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Portable electronic devices and electric cars use lithium-ion batteries, but clumping lithium alloys limit their lifespan. Due to their strong electronic conductivity, volumetric capacity, and high energy density, researchers are conducting research on electrochemical metal cells utilizing tellurium for high-performance batteries. Theoretically, lithium-tellurium batteries can improve energy densities three times more than lithium-ion batteries. However, metal-tellurium faces challenges such as low rate capability, unclear redox reactions, intermediate dissolution, and electrode volume changes. This study explores the enhancement of the energy storage capacity of next-generation batteries by fabricating coated electrode films as novel anodes from tellurium, silicon, and graphene. Physical, thermal, and morphological analysis of composite material are investigated by XRD, TEM, TGA, DSC, SEM, UV, and XPS analyses, revealing its rigidity as well as durability through its crystal structure alignment and thermal stability. In electrochemical analysis (CV) at various scan rates, samples that exhibit consistent and high specific capacity (Cp) values at different scan speeds (25, 50, and 100 mV/s) indicate excellent ability to store and maintain charge. Decreasing Cp values with increasing scan rates indicate that the speed of cycling limits the charge transfer kinetics and electrode performance. In EIS, the charge transfer resistances (Rct) for the pure Te, Te + Gr, Te + Si + Gr, and Te + Si samples are 759.07 Ω, 4.21 Ω, 36.39 Ω, and 164.90 Ω, respectively. The Te + Gr sample has the lowest Rct, indicating the best charge transfer efficiency at the electrode contact, whereas the Te + Si + Gr sample has a comparatively lower Rct, indicating better charge transfer kinetics. The combined result exhibits the synergistic impact of tellurium, silicon, and graphene in enhancing the energy storage capacity of future batteries across the industry.

Robot is an indispensable technology within the context of the Industrial 4.0 revolution, providing a wide range of applications in industry. The stability of a robot's manipulator is contingent upon its associated manipulator settings, hence influencing its overall quality. The assessment of stability has been examined in prior studies using a limited set of manipulator parameters, leading to a deficient comprehension of this phenomenon. In this study, a mathematical model of a flexible six-link manipulator is formulated using Lagrangian mechanics and various parameters. An innovative mathematical framework is developed to establish a correlation between stability and the motor acceleration and moment of inertia for the Universal Robot (UR5). Furthermore, extensive research has been conducted to examine the correlation between stiffness, damping, and deflection in the context of stability. In spite of this, fuzzy logic inference methods are employed to ascertain the relative significance of stiffness, damping, and deflection with regards to stability. Mathematical approaches are employed to validate the numerical values of several manipulator parameters. The findings of the study demonstrate that there is a positive correlation between motor acceleration and stability, indicating that as motor acceleration grows, stability also increases. Conversely, there is a negative correlation between stability and moment of inertia, suggesting that stability reduces as moment of inertia increases. In the case of stiffness, damping, and deflection, stiffness is the most important factor. When stiffness is high, stability is also high. However, when stiffness is minimal, stability is low. The implications of these findings are expected to have a positive impact on enhancing industrial productivity.

Objectives: Household hygiene and food safety are essential parts of food security; better food safety and hygiene will help reduce the chances of illness for young children and family members rarely studied in the selected area of coastal Bangladesh. The study aimed to discover the knowledge, attitude, and practice levels for cleanliness, hygiene, and food safety in the household. Methods: In this study, we employed a cross-sectional survey with simple random sampling to collect data from 384 childbearing mothers. The survey used the pretested, validated, and standardized (knowledge, attitude, and practice) questionnaire-model-based interview guide. Results: According to our study analysis, the knowledge, attitude, and practice scores among mothers were inadequate for household cleanliness and hygiene management. In the area context, knowledge efficiency was related to family type (joint and nuclear). Family economic conditions strongly influenced mothers’ attitudes and behavior toward knowledge, attitude, and practice score. Unemployed and illiterate mothers have lower knowledge, attitude, and practice scores. Educated mothers have better knowledge, attitude, and practice score compared to illiterate mothers ( p

This study aims to investigate the construction of professional identity among Bangladeshi university English as a Foreign Language (EFL) teachers and its influence on classroom performance. Employing a qualitative case study approach, data were gathered through semi-structured interviews and classroom observations. Interviews were conducted with two Bangladeshi university teachers who have significant experience in EFL teaching. The interview questions were designed based on the language teachers’ identity formation model, focusing on factors relevant to foundational competences. Content analysis was employed to analyze the collected data and identify emergent themes. The findings indicate that proficiency in language skills, contextual knowledge, self-awareness, disciplinary knowledge, and classroom management skills play pivotal roles in reshaping the professional identities of Bangladeshi university EFL teachers. Classroom observations revealed the strategies employed by these teachers in language use, pedagogical approaches, and classroom management to construct their professional identities. Despite aspirations to conduct classes solely in English, teachers often resorted to using the students' mother tongue for better comprehension. Based on these findings, the study suggests a focus on diverse teacher education programs in Bangladesh to produce more proficient teachers.

Abstract Alzheimer's disease, often known as dementia, is a severe neurodegenerative disorder that causes irreversible memory loss by destroying brain cells. People die because there is no specific treatment for this disease. Alzheimer's is most common among seniors 65 years and older. However, the progress of this disease can be reduced if it can be diagnosed earlier. Recently, artificial intelligence has instilled hope in the diagnosis of Alzheimer's disease by performing sophisticated analyses on extensive patient datasets, enabling the identification of subtle patterns that may elude human experts. Researchers have investigated various deep learning and machine learning models to diagnose this disease at an early stage using image datasets. In this paper, a new Deep learning (DL) methodology is proposed, where MRI images are fed into the model after applying various pre‐processing techniques. The proposed Alzheimer's disease detection approach adopts transfer learning for multi‐class classification using brain MRIs. The MRI Images are classified into four categories: mild dementia (MD), moderate dementia (MOD), very mild dementia (VMD), and non‐dementia (ND). The model is implemented and extensive performance analysis is performed. The finding shows that the model obtains 97.31% accuracy. The model outperforms the state‐of‐the‐art models in terms of accuracy, precision, recall, and F‐score.

Le charançon du riz figure souvent en tête de liste des principaux destructeurs de semences, causant des pertes économiques aux agriculteurs marginaux. Les méthodes conventionnelles impliquant des traitements chimiques pour atténuer ce problème présentent des risques environnementaux et sanitaires. Une expérience a été menée au laboratoire BRRI, Rangpur, pour évaluer l'efficacité de différentes parties du neem, de l'huile de neem et du naphtalène pour la gestion du charançon du riz. Un total de six traitements ont été effectués, dont un contrôle non traité (T1), selon une conception complètement randomisée (CRD) avec trois répétitions. Les traitements étaient les suivants : T2 = 5 feuilles de neem entières séchées, T3 = 0,25 ml d'huile de neem, T4 = 0,25 g de poudre de feuilles de neem, T5 = 0,25 g de mélange de feuilles de neem et de poudre de graines, T6 = 0,25 g de naphtalène et T7 = 0,25 g de poudre de graines de neem. Les résultats ont indiqué que T6 (76,67%) et T3 (66,67%) ont montré de meilleures performances en termes de mortalité des insectes, suivis de T5 (53,33%) et T7 (46,67%). Le plus petit nombre de F1 a émergé à T3 (14,00) et T6 (16,67), suivis de T5 (28,33) et T7 (31,33) en termes d'émergence de F1, indiquant leur efficacité dans le contrôle des capacités de reproduction des charançons du riz. Cependant, concernant la germination des graines, une germination des graines plus élevée a été trouvée à T5 (83,33%), T7 (83,00%), T6 (82,67%) suivi de T4 (80,33%) et T3 (79,33%). Les pourcentages de germination des graines par rapport aux témoins varient de 10 à 30. Les résultats expérimentaux suggèrent que l'utilisation d'insecticides synthétiques sur le riz de stockage peut être réduite en utilisant du naphtalène, de l'huile de neem, une combinaison de feuilles de neem et de poudre de graines, et de la poudre de graines de neem pour la gestion du charançon du riz.

