基于关联向量机回归的水质预测模型

提出了一种基于关联向量机回归的水质时间序列预测模型,并以该模型对氢离子浓度指数(p H值)、溶解氧(DO)、高锰酸盐指数(CODMn)和氨氮(NH3-N)4种重要水质指标进行预测.首先采用国家环保部发布的四川攀枝花龙洞水质自动监测数据进行实验,对该模型的有效性进行了验证;然后将关联向量机回归预测模型与支持向量机回归预测模型进行比较.为了比较不同核函数的预测效果,实验中预测模型的核函数分别采用了线性函数和高斯函数.实验结果表明,关联向量机回归模型的预测效果不亚于支持向量机回归模型;且在给出预测值时,还能同时给出预测结果的可信程度.     

SNAKES USED IN ETHNOMEDICINE IN NORTHEAST BRAZIL

This paper documents zootherapeutic practices in Northeast Brazil. It is primarily based on field surveys carried out in fishing villages located in the States of Maranhão and Paraíba, where dwellers provided information on snake species used as medicine, body parts used to prepare the remedies, and the illnesses to which the remedies were prescribed. The species used as medicinal drug and their respective families were: Crotalus durissus (rattlesnake), Bothrops leucurus (‘lance head’, a venomous snake), and Lachesis muta (bushmaster) of the family Crotalidae; and Boa constrictor (boa constrictor), Epicrates cenchria (‘salamanta’), and Eunectes murinus (anaconda) of the family (Boidae). These zootherapeutical resources were used for the cure of 14 illnesses. The most commonly cited species were Crotalus durissus (n=26) e Boa constrictor (n=6), Apparently, the medicinal use of snakes does not pose a threat for their population in the studied sites.     

论小城镇核心竞争力的构建和提升

小城镇作为中国城镇化进程的重要组成部分,对于我国城镇发展的作用举足轻重.研究我国小城镇的核心竞争力问题,有助于加深对小城镇经济发展的认识,帮助政府部门从更高的层次制定小城镇经济发展战略.本文界定了小城镇核心竞争力的概念,探讨了培育和提升小城镇经济核心竞争力的重要意义,并从自然环境、人文环境、基础设施、软件环境、创新能力及产业集群等方面对小城镇核心竞争力的构成进行分析;针对小城镇核心竞争力的构建和提升,提出了优化小城镇发展环境,完善小城镇创新体系,增强小城镇产业集群的发展等建议;得出了发展小城镇经济的关键是要增强其竞争力,而要保持小城镇经济持续的竞争优势,关键在于小城镇经济核心竞争力的培育和提升的结论,为促进我国小城镇经济的持续、快速发展及核心竞争力的构建与提升提供参考和借鉴.     

流动注射分光光度法在线分析水中总铁

采用流动注射邻菲哕啉分光光度法在线分析水中总铁,考察了显色剂、消解液、酸度、反应盘管长度、载流流量、注样体积、采样时间等因素对试验的影响。方法在0.100mg／L-10.0mg／L范围内线性良好,检出限为0.04mg／L,实际水样平行测定的RSD≤3.7％,加标回收率为95.0％-96.0％。     

Development of engine activity cycles for the prime movers of unconventional natural gas well development

With the advent of unconventional natural gas resources, new research focuses on the efficiency and emissions of the prime movers powering these fleets. These prime movers also play important roles in emissions inventories for this sector. Industry seeks to reduce operating costs by decreasing the required fuel demands of these high horsepower engines but conducting in-field or full-scale research on new technologies is cost prohibitive. As such, this research completed extensive in-use data collection efforts for the engines powering over-the-road trucks, drilling engines, and hydraulic stimulation pump engines. These engine activity data were processed in order to make representative test cycles using a Markov Chain, Monte Carlo (MCMC) simulation method. Such cycles can be applied under controlled environments on scaled engines for future research. In addition to MCMC, genetic algorithms were used to improve the overall performance values for the test cycles and smoothing was applied to ensure regression criteria were met during implementation on a test engine and dynamometer. The variations in cycle and in-use statistics are presented along with comparisons to conventional test cycles used for emissions compliance.

Implications: Development of representative, engine dynamometer test cycles, from in-use activity data, is crucial in understanding fuel efficiency and emissions for engine operating modes that are different from cycles mandated by the Code of Federal Regulations. Representative cycles were created for the prime movers of unconventional well development—over-the-road (OTR) trucks and drilling and hydraulic fracturing engines. The representative cycles are implemented on scaled engines to reduce fuel consumption during research and development of new technologies in controlled laboratory environments.     

Adaptive Water Resource Planning in the South Saskatchewan River Basin: Use of Scenarios of Hydroclimatic Variability and Extremes

The South Saskatchewan River Basin is one of Canada's most threatened watersheds, with water supplies in most subbasins over‐allocated. In 2013, stakeholders representing irrigation districts, the environment, and municipalities collaborated with researchers and consultants to explore opportunities to improve the resiliency of the management of the Oldman and South Saskatchewan River subbasins. Streamflow scenarios for 2025‐2054 were constructed by the novel approach of regressing historical river flows against indices of large‐scale ocean‐atmosphere climate oscillations to derive statistical streamflow models, which were then run using projected climate indices from global climate models. The impacts of some of the most extreme scenarios were simulated using the hydrologic mass‐balance model Operational Analysis and Simulation of Integrated Systems (OASIS). Based on stakeholder observations, the project participants proposed and evaluated potential risk management and adaption strategies, e.g., modifying existing infrastructure, building new infrastructure, changing operations to supplement environmental flows, reducing demand, and sharing supply. The OASIS model was applied interactively at live modeling sessions with stakeholders to explore practical adaptation strategies. Our results, which serve as recommendations for policy makers, showed that forecast‐based rationing together with new expanded storage could dramatically reduce water shortages.     

