Agricultural sector accelerates a nation’s economic growth towards sustainable development. There exists a significant relationship between agriculture and the environment. Sustainable agricultural development ensures food quality and in tandem prevents natural calamities like drought. However, in order to fulfill the food demand of a growing population, poor law quality and untenable agriculture practices arise, which in turn lead to environmental degradation. The current study explores the relationship between the agro-economic atmosphere and CO₂ emissions as a measure of environmental degradation in Bangladesh between the years of 1985 and 2017. To exhibit the long-run relationship of agricultural ecology and carbon dioxide emissions, three cointegrated equations- Fully-modified ordinary least square (FMOLS), Dynamic ordinary least square (DOLS), and Canonical cointegrated regression (CCR) were assessed. For cointegration, Bayer-Hanck cointegration was implied. In long-run estimates, it was found that livestock, rice area harvested, cereal production, and other crop production impeded environmental dilapidation. The Granger Causality Test enabled unidirectional causality towards burned biomass (crop residues), the agricultural economy, and carbon emissions. Therefore, this dimension’s causality concluded that carbon dioxide emissions were caused by cereal production, other agricultural production, and agricultural land production. The overall findings of this study could potentially assist the Government of Bangladesh and the necessary authorities for implementing synchronized policies to help reduce environmental pollution and set an example for other developing nations like Bangladesh.

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.

COVID-19 pandemic has disrupted schooling globally. Affecting millions of students, the conventional face-to-face (F2F) education system has been replaced by e-learning overnight. As the advantages, disadvantages, and technical challenges of this abrupt transformation were already well-documented, this study aimed to intensely scrutinize university students' experiences of e-learning practices in this new normal situation. Methods: Adopting the Interpretative Phenomenological Analysis (IPA), a smaller sample of respondents (N=25) was observed to gain deeper insights using semi-structured interviews. Data were analyzed and interpreted through thematic analysis. Findings revealed that most of the students have had unfavorable experiences with e-learning. The majority of students feel that e-learning has ruined their social relationships by isolating them from their peers and instructors. A significant number of students were observed to be anxious about their future due to unstable financial status, poor learning outcomes, and unfair evaluation processes. Moreover, poor self-esteem, anxiety, and depressive symptoms have been observed among a significant portion of the students. The overall findings of this study are meant to assist stakeholders in taking the necessary steps to address the aforementioned issues and ensure an improved learning experience, particularly in an e-learning environment.

The computer vision industry has experienced a significant surge in growth, resulting in numerous promising breakthroughs in computer intelligence. The present review paper outlines the advantages and potential future implications of utilizing this technology in education. A total of 84 research publications have been thoroughly scrutinized and analyzed. The study revealed that computer vision technology integrated with a mobile application is exceptionally useful in monitoring students’ perceptions and mitigating academic dishonesty. Additionally, it facilitates the digitization of handwritten scripts for plagiarism detection and automates attendance tracking to optimize valuable classroom time. Furthermore, several potential applications of computer vision technology for educational institutions have been proposed to enhance students’ learning processes in various faculties, such as engineering, medical science, and others. Moreover, the technology can also aid in creating a safer campus environment by automatically detecting abnormal activities such as ragging, bullying, and harassment.