Financial performance evolution of Yellow by BEXIMCO

This internship report is submitted in a partial fulfillment of the requirements for the degree of Bachelor of Business Administration,2015.Cataloged from PDF version of Internship report.Includes bibliographical references (page 59).Yellow is a design driven brand that celebrates creative and original thinking to highlight a lighthearted and optimistic view of life through a superior quality product. Yellow started its journey from 2004 in a very short premise. Now it has gone international. There is no annual report available for YELLOW for general people. YELLOW is a part of BEXTEX Ltd. Financial reports are made under BEXTEX’S name by summing all the firms’ expenses and earnings, who are under BEXTEX Ltd. No financial reports are published under the name of YELLOW or other firms who belongs to BEXTEX Ltd. But as I worked as an intern in the company, I had access in the internal data. That’s why I got few financial statements and I have worked with that information. This report applies Financial Performance Yellow by Beximco. . Different financial ratios are evaluated such as liquidity ratios, asset management ratios, profitability ratios, debt management ratios and finally measure the best performance of the company. The graphical analysis and comparisons are applied for the measurement of all types of financial ratio analysis I hope this report will help the concerned management to take ideas about the past performance and avoid the short comes and take the positive aspects to apply in future.Md. Tanvir HossainB. Business Administratio

Assessment on Social Vulnerability and Response Towards Natural Disaster in A Disaster-Prone Coastal Village: An Example from Bangladesh

Due to geographical locations, the Southwestern coastal region of Bangladesh is frequently experiencing climate change induced disasters such as cyclones, floods, and tidal surges. However, local communities at this region have a long history of coping with the adverse effects of these disasters. Consequently, this research assessed the social vulnerability towards natural disasters through local peoples’ perception and identified the existing immediate response against natural disasters at Kazirchar village in Muladi Upazila of Barishal district of the coastal region. In this study, a well-structured questionnaire survey, and focus group discussions were conducted to collect primary data. The collected data were processed and analysed to present the existing impacts of natural disasters. Besides, the immediate responses were categorized into different sectors. The study found that, the most prevalent coastal disaster in Kazirchar village was cyclone. About 48% of surveyed respondents opined that high cost of living was the main reason for increasing the vulnerability towards disasters. To adapt with disaster impacts, 58% respondents of this village need to travel long distances to collect drinking water. On the other hand, during flood, 26% people took shelter on government-owned high lands, whereas 40% shifted temporarily to their neighbors who are living in house with a high land elevation. This research concludes that the village has a low prior preparedness against various disasters, less knowledge about disaster, less coordination and poor collaboration between government organization (GOs) and non-governmental organizations (NGOs) regarding disaster risk reduction. It is expected that this study will act as a source of information for taking natural disaster management initiatives and the findings of this study will push the policy makers to develop and implement long term adaptation strategies in coastal areas of Bangladesh particularly in Barishal district

Experiences of intersex individuals in Bangladesh: some reflections

No abstract available

Facebook Marketing and Its Influence on Consumer Purchase Behaviour in the Context of Bangladesh

Facebook is a widely used social media platform where people usually spend a lot of time. Presently, it is considered a great way to outspread information globally through its artificial intelligence-based targeted control. As a result, Facebook also plays a vital role in the expansion of businesses due to its huge number of audiences around the universe. Nowadays to reach these customers very quickly and easily, businessmen around the world are utilizing Facebook as one of the best tools for marketing purposes. In Bangladesh, almost every person who possesses a smartphone or has internet accessibility uses Facebook as their primary social networking website. This frequent use of Facebook should have an influence on digital marketing. In this paper, we have tried to evaluate the influence of Facebook Marketing on customers’ purchase behavior in the context of Bangladesh through an online survey and some face-to-face interviews. Secondary data are also collected from existing research, journals papers, online reports, and websites. After the analyses, it can be stated that Facebook Marketing, having a list of positive customer feedback, has a great influence on customer purchase behavior in Bangladesh. From the positive reviews of existing customers, it can also be said that the influence rate of new customers is very high as well. Keywords:Facebook Marketing, Customers Buying Behaviour, Influence of Facebook Marketing, Digital Marketing DOI: 10.7176/EJBM/13-21-03 Publication date: November 30th 202

Caesarean delivery and its association with educational attainment, wealth index, and place of residence in Sub-Saharan Africa : a meta-analysis