This article represents an analysis of the performance of multi-layer surface plasmon resonance (SPR) biosensors in detecting the transferable human SARS-CoV-2 Omicron (B.1.1.529) variant. The proposed multi-layer SPR biosensor performance is enhanced by integrating fine-tuning prisms, plasmonic metals, and two-dimensional (2D) transition metal dichalcogenides (TMDs) materials. To evaluate the performance of the multi-layer SPR sensor, the transfer matrix method (TMM) is employed. In numerical result, the proposed (CaF2/Cu/BP/Graphene) structure demonstrates the most favorable sensitivity and detection accuracy, characterized by a 410° angle shift sensitivity/refractive index unit (RIU). Additionally, the sensor achieves a detection accuracy (DA) of 0.4713, a quality factor (QF) of 94.25 RIU−1, a figure of merit (FOM) of 91.87, and a combined sensitivity factor (CSF) of 90.36. The presented sensor is also capable of detecting target biomolecule binding interactions between ligands and analytes at a range of concentrations (from 0 nM to 1000 nM), implying its potential use for detecting the omicron virus strain. The outcomes highlight the effectiveness of the presented sensor for real time, and label free detection, particularly in identifying the Omicron viral strain. Eventually, this research promises advanced biosensor technology, crucial for rapid viral variant detection and diagnostics.

Excellent characteristics and a wide range of applications made nanotechnology a key focus for modern researchers. However, environment-friendly and cost-effective measures still need to be taken to synthesize nanoparticles. This research focused on synthesizing Green Ceramic-based Nanoparticles (GCNPs) using the sol-gel method. This method is environment-friendly and cost-effective. Different analytical techniques were employed to characterize the obtained GCNPs. Crystallographic parameters were obtained through the X-ray diffraction (XRD) analysis. Morphological analysis was performed by Field Emission Scanning Electron Microscope (FESEM) analysis. The presence of different elements was identified by elemental analysis (EDX). Various functional groups present in the GCNPs were identified by Fourier Fourier-transformed infrared Spectroscopy (FTIR) analysis. XPS and zeta potential analyses composition characterization and surface charge stability, respectively. Antibacterial strains against E. coli were performed. The FTIR analysis confirmed the presence of different organic compounds in the synthesized GCNPs which helped to increase bacterial inhibition in the antibacterial test. The FESEM images confirmed irregularity in the shape and aggregation of the synthesized GCNPs. The minimum average particle size was obtained from sample S2 which is 376.35 nm. EDX analysis confirmed the presence of silicon particles in the GCNPs. The crystalline nature of the GCNPs was assured by XRD analysis. The silicon percentages were higher than the other atoms shown by the XPS analysis. A significant amount of bacterial inhibition which was 18.0 mm obtained from sample S3. Finally, GCNPs were prepared, characterised, and significantly applied for diverse implementation for the safety of the healthcare field on a broad scale.

Herein, the LiMn2O4 (LMO) cathode was modified using ultrasonic-assisted electrochemically synthesized graphene to enhance lithium-ion batteries' charging and discharging performance. Graphene was synthesized from graphite using an electrochemical exfoliation process in which 0.1 M molar (NH4)2SO4 was utilized as the electrolyte with +10 to +12V DC power, followed by ultrasonication in acetone for 2 h. The FESEM, EDX, XRD, Raman, FTIR, UV–vis, and TGA results suggested that ultrasonically treated graphene (EG1) is superior to electrochemically exfoliated graphene (EG2). Thus, EG1 was used to modify the LMO cathode to fabricate lithium-ion batteries. Afterward, the electrochemical performances of the LMO and LMO/EG1 cathode batteries were investigated. Surface morphological analysis revealed that EG1 is composed of two-dimensional, planar, brighter, and less oxidized graphene nanosheets with an average particle size of 18.02 nm. XRD results exhibited that EG1 has a smaller crystalline size and a thinner average stacking thickness of its layered structure than EG2. According to Raman analysis, the intensity ratio I2D/IG of EG2 and EG1 were 0.70 and 0.81, respectively, deduced that both are multi-layered graphene structures; however, EG1 contains a lesser number of graphene layers than EG2. The electrochemical analysis showed that LMO/EG1 cathode batteries have 89 % coulombic efficiency at 0.1C, while LMO batteries have only 81 %. The discharge capacity retention rate of the LMO batteries was 71.4 %, while it was 94.8 % for LMO/EG1 after observing 100 cycles at 0.1 C. Therefore, LMO/EG1 has excellent cycle stability and electrochemical performance and could potentially enhance the performance in hybrid automotive and electronic devices.

Rice stands as one of the most water-intensive crops in agriculture, demanding a substantial volume of water annually for cultivation in Bangladesh. To address this considerable water requirement, the International Rice Research Institute (IRRI) introduced the alternate wetting and drying (AWD) irrigation method. This approach necessitates consistent manual oversight to maintain the desired water levels in the field. In pursuit of reducing this manual effort, a study was conducted at Bangabandhu Sheikh Mujibur Rahman Agricultural University. The study aimed to develop an automated version of the AWD irrigation system, assess its impact on plant growth and yield-contributing factors, and investigate water use efficiency through using that automated system. The automated AWD system incorporated water level controllers, solenoid valves, and water level detection probes to regulate water levels in the paddy field. The experiment followed a Randomized Complete Block Design (RCBD) with three treatments: T1 (Conventional Irrigation - CI), T2 (AWD), and T3 (Automated Alternate Wetting and Drying - AAWD), each replicated four times. The findings indicated minimal variation in growth and development parameters of the rice plants between the CI and AWD treatments. Likewise, yield components demonstrated no significant differences among the various treatments. Notably, the treatment with automated alternate wetting and drying (AAWD), namely T3, displayed the highest water use efficiency (WUE) at 65.20 kg/ha/cm, while the lowest WUE of 52.56 kg/ha/cm was observed in the conventional irrigation (CI) treatment T1. The results underscore the clear advantage of adopting an automated AWD system, yielding a 20% reduction in irrigation water usage compared to the conventional approach. This transition also minimizes the need for labor-intensive interventions in the paddy fields of Bangladesh, illustrating the potential for more efficient and sustainable rice cultivation practices.

Titanium and its alloys are commonly used in dental applications due to its superior mechanical properties, corrosion resistance, and biocompatibility. However, infection may reduce its lifetime and cause dental-related infections. This research work has been performed to improve the antibacterial and antifungal performance of the synthesized composite. To do so, Ag2O has been added with TiO2 to manufacture silver titanium composite by sintering method. The composite samples underwent Scanning Electron Microscope (SEM), X-ray diffraction (XRD), and antimicrobial and antifungal analyses. The SEM images have confirmed the proper distribution of Ag2O in the samples. Percentages of crystallinity were determined by XRD analysis, which established the crystallinity of the manufactured samples. The maximum percentage of crystallinity was obtained from sample 1 which was 89.33%. The zone of inhibition confirmed excellent antibacterial and antifungal properties from all the samples. Zone of inhibition was obtained 20 mm against the gram-positive S. aureus bacterium. Besides, a 20 mm inhibition zone was also obtained against Aspergillus niger. The manufactured composites can be good candidates for dental applications based on the results and analysis.

