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The aim of this multi-country, cluster-randomized trial is to test the impact of pharmacy-based health promotion to reduce the blood pressure of individuals with hypertension over a 12-month period in Bangladesh and Pakistan. The trial will be implemented with two arms. In Bangladesh, the estimated sample size is around 3600 hypertensive patients. In Pakistan, we will select samples equivalent to 10% of the participants from Bangladesh, comprising 360 hypertensive patients from four pharmacies. Community pharmacies will be randomized into one of two parallel groups (allocation ratio 1:1). Pharmacy professionals in the treatment arm will provide their patients with educational training and counseling, as well as phone calls/mobile text messages and care coordination in the health sector, as part of the intervention. The study will be conducted in three phases: a baseline survey with intervention, a midline survey with intervention and follow-up, and an endline survey with impact evaluation. The primary outcome of the study will be BP. The secondary outcomes will be BP controlled to target, treatment adherence, quality of life, mortality or hospital admission rates resulting from hypertension and its related complications, incremental cost per health-related quality of life gained, knowledge on healthy lifestyle and dietary behavior, and change in the prevalence of current smoking status. [ABSTRACT FROM AUTHOR]

Mass spectrometry imaging (MSI) is essential for visualizing drug distribution, metabolites, and significant biomolecules in pharmacokinetic studies. This study mainly focuses on imipramine, a tricyclic antidepressant that affects endogenous metabolite concentrations. The aim was to use atmospheric pressure matrix-assisted laser desorption/ionization (AP-MALDI)-MSI combined with different dimensionality reduction methods to examine the distribution and impact of imipramine on endogenous metabolites in the brains of treated wild-type mice. Brain sections from both control and imipramine-treated mice underwent AP-MALDI-MSI. Dimensionality reduction methods, including principal component analysis, multivariate curve resolution, and sparse autoencoder (SAE), were employed to extract valuable information from the MSI data. Only the SAE method identified phosphorylcholine (ChoP) as a potential marker distinguishing between the control and treated mice brains. Additionally, a significant decrease in ChoP accumulation was observed in the cerebellum, hypothalamus, thalamus, midbrain, caudate putamen, and striatum ventral regions of the treated mice brains. The application of dimensionality reduction methods, particularly the SAE method, to the AP-MALDI-MSI data is a novel approach for peak selection in AP-MALDI-MSI data analysis. This study revealed a significant decrease in ChoP in imipramine-treated mice brains. [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]

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

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]

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]

In a time of environmental degradation and increasing demand for safe food production, traditional fish farming is gaining global attention. Utilizing indigenous agricultural methods founded on traditional knowledge contributes to sustainability by safeguarding the ecosystem and preserving biodiversity. However, it is still less studied whether traditional farming systems based on indigenous knowledge currently in place are improving the socioeconomic conditions of farmers. Hence, this study was conducted with the following objectives: (i) to reveal the present status of traditional fish farming systems, (ii) to define the socioeconomic profile of the farmers, (iii) to identify the problems associated with traditional fish farming, and (iv) to show the inter-relationship between fish farming and socioeconomic development. For achieving these objectives, data were collected from 100 small-scale fish farmers from a rural coastal area of Bangladesh through a well-structured questionnaire, focus group discussion, and cross-check interviews. Our findings showed that most of the homestead ponds were small-sized (44%) and shallow (61%) where a polyculture system was prevalent (91%). The majority of the ponds (77%) were found to be perennial, 60% of which had single ownership. Socioeconomic data revealed that the highest number of farmers (42%) earned 1000.00 to 1500.00 USD annually, and 62% of the respondents took fish farming as their secondary occupation. Among the farmers, 62% had primary education, whereas 7% had no education, and only 26% of the farmers had official training in fish farming, indicating that culture management was mainly based on indigenous knowledge. A total of 55% of the farmers had 5 to 10 family members, and 80% of them lived in joint families. Furthermore, 40% of the farmers owned tin shed houses, whereas the maximum (60%) utilized katcha toilets. However, almost half of the farmers (57%) utilized their own funds for fish farming, and the majority (90%) had access to their own tube well. The study found that the biggest obstacles to fish farming were pressure from large families, a lack of education and training, a lack of quality seed and feed, outbreaks of fish diseases, an inadequate supply of water during the dry season, and a lack of adequate funding. However, Pearson correlation showed that there was a significant positive association between age and experience (r = 0.908, p < 0.01) and age and income (r = 0.326, p < 0.01). Multiple regression analyses also demonstrated that age and experience in fish farming played a significant role in increased annual income. In conclusion, 94% of the respondents claimed that fish farming had improved their socioeconomic situation. Homestead pond fish farming through indigenous knowledge increased household fish consumption with a source of protein and micronutrients, improved dietary diversity, and generated extra household income, which inferred their better sustenance. [ABSTRACT FROM AUTHOR]

