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ObjectivesMask adherence continues to be a critical public health measure to prevent transmission of aerosol pathogens, such as SARS-CoV-2. We aimed to develop and deploy a computer vision algorithm to provide real-time feedback of mask wearing among staff in a hospital.DesignSingle-site, observational cohort study.SettingAn urban, academic hospital in Boston, Massachusetts, USA.ParticipantsWe enrolled adult hospital staff entering the hospital at a key ingress point.InterventionsConsenting participants entering the hospital were invited to experience the computer vision mask detection system. Key aspects of the detection algorithm and feedback were described to participants, who then completed a quantitative assessment to understand their perceptions and acceptance of interacting with the system to detect their mask adherence.Outcome measuresPrimary outcomes were willingness to interact with the mask system, and the degree of comfort participants felt in interacting with a public facing computer vision mask algorithm.ResultsOne hundred and eleven participants with mean age 40 (SD15.5) were enrolled in the study. Males (47.7%) and females (52.3%) were equally represented, and the majority identified as white (N=54, 49%). Most participants (N=97, 87.3%) reported acceptance of the system and most participants (N=84, 75.7%) were accepting of deployment of the system to reinforce mask adherence in public places. One third of participants (N=36) felt that a public facing computer vision system would be an intrusion into personal privacy.Public-facing computer vision software to detect and provide feedback around mask adherence may be acceptable in the hospital setting. Similar systems may be considered for deployment in locations where mask adherence is important.

The trade-off between spatial and temporal resolution remains a fundamental challenge in machine vision. A captured image often contains a significant amount of redundant information, and only a small region of interest (ROI) is necessary for object detection and tracking. In this paper, we first systematically characterize the effects of ROI on camera capturing, data transmission, and image processing. We then present the closed-loop ROI algorithm capable of high spatial and temporal resolution as well as wide scanning field of view (FOV) in single and multi-object detection and tracking via real-time wireless video streaming. With the feedback from real-time object tracking, the wireless camera is able to capture and transmit only the ROI which in turn enhances both the spatial and temporal resolution in object tracking. In addition, the proposed approach can still maintain a large FOV by processing regions outside of the ROI at lower spatial and temporal resolutions. When applied to a high spatial resolution wireless stream (5 MegaPixels), the closed-loop ROI algorithm improves the temporal resolution by up to $10\times $ (from 2.4FPS to 22.5FPS). Specifically, camera processing is improved by up to $4.7\times $ , data transmission is improved by up to $160\times $ , and PC processing is improved by up to $2.5\times $ . In a person tracking experiment, the closed-loop ROI algorithm enables a wide-angle camera to outperform both a normal wide-angle camera–which suffers from poor temporal resolution and motion blur–and a pan & tilt camera–which cannot automatically refresh tracking after the tracking is lost.

Xenobiotic compounds are synthetic compounds commonly used in industries like dye industries, pharmaceutical industries, pesticides manufacturing, explosives, and other industrial chemicals. These compounds have been released into our ecosystem due to anthropogenic activities and improper waste disposal and cause consequential damage due to their lethal nature. A massive number of enzymes from plants and microorganisms have been reportedly involved in the biodegradation of toxic organic contaminants. Bioremediation is an economical and sustainable part of biotechnology that is dependent on microbial enzymes. Research in this topic would contribute towards the development of advanced bioprocess technology for the reduction of the toxicity of the pollutants and also to acquire beneficiary novel compounds.

These studies Review the plant species for phytoremediation potential and capability to consumption and accrue Heavy metals concentration. Natural renewable resources are valuable assets for human development. Extreme utilization of the resources and severely contaminated due to the influence of human activity on nature. Resources Contamination with toxic metals is a wide-ranging environmental issue resultant from various sources like Inorganic fertilizer, pesticides, leaching, and dumping of pollutants. The Remediation of sites polluted with toxic metals is predominantly difficult. Conventional techniques for recovery are expensive and environmentally uncongenial. Plant-based technology known as Phytoremediation has been proposed as an economical environment-friendly alternative technology to the conventional remediation approaches.

Aim: The aim of this study was to assess the existing knowledge, attitude, and practices of “oral health care” in the prevention of early childhood caries (ECCs) among parents of children in Belagavi city. Materials and Methods: A cross-sectional study was conducted in the outpatient Department of Pedodontics and Preventive Dentistry, KLE VK Institute of Dental Sciences, Belagavi, Karnataka. Institutional Ethical Clearance was obtained. The study was conducted during the month of April 2014 to October 2014 after taking prior informed consent from the 218 parents. Inclusion criteria were parents getting their children treated for dental caries and who were willing to participate. Parents who could not read and write were excluded from the study. The self-administered, close-ended questionnaire was written in English. It was then translated in local languages, i.e. Kannada and Marathi, and a pilot study was conducted on 10 parents to check for its feasibility and any changes if required were done. Results: The response rate was 100% as all 218 parents completed the questionnaire. Of 218 parents, 116 were mothers and 102 were fathers. The overall mean knowledge score was 69.5%. The overall mean attitude score was 53.5%. The overall attitude toward prevention of ECC was not in accordance to knowledge. The overall mean of “good” practices and “bad” practices score was 33.5% and 18.5%, respectively. Good knowledge and attitude toward oral health do not necessarily produce good practices.

Grid computing provides integrated high-end compute resources across administrative domains. More and more grid infrastructures are being used for mission-critical scientific and engineering applications. Ensuring security and safety of grid environment is a key challenge faced by grid community. First step towards grid security is to be aware of vulnerabilities and weaknesses in the entire grid. In this paper, we address this particular aspect wherein we firstly present a system called Security Assessment System (SAS) that is being used in the Indian Grid Computing Initiative GARUDA. This system is built with capabilities of carrying out periodic assessment of the entire grid resources and providing security assessment of each entity such as hosts, applications. Secondly, we present the architecture and internals of SAS where we have seamlessly integrated our solution in a framework by interfacing it with widely used Globus grid middleware. Finally, we present our results based on live deployments in the Indian Grid environment.