Alzheimer’s disease (AD) is one of the most prevailing neurodegenerative diseases, characterized by memory dysfunction and the presence of hyperphosphorylated tau and amyloid β (Aβ) aggregate in multiple brain regions, including the hippocampus and cortex. The exact etiology of AD has not yet been confirmed. However, epidemiological reports suggest that populations who were exposed to environmental hazards are more likely to develop AD than those who were not. Arsenic (As) is a naturally occurring environmental risk factor abundant in the Earth’s crust and human exposure to As predominantly occurs through drinking water. Convincing evidence suggests that As causes neurotoxicity and impairs memory and cognition although the hypothesis and molecular mechanism of As-associated pathobiology in AD are not clear yet. However, exposure to As and its metabolites leads to various pathogenic events such as oxidative stress, inflammation, mitochondrial dysfunctions, ER stress, apoptosis, impaired protein homeostasis, and abnormal calcium signaling. Evidence has indicated that As exposure induces alterations that coincide with most of the biochemical, pathological, and clinical developments of AD. Here, we overview existing literature to gain insights into the plausible mechanisms that underlie As-induced neurotoxicity and the subsequent neurological deficits in AD. Prospective strategies for the prevention and management of arsenic exposure and neurotoxicity have also been discussed.

Alzheimer’s disease (AD) is a progressive neurodegenerative disorder characterized by a decline in cognitive function with neuronal damage. Although the precise pathobiology of AD is still elusive, accumulating evidences suggest that mitochondrial dysfunction is one of the underlying causes of AD. Mutations of mitochondrial or nuclear DNA that encode mitochondrial constituents may cause mitochondrial dysfunctions. In particular, dysfunction of electron transport chain complexes along with interactions of mitochondrial pathological proteins are associated with mitochondrial dysfunctions in AD. Mitochondrial dysfunction causes an imbalance in reactive oxygen species, leading to oxidative stress (OS) and vice-versa. Neuroinflammation is another potential contributory factor to induce mitochondrial dysfunction. Phytochemicals or other natural compounds have the potential to scavenge oxygen free radicals and enhance cellular antioxidant defense system, and thereby protect against OS-mediated cellular damage. Phytochemicals can also modulate other cellular processes, including autophagy and mitochondrial biogenesis. Pharmacological intervention through neuroprotective phytochemicals can, therefore, be a potential strategy to combat mitochondrial dysfunctions as well as AD. This review focuses on the role of phytochemicals to mitigate mitochondrial dysfunction in the therapy of AD pathogenesis.

Beyond their significant contribution to the dietary and industrial supplies, marine algae are considered to be a potential source of some unique metabolites with diverse health benefits. The pharmacological properties, such as antioxidant, anti-inflammatory, cholesterol homeostasis, protein clearance and anti-amyloidogenic potentials of algal metabolites endorse their protective efficacy against oxidative stress, neuroinflammation, mitochondrial dysfunction, and impaired proteostasis which are known to be implicated in the pathophysiology of neurodegenerative disorders and the associated complications after cerebral ischemia and brain injuries. As was evident in various preclinical studies, algal compounds conferred neuroprotection against a wide range of neurotoxic stressors, such as oxygen/glucose deprivation, hydrogen peroxide, glutamate, amyloid β, or 1-methyl-4-phenylpyridinium (MPP+) and, therefore, hold therapeutic promise for brain disorders. While a significant number of algal compounds with promising neuroprotective capacity have been identified over the last decades, a few of them have had access to clinical trials. However, the recent approval of an algal oligosaccharide, sodium oligomannate, for the treatment of Alzheimer's disease enlightened the future of marine algae-based drug discovery. In this review, we briefly outline the pathophysiology of neurodegenerative diseases and brain injuries for identifying the targets of pharmacological intervention, and then review the literature on the neuroprotective potentials of algal compounds along with the underlying pharmacological mechanism, and present an appraisal on the recent therapeutic advances. We also propose a rational strategy to facilitate algal metabolites-based drug development.

Autophagy refers to the degradation of cytoplasmic constituents by a lysosomal-mediated pathway, which plays a critical role in maintaining cellular homeostasis. Importantly, dysregulation of autophagy has been implicated in multiple neurodegenerative disorders. Previous studies reported that autophagy affects the processing of amyloid precursor protein (APP), thus stimulating β‐amyloid (Aβ) production in Alzheimer’s disease (AD) eventually. Although the mechanism of autophagy modulation on APP processing and its pathogenesis has not yet been fully elucidated at the molecular level, but modulation of autophagy has received considerable attention as a promising approach for the treatment of AD. In the early stage of AD, Aβ may prompt autophagy to facilitate its removal via mTOR‐independent as well as-dependent pathways. However, a recent study proposed that autophagy processes are not properly regulated as AD continues to progress, and consequently, the production of Aβ tends to accumulate rapidly. Meanwhile, a number of autophagy-related genes (Atg) as well as APP genes are also thought to influence the development of AD, which may serve as a bi‐directional link to autophagy and AD pathology. In this review, we summarized current observations related to autophagy regulation and APP processing, focusing on their dynamic modifications associated with the progression of AD. Recent findings together highlight the essential role of autophagy in the removal and clearance of APP and Aβ deposition in the pathological condition of AD.

CCNs are specific type of matricellular proteins, which are essential signaling molecules, and play multiple roles in multicellular eukaryotes. This family of proteins consists of six separate members in mammals. The architecture of CCN proteins is multimodular and comprises four distinct motifs. CCN proteins achieve their specific physiological functions by binding to integrin receptors. The CCN family has been implicated in both cure and disease with impacts on biological interactions, such as cell adhesion, chemotaxis and migration, mitogenesis, cell survival, angiogenesis, differentiation, tumorigenesis, immune functions, chondrogenesis, and wound healing. Breast cancer is the most commonly diagnosed cancer worldwide and the leading cause of cancer mortality among women triggered by atypical expression of CCNs. A favorable or unfavorable association between various CCNs has been reported in patients with breast carcinomas. Aberrant expression of CCN1 intensifies the proliferation of epithelial cells that line the lobes and ducts of the breast. Evidence also shows that the expression of CCN2 can ameliorate tumor growth and metastasis. However, CCN3 (NOV), CCN5 (WISP-2), and CCN6 (WISP-3) are consistent with neoplastic development and metastasis repression. Particular CCN members can develop tumors and cancer progression, whereas others can competitively counter the processes. Several studies have been conducted on CCN proteins and cancer in recent years. In our study, we intend to provide an overview of those research works while keeping breast carcinoma on focus. We believe that the importance of the CCN protein family in breast cancer should be reconsidered.

COVID-19 infection is extremely dangerous for persons with comorbidities such as kidney disease and diabetes. Although many people of all ages and socioeconomic backgrounds have suffered due to this pandemic, those with underlying medical conditions like kidney disease and diabetes are more vulnerable to becoming infected with COVID-19 related to weak immunity. However, the role of vaccination in the co-infection of COVID-19 with diabetics is not available in the literature. Therefore, we examine the unique challenges presented by the co-infection of COVID-19 in individuals with diabetes, focusing on its disease transmission dynamics. A mathematical modelling technique is to be employed in this work to analyse the dynamics of COVID-19 outbreaks with seven compartments, including vaccination with comorbidities such as diabetes. We also investigated analytically by displaying the solutions' existence, boundedness, positivity and sensitivity. After calculating the basic reproduction numbers, the stability analysis of model equilibrium points is also covered. If the reproduction numbers are less than unity, the disease-free equilibrium points of the model appear to be both locally and globally stable. The findings of this study are that as the vaccination rate rises, the incidence of COVID-19 and its co-infections with diabetes decreases. Effective disease treatment strategies may be based partly on the possible impact of vaccination on the co-infection of COVID-19 related to diabetic disease insights.

The study aims to provide technical information on the development and application of hazard analysis and critical control points (HACCP) in one of Dhaka's popular baking (cake) industries. A generic HACCP plan in accordance with legal requirements was created after a detailed analysis of data collected from the company. Every step of the production was examined for biological, chemical, and physical hazards. The prerequisite program was designed to address some hazards prior to production, thereby simplifying the HACCP plan. The critical control points were determined by answering the questions in the decision trees. Finally, the HACCP control chart was created to include critical limits, monitoring, and corrective action as components of several HACCP principles. One critical control point (CCP) and two operational pre-requisite programs (oPRPs) were identified throughout the manufacturing process.

This study aims to determine the present and future scopes of the digital economy in Bangladesh to build a developed and prosperous country by 2041. Simultaneously, it analyses the components of the Digital Economy from numerous perspectives from contributing to Bangladeshi economy with an adaptation of the 4th Industrial Revolution and emerging technologies. In the methodology section, qualitative approach is conducted to determine the research objectives where secondary data is used. Around 100 papers are collected and 51 articles are used for conducting this study. The findings of the study are to present the current state of the digital economy which is developing trends that contribute to national GDP for the adaptation of the 4IR for the transformation of smart Bangladesh. From the conceptual implication, companies and individuals are aware of the digital economy, which would lessen digital divide and create a strong link between technology and the economy. Furthermore, establishing customer confidence and trust would be a big issue for Bangladesh's digital platform economy in the future days. From a practical standpoint, IT industries and commercial organizations would have to deal with emerging 4IR and its technologies. The job market would also be expanded in a variety of areas, which would ultimately benefit the national economy. According to the study's conclusions, the digital economy is predicted to expand its commercial and corporate opportunities. Future research might be extended based on qualitative approach towards a digital Bangladesh and create a better developing economy.

Crossbreeding in dairy cattle with exotic breeds continues to be an appealing practice to the dairy farmers of Bangladesh. However, there is limited knowledge regarding the impact of crossbreeding on both the physical attributes and milk quality traits of crossbred cattle in Bangladesh. Therefore, the primary objective of this study was to evaluate the impact of crossbreeding Bangladeshi local cattle with the exotic Holstein breed on their body characteristics and milk quality. To achieve the goal, data pertaining to body traits and milk samples were gathered from a total of 981 cows from 19 dairy farms located in the northwestern region of Bangladesh. A trained evaluator measured body condition score (BCS), udder score, locomotion score, and body conformation traits. Milk yield information was acquired from official records, while milk composition details were determined through milk analysis. The average measurements for body traits were as follows: wither height (WH) at 138 cm, body length (BL) at 155 cm, and heart girth (HG) at 203 cm. Notably, crossbred cows (Holstein x Local cattle) exhibited greater values for WH, BL, HG, BCS, and udder score than their Bangladeshi local counterparts. Furthermore, the average daily milk yield of sampled cows was recorded at 8.7 kg, with fat and protein contents of 3.78% and 3.67%, respectively. It is worth noting that crossbred cows produced a higher volume of milk compared to Bangladeshi local cattle. However, milk from crossbred cows displayed lower fat and protein content, although their somatic cell score (SCS) remained similar. Additionally, milk from crossbred cows exhibited a longer coagulation time when compared to that of Bangladeshi local cattle. A more comprehensive assessment of the crossbreeding scheme, particularly in comparison to Holstein, would necessitate further research, including an examination of its impact on cheese yield traits, health, fertility, and longevity.

The great lockdown of the current COVID-19 pandemic has significant consequences on the global Higher Education Studies (HES).To find the relevance of eLearning in the HES, our study calculates the economic costs of higher education during Covid-19 in Bangladesh, which includes both stu-dents’ cost and institutional cost. The study used a purposive random sample survey conducted on 105 students enrolled in higher education in different categories of institutions to identify the stu-dents’ cost during this pandemic. The institutional cost of higher education is analyzed by breaking down the budget allocated in the education sector in Bangladesh and reviewing the literature. The result indicates that the HES of Bangladesh experiences a huge economic cost due to this pandemic and the study found eLearning can reduce the economic impact of HES. In the post-COVID-19 world, higher education will never be the similar because many institutions that already had experi-ence a huge advantage from online education. The findings of the study might be helpful for the policymakers to frame effective education policies during any bizarre situation that creates huge cost in higher education sector.

The study of angiosperm flora, endemic plants in the literature, and investigations of ‘POWO Build a checklist’ were used to compile an updated list of Bangladesh's endemic plants. According to the study, at least 49 (1.24%) of Bangladesh's 3,956 plant species are endemic to the country including 5 varieties, belonging to 41 genera in 26 families. Magnoliopsida account for thirty of them, Liliopsida for the remaining sixteen, and Pteridohpytes for the final three. The four families Zingiberaceae (9 taxa), Araceae (6 taxa), Rubiaceae (4 taxa), and Euphorbiaceae (3 taxa), include the most endemic taxa. The five most numerous endemic taxa belong to the Curcuma genus. The endemic flora, which is mostly found in the districts of Chattogram, Moulvibazar, and Rangamati, consists of 13 tree species, 4 shrubs, 5 climbers, and 27 herbaceous plant species.

Human civilizations are under enormous threats due to the outbreak of novel coronavirus (COVID-19) originated from Wuhan, China. The asymptomatic carriers are the potential spreads of this novel virus. Since, guaranteed antiviral treatments have not been available in the market so far, it is really challenging to fight against this contagious disease. To save the living mankind, it is urgent to know more about how the virus transmits itself from one to another quite rapidly and how we can predict future infections. Scientists and Researchers are working hard in investigating to understand its high infection rate and transmission process. One possible way to know is to use our existing COVID-19 infection data and prepare a useful model to predict the future trend. Mathematical modelling is very useful to understand the basic principle of COVID-19 transmission and provide necessary guidelines for future prediction. Here, we have reviewed 9 distinct commonly used models based on Mathematical implementations for COVID-19 transmission and dig into the deep head to head comparison of each model. Finally, we have discussed interesting key behaviour of each model, relevant upcoming important issues, challenges and future directions.

Bioconvective flows have attracted attention in recent years due to actual and potential applications. In this paper, we consider a steady and laminar convective MHD flow of a nanofluid with heat, mass and microorganism transfer with a heat source/sink present. In addition, we assume there exists a first order chemical reaction. The governing partial differential equations (PDEs) are reduced to ordinary differential equations (ODEs) using the scaling group transformation and the associated boundary value problem is then solved. The influences of selected governing parameters on the dimensionless velocity, temperature, nanoparticle concentration, density of motile microorganisms, skin friction, heat transfer, mass transfer, and motile microorganism density rates are computed and discussed

Mangrove vegetation plays a vital role in habitat and nursing ground for different organisms and prevents coastal erosion caused by wave and tide action. In recent years the mangrove vegetation in Chattogram coast, Bangladesh, has been interrupted by other infrastructural development, which has a destructing effect on the surrounding environment. Land surface temperature analysis of an area helps learn about different environmental conditions, weather, and climate. It is also essential to monitor the rising temperature and global warming, the biggest threat to humanity. NDBI and NDVI are the efficient process for monitoring vegetation and build up areas of a geographical location. This study focused on those analyses to understand the importance of mangrove vegetation in the Salimpur area and surrounding coastal areas of Chattogram by studying the relationship between NDVI and NDBI, NDVI and LST, NDBI, and LST. The outcome indicates that a higher vegetation index results in lower land surface temperature during different periods, negatively correlated. This study also found a strong positive correlation between buildup index (NDBI) and land surface temperature (LST), which means Land Surface temperature was found higher in Buildup areas. The vegetation areas are greatly affected by the buildup areas. The correlation between buildup areas and vegetation areas was strongly negative, which means an increase of NDBI decreases NDVI, and a decrease of NDBI increases NDVI.

