First trimester chorionic villus sampling versus mid-trimester genetic amniocentesis-preliminary results of a controlled prospective trial

This controlled prospective study assesses the relative risks of first trimester chorionic villus sampling (CVS) versus mid-trimester gentic amniocentesis (GA). CVS subjects and amnio-centesis controls were comparable with regard to several confounding variables which might influence the risk of pregnancy loss including maternal age, smoking, alcohol consumption, gestational age at study entry, and history of vaginal bleeding or poor prior reproductive outcome. The most common indication for prenatal diagnosis was advanced maternal age (n = 511). In this subgroup, spontaneous abortion (<24 weeks) occurred in 2·9 per cent of CVS subjects versus 4−3 per cent of amniocentesis controls. The sum of spontaneous and therapeutic abortions (<24 weeks) was identical (5·3 per cent) in both groups. Therefore, intervention in the CVS group (i.e., therapeutic abortion for cytogenetic abnormalities) did not influence the observed risk of pregnancy loss. Overall perinatal mortality rates were also similar in both groups. No significant differences were identified for a number of pregnancy outcome parameters including 5 min Apgar score, birth weight, body length, head circumference, gestational age at delivery, preterm delivery, fetal growth retardation, congenital malformations, and neonatal complications. Preliminary results of this controlled prospective study suggest that chorionic villus sampling carries a low and acceptable risk.     

Assessing the Effectiveness of Winter Cover Crops for Controlling Agricultural Nutrient Losses

A nutrient loss reduction strategy is necessary to guide the efforts of improving water quality downstream of an agricultural watershed. In this study, the effectiveness of two winter cover crops, namely cereal rye and annual ryegrass, is explored as a loss reduction strategy in a watershed that ultimately drains into a water supply reservoir. Using a coupled optimization-watershed model, optimal placements of the cover crops were identified that would result in the tradeoffs between nitrate-N losses reduction and adoption levels. Analysis of the 10%, 25%, 50%, and 75% adoption levels extracted from the optimal tradeoffs showed that the cover crop placements would provide annual nitrate-N loss reductions of 3.0%–3.7%, 7.8%–8.8%, 15%–17.5%, and 20.9%–24.3%, respectively. In addition, for the same adoption levels (i.e., 10%–75%), sediment (1.8%–17.7%), and total phosphorus losses (0.8%–8.6%) could be achieved. Results also indicate that implementing each cover crop on all croplands of the watershed could cause annual water yield reduction of at least 4.8%, with greater than 28% in the months of October and November. This could potentially be detrimental to the storage volume of the downstream reservoir, especially in drought years, if cover crops are adopted in most of the reservoir's drainage area. Evaluating water yield impacts, particularly in periods of low flows, is thus critical if cover crops are to be considered as best management practices in water supply watersheds.     

基于GA-ELM的冲击地压危险性预测研究

为提高冲击地压预测的效率和准确率,在分析冲击地压影响因素的基础上,提出了一种将遗传算法(GA)与极限学习机(ELM)相结合的冲击地压预测的新方法。为了避免ELM受输入权值矩阵和隐含层偏差随机性的影响,算法采用GA对ELM的输入权值矩阵和隐含层偏差进行优化,建立GA-ELM冲击地压预测模型。利用某矿冲击地压统计数据对该模型进行了实例分析,将ELM、SVM和BP算法预测结果与该模型进行了对比分析。结果表明:GA-ELM模型具有较高的预测精度,可以相对准确、有效地对冲击地压发生的可能性进行预测。     

Simulation-based fault propagation analysis—Application on hydrogen production plant

Recently production of hydrogen from water through the Cu–Cl thermochemical cycle is developed as a new technology. The main advantages of this technology over existing ones are higher efficiency, lower costs, lower environmental impact and reduced greenhouse gas emissions. Considering these advantages, the usage of this technology in new industries such as nuclear and oil is increasingly developed. Due to hazards involved in hydrogen production, design and implementation of hydrogen plants require provisions for safety, reliability and risk assessment. However, very little research is done from safety point of view. This paper introduces fault semantic network (FSN) as a novel method for fault diagnosis and fault propagation analysis by using evolutionary techniques like genetic programming (GP) and neural networks (NN), to uncover process variables’ interactions. The effectiveness, feasibility and robustness of the proposed method are demonstrated on simulated data obtained from the simulation of hydrogen production process in Aspen HYSYS^®. The proposed method has successfully achieved reasonable detection and prediction of non-linear interaction patterns among process variables.     

