Fitting Multi-Layer Feed Forward Neural Network and Autoregressive Integrated Moving Average for Dhaka Stock Exchange Price Predicting

The stock market plays a vital role in the economic development of any country. Stock market performance can be measured by the market capitalization ratio as well as many other factors. The primary purpose of this study is to predict the movement of the stock market based on the total market capitalization of the Dhaka Stock Exchange (DSE) using autoregressive integrated moving average (ARIMA) models as well as artificial neural networks (ANN). The data set covers monthly time series data of total market capitalization from November 2001 to December 2018. This study also shows the best model for forecasting the movement of DSE market capitalization. The ARIMA (2,1,2) model is chosen from among the several ARIMA model combinations. From several artificial neural networks (ANN) models as a modern tool, a three-layer feed-forward topology using a backpropagation algorithm with five nodes in the hidden layer, one lag, and a learning rate equal to 0.01 is selected as the best model. Finally, these selected two models are compared based on the Root-Mean-Square Error (RMSE), Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE), and Theil’s U statistic. The results showed that the estimated error of ANN is less than the estimated error of the traditional method. Doi: 10.28991/ESJ-2022-06-05-09 Full Text: PD

Testing a global standard for quantifying species recovery and assessing conservation impact.

Recognizing the imperative to evaluate species recovery and conservation impact, in 2012 the International Union for Conservation of Nature (IUCN) called for development of a "Green List of Species" (now the IUCN Green Status of Species). A draft Green Status framework for assessing species' progress toward recovery, published in 2018, proposed 2 separate but interlinked components: a standardized method (i.e., measurement against benchmarks of species' viability, functionality, and preimpact distribution) to determine current species recovery status (herein species recovery score) and application of that method to estimate past and potential future impacts of conservation based on 4 metrics (conservation legacy, conservation dependence, conservation gain, and recovery potential). We tested the framework with 181 species representing diverse taxa, life histories, biomes, and IUCN Red List categories (extinction risk). Based on the observed distribution of species' recovery scores, we propose the following species recovery categories: fully recovered, slightly depleted, moderately depleted, largely depleted, critically depleted, extinct in the wild, and indeterminate. Fifty-nine percent of tested species were considered largely or critically depleted. Although there was a negative relationship between extinction risk and species recovery score, variation was considerable. Some species in lower risk categories were assessed as farther from recovery than those at higher risk. This emphasizes that species recovery is conceptually different from extinction risk and reinforces the utility of the IUCN Green Status of Species to more fully understand species conservation status. Although extinction risk did not predict conservation legacy, conservation dependence, or conservation gain, it was positively correlated with recovery potential. Only 1.7% of tested species were categorized as zero across all 4 of these conservation impact metrics, indicating that conservation has, or will, play a role in improving or maintaining species status for the vast majority of these species. Based on our results, we devised an updated assessment framework that introduces the option of using a dynamic baseline to assess future impacts of conservation over the short term to avoid misleading results which were generated in a small number of cases, and redefines short term as 10 years to better align with conservation planning. These changes are reflected in the IUCN Green Status of Species Standard

A REFLECTION OF COVID-19 PANDEMIC ON THE TOURISM SECTOR IN BANGLADESH: FINANCIAL AND ECONOMIC ASPECTS

Bangladesh has been experiencing the tourism industry as one of the most potential sectors proving a great contribution to the economy in recent years. However, at the beginning of 2020, this sector has transformed reversely by the consequences of the outbreak of COVID-19. Continuous restrictions on movement in domestic and international borders make the tourism sector employees jobless and generate fewer turnovers. This research attempts to quantify the adverse effect of COVID-19 on the tourism sector as well as the country's economy, spheres of tourism and business and suggests some short-term and long-term approaches to recover the situation. The study draws a contrast between past and present year trends, from where we may get vigorous and prevailing information about the pandemic significance and may contribute to initiating and implementing some suitable tactics for retrieval from the state in further heightening the tourism industry. This study may aid in the better understanding and identification of the demands of the general public in terms of tourism by the relevant authorities in the tourist sector. This will also assist in developing the potential of domestic tourism and preparing the tourism sites in Bangladesh for the post-pandemic phase by implementing appropriate measures in the short term

Role of women's empowerment in determining fertility and reproductive health in Bangladesh: a systematic literature reviewAJOG Global Reports at a Glance

INTRODUCTION: Research on fertility and reproductive health has expanded rapidly. However, questions regarding the association between women empowerment and fertility in terms of the reproductive health status in Bangladesh remain unanswered. This study aimed to address these questions through a systematic literature review. METHODS: In this review study, the PubMed, Scopus, Banglajol, and Google Scholar databases were searched systematically and screened in terms of the inclusion and exclusion criteria. Data from 15 articles included in this review were extracted for further assessment. RESULTS: Fifteen studies with a total of 212,271 participants from Bangladesh met our selection criteria. Most of the articles were conducted on ever-married women aged 15 to 49 years using nationally representative Bangladesh Demographic and Health Survey data. The major religions were Islam (86.8%–90.2%) and Hinduism (10%–13%). The age of women at first marriage varied from 14 to 20 years, and the age at first birth ranged from 16 to 22 years. The fertility rate in Bangladesh has reduced remarkably over the period from 1975 to 2022. After controlling for other social and health factors, the study found that empowerment factors such as women's education, working status, involvement in household decision-making, participation in economic decision-making, and freedom in movement influenced the fertility and reproductive health status in Bangladesh. CONCLUSION: As an initial step, this study found a negative relationship between women's empowerment and the control of fertility and reproductive health. Greater policy focus should be directed toward women empowerment factors to improve the fertility situation and reproductive health status in Bangladesh and other countries with similar sociodemographic profiles

