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Both plants and bodies of water are crucial to the health of the urban landscape. The degree to which these factors contribute to cooling appears, however, to change depending on factors such as location, time of year, and the mix of land use and land cover. The purpose of this study was to investigate the potential role of trees and water in Rajshahi City Corporation in reducing urban heat island effect. As a first step, satellite images are processed to generate the normalized difference vegetation index (NDVI) and the modified normalized difference water index (MNDWI). The second step is to produce maps of vegetation and water features by using a decision tree (DT) algorithm fed with threshold values from the indices. After that, thermal bands from the Landsat 8 OLI and MODIS Terra Earth observation data are used to create a map of the land surface temperature (LST). Finally, this study assessed the effect of vegetation and water coverage on global surface temperatures by analyzing their spatial distributions. Different kinds of land cover can be found in and around urban centers. Therefore, this study chose two types of water bodies (big and small) and two types of vegetation (sparse and attached/compact) for experiment. Water bodies produce cooler temperatures than other land cover types, as shown by the data. It has been found, however, that cooling rates differ across large and small bodies of water. The surface temperatures of large bodies of water are typically lower than those of smaller bodies of water. Accordingly, it appears that expansive areas significantly impact the cooling of metropolitan environments. The findings also demonstrate a difference in surface temperature between areas of dense and sparse vegetation. The cooling impact of the sparse vegetation is much less than that of the dense and widespread vegetation. There was a significant relationship between surface warming and vegetation cover in this study (R2 = 0.81). Contrarily, the presence of water and vegetation is strongly correlated (R2 = 0.88) with surface warming. The findings also show that surface warming differs depending on land use. According to a study of four typical RCC locations, business districts and industrial zones have a far greater impact on local surface temperatures than do residential developments. The experiment demonstrates that the residential area with a high proportion of vegetation had a lower average temperature by nearly 2°C. The study’s findings highlight the value of maintaining urban parks and water features.

AbstractUsing the assertions of the social exchange theory, this study investigates the moderating effect of supervisory role in human resource management (HRM) practices and employee engagement relationships. This study used a cross-sectional survey design and collected data from 280 employees in Bangladesh’s readymade garments (RMG) industry. We tested the hypothesized model in SMART-PLS software through a structural equation model (SEM). An importance-performance matrix analysis (IPMA) was also performed to prioritize managerial actions. According to our findings, HRM practices have a significant relationship with employee engagement in the RMG industry, and the supervisory role of line managers moderates this relationship. Specifically, employee engagement increases in tandem with positive supervisory roles and vice versa. The IPMA analysis demonstrates that training and development is the most important determinant of employee engagement. Firms will benefit from increased employee engagement if line managers are empowered to implement HRM practices. This study expands the employee engagement literature by investigating different aspects of HRM practices in a globally dominant labor-intensive industry. It highlights the priority areas of HRM practices to foster employee engagement. However, the study is limited to Bangladesh’s RMG industry, though the findings are more applicable to labor-intensive manufacturing industries. Therefore, a full-length generalization across industries might not be feasible.

This study explores the factors influencing users' behavioral intentions, attitudes and actual adoption of quick response (QR) mobile payment in the least developed country (LDC) of Bangladesh, by extending the original unified theory of acceptance and use of technology (UTAUT) model. The study conducts a mixed-methods investigation by combining the partial least squares (PLS) and focus group discussion (FGD) methods to empirically evaluate the research model and cross-validate the findings. Using purposive sampling, data were gathered from 412 respondents, followed by 10 respondents who took part in the FGD, who all met the sample criteria. The study findings indicate that performance expectancy, effort expectancy, and social influence significantly positively influence users' behavioral intention, while self-concept, perceived self-efficacy, and habit substantially influence their attitudes towards using QR mobile payments. The findings also confirm a positive effect of users’ attitudes toward using QR mobile payment on both behavioral intention and actual use, and a positive effect of behavioral intention on the actual use of QR mobile payments. These findings offer several important theoretical and managerial implications.

