液相-电喷雾质谱法测定PVC玩具中邻苯二甲酸酯类增塑剂

本文采用液相-电喷雾质谱(HPLC-ESIMS)法对聚氯乙烯玩具中的六种邻苯二甲酸酯类增塑剂 (DEHP、DNOP、BBP、DBP、DINP和 DIDP)进行了测定.样品用21的氯仿-甲醇溶液在索氏提取器中浸提, 以乙晴-水为流动相进行梯度淋洗分离, 检测波长为224nm, DEHP、DNOP、BBP、DBP的检出限大约为5×10-6, DINP和DIDP因是其同分异构体的混合物, 峰比较宽, 灵敏度不高, 检出限大约为5×10-5. 本方法适用于PVC儿童用品和玩具中DEHP、DNOP、BBP、DBP、DINP和DIDP等邻苯二甲酸酯增塑剂的测定.     

出口须知

欧洲禁止六类酞酸盐用于玩具生产 欧洲议会近期通过一项法令,禁止六类酞酸盐用于玩具生产．其中DEHP、DBP和BBP（注：均为英文名称）三类产品将全面遭禁,而另外三类（DINP、DIDP和DNOP）产品将被禁止用于可能被儿童放入嘴中的玩具。     

食品塑料包装材料中邻苯二甲酸酯类化合物的GC／MS分析方法

[目的]探讨食品塑料包装材料中邻苯二甲酸酯类化合物的GC/MS测定方法.[方法]采用毛管柱气相色谱-质谱联用仪(GC/MS)的选择离子监测方式(SIM)对样品进行检测.[结果]该方法具有良好的线性相关性,相关系数分别为0.9998(DBP),0.9998(BBP),0.9997(DEHP),1.0(DINP),0.998(DNOP),0.9999(DIDP),回收率分别为82.3%～90.1%(DBP)、79.6%～87.8%(BBP)、87.2%～96.2%(DEHP)、80.4%～88.6%(DINP)、79.5%～86.5%(DNOP)和98.4%-108%(DIDP),变异系数均小于10%(n=3).[结论]该方法操作简便、快捷,可靠,灵敏度高.     

气相色谱-质谱法分析玩具PVC塑料中的邻苯二甲酸酯增塑剂

[目的]研究开发针对PVC玩具中包括欧盟指令1999/815/EC禁用的DBP、BBP、DEHP、DNOP、DINP、DIDP在内的8种增塑剂的GC/MS测定方法.[方法]采用二氯甲烷做萃取剂,用溶剂抽提仪在两个小时内实现快速增塑剂提取,采用总离子流色谱(TIC)和选择离子色谱(SIM)测定增塑剂含量.[结果]解决了含多种同分异构体的DINP、DIDP与DNOP之间色谱峰重叠的问题,具有较好的线性关系及回收率.[结论]可满足欧盟法规的检测限要求.     

安捷伦推出食品原物料与成品中13种增塑剂（Phthalate）快速检测方法

安捷伦最近推出利用超高灵敏的分析工具一快速液相串联质谱仪进行微量分析方法。快速液相色谱串联质谱仪可以减少系统背景干扰与溶剂使用量,同时搭配简单萃取与稀释的样品前处理方法,可以同时分析13种邻苯二甲酸酯类：DMP、DEP、DAP、DPP、DBP、BBP、DCP（Dicyclohexy!phthalate）、DNHP、DEHP、DEHA、DNOP、DINP和DIDP。本方法快捷、准确是解决大批量样品,高通量分析的最佳方法。     

出口导航

欧盟或将颁布四类邻苯二甲酸盐禁令继日本、瑞典、加拿大、印度等国纷纷修改邻苯二甲酸盐的限制措施后,丹麦向欧洲化学品管理局(ECHA)提交了一份关于建议欧盟市场全面禁止含邻苯二甲酸二-2-乙基己酯(DEHP)、邻苯二甲酸丁苄酯(BBP)、邻苯二甲酸二丁酯(DBP)及邻苯二甲酸二异丁酯(DIBP)4类物质的议案。     

食品包装材料中邻苯二甲酸酯增塑剂残留的检测

针对食品包装材料中邻苯二甲酸酯（PAEs）增塑剂残留,采用加速溶剂萃取（ASE）和GC／MS联用技术分析5种PAEs（DMP,DEP,DBP,BBP,DEHP）,结果表明加速溶剂萃取用于食品包装材料中PAEs的提取,最佳温度条件为120℃,最佳循环次数为3次。方法检出限达到0．1mg／kg．回收率达到95．5％-99．8％;并且具有很好的重现性和精密度。     

