall, our study suggests that a well-fitted and adversarially robust model can provide consistent and reliable diagnosis for cancer.

The World Health Organization declared coronavirus disease 2019 (COVID-19) a pandemic on March 11, 2020. COVID-19, the current global health emergency, is wreaking havoc on human health systems and, to a lesser degree, on animals globally. The outbreak has continued since the first report of COVID-19 in China in December 2019, and the second and third waves of the outbreak have already begun in several countries. COVID-19 is expected to have adverse effects on crop production, food security, integrated pest control, tourism, the car industry, and other sectors of the global economy. COVID-19 induces a range of effects in livestock that is reflected economically since human health and livelihood are intertwined with animal health. We summarize the potentially harmful effects of COVID-19 on livestock and possible mitigation steps in response to this global outbreak. Mitigation of the negative effects of COVID-19 and future pandemics on livestock requires the implementation of current guidelines.

Trichosanthes dioica seed extract was loaded on a QA-cellulose column and the unbound fraction with the chitinase activity was run on SDS-PAGE. Multiple bands were observed and were separated by a Sephadex G-50 column. The combination of the 6 and 33 kDa masses supported the degradation of chitinase as purified earlier. Only the 33 kDa fraction contained sugar and showed chitinase activity. The chitinase was also isolated by using a chitin column. At 200 µg/ml protein concentration, the chitinase inhibited 49.1 %, 48.8 % and 38.12 % of Ehrlich ascites carcinoma, HCT-116 and MCF-7 cells growth, respectively, in a dose-dependent manner. Exactly, 46 % and 82 % EAC cell growth inhibition were observed after treating the EAC cells bearing Swiss albino mice with the chitinase at the doses of 1.0 and 2.0 mg/Kg/day respectively. EAC, HCT-116 and MCF-7 cells growth inhibitions were due to the induction of apoptosis. ROS was accumulated in HCT-116 and MCF-7 cells. After treatment of HCT-116 cells, the expression level of p53 and TNFα genes increased and PARP gene decreased. On the other hand, elevated expression was observed for PARP, MAPK, NFκB, FAS, FADD, and Caspase-8 genes in MCF-7 cells. The induction of apoptosis in HCT-116 was further confirmed by caspase protein expression. The chitinase causes ‘S’ cell cycle arrest in MCF-7 and HCT-116 cells. T. dioica seed chitinase inhibited EAC, HCT-116 and MCF-7 cells by inducing apoptosis in vitro and EAC in vivo in mice. These promising results indicated that T. dioica seed chitinase can be an anticancer agent.

The co-existence of the colistin resistance (mcr) gene with multiple drug-resistance genes has raised concerns about the possibility of the development of pan-drug-resistant bacteria that will complicate treatment. This study aimed to investigate the antibiotic resistance profiles and co-existence of antibiotic resistance genes among the colistin-resistant Enterobacteriaceae isolates recovered from poultry and poultry meats. The antibiotic susceptibility to various classes of antibiotics was performed using the Kirby-Bauer disk diffusion method and selected antimicrobial resistance genes were detected using PCR in a total of 54 colistin-resistant Enterobacteriaceae isolates including Escherichia coli (E. coli) (n = 32), Salmonella spp. (n = 16) and Klebsiella pneumoniae (K. pneumoniae) (n = 6) isolates. Most of the isolates had multi-drug resistance (MDR), with antibiotic resistance against up to seven classes of antibiotics. All mcr-harbouring, colistin-resistant Enterobacteriaceae isolates showed this MDR (100%) phenotype. The mcr-1 harbouring E. coli isolates were co-harbouring multiple antibiotic resistance genes. The seven most commonly identified resistance genes (blaTEM, tetA, floR, aac-3-IV, aadA1, fosA, aac(6_)-lb) were detected in an mcr-1-harbouring E. coli isolate recovered from a cloacal swab. The mcr-5 harbouring Salmonella spp. isolate recovered from poultry meats was positive for blaTEM, tetA, floR, aac-3-IV, fosA and aac(6_)-lb genes. In conclusion, the colistin-resistant Enterobacteriaceae with mcr genes co-existing multiple clinically important antimicrobial resistance genes in poultry and poultry meats may cause potential future threats to infection treatment choices in humans and animals.

