废催化剂浸出规律的静态实验方法

利用静态浸出实验方法对废催化剂中重金属在不同固水比和浸出次数条件下的浸出规律进行了系统研究。实验发现浸出次数大于３次后,重金属的浸出浓度和浸出速率趋于稳定,同时固水比的增加也没有明显改变废催化剂中重金属的浸出。认为在浸取次数大于３次以后,随着表面溶质的溶解,浸出过程主要为内扩散所控制。     

活性炭纤维吸附／热解吸／毛细管气相色谱法测定低浓度VOCs的方法

本文以活性炭纤维为吸附材料,建立了活性炭纤维吸附／二次热解吸 缩／毛细管气相色谱法测定空气中ＶＯＣＳ的方法,讨论了吸附剂的安全采样体积,湿度控制及分析方法的精密度,检出限和回收率。本法对苯,甲苯,四氯乙烯,对－二甲苯和苯乙类的最低可测浓度分别为０．１３,０．０２,０．１２,０．０５和０．０５μｇ．ｍ＾－３,适用于低浓度ＶＯＣＳ样品的测定。     

黄土高陡边坡建筑动力临坡安全距离试验研究

针对黄土高陡边坡独特的动力易损性以及黄土地区典型的建筑分布特点,以黄土高陡边坡坡顶建筑物的动力临坡安全距离为研究目标,采用大型振动台模型试验的方法,通过输入振幅逐级增大的地震波,对比分析了坡顶、坡脚处建筑物的动力响应与破坏过程,揭示了强震作用下临坡建筑的失稳特征与动力临坡安全距离。结果表明:坡顶建筑物的破坏程度与动力响应比坡底建筑强烈,随着边坡的破坏,坡顶建筑物有发生向坡面一侧倾覆的风险,滑坡土体最高堆积至坡下建筑物4层高度处;坡顶建筑地基基础呈“不对称式拉剪破坏”,加速度沿楼体高度有放大效应,且随着地震荷载幅值的增大,放大效应更加明显;土与建筑结构相互作用下,坡顶裂缝竖向发展可达50 cm,对照原型,黄土高陡边坡的竖向裂缝深度可达25 m,试验结果与1989年塔吉克斯坦5.5级地震震害相符。坡高为35 m,坡脚角度为70°的黄土高陡边坡,在强震荷载作用下,坡顶多层建筑的临坡安全距离最小值为20 m。     

Mechanism of complexation of toxic arsenate,selenate, and molybdate with hydrotalcites

Environmental Chemistry Letters - Wastewater from the uranium mining industry contains toxic arsenate (AsO43–), selenate (SeO42–), and molybdate (MoO42–) that can be removed by...     

MSWNet: A visual deep machine learning method adopting transfer learning based upon ResNet 50 for municipal solid waste sorting

● MSWNet was proposed to classify municipal solid waste. ● Transfer learning could promote the performance of MSWNet. ● Cyclical learning rate was adopted to quickly tune hyperparameters. An intelligent and efficient methodology is needed owning to the continuous increase of global municipal solid waste (MSW). This is because the common methods of manual and semi-mechanical screenings not only consume large amount of manpower and material resources but also accelerate virus community transmission. As the categories of MSW are diverse considering their compositions, chemical reactions, and processing procedures, etc., resulting in low efficiencies in MSW sorting using the traditional methods. Deep machine learning can help MSW sorting becoming into a smarter and more efficient mode. This study for the first time applied MSWNet in MSW sorting, a ResNet-50 with transfer learning. The method of cyclical learning rate was taken to avoid blind finding, and tests were repeated until accidentally encountering a good value. Measures of visualization were also considered to make the MSWNet model more transparent and accountable. Results showed transfer learning enhanced the efficiency of training time (from 741 s to 598.5 s), and improved the accuracy of recognition performance (from 88.50% to 93.50%); MSWNet showed a better performance in MSW classsification in terms of sensitivity (93.50%), precision (93.40%), F1-score (93.40%), accuracy (93.50%) and AUC (92.00%). The findings of this study can be taken as a reference for building the model MSW classification by deep learning, quantifying a suitable learning rate, and changing the data from high dimensions to two dimensions.     

