浅谈食品检验检测的质量管理措施

随着食品产业链全球化的推进,食品检验检测质量管理面临日益严峻的挑战。近年来,国家通过推动先进设备普及、优化数据管理和系统化培训等多项措施,为食品安全构筑了有力的保障。以2020年颁布的《国家食品安全抽样检验工作规范》为例,政府明确要求各类食品样品的检验检测“精准、科学、可追溯”,这不仅凸显了食品质量管理的精细化要求,也表明数据管理的重要性。在多重政策的推动下,我国食品检验检测水平已实现质的飞跃,但面对复杂的市场环境和新兴食品安全问题,仍需进一步加强相关的质量管理工作。

曳引式电梯轮槽磨损及其检验检测探析

在电梯安全运行的过程中,应当加强电梯日常检验和检测工作,尤其是对曳引式电梯轮槽磨损情况的检验和检测工作.曳引式电梯轮槽是电梯安全运行过程中,重要的保护屏障.本文将曳引式电梯轮槽磨损带来的影响和安全隐患作为重点阐述对象,对其检验和测验的方式进行筒要的分析,在最大程度上保证电梯的安全运行.

Hypothesis testing analysis and unknown parameter estimation of GPS signal detection

Hypothesis testing analysis and unknown parameter estimation of both the intermediate frequency(IF) and baseband GPS signal detection are given by using the generalized likelihood ratio test(GLRT) approach,applying the model of GPS signal in white Gaussian noise,It is proved that the test statistic follows central or noncentral F distribution,It is also pointed out that the test statistic is nearly identical to central or noncentral chi-squared distribution because the processing samples are large enough to be considered as infinite in GPS acquisition problem.It is also proved that the probability of false alarm,the probability of detection and the threshold are affected largely when the hypothesis testing refers to the full pseudorandom noise(PRN) code phase and Doppler frequency search space cells instead of each individual cell.The performance of the test statistic is also given with combining the noncoherent integration.

Experimental study on the compressive strength of grouted concrete block masonry based on nondestructive detection methods

Existing nondestructive detection methods were adopted to test the compressive strength of grouted concrete block masonry,i.e.the rebound method,pulling-out method and core drilling method were employed to test the strength of block,mortar and grouted concrete,respectively.The suitability of these methods for the testing of strength of grouted concrete block masonry was discussed,and the comprehensive strength of block masonry was appraised by combining existing nondestructive or micro-destructive detection methods.The nondestructive detection test on 25 grouted concrete block masonry specimens was carried out.Experimental results show that these methods mentioned above are applicable for the strength detection of grouted concrete block masonry.Moreover,the formulas of compressive strength,detection methods and proposals are given as well.

Computational prediction and experimental validation of novel markers for detection of STEC O157:H7

AIM:To identify and assess the novel makers for detection of Shiga toxin producing Escherichia coli (STEC) O157:H7 with an integrated computational and experimental approach. METHODS:High-throughput NCBI blast (E-value cutoff e-5) was used to search homologous genes among all sequenced prokaryotic genomes of each gene encoded in each of the three strains of STEC O157:H7 with complete genomes,aiming to find unique genes in O157:H7 as its potential markers. To ensure that the identified markers from the three strains of STEC O157:H7 can serve as general markers for all the STEC O157:H7 strains,a genomic barcode approach was used to select the markers to minimize the possibility of choosing a marker gene as part of a transposable element. Effectiveness of the markers predicted was then validated by running polymerase chain reaction (PCR) on 18 strains of O157:H7 with 5 additional genomes used as negative controls. RESULTS:The blast search identified 20,16 and 20 genes,respectively,in the three sequenced strains of STEC O157:H7,which had no homologs in any of the other prokaryotic genomes. Three genes,wzy,Z0372 and Z0344,common to the three gene lists,were selected based on the genomic barcode approach. PCR showed an identification accuracy of 100% on the 18 tested strains and the 5 controls. CONCLUSION:The three identified novel markers,wzy,Z0372 and Z0344,are highly promising for the detection of STEC O157:H7,in complementary to the known markers.