Background Global challenges of hunger, food insecurity, and malnutrition persist, with nearly one in three people lacking sufficient food access. The COVID-19 pandemic exacerbated these issues, particularly in Africa, where 59.6% of the population grapples with food insecurity. Malawi faces high stunting and anaemia rates in children, driven by poverty, inadequate health services, and improper diet. Despite progress, the prevalence remains above regional averages. Research reveals imbalanced diets in Malawi, primarily reliant on maize, risking micronutrient deficiencies. This study examines diet affordability in the context of rising costs and low incomes, aiming to influence policy in addressing undernutrition in Malawi and highlighting the overlooked role of affordability in nutrition access. Objectives This assessment aimed to estimate the minimum cost of a nutritious diet using locally available and culturally acceptable food items in Malawi. The objective was to explore how economic constraints affect Malawian households, particularly the poor and ultra-poor, in accessing such diets. Additionally, it sought answers to questions about cost changes over 12 months and affordability among different wealth groups in the country. Methods This study involved secondary data analysis by employing the Cost of the Diet (CotD) research method and software. The World Food Programme’s Minimum Expenditure Basket (MEB) provided monthly food prices for 28 items from April 2021 to March 2022. Comparing the cost of a nutritious diet with per capita income from the Malawi Poverty Report, we estimated the affordability gap. Food price data was from 77 markets in 25 districts, ensuring national representation. Results The annual cost of a culturally acceptable nutritious diet for a five-person household from April 2021 to March 2022 was MWK 84,658/month (≈$103). The diet’s cost increased by 25% during the period, from MWK 2,519 to MWK 3,140 per day. Only average urban households had sufficient income to afford the diet, with a 9.7% surplus. Ultra-poor, poor, rural, and average Malawian households faced affordability gaps of 139.5%, 61.4%, 48.5%, and 32%, respectively. Closing the affordability gap would require additional monthly income of 29,134 kwacha (≈$35.5) for an average Malawian household, 37,481 kwacha for a typical rural household, 42,452 kwacha for a poor household, and 58,885 kwacha for an ultra-poor household. Conclusion The CotD assessment revealed a significant increase in the cost of a nutritious diet over the past 12 months. Most of the population cannot afford the cheapest nutritious diet. The recent currency devaluation may worsen the situation. Cash, voucher or food distribution could help close the affordability gap for poor and ultra-poor households. Regular monitoring and ongoing updates of the CotD results are necessary for informed decision-making.

ABSTRACT: The study examined how adding phytase to nonphytate phosphorus (NPP) diets affected performance, egg quality, reproductive hormones, and plasma biochemical indices in 73- to 80-wk-old laying hens. Six treatments with 5 replicates of 18 Hy-Line brown laying hens each were randomly assigned. Three isonitrogenous, isocaloric diets containing consistent calcium levels (3.8%) were formulated to contain 0.20, 0.25, and 0.30% NPP, treated with or without phytase supplementation (1,000 FYT per kg feed, Ronozyme HiPhos-L, Aspergillus oryzae 6-phytase). The results showed that the addition of phytase to the diet containing 0.20, 0.25, and 0.30% NPP increased egg production by 1.50, 1.64, and 0.97%, respectively, and improved eggshell thickness. Also, use of phytase in the diet contain 0.25, and 0.30% NPP increased the plasma concentration of albumin (ALB), high-density lipoprotein (HDL), phosphorus (P), and plasma follicle‐stimulating hormone (FSH), plasma calcium (Ca), estradiol‐17β (E2β), and luteinizing hormone (LH). In contrast, the egg weight, feed intake, egg mass, feed conversion ratio, albumen height, Haugh unit, yolk, and shell color were unaffected. It can be advisable to use phytase supplementation in an elderly laying hen's diet contain 0.25, and 0.30% NPP to improve shell quality and positively impact reproductive hormones leading to the persistence of egg production.

Alkene epoxidation with TBHP as an oxidising reagent using heterogeneous Mo(VI) catalyst is an environmentally friendly process since it eliminates acid waste and chlorinated by-products often associated with the conventional industrial method that uses stoichiometric peracid such as peracetic acid and m-chloroperbenzoic acid. Polybenzimidazole supported Mo(VI) complex, i.e., PBI.Mo has been successfully prepared, characterised and assessed for the epoxidation of 1,5-hexadiene in the presence of tert-butyl hydroperoxide (TBHP) as an oxidising reagent. A quadratic polynomial model has been developed, demonstrating the yield of 1,2-epoxy-5-hexene in four independent variables. The effects of different parameters such as reaction temperature, feed mole ratio of 1,5-hexadiene to TBHP, catalyst loading, and reaction time were studied. Response surface methodology (RSM) using Box-Behnken Design (BBD) was employed to study the interaction effect of different variables on the reaction response. This study presents the optimization of 1,5-hexadiene epoxidation in a batch reactor using TBHP as an oxidant and a polymer-supported Mo(VI) catalyst.

Corrosion is a major issue in every industrial system. As a result of its widespread application, aluminum suffers enormous annual losses due to corrosion. Scientists are continually on the lookout for effective anti-corrosion strategies. Corrosion may be reduced in a number of ways, but many of them are harmful to the environment, so it's important to find a green alternative. Corrosion inhibitors in aluminum alloys can be found in green tea and tulsi extract. In this research, we found that aluminum alloy 1100 (Al-1100) ina 10% NaOH solution was inhibited by both green tea and Tulsi extract. Samples of AL alloy are submerged in 10% NaOH solutions with and without an inhibitor for a total of 25 days. The weight-loss technique is used to determine the effectiveness of an inhibitor, with tulsi extract far outperforming green tea with the best efficiency of 83.93% compared to the greatest efficiency of 14.29% for green tea. After being submerged in an inhibitory solution, an aluminum alloy surface developed an adsorbed protective layer, which is chemical adsorption, as seen by FTIR (Fourier-Transform Infrared Spectroscopy) spectroscopy. Green inhibitors those are present on the surface of the aluminum alloys are less corrosive confirmed by the SEM (Scanning Electron Microscopy) analysis. The chemical particles were found to be present as a coating over AL alloy surfaces, as determined by EDS (Energy Dispersion Spectroscopy) testing. In a10% NaOH solution, Al-1100 is inhibited more effectively by tulsi extracts than by green tea extracts.

Aluminum is utilized in many applications and it is constantly corroding and losing strength. Corrosion impacts every area of the economy and creates substantial issues. Most approaches for reducing corrosion are environmentally harmful. Green tea and Tulsi extract are two potential choices for use as green corrosion inhibitors in aluminum alloys. This study set out to examine whether or not extracts from green tea and Tulsi might inhibit the corrosion of aluminum alloy 1100 in an10% H2SO4 solution. When it refers to weight reduction, green tea's maximum efficacy of inhibition is 71.43%, whereas tulsi extract is 85.71%. FTIR spectroscopy demonstrated that an adsorbent protective layer formed on the surface of the aluminum after it was immersed in an inhibited solution. The SEM morphology reveals that the presence of a green inhibitor reduces corrosion on the surface of Al alloy 1100. EDS analysis reveals that the chemical particles form a coating over the Al alloy surfaces. Tulsi extracts have been shown to be more efficient for inhibiting Al alloy 1100 in10% H2SO4 Solution than green tea extracts.

Abstract English is regarded as a compulsory subject in Bangladesh, which learning starts at the very early stage of a learner. However, after spending almost 12 years in learning English, learners’ oral skill is not seen up to the mark when they enter the university for tertiary education. Sometimes, they are noticed to have their unwillingness to communicate with others. Hence, the current study aims to explore the experiences of Bangladeshi university students’ willingness to communicate (WTC) by employing a multiple case study method. 10 undergraduate students from a private university were interviewed. Apart from semi-structured interview, classroom observations were also carried out for data collection. The obtained data were analysed through the content analysis process. The findings show that students’ earlier experiences of learning English have been positive; however, they think grammar-based English learning is an obstacle in the development of their oral communication. The study also reveals that learners’ WTC is greatly influenced by classroom environment that enhances or declines their interest to communicate with others. Based on the findings, the study suggests that incorporating more drills in English classes by engaging learners with real-life based conversations, dialogues and so forth can enhance learners’ WTC. Hence, learners’ real voice would help the policymakers and language instructors to take the issue into consideration and way-out timely measures.