震后灾害链生机制及其对汶川地震城镇重建的影响

汶川8级大地震对地表产生强烈扰动,导致次生山地灾害极度发育,影响到震后灾害的活动特征及其相应的减灾对策。震后松散固体物质急剧增加、流域微地貌变化明显(沟道堵塞严重)、水文变化利于侵蚀和洪峰,使得灾害群发链生:崩塌、滑坡→泥石流→堰塞湖→溃决洪水(泥石流),8月中旬灾区各地因强降雨而大规模爆发泥石流堵塞河道,洪水冲毁掩埋重建城镇,给地震重灾区造成巨大损失。从以汶川县映秀镇为例,在阐述灾害链研究成果的基础上,分析震后灾害链的形成条件、成灾过程以及对城镇重建居民点的危害特点,进而提出灾害防治措施,为灾后城镇建设防灾减灾提供参考建议。     

基于合成孔径雷达的城市建筑地震受损分析

汶川地震灾区位于青藏高原东缘,该地区云雨天气较多,光学遥感受制约较大,而微波能够穿透云、雾、小雨等,且不受太阳光线的影响,雷达遥感具有全天时、全天候的特点,因而可以弥补光学遥感的不足。根据房屋受地震破坏后影响雷达回波强度,在雷达影像上表现为亮度及纹理不同的原理,本论文利用不同分辨率的COSMO-SkyMed和Radarsat等SAR数据,将其与震前的SPOT影像进行配准后,通过纹理分析等处理,对都江堰市区、北川县城曲山镇等受灾较为严重的城镇进行分析解译,利用雷达影像判读出倒塌房屋的信息,以及地震次生山地灾害对城镇的破坏。     

Cadmium uptake by different rice genotypes that produce white or dark grains

IntroductionCadmium(Cd)isanon essentialtracemetalthathasadverseeffectsonplants,animalsandhumans.EnvironmentalcontaminationwithCdduetoanthropogenicactivities,suchasmining,industry,agricultureandwastedisposalhasbeenincreasingsincethebeginningofthe 2 0thcentury (Alloway,1995) .ResearchoncontrollingCdpollutionassociatedwithassessingandmanagingacuteinjurytohumanhealththroughoccupationalexposureanddisposalofCdfromindustrialpointsourcestolocalpopulationsthroughseveralpathwayshasmadeconsiderableadva…     

The integration of HAZOP expert system and piping and instrumentation diagrams

The main purpose of hazard and operability (HAZOP) analysis is to identify the potential hazards in the process design which nowadays is generally developed through a computer aided design (CAD) package. Due to the time and effort consuming nature of HAZOP, it is not done in every engineering firm for every design project. To make HAZOP an integral part of process design, an integration framework is proposed in this paper to seamlessly integrate the commercial process design package Smart Plant P&ID (SPPID, Intergraph) with one of the HAZOP expert systems (named as LDGHAZOP) developed by authors. This integration makes it possible to perform HAZOP analysis easily at anytime of the whole lifecycle of a chemical plant as long as the process design is available, which might help the improvement of design quality. One industrial case study is used to illustrate the ability of the integrated system.     

通过式固相萃取/超高效液相色谱-串联质谱法测定蔬菜中18种农药残留

建立了超高效液相色谱-串联质谱(UPLC-MS;MS)快速测定蔬菜中18种农药残留的方法.样品经乙腈提取后,经Oasis PRiME HLB固相萃取柱净化,采用ACQUITY UPLC HSS T3 C18(50 mm×2.1 mm,1.8μm)色谱柱进行分离,以0.1%甲酸水溶液和乙腈作为流动相进行梯度洗脱.采用电喷雾电离源、正离子模式下以多反应监测(MRM)进行定性和定量分析.结果表明,18种农药在0.5—50μg·L^-1范围内线性关系良好(r2>0.995),方法最低检出限为0.4—1.5μg·kg^-1,最低定量限为1.4—5.0μg·kg^-1.在韭菜、芹菜、番茄、白菜基质中,5、10、50μg·kg^-1添加水平下的加标回收率为60.2%—126.9%,相对标准偏差(RSD)为0.4%—21.6%(n=3).