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Abstract Background and Aim Allergenic foods can trigger skin conditions, yet their impact in Bangladesh remains underexplored. This study aims to investigate the potential association between exposure to allergenic foods and the development of skin disease across Bangladesh. Methods We conducted a cross‐sectional survey with 970 respondents from the divisions of Dhaka, Sylhet, Rangpur, and Chattogram who self‐reported skin disease triggered by food allergens. We analyzed the data using multiple response analysis and principal component logistic regression. Results Approximately 64% of respondents had skin disease attributable to allergenic foods, with a relatively higher proportion among females (52%) than males (48%). Beef (67%), Brinjal (47.1%), Hilsa (45.8%), and Shrimp (23.7%) were the most frequently cited allergenic foods. Principal component logistic regression identified two highly significant principal components: the first representing Hilsa, Beef, and Brinjal (odds ratio = 2.256), and the sixth reflecting Corn (odds ratio = 1.342). Individuals who consumed foods with high loadings of the first principal component were 125.6% more likely to develop skin disease than nonconsumers, while those exposed to Corn had a 34.2% higher risk. Conclusion The findings highlight prevalent allergenic foods in Bangladesh and their substantial impact on skin health, underscoring the need for dietary awareness and tailored interventions to mitigate allergic skin conditions in this population.

Abstract Background Malaria is one of the most prominent illnesses affecting children, ranking as one of the key development concerns for many low- and middle-income countries (LMICs). There is not much information available on the use of anti-malarial drugs in LMICs in children under five. The study aimed to investigate disparities in anti-malarial drug consumption for malaria among children under the age of five in LMICs. Methods This study used recent available cross-sectional data from the Malaria Indicator Survey (MIS) datasets across five LMICs (Guinea, Kenya, Mali, Nigeria, and Sierra Leone), which covered a portion of sub-Saharan Africa. The study was carried out between January 2, 2023, and April 15, 2023, and included children under the age of five who had taken an anti-malarial drug for malaria 2 weeks before the survey date. The outcome variable was anti-malarial drug consumption, which was classified into two groups: those who had taken anti-malarial drugs and those who had not. Results In the study of LMICs, 32,397 children under five were observed, and among them, 44.1% had received anti-malarial drugs. Of the five LMICs, Kenya had the lowest (9.2%) and Mali had the highest (70.5%) percentages of anti-malarial drug consumption. Children under five with malaria are more likely to receive anti-malarial drugs if they are over 1 year old, live in rural areas, have mothers with higher education levels, and come from wealthier families. Conclusion The study emphasizes the importance of developing universal coverage strategies for anti-malarial drug consumption at both the national and local levels. The study also recommends that improving availability and access to anti-malarial drugs may be necessary, as the consumption of these drugs for treating malaria in children under the age of five is shockingly low in some LMICs.

Abstract Background The coronavirus disease 2019 (COVID‐19) pandemic has had a severe impact on population health. The genetic determinants of severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) in southern Bangladesh are not well understood. Methods This study aimed to determine the genomic variation in SARS‐CoV‐2 genomes that have evolved over 2 years of the pandemic in southern Bangladesh and their association with disease outcomes and virulence of this virus. We investigated demographic variables, disease outcomes of COVID‐19 patients and genomic features of SARS‐CoV‐2. Results We observed that the disease severity was significantly higher in adults (85.3%) than in children (14.7%), because the expression of angiotensin‐converting enzyme‐2 (ACE‐2) diminishes with ageing that causes differences in innate and adaptive immunity. The clade GK (n = 66) was remarkable between June 2021 and January 2022. Because of the mutation burden, another clade, GRA started a newly separated clustering in December 2021. The burden was significantly higher in GRA (1.5‐fold) highlighted in mild symptoms of COVID‐19 patients than in other clades (GH, GK, and GR). Mutations were accumulated mainly in S (22.15 mutations per segment) and ORF1ab segments. Missense (67.5%) and synonymous (18.31%) mutations were highly noticed in adult patients with mild cases rather than severe cases, especially in ORF1ab segments. Moreover, we observed many unique mutations in S protein in mild cases compared to severe, and homology modeling revealed that those might cause more folding in the protein's alpha helix and beta sheets. Conclusion Our study identifies some risk factors such as age comorbidities (diabetes, hypertension, and renal disease) that are associated with severe COVID‐19, providing valuable insight regarding prioritizing vaccination for high‐risk individuals and allocating health care and resources. The findings of this work outlined the knowledge and mutational basis of SARS‐CoV‐2 for the next treatment steps. Further studies are needed to confirm the effects of structural and functional proteins of SARS‐CoV‐2 in detail for monitoring the emergence of new variants in future.