Dverview and Main Advances in Permutation Tests for Linear Regression Models

When the population, from which the samples are extracted, is not normally distributed, or if the sample size is particularly reduced, become preferable the use of not parametric statistic test. An alternative to the normal model is the permutation or randomization model. The permutation model is nonparametric because no formal assumptions are made about the population parameters of the reference distribution, i.e., the distribution to which an obtained result is compared to determine its probability when the null hypothesis is true. Typically the reference distribution is a sampling distribution for parametric tests and a permutation distribution for many nonparametric tests. Within the regression models, it is possible to use the permutation tests, considering their ownerships of optimality, especially in the multivariate context and the normal distribution of the response variables is not guaranteed. In the literature there are numerous permutation tests applicable to the estimation of the regression models. The purpose of this study is to examine different kinds of permutation tests applied to linear models, focused our attention on the specific test statistic on which they are based. In this paper we focused our attention on permutation test of the independent variables, proposed by Oja, and other methods to effect the inference in non parametric way, in a regression model. Moreover, we show the recent advances in this context and try to compare them.

Non-Specific Factors Involved in the Treatment： Its Influence on Treatment Adherence

Introduction： The effectiveness of treatment depends on the efficacy of the therapy and the level of compliance of the patient. NF （non-specific factors） involved in treatment are all those effects that do not depend on the pharmacological properties of the drug. Materials and Methods： The job lasted a year. The sample consisted of patients with mental health disorders and was divided into two groups. Treatment compliance was measured with the Morisky-Green Test. Results were compared using the chi square test and relative risk. Results and Discussion： Group A had 23 patients ending 91.3% of them and group B of 22 patients, ending the 77.27%. At the beginning of the study, we found in the group A 0.86 NF/patients while in the group B 0.82 NF/patient. At the end of the study there was a 54.65% decrease in group A while in group B the proportion remained. At the beginning of the study both groups had approximately 40% of compliant patients. Data that remained in the control group rose to 80.95% in group A at the end of the study. Conclusions： The work demonstrates the negative influence of these factors on adherence to treatment.

DID SPECULATIVE ACTIVITIES CONTRIBUTE TO HIGH CRUDE OIL PRICES DURING 1993 TO 2008?

By applying two nonlinear Granger causality testing methods and rolling window strategy to explore the relationship between speculative activities and crude oil prices, the unidirectional Granger causality from speculative activities to returns of crude oil prices during the high price phase is discovered. It is proved that speculative activities did contribute to high crude oil prices after the Asian financial crisis and OPEC＇s output cut in 1998. The unidirectional Granger causality from returns of crude oil prices to speculative activities is significant in general. But after 2000, with the sharp rise in crude oil prices, this unidirectional Granger causality became a complex nonlinear relationship, which cannot be detected by any linear Granger causaIity test.

A NONPARAMETRIC TEST AGAINST AN UMBRELLA ALTERNATIVE FOR STRATIFIED DATA

Trend test in dose-response has been a central problem in medicine. This paper treats the problem of comparing umbrella pattern treatment effects. Under an ordered m × r × k table, this article considers testing the hypothesis that all multinomial populations are conditional independence against the alternative that they are in an umbrella trend. For this hypothesis test problem, this article introduces a model-free test method by using likelihood ratio test statistic and gives the asymptotic distribution of the test statistic. Simulation study is conducted to compare the empirical power per- formed via the proposed method and others. Finally, two real data are studied to illustrate the validity of the proposed method.

SUMMATION OF ABSOLUTE VALUE TEST FOR MULTIPLE OUTCOME COMPARISON WITH MODERATE EFFECT

In biomedical research,in order to evaluate the effect of a drug,investigators often need to compare the differences between one treatment group and another one by using multiple outcomes.The rank-sum tests can handle the case where the outcome differences between two groups are in the same direction.If they are not,MAX can handle it and is very useful when one/some of the differences is/are relatively larger than the others.When the individual outcome difference between two groups is moderate,a new method,summation of the absolute value of rank-based test for each outcome,is proposed in this work.Power comparison with the existing methods based on simulation studies and a real example show that the proposed test is a robust test,and works well when the difference for each outcome is moderate.The authors also derive some theoretical results for comparing the power between MAX and the the proposed method.

