Effects of Different Relative Humidities on Flax Fibers prior to Manufacturing Their Composites Based on the Shear Response

The moisture absorption behavior of flax fiber-reinforced epoxy composites is deliberated to be a serious issue. This property restricts their usage as outdoor engineering structures. Therefore, this study provides an investigation of moisture in flax fibers on the performance of the flax/epoxy composite materials based on their shear responses. The ±45° aligned flax fibers exposed to different relative humidities (RH) and the vacuum infusion process was used to manufacture the composite specimens. The optimum shear strength (40.25 ± 0.75 MPa) was found for the composites manufactured with 35% RH-conditioned flax fibers, but the shear modulus was reduced consistently with increasing RH values. Although shear strength was increased because of fiber swelling with increased moisture absorption rate until 35% RH environments with good microstructures, nonetheless, strength and modulus both started to decrease after this range. A very poor microstructure has been affirmed by the SEM images of the composite samples conditioned at 90% RH environments

Integrated bioinformatics and statistical approach to identify the common molecular mechanisms of obesity that are linked to the development of two psychiatric disorders: Schizophrenia and major depressive disorder

Obesity is a chronic multifactorial disease characterized by the accumulation of body fat and serves as a gateway to a number of metabolic-related diseases. Epidemiologic data indicate that Obesity is acting as a risk factor for neuro-psychiatric disorders such as schizophrenia, major depression disorder and vice versa. However, how obesity may biologically interact with neurodevelopmental or neurological psychiatric conditions influenced by hereditary, environmental, and other factors is entirely unknown. To address this issue, we have developed a pipeline that integrates bioinformatics and statistical approaches such as transcriptomic analysis to identify differentially expressed genes (DEGs) and molecular mechanisms in patients with psychiatric disorders that are also common in obese patients. Biomarker genes expressed in schizophrenia, major depression, and obesity have been used to demonstrate such relationships depending on the previous research studies. The highly expressed genes identify commonly altered signalling pathways, gene ontology pathways, and gene-disease associations across disorders. The proposed method identified 163 significant genes and 134 significant pathways shared between obesity and schizophrenia. Similarly, there are 247 significant genes and 65 significant pathways that are shared by obesity and major depressive disorder. These genes and pathways increase the likelihood that psychiatric disorders and obesity are pathogenic. Thus, this study may help in the development of a restorative approach that will ameliorate the bidirectional relation between obesity and psychiatric disorder. Finally, we also validated our findings using genome-wide association study (GWAS) and whole-genome sequence (WGS) data from SCZ, MDD, and OBE. We confirmed the likely involvement of four significant genes both in transcriptomic and GWAS/WGS data. Moreover, we have performed co-expression cluster analysis of the transcriptomic data and compared it with the results of transcriptomic differential expression analysis and GWAS/WGS

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

An Efficient Solution to Travelling Salesman Problem using Genetic Algorithm with Modified Crossover Operator

The traveling salesman problem (TSP) is a famous NP-hard problem in the area of combinatorial optimization. It is utilized to locate the shortest possible route that visits every city precisely once and comes back to the beginning point from a given set of cities and distance. This paper proposes an efficient and effective solution for solving such a query. A modified crossover method using Minimal Weight Variable, Order Selection Crossover operator, a modified mutation using local optimization and a modified selection method using KMST is proposed. The crossover operator (MWVOSX) chooses a particular order from multiple orders which have the minimum cost and takes the remaining from the other parent in backward and forward order. Then it creates two new offspring. Further, it selects the least weight new offspring from those two offspring. The efficiency of the proposed algorithm is compared to the classical genetic algorithm. Comparisons show that our proposed algorithm provides much efficient results than the existing classical genetic algorithm

Prevalence of COVID-19 Vaccine Hesitancy in South Asia: A Systematic Review and Meta-Analysis