Development of a novel myconanomining approach for the recovery of agriculturally important elements from jarosite waste

In this study, an ecofriendly and economically viable waste management approach have been attempted towards the biosynthesis of agriculturally important nanoparticles from jarosite waste. Aspergillus terreus strain J4 isolated from jarosite(waste from Debari Zinc Smelter,Udaipur, India), showed good leaching efficiency along with nanoparticles(NPs) formation under ambient conditions. Fourier-transform infrared spectroscopy(FT-IR) and transmission electron microscopy(TEM) confirmed the formation of NPs. Energy dispersive X-ray spectroscopy(EDX analysis) showed strong signals for zinc, iron, calcium and magnesium,with these materials being leached out. TEM analysis and high resolution transmission electron microscopy(HRTEM) showed semi-quasi spherical particles having average size of 10‐50 nm. Thus, a novel biomethodology was developed using fungal cell-free extract for bioleaching and subsequently nanoconversion of the waste materials into nanostructured form. These biosynthesized nanoparticles were tested for their efficacy on seed emergence activity of wheat(Triticum aestivum) seeds and showed enhanced growth at concentration of 20 ppm. These nanomaterials are expected to enhance plant growth properties and being targeted as additives in soil fertility and crop productivity enhancement.     

天目湖沙河水库热分层变化及其对水质的影响

为揭示亚热带水库热分层的季节性变化特征、影响因素及水质效应,以最大水深11 m的江苏溧阳天目湖沙河水库为例,基于对水库坝前区(TM1)3~11月逐时的水温监测及对该水库2009~2016年相关水质和气象指标监测,分析了该水库热分层的形成和消失时间、驱动因素及其对水质的影响.结果表明,天目湖沙河水库呈典型的亚热带单循环混合模式:春季随着太阳辐射的增强,水温逐渐升高,当表层水温升至21℃左右时,热分层稳定形成,在整个5~9月期间水体热分层十分稳定;秋季随着太阳辐射的减弱,水温逐渐降低,当表层水温降至19℃左右时,热分层基本消失,在10~4月期间水体呈混合状态.热分层期间,表层和底层的水温差随太阳辐射的增强而增加;日均气温超过30℃的情况下,水体热分层更加稳定;夏季强降雨过程降低了水体表层的温度、减弱了上层5 m水体的温度分层,但对5 m以下深度的热分层状况基本无影响.水温分层对水库水质产生一定的影响:热分层期间,底层水体处于厌氧状态,底层水体氨氮浓度明显增加;热分层消失后,底层水体溶解氧、总磷及悬浮颗粒物含量均增加.研究表明,对于四季分明的亚热带中等深度的水库而言,水体热分层主要受太阳辐射的控制,稳定的热分层有利于蓝藻门相关种属藻类的生长,热分层形成及消散阶段改变了沉积物的营养盐释放及供给水体的强度,对水体水质形成冲击.在水库水质监控及生态保护管理中,应关注热分层过程的不利影响,并探索相关灾害的防控技术.     

垃圾填埋气对植物生长影响初探

以11种上海常见绿化植物的盆栽幼苗为对象,在上海顾村垃圾填埋场就填埋气对这些植物幼苗生长和生理特征的影响进行了初步分析和比较。研究测定的形态指标和生理指标主要包括：生长势、存活率、株高变化、叶绿素含量和脯氨酸含量。结果表明：1）距离填埋气排放口越近的植物生长越差,存活率越低,株高变矮。2）距离填埋气排放口越近的植物叶绿素含量越小,脯氨酸含量越高。3）狗牙根（Cynodon dactylon）、构树（Broussonetia papyrifera）等植物出现了受害后的恢复性生长,暗示了其对垃圾填埋气良好的适应性,而蚊母树（Distylium racemosum）存活率低且生长势差,暗示了其对垃圾填埋气的极度不适应。本研究的结果可以为在高浓度填埋气环境下对垃圾填埋场进行近自然植被恢复提供一定的研究基础。     

城市绿地土壤呼吸时空变异及其影响因素

2012年7月-2012年12月,采用LI—COR-8100测定了柳树、圆柏和杏树3种北京绿化树木的土壤呼吸速率,并分析了生物因子和非生物因子对土壤呼吸的影响。结果表明：3个树种的土壤呼吸速率平均值为：柳树3．53μmol／（m2·s）,圆柏2．68μmol（m2·s）,杏树2．38μmol／（m2·s）;3种树木土壤呼吸速率呈现相似的月动态,与温度呈极显著指数相关,而与土壤水分相关性不显著。8月柳树和圆柏的土壤呼吸显著高于杏树;9月柳树的土壤呼吸显著高于圆柏和杏树;10—11月3种树木之间差异性不显著。8—9月土壤呼吸速率和温度、树木胸径、总碳、总氮、有机碳及硝态氮显著相关,而与碳氮比、叶面积指数呈极显著负相关。逐步回归分析表明,8—9月间3种树木的土壤呼吸主要受到树木胸径和叶面积指数的影响,模型解释率为42．0％（p=0．001）。