Graphyne has attractive electronic properties that make it a possible replacement of silicon in FET technology. In FET technology, the goal is to achieve low power dissipation and lower subthreshold swing. In this study, we focused on achieving these goals and studied the electronic properties of α-graphyne nanoribbons. We simulated the transfer and output characteristics of an α-graphyne ballistic nanoribbon FET. We used the tight-binding model with nearest-neighbor approximation to obtain the band structure which gives the same band structure as the one found from the DFT. In order to simulate the I-V characteristics of the transistor we used the non-equilibrium Green's function (NEGF) formalism. The results show that the modeled FET can provide a high Ion/Ioff ratio and low subthreshold swing. We also studied the effects of defects as defects cannot be avoided in any practical device. The study shows that the Ion/Ioff ratio and subthreshold swing improves as defects are added, but the delay time and dynamic power dissipation worsen. [ABSTRACT FROM AUTHOR]

A cheap and disposable pencil graphite electrode (PGE) was developed by the incorporation of amine groups (Am-PGE-1). A further improvement in the performance was observed when the aminated electrode (Am-PGE-1) was activated by applying a negative potential scan (Am-PGE-2). The electrochemical transport properties were evaluated through cyclic voltammetry (CV) and electrochemical impedance spectroscopy (EIS). The Nyquist plot showed a reduced charge transfer resistance value of 24.3 Ω for Am-PGE-2, while it was 95.1 Ω for bare PGE. Thus, Am-PGE-2 was used as a sensing platform for the detection of catechol. It was found that the electrochemical response of catechol oxidation at Am-PGE-2 was twice than the current obtained for bare PGE. Additionally, the effect of pH of the supporting electrolyte and reaction kinetic were studied. The heterogeneous electron transfer rate constant was calculated to be 0.01 s−1. Moreover, CV study revealed that the redox reaction of catechol was a quasi-reversible and diffusion-controlled process. The square wave voltammetry (SWV) technique was applied for the quantitative determination of catechol. The peak current showed a linear dependency on the concentration of catechol from 3 to 150 µM. Furthermore, the analyte could be detected as low as 3.86 µM. Likewise, the sensor demonstrates a good selectivity towards the target analyte than the other possible interfering molecules or ions. Aiming to examine practical applicability, real samples, such as river and household tap water, were tested by using the proposed transducer, and the satisfactory recoveries demonstrate the effectiveness of Am-PGE-2 in real life applications. [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]

