Classification of cyclic alternating patterns of sleep using EEG signals.

Cyclic alternating patterns (CAP) occur in electroencephalogram (EEG) signals during non-rapid eye movement sleep. The analysis of CAP can offer insights into various sleep disorders. The first step is the identification of phases A and B for the CAP cycles.

Quantum Rectification Based on Room Temperature Multidirectional Nonlinearity in BiTe.

Recent interest in quantum nonlinearity has spurred the development of rectifiers for harvesting energy from ambient radiofrequency waves. However, these rectifiers face efficiency and bandwidth limitations at room temperature. We address these challenges by exploring BiTe, a time-reversal symmetric topological quantum material.

FlavorDB2: An updated database of flavor molecules.

Flavor is expressed through the interaction of molecules via gustatory and olfactory mechanisms. Knowing the pivotal role of flavor molecules in food and fragrances, the existence of a comprehensive repository becomes valuable. Such a repository encompasses the information of flavor molecules characterizing their flavor profile, chemical properties, regulatory status, consumption statistics, taste/aroma threshold values, reported uses in food categories, and synthesis.

Optimized deep maxout for crowd anomaly detection: A hybrid optimization-based model.

Monitoring Surveillance video is really time-consuming, and the complexity of typical crowd behaviour in crowded situations makes this even more challenging. This has sparked a curiosity about computer vision-based anomaly detection. This study introduces a new crowd anomaly detection method with two main steps: Visual Attention Detection and Anomaly Detection.

Robustaflavone as a novel scaffold for inhibitors of native and auto-proteolysed human neutrophil elastase.

Human neutrophil elastase (HNE) plays a key role in initiating inflammation in the cardiopulmonary and systemic contexts. Pathological auto-proteolysed two-chain (tc) HNE exhibits reduced binding affinity with inhibitors. Using AutoDock Vina v1.

An overview: total synthesis of arborisidine, and arbornamine.

Arborisidine and Arbornamine are two monoterpenoid indole alkaloids that were isolated from the Malayan Kopsia arborea plant. This review provides valuable information about the total and formal syntheses of these alkaloids. The synthesis strategies discussed in this review, such as Pictet-Spengler cyclization, chemo- and stereoselective oxidative cyclization, Michael/Mannich cascade process, and intramolecular N-alkylation, can be useful for developing new methods to synthesize these and other similar compounds.

Human exposure to uranium through drinking water and its detrimental impact on the human body organs.

Human exposure to high concentrations of uranium is a major concern due to the risk of developing numerous internal organ malignancies over time. In addition to the numerous attributes of uranium in the nuclear power industry, the radiological characteristics and chemical toxicity of uranium present a substantial risk to human health. This study aims to evaluate potential negative health impacts associated with the ingestion of uranium through drinking water in the Noida and Greater Noida region within the Gautam Buddha districts of Uttar Pradesh (India), due to extreme industrial revolution in this geological location.

Fuzzy lattices assisted EJAYA Q-learning for automated pulmonary diseases classification.

This work proposes a novel technique called Enhanced JAYA (EJAYA) assisted Q-Learning for the classification of pulmonary diseases, such as pneumonia and tuberculosis (TB) sub-classes using chest x-ray images. The work introduces Fuzzy lattices formation to handle real time (non-linear and non-stationary) data based feature extraction using Schrödinger equation. Features based adaptive classification is made possible through the Q-learning algorithm wherein optimal Q-values selection is done via EJAYA optimization algorithm.

Advancement in Synthetic Strategies of Phosphorus Heterocycles: Recent Progress from Synthesis to Emerging Class of Optoelectronic Materials.

Organophosphorus heterocycles have long been acknowledged for their significant potential across diverse fields, including catalysis, material science, and drug development. Incorporating phosphorus functionalities into organic compounds offers a means to effectively tailor their medicinal properties, augment biological responses, and enhance selectivity and bioavailability. The distinctive physical and photoelectric characteristics of phosphorus-containing conjugated compounds have garnered considerable interest as promising materials for organic optoelectronics.

Two-dimensional chiral perovskites with large spin Hall angle and collinear spin Hall conductivity.

Two-dimensional hybrid organic-inorganic perovskites with chiral spin texture are emergent spin-optoelectronic materials. Despite the wealth of chiro-optical studies on these materials, their charge-to-spin conversion efficiency is unknown. We demonstrate highly efficient electrically driven charge-to-spin conversion in enantiopure chiral perovskites (R/S-MB)(MA)PbI (〈〉 = 4), where MB is 2-methylbutylamine, MA is methylamine, Pb is lead, and I is iodine.

Harnessing the power of hybrid deep learning algorithm for the estimation of global horizontal irradiance.

