Decision making during the prenatal diagnostic procedure. A questionnaire and interview study of 211 women participating in prenatal diagnosis

Counselling in connection with prenatal diagnosis (PND) is a common task for the obstetrician and the midwife. However, the decision making processes of pregnant women are not completely known, for instance, the questions of women's autonomy, the decision on how to act in the case of an abnormal test, and the partner's participation in the decision. A questionnaire and interview study was carried out among 211 women undergoing PND by amniocentesis or chorionic villus biopsy. Most women in the sample indicated that PND was completely voluntary. However, at the same time almost every woman reported that it was difficult to decline from PND when offered. Even before the visit to register at the antenatal clinic, most of the women (83 per cent) had made up their minds to have PND. At the time of the test, many of the participants (62 per cent) had decided in favour of a legal abortion if the test indicated an abnormality in the fetus. At the same time, however, the data indicate a need for reflection and ambivalence, which the medical staff have to accept. In the questionnaire most of the women stated that they and their partners had similar attitudes towards PND, but when interviewed 38 per cent of the women admitted some differences between their own attitudes and their partners'. Although some women reported considerable deliberation and ambivalence, most of them said that they would undergo PND in another pregnancy.     

制浆造纸工业废水达标可行性研究

2008年6月颁布的《制浆造纸工业水污染物排放标准》(GB 3544-2008)与原标准(GB 3544-2001)相比,增加了控制排放的污染物项目,污染物排放控制要求也大幅提高,传统的废水二级生化处理工艺已不能满足新标准要求。文章通过梳理和分析调研及现场监测的资料和数据,提出目前制浆造纸企业通过有效的技术改造和升级,增加废水三级深度处理流程,在加强管理的情况下可以实现废水稳定达标排放。但不可避免会增加企业建设和运营成本,大中型制浆造纸企业尚可接受,对小型企业的冲击则相对较大。同时提出目前制浆造纸企业废水处理仍存在一些技术和管理方面的问题,尚需通过制定技术规范、强化环境监管、深入开展相关基础研究等多方面对策,优化制浆造纸行业结构调整,确保行业污染物减排。     

极低频电磁场对健康影响的流行病学调查及人体测试研究进展

流行病学调查结果表明，环境的极低频电磁场暴露与人群某些肿瘤，如白血病、乳腺癌、脑肿瘤等，以及生殖、神经、心血管和内分泌等系统疾患的发病相关，这些结果在一定程度上得到实验室人体测试的支持。然而，极低频电磁场对健康影响的确切效应，迄今尚未能作出结论，亟等进一步开展多层次、多水平的研究。     

多频管中电流法防腐层检测评级参数影响研究

多频管中电流法通过计算管道防腐层绝缘电阻来判断管道外防腐层的状态,近年来得到较为广泛的应用.但对于丘陵山地的埋地输油气气管道,其评价结果与实际状态有一定差距.通过研究发现,评价结果与实际状态不符的主要原因是:管道分布电容、管道分布电感在GDWFF处理软件中对防腐层评价结果影响较大,尤其是管道分布电感是关键参数.为此,修正了多频管中电流法评价软件给出的管道分布电感推荐值,并采用现场开挖的方式进行验证,说明评价结果更符合山地实际.     

环保设施现状评价模式的研究

对环保设施运行现状定量评价模式进行探讨。模式从环保设施的整体、细节、管理和环境影响4个方面分析,采用调查、公式计算、插值、专家评分等方式,对环保设施运行的现状进行评分,建立了一个以计权方式定量评分来评价废气、废水处理设施现状的评价模式。     

强化水旋澄清池技术处理黄河高浊度水的试验研究

由于兰州段夏季黄河水的浊度较高,直接影响了自来水厂的正常运行,而目前水厂所用工艺无法满足高浊度水的处理要求,因此,采用自主研究开发的具有特殊结构的水旋澄清池对黄河高浊度水进行了强化处理的试验研究。研究结果表明：在多点投药混合方式下,强化水旋澄清池可提高浊度的处理效果;若在投加无机絮凝剂PAC后,再投加有机絮凝剂PAM进行复配作用,不仅可降低无机絮凝剂的用量,节约制水成本,而且提高了自来水厂的出水水质;结果也表明该水旋澄清池技术能够推广应用于黄河高浊度水的强化处理工艺中。     

