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Introduction Participation of men in maternal and child health (MCH) is crucial for the reduction of infant and maternal mortality. MCH care services have been focused on providing information and services to women, but males’ behaviour and decisions affect the health of the child and mother. Objectives The objectives of the study were to assess the perception and participation of males in MCH care as well as, to identify the association of their perception and participation with socio-demographic characteristics and to find out the correlation between perception and participation regarding MCH care. Materials and Methods A descriptive type of observational study with a cross-sectional design was conducted among 125 male residents from selected subcentres in Budge Budge II block of South 24 Parganas. Data were collected by face-to-face interviews using a predesigned, pretested, structured schedule. Multivariable binary logistic regression was done to identify the association between dependent and independent variables (P < 0.05). The correlation between perception and participation was assessed by Spearman’s rho. Results The mean age of the participants was 34.3 (±5.6) years with most (59.2%) between the ages of 31–40 years of age. About 24% were unaware of pregnancy registration time, and 30.4% did not know the number of minimum antenatal check-ups. In total, 20% of study participants did not accompany their partner to the Antenatal Care (ANC) clinic, 6.4% did not accompany them during delivery, and almost 33.6% did not accompany their child to the immunization session. No variables were found to be significantly associated with the dependent variables. A statistically significant positive correlation was found between perception and participation (ρ = 0.3). Conclusion Men’s perception and participation in MCH care services were found to be reasonably good though they can be improved. Awareness raises about the importance of men’s role in supporting their partner’s health during pregnancy and postpartum, as well as the overall well-being of their children through public health campaigns, community events, and targeted educational programs.

Introduction: Psychological distress among older adults in India is a concerning issue due to the aging population, the unique challenges they face, and limited access to mental health resources. Understanding and addressing this concern are crucial for promoting better mental health and overall quality of life. This study aims to estimate the prevalence of psychological distress among older adults in selected subcenters of Budge Budge II block, West Bengal; and to find out the factors associated with psychological distress among the study participants. Methods: A descriptive cross-sectional study was conducted among 180 persons aged ≥60 years from different subcenters of the Budge Budge II block selected by multistage random sampling from May 2023 to July 2023 by face-to-face interview using a predesigned, pretested, structured schedule comprising the Kessler Psychological Distress Scale. Multivariable binary logistic regression was done to identify the sociodemographic factors associated with psychological distress. Results: In this study among 180 elderly individuals, the mean age was 67 (±6.34) years, with 65.5% in the 60–69 age group. Nearly two-thirds (70.5%) had no psychological distress, while 18.9%, 5%, and 5.6% had mild, moderate, and severe distress, respectively. Participants who were belonging to the age group 70–79 years [aOR (95% confidence interval [CI]) = 3.31 (1.27–8.63)], widowed or separated (aOR [95% CI] = 3.53 [1.33–9.31]), functionally dependent (aOR [95% CI]) = (8.89 [1.49–53.23]), and economically dependent (aOR [95% CI] = 7.81 [3.21–19.03]) were statistically significant covariates of psychological distress. Conclusion: Nearly one-third of the elderly were suffering from psychological distress. Preventive measures for psychological disorders should be integrated into public health at the local level by providing specialist outpatient services to diagnose and treat common psychological disorders at the primary health center level.

Background and objectives: Children comprised a significant part of the population during the second and third waves of the COVID-19 pandemic. The objectives of this study were to estimate the seroprevalence of COVID-19 IgG antibody among the children aged 6 to 14 years and to determine, if any, the factors associated with seropositivity. Methods: This cross-sectional study was conducted in a selected block of West Bengal, India over a period of 1 year (April 2022-March 2023) among children. Thirty villages in the block were selected by cluster sampling technique. COVID-19 IgM/IgG Rapid Antibody Test Kit (ICMR approved) was used for the detection of SARS-CoV-2 IgG antibodies. Data were analyzed by appropriate statistical tests. Results: Total 600 children were enrolled in the study.SARS-CoV-2 IgG antibody was positive in 57.2% children. The seropositivity rate (91.8%) was significantly (p0.05). Conclusion: SARS-COV-2 IgG antibody was positive in a high proportion of children residing in rural areas indicating asymptomatic coronavirus infections among rural population. Socio-demographic factors such as higher age group and father’s education were significantly associated with seropositivity. July 2024; Vol. 18(2):010. DOI:https://doi.org/10.55010/imcjms.18.022 *Correspondence: Vineeta Shukla, Department of Community Medicine, Infectious Diseases and Beliaghata General Hospital, Kolkata, India. Email: vineeta1992@gmail.com

Zinc performs different metabolic functions in human body and its deficiency is a major concern mainly in the third world countries. Fortification of Zn in grain crops may have the possibility to meet the challenge. The present study was designed utilizing plasma technology for paddy crop in two ways: (i) seed treatment with gliding arc argon-oxygen-ZnSO4-H2O discharge plasma jet in combination with nebulizing system for the fortification of Zn in the seeds, and (ii) plasma treated water (PTW) was sprayed to the plants cultivated from treated seeds and thereby investigated the growth and development of paddy plants defence system, nutritional composition and yield of paddy. Gliding arc argon-oxygen-ZnSO4-H2O discharge plasma jet was employed to treat paddy seeds with nebulizing system for the duration of 2-, 4-, 6-, and 8 min and the 4 min treatment condition provided the maximum 98 % germination among the conditions considered. Seedlings germinated from the 4 min treated seeds were resettled in the research area and PTW were applied two, four, and six times at the time of their growing period. The results reveal that the growth parameters, and the plants defence mechanisms were enhanced. Further, Zn concentration in the grains and the yield of paddy were increased by 59.07 %, 24.06 % and 38.94 %, 22.27 % respectively, compared to control and the plants grown from the treated seeds where no PTW foliar spray was applied. This investigation exposed that the fortification of Zn in seed by plasma processing and PTW spray to the plants which in turn improved seed germination, enzymatic activities, Zn accumulation in rice, and yield. It is fascinating that the paddy harvesting time was reduced more than two weeks compared to control.

Abstract Background The high incidence of low birth weight (LBW) is associated with an increased risk of infant mortality, adverse pregnancy outcomes for mothers, and a decline in overall health and well-being. The current study aimed to identify the various determinants of LBW and its effect on adverse health and nutritional outcomes of children aged 0–23 months in Bangladesh. Methods Bangladesh Demography and Health Survey (BDHS) 2017-18 data was used. A chi-square test and multivariable logistic regression analysis were used to find out the associations between independent variables and outcomes (e.g., LBW, child illness and undernutrition). Results The overall prevalence of LBW among was 16.3%. Mother with no formal education (AOR = 2.64, 95% CI = 0.55–3.30, p = 0.01), female child (AOR = 1.31, 95% CI = 1.04–1.65, p = 0.023); and poorest economic status (AOR = 1.69, 95% CI = 1.13–2.51, p = 0.010), were identified significant determinants of LBW. Of home environment and hygiene factors, unimproved toilet facilities (AOR = 1.38, 95% CI = 1.03–1.84, p = 0.030) had a significant effect on LBW. In addition, children born with LBW were more likely to suffer fever (AOR = 1.26, 95% CI = 1.05–1.60, p = 0.050), stunting (AOR = 2.42, 95% CI = 1.86–3.15, p =

Introduction: Out-of-pocket expenditure (OOPE) has a negative impact on Quality of life (QoL) of People Living with HIV (PLHIV)which can increase the risk of slipping into poverty. Objectives: Primary Objective of this study was to estimate the burden of OOPE in seeking health care among HIV patients attending the Anti-retroviral therapy (ART) centre of a tertiary care hospital; and secondary objectives were to assess their QoL, to identify the association of socio-demographic characteristics with the OOPE & QoL and to find out the correlation between OOPE and QoL. Method: A cross-sectional study was conducted among 232 patients attending ART centre of a tertiary care hospital in Kolkata using a pre-designed, pre-tested, structured schedule. Multivariable binary logistic regression was done to identify the association of their socio-demographic characteristics and clinical profile with the OOPE and QoL. Results: About 41.4% of the study population rated their QoL as neither poor nor good, 18.9% as ‘good’. All the participants reported OOPE; 20.7% in the form of direct health expenditure. Participants belonging to the age group 18-39 years, residing in a joint family, had family member infected with HIV and had associated co-morbidity were statistically significant covariates of direct health expenditure; whereas participants belonging to the age group ≥40 years, living in a joint family, involved in an unskilled occupation, and belonging to middle and lower middle were statistically significant covariates of poor QoL. Conclusion: OOPE was experienced by all participants. As per the study findings Qol was neither poor nor good among participants. With increase in OOPE, the QoL worsened.

