Genes and Gene Networks Related to Age-associated Learning Impairments

The incidence of cognitive impairments, including age-associated spatial learning impairment (ASLI), has risen dramatically in past decades due to increasing human longevity. To better understand the genes and gene networks involved in ASLI, data from a number of past gene expression microarray studies in rats are integrated and used to perform a meta- and network analysis. Results from the data selection and preprocessing steps show that for effective downstream analysis to take place both batch effects and outlier samples must be properly removed. The meta-analysis undertaken in this research has identified significant differentially expressed genes across both age and ASLI in rats. Knowledge based gene network analysis shows that these genes affect many key functions and pathways in aged compared to young rats. The resulting changes might manifest as various neurodegenerative diseases/disorders or syndromic memory impairments at old age. Other changes might result in altered synaptic plasticity, thereby leading to normal, non-syndromic learning impairments such as ASLI. Next, I employ the weighted gene co-expression network analysis (WGCNA) on the datasets. I identify several reproducible network modules each highly significant with genes functioning in specific biological functional categories. It identifies a “learning and memory” specific module containing many potential key ASLI hub genes. Functions of these ASLI hub genes link a different set of mechanisms to learning and memory formation, which meta-analysis was unable to detect. This study generates some new hypotheses related to the new candidate genes and networks in ASLI, which could be investigated through future research

New Algorithm For Detection of Spinal Cord Tumor using OpenCV

The spinal cord one of the most sensitive and significant parts of the human body lies protected inside the spine the backbone and contains bundles of nerves Any minor problem in the spinal cord can cause debilitation of internal and external functions of the human body One of the complications in the spinal cord is tumor - abnormal growth of tissue In this project we present a new algorithm based on OpenCV to detect spinal cord tumors from MRI sagittal image without human intervention The new algorithm can detect tumor-like substances adjacent to the spinal cord Tests carried out on spinal cord MRI images 33 cervical spinal images showed approximately 90 91 of accuracy rate in detecting tumor

MCFFA-Net: Multi-Contextual Feature Fusion and Attention Guided Network for Apple Foliar Disease Classification

Numerous diseases cause severe economic loss in the apple production-based industry. Early disease identification in apple leaves can help to stop the spread of infections and provide better productivity. Therefore, it is crucial to study the identification and classification of different apple foliar diseases. Various traditional machine learning and deep learning methods have addressed and investigated this issue. However, it is still challenging to classify these diseases because of their complex background, variation in the diseased spot in the images, and the presence of several symptoms of multiple diseases on the same leaf. This paper proposes a novel transfer learning-based stacked ensemble architecture named MCFFA-Net, which is composed of three pre-trained architectures named MobileNetV2, DenseNet201, and InceptionResNetV2 as backbone networks. We also propose a novel multi-scale dilated residual convolution module to capture multi-scale contextual information with several dilated receptive fields from the extracted features. Channel-based attention mechanism is provided through squeeze and excitation networks to make the MCFFA-Net focused on the relevant information in the multi-receptive fields. The proposed MCFFA-Net achieves a classification accuracy of 90.86%.Comment: 7 pages, 6 figures, ICCIT 2022 submission, Conferenc

Using an information ecology approach to identify research areas : findings from Bangladesh

The primary purpose of this mapping exercise was to gather intelligence for development of a methodology to assess the impact of public access to ICT. The paper aims to capture the experiences of villagers in Bangladesh, focusing on how rural people interact within and outside their community to collect, use, and assimilate information and knowledge for various livelihood and social purposes. This “Information Ecology Mapping” exercise is part of the larger project, “The Global Impact Study of Public Access to information and Communication Technologies.

