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Heavy metals (HMs) are ubiquitous in terrestrial and aquatic environments due to unplanned industrial waste discharge, the release of untreated wastewater, and improper mining activities. In particular, the concentrations of HMs are found to be higher in aquatic environments. As a result, the aquatic biota was heavily affected by HM contamination. This critical review aims to understand the sources and toxicity of HMs in commercial fish species, explore their ecological exchange, and examine the related human health challenges in Bangladesh. A modified PRISMA review technique is used in this paper to analyze the current status and research limitations of HM studies in Bangladesh fish species and their toxicity within aquatic food webs. Briefly, we searched several keywords to explore the research trend of HM concentrations and toxicity in fish species. Furthermore, potential toxicity and risk assessment of HMs through the aquatic food chain in Bangladesh were explored. On the other hand, a cross-tabulation approach was used to process the toxicity findings of HMs. Previous studies indicate that fish species can possess comparatively higher HMs than river water due to ecological exchange factors, including bioaccumulation and biotransformation. This review focuses on Bangladesh, highlighting areas for improvements and the need for further study to achieve a transparent understanding of HM deposition in fish species and the sustainable management of aquatic food chain toxicity., (© 2024. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

Universities play a crucial role in urban economic and structural development. The government of Bangladesh has undertaken the initiative to establish a public university in each of the 64 districts. These newly founded universities have the potential to impact urban growth significantly. We aimed to project university-induced urban expansion to address this knowledge gap and identify the mechanisms driving urban growth. The classification of supervised and unsupervised methods was employed to analyze urban development for the years 2000, 2010, 2016, and 2022. We used the Cellular Automata and Markov Chain approach to forecast future urban growth and land transition capacity. Additionally, the driving factors and selection of the study area were derived from Focus Group Discussions (FGD), Key Informant Interviews (KII), Probit Model, and Perception Index (PI). The findings of this study reveal a 1.6% urban growth rate within ten years of the establishment of the university, while urban expansion accelerated to 29.78% after ten years. The predictions also indicate a sustained urban growth rate of 4.7% by 2042. Furthermore, the PI index demonstrates that the establishment of the university has resulted in high demand for rental housing, serving as one of the primary drivers of urban expansion. Moreover, the Probit model highlights strong economic capability, proximity to the town, railway station, hospital, and easy access to credit as vital facilitators behind the drivers of urban expansion. Policymakers, the scientific community, and urban planners can benefit from this study in pursuing sustainable city development through university establishment., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Rahman et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

The water-soluble metal complexes with Schiff base (SB) ligands are of great interest to green chemistry researchers due to their stability, cost-effectiveness, eco-friendly, electron-donating ability, and various applications. They have high potential to express their biological activity including anti-inflammatory, anticancer, antibacterial, antifungal, antioxidant, and DNA binding and cleavage. In the recent era, transition metal complexes have played a significant role in different processes such as hydrogenation, carbonylation, oxidation, reduction, epoxidation, hydrolysis, decomposition, and polymerization reactions in industry. However, their limited aqueous solubility may be the major limitation to their potential catalytic, industrial, and clinical applications. In industrial catalytic processes, it has been proven that water can be used as a solvent to minimize the environmental effect of different reactions as well as simple and complete separation. Water is a green solvent, flexible, non-toxic, safe, readily available, environmentally harmless, and inexpensive. Attaching different substituents on Schiff bases enhances the water solubility and catalytic activity. Studies on water-soluble SB complexes will explore these aspects and their prospects for the future evolution of their diverse applications., Competing Interests: The authors have declared there exist no competing interests., (This journal is © The Royal Society of Chemistry.)

Lead-free double perovskites are unique materials for transport and optoelectronic applications that use clean resources to generate energy. Using first-principle computations, this study thoroughly investigates the structural, thermoelectric, and optical attributes of A 2 TlAgF 6 (A = Rb, Cs). Tolerance factor and formation energy estimates are used to verify that these materials exist in the cubic phase. Elastic constants with high melting temperature values are ductile when evaluated for mechanical stability using the Born stability criterion. The optical absorption band is adjusted from 2 to 4 eV via band gaps of 1.88 and 1.99 eV, as indicated by band structures. Analysis of optical properties reveals perfect absorption in the visible spectrum, whole polarization, and low optical loss. Furthermore, thermoelectric properties are assessed at 300, 500, and 700 K in the range of -0.5 to 3 eV for chemical potential (μ). The materials exhibit significant improvements in the Figure of Merit scale due to their elevated electrical conductivity, Seebeck coefficient, and extremely low thermal conductivity values., (© 2024 Wiley Periodicals LLC.)

Copper doped magnesium ferrite, Mg 1 - x Cu x Fe 2 O 4 (x = 0.0-1.0) nanomaterials were synthesized via. sol-gel method sintered at 600 °C for 2 h. The synthesized materials were characterized using modern sophisticated techniques viz. X-ray diffraction (XRD), Scanning electron microscopy (SEM), Transmission electron microscopy, Energy dispersive x-ray spectroscopy (EDS), Vibrating sample magnetometer, UV-visible diffuse reflectance spectra and Impedance analyzer. XRD analysis revealed that all the samples were single phase cubic spinel structure with Fd3m space group and investigated the change in structural parameters with copper concentration. The average crystallite size in the range of 11-23 nm and lattice parameters decrease with increasing Cu doping, due to the cationic distribution and ionic radius. The SEM images show the agglomeration of the particles with spherical like shape and elemental percentage were obtained from EDX. The saturation magnetization showed an increasing trend with increasing Cu concentration at a certain level and then decreases due to the rearrangement of cations at tetrahedral and octahedral sites. The Coercivity, Retentivity and magnetic crystalline anisotropy increase with changing dopant concentration. The magnetic measurements showed enhanced saturation magnetization at certain level (28.96emu/gm) and increase in coercivity up to 1102 Oe with changing dopant concentration. The estimated band gap energy is found to increase with Cu content. The dielectric constant, dielectric loss and impedance show normal behavior of ferrite. The frequency dependent dielectric constant decrease and tan delta shows a relaxation behavior at low frequencies. The synthesized nano Mg-Cu nanoparticles will be applied as humidity sensor, gas sensor, microwave devices and photocatalyst., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2024 The Authors.)

Heat waves significantly impact people's lives and livelihoods and are becoming very alarming and recognized as hot topics worldwide, including in Bangladesh. However, much less is understood regarding recent hotspots, the frequency of heat waves over time, and their underlying causes in Bangladesh. The objective of the study is to explore the current scenario and frequency of heat waves and their possible causes across Bangladesh. The Mann-Kendall and Sen's slope techniques were used to determine seasonal and annual temperature trend patterns of heat wave frequencies. Daily maximum temperature datasets collected from the Bangladesh Meteorological Department (BMD) during 1991-2021 are applied. The frequency of days with Tmax≥ 36°C as the threshold was used to compute different types of heat waves based on the BMD's operational definition. The results show that the mild heat wave (MHW) days followed the subsequent hotspot order: Rajshahi (103) > Chuadanga (79), Ishurdi (60), and Jessore (58), respectively. The frequency of days with Tmax≥36°C was persistence for many days in 2014, especially in the western part of Bangladesh compared to other parts. Similarly, the heat waves condition shown its deadliest event by increasing more days in 2021. The highest increasing trend was identified at the Patuakhali site, with a rate of 0.516 days/year, while the highest decreasing trend was noticed at the Chuadanga site, with a rate of -0.588 days/year. The frequency of days (Tmax≥36°C) is an increasing trend in the south-western part of Bangladesh. The synoptic condition in and around Bangladesh demonstrates that the entrance of heat waves in Bangladesh is due to the advection of higher temperatures from the south/southwest of the Bay of Bengal. The outcomes will guide the national appraisal of heatwave effects, shedding light on the primary causes of definite heatwave phenomena, which are crucial for developing practical adaptation tools., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Rahman et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Background: The surge in digital media consumption, coupled with the ensuing consequences of digital addiction, has witnessed a rapid increase, particularly after the initiation of the COVID-19 pandemic. Despite some studies exploring specific technological addictions, such as internet or social media addiction, in Bangladesh, there is a noticeable gap in research focusing on digital addiction in a broader context. Thus, this study aims to investigate digital addiction among students taking the university entrance test, examining its prevalence, contributing factors, and geographical distribution using GIS techniques., Methods: Data from a cross-sectional survey were collected from a total of 2,157 students who were taking the university entrance test at Jahangirnagar University, Bangladesh. A convenience sampling method was applied for data collection using a structured questionnaire. Statistical analyses were performed with SPSS 25 Version and AMOS 23 Version, whereas ArcGIS 10.8 Version was used for the geographical distribution of digital addiction., Results: The prevalence of digital addiction was 33.1% (mean score: 16.05 ± 5.58). Those students who are attempting the test for a second time were more likely to be addicted (42.7% vs. 39.1%), but the difference was not statistically significant. Besides, the potential factors predicted for digital addiction were student status, satisfaction with previous mock tests, average monthly expenditure during the admission test preparation, and depression. No significant difference was found between digital addiction and districts. However, digital addiction was higher in the districts of Manikganj, Rajbari, Shariatpur, and Chittagong Hill Tract areas, including Rangamati, and Bandarban., Conclusions: The study emphasizes the pressing need for collaborative efforts involving educational policymakers, institutions, and parents to address the growing digital addiction among university-bound students. The recommendations focus on promoting alternative activities, enhancing digital literacy, and imposing restrictions on digital device use, which are crucial steps toward fostering a healthier digital environment and balanced relationship with technology for students., (© 2024. The Author(s).)