This paper has tried to assess the impact of COVID-19 on stock return in different sectors listed under Dhaka Stock Exchange in Bangladesh during the period from 08 March 2020 to 15 September 2020. To measure the impact of COVID-19 on stock return, daily change in number of confirmed cases and deaths have been used as independent variables and DSE stock return has been taken as variable of interest. Data were collected from Bangladesh Government’s official portal, DSE archive and annual reports of listed firms. Sample is selected using two stage sampling method which is a probabilistic model. To test the validity of the used model, Pearson’s correlations analysis, Breusch and Pagan’s heteroscedasticity test, White’s homoscedasticity test and Hausman’s fixed random tests are conducted. After testing the validity, fixed effect method of panel data regression model has been used to test the two hypotheses. The result reveals that most of the sectors responded negatively to the growth in COVID-19 confirmed cases. It is also observed that selected sectors reacted more proactively to the growth in number of deaths as compared to the growth in number of confirmed cases. Where banking and textile sectors are the most sufferers to the growth of both confirmed cases and deaths, pharmaceuticals & chemicals industry proved out to be the gainers. The findings will have policy implications for the regulators as well as for the investors to design the optimum portfolio of investment. The study will add new dimensions to the existing literature.

Applying flame retardant finish on jute makes flame protective jute products that can be another diversified use of it. The target of this experiment is to observe the flame retardancy improvement of the fabric properties after finishing treatment with various flame retardant chemicals. The untreated (raw) and H2O2 bleached jute fabrics having plain weave were used in this experiment. Borax, diammonium phosphate (DAP) and thiourea were used as flame retardant chemicals. The combinations of these chemicals were applied to the fabrics by the pad-dry-cure method with various concentrations. Vertical flammability, breaking load percentage, and weight gain percentage were performed on all samples to observe the change in fabric properties. Significant improvement was found for all chemical combinations compared to untreated fabrics. Here, the flame spread time and weight gain percentage increase, but the breaking load percentage decreases for every combination. Among all combinations, the borax and DAP combination especially at 6% concentration shows the 305% improvement of flame spread time for raw jute and 276% for bleached jute fabric. In contrast, the borax and thiourea combination showed the progress of weight gain percentage. Besides, better wash durability was reported for all samples after five washing cycles. These flame-retardant jute fabrics have prospective industrial applications as brattice cloth in mines and many other potential fields of applications such as flame-retardant kitchen aprons, furnishings for a public hall, theater and hospitals.

Solar disinfection (SODIS) is a simple and low-cost household water treatment (HWT) option used for disinfection of drinking water. In this study, the bacterial inactivation potential of SODIS was evaluated under the solar irradiance observed in different seasons in Bangladesh according to WHO evaluation protocol of HWT, and the SODIS experiments were conducted for both transmissive and reflective reactors using PET bottles and plastic bags. In summer, log reduction value (LRV) more than 5 was observed for the transmissive PET reactors for 6 to 8 hr exposure to sunlight and the treated water complied with the microbial standard of zero colony forming units/100 mL in drinking water. In monsoon and winter, LRV > 4 can be achieved for 16 hr and 8 hr exposure to sunlight, respectively, using reflective reactors. The plastic bag was found to be more effective than PET. A safe exposure time was estimated from the Weibull model to be maintained for SODIS application to achieve 4.0 LRV and also to prevent the re-growth of microorganisms in the treated water. A significant re-growth of microorganisms was observed in the treated water, thus SODIS with other HWT processes can be recommended for use in communities with an unsafe drinking water supply. HIGHLIGHTS Address the effectiveness of SODIS under the local irradiance observed in Bangladesh.; Used both reflective and transmissive reactors.; Complete inactivation achieved under strong sunlight condition.; Reflective reactors are more effective.; A safe exposure time was estimated.;

The purpose of this study is to predict the areas in financial statements susceptive to fraud in the banking sector of Bangladesh. Data of 13 years ranging from 2006 to 2018 of 29 listed banks in Bangladesh were examined for the purpose of this study. Financial data suggested by International Standard on Auditing (ISA) 240 as fraud risk indicators were used as the independent variables and banks identified by Centre for Policy Dialogue (CPD) to be engaged in fraud, scam and heists were taken as dependent variable. Multilayer Perceptron Network (MLP), a class of feedforward Artificial Neural Network (ANN) model was used as the analytical tool. It is found that loan disbursement, assets, profit, operating expenses and tax are the areas that can signal the probable fraud in financial statements of the listed banks of Bangladesh. The findings of this study will have policy implications for auditors and the regulators of money market in Bangladesh.