粮谷中熏蒸剂残留量的气相色谱测定

采用通过改进了的Bielorai蒸馏提取器，建立了粮谷中熏蒸剂残留量的气相色谱测定方法。本方法提高了低沸点熏蒸剂的回收率。结果表明熏蒸剂在0．004μg／mL～4．000μg／mL时具有良好的线性关系，相关系数r=0．9999。不同熏蒸剂方法检出限为0．020mg／kg-0．004mg／kg（S／N〉3）。在5个添加水平上进行加标回收试验（n=10），平均回收率为93．37％～98．43％。该方法简单、灵敏、高效、成本低。     

欧盟标准将出台 我儿童用品面临挑战

2007年1月16日起,欧盟最新颁布的关于邻苯二甲酸盐的新指导标准(第2005/84/EC)将开始执行。该标准将取代欧盟各成员国实施的不同的对邻苯二甲酸盐的强制执行标准,并取代欧盟以前实施的临时措施。根据新标准要求,DEHP(邻苯二甲酸二己酯)、DBP(邻苯二甲酸二丁酯)和BBP(邻苯二甲酸     

液相色谱-质谱／质谱法测定牛奶和奶粉中地塞米松残留量

本文建立了一种测定牛奶和奶粉中地塞米松残留量的液相色谱-质谱／质谱方法。样品用乙腈提取,C18固相萃取柱净化,液相色谱-质谱／质谱仪测定,采用基质匹配外标曲线法定量。在2．0—400ng／mL浓度范围内呈良好线性。本方法的测定低限：牛奶为0．2μg／kg,奶粉为1．0μg／kg。牛奶样品在添加浓度0．2-10μg／kg范围内,回收率为70．0％-110．0％;奶粉样品在添加浓度1．0—10μg／kg范围内,回收率范围为65．0％-100．0％。相对标准偏差在8．65％-12．8％之间。     

食用植物油中邻苯二甲酸酯类的污染的风险分析与控制

2014-2015年,通过对235个批次植物油采用GC-MS-MS测定法对邻苯二甲酸酯(下称塑化剂)中的邻苯二甲酸二(2-乙基)己酯(DEHP)、邻苯二甲酸二异丁酯(DINP)和邻苯二甲酸二丁酯(DBP)3项指标残留量进行测定并统计。结果表明,超过限量标准的有49批次,超标率达20.8%。对塑化剂的污染源进行调查研究,认为直接接触油脂的塑料材质是主要污染源。为此提出了控制塑化剂污染的措施,应对包材、原料及生产中使用的塑料类管材等进行控制,从而可有效的解决植物油中的污染问题。     

Analysis of diisononyl phthalate in PVC consumer products used by children

Diisononyl phthalate (DINP) is widely added as a plasticizer in the production of polyvinyl chloride (PVC) used in children’s products. Forty-two plastic products intended for mouthing, or with a high potential for mouthing, by children of age group 0.5-3 years were analyzed for total and leachable phthalate contents. DINP was found in 64% of products tested and its concentration ranged from 3.9 to 44%. Migration of DINP from PVC products into saliva simulant was studied using simulated chewing activity and an Instron Universal Testing Machine. Under the conditions used in this study, the DINP migration rates from teethers and squeeze toys were found to vary from 0.04 to 1.29 µg/10 cm 2 /h. The migration rates show a 40-fold variation within the plastic products tested. However, 83% of the products showed a migration rate of <0.32 µg/10 cm2/h. The mean value was found to be 0.3 µg/10 cm2/h with a distribution median of 0.23 µg/10 cm2/h.     

高效液相色谱法测定禽蛋中的三聚氰胺

本实验建立了禽蛋中三聚氰胺的测定方法。采用高效液相色谱仪,乙腈：（0.01mol/L辛烷磺酸钠和0.01mol/L柠檬酸）=10：90作为流动相,C18色谱柱,检测波长为240nm。结果表明：在0.5-100μg/mL浓度范围,线性关系良好,r=0.9995;变异系数为0.6%;试样测定的相对标准偏差（RSD）〈3%。本法操作简便,测定结果准确。     

决策可靠性分析及在SAR图像目标识别中的应用

决策融合是提高合成孔径雷达（Synthetic Aperture Radar,SAR）目标识别性能的重要手段，然而，可靠性较弱的决策往往会导致最终决策融合的效果变差。将可靠性分析引入基于决策融合的SAR目标识别方法中，分别计算各个决策的可靠性系数并选取可靠性的决策参与最终的决策融合。为了验证方法的有效性，分别将提出的可靠性分析应用于多特征决策融合以及多分类器决策融合并基于MSTAR（Moving and Stationary Target Acquisition and Recognition）数据集进行了目标识别实验。在基于主成分分析、线性鉴别分析和非负矩阵分解三种特征进行多特征决策融合的条件下，所提方法和直接进行决策融合的方法的识别率分别为97.47%和96.50%。在基于K近邻、支持向量机和稀疏表示分类器的多分类器决策融合中，所提方法和直接进行决策融合的方法的识别率分别为97.10%和96.28%。实验结果充分证明了所提方法的有效性。     

