Monitoring the effects of vegetation cover losses on land surface temperature dynamics using geospatial approach in Rajshahi City, Bangladesh

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A Meandered Line Patch Antenna at Low Frequency Range for Early Stage Breast Cancer Detection

Every year a concerning number of women are affected by breast cancer which is one of the deadliest and common types of cancers. Breast cancer is curable at early stages. For detecting breast cancer, there are several methods such as MRI, Mammography, Tomography, Ultrasound, and biopsy are available in medical technology. Still, none of them are as easy and efficient as a microwave imaging technique, in this method, the antenna plays an important role. Therefore, this paper focuses on developing an antenna at a low-frequency range for microwave imaging techniques to detect cancerous tissue inside the breast. For this, the antenna parameters, i.e., return loss, VSWR, directivity, current density, and specific absorption rate were studied, by setting the antenna over without tumor and with tumor breast as up-side-down, to ensure the compatibility of the antenna for the technique as well as for the patient’s body. A 5mm radius cancerous tumor was created inside the breast with dielectric conductivity of 4 and relative permittivity of 50. Cancerous cells were detected by reading the antenna parameters’ comparison between the healthy breast and the affected breast. The whole study was conducted by using CST MICROWAVE STUDIO SUITE 2020.

Synthesis and Characterization of Functionalized Silica-Nanoparticles and their Applications for the Removal of Pesticides from Aqueous Solution

Silica nanoparticles functionalized with three different active functional groups (C-8, cyano-propyl, and methacrylate (MA)) were synthesized, characterized and applied for the removal of ten carbamate pesticides from aqueous solution. Two methods were used for the synthesis of functionalized silica (grafting and sol-gel method). SEM, FTIR, and HCN were used for the characterization of the particles, while LC-MS/MS was used for the quantitative analysis of carbamate pesticides in the non-treated and treated aqueous solutions. The characterization results indicated the formation of uniformed, spherical and mono-dispersed particles when the cyano and MA particles were prepared by the Sol-gel. Also, results indicated that all of the synthesized particles were enhances for the removal of carbamate pesticides, and MA prepared by the Sol-gel methods had the highest ? removal for most of the carbamate pesticides tested.qscienc

LLDNet: A Lightweight Lane Detection Approach for Autonomous Cars Using Deep Learning

Lane detection plays a vital role in making the idea of the autonomous car a reality. Traditional lane detection methods need extensive hand-crafted features and post-processing techniques, which make the models specific feature-oriented, and susceptible to instability for the variations on road scenes. In recent years, Deep Learning (DL) models, especially Convolutional Neural Network (CNN) models have been proposed and utilized to perform pixel-level lane segmentation. However, most of the methods focus on achieving high accuracy while considering structured roads and good weather conditions and do not put emphasis on testing their models on defected roads, especially ones with blurry lane lines, no lane lines, and cracked pavements, which are predominant in the real world. Moreover, many of these CNN-based models have complex structures and require high-end systems to operate, which makes them quite unsuitable for being implemented in embedded devices. Considering these shortcomings, in this paper, we have introduced a novel CNN model named LLDNet based on an encoder–decoder architecture that is lightweight and has been tested in adverse weather as well as road conditions. A channel attention and spatial attention module are integrated into the designed architecture to refine the feature maps for achieving outstanding results with a lower number of parameters. We have used a hybrid dataset to train our model, which was created by combining two separate datasets, and have compared the model with a few state-of-the-art encoder–decoder architectures. Numerical results on the utilized dataset show that our model surpasses the compared methods in terms of dice coefficient, IoU, and the size of the models. Moreover, we carried out extensive experiments on the videos of different roads in Bangladesh. The visualization results exhibit that our model can detect the lanes accurately in both structured and defected roads and adverse weather conditions. Experimental results elicit that our designed method is capable of detecting lanes accurately and is ready for practical implementation

Polyphenols: Role in Modulating Immune Function and Obesity

Polyphenols, long-used components of medicinal plants, have drawn great interest in recent years as potential therapeutic agents because of their safety, efficacy, and wide range of biological effects. Approximately 75% of the world’s population still use plant-based medicinal compounds, indicating the ongoing significance of phytochemicals for human health. This study emphasizes the growing body of research investigating the anti-adipogenic and anti-obesity functions of polyphenols. The functions of polyphenols, including phenylpropanoids, flavonoids, terpenoids, alkaloids, glycosides, and phenolic acids, are distinct due to changes in chemical diversity and structural characteristics. This review methodically investigates the mechanisms by which naturally occurring polyphenols mediate obesity and metabolic function in immunomodulation. To this end, hormonal control of hunger has the potential to inhibit pro-obesity enzymes such as pancreatic lipase, the promotion of energy expenditure, and the modulation of adipocytokine production. Specifically, polyphenols affect insulin, a hormone that is essential for regulating blood sugar, and they also play a role, in part, in a complex web of factors that affect the progression of obesity. This review also explores the immunomodulatory properties of polyphenols, providing insight into their ability to improve immune function and the effects of polyphenols on gut health, improving the number of commensal bacteria, cytokine production suppression, and immune cell mediation, including natural killer cells and macrophages. Taken together, continuous studies are required to understand the prudent and precise mechanisms underlying polyphenols’ therapeutic potential in obesity and immunomodulation. In the interim, this review emphasizes a holistic approach to health and promotes the consumption of a wide range of foods and drinks high in polyphenols. This review lays the groundwork for future developments, indicating that the components of polyphenols and their derivatives may provide the answer to urgent worldwide health issues. This compilation of the body of knowledge paves the way for future discoveries in the global treatment of pressing health concerns in obesity and metabolic diseases

Enhancing Monkeypox diagnosis and explanation through modified transfer learning, vision transformers, and federated learning