Abstract Globally, artificial intelligence (AI) occupies a burgeoning space among recruiters as it replaces many of the recruitment and selection tasks while hiring the talents. Despite the existence and acceptance of AI being unprecedented among savvy recruiters, the study of it in developing countries’ contexts is still at a fancy stage. Particularly, the extant literature documented that very little is known about the intention and actual use (AU) of AI to hire talents with the intervening effects of voluntariness of usage (VU), tenure, and education of the recruiters elsewhere. Hence, using the doctrine of the extended unified theory of acceptance and use of technology (UTAUT), the present study aims to unpack the intention and AU of AI among hiring professionals in the context of Bangladesh, a developing country in the South Asian region. A multi-item questionnaire survey was employed to collect the data of recruiters from talent acquisition departments in both manufacturing and service organizations with a convenience sampling technique. We used partial least square-based structural equation modeling (PLS-SEM) version 4.0.8.9 to analyze the data. Results showed that performance expectancy (PE), facilitating conditions (FC), and hedonic motivation (HM) have a significant influence on the intention to use (IU) AI (p

Although scholars have explored the drivers of students’ e-learning intention, actual responses to online classes and the impact of online classes on student performance and the satisfaction-performance link remain under-explored. Thus, this study aimed to investigate higher education students' attendance, performance, and satisfaction with online classes. We collected data from two sources: (i) a cross-sectional survey of 214 undergraduate students in two phases and (ii) the administrative office. Data were analyzed using partial least square structural equation modeling via the Smart PLS (4.0.8.9). The results showed that students’ response to online classes is influenced by their intentions and other external antecedents, which in turn determine satisfaction. However, no statistical evidence was found for the relationship between student satisfaction and performance. The findings of this study contribute to the extension of theoretical models, such as the theory of planned behavior, the theory of reasoned actions, and the technology acceptance model used in the domain of online learning. The study findings have significant practical implications for the acceptance and use of e-learning.

Objective: The study aimed to assess two portable glucometers and an automated hematology analyzer for monitoring diabetes in cats. Glucose concentrations in the cats' blood samples were determined, and the factors influencing the glucose level were identified in this study. Material and Methods: The study was conducted at the Teaching Veterinary Hospital of Chattogram Veterinary and Animal Sciences University with 30 cats. Blood samples were collected, and their glucose levels were measured using two portable glucometers (Glucotest Prime® and Accu-Chek®) and an automated hematology analyzer (BIOBASE-Silver, BIOBASE). Results: The study showed that local and exotic breeds showed almost the same percentage of diabetes cases with all monitoring devices. Older (Glucotest Prime: before meal = 78.6%, after meal = 85.8%), (Accu-Chek: before meal = 71.5%, after meal = 71.5%), (Hematology analyzer: before meal = 71.5%, after meal = 78.6%), and obese (p = 0.002; before meal = 91%, after meal = 91% with all monitoring devices) animals had a higher occurrence of diabetes than young and non-obese animals. Both male and female cats showed almost equal numbers of diabetes cases. Conclusion: Several factors, like breed, older age, obesity, and gender, are prominent risk factors for diabetes in cats. The study concludes that feline diabetes is of similar concern to human diabe¬tes and can be regularly monitored with a portable glucometer and hematology analyzer. [Vet. Res. Notes 2023; 3(3.000): 11-15]

The current study seeks to explore the vulnerabilities typically encountered by female migrants in the informal sector in Dhaka city. It used a qualitative research approach, purposively selecting four areas from Dhaka city. Twenty-five semi-structured in-depth interviews during eight months of participant observation were conducted to accomplish the study objective. The authors used the capability approach theory to elucidate the phenomenon of vulnerability experienced by female migrants in the informal sector. The thematic data analyses were performed using the Granheim approach and NVivo 12 software. The findings of this study suggest that migrant women who work on the street face a number of significant challenges. These challenges include sexual assault and harassment, social stigma and cultural barriers, financial obstacles, and extortion and bribery. The authors recommend that governments provide access to state credits, social security, health insurance, and other forms of social protection for informal sector workers. The finding revealed that informal workers are often excluded from these essential benefits, making it difficult for such workers to expand their businesses or have a safety net in case of illness, unemployment, or other shocks.

