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Academic interest in understanding the role of financial technology (FinTech) in sustainable development has grown exponentially in recent years. Many studies have highlighted the context, yet no reviews have explored the integration of FinTech and sustainability through the lens of the banking aspect. Therefore, this study sheds light on the literature trends associated with FinTech and sustainable banking using an integrated bibliometric and systematic literature review (SLR). The bibliometric analysis explored publication trends, keyword analysis, top publisher, and author analysis. With the SLR approach, we pondered the theory-context-characteristics-methods (TCCM) framework with 44 articles published from 2002 to 2023. The findings presented a substantial nexus between FinTech and sustainable banking, showing an incremental interest among global scholars. We also provided a comprehensive finding regarding the dominant theories (i.e., technology acceptance model and autoregressive distributed lag model), specific contexts (i.e., industries and countries), characteristics (i.e., independent, dependent, moderating, and mediating variables), and methods (i.e., research approaches and tools). This review is the first to identify the less explored tie between FinTech and sustainable banking. The findings may help policymakers, banking service providers, and academicians understand the necessity of FinTech in sustainable banking. The future research agenda of this review will also facilitate future researchers to explore the research domain to find new insights.

The occurrence of rainfall is significantly affected by climate change around the world. While in some places this is likely to result in increases in rainfall, both winter and summer rainfall in most parts of New South Wales (NSW), Australia are projected to decrease considerably due to climate change. This has the potential to impact on a range of hydraulic and hydrologic design considerations for water engineers, such as the design and construction of stormwater management systems. These systems are currently planned based on past extreme rain event data, and changes in extreme rainfall amounts due to climate change could lead to systems being seriously undersized (if extreme precipitation events become more common and/or higher in magnitude) or oversized (if extreme rainfall events become less frequent or decrease in magnitude). Both outcomes would have potentially serious consequences. Consequently, safe, efficient, and cost-effective urban drainage system design requires the consideration of impacts arising from climate change on the approximation of design rainfall. This study examines the impacts of climate change on the probability of occurrence of daily extreme rainfall in New South Wales (NSW), Australia. The analysis was performed for 29 selected meteorological stations located across NSW. Future design rainfall in this research was determined from the projected rainfall for different time periods (2020 to 2039, 2040 to 2059, 2060 to 2079, and 2080 to 2099). The results of this study show that design rainfall for the standard return periods was, in most cases, lower than that derived employing the design rainfall obtained from the Australian Bureau of Meteorology (BoM). While most of the analysed meteorological stations showed significantly different outcomes using the climate change scenario data, this varied considerably between stations and different time periods. This suggests that more work needs to be performed at the local scale to incorporate climate change predicted rainfall data into future stormwater system designs to ensure the best outcomes.

CyVerse, the largest publicly-funded open-source research cyberinfrastructure for life sciences, has played a crucial role in advancing data-driven research since the 2010s. As the technology landscape evolved with the emergence of cloud computing platforms, machine learning and artificial intelligence (AI) applications, CyVerse has enabled access by providing interfaces, Software as a Service (SaaS), and cloud-native Infrastructure as Code (IaC) to leverage new technologies. CyVerse services enable researchers to integrate institutional and private computational resources, custom software, perform analyses, and publish data in accordance with open science principles. Over the past 13 years, CyVerse has registered more than 124,000 verified accounts from 160 countries and was used for over 1,600 peer-reviewed publications. Since 2011, 45,000 students and researchers have been trained to use CyVerse. The platform has been replicated and deployed in three countries outside the US, with additional private deployments on commercial clouds for US government agencies and multinational corporations. In this manuscript, we present a strategic blueprint for creating and managing SaaS cyberinfrastructure and IaC as free and open-source software.

Climate change impacts have the potential to alter the design rainfall estimates around the world. Decreasing trends in the summer and winter rainfall in New South Wales (NSW), Australia have already been observed due to climate variability and change. The derivation of design rainfall from historical rainfall, which is required for the design of stormwater management infrastructure, may be ineffective and costly. It is essential to consider climate change impacts in estimating design rainfall for the successful design of stormwater management infrastructure. In this study, the probability of the occurrence of daily extreme rainfall has been assessed under climate change conditions. The assessment was performed using data from 29 meteorological stations in NSW, Australia. For the evaluation of future design rainfall, the probability of the occurrence of extreme rainfall for different recurrence intervals was developed from daily extreme rainfall for the periods of 2020 to 2099 and compared with the current Australian Bureau of Meteorology (BoM) design rainfall estimates. The historical mean extreme rainfall across NSW varied from 37.71 mm to 147.3 mm, indicating the topographic and climatic influences on extreme rainfall. The outcomes of the study suggested that the future design rainfall will be significantly different from the current BoM estimates for most of the studied stations. The comparison of the results showed that future rainfall in NSW will change from −4.7% to +60% for a 100-year recurrence interval. However, for a 2-year recurrence interval, the potential design rainfall change varies from an approximately 8% increase to a 40% decrease. This study revealed that the currently designed stormwater management infrastructure will be idle in the changing climate.

