Risk assessment and ranking of pesticide residues in Chinese pears

The presence of pesticide residues in pears is a serious health concern. This study presents the results from a 2-year investigation （2013-2014） that used gas chromatography, GS/MS and UPLC/MS-MS to measure the levels of 104 pesti- cides in 310 pear samples. In 93.2% of the samples, 43 pesticides were detected, of which the maximum residue levels （MRLs） were exceeded in 2.6% of the samples. Multiple residues （two to eight compounds） were present in 69.7% of the samples; one sample contained nine pesticides and one sample contained 10. Only 6.8% of the samples did not contain residues. To assess the health risks, the pesticide residue data have been combined with daily pear consumption data for children and adult populations. A deterministic model was used to assess the chronic and acute exposures based on the Joint Meeting on Pesticide Residues （JMPR） method. A potential acute risk was demonstrated for children in the case of bifenthrin, which was found to be present at 105.36% of the acute reference dose （ARfD） value. The long- term exposure of the Chinese consumer to pesticide residues through the consumption of raw pears was far below the acceptable daily intake （ADI） criterion. Additionally, the matrix ranking scheme was used to classify risk subgroups of pesticides and pear samples. In general, 95.5% of samples were deemed to be safe and nine pesticides were classified as being of a relatively high risk. The findings indicated that the occurrence of pesticide residues in pears should not be considered a serious public health problem. Nevertheless, a more detailed study is required for vulnerable consumer groups, especially children. Continuous monitoring of pesticides in pears and tighter regulation of pesticide residue standards are recommended.

Study of Multistage Project Risk Identification-Assessment Process Based on Objective Orientation

Risk management of projects is about the real time ev aluation and making of decisions proactively in order to maximize the probabilit y of achieving or surpassing the targets set for project objectives. Project objective generally includes three elements: time, cost, quality. Risk occurrin g in the projects will affect these three factors to some various degrees in the end. There are different emphases in each stage and integrated balanced goals b etween the three factors. A large complex engineering project generally consists of several stages each of which has variable objective combinations leading to variable important risks. In order to achieve strategic goals on the schedule under the restriction of lim ited resources, the paper gives the analysis of the so-called risk identificati on-assessment process on the basis of objective orientation. In this paper the set of involved mostly hazards is presented in terms of given objective weight v ector, and so is the model of risk ranking .By reducing the range of risk factor s step by step, risk manager could pay more attention to important ventures and effectively control of them. According to different objective combination at different stages, primary risk f actor sets at different stages are given. With the probability and their various effects to project objectives, evaluation of these sets is made aiming to r educing of the scope of risks and providing decision maker with a better decisio ns support. Successful projects are those, which focus on the relevant business objectives t hroughout the whole process and seek to information integration across project l ife cycle. This paper also introduces the idea of real time process of risk iden tification-assessment and presents a flow chart as a demonstration.

Which metal represents the greatest risk to freshwater ecosystem in bohai region of china?

Metals discharged from industrial effluents,agricultural wastewater,and sewage runoff by rapid urbanization are of concern as contaminants of freshwater ecosystem because of their persistence and high toxicity to aquatic organisms.This study attempted to identify which metal posed the greatest risk to freshwater ecosystem in the Bohai Region,China.The metals arsenic(As),cadmium(Cd),chromium(Cr),copper(Cu),zinc(Zn),lead(Pb),nickel(Ni),mercury(Hg),iron(Fe),and manganese(Mn)were compared against norfloxacin and gamma-hexachlorocyclohexane(lindane).By comparing the median reported environmental and ecotoxicity concentrations,it showed that Cu,Fe,Zn,Mn,and Cr were the top five metals of concern.Of these,Cu was deemed to represent the highest risk and Hg the lowest risk.The risks for all metals were higher than those for norfloxacin and lindane.Almost all the metals except Hg had water concentrations that exceeded levels where ecotoxicity effects had been recorded in the literature.A comparison with the measurements across the UK rivers suggested that all metals examined had water concentrations about 5-to 10-fold higher than the UK median values except for Cu,Fe,Cd,and Pb.The Fuyang River,a tributary of the Haihe River Basin,seemed to be the location with the highest metal concentrations.However,comparing the post-2010 period to 2000-2009,concentrations of all the metals had fallen except for Fe and Mn,so risks have decreased over the last 7 yr with the greatest improvements for Cd and Pb.While metals still pose high risks to freshwater ecosystem in this region,there is encouragement that some control measures are taken into effect.

Degrees of freedom in low rank matrix estimation

The objective of this paper is to quantify the complexity of rank and nuclear norm constrained methods for low rank matrix estimation problems. Specifically, we derive analytic forms of the degrees of freedom for these types of estimators in several common settings. These results provide efficient ways of comparing different estimators and eliciting tuning parameters. Moreover, our analyses reveal new insights on the behavior of these low rank matrix estimators. These observations are of great theoretical and practical importance. In particular, they suggest that, contrary to conventional wisdom, for rank constrained estimators the total number of free parameters underestimates the degrees of freedom, whereas for nuclear norm penalization, it overestimates the degrees of freedom. In addition, when using most model selection criteria to choose the tuning parameter for nuclear norm penalization, it oftentimes suffices to entertain a finite number of candidates as opposed to a continuum of choices. Numerical examples are also presented to illustrate the practical implications of our results.