基于人工神经网络理论的船舶动力装置安全综合评价模型

为提高船舶动力装置安全综合评价水平，依据人工神经网络的基本原理，分析了BP神经网络模型的基本原理和优化策略，将其应用于船舶动力装置的安全评价之中。提出了基于神经网络理论的船舶动力装置综合安全评价模型及实现方法，并以实例论证了此方法的可行性。     

NABat: A top-down,bottom-up solution to collaborative continental-scale monitoring

Collaborative monitoring over broad scales and levels of ecological organization can inform conservation efforts necessary to address the contemporary biodiversity crisis. An important challenge to collaborative monitoring is motivating local engagement with enough buy-in from stakeholders while providing adequate top-down direction for scientific rigor, quality control, and coordination. Collaborative monitoring must reconcile this inherent tension between top-down control and bottom-up engagement. Highly mobile and cryptic taxa, such as bats, present a particularly acute challenge. Given their scale of movement, complex life histories, and rapidly expanding threats, understanding population trends of bats requires coordinated broad-scale collaborative monitoring. The North American Bat Monitoring Program (NABat) reconciles top-down, bottom-up tension with a hierarchical master sample survey design, integrated data analysis, dynamic data curation, regional monitoring hubs, and knowledge delivery through web-based infrastructure. NABat supports collaborative monitoring across spatial and organizational scales and the full annual lifecycle of bats.     

高锰酸盐指数测定中影响因素的探讨

通过对酸性法测定高锰酸盐指数全过程的分析,结果表明水样静置时间、水样浓度、水浴时间、反应温度等因素影响测定结果。文章总结了测定过程中需要注意的几个关键环节,确保获得准确数据。     

液相微萃取-气质联用法测定扎龙水样中增塑剂

采用液相微萃取前处理方法与气相色谱—质谱联用技术相结合对扎龙水样中增塑剂进行测定。     

碘量法测定水中溶解氧有关问题的探讨及改进

碘量法测定溶解氧时,采用NH3·H2O—KI代替NaOH(KOH)—KI固定溶解氧,用H2SO4—H3PO(41+1)混合酸代替H2SO4溶解沉淀,使沉淀沉降速度加快,分界线明显,沉淀溶解也更完全。同时做样品空白实验,校正了氧化还原性物质产生的干扰,对废水有明显的抗干扰能力。通过对蒸馏水、自来水、池塘水、废水进行溶解氧测定,结果均非常满意。     

固相萃取-气相色谱法测定水样中马拉硫磷残留

采用C-18小柱萃取、毛细管柱分离、气相色谱氢火焰离子化检测器（FID）测定水样中的马拉硫磷,检测限为0．12μg／L。试验了样品流量和洗脱剂对回收率的影响,结果表明样品流量为6mL／min、二氯甲烷作洗脱剂时,回收率较好。测定蒸馏水、地下水和河水样品,相对标准偏差〈2．2％。加标回收率在79．0％-109％之间。     

Approximating the distribution of recreational visits from on-site survey data

While convenient and often used, on-site surveys are biased by the fact that users who visit the site more often are proportionately more likely to be sampled. This so-called avidity or size biased sampling results in over-estimating the visitation patterns of the average user. This analysis develops a rule of thumb method that may easily be applied by recreation site managers to visitation data collected on-site in order to infer behavior of the average user of the site. The key assumption that drives the derivation is that the visitation data of users is logarithmically distributed. To evaluate the methodology, we analyze several data sets of recreational users assuming that they reflect the populations of users and from these construct hypothetical on-site samples.     

Secondary arsenic minerals in the environment: A review

Information on arsenic (As) speciation in solid materials is critical for many environmental studies concerned with As stability and/or mobility in natural As-impacted soils and mining or industrial sites contaminated by As. The investigation of these systems has provided evidence for a number of secondary As minerals that have often played a significant role in As mobility in the solid phase–water system. This paper presents a list of environmentally important secondary As minerals in contaminated soil and waste systems, summarizes the information about their origin, occurrence, environmental stability and thermodynamics, and proposes several important avenues for further investigation.     

基于模糊神经网络的机动车驾驶教练员职业适宜性研究

提出应用模糊神经网络系统,建构教练员职业适宜性的3个要素(即心理素质、驾驶技能和知识的表达阐述能力)的学习样本,分析"三要素"的8项特征参数指标——场依存性、速度估计能力、交通安全意识、简单反应、选择反应、跟踪能力、行车注意力、表达阐述能力等,使用K-均值法对实验样本进行初始分类,形成标准学习样本,使用该样本对所构建系统进行训练和调试。利用经调试训练后的系统,依据所测教练员的心理、心理参数对其职业适宜性进行评价。试验表明:建立的教练员职业适宜性仿真模型能取得很好的评价效果。     

Characterization of distribution of pesticide residues in crop units

The characteristic features of distribution of pesticide residues in crop units and single sample increments were studied based on more than 19,000 residue concentrations measured in root vegetables, leafy vegetables, small-, medium- and large-size fruits representing 20 different crops and 46 pesticides. Log-normal, gamma and Weibull distributions were found to provide the best fit for the relative frequency distributions of individual residue data sets. The overall best fit was provided by lognormal distribution. The relative standard deviation of residues (CV) in various crops ranged from 15–170%. The 100–120 residue values being in one data set was too small to identify potential effects of various factors such as the chemical and physical properties of pesticides and the nature of crops. Therefore, the average of CV values, obtained from individual data sets, were calculated and considered to be the best estimate for the likely variability of unit crop residues for treated field (CV = 0.8) and market samples (CV = 1.1), respectively. The larger variation of residues in market samples was attributed to the potential mixing of lots and varying proportion of non-detects. The expectable average variability of residues in composited samples can be calculated from the typical values taking into account the sample size.