非柔性连接石化储罐配管温差应力分析与对策

储罐配管在温差作用下产生热位移会导致管壁产生热应力，未采用柔性连接的配管由于热应力集中作用可能发生破漏。针对与石油化工储罐非柔性连接的配管的安全问题，应用ANSYS有限元分析软件模拟计算石化企业典型配管的热应力分布；根据不同类型配管的分析结果，提出了工程技术与管理方面的针对性安全措施。研究结果表明:温差效应对石化储罐配管热应力影响显著，随内外温差的增加，配管应力集中的区域增大，最大热应力值增大；补偿措施能够改善配管的柔性，降低配管应力；约束载荷限制配管热膨胀从而增大配管应力；三通管是多根配管接合的区域，这种复杂管道交汇处会形成明显应力集中。研究结果对于提高石油化工非柔性连接配管安全性有一定的指导意义。     

Mitigating Impact of Devils Lake Flooding on the Sheyenne River Sulfate Concentration

Devils Lake is a terminal lake located in northeast North Dakota. Because of its glacial origin and accumulated salts from evaporation, the lake has a high concentration of sulfate compared to the surrounding water bodies. From 1993 to 2011, Devils Lake water levels rose by ~10 m, which flooded surrounding communities and increased the chance of an overspill to the Sheyenne River. To control the flooding, the State of North Dakota constructed two outlets to pump the lake water to the river. However, the pumped water has raised concerns about of water quality degradation and potential flooding risk of the Sheyenne River. To investigate these perceived impacts, a Soil and Water Assessment Tool (SWAT) model was developed for the Sheyenne River and it was linked to a coupled SWAT and CE‐QUAL‐W2 model that was developed for Devils Lake in a previous study. While the current outlet schedule has attempted to maintain the total river discharge within the confines of a two‐year flood (36 m³/s), our simulation from 2012 to 2018 revealed that the diversion increased the Sheyenne River sulfate concentration from an average of 125 to >750 mg/L. Furthermore, a conceptual optimization model was developed with a goal of better preserving the water quality of the Sheyenne River while effectively mitigating the flooding of Devils Lake. The optimal solution provides a “win–win” outlet management that maintains the efficiency of the outlets while reducing the Sheyenne River sulfate concentration to ≤600 mg/L.     

中国生态环境科技创新体系建设研究

分析国内外生态环境科技创新的发展现状，相比较国外以市场机制为导向、以企业为创新主体、政府通过政策和管辖支撑创新的体系特征，我国已形成四大类环境类科创载体，但尚未形成成熟有效的技术成果产业化机制以及市场与政策协同促进科技创新的发展模式。本文根据生态环境科技创新的强政策驱动性、技术验证放大周期长以及集成性强的特点，重点通过环境技术研发、技术成果转化、技术放大与赋能、产业拓展与推广四个方面阐述了生态环境科技创新体系建设的主要环节：环境技术的研发由以科研机构为主的传统自发性研发、企业迭代性研发和联合应用型研发组成；技术成果的转化经历挖掘发现、技术识别与判断、知识产权评估评价后进入已成立的企业或新设公司，在这一过程中，成果转化专业队伍起着至关重要的作用；技术放大与赋能旨在为有创新技术的企业提供科技创新政策、二次研发中试验证、首台套工程案例、投融资等资源的对接，以协助初创企业成长；产业的拓展与推广则通过为解决环境问题形成集成方案、孵化平台为企业背书和产业政策匹配等方式助力企业长期发展。最后从加强专业化创新平台、技术评估体系、成果转化人才培养体系建设以及疏通投融资渠道等方面对中国未来生态环境科技创新发展提出相关建议。     

分层开采工艺对地表沉降的影响研究

分层开采是厚煤开采的经典工艺,这种工艺对地表沉降的影响比较复杂。通过测试原岩物理力学参数,利用有限元软件flac3D对分层和一次采全高时地表沉降进行了数值模拟。结果表明,如果采高较小,砌体梁距煤层较近,且采完上分层后长时间停采,给顶板再生留足时间,分层开采较一次采全高对地表沉降影响要小。     

基于支持向量回归机的南黄海浒苔分布面积预测模型

绿潮作为一种新型的海洋灾害,已经引起了各个国家的重视.依据2012年南黄海海域浒苔遥感监测分布面积数据,选取了温度、天气状况、风向、风力、浪高5种影响浒苔扩散的气候因子,建立了基于SVR的浒苔分布面积预测模型,并与经典的最近邻点插值模型、线性插值模型、3次样条函数插值模型和分段3次Hermite插值模型进行了回归效果的对比.分析结果表明,基于SVR的浒苔分布面积预测模型能够为浒苔遥感数据的插补提供一种方法,且回归效果优于传统的回归方法,为浒苔的防治提供辅助决策信息.     

