铬的生物地球化学及生物效应

铬的生物地球化学行为及生物效应研究受到了广泛重视,其主要有以下特征：铬在地球和各环境及生物要素中皆有分布,但分布不均;Cr(Ⅲ)和Cr(Ⅵ)都具有毒性,但Cr(Ⅲ)的毒性和在环境中的迁移能力皆小于Cr(Ⅵ);具有生理活性功能的是Cr(Ⅲ),其生物学效应符合Bertrand最适营养浓度定律;适当条件下,Cr(Ⅲ)和Cr(Ⅵ)可以发生相互转换,从而实现铬在环境中的转移和富集。     

攀钢冶炼废渣中重金属地球化学特征及其环境效应

为治理钢铁冶炼产生的废渣对环境造成的污染,通过对废矿渣堆以及周围土壤中重金属元素的地球化学特征分析,研究了它对附近环境造成破坏的影响因素及污染程度.结果表明:(1)冶炼废渣中重金属元素趋向于富集在比表面积大的颗粒上,易于进入大气中产生环境污染;(2)矿渣堆对环境的破坏以降尘为主要形式,与距离及地形因素呈一定相关;(3)...     

宜宾市翠屏区宋家乡土壤地球化学质量评价及意义

在表层土壤系统采样调查的基础上,进行了相关的灌溉水、饮用水以及土壤有机物和大气降尘等的测试,分析结果显示,宜宾市翠屏区宋家乡土壤存在重金属元素超标趋势,尤其是镉。采用地质累积指数法和污染程度分析对翠屏区宋家乡地区土壤质量进行了评价和分析,为该区土壤资源、环境评价和农业经济发展规划提供了实用地球化学信息。     

自贡市城市地质环境分区评价

从自然地理条件、地质条件、环境质量、环境地质问题等方面着手,以地形地貌、区域地壳稳定性、岩（土）体工程地质特征、环境污染、地质灾害为要素开展了自贡市城市地质环境质量评价;采用了权重法、层次分析法等计算方法得出了地质环境综合评价指数,对自贡市进行了地质环境评价分区;为城市的发展规划提供了可靠的地质依据。     

环保部:2030年消除中部地区饮用水安全隐患

<正>不久前,环保部召开中部地区发展战略环境评价总体成果验收会,会上发布了《中部地区发展战略环境评价报告(送审稿)》(下简称评价报告)。评价报告提出中部地区2030年实现空气质量全面改善等绿色崛起目标。中部地区战略环境评价研究范围包括中原经济区、武汉城市圈、长株潭城市群、皖江城市带、鄱阳湖生态经济区等重     

中国一些地区温泉中天然气的地球化学特征及碳、氦同位素组成

中国一些地区温泉气的主要组分是CO_2或N_2,烷烃气含量低或无,同时含极微量的氦。温泉气的δ~(13)C_1主频率峰在-20‰至-22‰,说明温泉气的甲烷主要是无机成因的。温泉气的δ~(13)C_(CO_2)主频率峰在-4‰至-8‰,反映温泉气的CO_2也主要是无机成因的。δ~(13)C_(CO_2)值与CO_2含量正相关,其回归方程为δ~(13)C_(CO_2)(‰)≈0.966lgCO_2-6.354,δ~(13)C_(CO_2)值与N_2含量负相关,其回归方程为δ~(13)C_(CO_2)(‰)≈-3.193-0.109 N_2。根据氦同位素组成特点,可划分出幔源温泉气和壳源温泉气,前者R/R_a>1,后者R/R_a<1。     

多氯联苯的环境行为*

本文从多氯联苯(PCBs) 的污染状况、分析方法、环境中的迁移转化、多介质模型及风险评价5 个方面综合论述了多氯联苯的环境行为, 并指出要降低PCBs 对生态环境的破坏, 需要更深入地研究PCB s 的环境行为和归趋, 大力加强其风险评价工作, 这已成为21 世纪的优先研究领域之一。     

反相高效液相色谱法测定某些有机化合物的分配系数

有机化合物的分配系数(K_(ow))是表示有机物质疏水性或亲脂性的程度,是评价农药和工业化合物对环境潜在性危害的重要物理化学参数。用K_(ow)还可推测有机化合物的水的溶解度、土壤吸附系数、生物浓缩趋势以及在自然环境中的降解速率等。所以K_(ow)无论是在对有机物对环境潜在性危害的评价,还是在总结化学结构与生物活性关系中都是重要的指     

