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• Fusion of advanced deep-learning models CNN, LSTM, DNN and RNN with GA optimizes GWPZ mapping. • Overlaying GWPZ with drought maps unveils links between drought levels and groundwater potential. • CMIP6 climate models project changing GWPZ under different socioeconomic scenarios. • Workshops and local collaboration empower communities for sustainable water management. This study presents a novel approach to groundwater resource assessment and drought vulnerability, achieved through integrating cutting-edge deep-learning algorithms into a comprehensive framework. In regions susceptible to drought, ensuring groundwater availability is of paramount importance. Addressing this critical need, our research employs an ensemble of advanced algorithms, including long short-term memory, convolutional neural network, deep neural network, and recurrent neural network. These algorithms are further enhanced through optimization using a genetic algorithm to map groundwater potential zones (GWPZ). Leveraging model validation based on the area under the receiver operating characteristic curve (AUCROC), the long short-term memory-genetic algorithm model emerges as the superior algorithm, boasting the highest values of AUCROC: 0.995 for training and 0.996 for testing). Utilizing this optimized model, this study developed the GWPZ map, subsequently overlaying it with established drought maps developed by the Bangladesh Agricultural Research Council across distinct periods—Pre-Kharif, Kharif, and Rabi. The derived baseline GWPZ spatial distribution revealed five categories—very low (34.99%), low (27.67%), moderate (13.26%), high (11.71%), and very high (12.37%)—and their intersection with drought-prone regions, indicative of probabilities of drought occurrence ranging from very severe to low (15.14% to 24.69%). Moreover, employing the best-predicted model, this study projected future GWPZ for 2050 and 2100 using the coupled model intercomparison project 6 general circulation model data under the ambit of three distinct shared socioeconomic pathways (SSPs): SSP1-2.6, SSP2-4.5, and SSP5-8.5. Our findings suggested a contraction in the groundwater potential area by the end of the twenty-first century (2100). This pioneering integration sheds light on the intricate relationship between groundwater availability and drought susceptibility, furnishing invaluable insights for formulating targeted water resource management strategies. By amalgamating advanced computational techniques with geospatial analyses, this research contributes to a more comprehensive grasp of water resource dynamics within the context of escalating climate challenges. Consequently, it offers a foundation for informed decision-making and implementing sustainable water management practices in regions grappling with the dual challenges of groundwater scarcity and recurrent droughts. [ABSTRACT FROM AUTHOR]

Knowledge of gender-specific drug distributions in different organs are of great importance for personalized medicine and reducing toxicity. However, such drug distributions have not been well studied. In this study, we investigated potential differences in the distribution of imipramine and chloroquine, as well as their metabolites, between male and female kidneys. Kidneys were collected from mice treated with imipramine or chloroquine and then subjected to atmospheric pressure matrix-assisted laser desorption ionization-mass spectrometry imaging (AP-MALDI-MSI). We observed differential distributions of the drugs and their metabolites between male and female kidneys. Imipramine showed prominent distributions in the cortex and medulla in male and female kidneys, respectively. Desipramine, one of the metabolites of imipramine, showed significantly higher (*** p < 0.001) distributions in the medulla of the male kidney compared to that of the female kidney. Chloroquine and its metabolites were accumulated in the pelvis of both male and female kidneys. Interestingly, they showed a characteristic distribution in the medulla of the female kidney, while almost no distributions were observed in the same areas of the male kidney. For the first time, our study revealed that the distributions of imipramine, chloroquine, and their metabolites were different in male and female kidneys. [ABSTRACT FROM AUTHOR]

Bacillus pumilus TUAT1 acts as plant growth–promoting rhizobacteria for various plants like rice and Arabidopsis. Under stress conditions, B. pumilus TUAT1 forms spores with a thick peptidoglycan (PGN) cell wall. Previous research showed that spores were significantly more effective than vegetative cells in enhancing plant growth. In Arabidopsis , lysin motif proteins, LYM1, LYM3 and CERK1, are required for recognizing bacterial PGNs to mediate immunity. Here, we examined the involvement of PGN receptor proteins in the plant growth promotion (PGP) effects of B. pumilus TUAT1 using Arabidopsis mutants defective in PGN receptors. Root growth of wild-type (WT), cerk1-1, lym1-1 and lym1-2 mutant plants was significantly increased by TUAT1 inoculation, but this was not the case for lym3-1 and lym3-2 mutant plants. RNA-seq analysis revealed that the expression of a number of defense-related genes was upregulated in lym3 mutant plants. These results suggested that B. pumilus TUAT1 may act to reduce the defense response, which is dependent on a functional LYM3. The expression of the defense-responsive gene, WRKY29 , was significantly induced by the elicitor flg-22, in both WT and lym3 mutant plants, while this induction was significantly reduced by treatment with B. pumilus TUAT1 and PGNs in WT, but not in lym3 mutant plants. These findings suggest that the PGNs of B. pumilus TUAT1 may be recognized by the LYM3 receptor protein, suppressing the defense response, which results in plant growth promotion in a trade-off between defense and growth. [ABSTRACT FROM AUTHOR]

Neutrophils are the principal trouper of the innate immune system. Activated neutrophils undergo a noble cell death termed NETosis and release a mesh-like structure called neutrophil extracellular traps (NETs) as a part of their defensive strategy against microbial pathogen attack. This web-like architecture includes a DNA backbone embedded with antimicrobial proteins like myeloperoxidase (MPO), neutrophil elastase (NE), histones and deploys in the entrapment and clearance of encountered pathogens. Thus NETs play an inevitable beneficial role in the host's protection. However, recent accumulated evidence shows that dysregulated and enhanced NET formation has various pathological aspects including the promotion of sepsis, pulmonary, cardiovascular, hepatic, nephrological, thrombotic, autoimmune, pregnancy, and cancer diseases, and the list is increasing gradually. In this review, we summarize the NET-mediated pathophysiology of different diseases and focus on some updated potential therapeutic approaches against NETs. [ABSTRACT FROM AUTHOR]

Oral lesions are a prevalent manifestation of oral disease, and the timely identification of oral lesions is imperative for effective intervention. Fortunately, deep learning algorithms have shown great potential for automated lesion detection. The primary aim of this study was to employ deep learning-based image classification algorithms to identify oral lesions. We used three deep learning models, namely VGG19, DeIT, and MobileNet, to assess the efficacy of various categorization methods. To evaluate the accuracy and reliability of the models, we employed a dataset consisting of oral pictures encompassing two distinct categories: benign and malignant lesions. The experimental findings indicate that VGG19 and MobileNet attained an almost perfect accuracy rate of 100 % , while DeIT achieved a slightly lower accuracy rate of 98.73%. The results of this study indicate that deep learning algorithms for picture classification demonstrate a high level of effectiveness in detecting oral lesions by achieving 100 % for VGG19 and MobileNet and 98.73 % for DeIT. Specifically, the VGG19 and MobileNet models exhibit notable suitability for this particular task. [ABSTRACT FROM AUTHOR]