IntroductionDementia is one of the major global health issues among the aging population, characterized clinically by a progressive decline in higher cognitive functions. This paper aims to apply various artificial intelligence (AI) approaches to detect patients with mild cognitive impairment (MCI) or dementia accurately.MethodsQuantitative research was conducted to address the objective of this study using randomly selected 343 Saudi patients. The Chi-square test was conducted to determine the association of the patient’s cognitive function with various features, including demographical and medical history. Two widely used AI algorithms, logistic regression and support vector machine (SVM), were used for detecting cognitive decline. This study also assessed patients’ cognitive function based on gender and developed the predicting models for males and females separately.ResultsFifty four percent of patients have normal cognitive function, 34% have MCI, and 12% have dementia. The prediction accuracies for all the developed models are greater than 71%, indicating good prediction capability. However, the developed SVM models performed the best, with an accuracy of 93.3% for all patients, 94.4% for males only, and 95.5% for females only. The top 10 significant predictors based on the developed SVM model are education, bedtime, taking pills for chronic pain, diabetes, stroke, gender, chronic pains, coronary artery diseases, and wake-up time.ConclusionThe results of this study emphasize the higher accuracy and reliability of the proposed methods in cognitive decline prediction that health practitioners can use for the early detection of dementia. This research can also stipulate substantial direction and supportive intuitions for scholars to enhance their understanding of crucial research, emerging trends, and new developments in future cognitive decline studies.

Understanding the factors that influence smoking cessation among young people is crucial for planning targeted cessation approaches. The objective of this review was to comprehensively summarize evidence for predictors of different smoking cessation related behaviors among young people from currently available systematic reviews. We searched six databases and reference lists of the included articles for studies published up to October 20, 2023. All systematic reviews summarizing predictors of intention to quit smoking, quit attempts, or smoking abstinence among people aged 10-35 years were included. We excluded reviews on effectiveness of smoking cessation intervention; smoking prevention and other smoking behaviors; cessation of other tobacco products use, dual use, and polysubstance use. We categorized the identified predictors into 5 different categories for 3 overlapping age groups. JBI critical appraisal tool and GRADE-CERqual approach were used for quality and certainty assessment respectively. A total of 11 systematic reviews were included in this study; all summarized predictors of smoking abstinence/quit attempts and two also identified predictors of intention to quit smoking. Seven reviews had satisfactory critical appraisal score and there was minimal overlapping between the reviews. We found 4 'possible' predictors of intention to quit smoking and 119 predictors of smoking abstinence/quit attempts. Most of these 119 predictors were applicable for ~10-29 years age group. We had moderate confidence on the 'probable', 'possible', 'insufficient evidence', and 'inconsistent direction' predictors and low confidence on the 'probably unrelated' factors. The 'probable' predictors include a wide variety of socio-demographic factors, nicotine dependence, mental health, attitudes, behavioral and psychological factors, peer and family related factors, and jurisdictional policies. These predictors can guide improvement of existing smoking cessation interventions or planning of new targeted intervention programs. Other predictors as well as predictors of intention to quit smoking need to be further investigated among adolescents and young adults separately.

Abstract Background Food insecurity indicates the difficulty of constantly obtaining adequate food because of limited economic resources. Food insecurity challenges the desired health outcomes. Although extensive literature has examined the associations between food security and health, low-wage informal sector workers have been less frequently addressed in this topic. The present study has focused on food insecurity among the workers working in the informal sector enterprises who experienced entrenched disadvantage during COVID-19 and examines the relationship between food insecurity and health status as measured by self-reported physical and mental health conditions. Methods This study has utilized cross-sectional data collected from workers working in informal manufacturing and business enterprises in Dhaka city of Bangladesh. The Food Insecurity Experience Scale (FIES) with eight items is used to screen for food insecurity, and the Short Form 12v2 (SF12v2) scale with 12 questions, and validated for use with Bengali respondents, is used to measure the health status of the informal workers. A health production function has been constructed where the health status (both physical and mental) of workers is associated with food insecurity and other socio-economic and health care factors. Empirical analyses of the study have included descriptive statistics, mean score comparisons, and multivariate regression analyses to identify the predictive factors of the physical and mental health status of the workers. Results A moderate to severe food insecurity is found to be responsible for the poor health status (both physical and mental) of the selected working group population. Moreover, age over 40 years, having a large family, dissatisfaction with the work place, and the prevalence of occupational health risks are linked to lower physical health, while dissatisfaction with the work place and the incidence of severe diseases contribute to poor mental health status along with food insecurity. Conclusions Extending social and economic protection towards health coverage and basic consumption is suggested as an immediate action to save lives and ensure productivity of the informal workers. Besides, an increase in income and ensuring decent working conditions are also recommended for the health, safety and satisfaction of workers working in informal sector enterprises.