This experiment was carried out to determine the overall prevalence of pigeon diseases and especially emphasized on prevalence of parasitic diseases in study areas. During this study 45 farms were selected which have >20 pair of pigeon for commercial and >10 pair pigeon for traditional farm in the three study area namely Rajshahi, Natore and Pabna district of Bangladesh. The data were collected from different farm within the study area through a questionnaire and interview schedule with the farm owners. During one year of study period a total Out of 3677 pigeon, positive case in cage of external parasites were 722 and internal parasite positives 114 from 263 fecal sample. The overall prevalence of gastrointestinal and external parasites in pigeon at northern Bangladesh is obtained. The infestation of lice Columbaecula columbae and fly Pseudolynchia canariensis were observed 18.08% and 1.55% respectively. The present study found two species of ectoparasites lice and fly. Diversity of ectoparasite in birds infestation may be depend on many factors, which may include home range, behavior, size and roosting habit of the host. The overall prevalence of gastrointestinal parasites in pigeon are founded that 43.34% in research area. Specific incidence was 22.81% in Ascariasis, 18.63% in Capilariasis and 1.90% in Raillietina parasite in pigeon. Ascaridia colombae is one of the most common (22.81%) helminth species in pigeons in this study. The effect of breed of pigeon observed in present studies the highest in indigenous (63.47%) and lowest exotic (36%) prevalence of gastrointestinal parasite was observed. The specific percentages of Ascariasis, Capilariasis and Raillatina gastrointestinal parasites of pigeon were found 20% & 31.74%; 14% & 30.15% and 2% & 1.58% in exotic & indigenous breed, respectively. In the present study, there is a relation between the occurrence of gastrointestinal parasitic infections with the age of the pigeons which showed that high prevalence in adults (50%) and compare to young (22.22%). but it was statistically significant (P>0.05). In relation with farming system the gastrointestinal parasitic incidence of pigeon was observed in modern and tradition farming system, the highest incidence was 71.16% in traditional & lowest 31.14% in modern farming. When observed specifically in Ascariasis, Capillariasis & Raillietina were 16.39% & 37.41%; 13.11% & 31.25% and 1.63% & 2.5% in modern & traditional, respectively. The effect of regions on the prevalence of gastrointestinal parasites in pigeon was observed in Pabna (68.32%), Natore (57.84%) and Rajshahi (33.33%). The specific percentages of Ascariasis, Capilariasis and Raillatina gastrointestinal parasites of pigeon were 18.18%, 33.33% & 26.31%; 14.54%, 33.33% & 23.38% and 0.606%, 1.66% & 7.89% in Rajshahi, Pabna and Natore, respectively.

Artificial intelligence (AI) techniques have grown rapidly in recent years in the context of computing with smart mobile phones that typically allows the devices to function in an intelligent manner. Popular AI techniques include machine learning and deep learning methods, natural language processing, as well as knowledge representation and expert systems, can be used to make the target mobile applications intelligent and more effective. In this paper, we present a comprehensive view on mobile data science and intelligent apps in terms of concepts and AI-based modeling that can be used to design and develop intelligent mobile applications for the betterment of human life in their diverse day-to-day situation. This study also includes the concepts and insights of various AI-powered intelligent apps in several application domains, ranging from personalized recommendation to healthcare services, including COVID-19 pandemic management in recent days. Finally, we highlight several research issues and future directions relevant to our analysis in the area of mobile data science and intelligent apps. Overall, this paper aims to serve as a reference point and guidelines for the mobile application developers as well as the researchers in this domain, particularly from the technical point of view.

Apoptosis, also known as the programmed death of cells, is responsible for maintaining the homeostasis of tissues and this function is carried out by caspases. The process of apoptosis is carried out via two distinct pathways: the extrinsic pathway, which is governed by death receptors, and the intrinsic pathway, also known as the mitochondrial pathway. The BCL-2 protein family encoded by the BCL-2 gene, located at the 18q21.33 chromosomal location, is in charge of regulating the intrinsic pathway, which is responsible for inducing cell death via the permeabilization of the mitochondrial membrane and the release of apoptosis - inducing components. The BCL-2 homology (BH1, BH2, BH3, BH4) domains of this family proteins are crucial for their functioning and their common BH domains allow interactions between members of the same family and can also serve as indications of pro- or anti-apoptotic activity. A direct correlation may be shown between the overexpression of BCL-2 and the postponement of cell death. It has been determined that a change in the expression of BCL-2 is the root cause of a variety of malignancies, including lung, breast, melanoma, and chronic lymphocytic leukemia, Multiple Sclerosis, Diabetes. In this review, we discuss the therapeutic potential of regulating BCL-2 family connections and their relevance to health and disease.

Bangladesh is located in the alluvial floodplain of the Ganges–Brahmaputra–Meghna (GMB) river system and its numerous tributaries. In this country, the frequency, as well as severity, of riverbank erosion is high. To examine the impacts of riverbank erosion on rural food security, a baseline survey was conducted in Zajira, Bangladesh. The findings show that most people in the study area are affected by riverbank erosion. Moreover, agricultural production is gradually decreasing as a result of loss of farmland due to the catastrophe and its impacts. In some cases, people lose their entire homestead and are left with few income opportunities and low purchasing power. Consequently, they face the constant threat of a food crisis. The affected people follow some coping mechanisms to face these stressful situations, such as relying on less expensive or less preferred food items. While the local-government authorities have implemented some programmes to assist them, such as food aid and social-safety-net schemes, these are insufficient, due to the government's limited institutional resources and capacities. These findings suggest that for formulating effective rural-development plans, assessing the impact of riverbank erosion on the food security of people living in the affected areas is a prerequisite.

Groundwater plays a pivotal role as the largest potable water sources in Bangladesh. However, the quality of the groundwater faces challenges due to xenobiotic compounds in it. Excess amount of arsenic (As) has already been found in groundwater in many parts of Bangladesh. Thus, this study was conducted to assess the water quality and associated human health risk in central Bangladesh. A total of 99 groundwater samples from the central part of Bangladesh were analyzed to assess human health risk due to high level of nitrate (NO3-) and other trace elements i.e. arsenic (As), iron (Fe), and manganese (Mn). It was found that NO3- concentration (253.17 mg/L) in the groundwater samples exceeds the recommended guideline value by the WHO (50 mg/L). Moreover, this study area also characterized with elevated concentration of As (19.44 µg/L), Fe (811.35 µg/L), and Mn (455.18 µg/L) in the groundwater. Non-carcinogenic human health risk was calculated by justifying HQ (Hazard Quotient) and HI (Hazard Index) and attributed potential conjunctive human health risks due to NO3-, As, Fe and Mn in the study area. Moreover, high carcinogenic risk was found due to As contamination in the groundwater samples in the study area.

The allosteric SERCA (Sarcoplasmic/Endoplasmic Reticulum Ca2+-ATPase) activator CDN1163 has been recently added to the group of pharmacological tools for probing SERCA function. We chose to investigate the effects of the compound on T lymphocyte Ca2+ stores, using the well-described Jurkat T lymphocyte as a reliable cell system for Ca2+ signaling pathways. Our study identified the lowest concentrations of the SERCA inhibitors thapsigargin (TG) and 2,5-di-(tert butyl)-1,4-benzohydroquinone (tBHQ) capable of releasing Ca2+, permitting the differentiation of the TG-sensitive SERCA 2b Ca2+ store from the tBHQ-sensitive SERCA 3 Ca2+ store. We proceeded to test the effects of CDN1163 on Ca2+ stores, examining specific actions on the SERCA 2b and SERCA 3 Ca2+ pools using our low dose SERCA blocker regimen. In contrast to previous work, we find CDN1163 exerts complex time-sensitive and SERCA isoform-specific actions on Ca2+ stores. Surprisingly, short-term exposure (0-30 minutes) to CDN1163 perturbs T cell Ca2+ stores by suppressing Ca2+ uptake with diminished Ca2+ release from the SERCA 2b-controlled store. Concomitantly, we find evidence for a SERCA-activating effect of CDN1163 on the SERCA 3 regulated store, given the observation of increased Ca2+ release inducible by low dose tBHQ. Intriguingly, longer-term (>12 hours) CDN1163 exposure reversed this pattern, with increased Ca2+ release from SERCA 2b-regulated pools, yet decreased Ca2+ release responses from tBHQ-sensitive SERCA 3 pool. Our results reveal differential effects of CDN1163 on Ca2+ stores regulated by distinct SERCA isoforms, prompting the need for careful interpretation of the compound’s effects, particularly in cells expressing multiple SERCA isoforms.

Urinary tract infections (UTIs) caused by pathogens, particularly E. coli, have spontaneously become resistant to antimicrobial drugs in recent years. Therefore, regular monitoring and alternative strategies for the antimicrobial agent are crucial for combating antimicrobial resistance and bacterial biofilms. Here, we report a new cobalt iron oxide-conjugated tin oxide nanocomposite that can kill bacteria and treat multidrug-resistant E. coli posing UTIs. Following the isolation and identification of E. coli, we tested 57/134 samples against sixteen commonly used antibiotics phenotypically using the disk diffusion method to determine their sensitivity pattern. Of the 57 E. coli isolates, 66% (38/57) were multidrug-resistant. The E. coli isolates were resistant to cephradine (70.17%), ceftriaxone (59.64%), and azithromycin (59.64%), followed by cefixime (54.38%), cefuroxime sodium (52.63%), and co-trimoxazole (50.87%). X-ray diffraction results showed the crystallite sizes were about 5.68 and 8.84 nm in pure SnO2 nanoparticles and 95% SnO2-5% CoFe2O4 nanocomposite, respectively. Energy-dispersive X-ray spectroscopy and Fourier transform infrared determined the fundamental structure of the nanocomposite, encompassing Co, Fe, Sn, and O. Moreover, FTIR measurements implied that the distinct functional groups in both SnO2 and CoFe2O4 nanoparticles existed in a 95% SnO2-5% CoFe2O4 nanocomposite. Field emission scanning electron microscope analysis uncovered that the SnO2-CoFe2O4 nanocomposite had a size of roughly 24 nm and was spherical. In addition, the biosynthesized SnO2 nanoparticles and SnO2-CoFe2O4 nanocomposite were evaluated for their antibacterial activity. At a minimum 100 µg/mL concentration, SnO2 nanoparticles and SnO2-CoFe2O4 nanocomposite showed high antibacterial activity. The SnO2 nanoparticles and SnO2-CoFe2O4 nanocomposite demonstrated antibacterial activity on multidrug-resistant E. coli at 10 ± 0.7 and 16 ± 0.8 mm zone of inhibition, respectively. In conclusion, the new SnO2-CoFe2O4 nanocomposite might be a potential candidate for treating UTIs caused by drug-resistant E. coli in the foreseeable future.

Monkeypox virus (MPXV), causing zoonotic diseases in humans, is a member of Orthopoxvirus under Poxviridae family. The virus was first reported in monkeys in 1959 in Denmark and in humans in 1970 in the Congo. Outside Africa, the virus first appeared in the USA in 2003 and since then occurred sporadically. The virus reemerged in 2017 and now spreading globally. African wild rodent mammals are thought to be the reservoir of MPXV. Exotic trade of animals and international travel favors the dissemination of MPXV. Genetic analysis shows two clades of the MPXV. Smallpox vaccine shows cross-protection and people who never in contact with Orthopoxvirus affected more than exposed ones. Fever, muscle pain, headache, and vesicle formation are the dominant clinical sign. Guarnieri-like inclusions and Ballooning degenerations are important pathognomic lesion of MPXV. It may produce case fatality rate up to 11%. Genetic materials alterations may favor the reemergence of the virus. The continuing occurrence over 73437 cases in 109 countries shows that MPXV can spread among humans competently and can be a serious issue of global public health concern. Here, we summarize the existing knowledge about re-emergence and insights into MPXV which will be of useful to curb its occurrence.

The principal goal of this current study was to isolate a new potential probiotic strain to prepare contamination-free probiotic dahi in a dosage form with desired shelf life. To achieve our target, firstly, probiotic dahi was prepared by a probiotic strain, Lactobacillus acidophilus JB2CON (OM909067) (identified by 16S sequencing) isolated from natural dahi in Dhaka, Bangladesh. The isolate showed five probiotic features by in vitro test and had an antagonistic effect against five different pathogens. More interestingly, it inhibited Escherichia coli (diameter of zone of inhibition = 15.75±0.35) the most. In the time-kill analysis method, E. coli was killed totally within 5.50 hours of fermentation. Finally, the time duration of 14 days was an ideal shelf life, because the probiotic count increased but a slight change in pH did not affect the taste (sourness/acidity) of dahi. The most significant impact of this research is that the probiotic dahi of our experiment might be used as a cheap option for preventing pathogenic Escherichia coli-related foodborne diseases worldwide, especially in underdeveloped countries like Bangladesh.

Here we report the effect of substrate, sonication process, and post-annealing on the structural, morphological, and optical properties of ZnO thin films grown in the presence of isopropyl alcohol (IPA) at temperature 30 – 65 ℃ by successive ionic layer adsorption and reaction (SILAR) method on both soda lime glass (SLG) and Cu foil. The X-ray diffraction (XRD) patterns confirmed the preferential growth thin films along (002) and (101) plane of wurtzite ZnO structure while grown on SLG and Cu foil substrate respectively. Both XRD and Raman spectra confirmed the ZnO and Cu-oxide phases of the deposited films. Scanning electron microscope (SEM) image of the deposited films shows compact and uniformly distributed grains for samples grown without sonication while using IPA at temperature 50 and 65 ℃. The post-annealing treatment improves the crystallinity of the films, further evident by XRD and transmission and reflection results. The estimated optical bandgaps are in the range of 3.37-3.48 eV for as-grown samples. Results revealed that high-quality ZnO thin films could be grown without sonication using IPA dispersant at 50 ℃, which is much lower than the reported results using the SILAR method. This study suggests that in the presence of IPA, the SLG substrate results in better c-axis oriented ZnO thin films than that of DI water, ethylene glycol, propylene glycol at the optimum temperature of 50 ℃. Air-annealing of the samples grown on Cu foils induced the formation of Cu_xO/ZnO junctions which is evident from the characteristic I-V curve including the structural and optical data.