Background and Aims: Mental health problem is a rising public health concern. People of all ages, specially Bangladeshi university students, are more affected by this burden. Thus, the objective of the study was to use tree-based machine learning (ML) models to identify major risk factors and predict anxiety, depression, and insomnia in university students., Methods: A social media-based cross-sectional survey was employed for data collection. We used Generalized Anxiety Disorder (GAD-7), Patient Health Questionnaire (PHQ-9) and Insomnia Severity Index (ISI-7) scale for measuring students' anxiety, depression and insomnia problems. The tree-based supervised decision tree (DT), random forest (RF) and robust eXtreme Gradient Boosting (XGBoost) ML algorithms were used to build the prediction models and their predictive performance was evaluated using confusion matrix and receiver operating characteristic (ROC) curves., Results: Of the 1250 students surveyed, 64.7% were male and 35.3% were female. The students' ages ranged from 18 to 26 years old, with an average age of 22.24 years (SD = 1.30). Majority of the students (72.6%) were from rural areas and social media addicted (56.6%). Almost 83.3% of the students had moderate to severe anxiety, 84.7% had moderate to severe depression and 76.5% had moderate to severe insomnia problems. Students' social media addiction, age, academic performance, smoking status, monthly family income and morningness-eveningness are the main risk factors of anxiety, depression and insomnia. The highest predictive performance was observed from the XGBoost model for anxiety, depression and insomnia., Conclusion: The study findings offer valuable insights for stakeholders, families and policymakers enabling a more profound comprehension of the pressing mental health disorders. This understanding can guide the formulation of improved policy strategies, initiatives for mental health promotion, and the development of effective counseling services within university campus. Additionally, our proposed model might play a critical role in diagnosing and predicting mental health problems among Bangladeshi university students and similar settings., Competing Interests: The authors declare no conflict of interest., (© 2024 The Authors. Health Science Reports published by Wiley Periodicals LLC.)

Monitoring and protecting freshwater habitats are paramount for a sustainable water management perspective. This study investigated potentially toxic elements (PTEs) in the potamic water of the Anday Stream Basin (Türkiye), Black Sea Region, for a hydrological year (from May 2020 to April 2021). Among PTEs, the highest average values were recorded for sodium (Na) at 41.3 mg/L and the lowest for mercury (Hg) at 0.009 μg/L and noted under quality guidelines. The stream was found to be at the level of "Low Heavy Metal Pollution" and "Low Contamination" based on the ecotoxicological risk indices. The highest calculated hazard quotient (HQ) value of 1.21E-02 for Cd was noted in the children via the dermal pathway and the lowest of 6.91E-06 for Fe in adults via the ingestion pathway. Results revealed a higher hazard index (HI) value of 1.50E-02 for Cd to children and the lowest of 1.98E-05 for Fe to adults. As a result of applying agricultural risk indices, the stream showed sodium adsorption ratio values less than 6 and was found to be "Excellent" for agriculture. However, the sodium percentage values were less than 20 and found "Permissible" and the magnesium hazard > 50 and noted as "Unsuitable" for agriculture. Statistical analysis revealed that natural factors mainly attributed to PTE contamination of the Anday Stream Basin., (© 2024. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

Background: Socioeconomic inequality in antenatal care visits is a great concern in developing countries including Bangladesh; however, there is a scarcity of investigation to assess the factors of inequality and these changes over time. In this study, we investigated the trend of socioeconomic inequalities (2004-2017) in 1+ANC and 4+ANC visits, and extracted determinants contributions to the observed inequalities and urban-rural disparities in Bangladesh over the period from 2011 to 2017., Methods: The data from the Bangladesh Demographic and Health Surveys (BDHS) conducted in 2004, 2007, 2011 and 2017 were analyzed in this study. The analysis began with exploratory and bivariate analysis, followed by the application of logistic regression models. To measure the inequalities, the Erreygers concentration index was used, and regression-based decomposition analyses were utilized to unravel the determinant's contribution to the observed inequalities. The Blinder-Oaxaca type decomposition is also used to decompose the urban-rural disparity into the factors., Results: Our analysis results showed that the prevalence of 1+ANC and 4+ANC visits has increased across all the determinants, although the rate of 4+ANC visits remains notably low. The magnitudes of socioeconomic inequality in 4+ANC visits represented an irregular pattern at both the national and urban levels, whereas it increased gradually in rural Bangladesh. However, inequalities in 1+ANC visits declined substantially after 2011 across the national, rural and urban areas of Bangladesh. Decomposition analyses have suggested that wealth status, women's education, place of residence (only for 4+ANC visits), caesarean delivery, husband education, and watching television (TV) are the main determinants to attribute and changes in the level of inequality and urban-rural disparity between the years 2011 and 2017., Conclusions: According to the findings of our study, it is imperative for authorities to ensure antenatal care visits are more accessible for rural and underprivileged women. Additionally, should focus on delivering high-quality education, ensuring the completion of education, reducing income disparity as well as launching a program to enhance awareness about health facilities, and the impact of caesarean delivery., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Biswas et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Background: In South Asia, cardiovascular diseases (CVDs) are an increasing public health concern. One strategy for dealing with the growing CVDs epidemic is to make health facilities more ready to provide CVDs services. The study's objectives were to: (1) assess healthcare facilities' readiness to offer CVDs services; and (2) identify the variables that influence such readiness., Methods: This study employed data from the Afghanistan Service Provision Assessment Survey 2018-2019, Bangladesh Health Facility Survey 2017, and Nepal Health Facility Survey 2021 that were cross-sectional and nationally representative. In Afghanistan, Bangladesh, and Nepal, 117, 368, and 1,381 health facilities, respectively, were examined. A total of 10 items/indicators were used to measure a health facility's readiness to provide CVDs services across three domains., Results: The mean readiness scores of managing CVDs were 6.7, 5.6, and 4.6 in Afghanistan, Bangladesh, and Nepal, respectively. Availability of trained staff for CVD services are not commonly accessible in Afghanistan (21.5%), Bangladesh (15.3%), or Nepal (12.9%), except from supplies and equipment. Afghanistan has the highest levels of medicine and other commodity availability. Among the common factors linked with readiness scores, we ought to expect a 0.02 unit rise in readiness scores for three nations for every unit increase in number of CVDs care providers. In Afghanistan, Bangladesh, and Nepal, availability of both diagnosis and treatment facilities was associated with increases in readiness scores of 27%, 9%, and 17%, respectively. Additionally, an association was observed between nation-specific facility types and the readiness scores., Conclusions: Country-specific factors as well as universal factors present in all three nations must be addressed to improve a health facility's readiness to provide CVDs care. To create focused and efficient country-specific plans to raise the standard of CVD care in South Asia, more investigation is necessary to ascertain the reasons behind country-level variations in the availability of tracer items., Competing Interests: The authors have no competing interests to declare., (Copyright: © 2024 The Author(s).)