Abstract Background and Aims The study aimed to evaluate the pharmacological properties of methanolic extracts of leaves and barks of Woodfordia fruticosa (L.) Kurz (family: Lythraceae) focusing on antioxidant, thrombolytic, anti‐inflammatory, antibacterial, analgesic, and antidiarrheal effects. Methods 1,1‐Diphenyl‐2‐picrylhydrazyl (DPPH) free radical scavenging assay, clot lysis, disc diffusion, and membrane stabilizing methods were employed to assess in vitro antioxidant, thrombolytic, antibacterial, and anti‐inflammatory properties of the leaf and bark methanolic extracts (ME) of W. fruticosa and different organic solvents, that is, petroleum ether (PE), dichloromethane (DCM), chloroform (CL), and aqueous (AQ) fractions. In addition, in vivo central and peripheral analgesic and antidiarrheal activities of both crude extracts were evaluated at two doses (200 and 400 mg/kg of body weight [bw]). Results All the extracts and fractions showed promising antioxidant properties by scavenging DDPH free radicals with IC50 of 6.11–20.79 μg/mL. AQ fraction (41.24%) of leaves and ME (44.90%) of bark exerted notable in vitro thrombolytic activity. The CL fraction of leaves and AQ fraction of the bark showed 43.16% and 45.37% inhibition of RBC hemolysis, respectively, compared to the inhibition of RBC hemolysis by aspirin in a hypotonic‐induced membrane stabilizing assay. Besides, both extracts were observed to provide significant (p

In recent years, small molecule inhibition of LDHA (Lactate Dehydrogenase A) has evolved as an appealing option for anticancer therapy. LDHA catalyzes the interconversion of pyruvate and lactate in the glycolysis pathway to play a crucial role in aerobic glycolysis. Therefore, in the current investigation LDHA was targeted with bioactive phytochemicals of an ethnomedicinally important plant species Oroxylum indicum (L.) Kurz. A total of 52 phytochemicals were screened against LDHA protein through molecular docking, ADMET (Absorption, Distribution, Metabolism, Excretion and Toxicity) assay and molecular dynamics simulation to reveal three potential lead compounds such as Chrysin-7-O-glucuronide (−8.2 kcal/mol), Oroxindin (−8.1 kcal/mol) and Oroxin A (−8.0 kcal/mol). ADMET assay unveiled favorable pharmacokinetic, pharmacodynamic and toxicity properties for all the lead compounds. Molecular dynamics simulation exhibited significant conformational stability and compactness. MM/GBSA free binding energy calculations further corroborated the selection of top candidates where Oroxindin (−46.47 kcal/mol) was found to be better than Chrysin-7-O-glucuronide (−45.72 kcal/mol) and Oroxin A (−37.25 kcal/mol). Aldolase reductase and Xanthine dehydrogenase enzymes were found as potential drug targets and Esculin, the FDA approved drug was identified as structurally analogous to Oroxindin. These results could drive in establishing novel medications targeting LDHA to fight cancer.

Certain benthic polychaetes, such as species within the genus Namalycastis, are employed in the diet of gravid shrimps in aquaculture due to their amino acids and highly unsaturated fatty acid content, enhancing the quality of gravid shrimp. Despite its importance in the rapidly developing shrimp culture industry, the population parameters of this economically valuable species are unknown. Therefore, the present study examines the population parameters of Namalycastis fauveli to assess its occurrence, growth, recruitment, exploitation level, and stock status in Bangladesh. Monthly samplings of N. fauveli and environmental variables were collected from five sites of the Cox’s Bazar coast using a square-shaped mud corer with a 0.093 m2 (or 1.0 ft2) mouth opening from August 2020 to July 2021 to measure or estimate. Within the 8.0–30.0 cm depth range of the intertidal zone, polychaete samples were collected from the sediment. The results showed negative allometric growth (b < 3), but there was a significant L–W relationship (p < 0.05, r2 = 0.43 to 0.94). The estimated L∝, K, and ϕ were 22.05 cm, 0.99 year−1, and 2.69, respectively, while total mortality (Z) was 4.56 year−1. It was calculated that the fishing mortality and capture probability proportionally increased with the total length at a certain age. Recruitment mostly occurred in October and March, and temperature had a greater impact than salinity. The evaluated exploitation level (E = 0.57) indicated that the stock was overexploited. Thus, the above results provide some valuable information for shrimp farmers and stakeholders, as well as for policymakers in the move towards restoration, species conservation, and efficient management of N. fauveli natural stocks.

The future of the world is becoming more uncertain owing to climate change. The unfolding impacts of climate change are affecting human societies and natural ecosystems. Projections of climate change impacts are associated with a cascade of uncertainties including greenhouse gas emissions scenarios, climate models, and associated processes. Climate models are essential for predicting flow and flood peaks, necessitating proper means of quantification and re-use to help refine the predictions made. This study presents an innovative new framework to quantify flood damage assessment as the climate changes. To integrate uncertainty in modelling catchment behaviour, the Quantile Flow Deviation (QFD) metric was used to attribute different sources of uncertainty, including those from variations in climate from point measurements and from extrapolation to flood peaks from the limited observed flows that are available. The square root of error variance (SREV) calculated from global climate model (GCM) precipitation outputs was used to quantify climate change uncertainty, thereby enabling the estimation of the uncertainty in modelled streamflow to allow the extent of change in flood damage to be assessed. Using data from the Leaf River catchment in the USA, this study presents the increase in flood damage uncertainty resulting from explicit consideration of uncertainty as well as the change in the climate as a function of global temperature rise. HIGHLIGHTS Uncertainty in flood magnitudes resulting from climate change for the current climate is quantified.; A new framework for quantifying flood damage assessment considering climate change impact is developed.; Flood damage uncertainty with temperature increases to date of 1 and of 2 °C before the end of this century is investigated.;