Like many other countries, the economy and society of Japan have been severely affected by the COVID-19 outbreak, and the fishery sector particularly seafood is no exception. Among seafood, since luxury seafood is more commonly consumed at restaurants it has a higher possibility of getting affected by the pandemic compared with cheap popular seafood for the masses. Considering this motivation, this study investigates the variations in the COVID-19 impact on luxury and cheap seafood prices in the Tokyo Toyosu wholesale market. Using the non-linear autoregressive distributed lag model (NARDL), the study identifies that an increase in the hours of stay-at-home during the initial stage of the pandemic is causing a negative influence on both cheap and luxury seafood prices and that this negative impact was severer in the luxury seafood prices. The study also finds a positive influence from the hours of stay-at-home on some cheap popular seafood like horse mackerel and sardine during the third state of emergency (SOE) where at least most of the elderly people have received their first vaccine dose but the negative impact from the SOE measure remained on luxury seafood. It is evident from the findings that the luxury seafood market is heavily dependent on the restaurant sector, which will likely suffer adverse effects when human mobility is restricted. In the event of a pandemic like COVID-19, policymakers should stabilize the price and provide subsidies to the luxury seafood stakeholders. [ABSTRACT FROM AUTHOR]

This column examines readiness for 4IR technology adoption in public libraries in Bangladesh. It explores the current state of adoption, the challenges faced during implementation, and the potential benefits. With the convergence of advanced technologies such as AI, IoT, blockchain, and autonomous systems, libraries can transform into vital community centers and preserve cultural heritage. The findings provide an overview of the current state of adoption, identify opportunities and challenges, and emphasize the need for further research to understand the impact of these technologies on libraries in Bangladesh. [ABSTRACT FROM AUTHOR]

Dhaka city is experiencing rapid land cover changes, and the effects of climate change are highly visible. Investigating their combined influence on runoff patterns is vital for sustainable urban planning and water resources management. In this work, multi-date land cover classification was performed using a random forest (RF) algorithm. To validate accuracy of land cover classification, an assessment was conducted by employing kappa coefficient, which ranged from 85 to 96%, indicating a high agreement between classified images and the reference dataset. Future land cover changes were forecasted with cellular automata-artificial neural network (CA-ANN) model. Further, soil conservation service -curve number (SCS-CN) rainfall-runoff model combined with CMIP6 climate data was employed to assess how changes in land cover impact runoff within Dhaka metropolitan development plan (DMDP) area. Over the study period (2020–2100), substantial transformations of land cover were observed, i.e., built-up areas expanded to 1146.47 km2 at the end of 2100, while agricultural areas and bare land diminished considerably. Consequently, monsoon runoff increased from 350.14 to 368.24 mm, indicating elevated hydrological responses. These findings emphasized an intricate interplay between urban dynamics and climatic shifts in shaping runoff patterns, underscoring urgency of incorporating these factors into urban planning strategies for sustainable water resources management in a rapidly growing city such as Dhaka. [ABSTRACT FROM AUTHOR]

• Plants are sessile; they cannot move to avoid adverse environmental conditions. • Pathogenesis-related proteins (PRs) are induced in the plant by imposing different biotic stresses. • PR proteins are divided into nineteen families (PR-1 to PR-19), with 17 verified and two hypothetical PR families found and categorised based on their biochemical nature. • PRs' insights roles across various stresses have been mentioned. Plants are sessile; they cannot move to avoid adverse environmental conditions. Pathogenesis-related (PR) proteins are induced in the plant by imposing different biotic stresses such as pathogens and abiotic stresses like drought, cold, salinity, heavy metal etc. There are currently nineteen families of PR proteins (PR-1 to PR-19), with 17 confirmed and two putative PR families identified and classified based on their biochemical nature. PR proteins promote innate resistance in plants by disintegrating fungal cell walls, permeabilizing membranes, suppressing transcription, and inactivating ribosomes. Previous research has shown that they play an important role in determining resistance to phytopathogens, making them a promising candidate for developing disease-resistant crop varieties. Plant genetic engineering could be used to create disease-resistant transgenic crops by utilizing several PR genes (thaumatin, osmotin-like proteins, chitinases, glucanases, defensins, thionins, oxalate oxidase, oxalate oxidase-like proteins/germin-like proteins, and LTPs). In this review, we attempt to demonstrate the types and biochemical nature of various PR proteins, as well as their insight mechanism for pathogen resistance and the use of PR proteins for disease-tolerant plants developed at a low cost. [ABSTRACT FROM AUTHOR]

Transportation is a significant contributor to greenhouse gas emissions. Therefore, the apparent solution to this environmental degradation parameter is to green the transport sector to ensure environment-friendly vehicles' operation and avoid poisonous gases in different countries. In light of this context, we develop a green transportation index and scrutinize its role in the environmental degradation proxied by the ecological footprint in the case of the top 10 energy transition countries covering data from 1990 to 2018. We implement a novel and sophisticated econometric technique for data analysis, quantiles via moments, due to potential heterogeneity in the variables and panel units. Our results confirm a monotonic combative profile of green transportation on the ecological footprint in reducing environmental degradation. In addition, the control variables, i.e., innovation, domestic investment, and institutional quality, are conducive to conserving environmental quality by decreasing the ecological footprint. However, urbanization still increases the ecological footprint and environmental degradation in these economies. Our investigated results are robust across the DH panel causality test. Therefore, we propose some important policy implications regarding green transportation exploitation to ease the ecological footprint for a sustainable environment. • The green transport-environmental sustainability nexus is studied. • This study uses the quantiles via moments approach in 10 energy transition nations. • The study's result shows a negative effect of green transport on ecological footprints. • Innovation and domestic investment are conducive to environmental sustainability. • Urbanization is harmful but institutional quality is favorable for ecological balance. [ABSTRACT FROM AUTHOR]

Blumea lacera (Burm. f.) DC. is an aromatic annual herb that has traditionally been used to treat or protect against diabetes. Although it has infallible uses, its supply is limited due to its short lifespan. In this study, we aim to investigate the anti-diabetic potential of its micropropagated plants in type 2 diabetic mammalian (mouse) model and further expand the molecular mechanistic understanding of its activity. The water extract of the micropropagated plants was tested in mice with streptozotocin-induced diabetes. The extract effectively suppressed glucose levels prevented weight loss, and improved dyslipidemia in mice. Additionally, it improved liver injury as well as all investigated toxicity indicators, including serum glutamate-pyruvate transaminase, serum glutamic oxaloacetic transaminase, and serum anti-inflammatory marker C-reactive protein. The intramolecular interaction study revealed that the innate polyphenolic constituents of this plant more profoundly inhibited α-amylase, α-glucosidase, and lipase compared to the standard. The prolific bioactive compounds of the micropropagated plant could be attributed to these superior anti-diabetic effects, presumably via an elaborate inhibition of carbohydrate and lipid hydrolyzing enzymes. Thus, the obtained results provide solid experimental proof of the year-round utility of micropropagated plants as a standard source plant material of Blumea lacera (Burm. f.) DC. for drug research and therapeutic production. [ABSTRACT FROM AUTHOR]

In recent years, most countries have shown keen interest in achieving spectacular economic development through diversifying and sophisticating their export growths. This growth uprising process requires energy consumption. Amid this scenario, this study delves into whether the disaggregate energy consumption (renewable and non-renewable) promotes export diversification and sophistication strategies in OECD countries during 1990–2019. The contribution of this study is to construct two novel indices, e.g., export diversification and sophistication and incorporate them into the study model as the dependent variables. Moreover, using the CS-ARDL approach, the study finds that disaggregate energy consumption contributes to spurring export diversification and sophistication for the OECD countries where non-renewable energy consumption's influence is more potent than renewable energy. Besides, the regressors, such as FDI, human capital, and institutional quality, also promote export diversification and sophistication in the OECD countries. Finally, this research validates the findings yielded from the CS-ARDL method by employing the System GMM (SGMM) approach due to the endogeneity issue appearing in the panel data. This study puts notable policy recommendations based on explored findings. [ABSTRACT FROM AUTHOR]