Background: The COVID-19 pandemic has imposed unprecedented suffering on social and individual levels worldwide. Vaccines against COVID-19 have been prioritized as a crucial strategy for ending the pandemic as well as minimizing its consequences., Objectives: This study aimed to determine the uptake of COVID-19 vaccine among high-risk urban populations in Southern Thailand using the Capability, Opportunity, Motivation, and Behavior (COM-B) model., Methods: We conducted a web-based cross-sectional study in the Hat Yai district, Songkhla province in Southern Thailand, in September and October 2021. The questionnaire was composed of sections on sociodemographic characteristics, COVID-19 vaccination status, and COM-B constructs. We employed a multivariable logistic regression analysis to determine factors associated with the uptake of the COVID-19 vaccine. We set statistical significance at p < 0.05., Results: In this study, females constituted 54.7% of the total participants (n = 358), and nearly half of the participants (45.8%) were in the younger age group (18-29). Of all the participants, 59.5% (95%CI: 54.2%-64.6%) received at least one dose of the COVID-19 vaccine. Factors associated with the uptake of COVID-19 vaccine and their adjusted OR (95% CI) were being married: 3.59 (2.06-6.24), having a graduate degree: 2.34 (1.38-3.96), gainfully employed: 3.30 (1.91-5.67), having a high level of opportunity: 2.90 (1.48-5.66), and having a high level of motivation: 2.87 (1.17-17.08)., Conclusion: The uptake of COVID-19 vaccines was moderate in this population. Moreover, the results showed that the COM-B model is useful in predicting COVID-19 vaccine uptake. The findings of this study could be used to aid future public health interventions in any event of outbreaks similar to COVID-19 disease in Thailand and beyond., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Suwanbamrung et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Objectives: Although there is some evidence that flood exposure in Bangladesh and other developing countries increases the risk of chronic undernutrition in children, the underlying mechanisms are, to our knowledge, unknown. The objectives of this research are to examine the association between recurrent flood exposure and the likelihood of chronic undernutrition in children and to investigate the mediators of this association., Methods: This cross-sectional study was conducted in the Naogaon District in northern Bangladesh. Purposive sampling was used to choose 800 children between the ages of 12 and 59 mo in equal numbers in the specified flood-affected and flood-unaffected areas: 400 children from the flood-affected area and 400 from the flood-unaffected area. The nutrition indicator height for age, expressed as z scores, was used to define child chronic undernutrition. Our study focused on children who have been exposed to multiple floods in the past 5 y., Results: In our sample data, children who had experienced flooding had a 1.74-times higher chance of having chronic undernutrition (95% CI, 1.53-2.28) than children who had not experienced flooding. The mediation analyses found inadequate minimum dietary diversity, history of diarrhea, not being fully vaccinated, not using clean cooking fuel, and not having a separate kitchen contributed 19.5%, 10%, 9.8%, 14.8%, and 10%, respectively, to the flood exposure-child undernutrition association., Conclusions: Flood exposure was found associated with the likelihood of child chronic undernutrition, and this relationship was mediated through lack of having a separate kitchen, history of diarrhea, insufficient vaccination, use of unclean cooking fuel, and poor minimum dietary diversity. Interventions to reduce the prevalence of these risk factors could contribute to reducing the disparities in child undernourishment brought on by exposure to flooding., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Inc. All rights reserved.)

Thrace is a part of the Marmara Region northwest of Türkiye. This region hosts several lentic ecosystems used for irrigation and drinking water supply. The present study was conducted to analyze the temporal distributions of water quality parameters (WQPs) of lentic ecosystems (lacustrine habitats), including lakes (L1-L2), reservoirs (R1-R12), and ponds (P1-P19) of the Thrace Region. Thirty-three lacustrine habitats were identified in the region. Freshwaters were collected in the wet (end of winter) and dry (end of summer) seasons of 2021-2022 and tested for 12 WQPs. Data was evaluated for the water quality index (WQI) and nutrient pollution index (NPI) and their overall quality level. For the evaluation of non-carcinogenic health risk indices of WQPs, the chronic daily index (CDI), hazard quotient (HQ), and hazard index (HI) were applied. Cluster analysis (CA), Pearson correlation index (PCI), and principal component analysis (PCA) were used to classify the lacustrine habitats and identify the source of WQPs. The average values were as follows: 9.28 mg/L for dissolved oxygen (DO), 94.6% for oxygen (O 2 ) saturation, 9.29 for pH, 613 μS/cm for electrical conductivity (EC), 3.96 NTU for turbidity, 358 mg/L for total dissolved solids (TDS), 3.17 mg/L for nitrate (NO 3 ), 0.05 mg/L for nitrite (NO 2 ), 1.01 mg/L for phosphate (PO 4 ), 78.5 mg/L for sulfate (SO 4 ), and 102 mg/L for chloride (Cl). Results showed a significant increase in WQPs, including NO 3 , NO 2 , and PO 4 , in the wet season, while the salinity decreased from the dry to wet season. Results revealed that HI values of water contaminants in lacustrine habitats were noted to be less than one. Based on determined WQPs, the present study recommends using lacustrine water habitats for irrigation, drinking, and other domestic and industrial purposes., (© 2024. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Multi-hazards are a great concern in the present world. Likewise, the coastal part of Bangladesh is highly vulnerable to multi-hazards, including waterlogging, surface water salinity, land use change, prolonged dry seasons, and groundwater salinity. Multi-hazards and associated risks make local adaptations more difficult over time. Thus, the purpose of this study is to explore the connection between multi-hazards and their associated socio-ecological risks in the southwestern coastal part of Bangladesh. Mixed-methods approaches were used to collect all the data, and statistical analyses were performed to analyze the data. Results revealed that waterlogging significantly influenced local food access, poverty, child marriage, and divorce problems. Surface water salinity and land use change showed significant differences with the widening of salinity-affected areas. Waterlogging, land use change, and a prolonged dry season all showed significant differences in freshwater access. Prolonged dry seasons and groundwater salinity both have a significant impact on human health. Waterlogging and groundwater salinity significantly influence human migrations. These findings may strengthen local adaptation policies for salinity hazards, land use planning, household poverty, food access, livelihoods, water access, health effects, child marriage, and human migration. In addition, our findings indicate the potential to address the existing knowledge gaps pertaining to coastal hazards, risks, and adaptation issues., Competing Interests: Declaration of competing interest The authors disclose that they have no competing interests., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

Floods occur frequently in Romania and throughout the world and are one of the most devastating natural disasters that impact people's lives. Therefore, in order to reduce the potential damages, an accurate identification of surfaces susceptible to flood phenomena is mandatory. In this regard, the quantitative calculation of flood susceptibility has become a very popular practice in the scientific research. With the development of modern computerized methods such as geographic information system and machine learning models, and as a result of the possibility of combining them, the determination of areas susceptible to floods has become increasingly accurate, and the algorithms used are increasingly varied. Some of the most used and highly accurate machine learning algorithms are the decision tree models. Therefore, in the present study focusing on flood susceptibility zonation mapping in the Trotus River basin, the following algorithms were applied: forest by penalizing attribute-weights of evidence (forest-PA-WOE), best first decision tree-WOE, alternating decision tree-WOE, and logistic regression-WOE. The best performant, characterized by a maximum accuracy of 0.981, proved to be forest-PA-WOE, whereas in terms of flood exposure, an area of over 16.22% of the Trotus basin is exposed to high and very high floods susceptibility. The performances applied models in the present work are higher than the models applied in the previous studies in the same study area. Moreover, it should be noted that the accuracy of the models is similar with the accuracies of the decision tree models achieved in the studies focused on other areas across the world. Therefore, we can state that the models applied in the present research can be successfully used in by the researchers in other case studies. The findings of this research may substantially map the flood risk areas and further aid watershed managers in limiting and remediating flood damage in the data-scarce regions. Moreover, the results of this study can be a very useful for the hazard management and planning authorities., (© 2023 Society for Risk Analysis.)

