咸阳常用装饰石材及釉面砖天然放射性水平

报道了咸阳市常用装饰石材及彩釉砖样品中天然放射性核素含量的调查分析结果,并据国家建筑材料放射性核素含量最新标准进行分类分析。分析结果表明,所调查的装饰石材样品中天然放射性核素^226Ra、^232Th、^40K的比活度范围分别为9.92～330.21 Bq/kg,12.86～300.20 Bq/kg,41.57～1830.64 Bq/kg。依据国家最新标准,24个装饰石材样品中1个样品属于B类、2个样品属于C类,这些样品不能用于住宅的内装饰;其余21个属于A类,使用范围不受限制。4个彩釉砖样品均属A类。     

基于小程序的海洋牧场台风灾害预警预报服务

台风多要素信息及灾情状况是海洋牧场各方急切想掌握的,而应用于海洋牧场灾害预警专报服务还未见报道,基于此开发了海洋牧场台风灾害预警预报服务小程序.结合wx.request请求获取第三方要素数据与自建云数据库访问灾情数据.搭建海洋牧场台风灾害预警预报服务的层次结构体系构架,推出海洋牧场气象要素预警预报、海洋牧场水文要素预警...     

应用物种DNA条形码识别太湖流域部分底栖无脊椎动物种类

将物种DNA条形码实际应用于太湖流域底栖无脊椎动物分类,并与形态学分类结果比对,结果表明,DNA条形码技术可应用于本流域底栖无脊椎动物分类,但现阶段无法替代形态学鉴定,主要原因是太湖流域底栖无脊椎动物的绝大多数物种COⅠ基因特征序列是未知的或是BLAST所拥有的分类程度不够,提出在今后的研究中应探索建立太湖流域底栖无脊椎动物COⅠ基因数据库。     

脱硫真空皮带机脱水效果影响因素分析

通过对真空皮带机脱水效果的影响因素和真空皮带机结构特点进行分析,总结了运行过程中影响真空皮带机脱水效果的常见故障,提出了优化改造方案,解决了真空皮带机脱水效果差、设备故障率高等缺陷。     

一种系统化的生产安全事故分级新方法研究

为了强化《生产安全事故报告和调查处理条例》(493号令)对事故管理及其影响评价的重要作用。笔者在论证了关于提出事故分级新方法的必要性后,在前人已有研究成果的基础上,结合生产安全事故特点,初步提出了一种基于"人员伤亡、财产损失、社会影响和环境污染"四个指标的系统化事故分级新方法。该事故分级理念及方法能更好地切合生产安全事故定义,对新时期下事故分级理念中事故影响多样性内涵的引入是一种积极和有效的探索,具有一定意义。     

水电背景的鱼类救护工程与投资回报:中国鱼类资源前景堪忧

随着我国水电事业的飞速发展,鱼类资源正面临着极大的威胁,鱼类救护工程越来越受到重视。从增殖放流、过鱼设施、栖息地保护等三个鱼类救护工程的角度,浅谈了我国鱼类救护工程的现状:增殖放流工程备受关注,放流规模与投入资金大幅度上升,但实际效果不够突出;过鱼设施建设近年来呈快速发展态势,初期监测过鱼效果较好,但是否达到设计要求尚无定论,缺乏过鱼效果评价的科学体系且相关管理法规不到位;鱼类栖息地保护工程开始被重视,在研究尝试之后已经取得一定的效果。建议相关部门审慎对待对增殖放流的投入、加强放流鱼种鱼苗及实际效果的研究评估;增加过鱼设施投入资金并加强过鱼设施的建设和研究,完善实际过鱼效果评估方法,加大鱼道运营管理执法力度;加大对栖息地保护方式的研究投入,使被破坏的鱼类栖息地得到恢复。     