2022年《理化检验-化学分册》专题报道北大核心CSCD

《理化检验-化学分册》杂志将在近年开展专题报道的基础上,拟在2022年继续于第5、7、9期分别推出以“食品质量安全”“环境污染物”和“新材料成分”等分析对象为主的3期专题报道,热忱欢迎相关领域的检测技术人员踊跃投稿.具体内容涉及:1)食品质量安全分析目前我国食品质量安全保障体系已基本建成,但仍然面临很多问题,食品质量安全评价将迎来更智慧的新时代.本专题将重点关注食品添加剂,食品及食品接触材料中的药物残留、化学毒素、重金属等有害物质检测的新方法,以及纳米技术、生物芯片等新技术在食物安全快速检测方面的应用.2)环境污染物分析工业快速发展、农村城镇化过程、城市废弃物均对环境安全造成巨大威胁.本专题将重点关注环境介质中各种污染物种类、成分、存在形态及各形态含量的分析测定.研究对象包括传统典型污染物(如重金属与有机金属化合物、持久性有机污染物)、长期低剂量暴露污染物(如抗生素类药物、饮用水消毒副产物、藻毒素、环境内分泌干扰物)和灾害与紧急事件污染物.     

中国层控矿床地球化学研究

层控矿床是指那些局限于一定地层并与岩浆活动没有直接联系的矿床。沉积矿床一般不包括于层控矿床中,尽管它也受地层控制。“中国层控矿床地球化学”课题研究的最终成果包括专著三卷(1984、1987、1988)和研     

Fuzzy model prediction of Co (III)Al2O3 catalytic behavior in Fischer-Tropsch synthesis

The application of Co(Ⅲ)/Al2O3 catalyst in Fischer-Tropsch synthesis(FTS)was studied in a wide range of synthesis gas conversions and compared with Fuzzy Simulation results.Present study applies fuzzy model to predicting the product composition of CH4,CO2 and CO in Fischer-Tropsch process for natural gas synthesis,in which the input vector was 4-dimension including four variables(operating pressure, operating temperature,time and CO/H2 ratio)of 70 different experiments and the output product is a composition of CO2,CO and CH4. The Mamdani algorithm has been applied to the training of the fuzzy system and the test set was used to evaluate the performance of the system including R2,ARE,AARE and SD.The results demonstrated that the predicted values from the model were in good consistency with the experimental data.The work indicates how fuzzy inference system(FIS),as a promising predicting technique,would be effectively used in FTS.     

Estimation of concrete compressive strength by a fuzzy logic model

Concrete mix design is a process of proportioning the ingredients in right proportions. The aim of this study is to design a fuzzy logic model for determination of the compressive strength of a concrete. The datasets which have been loaded into a fuzzy logic model contain 1,030 concrete mixtures. Input fields of the fuzzy expert system are weight percent of cement, water, blast furnace slag, fly ash, super plasticizer, fine aggregate, coarse aggregate, and age of the concrete. Output field is concrete compressive strength. Finally, 897 rules used for this fuzzy logic modeling.     

Molecular Processors: From Qubits to Fuzzy Logic

Single molecules or their assemblies are information processing devices. Herein it is demonstrated how it is possible to process different types of logic through molecules. As long as decoherent effects are maintained far away from a pure quantum mechanical system, quantum logic can be processed. If the collapse of superimposed or entangled wavefunctions is unavoidable, molecules can still be used to process either crisp (binary or multi‐valued) or fuzzy logic. The way for implementing fuzzy inference engines is declared and it is supported by the examples of molecular fuzzy logic systems devised so far. Fuzzy logic is drawing attention in the field of artificial intelligence, because it models human reasoning quite well. This ability may be due to some structural analogies between a fuzzy logic system and the human nervous system.     

Intelligent control of a pH process

A new strategy, to augment the pH process control is offered in this paper. The intelligent controller proposed herein is based on an inverse neural plant model. An integration term is introduced to improve the pure inverse neural controller performance. This element, adjusted by a fuzzy system with respect to the control error, operates in parallel with the neural controller to ensure offset-free performance, in case of system uncertainties or modelling mismatch. Four fuzzy rules were applied to generate the integrator parameters. Experimental results, carried out under pH control on a laboratory scale set-up, demonstrate the feasibility of the proposed control system. Presented at the 35th International Conference of the Slovak Society of Chemical Engineering, Tatranské Matliare, 26–30 May 2008.     

