Behavioral Impacts of the Fear of AIDS: A Sociological Model

The paper demonstrates the conceptual meaning and utility of a sociological model for identifying correlates of the fear of AIDS and its consequent changes on peoples\u27 behaviors. A sociological notion of levels of analysis is employed for classifying correlates of AIDS\u27 fears under structural and individual categories. A tentative list of these correlates and their projected relationship with peoples\u27 fears is suggested to illustrate the model

Geotechnical Appraisal of the Thar Open Cut Mining Project

This paper is concerned with a slope stability appraisal of the proposed open cut mining operations in the Thar lignite field in Sindh, Pakistan. The Thar coalfield covers an area of approximately 9 000 km2 and is estimated to contain 193 billion tonnes of lignite resources. The design of safe high wall slopes is necessary to ensure mine safety and overall economical viability of the mining operations. In the Thar lignite field, the presence of three main aquifers induces pore pressure in the rock mass surrounding the lignite seams and makes high wall slopes potentially unsafe. It is, therefore, necessary to dewater the rock mass before commencing mining excavations. A proposed mine dewatering scheme to facilitate rock mass dewatering surrounding the mining excavations and a description of the slope stability analysis of the high wall using the software “SLIDE” version 5 is outlined. Three computer models with slope angles of 28o, 29o and 30o, incorporating a plane failure mode, were analyzed to investigate the stability of pit slopes. The generalized stratigraphy of borehole RE-25 has been used for the development of the computer models. The main conclusions of this study are that the slope angle of 28o is quite acceptable for a Stability Factor (SF) ≤ 1.3 whereas the excavated slopes with slope angles ≥ 29o are not safe against the plane failure for SF\u3e1.3. This assessment was followed by a slope stability analysis incorporating circular failure modes. Five models incorporating various slope angles ranging from 23o to 27o and one model incorporating combined slope angles of 23o in dune sand and 26o in the rest of the strata were developed and analysed. The main conclusions from this study are that the dune sand layer (having a thickness of 48 m) is acceptable for a SF of 1.3 at slope angle ≤ 23o, while the rest of the strata is acceptable for SF=1.3 at slope angles ≤ 26o. The overburden to lignite extraction ratio for this slope design has been calculated as 3:1 or 3 m3 of overburden over 1 t of lignite

A Study of Probable Submerged Area in the Catchment with the Change in Elevation of Sundarijal Hydropower Dam in Nepal

Sundarijal Watershed in Shivapuri National Park, Nepal has been providing services to Kathmandu Valley population in terms of Hydropower Generation and Drinking Water Supply. In this study, the probable submerged area in the catchment with the change in elevation of Sundarijal Hydropower Dam is calculated with the help of GIS-based tools and land use maps. In addition, assessment of the impacts on the vicinity due to the impounding reservoir is prepared. We hope that this study will be useful in designing of dam of an optimum elevation with minimum effects on the environment and maximum efficiency for sustainable period

Vascular Implications of COVID-19: Role of Radiological Imaging, Artificial Intelligence, and Tissue Characterization: A Special Report

The SARS-CoV-2 virus has caused a pandemic, infecting nearly 80 million people worldwide, with mortality exceeding six million. The average survival span is just 14 days from the time the symptoms become aggressive. The present study delineates the deep-driven vascular damage in the pulmonary, renal, coronary, and carotid vessels due to SARS-CoV-2. This special report addresses an important gap in the literature in understanding (i) the pathophysiology of vascular damage and the role of medical imaging in the visualization of the damage caused by SARS-CoV-2, and (ii) further understanding the severity of COVID-19 using artificial intelligence (AI)-based tissue characterization (TC). PRISMA was used to select 296 studies for AI-based TC. Radiological imaging techniques such as magnetic resonance imaging (MRI), computed tomography (CT), and ultrasound were selected for imaging of the vasculature infected by COVID-19. Four kinds of hypotheses are presented for showing the vascular damage in radiological images due to COVID-19. Three kinds of AI models, namely, machine learning, deep learning, and transfer learning, are used for TC. Further, the study presents recommendations for improving AI-based architectures for vascular studies. We conclude that the process of vascular damage due to COVID-19 has similarities across vessel types, even though it results in multi-organ dysfunction. Although the mortality rate is ~2% of those infected, the long-term effect of COVID-19 needs monitoring to avoid deaths. AI seems to be penetrating the health care industry at warp speed, and we expect to see an emerging role in patient care, reduce the mortality and morbidity rate

Economics of Artificial Intelligence in Healthcare: Diagnosis vs. Treatment

Motivation: The price of medical treatment continues to rise due to (i) an increasing population; (ii) an aging human growth; (iii) disease prevalence; (iv) a rise in the frequency of patients that utilize health care services; and (v) increase in the price. Objective: Artificial Intelligence (AI) is already well-known for its superiority in various healthcare applications, including the segmentation of lesions in images, speech recognition, smartphone personal assistants, navigation, ride-sharing apps, and many more. Our study is based on two hypotheses: (i) AI offers more economic solutions compared to conventional methods; (ii) AI treatment offers stronger economics compared to AI diagnosis. This novel study aims to evaluate AI technology in the context of healthcare costs, namely in the areas of diagnosis and treatment, and then compare it to the traditional or non-AI-based approaches. Methodology: PRISMA was used to select the best 200 studies for AI in healthcare with a primary focus on cost reduction, especially towards diagnosis and treatment. We defined the diagnosis and treatment architectures, investigated their characteristics, and categorized the roles that AI plays in the diagnostic and therapeutic paradigms. We experimented with various combinations of different assumptions by integrating AI and then comparing it against conventional costs. Lastly, we dwell on three powerful future concepts of AI, namely, pruning, bias, explainability, and regulatory approvals of AI systems. Conclusions: The model shows tremendous cost savings using AI tools in diagnosis and treatment. The economics of AI can be improved by incorporating pruning, reduction in AI bias, explainability, and regulatory approvals. © 2022 by the authors