Marburg virus (MARV) has been a major concern since 1967, with two major outbreaks occurring in 1998 and 2004. Infection from MARV results in severe hemorrhagic fever, causing organ dysfunction and death. Exposure to fruit bats in caves and mines, and human-to-human transmission had major roles in the amplification of MARV outbreaks in African countries. The high fatality rate of up to 90% demands the broad study of MARV diseases (MVD) that correspond with MARV infection. Since large outbreaks are rare for MARV, clinical investigations are often inadequate for providing the substantial data necessary to determine the treatment of MARV disease. Therefore, an overall review may contribute to minimizing the limitations associated with future medical research and improve the clinical management of MVD. In this review, we sought to analyze and amalgamate significant information regarding MARV disease epidemics, pathophysiology, and management approaches to provide a better understanding of this deadly virus and the associated infection.

Globally, scholars and practitioners are becoming increasingly interested in determining the interaction between finance and environmental sustainability. However, a few studies have investigated and organized existing information in the context of the green finance of banks in developing countries. The purpose of our study is to find major dimensions of green finance and research gaps from a thorough evaluation of the literature. As a result, existing research on green finance in the banking industry has been evaluated in this paper with a focus on green finance and sustainable development. This study employs the content analysis method and it analyzes and summarizes a total of 53 relevant previous studies in the field of green finance. The findings of this research reveal 21 crucial dimensions of green finance in Bangladesh. The primary green finance products of Bangladeshi banks include green securities, green investments, climate finance, green insurance, green credit, green bonds and green infrastructure. The other factors include environmental performance and green economic growth, energy efficiency, green finance policy and environmental protection and the risk impact of bank policy formulation. The findings of this study will help policymakers to understand the green finance concept and its associated variables, which need to be considered when adopting and implementing green finance.

The primary purpose of this research is to highlight the effectiveness and challenges of Online Learning (OL) for Bangladesh during COVID-19. Besides, the researchers have proposed some suggestions based on the findings of this research to overcome from those challenges. Fifteen students using purposive sampling from Bangladesh's private, public, and national universities have taken as a study sample. Researchers generated headings which will be asked to the respondents in relation to the research questions through the secondary sources (published articles, journals, reports, conference proceedings, newspapers, and government records). After that, data triangulation has been validated by the semi-structured interview of 15 students. According to the findings, online learning is now somehow effective; but, it faces several challenges in Bangladesh's educational system. The students, guardians, university authorities such as University Grant Commission (UGC) and the Ministry of Education will be benefited from these findings. The study only looked at Bangladeshi students' viewpoints, which may or may not be similar to those of other countries. As a result, generalization of the findings is less possible; consequently, more students from other countries should be included in the future.

An estuary represents a transition point between freshwater and saltwater and has a complex but productive environment due to a strong interplay between geological, physical, chemical, and biological processes. In Bangladesh, the ecological factors and biodiversity of different estuaries have been investigated for the last 35 years. However, the data is widely scattered, not easily accessible, unpublished, and/or in the form of grey literature. In this study, an attempt has been made to aggregate information available on the geo-environmental and biodiversity status of estuaries for their sustainable management. The biological and environmental data of 21 estuaries along the Bangladesh coast were collected from previously published literature and analyzed. The analyses revealed that the estuarine environment of Bangladesh is very dynamic and diverse like other tropical estuaries. The physico-chemical and geological parameters in estuaries significantly varied due to monsoon patterns, nutrient influx, salinity intrusion, riverine discharge, siltation, and human interventions in estuaries. Among the key environmental variables, such as salinity (3.7–30 ppt), pH (7.04–8), dissolved oxygen (3.30–13.63 mg/L), and water temperature (21–30°C) varied. Over 830 faunal and floral species of 273 genera were recorded from the estuarine environment, including 208 fishes, 87 species of phytoplankton, and 67 species of zooplankton in this region. This study suggests the development of an appropriate policy to protect valuable, productive, and diverse ecosystems, especially for erosion control, pollution abatement, and habitat destruction, particularly in the mangrove forests and their associated habitats of Bangladesh.

