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A novel deep learning framework with temporal attention convolutional networks for intrusion detection in IoT and IIoT networks
Time-managed PAPR use enables a balanced approach to infection control and personal freedom
Abstract Full lockdowns during airborne-disease pandemics impose substantial socio-economic costs. To address this, to the best of the author’s knowledge, three prior contributions were made for the first time: (i) proposed a concept in which medical-grade Powered Air-Purifying Respirators (PAPRs) used by the general public can serve as an engineering alternative to lockdowns; (ii) disclosed a proof-of-concept PAPR with aerosol-blocking performance comparable to medical devices at a parts cost of USD 40; and (iii) demonstrated via mathematical modeling that if more than 55% of the population wears PAPRs continuously—or if everyone wears them intermittently to a moderate extent—the effective reproduction number R t can be reduced from 2.0 to 0.9. Building on these prior results, this study proposes and prototypes an IoT-based management framework—the PAPR Wearing-Status Networked Management System (PWS-NET)—that seeks to reconcile governmental infection control with individuals’ freedom to choose the time and place of non-wearing. The core metric is Saved Allowance Time (SAT), i.e., an accumulative daily allowance for mask-off periods. The prototype integrates three components: (a) real-time wearing detection for PAPRs using a differential-pressure sensor, (b) user-declared location via a smartphone application, and (c) a rule-based web server that updates SAT on a daily basis. Scenario tests that emulate realistic use conditions confirmed correct operation of SAT updates and violation judgments, as well as effective real-time visual feedback to users. Constructed entirely from off-the-shelf components, the prototype is intended as a starting point for large-scale field studies aimed at integrating SAT-based governance into public-health policy for future outbreaks.
Seasonal dynamics and species diversity of Anopheles mosquitoes in malaria endemic districts of Southern Odisha India
Identifying the biomarkers associated with G protein-coupled receptors of parkinson’s disease
Multispectral optoelectronic sensor to detect peripheral blood pulsatile variations with equivalent performance in light, medium and dark skin tones
Fusion of EEG feature extraction and CNN-MSTA transformer emotion recognition classification model
E2F1-mediated PKMYT1 upregulation promotes prostate cancer progression by inhibiting the PPAR signaling pathway
Age-stratified analysis of therapeutic, immune, and glycosylation gene expression in colorectal cancer using machine learning
Choosing dialysis modality in patients aged 75 and above with end-stage kidney disease: a multicenter cohort study
Computational insights into a protease inhibitor from Streptomyces globosus VITSMAB-2 molecular docking and dynamics simulations against SARS-CoV-2 main protease
Abstract Viral proteases are critical components in the life cycles of many dangerous viruses, playing a direct role in facilitating viral replication. Targeting these enzymes through inhibition offers a promising strategy for advancing antiviral agents. This study explores the potential of pigmented actinomycetes from high-altitude terrestrial environments as sources of antiviral agents against SARS-CoV-2, with a particular focus on identifying protease inhibitors. From this unique ecological niche, Streptomyces globosus VITSMAB2 was isolated and identified as a promising candidate due to its significant protease-inhibiting capabilities. Both qualitative and quantitative assays confirmed its strong inhibitory activity against key proteases, especially cysteine and serine proteases such as papain and trypsin. Protease inhibitory compounds were partially purified using Ultra-Performance Liquid Chromatography (UPLC), and their identities were determined through Gas Chromatography–Mass Spectrometry (GC-MS) analysis. Among the identified compounds, phenyl carbamate was the most prevalent and emerged as the lead molecule as protease inhibitor. Molecular docking studies revealed that phenyl carbamate exhibited strong binding interactions with the main protease (M-pro) of SARS-CoV-2, highlighting its potential as an antiviral agent. Additionally, assessments of the compound’s drug-likeness and ADME/T (absorption, distribution, metabolism, excretion, and toxicity) profiles indicated favorable pharmacokinetic properties, supporting its candidacy for therapeutic development. Molecular dynamics simulations further confirmed the stability of the phenyl carbamate-M-protease complex, reinforcing the compound’s antiviral potential. Therefore, phenyl carbamate shows considerable promise as a lead antiviral compound and merits further validation through extensive in vitro and in vivo experimentation to fully assess its therapeutic efficacy.