Deglobalization, as opposed to the term globalization, appears in the world order due to local solutions to problems and border controls, ignoring the principles of treaties, trade wars, and the expansion of regionalism. In addition, slowbalization helps shrink the global flow of trade, information, and societal and cultural exchange dynamism. However, this scary global order, as triggered by deglobalization and slowbalization, significantly impacts the income factors of allied nations. Against this background, we aim to investigate whether deglobalization and slowbalization proxied by the influencing magnitudes of globalization dimensions (e.g., globalization de facto and de jure, internet diffusions, and trade openness) impact the income inequality of the 12 post-Soviet countries, considering the panel data during 1991–2019. To this end, we apply the quantiles via moments approach to investigate the time-varying connectedness between variables that have country and data-centric heterogeneities. Our findings depict that deglobalization is futile in affecting the post-Soviet countries' income dynamics, as globalization negatively affects income inequality in diverse quantiles. Specifically, globalization de facto (globalized policy-implementation spectrum) and internet diffusions have a significantly negative influence on reducing income inequality from low to medium quantiles (q.25–q.75). Globalization de jure (globalized policy-decision spectrum) and trade openness are statistically insignificant in entire quantiles (q.25–q.95), implying the likely existence of slowbalization. Finally, government expenditures and governance quality are monotonically negative in reducing income inequality at all quantiles (q.25–q.95). Therefore, policy suggestions enclose galvanizing globalization potentials in curbing income inequality to keep away the distressful phases of deglobalization and slowbalization. [ABSTRACT FROM AUTHOR]

The coronavirus disease (COVID-19) adversely impacted the fisheries sector of Bangladesh, particularly affecting the outcomes for women workers of the fish and shellfish processing plants (FSPPs). This study aimed to assess the impacts of COVID-19 on the women workers of the FSPPs by collecting data through 151 questionnaire surveys and two focus group discussions (FGDs) from September to December 2021. During COVID-19, 32.1 % of respondents’ food consumption decreased slightly, and 16.6 % reduced drastically. Children of 18.2 % of the respondents had no access, and 16.9 % had insufficient access to online class facilities. Increased livelihood costs and decreased household income posed adverse economic impacts on women. Formal paid hours and overtime job opportunities were reduced because foreign buyers cancelled orders during the pandemic. Gender-based violence and social insecurity increased. Respondents (13.2 %) reported increased mistreatment by their husbands during the pandemic. Women workers’ mental health deteriorated as their anxiety and insecurity about life increased during the pandemic. This study recommends overcoming the adverse effect of COVID-19 or COVID-like pandemics in the future. To ensure proper food consumption and reduce adverse economic impacts, the government should offer a special relief package, financial incentives and flexible low-interest loans. Related authorities should ensure that every child has the opportunity and access to participate in online classes during COVID-19 or COVID, like pandemics in the future. [ABSTRACT FROM AUTHOR]

The main purpose of the study is to analyze the scientific productions published in scientific databases on Industrial Revolution (4IR) and libraries. The researchers investigated the scientific productions that were produced during the last decade (2010 to 2021) and indexed them in the Scopus database. The databases were inspected by VOSviewer and Biblioshiny software for those documents related to the 4IR and library. The keywords are used "Industrial Revolution*" AND "Librar*" in searching. The database's total results are 178. The selection of years shrinks the outputs to 98 publications. Published articles in English, 4IR, and libraries met several important inclusion and exclusion benchmarks for this evaluation. The study found the largest scholarly publication resulting from the country 'USA' (n=10), 'South Africa' (n=8) and Indonesia (n=7) from the total results. The study revealed that Library Hi Tech News provided the majority of the publications (n=06) and Journal of Physics Conference Series and Library Philosophy and Practice ranked 2nd (n=03) and 3rd (n=03) respectively. The research found the most productive organizations were Universiti Teknologi Malaysia ranked 1st (n=10), University Library ranked 2nd (n=8) and Konkuk University ranked 3rd (n= 8). The study found Matofska, B. (n=8) as the most productive author and 2020 (n=28) as the most productive year in the field. The co-occurrence analysis confirmed that the study formed 2 clusters. This scientometric analysis illustrated the overall research flow and scenario along with research growth, productive authors, prolific sources and affiliations in the field that will show the path of the research scholars. [ABSTRACT FROM AUTHOR]

The primary aim of this attempt is to provide a thorough overview of Information Seeking Behavior (ISB) research within Library and Information Science (ISB) utilizing sophisticated bibliometric analysis tools. We searched the bibliographical data from Scopus and examined with the help of Biblioshiny and VOSviewer to demonstrate the visualization. A total of 1957 documents were included in the dataset. The growth rate is calculated at 7.88%. The total quantity of references quoted across all the documents in the dataset amounts to 57870. The study exposed that the highest number of articles (n=140) were produced in the year 2012 followed by the year 2013 (n=130). The study found USA was the top (Total production=1825) publishing country leading by a significant margin, followed by the UK, India, Canada, China, Iran, Australia, Nigeria, Pakistan, and South Africa. Library Philosophy and Practice leads with the highest number of publications, indicating its significant relevance and impact in the field, followed by other journals like Health Information and libraries journal, Journal of the medical library association. The study highlighted the frequency of usage of specific information and information-seeking terms in the dataset such as human and humans and information seeking as the most commonly used terms. The study delivers a bibliometric study of publications available in the Scopus database on ISB in the area of LIS of the period of 1966-2022. [ABSTRACT FROM AUTHOR]

Mineral resources are essential raw materials to generate electricity, fuel vehicles, and heat homes and workplaces. Besides, the global agenda of clean energy deployment, including solar photovoltaics (PV), wind turbines, electric vehicles (EV), and storage facilities, calls for a considerable volume of critical minerals, which elevates their respective import demands. This highly concentrated source of those minerals poses a significant concern triggered by the augmented geopolitical tensions and economic policy uncertainties. In light of this context, our objective is to estimate the response of mineral import demand to global geopolitical risk events and economic policy uncertainty covering monthly data from January 1996 to December 2020. In doing so, we apply the cross-quantilogram (CQ) and the quantile-on-quantile (QQ) regression approaches due to the fat-tailed nature of the data property. Besides, these quantile-based data analysis procedures are appropriate for non-normal data sets and show the co-movement of the variables of interest under a bi-variate modelling approach. More importantly, these two techniques also exhibit the quantile connectedness among the variables in the bearish and bullish conditions. Moreover, our findings show that mineral import demand responds negatively to the USA's (own) and global geopolitical risk events at the high quantiles under long memory. In addition, this demand reacts positively to the USA's (own) and global economic policy uncertainty in entire quantiles under long memory. Therefore, our policy suggestions are concerned with tackling geopolitical tensions and economic policy uncertainty by adopting pre-emptive measures within a viable institutional mechanism to continue impressive mineral trade flows. [ABSTRACT FROM AUTHOR]