The present study aims to assess the prospects for cleaner production (CP) and sustainable development (SD) of informally operated small manufacturing enterprises, which are frequently blamed for uncontrolled waste disposal and causing pollution to the environment. The economic efficiency level of these firms has been explored to this end, and the metallic pollution loads in the surrounding environment have been scientifically analyzed to investigate the nexus between these two. DEA (Data Envelopment Analysis)-Tobit analysis has been employed, and a pollution load index (PLI) of heavy metal pollution comprising two environmental compartments (soil and water) has been constructed based on the concentration level of metalloid pollutants in the samples collected from the surrounding areas of the studied informal firms in Bangladesh. The study disproves CP practice in majority of the informal firms in Bangladesh by observing a positive relationship between firm-level efficiency and pollution load sourced from their production activities. Afterwards, this study estimates the eco-efficiency level of firms by considering pollution load as an undesirable output and minimizing its impact in an input-oriented DEA model. Applying the eco-efficiency scores in censored Tobit regression analysis, the outcome endorses the prospect of CP for informally operated enterprises in Bangladesh. However, the CP prospect can only materialize if and only if firms are provided with adequate technical, financial, and strategic support for achieving eco-efficiency in their production. The informal and marginal nature of the studied firms restricts them from getting access to the facilities and support services needed for implementing CP and moving towards sustainable manufacturing. Therefore, this study recommends green practices in informal manufacturing and limiting the informal firms by bringing them gradually under the coverage of formalization, which is in line with the achievement of the targets mentioned in Sustainable Development Goal 8.

Shigellaa Gram-negative, non-motile bacillus, is the primary causative agent of the infectious disease shigellosis, which kills 1.1 million people worldwideevery year. The children under the age of five are primarily the victims of this disease. This study has been conducted to assess the prevalence of shigellosis through selective plating, biochemical test and conventional PCR assays, where the samples were collected from suspected diarrheoal patients. Invasive plasmid antigen H (ipaH) and O-antigenic rfc gene were used to identify Shigella spp. and S. flexneri respectively. For validation of these identification, PCR product of ipaH gene of a sample (Shigella flexneri MZS 191) has been sequenced and submitted to NCBI database (GenBank accession no- MW774908.1). Further this strain has been used as positive control. Out of 204, around 14.2% (n = 29)(P> 0.01) pediatric diarrheoal cases were screened as shigellosis. Another interesting finding was that most of shigellosis affected children were 7 months to 1 year (P> 0.01).The significance of this study lies in the analyses of the occurrenceand the molecular identification of Shigellaspp. and S. flexneri that can be utilized in improving the accurate identification and the treatment of the most severe and alarming shigellosis.

The role of metabolites, nutrients, and toxins (MNTs) in sera at the end of pregnancy and of their association with offspring respiratory and allergic disorders is underexplored. Untargeted approaches detecting a variety of compounds, known and unknown, are limited. In this cohort study, we first aimed at discovering associations of MNTs in grandmaternal (F0) serum with asthma, immunoglobulin E, skin prick tests, exhaled nitric oxide, and lung function parameters in their parental (F1) offspring. Second, for replication, we tested the identified associations of MNTs with disorders in their grandchildren (F2-offspring) based on F2 cord serum. The statistical analyses were sex-stratified. Using liquid chromatography/high-resolution mass spectrometry in F0, we detected signals for 2286 negative-ion lipids, 59 positive-ion lipids, and 6331 polar MNTs. Nine MNTs (one unknown MNT) discovered in F0-F1 and replicated in F2 showed higher risks of respiratory/allergic outcomes. Twelve MNTs (four unknowns) constituted a potential protection in F1 and F2. We recognized MNTs not yet considered candidates for respiratory/allergic outcomes: a phthalate plasticizer, an antihistamine, a bile acid metabolite, tryptophan metabolites, a hemiterpenoid glycoside, triacylglycerols, hypoxanthine, and polyphenol syringic acid. The findings suggest that MNTs are aspirants for clinical trials to prevent adverse respiratory/allergic outcomes.

This paper explores the impacts of informal economic activities and institutional capacity, particularly, corruption control on the environmental quality degradation of emerging economies under the prevailing socio-economic conditions and energy use patterns of the countries. The study utilizes key environmental degradation indicators: Carbon dioxide (CO2) emissions, ecological footprints (EFs), and Nitrous Oxide (NO) emissions, and a panel dataset of 15 emerging countries for the period 2002–2019 to undertake an empirical investigation. The pooled mean group (PMG)-ARDL estimator, Fully Modified OLS (FMOLS), Dynamic OLS (DOLS) and Augmented Mean Group (AMG) methods have been applied as empirical investigation techniques. The empirical findings reveal that in the long-run informal economic activities positively affect the environmental quality with fewer recorded emissions of CO2 and EFs while these activities affect negatively to NO emissions. This study has also found that corruption control improves environmental quality by reducing EFs and NO emissions but works to the opposite by increasing recorded CO2 emissions. An increase in economic growth and renewable energy consumption improves environmental quality in emerging countries, while consumption of non-renewable energy degrades the environmental quality. The robust empirical findings advocate policy initiatives for intense monitoring of informal activities and implementation of indirect tax policy to regulate informal activities and the pollution they cause. Careful measures of corruption control and initiatives to bring the informal economic activities into a formal framework are suggested to reduce CO2 and NO emissions. An increase in economic growth with more focus on renewables and phasing out non-renewables can ensure green growth in emerging countries.