Fish recruitment prediction, using robust supervised classification methods

Improving our ability to predict recruitment is a key element in fisheries management. However, the interactions between population dynamics and different environmental factors are complex and often non-linear, making it difficult to produce robust predictions. ‘Machine-learning’ techniques (in particular, supervised classification methods) have been proposed as useful tools, to overcome such difficulties. In this study, a methodology is proposed to build a robust classifier for fish recruitment prediction with sparse and noisy data. The methodology consists of 4 steps: (1) a semi-automated recruitment discretization method; (2) supervised discretization of predictors; (3) multivariate and non-redundant predictors selection; (4) learning a probabilistic classifier. In terms of fisheries management, the classifier estimated performance has important consequences and, to be useful, the manager needs to know the risk that is being taken when using this number. Probabilistic classifiers such as ‘naive Bayes’, have the advantage that, in addition to the predictions, estimate also the probability of each possible outcome. Anchovy (Engraulis encrasicolus) and hake (Merluccius merluccius) recruitments are used as application examples. ‘Two-intervals’ recruitment discretization accomplishes 70% accuracies and Brier scores of around 0.10, for both anchovy and hake recruitment. In comparison, ‘three-intervals’ recruitment discretization accomplishes 50% accuracies; and Brier scores of around 0.25 for anchovy and 0.30 for hake recruitment. These statistics are the result of validating not only the classifier, but also the previous steps, as a whole methodology.     

Automated detection of frog calls and choruses by pulse repetition rate

Anurans (frogs and toads) are among the most globally threatened taxonomic groups. Successful conservation of anurans will rely on improved data on the status and changes in local populations, particularly for rare and threatened species. Automated sensors, such as acoustic recorders, have the potential to provide such data by massively increasing the spatial and temporal scale of population sampling efforts. Analyzing such data sets will require robust and efficient tools that can automatically identify the presence of a species in audio recordings. Like bats and birds, many anuran species produce distinct vocalizations that can be captured by autonomous acoustic recorders and represent excellent candidates for automated recognition. However, in contrast to birds and bats, effective automated acoustic recognition tools for anurans are not yet widely available. An effective automated call-recognition method for anurans must be robust to the challenges of real-world field data and should not require extensive labeled data sets. We devised a vocalization identification tool that classifies anuran vocalizations in audio recordings based on their periodic structure: the repeat interval-based bioacoustic identification tool (RIBBIT). We applied RIBBIT to field recordings to study the boreal chorus frog (Pseudacris maculata) of temperate North American grasslands and the critically endangered variable harlequin frog (Atelopus varius) of tropical Central American rainforests. The tool accurately identified boreal chorus frogs, even when they vocalized in heavily overlapping choruses and identified variable harlequin frog vocalizations at a field site where it had been very rarely encountered in visual surveys. Using a few simple parameters, RIBBIT can detect any vocalization with a periodic structure, including those of many anurans, insects, birds, and mammals. We provide open-source implementations of RIBBIT in Python and R to support its use for other taxa and communities.     

基于熵权-集对分析模型的重大危险源安全等级评价研究

针对国内危险化学品事故频发,但危险源分级监管研究不足的现状,尝试将集对分析理论应用于重大危险源安全等级评价中。以评价指标集合与分级标准集合构成一组集对,利用熵权法计算出各项评价指标的客观权重,再结合同异反联系度函数求出各指标单项联系度及加权平均联系度,以此为依据判定重大危险源的安全等级。研究案例的实施情况表明,熵权-集对分析模型充分考虑了危险源安全因素中的不确定性,并且通过熵权值能够识别出影响系统安全的关键指标;与传统方法相比,该模型具有较高的可行性和易操作性,可以为重大危险源的安全监管和事故预防工作提供理论支持。     

浅谈C语言字符串格式化

介绍了C语言格式式化输出类操作函数,对该类函数的实现方式和C语言可变参数的工作原理进行了较为详细的阐述,同时,构造了一个方便通用的格式化输出函数,为数据数据格式化操作提供了一条灵活便捷有效的处理途径.