Caesarean delivery (C-section) has been increasing worldwide; however, many women from developing countries in Sub-Saharan Africa are deprived of these lifesaving services. This study aimed to explore the impact of certain socioeconomic factors, including respondent’s education, husband’s education, place of residence, and wealth index, on C-section delivery for women in Sub-Saharan Africa. We used pooled data from 36 demographic and health surveys (DHS) in Sub-Saharan Africa. Married women aged 15–49 years who have at least one child in the last five years were considered in this survey. After inclusion and excluding criteria, 234,660 participants were eligible for final analysis. Binary logistic regression was executed to determine the effects of selected socioeconomic factors. The countries were assembled into four sub-regions (Southern Africa, West Africa, East Africa, and Central Africa), and a meta-analysis was conducted. We performed random-effects model estimation for meta-analysis to assess the overall effects and consistency between covariates and utilization of C-section delivery as substantial heterogeneity was identified (I2 > 50%). Furthermore, the meta-regression was carried out to explain the additional amount of heterogeneity by country levels. We performed a sensitivity analysis to examine the effects of outliers in this study. Findings suggest that less than 15% of women in many Sub-Saharan African countries had C-section delivery. Maternal education (OR 4.12; CI 3.75, 4.51), wealth index (OR 2.05; CI 1.94, 2.17), paternal education (OR 1.71; CI 1.57, 1.86), and place of residence (OR 1.51; CI 1.44, 1.58) were significantly associated with the utilization of C-section delivery. These results were also consistent in sub-regional meta-analyses. The meta-regression suggests that the total percentage of births attended by skilled health staff (TPBASHS) has a significant inverse association with C-section utilization regarding educational attainment (respondent & husband), place of residence, and wealth index. The data structure was restricted to define the distinction between elective and emergency c-sections. It is essential to provide an appropriate lifesaving mechanism, such as C-section delivery opportunities, through proper facilities for rural, uneducated, impoverished Sub-Saharan African women to minimize both maternal and infant mortality

Antioxidant Potential and Brine Shrimp Lethality bioassay of Spilanthes acmella Flower Extract

The current research study has been carried out to explore the antioxidant activity and brine shrimp lethality bioassay of different fractions from the flower extract of Spilanthes acmella. Besides, this experiment was also assessed to find out the proximate analysis and phytochemical screening by following the perfect protocol. To fractionate by soxhletion using sequential extraction techniques powdered flower of the plant were treated with different solvents including n-hexane, chloroform, ethanol and water. For the evaluation of antioxidant activity, total antioxidant capacity determination, determination of total phenolic content and total Flvonoids contents by aluminium tricholoride method were used. In addition, ascorbic acid and gallic acid was used as a standard antioxidant compound in these studies. Concerning the proximate analysis, moisture content, total ash value, acid insoluble ash and water soluble ash value were found 8.6%, 3.76%, 3.30%, 3.20% respectively. To evaluate cytotoxicity, the brine shrimp lethality bioassay was used. For phytochemical screening different extract of those solvents were utilized that disclosed the presence of alkaloids, flavonoids, phenolic compounds, Tannins, amino acids on different fractions but the absence of reducing sugar and saponins. The results of all assay showed that all the extracts of Spilanthes acmella flower possess significant antioxidant activity. In brine shrimp lethality bioassay, ethanol extract of flower effect to brine shrimp nauplii and exhibiting highest toxicity having LC50 value 1.20 μg/ml as compared to standard dimethyl sulfoxide (LC50 1.31 µg/ml). These evaluations suggest that Spilanthes acmella flowers might be a better source of antioxidants and possess important cytotoxic effect

Parkinson's Disease Detection through Vocal Biomarkers and Advanced Machine Learning Algorithms

Parkinson's disease (PD) is a prevalent neurodegenerative disorder known for its impact on motor neurons, causing symptoms like tremors, stiffness, and gait difficulties. This study explores the potential of vocal feature alterations in PD patients as a means of early disease prediction. This research aims to predict the onset of Parkinson's disease. Utilizing a variety of advanced machine-learning algorithms, including XGBoost, LightGBM, Bagging, AdaBoost, and Support Vector Machine, among others, the study evaluates the predictive performance of these models using metrics such as accuracy, area under the curve (AUC), sensitivity, and specificity. The findings of this comprehensive analysis highlight LightGBM as the most effective model, achieving an impressive accuracy rate of 96% alongside a matching AUC of 96%. LightGBM exhibited a remarkable sensitivity of 100% and specificity of 94.43%, surpassing other machine learning algorithms in accuracy and AUC scores. Given the complexities of Parkinson's disease and its challenges in early diagnosis, this study underscores the significance of leveraging vocal biomarkers coupled with advanced machine-learning techniques for precise and timely PD detection