An Integrated Monte Carlo Methodology for the calibration of water quality models

This paper proposes an Integrated Monte Carlo Methodology (IMCM) to solve the parameter estimation problem in water quality models. The methodology is based on Bayesian approach and Markov Chain Monte Carlo techniques and it operates by means of four modules: Markov Chain Monte Carlo (MCMC), Moving Feasible Ranges (MFR), Statistical Analysis of the Joint Posterior Distribution (SAD) and Uncertainty Propagation Analysis (UPA). The main innovation of the new proposal lies in the combination of MCMC and MFR modules which provides the joint posterior distribution of the calibrated parameters following the classical Bayesian approach. While MCMC module, based on Shuffled Complex Evolution Metropolis (SCEM-UA) algorithm, is specially designed to sample complex joint posterior shapes within certain parameter ranges, the MFR readjusts these ranges until the coverage of the feasible parameter space is guaranteed. Once the joint posterior distribution is properly defined, the SAD provides the parameter statistics and the UPA performs an analysis of the uncertainty propagation through the model. The possibilities of the new proposal have been tested on the basis of a simple model featuring different activated sludge batch experiments. IMCM has been implemented in Matlab and it is prepared to be easily connected to any software package.     

Location set covering for waste resource recycling centers in Taiwan

The efficiency of Taiwan's waste management and resource recycling systems has been well recognized in recent years, but the present model used to locate recycling centers and to assign collection depots to those centers continues to show low efficiency. To address this issue, the study herein suggests implementing a new location-planning and assignment model to reduce the number of existing recycling centers. Such a reduction would reduce the use of land resources. Moreover, the total transportation distance would decrease through the efficient assignment of collection depots to recycling centers. On the basis of results from previous studies, this study proposes a 2-stage location set covering problem-P-median integrated model that obtains exact solutions using heuristic algorithms on the basis of set operations. The results of numerical analyses show that the model introduced in this study is effective in solving the problems stated above as well as in improving the layout of Taiwan's existing recycling centers.     

基于GA优化算法的平遥县大气环境质量评价研究

本文以平遥县城及周边区域环境空气质量监测结果为依据,采用具有全局优化的遗传算法（GA）对平遥县及周边区域大气环境质量污染现状进行评价。用大气污染危害指数的普适公式和参数优化后的污染危害指数公式确定污染危害指数的取值范围与评价级别之间的对应关系,由此得出较符合平遥县及周边区域实际的评价结果,同时针对具体情况对此结果进行简单的分析。     

Kinetic parameter estimation for decomposition of organic peroxides by means of DSC measurements

The thermal stability of organic peroxides (cumene hydroperoxide 80 wt% and dicumyl peroxide) was studied by means of calorimetric measurement (DSC, TA Q1000) in an isotherm mode and a dynamic mode. Analysis of power profiles released in the isothermal mode was combined with the analysis of the decomposed compounds by a gas chromatograph/mass spectrometer (GC/MS) to determine the reaction mechanisms corresponding to each of the two reactions. In this work, a methodology for estimating kinetic parameters was based on the comparison of the power profile (dynamic mode) given by the model to that obtained experimentally by changing the parameters values. Parameter estimation is achieved using the mixed estimation method where a genetic algorithm is combined with a locally convergent method.     

遗传资源获取与惠益分享:在兴都库什-喜马拉雅地区的机遇与挑战

在分析兴都库什-喜马拉雅地区生物资源和生物贸易特点基础上,本文就《国际生物多样性公约》框架下的《名古屋议定书》在本地区实施的主要机遇和挑战进行了分析。研究认为,本地区各国在具体执行议定书时面临的困难依然严峻,应该不断在议定书的法律框架下规范遗传资源以及相关传统知识的贸易、使用与共享机制。同时,不断完善法律体系建设,提高全民资源保护意识、建立良好信用制度,提高遗传资源获取和鉴定的科学技术水平。