Blast and bacterial blight (BB) are the two major rice diseases in the world including Bangladesh. In this study, BB resistance genes (Xa21 and xa13) and blast resistance (Pi9 and Pb1) genes were pyramided into a mega variety, BRRI dhan29 through marker-assisted backcross breeding. IRBB58 was used as a BB-resistant donor and Pi9-US2, and Pb1-US2 were used as blast-resistant donors. Backcross was done between BRRI dhan29 and donor parents to develop BC3F1 population and then selfing was done to develop BC3F6 population. BC3F2 population was genotyped and phenotyped for segregation analysis and BC3F6 was evaluated for genotyping, phenotyping and morphological traits and yields. Chi-square analysis of BC3F2 data revealed that blast and BB resistance followed the single gene mendelian fashion (1:2:1 and 3:1). Two to four gene combinations were found in the advanced lines of the BC3F6 population. The yield of the advanced lines ranged from 6.42 (t ha−1) to 9.5 (t ha−1) and they showed resistant against blast and BB with mean disease scores ranging from 0.67 to 2.33 and 0.33–2.33, respectively. Finally, eight lines having four genes (xa13, Xa21, Pi9 and Pb1) were selected for multilocational (five locations) trials for yield performance and disease reaction. Mean yield data of eight advanced lines of all locations were varied from 6.48±0.15–8.38±0.11 t ha−1 and all the lines showed resistant reactions against blast (score 0.53–1) and BB (score 0.6–0.87) disease. The highest yield was found in BR (Path) 13800-BC3–224–12 (G28, 8.38±0.11 t ha−1) followed by BR (Path) 13800-BC3–134–252 (G26, 8.28±0.08 t ha−1) and BR (Path) 13800-BC3–136–115 (G12, 8.24±0.07 t ha−1). Pyramided advanced lines of this study could be released as BB and blast-resistant varieties or could be utilized as donor parents in resistant breeding.

This study optimised ultrasound-assisted extraction (UAE) temperature, time, and ethanol concentration to investigate total phenolic content (TPC), total flavonoid content (TFC), and antioxidant activity (DPPH free radical scavenging activity assay) from hog plum peel and seed. Optimisation used Response Surface Methodology (RSM) with a Box-Behnken design (BBD) of three factors at three levels. The variables for both peel and seed were temperature (40–60 °C), time (30–60 min), and ethanol concentrations (40–80 %). Fifteen experimental runs were conducted, using a second-order polynomial model (quadratic) and analysis of variance (ANOVA) to predict the responses and validate the model. The results revealed that the moisture, protein, fat, crude fibre, ash, and carbohydrate content of hog plum seed and peel differences in their nutrient content. Additionally, peel contains a TPC of 95–104 mg GAE/100 g DM, DPPH activity of 68–92 %, and TFC of 1.622–2.312 mg QE/g DM, while TPC varies between 97 and 110 mg GAE/100 g DM, DPPH activity ranges from 71 to 95 %, and TFC of 1–22 mg QE/g DM for seed. The R2 value of both peel and seed for TPC, TFC, and DPPH activity was 0.99, indicating that the quadratic model is satisfactory for analysing interactions between response and independent variables. Furthermore, RSM analysis identified the optimal extraction conditions of both peel and seed for maximising TPC, TFC, and DPPH activity at a temperature of 59.82 °C, a time of 41.08 min, and 76.64 % ethanol concentration. Under the optimal settings, the observed values were 108.34 ± 7.23 (peel) and 101.45 ± 3.65 mg GAE/100 g DM (seed) for TPC, 2.98 ± 2.10 (peel), and 3.98 ± 1.34 mg QE/g DM (seed) for TFC, and 85.13 ± 5.43 (peel), and 84.35 ± 4.10 % (seed) for DPPH activity. This study establishes a framework for further investigation into UAE parameters and extraction solvents to enhance the extraction efficiency of hog plum seed and peel.

The main purpose of this paper is to investigate the environmental repercussions of a booming economy, fossil fuel, renewable energy, globalisation, technological innovation, and forest cover in Poland from 1990 to 2018. This study used greenhouse gas (GHG) emissions and load capacity factor as proxies of ecological damage to provide a comprehensive assessment of the surrounding ecosystem in Poland to help implement future policies to reduce emissions and achieve environmental sustainability. Besides, Poland is the only European Union (EU) country lacking a climate neutrality objective and policy instruments to mitigate ecological concerns. The Autoregressive Distributed Lag (ARDL) bounds model and the Dynamic Ordinary Least Squares (DOLS) procedure evaluated yearly data from 1990 to 2018. The empirical outcomes of the DOLS point out that economic growth and fossil fuel energy use enhance GHG emissions despite reducing the load capacity factor in Poland. Instead, renewable power, globalisation, technological innovation, and forest cover might help to reduce GHG emissions and enhance the load capacity factor in Poland. The concluding thoughts from this study suggest the implementation of policies that support raising additional funding for eco-friendly technology studies while promoting renewable energy use and enhancing forest carbon sinks.

BackgroundFetal macrosomia, marked by excessive birth weight, is a significant public health issue in developing countries, yet it has received less attention compared to low birth weight. This study aims to determine the prevalence of fetal macrosomia in Bangladesh and its associated factors.MethodsThe study utilized data from 4,754 women with complete birth weight information of their children from the Bangladesh Multiple Indicator Cluster Survey (MICS) −2019, defining fetal macrosomia as newborns with a birth weight ≥4,000 g regardless of gestational age. Bivariate logistic regression assessed associations between independent variables and fetal macrosomia, presenting adjusted odds ratios (AOR) and a 95% confidence interval (CI), while controlling for potential confounders such as women's age, wealth index, education, healthcare utilization, comorbidities, newborn sex, and place of residence.ResultsThe prevalence of fetal macrosomia was 11.6%. Significant associations with fetal macrosomia included higher maternal age group (30–34 years) (AOR = 1.36, 95% CI = 1.07–1.74), secondary level of mother's education (AOR = 1.95, 95% CI = 1.43–2.66), experienced physical attacks (AOR = 1.41, 95% CI = 1.06–1.88), hypertension during pregnancy (AOR = 1.54, 95% CI = 1.15–2.07), and rural residence (AOR = 1.25, 95% CI = 1.15–1.49). Female infants had 18% lower odds of being macrosomic compared to male infants (AOR = 0.82, 95% CI = 0.72–0.93).ConclusionOne in ten infants in Bangladesh are born with macrosomia, necessitating a multi-faceted approach involving improving maternal nutrition, promoting healthy lifestyles, enhancing access to quality prenatal care, and addressing socioeconomic, residential, and healthcare system challenges, underlining the importance of further community-based research to expand the study's scope.

This study investigated the determinants of financing decisions of firms from the Middle East and North Africa (MENA) region, particularly the effect of public corruption on financing decisions and the effect of disorder following the Arab Spring on public corruption-financing structure relationship. The study encompasses a total of 800 business entities from 14 different countries, spanning the time frame of 2005–2018. Data is analyzed through the application of static fixed effects and dynamic GMM-System models. Results indicate that large, tangible companies prefer debt, whereas profitable companies with more room for growth choose equity. Less corruption is associated with increased corporate debt. The use of debt decreased because of the Arab Spring, and corruption's effect on leverage became weaker. The speed of adjustment to the target leverage is comparatively slow for book leverage, while it is significantly greater for market leverage. These outcomes are consistent with the pecking order behavior resulted from increasing information asymmetry, but the tradeoff theory has some support as well. The implications of this study entail the need for enhancing investor protection, strengthening control measures, increasing transparency, and fostering the overall growth of the financial system to facilitate enterprises' use of debt financing, particularly in the post-Arab Spring era. This paper provides fresh empirical evidence demonstrating the effect of the Arab Spring on capital structure and on the relationship between country corruption and capital structure in the MENA region. The paper also expands the body of research on capital structure and corruption across countries by providing empirical findings from a region that has been relatively overlooked in previous scholarly works.