Introduction Childhood cancer is a leading cause of death. It is unclear whether the COVID-19 pandemic has impacted childhood cancer mortality. In this study, we aimed to establish all-cause mortality rates for childhood cancers during the COVID-19 pandemic and determine the factors associated with mortality.Methods Prospective cohort study in 109 institutions in 41 countries. Inclusion criteria: children

Background: India bears a disproportionate burden of undernutrition. Access to an affordable, nutritious diet is one of the critical challenges. There is a need to assess the cost of a nutritious diet and find ways to understand and minimise the affordability gap through a comprehensive approach. Objective: The present study was conducted in the West Singhbhum district of Jharkhand, India. Its objective was to find out the cost of various diets, and their affordability, based on households’ accounting for their total food expenditure, and assessing the coverage of essential governments’ nutrition-specific interventions to use a model for suggesting ways to minimise the affordability gap. We also estimate the potential impact of nutrition-sensitive programmes on household food affordability. Methodology: The study employed the Cost of the Diet (CotD) methodology, a mixed-method, cross-sectional assessment, where the research team conducted surveys in 16 markets, 12 focus group discussions (FGDs) and 96 individual interviews (IDIs). Additionally, 434 household-level surveys were conducted to understand income, expenditure patterns in the localities and uptake of key nutrition-sensitive interventions. Secondary information from the 68th round of the National Sample Survey 2012 were used to assess rural Jharkhand’s non-food expenditure (NFE). Data were analysed primarily using the Save the Children’s Cost of the Diet software version 2.5.2. Results: The cost of the diet increased with an increase in the diet quality – from a basic energy-only diet costing INR 33,892 ($505.85)[1] per year for a standard household with 6 members to a food-habit nutritious diet (FHAB) costing INR 70,627 ($1054.13) per year. More than half of the sampled households could not afford a nutritious diet. The poorest quartile was spending 56.8% of income on food, compared to 33.7% for the richest quintile. Conclusion: The cost of a FHAB diet should be used as a benchmark to track the progress of beneficiary groups in upcoming socio-economic assessments. Changes in the affordability gap should be observed to assess whether new initiatives have worked. Optimal coverage of existing nutrition-specific and nutrition-sensitive programmes has the potential to reduce the cost of a FHAB nutritious diet by up to 30%. [1] $1=INR 67 (The exchange rate at the time of data collection, December 2019)

Enhancing the output power of triboelectric nanogenerators (TENGs) requires the creation of micro or nano-features on polymeric triboelectric surfaces to increase the TENGs’ effective contact area and, therefore, output power. We deploy a novel bench-top fabrication method called dynamic Scanning Probe Lithography (d-SPL) to fabricate massive arrays of uniform 1 cm long and 2.5 µm wide nano-features comprising a 600 nm deep groove (NG) and a 600 nm high triangular prism (NTP). The method creates both features simultaneously in the polymeric surface, thereby doubling the structured surface area. Six thousand pairs of NGs and NTPs were patterned on a 6×5 cm2 PMMA substrate. It was then used as a mold to structure the surface of a 200 µm thick Polydimethylsiloxane (PDMS) layer. We show that the output power of the nano-structured TENG is significantly more than that of a TENG using flat PDMS films, at 12.2 mW compared to 2.2 mW, under the same operating conditions (a base acceleration amplitude of 0.8 g).

The urban areas of Bangladesh suffer from severe air quality problem especially in dry season (November-April) when the PM concentrations frequently rise to 7-8 times of the WHO guideline value. The Clean Air and Sustainable Environment (CASE) Project of the Department of Environment has deployed countrywide continuous air monitoring systems to regularly monitor the air quality of the urban areas of Bangladesh. In this paper hourly concentrations of PM10 and PM2.5 captured using β-attenuation method from 2013 to April 2018 in six important cities located in different regions of the country were exhaustively analyzed. Statistical analyses, diurnal and seasonal trends, and polar plots of PM concentrations were examined. Long range sources were spotted by Concentration Weighted Trajectory (CWT) method, where the trajectories were calculated using HYSPLIT-4 model. The analyses identified cities in the middle of the country (Dhaka, Narayanganj, Gazipur) as the most polluted ones while the city to the northeast region (Sylhet) was the least polluted. Average PM10 concentrations at Dhaka, Chattogram, Narayanganj, Gazipur, Sylhet and Barisal stations in dry seasons (November-April) were found 238.7±155.4, 190.7±108.5, 303.6±161.4, 227.3±142.7, 151.7±105.0 and 170.7±108.4 μg m-3 respectively whereas those in wet seasons (May-October) were 75.0±51.6, 55.5±40.8, 102.4±84.4, 60.6±48.5, 52.7±38.3, and 54.4±41.6 μg m-3 respectively. Correlative study of diurnal variations in PM concentrations and meteorological parameters revealed that the congenial meteorology aided in developing higher concentrations of both PM10 and PM2.5 during nighttime. Sources located to the northwestern districts (Naogao, Rangpur, Bogura) were traced by the CWT method contributing to the air pollution in other regions of the country. Outside the boundary, sources in Nepal, and Delhi-NCR and Uttar Pradesh regions of India could have contributed to fine particles at the middle of the country.

This paper proposes a distributed dynamic state estimation algorithm considering packet losses in interconnected smart grid subsystems. Particularly, the distributed filter structure is developed in an interconnected way where the packet dropouts occur in communication links between them. The system error dynamic between true and estimate state is written in a compact form after combining all estimation errors. It can be transformed into the linear matrix inequality framework after introducing semidefinite programming variables. Finally, the local and neighboring gains for the distributed estimator are computed after solving the convex optimization problem. The explore method is applied to the IEEE 14-bus system. In doing this, the state-space model of IEEE 14-bus is obtained using the Holt-Winters method. Simulation results are demonstrated considering packet losses and cyber attacks.

Abstract Background Skin burn wound is a notable medical burden worldwide. Rapid and effective treatment of burnt skin is vital to fasten wound closure and healing properly. Amniotic graft and Aloe vera are widely used as wound managing biomaterials. Sophisticated processing, high cost, availability, and the requirement of medics for transplantation limit the application of amnion grafts. We aim to prepare a novel gel from amnion combined with the Aloe vera extract for burn wound healing which overcome the limitations of graft. Methods Two percent human amniotic membrane (AM), Aloe vera (AV) and AM+AV gels were prepared. In vitro cytotoxicity, biocompatibility, cell attachment, proliferation, wound healing scratch assays were performed in presence of the distinct gels. After skin irritation study, second-degree burns were induced on dorsal region of Wistar rats; and gels were applied to observe the healing potential in vivo. Besides, macroscopical measurement of wound contraction and re-epithelialization; gel treated skin was histologically investigated by Hematoxylin and eosin (H&E) staining. Finally, quantitative assessment of angiogenesis, inflammation, and epithelialization was done. Results The gels were tested to be non-cytotoxic to nauplii and compatible with human blood and skin cells. Media containing 500 μg/mL AM+AV gel were observed to promote HaCaT and HFF1 cells attachment and proliferation. In vitro scratch assay demonstrated that AM+AV significantly accelerated wound closure through migration of HaCaT cells. No erythema and edema were observed in skin irritation experiments confirming the applicability of the gels. AV and AM+AV groups showed significantly accelerated wound closure through re-epithelialization and wound contraction with P

Known stoichiometric models of a two species producer-grazer ecosystem have either neglected spatial dynamics or failed to track free phosphorus in the media. In this paper we present a spatially heterogeneous model that tracks phosphorus content in the producer and free phosphorus in the media. We simulate our model numerically under various environmental conditions. Multiple equilibria, with bistability and deterministic extinction of the grazer, are possible here. In conditions that had been previously studied without tracking free phosphorus we find cases where qualitatively different behavior is observed. In particular under certain environmental conditions previous models predict stable equilibria where our model predicts stable limit cycles near the surface. Oscillatory dynamics can have consequences on the population densities, which may spend some time at low values throughout the cycles where they are in danger of stochastic extinction.