Global crop yield and food security are being threatened by phytophagous insects. Innovative methods are required to increase agricultural output while reducing reliance on hazardous synthetic insecticides. It appears to be quite effective at reducing production costs and boosting farm profitability to use the ground-breaking CRISPR-Cas technology to create plants that are insect resistant. In contrast, this new technique can modify an insect's genome to either produce gene drive or get beyond an insect's tolerance to various insecticides. This paper reviews and critically discusses the use of CRISPR-Cas genome editing technology in long-term insect pest management. The emphasis of this review is on the prospective uses of the CRISPR-Cas system for insect stress management in crop production by creating genome-edited crops and insects. The potential and difficulties of using CRISPR-Cas technology to reduce pest stress in crop plants are critically examined and discussed.

The goal of the current study was to discover a novel potential probiotic strain of Lactobacillus spp. with anti-Escherichia coli activity from locally produced yogurt in Tongi, Gazipur, Bangladesh, compare its antagonistic activity with a commercial probiotic mixture of several strains, and approve a novel method for confirming the viability and relative abundance of the microbial community in a probiotic mixer. We carried out 16S sequencing, 16S metagenomics, Transmission Electron Microscopy (TEM) analysis, and other in vitro laboratory experiments to reach this objective. The strain TY-11 was identified as Lactobacillus delbrueckii subsp. indicus (16S sequence accession number OQ652026). It was gram-positive, anaerobic, lactose fermenting, and round-ended rod that typically measured 0.7 to 1.3 µm by 2.2 to 9 µm. In addition to having seven probiotic characteristics, it also showed an antagonistic impact on six different pathogens, but what's more noteworthy is that E. coli was the pathogen it inhibited most strongly (inhibition zone diameter was 18.88±0.18 mm). The most important and ground-breaking finding of this work was determining the probiotic features of a new probiotic strain, TY-11, whose antibacterial activity was virtually as effective as that of the probiotic combination with three different strains. Furthermore, the results of 16S high throughput sequencing and the conventional plate count method demonstrated a strong correlation (0.999) at the genus level, indicating that the use of both of these approaches in combination may be a practical way to assess the relative abundance of the microbial community and their viability in commercially available probiotic blends.

Application of chemical pesticides to protect agricultural crops from pests and diseases is discouraged due to their harmful effects on human and environment. Therefore, alternative approaches for crop pro-tection through microbial or microbe originated pesticides have been gaining momentum. Wheat blast is a destructive fungal disease caused by Magnaporthe oryzae Triticum (MoT) pathotype, which poses a seri-ous threat to global food security. Screening of secondary metabolites against MoT revealed that antimy-cin A isolated from a marine Streptomyces sp. had significant inhibitory effect on mycelial growth in vitro. This study aimed to investigate the inhibitory effects of antimycin A on some critical life stages of MoT and evaluate the efficacy of wheat blast disease control by this natural product. Bioassay indicated that antimycin A suppressed mycelial growth, conidiogenesis, germination of conidia and formation of ap-pressoria in germinated conidia of MoT in a dose-dependent manner with minimum inhibitory concen-tration 0.005 μg/disk. If germinated, antimycin A induced abnormal germ tubes (4.8%) and suppressed the formation of appressoria. Interestingly, application of antimycin A significantly suppressed wheat blast disease in both seedling and heading stages of wheat supporting the results from invitro study. This is the first report on inhibition of mycelial growth, conidiogenesis, conidia germination, detrimental morphological alterations in germinated conidia, and suppression of wheat blast disease caused by a Triticum pathotype of M. Oryzae. Further study is required to unravel the precise mode of action of this promising natural compound for considering it as a biopesticide to combat wheat blast.

Oil palm is one of the most important crops in Malaysia. Lately, the production of oil palm has been reduced due to a variety of factors, including the weather and climate. Temperature, wind speed, relative humidity, sunshine, and rainfall distribution all have an impact on palm tree growth and development, which in turn has an impact on oil palm production. This paper aims to investigate the effects of some weather elements (temperature, wind speed, relative humidity, sunshine, and rainfall) on oil palm production in Peninsular Malaysia. Data were analyzed using the Statistical Package for Social Sciences (SPSS 20.0 version), with descriptive statistics, and multiple linear regression (MLR). The MLR model determined the strength of the relationship between oil palm yield (dependent variable) and the changing variables of temperature, sunshine, wind speed, relative humidity, and rainfall (independent variables). The findings revealed that temperature, wind speed, relative humidity, sunshine, and rainfall have a low impact on oil palm production and yield turnover. The R2 value of 0.202 shows that the independent variables explained only 20.2% of the fluctuation in palm oil production. The study recommends working within an integrated approach involving scientific research, planting, improving variety, improving regional academic leadership, and engaging private and public stakeholders, emphasized collaborative efforts with researchers in consumer countries, and strengthening the capacity of growers to best agroecological practices.

Irrigation and fertilizer are two essential factors affecting rice root traits and yield. In this respect, a pot experiment was performed at the boro (dry season irrigated) season of 2021-22 in the Department of Agronomy of Bangladesh Agricultural University, Mymensingh, Bangladesh. The variety Binadhan-10 was planted at two irrigation conditions i.e. saturation (S) and continuous flooding (CF); two potassium (K) dose e.g. 65 kg ha-1 (K65) and 98 kg ha-1 (K98) and two nitrogen (N) dose i.e. 140 kg ha-1 (N140) and 210 kg ha-1 (N210). The experiment was laid in split plot design and replicated thrice. The findings confirmed the effectiveness of irrigation, K and N on root number (RN), root length (RL), root volume (RV), leaf area index (LAI), total dry matter (TDM), yield attributes and yield. Considering interaction among irrigation, K and N, S condition with K65 and N140 showed best performance. At 80 DAT, the highest RN (373.00), RL (1700.00 cm), RV (8.90 cm3 hill-1), LAI (4.94) and TDM (25.83 g plant-1) was obtained from this combination. Grain yield (GY) and root traits except root porosity, showed a significant positive association. Grain yield (GY) was highest (27.12 g pot-1) in S condition with K65 and N140.

Abstract Successful treatment against infectious agents depends on rapid and accurate detection of the causative organisms. Misdiagnosis can hamper such success while leading to improper advising of antibiotics. In Bangladesh, the majority of the diagnostic centers detect and identify pathogens through culture and biochemical test-based methods and suggest antibiotics based solely on the results of disk-diffusion methods. This pilot study tried to validate the identity of the isolates characterized by diagnostic facilities near Dhaka. One hundred and twenty pre-characterized clinical isolates were analyzed biochemically and genotypically. Random Amplification of Polymorphic DNA-PCR, rcsA, and phoA genes-based PCR, and Loop-Mediated Isothermal Amplification (LAMP)-based identification of Klebsiella pneumoniae and Escherichia coli, respectively, followed by 16S rRNA sequencing confirmed misidentification of some clinical pathogens of other genera as Klebsiella spp. and E. coli. According to the antibiotic susceptibility testing guidelines, antibiotic choice, sensitivity pattern, and breakpoint measurement are different for each group of organisms. The lack of adherence to proper standards results in misdiagnosis and may facilitate the development of antibiotic resistance. The pilot study observers misidentification of clinical pathogens identified by the diagnostic centers. Well-characterized rapid molecular techniques like LAMP are suggested in clinical diagnosis to avoid misdiagnosis and subsequently circumvent antibiotic resistance development.

Brain tumors are frequently classified with high accuracy using convolutional neural networks (CNNs) and better comprehend the spatial connections among pixels in complex pictures. Due to their tiny receptive fields, the majority of deep convolutional neural network (DCNN)-based techniques overfit and are unable to extract global context information from more significant regions. While dilated convolution retains data resolution at the output layer and increases the receptive field without adding computation, stacking several dilated convolutions has the drawback of producing a grid effect. To handle gridding artifacts and extract both coarse and fine features from the images, this research suggests using a dilated parallel deep convolutional neural network (PDCNN) architecture that preserves a wide receptive field. To reduce complexity, initially, input images are resized and then grayscale transformed. Data augmentation has since been used to expand the number of datasets. Dilated PDCNN makes use of the lower computational overhead and contributes to the reduction of gridding artifacts. By contrasting various dilation rates, the global path uses a low dilation rate (2,1,1), while the local path uses a high dilation rate (4,2,1) for decremental even numbers to tackle gridding artifacts and extract both coarse and fine features from the two parallel paths. Using three different types of MRI datasets, the suggested dilated PDCNN with the average ensemble method performs better. The accuracy provided by the Multiclass Kaggle dataset-III, Figshare dataset-II, and Binary tumor identification dataset-I is 98.35%, 98.13%, and 98.67%, respectively. In comparison to state-of-the-art techniques, the suggested structure improves results by extracting both fine and coarse features, making it efficient.

Numerous study reports on chitosan hydrogels in different forms such as films, porous structures, nanoparticles, and microspheres for biomedical applications, however, this study concentrates on their modifications with different crosslinking agents and observing their effects on drug loading and releasing capacities. Linear chitosan along with crosslinked by two major cross-linkers, i.e., genipin and disulfide have been used to formulate three different hydrogel systems. The cross-linking process is heavily impacted by the temperature and the pH conditions. Three different drugs, i.e., thymoquinone, gefitinib, and erlotinib are loaded in phosphate buffer solutions and infused with three different hydrogel systems, thus, a total of nine combinations are studied and analyzed for drug loading and releasing capabilities with Ultraviolet–visible (UV-Vis) spectroscopy. This study finds thymoquinone shows the lowest loading efficacy compared to two other drugs in all three systems. Gefitinib shows stable loading and releasing regardless of crosslinking systems and genipin crosslinked system shows stable loading and releasing with all three drug molecules. These experimental results agree well with the findings of our previously published results conducted with molecular dynamics simulations.

Arjunolic acid (AA) is a triterpenoid saponin majorly found in the Terminalia arjuna and is claimed to exert the cardiovascular protective effects as a phytomedicine. However, it is unclear how AA exerts the effects at the molecular level. Hence, this study used an in vitro model using lipopolysaccharide (LPS)-stimulated H9C2 and C2C12 myotubes to investigate the cardioprotective effects of arjunolic acid (AA) via MyD88-dependant TLR4 downstream signaling markers expression. The myotubes were developed by differentiating rat H9C2 and mouse C2C12 myoblast cells. The MTT viability assay was used to assess the cytotoxicity of AA. LPS induced in vitro cardiovascular disease model was developed in H9C2 and C2C12 myotubes. The treatment groups were designed such as control (untreated), LPS control, positive control (LPS+ pyrrolidine dithiocarbamate (PDTC)-25 µM), and treatment groups were co-treated with LPS and three doses of AA (50, 75, and 100 µM). The changes in the expression of TLR4 downstream signaling markers were evaluated through High Content Screening (HCS) and Western Blot (WB) analysis. The outcomes demonstrated that the expression of MyD88, MAPK, JNK, and NFκB markers were significantly upregulated in the LPS-treated groups compared to the untreated control. Evidently, the HCS analysis revealed that MyD88, NF-κB, p38, and JNK were significantly downregulated in the H9C2 myotube in the AA treated groups (50, 75, and 100 µM). For, the C2C12 myotube, the expression of NFκB was downregulated. TLR4 marker expression in H9C2 and C2C12 myotubes was subsequently decreased by AA treatment, suggesting possible cardioprotective effects of AA.

Thalassemia is one of the most prevalent genetic disorders worldwide which has been previously found to have an association with several physiological and organ complications. Several studies found both its positive and inverse correlation with glomerular filtration rate (GFR). Therefore, in this meta-analysis, we tried to assess the accurate correlation of thalassemia with GFR. We searched in Google Scholar, PubMed, and ScienceDirect, and from the initial 96 articles we finally could include 15 studies. The quality and publication bias assessment confirmed that all the studies were of high to moderate quality with no publication bias. The main outcome of the mean difference (MD) was -6.45, 95%CI: -18.50, 5.60 (P<0.00001), which indicated a negative correlation of GFR with thalassemia. The sensitivity analyses found one study as a slight outlier and reanalyzing the data excluding that study MD was achieved as -13.90, 95%CI: -24.22, -3.59 (P<0.00001) which even strongly supports our main outcome. Our result determined that the GFR is generally higher in healthy people as compared to thalassemia patients.

NACA 0015 and NACA 4415 aerofoil are most common four digits and broadly used aerodynamic shape. Both of the shapes are extensively used for various kind of applications including turbine blade, aircraft wing and so on. NACA 0015 is symmetrical and NACA 4415 is unsymmetrical in shape. Consequently, they have big one-of-a-kind in aerodynamic traits at the side of widespread differences of their utility and performance. Both of them undergo the same fluid principle while applied in any fluid medium giving dissimilar outcomes in aerodynamics behavior. On this work, experimental and numerical investigation of each NACA 0015 and NACA 4415 is done to decide their performance. For this purpose, aerofoil section is tested for a prevalence range attack of angle (AOA). The study addresses the performance of NACA 0015 and NACA 4415 and evaluates the dynamics of flow separation, lift, drag, pressure and velocity contour and so on. This additionally enables to layout new optimistic aerofoil, which is critical to enhance the efficiency and performance of an aircraft in terms of lift enhancement and drag reduction.

In this study, we consider a Lambert series whose coefficients are the sum of divisors function. Utilizing the Lambert series in the sequel we introduce a normalized linear operator JR_(α,β) (z) by applying the convolution with Rabotnov function. We then, acquire sufficient conditions for JR_(α,β) (z) to be Univalent, Starlike and Convex respectively. In each component of this study, we expand the derived results by applying two Robin's inequalities, one of which is equivalent to the Riemann hypothesis.

The COVID-19 pandemic has affected millions of people globally, with respiratory organs being strongly affected in individuals with comorbidities. Medical imaging-based diagnosis and prognosis have become increasingly popular in clinical settings to detect COVID-19 lung infections. Among various medical imaging modalities, ultrasound stands out as low-cost, mobile, and radiation-safe imaging technology. In this comprehensive review, we focus on ultrasound-based AI studies for COVID-19 detection that use public or private lung ultrasound datasets. We surveyed articles that used publicly available lung ultrasound datasets for COVID-19 and reviewed publicly available datasets and organize ultrasound-based AI studies per dataset. We analyzed and tabulated studies in several dimensions, such as data preprocessing, AI models, cross-validation, and evaluation criteria. In total, we reviewed 42 articles, where 28 articles used public datasets, and the rest used private data. Our findings suggest that ultrasound-based AI studies for the detection of COVID-19 have great potential for clinical use, especially for children and pregnant women. Our review also provides a useful summary for future researchers and clinicians who may be interested in the field.