South Asia is the most polluted region in the world and is struggling to deal with the effects of growing CO2 emissions and the ecological impact it has left. The region needs to identify the variables that are most effective in reducing pollution in order to achieve long-term sustainable growth. The current study aims to investigate the environmental impacts of the current and projected urbanization rate, the service sector, and the availability of natural resources to test the environmental Kuznets-curve (EKC) theory in six South Asian countries (SAARC). With cross-sectional dependence present, this research examines panel data from 1972 to 2021 using the newly developed Driscoll Kraay Standard Error (DKSE) approach. To check the robustness of DKSE estimation, the study employs a novel Cross Sectional Autoregressive Distributive Lag (CS-ARDL) method. The results of DKSE show that GDP significantly minimizes CO2 emissions in both the short and long run. At the same time, GDP2, urbanization, and the service sector increase CO2 emissions in the South Asian region. The DKSE estimator also shows that industrialization and abundant natural resources have insignificant impacts on CO2 emissions. Inconsistent with the EKC hypothesis, the findings show that higher economic growth leads to increased environmental pollution and CO2 levels. Meanwhile, the CS-ARDL analysis found that GDP and industrialization reduce CO2 emissions, while urbanization, GDP2, and natural resource availability increase CO2 emissions. This research emphasizes the need for establishing appropriate industrialization and urbanization strategies and promoting cleaner energy adoption to reduce CO2 emissions.

The transition of the automotive sector to electric vehicles (EVs) necessitates research on charging demand forecasting for optimal station placement and capacity planning. In the literature, extensive studies have been conducted on model-based and probabilistic EV charging demand forecasting schemes. The studies provide a solid research foundation but result in complicated models with limited scalability. Meanwhile, emerging machine learning techniques bring promising prospects, yet exhibit suboptimal performance with insufficient data. Additionally, existing studies often overlook several critical areas such as overcoming data scarcity, security and privacy concerns, managing the inherent stochasticity of demand data, selecting forecasting methods for a specific feature, and developing standardized performance metrics. Considering the impact of the research topic, EV charging demand forecasting demands careful study. In this paper, we present a comprehensive survey of EV charging demand forecasting, focusing on both probabilistic and learning algorithms. First, we introduce the general procedure of EV charging demand forecasting, encompassing data sources, data pre-processing, and the key EV features. We then provide a taxonomy of existing EV charging demand forecasting techniques, followed by a critical analysis and comparative study of state-of-the-art research. Finally, we discuss open issues, which offer useful insights and future direction for various stakeholders.

The study analysed the impact of tourism, trade, consumption expenditure, electricity usage, and population on carbon dioxide emissions (CO2) in leading tourist destinations. The study uses a panel dataset of 32 countries from different continents between 2001 and 2020 and applies the generalized method of moments (GMM) and Quantile Regression approaches. The results suggest that tourism (arrivals and revenues) can reduce environmental degradation, and that CO2 emissions increase due to factors such as GDP per capita, electricity consumption, and population growth. Trade openness can reduce CO2 emissions, and controlling for final consumption also indicates a decrease in CO2 emissions. The study suggests that sustainable tourism practices, responsible consumption, and larger international integration may play a role in mitigating CO2 emissions. Leading tourist destinations should develop sustainable urban areas to accommodate population growth, and embrace eco-friendly technologies, infrastructure, and consumption patterns to promote sustainable economic growth while reducing CO2 emissions.

Sustainable agriculture is an important target of the Sustainable Development Goals (SDGs). Information and communication technologies (ICT) could be an important instrument to assist developing countries in achieving this goal. This study investigates the short- and long-term effects of ICT-related factors (telephone, Internet, mobile phone use) alongside traditional inputs (agricultural land, labor, fertilizer) on sustainable agricultural production in Bangladesh using an autoregressive distributed lag (ARDL) model from 2000 to 2020. In the short term, telephone use and labor involved in agriculture have a positive impact on agricultural production. Conversely, the influence of internet use, mobile phone use, and agricultural land on agricultural production is negative in the short run. In the long run, these relationships have undergone substantial changes. The positive effects of telephone usage and agricultural labor demonstrate a decreasing trend, but the impacts of Internet usage, mobile phone usage, and total agricultural land display a progressively favorable pattern in the long run. Notably, the use of fertilizers has been found to have a positive impact on long-term agricultural production. This study offers valuable insights into the evolving role of ICT in agricultural sustainability, emphasizing the need for context-specific policy interventions that consider both short- and long-term benefits. Doi: 10.28991/HEF-2023-04-04-01 Full Text: PDF

About 14% of adolescents experience mental illnesses globally. The rate increased after the COVID-19 pandemic. This study aimed to estimate the prevalence of COVID-related major mental illnesses (depression and anxiety) and their predictors among adolescents. This community-based cross-sectional study was conducted among 350 adolescents aged 10–19 years, recruited from rural communities in West Bengal, India. The study areas included 27 subcenters in the Budge Budge II Block, which comprised 191,709 population and 45,333 households. Data were collected from randomly selected households by trained research assistants through house-to-house interviews. Pretested standardized questionnaires, Patient Health Questionnaire (PHQ) for depression, Generalized Anxiety Disorder (GAD) for anxiety, and a demographic questionnaire were used for data collection. The prevalence of anxiety was 35.7% (125 out of 350), and the prevalence of depression was 30.0% (105 out of 350). Females had significantly higher scores of anxiety (6.67 ± 4.76 vs. 3.42 ± 3.17, respectively, p < 0.001) and depression (5.51 ± 4.99 vs. 3.26 ± 3.86, respectively, p < 0.001) compared to males. Adolescents who had COVID-19 cases or deaths in the family had significantly higher scores of anxiety and depression compared to those who did not have these events. In multivariate analysis, the statistically significant predictors of anxiety were COVID-19 death in the family, COVID-19 cases in the family, female gender, and a lower income group (p < 0.001 for all). For depression, the significant predictors included COVID-19 death in the family, COVID-19 cases in the family, female gender, a lower income group, and a higher age group in adolescents (p < 0.001 for all). Based on the study results, we recommend that immediate attention is needed for adolescents’ mental health support and coping with stresses following COVID-19.

A facile chemical synthetic method was used to synthesize CuxO thin films on glass substrate via in-situ chemical reaction of CuI thin films in NaOH solution at ambient temperature. CuI thin films were produced by a low-cost plasma-assisted dissociation of the chemical vapor of CuI in acetonitrile (CH3CN) at a pressure of 60 Torr. The prepared CuxO thin films were annealed at various temperatures. The XRD studies unveiled the amorphous character of the CuxO thin films. The SEM images indicated that the surfaces of the films were smooth and smoothness depended on annealing temperature. The EDS studies revealed the presence of huge amounts of C and O with a little amount of Cu in the films which resulted due to the deposition of C produced through dissociation of CH3CN in plasma and O produced from chemical reaction in solution. The optical studies showed that transmittance of the CuxO thin films decreased from that of the CuI thin films and depended on the annealing temperatures. The bandgap of the CuxO thin films decreased with annealing temperature and was in the range of 2.30–2.98 eV. The CuxO thin films exhibited resistivity switching behavior in the first heating-cooling cycle and then the resistivity increased with temperature indicating the metallic behavior. These results are propitious for the application CuxO thin films in solar cells and memristor devices.

This research paper explores the presence of the Environmental Kuznets Curve (EKC) in Bangladesh, delving into the intricate relationships among GDP, industrialization, renewable energy utilization, and CO2 emissions. Utilizing the Stochastic Impacts by Regression on Population, Affluence, and Technology (STIRPAT) model, our investigation spans the 1992 to 2021 timeframe, offering a comprehensive analysis of the interplay between these crucial factors in the context of Bangladesh's environmental sustainability. In this study, the F-bound test is utilized to establish the cointegration relationship among variables. And the short-run and long-run elasticity of explanatory variables is investigated by employing the Autoregressive Distributed Lag (ARDL) approach. This research also employed a pairwise granger causality test to explore the direction of causality between them. Empirical results prove the existence of a cointegration relationship among CO2 emission, GDP per capita, a quadratic form of GDP per capita, renewable energy, industrialization, and population. The findings provide strong support for the presence of the EKC in the case of Bangladesh. Besides that, significant inverse relationship was also obtained between CO2 emission and renewable energy consumption. Additionally, the study found the detrimental long-term effects of industrialization on the environment. The EKC hypothesis argues that Bangladesh can accomplish sustainable economic development. To attain the goal country should adopt appropriate government policies and ensure their implication. This study strongly advocates using sustainable energy sources and implementing regulations on pollutant industries.

