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。     

粘虫颗粒体病毒及其增效因子对粘虫核型多角体病毒的增效作用

生物测定的结果表明,粘虫颗粒体病毒ＰｕＧＶ－Ｐｓ及其增效因子对粘虫核型多角体病毒ＰｓＮＰＶ均有明显的增效作用．粘虫颗粒体病毒不仅能提高粘虫感染ＰｓＮＰＶ的死亡率,而且ＮＰＶ、ＧＶ两种病毒混合感染使粘虫幼虫代谢发育受到抑制,表现为生长缓慢、体重减少等．增效因子的增效作用表现在能显著提高粘虫幼虫的死亡率,降低核型多角体病毒的半致死浓度ＬＣ５０,并缩短半致死时间ＬＴ５０．     

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.     

活性粉煤灰增湿脱硫机理及数学模型的研究

在双膜理论和传质理论基础上分析了活性粉煤灰增湿脱硫机理,并建立了简化的脱硫模型,考虑烟气流量和脱硫剂加入量两个脱硫效率的影响因素时,将数学模型的计算值与实验值进行了比较,结果比较吻合。     

企业节能量计算方法浅析

阐述了企业在实施节能降耗过程中普遍采用的节能量计算方法,对产品单耗节能量和技术措施节能量进行了分析,并对比了采用单耗法和技术措施法计算节能量的适用范围和局限性,指出两种方法对企业的意义,提出了在节能量计算过程中的注意事项和几点认识。     

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…