Encouraging Offline Banking Customers to Adopt Online Banking: A Study on Customers of Dhaka City

While the use of technologies in banking services is on the rise worldwide, a substantial percentage of customers, specially in developing countries, still prefer the traditional forms of banking. This study aims to investigate the factors that inhibit customers of offline banking to switch towards online banking. In addition, it also identifies the factors that influence those customers positively towards online banking. Data were collected from 236 customers who conduct transactions traditionally in different banks in Dhaka city and who do not take any online services from any bank. The data collected from the survey were analyzed using the IBM SPSS package. Both descriptive and inferential statistical tools were used for analysis. Our study shows that customers of offline banking have lack of trust/confidence in online banking services and consider the services are associated with risk, which inhibits them to switch to online banking. On the other hand, customers of offline banking are found to perceive that online banking services are useful and facilitating conditions are favorable for taking online services. However, the customers are found to be in a confusing state about the ease of use of the services. Interestingly, about 71% of the traditional customers are found to switch to online banking mode if their concerns with the later system are addressed. Finally, based on these findings, implications for banking practitioners and policy makers are articulated. Keywords: Offline banking, switching, adoption, online banking, Dhaka DOI: 10.7176/EJBM/13-3-06 Publication date: January 31st 202

Emotion Language Acquisition in Young Children

Young children gradually acquire the ability to label emotions with words; yet how children understand and develop emotion language is an under researched area. According to linguistic research, syntactical bootstrapping is a prominent factor in a child’s concept learning. While, research in emotion development suggests that children use physical context to guide the learning of emotion concepts. The present studies built off of this literature to examine the role of both syntax and context in children’s (aged 3-5) ability to understand that a novel word refers to an emotion category. In Study 1, (N=120) children watched videos of puppets presenting a novel ‘alien’ word in one of three syntactical structures (is, feels and feels about). After the video, children completed an image selection task in which they could choose one of three images, either a state of being (e.g., cold), an action (e.g., running) or an emotion (e.g., surprised) to indicate what the alien word meant. In Study 2, (N=113) context was included in conjunction with the different syntactical structures. Children watched 7 videos in which an alien portrayed an emotional scenario. After each video the child completed the same image selection task as in Study 1. Across studies, we found that that emotion images are chosen more consistently with age, syntactic structure, and that physical context increases emotion choices.Bachelor of Scienc

The relationship between fake news and fake medicines: how misinformation has fuelled the sale of COVID-19 substandard and falsified medical products

As waves of COVID-19 continue to threaten public health, an increasing volume of disease-related information is widely accessible, and not all of it is accurate or reliable. The World Health Organisation (WHO) described this overabundance of information, misinformation, and disinformation as an "infodemic", making it difficult for many to distinguish fact from fiction. These definitions are complex and transitional; however, misinformation is defined as the "inadvertent sharing of false information", whereas disinformation is more sinister in origin and constitutes "the deliberate creation and sharing of information known to be false." The infodemic encapsulates both intentional and unintentional erroneous sources. Ultimately, the patient safety consequences remain the same, including amplifying vaccine hesitancy and propagating dangerous "coronavirus cures" myths, leading to higher COVID related mortality rates. Disinformation, desperation, and panic drive the production and sale of falsified medical products. The WHO estimates 1 in 10 medical products in low-and-middle-income countries (LMIC) settings are substandard or falsified (SF), which may worsen diseases, cause disability or even death. Ultimately, SF products undermine public trust in COVID-19 vaccines and treatments, all sectors must come together in this crisis to ensure quality covid medical products are distributed safely and fairly to end the pandemic sooner rather than later. &nbsp

Computer Vision-based Robotic Arm for Object Color, Shape, and Size Detection

Various aspects of the human workplace have been influenced by robotics due to its precision and accessibility. Nowadays, industrial activities have become more automated, increasing efficiency while reducing the production time, human labor, and risks involved. With time, electronic technology has advanced, and the ultimate goal of such technological advances is to make robotic systems as human-like as possible. As a result of this blessing of technological advances, robots will perform jobs far more efficiently than humans in challenging situations. In this paper, an automatic computer vision-based robotic gripper has been built that can select and arrange objects to complete various tasks. This study utilizes the image processing methodology of the PixyCMU camera sensor to distinguish multiple objects according to their distinct colors (red, yellow, and green). Next, a preprogrammed command is generated in the robotic arm to pick the item employing Arduino Mega and four MG996R servo motors. Finally, the device releases the object according to its color behind the fixed positions of the robotic arm to a specific place. The proposed system can also detect objects' geometrical shapes (circle, triangle, square, rectangle, pentagon, and star) and sizes (large, medium, and small) by utilizing OpenCV image processing libraries in Python language. Empirical results demonstrate that the designed robotic arm detects colored objects with 80% accuracy. It performs an excellent size and shapes recognition precision in real-time with 100% accuracy