Millions of individuals throughout the world suffer from lymphatic filariasis (LF), which is a morbid disease caused by Wuchereria bancrofti, Brugia malayi, and Brugia timori. These infections belong to tissue-invading nematodes and are one of the major neglected tropical diseases that often result in permanent and enduring disability among individuals in endemic regions. Due to combination therapy, LF eradication has drastically decreased infections globally. The development of blood micro-sampling techniques allowing precise quantitation of drugs in blood would facilitate pharmacokinetic (PK) studies in remote populations. Therefore, an LC-MS/MS bioanalytical method was utilized to analyze albendazole (ABZ), albendazole sulfone (ABZ-ON), albendazole sulfoxide (ABZ-OX), and probenecid (PR) in plasma and dried blood spots. Solid-phase extraction was utilized to extract the analyte from both plasma and blood-spiked DBS. Analytes of interest were eluted with a gradient mobile system using 0.05% formic acid in water (A) and 0.05% formic acid in methanol (B) and separated using a reversed-phase Acquity ®BEH C18 UPLC column (100 × 2.1 mm, 1.7 µm). Precision and accuracy at each QC level were within the acceptable limit, i.e., ±15% for all analytes in both the matrices. Tests for stability under laboratory and storage conditions indicated that no notable changes were observed for plasma and DBS. The LC-MS/MS method demonstrated its capability to consistently identify all target analytes (ABZ, ABZ-ON, ABZ-OX, and PR) at low concentrations, even at the small specimen volumes obtained from DBS cards. This confirms the efficacy and durability of DBS cards as a micro-sampling technique. Moreover, it enhances collection efforts for therapeutic drug monitoring in remote locations for patients infected with lymphatic filariasis.

Abstract Despite economic growth and poverty reduction, under-5 child undernutrition is still rampant in South Asian countries. This study explored the prevalence and risk factors of severe undernutrition among under-5 children in Bangladesh, Pakistan, and Nepal for comparison using the Composite Index of Severe Anthropometric Failure. We utilised information on under-5 children from recent Demographic Health Surveys. We used multilevel logistic regression models for data analysis. The prevalence of severe undernutrition among under-5 children was around 11.5%, 19.8%, and 12.6% in Bangladesh, Pakistan, and Nepal, respectively. Children from the lowest socioeconomic quintile, and children born with low birth weight were key factors associated with severe undernutrition in these countries. The factors, parental education, maternal nutritional status, antenatal and postnatal care, and birth order were not homogeneous in explaining the determinants of child severe undernutrition across the countries. Our results suggest that the poorest households, and low birth weight of children have significant effects on severe undernutrition among under-5 children in these countries, which should be considered to formulate an evidence-based strategy to reduce severe undernutrition in South Asia.

Conventional banks are 'indirectly' allowed to take more risk under the shadow of sovereign guarantees. Banks commit moral hazards as any major banking crisis will be 'cushioned' by deposit insurance and bailed out using the taxpayer's money. This study offers an alternative explanation for the determinants of banks' credit risk, particularly those from the Islamic regions. Although conventional banks and Islamic banks may share state and social cushioning systems, Islamic banks are strictly prohibited by moral and religious principles from gambling with depositors' funds, even if there is a cushion available to bail them out. However, banks belonging to collective societies, such as those in the MENA area, may be inclined to take more risks due to the perception of having a larger safety net to protect them in the event of failure. We analyse these theoretical intersections by utilising a dataset consisting of 320 banks from 20 countries, covering the time span from 2006 to 2021. Our analysis employs a combination of Ordinary Least Squares (OLS), Fixed Effects (FE), and 2-step System-GMM methodologies. Our analysis reveals that Islamic banks are less exposed to credit risk compared to conventional banks. We contend that the stricter ethical and moral ground and multi-layer monitoring system amid protracted geopolitical and post-pandemic crises impacting Islamic countries contribute to the lower credit risk. We examine the consequences for credit and liquidity management in Islamic banks and the risk management strategies employed by Islamic banks, which can serve as a valuable reference for other banks.

Abstract Copper iodide (CuI) thin films were prepared on a glass substrate by a facile high pressure (HP)‐PECVD method at room temperature. For this, CuI powder was dissolved in CH3CN. The CuI vapor with plasma was investigated by Optical Emission Spectroscopic (OES) data for identifying the species in the plasma. The XRD study reveals the polycrystalline nature of the films. The SEM analyses indicate the homogeneity of the films. The EDS mapping confirms that the thin films mostly consisted of carbon followed by nitrogen, copper and iodine, respectively. The band gaps of CuI thin films were in the range of ~2.71–3.14 eV. The high transmittance and band gap engineering in HP‐PECVD‐synthesized CuI thin films indicates their potential use as window and hole transport layers in low cost solar cells.

Fear of crime is an important public health problem that impacts people’s quality of life, health, and wellbeing, and causes mental health ailments (e.g., anxiety). This study aimed to determine whether there was an association between fear of crime, educational attainment, and self-rated health and anxiety among women residing in a county in east-central Sweden. A sample (n = 3002) of women aged 18–84 years surveyed in the Health on Equal Terms survey carried out in 2018 was included in the study. Bivariate and multivariate regression analysis was performed on the relationship between the composite variables fear of crime, educational attainment, and self-rated health and anxiety. Women with primary education or similar who reported fear of crime had increased odds of poor health (odds ratio (OR) 3.17; 95% confidence interval (CI) 2.40–4.18) compared with women with primary education/similar and no fear of crime (OR 2.90; CI 1.90–3.20). A statistically significant relationship persisted in the multivariate analysis after controlling for other covariates, although the odds were reduced (OR 1.70; CI 1.14–2.53 and 1.73; CI 1.21–2.48, respectively). Similarly, in the bivariate analysis, women who reported fear of crime and who only had primary education had statistically significant odds of anxiety (OR 2.12; CI 1.64–2.74); the significance was removed, and the odds were reduced (OR 1.30; CI 0.93–1.82) after adjusting for demographic, socioeconomic, and health-related covariates. Women with only primary education or similar who reported fear of crime had higher odds of poor health and anxiety compared with those with university education or similar, with and without fear of crime. Future studies (including longitudinal ones) are warranted—on the one hand, to understand possible mechanisms of the relationship between educational attainment and fear of crime and its consequences to health, and on the other, to explore low-educated women’s own perceptions regarding factors underlining their fear of crime (qualitative studies).

During the COVID-19 pandemic, people’s health behavioral changes have been transposed into a new dimension. Coping with the COVID-19 pandemic may have an impact on sustained health behavior (SHB). Therefore, this study aimed to explore the validity and reliability of the COVID-19 Coping Scale among working-age individuals and to assess whether coping with COVID-19-related stress could influence SHB in this population. A cross-sectional study was conducted based on the population of the city of Dhaka in Bangladesh. A total of 263 working-age individuals (19–65 years) participated in the study. The present study results confirmed the COVID-19 Coping Scale was a valid and reliable instrument for this population. Moreover, the present finding indicated decreased odds of SHB for individuals who rated lower scores on coping with COVID-19 compared to individuals who rated higher scores; the result remained significant after controlling for gender and education (OR 0.68, 95% CI: 0.54–0.87). The present study suggests two important findings: (i) the instrument used in this study was valid and reliable in this population, and (ii) coping with COVID-19-related stress may be an important aspect of practicing SHB. Policymakers may use the highlighted findings to facilitate sustainable health behavior for long-term health benefits and to tackle future pandemics like COVID-19 or in a similar context.

BACKGROUND: Access to safe water, sanitation, and hygiene (WASH) is the most basic need for mankind. Poor WASH practices are associated with various waterborne diseases, especially in developing countries such as India. The aim of the study was to assess WASH practices among residents of different slum settlements in a ward of Kolkata, identify the factors associated with WASH practice, and explore the barriers faced by the families and municipal staff in providing adequate WASH services to the community. MATERIALS AND METHODS: An observational study, cross-sectional in design with a convergent parallel mixed–methods approach, was conducted in different slum settlements in a ward of Kolkata. Quantitative data were collected by face-to-face interview, spot observation, and measuring the living area, door, and window spaces. Key informant interviews were conducted with the medical officer, ward vector-control coordinator, and municipal waste handlers, in addition to in-depth interviews with respondents who had unsatisfactory WASH practices. SPSS version 25.0 was used to analyze the quantitative data. Qualitative data were analyzed thematically using Atlas.ti 22. RESULTS: The overall WASH practices were considered satisfactory in 58.8% of the households. Education of the respondents up to the secondary level, presence of overcrowding, and inadequate ventilation in the house had statistically significantly higher odds of unsatisfactory practice. Poor living conditions, difficulty in collecting and storing water, waterlogging, blocked sewage drains, common toilets for men and women, and lack of motivation were the primary obstacles identified by the residents. CONCLUSION: Unsatisfactory WASH practices were observed among a high proportion of the slum population. Community engagement and education regarding WASH in communities is strongly recommended along with improvement of infrastructure and capacity building.