Bangladesh has a unique coastal system with both proximity of climatic vulnerability and opportunity, having rich coastal resources. The upkeep of people's livelihoods in the coastal zone largely depends on the degree to which key stakeholders at all levels of decision-making can participate in climate adaptation planning and implementation processes. These facts are well recognized in Bangladesh's Integrated Coastal Zone Management Plan (ICZM), National Adaptation Program of Action (NAPA), and the Bangladesh Climate Change Strategy and Action Plan (BCCSAP), which emphasize the need for integrated multi-level decision-making at all stages of the adaptive management cycle. The aim of this article is to assess the value of coastal community engagement in Bhola and Satkhira districts of Bangladesh and highlight priority programs that may increase adaptive capacity in the face of climate change. To this end, interviews were conducted involving local farmers, fishers, women householders, businessmen, and other local leaders, thus yielding a total 240 participants who informed this empirical research. Case studies of villages of these districts highlight helpful examples of adaptation initiatives that may increase people's capacity to respond to the adverse effects of climate change, both autonomously as villagers, and as part of a coordinated program to reduce vulnerability. Issues flagged for urgent attention include water management, socioeconomic conditions, and migration away from coastal districts. The findings point to both potential interventions and a need to better prioritize adaptation options and strategies that are suitable for local contexts. In some cases, these options reflect existing Indigenous and local knowledge (ILK) and adaptation practices which may be both supported and leveraged through the coordinated implementation of different aspects of government policies.

Introduction: There is an outbreak of hepatitis E virus (HEV) infection in Chittagong, Bangladesh in the year 2018. Due to unavailability of data of HEV infections in this region, objectives of the present study are to find the viral load and genotype the HEV infections. Methods: It was an observational study done in a tertiary care hospital during one year. A total of 125 Ig-M HEV positive cases were recruited tested by ELISA. After collection blood samples those were sent to Sliea Gen L.L.C, Texas, USA for detection of viral load and genotype maintaining proper procedure. Ethical clearance was taken from the hospital authority and informed written consent was taken from all patients and funding was provided by Sliea Gen L.L.C. USA. Results: Among the total 125 study patients, male was 90(72') and female was 35(29') where 7(5.6') were pregnant. Among them most 45(36.0') were at age group 30-40 years. Mean ± SD of age was 33.78 ± 14.29 years. All (100') cases were Ig-M Anti HEV positive and 9(7.2') cases were also positive for HBsAg, 1(0.8') cases were Anti HCV positive and none was Anti HAV positive. Regarding viral load Log 4-6 were found in 55(44.0') cases and >Log 6 were found in 23(18.4') cases and again 30(24.0') cases had 1000-10,000 IU/ml, 25(20.0') cases had 1,0,000-1,00,000 IU/ml and 23(18.4') cases had 1.00,000- 10,00,000 IU/ml viral load. Genotype 1F was found in 68(54.4') cases as the only genotype and no other genotype was found in the sample. Conclusion: So, in this region Chittagong, Bangladesh genotype 1F is the main genotype found and also they showed variable viral load.

Background. Multidrug-resistant (MDR) clones of Klebsiella pneumoniae (Kpn) have been increasingly documented in community-acquired and nosocomial infections all around the globe. Extended-spectrum β-lactamases (ESBLs) are a rapidly evolving group of β-lactamase enzymes derived from SHV genes by mutations. This research work aimed to investigate and analyze the widespread prevalence of Kpn antibiotic resistance in different areas of the southern part of Bangladesh. Methods. This particular study was executed and implemented by using 501 clinical samples or isolates from two different hospitals in Chattogram. The disk diffusion method was used to detect Kpn’s sensitivity to 16 antibiotics in a drug susceptibility test. By using the PCR technique, the widespread prevalence of antibiotic-resistant gene blaSHV-11 was studied. Sequencing along with phylogenetic analysis was utilized to verify isolates with the blaSHV-11 gene. Results. Almost all of the Kpn isolates were spotted to be antibiotic-resistant. These Kpn isolates were resistant to β-lactams, aminoglycosides, and quinolones at high levels. The spatial analysis displayed that infections involving Kpn were more common in the urban areas (70%) than in the rural areas (30%). Neonates had substantially higher levels (p