Does Globalization Trigger an Ecological Footprint? A Time Series Analysis of Bangladesh

Climate change has become a pitfall towards economic growth, sustainable development, and ecological balance, which is not different in Bangladesh. This study investigates the relationship between the ecological footprint and the globalisation of Bangladesh in 1980-2021. The auto-regressive distributed lag model (ARDL) bound test confirms the long-run relationship among carbon footprint, ecological footprint, globalisation, and other control variables. Long-run and short elasticity confirm that globalisation, population density, energy consumption, and political and economic globalisation stimulate ecological footprint. On the other hand, economic growth is a culprit of ecological footprint. It reflects alternative signs with an ecological footprint. On carbon footprint, results are similar to ecological footprint except for energy consumption. As ecological footprint increases, people consume more energy in the short run while less energy in the long run. Laws enforced in the last or previous decades regarding environmental issues need more strictness and acceptability to utilise energy through advanced technology and robust inflows from the foreign sector

Impact of Social Media on Knowledge of the COVID-19 Pandemic on Bangladeshi University Students

This study aimed to examine the role and impact of social media on the knowledge of the COVID-19 pandemic in Bangladesh through disseminating actual changes in health safety, trust and belief of social media’s coverage statistics, isolation, and psychological numbness among students. This study used a cross-sectional design in which a quantitative approach was adopted. Data from an online survey were collected in a short period of time during the early stages of COVID-19 to determine the relationship between social media activity and knowledge of the COVID-19 pandemic with accuracy. A total of 189 respondents were interviewed using structured questionnaires during the onset of the COVID-19 outbreak in Bangladeshi university students. Exploratory factor analysis (EFA) and path analysis were performed. Out of 189 respondents, about 80% were aged between 16 and 25 years, of which nearly 60.33% were students. This study explored four factors—knowledge and health safety, trust in social media news, social distancing or quarantine, and psychological effect—using factor analysis. These four factors are also found to be positively associated in path analysis. Validation of the model was assessed, revealing that the path diagram with four latent exogenous variables fit well. Each factor coefficient was treated as a factor loading (β = 0.564 to 0.973). The results suggested that the measurement models using four elements were appropriate. The coefficient of determination was 0.98, indicating that the model provided an adequate explanation. Social media is transforming the dynamics of health issues, providing information and warnings about the adverse effects of COVID-19, having a positive impact on lockdown or quarantine, and promoting psychological wellness. This comprehensive study suggested that social media plays a positive role in enhancing knowledge about COVID-19 and other pandemic circumstances

Students’ Satisfaction in Online Class during COVID-19: An Empirical Study in Bangladesh Context

The COVID-19 pandemic caused higher education institutions to switch to online learning. This unique endeavor is being investigated to protect high-quality education. Due to its hasty and emergency implementation, students may have different opinions about this new education system. The primary objective of this study is to investigate the relationships between constructs such as students’ perceived effectiveness, institutional facility, teaching material, and overall satisfaction during the COVID-19 outbreak. Adopting a quantitative research approach, this study was conducted between November 8, 2020, and February 12, 2021, in private universities in Bangladesh. Data were utilized in structural equation modeling (SEM). The findings revealed that perceived effectiveness (0.68, p-value = 0.01), institutional facility (0.23, p-value = 0.01), and teaching material (0.14, p-value = 0.01) are all positively and significantly associated with satisfaction with an online class module. In addition, trajectory analysis establishes a link between satisfaction and effectiveness in e-learning through the SEM. The results of the study also indicate a strong and positive correlation between satisfaction with an online class module and perceived effectiveness, institutional setting, and teaching material. This study will serve as a catalyst for understanding students’ satisfaction in an online environment, as well as a benchmark for various stakeholders, particularly policymakers, practitioners, academicians, and institution owners, to take the necessary steps to ensure a sustainable online learning platform

Physio-psychosocial risk of depression among college-going adolescents: A cross-sectional study in Bangladesh

Background: Depression among adolescents is a growing concern worldwide, including in Bangladesh. This study aimed to investigate depression and its associated factors among college-going adolescents in Bangladesh. Methods: A cross-sectional survey was conducted among 1919 college-going adolescents through a Google-based questionnaire covering all administrative divisions of Bangladesh. Respondents’ socio-demographic information was collected, and the Patient Health Questionnaire-9 (PHQ-9) was used to assess depression. Different statistical analyses, including descriptive statistics, Chi-square test, and multinomial logistic regression, were performed to analyze the data. Results: The results showed that a majority of the adolescents (65.5 %) were female and identified as Muslim (92.0 %). The average age was 17.5 years, with 33.9 % reporting pre-marital relationships and 10.7 % engaging in daily exercise. Alarmingly, over 80 % of college-going adolescents experienced moderate to severe depression (24.3 % moderate; 29.1 % moderately severe, and 26.8 % severe). Factors including gender, social media use, physical exercise, pre-marital relationships, religious practices, experiences of blackmail, and major physical illnesses have significant association (p < 0.001) with the increased risk of depression among college-going adolescents in Bangladesh. The multinomial logistic regression analysis found female adolescents, social media users, those not engaged in regular exercise, individuals in pre-marital relationships, non-practitioners of religion, victims of blackmail, and those with major physical illnesses had the higher odds of experiencing moderate to severe depression. Conclusion: The high depression level among Bangladeshi college-going adolescents underscores the urgent need for targeted mental health intervention to address associated risk factors and promote the well-being of college-going adolescents in Bangladesh