Test-driven verification/validation of model transformations

Why is it important to verify/validate model transformations？ The motivation is to improve the quality of the trans- formations, and therefore the quality of the generated software artifacts. Verified/validated model transformations make it possible to ensure certain properties of the generated software artifacts. In this way, verification/validation methods can guarantee different requirements stated by the actual domain against the generated/modified/optimized software products. For example, a verified/ validated model transformation can ensure the preservation of certain properties during the model-to-model transformation. This paper emphasizes the necessity of methods that make model transformation verified/validated, discusses the different scenarios of model transformation verification and validation, and introduces the principles of a novel test-driven method for verifying/ validating model transformations. We provide a solution that makes it possible to automatically generate test input models for model transformations. Furthermore, we collect and discuss the actual open issues in the field of verification/validation of model transformations.

Color change in a marine isopod is adaptive in reducing predation

Although background matching is a common form of camouflage across a wide diversity of animals, there has been surprisingly little experimental work testing the fitness consequences of this camouflage strategy, especially in marine ecosystems. In this study, we tested whether color camouflage enhances survival of the intertidal marine isopod Pentidotea （Idotea） wosnesenskii, quantified patterns of camouflage in different algal habitats, and examined how algal diet affected color change and growth using laboratory assays. In the field, isopods collected from two differently colored algal habitats （the brown alga Fucus distichus and the red alga Odonthaliafloccosa） matched the color of their respective algal habitats, and also differed significantly in body size： smaller red isopods were found on red algae, while larger brown isopods were found on brown algae. Predation ex- periments demonstrated these color differences had fitness benefits： brown isopods that matched their brown algae habitats sur- vived at higher rates than red unmatched isopods. Surprisingly, despite the propensity of isopods to match their algal habitats, algal diet had no effect on color change in color change experiments. Instead, isopods in all treatments turned browner, matching the color of the algal habitat that many isopods are found on as adults. In summary, our data supported our hypothesis that back- ground matching serves an adaptive function in reducing predation, with important evolutionary implications for explaining the wide variation in color change mechanisms in idoteid isopods [Current Zoology 61 （4）： 739-748, 2015].

SAMPLE-SIZE DETERMINATION FOR TWO INDEPENDENT BINOMIAL EXPERIMENTS

Sample size determination is commonly encountered in modern medical studies for two inde- pendent binomial experiments. A new approach for calculating sample size is developed by combining Bayesian and frequentist idea when a hypothesis test between two binomial proportions is conducted. Sample size is calculated according to Bayesian posterior decision function and power of the most powerful test under 0-1 loss function. Sample sizes are investigated for two cases that two proportions are equal to some fixed value or a random value. A simulation study and a real example are used to illustrate the proposed methodologies.

Inspection of reinforced concrete interface delamination using ultrasonic guided wave non-destructive test technique

An ultrasonic-guided wave(UGW) is a very promising tool in the field of structural health monitoring and non-destructive test.Numerical analysis was used to simulate the propagation in the rebar and explore the characteristics of UGW in the steel rebar waveguide.Two-dimensional fast Fourier transform was used to process the numerical results and to evaluate the damage.Subsequently,different UGW test influence factors were investigated.The results clearly showed that both the group velocity and the amplitude of longitudinal modes were not very sensitive to stress and temperature variations.However,the received UGW signal energy decreased with the increasing concrete strength.Finally,the interface condition between the concrete and the rebar was investigated.Time-domain and frequency-domain analyses were used to process the received signals.Different interface delamination lengths of the UGW energy attenuation were analyzed and a relationship was obtained.This study successfully proved that UGW is an effective tool in the non-destructive test of reinforced concrete interface delamination.

GROUP CONTINGENCY TEST FOR TWO OR SEVERAL INDEPENDENT SAMPLES

This paper proposes a new and distribution-free test called ＂Group Contingency＂ test （GC, for short） for testing two or several independent samples. Compared with traditional nonparametric tests, GC test tends to explore more information based on samples, and it＇s location-, scale-, and shapesensitive. The authors conduct some simulation studies comparing GC test with Wilcoxon rank sum test （W）, Kolmogorov-Smirnov test （KS） and Wald-Wolfowitz runs test （WW） for two sample case, and with Kruskal-Wallis （KW） for testing several samples. Simulation results reveal that GC test usually outperforms other methods.