The α-D-glucopyranoside and its derivatives were as the cardinal investigation for developing an effective medication to treat the highest deadly white spot syndrome virus (WSSV) diseases in Shrimp. In our forthcoming work, both computational tools, such as molecular docking, quantum calculations, pharmaceutical kinetics, ADMET, and their molecular dynamics, as well as the experimental trial against WSSV, were executed to develop novel inhibitors. In the beginning, molecular docking was carried out to determine inhibitors of the four targeted proteins of WSSV (PDB ID: 2ED6, 2GJ2, 2GJI, and 2EDM), and to determine the binding energies and interactions of ligands and proteins after docking. The range of binding affinity was found to be between −5.40 and −7.00 kcal/mol for the protein 2DEM, from −5.10 to 6.90 kcal/mol for the protein 2GJ2, from −4.70 to −6.2 kcal/mol against 2GJI, and from −5.5 kcal/mol to −6.6 kcal/mol for the evolved protein 2ED6 whereas the L01 and L03 display the highest binding energy in the protein 2EDM. After that, the top-ranked compounds (L01, L02, L03, L04, and L05), based on their high binding energies, were tested for molecular dynamics (MD) simulations of 100 ns to verify the docking validation and stability of the docked complex by calculating the root mean square deviation (RMSD) and root mean square fluctuation (RMSF). The molecules with the highest binding energy were then picked and compared to the standard drugs that were been applied to fish experimentally to evaluate the treatment at various doses. Consequently, approximately 40–45% cure rate was obtained by applying the dose of oxytetracycline (OTC) 50% with vitamin C with the 10.0 g/kg feed for 10 days. These drugs (L09 to L12) have also been executed for molecular docking to compare with α-D-glucopyranoside and its derivatives (L01 to L08). Next, the evaluation of pharmacokinetic parameters, such as drug-likeness and Lipinski’s principles; absorption; distribution; metabolism; excretion; and toxicity (ADMET) factors, were employed gradually to further evaluate their suitability as inhibitors. It was discovered that all ligands (L01 to L12) were devoid of hepatotoxicity, and the AMES toxicity excluded L05. Additionally, all of the compounds convey a significant aqueous solubility and cannot permeate the blood-brain barrier. Moreover, quantum calculations based on density functional theory (DFT) provide the most solid evidence and testimony regarding their chemical stability, chemical reactivity, biological relevance, reactive nature and specific part of reactivity. The computational and virtual screenings for in silico study reveals that these chosen compounds (L01 to L08) have conducted the inhibitory effect to convey as a possible medication against the WSSV than existing drugs (L09, L10, L11 and L12) in the market. Next the drugs (L09, L10, L11 and L12) have been used in trials.

This study aims to review the potential benefits of peak load shaving in a microgrid system. The relevance of peak shaving for a microgrid system is presented in this research review at the outset to justify the peak load shaving efficacy. The prospective benefits of peak shaving in microgrid systems, including technological, economic, and environmental advantages, are thoroughly examined. This review study also presents a cost–benefit numerical analysis to illustrate the economic viability of peak load shaving for a microgrid system. Different peak shaving approaches are briefly discussed, as well as the obstacles of putting them into practice. Finally, this review study reveals some potential future trends and possible directions for peak shaving research in microgrid systems. This review paper lays a strong foundation for identifying the potential benefits of peak shaving in microgrid systems and establishing suitable projects for practical effectuation.

Energy distribution technique is an essential obligation of an intelligent household system to assure optimal and economical operation. This paper considers a small-scale household system detached from the power grids consisting of some electrical components in day-to-day life. Optimal power distribution generated from a photovoltaic system is vital for ensuring economic and uninterrupted power flow. This paper presents an optimal energy distribution technique for a small-scale smart household system to ensure uninterrupted and economical operation. A photovoltaic (PV) system is considered as the primary generation system, and a battery energy storage system (BESS) is viewed as a backup power supply source. The actual load and PV generation data are used to validate the proposed technique collected from the test household system. Two different load profiles and photovoltaic power generation scenarios, namely summer and winter scenarios, are considered for case studies in this research. An actual test household system is designed in MATLAB/Simulink software for analyzing the proposed technique. The result reveals the effectiveness of the proposed technique, which can distribute the generated power and utilize the BESS unit to ensure the optimal operation. An economic analysis is conducted for the household system to determine the economic feasibility. The capital investment of the system can be returned within around 5.67 years, and the net profit of the system is 2.53 times more than the total capital investment of the system. The proposed technique can ensure economical operation, reducing the overall operating cost and ensuring an environment-friendly power system. The developed strategy can be implemented in a small-scale detached interconnected smart household system for practical operation to distribute the generated energy optimally and economically.

BACKGROUND:Bipolar disorder (BPD) is a major mental disorder which not only affects the personal and social functioning of an individual, but also inflicts a huge economic burden on the family. Yet, the study of BPD in Bangladesh is rare and poorly documented. Responding to the dire need, we conducted a new study to determine the prevalence of, and detect the associated factors of, BPD among married women in Rajshahi City, Bangladesh. METHODS:We conducted a cross-sectional study, selecting households in Rajshahi City using a multi-stage random sampling design. The data consisted of 279 married women, who were screened for BPD using the bipolar spectrum diagnostic scale (BSDS). Frequency distribution, chi-square test and binary logistic regression model were used respectively to determine the prevalence, identify the associated factors and quantify their effects on BPD. RESULTS:The prevalence of BPD among married women in Rajshahi City was 2.5%, with an additional 7.2% classified as probable BPD. A binary logistic regression analysis established the following six main factors of BPD: (1) comorbid mental disorder [AOR = 8.232, 95% CI = (1.397, 50.000), p

BACKGROUND:World Health Organization (WHO) suggests that exclusive breastfeeding (EBF) is the best nutrition for the neonate. Still, it remains a big challenge to establish EBF not only in Bangladesh but also in any developing countries. OBJECTIVE:The aim of this study was to determine the level of knowledge and practices on EBF and its relationship between different socioeconomic and demographic factors among mothers having at least one child of aged 6-12 months in the rural area of Rajshahi District, Bangladesh. METHODOLOGY:A community clinic (CC) based study has been conducted by using semi-structured questionnaire. A total of 513 mothers having at least one child aged 6-12 months from 32 different CC in the rural area of Rajshahi District, Bangladesh during September to December 2015. A composite index, chi-square test, and logistic regression model were utilized in this study. RESULTS:The prevalence of knowledge and practices on EBF were 34.5% and 27.9% among mothers having at least one child aged 6-12 months. From the analyses, mothers age of ≥21 years were (adjusted odds ratio (AOR) = 13.840, 95% CI: 7.394-25.904; p

BackgroundUntil now, no vaccine or effective drug is available for the control, prevention, and treatment of COVID-19. Preventive measures are the only ways to be protected from the disease and knowledge of the people about the preventive measures is a vital matter.ObjectivesThe aim of the study was to assess the knowledge of the general people in Rajshahi district, Bangladesh regarding the COVID-19 preventive measures.MethodologyThis cross sectional study was conducted from March 10 to April 25, 2020. Data were collected with a semi-structured questionnaire from 436 adult respondents selected by using a mixed sampling technique. Frequency analysis, chi-square test, and logistic regression model were utilized in this study. SPSS (IBM, Version 22) was used for data analysis. 95% confidence interval and p-value = 0.05 were accepted for statistical significance.ResultsOnly 21.6% of the respondents had good knowledge of the COVID-19 preventive measures. The highest 67.2% of them knew that washing hands with soap could prevent the disease, but contrarily, the highest 72.5% did not know that avoidance of touching mouth, nose, and eyes without washing hands was a preventive measure. Only 28.4% and 36.9% of the respondents knew that maintaining physical distancing and avoiding mass gatherings were measures of prevention of COVID-19 respectively. The younger age (≤25 years), low family income (≤15,000 Bangladeshi Taka (BDT), occupation others than business and service, and nuclear family had the lower odds of having no/less knowledge about the preventive measures.ConclusionsThe knowledge level of the general people regarding prevention of COVID-19 was alarmingly low in Bangladesh. The government of Bangladesh, health policy makers and donor agencies should consider the findings and take immediate steps for improving knowledge of the public about prevention of the disease.