Using an ensemble classifier based on sequential floating forward selection for financial distress prediction problem

Financial distress prediction (FDP) is a significant issue investigated by researchers, credit institutions and banks. Although extensive research has been conducted in this area, applications of combined feature selection (FS) methods and classification models are subjects that have been addressed intensely in recent years. One of the most important issues in the FDP problem is to employ an effective FS algorithm, leading to an acceptable level of performance accuracy in the implementation stage. Hence, this study primarily attempted to introduce a precise FS model and compared the obtained results with those of other conventional models tackling FDP in terms of accuracy. The proposed method involved the sequential floating forward selection (SFFS) algorithm applied as a wrapper FS technique to determine the best subset of features. At the classification stage, the support vector machine (SVM), owing to its good performance, demonstrated in numerous studies, in solving classification problems, was deployed. The performance of the proposed method was compared with those of other current well-known FS methods including artificial bee colony (ABC), genetic algorithm (GA) and sequential forward selection (SFS) (all of which are categorized under wrapper methods), and principal component analysis (PCA), relief and information gain (IG) (best known as filter techniques) for our given datasets. The results indicated that a combined model of SVM based on the SFFS approach can yield greater accuracy than the other methods applied for our defined domestic and foreign datasets. Therefore, the SFFS-SVM ensemble classifier can be considered a promising addition to existent models when confronting the FDP issue.     

WATERLESS COOKING – INFLUENCE ON ENERGY CONSUMPTION AND NUTRIENT RETENTION

The purpose of this study was to measure the energy requirements of cooking vegetables in a minimal amount of water (‘waterless’) versus the conventional method of cooking vegetables and to determine the retention of certain vitamins and minerals. The vegetables used were potatoes (tubers), peas (legumes), carrots (roots), and cabbage (leaves). Nutrients analysed were ascorbic acid, thiamin, riboflavin, iron, zinc, and magnesium.     

Assessing Customer Satisfaction in a V-commerce Environment

This article describes the design and implementation of a non-intrusive method of assessing customer satisfaction in a voice-enabled electronic commerce environment. After recording a customer's speech voice during his or her interaction with a voice-enabled Web system (VWS), a subsequent questionnaire survey was immediately administered to identify the satisfaction level of the customer. Afterward, a collection of recorded customer voice files and the corresponding values of customer satisfaction were used to construct an artificial neural network-based expert system, the satisfaction level assessment system (SLAS), which was thereafter integrated into VWS for automatically detecting the satisfaction level of VWS users. Experiments were performed to test the feasibility and applicability of the proposed method, and good preliminary results were derived. Instead of using the conventional questionnaire-based approach, SLAS is non-intrusive because it does not require users to fill out any questionnaire. The proposed method can be used by various voice-based business applications, such as call centers and customer relationship management, to achieve the business objective of improving customer satisfaction, enforcing customer loyalty, increasing re-purchase rate, and enhancing enterprise's benefits. The proposed SLAS (including method and system) that was filed for patent application was recently approved by the Taiwan Intellectual Property Office under Patent No. I268478.     

基于负荷平衡的混合式中继选择新算法

现有的中继选择算法通常带来中继负荷失衡问题,可能导致中继节点资源的非公平利用。为解决这个问题,首先对中继负荷失衡问题进行了分析,接着使用链路信噪比和中继节点负荷作为模糊控制的输入参量,提出了负荷平衡中继选择（LBRS）算法;其次,针对LBRS算法中存在的低信噪比区域误比特率偏高的问题,进一步提出了LBRS的改进算法,即基于负荷平衡的混合式中继选择（HRS）算法。仿真结果表明,与典型的最优中继选择（BRS）算法比较,HRS算法在平衡中继节点负荷上具有非常显著的优势,在误比特率性能上稍逊,总的来说是一种性能优异的中继选择算法。     

ISSR技术用于三种大米的鉴定

使用分子生物学方法,通过构建ISSR分子标记图谱,对地理标志产品增城丝苗米7个品种、马坝油粘米3个品种、盘锦大米5个品种进行分析。结果显示,该方法可完全区分实验所分析的15个品种。