STIT-Net- A Wavelet based Convolutional Transformer Model for Motor Imagery EEG Signal Classification in the Sensorimotor Bands.

Motor Imagery (MI) electroencephalographic (EEG) signal classification is a pioneer research branch essential for mobility rehabilitation. This paper proposes an end-to-end hybrid deep network "Spatio Temporal Inception Transformer Network (STIT-Net)" model for MI classification. Discrete Wavelet Transform (DWT) is used to derive the alpha (8-13) Hz and beta (13-30) Hz EEG sub bands which are dominant during motor tasks to enhance the performance of the proposed work.

Impact of mechanical engineering innovations in biomedical advancements.

Abstract: The principal objective of the present paper is to meticulously review the family of biomaterials used in implants. A spectrum of applications of biomaterials in the perspective of prosthesis is also presented. This paper also emphasises on the review of the recent advancements in the field of biomedical implants with respect to mechanical engineering perspective.

Microbial-Derived Biopolymers: A Pathway to Sustainable Civil Engineering.

Modern innovations increasingly prioritize eco-friendliness, aiming to pave the way for a sustainable future. The field of civil engineering is no exception to this approach, and, in fact, it is associated with almost every sustainable development goal framed by the United Nations. Therefore, the sector has a pivotal role in achieving these goals.

People's Attitude and Perception of the Pandemic on Twitter: A Case Study of COVID-19 in India.

Background Understanding the attitudes and perceptions of the general population is necessary for organizing health promotion initiatives. During outbreaks, social media has a significant impact on creating social perceptions. This study aims to identify and examine the emotions expressed and topics of discussion among Indian citizens related to COVID-19 third wave, from the messages posted on Twitter using text mining techniques.

Cholesterol-Lowering Activity of KS6I1 in High-Cholesterol Diet-Induced Hypercholesterolemic Mice.

Hypercholesterolemia is a risk factor of coronary heart disease and cholesterol-lowering probiotics are seen as alternative to drugs for the management of this condition. In the present study, we evaluated the cholesterol-lowering activity of KS6I1 in high-cholesterol diet-induced hypercholesterolemic mice. The mice were fed with high-cholesterol diet (HCD) and were divided into three groups: HCD group, KS6I1 group (fed with HCD + 200 μl of 10 CFU/ml KS6I1), and L.

Exploring the frontiers of metal additive manufacturing in orthopaedic implant development.

This paper provides a thorough analysis of recent advancements and emerging trends in the integration of metal additive manufacturing (AM) within orthopedic implant development. With an emphasis on the use of various metals and alloys, including titanium, cobalt-chromium, and nickel-titanium, the review looks at their characteristics and how they relate to the creation of various orthopedic implants, such as spinal implants, hip and knee replacements, and cranial-facial reconstructions. The study highlights how metal additive manufacturing (AM) can revolutionize the field by enabling customized implant designs that take patient anatomical variances into account.

Thermogravimetric analysis of rice husk and low-density polyethylene co-pyrolysis: kinetic and thermodynamic parameters.

The purpose of this study is to examine how co-pyrolysis of low-density polyethylene (LDPE) and rice husk is impacted by LDPE. It also looks into the physicochemical characteristics, thermal behavior, and kinetic parameters of these materials. To understand the thermal behavior through TGA, rice husk and LDPE blends in the ratios of LDPE: RH (50:50), LDPE: RH (25:75), and LDPE: RH (75:25) were prepared and tested.

Predictive modeling and optimization of a waste cooking oil biodiesel/diesel powered CI engine: an RSM approach with central composite design.

Due to the restrictions of the diesel engine emissions and the massive demand of energy, the fossil diesel fuel has been consumed quickly and the resources cannot suffice the demand. Alternative fuels that include bio alcohols, hydrogen and biodiesel can make up the diesel fuel depletion. Biodiesel is convenient for diesel engine operation due to its properties like fossil diesel properties.

Assessing thermal and economic performance of solar dryers in sustainable strategies for bottle gourd and tomato preservation.

The traditional approach of open-sun drying is facing contemporary challenges arising from the widespread adoption of energy-intensive methods and the quality of drying. In response, solar dryers have emerged as a sustainable alternative, utilizing solar thermal energy to effectively dehydrate vegetables. This study investigates the performance of a single-basin, double-slope solar dryer utilizing natural convection for drying bottle gourds and tomatoes, presenting a sustainable alternative to traditional open-sun drying.

Performance optimization for solar photovoltaic thermal system with spiral rectangular absorber using Taguchi method.

Solar collector systems efficiently transform sunlight into energy that may be used to meet various needs. This research aimed to use the Taguchi method to determine the ideal operating parameters for a solar thermal collector with a rectangular spiral absorber. Controllable parameters including mass flow rate, solar radiation, and absorber design were manipulated during the energy recovery process, and features like PV temperature and outlet water temperature were used to assess the system's effectiveness.

Experimentation on Sargassum wightii as a flash powder igniter for attaining eco-friendly combustion on pyrotechnics.

Firecrackers are a vital element of cultural festivities that happen worldwide. However, the hazardous by-products they emit have a significant impact on environmental pollution, leading to the greenhouse effect and climate change. Aluminium powder serves as the fuel in the traditional flash powder mixture, nitrate of potassium serves as an oxidizing agent, and sulphur acts as the igniter at exact concentrations.