Cyber-Physical System (CPS) is a symbol of the fourth industrial revolution (4IR) by integrating physical and computational processes which can associate with humans in various ways. In short, the relationship between Cyber networks and the physical component is known as CPS, which is assisting to incorporate the world and influencing our ordinary life significantly. In terms of practical utilization of CPS interacting abundant difficulties. Currently, CPS is involved in modern society very vastly with many uptrend perspectives. All the new technologies by using CPS are accelerating our journey of innovation. In this paper, we have explained the research areas of 14 important domains of Cyber-Physical Systems (CPS) including aircraft transportation systems, battlefield surveillance, chemical production, energy, agriculture (food supply), healthcare, education, industrial automation, manufacturing, mobile devices, robotics, transportation, and vehicular. We also demonstrated the challenges and future direction of each paper of all domains. Almost all articles have limitations on security, data privacy, and safety. Several projects and new dimensions are mentioned where CPS is the key integration. Consequently, the researchers and academicians will be benefited to update the CPS workspace and it will help them with more research on a specific topic of CPS. 158 papers are studied in this survey as well as among these, 98 papers are directly studied with the 14 domains with challenges and future instruction which is the first survey paper as per the knowledge of authors. [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]

The net contribution of the decomposed measures of foreign direct investment (FDIs), e.g., the inward and outward flows of FDIs, to domestic investment is still inconclusive in the case of underdeveloped and developing countries. The current literature bears testimony to this fact. Hence, this research examines the impact of inward and outward foreign direct investments (FDIs) on the domestic investment in Bangladesh. This study considers annual time series data from 1976 to 2019 and estimates this data property under the augmented ARDL approach to cointegration. In addition, this research employs the dynamic ARDL simulation technique in order to forecast the counterfactual shock of the regressors and their effects on the dependent variable. The results from the augmented ARDL method suggest that the inward FDI has a positive impact on domestic investment, while the outward FDI is inconsequential in both the long run and the short run. Besides, our estimated findings also show the economic growth's long-run and short-run favorable effects on domestic investment. At the same time, there is no significant impact of real interest rates and institutional quality on domestic investment in the long run or the short run in Bangladesh. In addition, the counterfactual shocks (10% positive and negative) to inward FDI positively impact domestic investment, indicating the crowding-in effect of the inward FDI on the domestic investment in Bangladesh. As the inward FDI flow is a significant determinant for sustained domestic investment in Bangladesh, the policy strategy must fuel the local firms by utilizing cross-border investment. [ABSTRACT FROM AUTHOR]

Coastal homestead ponds are flooded during the rainy season and only hold water for five to six months. For coastal rural people, these ponds have a substantial impact on household nutrition and income generation. However, choosing the right culture techniques, stocking density, and seed size are necessary for fish aquaculture to be effective in this sort of seasonal pond. Hence, an adaptive field experiment was conducted to reveal the growth performance, yield and cost–benefit using advanced carp fingerling at different stocking densities in homestead ponds. Advanced fingerlings of Gibelion catla, Labeo rohita, Cirrhinus cirrhosus, and Labeo calbasu with the mean individual stocking weight of 243 ± 1.87 g, 223.56 ± 2.35 g, 155.89 ± 1.69 g, and 158.72 ± 1.35 g, respectively, were stocked at three different stocking densities, e.g., 825 kg ha−1 in T1, 560 kg ha−1 in T2 and 370 kg ha−1 in T3 and reared for 5 months. Homemade supplementary feed with protein content of 24.25% was supplied twice daily. The specific growth rate (SGR) was recorded highest at T3 for all the cultured species as L. rohita (1.15 ± 0.01% day−1), followed by G. catla (1.12 ± 0.004% day−1), L. calbasu (1.09 ± 0.01% day−1), and C. cirrhosus (0.98 ± 0.002% day−1), respectively. An inverse relationship was detected between fish growth and stocking density for all treatments. A similar pattern was observed in the survival rate, where reduced survival rates were recorded at T1 for all species. Significant variation (p < 0.05) was found among the treatments in terms of final weight, SGR, and survival rate. Economics of the carp polyculture also showed the highest net benefit (2609.77 ± 2.02 USD ha−1) and benefit–cost ratio (2.06 ± 0.002) at T3. Rearing of fish at 370 kg ha−1 stocking density yielded 129.21% and 110.96% higher production in T3 than T1 and T2, respectively. Overall, T3 treatment was more appropriate than T1 and T2 due to its low FCR, low investment but high survival rate, and net return. Therefore, stocking homestead ponds with advanced carp fingerling with a density of 370 kg per ha can be suggested as for increasing fish production and benefit in the homestead ponds of coastal rural area. In addition, further research is recommended to find out the effects of feeding and sources of seeds on the production performances. [ABSTRACT FROM AUTHOR]