This study aims to develop statistical and machine learning methodologies for forecasting yearly electricity consumption in Saudi Arabia. The novelty of this study include (i) determining significant features that have a considerable influence on electricity consumption, (ii) utilizing a Bayesian optimization algorithm (BOA) to enhance the model’s hyperparameters, (iii) hybridizing the BOA with the machine learning algorithms, viz., support vector regression (SVR) and nonlinear autoregressive networks with exogenous inputs (NARX), for modeling individually the long-term electricity consumption, (iv) comparing their performances with the widely used classical time-series algorithm autoregressive integrated moving average with exogenous inputs (ARIMAX) with regard to the accuracy, computational efficiency, and generalizability, and (v) forecasting future yearly electricity consumption and validation. The population, gross domestic product (GDP), imports, and refined oil products were observed to be significant with the total yearly electricity consumption in Saudi Arabia. The coefficient of determination R2 values for all the developed models are >0.98, indicating an excellent fit of the models with historical data. However, among all three proposed models, the BOA–NARX has the best performance, improving the forecasting accuracy (root mean square error (RMSE)) by 71% and 80% compared to the ARIMAX and BOA–SVR models, respectively. The overall results of this study confirm the higher accuracy and reliability of the proposed methods in total electricity consumption forecasting that can be used by power system operators to more accurately forecast electricity consumption to ensure the sustainability of electric energy. This study can also provide significant guidance and helpful insights for researchers to enhance their understanding of crucial research, emerging trends, and new developments in future energy studies.

Electricity consumption and government policy are two vital elements for economic growth. Thus, this study explores the roles of electricity use and government policy in the economic growth of the selected four South Asian countries over the period from 1980 to 2014. The study includes the government policy variable in the extended Cobb–Douglas production function of the electricity driven growth model, which was absent in earlier studies. The pooled mean group-based panel autoregressive distributed lag (P-ARDL) method is used for empirical investigation, while fully modified ordinary least squares (FMOLS) and dynamic ordinary least square (DOLS) methods are used for checking the sensitivity of the P-ARDL estimates. Our results reveal that the effects of electricity, government spending, financial development and capital formation have significant positive effects on the economic growth of South Asia. However, exports and imports are found to have detrimental effects. Causality test reveals a unidirectional causality from electricity consumption to economic growth that supports the growth hypothesis. Following the findings, important policy recommendations are made to foster the economic growth in the South Asian countries.

ObjectiveThis study was performed to investigate the prevalence of multidrug resistance and molecular characterization of Klebsiella pneumoniae (KPN) from clinical isolates in the southern region of Bangladesh. Additional analysis of the prevalence of blaNDM-1, blaSHV-11, uge genes of KPN was also carried out among these clinical isolates.MethodThe study was carried out using 1000 clinical isolates collected from two different hospitals of Chattogram. A drug susceptibility test was performed by the disk diffusion method to detect KPN's response to 16 antibiotics. The presence of antibiotic-resistant and (or) virulent genes blaNDM-1, blaSHV-11, uge were investigated using the PCR technique. Isolates having blaNDM-1, blaSHV-11, uge gene were further validated by sequencing followed by phylogenetic analysis. Phylogenetic relationships among these isolates were determined by Clustal omega and MEGA7.ResultA total of 79%, 77%, 74.9%, 71%, 66% and 65% isolates exhibited resistance against cefuroxime, cefixime, cefotaxime, ceftazidime, cefepime and ceftriaxone respectively. The frequency of resistance to other antibiotics varied from 26.5% to 61.8%. PCR analysis showed that 64% of strains harbored blaNDM-1 gene, and 38% strains harbored blaSHV-11 gene. Moreover, 47% of samples were carrying uge gene, and 19% of samples carried blaNDM-1, blaSHV-11, uge genes together.ConclusionIn this study, we've analysed the pattern of expression as well as prevalence of blaNDM-1, blaSHV-11, and uge genes in Klebsiella isolates. Upon molecular and statistical analysis, we found a high prevalence of multi-drug resistance KPN strains in the isolates. The Klebsiella isolates were confirmed to harbor multiple ESBL genes and 64% of the isolates were found to be producing NDM-1. As multidrug resistance is an alarming issue, continuous surveillance and routine clinical detection of resistant bacteria and plasmids are necessary to prevent catastrophic public health incidents.

This article focuses on developing both statistical and machine learning approaches for forecasting hourly electricity demand in Ontario. The novelties of this study include (i) identifying essential factors that have a significant effect on electricity consumption, (ii) the execution of a Bayesian optimization algorithm (BOA) to optimize the model hyperparameters, (iii) hybridizing the BOA with the seasonal autoregressive integrated moving average with exogenous inputs (SARIMAX) and nonlinear autoregressive networks with exogenous input (NARX) for modeling separately short-term electricity demand for the first time, (iv) comparing the model’s performance using several performance indicators and computing efficiency, and (v) validation of the model performance using unseen data. Six features (viz., snow depth, cloud cover, precipitation, temperature, irradiance toa, and irradiance surface) were found to be significant. The Mean Absolute Percentage Error (MAPE) of five consecutive weekdays for all seasons in the hybrid BOA-NARX is obtained at about 3%, while a remarkable variation is observed in the hybrid BOA-SARIMAX. BOA-NARX provides an overall steady Relative Error (RE) in all seasons (1~6.56%), while BOA-SARIMAX provides unstable results (Fall: 0.73~2.98%; Summer: 8.41~14.44%). The coefficient of determination (R2) values for both models are >0.96. Overall results indicate that both models perform well; however, the hybrid BOA-NARX reveals a stable ability to handle the day-ahead electricity load forecasts.