This work aims to improve the flame retardancy of jute fabric. Raw and bleached plain weave jute fabric was used in this work. Flame retardants borax, diammonium phosphate and thiourea were applied in different concentrations in a raw and bleached jute fabric with the padding method. The influences of flame retardant finishing on the vertical flammability behaviour and tensile properties as well as wash resistance were inves¬tigated. Flame spread time was found to significantly increase when these simple flame retardant finishing agents were used. It was found that the borax-treated raw and bleached specimens exhibited higher flame spread time among all. The assessment of physical properties such as weight gain percentage and breaking load along warp and weft direction of the control and treated fabrics revealed that the increase of flame retardant finishing weight gain caused a decrease in breaking load. Furthermore, the specimens treated with borax and diammonium phosphate flame retardant showed better results than thiourea for flame retardancy and wash durability. These flame retardant jute fabrics have industrial protective textile applications as brattice cloth in mines and many other potential fields of application, e.g. flame retardant kitchen apron, furnishings for public hall, theatre and hospital, etc.

Osteoarthritis (OA) is a degenerative joint disease, which significantly affects middle-aged and elderly people. Although primarily identified via hyaline cartilage change based on medical images, technical bottlenecks like noise, artifacts, and modality impose an enormous challenge on high-precision, objective, and efficient early quantification of OA. Owing to recent advancements, approaches based on neural networks (DNNs) have shown outstanding success in this application domain. However, due to nested non-linear and complex structures, DNNs are mostly opaque and perceived as black-box methods, which raises numerous legal and ethical concerns. Moreover, these approaches do not have the ability to provide the reasoning behind diagnosis decisions in the way humans would do, which poses an additional risk in the clinical setting. In this paper, we propose a novel explainable method for knee OA diagnosis based on radiographs and magnetic resonance imaging (MRI), which we called DeepKneeExplainer. First, we comprehensively preprocess MRIs and radiographs through the deep-stacked transformation technique against possible noises and artifacts that could contain unseen images for domain generalization. Then, we extract the region of interests (ROIs) by employing U-Net architecture with ResNet backbone. To classify the cohorts, we train DenseNet and VGG architectures on the extracted ROIs. Finally, we highlight class-discriminating regions using gradient-guided class activation maps (Grad-CAM++) and layer-wise relevance propagation (LRP), followed by providing human-interpretable explanations of the predictions. Comprehensive experiments based on the multicenter osteoarthritis study (MOST) cohorts, our approach yields up to 91% classification accuracy, outperforming comparable state-of-the-art approaches. We hope that our results will encourage medical researchers and developers to adopt explainable methods and DNN-based analytic pipelines towards an increasing acceptance and adoption of AI-assisted applications in the clinical practice for improved knee OA diagnoses.

Direct exposure to mosquito coil smoke (MCS) is a regular event in the entire life of most tropical country peoples, although it has countable significant health implications. However, noxious effect of mosquito coil smoke exposure on living being remains elusive. Herein, to address the mosquito coil smoke implication on health, Swiss albino mice were directly used to detect the health indicator alteration upon MCS administration as experimental model. In total 45 albino mice were grouped and exposed with MCS in two different time period viz, short time for 20 days and long time for 40 days. At the end of exposed time period, blood samples were collected and various health indicators analyzed. We revealed that biochemical indicators like serum aspartate aminotransferase (AST), alkaline phosphatase (ALP), alanine aminotransferase (ALT), bilirubin, urea, glucose, cholesterol, and triacylglycerol (TG) as well as hematological indicators like red blood cell (RBC), hemoglobin (Hb) and leukocyte (white blood cell) were significantly augmented in the exposed mice as compared to controls. In contrast, serum levels of total protein and albumin were remarkably decreased while serum creatinine and globulin level remained relatively unchanged. Furthermore, the microscopic analysis showed that the histopathological lesions were present on the lung tissue of exposed mice resulting, the alveolar septa and bronchiolar epithelial thickening, emphysema, and atelectasis of lung tissue as well as increased alveolar macrophages. Despite of, liver histopathology of the exposed mice showed same findings with a little deviation. Collectively, our findings propose that inhaling mosquito coil smoke induce significant health hazards on mice model followed by modification of vital health indicators and histological tissue-alignment alterations of lung and liver tissues. [ J Adv Biotechnol Exp Ther 2020; 3(2.000): 122-127]

