Seismic health monitoring of RC frame structures using smart aggregates

Structural health monitoring of RC structures under seismic loads has recently attracted much attention in the earthquake engineering research community. In this study, a piezoceramic-based device called "smart aggregate" was used for the health monitoring of RC frame structures under earthquake excitations. Three RC moment frames instrumented with smart aggregates were tested using a shaketable with different ground excitation intensities. Distributed piezoceramic- based smart aggregates were embedded in the RC structures and used to monitor their health condition during the tests. The sensitivity and effectiveness of the proposed piezoceramic-based approach were investigated and evaluated by analyzing the measured responses. The displacement ductility demand of the structural members was calculated and compared with the damage index determined from the health monitoring system. The comparison shows that the damage index is compatible with the calculated ductility demand.     

Using rough set theory to identify villages affected by birth defects: the example of Heshun,Shanxi, China

This article uses rough set theory to explore spatial decision rules in neural-tube birth defects and searches for novel spatial factors related to the disease. The whole rule induction process includes data transformation, searching for attribute reducts, rule generation, prediction or classification, and accuracy assessment. We use Heshun as an example, where neural-tube birth defects are prevalent, to validate the approach. About 50% of the villages in Heshun are used as the sample data, from which all of the rules are extracted. Meanwhile, the other villages are used as reference data. The rules extracted from the training data are then applied to the reference data. The result shows that the rules' generalization is reasonably good. Moreover, a novel relationship between the spatial attributes and the neural-tube birth defects was discovered. That is, the villages that lie in Watershed 9 of this district and that are also associated with a gradient of between 16° and 25° are vulnerable to neural-tube birth defects. This result paves the road for predicting where high rates of neural-tube birth defects will occur and can be used as a preliminary step in finding a direct cause for the disease.     

东南亚红树林时空变化趋势及驱动因素分析

为揭示东南亚红树林的时空变化特征及其变化驱动因素,基于Google Earth Engine (GEE)云计算平台,利用Landsat系列卫星数据及红树林分布数据集,采用趋势分析法分析了1990—2020年东南亚红树林的时空变化趋势,并利用地理探测器分析其时空变化的驱动因子。结果表明：1) 1990—2020年东南亚红树林面积整体呈下降趋势,面积减少1 467 883.1 hm²,年平均流失速率达1.1%;2)红树林面积增加的区域主要分布在菲律宾、印度尼西亚西部和东部以及越南北部等区域;3) 1990—2020年东南亚红树林退化的区域远远多于改善的区域,退化的区域占红树林总分布面积的79.25%,改善的区域占20.32%,仅0.43%的区域稳定不变;4)红树林变化受驱动因素的影响程度排序主要为养殖池面积>人口>红树林距道路的最短距离>年均温>年均降雨>地形,且各因子之间呈现交互增强作用,增强效果较为明显的主要有：养殖池面积-人口、养殖池面积-红树林距道路最短距离、人口-红树林距道路最短距离。     

广州南沙湿地公园鸟类2014—2018年际动态及其对生境变化的响应

为了解广州南沙湿地鸟类迁徙规律,揭示鸟类整体迁徙动态变化,于2014年1月至2018年12月,连续在每月下旬日落前3 h采用样点法和样线法对南沙湿地公园鸟类群落多样性进行调查。结果显示：1) 2014—2018年共记录到鸟类139种,以冬候鸟为主。2）鸟类物种数年际波动较大,丰富度年际变化不明显,即鸟类种类在逐渐增加的同时,个体数量趋于稳定。3）鸟类月度变化呈现明显的候鸟迁徙规律,越冬期急速上升,繁殖期平缓。越冬水鸟迁飞时间有提前的趋势,且在富有食物来源的浅水滩涂地和在无瓣海桑等高大茂盛的红树林群落有更多种类与数量的水鸟分布。最后,建议在注重绿化连续性和整体性的同时,保护和管理鸟类的栖息环境,适当扩大滩涂地面积,增加红树林种植面积以及合理地围垦,科学维持浅水滩涂和红树林种植面积比例,吸引更多越冬候鸟。     

承压井水位对含水层潮汐应力响应是否满足不排水条件的检验

以Hsieh模型为基础,提出了利用地震前后承压井水位潮汐分波的振幅及初始相位变化与否作为判断依据,检验井水位对含水层潮汐应力响应是否满足不排水条件的简便方法.将该判别方法用于分析会理川-06井和川-18片水位观测数据,利用Baytap-G潮汐分析方法分别计算出3次选定地震前后两井水位各分波(M2和O1)振幅和相位值.结...     