利用3S技术动态监测天山草地农业产量及其成因分析

在新疆阜康县大量“天地”资料观测基础上，利用3S(RS、GIS和GPS)技术和生态系统分析方法，对新疆天山草地农业资源进行了系统的动态监测和大面积估产研究。结果表明，该县草地和森林面积1998年比1988年分别下降了17．5％和51．o％，而农业用地面积和沙漠危害面积却分别增加了57．8％和21．2％，实现了利用3s技术系统准确监测新疆阜康县草地农业资源动态变化，其大面积草地遥感估产精度达到75．8％以上。最后，建立了新型PPR估产模型，其估产精度达到81．76％以上，并给出了理论生态成因解释与定量分析结果等。     

Risk-evaluation of Hi-tech Enterprise in the Process of Approaching Global Market

In the high technology industry, small and medium sized technology enterprises (SMSTEs) play a pivotal role in advancing the whole industry. To achieve sustainable development, they need to extend their scope of business activities beyond a national view and exploit international market actively to meet international competitions that increase quickly in the form of allocating resources within the scope of the world. However, the SMSTEs are also facing risks associated with themselves during the process of exploiting international market owing to their own restrictions, so what they should do is to consider risk evaluations in exploiting the international market.     

Prenatal prediction of childhood-onset spinal muscular atrophy (SMA) in Turkish families

Childhood-onset spinal muscular atrophy (SMA) is one of the most common neurodegenerative genetic disorders. SMN1 is the SMA-determining gene deleted or mutated in the majority of SMA cases. There is no effective cure or treatment for this disease yet. Thus, the availability of prenatal testing is important. Here we report prenatal prediction for 68 fetuses in 63 Turkish SMA families using direct deletion analysis of the SMN1 gene by restriction digestion. The genotype of the index case was known in 40 families (Group A) but unknown in the remaining 23 families (Group B). A total of ten fetuses were predicted to be affected. Eight of these fetuses were derived from Group A and two of these fetuses were from Group B families. Two fetuses from the same family in Group A had the SMNhyb1 gene in addition to homozygous deletion of the NAIP gene. One fetus from Group A was homozygously deleted for only exon 8 of the SMN2 gene, and further analysis showed the presence of both the SMN1 and SMNhyb1 genes but not the SMN2 gene. In addition, one carrier with a homozygous deletion of only exon 8 of the SMN1 gene was detected to have a SMNhyb2 gene, which was also found in the fetus. To our knowledge, these are the first prenatal cases with SMNhyb genes. Follow-up studies demonstrated that the prenatal predictions and the phenotype of the fetuses correlated well in 33 type I pregnancies demonstrating that a careful molecular analysis of the SMN genes is very useful in predicting the phenotype of the fetus in families at risk for SMA. Copyright © 2002 John Wiley & Sons, Ltd.     

Determinants of Farmers’ Adoption of Improved Soil Conservation Technology in a Middle Mountain Watershed of Central Nepal

This study explores different socio-economic and institutional factors influencing the adoption of improved soil conservation technology (ISCT) on Bari land (Rainfed outward sloping terraces) in the Middle Mountain region of Central Nepal. Structured questionnaire survey and focus group discussion methods were applied to collect the necessary information from farm households. The logistic regression model predicted seven factors influencing the adoption of improved soil conservation technology in the study area including years of schooling of the household head, caste of the respondent, land holding size of the Bari land, cash crop vegetable farming, family member occupation in off farm sector, membership of the Conservation and Development Groups, and use of credit. The study showed that technology dissemination through multi-sectoral type community based local groups is a good option to enhance the adoption of improved soil conservation technology in the Middle Mountain farming systems in Nepal. Planners and policy makers should formulate appropriate policies and programs considering the farmers' interest, capacity, and limitation in promoting improved soil conservation technology for greater acceptance and adoption by the farmers.     

人工神经网络在预测深基坑周边地表沉降变形中的应用研究

深基坑开挖引起的周边地表变形预测是一个复杂非线性问题,引起地表沉降的影响因素很多,各因素之间呈高度的非线性关系。传统的基坑用边地表沉降变形预测方法存在着一定的局限性,其预测精度有待提高,而人工神经网络是一种多元非线性动力学系统,可以灵活方便地对多成因的复杂未知系统进行高度建模,实现全面考虑各种主要影响因素的深基坑周边地表沉降变形预测。本文介绍了误差反向传播(BP)网络模型的结构、学习过程及其算法的改进,径向基函数(RBF)网络模型的结构及其学习过程;分析了影响深基坑开挖周边土体沉降变形的主要影响因素;以25个基坑工程的地表沉降实测资料为训练样本,建立了11个输入影响因素的BP神经网络模型和RBF神经网络模型,通过对样本的学习训练过程及对5个检验样本的预测精度,说明了人工神经网络用于预测基坑周边地表沉降的可行性和准确性。