地震预警系统中的算法研究

通过对地震预警系统中基本算法的研究,在现有方法的基础上提出了一套地震参数快速估算的算法,以应用于地震预警系统中。该算法根据某些噪音的特殊性质,通过引入两个参数:触发时窗与取消阈值,对常用的P波初到判断方法STA/LTA(长时窗平均/短时窗平均)算法进行改进,以消除P波到达前的异常跳动点与脉冲噪音的影响,对P波到达进行识别。在识别到P波到达后,该算法实时的从P波初到后3s时窗内的竖向数据中提取出12类特征性质不同的计算参数作为估算震级,震中距等地震参数的依据,提高了震级、震中距的估算精度,减少了在大震下估算的离散性,取得了较好的结果。该算法可在地震P波到达后的几秒钟内,估算出地震相关参数,在S波到达前发出预警,并为采取相应的措施以及震后求援行动提供判断依据,达到防灾减灾的目的。     

微波辅助改性壳聚糖的制备及其絮凝性能

以壳聚糖、阳离子醚化剂二甲基二烯丙基氯化铵为原材料,采用微波辐射的方法,制备了壳聚糖接枝共聚物（壳聚糖-二甲基二烯丙基氯化铵）,并通过红外光谱分析对改性壳聚糖进行了表征。以接枝率为标准,确定改性壳聚糖的最佳反应条件,并以高岭土悬浊液和实际生活污水作为处理对象,测定了改性壳聚糖的絮凝性能。结果表明,壳聚糖接枝共聚物的最佳制备条件是微波反应温度55℃,反应时间20 min,壳聚糖0.5 g,微波功率270 W,阳离子醚化剂的浓度20%,在此条件下,合成的改性壳聚糖的接枝率为80%。红外光谱分析结果显示,已成功地合成了壳聚糖-二甲基二烯丙基氯化铵接枝共聚物。在絮凝实验中,壳聚糖接枝共聚物的去浊率最高达到91%,COD去除率最高达到77%。其结果表明,壳聚糖接枝共聚物的絮凝性能明显高于原料壳聚糖。     

对锅炉烟气处理的技术改造

对锅炉烟气处理工艺进行了改造，运行结果表明，改造后的处理效果明显提高，解决了烟尘及SO2排放浓度的超标问题，实现了达标排放。     

Restructured frame‐of‐reference training improves rating accuracy

The use of heuristic judgments is prevalent in organizations and negatively impacts accurate employee assessments. To minimize the negative impact of heuristic judgments (i.e., anchoring and adjustment), we aim to improve rating accuracy by restructuring frame‐of‐reference (FOR) training. We conducted five studies (N = 1,143) using different samples (three including participants with hiring experience), training environments (onsite and online), and rating contexts (evaluations of sales representatives, teachers, contract negotiation specialists, and retail store managers). Across the five studies, the average improvement in rating accuracy was at least twice as large for restructured FOR (vs. control) training as it was for typical FOR (vs. control) training; the difference in rating accuracy between restructured and typical FOR training was statistically significant. Furthermore, minimizing the anchoring effect rather than increasing opportunities for rating adjustments improved rating accuracy (Study 4). Finally, restructured FOR training achieved higher criterion validity (i.e., a higher strength of the association between ratings regarding a target and the target's objective performance) than did typical FOR training (Studies 3 and 5). We discuss implications for improving the effectiveness of diverse training programs and the accuracy of judgments in organizations.     

防洪物资储备决策方法初探

根据防洪抢险物资储备属于一种信息不全型决策问题的特点,本文提出了一种用于确定每年防灾物资准备量概率排序决策模型,并以孙不河流泥石流灾害预报火灾决策为例进行说明。     

4种农药对土壤脱氢酶活性的影响

通过天王星、功夫、久效磷、氧化乐果4种农药对土壤脱氢酶活性的抑制性进行试验,确认了实验条件的影响因素,同时分析了不同农药用量、不同土样用量及不同培养时间对脱氢酶活性的影响。试验结果表明,4种农药在不同情况下对脱氢酶活性均有不同程度的抑制作用,表明了在本地区特有的农业环境条件下,农用化学物质可能会影响和破坏农业生态环境。     

Identification of Odor Causing Compounds in a Commercial Dairy Farm

The odorous air emissions from confined animal feeding operations (CAFOs), such as swine, poultry and dairy farms, are increasingly raising community complaints. Odorous emissions can result in health damages, psychological discomforts and adverse aesthetic effects in the community. However, these emissions are not well characterized up to now due to the lack of legislation, the limitations in sampling and instrumentation techniques, and the complexity of the emissions themselves. This study is aimed at the development of a high volume sampler and sorbent assembly to identify the odor causing compounds from a diary CAFO. The sorbent was custom designed to target the potential compounds that may exist in a dairy farm and was validated in laboratory with a synthetic odor from the swine manure. The actual samples at the diary farm were collected in spring and summer of 2005. The sorbents were solvent extracted and individual odor compounds were identified using GC–MS (gas chromatography–mass spectroscopy). The data obtained indicated that high volume sampling can shorten the sampling time from days to within 4 h. Both volatile organic compounds (VOCs) and volatile fatty acids (VFAs) have been identified from the dairy farm, such as phenol, methylphenol, 4-ethyl phenol, indole, methyl indole, benzyl alcohol, hexanoic acid, valeric acid and iso-valeric acid, together with some nitrogen containing compounds that have not been reported before.     

用灰关联分析和神经网络方法预测煤与瓦斯突出

本文应用灰色系统理论的灰色关联分析,对煤与瓦斯突出影响因素进行灰关联分析,得出了各影响因素对煤与瓦斯突出影响程度的大小排序,选择灰关联分析的五个优势因子:瓦斯放散初速度、坚固性系数、瓦斯压力、煤体破坏类型和开采深度,作为输入参数,用计算机对神经网络编写程序,建立了煤与瓦斯突出预测的神经网络模型.用我国典型突出矿井的煤与瓦斯突出实例作为学习样本,对网络进行训练学习,并以云南恩洪煤矿的煤与瓦斯突出实例作为预测样本进行验证.     

高危职业危害监测内涵及预警系统探讨

我国目前职业病危害形势严峻,职业卫生管理和服务模式不能适应社会发展的需求,优先管理高危职业危害,建立高危职业危害监测预警系统是控制和减少重大职业危害事故的关键.通过职业危害监测、风险评估、风险分级和预警等术语阐述高危职业危害监测的内涵,并探讨建立利用现有技术平台、重点监控、多部门合作、多层次的纵向多维监测预警系统.