In most cases, the official documents related to guidelines and frameworks are complicated, long, and hard to understand for general readers, regardless of whether the government and financial companies follow international standards or not. In this context, the current study examines how the green bond (GB) guidelines created by the Japanese government are aligned with the Green Bond Principles (GBP) and Climate Bonds Standard (CBS) through a text mining technique. It also investigates whether the GB frameworks for the Japanese public and private companies follow the GB guidelines of the Japanese government. While the CBS is the guideline that focuses on climate bonds, the GBP specializes in GB whose scope is broader. The word frequency and word cloud analyses identify that the documents created by the Japanese government and companies have more similarities with the GBP, indicating that the Japanese GB guidelines and frameworks are more aligned with the GBP than the CBS. A pairwise word network matrix analysis also reveals that the Japanese GB guidelines and frameworks are more focused on broader environmental issues and sustainability than the CBS, which had more similarities with the GBP than the CBS. [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]

The state of emergency (SOE) period in Tokyo under the COVID-19 pandemic restricted people to staying in their homes and changed human mobility, which has impacted the major agricultural markets in Tokyo. In this research, we analyzed how the changes in people's staying-at-home behaviors during the four SOE periods (7 April 2020–28 October 2021) in Tokyo affected the daily market prices of cabbage, tomato, Japanese radish, carrot, and potato. Using the autoregressive distributed lag (ARDL) model, the study reveals that all the investigated vegetables except potatoes have a long-term relationship with the staying-at-home index. The long-term influence of staying-at-home behaviors on cabbage, tomato, radish, and carrot markets during the early SOE periods had a negative impact on these vegetable prices, indicating that an increase in the hours of staying-at-home as related to SOE measures might have decreased the demand for these vegetables. The negative impact of the stay-at-home index on vegetable prices lessened in the fourth SOE period, likely because more people did not remain in their homes. Moreover, the study findings reveal that, compared to less perishable vegetables, the price of perishable vegetables is more likely to have been affected by human mobility constraints during the pandemic. Therefore, agricultural policymakers should consider providing subsidies to producers based on the negative influence on market prices of perishable and less perishable vegetables in pandemic situations, such as COVID-19. [ABSTRACT FROM AUTHOR]

The livelihood sustainability of the Rohingya refugees relocated in Bhashan Char, Bangladesh, has been questioned by various international stakeholders due to the remoteness and perceived vulnerabilities of the island. The Bangladesh government, a few international organizations, and some non-government organizations are working on developing livelihood opportunities in there. But there is scarce study about the livelihood opportunities and challenges of the Rohingyas living there. This study explores the vulnerabilities and livelihood opportunities of Rohingyas in Bhashan Char so as to help increase their resilience. The vulnerabilities include natural, geographical, and climatic shocks and stresses (e.g., cyclone, floods, storm surge, sea-level rise, geographical position). However, there are ample opportunities for their livelihood development, despite some challenges which can be overcome with concerted efforts. The opportunities include intensification and extensification of livelihood activities, such as modern agriculture, fish farming, livestock rearing, small business, handicraft, fishing net mending, crab fattening, biofloc aquaculture, and fish cage culture, but turning these opportunities into reality requires sufficient investment and internationally positive attitude. Better shelter, better disaster preparedness, cultural practices, education, and skill development can increase their capacity to bounce back, absorb shocks, and make them more resilient. National and international humanitarian organizations should plan to enhance the resilience of the Rohingya communities living in Bhashan Char and the island itself so that they can sustain in the long run, even after their anticipated repatriation to Myanmar. [ABSTRACT FROM AUTHOR]