A Medical Decision Support Platform for Identifying Thrombospondin 1 in Non-alcoholic Fatty Liver Disease via Immuno-Infiltration Analysis.

Non-alcoholic fatty liver disease (NAFLD) and myocardial infarction (MI) are two major health burdens with significant prevalence and mortality. This study aimed to explore the co-expressed genes to understand the relationship between NAFLD and MI and identify potential crucial biomarkers of NAFLD-related MI using bioinformatics and machine learning. Functional enrichment analysis was conducted, a co-protein-protein interaction (PPI) network diagram was constructed, and support vector machine-recursive feature elimination (SVM-RFE) and least absolute shrinkage and selection operator (LASSO) techniques were employed to identify one differentially expressed gene (DEG), Thrombospondin 1 (THBS1).

Brain tumor classification for combining the advantages of multilayer dense net-based feature extraction and hyper-parameters tuned attentive dual residual generative adversarial network classifier using wild horse optimization.

In this manuscript, attentive dual residual generative adversarial network optimized using wild horse optimization algorithm for brain tumor detection (ADRGAN-WHOA-BTD) is proposed. Here, the input imageries are gathered using BraTS, RemBRANDT, and Figshare datasets. Initially, the images are preprocessed to increase the quality of images and eliminate the unwanted noises.

Green synthesis of calcium nanoferrites using leaf extract of for photocatalysis of malachite green dye.

The calcium ferrite nanoparticles were made by the sol-gel process. X-ray diffraction, a scanning electron microscope, and UV-vis spectroscopy were used to analyze the material. There is an orthorhombic phase in the space group .

A Simple and Rapid Method of Probiotic Bacterial Ghost Cell Preparation to Deliver Mycobacterium tuberculosis Antigen.

A bacterial ghost cell is an empty cell envelope of bacteria lacking cytoplasmic content. Bacterial ghost cells (BGs) can be used for various applications such as vaccines, adjuvants, and drug delivery systems. Since BGs offer many advantages over classically prepared vaccines, developing novel methods for the preparation of high-quality BGs remains to be an interesting field of study by various research groups.

A preliminary study of combustion flame by digital image processing and residue for fireworks flash powder.

Fireworks play a vital role in festive celebrations and entertainment. These fireworks industries are administered by the Petroleum and Explosives Safety Organisation (PESO), Nagpur, Government of India. Even though PESO prescribed the standard composition for various fireworks products, concerns persist regarding the potential deviation from these standards, particularly in the pursuit of increased noise levels to attract consumers.

Fault causes and its detection in standalone PV system using ANN and GEO technique.

Power generation systems using photovoltaic (PV) technology have become increasingly popular due to their high production efficiency. A partial shading defect is the most common defect in this system under the process of production, diminishing both the amount and quality of energy produced. This paper proposes an Artificial Neural Network and Golden Eagle Optimization based prediction of the fault and its detection in a standalone PV system to recover the optimum performance and diagnosis of the PV system.

Diverse approaches to express recombinant spike protein: A comprehensive review.

The spike protein of the Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) is responsible for infecting host cells. It has two segments, S1 and S2. The S1 segment has a receptor-binding domain (RBD) that attaches to the host receptor angiotensin-converting enzyme 2 (ACE2).

Structural and functional insights of sortases and their interactions with antivirulence compounds.

Sortase proteins play a crucial role as integral membrane proteins in anchoring bacterial surface proteins by recognizing them through a Cell-Wall Sorting (CWS) motif and cleaving them at specific sites before initiating pilus assembly. Both sortases and their substrate proteins are major virulence factors in numerous Gram-positive pathogens, making them attractive targets for antimicrobial intervention. Recognizing the significance of virulence proteins, a comprehensive exploration of their structural and functional characteristics is essential to enhance our understanding of pilus assembly in diverse Gram-positive bacteria.

TO-LAB model: Real time Touchless Lung Abnormality detection model using USRP based machine learning algorithm.

Background: Due to the increasing prevalence of respiratory diseases and the importance of early diagnosis. The need for non-invasive and touchless medical diagnostic solutions has become increasingly crucial in modern healthcare to detect lung abnormalities.

Objective: Existing methods for lung abnormality detection often rely on invasive and time-consuming procedures limiting their effectiveness in real-time diagnosis.

Multi-instance learning attention model for amyloid quantification of brain sub regions in longitudinal cognitive decline.

Amyloid PET scans help in identifying the beta-amyloid deposition in different brain regions. The purpose of this study is to develop a deep learning model that can automate the task of finding amyloid deposition in different regions of the brain only by using PET scan and without the corresponding MRI scan. 2647 F-Florbetapir PET scans are collected from Alzheimer's Disease Neuroimaging Initiative (ADNI) from multiple centres taken over a period.

The synergistic interplay of artificial intelligence and digital twin in environmentally planning sustainable smart cities: A comprehensive systematic review.

The dynamic landscape of sustainable smart cities is witnessing a significant transformation due to the integration of emerging computational technologies and innovative models. These advancements are reshaping data-driven planning strategies, practices, and approaches, thereby facilitating the achievement of environmental sustainability goals. This transformative wave signals a fundamental shift - marked by the synergistic operation of artificial intelligence (AI), artificial intelligence of things (AIoT), and urban digital twin (UDT) technologies.