Transformer-Based Deep Learning Model for Stock Price Prediction: A Case Study on Bangladesh Stock Market

In modern capital market the price of a stock is often considered to be highly volatile and unpredictable because of various social, financial, political and other dynamic factors. With calculated and thoughtful investment, stock market can ensure a handsome profit with minimal capital investment, while incorrect prediction can easily bring catastrophic financial loss to the investors. This paper introduces the application of a recently introduced machine learning model - the Transformer model, to predict the future price of stocks of Dhaka Stock Exchange (DSE), the leading stock exchange in Bangladesh. The transformer model has been widely leveraged for natural language processing and computer vision tasks, but, to the best of our knowledge, has never been used for stock price prediction task at DSE. Recently the introduction of time2vec encoding to represent the time series features has made it possible to employ the transformer model for the stock price prediction. This paper concentrates on the application of transformer-based model to predict the price movement of eight specific stocks listed in DSE based on their historical daily and weekly data. Our experiments demonstrate promising results and acceptable root mean squared error on most of the stocks.Comment: 16 Pages, 14 Figures (including some containing subfigures

Smaller size packs a stronger punch - Recent advances in small antibody fragments targeting tumour-associated carbohydrate antigens

Attached to proteins, lipids, or forming long, complex chains, glycans represent the most versatile post-translational modification in nature and surround all human cells. Unique glycan structures are monitored by the immune system and differentiate self from non-self and healthy from malignant cells. Aberrant glycosylations, termed tumour-associated carbohydrate antigens (TACAs), are a hallmark of cancer and are correlated with all aspects of cancer biology. Therefore, TACAs represent attractive targets for monoclonal antibodies for cancer diagnosis and therapy. However, due to the thick and dense glycocalyx as well as the tumour micro-environment, conventional antibodies often suffer from restricted access and limited effectiveness in vivo. To overcome this issue, many small antibody fragments have come forth, showing similar affinity with better efficiency than their full-length counterparts. Here we review small antibody fragments against specific glycans on tumour cells and highlight their advantages over conventional antibodies

Evaluation of Antidiabetic Potential of Mangifera indica Leaf in Streptozotocin-Induced Type 2 Diabetic Rats: Focus on Glycemic Control and Cholesterol Regulation

Mangifera indica (Anacardiaceae family) is renowned for its diverse pharmacological properties, encompassing antidiabetic, antioxidant, and anti-inflammatory effects. The present study delves into the insulin-releasing and glucose-lowering potential of the ethanolic extract of Mangifera indica (EEMI) leaves in streptozotocin-induced type 2 diabetic (STZ-T2D) rats, concurrently investigating its phytoconstituents. EEMI’s effects on insulin secretion were measured using BRIN BD11 β-cells and isolated mouse islets. Its enzymatic inhibitory properties on carbohydrate digestion, and absorption, and free radicals were investigated using in vitro methods. In vivo parameters including the lipid profile and liver glycogen content were assessed in STZ-T2D rats. EEMI exhibited a dose-dependent increase in insulin secretion from clonal pancreatic BRIN BD11 β-cells and isolated mouse islets. EEMI inhibited starch digestion, glucose diffusion over time, and DPPH activity in vitro. In acute in vivo studies, EEMI improved food intake and oral glucose tolerance. Moreover, following 28 days of treatment with EEMI, a remarkable amelioration in body weight, fasting blood glucose, plasma insulin, liver glycogen content, total cholesterol, triglyceride, LDL, VLDL, and HDL levels was observed. Further phytochemical analysis with EEMI identified the presence of alkaloids, tannins, saponins, steroids, and flavonoids. The synergistic effects of EEMI, potentially attributable to naturally occurring phytoconstituents, hold promise for the development of enriched antidiabetic therapies, offering a promising avenue for the management of type 2 diabetes