Peak load reduction is one of the most essential obligations and cost-effective tasks for electrical energy consumers. An isolated microgrid (IMG) system is an independent limited capacity power system where the peak shaving application can perform a vital role in the economic operation. This paper presents a comparative analysis of a categorical variable decision tree algorithm (CVDTA) with the most common peak shaving technique, namely, the general capacity addition technique, to evaluate the peak shaving performance for an IMG system. The CVDTA algorithm deals with the hybrid photovoltaic (PV)—battery energy storage system (BESS) to provide the peak shaving service where the capacity addition technique uses a peaking generator to minimize the peak demand. An actual IMG system model is developed in MATLAB/Simulink software to analyze the peak shaving performance. The model consists of four major components such as, PV, BESS, variable load, and gas turbine generator (GTG) dispatch models for the proposed algorithm, where the BESS and PV models are not applicable for the capacity addition technique. Actual variable load data and PV generation data are considered to conduct the simulation case studies which are collected from a real IMG system. The simulation result exhibits the effectiveness of the CVDTA algorithm which can minimize the peak demand better than the capacity addition technique. By ensuring the peak shaving operation and handling the economic generation dispatch, the CVDTA algorithm can ensure more energy savings, fewer system losses, less operation and maintenance (O&M) cost, etc., where the general capacity addition technique is limited.

Introduction: Growth failure among children and micronutrient deficiency among children and women is one of the major nutritional problems in Bangladesh. According to a 2011 estimate, half of the children and 40% women were anaemic, and the prevalence of stunting and underweight was 40% and 36% among children, while a quarter of non-pregnant adult women were chronically energy deficient. The problem was magnified among the extreme poor population. Previously, standalone initiatives have attempted to tackle undernutrition and micronutrient deficiency separately, but there have been few attempts to integrate these two approaches; and credible evidence from experimental studies was sought from the government and development partners to guide future policy and investment decisions. Aims & Objectives: This study aimed to determine the effect of an intervention package, containing deworming at six-monthly intervals, daily multiple-micronutrient powder (MNP containing 15 ingredients) supplementation for twelve months, and flip flop (thong) shoes in reducing anaemia among extremely poor women and children under-five, as well as to assess the effect on growth failure. Methods: The study employed a two-arm cluster randomised trial design involving 537 women and 168 under-five children in 21 clusters within the intervention arm, while the comparison clusters contained a total of 503 women and 139 under-five children in another 21 clusters. The implementation took place between December 2010 and December 2011. Anaemia prevalence was the primary outcome; growth failure (measured by anthropometry), the prevalence of diarrhoea, and passed worms were assessed as secondary outcomes. The analysis was conducted based on cluster-level summaries of mean and prevalence, and the differences between groups were compared using independent sample t-tests. Results: The study detected a significant effect on anaemia. At endline, the prevalence of anaemia among the women in the intervention clusters was 52% less than the comparison clusters (mean difference 18.1%, 95% CI: 11.1% to 25.1%, P

In contrast to the traditional centralized power system state estimation approaches, this paper investigates the optimal filtering problem for distributed dynamic systems. Particularly, the interconnected synchronous generators are modeled as a state-space linear equation where sensors are deployed to obtain measurements. As the synchronous generator states are unknown, the estimation is required to know the operating conditions of large-scale power networks. Availability of the system states gives the designer an accurate picture of power networks to avoid blackouts. Basically, the proposed algorithm is based on the minimization of the mean squared estimation error, and the optimal gain is determined by exchanging information with their neighboring estimators. Afterward, the convergence of the developed algorithm is proved so that it can be applied to real-time applications in modern smart grids. Simulation results demonstrate the efficacy of the developed algorithm.

As the electricity demand continues to grow and renewable energy resources are incorporated into the grid, an effective dynamic state estimation is required for monitoring and grid synchronization. This paper proposes a microgrid state estimation approach considering the unreliable communication channels. Particularly, the renewable microgrid incorporating distributed energy resources, such as solar panels, are represented as a state-space linear model. Then, the wireless sensor network is adopted to sense the microgrid states. For long-distance transmission, we propose an innovative smart grid infrastructure, which is easy to design and offers a reliable two-way communication. In this infrastructure, the modulated signal is transmitted over an unreliable channel, which causes signal distortions. After demodulation and dequantization, the received signal at the energy management system is used the fading Kalman filter algorithm. Using the tunable forgetting factor in the predicted error covariance step, this algorithm aims to minimize the estimation errors so the estimated states reflect the true system states. Simulations results indicate that the developed approach estimates the system states within 0.25 seconds.

In order to provide intelligent services, the Internet of Things (IoT) facilitates millions of smart cyber-physical devices to be enabled with network connectivity to sense, collect, process, and exchange information. Unfortunately, the traditional communication infrastructure is vulnerable to cyber attacks and link failures, so it is a challenging task for the IoT to explore these applications. In order to begin research and contribute into the IoT-based cyber-physical digital world, one will need to know the technical challenges and research opportunities. In this study, several key technical challenges and requirements for the IoT communication systems are identified. Basically, privacy, security, intelligent sensors/actuators design, low cost and complexity, universal antenna design, and friendly smart cyber-physical system design are the main challenges for the IoT implementation. Finally, the authors present a diverse set of cyber-physical communication system challenges such as practical implementation, distributed state estimation, real-time data collection, and system identification, which are the major issues require to be addressed in implementing an efficient and effective IoT communication system.

In this article, numerically a surface plasmon resonance (SPR) biosensor is developed based on Graphene-MOS2 with TiO2SiO2 hybrid structure for the detection of formalin. Based on attenuated total reflection (ATR) method, we used angular interrogation technique to sense the presence the formalin by observing the change of “minimum reflectance with respect to SPR angle” and “maximum transmittance with respect to surface plasmon resonance frequency (SPRF)”. Here, we used Chitosan as probe analyte to perform chemical reaction with formalin (formaldehyde) which is consider as target analyte. Simulation results show a negligible variation of SPRF and SPR angle for improper sensing of formalin that confirms absence of formalin whereas for proper sensing is considerably countable that confirms the presence of formalin. Thereafter, a comparison of sensitivity for different sensor structure is made. It is observed that the sensitivity without TiO2, SiO2, MoS2 and Graphene (conventional structure) is very poor and 73.67% whereas the sensitivity with graphene but without TiO2, SiO2 and MoS2 layers is 74.67% consistently better than the conventional structure. This is due to the electron loss of graphene, which is accompanying with the imaginary dielectric constant. Furthermore, the sensitivity without TiO2, SiO2 and graphene but with MoS2 layer is 79.167%. After more if both graphene and MoS2 are used and TiO2 and SiO2 layers are not used then sensitivity improves to 80.5%. This greater than before performance is due to the absorption ability and optical characteristics of graphene biomolecules and high fluorescence quenching ability of MoS2. Further again, if TiO2SiO2 composite layer is used with the Graphene-MoS2 then the sensitivity enhances from 80.5% to 82.5%. Finally, the sensitivity for the proposed structure has been carried out, and result is 82.83%, the highest value among all the previous structures to integrate the advantages of graphene, MoS2, TiO2 and SiO2. Keywords: ATR, Biosensor, Surface plasmon resonance, Formalin, Resonance angle, Resonance frequency, Graphene, MoS2, TiO2, SiO2

Hypogonadism, associated with low levels of testosterone synthesis, has been implicated in several diseases. Recently, the quest for natural alternatives to prevent and treat hypogonadism has gained increasing research interest. To this end, the present study explored the effect of S-allyl cysteine (SAC), a characteristic organosulfur compound in aged-garlic extract, on testosterone production. SAC was administered at 50 mg/kg body weight intraperitoneally into 7-week-old BALB/c male mice in a single-dose experiment. Plasma levels of testosterone and luteinizing hormone (LH) and testis levels of proteins involved in steroidogenesis were measured by enzymatic immunoassay and Western blot, respectively. In addition, mouse testis-derived I-10 cells were also used to investigate the effect of SAC on steroidogenesis. In the animal experiment, SAC significantly elevated testosterone levels in both the plasma and the testis without changing the LH level in plasma and increased phosphorylated protein kinase A (p-PKA) levels. Similar results were also observed in I-10 cells. The findings demonstrating the increasing effect of SAC on p-PKA and mRNA levels of Cyp11a suggest that SAC increases the testosterone level by activating the PKA pathway and could be a potential target for hypogonadism therapeutics.

