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.     

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.     

On the Environmental Efficiency of Water Storage: the Case of a Conjunctive use of Ground and Rainwater

Rainwater harvesting, consisting in collecting runoff from precipitation, has been widely developed to stop groundwater declines and even raise water tables. However, this expected environmental effect is not self-evident. We show in a simple setting that the success of this conjunctive use depends on whether the runoff rate is above a threshold value. Moreover, the bigger the storage capacity, the higher the runoff rate must be to obtain an environmentally efficient system. We also extend the model to include other hydrological parameters and ecological damages, which respectively increase and decrease the environmental efficiency of rainwater harvesting.     

Overview of Proposal Revisions to the superfund Hazard Ranking System

The Comprehensive Environmental Response, Compensation, and Liability Act of 1980 required the federal government to establish criteria for setting priorities among releases of hazardous substances, pollutants, and contaminants. The U.S. Environmental Protection Agency responded by developing the Hazard Ranking System (HRS), which is a scoring system used to establish the National Priorities List (NPL). The Superfund Amendments and Reauthorization Act of 1986 required EPA to amend the HRS so it will more accurately assess relative risks and take into account certain specific elements of risk. On December 23,1988, EPA published in the Federal Register the proposed rule to revise the HRS.1 EPA expects to issue the final rule in 1990 after reviewing public comments. This paper describes the proposed revisions and summarizes major technical findings that support the revisions. As a result of the HRS revisions, there may be some changes in the types of sites that score high enough to be placed on the NPL. A projection of those changes is discussed.     

Indicator framework for sustainable production planning and controlling

Production facilities serve to transform raw materials into products, usually with the goal of achieving a designated output, in terms of quantity and quality, with the minimum of cost and labour. With the aid of production planning and controlling (PPC) systems, raw material inputs, and labour can be planned to achieve a determined output of products. In general, the role of environmental and social aspects is neglected in production planning processes. Because of the growing pressure from politics and customers, sustainable production of products is becoming more important. One possibility for supporting sustainable manufacturing is, to integrate sustainable aspects in the production planning process. This paper presents input and output information for current PPC systems and discusses the need for additional information necessary for sustainable PPC. For this approach, a text review of cooperate social responsibility (CSR) reporting indicators provided by the GRI was performed. Based on the text review, an input-output model has been developed for conventional and another one for sustainable PPC systems. Through the comparison of the two input-output models, challenges and requirements for sustainable PPC systems have been defined as a basis for future work and analyses.     

Environmental impact and human exposure to PCBs in Guiyu, an electronic waste recycling site in China

PCB levels in fish (collected from local rivers), atmosphere and human milk samples have been studied to determine the exposure levels of PCBs for local residents and e-waste workers in Guiyu, a major electronic waste scrapping center in China. The source appointment and correlation analyses showed that homologue composition of PCBs in 7 species of fish were consistent and similar to commercial PCBs Aroclor 1248. PCB levels in air surrounding the open burning site were significantly higher than those in residential area. Inhalation exposure contributed 27% and 93% to the total body loadings (the sum of dietary and inhalation exposure) of the local residents, and e-waste workers engaged in open burning respectively. Total PCB concentrations in human milk ranged from N.D. to 57.6 ng/g lipid, with an average of 9.50 ng/g lipid. The present results indicated that commercial PCBs derived from e-waste recycling are major sources of PCBs accumulating in different environmental media, leading to the accumulation of high chlorinated biphenyls in human beings.     

Assessing and managing intensification in smallholder dairy systems for food and nutrition security in Sub-Saharan Africa

Smallholder farmers play an important part in the dairy value chain in Sub-Saharan Africa. Three technological approaches have been used to improve productivity. These are through, applying agricultural ecological processes (ecological intensification), utilising modern livestock breeding (genetic intensification), and socio-economic intensification. Ecological intensification includes continuous housing of cows applying a cut-and-carry feeding system, introduction of purpose-bred forages and pastures, and the introduction of agro-forestry within the dairy systems. Genetic intensification strategies include: importation of dairy breeds such as Holstein–Friesian (HF) and cross-breeding of the indigenous breeds with HF. Training and capacity-building activities to create sustainable livelihoods have been initiated for farming and technological practices of animal husbandry, but also to enhance appropriate leadership and corporative-building skills that would create and support an enabling environment for sustainability. These improvements and initiatives in the service delivery have been championed by national governments, development partner institutions, or non-governmental organisations through different programmes. Challenges of intensification include matching management to genetic potential of imported and cross-bred improved dairy breeds, ensuring low post-harvest losses, proper utilisation, and reducing environmental impact. Using examples from Kenya, Malawi, Mozambique, Tanzania, and Zambia, this paper reviews the management and assessment approaches used in fostering smallholder dairy development strategies and dairy’s contribution to sustainable livelihoods in the face of intensification.