IntroductionThis study examines the relationship between emotional intelligence (EI) and academic stress among tertiary-level students who continued academic activities remotely during the pandemic and the mediating role of social support (SS) in the relationship.MethodsUsing a cross-sectional survey design, 429 students studying business, engineering, social science, and science in Bangladesh provided data via Qualtrics. Using the Structural Equation Modeling in SmartPLS 4 (4.0.8.9), we modeled emotional intelligence as the reflective-formative and social support (support from family, friends, and significant other) and perceived academic stress as the reflective-reflective, second-order constructs. We also conducted a one-way between-groups analysis of variance (ANOVA) to investigate the impact of gender (male and female) and current stage of academic study (Undergraduate year one to four and post-graduation) on emotional intelligence and academic stress, respectively.Results and discussionResults show that all the hypothesized relationships are statistically significant: EI is negatively related to perceived academic stress, and SS significantly mediates the relationship between EI and academic stress. Hence, essential strategies are suggested to help students for managing academic stress.

ABSTRACTParks and green spaces in neighborhoods encourage physical exercise. Lack of POS design guidelines, budget restrictions, and public input have rendered these few POSs obsolete and unable to meet modern visitor needs. The objectives of this study are to understand and evaluate the residents’ perceptions regarding existing open space and its relationship with the city’s livability. Public open space physical and activity parameters were surveyed using a field physical and observation survey—an interview based on a questionnaire collected opinions about public open spaces. After gathering stakeholder data, the Spearman correlation in SPSS is used to analyze the association between public open space perception and quality of life. The study shows that the mean value of satisfaction level is 2.95. Which indicates the overall satisfaction level is “unsatisfied to neutral.” On the other hand, the correlation coefficient between public open space and City Livability is 0.1752 or 17.5%. It indicates that public open space account for 17.5% of the variance in city livability, with the remaining variance explained by other factors. The most significant takeaway from qualitative data analysis is that there is no blueprint technology for providing, managing, and maintaining public open spaces in the BCC area.

Phenotyping is used in plant breeding to identify genotypes with desirable characteristics, such as drought tolerance, disease resistance, and high-yield potentials. It may also be used to evaluate the effect of environmental circumstances, such as drought, heat, and salt, on plant growth and development. Wheat spike density measure is one of the most important agronomic factors relating to wheat phenotyping. Nonetheless, due to the diversity of wheat field environments, fast and accurate identification for counting wheat spikes remains one of the challenges. This study proposes a meticulously curated and annotated dataset, named as SPIKE-segm, taken from the publicly accessible SPIKE dataset, and an optimal instance segmentation approach named as WheatSpikeNet for segmenting and counting wheat spikes from field imagery. The proposed method is based on the well-known Cascade Mask RCNN architecture with model enhancements and hyperparameter tuning to provide state-of-the-art detection and segmentation performance. A comprehensive ablation analysis incorporating many architectural components of the model was performed to determine the most efficient version. In addition, the model’s hyperparameters were fine-tuned by conducting several empirical tests. ResNet50 with Deformable Convolution Network (DCN) as the backbone architecture for feature extraction, Generic RoI Extractor (GRoIE) for RoI pooling, and Side Aware Boundary Localization (SABL) for wheat spike localization comprises the final instance segmentation model. With bbox and mask mean average precision (mAP) scores of 0.9303 and 0.9416, respectively, on the test set, the proposed model achieved superior performance on the challenging SPIKE datasets. Furthermore, in comparison with other existing state-of-the-art methods, the proposed model achieved up to a 0.41% improvement of mAP in spike detection and a significant improvement of 3.46% of mAP in the segmentation tasks that will lead us to an appropriate yield estimation from wheat plants.

Purpose – This study aims to explore the influence of perceived hope, intrinsic spirituality and supervisor support on job involvement at the time of work from home during the COVID-19 pandemic. Design/methodology/approach – The sample included 263 employees working from home (WFH) for the first time in their careers due to COVID-19. The authors applied structural equation model and multigroup analysis (MGA) in SmartPLS3 to examine the hypothesized relationships, and artificial neural network (ANN) analysis to determine the relative influence of the antecedents. Findings – Results indicate that both personal (such as perceived hope and intrinsic spirituality) and job (supervisor support) resources determine job involvement during remote working, with a moderating impact of age on the relationship between intrinsic spirituality and job involvement. The ANN analysis shows that perceived hope is the most influential determinant of job involvement when employees work from home. Practical implications – This study suggests that when employees work remotely, organizations can generate higher job involvement by conveying a higher perception of hope and spirituality and providing supervisor support through planned hope interventions, promoting prosocial behavior and making changes in leadership style (check on instead of check-in). Originality/value – This study extends the job demands-resources (JD-R) model with new insights into the impact of personal and job resources on job involvement during the new normal remote working era.