The Monkeypox outbreak has emerged as a pressing global health challenge, evidenced by rising cases across nations. Individuals afflicted exhibit diverse dermatological symptoms that risk further transmission via contamination. Our study assessed the efficacy of three modified transfer learning models (M-VGG16, M-ResNet50, M-ResNet101) alongside vision transformers (ViT) across four investigations. We achieved high accuracy in discriminating Monkeypox cases, with M-VGG16 achieving 88%, 76%, and 77% accuracy in Studies One, Two and Four and M-ResNet50 achieving 89% in Study Three. To comprehend triggers for Monkeypox onset, we utilized Local Interpretable Model-Agnostic Explanations (LIME) to explain predictions visually. LIME alignments underscored our models' high accuracy, correlating with segmented identification of infected regions. Further, we implemented Federated Learning on decentralized data to evaluate generalization capabilities. Blending established deep learning with emerging decentralized learning and explanation techniques is vital in improving predictive accuracy and elucidating Monkeypox intricacies amid the persisting global outbreak. Our study emphasizes the continued relevance of pioneering techniques while introducing new approaches to address this major health challenge

Clinically proven natural products, vitamins and mineral in boosting up immunity: A comprehensive review

Background: and Purposes: The terminology “immune boost-up” was the talk of the topic in this Covid-19 pandemic. A significant number of the people took initiative to increase the body's defense capacity through boosting up immunity worldwide. Considering this, the study was designed to explain the natural products, vitamins and mineral that were proved by clinical trail as immunity enhancer. Methods: Information was retrieved from SciVerse Scopus ® (Elsevier Properties S. A, USA), Web of Science® (Thomson Reuters, USA), and PubMed based on immunity, nutrients, natural products in boosting up immunity, minerals and vitamins in boosting up immunity, and immune booster agents. Result: A well-defined immune cells response provide a-well functioning defense system for the human physiological system. Cells of the immune system must require adequate stimulation so that these cells can prepare themselves competent enough to fight against any unintended onslaught. Several pharmacologically active medicinal plants and plants derived probiotics or micronutrients have played a pivotal role in enhancing the immune boost-up process. Their role has been well established from the previous study. Immune stimulating cells, especially cells of acquired immunity are closely associated with the immune-boosting up process because all the immunological reactions and mechanisms are mediated through these cells. Conclusion: This article highlighted the mechanism of action of different natural products, vitamins and mineral in boosting up the immunity of the human body and strengthening the body's defense system. Therefore, it is recommended that until the specific immune-boosting drugs are available in pharma markets, anyone can consider the mentioned products as dietary supplements to boost up the immunity

Novel Mutation in the Feline <i>GAA</i> Gene in a Cat with Glycogen Storage Disease Type II (Pompe Disease)

Glycogen storage disease type II (Pompe disease: PD) is an autosomal recessively inherited fatal genetic disorder that results from the deficiency of a glycogen hydrolyzing enzyme, acid α-glucosidase encoded by the GAA gene. Here, we describe the molecular basis of genetic defects in an 8-month-old domestic short-haired cat with PD. The cat was previously diagnosed with PD based on the clinical and pathological findings of hypertrophic cardiomyopathy and excessive accumulation of glycogen in the cardiac muscles. Sanger sequencing was performed on 20 exons of the feline GAA gene using genomic DNA extracted from paraffin-embedded liver tissues. The affected cat was found to be homozygous for the GAA:c.1799G>A mutation resulting in an amino acid substitution (p.R600H) of acid α-glucosidase, a codon position of which is identical with three missense mutations (p.R600C, p.R600L, and p.R600H) causing human infantile-onset PD (IOPD). Several stability and pathogenicity predictors have also shown that the feline mutation is deleterious and severely decreases the stability of the GAA protein. The clinical, pathological, and molecular findings in the cat were similar to those of IOPD in humans. To our knowledge, this is the first report of a pathogenic mutation in a cat. Feline PD is an excellent model for human PD, especially IOPD

Prevalence and multidrug resistance pattern of Salmonella isolated from resident wild birds of Bangladesh

Aim: Salmonellosis is one of the most common zoonotic diseases, and the presence of antimicrobial resistant Salmonella in wild birds is global public health threat. Throughout the last decades, multidrug resistance of Salmonella spp. has increased, particularly in developing countries. Therefore, a cross-sectional study was conducted to investigate the prevalence of Salmonella spp. and antimicrobial resistance pattern against Salmonella spp. from two species of resident wild birds namely house crow (Corvus splendens) and Asian pied starling (Gracupica contra). Materials and Methods: Samples were collected from cloacal swabs of house crows and Asian pied starling for isolating Salmonella spp. (bacteriological culture methods) followed by antimicrobial susceptibility testing (disk diffusion method) against Salmonella spp. isolates during March to December 2014. Results: The prevalence of Salmonella in Asian pied starling and house crows were 67% and 65%, respectively. Within the category of samples from different species, the variation in prevalence was not varied significantly (p>0.05). Isolated Salmonella spp. was tested for resistance to six different antimicrobial agents. Among six antimicrobial tested, 100% resistance were found to penicillin, oxacillin, and clindamycin followed by erythromycin (50-93%), kanamycin (7-20%), and cephalothin (30-67%) from both species of birds. Kanamycin remained sensitive in (70-73%), cephalothin (26-70%), and erythromycin appeared to be (0-30%) sensitive against Salmonella spp. isolates. Isolated Salmonella spp. was multidrug resistant up to three of the six antimicrobials tested. Conclusion: It can be said that the rational use of antimicrobials needs to be adopted in the treatment of disease for livestock, poultry, and human of Bangladesh to limit the emergence of drug resistance to Salmonella spp