Oyster Mushroom (Pleurotus ostreatus), an edible mushroom, is traditionally being used as a curing. However, hypoglycemic as well as antidyslipidemic effects on methanolic and ethyl acetate extracts of oyster mushroom in streptozotocin-treated diabetic rat model was not investigated yet. Here, we investigated that oral administration of 200 mg/kg oyster mushroom for 30 days were estimated through evaluating the fasting blood glucose level and blood lipid profile of diabetic rat. The results from our studies explained that P. ostreatus oyster mushroom considerably decreased blood glucose level initiated after treatment on second week. However, oyster mushroom was significantly reduced in plasma triglycerides (TG), total cholesterol (TC), as well as low-density lipoprotein-cholesterol (LDL-C). Additionally, high density lipoprotein-cholesterol (HDL-C) was enhanced by the treatment of oyster mushroom. Therefore, the current study suggests that P. ostreatus has antihyperglycemic and antidyslipidemic effect on diabetic rat model. [ J Adv Biotechnol Exp Ther 2020; 3(1.000): 49-55]

This study assessed the strength and durability parameters of brick aggregate concrete (BAC) incorporating rice husk ash (RHA) as a partial replacement of cement. For this, concrete cylinders (100 mm × 200 mm) were made with 0% (control) to 25% RHA as a partial replacement of ordinary Portland cement (OPC) at a mix proportion of 1 : 1.5 : 3 and a water-to-binder (w/b) ratio of 0.50. Specimens were immersed separately in normal water, 3% sodium chloride (NaCl), 5% sodium sulfate (Na2SO4), 5% magnesium sulfate (MgSO4), 1% hydrochloric acid (HCl), and 1% sulfuric acid (H2SO4) solutions for several immersion periods. The slump test results indicated that the workability of BAC containing RHA (RBAC) decreased about 29.69%–75.02% compared to control (0% RHA). After 90 days, the BAC containing RHA (up to 15% replacement) was found approximately 2.28%–6.64% greater compressive strength than that of control concrete. In addition, water absorption and porosity of RBAC were around 17.59%–40.73% and 12.12%–35.68% lower than that of control concrete, respectively. Similarly, RBAC (up to 25% replacement) exhibited roughly 35.62%–54.79% higher resistance against chloride attack and 0.39%–4.56% better resistance against Na2SO4 attack (up to 15% replacement), however, it exhibited inferior resistance against MgSO4 attack compared to control. Meanwhile, BAC with 10% RHA showed about 5.35% and 1.00% superior performance than that of control concrete against HCl and H2SO4 attack, respectively. The relationships between the strength and durability parameters of RBAC also suggested that RHA contributes to improving the strength and durability parameters of BAC.

Reactive oxygen species (ROS)-the byproduct of regular cell activity formed by various cellular components—play a significant role in pathological and physiological conditions. Alternatively, antioxidants are compounds that reduce or scavenge reactive species in cells. An asymmetry between the antioxidant defense system and ROS from intracellular and extracellular sources cause chronic diseases such as cancer, inflammation, tumorigenesis, cardiovascular and neurogenerative diseases. However, Panax ginseng and its secondary metabolites (known as ginsenosides, phenolic compounds, peptides, acid polysaccharides, polyacetylene, and alkaloids) are well-recognized as antioxidants in many in vitro and in vivo experiments which show beneficial activity in regulating ROS in these diseases. There are extensive evidences that P. ginseng can destroy cancer cells specifically by increasing oxidative stress through ROS generation without significantly harming normal cells. Additionally, numerous studies have examined the antioxidant activity of ginseng and its derivatives on ROS-mediated signaling pathways which are discussed herein. This review summarizes the potential antioxidant activity of P. ginseng in several chronic diseases, and gives updated research evidence with related mechanisms and the future possibilities of nano-formulated compounds of P. ginseng and other polyphenols.

ABSTRACT: Nutrient contents of sugar palm (Borassus flabellifer) fruit pulp (SPFP) cultivated in Bangladesh are yet to be well-reviewed. Moreover, the nutrient contents of other popularly consumed edible portions of sugar palm fruit, i.e., immature endosperm (IE), and germinated endosperm (GE) are not studied yet. The current study showed that SPFP, IE, and GE were rich in carbohydrate, fiber, sodium, potassium, and zinc. IE contained the highest amount of fiber, while SPFP contained the highest amount of copper. Twenty-five phytochemicals having known antidiabetic effects were investigated for their presence in pulp, immature & germinated endosperm. GE contained the highest number of phytochemicals (23) followed by IE (19) and SPFP (14). Diabetic patients usually avoid edible portions of sugar palm, fearing that these may further deteriorate existing hyperglycemia. In the present study, this suspicion was investigated in alloxan-induced diabetic rats through supplementary feeding of SPFP, IE, & GE in addition to the regular diet for the nine consecutive weeks. Study results clearly showed that SPFP, IE, & GE significantly reduced fasting blood glucose (FBG) levels of experimental rats. GE showed maximum antidiabetic effects followed by IE and SPFP, respectively. GE, and IE returned the FBG levels within normal range by the end of the sixth week but not by the SPFP. Endosperms supplemented diabetic rats maintained the normal FBG levels even after withdrew the supplementary diets. These results suggested that supplemental feeding of the GE and IE to the experimental diabetic rats may restore alloxan damaged pancreatic β-cell function, and the reasons might be the presence of fiber, zinc and phytochemicals content of the endosperm.

