Seasonal variation and ecological risk assessment of Pharmaceuticals and Personal Care Products (PPCPs) in a typical semi-enclosed bay — The Bohai Bay in northern China

The Bohai Bay as a typical semi-enclosed bay in northern China with poor water exchange capacity and significant coastal urbanization, is greatly influenced by land-based inputs and human activities. As a class of pseudo-persistent organic pollutants, the spatial and temporal distribution of Pharmaceuticals and Personal Care Products (PPCPs) is particularly important to the ecological environment, and it will be imperfect to assess the ecological risk of PPCPs for the lack of systematic investigation of their distribution in different season. 14 typical PPCPs were selected to analyze the spatial and temporal distribution in the Bohai Bay by combining online solid-phase extraction (SPE) and HPLC-MS/MS techniques in this study, and their ecological risks to aquatic organisms were assessed by risk quotients (RQs) and concentration addition (CA) model. It was found that PPCPs widely presented in the Bohai Bay with significant differences of spatial and seasonal distribution. The concentrations of ∑PPCPs were higher in autumn than in summer. The distribution of individual pollutants also showed significant seasonal differences. The high values were mainly distributed in estuaries and near-shore outfalls. Mariculture activities in the northern part of the Bohai Bay made a greater contribution to the input of PPCPs. Caffeine, florfenicol, enrofloxacin and norfloxacin were the main pollutants in the Bohai Bay, with detection frequencies exceeding 80 %. The ecological risk of PPCPs to algae was significantly higher than that to invertebrates and fish. CA model indicated that the potential mixture risk of total PPCPs was not negligible, with 34 % and 88 % of stations having mixture risk in summer and autumn, respectively. The temporary stagnation of productive life caused by Covid-19 weakened the input of PPCPs to the Bohai Bay, reducing the cumulative effects of the pollutants. This study was the first full-coverage investigation of PPCPs in the Bohai Bay for different seasons, providing an important basis for the ecological risk assessment and pollution prevention of PPCPs in the bay. © 2022 Elsevier B.V.

Early Predication of Covid-19 by Machine Learning Algorithms

In COVID-19 is the most significant issue for the human community. The virus is easily converted into a new variant, which behaves differently from the previous one. Besides its changing behavior, its transmission and infection rate are very high which causes high death rate. It is a very challenging situation for the healthcare system to early diagnosis of diseases so that predict the transmission growth of virus the number of new, confirmed, recovered, and dead cases can be reduced. To deal with these issues, some prediction tools are required which can help to test and find the cause of existing cases so that it can help the effective and rapid arrangement to overcome the pandemic. To address this issue, we propose a symptom-base Recommendation System which are tested over the dataset by applying the concept of Machine Learning algorithms. In this work, we test our proposed system by suing various machine learning algorithm like LR, SVM, Navie Bays,KNN,Random Forest etc. The experimental results reveal that the proposed system is capable to diagnose the disease accurately approximate 99%. Copyright © 2022 Wolters Kluwer Medknow Publications. All rights reserved.

A computational investigation of COVID-19 transmission inside hospital wards and associated costs.

The COVID-19 pandemic has placed a particular burden on hospitals: from intra-hospital transmission of the infections to reduced admissions of non-COVID-19 patients. There are also high costs associated with the treatment of hospitalised COVID-19 patients, as well as reductions in revenues due to delayed and cancelled treatments. In this study we investigate computationally the transmission of COVID-19 inside a hospital ward that contains multiple-bed bays (with 4 or 6 beds) and multiple single-bed side rooms (that can accommodate the contacts of COVID-19-positive patients). The aim of this study is to investigate the role of 4-bed bays vs. 6-bed bays on the spread of infections and the hospital costs. We show that 4-bed bays are associated with lower infections only when we reduce the discharge time of some patients from 10 days to 5 days. This also leads to lower costs for the treatment of COVID-19 patients. In contrast, 6-bed bays are associated with reduced hospital waiting lists (especially when there are also multiple side rooms available to accommodate the contacts of COVID-19-positive patients identified inside the 6-bed bays).

Development of Quantitative Real-Time PCR for Detecting Environmental DNA Derived from Marine Macrophytes and Its Application to a Field Survey in Hiroshima Bay, Japan

The sequestration and storage of carbon dioxide by marine macrophytes is called blue carbon;this ecosystem function of coastal marine ecosystems constitutes an important countermeasure to global climate change. The contribution of marine macrophytes to blue carbon requires a detailed examination of the organic carbon stock released by these macrophytes. Here, we introduce a quantitative real-time polymerase chain reaction (qPCR)-based environmental DNA (eDNA) system for the species-specific detection of marine macrophytes. and report its application in a field survey in Hiroshima Bay, Japan. A method of qPCR-based quantification was developed for mangrove, seagrass, Phaeophyceae, Rhodophyta and Chlorophyta species, or species-complex, collected from the Japanese coast to investigate their dynamics after they wither and die in the marine environment. A trial of the designed qPCR system was conducted using sediment samples from Hiroshima Bay. Ulva spp. were abundant in coastal areas of the bay, yet their eDNA in the sediments was scarce. In contrast, Zostera marina and the Sargassum subgenus Bactrophycus spp. were found at various sites in the bay, and high amounts of their eDNA were detected in the sediments. These results suggest that the fate of macrophyte-derived organic carbon after death varies among species.