Background and Aim: Social media is undeniably more accessible and more appreciated today. It is undoubtedly one of the most crucial instruments for student communication. Mental health status can also meaningfully influence the students at the higher levels of the educational institutions. This study aims to evaluate the social media usage of university students and its impact on academic performance and mental health., Methods: To examine under confirmatory factor analysis (CFA) several scale measurements were confirmed by justifying the validity and reliability of several necessary indices and structural equation model. The mediation analysis was also estimated to evaluate the students' Social media addiction (employed Bergen Social Media Addiction Scale) under maximum likelihood estimation with 2000 bootstrapping and 95% bias-corrected bootstrap confidence intervals., Results: This study shows that the usage of social media significantly improves academic performance on psychological well-being, with a Comparative Fit Index of 0.921 and an RMSEA of 0.06 indicating a good fit of the CFA model. Finally, we exhibit a strong statistically significant positive impact of social media usage on academic success, and as supporting the hypothesis, the study observed a positive mediating role of mental health between social media addiction and academic performance., Conclusion: The present research investigations produced unique results, that is, online social media enhances mental health and mediates the link between social media addiction and academic performance in Bangladeshi students. This finding also add to the empirical database on social media usage and have significant theoretical and practical ramifications., Competing Interests: The authors declare that all authors have read and approved the final version of the manuscript. They also declare that the corresponding author has full access to all the data in this study and takes full responsibility for the integrity of the data and the accuracy of the data analysis., (© 2024 The Authors. Health Science Reports published by Wiley Periodicals LLC.)

An enormous amount of power is required in a rising nation like Bangladesh, where achieving economic growth without endangering the environment is a burning issue. The majority of people who live in coastal areas of Bangladesh do not have sufficient access to electricity. There are almost 40 million people living along Bangladesh's 724-km shoreline. Furthermore, it is remarkable that coastal regions have year-round winds, strong enough to generate enormous amounts of power. The viability and promise of wind energy in Bangladesh's southern regions are highlighted in this study. The places demonstrate the possibility for cheaper power production at 30 m-40 m altitudes. The rate of electricity does, however, rise with height. The main objective of this study is to analyze the prospect of wind energy in Sandwip and Kalapara coastal areas of Bangladesh. The data from 1990 to 2020 was taken from the database from the Bangladesh Meteorological Department (BMD) and NASA's NREL (National Renewable Energy Laboratory). These data sources were used to determine the wind power density, wind power output, energy yield, and finally estimate the CO 2 emission reduction. In this paper, a novel approach to the wind energy on selected coastal area is presented and realistic calculation of energy output is carried out of the planned wind system. Finally calculated the realistic CO 2 emission reduction by using this approach for a sustainable future. Estimation reveals that about 162.43 GWh of electricity can be generated annually by installing 684 wind towers on southern Kalapara (Khepupara) area and about 257.25 GWh of electricity can be generated annually by installing 1024 wind tower on the periphery of Sandwip area. So, if 1,768 wind turbines are installed on the Sandwip and Kalapara coastal region instead of burning fossil fuels, about 1,11,373.29 tons of CO 2 will be prevented from being emitted annually., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2024 The Authors.)

Although many studies have focused on chromium removal from aqueous media by ternary Nano adsorbents, still the integrated kinetics, equilibrium, and thermodynamic mechanisms of chromium removal remain unknown. Thus in this study, we have synthesized a novel ternary oxide nanocomposite comprising iron, manganese, and stannous (Fe2O3-MnO2-SnO2) in a facile method as a promising adsorbent for the removal of Cr(VI) from an aqueous medium. The Fe2O3-MnO2-SnO2 system was firstly characterized by FTIR, XRD, TGA, BET, and SEM/EDX. The effect of parameters, for instance, pH, temperature, initial Cr(VI) intensity, and adsorbent dose, have been examined to optimize the Cr(VI) adsorption performance. The adsorption of Cr(VI) onto Fe2O3-MnO2-SnO2 nanoadsorbent is associated with an adsorption/reduction mechanism. Using an initial Cr(VI) intensity of 50 mg L-1, 200 rpm agitation, 2.5-g L-1 of adsorbent, pH 2, 90 minutes adsorption time, and 298 K temperature, a maximum adsorption capability of 69.2 mg Cr(VI) g-1 for Fe2O3-MnO2-SnO2 was obtained. Models of pseudo-2nd-order kinetics and Langmuir's isotherm were best suited to the investigated data. Besides, thermodynamic parameters show that Cr(VI) adsorption onto Fe2O3-MnO2-SnO2 was random and dominated by entropy. The reusability of Fe2O3-MnO2-SnO2 was found to be consistently high (remaining above 80% for Cr(VI)) over four adsorption-desorption cycles. Chromium adsorption from the tannery wastewater was achieved 91.89% on Fe2O3-MnO2-SnO2. Therefore, Fe2O3-MnO2-SnO2 nanoparticles, being easy to be synthesized, reusable and having improved adsorption capability with higher surface area, could be a desirable option for removing Cr(VI) from aqueous environments., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 Uddin et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Background and Aims: Diabetes mellitus, characterized by high blood glucose, is an overwhelming public health concern globally, including in Bangladesh. The implication of this trend may pose a significant challenge to the health systems due to the lack of awareness and improper management of this chronic disease. To formulate strategies for public health planning, this study aims to explore the potential risk factors for elevated blood glucose levels among Bangladeshi individuals using advanced statistical methods and a nationally representative data set., Methods: This study utilized data from the 2017-18 Bangladesh Demographic and Health Survey and included 11,863 individuals. A nonparametric Kruskal-Wallis test assessed the significant association between fasting plasma glucose levels and various risk factors. Additionally, a robust quantile regression model was applied to examine the net effects of each risk factor at different quantiles of the distribution., Results: The prevalence of diabetes is 8.1% among individuals in the study population, with variations observed across different administrative divisions in the country. Respondents from the Dhaka division respondents had a higher likelihood (24.1%) of having elevated plasma glucose and the Rangpur division had a lower risk (10.3%) of developing diabetes disease. This study identified several potential risk factors associated with elevated blood glucose levels, including hypertensive disease, overweight and obese body mass index, higher economic status, reduced physical activities, and older age, significantly contributing to develop diabetes mellitus., Conclusion: This study recommends promoting healthy lifestyles, increased physical activity, effective hypertension management, obesity reduction, and nationwide screening programs to control diabetes and noncommunicable diseases in Bangladesh. These preventive measures are crucial for reducing the existing prevalence of diabetes and working toward achieving the Sustainable Development Goals by 2030., Competing Interests: The authors declare no conflict of interest., (© 2023 The Authors. Health Science Reports published by Wiley Periodicals LLC.)

Many minerals and compounds show thermoluminescence (TL) properties but only a few of them can meet the requirements of an ideal dosimeter. Several phosphate materials have been studied for low-dose dosimetryin recent times. Among the various phosphates, ABPO 4 -type material shows interesting TL properties. In this study, an ABPO 4 -type (A = Lithium, B=Calcium) phosphor is synthesized using a modified solid-state diffusion method. Temperature is maintained below 800 °C in every step of phosphor preparation to obtain the pure phase of Lithium calcium phosphate (LiCaPO 4 ). The purpose of this work is to synthesize LiCaPO 4 using a simple method, examine its structural and luminescence properties in order to gain a deeper understanding of its TL characteristics. The general TL properties, such as TL glow curve, dose linearity, sensitivity, and fading, are investigated. Additionally, this study aims to determine various kinetic parameters through Glow Curve Deconvolution (GCD) method using the Origin Lab software together with the Chen model. XRD analysis confirmed the phase purity of the phosphor with a rhombohedral structure. Lattice parameters, unit cell volume, grain size, dislocated density, and microstrain were also calculated from XRD data. Raman analysis and Fourier Transform Infrared analysis were used to collect information about molecular bonds, vibrations, identity, and structure of the phosphor. To investigate TL properties and associated kinetic parameters, the phosphor was irradiated with 6.0 MV (photon energy) and 6.0 MeV (electron energy) from a linear accelerator for doses ranging from 0.5 Gy to 6.0 Gy. For both photon and electron energy, TL glow curves have two identical peaks near 200 °C and 240 °C.The TL glow curves for 0.5 Gy-6 Gy are deconvoluted, then fitted with the appropriate model and then calculated the kinetic parameters. Kinetic parameters such as geometric factor (μ g ), order of kinetics, activation energy (E), and frequency factor (s) are obtained from Chen's peak shape method. The dose against the TL intensity curve shows that the response is almost linear in the investigated dose range. For photon and electron energy, the phosphor is found to be the most sensitive at 2.0 Gy and 4.0 Gy, respectively. The phosphor shows a low fading and after 28 days of exposure, it shows a signal loss of better than 3%. The studied TL properties suggest the suitability of LiCaPO 4 in radiation dosimetry and associated fields., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