ObjectiveEarly childhood functional difficulty poses a substantial worldwide public health challenge, leading to adverse effects on children’s quality of life and overall productivity. Moreover, it represents a significant social and economic problem in Bangladesh. Therefore, the current study aimed to identify factors contributing to childhood functional difficulty in Bangladesh within the context of urban–rural areas.MethodsA nationally representative cross-sectional survey data from Multiple Indicator Cluster Survey (MICS), 2019 in Bangladesh was used in this study. Chi-square test and multivariable logistic regression analyses were carried out to identify factors associated with childhood functional difficulty.ResultsFunctional difficulties were found in approximately 3.3% of children 2–4 years of age in urban areas and 2.5% in rural areas. Having a mother with functional difficulties and undernutrition were identified as significant factors common in both urban and rural areas. Further, mothers who had no formal education (AOR = 2.76, 95%CI = 1.18–6.45) and experienced infant death (AOR = 1.94, 95%CI = 1.01–3.70) were identified as significant factors of functional difficulty in urban areas. On the other hand, in rural areas, no access to mass media, children with acute respiratory infection (ARI) (AOR = 2.13, 95%CI = 1.39–3.28), female sex (AOR = 0.69, 95%CI = 0.53–0.91), child undernutrition (AOR = 1.73, 95%CI = 1.32–2.27) and poorer socio-economic status (AOR = 1.95, 95%CI = 1.08–3.55) were found significant factors.ConclusionFunctional difficulty was found to be present in one out of every 35 children age 2 to 4 years in Bangladesh. Childhood functional difficulties were reported slightly higher in urban areas as compared to rural areas. Reducing childhood difficulties in urban areas demands comprehensive strategies: quality healthcare, inclusive education, community support, better information systems, and collaboration. To achieve urban–rural parity in child health, address disparities in economic development, healthcare, and education, especially for girls.

Background: “Telemedicine” is used to provide accessible, quality healthcare to distant people. Globally and also in India, telemedicine was implemented and accelerated during the COVID-19 pandemic. In West Bengal, telemedicine is known as “Swasthya Ingit.” The purpose of the study was to find out the utilization of Swasthya Ingit and to explore challenges faced by community health officers (CHO) and medical officers during consultation in a hub of South 24 Parganas in West Bengal. Materials and Methods: A descriptive record-based, cross-sectional approach with convergent parallel mixed methods was undertaken for 3 months (May–July 2023). A total of 6,775 consultations with Swasthya Ingit was used for quantitative purpose. Data were analyzed using Microsoft Excel 2019 by suitable descriptive statistics. An in-depth interview was conducted for the qualitative strand, and the data were analyzed thematically. Results: A total of 6,775 Teleconsultations were given, of which 76% were utilized by South 24 Parganas district. The maximum consultation was provided to the Baruipur block. Of the attended patients, 71% were female, 73% were adults, and 37% suffered from noncommunicable diseases (NCDs). During the consultation, CHO identified network issues, overburden, lack of workforce resources, and target achievement. Conclusion: Most of the population of South 24 Parganas utilized teleconsultation for NCDs. Lifestyle modification is necessary, along with medication, to combat the then-on-communicable disease burden. The thematic analysis revealed challenges faced by CHO—CHO overburdened with work, weak network issues, pressure of target achievement, and lack of workforce and resources.

Abstract Early detection of cancer will improve survival rates. The blood biomarker 5-hydroxymethylcytosine has been shown to discriminate cancer. In a large covariate-controlled study of over two thousand individual blood samples, we created, tested and explored the properties of a 5-hydroxymethylcytosine-based classifier to detect colorectal cancer (CRC). In an independent validation sample set, the classifier discriminated CRC samples from controls with an area under the receiver operating characteristic curve (AUC) of 90% (95% CI [87, 93]). Sensitivity was 55% at 95% specificity. Performance was similar for early stage 1 (AUC 89%; 95% CI [83, 94]) and late stage 4 CRC (AUC 94%; 95% CI [89, 98]). The classifier could detect CRC even when the proportion of tumor DNA in blood was undetectable by other methods. Expanding the classifier to include information about cell-free DNA fragment size and abundance across the genome led to gains in sensitivity (63% at 95% specificity), with similar overall performance (AUC 91%; 95% CI [89, 94]). We confirm that 5-hydroxymethylcytosine can be used to detect CRC, even in early-stage disease. Therefore, the inclusion of 5-hydroxymethylcytosine in multianalyte testing could improve sensitivity for the detection of early-stage cancer.

IntroductionDepression is a common mental health disorder and one of the major causes of disability. This study aimed at investigating the relationship of acne severity and acne-related quality of life with depressive symptoms, and the mediating effect of acne-related quality of life in a relationship between acne severity and depressive symptoms.MethodsThis is a cross-sectional study. Data were collected from acne patients attending a tertiary-level hospital, using a questionnaire that comprised three validated instruments – Investigator’s Global Assessment (a single item) scale, Cardiff Acne Disability Index, and Beck Depression Inventory for measuring acne severity, acne-related quality of life, and depressive symptoms, respectively. Logistic regression and linear regression were used to examine the association between acne severity and depressive symptoms and a correlation between the acne-related quality of life and depressive symptoms, respectively. A mediation analysis was also performed to see the mediation effects of acne-related quality of life in a relationship between acne severity and depressive symptoms.ResultsA total of 185 acne patients (155 females, 83.8%) with a mean age was 22.55 ± 8.67 years were included in the study. Adolescents and young adults with severe and moderate acne had 6.14-and 2.28 times higher odds of depression compared to their peers with mild acne, respectively. Patients with low levels of acne-related quality of life had a higher level of depressive symptoms (β = 0.42, p

The adhesion systems employed by migrating cortical neurons are not well understood. Genetic deletion studies of focal adhesion kinase (FAK) and paxillin in mice suggested that these classical focal adhesion molecules control the morphology and speed of cortical neuron migration, but whether β1 integrins also regulate migration morphology and speed is not known. We hypothesized that a β1 integrin adhesion complex is required for proper neuronal migration and for proper cortical development. To test this, we have specifically deleted β1 integrin from postmitotic migrating and differentiating neurons by crossing conditional β1 integrin floxed mice into the NEX-Cre transgenic line. Similar to our prior findings with conditional paxillin deficiency, we found that both homozygous and heterozygous deletion of β1 integrin causes transient mispositioning of cortical neurons in the developing cortex when analyzed pre- and perinatally. Paxillin and β1 integrin colocalize in the migrating neurons and deletion of paxillin in the migrating neuron causes an overall reduction of the β1 integrin immunofluorescence signal and reduction in the number of activated β1 integrin puncta in the migrating neurons. These findings suggest that these molecules may form a functional complex in migrating neurons. Similarly, there was an overall reduced number of paxillin+ puncta in the β1 integrin deficient neurons, despite the normal distribution of FAK and Cx26, a connexin required for cortical migration. The double knockout of paxillin and β1 integrin produces a cortical malpositioning phenotype similar to the paxillin or β1 integrin single knockouts, as would be expected if paxillin and β1 integrin function on a common pathway. Importantly, an isolation-induced pup vocalization test showed that β1 integrin mutants produced a significantly smaller number of calls compared to their littermate controls when analyzed at postnatal day 4 (P4) and revealed a several days trend in reduced vocalization development compared to controls. The current study establishes a role for β1 integrin in cortical development and suggests that β1 integrin deficiency leads to migration and neurodevelopmental delays.