Vaccine uptake and coverage in susceptible populations are needed through effective vaccination campaigns to address the COVID-19 pandemic in South Asian countries. We aimed to measure the pooled proportion of COVID-19 vaccine hesitancy in this regard. Research articles published between January 1, 2020, to December 31, 2021, were searched through Medline, PubMed, Cochrane, Google Scholar, and the WHO COVID-19 database. The Joanna Briggs Institute (2014) tool for prevalence studies was used to assess data quality. We performed a meta-regression test and a sensitive analysis among the studies and used the DerSimonian and Laird random-effects model to measure the pooled effect estimates. Subgroup analyses were performed concerning vaccine hesitancy, countries, study population, study level, and the time since the first outbreak of the pandemic. A total of 43 studies out of 598 published articles across the eight countries in South Asia were included. The pooled proportion of COVID-19 vaccine hesitancy was 26.5% (95% CI [22, 31], I2 = 99.59%). Vaccine hesitancy was higher in Afghanistan (37%), Pakistan (33%), and Bangladesh (28.9%); among the general population (29%); at community levels (27.9%); and the duration of time of 1–12 months since the first outbreak in each country (27.5%). Vaccine hesitancy exists in South Asia with different rates among countries, population sub-groups, communities, study- levels, duration of time since the first outbreak, and study population. Therefore, enhancing public awareness of vaccination and vaccine hesitancy is required to prevent future pandemics

Progress in multijunction solar cells

The advanced multijunction solar cell (MJSC) has emerged as a frontrunner with higher efficiency in photovoltaic literature. It started its journey with a modest 20% efficient tandem solar cell, and today, it has reached an impressive 47.1% photoconversion efficiency (PCE) with six junction combinations. Since the early 1990s, these solar cells have been utilised for space applications. Recently, there has been a trend of using this genre for terrestrial applications as well. However, the complexity and high cost of the fabrication procedure have been the significant challenges over the last three decades. The photovoltaic (PV) community has witnessed a variety of fabrication approaches to address these hurdles. This paper reviews the progression of computational and experimental research approaches of III-V MJSCs and their fabrication processes. In addition, it addresses the barriers hindering the progress of these cells and their prospects. This review gathers insights from a handful number of articles on III-V MJSCs to provide a comprehensive guide for the new entrants, experts and practitioners about the research methodologies, growth techniques, current status, challenges, and opportunities in a timely and conscious manner.Comment: 17 pages, 4 figure

Evaluation of out-patient care educational environment of National Defence University, Malaysia utilizing the ACLEEM Inventory

Purpose: A friendly educational environment is required for optimal learning, and students should be asked to provide feedback on their experiences to improve curriculum. Moreover, students’ academic progress, mental growth, and physical well-being are influenced by the educational and clinical environment of the institute. Essential constituents of the educational climate include atmosphere, number of proper teaching-learning sessions and available amenities. Primary health care and ambulatory settings allow students ample opportunities to interact with patients and observe health promotional activities more often practiced at the community levels. The study aims to evaluate the outpatient care educational environment of National Defense University of Malaysia by seeking feedback from medical students using Ambulatory Care Educational Environment Measure (ACLEEM) instrument. Methods: This was a cross-sectional study. The study participants were medical students of the earlier mentioned university. The universal sampling method was adopted. The ACLEEM validated instrument was utilized for the data collection. The instrument was developed on the basis of 5-point Likert Scale (Minimum: 0, and Maximum: 4). Results: The response rate 100%. Most respondents were male, Malay and Muslim. The total mean score was 1.0±0.4. The domain mean scores for clinical teaching, clinical training, and support were 0.8±0.4, 1.1±0.4, and 1.1±0.5, respectively. Conclusions: The ACLEEM questionnaire was found to be valid and reliable for local UPNM, Malaysian context. However, the overall ACLEEM scores reported for the present study is low, and some areas that could be improved. The UPNM authority should take appropriate measures to improve the educational environment to enhance the academic experiences of the medical students