Separation of dissolved iron from the aqueous system with excess ligand

A new technique for the separation and pre-concentration of dissolved Fe(III) from the ligand-rich aqueous system is proposed. A solid phase extraction (SPE) system with an immobilized macrocyclic material, commonly known as molecular recognition technology (MRT) gel and available commercially, was used. Synthetic Fe(III) solution in aqueous matrices spiked with a 100-fold concentration of EDTA was used. Dissolved iron that was ‘captured’ by the MRT gel was eluted using hydrochloric acid and subsequently determined by graphite furnace atomic absorption spectrometry. The effect of different variables, such as pH, reagent concentration, flow rate and interfering ions, on the recovery of analyte was investigated. Quantitative maximum separation (∼100%) of the dissolved Fe(III) from synthetic aqueous solutions at a natural pH range was observed at a flow rate of 0.2 mL min^-1. The extraction efficiency of the MRT gel is largely unaltered by the coexisting ions commonly found in natural water. When compared with different SPE materials, the separation performance of MRT gel is also much higher.     

In silico prediction of Tetrahymena pyriformis toxicity for diverse industrial chemicals with substructure pattern recognition and machine learning methods

There is an increasing need for the rapid safety assessment of chemicals by both industries and regulatory agencies throughout the world. In silico techniques are practical alternatives in the environmental hazard assessment. It is especially true to address the persistence, bioaccumulative and toxicity potentials of organic chemicals. Tetrahymena pyriformis toxicity is often used as a toxic endpoint. In this study, 1571 diverse unique chemicals were collected from the literature and composed of the largest diverse data set for T. pyriformis toxicity. Classification predictive models of T. pyriformis toxicity were developed by substructure pattern recognition and different machine learning methods, including support vector machine (SVM), C4.5 decision tree, k-nearest neighbors and random forest. The results of a 5-fold cross-validation showed that the SVM method performed better than other algorithms. The overall predictive accuracies of the SVM classification model with radial basis functions kernel was 92.2% for the 5-fold cross-validation and 92.6% for the external validation set, respectively. Furthermore, several representative substructure patterns for characterizing T. pyriformis toxicity were also identified via the information gain analysis methods.     

基于模糊模式识别的系统安全模糊综合评价

针对模糊综合评价的不足之处,提出把权广义距离之和模糊模式识别运用到模糊综合评价当中,建立了基于模糊模式识别的模糊综合评价模型.通过对陕西某高层建筑火灾危险评价实例证明,该模型能使系统安全评价结果更准确、合理.     

Selective separation of deltamethrin by molecularly imprinted polymers using a β-cyclodextrin derivative as the functional monomer

A deltamethrin-imprinted polymer (MIP₁) was prepared using bis(-6-O-butanediacid monoester)-β-cyclodextrin (BBA-β-CD) as the functional monomer and toluene 2,4-diisocyanate (TDI) as the cross-linker. In comparison to the molecularly imprinted polymer where β-CD was applied as the functional monomer (MIP₂), MIP₁ showed a higher specific binding capacity (ΔC_P) and an improved imprinting factor (IF) for deltamethrin. The selective recognition experiments demonstrated that compared to MIP₂, MIP₁ could better recognize its template over other substrates that had similar chemical structures. The solid phase extraction (SPE) of deltamethrin using MIP₁ as the adsorbent was further investigated. The recoveries of the molecularly imprinted solid phase extraction (MISPE) column for deltamethrin were 83.2–93.4% with relative standard deviations (RSD) of 2.03–6.19%. The method has been successfully applied to the enrichment of trace deltamethrin from real water samples.     