Abstract Background Plasma technology is an emerging sector in agriculture. The effect of low-frequency glow discharge (LFGD) plasma at medium pressure (10 torr) on maize morpho-physiological and agronomical behavior was investigated in the current studies. The LFGD plasma act as a secondary messenger to improve maize production. This cutting-edge plasma technology can be used in agriculture to boost agronomic possibilities. Materials and methods Maize seeds were treated with LFGD Ar + Air gas plasma for 30 s, 60 s, 90 s, and 120 s. The gas ratio of Ar + Air was 1:99. Plasma was produced with a high voltage (1–6 kV) and low (3–5 kHz) frequency power supply across the electrodes. The internal pressure was maintained at ~ 10 torrs with a vacuum pump in the plasma chamber. Inside the plasma production chamber, the gas flow rate was maintained at 1 L/min. Results Effect of LFGD Ar + Air plasma on seed germination, and growth parameters including, shoot length, root length, fresh weight, dry weight, plant height, stem diameter, and chlorophyll were measured and in comparison with the control the parameter scores increased by 4.89%, 3.18%, 1.77%, 5.53%, 1.90%, 5.16%, 1.90%, 1.98%, respectively. The SEM image of the seeds surface demonstrated remarkable changes caused by plasma treatment. In roots, APX and SOD activities improved by only 0.022% and 0.64%, whereas, in shoots their activities showed a 0.014% and 0.25% increment compared to control. Further, H2O2, soluble protein, and sugar content increased by 0.12%, 0.33%, 2.50% and 1.15%, 1.41%, 2.99%, 1.16% in shoots and roots, respectively, while NO showed no significant changes in plants. Interestingly, notable improvement were found in nutritional properties (protein 0.32%, fat 0.96%, fiber 0.22%, ash 0.31%, grain iron 1.77%, shoots iron 7.61%, and manganese 6.25%), while the moisture content was reduced by 0.93% which might be useful in prolonged seed storage and the long life viability of the seeds. However, zinc (Zn) content in maize seedlings from plasma-treated seeds showed no significant change. Conclusion The present study revealed that LFGD Ar + Air gas plasma is associated with the elevation of ROS in leaves and roots, which in turn improves the seed germination rate, agronomic traits, growth, enzymatic activity, and nutritional supplement in maize. Graphical Abstract

Abstract Background Coronavirus disease 2019 (COVID-19) is a highly infectious respiratory tract disease. The most common clinical manifestation of severe COVID-19 is acute respiratory failure. Respiratory rehabilitation can be a crucial part of treatment, but data lack for patients with COVID-19. This study investigates the effects of short-term respiratory rehabilitation (i.e., breathing exercises) on respiratory recovery among non-ICU hospitalised patients with COVID-19. Methods This was a quasi-experimental, pre-and post-test study. The study recruited 173 patients hospitalised with moderate to severe COVID-19. All the patients received standardised care for COVID-19, and 94 patients in the intervention group also received the intervention of breathing exercises, which included breathing control, followed by diaphragmatic breathing, deep breathing, or thoracic expansion exercise, and huffing (forced expiratory technique) and coughing. Data on the mean values of peripheral oxygen saturation (SpO2), need for oxygen therapy (litre/min), respiratory rate (breaths/minute), and heart rate (beats/minute) and were collected at baseline, 4 days, and 7 days after the baseline assessment. Analysis of variance on repeated measures was applied to compare the mean value of outcome measures of all the time points. Results The mean (± SD) age of the intervention (69.6% men) and control group (62.1% men) were 50.1 (10.5) and 51.5 (10.4) years, respectively. At 4-day of follow-up, SpO2 (96.6% ± 1.9 vs. 90.7% ± 1.8, P

Diarrhea and fever are prevalent childhood illnesses with potentially severe consequences, especially when they co-occur. This study investigates the prevalence and determinants of diarrhea, fever, and their coexistence among children under-five in Bangladesh. Data from the 2017–2018 Bangladesh Demography and Health Survey (BDHS) were analyzed using multivariable stepwise logistic regression with backward selection. This study found that 5.0% for diarrhea, 34.0% for fever, and 3.0% for the coexistence of both illnesses. Common factors associated with childhood diarrhea and fever included the child’s age (12–23 months), and the mother’s education. Diarrhea was associated with households with improved water sources and children in the Barisal division, while fever was linked to underweight children and those from more affluent backgrounds. The coexistence of both was significantly linked to underweight children, higher birth orders, and children from the Rajshahi division. Notably, child illnesses were associated with parental education, higher socio-economic status, and access to improved drinking water sources. Diarrhea affects one in 20 children, fever affects one in three, and the coexistence of both conditions affects one in 35 children in Bangladesh. The findings need further research and policy reviews to develop effective interventions and improve child health in Bangladesh.

Deep learning methods have shown early progress in analyzing complicated ECG signals, especially in heartbeat classification and arrhythmia detection. However, there is still a long way to go in terms of health-related data analysis. This research provides a duel structured and bidirectional Recurrent Neural Network(RNN) method for arrhythmia classification that addresses the issues with multilayered dilated convolution neural network (CNN) models. Initially, the data is preprocessed by Chebyshev Type II filtering that is faster and do not use statistical characteristics. Noise from the preprocesed filter is aslo removed by using Daubechies wavelet that can able to solve fractal problems and signal discontinuities. An then Z-normalization is done using Pan-Tompkins normalization technique for handling of different normally distributed samples. Finally, a generative adversarial network (GAN)-based synthetic signal is generated for recreation of signal to handle imbalanced signal class. The proposed Bidirectional RNN with Dilated CNN (BRDC) appears to take advantage of the potentiality of multilayered dilated CNN and bidirectional RNN unit (bidirectional gated recurrent Units, BiGRU - bidirectional long short-term memory, BiLSTM) architecture to generate fusion features. Finally, the signals are classified by fully connected layer and Rectified Linear Unit (ReLU) activation function. The PhysioNet 2017 challenge dataset is used to train and validate the proposed model. By combining fusion features with dilated CNN, the learned model significantly improves the classification performance and interpretability. The experimental findings show that, for MIT-BIH provided ECG (electrocardiogram) data to identify arrhythmia, the proposed BRDC model outperforms existing models with 99.90 % accuracy, 98.41 % F1, 97.96 % precision, and 99.90 % recall during training. One of the significant findings of this study is that the proposed approach can significantly reduce time length when employing RNN networks with multilayered dilated CNN. Overall, our hybrid model using BiGRU-BiLSTM and multi-layered dilated CNN provides a cost-effective ECG signal reduction and high-performance automated recognition technique to identify arrhythmia. Our future improvement will focus on the classification of numerous arrhythmia signal-based data, automatic and cloud based ECG classification.

Brain–Computer Interface technology plays a vital role in facilitating post-stroke patients’ ability to carry out their daily activities of living. The extraction of features and the classification of electroencephalogram (EEG) signals are pertinent parts in enabling such a system. This research investigates the efficacy of Transfer Learning models namely ResNet50 V2, ResNet101 V2, and ResNet152 V2 in extracting features from CWT converted wink-based EEG signals, prior to its classification via a fine-tuned Support Vector Machine (SVM) classifier. It was shown that ResNet152 V2-SVM pipeline could achieve an excellent accuracy on all train, test and validation datasets.

The rice-maize (R-M) system is rapidly expanding in Bangladesh due to its greater suitability for diverse soil types and environments. The present conventional method of cultivating puddled transplanted rice and maize is input-intensive, decreases soil health through intense ploughing, and ultimately reduces farm profitability. There is a need to investigate alternatives. Accordingly, we conducted a replicated 2-year (2020–2021) field study to investigate the effects of conservation agriculture (CA) based tillage and crop establishment (TCE) techniques and residue management practices on the physical, chemical, and biological properties of soil along with crop productivity and the profitability of rice-maize systems in the sandy loam soil of Northwest Bangladesh. Two TCE techniques Puddled transplanted rice (PTR) followed by Conventional tillage maize (CTM) and strip tillage direct-seeded rice (STDSR) followed by strip-tilled maize (STM) were assigned to the main plots and different percentages of crop residue retention (0, 25, and 50% by height) were allocated to the subplots. Results showed that a reduction in bulk density (BD), soil penetration resistance (SPR), and increased soil porosity were associated with STDSR/STM-based scenarios (strip tillage coupled with 25 and 50% residue retention). The soil organic carbon (SOC) fractions, such as dissolved organic C (DOC), light and heavy particulate organic matter C (POM-C), MAOM, and microbial biomass C (MBC) levels in the 0–10 cm layer under ST based treatments were 95, 8, 6, 2 and 45% greater, respectively, compared to CT with no residue treatment. When compared to the CT treatment, the DOC, light POM-C, heavy POM-C, and MAOM in the 10–20 cm layer with ST treatment were 8, 34, 25, 4 and 37% higher, respectively. Residue retention in ST increased average rice, maize, and system yields by 9.2, 14.0, and 14.12%, respectively, when compared to CT. The system gross margin and benefit-cost ratio (BCR) were $1,515 ha−1 and 1.90 under conventional tillage to $1,696 ha−1 and 2.15 under strip-tillage practices. Thus, our study suggests that CA could be an appropriate practice for sustaining soil fertility and crop yield under R-M systems in light-textured soils or other similar soils in Bangladesh.