The TALE gene family is an important transcription factor family that regulates meristem formation, organ morphogenesis, signal transduction, and fruit development. A total of 24 genes of the TALE family were identified and analyzed in tomato. The 24 SlTALE family members could be classified into five BELL subfamilies and four KNOX subfamilies. SlTALE genes were unevenly distributed on every tomato chromosome, lacked syntenic gene pairs, and had conserved structures but diverse regulatory functions. Promoter activity analysis showed that cis-elements responsive to light, phytohormone, developmental regulation, and environmental stress were enriched in the promoter of SlTALE genes, and the light response elements were the most abundant. An abundance of TF binding sites was also enriched in the promoter of SlTALE genes. Phenotype identification revealed that the green shoulder (GS) mutant fruits showed significantly enhanced chloroplast development and chlorophyll accumulation, and a significant increase of chlorophyll fluorescence parameters in the fruit shoulder region. Analysis of gene expression patterns indicated that six SlTALE genes were highly expressed in the GS fruit shoulder region, and four SlTALE genes were highly expressed in the parts with less-developed chloroplasts. The protein-protein interaction networks predicted interaction combinations among these SlTALE genes, especially between the BELL subfamilies and the KNOX subfamilies, indicating a complex regulatory network of these SlTALE genes in chloroplast development and green fruit shoulder formation. In conclusion, our result provides detailed knowledge of the SlTALE gene for functional research and the utilization of the TALE gene family in fruit quality improvement. [ABSTRACT FROM AUTHOR]

To investigate the effect of the maternal gut microbiome on fetal endochondral bone formation, fetuses at embryonic day 18 were obtained from germ-free (GF) and specific-pathogen-free (SPF) pregnant mothers. Skeletal preparation of the fetuses' whole bodies did not show significant morphological alterations; however, micro-CT analysis of the tibiae showed a lower bone volume fraction in the SPF tibia. Primary cultured chondrocytes from fetal SPF rib cages showed a lower cell proliferation and lower accumulation of the extracellular matrix. RNA-sequencing analysis showed the induction of inflammation-associated genes such as the interleukin (IL) 17 receptor, IL 6, and immune-response genes in SPF chondrocytes. These data indicate that the maternal gut microbiome in SPF mice affects fetal embryonic endochondral ossification, possibly by changing the expression of genes related to inflammation and the immune response in fetal cartilage. The gut microbiome may modify endochondral ossification in the fetal chondrocytes passing through the placenta. [ABSTRACT FROM AUTHOR]

The sewerage system is a primary element of a city and is responsible for the congestion of both rain and gray water from homes and industries. It is essential to have a monitoring system and a plan to perform prior expansion in the sewerage management system, to avoid massive disruption. However, there is no monitoring system in several overpopulated cities in the world, and the expansion process faces myriad difficulties and takes much time. This paper presents a model for an intelligent sewerage management system that provides real-time monitoring without any major changes to the previous system, using water sensors, a Global System for Mobile Communications (GSM) module, and a micro-controller. The condition of the sewerage acts as an input through the sensors; then, the microcontroller stores the value in the cloud and performs waste collection depending on the current situation. Meanwhile, after processing, the information reaches the monitoring system. Various trial installations of the proposed system have shown that it enables real-time monitoring to observe live conditions and helps to prevent sewerage blockage caused by solid waste. Considering a deficient cost model, this system can intensify the performance of poorly managed sewerage systems. [ABSTRACT FROM AUTHOR]