The software design of autonomous vehicles (AVs) incorporates artificial intelligence (AI) characteristics to enhance their safety and overall driving performance. Central to vehicle’s operation is the ability to reason effectively in complex and uncertain environments. However, traditional logical systems, such as monotonic logic, often struggle to handle the inherent uncertainties and exceptions encountered in real-world scenarios. This paper proposes the utilization of non-monotonic logic in order to enhance the reasoning capabilities of autonomous vehicles. By incorporating non-monotonic reasoning, vehicles can navigate intricate traffic scenarios, make plausible inferences, and adapt their decisions when faced with conflicting information. This research aims to provide a comprehensive review of non-monotonic logic's application in autonomous vehicles, highlighting its advantages over traditional logical systems and its potential impact on safety and performance. Additionally, through this research, we seek to contribute to the advancement of autonomous driving technology by enhancing the reasoning capabilities of vehicles in various scenarios, such as car- following related to critical safety events. The personalized cognitive agent is proposed in driving behavior to consider particularly in their assumptions of homogeneous drivers. The personalized cognitive agent is incorporating heterogeneous driving behaviors, based on individual user preferences, characteristics, and needs. Driving behavior is a complex interplay of various factors, encompassing both human and external elements. Human factors, including age, experience, and gender, contribute significantly to how individuals navigate the roads. These factors influence decisions, reactions, and risk-taking tendencies on the part of drivers. Additionally, external factors such as weather conditions further compound this intricate dynamic, requiring drivers to adapt their behavior to the prevailing environment. The goal of a personalized cognitive agent is to provide tailored and customized experiences to cognitive vehicles, taking into account the unique requirements and individual preferences of occupants inside autonomous vehicles.

Bangladeshi medicinal plants (BMP) have been used as traditional medicinal plants to treat chronic inflammatory diseases, but the antioxidant and anti-inflammatory effects of the bark of BMP are not yet known. The objective of this study was to determine antioxidant and anti-inflammatory activities using methanolic extracts of bark obtained from 15 medicinal spices of Bangladesh plants. The bark methanol extracts of BMP evaluated the total antioxidant activity and anti-inflammatory effect of lipopolysaccharide (LPS)-induced inflammation in RAW 264.7 macrophages. Among the 15 bark extracts of BMP, Albizia odoratissima (A. odoratissima), Engelhardia spicata (E. spicata), and Shorea robusta (S. robusta) showed the highest total phenolic contents and total antioxidant capacity by reducing free radicals scavenging activity. In particular, the three bark extracts significantly reduced the mRNA expression of LPS-induced inflammatory cytokines and inflammation-inducible enzymes in macrophages. Also, the mRNA expression of NADPH oxidase 2 was significantly suppressed by three bark extracts in LPS-induced RAW 264.7 macrophages. The results suggest that among the 15 bark extracts obtained from medicinal plant in Bangladesh, three bark extracts of A. odoratissima, E. spicata, and S. robusta exert total antioxidant capacity by reducing free radicals scavenging activity and inhibitory effects on LPS-stimulated inflammation in macrophages.

The dynamic landscape of AI adoption and its impact on employment in Malaysia demands a multifaceted approach to navigate the challenges and harness the opportunities presented. While the government's commitment to fostering AI adoption through initiatives like the National AI Framework and the Malaysia Digital Economy Blueprint is commendable, it is imperative to address concerns regarding job displacement and ensure inclusive growth. This study identifies the pressing research problem of workforce readiness for the AI-driven future, emphasizing the need to explore strategies for reskilling and upskilling affected workers. By employing critical lenses such as Marxist, feminist, and postcolonial perspectives, scholars highlight the power dynamics and societal implications inherent in AI deployment, guiding the development of policies and interventions that prioritize workers' interests and address social inequalities. Moving forward, a comprehensive approach combining policy interventions, educational reforms, and inclusive strategies is essential to maximize the benefits of AI adoption while mitigating its potential risks. Longitudinal studies, interdisciplinary research, and comparative analyses will further advance our understanding and inform evidence-based policymaking in this evolving field. Ultimately, by prioritizing workforce preparedness, social equity, and sustainable development, Malaysia can position itself as a leader in the AI-driven global economy, fostering a resilient, inclusive, and prosperous society for all.

Molecular dynamics(MD) simulations are playing an increasingly important role in structure-based drug discovery (SBDD). Here we review the use of MD for proteins in aqueous solvation, organic/aqueous mixed solvents (MDmix) and with small ligands, to the classic SBDD problems: binding mode and binding free energy predictions. The simulation of proteins in their condensed state reveals the solvent structure and preferential interaction sites (hot spots) on the protein surface. This information is largely transferable across all classes of protein ligands (from water to drugs) and can be used very effectively to understand ligand recognition and improve the predictive capability of well-established methods such as molecular docking. MD simulations for protein and drug or drug-like compounds are now being used but are still computationally expensive and can only be applied to specific cases. On the other hand, MDmix simulations can now be used in SBDD and we will describe the latest developments and implementations. We expect to see an increase in the application of these techniques to a plethora of protein targets to identify new drug candidates with the advent of new tools and faster computers.

The present research was titled “A Study on Dark Triad Personality and Emergency Response and Psychological Adaptation among Young Adults during Pandemic.” The purpose of the study was to explore the association between the dimensions of dark triad personality namely narcissism, psychopathy, Machiavellianism and the dimensions of emergency response and psychological adaptation namely worry, agitation, awareness, prosociality, perceived self-efficacy. The correlation between the dimensions of dark triad personality and the dimensions of emergency response and psychological adaptation. Gender differences were also studied for the dimension dark triad personality. The results showed that a strong positive correlation existed between narcissism and agitation, Machiavellianism and worry and Machiavellianism and agitation. Narcissism and psychopathy were found to be strong predictors of agitation. Significant Gender differences were noted on the dimensions of psychopathy and Machiavellianism where males scored higher than females.

From 2008 to 2024, the Newborn Screening Translational Research Network (NBSTRN), part of the National Institute of Child Health and Human Development (NICHD) Hunter Kelly Newborn Screening Program, served as a robust infrastructure to facilitate groundbreaking research in newborn screening (NBS), rare disease, and genomics. Over fifteen years, NBSTRN developed into a significant international network, supporting innovative research on novel technologies to screen, diagnose, treat, manage, and understand the natural history of more than 280 rare diseases. A key component of these efforts has been the development of resources and expertise for the newborn screening community in ethical, legal, and social issues (ELSI). This paper presents findings from a survey conducted by the NBSTRN team with input from one of theNBSTRN's expert workgroups, the Bioethics and Legal Workgroup. With responses from 88 members of the NBS community including researchers and state NBS programs, the survey found that individuals rely on internal and collegial ELSI resources and highlighted a substantial demand for structured, accessible training and resources. The survey’s insights emphasize the importance of privacy and informed consent in NBS research, and suggested a need for improved collaborative tools and educational programs focused on ELSI for the NBS community. The survey results may inform future efforts in ELSI and NBS research including the development of expanded ELSI tools that leverage digital platforms and consultative services.

Wheat blast caused by the hemibiotroph fungal pathogen Magnaporthe oryzae Triticum (MoT) pathotype, is a destructive disease of wheat in South America and Bangladesh. Generation of reactive oxygen species (ROS) is one of the defense responses in plants during the infection process by a pathogen. However, empirical evidence on regulation of ROS in wheat and other host and non-host plants towards MoT is limited. This study aimed to determine the susceptibility of some major cereals and weeds of Bangladesh and compare the antioxidant enzyme activities in host and non-host plants in response to artificial inoculation by MoT. Seedlings of wheat, maize, barley and swamp rice grass were susceptible to MoT and produced considerable number of conidia on infected leaves (host). Rice seedlings showed a resistant response in our laboratory conditions (non-host). The activities of ROS-detoxifying enzymes; catalase (CAT), ascorbate peroxidase (APX), Glutathione peroxidase (GPX), Glutathione S-transferase (GST), Peroxidase (POX) increased in all plants after inoculation by MoT with a few exceptions. Interestingly, an early and very high accumulation of CAT was observed within 24 hours of inoculation (hai) in wheat, barley, maize and swamp rice grass while H2O2 concentration was low during that time and immediately after that (24-48 hai). In contrast, an early and high accumulation of H2O2 was observed in rice at 48 hai with little CAT activity only at a late stage. The APX, GST and POD activity was also increased due to the inoculation of MoT at the early stage of infection in rice but were very high at the disease progression stage in wheat, barley, maize and swamp rice grass. GPX activity gradually decreased with the increase of time in rice. Taken together, our results suggest that a robust and late induction of most of the antioxidant enzyme activities occurs in susceptible/host plants whereas an early induction of antioxidant enzyme activities occurs in resistant/ non-host plant but with slow kinetics.

CO2 geological sequestration in coal seams can achieve the dual objectives of CO2 emission reduction and enhanced coalbed methane production, making it a highly promising carbon capture and storage technology. However, the injection of CO2 into coal reservoirs in the form of supercritical fluid (ScCO2) leads to complex physicochemical reactions with the coal seam, altering the properties of the coal reservoir and impacting the effectiveness of CO2 sequestration and methane production enhancement.In this paper, theoretical calculations based on ReaxFF-MD were conducted to study the interaction mechanism between ScCO2 and the macromolecular structure of both low-rank and high-rank coal, to address the limitations of experimental methods. The reaction of ScCO2 with low-rank coal and high-rank coal exhibits significant differences. At swelling stage, the low-rank coal experiences a decrease in aromatic structure and aliphatic structure, high-rank coal shows an increase in aromatic structure and a decrease in aliphatic structure, while swelling phenomenon is more pronounced in high-rank coal. At dissolution stage, low-rank coal is initially decomposed into two secondary molecular fragments, and then recombine to form new molecular structure, the aromatic structure increased and the aliphatic structure decreased. In contrast, high-rank coal occurs stretches-breakage-movement-reconnection, a reduction in aromatic structure and an increase in aliphatic structure.The primary reasons for these variations lie in distinct molecular structure compositions and the properties of ScCO2, leading to different reaction pathways of functional group and aromatic structure. The reaction pathways of functional groups and aromatic structures in coal can be summarized as follows: the breakage of the O-H bond in hydroxyl groups, the breakage of the C-OH bond in carboxyl groups, transformation of aliphatic structures into smaller hydrocarbon compounds or formation of long-chain alkenes, and various pathways involving broken, rearrangement, recombination of aromatic structures. In low-rank coal, there is a higher abundance of oxygen-containing functional groups and aliphatic structures. The breakage of O-H and C-OH chemical bonds results in the formation of free radical ions, while some aliphatic structures detach to produce hydrocarbons. Additionally, some of these aliphatic structures combine with carbonyl groups and free radical ions to generate new aromatic structures. Conversely, in high-rank coal, the lower content of oxygen-containing functional groups and aliphatic structures, along with stronger intramolecular forces, results in fewer chemical bond breakages and makes it less conducive to the formation of new aromatic structures.These results elucidate the specific deformations of different chemical groups, offering a molecular-level understanding of the interaction between CO2 and coal.

Multidrug resistant organisms (MDROs) outbreaks have been steadilyincreasing in Intensive care units (ICUs). Still, healthcare institutions and workers (HCW) reached no unanimity on how and when implementing infection prevention and control (IPC) strategies. We aimed to provide a pragmatic, physician practice-oriented, resume of strategies towards different MRDOs outbreaks in ICU. We performed a narrative review on IPC in ICUs, investigating patient-to-staff ratios, education, isolation, decolonization, screening and hygiene practices, outbreak reporting, cost-effectiveness, reproduction-number(R0), and future perspectives. The most effective IPC strategy remains unknown. Most studies focus on a specific pathogen or disease, making the clinician losing the big picture. IPC strategies proved their cost-effectiveness regardless typology, country, or pathogen. A standardized, universal, pragmatic protocol for HCW education should be elaborated. Likewise, a rapid outbreak recognition tool elaboration (i.e., an easy-to-use mathematical model) would improve early diagnosis and spreading prevention. Further studies are needed to express in favor or against MDROs decolonization. New promising strategies are emerging and need to be tested in the field. The lack of IPC strategies application has made, and still makes ICUs a major MDROs reservoir into the community. In a not-too-distant future genetic engineering and phage therapies could represent a plot-twist in MDROs IPC strategies.

Seasonal snowpacks, characterized by their snow water equivalent (SWE), play a major role in the hydrological cycle, snow melt contributions to floods and the subsequent availability of water resources downstream. Accurately estimating SWE and understanding its spatial and temporal variations presents a considerable challenge, particularly within mountainous regions characterized by complex terrain and limited observational data. Seeking to enhance the performance of the widely used Soil and Water Assessment Tool (SWAT), we report a new approach characterising snowpack behaviour incorporating both modelled and remotely sensed derived SWE calibration data. We focus on the Chenab River Basin (CRB) a headwater catchment of the Indus Basin, globally significant in terms of human inhabitants and intensifying flood risk due to climate change. We conducted a thorough assessment of five satellite-derived and reanalysis-based precipitation datasets: ERA5-Land, CMORPH, TRMM, APHRODITE, and CPC UPP. This reveals significant levels of uncertainty in global precipitation products when compared to reference data from observed stations as well as in the resulting simulated streamflow from the SWAT model. Subsequently, we expanded the scope of the SWAT model to encompass the spatial and temporal simulation of SWE. This was achieved by incorporating information from remotely sensed and modelled SWE products, manually adjusting snow parameters in R-SWAT for both the main basin and at sub-basin scales. Integrating SWE from reference snow products into the calibration process, alongside streamflow data, substantially enhanced modelling accuracy to simulate SWE compared to the conventional auto-calibration and single-variable approaches reliant solely on streamflow data. This approach results in considerable improvement in SWE predictions and to some extent in streamflow simulation in catchments dominated by snow. This research highlights the potential of remote sensing and modelled SWE parameterisation in the absence of in-situ snowpack data in high-altitude environments. An improved understanding of SWE behaviour is vital for predicting hydrological responses spanning hazards to water resources in the populous downstream regions of the Indus Basin, especially in the face of climate change.