In modern days, economic growth is energy‐dependent and vice versa. Earlier studies concentrated a bit to analyze the influence of globalization and politico‐administrative factors on the energy consumption‐economic growth nexus in developing economies. The motivation for the current research is to scrutinize the energy consumption‐economic growth nexus while accounting for the influence of globalization and country risk indicators—the politico‐administrative factors in a panel of 4 South Asian countries (Bangladesh, India, Pakistan, and Sri Lanka) during 1980–2018. To check the issues of heterogeneity and cross‐sectional independence, the study employs the pooled mean group estimation method. The investigated results provide a nexus between energy consumption and economic growth where globalization ‐ a long‐run force positively affects this nexus in the long run and negatively in the short run. Besides, the politico‐administrative factors have an adverse impact in the long run and an insignificant effect on this nexus in the short run. The Dumitrescu–Hurlin non‐causality test establishes the feedback hypothesis concerning energy consumption‐economic growth nexus in South Asian economies. The study results remain robust across the dynamic ordinary least square estimator. Therefore, this study suggests sustaining the energy‐growth nexus to properly handle globalization and politico‐administrative and the Covid‐19 pandemic issues through institutional quality. Moreover, the objective‐oriented policies are critical to strengthening the energy‐growth nexus without decaying environmental quality in South Asian countries. [ABSTRACT FROM AUTHOR]

Cracks in concrete cause initial structural damage to civil infrastructures such as buildings, bridges, and highways, which in turn causes further damage and is thus regarded as a serious safety concern. Early detection of it can assist in preventing further damage and can enable safety in advance by avoiding any possible accident caused while using those infrastructures. Machine learning-based detection is gaining favor over time-consuming classical detection approaches that can only fulfill the objective of early detection. To identify concrete surface cracks from images, this research developed a transfer learning approach (TL) based on Convolutional Neural Networks (CNN). This work employs the transfer learning strategy by leveraging four existing deep learning (DL) models named VGG16, ResNet18, DenseNet161, and AlexNet with pre-trained (trained on ImageNet) weights. To validate the performance of each model, four performance indicators are used: accuracy, recall, precision, and F1-score. Using the publicly available CCIC dataset, the suggested technique on AlexNet outperforms existing models with a testing accuracy of 99.90 % , precision of 99.92 % , recall of 99.80 % , and F1-score of 99.86 % for crack class. Our approach is further validated by using an external dataset, BWCI, available on Kaggle. Using BWCI, models VGG16, ResNet18, DenseNet161, and AlexNet achieved the accuracy of 99.90 % , 99.60 % , 99.80 % , and 99.90 % respectively. This proposed transfer learning-based method, which is based on the CNN method, is demonstrated to be more effective at detecting cracks in concrete structures and is also applicable to other detection tasks. [ABSTRACT FROM AUTHOR]

In this writeup, we have discussed the role of ideals on σ-topological spaces. Using this idea, we have also studied and discussed two operators ()∗σ and ψσ. We have extended this concept to a new generalized set and investigated some basic properties of these concepts using ()∗σ and ψσ operators. [ABSTRACT FROM AUTHOR]

The purpose of the study is to present a model plan for developing an effective digital maintenance system with the help of institutional repository software in university library premises. This work is an investigative study of digital maintenance activities for sustainable development of the digital publications and intellectual outputs of universities in Bangladesh. The researchers investigated the university and university website and found that only 11% university libraries were active in preserving their digital resources while 89% of university libraries were either in the dark or less reluctant to adopt the system. Researchers realized that due to lack of proper guidelines and an ideal model plan, most of the university libraries were far behind in adopting a repository system for safeguarding their intellectual outputs. Hence this study describes a model plan for the university libraries of Bangladesh to create a sustainable preservation system easily and effectively. The model plan in this study was based on observation and review of the literature in the concerned field. All university authorities can follow the mentioned model for sustainable maintenance of their intellectual digital assets. [ABSTRACT FROM AUTHOR]

Geopolitical risks significantly impact global energy consumption, hindering material trade and influencing policy decisions. Specifically, the Russian uranium supply for US nuclear energy production faces geopolitical risks despite being exempt from ongoing sanctions imposed by Western and European entities during the Russia-Ukraine conflict. We investigate the effect of global, Russian, and US geopolitical risks on US nuclear-energy consumption driven by Russian uranium exports from January 1996 to December 2019. The cross-quantilogram analysis reveals a negative influence of global geopolitical risks on Russian uranium export-driven US nuclear-energy consumption in lower quantiles, and a positive effect in medium to upper quantiles under long memory. Interestingly, Russian geopolitical risks do not have any significant effect, while US geopolitical risks positively impact from the medium to upper quantiles in extended memory. Hence, our policy suggestion is solely concerned with adequately dealing with global geopolitical risks under the global governance platform to enhance worldwide uranium trade for nuclear energy consumption in the USA. • Studies global, Russian and US geopolitical risks' effects on Russian uranium export-driven US nuclear energy use. • Applies the cross-quantilogram and wavelet coherency analysis approaches. • Finds global geopolitical risks' negative impact on Russian uranium export-driven US nuclear energy use. • Russian own geopolitical risks have no significant effect on Russian uranium export-driven US nuclear energy use. • US geopolitical risks affects Russian uranium export-driven US nuclear power consumption. [ABSTRACT FROM AUTHOR]

In the pursuit of sustainable development, the presence of a robust financial sector plays a crucial role in the advancement of the green movement. However, the green bond market faces vulnerability due to the existence of geopolitical threats. This study employs empirical methods to investigate the quantile dependence of geopolitical risks originating from Russia and Ukraine on green finance. Specifically, the cross-quantilogram and partial cross-quantilogram approaches are utilized, analyzing daily data spanning from February 24, 2022, to May 26, 2023. The findings obtained from the cross-quantilogram approach reveal a pronounced negative quantile dependence between the geopolitical risks of both countries and green finance during bearish market conditions (q.10–q.40) in the short-term memory. Conversely, during the initial memory, a strong positive dependence is observed at the bullish (q.70–q.95) market conditions. However, no significant dependence is detected at either bearish or bullish market states concerning long-term memory. Interestingly, when employing the partial cross-quantilogram approach, a slightly negative association is observed at both bearish and bullish market conditions for long-term memory. These empirical findings provide valuable insights into the decision-making process for green investments, taking into account the dynamic nature of market conditions influenced by geopolitical risks stemming from the Russia–Ukraine conflict. Therefore, it is prudent for the governments to establish collaborations with private sectors and international agencies to fund green projects, thereby expediting green investment and mitigating geopolitical risks, with a focus on long-term investment, given the current absence of significant long-term detrimental effects of geopolitical risks on green bonds at the global level. [ABSTRACT FROM AUTHOR]

The global shift towards clean energy sources necessitates a substantial supply of critical minerals to drive renewable energy technologies such as concentrating solar-thermal power (CSP) and solar photovoltaics (PV). This growing demand for mineral resources underscores the need to examine the import-demand function of minerals in relation to solar energy generation in China, spanning the period from 1996 to 2019. By employing both conventional autoregressive distributed lag (ARDL) and dynamic ARDL (DARDL) simulation methods, our study reveals a positive and significant long-term relationship between mineral import demand and installed solar capacity. Furthermore, our analysis demonstrates that the average mineral price elasticity adheres to the Marshallian demand premise, while the substitution effect between mineral prices and oil prices contradicts this premise. Conversely, the impact of exchange rates on mineral import demand is found to be negligible. However, our findings indicate that long-term economic growth fosters mineral import demand. To ensure the robustness of our results, we conduct a dynamic ARDL simulation-based counterfactual analysis to measure the threshold level of mineral response to (±) shocks in the regressors, including oil and mineral prices, exchange rates, and GDP growth. These findings provide valuable insights for policy recommendations in China, emphasizing the importance of maximizing mineral resources to augment solar power production and achieve the global objective of a carbon-neutral landscape in the twenty-first century. [ABSTRACT FROM AUTHOR]