Factors contributing to online child sexual abuse in Bangladesh: A qualitative inquiry [version 3; peer review: 2 approved]

Background Children globally, including in Bangladesh, are facing various forms of online sexual abuse including sextortion, exploitation, body shaming, and blackmail. They are also coerced into engaging in intimate activities, harassed through the sending of sexual content, among other forms of abuse. We aimed to explore the root cause of online child sexual abuse (OCSA) in Bangladesh. Methods This qualitative research design utilized in-depth interviews (IDIs) and key informant interviews (KIIs) between February and April 2022. The study sample comprised 21 school-going children aged 13−17 years, selected from two different geographical settings (10 from rural areas and 11 from urban areas) in Bangladesh using purposive sampling techniques. They participated in in-depth interviews (IDIs) while additional data was obtained through key informant interviews (KIIs) with 11 multidisciplinary stakeholders. Results Children from both rural and urban areas reported facing abuse in various ways, such as being asked to send naked photos, being invited to be naked in video calls, and being invited to have virtual sex, among others, over the internet. Conclusions The government should consider integrating OCSA education into secondary levels. Additionally, there should be efforts to ensure a safe online environment through content scrutiny, promotion of outdoor activities, and community campaigns. An anonymous reporting system must be implemented, and strict measures under the Children's Act must be enforced against perpetrators. Further intervention studies are needed to ensure effective child protection measures in Bangladesh

Comparative analysis of antioxidant potential in leaf, stem, and root of Paederia foetida L.

Paederia foetida L. is widely used for the treatment of myriad ailments. Thus, searching for plant parts having greater antioxidant potential would make it easy to get suitable materials for herbal drugs. The present effort was made to explore the antioxidant potentials in the plant parts of P. foetida grown under natural conditions by means of physiological and biochemical analyses. The young leaves showed the highest reservoir of non-enzymatic antioxidants such as chlorophylls (0.96 mg g-1), carotenoids (0.43 mg g-1), anthocyanins (53.99 µg g-1), phenolics (728.24 µg g-1), flavonoids (4178.05 µg g-1), and proline (1.46 µmol g-1) as compared to others. Total antioxidant activity was found to be the highest in young leaves (84.82 %) followed by young stems (80.24 %) and matured leaves (79.78 %). Analysis of enzymatic antioxidants resulted in the superior activity of ascorbate peroxidase (13.58 µmol min-1 mg-1) and glutathione S-transferase (3409 nmol min-1 mg-1) in young leaves whereas the highest rate of catalase (409.85 µmol min-1 mg-1) and peroxidase (3.5 nmol min-1 mg-1) activity were found in matured leaves. However, comparatively higher content of reactive oxygen species; hydrogen peroxide, and lipid peroxidation product; malondialdehyde in matured leaves than that of young leaves suggests that young leaf is a suitable source for herbal medicine

Electrical conductivity and total dissolved solid of raw milk for the detection of bovine subclinical mastitis

Background and Aim: Bovine subclinical mastitis (SCM) is highly prevalent among dairy cattle. A cross-sectional study was conducted in Bangladesh to evaluate the performance of electric conductivity (EC) and total dissolved solids (TDS) tests for the detection of SCM. Materials and Methods: We randomly selected 108 milk samples from cows of different breeds in the primary milk-producing region of Pabna and Sirajgonj districts of Bangladesh. Samples were subjected to the California mastitis test (CMT), white side test (WST), electric conductivity (EC), TDS, and culture. A cow was considered positive for SCM if it tested positive in CMT, WST, and culture, whereas a cow was considered negative for SCM if it tested negative in all three methods. These gold standards have been used to evaluate the performance of the EC and TDS tests. The optimal EC and TDS cutoff values for the detection of SCM were determined using the “optimal cutoff” function in R version 4.3.1. Results: The optimal EC cutoff value for SCM detection was found to be 6159 μS/cm or 6.16 mS/cm. A positive likelihood ratio (LR+) of 31.2 and an area under the curve (AUC) of 0.905 were obtained for this cutoff value. The optimal cutoff value for TDS was 3100 mg/L of milk, which resulted in a positive LR+ of 45.5 and an AUC of 0.924. Conclusion: To the best of our knowledge, this is the first study to evaluate the performance of EC and TDS tests in detecting SCM in Bangladesh. These results suggest that EC and TDS tests, which are inexpensive, rapid, and easy to conduct, can effectively detect SCM at the farm level