COVID-19 and beliefs about tobacco use: an online cross-sectional study in Iran

Environmental Science and Pollution Research - There is mixed evidence surrounding the relationship between tobacco use and COVID-19 infection/progression. The current study investigates beliefs...     

Changes in fetal heart rate pattern after intrauterine paracentesis in one twin with meconium peritonitis

We report a case of in utero paracentesis of ascites in a fetus with meconium peritonitis due to volvulus at 34 weeks which resulted in the correction of an abnormal fetal heart rate pattern and enabled vaginal delivery by preventing abdominal dystocia. The intrauterine intervention also helped to establish the diagnosis and potentially reduced the respiratory compromise after birth. Copyright © 2001 John Wiley & Sons, Ltd.     

Analysis of pollutant levels in central Hong Kong applying neural network method with particle swarm optimization

Air pollution has emerged as an imminent issue in modernsociety. Prediction of pollutant levels is an importantresearch topic in atmospheric environment today. For fulfillingsuch prediction, the use of neural network (NN), and inparticular the multi-layer perceptrons, has presented to be acost-effective technique superior to traditional statisticalmethods. But their training, usually with back-propagation (BP)algorithm or other gradient algorithms, is often with certaindrawbacks, such as: 1) very slow convergence, and 2) easilygetting stuck in a local minimum. In this paper, a newlydeveloped method, particle swarm optimization (PSO) model, isadopted to train perceptrons, to predict pollutant levels, andas a result, a PSO-based neural network approach is presented. The approach is demonstrated to be feasible and effective bypredicting some real air-quality problems.     

Tree species in relation to soil moisture regime in northwestern Ontario,Canada

Selected data on site, vegetation cover, and soil, including soil moisture regime (SMR), were collected from 2 167 field plots in northwestern Ontario, Canada. SMR provides an estimate of an averaged, annualized soil moisture supply throughout a complete vegetation cycle. SMR is based upon a relative scale that subjectively ranks sites from , 0, and 1 through 9 along a soil moisture continuum which relates to a dry to wet gradient. SMR may be generally correlated to tree growth, stand composition, degree of competition, nutrient availability and overall site quality.This paper reports on relationships between SMR and major tree species. Results highlight relationships between SMR class and the broad ecological ranges of several tree species. In northwestern Ontario, the determination of SMR can help resource managers to better understand the ecology of boreal sites.     

Using improved neural network model to analyze RSP,NOx and NO2 levels in urban air in Mong Kok,Hong Kong

As the health impact of air pollutants existing in ambient addresses much attention in recent years, forecasting of airpollutant parameters becomes an important and popular topic inenvironmental science. Airborne pollution is a serious, and willbe a major problem in Hong Kong within the next few years. InHong Kong, Respirable Suspended Particulate (RSP) and NitrogenOxides NO_x and NO₂ are major air pollutants due to thedominant diesel fuel usage by public transportation and heavyvehicles. Hence, the investigation and prediction of the influence and the tendency of these pollutants are ofsignificance to public and the city image. The multi-layerperceptron (MLP) neural network is regarded as a reliable andcost-effective method to achieve such tasks. The works presentedhere involve developing an improved neural network model, whichcombines the principal component analysis (PCA) technique and theradial basis function (RBF) network, and forecasting thepollutant levels and tendencies based in the recorded data. Inthe study, the PCA is firstly used to reduce and orthogonalizethe original input variables (data), these treated variables arethen used as new input vectors in RBF neural network modelestablished for forecasting the pollutant tendencies. Comparingwith the general neural network models, the proposed modelpossesses simpler network architecture, faster training speed,and more satisfactory predicting performance. This improvedmodel is evaluated by using hourly time series of RSP, NO_x and NO₂ concentrations collected at Mong Kok Roadside Gaseous Monitory Station in Hong Kong during the year 2000. By comparing the predicted RSP, NO_x and NO₂ concentrationswith the actual data of these pollutants recorded at the monitorystation, the effectiveness of the proposed model has been proven.Therefore, in authors' opinion, the model presented in the paper is a potential tool in forecasting air quality parameters and hasadvantages over the traditional neural network methods.     

Application of multimedia exposure assessment to drinking water

A potentially important exposure route for humans is the ingestion of chemicals via drinking water. If comprehensive exposure assessments are to be completed for either existing or proposed new chemicals and cost effective control strategies developed, then a quantitative understanding of multimedia transport and fate of specific chemical pollutants must be achieved. Mathematical models provide a powerful framework into which quantitative relationships may be placed to provide guidance in reaching water quality goals. Existing, state-of-the-art media-specific toxic organic transport and fate models for atmospheric (DiDOT), land surface (NPS) and surface water processes (EXAMS) and potable water treatment (WTP) have been linked to demonstrate the technical feasibility of such an approach. Limited application and sensitivity testing of this linked modeling system has shown that the impact of various source loadings and control strategies on drinking water quality can be estimated.     

Declines in organochlorines in eggs of red-breasted mergansers from Lake Michigan, 1977–1978 versus 1990

From 1977–1978 to 1990, concentrations of polychlorinated biphenyls (PCBs) and most organochlorine pesticides declined in eggs of red-breasted mergansers (Mergus serrator) nesting on islands in northwestern Lake Michigan. Total PCBs decreased 60% (from 21 ppm in 1977–1978 to 8.5 ppm in 1990) and p,p-DDE decreased 66% (from 6.5 to 2.2 ppm). Dieldrin decreased only 16% (from 0.82 to 0.69 ppm). In 1990, 79.1% of incubated eggs hatched, which was not significantly different from the 83.5% that hatched in 1977–1978.The U.S. Government right to retain a non-exclusive, royalty free licence in and to any copyright is acknowledged.