Conventional and Advanced Methods Used for the Diagnosis of Fascioliosis, a Food-Borne Zoonotic Disease.

Fascioliosis is a food-borne zoonotic helminth infection caused by flatworms belonging to the family Fasciolidae, primarily affecting ruminants. The chronic form of fascioliosis is the most prevalent and is characterized by anemia, weight loss, cirrhosis, and liver dysfunction, along with atrophy, jaundice, and bottle jaw. In humans, infection results in fever, nausea, skin rashes, and severe abdominal pain.

Investigating the linkage between knowledge sharing attitude, self-efficacy, and behavior in Bangladeshi information technology sector: Knowledge sharing intention as a mediator.

The research aims to investigate how employees' knowledge-sharing behavior (KSB) is affected by knowledge-sharing attitude (KSA) and knowledge-sharing self-efficacy (KSSE) when knowledge-sharing intention (KSI) is a mediator at IT companies in Bangladesh, using the widely accepted Theory of Planned Behavior as the underlying research framework. This investigation is explanatory in nature which emphasizes on the link among variables and follows quantitative research method. Data was assembled in google form applying convenience sampling from 295 employees working in seven IT companies of Bangladesh.

A Taguchi-based study on the control factors of reinforced composites with the fiber of coir and pineapple leaves.

The use of composite materials, whether metallic or non-metallic, is becoming more popular nowadays because of some of their superior characteristics compared to the use of wood and metallic materials alone. From this perspective, a new natural fiber reinforced composite by varying the fiber orientation was developed in this study using coir and pineapple leaf fiber. This work uses the Taguchi method to investigate the different effects of control factors on mechanical and physical characteristics of the fabricated natural fiber-based composites.

Beyond Serology: A Meta-Analysis of Advancements in Molecular Detection of Brucella spp. in Seronegative Animals and Biological Samples.

Background: Brucellosis is a zoonotic disease caused by Brucella spp., affecting various animals and humans, leading to significant economic and public health impacts. Traditional diagnostic methods, mainly serological, often fail to detect seronegative carriers, which continue to spread the infection.

Refining breast cancer classification: Customized attention integration approaches with dense and residual networks for enhanced detection.

Objective: Breast cancer detection is critical for timely and effective treatment, and automatic detection systems can significantly reduce human error and improve diagnosis speed. This study aims to develop an accurate and robust framework for classifying breast cancer into benign and malignant categories using a novel machine learning architecture.

Methods: We propose a dense-ResNet attention integration (DRAI) architecture that combines DenseNet and ResNet models with three attention mechanisms to enhance feature extraction from the BreakHis dataset.

Exploring happiness factors with explainable ensemble learning in a global pandemic.

Happiness is a state of contentment, joy, and fulfillment, arising from relationships, accomplishments, and inner peace, leading to well-being and positivity. The greatest happiness principle posits that morality is determined by pleasure, aiming for a society where individuals are content and free from suffering. While happiness factors vary, some are universally recognized.

Myrrh Oleo-Gum Resin as a Functional Additive in Pectin and κ-Carrageenan Composite Films for Food Packaging.

Myrrh oleo-gum-resin (MOGR) is a natural substance that has a rich history of medicinal use due to its anti-inflammatory, antimicrobial, and antioxidant properties. The present study reports on the fabrication and assessment of pectin and K-carrageenan composite films infused with varying proportions (0.3%, 0.

Optimizing hypertension prediction using ensemble learning approaches.

Hypertension (HTN) prediction is critical for effective preventive healthcare strategies. This study investigates how well ensemble learning techniques work to increase the accuracy of HTN prediction models. Utilizing a dataset of 612 participants from Ethiopia, which includes 27 features potentially associated with HTN risk, we aimed to enhance predictive performance over traditional single-model methods.

Quality aspects of paddy grain and seed dried in HSTU mobile grain and seed dryer integrated with a dual heating system.

Proper drying and excellence of dried grain and seed are the key concerns of millers, farmers and seed growers. The performance of a new Hajee Mohammad Danesh Science and Technology University (HSTU) mobile grain and seed dryer (HMD) integrated with dual heating system was assessed regarding the quality of dried seed and grain. The HMD was found to be capable of drying 720 ± 10 kg paddy in a batch and drying period varied between 7 and 8 h at drying air temperatures of 65 °C.

The Design and Implementation of Kerberos-Blockchain Vehicular Ad-Hoc Networks Authentication Across Diverse Network Scenarios.

Vehicular Ad-Hoc Networks (VANETs) play an essential role in the intelligent transportation era, furnishing users with essential roadway data to facilitate optimal route selection and mitigate the risk of accidents. However, the network exposure makes VANETs susceptible to cyber threats, making authentication crucial for ensuring security and integrity. Therefore, joining entity verification is essential to ensure the integrity and security of communication in VANETs.

Bael () fruit-based effervescent tablet formulations: Impact on physicochemical properties, bioactive compounds, and sensory attributes.

This study investigates the formulation and optimization of effervescent tablets made from freeze-dried bael () fruit pulp, focusing on selecting appropriate excipients to enhance stability and ensure the effective release of its bioactive compounds for health benefits. The formulations-S (100 % fruit pulp), S (20 % citric acid), S (10 % citric acid and 10 % ascorbic acid), and S (20 % ascorbic acid) combined with equal parts of dried bael pulp, sodium bicarbonate, sugar, polyethylene glycol, and stevia were assessed for their physicochemical properties, bioactive compounds, and sensory study. The S demonstrated the fastest dissolution time (189 s), along with the lowest bulk density (0.