Accurately and precisely estimating global horizontal irradiance (GHI) poses significant challenges due to the unpredictable nature of climate parameters and geographical limitations. To address this challenge, this study proposes a forecasting framework using an integrated model of the convolutional neural network (CNN), long short-term memory (LSTM), and gated recurrent unit (GRU). The proposed model uses a dataset of four different districts in Rajasthan, each with unique solar irradiance patterns.

Anaerobic digestion of herbal waste: a waste to energy option.

Herbal waste produced during the manufacturing of herbal products is a potential feedstock for anaerobic digestion due to high amount of organic matter that can be transformed into biogas as an energy resource. Therefore, the present study was undertaken to convert herbal waste produced during the manufacturing of common of Ayurveda products into biogas through anaerobic digestion process using batch test study under controlled mesophilic temperature conditions of 35 °C with food to inoculum ratio of 0.75.

Emerging pollutant in surface water bodies: a review on monitoring, analysis, mitigation measures and removal technologies of micro-plastics.

Water bodies play a crucial role in supporting life, maintaining the environment, and preserving the ecology for the people of India. However, in recent decades, human activities have led to various alterations in aquatic environments, resulting in environmental degradation through pollution. The safety of utilizing surface water sources for drinking and other purposes has come under intense scrutiny due to rapid population growth and industrial expansion.

A two-stage transformer based network for motor imagery classification.

Brain-computer interfaces (BCIs) are used to understand brain functioning and develop therapies for neurological and neurodegenerative disorders. Therefore, BCIs are crucial in rehabilitating motor dysfunction and advancing motor imagery applications. For motor imagery, electroencephalogram (EEG) signals are used to classify the subject's intention of moving a body part without actually moving it.

Phenol biodegradation using bio-filter tower packed column with immobilized bacterial consortium: a batch test study.

The effluents from pulp and paper manufacturing industries contain high concentrations of phenol, which when discharged directly into surface water streams, increases the biological oxygen demand (BOD) and chemical oxygen demand (COD). In this study, two dominant bacteria SP-4 and SP-8 were isolated from the effluent emanating with a pulp and paper industry. The selected phenol-degrading isolates were identified as Staphylococcus sp.

B-SAFE: Blockchain-Enabled Security Architecture for Connected Vehicle Fog Environment.

Vehicles are no longer stand-alone mechanical entities due to the advancements in vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communication-centric Internet of Connected Vehicles (IoV) frameworks. However, the advancement in connected vehicles leads to another serious security threat, online vehicle hijacking, where the steering control of vehicles can be hacked online. The feasibility of traditional security solutions in IoV environments is very limited, considering the intermittent network connectivity to cloud servers and vehicle-centric computing capability constraints.

Satellite or ground-based measurements for air pollutants (PM, PM, SO, NO, O) data and their health hazards: which is most accurate and why?

Air pollution is growing at alarming rates on regional and global levels, with significant consequences for human health, ecosystems, and change in climatic conditions. The present 12 weeks (4 October 2021, to 26 December 2021) study revealed the different ambient air quality parameters, i.e.

Auto-BCS: A Hybrid System for Real-Time Breast Cancer Screening from Pathological Images.

Breast cancer is recognized as a prominent cause of cancer-related mortality among women globally, emphasizing the critical need for early diagnosis resulting improvement in survival rates. Current breast cancer diagnostic procedures depend on manual assessments of pathological images by medical professionals. However, in remote or underserved regions, the scarcity of expert healthcare resources often compromised the diagnostic accuracy.

ECG arrhythmia detection in an inter-patient setting using Fourier decomposition and machine learning.

ECG beat classification or arrhythmia detection through artificial intelligence (AI) is an active topic of research. It is vital to recognize and detect the type of arrhythmia for monitoring cardiac abnormalities. The AI-based ECG beat classification algorithms proposed in the literature suffer from two main drawbacks.

Structural effect of the H992D/H418D mutation of angiotensin-converting enzyme in the Indian population: implications for health and disease.

The Non synonymous SNPs (nsSNPs) of the renin-angiotensin-system (RAS) pathway, unique to the Indian population were investigated in view of its importance as an endocrine system. nsSNPs of the RAS pathway genes were mined from the IndiGenome database. Damaging nsSNPs were predicted using SIFT, PredictSNP, SNP and GO, Snap2 and Protein Variation Effect Analyzer.

RC-LAHR: Road-Side-Unit-Assisted Cloud-Based Location-Aware Hybrid Routing for Software-Defined Vehicular Ad Hoc Networks.

The reliability of the communication link is quite common and challenging to handle as the topology changes frequently in vehicular ad hoc networks (VANETs). Another problem with VANETs is that the vehicles are from different manufacturers. Hence, the heterogeneity of hardware is obvious.

Segmentation of Brain MRI Images using Multi-Kernel FCM EHO Method.

Background: In image processing, image segmentation is a more challenging task due to different shapes, locations, image intensities, etc. Brain tumors are one of the most common diseases in the world. So, the detection and segmentation of brain tumors are important in the medical field.