This study aimed to investigate the effect of extensibility on cotton blended polyester-spandex core-spun yarn in the weft direction of 3/1 right-handed Z-twill denim. For the preparation of samples, 100% ring spun cotton yarn of 42 tex (14s/1 Ne) was used as warp, and 70:30, 30:70, 60:40, and 40:60 cotton-polyester core-spun yarn of 30 tex (20s/1) was used in the weft direction. Four categories of denim fabric were fabricated by using the air-jet weaving machine. Spandex yarn was used as a core material of weft with a percentage of 2%, 2.5%, 1.9%, and 1.8% respectively. Different physio-mechanical characteristics namely tensile and tearing strength, GSM, growth and recovery percentage, initial modulus, bending length, drape co-efficiency, abrasion resistance, flexural rigidity were evaluated to justify the quality of fabricated pieces of denim. Water wicking and breathability were taken into consideration when determining comfort. Higher cotton containing specimens exhibited lower tensile and tearing strength. Additionally, the produced denim fabrics showed balanced drapability and good breathability.

Tropical forest ecosystem act as a carbon sink and plays a vital role in climate change mitigation. The carbon storage capacity of tropical forest ecosystems is declining gradually in recent years. But studies regarding the multiple drivers of tree and soil carbon in the tropical forest ecosystems are scarce. Our study aims to quantify the tree and soil carbon storage capacity and to explore how these carbon storages are associated with both biotic (stand structure, anthropogenic disturbance) and abiotic drivers (climate, topography, and soil) simultaneously in tropical forest ecosystems. The present study was conducted in two forest-protected areas of Bangladesh, namely- Satchari National Park (SNP), and Khadimnagar National Park (KNP). Results showed that tree carbon stock was 72.9 t ha−1 and 58.2 t ha−1 in SNP and KNP, respectively. Besides, soil carbon was 77.1 t ha−1 in SNP and 130.5 t ha−1 in KNP. We found that tree carbon was positively correlated with all stand structure parameters. However, soil carbon was negatively correlated with tree richness, height, and basal area. Anthropogenic disturbance had a negative correlation with tree carbon and a positive correlation with soil carbon stock. No significant correlation was observed between tree carbon and local climatic parameters. But soil carbon had a positive correlation with annual precipitation and a negative correlation with annual mean temperature. Furthermore, tree carbon was positively associated with elevation and slope whereas soil carbon was negatively associated with elevation. Tree carbon was negatively correlated with silt% but positively with sand%. Conversely, soil carbon showed significant positive associations with soil moisture, bulk density, soil pH, and soil silt%. Our study provides a comprehensive insight on the understandings of key drivers of tree and soil carbon storage in the tropical forest ecosystem of Bangladesh. We concluded that anthropogenic disturbance and stand characteristics regulate tree carbon stock while soil carbon is mainly associated with local climate and soil properties in the studied tropical forest ecosystems.

ABSTRACT: Background: Bipolar disorder (BPD) disrupts both personal and family life. In Bangladesh, studies on BPD and family issues are scanty. Therefore, we examined the impact of BPD on family relationships among married adults in Rajshahi City, Bangladesh. Methods: 708 married adults were recruited in this study, and they were selected using multistage random sampling and interviewed them with a self-developed questionnaire. The Bipolar Spectrum Disorder Scale was used for screening BPD. Interpersonal relationships and overall family relationship were measured based on the participants’ responses to four statements. Chi-square test and binary logistic regression model were used in this study. Results: This study revealed that 3.2% and 4.8% married adults had poor relationships with their spouses and family members respectively. 5.8% adults perceived they were given poor importance in decision making about family matters, and 15.8% thought the family provided poor healthcare services in their sickness. 19.9% respondents chose a poor category of overall family relationship. Wives had higher rates of poor category of interpersonal relationship factors compared to males. BPD was found as a predictor of interpersonal relationship factors among married adults: relationship with spouse (p