Navigating LDC graduation: modelling the impact of RCEP and CPTPP on Bangladesh

Bangladesh will graduate from the LDC list by 2026. Currently, Bangladesh's exports of readymade garments (RMG) benefit from international support measures which allow preferential trade in major export destinations, such as the EU. After graduation, Bangladesh's exports, particularly RMG, will face competition from mega trading blocs, such as RCEP and CPTPP. This article employs the GTAP model to estimate the impact of Bangladesh's graduation from the LDC category and how mega FTAs are likely to affect Bangladesh's exports and potential welfare. The model also considers the scenarios of either United States or the UK or both joining the CPTPP. The model results show that Bangladesh's graduation will lead to a fall in GDP and RMG exports by 1.53% and 11.8%, respectively. The negative impact is magnified when we factor in the mega-trading blocs. Further negative impacts are observed when either United States or the UK or both join the CPTPP

Screening for microbial load and antibiotic resistance pattern in Escherichia coli isolated from paper currency circulating in Kushtia, Bangladesh

Background: Paper currency is used for every type of commerce and plays an important role in the life of human beings. They are exchanged and come into contact with different environments and many different individuals during their circulation. Therefore, they can become contaminated with microorganisms and transfer bacteria across environments. The present study was aimed for quantitative assessment of microorganisms in circulated paper currency from Kushtia, Bangladesh and antibiotic resistant profiles of isolated Escherichia coli.Methods: A total of 10 paper currency samples currently in circulation involving three denominations (5, 10 and 500) were randomly collected from individuals involved in various occupations including street beggar, local hotel, bus conductor, poultry seller, vegetable seller, fish seller, commercial bank, ATM booth, tea seller, grocery store in Kushtia city, Bangladesh. Selective culture and biochemical tests were performed for the isolation and identification of microbial pathogens. Antibiotic resistance profiles were evaluated for isolated Escherichia coli using Kirby-Bauer method according to CLSI guidelines.Results: Aerobic mesophilic bacteria, Enterobacteriaceae and Pseudomonas spp. were the highest in paper currency from local hotel and ATM booth. Enterobacteriaceae (including coliforms) were predominantly present in paper currencies collected from local hotel, grocery, fish seller and beggar while Pseudomonas spp. were found in currency notes obtained from ATM booth, poultry farm, vegetable seller and local hotel. Antibiotic resistant profiles of E. coli isolated from local hotel currency showed that 50% of E. coli isolates were multidrug resistant. The highest resistant profile was observed against penicillin (95%) followed by polypeptide (75%), cephalosporin (50%), quinolone (30%) and sulfonamide (5%) groups of antibiotics.Conclusions: Multiple antibiotic resistant pathogenic bacteria are prevalent in paper currency regardless of their sources. Paper currency could contribute in transmission of infectious disease as well as in antibiotic resistance, therefore, should be handled carefully

The Impact of COVID-19 and the Challenges of Post-COVID Rehabilitation in a Developing Country

The coronavirus disease 2019 (COVID-19) and its impact on human functioning are gaining increased interest. Like many other lower-income countries, the Bangladesh health and rehabilitation sector was adversely affected by COVID-19. Multiple challenges were identified for preparedness and medical rehabilitation during COVID-19 surges. Appropriate supervision of multispecialty long COVID clinics and attention to rehabilitation teamwork are important. Rehabilitation plays a key role in the management of patients with COVID-19 and can reduce the length of hospital stay and improve health outcomes. While waiting for people to be fully vaccinated; ensuring equitable access to COVID-19 vaccination, health care, and rehabilitation services among people with disabilities should be a part of the core mission during the pandemic. All levels of care including, critical, post-acute, or long covid clinic scale-up of rehabilitation services are needed. A physiatrist-led rehabilitation team approach is vital for the adaptation of rehabilitation interventions to improve the functional outcomes of persons with impairment and disability affected by COVID-19

A Feasibility Study of a CHP System in a Commercial Facilities: Sizing and Parameters Analysis

The focus of this report is to design a CHP system using energy demand load profile for a food distribution center. This study has investigated energy requirements in food industry. The main distinction of this report is to carry out economic and environmental analysis of a CHP system. Case studies based on food industry demonstrates that the CHP system is able to run continuously at optimal efficiency and operational costs of the CHP system can be effectively reduced in both electric and heating cost