Electrification can advance sustainability and social development. This study investigates the contribution of electrification to various aspects of societal development, i.e., educational development, human development, and gender inequality, within the purview of economic globalization, economic growth, and governmental policies in Bangladesh, covering the data during 1990–2019. Employing the dynamic autoregressive distributed lag (DARDL) simulation approach, we have established a positive impact of electricity on the decomposed parameters of social development in Bangladesh. Finally, we employ the DARDL simulation-based counterfactual analysis procedure, testing the effects of 1% and 5% (±) shocks to the regressors and their effects on the dependent variables. • We examine the role of electrification in Bangladesh's social development. • We utilize the dynamic ARDL simulation co-integration and counterfactual techniques. • We find the favourable effect of electrification on societal dynamics. • Economic globalization and economic growth have a positive role in social development. • Governmental policy has a heterogenous impact on social development. [ABSTRACT FROM AUTHOR]

Many researchers investigate the socio-demographic and economic factors-induced energy consumption, particularly fossil fuel-based non-renewable energy consumption, but there exists a scarcity to study on the same factors-driven renewable energy consumption along with institutional quality factor. Given this, our research strives to analyse the relative influence of income growth, foreign direct investment, domestic investment, urbanization, physical infrastructure, and institutional quality on renewable and non-renewable energy consumption in Bangladesh for the period of 1990–2019 using the dynamic ARDL (DARDL) simulations method. The empirical findings divulge that income growth shows positive and negative effect on renewable and non-renewable energy consumption, respectively. Domestic investment has positive effect for renewable and non-renewable energy consumption. Foreign direct investment is found to have positive influencing factor for renewable energy consumption. Urbanization negatively impacts renewable energy consumption but urbanization affects non-renewable energy consumption positively. Physical infrastructure is a negative and positive determinant of renewable and non-renewable energy consumption, respectively. Institutional quality positively affects renewable energy consumption. The robustness of the results is comparatively exhibited using the DARDL simulations area plots where 20% positive and negative shocks to the predictors on the predicted variables are presented. [Display omitted] • Influencing factors of renewable and non-renewable energy consumption are discussed. • Economic growth promotes renewable energy consumption. • Domestic investment adds to renewable energy consumption. • Foreign direct investment promotes and declines non-renewable energy consumption. • Physical infrastructure is a negative and significant determinant of renewable energy consumption. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of the study is to identify the big data adoption in information institutions as well as to justify the understanding and expertise level of information professionals. The study tried to identify the adoption of big data in the information institutions of Bangladesh. Materials and Methods: A structured questionnaire was adapted cautiously for conducting the study. The Questionnaire was sent to more than 50 professionals of information institutions via email and FB messenger. The respondents are the professionals and faculty members who had the minimum qualification of bachelor/master/postgraduate degree in information science and library management. Among them, 25 respondents from 20 information institutions replied. Result: The study found that most of the information institutions yet to adopt big data properly in Bangladesh. Twenty percent of institutions adopted big data whereas eighty percent did not adopt it even some of the institutions are not aware of big data. The study found that sixty percent of professionals are not aware of the monthly amount of data used in their institutions. The results found that information professionals are, in general, positive in big data adoption. The study also assessed the understanding level of them. Conclusion: The effort has been made to explore the current awareness activities of big data and its adoption in the information institutions of Bangladesh for the first time that will trigger further study on big data. [ABSTRACT FROM AUTHOR]

Mutagenesis is an important technique for creating novel mutants having improved agronomic traits. In this study, LD50 was determined at 807 Gy depending on the germination percentage of tomato seeds irradiated with cobalt-60, using absorbed gray (Gy) dose of 50, 100, 150, 200, 250, 500, and 1000 Gy with control. GR30 and GR50 values were 214 and 502 Gy based on the regression formula on seedling length. Though LD50 is important, the dose range between 214(GR30) and 502(GR50) is more functional to get desirable mutation as the survival of the mutants is more important than germination. The variation was observed in all of the agronomical traits among the treatments. Most of the morphological traits were found better at 250 Gy in comparison with the control and the value decreased sharply at higher doses followed. The highest weight of single fruit was 145.33 g recorded at 250 Gy while the lowest was 70.67 g noted at 500 Gy. The highest fruit yield per plant was 1270 gm obtained at 250 Gy and the lowest was 800 gm found at 500 Gy. Shelf life was found better (34 days) at the 250 Gy dose level and the lowest was 6 days got in the control treatments. [ABSTRACT FROM AUTHOR]

This paper investigates the nexus between energy consumption and economic growth in Bangladesh over the period 1971–2018 using the autoregressive distributed lag (ARDL) approach to cointegration. The main contribution of this study is the inclusion of exogenous dynamic (globalisation) and endogenous factor (political risk indicator measured by political terror scale (PTS)) to the energy consumption–economic growth nexus. The study explores an energy consumption–economic growth nexus where globalisation and PTS have both positive and negative influences on this relationship in the short run and long run. The Toda–Yamamoto Granger causality test confirms the feedback hypothesis, that is bidirectional causal relationship between energy consumption and economic growth, and the result is further verified by the impulse response function. Therefore, policymakers should enhance the availability of energy for people and industries to continue the existing momentum of economic growth. Besides, the government should cautiously deal with both the globalisation and political risk issues about energy consumption–economic growth nexus in Bangladesh. [ABSTRACT FROM AUTHOR]

Arsenic, a major environmental toxicant and pollutant, is a global public health concern. Among its many adverse effects, arsenic is immunotoxic, but its effects on human neutrophil functions are not yet well-defined. In this study, we aimed to evaluate the in vitro effects of acute low-dose NaAsO2 exposure on human polymorphonuclear neutrophils (PMNs) for 12 h on the following innate defense mechanisms: formation of neutrophil extracellular traps (NETs), production of reactive oxygen species (ROS), and phagocytosis. Phorbol myristate acetate (PMA) was added to induce NETs formation, which was quantified by measuring cell-free extracellular DNA (cf-DNA), myeloperoxidase-conjugated (MPO)-DNA and neutrophil elastase-conjugated (NE)-DNA, and confirmed by immunofluorescence labeling and imaging. Extracellular bactericidal activity by NETs was evaluated by co-culturing Escherichia coli and PMNs in the presence of a phagocytic inhibitor. Levels of NETs in the culture medium after PMA stimulation was significantly lower in PMNs pre-exposed to arsenic than those not exposed to arsenic. Immunofluorescence staining and extracellular bactericidal activity by NETs revealed similar results. Phagocytosis and ROS production by PMNs were also significantly reduced by arsenic pre-exposure. Together, our findings provide new insights in arsenic immunotoxicity and suggest how it increases susceptibility to infectious diseases in humans. [ABSTRACT FROM AUTHOR]