Current low meat production in Omani goats under traditional feeding regimes justifies a study of the effects of Spirulina Platensis (SP) supplementation on goats’ performance. Hence, this study aimed to evaluate the effect of incorporating SP into diets on carcass characteristics, fatty acid profile and meat quality traits of two Omani goat breeds. Thirty-six eleven-month-old bucks from the Jabbali and Sahrawi goat breeds (n= 18/breed) were divided into three groups (control, Treatment 1, and treatment 2). All animals received a conventional concentrate feed ration (con-trol (CON) consisting of pellets creep fed. Animals were fed SP daily with Treatment 1 (T1) fed at 2g/head and Treatment 2 (T2) fed at 4g/head. Sahrawi bucks showed a highly significant response to SP feeding compared to Jabbali bucks. Average daily gain and carcass traits (body length, leg length and the rack weight) of Sahrawi bucks were significantly higher in the T1 group than in the CON group. The weights of omental and kidney fat increased in T1 group of Sahrawi goats, while it increased in T2 group of Jabbali goats compared to CON group. Ultimate pH increased in T1 group and meat color (lightness) increased in T2 group in both LD and SM muscles of Sahrawi goats. Most of PUFA n-6 and n-6/n-3 ratio increased in T1 group, while most of MUFA2 and PUFA n-3 fatty acids increased in T2 group of Sahrawi goats. In addition, a significant decrease in pentadecanoic and margaric acids of Sahrawi goats was observed by adding SP to the diet com-pared to the control group. The study concluded that incorporating SP (2g and 4g/head) into the diet of Omani goats, especially Sahrawi goats, can increase growth performance, improve fatty acid composition and meat quality.

The multidrug resistance transporter NorM is an important drug resistance pump and plays a critical role in multidrug resistance in bacteria and mammals. In this study we carried out molecular dynamics simulation to study the mechanism of Na+ binding and dynamical structures of two long loops in the substrate-releasing process in substrate binding NorM. Our simulation study identified several key residues (D41, E261 D377) along the Na+ binding pathway and a multi-state ion-binding mechanism is proposed based on the simulation study. In this proposed model, the transport of Na+ is a multi-stage process with D41 being the first station for binding to Na+, followed by Na+ binding to the second station E262 and finally to the cation-binding site of E262 and D377. During the transport of Na+, the transmembrane components TM1, TM7 and TM2 are rearranged to facilitate the ion transport as well conformational changes of NorM to a closed state. Further, substrate-bound simulation revealed that Loop3-4 and Loop9-10 control the substrate-releasing process.

Background: The practice of self-medication is common worldwide and is an important component of medical self-care. However, the practice can be dangerous and is linked to various risks for the patients and the entire community. This study aimed to estimate the prevalence and factors associated with self-medication among Bangladeshi adults. Methods: A cross-sectional survey was conducted between April and June 2021 among Bangladeshi adults (aged &gt;19 years) using convenient sampling. A total of 1320 data were collected through face-to-face interviews using a standardized questionnaire. Multivariable logistic regression analysis was used to identify factors associated with self-medication practice (SMP). Results: Overall, 41% of adults in our survey reported SMP. The most common illnesses that prompted SMP were common cold/flu (66.4%), gastric problems (65%), and headache (64.4%). The most frequent reasons for SMP were to get better services (30.59%), perceive SMP without side effects (23.28%), and save time with effectiveness (14.56%). Potential risk factors included 10 years (AOR = 1.91; 95% CI: 1.04 - 3.50) and &gt;12 years of schooling (AOR = 5.03; 95% CI: 2.27 - 11.15), being a businessman (AOR = 4.64; 95% CI: 1.74 - 12.37), having ≤6 family members (AOR = 2.13; 95% CI: 1.40 - 3.24), being a member of a social group (AOR = 1.53; 95% CI: 1.10 - 2.12), a health status check after every six months (AOR = 1.52; 95% CI: 1.08 - 2.13), and current ill-health (AOR = 1.41; 95% CI: 1.06 - 1.87). Protective factors identified included ≤30 years of age (AOR = 0.40; 95% CI: 0.17 - 0.93), and practice of modern (AOR = 0.39; 95% CI: 0.22- 0.69) and herbal (AOR = 0.45; 95% CI: 0.21- 0.97) healing types. Conclusion: More than one-third of the study participants reported practicing self-medication. Increasing the community’s awareness of the extreme consequences of SMP and not just the average experience might sway individuals away from SMP, and implementing strict jurisdiction could be a way to minimize the SMP.

One of the major concerns in structural health management (SHM) is the early detection of a growing crack. Using this, future damage due to crack propagation can be mitigated or eliminated by implementing proper repair and maintenance. Acoustic Emission (AE) is a non-destructive testing (NDT) method with potential applications for locating and monitoring fatigue cracks. The research presented in this paper focuses on SHM using AE. A novel AE signal analysis approach was proposed in order to detect crack initiation and assess small crack lengths. Experimental investigation indicated that initiation of a crack could be identified through the statistical analysis of the resulting features of the AE signals. A probabilistic AE-based model for small fatigue crack sizing was developed and the uncertainties of the model were estimated. In addition, a probabilistic model validation approach was implemented to confirm accurate estimation of the results. The outcome of this research can be used to evaluate the integrity of structures under fatigue loading. The proposed approach can also be applied as an approach to manage health and assess prognosis of structures.

Tarsal tunnel syndrome is a focal compressive neuropathy of the posterior tibial nerve or one of its associated branches. Brief mention is made in the literature of the use of corticosteroid injections for this condition. The basic technique of hydrodissection is used for other nerve entrapments and includes identifying the region of nerve compression, and the injection of a fluid medium to dissect between structures or fascial planes. We introduce our treatment protocol using a methylprednisolone/sterile water/ropivacaine hydrochloride injectate mix and peripheral nerve stimulation to a perform hydrodissection technique for tarsal tunnel syndrome.

Background: According to the National Highway Traffic Safety Administration, 116 pedestrians were killed in motor vehicle crashes in Ohio in 2015. However, no study to date has analyzed crashes in Ohio exploring the factors contributing to the pedestrian injury severity resulting from motor vehicle crashes. This study fills this gap by investigating the crashes involving pedestrians exclusively in Ohio. Materials and Methods: This study uses the crash data from the Highway Safety Information System, from 2009 to 2013. The explanatory factors include the pedestrian, driver, vehicle, crash, and roadway characteristics. Both fixed- and random-parameters ordered probit models of injury severity (where possible outcomes are major, minor, and possible/no injury) were estimated. Results: The model results indicate that being older pedestrian (65 and over), younger driver (less than 24), driving under influence (DUI), being struck by truck, dark-unlighted roadways, six-lane roadways, and speed limit of 40 mph and 50 mph were associated with more severe injuries to the pedestrians. Conversely, older driver (65 and over), passenger car, crash occurring in urban locations, daytime traffic off-peak (10 AM to 3:59 PM), weekdays, and daylight condition were associated with less severe injuries. Conclusion: This study provides specific safety recommendations so that effective countermeasures could be developed and implemented by the policy makers, which in turn will improve overall highway safety.

Chronic unpredictable environmental stress (CUES) may induce predisposition to diabetes mellitus. This study investigates the role of CUES on impaired homeostasis. Stressed group mice (n = 20) were exposed to CUES for 16 weeks. Weekly body weight, feed consumption, feed efficiency ratio, fasting blood glucose were monitored. Plasma HbA1c, plasma cortisol, plasma epinephrine and plasma insulin, serum lipids, antioxidants and carbohydrate metabolizing enzymes activity were assessed along with DNA damage and histopathological examination of liver, kidney, pancreas, spleen and skeletal muscles. Fasting blood glucose levels & HbA1c in the stressed were significantly higher compared to control (p < 0.001). Serum lipids were found insignificantly higher in stressed mice compared to control. Body weights of the stressed mice and feed efficiency ratio were found significant (p < 0.001). Plasma corticosterone, plasma epinephrine, HOMA-IR was found to be significantly higher in the stressed group (p < 0.001). Plasma insulin level was found to be significantly lower in the stressed group (p < 0.001). Significant changes were observed in antioxidants level, carbohydrate metabolizing enzymes activity, peripheral tissues and DNA integrity. CUES initiates pathogenesis of diabetes.

This research introduces a pioneering solution to the challenges posed by gastrointestinal tract (GI) cancer in radiation therapy, focusing on the imperative task of precise organ segmentation for minimizing radiation-induced damage. GI imaging has historically used manual demarcation, which is laborious and uncomfortable for patients. We address this by introducing the ResECA-U-Net deep learning model, a novel combination of the UNet and ResNet34 architectures. Furthermore, we further augment its functionality by incorporating the Efficient Channel Attention (ECA-Net) methodology. By utilizing data from the UW-Madison Carbone Cancer Centre, we carefully investigate several image processing techniques designed to capture critical local characteristics. With its foundation in computer vision concepts, the ResECA-U-Net model is excellent at extracting fine details from GI images. Sophisticated metrics such as intersection over union (IoU) and the dice coefficient are used to evaluate performance. Our study's outcomes demonstrate the effectiveness of the suggested method, yielding an impressive 96.27% Dice coefficient and 91.48% IoU. These results highlight the significant contribution that our strategy has made to the advancement of cancer therapy. Beyond its scientific merits, this work has the potential to significantly enhance cancer patients' quality of life and provide better long-term outcomes. Our work is a significant step towards automating and optimizing the segmentation process, which can potentially change how GI cancer is treated completely.

Background: Intrauterine transfusion (IUT) of the donor and partial exchange (pET) of the recipient is a temporizing treatment for pregnancies with Twin Anemia Polycythemia Sequence (TAPS). We sought to give a detailed description of the procedural approach and outcomes for sequential donor IUT and recipient pET in TAPS. Methods: Retrospective study of spontaneous TAPS referred to the Johns Hopkins Center for Fetal Therapy treated with donor IUT followed by recipient pET utilizing a double-syringe set up. Procedure characteristics and outcomes as well as accuracy of existing transfusion formulas were analyzed and compared with the literature. Results: 5 of 78 patients with spontaneous TAPS underwent a total of 19 combined IUT/pET procedures (median first procedure to delivery interval 5.6 weeks [interquartile range IQR 1.9-6.0]). One pET was stopped for fetal decelerations. Patients delivered at 33.0 weeks [IQR 31.9-33.3] with two survivors and no neonatal transfusion requirements. IUT volumes were 48 ml [IQR 39-63 ml] and pET volumes 32 ml [IQR 20-50] utilizing aliquots of 5 – 20 mls for the latter (p=0.021). For IUTs, assumption of a fetal blood volume below 150 ml/kg underestimated required transfusion volume. For pETs, all formulas required adjustment of dilution volume based on bedside testing (p&lt;0.05 for all). Conclusions: Donor transfusion followed by partial exchange in the recipient can prolong pregnancy in spontaneous TAPS and obviate the need for neonatal transfusion. A double-syringe setup facilitates efficient saline exchange. Because the accuracy of volume formulas is limited, bedside testing is recommended to achieve the target hemoglobin.

The importance of bio robotics has been increasing day by day. Researchers are trying to mimic nature in a more creative way so that, the system can easily adopt the complex nature and its environment. Hence, bio robotic gripper plays a role in physical connection between the environment and bio robotics system. While handling the physical world in biorobots gripper, the complexity occurs in feedback system where sensor plays a vital role. Therefore, human centered gripper sensor has a good impact on bio robotics field. But categorical classification and their selection process is not very systematic. This review paper follows PRISMA methodology to summarize the previous works on bio robotics gripper sensor and its selection process.. This paper discusses challenges in soft robotics systems, and the importance of sensing systems to facilitate critical control mechanisms along with their selection considerations. Furthermore, a classification of soft actuation based on gripper has been introduced. Moreover, some unique characteristics for soft robotics sensor are explored namely compliance, flexibility, multifunctionality, sensor nature, surface properties, and material requirements. In addition, a categorization of sensors for soft robotic gripper in terms of modalities has been established ranging from the tactile and force sensor to slippage sensor. Various tactile sensors ranging from piezoelectric sensing to optical sensing are explored as it has utmost importance in soft gripper to effectively address the increasing requirements for intelligence and automation. Finally, taking everything into consideration, a flow diagram has been suggested for selecting sensors specific to soft robotics applications.

The wetlands in northeastern Bangladesh are home to some of the most prolific and valuable ecosystems on the planet, offering a wide range of benefits to both the local and wider communities. A limited number of research on this topic have been carried out in various wetlands in coastal hilsa, but none have been located in the northeastern region of Bangladesh. Thus, the goal of this study was to better understand the most commercially relevant species (anadromous hilsa) in northeastern Bangladesh as well as to assess the wetland ecosystem services more thoroughly with the contribution of their fish genetic resources. In addition to laboratory studies, fieldwork was done in the fishing settlements along the Surma River, Hakaluki Haor, and Tanguar Haor. The study classified 77 fish species into 21 subcategories of ecosystem services, of which 56% were not threatened, 17% were vulnerable, and 10% were highly endangered. The species Hilsa was found to be the most economically significant, accounting for 1% of the GDP overall. The study determined if the hilsa stock of the examined wetlands maintains a single or several subpopulations in comparison to other parts of the country when they migrate from saline water to northeastern Bangladesh (freshwater). But when compared to other groups, the FST score was between 0.000 to 0.017, indicating that the populations are identical and that there is genetic material sharing between them. Additionally, these statistics imply that the Sylhet haor and adjacent river systems contain a single stock of Hilsa fish. Nevertheless, a number of stresses and risks, including overexploitation, illicit and destructive fishing, siltation, and natural disasters like flash floods, have been linked to changes in the supply of hilsa and other ecosystem services. This study also emphasizes the necessity of policy attention and research to address the concerns.

Population concentration in cities brings new risks as an increase in pollution, which causes urban health problems. In order to address this problem, traffic reduction measures are being implemented, as pedestrianization areas and the definition of Low Emissions Zones (LEZ). When the effectiveness of these types of measures is in doubt, smart city tools provide data that can be used to scientifically asses their impact. This article analyzes the situation of Madrid Central (Spain), a LEZ subject to controversy. We apply statistical and regression analyses to evaluate the effectiveness of this measure to reduce air pollution and outdoor noise. According to the results, this LEZ was able to significantly reduce NO$_2$, PM$_{2.5}$, and PM$_{10}$ concentration locally, having the same positive impact in the rest of the city. In terms of noise, this measure is able to mitigate background noise levels generated by the road traffic.

The rapid expansion of Bangladesh's financial infrastructure, coupled with the increasing digitization of banking services, underscores the critical importance of cybersecurity. Machine learning and deep learning methodologies have emerged as potent tools in combating cyber threats such as intrusion, malware, and fraud. By harnessing artificial intelligence and data-driven analysis, these techniques enable real-time scrutiny of vast banking data, facilitating proactive defense against cyberattacks. Bangladesh's evolving financial landscape, characterized by governmental digitalization initiatives and a national financial inclusion strategy, heightens the imperative for robust cybersecurity measures. This paper explores the application of machine learning and deep learning techniques in bolstering banking cybersecurity within the context of Bangladesh's burgeoning digital economy.