Safe levels of heavy metals in the surface water and sediment of the eastern Bay of Bengal coast have not been universally established. Current study characterized heavy metals such as arsenic (As), chromium (Cr), cadmium (Cd) and lead (Pb) in surface water and sediments of the most important fishing resource at the eastern Bay of Bengal coast, Bangladesh. Both water and sediment samples were analyzed using inductively coupled plasma mass spectrometer. Considering both of the seasons, the mean concentrations of Cr, As, Cd, and Pb in water samples were 33.25, 8.14, 0.48, and 21.14 μg/L, respectively and in sediment were 30.47, 4.48, 0.20, and 19.98 mg/kg, respectively. Heavy metals concentration in water samples surpassed the acceptable limits of usable water quality, indicating that water from this water resource is not safe for drinking, cooking, bathing, and any other uses. Enrichment factors also directed minor enrichment of heavy metals in sediment of the coast. Other indexes for ecological risk assessment such as pollution load index (PLI), contamination factor (CF), geoaccumulation index (I geo ), modified contamination degree (mC d ), and potential ecological risk index (PERI) also indicated that sediment of the coastal watershed was low contamination. In-depth inventorying of heavy metals in both water and sediment of the study area are required to determine ecosystem health for holistic risk assessment and management., Competing Interests: Declaration of competing interest The authors declare that they have no conflict of interest., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

Background: Over the past few decades, diabetes has become a serious public health concern worldwide, particularly in Bangladesh. The advancement of artificial intelligence can be reaped in the prediction of blood glucose levels for better health management. However, the practical validity of machine learning (ML) techniques for predicting health parameters using data from low- and middle-income countries, such as Bangladesh, is very low. Specifically, Bangladesh lacks research using ML techniques to predict blood glucose levels based on basic noninvasive clinical measurements and dietary and sociodemographic information., Objective: To formulate strategies for public health planning and the control of diabetes, this study aimed to develop a personalized ML model that predicts the blood glucose level of urban corporate workers in Bangladesh., Methods: Based on the basic noninvasive health checkup test results, dietary information, and sociodemographic characteristics of 271 employees of the Bangladeshi Grameen Bank complex, 5 well-known ML models, namely, linear regression, boosted decision tree regression, neural network, decision forest regression, and Bayesian linear regression, were used to predict blood glucose levels. Continuous blood glucose data were used in this study to train the model, which then used the trained data to predict new blood glucose values., Results: Boosted decision tree regression demonstrated the greatest predictive performance of all evaluated models (root mean squared error=2.30). This means that, on average, our model's predicted blood glucose level deviated from the actual blood glucose level by around 2.30 mg/dL. The mean blood glucose value of the population studied was 128.02 mg/dL (SD 56.92), indicating a borderline result for the majority of the samples (normal value: 140 mg/dL). This suggests that the individuals should be monitoring their blood glucose levels regularly., Conclusions: This ML-enabled web application for blood glucose prediction helps individuals to self-monitor their health condition. The application was developed with communities in remote areas of low- and middle-income countries, such as Bangladesh, in mind. These areas typically lack health facilities and have an insufficient number of qualified doctors and nurses. The web-based application is a simple, practical, and effective solution that can be adopted by the community. Use of the web application can save money on medical expenses, time, and health management expenses. The created system also aids in achieving the Sustainable Development Goals, particularly in ensuring that everyone in the community enjoys good health and well-being and lowering total morbidity and mortality., (©Masuda Begum Sampa, Topu Biswas, Md Siddikur Rahman, Nor Hidayati Binti Abdul Aziz, Md Nazmul Hossain, Nor Azlina Ab Aziz. Originally published in JMIR Diabetes (https://diabetes.jmir.org), 24.11.2023.)

Background: Many low-income countries continue to have high fertility levels and unmet need for family planning (FP) despite progress in increasing access to modern contraceptive methods and in reducing the total fertility rate (TFR). Health facilities in sub-Saharan Africa (SSA) and South Asia (SA) are thought to be unable to adequately deal with the burden of high unmet FP demands due to their weaker health systems. As a result, determining the readiness of health facilities that offer FP services is critical for identifying weaknesses and opportunities for continued development of FP health systems in those regions. Service Provision Assessment (SPA) tools-which break down health systems into measurable, trackable components-are one useful way to assess service readiness and the ability of health institutions to deliver FP services., Methods: Using data from nationally representative SPA surveys, we conducted a study that aimed to: (1) evaluate healthcare facilities' readiness to provide FP services; and (2) identify the factors that affect FP service readiness. Using a cross-sectional survey design, we used data from SPA surveys conducted in 10 low-resource SA and SSA countries: Afghanistan, Bangladesh, Kenya, Malawi, Namibia, Nepal, Rwanda, Senegal, Tanzania, and the Democratic Republic of the Congo (DRC). We analyzed data from public and private health facilities in Afghanistan (84), Bangladesh (1,303), Kenya (567), Malawi (810), Namibia (357), Nepal (899), Rwanda (382), Senegal (334), Tanzania (933), and the DRC (1,061) for a total of 6,730 facilities. We used 17 items/indicators recommended by the Service Availability and Readiness Assessment to measure a health facility's readiness to provide FP services across four domains., Results: Only 3.6% to 34.1% of the health facilities were reporting at least 75% (12-13 of 17) of the relevant items for FP service provision. Most of the health facilities in the countries under investigation suffered from lack of readiness, meaning that they did not fulfill at least 75% of the standards (12-13 items of 17 items on the availability of trained staff and guidelines, equipment, and commodities components). The factors associated with higher readiness scores varied among the 10 countries analyzed. Regression models showed that increases in the number of FP healthcare providers available at a health facility and infection control measures for FP exams were factors linked to increased readiness scores in all 10 countries. The low readiness of health facilities to provide FP services in the countries studied showed that the health systems in these low-resource settings faced significant problems with providing FP services. Differences in country-specific variability in the characteristics linked with better preparedness ratings could be attributed to data collected across different years in different nations or to country-specific healthcare financing policies., Conclusions: To increase a health facility's readiness to offer FP services, country-specific factors must be addressed, in addition to common factors found in all 10 countries. Further research is required to determine the causes of country-level differences in FP tracer item availability to develop targeted and effective country-specific strategies to improve the quality of FP services in the SA and SSA regions and address unmet need for FP., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 Rahman et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Bangladesh has been ranked as one of the world's top countries affected by climate change, particularly in terms of agricultural crop sector. The purpose of this study is to identify spatial and temporal changes and trends in long-term climate at local and national scales, as well as their implications for rice yield. In this study, Modified Mann-Kendall and Sen's slope tests were used to detect significant trends and the magnitude of changes in temperature and rainfall. The temperature and rainfall data observed and recorded at 35 meteorological stations in Bangladesh over 65-years in the time span between the years 1949 and 2013 have been used to detect these changes and trends of variation. The results show that mean annual Tmean, Tmin, and Tmax have increased significantly by 0.13°C, 0.13°C, and 0.13°C/decade, respectively. The most significant increasing trend in seasonal temperatures for the respective Tmean, Tmin, and Tmax was 0.18°C per decade (post-monsoon), 0.18°C/decade (winter), and 0.23°C/decade (post-monsoon), respectively. Furthermore, the mean annual and pre-monsoon rainfall showed a significant increasing trend at a rate of 4.20 mm and 1.35 mm/year, respectively. This paper also evaluates climate variability impacts on three major rice crops, Aus, Aman, and Boro during 1970-2013. The results suggest that crop yield variability can be explained by climate variability during Aus, Aman, and Boro seasons by 33, 25, and 16%, respectively. Maximum temperature significantly affected the Aus and Aman crop yield, whereas rainfall significantly affected all rice crops' yield. This study sheds light on sustainable agriculture in the context of climate change, which all relevant authorities should investigate in order to examine climate-resilient, high-yield crop cultivation., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 Alam et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Rainfall, temperature, and reference evapotranspiration (ET 0 ) have a significant influence on irrigation, aridity, flooding, and crop water requirements. The primary aims of this study were to analyze the trends in rainfall, temperature, and ET 0 in seven sub-climatic zones of Bangladesh from 1989 to 2020, as well as examine their interrelationships. The Modified Mann-Kendall method was employed to assess trends, while linear regression was used for trend validation. ET 0 was calculated using the FAO-56 Penman-Monteith method, and Sen's slope was utilized to quantify the magnitude. Spatial analysis was conducted using Inverse Distance Weighting techniques. The findings revealed that annual rainfall increased only in the south-eastern zone, while the other zones experienced a decline. No significant changes were observed in annual maximum temperature, except in the south-eastern, north-eastern, and south-central zones, which showed variations ranging from 0.02 to 0.05 (°C/year). However, the yearly minimum temperature increased in all zones. Additionally, negative changes were observed in the annual magnitude of ET 0 for all zones and seasons, except for the south-eastern and north-eastern zones, with a range of 0.01-0.02 mm/year. It was also noted that rainfall and ET 0 displayed a strong decreasing relationship, except during the pre-monsoon season. Regarding regional variation, the northern regions exhibited a significant decreasing trend in both rainfall and ET 0 . The study identified key challenges, including water scarcity and irrigation difficulties due to declining rainfall and evapotranspiration, increased aridity, changing flood patterns, temperature-related impacts on crop growth, regional disparities in climate trends, and the need for effective climate change adaptation measures. Therefore, the study's findings can contribute to knowledge in areas such as irrigation scheduling, promoting climate-smart agricultural practices, encouraging crop diversification to reduce dependence on water-intensive crops cultivation, and planning resilient water resource management to minimize the effects of environmental shifts, regulate human operations, and implement disaster remedial actions in Bangladesh., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper, (© 2023 The Authors.)