The experiment was conducted on the growth and yield of okra using nutrient management through different types of fertilizers and netting at the Horticulture Farm of Bangladesh Agricultural University (BAU), Mymensingh. There were netting treatments, viz. N1 = Control (no net) and N2= Net (blue color) along with fertilizer treatments viz. T1 = no fertilizer (control), T2 = vermicompost @ 10 t ha−1, T3 = vermicompost @ 15 t ha−1, T4 = combined application of 2/3 part organic (T3) and 1/3 part inorganic (T5), and T5 = inorganic fertilizers. Temperature (◦C) and relative humidity (%) were recorded under net and at the open condition daily during production stage (month of May) However, the value didnt differ significantly. Growth parameters of okra viz. plant height, pod length, pod diameter, and pods of okra were found the highest from T4N2 treatment combination which was significantly higher from other combinations. The lowest growth and yield of okra was found from the treatment combination of T1N1. First flowering was observed in T4N2 at 32 days after planting of okra seeds. Vermicompost at different rates (10 t ha−1 and 15 t ha−1) with net gave lower production of okra compared to inorganic fertilizer treatments with net. The highest yield of okra (19.65 t ha−1) was found from the combined effect of T4N2 which was 56.74% higher compared to control (T1N1). [Fundam Appl Agric 2019; 4(1.000): 627-631]

Cancer is one of the deadliest diseases caused by abnormal behaviors of genes that control the cell division and growth. Genomics data and clinical outcomes from multiplatform and heterogeneous sources are used to make clinical decisions for the cancer patients, where both multimodality and heterogeneity impose significant challenges to bioinformatics tools and algorithms. Numerous works have been proposed to overcome these challenges by using sophisticated bioinformatics and machine learning algorithms as either primary or supporting tools. In this paper, we propose a new approach to analyze genomics data from The Cancer Genome Atlas (TCGA) to classify breast cancer patients based on their subtypes and survival rates. Since multiple factors such as estrogen receptor (ER), progesterone receptor (PGR), and human epidermal growth factor receptor 2 (HER2) statuses are involved in breast cancer diagnosis, we used DNA methylation, gene expression (GE), and miRNA expression data by creating a multiplatform network called Multimodal Autoencoders (MAE) classifier to support each data type. Experiment results demonstrate that our approach is promising with high confidence for predicting both breast cancer subtypes and survival rates. In particular, we achieved state-of-the-art results with accuracies of 91% and 86%, respectively for the ER and PGR-based subtype prediction and moderately low accuracy for the HER2-based subtype prediction as well as we perceived reasonably low MSE and positive coefficient of determination (R2) scores in case of survival prediction. Additionally, we created unimodal and multimodal features from each input type and trained decision tree (DT), Naive Bayes (NB), K-nearest neighbors (KNN), logistic regression (LR), support vector machine (SVM), random forest (RF), and gradient boosting trees (GBT) as ML baseline models. Finally, we use the model averaging ensemble of top-3 models to report the final prediction.

Water is the ultimate and mostly used media during textile materials processing, especially in colouration. This study investigated the possibilities of using seawater for cotton and polyester fabrics dyeing. Single jersey fabrics made of 100 percent cotton and polyester were dyed using a standard recipe and two separate water source as dyeing mediums. It has been focused on the assessment of colour fastness to wash, perspiration, saliva, rubbing, water, light and colour difference value due to compare the efficiency of dyeing media. The results revealed that the cotton fabric dyed with seawater showed lighter shade than that of ground water sample. But for polyester fabric darker shade was obtained compared to ground water. The cotton sample dyed with sea water carried about 15% higher colour strength than ground water dyed sample but for polyester it was very negligible, only 3%. Moreover, the results of colour fastness to wash, perspiration, saliva, rubbing, water and light for seawater dyed samples of cotton and polyester were shown satisfactory outcomes having the grading of 4–5 in most of the cases. This exploration established that commercial dyeing processes were robust and can be practically transferable into the seawater medium for cotton and polyester fabrics.

The importance of local climate and biodiversity in tropical forest's ability to provide critical ecosystem services is well documented, whereas the relationship among local climatic factors and biodiversity with soil ecosystem functions largely remain unclear. We investigated the importance of local rainfall regime and indicators of plant (tree, herb, and shrub) diversity (richness and abundance) on soil ecosystem functions in two tropical forest ecosystems of north-east Bangladesh. We considered six soil parameters, i.e. soil water regulation (SWR), soil physical stability (SPS), soil microbial habitat (SMH), soil pH (pH), medium of plant growth (MPG), and soil aggregate stability (SAS) as indicators of soil ecosystem functions. Our study finds four rainfall parameters having significant (p < 0.05) positive effects on soil water regulation, soil physical stability, microbial habitat, soil pH, medium of plant growth, and soil aggregate stability. Tree species abundance had positive effects on SPS (p < 0.001) and MPG (p < 0.05), while tree species richness had negative effects on SMH (p < 0.001) and MPG (p < 0.01). Soil aggregate stability was negatively (p < 0.05) affected by tree species abundance, whereas tree species richness positively (p < 0.0001) affected SAS. We found no significant effects of tree species abundance and richness on pH and SWR. The abundance of herbaceous species had positive impacts on MPG (p

