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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.  相似文献   
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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.  相似文献   
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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 NOx 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, NOx and NO2 concentrations collected at Mong Kok Roadside Gaseous Monitory Station in Hong Kong during the year 2000. By comparing the predicted RSP, NOx 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.  相似文献   
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The increased demand of alternative energy sources has created interest in biodiesel and biodiesel blends; biodiesel is promoted as a diesel substitute that is safer, produces less harmful combustion emissions, and biodegrades more easily. Like diesel spills, biodiesel can have deleterious effects on the aquatic environments. The effect of neat biodiesel, biodiesel blends, and diesel on Oncorhynchus mykiss and Daphnia magna was evaluated using acute toxicity testing. Static nonrenewal bioassays of freshwater organisms containing B100, B50, B20, B5, and conventional diesel fuel were used to compare the acute effects of biodiesel to diesel. Mortality was the significant end point measured in this study; percent mortality and lethal concentration (LC50) at different exposure times were determined from the acute toxicity tests performed. Trials were considered valid if the controls exhibited > 90% survival. Based on percentage of mortality and LC50 values, a toxicity ranking of fuels was developed.  相似文献   
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Setting universal goals for sustainability is problematic and may hinder the adoption of sustainable pathways as different sectors of society often have differing opinions on not just what sustainability means for them, but also what is of priority to them. This paper tests a set of psychographic, behavioural, lifestyle and social identities to segment the public on sustainability. We evaluate general knowledge, apply social-choice tools to identify public priorities, and then apply segmentation to reveal broad strata of community profiles around these choices. We discuss our findings in the context of moving beyond knowledge on sustainability and general public choices, to more nuanced messaging and engagement that respects differences in sustainability orientations. We suggest that by focusing on what matters most for different segments of society, there is potential to design effective processes to engage with people and acquire better ownership of sustainability.  相似文献   
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Highly erratic rainfall patterns in northern Benin complicate the ability of rural farmers to engage in subsistence agriculture. This research explores gender-specific responses to climate variability in the context of agrarian Benin through a household survey (n = 260) and an experimental gaming exercise among a subset of the survey respondents. Although men and women from the sample population are equally aware of climate variability and share similar coping strategies, their specific land-use strategies, preferences, and motivations are distinct. Over the long term, these differences would likely lead to dissimilar coping strategies and vulnerability to the effects of climate change. Examination of gender-specific land-use responses to climate change and anticipatory learning can enhance efforts to improve adaptability and resilience among rural subsistence farmers.  相似文献   
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Coastal fisheries are a critical component of Pacific island food systems; they power village economies and provide nutritious aquatic foods. Many coastal women and men actively fishing in this region rely on multi-species fisheries, which given their extraordinary diversity are notoriously difficult to both characterize, and to manage. Understanding patterns of fishing, diversity of target species and drivers of these patterns can help define requirements for sustainable management and enhanced livelihoods. Here we use a 12-month data set of 8535 fishing trips undertaken by fishers across Malaita province, Solomon Islands, to create fisheries signatures for 13 communities based on the combination of two metrics; catch per unit effort (CPUE) and catch trophic levels. These signatures are in turn used as a framework for guiding suitable management recommendations in the context of community-based resource management. While a key proximate driver of these patterns was fishing gear (e.g. angling, nets or spearguns), market surveys and qualitative environmental information suggest that community fishing characteristics are coupled to local environmental features more than the market value of specific species they target. Our results demonstrate that even within a single island not all small-scale fisheries are equal, and effective management solutions ultimately depend on catering to the specific environmental characteristics around individual communities.Supplementary InformationThe online version contains supplementary material available at 10.1007/s13280-021-01690-z.  相似文献   
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