In many cases, poor management of water supplies is to blame for a crisis. Scholars and practitioners have proposed developing enhanced modalities of water governance that promote the implementation of Integrated Water Resources Management (IWRM) to meet the interconnected problems of assuring access to sustainable water supplies for the world's populations. Therefore, this research aims to do two things: 1) evaluate the current status of water and related resources, and 2) create an operational decision-support system for the sustainable use of water resources based on integrated water resources management (IWRM). Beneficiaries are involved in all stages of the planning process, from the first brainstorming to the final evaluation. There hasn't been anything quite like these kinds of efforts before because they do not actively include community groups and government agencies in project design and money distribution. Matching water resources with various users (farmers, fisherman, women, and others) and their agriculture and fisheries development requirements was the focus of this study, which took an integrated participatory approach. Therefore, water management agencies are established through participatory water management. Beneficiaries realized that collective action results in the empowerment of all community members through capacity building and participatory water management. Because of this plan, agricultural progress in the area under consideration will proceed smoothly.

Urban Residential land development and redevelopment intensity (LDR) act as an essential index to understand magnitude of urban livability and sustainable development. Recent urbanization pattern of Rajshahi city has made a rising demand for land, which made it a precious commodity. As a result of it, Rajshahi City Corporation (RCC) area is undergoing significant residential LDR in recent years. The understanding of factors influencing this residential LDR has great importance in real estate development as well as overall housing situation of thecity. For this purpose, this study tries to explore the spatial characteristics of LDR. Relative Operating Characteristics (ROC) test statistics (>0.5) with improve hedonic model are set out to identify the internal drivers of LDR. Finally, geostatistics is explored by integrating methods of Geographic Information System (GIS) and SPSS regression analysis to analyze the correlation between LDR and driving factors. The spatial distribution of residential LDR has shown a strong distance decline law. One of the most exciting findings was that increase in distance to Central Business District (CBD) from the residential land has a slight influence on LDR. The outcomes of the paper will be beneficial for investors and policy-makers in their development decision-making processes.

During the 17th-18th century colonial period on the Indian subcontinent, British colonial architecture flourished – including in the Bengal Delta. Although colonial architecture was inherently different from the traditional architecture of this tropical region, the monsoon climate and deltaic landscape forced colonial style buildings to incorporate a number of tropical architectural features to ensure climatic comfort. In the contemporary period, due to pressure from population density, many colonial buildings have been demolished and replaced with multi-story buildings. However, the tropical forces of this deltaic region need to be evaluated in order to re-create climate responsive architecture. This study aims to identify tropical architectural features inherent within colonial buildings of Khulna, Bangladesh, a city which formed a junction in the deltaic region during the colonial period. Four colonial buildings have been selected as case studies: two residential buildings, one mixed-use building, and a school. Tropical features were analysed from photographic data, and reproductions of plans and sections of the selected buildings, in order to reveal the significant tropical architectural features of these colonial period buildings. The case studies reveal structural and design elements that aided ventilation and air flow, and controlled solar radiation, humidity and driving rain. The findings aim to encourage practicing architects to rethink climate responsiveness in contemporary buildings in Bangladesh, by revealing how, a century ago, colonial buildings were influenced by the tropical deltaic climate, which impacted foreign architectural ideology and practice.