BackgroundAlthough Bangladesh has made noticeable progress in reducing the prevalence of stunting, wasting, and being underweight among under-5 children, it has not been very successful in reducing overall severe anthropometric failure (SAF) among them. Therefore, the study aims to identify the prevalence and risk factors of SAF measured by the Composite Index of Severe Anthropometric Failure (CISAF) among under-5 children in Bangladesh.MethodsData was drawn from a cross-sectional Bangladesh Demographic Health Survey (BDHS) conducted in 2017–2018. A bivariate analysis (Chi-square test) and logistic regression analysis were used to estimate the unadjusted, and age and sex-adjusted prevalence of SAF. Odds ratio (OR) and confidence interval (CI) were assessed using logistic regression analysis to identify the various risk factor of SAF.ResultsThe overall adjusted prevalence of under-5 child SAF was 11.3% (95% CI: 10.6–12.0) and it was highly prevalent among children of uneducated mothers (adjusted, 22%, 95% CI: 17.3–26.8). The key factors associated with SAF were children in the age group 24–35 months (OR: 2.43, 95% CI: 1.83–3.23), children born with low birth weight (OR: 3.14, 95% CI: 2.24–4.97), children of underweight mothers (OR: 1.82, 95% CI: 1.44–2.29), children of parents with no formal education (OR: 2.28, 95% CI: 1.56–3.31) and children from lower socio-economic status (OR: 2.25, 95% CI: 1.55–3.26).ConclusionPrioritizing and ensuring context-specific interventions addressing individual, community, public policy, and environment level risk factors from policy level to implementation to reduce structural and intermediary determinants of under-5 SAF.

Abstract The patients who are impaired with neurodegenerative disorders cannot command their muscles through the neural pathways. These patients are given an alternative from their neural path through Brain-Computer Interface (BCI) systems, which are the explicit use of brain impulses without any need for a computer's vocal muscle. Nowadays, the steady-state visual evoked potential (SSVEP) modality offers a robust communication pathway to introduce a non-invasive BCI. There are some crucial constituents, including window length of SSVEP response, the number of electrodes in the acquisition device and system accuracy, which are the critical performance components in any BCI system based on SSVEP signal. In this study, a real-time hybrid BCI system consists of SSVEP and EMG has been proposed for the environmental control system. The feature in terms of the common spatial pattern (CSP) has been extracted from four classes of SSVEP response, and extracted feature has been classified using K-nearest neighbors (k-NN) based classification algorithm. The obtained classification accuracy of eight participants was 97.41%. Finally, a control mechanism that aims to apply for the environmental control system has also been developed. The proposed system can identify 18 commands (i.e., 16 control commands using SSVEP and two commands using EMG). This result represents very encouraging performance to handle real-time SSVEP based BCI system consists of a small number of electrodes. The proposed framework can offer a convenient user interface and a reliable control method for realistic BCI technology.

The impact of atmospheric glow discharge plasma and plasma activated water on reducing rice seed-borne brown spot disease was investigated. It has been shown that the generation of reactive oxygen and nitrogen species by plasma containing electrons, positive or negative ions, and neutral species has antimicrobial activity. In this study, four plasmas were used for seed treatment viz., O2-air glow discharge plasma for 90 s, 120 s, air-plasma activated water for 9 and 12 min. Control (without treatment) and chemical treatment were used in order to compare the treatment effect. The plasma treatments used for this study showed a promising positive effect on seed germination and plant growth, and reduction of brown spot severity in the field. Among the plasmas, O2-air glow discharge plasma for 90s significantly increased seed germination (94.67%) compared to control (84.0%). Conidial suspension of Bipolaris oryzae treated with O2-air glow discharge plasma for 90 s and air-plasma activated water for 9 min successfully reduced the conidial germination ability of Bipolaris oryzae on Potato Dextrose Agar (PDA). The brown spot incidence and severity were significantly reduced in the plot which received seed treatment with O2-air glow discharge plasma for 90s and air-plasma activated water for 9 min. Interestingly, the same treatment remarkably enhances the plant growth parameters and yield of BRRI dhan28 compared to control treatment. [Fundam Appl Agric 2021; 6(2.000): 107-118]

A March–June 2021 representative serosurvey among Sitakunda subdistrict (Chattogram, Bangladesh) residents found an adjusted prevalence of severe acute respiratory syndrome coronavirus 2 antibodies of 64.1% (95% credible interval 60.0%–68.1%). Before the Delta variant surge, most residents had been infected, although cumulative confirmed coronavirus disease incidence was low.

Objectives: To determine IgG immune responses and hepatitis E virus (HEV) viral load, and to explore the associations with pregnancy. Methods: A total of 121 HEV-infected women (57 pregnant, 64 non-pregnant) were analysed. Quantitative reverse transcription PCR (RT-qPCR) was done for 78 HEV IgM-positive patients to determine viral load, and Sanger sequencing was performed for 62 HEV-RNA-positive patients to confirm genotyping. ELISA was conducted to determine HEV antibody and avidity indices. Results: The HEV genotype was identified as variant 1. Significant negative correlations were observed between log HEV copy number and log hepatitis E virus IgG antibody index in the late acute phase of jaundice for both pregnant women (r = −0.7971, p = 0.0002) and non-pregnant women (r = −0.9117, p = 0.0002). Pregnant women had significantly higher serum log viral copy numbers and lower IgG antibody indices than non-pregnant women in the late acute phase of HEV-induced jaundice (p = 0.0196 and p = 0.0303, respectively). Moreover, pregnant women with acute HEV hepatitis had higher cross-reactive IgG antibodies compared to the non-pregnant women (p = 0.0017). Five patients with HEV hepatitis died, of whom four were pregnant. Conclusions: Pregnancy might be associated with higher viral loads and a lower IgG response in the HEV-induced late acute phase of jaundice.

Abstract Background Impaired work ability and reduced life satisfaction due to long-term musculoskeletal pain, particularly in neck, shoulders and back, are considered occupational health problems that can result in workers taking sick leave. The aim of the study was to determine whether work ability and life satisfaction predict return to work (RTW) among women with long-term neck/shoulder and/or back pain, and to assess the ability of the Work Ability Index (WAI) and the Life Satisfaction Questionnaire (LiSat-11) to discriminate between those who did RTW and those who did not RTW (NRTW). Methods This is a cohort study with 1-year follow-up. A survey was sent to 600 women receiving sick leave benefits from the Swedish Social Insurance Agency. In total, 208 women responded at baseline, and 141 at a 1-year follow-up. To identify whether work ability and life satisfaction predicted RTW, multiple logistic regression analyses were performed with and without adjustment for type of work and pain intensity. To assess the discriminative ability of the WAI and the LiSat-11 for women who did RTW and those who did NRTW, receiver operating characteristic curves were fitted. Results Work ability predicted RTW, and the results remained significant after adjusting for type of work and pain intensity (OR 1.12, 95% CI: 1.04–1.22). Life satisfaction was not significant. The WAI at baseline adequately discriminated between RTW and NRTW after 1 year (Area under curve 0.78, 95% CI: 0.70–0.86), but the LiSat-11 did not. Conclusions This study supports a relationship between work ability and RTW among women on sick leave for long-term neck/shoulder and/or back pain. The results indicate that the WAI, but not the LiSat-11, can discriminate between RTW and NRTW in the population under study. Although the discriminative ability of the WAI needs to be verified in new samples before it can be recommended for use in rehabilitation settings, we suggest that healthcare professionals consider how women perceive their work ability in order to better support them in their RTW.