成本效益、政策认知与农村居民点整理农户补偿满意度研究

政策执行是政策目标实现的重要环节,政策执行的本质是主体之间考虑利益得失的利益博弈过程,利益推动行为主体执行或违反政策。农户是农村居民点整理的直接利益主体,农户自身利益需求与补偿政策的差异表现为补偿满意度,明晰农户补偿满意度影响因素,对解决农户利益需求缺位,提高农村居民点整理政策执行效率意义重大。本文在理论分析农村居民点整理农户补偿满意度影响因素的基础上,结合典型区域扬州市刘集镇农户补偿满意度调查,应用有序Logit模型,分析个人特征、家庭特征、成本效益及政策认知等因素对农村居民点整理农户补偿满意度的影响。研究结果表明:(1)农户补偿满意度受其自身和家庭禀赋特征影响,家庭劳动力人数较多、非农就业为主的农户,对农村土地的依赖性较低,补偿满意度会相应提升。(2)农户补偿满意度受成本效益因素显著影响,提高耕作便捷度、改善出行交通,会降低通勤成本,增加受益感知,进而提高农户补偿满意度;而日常消费上升、原有宅基地面积较大,会增加农户参与整理的成本投入,降低农户补偿满意度。(3)农户补偿满意度受政策认知因素明显影响,正面的政策制定评价、较高的政策执行满意度及农民收入增加的价值认同,均将提高农户补偿满意度。因此,应合理评估宅基地价值,重视农村居民点整理政策的长期影响评价,综合考量农村居民点整理政策实施前后农户的总成本和综合效益确定合理的补偿标准,以优化利益分配格局。并通过推进配套制度改革完善、规范政策执行机制等措施提高整理区农户的社会福利及政策认同。     

基于AlphaPose与REBA的手工搬运作业姿势风险评估方法

为有效预防职业性肌肉骨骼疾患(WMSDs),提出基于计算机视觉技术与快速全身评估(REBA)结合的作业姿势评估方法,以手工搬运作业为例,通过人体姿态识别AlphaPose模型检测作业姿势,利用提取的各关节点空间位置信息计算身体各部位关节角度;利用SG滤波法处理身体遮挡、光线等对数据的影响,有效保留数据变化信息的同时消除数据突变;根据身体关节角度范围与危害程度对应关系自动评判作业姿势的风险大小。研究结果表明：作业姿势评估方法可通过采集的视频数据自动评估搬运作业的姿势危险性,降低WMSDs风险,通过分析不同下蹲取物姿势风险,可论证作业姿势评估方法的可行性,为及时改善搬运作业中的不安全动作提供参考。     

基于未确知测度理论的安全生产状况评价研究

为研究我国省市的安全生产级别,基于未确知测度理论,建立安全生产状况评价的等级模型。根据实际情况,选取5项评价指标,建立各评价指标的未确知测度函数。利用熵确定各项指标的权重,避免人为主观性对评价的影响,根据多指标综合测度评价向量和置信度识别准则进行评判。结合2009年9省市对应指标统计数据,采用未确知理论对安全生产状况进行评价,并结合实际进行分析。该理论为省、市安全生产提供了指导性的建议和依据。     

属性识别理论模型应用于土壤重金属污染评价

土壤重金属污染评价是土壤环境质量评价研究的重要组成部分。基于模糊数学理论建立的属性识别理论模型在其他环境要素评价中已有所应用,现将其应用到土壤重金属污染评价中。该法能较好地把握土壤环境质量各级标准界限的模糊性,并继承了模糊数学方法本身在评价领域应用的优点,实际操作较为简便。为较客观地反映评价因子对土壤环境质量的影响,模型中引入重金属生物有效性的概念与传统权重系数确定法相结合构造各指标权重。该模型评价结果基本上与其他评价方法的结果相一致,并能较为客观地反映出土壤环境的污染状况。     

自然灾害的模糊识别模型及其应用

自然灾害是各种模糊因素综合作用的结果,模糊集理论与方法是评价自然灾害的重要手段。本文提出应用模糊识别模型进行自然灾害评价,以洪水灾害为例,将模糊识别结果同灰色关联度模型的评价结果进行了分析比较,结果表明,模糊识别结果比灰色关联度模型结果更客观、更符合实际。     

基于无人机的施工扬尘污染源自动监测系统设计与实现

施工扬尘是大气污染物的主要来源和施工环境监测的重点对象,但传统监测手段的效率和效果有限。为此,综合使用无人机和图像识别技术,以HSV特征提取、直方图对比、非零像素点计算为核心,设计了施工扬尘污染源自动监测系统的结构、功能及运行流程,并对运行效果进行了测试。研究和测试表明:该系统可实现监测区航拍、污染源特征提取、污染源存在性检验、污染源种类判定和污染源分布区面积计算;该系统污染源存在性检验正确率为71%,污染源面积计算效率较高,污染源特征比对效果相对稳定,基本满足施工扬尘污染源监测需求。