Rajshahi is considered as one of the most growing cities in Bangladesh with enormous potentialities for physical and environmental development. The city has taken over air pollution, and it should now shift their focus on preparing to face the consequences of rapid urban growth. With unorganised solid waste management even after the absence of industries and mega industries, the city has a chance of collapsing in the period of potential future massive development movement. In order to combat this potential risk during that period, the landfill can be applicable in this developing city being the cheapest and straightforward method. Concerning this, this study attempts to identify suitable places to dispose of Metropolitan Solid Waste (MeSW). To select suitable sites for landfills, several critical factors, such as geology/hydrogeology, land use, aspect, slope, and distance from the surface water body, settlements, roads, railway, and protected areas, were chosen according to standards and regulations. Weights of criteria are determined using the Fuzzy Analytical Hierarchy Process (F-AHP), and then the weighted overlay analyses are used to nominate landfill sites. According to findings extracted, only about 6% area is highly suitable, and 22% of the area is moderately suitable for the landfill site development. Considering parameters such as minimum required area for landfills, buffer distance from residents, major roads and agricultural lands, political and management issues, and having discussions with key personnel, the study opts two potential sites for landfill development. Inappropriate landfill locations other than this will lead to adverse environmental, economic, and ecological externalities.

Policies throughout the world are presently focused on achieving a better quality of life and a longer life span through increased financial feasibility, ecological harmony, and economic stability. This effort seeks to empirically assess the impact of economic, health, environmental, and demographic factors on life expectancy in 36 high-income and 65 middle-income nations from 2000 to 2019. Using panels corrected standard errors (PCSEs) regression, this paper assures that high-income nations have significantly longer lifespans. The factors that lead most to this strengthening include GDP per capita, population growth, financial development, food production, and fertility rates. However, high-income countries tend to have shorter life expectancy due to rising mortality rates and carbon dioxide emissions. In middle-income nations, life expectancy falls significantly as a result of rising food production, health expenses, fertility rates, and economic hardship. Still, improving lifespan in middle-income nations is a result of multiple factors, including rising rates of GDP per capita, financial development, inequality in earnings between rural and urban places, and growing populations. The accuracy and credibility of the results are confirmed by using Driscoll-Kraay standard error estimates, feasible generalized least squares, random effect, and fixed effect approaches. The study's results point to the notion that these countries should put more emphasis on demographic and economic factors that lengthen life expectancy. Further, as health and environmental issues contribute to a shorter life expectancy, governments should place a greater priority on these fields. [ABSTRACT FROM AUTHOR]

Controlling rabies among free-roaming street dogs has been a huge challenge in many parts of the world. Vaccination is a commonly used strategy to control rabies, however, sufficient vaccination coverage is very challenging when it comes to street dogs. Also, dog rabies data is scarce, making it difficult to develop proper strategies. In this study, we use a logistic growth incorporated epidemic model to understand the prevalence of rabies in the dog population of Dhaka, Bangladesh. The study shows that, the basic reproduction number for dog rabies in Dhaka lies between 1.1 to 1.249 and the environmental carrying capacity lies approximately between 58,110 to 194,739. Considering the vaccination and neuter programs administered in the last decade, we attempt to explain rabies transmission among dogs in this population. We found that the high basic reproduction number is associated with high environmental carrying capacity and vice versa. Further, we compare different type of control strategies, viz., constant vaccination, pulse vaccination, and optimal vaccination strategies. In the case of high environmental carrying capacity, vaccination, and neuter strategy is not sufficient for controlling rabies in street dogs, whereas carrying capacity control through waste management coupled with vaccination and neuter is more effective. [ABSTRACT FROM AUTHOR]

The most crucial industries for growth, particularly in developing countries, are agriculture, tourism, and the fertilizer industry. These businesses are also linked to environmental deterioration. The current study uses empirical research to inspect the links between carbon dioxide (CO2) secretions and Gross Domestic Product (GDP) progression, government expenditure, tourism, fertilizer usage, renewable and non-renewable energies, and agricultural production. Information commencing from six South Asian nations is used to produce the findings between 1991 and 2019. Following the establishment of stationary and cointegration, a static analysis using a Fixed Effect and Random Effect Model and a dynamic analysis using a One Step Difference and System GMM (Generalized Method of Moments) are performed. This article employs Mean Group (MG) and Augmented Mean Group (AMG) approaches to increase robustness, while multicollinearity, heteroscedasticity, autocorrelation, and Cross-Sectional Dependency (CSD) are used for post-estimation. According to the study, the selected South Asian region's agricultural, fertilizer use, non-renewable energy use, tourism, GDP growth, and government spending all result in a rise in CO2 emissions, while using clean energy reduces those emissions and is crucial to reducing those emissions. The study offers some policy ramifications concerning green farming and tourism.