In recent years, the obesity epidemic has escalated into a serious public health catastrophe that is only getting worse. However, research into the pathophysiological pathways behind the obesity development and the illnesses that it is associated with is ongoing. In the last decades, it is now clear that the gut microbiota plays a significant role in the genesis and progression of obesity and obesity-related illnesses, particularly changes in its metabolites and composition as obesity progresses. Here, we provide a summary of the processes by which variations in gut metabolite levels and the composition of gut microbiota affect obesity and associated disorders. The bacteria residing in the gut release several chemicals that influence the appetite control, metabolism, and other systems. Since it can either encourage or restrict the deposition of fat in several different ways, the gut microbiota's role in obesity is debatable. Additionally, we go over potential therapeutic approaches that could be utilized to alter gut microbiota composition and focus on the important metabolic pathways associated with obesity and metabolic disorders linked to obesity. [Display omitted] [ABSTRACT FROM AUTHOR]

In the solar industry, there has been a growing interest in inorganic cubic perovskite materials due to their remarkable structural, electronic, and optoelectronic properties. Through the use of the first-principles density functional theory (FP-DFT), we thoroughly analyze the impact of strain-induced structural, electronic and optical properties of Sr 3 AsCl 3. At Γ point, the unstrained Sr 3 AsCl 3 compound exhibits a direct bandgap of 1.649 eV/2.473 eV for PBE/HSE. When the relativistic spin-orbital coupling (SOC) effect is accounted for, the bandgap of the Sr 3 AsCl 3 compound is reduced to 1.589 eV/2.41 eV for PBE/HSE. Besides, the bandgap of Sr 3 AsCl 3 exhibits a decreasing trend under compressive strain and an increasing trend under tensile strain. The photon energy spectrum shows a blue shift in the absorption-coefficient, electron loss function, and dielectric function under compressive strain, while a red shift is observed under tensile strain. Dielectric constant of Sr 3 AsCl 3 's spikes are found to shift toward lesser photon energy under growing compressive strain (red-shift), while shifting toward upper photon energy under growing tensile strain (blue-shift). Consequently, the Sr 3 AsCl 3 compound is particularly well suited for use in solar cells for energy generation and light control. [Display omitted] • Structural, electronic, and optical properties of inorganic cubic perovskite Sr 3 AsCl 3 were studied utilizing the first-principles density-functional theory (FP-DFT) in Quantum Espresso. • In the calculation of electronic and optical properties, the influences of compressive and tensile strains were also investigated. • The effect of spin-orbital coupling (SOC) was introduced in the calculation of electronic and optical properties. [ABSTRACT FROM AUTHOR]

Understanding biodiversity and community composition is a prerequisite to sustainable exploitation and conservation of fisheries. We assessed the spatial and seasonal patterns of fish community composition and biodiversity in seasonal no‐take riverine sanctuaries in Bangladesh, which aim to conserve the anadromous hilsa shad (Tenualosa spp. and Hilsa keele). Fish samples were collected during monsoon, as well as pre‐ and postmonsoon, from five sites within two sanctuaries and one site in an open fishing area. Although total abundance was similar along the rivers, species richness was significantly higher at the open fishing site due to its connectivity to nearby habitats. The diversity apparently decreased in a downstream direction. Fish communities at two upstream sites were separated from other sites in multivariate space largely due to higher abundance of hilsa at downstream sites and presence of floodplain‐oriented species at the two upstream sites. Short body length and high trophic level at all sites indicated that fish communities were overexploited. Our results also indicated that riverine hilsa sanctuaries in Bangladesh are rich in fish species diversity and support several threatened species designated by the International Union for Conservation of Nature (IUCN). Our study also suggested that since hilsa abundance shapes community patterns, it can therefore impact riverine ecosystem functioning in the sanctuary areas. The findings of this study can serve as an important baseline for future biodiversity assessment, conservation and impact assessment of conservation in rivers, and therefore help to establish multispecies ecosystem‐based management of riverine fisheries around the world. [ABSTRACT FROM AUTHOR]

This study used multi-date Landsat images to quantify mangrove cover changes in the whole of Bangladesh from 1976 to 2015. Images were pre-processed with an atmospheric correction using Dark Object Subtraction (DOS) and Relative Radiometric Normalization (RRN) using Pseudo-Invariant Features (PIFs). Land Use/Land Cover (LU/LC) classification map was generated using Maximum Likelihood (MaxLike) algorithm, indicating the areal extent of mangroves increased by 3.1% between 1976 and 2015, where 1.79% of this increase occurred between 2000 and 2015. Though mangrove areas remained almost constant in the Sundarbans, Chakaria Sundarbans has almost disappeared between 1976 and 1989. The overall accuracy of Landsat MSS, TM, ETM+, and L8 OLI classified images were 80%, 80%, 87%, and 97% respectively. The study also found deforestation, shrimp & salt farm, coastal erosion and sedimentation, and mangrove plantation could be responsible for mangrove changes in Bangladesh. [ABSTRACT FROM AUTHOR]

Most researchers consider CO 2 emissions to be the primary indicator of environmental degradation. Similarly, ecological footprint appears to be a significant proxy for environmental degradation in recent research due to its multifaceted impact on the natural environment. With this in mind, this study investigates fluctuations in CO 2 emissions and ecological footprint as indicators of environmental degradation in Bangladesh from 1980 to 2020, and how they are influenced by net savings, natural resource depletion, technological innovation, and democracy. The non-linear ARDL (NARDL)-based asymmetric analysis finds that positive changes in net savings, natural resource depletion, and democracy positively impact both parameters of environmental degradation in the long run. On the other hand, a positive change in technological innovation reduces these parameters in the long run. Likewise, negative changes in net savings and technological innovation reduce environmental degradation. In contrast, negative changes in natural resource depletion and democracy exacerbate these two parameters and degrade environmental quality in the long run. However, there are some variations in the short-run influence of the predictors on the predicted variable. Overall, the findings of this study suggest that policymakers must strategically exploit natural resources, net savings, technology diffusion, and democratic principles to preserve the natural environment in Bangladesh. [ABSTRACT FROM AUTHOR]

Aquaculture involves cultivating various marine and freshwater aquatic creatures within regulated environments. Monitoring the aquatic environmental conditions in real-time is crucial for successful fish farming. The Internet of Things (IoT) offers significant potential for real-time monitoring, and this paper introduces an IoT framework designed for efficient monitoring and effective control of various water-related aquatic environmental parameters. The proposed system is implemented as an embedded system utilizing sensors and an Arduino microcontroller. In cultivating pond water, diverse sensors such as pH, temperature, and turbidity sensors are deployed, with each sensor connected to an Arduino Uno-based microcontroller board. These sensors collect data from the water, which is then stored as a CSV file in an IoT cloud platform called ThingSpeak through the Arduino microcontroller. To gather data for analysis, we conducted measurements across five ponds, varying in size and environmental conditions. After getting the real-time data, we compared our experimental results with the standard reference values. As a result, we could take the decision of whether a pond is suitable for cultivating fish or not. After that, we labeled the data with 11 fish categories: Katla, sing, prawn, shrimp, rui, tilapia, pangas, karpio, magur, silver carp, and koi. The data was analyzed using 10 machine learning (ML) algorithms, including J48, Random Forest, K Nearest Neighbors (K-NN), K*, Logistic Model Tree (LMT), Reduced Error Pruning Tree (REPTree), Jumping Rule Inference with Pruned Search (JRIP), Partial Decision Trees (PART), Decision Table, and Logit boost. After experimental analyses, it was discovered that only three of the five ponds were ideal for fish farming, and those three ponds only met the required standards for pH, Temperature, Turbidity, and Conductivity. Among the state-of-art machine learning algorithms, Random Forest achieved the highest score of performance metrics as accuracy 94.42%, kappa statistics 93.5%, and Avg. TP Rate 94.4%. In addition, we calculated the Biochemical Oxygen Demand (BOD), Chemical Oxygen Demand (COD), and Dissolved Oxygen (DO) for one scenario. This study includes prototype hardware details of the proposed IoT system. [ABSTRACT FROM AUTHOR]