Unrestricted Hartree-Fock Analysis of Sr3−x_{3-x}Cax_xRu2_2O7_7

We investigated the electronic and magnetic structure of Sr$_{3-x}$Ca$_x$Ru$_2$O$_7$ ($0 \leq x \leq 3$) on the basis of the double-layered three-dimensional multiband Hubbard model with spin-orbit interaction. In our model, lattice distortion is implemented as the modulation of transfer integrals or a crystal field. The most stable states are estimated within the unrestricted Hartree-Fock approximation, in which the colinear spin configurations with five different spin-quantization axes are adopted as candidates. The obtained spin structures for some particular lattice distortions are consistent with the neutron diffraction results for Ca$_3$Ru$_2$O$_7$. Also, some magnetic phase transitions can occur due to changes in lattice distortion. These results facilitate the comprehensive understanding of the phase diagram of Sr$_{3-x}$Ca$_x$Ru$_2$O$_7$.Comment: 16 pages, 7 figure

Observation of Multi-Gap Superconductivity in GdO(F)FeAs by Andreev Spectroscopy

We have studied current-voltage characteristics of Andreev contacts in polycrystalline GdO$_{0.88}$F$_{0.12}$FeAs samples with bulk critical temperature ${T_c}$ = (52.5 \pm 1)K using break-junction technique. The data obtained cannot be described within the single-gap approach and suggests the existence of a multi-gap superconductivity in this compound. The large and small superconducting gap values estimated at T = 4.2K are {\Delta}L = 10.5 \pm 2 meV and {\Delta}S = 2.3 \pm 0.4 meV, respectively.Comment: 5 pages, 4 figures, submitted to JETP Letter

Zinc oxide nanoparticles prepared through microbial mediated synthesis for therapeutic applications: a possible alternative for plants

Zinc oxide nanoparticles (ZnO-NPs) synthesized through biogenic methods have gained significant attention due to their unique properties and potential applications in various biological fields. Unlike chemical and physical approaches that may lead to environmental pollution, biogenic synthesis offers a greener alternative, minimizing hazardous environmental impacts. During biogenic synthesis, metabolites present in the biotic sources (like plants and microbes) serve as bio-reductants and bio-stabilizers. Among the biotic sources, microbes have emerged as a promising option for ZnO-NPs synthesis due to their numerous advantages, such as being environmentally friendly, non-toxic, biodegradable, and biocompatible. Various microbes like bacteria, actinomycetes, fungi, and yeast can be employed to synthesize ZnO-NPs. The synthesis can occur either intracellularly, within the microbial cells, or extracellularly, using proteins, enzymes, and other biomolecules secreted by the microbes. The main key advantage of biogenic synthesis is manipulating the reaction conditions to optimize the preferred shape and size of the ZnO-NPs. This control over the synthesis process allows tailoring the NPs for specific applications in various fields, including medicine, agriculture, environmental remediation, and more. Some potential applications include drug delivery systems, antibacterial agents, bioimaging, biosensors, and nano-fertilizers for improved crop growth. While the green synthesis of ZnO-NPs through microbes offers numerous benefits, it is essential to assess their toxicological effects, a critical aspect that requires thorough investigation to ensure their safe use in various applications. Overall, the presented review highlights the mechanism of biogenic synthesis of ZnO-NPs using microbes and their exploration of potential applications while emphasizing the importance of studying their toxicological effects to ensure a viable and environmentally friendly green strategy

Nutrition, atherosclerosis, arterial imaging, cardiovascular risk stratification, and manifestations in COVID-19 framework: a narrative review.

Background: Atherosclerosis is the primary cause of the cardiovascular disease (CVD). Several risk factors lead to atherosclerosis, and altered nutrition is one among those. Nutrition has been ignored quite often in the process of CVD risk assessment. Altered nutrition along with carotid ultrasound imaging-driven atherosclerotic plaque features can help in understanding and banishing the problems associated with the late diagnosis of CVD. Artificial intelligence (AI) is another promisingly adopted technology for CVD risk assessment and management. Therefore, we hypothesize that the risk of atherosclerotic CVD can be accurately monitored using carotid ultrasound imaging, predicted using AI-based algorithms, and reduced with the help of proper nutrition. Layout: The review presents a pathophysiological link between nutrition and atherosclerosis by gaining a deep insight into the processes involved at each stage of plaque development. After targeting the causes and finding out results by low-cost, user-friendly, ultrasound-based arterial imaging, it is important to (i) stratify the risks and (ii) monitor them by measuring plaque burden and computing risk score as part of the preventive framework. Artificial intelligence (AI)-based strategies are used to provide efficient CVD risk assessments. Finally, the review presents the role of AI for CVD risk assessment during COVID-19. Conclusions: By studying the mechanism of low-density lipoprotein formation, saturated and trans fat, and other dietary components that lead to plaque formation, we demonstrate the use of CVD risk assessment due to nutrition and atherosclerosis disease formation during normal and COVID times. Further, nutrition if included, as a part of the associated risk factors can benefit from atherosclerotic disease progression and its management using AI-based CVD risk assessment