Spatiotemporal rainfall trend analysis as an indicator of climatic change provides critical information for improved water resource planning. However, the spatiotemporal changing behavior of rainfall is much less understood in a tropical monsoon-dominated country like Bangladesh. To this end, this research aims to analyze spatiotemporal variations in rainfall for the period 1980-2020 over Bangladesh at seasonal and monthly scales using MAKESENS, the Pettitt test, and innovative trend analysis. Multilayer Perception (MLP) neural network was used to predict the next 8 years' rainfall changes nationally in Bangladesh. To investigate the spatial pattern of rainfall trends, the inverse distance weighting model was adopted within the ArcGIS environment. Results show that mean annual rainfall is 2432.6 mm, of which 57.6% was recorded from July to August. The Mann-Kendall trend test reveals that 77% of stations are declining, and 23% have a rising trend in the monthly rainfall. More than 80% of stations face a declining trend from November to March and August. There is a declining trend for seasonal rainfall at 82% of stations during the pre-monsoon, 75% during the monsoon, and 100% during the post-monsoon. A significant decline trend was identified in the north-center during the pre-monsoon, the northern part during the monsoon, and the southern and northwestern portions during the post-monsoon season. Predicted rainfall by MLP till 2030 suggests that there will be little rain from November to February, and the maximum fluctuating rainfall will occur in 2025 and 2027-2029. The ECMWF ERA5 reanalysis data findings suggested that changing rainfall patterns in Bangladesh may have been driven by rising or reducing convective precipitation rates, low cloud cover, and inadequate vertically integrated moisture divergence. Given the shortage of water resources and the anticipated rise in water demand, the study's findings have some implications for managing water resources in Bangladesh., (© 2023. Springer Nature Limited.)

The current cross-sectional study was conducted among 864 older adults aged ≥ 60 years residing in Rohingya refugee camp through face-to-face interviews during November-December 2021. COVID-19-related anxiety was measured using the five-point Coronavirus Anxiety Scale (CAS) and perceived stress using the 10-point Perceived Stress Scale (PSS). The linear regression model identified the factors associated with COVID-19-related anxiety and perceived stress. The prevalence of COVID-19-related anxiety and perceived stress was 68% and 93%, respectively. The average COVID-19-related anxiety score expected to be significantly higher among those who were physically inactive, concerned about COVID-19, had a close friend/family member diagnosed with COVID-19, and had some difficulty in getting food and routine medical care during the COVID-19 pandemic. Meanwhile, the average perceived stress score was expected to be significantly higher among those without partners, who were feeling overwhelmed by COVID-19, and who experienced COVID-19-related anxiety during the pandemic. The findings suggest providing immediate psychosocial support to older Rohingya adults., (© 2023. The Author(s).)

The elevated concentrations of heavy metals in soil considerably threaten ecological and human health. To this end, the present study assesses metals pollution and its threat to ecology from the mid-channel bar's (char) agricultural soil in the Damodar River basin, India. For this, the contamination factor (CF), enrichment factor (EF), geoaccumulation index (I geo ), pollution index, and ecological risk index (RI) were measured on 60 soil samples at 30 stations (2 from each station, i.e., surface and sub-surface) in different parts of the mid-channel bar. The CF and EF indicate that both levels of char soil have low contamination and hence portray a higher potential for future enrichment by heavy metals. Moreover, I geo portrays that soil samples are uncontaminated to moderately contaminated. Further, pollution indices indicate that all the samples (both levels) are unpolluted with a mean of 0.062 for surface soils and 0.048 for sub-surface soils. Both levels of the char have a low potentiality for ecological risk with an average RI of 0.20 for the surface soils and 0.19 for the sub-surface soils. Moreover, Technique for order preference by similarity to ideal solution (TOPSIS) indicates that the sub-surface soils have lower pollution than the surface soils. The geostatistical modeling reveals that the simple kriging technique was estimated as the most appropriate interpolation model. The present investigation exhibits that reduced heavy metal pollution is due to the sandy nature of soils and frequent flooding. However, the limited pollution is revealed due to the intensive agricultural practices on riverine chars. Therefore, this would be helpful to regional planners, agricultural engineers, and stakeholders in a basin area., (© 2023. The Author(s).)

The emerging technologies of Industry 4.0 (I4.0) are crucial to incorporating agility, sustainability, smartness, and competitiveness in the business model, enabling long-term sustainability practices in the pharmaceutical supply chain (PSC). By leveraging the latest technologies of I4.0, pharmaceutical companies can gain real-time visibility into their supply chain (SC) operations, allowing them to make data-driven decisions that improve SC performance, efficiency, resilience, and sustainability. However, to date, no research has examined the critical success factors (CSFs) that enable the pharmaceutical industry to adopt I4.0 successfully to enhance overall SC sustainability. This study, therefore, analyzed the potential CSFs for adopting I4.0 to increase all facets of sustainability in the PSC, especially from the perspective of an emerging economy like Bangladesh. Initially, sixteen CSFs were identified through a comprehensive literature review and expert validation. Later, the finalized CSFs were clustered into three relevant groups and analyzed using a Bayesian best-worst method (BWM)-based multi-criteria decision-making (MCDM) framework. The study findings revealed that "sufficient investment for technological advancement", "digitalized product monitoring and traceability", and "dedicated and robust research and development (R&D) team" are the top three CSFs to adopt I4.0 in the PSC. The study's findings can aid industrial practitioners, managers, and policymakers in creating effective action plans for efficiently adopting I4.0 in PSC to avail of its competitive benefits and ensure a sustainable future for the pharmaceutical industry., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 Debnath et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Objectives: This study intends to evaluate Dhaka city slum dwellers' responses to Dengue fever (DF). Methods: 745 individuals participated in a KAP survey that was pre-tested. Face-to-face interviews were performed to obtain data. Python with RStudio was used for data management and analysis. The multiple regression models were applied when applicable. Results: 50% of respondents were aware of the deadly effects of DF, its common symptoms, and its infectious nature. However, many were unaware that DF could be asymptomatic, a previously infected person could have DF again, and the virus could be passed to a fetus. Individuals agreed that their families, communities, and authorities should monitor and maintain their environment to prevent Aedes mosquito breeding. However, overall 60% of the study group had inadequate preventative measures. Many participants lacked necessary practices such as taking additional measures (cleaning and covering the water storage) and monitoring potential breeding places. Education and types of media for DF information were shown to promote DF prevention practices. Conclusion: Slum dwellers lack awareness and preventative activities that put them at risk for DF. Authorities must improve dengue surveillance. The findings suggest efficient knowledge distribution, community stimulation, and ongoing monitoring of preventative efforts to reduce DF. A multidisciplinary approach is needed to alter dwellers' behavior since DF control can be done by raising the population's level of life. People and communities must perform competently to eliminate vector breeding sites., Competing Interests: The authors declare that they do not have any conflicts of interest., (Copyright © 2023 Rahman, Tanni, Roy, Islam, Al Raji Rumi, Sadman Sakib, Abdul Quader, Bhuiyan, Shobuj, Sayara Rahman, Haque, Faruk, Tahsan, Rahman, Alam and Md. Towfiqul Islam.)