Abstract Background Antioxidants play an important role in protecting cellular damage by reactive oxygen species. The aim of the present study is to assess the phytochemical nature, antioxidant and antibacterial activities of petroleum ether, chloroform, methanol, and aqueous extracts of Crotalaria pallida stem. Methods The preliminary screening of the various extracts was carried out using standard methods. Total phenolic content (TPC) was determined by the modified Folin-Ciocalteu method and antioxidant activities were assayed using 2,2-diphenyl-1-picrylhydrazyl (DPPH) radical scavenging activity, reducing power assay, total antioxidant capacity (TAC) and reduction of ferric ions. Antibacterial activity of different extracts were assayed against Gram-positive and Gram-negative bacterial strains by observing the zone of inhibition using disc diffusion method, where Staphylococcus aureus, Bacillus cereus, Escherichia coli and Pseudomonas aeruginosa were used as bacterial strains. Results Petroleum ether, chloroform, methanol and aqueous extracts of stem exhibited remarkable antioxidant activity in terms of all the assays tested. Petroleum ether extract (PEE) showed DPPH radical scavenging activity with IC50 value of 126.96 µg/ml. In antibacterial assay, the PEE and chloroform extract (CE) showed mild to moderate antibacterial activity against all the bacterial strains except B. cereus while methanol extract (ME) showed no inhibitory effect against any of the tested bacteria. Conclusion PEE, CE and ME of C. pallida stem were found to be the most effective free radical quencher and a potent source of natural antioxidants as well as antibacterial activity. Thus justifying their traditional use in green therapeutics.

Food security is considered as the most important global challenge. Therefore, identifying long-term drivers of food security and their connections is essential to steer policymakers determining policies for future food security and sustainable development. Given the complexity and uncertainty of multidimensional food security, quantifying the extent of uncertainty is vital. In this study, we investigated the uncertainty of a coupled hydrologic food security model to examine the impacts of climatic warming on food production (rice, cereal and wheat) in a mild temperature study site in China. In addition to varying temperature, our study also investigated the impacts of three CO2 emission scenarios—the Representative Concentration Pathway, RCP 4.5, RCP 6.0, RCP 8.5—on food production. Our ultimate objective was to quantify the uncertainty in a coupled hydrologic food security model and report the sources and timing of uncertainty under a warming climate using a coupled hydrologic food security model tested against observed food production years. Our study shows an overall increasing trend in rice, cereal and wheat production under a warming climate. Crop yield data from China are used to demonstrate the extent of uncertainty in food security modeling. An innovative and systemic approach is developed to quantify the uncertainty in food security modeling. Crop yield variability with the rising trend of temperature also demonstrates a new insight in quantifying uncertainty in food security modeling.

Present study on fishing gears and methods in the Chalan Beel was conducted during the period of July 2011 to June 2014. The Chalan Beel is the large network of fluvial waters body that harbors rich ichthyofaunal diversity. Most of the fishing methods of the Chalan Beel are primitive, based on indigenous traditional knowledge and well suited to turbulent nature of the streams. In this study thirty fishing methods and gears have been documented and classified into five categories- fishing nets, traps, wounding gears, hooks and lines, and others. Many of these were harmful to fishes as well as aquatic biodiversity. Effective measurements are required to make proper use of the Chalan Beel.

The present study on fishing technique using sutijal (purse net) in the Chalan Beel was conducted for a period of 3 years from July 2011 to June 2014. Net description, operation details and catch composition were studied through field survey in different parts of studied wetland. Three different categories of sutijal were recorded. Catch composition revealed that all types of aquatic organisms are being caught by this net. Benefit-cost ratio of studied fishing net was also calculated. Frequent fishing by this net, especially in streams of remote areas of the Chalan Beel resulting in decline of fish species and abundance. Appropriate management steps are recommended to get rid of this destructive fishing gear.

Abstract The study was conducted to know the cyclic changes in gonadal maturation and to investigate the developmental stages of oocytes and testicular germ cells of an air-breathing fish, Channa striata. Fish were sampled monthly from lentic and lotic environments of three geographical locations of Bangladesh from December to November and the histological analysis of their gonad was done to evaluate the objectives. The highest mean GSI was 5.95 ± 0.20 for female in July and 0.14 ± 0.01 for male also in July showing that the gonadal development reached its peak during this month. The highest mean oocyte diameter was 1257.50 ± 24.17 μm observed in July implying that the oocyte reached maturity in this month. Histological study of ovary revealed the evidence of early yolk granule stage and late yolk granule stage from April to July. In case of male four stages of spermatogenesis were distinguished and spermatozoa were highly abundant in June and July. So the monthly pooled values of GSI and the analysis of gonadal histology indicated that the peak breeding season of C. striata occurred in July in the lentic and lotic environments. Samples collected from lentic and lotic habitats are suggestive of no difference in the development of the gonad. The results of the present study will be useful for selective breeding programme, conservation and sustainable fishery management of C. striata in its natural habitat.