The once near-extinct Russell’s viper has recently come back to the area beyond its historical range. A couple of decades ago, its distribution was confined to 11 districts of Bangladesh. Hence, the study aims to update the distributional map of Russell’s Viper (Daboia russelii) across the country and find out the surges' causal factors. Both primary and secondary data were utilized in this study. It revealed that the distributional range of this snake was expanded from 22 to 33 districts in 2024. The respondents noted that climatic stressors like high humidity accompanied by hot weather, increased salinity, and increased frequency of flooding facilitated the spreading of the viper across the country. The cropping pattern and crop diversification were another major contributing factor. The shifting of the single-cropped area to a multi-cropped area in the Barind tract increased its main prey rats. Contrarily, the killing of natural predators such as foxes, monitor lizards and mongoose led to the rise in the snake population. The destruction of vegetation coverage in the upper part of the Padma Basin facilitated the movement of Russell's vipers downstream.

In the field of agricultural food production, the transition between organic and inorganic farming methods has been an issue of much debate. The debate, on one hand, stresses the urgency for the transition in order to preserve environment and health; and, on the other hand, emphasizes the pressure of maintaining food production for a large growing population. Thus, the dilemma is how to find an agricultural system that would balance between obtaining food security and ensuring a safe sustainably environment-friendly food production system. This article focuses on the debate, in the context of Bangladesh, and questions whether it is the proper time, and stage in the development process, to attempt the transition from inorganic conventional food production methods to organic food production methods. This article contemplates why the organic rice market is not expanding in Bangladesh, and attempts to explain the slow growth of the market through the two main factors of income constraint and lack of awareness among people about the environmental and health detriments of inorganic farming methods. The study is exploratory in nature, and finds that it is not mainly the lack of awareness but the income constraint that can be principally attributed to the slow expansion of the organic rice market in Bangladesh. Through exploring consumers’ awareness about organic farming methods and their demand for organic products, this study shows how income as the major constraint, besides price, affects consumers demand for organic and inorganic rice in Bangladesh. Income being identified as the major barrier reveals the potential of the organic rice market to grow in the future, as Bangladesh continues its journey towards becoming a middle-income country.

The evaluation of tourism sustainability has become of paramount importance for researchers and decision-makers to better protect tourist destinations, especially with the continuous increase in the number of tourists and visitors that alter the natural components of the environment and degrade ecosystems. Therefore, the use of geographical data is of great significance, particularly in environmental monitoring and land management, due to its ease of use and availability. However, calculating composite indices for sustainability involves several steps and requires a basic understanding of existing models. This article describes the development and design of a package of plugins in QGIS that serves as an easy-to-use tool for processing and automatically calculating economic, environmental, social indices, and the overall index of tourist sustainability. These plugins have been built in Python and designed as QGIS software plugins.

This research explores the predictive capabilities of autonomous driving systems by integrating human factor considerations within the context of safety-critical events. Recognizing the significance of human behaviors in influencing driving dynamics, the study employs advanced modeling techniques to enhance the accuracy of predictions in scenarios that demand heightened safety measures. Traditional rule-based systems and monotonic logic often fall short in addressing the complexities of safety-critical events. To overcome these limitations, the research proposes the application of non-monotonic logic, allowing for flexible and adaptive reasoning that accommodates exceptions and context-specific information.The study emphasizes the importance of incorporating individual differences among drivers, such as risk-taking tendencies, reaction times, decision-making processes, and driving styles. By considering these human factors, the research aims to develop realistic and accurate autonomous driving models that capture the nuances of real-world driving scenarios, especially in safety-critical situations. The predictive model takes into account both internal and external factors, enabling the autonomous system to anticipate and respond effectively to unforeseen events.The primary goal is to provide autonomous vehicles with the capability to make plausible inferences, handle conflicting data, and adapt their behavior in real-time during safety-critical events. The proposed model integrates personalized cognitive agents for each driver, incorporating their unique preferences, characteristics, and needs. This personalized approach aims to optimize the safety and efficiency of autonomous driving, contributing to the ongoing evolution of intelligent transportation systems.In conclusion, this research contributes to advancing the field of autonomous driving by introducing a predictive model that leverages human factor considerations to enhance safety in safety-critical events. The incorporation of non-monotonic logic and individualized cognitive agents signifies a comprehensive approach to address the challenges associated with predicting autonomous driving behavior, paving the way for safer and more reliable autonomous vehicles in dynamic and unpredictable environments.

This paper describes a new approach that can be used to determine the mechanical properties of unknown materials and complex material systems. The approach uses inverse finite element modelling (FEM) accompanied with a designed algorithm to obtain the modulus of elasticity, yield stress and strain hardening material constants of an isotropic hardening material model, as well as the material constants of the Drucker-Prager material model (modulus of elasticity, cap yield stress and angle of friction). The algorithm automatically feeds the input material properties data to finite element software and automatically runs simulations to establish a convergence between the numerical loading-unloading curve and the target data obtained from continuous indentation tests using common indenter geometries. A further module was developed to optimise convergence using an inverse FEM analysis interfaced with a non-linear MATLAB algorithm. A sensitivity analysis determined that the dual Spherical and Berkovich (S&B) approach delivered better results than other dual indentation methods such as Berkovich and Vickers (B&V) and Vickers and Spherical (V&S). It was found that better convergence values can be achieved despite a large variation in the starting parameter values and / or material constitutive model and such behaviour reflects the uniqueness of the dual S&B indentation in predicting complex material systems. The study has shown that a robust optimization method based on a non-linear least-squares curve fitting function (LSQNONLIN) within MATLAB and ABAQUS can be used to accurately predict a unique set of elastic plastic material properties and Drucker-Prager material properties. This is of benefit to the scientific investigation of properties of new materials or obtaining the material properties at different location of a part which might be not be similar due to manufacturing processes (e.g. different heating and cooling rates at different locations).

Microplastics, which are plastic particles smaller than 5 mm in size, are a growing environmental concern since they have been found in oceans, rivers, lakes, and even on land. These tiny particles can escape water filtration systems and end up in water bodies as well as through the degradation of the larger plastic products causing serious environmental and food safety concerns. This research represents the magnitude of this pollution, characterization of microplastic contamination, its type of polymer, and possible sources of this pollution in the rivers around Dhaka, Bangladesh. Quantitative analyses were done following the method suggested by the NOAA and other conventional methods. Among the rivers, Buriganga has the highest microplastic pollution with 3.654 items/L in surface water and 43.125 items/kg in sediment. The concentration in Shitalakshya and Turag rivers are 3.011 items/L and 2.051 items/L in surface water and 34.875 and 17.875 items/kg in sediment respectively. ANOVA test revealed a significant difference between the concentration level of microplastic in the surface water of the Burigana and Turag rivers. A positive correlation between the concentration level of microplastic in the surface water and the sediment was also found. On average 58% of the microplastics were found to be fibrous in surface water. Qualitative analyses were done to find the characteristics and chemical composition of the microplastics. Through the use of FTIR spectroscopy, the study identified different kinds of synthetic polymers in the sample including polyamide (Nylon), polyethylene (PE), polystyrene (PS), polypropylene (PP), polyethersulfone (PES), polyvinyl chloride (PVC), and polyethylene terephthalate (PET) and polyethylene were the most abundant polymer in the samples. This study involved the investigation of three distinct rivers located in the vicinity of Dhaka city

Cyber Physical Systems (CPS) is the integration of computation and physical process that makes a complete system such as the physical components, networked systems, embedded computers and software and linking together of devices and sensors for information sharing. Cyber Physical Systems are Smart Systems that comprises of the merging and integration of Industry Control Systems, Critical Infrastructures, Internet of Things (IoT) and Embedded Systems. Major industries such as the Chemical and Industrial Plants, Aviation Systems, National Grid, the Stock Exchange, Military Systems, and others depends heavily on these Cyber Physical Systems for financial and economic growth. The benefits of CPS nationally and globally are in the areas of Manufacturing, Energy, Transport, Healthcare and Communication. Cyber Physical Systems incorporates Physical systems, Digital systems and Human elements on network infrastructures to provide interactive systems. However, these three key components the Physical systems, Digital systems and Human elements may have inherent threats and vulnerabilities on them that may run the risk of being compromise, exploited, attacked or hacked. Cybercriminals in their quest to bring down these systems and may cause disruption of services either for fame, revenge, political motive, economic war, cyber terrorism and cyber war. The study seeks to review the risks that are associated with these three key components Physical systems, Digital systems and Human elements. The study considered four main risk mitigation goals for this purpose, and these are Business Value, Organizational Requirements, Threat Agent and Impact based on the review results. We used Analytical Hierarchical Process (AHP) to determine the relative importance of these goals that contributes to developing cybercrime and rich in CPS. For the results, the prioritized goals are then used to assess the risks using a semi-quantitative approach to determine the net threat level.

Wheat is threatened by global warming. This study aimed to characterize based on DNA profile and identify heat-tolerant wheat genotypes. Fifteen wheat genotypes were sown in Nov 21 and Dec 21 and evaluated within 13 SSR markers. A dendrogram classified the genotypes into two main groups. The highest genetic distances (0.93) were drawn between BAW 1290 and BARI Gom 28, and the lowest one between Nadi 2 and BAW 1147. Heat susceptibility index (HSI) values for 1000-grain weight (TGW) and grain yield indicated moderate heat tolerance in Cluster I genotypes (HSI 0.50-1.00), closely matching Group A's Cluster II members. In Group B, Cluster III genotypes had higher HSI (1.04-1.23) and significant reductions in TGW and grain yield under heat stress, indicating heat susceptibility. The varieties BARI Gom 25, 26, 27, 28, 29, and 30 were identified as heat-stress tolerant. This research provides insights for future heat stress-molecular breeding programs.

Bangladesh faces significant wheat grain deficiency compared to its demand due to the lengthy process (10-12 years) required to release a variety through a conventional breeding approach. Traditional breeding methods involve several years of various types of crosses between male and female parents and/or progenies, along with recurrent selection-crossing to obtain a homozygous line (F₁ to F₆ generations) with desired traits within almost 10 years. The double haploid (DH) method is also a time-saving, easier, and more reliable technique to achieve the desired traits in homozygous lines within 2-3 years. DH lines were produced by crossing two F₁ hybrids of spring wheat with maize. 0.1% solution of colchicine was applied to produce DH of F₂ progeny of wheat in the study. 80.8% (340) of the 421 pollinated florets from the two F₁ wheat hybrids were produced as green parthenocarpic caryopses (GPCs) (F₂). 35 of the 70 rescued embryos (or 20.6% of the GPCs) germinated. The germinated embryos regenerated 10 haploid green plants (14.3% of total embryos). After being applied colchicine, 8 of the regenerated haploid (H₁) plants made it. Out of the 8 plants that made it through, only one developed homozygous double haploid seed (DH₁ seed). These seeds were multiplied to produce DH₂, used in the preliminary yield in the next year. The results demonstrated the potential of this method to produce a homozygous line within a short period (2-3 years) by doubling the haploid line generated through pollination of spring bread wheat F₁ with maize.

In this work, an analog front-end (AFE) circuit for Electrocardiogram (ECG) detection system has been designed, implemented, and investigated in an industry-standard Cadence simulation framework using advanced technology node of 45 nm. The AFE consists of an instrumentation amplifier, a Butterworth band-pass filter (with fifth-order low-pass and second-order high-pass sections), and a second-order notch filter- all are based on two-stage, Miller-compensated operational transconductance amplifiers (OTA). The OTAs have been designed employing the $g_m/I_D$ methodology. Both the pre-layout and post-layout simulation were carried out. The layout consumes an area of 0.0058 mm$^2$ without the resistors and capacitors. Analysis of various simulation results were carried out for the proposed AFE. The circuit demonstrates a post-layout bandwidth of 239 Hz with a variable gain between 44 to 58 dB, a notch depth of -56.4 dB at 50.1 Hz, a total harmonic distortion (THD) of -59.65 dB (less than 1\%), an input referred noise spectral density of $

Particulate Organic Carbon (POC) plays a crucial role in the marine carbon cycle, influencing carbon flux and many important ocean biogeochemical processes in the Bay of Bengal. The purpose of this study was to examine the seasonal and annual variability of POC in the Bay of Bengal (BoB) region and its correlation with Sea Surface Temperature (SST) and Chlorophyll-a (Chlor_a). This study uses level-3 POC, Chlor_a, and SST data from the Moderate Resolution Imaging Spectroradiometer (MODIS) Aqua satellite. The surface POC concentration in the Bay of Bengal declined at a rate of -1.30 mgm^-3y^-1 over a ten-year period (2003-12) and ranged from 86.48 mgm^-3 to 110.93 mgm^-3 with an average of (93.74±7.50 mgm^-3). Seasonally, the mean POC was highest (97.40 mgm^-3) during the post-monsoon (October-November) and lowest (79.36 mgm^-3) in the pre-monsoon (March-May). Seasons were observed to have statistically significant differences in POC concentration in the study area (F_(3,2155) = 6.298; p <0.05). A strong positive correlation between POC and Chlorophyll was observed whereas a week positive correlation between POC and SST was observed. POC was observed to be very prominent in post-monsoon (97.40 mgm^-3) and in northeast-monsoon (97.14 mgm^-3) and moderate to low in southwest (81.12 mgm^-3) and pre-monsoon (79.36 mgm^-3). The Bay of Bengal’s annual mean POC:Chlor_a ratio ranged from 97.56 mgm^-3 to 332.89 mgm^-3, indicating a significant impact of biological processes on POC composition. To see how POC fluctuation affects biogeochemical processes in the Bay of Bengal, deeper investigation is required.

Dehydration of hydrogen gas is one of the important steps in many industrial purposes thus, drying systems have been developed with high-efficiency and relative effect. In this article, the basic principles and design of a three-bed TSA (Temperature Swing Adsorption) dryer for dehydration operation of hydrogen gas drying are described in detail. The text commences with an in-depth explanation of the basic principles behind TSA technology such as adsorption and desorption mechanisms, thermodynamic considerations and material selection for adsorbents. This paper also deals with the detailed design of a three-bed TSA dryer, explaining about various fabricating details that influences both performance and total operability. The third part focuses the operational phase, and especially in cycle time, regeneration strategy and efficiency of energy. Advanced optimisation techniques are employed to lower energy consumption, increase throughput capacity and improve overall system. This detailed study will be of great help for engineers and investigators working on TSA systems design and optimization to dehydrate hydrogen gas, contributing towards the betterment in this important field dealing with industrial gas processing.

