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There is a debate in the literature about the relationship between green innovation, environmental management, environmental performance, and the value of a firm. Herein, the effects of green innovation and environmental management on environmental performance are analysed using a stochastic frontier model for energy-intensive listed companies from 2011 to 2017; the effects thereof on the value of a firm are assessed empirically. The results show that green innovation and environmental management have a positive effect on corporate environmental performance, and green innovation plays a complete mediating role between environmental management and environmental performance. The significant positive effect of green innovation on value of a firm confirms Porter's hypothesis, but the positive effect of environmental management on value of a firm is not verified. Finally, recommendations that are aimed at improving corporate environmental performance are given.Adsorptive separation of heavy metals from wastewater is a viable approach to reuse it and avoid environmental pollution. The productive employment of adsorptive separation at a commercial scale, however, relies on the optimized conditions of an adsorber bed holding maximum and selective isolation of the heavy metals. The experimental route includes a significant trial and error approach, is time-consuming, involves operating cost, and remains economically unattractive. Contrarily, simulation of a mathematical model mimicking the adsorption system along with experimental validation can significantly minimize optimization efforts and suggests the best conditions of separation. In this work, a convective-dispersive model and adsorption model for fixed bed adsorption of copper (Cu), chromium (Cr), and cadmium (Cd) metals over wheat bran biosorbent are simulated using the gPROMS tool for benchmarking. The influence of feed flow rate, bed height, and metal concentration is studied, and breakthrough profiles of all heavy metals are predicted and matched with the literature. The error values (R2 and RMSE) and Chi-squared values determined from gPROMS simulations matched well with the previously available MATLAB-simulated data. After a successful benchmarking, we modeled pilot-scale adsorption of Cr on coconut coir (or Biosorbent) in a gPROMS simulation environment. A detailed method and algorithm of gPROMS simulation for Cr isolation is provided. The influence of feed flow rate, bed height, and initial metal concentration is studied on the breakthrough curves of the Cr. The optimum operating condition for the pilot-scale isolation of Cr from the water is suggested. The parameters, such as the axial dispersion coefficient and distribution coefficient, are determined.Environmental noise has been growing in recent years, causing numerous health problems. Highly sensitive environments such as hospitals deserve special attention, since noise can aggravate patients' health issues and impair the performance of healthcare professionals. This work consists of a systematic review of scientific articles describing environmental noise measurements taken in hospitals between the years 2015 and 2020. The researchers started with a consultation of three databases, namely, Scopus, Web of Science, and ScienceDirect. The results indicate that for the most part, these studies are published in journals in the fields of medicine, engineering, environmental sciences, acoustics, and nursing and that most of their authors work in the fields of architecture, engineering, medicine, and nursing. These studies, which are concentrated in Europe, the Americas, and Asia, use as reference values sound levels recommended by the World Health Organization. Leq measured in hospital environments showed daytime values ranging from 37 to 88.6 dB (A) and nighttime values of 38.7 to 68.8 dB (A). Leq values for outdoor noise were 74.3 and 56.6 dB (A) for daytime and nighttime, respectively. The measurements were taken mainly inside hospitals, prioritizing more sensitive departments such as intensive care units. There is a potential for growth in work carried out in this area, but research should also include discussions about guidelines for improvement measures aimed at reducing noise in hospitals.The present study was carried out to investigate the ameliorative effects of melatonin against nicotine-induced heart and lung toxicity. For this purpose, 75 mature male Sprague Dawley (SD) rats weighing 150-170 g were randomly divided into five groups (15 rats each) control group (rats were I/P injected with 1% ethanol in saline), nicotine group (rats were I/P injected with 0.6 mg/kg body weight), and combined nicotine and melatonin groups (rats received nicotine as in the previous group and melatonin at a dose of 1, 5, or 10 mg/kg body weight, respectively); all treatments were continued for 21 days. Fasting blood samples were collected from each rat at the 11th day and one day after the end of the last injection (22nd day) for complete blood count (CBC) determination, while sera were collected for the determination of lipid profiles. Malondialdehyde (MDA) concentration, superoxide dismutase (SOD) activity, and reduced glutathione (GSH) as well as DNA fragmentation percentage were assessed in cardiac tissuencluded that melatonin has a protective effect on the heart and lungs against the harmful effect of nicotine.The COVID-19 is still a huge challenge that seriously threatens public health globally. Previous studies focused on the influence of air pollutants and probable meteorological parameters on confirmed COVID-19 infections via epidemiological methods, whereas the findings of relations between possible variables and COVID-19 incidences using geographical perspective were scarce. In the present study, data concerning confirmed COVID-19 cases and possible affecting factors were collected for 325 cities across China up to May 27, 2020. The geographically weighted regression (GWR) model was introduced to explore the impact of probable determinants on confirmed COVID-19 incidences. Some results were obtained. AQI, PM2.5, and PM10 demonstrated significantly positive impacts on COVID-19 during the most study period with the majority lag group (P less then 0.05). Selleck Pitstop 2 Nevertheless, the relation of temperature with COVID-19 was significantly negative (P less then 0.05). Especially, CO exhibited a negative effect on COVID-19 in most study period with the majority lag group.

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