The 2021 WHO and UNICEF Estimates of National Immunization Coverage (WUENIC) reported approximately 25 million under-vaccinated children in 2021, out of which 18 million were zero-dose children who did not receive even the first dose of a diphtheria-tetanus-pertussis-(DPT) containing vaccine. The number of zero-dose children increased by six million between 2019, the pre-pandemic year, and 2021. A total of 20 countries with the highest number of zero-dose children and home to over 75% of these children in 2021 were prioritized for this review. Several of these countries have substantial urbanization with accompanying challenges. This review paper summarizes routine immunization backsliding following the COVID-19 pandemic and predictors of coverage and identifies pro-equity strategies in urban and peri-urban settings through a systematic search of the published literature. Two databases, PubMed and Web of Science, were exhaustively searched using search terms and synonyms, resulting in 608 identified peer-reviewed papers. Based on the inclusion criteria, 15 papers were included in the final review. The inclusion criteria included papers published between March 2020 and January 2023 and references to urban settings and COVID-19 in the papers. Several studies clearly documented a backsliding of coverage in urban and peri-urban settings, with some predictors or challenges to optimum coverage as well as some pro-equity strategies deployed or recommended in these studies. This emphasizes the need to focus on context-specific routine immunization catch-up and recovery strategies to suit the peculiarities of urban areas to get countries back on track toward achieving the targets of the IA2030. While more evidence is needed around the impact of the pandemic in urban areas, utilizing tools and platforms created to support advancing the equity agenda is pivotal. We posit that a renewed focus on urban immunization is critical if we are to achieve the IA2030 targets.

Abstract Background Hip dysplasia is common among children with cerebral palsy (CP), particularly in spastic CP. It can result in pain, reduced function and quality of life. However, the burden of hip dysplasia among children with CP in llow-and middle-income countries (LMICs) like Bangladesh is unknown. We aimed to define the burden of hip dysplasia among children with spastic CP in Bangladesh. Methods This study includes a subset of the Bangladesh CP Register (BCPR) study cohort who were registered between January and March 2015. The BCPR is a population-based surveillance of children with CP (aged

Background: Environmental enteropathy (EE), the adverse impact of frequent and numerous enteric infections on the gut resulting in a state of persistent immune activation and altered permeability, has been proposed as a key determinant of growth failure in children in low- and middle-income populations. A theory-driven systems model to critically evaluate pathways through which enteropathogens, gut permeability, and intestinal and systemic inflammation affect child growth was conducted within the framework of the Etiology, Risk Factors and Interactions of Enteric Infections and Malnutrition and the Consequences for Child Health and Development (MAL-ED) birth cohort study that included children from eight countries. Methods: Non-diarrheal stool samples (N = 22,846) from 1253 children from multiple sites were evaluated for a panel of 40 enteropathogens and fecal concentrations of myeloperoxidase, alpha-1-antitrypsin, and neopterin. Among these same children, urinary lactulose:mannitol (L:M) (N = 6363) and plasma alpha-1-acid glycoprotein (AGP) (N = 2797) were also measured. The temporal sampling design was used to create a directed acyclic graph of proposed mechanistic pathways between enteropathogen detection in non-diarrheal stools, biomarkers of intestinal permeability and inflammation, systemic inflammation and change in length- and weight- for age in children 0–2 years of age. Findings: Children in these populations had frequent enteric infections and high levels of both intestinal and systemic inflammation. Higher burdens of enteropathogens, especially those categorized as being enteroinvasive or causing mucosal disruption, were associated with elevated biomarker concentrations of gut and systemic inflammation and, via these associations, indirectly associated with both reduced linear and ponderal growth. Evidence for the association with reduced linear growth was stronger for systemic inflammation than for gut inflammation; the opposite was true of reduced ponderal growth. Although Giardia was associated with reduced growth, the association was not mediated by any of the biomarkers evaluated. Interpretation: The large quantity of empirical evidence contributing to this analysis supports the conceptual model of EE. The effects of EE on growth faltering in young children were small, but multiple mechanistic pathways underlying the attribution of growth failure to asymptomatic enteric infections had statistical support in the analysis. The strongest evidence for EE was the association between enteropathogens and linear growth mediated through systemic inflammation. Funding: Bill & Melinda Gates Foundation.