Given the significant concerns regarding carbon emission from the fossil fuels, global warming and energy crisis, the renewable distributed energy resources (DERs) are going to be integrated in the smart grid. This grid can spread the intelligence of the energy distribution and control system from the central unit to the long-distance remote areas, thus enabling accurate state estimation (SE) and wide-area real-time monitoring of these intermittent energy sources. In contrast to the traditional methods of SE, this paper proposes a novel accuracy dependent Kalman filter (KF) based microgrid SE for the smart grid that uses typical communication systems. Then this article proposes a discrete-time linear quadratic regulation to control the state deviations of the microgrid incorporating multiple DERs. Therefore, integrating these two approaches with application to the smart grid forms a novel contributions in green energy and control research communities. Finally, the simulation results show that the proposed KF based microgrid SE and control algorithm provides an accurate SE and control compared with the existing method.

Recently, the renewable distributed energy resources (DERs) have become more and more popular due to carbon-free energy sources and environment-friendly electricity generation. Unfortunately, these power generation patterns are mostly intermittent in nature and distributed over the electrical grid, which creates challenging problems in the reliability of the smart grid. Thus, the smart grid has a strong requisite for an efficient communication infrastructure to facilitate estimating the DER states. In contrast to the traditional methods of centralized state estimation (SE), we propose a distributed approach to microgrid SE based on the concatenated coding structure. In this framework, the DER state is treated as a dynamic outer code, and the recursive systematic convolutional (RSC) code is seen as a concatenated inner code for protection and redundancy in the system states. Furthermore, in order to properly monitor the intermittent energy source from any place, this paper proposes a distributed SE method. Particularly, the outputs of the local SE are treated as measurements, which are fed into the master fusion station. At the end, the global SE can be obtained by combining local SEs with corresponding weighting factors. The weighting factors can be calculated by inspiring the covariance intersection method. The simulation results show that the proposed method is able to estimate the system state properly.

This paper proposes an innovative internet of things (IoT) based communication framework for monitoring microgrid under the condition of packet dropouts in measurements. First of all, the microgrid incorporating the renewable distributed energy resources is represented by a state-space model. The IoT embedded wireless sensor network is adopted to sense the system states. Afterwards, the information is transmitted to the energy management system using the communication network. Finally, the least mean square fourth algorithm is explored for estimating the system states. The effectiveness of the developed approach is verified through numerical simulations.

Next-generation sequencing (NGS) is a revolutionary advancement allowing large-scale discovery of functional molecular markers that has many applications, including plant breeding. High-quality genomic DNA (gDNA) is a prerequisite for successful NGS library preparation and sequencing; however, few reliable protocols to obtain such plant gDNA exist. A previously reported nuclear pellet (NP) method enables extraction of high-yielding gDNA from fresh leaf tissue of maize (Zea mays L.), but the quality does not meet the stringent requirements of NGS. In this study, we optimized the NP method for whole-genome sequencing of rice (Oryza sativa L.) through the integration of simple purification steps. The optimized NP method relied on initial nucleus enrichment, cell lysis, extraction, and subsequent gDNA purification buffers. The purification steps used proteinase K, RNase A, phenol/chloroform/isoamyl alcohol (25:24:1), and chloroform/isoamyl alcohol (24:1) treatments for protein digestion and RNA, protein, and phenol removal, respectively. Our data suggest that this optimized NP method allowed extraction of consistently high-yielding and high-quality undegraded gDNA without contamination by protein and RNA. Moreover, the extracted gDNA fulfilled the quality metrics of NGS library preparation for the Illumina HiSeq X Ten platform by the TruSeq DNA PCR-Free Library Prep Kit (Illumina). We provide a reliable step-by-step guide to the extraction of high-quality gDNA from fresh leaf tissues of rice for molecular biologists with limited resources.

Salinity critically limits rice metabolism, growth, and productivity worldwide. Improvement of the salt resistance of locally grown high-yielding cultivars is a slow process. The objective of this study was to develop a new salt-tolerant rice germplasm using speed-breeding. Here, we precisely introgressed the hst1 gene, transferring salinity tolerance from “Kaijin” into high-yielding “Yukinko-mai” (WT) rice through single nucleotide polymorphism (SNP) marker-assisted selection. Using a biotron speed-breeding technique, we developed a BC3F3 population, named “YNU31-2-4”, in six generations and 17 months. High-resolution genotyping by whole-genome sequencing revealed that the BC3F2 genome had 93.5% similarity to the WT and fixed only 2.7% of donor parent alleles. Functional annotation of BC3F2 variants along with field assessment data indicated that “YNU31-2-4” plants carrying the hst1 gene had similar agronomic traits to the WT under normal growth condition. “YNU31-2-4” seedlings subjected to salt stress (125 mM NaCl) had a significantly higher survival rate and increased shoot and root biomasses than the WT. At the tissue level, quantitative and electron probe microanalyzer studies indicated that “YNU31-2-4” seedlings avoided Na+ accumulation in shoots under salt stress. The “YNU31-2-4” plants showed an improved phenotype with significantly higher net CO2 assimilation and lower yield decline than WT under salt stress at the reproductive stage. “YNU31-2-4” is a potential candidate for a new rice cultivar that is highly tolerant to salt stress at the seedling and reproductive stages, and which might maintain yields under a changing global climate.

Pregnane X receptor (PXR) is a nuclear receptor activated by various compounds, including prescribed drugs and dietary ingredients. Ligand-specific activation of PXR alters drug metabolism and affects many other physiological conditions. Species-specific ligand preference is a considerable challenge for studies of PXR function. To increase translational value of the results of mouse studies, humanized mouse model expressing human PXR (hPXR) has been developed. Menaquinone-4 (MK-4), one of vitamin K2 analogs prescribed in osteoporosis, is a PXR ligand. We hypothesized that MK-4 could modulate the physiological conditions endogenously influenced by PXR, including those that have not been yet properly elucidated. In the present study, we investigated the effects of a single oral treatment with MK-4 on hepatic gene expression in wild-type and hPXR mice by using quantitative RT-PCR and DNA microarray. MK-4 administration altered mRNA levels of genes involved in drug metabolism (Abca3, Cyp2s1, Sult1b1), bile acid synthesis (Cyp7a1, Cyp8b1), and energy homeostasis (Aldoc, Slc2a5). Similar mRNA changes of CYP7A1 and CYP8B1 were observed in human hepatocarcinoma HepG2 cells treated with MK-4. These results suggest that MK-4 may modulate bile acid synthesis. To our knowledge, this is the first report showing the effect of MK-4 in hPXR mice.