Abstract Despite its complexity and importance in managing water resources in populous deltas, especially in tidal areas, literatures on tidal rivers and their land use linkage in connection to water quality and pollution are rare. Such information is of prior need for Integrated Water Resource Management in water scarce and climate change vulnerable regions, such as the southwestern coast of Bangladesh. Using water quality indices and multivariate analysis, we present here the land use signatures of a dying tidal river due to anthropogenic perturbation. Correlation matrix, hierarchical cluster analysis, factor analysis, and bio-geo-chemical fingerprints were used to quantify the hydro-chemical and anthropogenic processes and identify factors influencing the ionic concentrations. The results show remarkable spatial and temporal variations (p

Objective: The present research work was undertaken with the objectives to investigate the prevalence and molecular detection of the causal agents of sub-clinical mastitis (SCM) in cows at milk shed areas in Sirajganj and Pabna districts, Bangladesh. Materials and methods: A total of 300 milk samples were randomly collected from Baghabari milk shed areas of Sirajganj and Pabna districts. The milk samples were subjected for California Mastitis Test (CMT) for identifying SCM. Total 81 positive samples were then used for the isolation and identification of associated bacteria and fungi using conventional microbiological examination and biochemical tests, followed by confirmation by polymerase chain reaction (PCR) using specific primers. Besides, universal primers were used for amplification and sequencing of PCR products where specific primers were not used. Results: The overall prevalence of SCM was 51% (n=153/300). Based on bacteriological examination and biochemical tests, several bacteria were identified in this study; the orgnaisms included Staphylococcus sp. (45.68%), Streptococcus uberis (14.81%), Escherichia coli (9.88%), Proteus sp. (19.75%), Salmonella sp. (1.23%), Acinetobacter sp. (7.41%), and fungus (1.23%). PCR technique confirmed the bacteria as Staphylococcus aureus (279-bp), Streptococcus uberis (884-bp), E. coli (16SrRNA 585-bp, stx1 606-bp, rfbO157 497-bp) and Salmonella sp. (Inv-A gene796-bp). Conclusion: This study reveals that SCM in dairy cattle is persisting in Sirajganj and Pabna districts of Bangladesh. Hygienic practices should be improved, and providing technical intereventions may reduce the rate of SCM in the study areas. [J Adv Vet Anim Res 2017; 4(4.000): 378-384]

Abstract Background Right coronary artery perforation extending to the sinus of Valsalva is a rare and potentially fatal complication of percutaneous coronary intervention. There are no definite guidelines on the management strategies for such complications. Treatment modality depends on the patient’s haemodynamic stability and the extent of aortic involvement. Polytetrafluoroethylene-covered stents have emerged as a revolutionary strategy, enabling efficient endovascular repair of the entry port of such dissections, particularly the coronary ostia, and obviating the need for high-risk emergent surgical intervention. Case presentation A 60 year old Bangladeshi gentleman underwent a coronary angiogram following a prior inferior ST elevation myocardial infarction (MI), 1 month previously. Coronary angiography done via right radial approach using 5 FR TIG catheter showed diffuse mid RCA disease with maximum 90% stenosis. Angioplasty of the RCA was planned. The RCA was cannulated with a 6-French JR 3.5 guiding catheter (USA). The lesion was crossed by a 0.014 inch guide wire and stented with a 2.75 × 38 mm novolimus-eluting DESyne stent, after predilatation. Immediately after stenting, a Type II perforation was observed in the ostial RCA, which progressed into the right coronary sinus of Valsalva. As the patient was haemodynamically stable with no ischaemia on ECG, we attempted to seal the ostial RCA with bare metal stents. Two successive bare metal stents failed to seal the aorto-coronary dissection. Ultimately, a 3.0 × 19 mm polytetrafluoroethylene-covered stent was deployed to seal the entry port in the ostial RCA, yielding a satisfactory angiographic result with only minimal contrast staining limited to the right sinus of Valsalva. The patient was closely monitored and discharged on dual antiplatelet therapy comprising of aspirin and prasugrel. He remained asymptomatic and with follow up echocardiograms showing no pericardial effusion nor extension of the dissection. Conclusions The polytetrafluoroethylene-covered stent provides a safe and effective means of sealing iatrogenic aorto-coronary dissections complicated by Ellis type II or II perforations, thus avoiding emergency surgery. However, as they are associated with increased incidence of stent thrombosis, an efficient and prolonged post-PCI antiplatelet regimen is recommended.