A cyclic naphthalene diimide (cyclic NDI, 1), carrying a benzene moiety as linker chain, was synthesized and its interaction with G-quadruplex DNAs of a-core and a-coreTT as a human telomeric DNA, c-kit and c-myc as DNA sequence at promoter region, or thrombin-binding aptamer (TBA) studied based on UV-VIS and circular dichroism (CD) spectroscopic techniques, thermal melting temperature measurement, and FRET-melting assay. The circular dichroism spectra showed that 1 induced the formation of different types of G-quadruplex DNA structure. Compound 1 bound to these G-quadruplexes with affinities in the range of 106-107 M-1 order and a 2:1 stoichiometry. Compound 1 showed 270-fold higher selectivity for a-core than dsDNA with a preferable a-core binding than a-coreTT, c-kit, c-myc and TBA in the presence of K+, which is supported by thermal melting studies. The FRET-melting assay also showed that 1 bound preferentially to human telomeric DNA. Compound 1 showed potent inhibition against telomerase activity with an IC50 value of 0.9 μM and preferable binding to G-quadruplexes DNA than our previously published cyclic NDI derivative 3 carrying a benzene moiety as longer linker chain. [ABSTRACT FROM AUTHOR]

Tomato spotted wilt virus impacts negatively on a wide range of economically important plants, especially tomatoes. When plants facing any pathogen attack or infection, increase the transcription level of plant genes that are produced pathogenesis-related (PR) proteins. The aim of this study is a genome-wide identification of PR-10 superfamily and comparative analysis of PR-10 and Sw-5b gene functions against tomato responses to biotic stress (TSWV) to systemic resistance in tomato. Forty-five candidate genes were identified, with a length of 64–210 amino acid residues and a molecular weight of 7.6–24.4 kDa. The PR-10 gene was found on ten of the twelve chromosomes, and it was determined through a genetic ontology that they were involved in six biological processes and molecular activities, and nine cellular components. Analysis of the transcription level of PR-10 family members showed that the PR-10 gene (Solyc09g090980) has high expression levels in some parts of the tomato plant. PR-10 and Sw-5b gene transcription and activity in tomato leaves were strongly induced by TSWV infection, whereas H8 plants having the highest significantly upregulated expression of PR-10 and Sw-5b gene after the inoculation of TSWV, and TSWV inoculated in M82 plants showed significantly upregulated expression of PR-10 gene comparatively lower than H8 plants. There was no significant expression of Sw-5b gene of TSWV inoculated in M82 plants and then showed highly significant correlations between PR-10 and Sw-5b genes at different time points in H8 plants showed significant correlations compared to M82 plants after the inoculation of TSWV; a heat map showed that these two genes may also participate in regulating the defense response after the inoculation of TSWV in tomato. [ABSTRACT FROM AUTHOR]

Among natural hazards, landslides are devastating in China. However, little is known regarding potential landslide-prone areas in Maoxian County. The goal of this study was to apply four deep learning algorithms, the convolutional neural network (CNN), deep neural network (DNN), long short-term memory (LSTM) networks, and recurrent neural network (RNN) in evaluating the possibility of landslides throughout Maoxian County, Sichuan, China. A total of 1290 landslide records was developed using historical records, field observations, and remote sensing techniques. The landslide susceptibility maps showed that most susceptible areas were along the Minjiang River and in some parts of the southeastern portion of the study area. Slope, rainfall, and distance to faults were the most influential factors affecting landslide occurrence. Results revealed that proportion of landslide susceptible areas in Maoxian County was as follows: identified landslides (13.65–23.71%) and non-landslides (76.29–86.35%). The resultant maps were tested against known landslide locations using the area under the curve (AUC). This study indicated that the DNN algorithm performed better than LSTM, CNN, and RNN in identifying landslides in Maoxian County, with AUC values (for prediction accuracy) of 87.30%, 86.50%, 85.60%, and 82.90%, respectively. The results of this study are useful for future landslide risk reduction along with devising sustainable land use planning in the study area. [ABSTRACT FROM AUTHOR]