季风湿润区冬季水汽收支年际及年代际变化特征

采用1958—2007年NCEP/NCAR再分析资料和我国160站降水资料,对东亚大陆季风湿润区冬季的水汽收支变化与大气环流和我国降水异常特征的关系进行研究。结果表明:冬季水汽收支时间序列表现出明显的长期气候变化趋势。挑选的水汽收支高、低值年不仅能够指示季风湿润区经向风的异常变化,还能够指示东亚冬季风的强弱和降水的异常变化。高值年,蒙古冷高压和阿留申低压偏弱,对流层低层为异常偏南风,整层为异常逆时针环流,30°N以南的辐合和上升运动强,大气水分收入增多,降水增加;低值年则相反。差值合成的异常降水量中心值可达40 mm以上,差值合成的水汽异常输入主要集中在600~900 hPa。合成的经向水汽收支占净收支变化的91.3%,纬向上相差较小。季风湿润区南、北区域的水汽收支及降水的差异明显,纬向的收入支出对此差异贡献较大。水汽收支的年代际特征,不仅能够指示水汽输送的强弱及从海洋输入水汽的多少,还能够指示季风湿润区降水的变化,且差值合成的异常降水量最大可达30 mm以上。     

南宁市空气质量状况分析

总结分析2002—2009年南宁市逐日及月平均、季平均、年平均空气质量状况。2002—2009年,南宁市空气质量优良率为96．8％,首要空气污染物主要为可吸入颗粒物和二氧化硫,而又以可吸入颗粒物居多。在2002年至2009年,西乡塘区是南宁市空气质量最好的城区,江南区是南宁市空气质量最差的城区。2005年以后,南宁市全...     

贺州自动站替换人工观测对资料连续性影响分析

对贺州站2004～2005年自动站与人工站平行观测的气温资料进行资料差异性分析,对气温月、日平均值及其平均差值进行了显著性检验,结果表明自动站气温和人工站气温数据差异性不显著,资料的连续性很好,但仍存在一定的系统误差.如能采用适当的方法进行订正,将极大地提高资料的可用性.     

激光雷达在大气混合层探测中的应用

利用香港的激光雷达资料,结合当地的探空资料和天气资料,分析激光雷达在观测大气混合层厚度及其特征。     

Logistic regression model for predicting the failure probability of a landslide dam

Landslides may obstruct river flow and result in landslide dams; they occur in many regions of the world. The formation and disappearance of natural lakes involve a complex earth–surface process. According to the lessons learned from many historical cases, landslide dams usually break down rapidly soon after the formation of the lake. Regarding hazard mitigation, prompt evaluation of the stability of the landslide dam is crucial. Based on a Japanese dataset, this study utilized the logistic regression method and the jack-knife technique to identify the important geomorphic variables, including peak flow (or catchment area), dam height, width and length in sequence, affecting the stability of landslide dams. The resulting high overall prediction power demonstrates the robustness of the proposed logistic regression models. Accordingly, the failure probability of a landslide dam can also be evaluated based on this approach. Ten landslide dams (formed after the 1999 Chi-Chi Earthquake, the 2008 Wenchuan Earthquake and 2009 Typhoon Morakot) with complete dam geometry records were adopted as examples of evaluating the failure probability. The stable Tsao-Ling landslide dam, which was induced by the Chi-Chi earthquake, has a failure probability of 27.68% using a model incorporating the catchment area and dam geometry. On the contrary, the Tangjiashan landslide dam, which was artificially breached soon after its formation during the Wenchuan earthquake, has a failure probability as high as 99.54%. Typhoon Morakot induced the Siaolin landslide dam, which was breached within one hour after its formation and has a failure probability of 71.09%. Notably, the failure probability of the earthquake induced cases is reduced if the catchment area in the prediction model is replaced by the peak flow of the dammed stream for these cases. In contrast, the predicted failure probability of the heavy rainfall-induced case increases if the high flow rate of the dammed stream is incorporated into the prediction model. Consequently, it is suggested that the prediction model using the peak flow as causative factor should be used to evaluate the stability of a landslide dam if the peak flow is available. Together with an estimation of the impact of an outburst flood from a landslide-dammed lake, the failure probability of the landslide dam predicted by the proposed logistic regression model could be useful for evaluating the related risk.