The rapid evolution of Artificial Intelligence (AI) and its widespread adoption have given rise to a critical need for understanding the underlying factors that shape users' behavioral intentions. Therefore, the main objective of this study is to explain user perceived behavioral intentions and use behavior of AI technologies for academic purposes in a developing country. This study has adopted the unified theory of acceptance and use of technology (UTAUT) model and extended it with two dimensions: trust and privacy. Data have been collected from 310 AI users including teachers, researchers, and students. This study finds that users' behavioral intention is positively and significantly associated with trust, social influence, effort expectancy, and performance expectancy. Privacy, on the other hand, has a negative yet significant relationship with behavioral intention unveiling that concerns over privacy can deter users from intending to use AI technologies which is a valuable insight for developers and educators. In determining use behavior, facilitating condition, behavioral intention, and privacy have significant positive impact. This study hasn't found any significant relationship between trust and use behavior elucidating that service providers should have unwavering focus on security measures, credible endorsements, and transparency to build user confidence. In an era dominated by the fourth industrial revolution, this research underscores the pivotal roles of trust and privacy in technology adoption. In addition, this study sheds light on users' perspective to effectively align AI-based technologies with the education system of developing countries. The practical implications encompass insights for service providers, educational institutions, and policymakers, facilitating the smooth adoption of AI technologies in developing countries while emphasizing the importance of trust, privacy, and ongoing refinement.

The role of genetic variation is utmost importance in the selection of a desirable genotype for breeding programs. In the northern region of Bangladesh, the performance of five short duration boro rice varieties (BRRI dhan28, BRRI dhan74, BRRI dhan81, BRRI dhan88, and Bangabandhu dhan100) on yield and yield-contributing traits were evaluated in four locations. Yield attributes tiller hill-1 (TN), panicle hill-1 (PN), filled grain panicle-1 (FG), panicle length (PL), 1000-grain weight (TGW), and harvest index (HI), showed a positive correlation with grain yield (GY). Conversely, spikelet sterility (SSP) and unfilled grains panicle-1 (UFG) showed negative associations with grain yield. Principal component analysis (PCA) revealed that the first three components accounted for 89.60% of variability. The highest positive eigenvalue was observed in DF, DM, BY, HI, PN, SY, TN, PL and GY in PC1, indicating their significant influence on the overall genotype variations. PC2 was primarily driven by plant height (PH) and FG, while PC3 driven by TGW and UFG. The results suggest that grain yield is highly influenced by FG, PH, DM, DF, PN, TN, PL, TGW, SY, BY, and HI. These components highlighted the importance in distinguishing rice genotypes with higher grain yield potential. By considering these traits, BRRI dhan74 have outperformed other varieties, followed by BRRI dhan88 and Bangabandhu dhan100. BRRI dhan74 is most suitable for all four location followed by BRRI dhan88. The traits such as PN, PL, FG, TGW, PH, & HI significantly influence rice yield and should be prioritized in breeding programs aimed at developing high-yielding rice varieties.

Organic semiconductors with wide bandgaps have potential applications in organic light-emitting diode displays, organic photovoltaic devices, organic field-effect transistors and solar cells. However, organic semiconductors are not good conductors of electricity. This study synthesizes the banana-graphene nanofibrous membrane using an electric spin process to form a tunable bandgap to enhance conductivity. The chemical process was followed to prepare liquid viscous from banana stalks. Different percentages of graphene (1.2 wt.%, 2.4 wt.% and 3.6 wt.%) were used with the liquid viscous to form sizeable and tunable bandgaps in the composites and enhance the conductivity of the materials. The results showed 5.67 %, 24.5 %, and 27.8 % lower bandgap for 1.2 wt.%, 2.4 %, and 3.6 wt.% graphene-contained samples, respectively, as compared to the polyvinyl alcohol (PVA) viscous fibre (3.35 eV). With the addition of graphene with PVA viscous fibre, the properties of electrospun nanofibrous graphene were changed from insulator to semiconductor. The band gap property was controlled by incorporating graphene with various percentages. The morphology of the surfaces showed that nanofibers are bonded with each other, and graphene nanoparticles are uniformly distributed. The results of this work can be considered to further progress in manufacturing nanocomposites for organic semiconductor applications.

Abstract Polypropylene (PP) is a versatile polymer with numerous applications that has undergone substantial changes in recent years, focusing on the demand for next-generation polymers. This article provides a comprehensive review of recent research in PP and its advanced functional applications. The chronological development and fundamentals of PP are mentioned. Notably, the incorporation of nanomaterial like graphene, MXene, nano-clay, borophane, silver nanoparticles, etc., with PP for advanced applications has been tabulated with their key features and challenges. The article also conducts a detailed analysis of advancements and research gaps within three key forms of PP: fiber, membrane, and matrix. The versatile applications of PP across sectors like biomedical, automotive, aerospace, and air/water filtration are highlighted. However, challenges such as limited UV resistance, bonding issues, and flammability are noted. The study emphasizes the promising potential of PP while addressing unresolved concerns, with the goal of guiding future research and promoting innovation in polymer applications. Graphical Abstract

Electric vehicles (EVs) are commonly recognized as environmentally friendly modes of transportation. They function by converting electrical energy into mechanical energy using different types of motors, which aligns with the sustainable principles embraced by smart cities. The motors of EVs store and consume electrical power from renewable energy (RE) sources through interfacing connections using power electronics technology to provide mechanical power through rotation. The reliable operation of an EV mainly relies on the condition of interfacing connections in the EV, particularly the connection between the 3- $\phi $ inverter output and the brushless DC (BLDC) motor. In this paper, machine learning (ML) tools are deployed for detecting and classifying the faults in the connecting lines from 3- $\phi $ inverter output to the BLDC motor during operational mode in the EV platform, considering double-line and three-phase faults. Several machine learning-based fault identification and classification tools, namely the Decision Tree, Logistic Regression, Stochastic Gradient Descent, AdaBoost, XGBoost, K-Nearest Neighbour, and Voting Classifier, were tuned for identifying and categorizing faults to ensure robustness and reliability. The ML classifications were developed based on the datasets of healthy and faulty conditions considering the combination of six critical parameters that have significance in reliable EV operation, namely the current supplied to the BLDC motor from the inverter, the modulated DC voltage, output speed, and measured speed, as well as the output of the Hall-effect sensor. In addition, the superiority of the proposed fault detection and classification approaches using ML tools was assessed by comparing the detection and classification efficiency through some statistical performance parameter comparisons among the classifiers.

Abstract L‐ and D‐ form oligo(lactic acid)s (OLLA and ODLA) grafted α‐cellulose (OLLA‐g‐cellulose and ODLA‐g‐cellulose) were prepared by the graft polycondensation reaction in C6H5CH3 medium at 130°C and 380 mm of mercury pressure. Para‐toluene sulphonic acid (5 wt% of oligo(lactic acid)) was used as a catalyst whereas potassium persulfate (0.01 wt% of oligo(lactic acid)) was used as a co‐catalyst in the graft polycondensation reaction. OLLA and ODLA with a degree of polymerization (DP) 6–7 used in polycondensation reaction were also prepared by ring‐opening polymerization of L‐ and D‐lactides at 140°C for 10 h with stannous octoate (C16H30O4Sn) as a motivator, L, and D monomer of lactic acids as co‐motivators. FTIR analysis proved the bonding of OLLA and ODLA onto the α‐cellulose surface. The thermal properties of poly(L‐lactic) acid (PLLA) composites were explored by thermal analysis (TG, DTA, and DTG). Degradation, melting, and maximum weight loss temperature of the composites were increased with the increase of grafted cellulose up to 10% and then decreased. TG and DTA results showed that the incorporation of grafted α‐cellulose (grafted cellulose) can improve the thermal properties of PLLA composites. Highlights Synthesis of oligo(lactic acid)s from L‐ and D‐lactides by ring‐opening polymerization reactions. α‐cellulose extraction and graft modification with oligo(lactic acid)s. Preparation of grafted α‐cellulose composite with PLLA matrix. Evaluation of thermal properties of the grafted α‐cellulose‐reinforced composites.