A novel adaptive neuro-fuzzy inference system model to predict the intrinsic mechanical properties of various cellulosic fibers for better green composites

In this work a novel adaptive neuro-fuzzy inference system model has been developed for the prediction of the intrinsic mechanical properties of various cellulosic natural fibers to enhance their selection for better green composite materials. The model combined modeling function of the fuzzy inference system with the learning capability of the artificial neural network. The developed model was built up based on experimental mechanical properties of various cellulosic fiber types commonly used for natural fiber reinforced composites, and the rules have been generated directly from the experimental data. The developed model was capable of predicting all of Young's modulus, ultimate tensile strength, and elongation at break properties from only two intrinsic properties of fibers namely; cellulose and moisture content. The adaptive neural fuzzy inference system (ANFIS) structure included five layers to realize the establishment and calculation of each model. The system architecture included the fuzzy input layer, product layer, normalized layer, de-fuzzy layer and total output layer. Results have been revealed that the model’s predictions were highly in agreement with other experimentally gained properties when compared with experimental results for verifying the approach. The accuracy of the developed model would enhance predicting other cellulosic fiber properties to develop better natural fiber composites in the near future.

     

Modelling of micro-electrochemical machining parameters used for machining of holes on copper plate

The electrochemical machining is a non-conventional machining process based on the electrolysis principle. It is used to machine various features on conducting engineering materials with the required accuracy and precision. So an attempt has been made to machine micro-holes on a 300 μm thick copper plate as an anode and a hollow stainless steel tool electrode of 250 μm diameter as the cathode. The machining operation is performed on the in-house developed micro-ECM experimental setup with controlled machining parameters voltage, concentration, and duty factor varied in three levels. A full factorial experimental plan is used to study the output responses material removal rate (MRR), radial overcut (ROC), circularity, and taper angle (TA). Later an adaptive neuro-fuzzy inference system (ANFIS) model has been developed and shown the effectiveness of the developed model in the paper. The Sugeno fuzzy model has been used in ANFIS to generate the fuzzy rules required for the model. Out of 27 experiments, 22 machining data are used for training the model, and the remaining 5 machining data are used for testing the developed model. The average error observed between the ANFIS predicted values and experimental values of MRR is 12.56%, circularity is 43.09%, ROC is 13%, and TA is 27.53%, respectively.     

Fuzzy modeling applied to optical and surface properties of a ferrocenylsiloxane polyamide solution

A fuzzy model was designed to predict changes in surface tension and maximum absorbance due to self-assembly in a DMF solution of poly{1,1′-ferrocene-diamide-[1,3-bis(propylene) tetramethyl-disiloxane} as a function of temperature and concentration. The building of fuzzy rule-based inference systems appears as a grey-box because it allows interpretation of the knowledge contained in the model as well as its improvement with a-priori knowledge. The method provides accurate results and increases the efficiency of utilizing the available information in the model. Small mean squared errors (0.0064 for absorbance and 0.79 for surface tension) and strong correlations between experiment and simulated results (0.93 and 0.97, respectively) were found during model validation. The results showed that it is feasible to apply a Mamdani fuzzy inference system to the estimation of optical and surface properties of a ferrocenylsiloxane polyamide solution.     

Studies on nucleation from solution of some analytically important metal chelates-II Nickel dimethylglyoximate

A new direct-mixing and rapid particle-counting system useful for studies on crystal nucleation solution is described. The methods used to calibrate and evaluate the system are reported together with the results obtained during studies on nucleation from solution of nickel dimethylglyoximate. The Volmer-Weber, Becker-D?ring model of the nucleation process is used to correlate the results.     

新的聚类方法综合评价血脂指标

本文结合中心聚类和模糊聚类提出了一个新的聚类方法。该法避免了在迭代过程中出现局部最小问题,并可给出每个样本归入每一类的成分矩阵,因而提供更多的聚类程度的信息。应用这种方法对正常人和冠心病患者的血脂指标进行了综合评价,结果满意。     

Uniformity analysis in nanocrystalline silver thin films using fuzzy inference system

An automatic and efficient technique to analyze the uniformity of nanoscale images using wavelets, feature similarity index measure (FSIM) and fuzzy inference system is reported. It has been successfully tested on scanning electron micrographs of nanocrystalline silver thin films. Thin films are prepared using on‐axis and off‐axis pulse laser deposition (PLD) technique. It is found that the film prepared using on‐axis PLD is more uniformly distributed and has smoother texture compared with that of the off‐axis technique. In order to analyze the images quantitatively, they are transformed to the wavelet domain to extract the localized frequency variations and a uniformity measure is derived using a fuzzy inference system for quantitatively analyzing the uniformity of each image. The surface plot of the FSIM values of the image is found to be an efficient tool for nanoscientists to evaluate the smoothness of the thin film surfaces. This study is expected to help the nanoscientists to understand these nanostructures in detail. Copyright © 2014 John Wiley & Sons, Ltd.