Heart failure (HF) is a complicated clinical syndrome that is considered an increasingly frequent reason for hospitalization, characterized by a complex therapeutic regimen, reduced quality of life, and high morbidity. Long-standing hypertension ultimately paves the way for HF. Recently, there have been improvements in the treatment of hypertension and overall management not limited to only conventional medications, but several novel pathways and their pharmacological alteration are also conducive to the treatment of hypertension. Beta-arrestin (β-arrestin), a protein responsible for beta-adrenergic receptors’ (β-AR) functioning and trafficking, has recently been discovered as a potential regulator in hypertension. β-arrestin isoforms, namely β-arrestin1 and β-arrestin2, mainly regulate cardiac function. However, there have been some controversies regarding the function of the two β-arrestins in hypertension regarding HF. In the present review, we try to figure out the paradox between the roles of two isoforms of β-arrestin in the treatment of HF.

The objective of this research is the assessment of the efficiency of a non-linear regression technique in predicting long-term seasonal rainfall. The non-linear models were developed using the lagged (past) values of the climate drivers, which have a significant correlation with rainfall. More specifically, the capabilities of SEIO (South-eastern Indian Ocean) and ENSO (El Nino Southern Oscillation) were assessed in reproducing the rainfall characteristics using the non-linear regression approach. The non-linear models developed were tested using the individual data sets, which were not used during the calibration of the models. The models were assessed using the commonly used statistical parameters, such as Pearson correlations (R), root mean square error (RMSE), mean absolute error (MAE) and index of agreement (d). Three rainfall stations located in the Australian Capital Territory (ACT) were selected as a case study. The analysis suggests that the predictors which has the highest correlation with the predictands do not necessarily produce the least errors in rainfall forecasting. The non-linear regression was able to predict seasonal rainfall with correlation coefficients varying from 0.71 to 0.91. The outcomes of the analysis will help the watershed management authorities to adopt efficient modelling technique by predicting long-term seasonal rainfall.

Little knowledge is available on students' attitudes and behavioural intentions towards using ChatGPT, a breakthrough innovation in recent times. This study bridges this gap by adding two relevant less-explored constructs (i.e., perceived enjoyment and perceived informativeness) to the technology acceptance model and illustrating the moderating effect of trust on the acceptance of ChatGPT. Data was collected from 344 private and public university students from Bangladesh, with the analysis done through structural equation modelling. The results highlight the significance of perceived usefulness, perceived ease of use and perceived informativeness in understanding students' attitudes towards using ChatGPT for learning, which subsequently predicts their behavioural intention to use it. Interestingly, students' level of enjoyment was triggered once the trust issue came into play, meaning perceived enjoyment had no substantial impact on attitude unless trust moderates the relationship between perceived enjoyment and attitude towards using ChatGPT.

IntroductionInfluenza infections present with wide-ranging clinical features. We aim to compare the differences in presentation between influenza and non-influenza cases among those with febrile respiratory illness (FRI) to determine predictors of influenza infection.MethodsPersonnel with FRI (defined as fever ≥ 37.5 °C, with cough or sore throat) were recruited from the sentinel surveillance system in the Singapore military. Nasal washes were collected, and tested using the Resplex II and additional PCR assays for etiological determination. Interviewer-administered questionnaires collected information on patient demographics and clinical features. Univariate comparison of the various parameters was conducted, with statistically significant parameters entered into a multivariate logistic regression model. The final multivariate model for influenza versus non-influenza cases was used to build a predictive probability clinical diagnostic model.Results821 out of 2858 subjects recruited from 11 May 2009 to 25 Jun 2010 had influenza, of which 434 (52.9%) had 2009 influenza A (H1N1), 58 (7.1%) seasonal influenza A (H3N2) and 269 (32.8%) influenza B. Influenza-positive cases were significantly more likely to present with running nose, chills and rigors, ocular symptoms and higher temperature, and less likely with sore throat, photophobia, injected pharynx, and nausea/vomiting. Our clinical diagnostic model had a sensitivity of 65% (95% CI: 58%, 72%), specificity of 69% (95% CI: 62%, 75%), and overall accuracy of 68% (95% CI: 64%, 71%), performing significantly better than conventional influenza-like illness (ILI) criteria.ConclusionsUse of a clinical diagnostic model may help predict influenza better than the conventional ILI definition among young adults with FRI.