Enhancing land cover object classification in hyperspectral imagery through an efficient spectral-spatial feature learning approach.

The classification of land cover objects in hyperspectral imagery (HSI) has significantly advanced due to the development of convolutional neural networks (CNNs). However, challenges such as limited training data and high dimensionality negatively impact classification performance. Traditional CNN-based methods predominantly utilize 2D CNNs for feature extraction, which inadequately exploit the inter-band correlations in HSIs.

Exploring bacterial key genes and therapeutic agents for breast cancer among the Ghanaian female population: Insights from In Silico analyses.

Breast cancer (BC) is yet a significant global health challenge across various populations including Ghana, though several studies on host-genome associated with BC have been investigated molecular mechanisms of BC development and progression, and candidate therapeutic agents. However, a little attention has been given on microbial genome in this regard, although alterations in microbiota and epigenetic modifications are recognized as substantial risk factors for BC. This study focused on identifying bacterial key genes (bKGs) associated with BC infections in the Ghanaian population and exploring potential drug molecules by targeting these bKGs through in silico analyses.

Preventing enzymatic browning of freshly cut green bananas through immersion in normal water, lemon juice, and coconut water.

The rising demand for freshly cut agricultural produce like bananas, apples, pears, potatoes, and roots due to health concerns and modern lifestyles has heightened awareness of their susceptibility to browning, which diminishes their appeal and contributes to food waste. The present study explored the efficacy of natural anti-browning agents in prolonging the quality and shelf-life of freshly cut green banana slices. The bananas underwent treatment with normal water (NW), lemon juice (LJ), and coconut water (CW), and the changes in physicochemical properties, such as browning intensity, color, firmness, total soluble solid (TSS), total phenolic content (TPC), total flavonoid content (TFC), and also microbial attributes, were evaluated during their storage at 4 ± 1°C for 12 days.

Towards privacy-preserving Alzheimer's disease classification: Federated learning on T1-weighted magnetic resonance imaging data.

Objective: This study aims to address the challenge of privacy-preserving Alzheimer's disease classification using federated learning across various data distributions, focusing on real-world applicability. The goal is to improve the efficiency of classification by minimizing communication rounds between clients and the central server.

Methods: The proposed approach leverages two key strategies: increasing parallelism by utilizing more clients in each communication round and increasing computation per client during the intervals between rounds.

Prevalence, Risk Factors, and Antimicrobial Resistance of and Species Isolated from Subclinical Bovine Mastitis.

Subclinical mastitis (SCM) is a prevalent serious disease among dairy cows worldwide. It poses a significant challenge to the dairy industry, animal welfare, and a threat to public health. The present study aimed to investigate the molecular detection, prevalence, and antimicrobial resistance of spp.

Effects of Titanium Dioxide Nanoparticles on Chick Embryo: Immunomodulatory, Hepatic and Biochemical Alterations.

Background: The utilization of titanium dioxide nanoparticles (TiO NPs) has significantly increased across various industries.

Objectives: This study rigorously explored the impact of TiO NPs exposure on chicken embryos, focusing particularly on alterations in the immune system, liver functionality and key biochemical markers.

Methods: The study involved three groups of 30 eggs each, subjected to increasing doses of TiO NPs: Group C (control), Group T1 (150 µg/mL) and Group T2 (300 µg/mL).

A Multi-level ensemble approach for skin lesion classification using Customized Transfer Learning with Triple Attention.

Skin lesions encompass a variety of skin abnormalities, including skin diseases that affect structure and function, and skin cancer, which can be fatal and arise from abnormal cell growth. Early detection of lesions and automated prediction is crucial, yet accurately identifying responsible regions post-dominance dispersion remains a challenge in current studies. Thus, we propose a Convolutional Neural Network (CNN)-based approach employing a Customized Transfer Learning (CTL) model and Triple Attention (TA) modules in conjunction with Ensemble Learning (EL).

Innovative probiotic yogurt: Leveraging green banana peel for enhanced quality, functionality, and sensory attributes.

Yogurt, a popular dairy product renowned for its nutritional benefits and probiotic content, serves as a functional food with potential health-promoting properties. The objective of this study was to investigate whether incorporating green banana peel polyphenol extract (GBPPE) into yogurt formulations enhances the viability and functionality of probiotics while also potentially improving the overall quality and health-promoting properties of the yogurts. GBPPE was extracted and added to the yogurt formulation at 0.

An explainable ensemble approach for advanced brain tumor classification applying Dual-GAN mechanism and feature extraction techniques over highly imbalanced data.

Brain tumors are one of the leading diseases imposing a huge morbidity rate across the world every year. Classifying brain tumors accurately plays a crucial role in clinical diagnosis and improves the overall healthcare process. ML techniques have shown promise in accurately classifying brain tumors based on medical imaging data such as MRI scans.

Varietal influence on bioactive compounds and antioxidant activity in chilies during development stages.

Numerous cultivars of chili are grown in Bangladesh for their nutritional and sensory attributes, serving as both spices and food items. Among many, indigenous chili cultivars in Bangladesh include Sada Akshi, Kajini, Dhani, and Naga are the important ones. The functional qualities of chili peppers are attributed to the plentiful presence of bioactive substances.