Background: Low-income families often depend on fuels such as wood, coal, and animal dung for cooking. Such solid fuels are highly polluting and are a primary source of indoor air pollutants (IAP). We examined the association between solid fuel use (SFU) and acute respiratory infection (ARI) among under-five children in Afghanistan and the extent to which this association varies by socioeconomic status (SES) and gender. Materials and Methods: This is a cross-sectional study based on de-identified data from Afghanistan’s first standard Demographic and Health Survey conducted in 2015. The sample consists of ever-married mothers with under-five children in the household (n=27,565). We used mixed-effect Poisson regression models with robust error variance accounting for clustering to examine the associations between SFU and ARI among under-five children after adjusting for potential confounders. We also investigated potential effect modification by SES and sex. Additional analyses were conducted using an augmented measure of the exposure to IAP accounting for both SFU and the location of cooking/kitchen (High Exposure, Moderate, and No Exposure). Results: Around 70% of households reported SFU, whereas the prevalence of ARI was 17.6%. The prevalence of ARI was higher in children living in households with SFU compared to children living in households with no SFU (adjusted prevalence ratio [aPR]= 1.10; 95%CI: 0.98, 1.23). We did not observe any effect modification by SES or child sex. When using the augmented measure of exposure incorporating the kitchen’s location, children highly exposed to IAP had a higher prevalence of ARI compared to unexposed children (aPR 1.17; 95% CI: 1.03, 1.32). SES modified this association with the strongest associations observed among children from the middle wealth quintile. Conclusion: The findings have significant policy implications and suggest that ARI risk in children may be reduced by ensuring clean cookstove as well as clean fuels and acting on the socio-environmental pathways.

Despite the expansion of financial institutions and proliferation of mobile financial services, reaching the unbanked and bringing them under formal financial services has become a policy concern in many developing countries. Due to the lack of financial accounts, unbanked people prefer informal, risky, and inconvenient mechanisms for receiving, sending and transferring money. Previous studies rely much on common intervention like no account maintenance and opening fees, easy documentation processes and money subsidies for opening financial accounts. This study aims to examine the impact of the motivational workshop on opening savings accounts through causality among the unbanked people in a setting where the respondents are unbanked despite having all the requirements and many institutional offers for opening savings accounts. We encouraged the unbanked people through a one-hour-long motivational workshop to open saving account. Based on our cross-sectional data and randomized controlled trial experiment among 505 unbanked Village Defense Party (VDP) members at Dhubil Union under Sirajganj in Bangladesh, we have the evidence that motivational workshop positively impacts opening ac-counts by 32.33 percent. However, the account opening rate differs in terms of respondent’s pref-erence for financial institutions. Our study also finds that unbanked people have the highest pref-erence for mobile financial services for opening accounts resulting in 15.33 percent. The result of the study has some policy implications for adopting effective strategies of financial access in many developing countries.

Zinc oxide (ZnO) as a semiconductor in its crystalline or amorphous form is still a promised material, especially under isobaric and isothermal ensembles. In this work, Parallel and Equilibrium Molecular Dynamics and DL_POLY_4 software are employed to predict the relationship between the behavior of ZnO chemical bonds and the phase transition literatures, using correlation function g(r) of Zn-Zn, Zn-O, and O-O pairs. Our system is composed of 5832 atoms of ZnO rocksalt structure (2916 atoms of Zn2+ and 2916 atoms of O2-), under the temperature of 300 (K) and the range of pressure 0-400 (GPa). The lengths of ZnO bonds, the standard error, standard deviation, the maximum of g(r), and the percentage of the variation of the bonds are analyzed. The interatomic interactions are modeled by the potential of Buckingham for short-range and Coulomb for long-range interactions. The calculations were run on the RAVEN Supercomputer of Cardiff University (UK). Our data are mostly in the vicinity of available information of bonds lengths; the rest can be deduced from the pressure of phase transition to use it as a new approach of phase transition confirmation. However, the rest of our results are still a prediction because of no results under extended pressure used in this work.

The permeation of dioxin-like pollutants, namely, chlorinated dibenzodioxins and dibenzofurans, through lipid membranes has been simulated using classic molecular dynamics (CMD) combined with the umbrella sampling approach. The most toxic forms of chlorinated dibenzodioxin and dibenzofuran, 2,3,7,8-tetrachloro-p-dibenzodioxin (TCDD) and 2,3,7,8-tetrachlorodibenzofuran (TCDF), and a dioleyl-phosphatidylcholine (DOPC) lipid membrane of 50 Å wide have been chosen for our study. The free energy profile shows the penetration process is largely favoured thermodynamically (DG≈-12 kcal/mol), with a progressively decrease of the free energy until reaching the energy minima at distances of 8Å and 9.5Å from the centre of the membrane for, respectively, TCDD and TCDF. At the centre of the membrane, both molecules display subtle local maxima with free energy differences of 0.5 and 1 kcal/mol with respect to the energy minima for TCDD and TCDF, respectively. Furthermore, the intermolecular interactions between the molecules and the lipid membrane have been characterized at the minima and the local maxima using hybrid quantum mechanics/molecular mechanics energy decomposition analysis (QM/MM-EDA). Total interaction energies of -17.5 and -16.5 kcal/mol have been found at the energy minima for TCDD and TCDF, respectively. In both cases, the dispersion forces govern the molecule-membrane interactions, no significant changes have been found at the local maxima, in agreement with the classical free energy profile. The small differences found in the results obtained for TCDD and TCDF point out the adsorption and diffusion processes through the cell membrane are not related to the different toxicity shown by these pollutants.

In this paper, we introduce the notions of nearly Sasakian and nearly Kähler statistical structures with a non-trivial example. The conditions for a real hypersurface in a nearly Kähler statistical manifold to admit a nearly Sasakian statistical structure are given. We also study Invariant and anti-invariant statistical submanifolds of nearly Sasakian statistical manifolds. At the end, some conditions under which such a submanifold of a nearly Sasakian statistical manifold is itself a nearly Sasakian statistical manifold are given.

Accurate diagnosis at an early stage of infection is essential for the successful management of any contagious disease. The COVID-19, caused by the SARS-CoV-2 virus is a pandemic that has affected 214 countries affecting more than 30.8 million people causing 0.957 million deaths as of third week of September, 2020. The primary diagnosis of the infection is done either by the molecular technique of RT-qPCR by detecting portions of the RNA of the viral genome or through immunodiagnostic tests by detecting the viral proteins or the antibodies produced by the host. As the demand for the test increased rapidly many naive manufacturers entered the market with novel kits and more and more laboratories also entered the diagnostic arena making the test result more error-prone. There are serious debates globally and regionally on the sensitivity and specificity of these tests and about the overall accuracy and reliability of the tests for decision making on control strategies. The significance of the test is also complexed by the presence of asymptomatic carriers, re-occurrence of infection in cured patients as well as by the varied incubation periods of the infection and shifting of the viral location in the host tissues. In this paper, we review the techniques available for SARS-CoV-2 diagnosis and probable factors that can reduce the sensitivity and specificity of the different test methods currently in vogue. We also provide a check-list of factors to be taken care to avoid fallacious practices to reduce false positive and false negative results by the clinical laboratories

Hospital readmission and length of stay prediction provide info to manage hospitals’ bed capacity and the number of required staff, especially during pandemics. We present a hybrid deep model called Genetic Algorithm-Optimized Convolutional Neural Network (GAOCNN) with a unique preprocessing method to predict hospital readmission and the length of stay in patients having various conditions. GAOCNN uses one-dimensional convolutional layers to predict hospital readmission and length of stay. The parameters of the layers are optimized using a genetic algorithm. To show the performance of the proposed model in patients with various conditions, we evaluate the model under three healthcare datasets; the Diabetes 130-US hospitals dataset, the COVID-19 dataset, and the MIMIC-III dataset. The diabetes 130-US hospitals dataset has information on both readmission and the length of stay, while COVID-19 and MIMIC-III datasets just include information on the length of stay. Experimental results show that the proposed model’s accuracy for hospital readmission is 97.2% for diabetic patients. Also, the accuracy of the length of stay prediction is 89%, 99.4%, and 94.1% for diabetic, COVID-19, and ICU patients, respectively. These results confirm the superiority of the proposed model compared to existing methods. Our findings offer a platform for managing healthcare funds and resources for patients with various diseases.

Photovoltaic is one of the promising renewable sources of power to meet the future challenge of energy need. Organic and perovskite thin film solar cells are an emerging cost-effective photovoltaic technology because of low-cost manufacturing processing and a light-weight. The main barrier of commercial use of organic and perovskite solar cells is the poor stability of devices. Encapsulation of these photovoltaic devices is one of the best ways to address this stability issue and enhance the device lifetime by employing materials and structures that possess high barrier performance for oxygen and moisture. The aim of this review paper is to find different encapsulation materials and techniques for perovskite and organic solar cells according to the present understanding of reliability issues. It discusses the available encapsulate materials and their utility in limiting chemicals such as water vapour, oxygen penetration. It also covers the mechanisms of mechanical degradation within the individual layers and solar cell as a whole, and possible obstacles to their application in both organic and perovskite solar cells. The contemporary understanding of these degradation mechanisms, their interplay and their initiating factors (both internal and external) are also discussed.

Conclusions: The quantitative method provides a large-scale overview of the biometry measurements of an entire practice. Image audits can then be focused on sonographers whose measurements are outliers, avoiding the time, complexity, and expense of auditing those whose measurements fall within the expected range. We encourage commercial software developers to include tools in their ultrasound reporting software to facilitate such quantitative review.

Since the start of the COVID-19 pandemic, the world has witnessed a digital revolution that has transformed the way information are broadcast and consumed. This rapid evolution was accompanied by an “infodemic” (Beaulieu, 2019), a transformation of workplaces (Lulli LG, 2021)and difficulties in managing information flows (Bendahan & Nader, 2020). In this scientific article, we examine the communication strategies adopted by hospital structures as they are perceived by staff, highlighting their psychological and professional experiences throughout the crisis period. The results of the study carried out among hospital staff (n=200) demonstrate that the perception of communication strategies is generally positive for 78.56% of participants (M=1.85). The assessments of the staff interviewed as for the effect of this communication on the psychological experience and on the management of professional tasks have a positive trend respectively (M=2.15) and (M=1.86)

Angiogenesis is a term that describes the formation of new blood and lymphatic vessels from a pre-existing vasculature. This allows tumour cells to acquire sustenance in the form of nutrients and oxygen and the ability to evacuate metabolic waste. As one of the hallmarks of cancer, angiogenesis has been studied extensively in animal and human models to enable better understanding of cancer biology and the development of new anti-cancer treatments. Angiogenesis plays a crucial role in the process of tumour genesis, because solid tumour need a blood supply if they are to grow beyond a few millimeters in size. On the other hand, there is growing evidence that some solid tumour exploit existing normal blood supply and do not require a new vessel formation to grow and to undergo metastasis. This review of the literature will present the current understanding of this intricate process and the latest advances in the use of angiogenesis-targeting therapies in the fight against cancer.

(1) Background: Various cutaneous adverse drug reactions (ADRs) are observed with the development of mRNA COVID-19 vaccines. To gain insight into the clinicopathologic features, we analyzed the correlation of histological and clinical data in 48 patients with these ADRs.; (2) Methods: Single-center retrospective study in patients with ADRs post-mRNA COVID-19 vaccination (mRNA-1273 and BNT162b2 vaccines).; (3) Results: Distant generalized ADRs prevailed (91%), often appearing clinically as spongiotic dermatitis or maculo-papular exanthema. Histopathological analysis revealed spongiotic changes (46%) and dermal superficial perivascular lympho-histiocytic infiltrates (17%). Eosinophils were found in 66% of biopsies, neutrophils in 29%, and plasma cells only in 8% of biopsies. Most ADRs occurred post-second vaccine dose (44%). Histologically spongiotic changes were associated with clinical features of spongiotic dermatitis in only 50% and maculo-papular exanthema in the remaining patients. ADRs represented an aggravation of preexisting skin disease in 23% of patients. ADRs regressed within 28 days or less in 53% of patients and persisted beyond a month in the remaining patients.; (4) Conclusions: Our study demonstrates a diverse spectrum of generalized ADRs, revealing correlations between histology and clinical features but also instances of divergence. The majority of ADRs are self-limited with a few extending beyond a month.

In the industrial sector, the financial gain is generally considered at the cost of environmental degradation. The environmental protection and economic benefit are common conflicting objectives in many optimization problems. In any multi-criteria problem, the most challenging part is to optimize the conflicting goals. But if these objectives become non-conflicting, then the problem can be solved with ease. This paper is all about minimizing the environmental impact of industrial processes while maximizing the net economic benefit. There is a general misconception of linking the environmental protection with a financial loss. This is not always true; the Eco-Efficiency or Cleaner Production Technology (CPT) is a perfect example to disprove this notion. Economics of CPT regarding water savings for the textile-processing sector in Pakistan has been analyzed in this paper. Changes in water use before and after the implementation of water conserving technologies in the textile sector of Pakistan from a study conducted by the Cleaner Production Institute (CPI) are utilized to perform a cost-benefit analysis. Direct financial benefits that could be achieved through the application of these technologies are presented only. Other environmental benefits, though not described here, are of no less importance. The study results reveal that very high potential of water savings exists for most of the investments on CPT.

Sustainable water resource management in Bangladesh's Gumti River Basin faces challenges from climate change, urbanization, and population growth. This study aimed to calibrate and validate the HEC-HMS model for the Gumti River to enhance flood prediction and water resource planning. The model was set up using precipitation, temperature, and discharge data from 2019-2021, with SRTM elevation data for catchment delineation. Manual calibration was performed for 2019-2020, followed by validation for 2021, using parameters such as Muskingum routing and SCS Curve Number. Model performance was evaluated using R², Nash-Sutcliffe efficiency (NSE), RSR, and PBIAS metrics. Results showed satisfactory to good performance, with R² values of 0.64 and 0.68 for calibration and validation, respectively. NSE values were within the satisfactory range, while PBIAS indicated very good performance with slight underestimation. The study concludes that the calibrated HEC-HMS model provides a reliable tool for simulating the Gumti River's hydrology, though there's room for improvement. Integration with flood frequency analysis, water quality monitoring, and climate change projections is recommended for comprehensive water resource management, alongside the implementation of Sustainable Water Resource Management principles and community engagement strategies.

The details of antigen-antibody interactions and the identification of epitopes are critical for the development of monoclonal antibody drugs. Ab42 is a native human-derived anti-CFH monoclonal antibody. In this study, the interaction between antigen pCFH and antibody (Ab42) was theoretically demonstrated by molecular docking and MD simulation, combined with free energy calculation and computational alanine scanning (CAS), and key amino acids and epitopes were identified. Experimental alanine scanning (EAS) was then carried out to verify the results of the calculation, and our results indicated that Ab42 antibody forms hydrogen bonds and interacts hydrophobically with pCFH through the Tyr315, Ser100, Gly33, and Tyr53 residues on its CDR, while the main pCFH epitopes are located at the six sites of Pro441, Ile442, Asp443, Asn444, Ile447, and Thr448. In conclusion, this study has explored the mechanism of antigen-antibody interaction from both theoretical and experimental aspects, and our results have important theoretical significance for the design and development of relevant antibody drugs.

