11 research outputs found

    Semi-automated sewage congestion detection and removal system in a simulated pipe set-up

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    The MMDA and LGUs perform manual labor in order to clean and maintain sewers in the Metro, but comes at a great cost in budget and in health. The main purpose of this study is to develop an automated sewage congestion detection and removal system and implement it using a physically simulated pipe and manhole setup. The means for clog detection would be a CMOS camera placed in a box with a light source, all of which are situated facing the glass panel outside the manhole setup. This set-up takes images and processes them using the concepts of thresholding, quadtree decomposition and morphological operations via MATLAB. The PIC microcontroller (PIC16f877A) is used for control and synchronization purposes between the image processing program and the hardware modules for declogging. The implementation of a Graphical User Interface (GUI) using MATLAB allowed the user to view the automated process correctly and to check the functions of each of the entire system using the Manual and PIC Mode. Finally, the submersible pump is employed for removing the sludge inside the manhole setup. At the end, significant portions of the choke, which is composed of sand, soil, fats, oils, greases and foliage, were removed by the group after subjecting the whole mechanism and control into several tests. To end with, a paper design was also prepared by the group regarding the actual setting in real life scenario of the simulated setup

    Figure 91 from: Breure ASH, Mogollón Avila V (2016) Synopsis of Central Andean Orthalicoid land snails (Gastropoda, Stylommatophora), excluding Bulimulidae. ZooKeys 588: 1-199. https://doi.org/10.3897/zookeys.588.7906

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    Anmerkungen

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    Risk of COVID-19 after natural infection or vaccinationResearch in context

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    Summary: Background: While vaccines have established utility against COVID-19, phase 3 efficacy studies have generally not comprehensively evaluated protection provided by previous infection or hybrid immunity (previous infection plus vaccination). Individual patient data from US government-supported harmonized vaccine trials provide an unprecedented sample population to address this issue. We characterized the protective efficacy of previous SARS-CoV-2 infection and hybrid immunity against COVID-19 early in the pandemic over three-to six-month follow-up and compared with vaccine-associated protection. Methods: In this post-hoc cross-protocol analysis of the Moderna, AstraZeneca, Janssen, and Novavax COVID-19 vaccine clinical trials, we allocated participants into four groups based on previous-infection status at enrolment and treatment: no previous infection/placebo; previous infection/placebo; no previous infection/vaccine; and previous infection/vaccine. The main outcome was RT-PCR-confirmed COVID-19 >7–15 days (per original protocols) after final study injection. We calculated crude and adjusted efficacy measures. Findings: Previous infection/placebo participants had a 92% decreased risk of future COVID-19 compared to no previous infection/placebo participants (overall hazard ratio [HR] ratio: 0.08; 95% CI: 0.05–0.13). Among single-dose Janssen participants, hybrid immunity conferred greater protection than vaccine alone (HR: 0.03; 95% CI: 0.01–0.10). Too few infections were observed to draw statistical inferences comparing hybrid immunity to vaccine alone for other trials. Vaccination, previous infection, and hybrid immunity all provided near-complete protection against severe disease. Interpretation: Previous infection, any hybrid immunity, and two-dose vaccination all provided substantial protection against symptomatic and severe COVID-19 through the early Delta period. Thus, as a surrogate for natural infection, vaccination remains the safest approach to protection. Funding: National Institutes of Health
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