Tomato spotted wilt virus (TSWV) is one of the most destructive diseases affecting tomato (Solanum lycopersicum) cultivation and production worldwide. As defenses against TSWV, natural resistance genes have been identified in tomato, including Sw-1a, Sw-1b, sw-2, sw-3, sw-4, Sw-5, Sw-6, and Sw-7. However, only Sw-5 exhibits a high level of resistance to the TSWV. Thus, it has been cloned and widely used in the breeding of tomato with resistance to the disease. Due to the global spread of TSWV, resistance induced by Sw-5 decreases over time and can be overcome or broken by a high concentration of TSWV. How to utilize other resistance genes and identify novel resistance resources are key approaches for breeding tomato with resistance to TSWV. In this review, the characteristics of natural resistance genes, natural resistance resources, molecular markers for assisted selection, and methods for evaluating resistance to TSWV are summarized. The aim is to provide a theoretical basis for identifying, utilizing resistance genes, and developing tomato varieties that are resistant to TSWV. [ABSTRACT FROM AUTHOR]

Quarantining at home during the COVID-19 pandemic significantly restricted human mobility such as visits to parks, grocery stores, workplaces, retail places, and transit stations. In this research, we analyzed how the changes in human mobility during the first wave of the COVID-19 pandemic, from February to April 2020 (i.e., between 17 February and 30 April 2020), affected the daily CO2 emissions for countries having a high number of coronavirus cases at that time. Our daily time-series analyses indicated that when average hours spent at home increased, the amount of daily CO2 emissions declined significantly. The findings suggest that for all three countries (the US, India, and France), a 1% increase in the average duration spent in residential areas reduced daily CO2 emissions by 0.17 Mt, 0.10 Mt, and 0.01 Mt, respectively, during the first wave period. Thus, confining people into their homes contributes to cutting down CO2 emissions remarkably. However, the study also reveals those activities such as visiting parks and going grocery shopping increase CO2 emissions, suggesting that unnecessary human mobility is undesirable for the environment. [ABSTRACT FROM AUTHOR]

Aerosol optical depth (AOD) is an important atmospheric parameter for climate change assessment, human health, and for total ecological situation studies both regionally and globally. This study used 21-year (2000–2020) high-resolution (1 km) Multiangle Implementation of Atmospheric Correction (MAIAC) algorithm-based AOD from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor onboard the Terra and Aqua satellites. MAIAC AOD was evaluated against Aerosol Robotic Network (AERONET) data across three sites (Xuzhou-CUMT, NUIST, and Taihu) located in Jiangsu Province. The study also investigated the spatiotemporal distributions and variations in AOD, with associated trends, and measured the impact of meteorology on AOD in the 13 cities of Jiangsu Province. The evaluation results demonstrated a high correlation (r = 0.867~0.929) between MAIAC AOD and AERONET data, with lower root mean squared error (RMSE = 0.130~0.287) and mean absolute error (MAE = 0.091~0.198). In addition, the spatial distribution of AOD was higher (>0.60) in most cities except the southeast of Nantong City (AOD < 0.4). Seasonally, higher AOD was seen in summer (>0.70) than in spring, autumn, and winter, whereas monthly AOD peaked in June (>0.9) and had a minimum in December (<0.4) for all the cities. Frequencies of 0.3 ≤ AOD < 0.4 and 0.4 ≤ AOD < 0.5 were relatively common, indicating a turbid atmosphere, which may be associated with anthropogenic activities, increased emissions, and changes in meteorological circumstances. Trend analysis showed significant increases in AOD during 2000–2009 for all the cities, perhaps reflecting a booming economy and industrial development, with significant emissions of sulfur dioxide (SO2), and primary aerosols. China's strict air pollution control policies and control of vehicular emissions helped to decrease AOD from 2010 to 2019, enhancing air quality throughout the study area. A notably similar pattern was observed for AOD and meteorological parameters (LST: land surface temperature, WV: water vapor, and P: precipitation), signifying that meteorology plays a role in terms of increasing and decreasing AOD. [ABSTRACT FROM AUTHOR]