A cross-sectional study was carried out to determine the prevalence of subclinical mastitis (SCM) among medium to large scale household dairy farms in southwestern district, Jhenaidah, Bangladesh during July to December 2019. A total of 78 (n=100) lactating cows from household dairy farms (N=32) having three or more dairy cows were selected randomly as sampled populations. Milk samples were screened for SCM by using Surf Field Mastitis Test (SFMT). The prevalence of SCM varied among farm level [71.9% (95% CI: 53.3-86.3)], individual animal level [67.9% (95% CI: 56.4-86.3)] and quarter level [29.5% (95% CI: 24.5-34.9)]. Descriptive statistics represented the farmers and farm demography, characteristics of the sampled population, and overall management feature. Random Effect Logistic Regression identified, Body Condition Score (BCS) [OR=3.8 and 2.9, at cows level and quarter level respectively (BCS-2 vs. BCS-≥3)], and breed [OR=5.1 and 2.9, at cows level and quarter level respectively (HF× Sahiwal vs. HF × Local)] as potential risk factors. This study shows that SCM is highly prevalent in the study area, which is a major threat to the dairy industry's production performance. Regular screening by SFMT, proper hygiene, improve the management system, and farmer’s awareness is required to control the disease.

Since the first coronavirus patient was identified in Bangladesh on March 8, the most controversial issue is about the exact level of the infection in Bangladesh. Conformity with the population density the number of COVID-19 tests is inadequate. As the number of tests increases, so does the number of infections, making it difficult to predict the spread of COVID-19 in Bangladesh. In this case, the unplanned initiatives are particularly responsible in other for unplanned measures, lack of public awareness, and lack of proper knowledge. In this case, the Ministry of Health has made three major mistakes, three important features of the medical system in Bangladesh have been mentioned. It is more effective to prevent COVID-19 by isolating the infected person by further testing COVID-19 until effective treatment is available and to provide adequate and effective masks and personal protective equipment (PPE). In this case, the COVID-19 testing kit invention has received a good response in many countries of the world. This study focuses on the comprehensive data verification, selection, and evaluation of COVID-19 in Bangladesh and its implications for the future, what to do to address and prevent the COVID-19 challenge, and effective treatment against the coronavirus (COVID-19). It is hopeful that the discussion of the material mentioned in this research paper will help to strike a balance between the government, citizens, and experts which will be feasible in improving the current situation in COVID-19 Bangladesh and reducing its severity.

Over the last few decades, there is a remarkable increase in air traffic worldwide; however, despite of rapid technological development and improved airport infrastructure, there is still an increasing number of aviation accidents and fatalities. In order to meet safety demands of Air Traffic Control (ATC), Machine Learning (ML) based aircraft conflict detection techniques are focused to predict events before they come to reality. This research presents a systematic literature review (SLR) about the applications of ML techniques in safety prediction of ATC system. Initially, the existing aircraft conflict prediction models are classified into three broad categories; logical, geometric and probabilistic. A formal process of SLR is then conducted which is initiated with preprocessing and effective searching. A series of filtering called title, abstract and objective-based are then applied to extract the most relevant articles. Detailed and critical reviews of selected articles are performed to identify challenges which are segregated into dataset, model and evaluation techniques, furthermore, the optimal solutions for each are proposed. Finally the matrices to map the identified challenged with their proposed solutions are constructed. This research serves as a foundation for future research and towards integration of ML based safety prediction techniques into modern ATC system.

Marangoni flow in foam fractionation in the lamellar film for the interior and exterior of a micro-foam was investigated. The three-dimensional node-film-Plateau Border system was modeled using computational fluid dynamics. The importance of the surfactant concentration of the foam fractionation column and air-liquid interface mobility on the Marangoni velocity in the film was emphasized. The study found that an increase in surfactant concentration in the reflux column significantly increases the Marangoni velocities. Additionally, a mobile interface results in a higher Marangoni flow, while a rigid interface leads to less intensive flow. The behavior of the Marangoni flow in both interior and exterior foam was explored, revealing that the flow in exterior foam has different behavior due to the presence of the wall, which reduces the Marangoni velocity compared to interior films.

Iron supplementation is associated with side effects and thus reduces the intake compliance. Because it has fewer side effects, a recent trial recommended low-iron micronutrient powder (MNP) for the prevention of anemia in Bangladeshi children exposed to a high concentration of iron from drinking groundwater. In the present study, we hypothesize that the low-iron MNP is a potential intervention to prevent childhood anemia in the low groundwater-iron settings in Bangladesh. A cross-sectional study was conducted in Bangladesh with children aged 2-5 years who drank groundwater containing a low level of iron (0-&lt;2 mg/L).The combined intake of iron was calculated from the key sources--diet, groundwater and MNPs. The intakes of iron were compared against the standard reference intake. The children’s hemoglobin was measured using a photometer. Combined intake of iron from dietary, groundwater and low-iron MNP in children was 5.8±2.0 and 6.9±2.5 mg/day comprising 193% and 169% of the Estimated Average Requirement in the 2-3 year-old and 4-5 year-old subgroups, respectively. Combined intake of bioavailable iron from dietary and groundwater sources was 0.42±0.023 and 0.22±0.019 mg/day in children exposed to groundwater concentration 0.8-&lt;2.0 mg/L and 0.0-&lt;0.8 mg/L respectively (p&lt;0.001). The mean concentration of hemoglobin in the respective groups was 12.17±0.94 mg/dl and 11.91±0.91 mg/dl (p=0.30). The combined intake of iron from dietary and groundwater sources was associated with maintenance of hemoglobin concentration at the non-anemic level in most of the children. The finding highlights the potential of low-iron MNP in controlling childhood anemia in this setting.

Dried blood spot (DBS) testing on confetti is one of the most common methods used to collect and extract DNA from field samples for molecular epidemiology of malaria studies. Here, we investigated whether ethanol or other solutions used to clean scissors are a source of sample contamination. DBS were prepared from 3 drops of blood from two Plasmodium falciparum cultures spotted on confetti, and 3 solutions (water, ethanol and DNase) were used to clean scissors between spots during DNA extraction. For each cleaning solution, two blank confetti were used as negative controls. Samples were analyzed by PCR-based genotyping of merozoite surface proteins 1 & 2 (msp-1 and msp-2), and P. falciparum chloroquine resistance transporter (Pfcrt). A total of 15 samples were analyzed. Based on msp-1 and msp-2 amplification, P. falciparum was detected on blank confetti when scissors were washed with ethanol. Based on Pfcrt amplification, DNA of P. falciparum was detected on blank confetti when scissors were cleaned with ethanol or water. No P. falciparum genes were detected on blank confetti when scissors were cleaned with DNase. Scissors cleaned with DNase prevented cross-contamination between samples during processing of dried blood spots, whereas ethanol (which is commonly used) fails to avert cross-contamination.

The present study was carried out at the north-eastern part of Bangladesh to investigate organochlorine pesticide (OCP) residues and microbiological quality of dried barb (Puntius sophore). Samples were collected from both producers and retailers from December 2016 to April 2017. A control sample was also prepared with the same raw fish used by the producers in the laboratory to compare the result. Gas Chromatography with Electron Capture Detector (GC-ECD) was used to detect and quantify OCP residues. Around 22 % (6) samples out of 27 were found contaminated with OCP residues. Among these six adulterated samples, four were from retailers and two from producers. Only Aldrin was detected in four samples and rest two samples were detected with both Aldrin + Dieldrin and Aldrin + Endrin. Aldrin was found between 0.332 to 0.967 ppm, Dieldrin 0.762 ppm, and Endrin 0.828 ppm. All these values were much higher than the Maximum Residual Limit (MRL) 0.1 ppm. Aerobic Plate Count (APC) of producer samples were ranged between log5.3 ± 0.02 to log5.4 ± 0.03, log6.2 ± 0.02 to log6.4 ± 0.02 for retailer samples and log5.0 ± 0.03 to log5.2 ± 0.04 for control samples. While fungal count was ranged between log3.2 ± 0.04 to log3.5 ± 0.04, log3.4 ± 0.04 to log3.6 ± 0.03 and log2.2 ± 0.05 to log2.5 ± 0.03 for producer, retailer and control samples respectively. All the producer and retailer samples and one-third of the control samples were found contaminated with Escherichia coli. Whereas, Salmonella sp. was detected as 13.3% in producer samples, 20% in retailer samples except for the control. In case of Vibrio sp., maximum count was found for retailer samples (13.3%), whereas, producer and control samples showed no detection. The finding of the present study revealed the presence of pesticides and poor microbiological quality of dried barb are alarming for the consumers of Bangladesh and which may cause chronic disease and potential long-term risk for human health.

In this paper, we introduce the notion of pointwise hemi-slant submanifolds of nearly Kaehler manifolds. Further, we study their warped products and prove the necessary and sufficient condition that a pointwise hemi-slant submanifold to be a warped product manifold. Also, we prove that every pointwise hemi-slant warped product submanifold $M=M_\perp\times_fM_\theta$ which is mixed totally geodesic in an arbitrary nearly Kaehler manifold $\tilde M$ satisfies $\|h\|^2\geq\frac{2p}{9}\cos^2\theta\|\nabla(\ln f)\|^2,$ where $\|h\|$ is the length of the second fundamental form of $M$ and $2p=\dim M_\theta$; while $\nabla(\ln f)$ is the gradient of $\ln f$ along $M_\perp$. The equality case of this inequality is also given.

Recently, we studied CR-slant warped products B1×fM⊥, where B1=MT×Mθ is the Riemannian product of holomorphic and proper slant submanifolds and M⊥ is a totally real submanifold in a nearly Kaehler manifold. In the continuation, in this paper, we study B2×fMθ, where B2=MT×M⊥ is a CR-product of a nearly Kaehler manifold and establish Chen’s inequality for the squared norm of the second fundamental form. Some special cases of Chen’s inequality are given.

(1) Background: Loss of weight is one of the practices which have been identified as key in reducing the risk of various forms of cancer. Therefore, this study is a systematic review and meta-analysis of studies related to the topic of loss of weight and risk of cancer and addresses the question, ‘does losing weight reduce the risk of cancer?’ Its purpose is to identify current high-quality evidence on such a question and synthesize such evidence before summarizing it given specific data attributes to improve decision-making processes on cancer management. (2) Methods: Research studies were identified from four main databases: PubMed, Science Direct, Google scholar, and Medline. A systematic review and meta-analysis of such studies were then conducted to reveal the most current evidence on the research topic. (3) Results: The studies showed that losing weight reduces cancer risk. Nonetheless, such intervention is not necessarily effective, especially in cases where patients may be at risk of developing cancer due to other risk factors. (4) Conclusions: The current study concludes that there is a need to implement effective interventions such as physical exercise, dietary restrictions, or both that can be effective in reducing weight to reduce the risk of cancer.

Alkaloids are the most diversified nitrogen-containing secondary metabolites having antioxi-dant, and antimicrobial properties and are extensively used in pharmaceuticals to treat different types of cancer. Nicotiana serves as a reservoir of anticancer alkaloids and is also used as a model plant for the de novo synthesis of various anti-cancer molecules through genetic engineering. Up to 4% of the total dry weight of Nicotiana was found to be composed of alkaloids where nicotine, nornicotine, anatabine, and anabasine are reported as the dominant alkaloids. And, among the alkaloids present in Nicotiana, β-carboline (Harmane and Norharmane), Kynurenines are found to show anti-tumor effects, especially in the case of colon and breast cancer. Creating new or shunting of existing biosynthesis pathways in different species of Nicotiana resulted in de novo or increased synthesis of different anti-tumor molecules or their derivatives or precursors includ-ing Taxadiane (~22.5 µg/g), Artemisinin (~120 μg/g), Parthenolide (~2.05 ng/g), Costunolide (~60 ng/g), Etoposide (~1 mg/g), Crocin (~400 µg/g), Catharanthine (~60 ng/g), Tabersonine (~10 ng/g), Strictosidine (~0.23 mg/g), etc. Enrich precursor pool especially Dimethylallyl Diphos-phate (DMAPP) and down-regulating of other bi-product pathways, compartmentalization or metabolic shunting, or organelle-specific reconstitution of the precursor pool might trigger the enhanced accumulation of the targeted anticancer alkaloid in Nicotiana.

Introduction: Alzheimer's disease (AD) is a progressive neurodegenerative disorder characterized by cognitive decline and memory loss, predominantly affecting older adults. Understanding the multifaceted factors contributing to AD is crucial for developing effective prevention and intervention strategies. This narrative review synthesizes current literature on the various factors influencing the development and progression of AD in older adult populations.Methods: A comprehensive search was conducted across electronic databases including PubMed, Web of Science, and PsycINFO using relevant keywords such as "Alzheimer's disease," "risk factors," "genetics," "environmental factors," and "lifestyle." Studies published between 2000 and 2023 were included, focusing on factors associated with AD in individuals aged 65 years and older.Results: The review identified several key factors contributing to AD in older adults. Genetic predisposition, particularly the presence of apolipoprotein E (APOE) ε4 allele, emerged as a significant risk factor. Environmental factors such as air pollution, pesticides, and heavy metals were also implicated. Furthermore, lifestyle factors including physical inactivity, poor diet, and smoking were associated with increased AD risk. Chronic conditions such as diabetes and cardiovascular diseases were found to exacerbate cognitive decline in older adults.Conclusion: This narrative review highlights the complex interplay of genetic, environmental, and lifestyle factors in the development and progression of Alzheimer's disease among older adults. Understanding these factors is crucial for targeted interventions aimed at reducing AD risk and improving cognitive health outcomes in aging populations. Future research should focus on longitudinal studies and personalized medicine approaches to elucidate specific mechanisms underlying AD pathogenesis and to develop effective preventive strategies.

The need for integrated high-frequency systems has increased significantly, leading to the development of efficient antennas operating in the 0.1-10 terahertz (THz) range. Using graphene as the conducting 2D material and hexagonal boron nitride (hBN) as the dielectric substrate, this research effort examines the design and performance evaluation of a THz band antenna functioning on supporting nanotechnology. The researchers contrasted the system’s performance with the 6G wireless network requirements after analyzing the antenna performance, radiation patterns, and impedance matching. According to this research, graphene, along with hBN can enhance antenna performance overall in the THz band and open pathways for advanced communication. The application of the designed antenna in a 6G wireless network will be tested through um MIMO configuration to achieve a higher data rate.