The current study aims to examine the symmetric and asymmetric effects of climate change (CC) on rice productivity (RP) in Malaysia. The Autoregressive-Distributed Lag (ARDL) and Non-linear Autoregressive Distributed Lag (NARDL) models were employed in this study. Time series data from 1980 to 2019 were collected from the World Bank and the Department of Statistics, Malaysia. The estimated results are also validated using Fully Modified Ordinary Least Squares (FMOLS), Dynamic Ordinary Least Squares (DOLS), and Canonical Cointegration Regression (CCR). The findings of symmetric ARDL show that rainfall and cultivated area have significant and advantageous effects on rice output. The NARDL-bound test outcomes display that climate change has an asymmetrical long-run impact on rice productivity. Climate change has had varying degrees of positive and negative impacts on rice productivity in Malaysia. Positive changes in temperature and rainfall have a substantial and destructive impact on RP. At the same time, negative variations in temperature and rainfall have a substantial and positive impact on rice production in the Malaysian agriculture sector. Changes in cultivated areas, both positive and negative, have a long-term optimistic impact on rice output. Additionally, we discovered that only temperature affects rice output in both directions. Malaysian policymakers must understand the symmetric and asymmetric effects of CC on RP and agricultural policies that will promote sustainable agricultural development and food security., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2023 The Authors.)

Objectives: We aimed to determine: (1) the prevalence and socio-economic distribution of undiagnosed, untreated, and uncontrolled diabetes mellitus (DM); (2) the relationship between socio-economic status (SES) and undiagnosed, untreated, and uncontrolled DM; and (3) if this relationship is mediated by gender., Study Design: Cross-sectional nationally representative household-based survey., Methods: We used data from the Bangladesh Demographic Health Survey from 2017 to 18. Our findings were based on the responses of 12,144 individuals aged 18 years and older. As a measure of SES, we focused on standard of living (hereinafter referred to as wealth). The study's outcome variables were prevalence of total (diagnosed + undiagnosed), undiagnosed, untreated, and uncontrolled DM. We used three regression-based approaches-adjusted odds ratio, relative inequality index, and slope inequality index-to assess different aspects of SES differences in the prevalence of total, undiagnosed, untreated, and uncontrolled DM. We used logistic regression analysis to look at the adjusted association between SES and the outcomes after gender stratification to see whether gender status moderates the association between SES and the targeted outcomes., Results: In our sample analysis, the age-adjusted prevalence of total, undiagnosed, untreated, and uncontrolled DM was 9.1%, 61.4%, 64.7%, and 72.1%, respectively. Females had a higher prevalence of DM and undiagnosed, untreated, and uncontrolled DM than males. When compared to people in the poor SES group, people in the rich and middle SES groups had 2.60 times (95% confidence interval [CI] 2.05-3.29) and 1.47 times (95% CI 1.18-1.83) higher chance of developing DM. When compared to individuals in the poor SES group, those in the rich SES groups were 0.50 (95% CI 0.33-0.77) and 0.55 times (95% CI 0.36-0.85) less likely to have undiagnosed and untreated DM., Conclusions: In Bangladesh, rich SES groups were more likely than poor SES groups to have DM, whereas poor SES groups with DM were less likely than rich SES groups to be aware of their disease and obtain treatment. The government and other concerned parties are urged by this study to pay more attention to developing suitable policy measures to reduce the risk of DM, particularly among rich SES groups, as well as targeted efforts to screen for and diagnose DM in socio-economically disadvantaged groups., (Copyright © 2023 The Royal Society for Public Health. Published by Elsevier Ltd. All rights reserved.)

The present study evaluates the impact of the COVID-19 lockdown on the water quality of a tropical lake (East Kolkata Wetland or EKW, India) along with seasonal change using Landsat 8 and 9 images of the Google Earth Engine (GEE) cloud computing platform. The research focuses on detecting, monitoring, and predicting water quality in the EKW region using eight parameters-normalized suspended material index (NSMI), suspended particular matter (SPM), total phosphorus (TP), electrical conductivity (EC), chlorophyll-α, floating algae index (FAI), turbidity, Secchi disk depth (SDD), and two water quality indices such as Carlson tropic state index (CTSI) and entropy‑weighted water quality index (EWQI). The results demonstrate that SPM, turbidity, EC, TP, and SDD improved while the FAI and chlorophyll-α increased during the lockdown period due to the stagnation of water as well as a reduction in industrial and anthropogenic pollution. Moreover, the prediction of EWQI using an artificial neural network indicates that the overall water quality will improve more if the lockdown period is sustained for another 3 years. The outcomes of the study will help the stakeholders develop effective regulations and strategies for the timely restoration of lake water quality., (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

In this study, we attempt to anticipate annual rice production in Bangladesh (1961-2020) using both the Autoregressive Integrated Moving Average (ARIMA) and the eXtreme Gradient Boosting (XGBoost) methods and compare their respective performances. On the basis of the lowest Corrected Akaike Information Criteria (AICc) values, a significant ARIMA (0, 1, 1) model with drift was chosen based on the findings. The drift parameter value shows that the production of rice positively trends upward. Thus, the ARIMA (0, 1, 1) model with drift was found to be significant. On the other hand, the XGBoost model for time series data was developed by changing the tunning parameters frequently with the greatest result. The four prominent error measures, such as mean absolute error (MAE), mean percentage error (MPE), root mean square error (RMSE), and mean absolute percentage error (MAPE), were used to assess the predictive performance of each model. We found that the error measures of the XGBoost model in the test set were comparatively lower than those of the ARIMA model. Comparatively, the MAPE value of the test set of the XGBoost model (5.38%) was lower than that of the ARIMA model (7.23%), indicating that XGBoost performs better than ARIMA at predicting the annual rice production in Bangladesh. Hence, the XGBoost model performs better than the ARIMA model in predicting the annual rice production in Bangladesh. Therefore, based on the better performance, the study forecasted the annual rice production for the next 10 years using the XGBoost model. According to our predictions, the annual rice production in Bangladesh will vary from 57,850,318 tons in 2021 to 82,256,944 tons in 2030. The forecast indicated that the amount of rice produced annually in Bangladesh will increase in the years to come., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 Noorunnahar et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

World's fossil fuels are disappearing rapidly due to multidimensional uses, mainly for electricity generation. Nevertheless, Bangladesh has also a very limited source of natural gas and coal for electricity production. Hence, the major goal of this review is to outlines the present status of installed renewable generations in the country and predict the future prospect. Despite the existence of literature's abundance on Bangladesh's potential for renewable energy (RE), and their prospects, nothing is covered about the phases of renewable energy projects like projects already completed and running, projects implementation ongoing, and projects under planning. Therefore, an endeavor has been made for the first time to expose Bangladesh's three phases of renewable energy, including projects that are currently operational, those that are still being implemented, and projects that are still in the planning stages. Data was collected from Bangladesh Power Development Board (BPDB), Bangladesh Bureau of Statistics (BBS), Infrastructure Development Company Limited (IDCOL), International Renewable Energy Agency (IRENA), Renewable Energy Policy Network for the 21st Century (REN21), International Hydropower Association (IHA), Sustainable and Renewable Energy Development Authority (SREDA), Ministry of Disaster Management and Relief (MODMR), and Ministry of Power, Energy and Mineral Resources (MOPMER). Based on these data, this research suggests that Bangladesh is generating 723.26 Megawatt (MW) electricity from renewable sources including 67.61% from solar, 31.80% from hydro, 0.58% from others including wind, biogas and biomass, where 489 MW electricity makes from over 6 million (63, 25, 278) of installed solar Photovoltaic (PV) systems till mid of April 2021 and a total of 6,408,721 numbers of RE plants are completed and running. Bangladesh is a prospective area for harvesting solar, wind, and bioenergy with limited hydropower, despite the fact that over 42% of rural societies still lack access to electricity. This review will help investors, shareholders, researchers and decision makers of both public and private sector to realize the latest renewable energy situation of Bangladesh, and for future planning and management in a sustainable way., Competing Interests: The authors declare no conflict of interest., (© 2023 The Authors.)