Background: Work Integration Social Enterprises (WISEs) constitute an important vehicle for providing employment opportunities for disadvantaged groups. Objective: The goal of this qualitative case study is to explore perceptions of health and wellbeing among employees working in a WISE located in the Gävleborg region, in east central Sweden. Methods: Data were gathered using 16 in-depth, semi-structured interviews with the social enterprise employees. Results: Findings were categorized into three main categories: the importance of financial independence and societal benefits; team spirit and a sense of belonging; and improved quality of life and wellbeing. Conclusion: The participants perceived that working in the WISE gave them a feeling of freedom and increased their self-esteem because of the possibility to earn an income. Also, they were satisfied with their job (e.g., with regard to work quality and flexibility) and believed that their work contributed to society. Moreover, through working in a WISE, the participants felt a sense of belonging and togetherness through interaction with co-workers and managers, and an improved quality of life for themselves and their families.

An early and reliable estimation of crop yield is essential in quantitative and financial evaluation at the field level for determining strategic plans in agricultural commodities for import-export policies and doubling farmer’s incomes. Crop yield predictions are carried out to estimate higher crop yield through the use of machine learning algorithms which are one of the challenging issues in the agricultural sector. Due to this developing significance of crop yield prediction, this article provides an exhaustive review on the use of machine learning algorithms to predict crop yield with special emphasis on palm oil yield prediction. Initially, the current status of palm oil yield around the world is presented, along with a brief discussion on the overview of widely used features and prediction algorithms. Then, the critical evaluation of the state-of-the-art machine learning-based crop yield prediction, machine learning application in the palm oil industry and comparative analysis of related studies are presented. Consequently, a detailed study of the advantages and difficulties related to machine learning-based crop yield prediction and proper identification of current and future challenges to the agricultural industry is presented. The potential solutions are additionally prescribed in order to alleviate existing problems in crop yield prediction. Since one of the major objectives of this study is to explore the future perspectives of machine learning-based palm oil yield prediction, the areas including application of remote sensing, plant’s growth and disease recognition, mapping and tree counting, optimum features and algorithms have been broadly discussed. Finally, a prospective architecture of machine learning-based palm oil yield prediction has been proposed based on the critical evaluation of existing related studies. This technology will fulfill its promise by performing new research challenges in the analysis of crop yield prediction and the development of an extremely effective model for the prediction of palm oil yields with the most minimal computational difficulty.

Cardiovascular autonomic neuropathy (CAN) is one of the most overlooked complications associated with diabetes. It is characterized by damage in the autonomic nerves regulating heart rate and vascular compliance. Ewing battery is currently the diagnostic tool of choice but is unable to detect sub-clinical CAN and requires patient cooperation. In addition, appropriate timing (day/night) of CAN diagnostic test was not explored in the past. Therefore, a novel approach is proposed herein to investigate the feasibility of using heart rate variability (HRV) features over 24 hours embedded within machine learning algorithms to provide a complete screening for patients suffering from CAN. 24-hour Holter ECG data were acquired from a Bangladeshi cohort (n = 95 patients [75 Diabetic and 25 healthy]). HRV features were extracted from every 5-minute segment of the HRV signal and used as input to four machine learning algorithms for hourly training and testing. A complete hierarchical step by step diagnosis procedure (4 tests) was developed; namely test 1 to check for being healthy or diabetic; test 2 to check for any microvascular complications (including neuropathy such as CAN, peripheral neuropathy (DPN), nephropathy (NEP), and retinopathy (RET)) or not; test 3 to check for presence of only CAN; test 4 to check for combined or multiple complications along with CAN. The highest levels of performance were achieved with accuracy measures of 85.5% (test 1 - convolutional neural network (CNN)), 98.5% (test 2 - CNN), 98.3% (test 3 - one-class support vector machines (SVM)), and 90.9% (test 4 - random forest). Hours 7:00 AM and 7:00 PM were found to be most significant in the diagnosis of CAN in diabetic patients (test 1, 3, and 4). Early screening of CAN by our proposed models could help primary healthcare centers stratify the risk leading to early treatment in preventing sudden cardiac death due to silent myocardial infarction. The approach is considered to be simple and effective, especially for under-resourced clinical settings.

A research article recommendation approach aims to recommend appropriate research articles to analogous researchers to help them better grasp a new topic in a particular research area. Due to the accessibility of research articles on the web, it is tedious to recommend a relevant article to a researcher who strives to understand a particular article. Most of the existing approaches for recommending research articles are metadata-based, citation-based, bibliographic coupling-based, content-based, and collaborative filtering-based. They require a large amount of data and do not recommend reference articles to the researcher who wants to understand a particular article going through the reference articles of that particular article. Therefore, an approach that can recommend reference articles for a given article is needed. In this paper, a new multi-level chronological learning-based approach is proposed for recommending research articles to understand the topics/concepts of an article in detail. The proposed method utilizes the TeKET keyphrase extraction technique, among other unsupervised techniques, which performs better in extracting keyphrases from the articles. Cosine and Jaccard similarity measures are employed to calculate the similarity between the parent article and its reference articles using the extracted keyphrases. The cosine similarity measure outperforms the Jaccard similarity measure for finding and recommending relevant articles to understand a particular article. The performance of the recommendation approach seems satisfactory, with an NDCG value of 0.87. The proposed approach can play an essential role alongside other existing approaches to recommend research articles.

Microglia, the resident immune cells of the central nervous system (CNS), are responsible for maintaining homeostasis in the brain by clearing debris and are suggested to be inefficient in Alzheimer’s Disease (AD), a progressive neurodegenerative disorder for which there is no disease-modifying drug. Besides pathological approaches, unbiased evidence from genome-wide association studies (GWAS) and gene network analysis implicate genes expressed in microglia that reduce phagocytic ability as susceptibility genes for AD. Thus, a central feature toward AD therapy is to increase the microglial phagocytic activities while maintaining synaptic integrity. Here, we developed a robust unbiased high content screening assay to identify potential therapeutics which can reduce the amyloid-beta (Aβ1–42) load by increasing microglial uptake ability. Our screen identified the small-molecule GW5074, an inhibitor of c-RAF, a serine/threonine kinase, which significantly increased the Aβ1–42 clearance activities in human monocyte-derived microglia-like (MDMi) cells, a microglia culture model that recapitulates many genetic and phenotypic aspects of human microglia. Notably, GW5074 was previously reported to be neuroprotective for cerebellar granule cells and cortical neurons. We found that GW5074 significantly increased the expression of key AD-associated microglial molecules known to modulate phagocytosis: TYROBP, SIRPβ1, and TREM2. Our results demonstrated that GW5074 is a potential therapeutic for AD, by targeting microglia.

The auditory evoked potential (AEP) has been considered a standard clinical instrument for hearing and neurological evaluation. Although several approaches for learning EEG signal characteristics have been established earlier, the hybridization concept has rarely been explored to produce novel representations of AEP features and achieve further performance enhancement for AEP signals. Moreover, the classification of auditory attention within a concise time interval is still facing some challenges. To address this concern, this study has proposed a hybridization scheme, represented as a hybrid convoluted k-nearest neighbour (CKNN) algorithm, consisting of concatenating the convolutional layer of CNN with k-nearest neighbour (k-NN) classifier. The proposed architecture helps in improving the accuracy of KNN from 83.23% to 92.26% with a 3-second decision window. The effect of several concise decision windows is also investigated in this analysis. The proposed architecture is validated by a publicly benchmark AEP dataset, and the outcomes indicate that the CKNN significantly outperforms other state-of-the-art techniques with a concise decision window. The proposed framework shows superior performance in a concise decision window that can be effectively used for early hearing deficiency diagnosis. This paper also presents several discoveries that could be helpful to the neurological community.

Abstract To establish whether 4-nitroquinoline N-oxide-induced carcinogenesis mirrors the heterogeneity of human oral squamous cell carcinoma (OSCC), we have performed genomic analysis of mouse tongue lesions. The mutational signatures of human and mouse OSCC overlap extensively. Mutational burden is higher in moderate dysplasias and invasive SCCs than in hyperplasias and mild dysplasias, although mutations in p53, Notch1 and Fat1 occur in early lesions. Laminin-α3 mutations are associated with tumour invasiveness and Notch1 mutant tumours have an increased immune infiltrate. Computational modelling of clonal dynamics indicates that high genetic heterogeneity may be a feature of those mild dysplasias that are likely to progress to more aggressive tumours. These studies provide a foundation for exploring OSCC evolution, heterogeneity and progression.