Abstract The present study investigates the spatiotemporal characteristics of aerosol optical depth (AOD), cloud properties, and TOA (Top Of Atmosphere) Net Cloud Radiative Effect (Net CRE) using MODIS (Moderate Resolution Imaging Spectroradiometer) Terra and CERES (Clouds and the Earth's Radiant Energy System) products over Bangladesh for the period 2001–2016. This study also explores the backward trajectory using a HYSPLIT (Hybrid Single Particle Lagrangian Integrated Trajectory) model from the National Oceanic and Atmospheric Administration (NOAA) to discover the origins of air masses. Results show annual values of AOD (0.55), Cloud Fraction (CF, 0.66), CER (Cloud Effective Radius, 14.89), COT (Cloud Optical Thickness, 15.25), CTP (Cloud Top Pressure, 639.17), CTT (Cloud Top Temperature, 262.52), WV (Water Vapor, 4.48), and Net CRE (−13.06) over Bangladesh. A seasonally peak is recorded for AOD (0.64) in MAM while for CF (0.96), CER (17.24), COT (21.12), WV (6.86), and Net CRE (−34.44) the peak is in JJA, and for CTP (884.06) and CTT (284.17) it is in DJF. By monthly the peak is recorded in June for AOD (0.73) and COT (24.86); for CER (17.87), WV (7.26), and Net CRE (−45.38) it is in July; for CF (0.97) it is in July/August; CTP (900.89) and for CTT (285.75) it is in February. Regression analysis shows annual increasing trends for AOD, CF, WV, COT, CTP, and CTT with negative trends for CER and Net CRE. AOD shows increasing trends in all seasons, whereas CF, CER and COT show increasing trends in DJF and MAM only. CTP and CTT show increasing trends in JJA and SON. WV shows an increasing trend in MAM, JJA, and DJF, whereas Net CRE shows an increasing trend in MAM and SON. Relationship study provides a better conclusion of AOD and cloud interaction based on the analysis of positive and negative correlation values over the study region. The backward trajectory indicated that the air masses originated from the Bay of Bengal, India, Nepal, Pakistan, and Iran. This study may be considered as a base document for further study on aerosols over Bangladesh using climate model simulation for the projection period. Graphical abstract Unlabelled Image Highlights • The relationship of AOD against cloud parameters and Net CRE over Bangladesh. • Aerosol and cloud products from Terra-MODIS are used for the period 2001–2016. • TOA Net CRE product from CERES sensor is also used in this study. • AOD, CF, WV, COT, CTP, and CTT show the increasing trends. • A NOAA HYSPLIT model exhibits that source of aerosol in Bangladeshare outside. [ABSTRACT FROM AUTHOR]

Effective texture feature is an essential component in any content‐based image retrieval system. In this study, new texture features based on image enhancement technique are presented. The authors have effectively exploited power‐law transform (PLT) to extract new spectral texture features called PLT‐based spectral features. Extensive experiments on the Brodatz texture database and Salzburg Textures image database prove the effectiveness of the proposed techniques and show that the proposed features significantly outperform the widely used Gabor and curvelet features. The proposed features are also compared with recently published Gaussian copula models of Gabor feature and local tetra patterns (LTrP). The experimental results confirm that the proposed features have more tolerance to scale, orientation and illumination distortion than the state‐of‐the‐art Gabor, curvelet, Gaussian copula models of Gabor and LTrPs. [ABSTRACT FROM AUTHOR]

This paper will discuss a new operator on ideal topological spaces and characterizations of some generalized open sets. Further, it will discuss some decompositions of generalized continuities and a brief discussion on resolvability. [ABSTRACT FROM AUTHOR]

The Internet of Things (IoT) has positioned itself globally as a dominant force in the technology sector. IoT, a technology based on interconnected devices, has found applications in various research areas, including healthcare. Embedded devices and wearable technologies powered by IoT have been shown to be effective in patient monitoring and management systems, with a particular focus on pregnant women. This study provides a comprehensive systematic review of the literature on IoT architectures, systems, models and devices used to monitor and manage complications during pregnancy, postpartum and neonatal care. The study identifies emerging research trends and highlights existing research challenges and gaps, offering insights to improve the well-being of pregnant women at a critical moment in their lives. The literature review and discussions presented here serve as valuable resources for stakeholders in this field and pave the way for new and effective paradigms. Additionally, we outline a future research scope discussion for the benefit of researchers and healthcare professionals. [ABSTRACT FROM AUTHOR]

The research was conducted to evaluate the problems and prospects of adopting conservation agriculture in Jamalpur and Bogra districts of Bangladesh. A total of 120 farmers (20 from focal and 100 from control group) were surveyed for collecting necessary data and information. A combination of descriptive statistics and mathematical techniques was used to analyze the data. Focal farmers followed the basic principles of conservation agriculture but control farmers continued conventional crop farming practices. Focal farmers were more profitable compared to control farmers in terms of wheat and bean production. Less production due to minimum tillage, difficulties in maintenance, lack of extension service etc. was the major problems faced by the farmers. Knowledge on soil conservation and soil quality improvement, use of organic fertilizer, etc. was found as strengths; management of crop residue, scarcity of cowdung, etc. were found as weaknesses; labour opportunities, market demand, etc. were found as opportunities; and climate change and price fluctuation were found as threats of adopting conservation agriculture. Regular extension contact, arrangement of training programmes and input support are to be ensured by different government and non-government organizations to motivate farmers for adopting conservation agriculture practice. [ABSTRACT FROM AUTHOR]

A free-standing, 3D, macro/microstructured atomic-cobalt/cobalt-oxide-reduced-graphene-oxide (Co/Co3O4-Gr) composite has been developed for complete water splitting. The self-assembled porous morphology associated with the metal/metal oxide active sites makes the whole surface of the electrode conducive toward catalyzing hydrogen and oxygen evolution in alkaline media at a low onset potential. The liquid-crystal-mediated free-standing electrocatalyst shows oxygen evolution at the onset potential of 1.38 V and at the potential of 1.66 V for a current density of 10 mA cm−2. These potentials are comparable to the corresponding values for Ru/C (1.46 and 1.62 V, respectively). In addition, the promising hydrogen evolution performance of our composite compared to Pt/C in alkaline media makes it an efficient bifunctional electrocatalyst for comprehensive water splitting, as well as provides guidance for future electrochemical energy material technologies. [ABSTRACT FROM AUTHOR]