Stock market responses to chemical accidents in Japan: An event study

Despite recent major chemical process accidents in Japan, the top management teams of firms still avoid taking costly risk reduction measures because of their low perceived impact on firm performance. The disclosure of information on accident risks might motivate managers to enhance workplace safety because of the subsequent evaluation of firms by investors in stock markets. If the disclosed risk information is newly available for investors, firms with a high risk of accidents would receive a poor evaluation by stock markets and thus managers would take risk reduction measures to prevent stock prices from declining. In this study, we conduct an event study analysis to examine whether accident risk information is already reflected in stock prices, using data on the Japanese chemical industry. The results of our event study show that the estimated cumulative average abnormal returns of firms' stocks are significantly negative after severe accidents actually occurred. This finding implies that risk information is not already reflected in the stock prices of Japanese chemical firms and that the disclosure of accident risk information has the potential to motivate the top management teams of firms to reduce their firms’ accident risk.     

Short-term wind speed forecasting based on random forest model combining ensemble empirical mode decomposition and improved harmony search algorithm

ABSTRACT

Wind speed forecasting plays an important role in power grid dispatching management. This article proposes a short-term wind speed forecasting method based on random forest model combining ensemble empirical modal decomposition and improved harmony search algorithm. First, the initial wind speed data set is decomposed into several ensemble empirical mode functions by EEMD, then feature extraction of each sub-modal IMF is performed using fast Fourier transform to solve the cycle of each sub-modal IMF. Next, combining the high-performance parameter optimization ability of the improved harmony search algorithm, two optimal parameters of random forest model, number of decision trees, and number of split features are determined. Finally, the random forest model is used to forecast the processing results of each submodal IMF. The proposed model is applied to the simulation analysis of historical wind data of Chaoyang District, Liaoning Province from April 27, 2015 to May 22, 2015. To illustrate the suitability and superiority of the EEMD-RF-IHS model, three types of models are used for comparison: single models including ANN, SVM, RF; EMD combination models including EMD-ANN, EMD-SVM, EMD-RF; EEMD combination models including EEMD-ANN, EEMD-SVM, EEMD-RF. The analysis results of evaluation indicators show that the proposed model can effectively forecast short-term wind data with high stability and precision, providing a reference for forecasting application in other industry fields.     

The hybrid model of empirical wavelet transform and relevance vector regression for monthly wind speed prediction

ABSTRACT

In order to improve the prediction ability for the monthly wind speed of RVR, the hybrid model of empirical wavelet transform and relevance vector regression (EWT-RVR) is proposed for monthly wind speed prediction in this study. Compared with empirical mode decomposition (EMD), empirical wavelet transform (EWT) can obtain a more consistent decomposition and have a mathematical theory. In order to testify the superiority of EWT-RVR, several traditional RVR models are used to compare with the proposed EWT-RVR method under the situation of the same embedding dimensions. The experimental results show that the proposed EWT-RVR method has a better prediction ability for monthly wind speed than RVR. It can be concluded that the proposed EWT-RVR method for monthly wind speed is effective.     

Evaluation of leachate composition by multivariate data analysis (MVDA)

Landfills generate emissions in the form of gas and leachate. The emissions are often measured within monitoring programmes. It is likely that the requirements of such monitoring programmes can be extended in the future, particularly in light of the increased interest in specific organic substances. Multivariate data analyses (MVDA) have been used to evaluate the possibility of predicting the content of specific organic substances from more common analyses. The results indicate that this is possible for a specific leachate. MVDA can also be used to reduce the number of analyses performed within existing monitoring programmes while retaining information about all the variables formerly included in the programmes.