The China–Pakistan Economic Corridor (CPEC) project passes through the Karakoram Highway in northern Pakistan, which is one of the most hazardous regions of the world. The most common hazards in this region are landslides and debris flows, which result in loss of life and severe infrastructure damage every year. This study assessed geohazards (landslides and debris flows) and developed susceptibility maps by considering four standalone machine-learning and statistical approaches, namely, Logistic Regression (LR), Shannon Entropy (SE), Weights-of-Evidence (WoE), and Frequency Ratio (FR) models. To this end, geohazard inventories were prepared using remote sensing techniques with field observations and historical hazard datasets. The spatial relationship of thirteen conditioning factors, namely, slope (degree), distance to faults, geology, elevation, distance to rivers, slope aspect, distance to road, annual mean rainfall, normalized difference vegetation index, profile curvature, stream power index, topographic wetness index, and land cover, with hazard distribution was analyzed. The results showed that faults, slope angles, elevation, lithology, land cover, and mean annual rainfall play a key role in controlling the spatial distribution of geohazards in the study area. The final susceptibility maps were validated against ground truth points and by plotting Area Under the Receiver Operating Characteristic (AUROC) curves. According to the AUROC curves, the success rates of the LR, WoE, FR, and SE models were 85.30%, 76.00, 74.60%, and 71.40%, and their prediction rates were 83.10%, 75.00%, 73.50%, and 70.10%, respectively; these values show higher performance of LR over the other three models. Furthermore, 11.19%, 9.24%, 10.18%, 39.14%, and 30.25% of the areas corresponded to classes of very-high, high, moderate, low, and very-low susceptibility, respectively. The developed geohazard susceptibility map can be used by relevant government officials for the smooth implementation of the CPEC project at the regional scale. [ABSTRACT FROM AUTHOR]

Just after the Indian government issued the first lockdown rule to cope with the increasing number of COVID-19 cases in March 2020, the energy consumption in India plummeted dramatically. However, as the lockdown relaxed, energy consumption started to recover. In this study, we investigated how COVID-19 cases affected Indian energy consumption during the COVID-19 crisis by testing if the lockdown release had a positive impact on energy consumption and if richer regions were quicker to recover their energy consumption to the level before the lockdown. Using the autoregressive distributed lag (ARDL) model, the study reveals that a long-run relationship holds between the COVID-19 cases and energy consumption and that the COVID-19 cases have a positive effect on Indian energy consumption. This result indicates that as lockdown relaxed, energy consumption started to recover. However, such a positive impact was not apparent in the Eastern and North-Eastern regions, which are the poorest regions among the five regions investigated in the study. This implies that poorer regions need special aid and policy to recover their economy from the damage suffered from the COVID-19 crisis. [ABSTRACT FROM AUTHOR]

This study empirically assesses the impacts of climatic events on the inland fishers (i.e., migratory and non-migratory) in Bangladesh and explores their responses to those events. Here, the migratory refers to the fishers who change their fishing location seasonally and voluntarily, whereas the non-migratory fishers fish in the same area. It is assumed that there exist differences in both the impacts of an event and the responses to the event between migratory and non-migratory fishers and therefore, a 'difference triangle' conceptual framework is developed and tested empirically under this research. Employing mix-method (qualitative and quantitative), a field study was conducted during July–October 2015 from the Padma River depended fishers. Identified climatic events under this study are: storms, changes in rainfall and temperature and riverbank erosion. The migratory and non-migratory fishers were affected quite similarly by storms and changes in rainfall and temperature. However, riverbank erosion affected only non-migratory fishers. Both the migratory and non-migratory fishers adopted different strategies to cope with different climatic events, like, they took shelter in safe places, sold productive assets, reduced food consumption, took credit from informal sources and employed their school-going children. As adaptation strategies, they modernized their fishing boats, intensified fishing, built embankments and diversified livelihoods. Unlike the impacts, considerable differences were found in their coping and adaptation strategies. Comparing to non-migratory fishers, a smaller number of migratory fishers sold their assets, took informal credit and intensified fishing and diversified their livelihoods. The result of this study indicates the significance of differences in the impacts of climatic events for the migratory and non-migratory fishers and therefore, this research has policy implication for the betterment of fishers' community in general. [ABSTRACT FROM AUTHOR]