• Examines middle-income nations' energy infrastructure-total productivity factor (TFP) nexus. • Constructs a novel energy infrastructure index using an unobserved component model (UCM). • Finds energy infrastructure-TFP nexus for both aggregated and disaggregated samples of middle-income economies. • Reveals a more intensified role of the energy infrastructure of upper-middle-income than the lower-middle-income countries. • Checks the robustness of the study findings using the Wavelet coherence analysis procedure. Even though there are numerous empirical investigations on energy consumption's impact on economic growth, the relationship between energy infrastructure and total factor productivity (TFP) appears to be understudied in academic literature. The present study examines the dynamic nexus between energy infrastructure and TFP for the panel data of 67 upper and middle-income countries during 1990–2019. First, we contribute to devising a comprehensive energy infrastructure index by covering qualitative and quantitative dimensions of energy resources using the unobserved-component model. Second, this study investigates the short and long-run relationship between the variables using the cross-sectional autoregressive distributed lag (CS-ARDL) approach. The investigation procedure confirms that energy infrastructure significantly and positively increases TFP in both the long and short run. In addition, diverse macroeconomic dynamics, e.g., foreign direct investment, human capital, technological advancement and trade openness, also positively influence TFP in these countries. Third, by categorizing the sample into upper-middle income and lower-middle income countries, this study finds higher coefficients of the energy infrastructure of the upper-middle-income group than the lower-middle-income economies to stimulate TFP. Furthermore, this study's results remain robust across the alternate estimation parameter, the wavelet coherence analysis technique. Finally, the study proposes some significant policy suggestions. [ABSTRACT FROM AUTHOR]

The aim of this paper is to introduce a new topology with the help of a-open sets. For this job, we shall define two new types of set and discuss its properties in detail and characterize Njastad.s α-open sets and Levine.s semi-open sets through these new types of set. [ABSTRACT FROM AUTHOR]

Coring is a surgical procedure in bone biopsy retrieval and dental/orthopaedic procedures, which may cause thermal damage to bone tissues adjacent to the coring zone. This study was performed to determine the temperature rise in bone by coring using a semi-empirical thermocouple approach. Concurrently, a custom-made dynamometer was used to measure the cutting and thrust forces during coring bovine cortical bone samples. The experimental results indicated that the cutting force, cutting speed, and depth of cut significantly affect the temperature rise in the cutting zone during coring process. In addition, acute temperature rises in the cutting zone occurred when the cutting speed exceeded threshold levels. The limited capacity of heat dissipation during coring is most likely responsible for such a sharp temperature rise with increasing cutting speed. Moreover, it was observed that the maximum size of potential thermal damage zone could reach to 3.0 mm in depth from the surface of the coring hole, assuming that thermal damage would occur when the temperature is greater than 47°C. Thus, proper cutting conditions need to be selected to avoid the potential thermal damage to bone during the coring procedures. [ABSTRACT FROM AUTHOR]

The capture and storage of CO2 have been suggested as an effective strategy to reduce the global emissions of greenhouse gases. Hence, in recent years, many studies have been carried out to develop highly efficient materials for capturing CO2. Until today, different types of porous materials, such as zeolites, porous carbons, N/B-doped porous carbons or metal-organic frameworks (MOFs), have been studied for CO2 capture. Herein, the CO2 capture performance of new hybrid materials, graphene-organic frameworks (GOFs) is described. The GOFs were synthesized under mild conditions through a solvothermal process using graphene oxide (GO) as a starting material and benzene 1,4-diboronic acid as an organic linker. Interestingly, the obtained GOF shows a high surface area (506 m2 g−1) which is around 11 times higher than that of GO (46 m2 g−1), indicating that the organic modification on the GO surface is an effective way of preparing a porous structure using GO. Our synthetic approach is quite simple, facile, and fast, compared with many other approaches reported previously. The synthesized GOF exhibits a very large CO2 capacity of 4.95 mmol g−1 at 298 K (1 bar), which is higher those of other porous materials or carbon-based materials, along with an excellent CO2/N2 selectivity of 48.8. [ABSTRACT FROM AUTHOR]

This study evaluated threeTrichodermastrains (T. harzianumTR05,T. virensTR06 andT. asperellumTR08) originating from Bangladesh as potential biological control agents against collar rot of tomato under greenhouse conditions. After seed treatment with TR05, a disease incidence of collar rot (5.36%) was lower than for TR06 (34.2%) and TR08 (20.8%). Germination percentage of tomato was highest for TR05 (90.3%). In soil treatment, inoculation with TR08 resulted in the lowest disease incidence (9.78%), and the disease incidence was statistically no different from that for TR05 (16.4%). Thus, TR05 and TR08 have potential as biological control agents of collar rot in tomato. [ABSTRACT FROM PUBLISHER]

To identify an effective ligand that binds to a G-quadruplex structure but not a double-stranded DNA (dsDNA), a set of biophysical and biochemical experiments were carried out using newly synthesized cyclic ferrocenylnaphthalene diimide (cFNDI, 1 ) or the non-cyclic derivative ( 2 ) with various structures of G-quadruplex DNAs and dsDNA. Compound 1 bound strongly to G-quadruplexes DNAs (10 6 M −1 order) with diminished binding to dsDNA (10 4 M −1 order) in 100 mM AcOH-AcOK buffer (pH 5.5) containing 100 mM KCl. Interestingly, 1 showed an approximately 50-fold higher selectivity to mixed hybrid-type telomeric G-quadruplex DNA ( K = 3.4 × 10 6 M −1 and a 2:1 stoichiometry) than dsDNA ( K = 7.5 × 10 4 M −1 ) did. Furthermore, 1 showed higher thermal stability to G-quadruplex DNAs than it did to dsDNA with a preference for c-kit and c-myc G-quadruplex DNAs over telomeric and thrombin binding aptamers. Additionally, 1 exhibited telomerase inhibitory activity with a half-maximal inhibitory concentration (IC 50 ) of 0.4 μM. Compound 2 showed a preference for G-quadruplex; however, the binding affinity magnitude and preference were improved in 1 because the former had a cyclic structure. [ABSTRACT FROM AUTHOR]

Identification of biallelic CNPY3 mutations in patients with epileptic encephalopathy and abnormal electroencephalography findings of Cnpy3 knock-out mice have indicated that the loss of CNPY3 function causes neurological disorders such as epilepsy. However, the basic property of CNPY3 in the brain remains unclear. We generated C-terminal 2xHA-tag knock-in Cnpy3 mice by i-GONAD in vivo genome editing system to investigate the expression and function of Cnpy3 in the mouse brain. 2xHA-tagged Cnpy3 was confirmed by immunoblot analysis using anti-HA and CNPY3 antibodies, although HA tagging caused the decreased Cnpy3 protein level. Immunohistochemical analysis of Cnpy3 2xHA knock-in mice showed that Cnpy3-2xHA was predominantly expressed in the neuron. In addition, Cnpy3 and Cnpy3-2xHA were both localized in the endoplasmic reticulum and synaptosome and showed age-dependent expression changes in the brain. Conventional Cnpy3 antibodies could not allow us to investigate the distribution of Cnpy3 expression in the brain, while HA-tagging revealed the expression of CNPY3 in neuronal cells. Taken together, we demonstrated that Cnpy3 2xHA knock-in mice would be useful to further elucidate the property of Cnpy3 in brain function and neurological disorders. • The generation of mice with HA-tagged Cnpy3 revealed that the protein is predominantly expressed in the neuron. • Cnpy3 was localized not only in the endoplasmic reticulum but also synaptosome. • Cnpy3 was highly expressed during the early postnatal period in the brain. • C terminus HA-tagging accelerated the degradation of the Cnpy3 protein. [ABSTRACT FROM AUTHOR]