This study was carried out to determine the spatiotemporal distributions of organic pollution parameters in the Meriç-Ergene River Basin subjected to intensive agricultural and industrial pressure. A total of 5 basin components, including Anadere (A), Çorlu (Ç), Tunca (T), Meriç (M), and Ergene (E) rivers, and 9 stations (A1, Ç1, T1, M1-M2, and E1-E4) were identified in the watershed, and surface water samples were collected in the dry (end of summer) and wet (end of winter) seasons of 2021-2022. The Water Quality Index (WQI) and Nutrient Pollution Index (NPI) were applied to the data to evaluate the overall water quality characteristics. The Chronic Daily Index (CDI), Hazard Quotient (HQ), and Hazard Index (HI) were applied to the data to reveal the probable noncarcinogenic health risks of organic contaminants. Cluster Analysis (CA) and Principal Component Analysis (PCA) were applied to the data to classify the sampling sites and identify the source apportionment of organic pollution parameters. The recorded spatiotemporal averages of the investigated parameters in the basin are as follows: 6.26 mg/L for DO, 9 for pH, 1626 μS/cm for EC, 985 mg/L for TDS, 1 ‰ for salinity, 6.88 mg/L for nitrate, 0.1 mg/L for nitrite, 1.8 mg/L for phosphate, 81 mg/L for sulfate, and 473 mg/L for chloride. The results indicate that the most contaminated components of the basin are Çorlu Stream and Ergene River, and in addition to their quite high salt and nutrient content, they have extreme hypoxic conditions to the extent that it is impossible for many aquatic organisms to live. The contamination degrees of the investigated basin components were determined using the organic pollution risk assessment indices as follows: Çorlu Stream > Ergene River > Anadere Stream > Tunca River > Meriç River., (© 2023. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

Social media platforms serve as essential modes of communication for billions of people around the world. They host a diverse range of content-from the personal and social to the political serving as an important channel for connecting people for spreading ideas. However, given their widespread penetration into everyday social and political life, they have become a tool for spreading rumors and disinformation that may often misrepresent or distort reality and have in many cases incited violence. In Bangladesh, perpetrators over the last decade have utilized social media platforms to spread rumors and to mobilize mobs to launch violent attacks on minority groups. Drawing from social movement theories on how the nexus between social media and political violence works, this paper examines a sample of five cases during the periods of 2011-2022. We exemplify minority attacks being instigated by social media rumors to understand their nature and causes thereof. The study finds that religious extremism, the absence of legal safeguards, and the culture of impunity are the primary triggers, to a varying degree, for the social media rumor-instigated attacks on minorities in Bangladesh., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Roy, Singh and Kamruzzaman.)

Background and Aims: The key interest of this research is to identify the causes of the ongoing increasing trends in caesarean section or C-section (CS) deliveries in both urban and rural areas of Bangladesh., Methods: This study analyzed all Bangladesh Demographic and Health Survey (BDHS) datasets through Chi-square and z tests and the multivariable logistic regression model., Results: CS deliveries were found to be more prevalent in urban than in rural areas of Bangladesh. Mothers above 19 years, above 16 years at first birth, overweight mothers, those with higher educational levels, those who received more than one antenatal care (ANC) visit, fathers having secondary/higher education degrees and employed as workers or in business, and mothers living in wealthy households in the cities of Dhaka, Khulna, Mymensingh, Rajshahi, and Rangpur divisions had a significantly higher likelihood of CS deliveries in urban areas. Contrastingly, mothers with ages between 20 and 39 years, above 20 years at first birth, normal weight/overweight mothers, those with primary to higher level of education, those in the business profession, fathers who also received primary to higher education, mothers who received more than one ANC visit, and those living in wealthy households in Dhaka, Khulna, Mymensingh, Rajshahi, and Rangpur divisions were more likely to have CS deliveries in rural areas. The 45-49 age group mothers had a five times higher likelihood of CS deliveries [odds ratio (OR): 5.39] in urban areas than in rural areas. Wealthy mothers were more likely to be CS-delivered in urban (OR: 4.84) than in rural areas (OR: 3.67)., Conclusion: The findings reveal a gradual upward alarming trend in CS deliveries with an unequal contribution of significant determinants in urban and rural areas of Bangladesh. Therefore, integrated community-level awareness programs are an urgent need in accordance with the findings on the risks of CS and the benefits of vaginal deliveries in this country., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (© 2023 Abdulla, Hossain, Rahman, Rahman and Rahman.)

The study examined the impact on bankers' mental health in terms of fear and anxiety and perceived job insecurity during COVID-19. It also evaluated the effectiveness of combating steps against COVID-19 taken by government and employers to reduce bankers' mental stress. Data were collected from 252 banking professionals in Bangladesh through questionnaire survey. Goodness of fit has been analyzed using Structural Equation Modeling (SEM). Furthermore, Exploratory and confirmatory factor analyses were applied for reliability test. The sampling adequacy was tested using KMO and Bartlett's Test, and the results showed the sample is significant. Cronbach's alpha and composite reliability (C.R) results indicate that the construct is reliable. The results showed fear & anxiety and perceived job insecurity have significant and positive impact on bankers' mental health implying their increase deteriorates bankers' mental health. It is observed that the study and its concerned subject matter absolutely unleashed the inner scenario of banking professionals in Bangladesh. According to this study, lockdown limitations should be used more wisely, and the mental health of the bankers should receive more immediate and consistent attention. In the event that workforce reduction measures are required to address the financial crisis, it is advised that banking sector give furloughs preference over layoffs., Competing Interests: The authors declare no conflict of interest., (© 2022 The Author(s).)

Marine debris is often detected everywhere in the oceans after it enters the marine ecosystems from various sources. Marine litter pollution is a major threat to the marine ecosystem in Bangladesh. A preliminary study was conducted to identify the sources of marine litter (plastics, foamed plastic, clothes, glass, ceramic, metals, paper, and cardboard) along the Bay of Bengal coast. From the observations, the range of abundance of the collected marine litter was 0.14-0.58 items/m 2 . From the ten sampling sites, the highest amount of marine litter was observed for aluminium cans (3500), followed by plastic bottles (3200). The spatial distribution pattern indicated that all the study areas had beach litter of all types of materials. The present investigation showed that plastics were the dominating pollutants in the marine ecosystem in Bangladesh. The clean-coast index (CCI) value indicated that the Cox's Bazar coast was clean to dirty class. The abundance, distribution, and pollution of marine litter along the coastal belts pose a potential threat to the entire ecosystem. This study will help come up with ways to manage and get rid of marine litter along the coast in an effective way., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

Background: The COVID-19 pandemic has resulted in serious mental health conditions, particularly among older adults. This research explored the prevalence of COVID-19-related anxiety and its associated factors among older adults residing in Bangladesh., Methods: This cross-sectional study was conducted among 1,045 older Bangladeshi adults aged ≥ 60 years through telephone interviews in September 2021. A semi-structured interview schedule was used to collect data on participants' characteristics and COVID-19-related anxiety. The anxiety level was measured using the Bengali version of the five-point Coronavirus Anxiety Scale (CAS). A linear regression model explored the factors associated with COVID-19-related anxiety., Results: Overall, the prevalence of COVID-19-related anxiety was 23.2%. The regression analysis revealed that the average COVID-19-related anxiety score was significantly higher among females (β: 0.43, 95% CI: 0.05 to 0.81), and among those who faced difficulty getting medicine (β: 0.57, 95% CI: 0.16 to 0.97), felt isolated (β: 0.60, 95% CI: 0.24 to 0.95), and felt requiring additional care during the pandemic (β: 0.53, 95% CI: 0.16 to 0.91). Alternatively, the average COVID-19-related anxiety score was significantly lower among those who were widowed (β: -0.46, 95% CI: -0.87 to -0.04) and living distant from the health centre (β: -0.48, 95% CI: -0.79 to -0.17)., Conclusion: The findings of the present study suggest providing immediate psychosocial support package to the older adults, particularly females and those who are vulnerable to receive health and social care support during the COVID-19 pandemic in Bangladesh., (© 2022. The Author(s).)

Competing Interests: Sumaira Zafar is a PhD student at the Asian Institute of Technology under the DENCLIM project funded by the Research Council of Norway (grant number 281077). The other authors declare no conflicts of interest.