Background: Dysfunctional uterine bleeding (DUB) is irregular uterine bleeding that occurs in the absence of recognizable pelvic pathology, general medical disease, or pregnancy. It reflects a disruption in the normal cyclic pattern of ovulatory hormonal stimulation to the endometrial lining. About 1–2% of women with improperly managed anovulatory bleeding eventually may develop endometrial cancer but determinants behind the disease are largely unknown. Objective: The present study aimed to find out the determinants of dysfunctional uterine bleeding. Materials and Methods: In this cross-sectional study 50 patients of dysfunctional uterine bleeding (DUB) were recruited from different tertiary hospitals in Dhaka city. Clinical parameters have been recorded using a predesigned questionnaire and analyzed using SPSS for Windows version 16.0 and Microsoft Office Excel. Results: In the studied patients, about 38% were suffering from type 2 diabetes mellitus, 12% from obesity and 18% from hypertension. Almost all the patients (96%) were suffering from anemia. Histological findings have shown that endometrium of 63% patients were in proliferative phase, about 16% were in secretory phase and 11% patients were with cystic hyperplasia. Ultrasonographic results have shown that about 72% of the patients had bulky uterus. Ninety two percent patients carried more than two pregnancies, and 40% patients carried >5 pregnancies. Conclusion: Bulky uterus and multiple pregnancies may be associated with dysfunctional uterine bleeding in Bangladeshi women.

In person who is unable to produce HBsAg, anti-HBc antibody is a helpful marker of hepatitis B virus (HBV) infection. In the present study, we have tried to find out the incidence of anti-HBc (IgG and IgM) among blood donors HBsAg negative. People came for donating blood voluntarily or for their relatives (n = 1000) was selected on inclusion and exclusion criteria. Purposefully selected and collated samples were first tested by HBsAg ELISA of third generation reagent. HBsAg negative sample was tested with anti-HBc ELISA. Positive found in the first test was retested. Out of 1,000 samples on duplicate test, 117 positives were detected. The incidence of anti-HBc antibody among apparently healthy blood donors was found 11.7%.

This paper considers a fluid dynamic traffic flow model appended with a closure linear velocity-density relationship which provides a first order hyperbolic partial differential equation (PDE) and is treated as an initial boundary value problem (IBVP). We consider the boundary value in such a way that one side of highway treat like there is a traffic controller at that point. We present the analytic solution of the traffic flow model as a Cauchy problem. A numerical simulation of the traffic flow model (IBVP) is performed based on a finite difference scheme for the model with two sided boundary conditions and a suitable numerical scheme for this is the Lax-Friedrichs scheme. Solution figure from our scheme indicates a desired result that amplitude and frequency of cars density and velocity reduces as time grows. Also at traffic controller point, velocity and density values change as desired manner. In further, we also want to introduce anisotropic behavior of cars(to get more realistic picture) which has not been considered here. Doi: 10.12777/ijse.5.1.25-30 [How to cite this article: Sultana, N., Parvin, M. , Sarker, R., Andallah, L.S. (2013). Simulation of Traffic Flow Model with Traffic Controller Boundary. International Journal of Science and Engineering, 5(1),25-30. Doi: 10.12777/ijse.5.1.25-30]

The research attempts to know the present extent of salinity and how much agricultural land has reduced gradually during last one decade in the study area. The collected soil samples were analyzed with different laboratory techniques. Plot to plot survey was conducted by using satellite image and ArcGIS10v was used to detect the agricultural land use change and soil salinity zoning map. Qualitative and quantitative data were collected by applying different methods like Focus Group Discussion (FGD), checklist, in-depth interview and Participatory Rural Appraisal (PRA) and finally these collected data were analyzed and presented. The present studies found that salinity exist in every portion of the study area which has fallen into moderate to highly saline zone categories. The research also found that the agricultural land use in the study area has been reducing gradually due to salinity. The study area has an area of 8018.666 hectare of which 15.1% is agricultural land and it was 24.52% before 10 years. Overall, the agricultural land is decreasing at the rate of 0.942% per year.

A study was conducted to determine the quality of water for irrigation from the surface water of water bodies inMuktagacha Upazila under Mymensingh District. Water samples from 19 different water bodies (river, pond, khal, canal, beel etc.) located all over the upazila were collected and analyzed for chemical composition and properties to classify them according to their suitability for irrigation. All water samples were found excellent to good and normal for irrigation in respect of salinity or Electrical Conductivity (EC) and Sodium Adsorption Ratio (SAR) respectively, and practically neutral to slightly alkaline in respect of pH. Considering boron concentration most of the samples was found to be excellent for all types of crops of the study area. Conventional Classification of water by Piper diagram have been done to show clustering of data points to indicate samples that have similar composition. Geographical Information System (GIS) have been used in mapping, which greatly aided in the understanding of and decision making in water resources management. Any initiativefor surface water development for planned irrigation practices is highly encouraged.