Publications by authors named "S P Mali"

Clinically significant problems such as kidney stones and stomach ulcers are linked to the activation of the urease enzyme. At low pH, this enzyme gives an ideal environment to Helicobacter pylori in the stomach which is the cause of gastric ulcers and peptic ulcers. In recent work, we have developed a library of 4-fluorocinnamaldehyde base thiosemicarbazones and assessed them for their potential against urease enzyme.

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Article Synopsis
  • Multiferroic materials combine ferroelectricity and magnetism, making them promising for applications like magnetic memory and spin transistors.
  • A new multiferroic chalcogenide semiconductor, CuMnSiTe, demonstrates unique properties such as a polar monoclinic crystal structure and canted antiferromagnetism below 35 K, along with significant magnetoelectric coupling.
  • Observations include high electric polarization at low temperatures and the potential for room-temperature ferroelectricity, marking it as a significant advancement in multiferroic materials research.
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The work being presented now combines severe gradient boosting with Shapley values, a thriving merger within the field of explainable artificial intelligence. We also use a genetic algorithm to analyse the HDAC1 inhibitory activity of a broad pool of 1274 molecules experimentally reported for HDAC1 inhibition. We conduct this analysis to ascertain the HDAC1 inhibitory activity of these molecules.

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Introduction: Cancer is the primary cause of death globally, and despite the significant advancements in treatment and survival rates, it is still stigmatized in many parts of the world. However, there is limited public health research on cancer stigma among the general female population in Nepal. Therefore, this study aims to determine the prevalence of cancer stigma and its associated factors in this group.

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One of the most familiar types of disease is Alzheimer's disease (AD) and it mainly impacts people over the age limit of 60. AD causes irreversible brain damage in humans. It is difficult to recognize the various stages of AD, hence advanced deep learning methods are suggested for recognizing AD in its initial stages.

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