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Sökning: WFRF:(Bhat Rahul)

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1.
  • Malik, Yashpal Singh, et al. (författare)
  • Coronavirus Disease Pandemic (COVID-19) : Challenges and a Global Perspective
  • 2020
  • Ingår i: Pathogens. - : MDPI AG. - 2076-0817. ; 9:7
  • Forskningsöversikt (refereegranskat)abstract
    • The technology-driven world of the 21st century is currently confronted with a major threat to humankind, represented by the coronavirus disease (COVID-19) pandemic, caused by the severe acute respiratory syndrome, coronavirus-2 (SARS-CoV-2). As of now, COVID-19 has affected more than 6 million confirmed cases and took 0.39 million human lives. SARS-CoV-2 spreads much faster than its two ancestors, SARS-CoV and Middle East respiratory syndrome-CoV (MERS-CoV), but has low fatality rates. Our analyses speculate that the efficient replication and transmission of SARS-CoV-2 might be due to the high-density basic amino acid residues, preferably positioned in close proximity at both the furin-like cleavage sites (S1/S2 and S2 ') within the spike protein. Given the high genomic similarities of SARS-CoV-2 to bat SARS-like CoVs, it is likely that bats serve as a reservoir host for its progenitor. Women and children are less susceptible to SARS-CoV-2 infection, while the elderly and people with comorbidities are more prone to serious clinical outcomes, which may be associated with acute respiratory distress syndrome (ARDS) and cytokine storm. The cohesive approach amongst researchers across the globe has delivered high-end viral diagnostics. However, home-based point-of-care diagnostics are still under development, which may prove transformative in current COVID-19 pandemic containment. Similarly, vaccines and therapeutics against COVID-19 are currently in the pipeline for clinical trials. In this review, we discuss the noteworthy advancements, focusing on the etiological viral agent, comparative genomic analysis, population susceptibility, disease epidemiology and diagnosis, animal reservoirs, laboratory animal models, disease transmission, therapeutics, vaccine challenges, and disease mitigation measures.
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2.
  • Malik, Yashpal Singh, et al. (författare)
  • Pitfalls and lessons for the future : Pitfalls and lessons for the future
  • 2021
  • Ingår i: Reviews in Medical Virology. - : John Wiley & Sons. - 1052-9276 .- 1099-1654. ; 31:5
  • Forskningsöversikt (refereegranskat)abstract
    • The clinical severity, rapid transmission and human losses due to coronavirus disease 2019 (Covid-19) have led the World Health Organization to declare it a pandemic. Traditional epidemiological tools are being significantly complemented by recent innovations especially using artificial intelligence (AI) and machine learning. AI-based model systems could improve pattern recognition of disease spread in populations and predictions of outbreaks in different geographical locations. A variable and a minimal amount of data are available for the signs and symptoms of Covid-19, allowing a composite of maximum likelihood algorithms to be employed to enhance the accuracy of disease diagnosis and to identify potential drugs. AI-based forecasting and predictions are expected to complement traditional approaches by helping public health officials to select better responses against Covid-19 cases. AI-based approaches have helped address the key issues but a significant impact on the global healthcare industry is yet to be achieved. The capability of AI to address the challenges may make it a key player in the operation of healthcare systems in future. Here, we present an overview of the prospective applications of the AI model systems in healthcare settings during the ongoing Covid-19 pandemic.
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3.
  • Raj, Rishabh, et al. (författare)
  • A Novel Cost-Effective Magnetic Characterization Tool for Soft Magnetic Materials Used in Electrical Machines
  • 2021
  • Ingår i: IEEE Transactions on Instrumentation and Measurement. - : IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC. - 0018-9456 .- 1557-9662. ; 70
  • Tidskriftsartikel (refereegranskat)abstract
    • Energy losses during the magnetization process of soft magnetic laminations depend on the excitation waveform. Manufacturers of magnetic materials may not provide lasses for different excitation waveforms. This may affect the accuracy of the predicted losses which are used to estimate the performance of electrical equipment during the predesign stage. Thus, a characterization tool which is capable of measuring hysteresis loops under controlled magnetization is required. Digital characterization systems available in literature use expensive commercial power amplifiers. In this work, a cost-effective power amplifier circuit is developed and interfaced with a LabVIEW program to characterize soft magnetic materials. The measurements for a sinusoidal excitation from the proposed setup are validated with those from a standard commercial measuring setup. The system is also used to measure hysteresis loops for arbitrary magnetization conditions (magnetic flux density (B) with harmonics). The proposed setup can operate over a frequency range 35-500 Hz. A small Epstein frame is also designed for measurements at higher frequencies (>200 and <500 Hz). A provision is also made to predict three components of dynamic hysteresis lasses at any frequency in the above range using the loss separation approach. This capability of the setup enables the user to predict the losses at frequencies beyond the capability of the tool. The predicted losses using this algorithm are validated with measured losses. The proposed setup is cost-effective and can be developed easily using basic electronic components.
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