Abstract To identify the causes of salinization and arsenic contamination of surface water on an embanked island (i.e., polder) in the tidal delta plain of SW Bangladesh we collected and analyzed water samples in the dry (May) and wet (October) seasons in 2012–2013. Samples were collected from rice paddies (wet season), saltwater ponds used for brine shrimp aquaculture (dry season), freshwater ponds and tidal channels (both wet and dry season), and rainwater collectors. Continuous measurements of salinity from March 2012 to February 2013 show that tidal channel water increases from ~0.15 ppt in the wet season up to ~20 ppt in the dry season. On the polder, surface water exceeds the World Health Organization drinking water guideline of 10 μg As/L in 78% of shrimp ponds and 27% of rice paddies, raising concerns that produced shrimp and rice could have unsafe levels of As. Drinking water sources also often have unsafe As levels, with 83% of tubewell and 43% of freshwater pond samples having >10 μg As/L. Water compositions and field observations are consistent with shrimp pond water being sourced from tidal channels during the dry season, rather than the locally saline groundwater from tubewells. Irrigation water for rice paddies is also obtained from the tidal channels, but during the wet season when surface waters are fresh. Salts become concentrated in irrigation water through evaporation, with average salinity increasing from 0.43 ppt in the tidal channel source to 0.91 ppt in the rice paddies. Our observations suggest that the practice of seasonally alternating rice and shrimp farming in a field has a negligible effect on rice paddy water salinity. Also, shrimp ponds do not significantly affect the salinity of adjacent surface water bodies or subjacent groundwater because impermeable shallow surface deposits of silt and clay mostly isolate surface water bodies from each other and from the shallow groundwater aquifer. Bivariate plots of conservative element concentrations show that all surface water types lie on mixing lines between dry season tidal channel water and rainwater, i.e., all are related by varying degrees of salinization. High As concentrations in dry season tidal channel water and shrimp ponds likely result from groundwater exfiltration and upstream irrigation in the dry season. Arsenic is transferred from tidal channels to rice paddies through irrigation. Including groundwater samples from the same area (Ayers et al. in Geochem Trans 17:1–22, 2016), principal components analysis and correlation analysis reveal that salinization explains most variation in surface water compositions, whereas progressive reduction of buried surface water by dissolved organic carbon is responsible for the nonconservative behavior of S, Fe, and As and changes in Eh and alkalinity of groundwater.

Objective: The study was conducted to assess the prevalence of subclinical mastitis in dairy cows at Baghabari milk shed area of Sirajganj and Pabna districts in Bangladesh. Materials and methods: A total of 300 milk samples were collected from crossbred dairy cows, and the milk samples were subjected for using California Mastitis Test (CMT). Besides, data related to farm management were taken from 60 farmers through direct interviews. The CMT was compared with White Slide Test (WST) and Surf Field Mastitis Test (SFMT). The samples showing strong positive reaction to mastitis by CMT were used for the isolation of associated bacteria using conventional bacteriological examinations and biochemical properties. The isolated bacteria were subjected for antibiogram studies by disc diffusion method. Results: Out of 300 samples, 153 (51%) revealed positive reactions denoting that the cows were suffering from subclinical mastitis. Of the 153 samples, 39(13%) were trace-positive, 56(18.56%) were weak-positive, 33(11%) were distinct-positive, and the rest 25(8.3%) samples were strongly positive. In comparison economically among CMT, WST and SFMT, SFMT was found to be the cheapest and easiest. In this study, the cows were mostly infected with mixed infection with Staphylococcus spp., Streptococcus spp., Escherichia coli, Salmonella spp., and some cows had single bacterial infection. It was observed that most of the microorganisms were sensitive to Gentamycin, Amoxicillin and Ceftriaxone, and were resistant to Penicillin, Ciprofloxacin and Colistin sulphate. Conclusion: Overall prevalence of subclinical mastitis in the crossbred dairy cows at Sirajganj and Pabna district is 51%. It indicates that subclinical mastitis is a major threat for dairy industry in the studied areas. Early detection and appropriate preventive measures are suggestive to successful control of the disease. [J Adv Vet Anim Res 2017; 4(3.000): 295-300]