不同产地西瓜农药残留分析与膳食风险评估

为明确不同产地西瓜农药残留状况,区分不同产区残留农药不同之处,本研究以新疆、山东、广西80个西瓜样品为研究对象,明确其60种农药残留水平的基础上,通过英国兽药委员会兽药残留风险排序方法对三产地西瓜残留农药进行排序、比较,并通过急性、慢性膳食摄入风险对其安全水平进行评估。结果显示:三产地共检出11种农药残留,新疆、山东、广西西瓜中残留农药种类分别为6、7、8种,且残留水平不同,检出农药风险得分也不同,其中广西检出的农药三唑磷、敌敌畏、咪鲜胺、苯醚甲环唑(24.60、24.60、18.30、18.15),山东检出的农药苯醚甲环唑、丙溴磷(18.50、18.10),新疆检出的农药农药苯醚甲环唑(18.20)风险得分相对较高。对检出农药进行急性、慢性膳食摄入风险结果显示西瓜中所有残留农药其%ADI、%ARf D值分别在0.01%～1.53%、0.03%～23.30%之间不等,其结果远小于100%。三地区样品中检出农药残留种类、残留水平、风险得分不同,需要根据产区重点关注相应农药,但残留农药水平属于安全限量内。     

Comparison of discriminability of common food acceptance scales for the elderly

This study was aimed to compare four commonly used methods for evaluating consumer acceptance (the 5-point and the 9-point hedonic scales) and preference (the ranking scale and the best-worst scaling) in terms of their ability in discriminating samples and perceived ease of use by the elderly. Elderly (n = 100) and young adult (n = 100) consumers participated in this study. Each consumer evaluated five commercial orange juice samples in duplicate for hedonic rating and preference rank separately and then evaluated ten sets of three samples for the best-worst scale, following the balanced incomplete block design. Nonparametric tests were employed as normality of data was violated. A significant sample effect was observed in all four methods (P < .001). Discriminating power of the best-worst scaling was more pronounced in the elderly than in the young adults; however, the best-worst scaling was easy to use for the young adults than for the elderly.     

An evolved VIKOR method for multiple-criteria compromise ranking modeling under T-spherical fuzzy uncertainty

The development of T-spherical fuzzy (T-SF) sets in qualitative multiple-criteria choice analysis has been well investigated, but little is explored about how the VIKOR (i.e., VIšekriterijumsko KOmpromisno Rangiranje in Serbian) mechanism is generalized into intricate T-SF environments. This paper has the objective of propounding a creative T-SF VIKOR methodology for compromise ranking modeling in multiple criteria analysis. The exploitation of the T-SF configuration brings about superior information space representation in response to intricate realistic environments. However, because of the increased complexity of decision situations involving T-spherical fuzziness, treatment with the T-SF information arises a pragmatic difficulty in developing methodological approaches to T-SF VIKOR. In light of this concern, this paper unfolds an analytical framework for the T-SF VIKOR method predicated on new notions of an evolved T-SF score function and the Minkowski-type T-SF distance measure along with its special cases of the Manhattan-, Euclidean-, and Chebyshev-type distances. The aspired and despised T-SF characteristics can be identified supported by the evolved T-SF score function of T-SF performance ratings. This paper gives a new delineation of the group utility, individual regret, and joint generalized measures with the aid of the Minkowski-type T-SF distance measure relative to the aspired/despised T-SF characteristics. A synthetic mechanism is built to validate the standards of acceptable advantage and stability and yield the ultimate compromise choices for multiple criteria decision aiding. The practicality of the T-SF VIKOR methodology in down-to-earth decision situations has been well demonstrated through the selection issues of warehouse locations and advertisement strategies. Moreover, the developed approach has shown better application outcomes than the past methods did. The comparative study with parametric analysis has revealed the steadiness and effectiveness of the compromise choice results in T-SF circumstances.     

The 9‐point hedonic scale and hedonic ranking in food science: some reappraisals and alternatives

The 9‐point hedonic scale has been used routinely in food science, the same way for 60 years. Now, with advances in technology, data from the scale are being used for more and more complex programs for statistical analysis and modeling. Accordingly, it is worth reconsidering the presentation protocols and the analyses associated with the scale, as well as some alternatives. How the brain generates numbers and the types of numbers it generates has relevance for the choice of measurement protocols. There are alternatives to the generally used serial monadic protocol, which can be more suitable. Traditionally, the ‘words’ on the 9‐point hedonic scale are reassigned as ‘numbers’, while other ‘9‐point hedonic scales’ are purely numerical; the two are not interchangeable. Parametric statistical analysis of scaling data is examined critically and alternatives discussed. The potential of a promising alternative to scaling itself, simple ranking with a hedonic R‐Index signal detection analysis, is explored in comparison with the 9‐point hedonic scale. © 2014 Society of Chemical Industry     

Multi-criteria ranking and receptor modelling of airborne fine particles at three sites in the Pearl River Delta region of China

The multi-criteria decision making methods, Preference Ranking Organization METHods for Enrichment Evaluation (PROMETHEE) and Graphical Analysis for Interactive Assistance (GAIA), and the two-way Positive Matrix Factorization (PMF) receptor model were applied to airborne fine particle compositional data collected at three sites in Hong Kong during two monitoring campaigns held from November 2000 to October 2001 and November 2004 to October 2005. PROMETHEE/GAIA indicated that the three sites were worse during the later monitoring campaign, and that the order of the air quality at the sites during each campaign was: rural site > urban site > roadside site. The PMF analysis on the other hand, identified 6 common sources at all of the sites (diesel vehicle, fresh sea salt, secondary sulphate, soil, aged sea salt and oil combustion) which accounted for approximately 68.8 ± 8.7% of the fine particle mass at the sites. In addition, road dust, gasoline vehicle, biomass burning, secondary nitrate, and metal processing were identified at some of the sites. Secondary sulphate was found to be the highest contributor to the fine particle mass at the rural and urban sites with vehicle emission as a high contributor to the roadside site. The PMF results are broadly similar to those obtained in a previous analysis by PCA/APCS. However, the PMF analysis resolved more factors at each site than the PCA/APCS. In addition, the study demonstrated that combined results from multi-criteria decision making analysis and receptor modelling can provide more detailed information that can be used to formulate the scientific basis for mitigating air pollution in the region.     

Prioritization of chemical hazards in spices and herbs for European monitoring programs

Monitoring programs are preferably risk-based, which allows focusing on the most relevant human health risks. In this study, a risk matrix was used to identify those chemical hazards that have the highest human health risk for the following spices and herbs: paprika/chilli powder, black pepper, nutmeg, basil, thyme, and parsley. Both the probability of occurrence and the severity of the hazard were assessed for 36 chemical compounds and classified into low, medium, high, and severe. Probability of occurrence was evaluated based on available monitoring data and RASFF notifications as well as possibilities for economic adulteration. Severity was assessed based on available toxicological reference values and classification of carcinogenicity. The results demonstrated that the mycotoxins aflatoxins and ochratoxin A, the pesticides chlorpyrifos and triazophos, and the dye Sudan I posed the highest human health risk for spices and herbs. These compounds should, therefore, have an increased monitoring frequency in these products.     

Human uncertainty in explicit user feedback and its impact on the comparative evaluations of accurate prediction and personalisation

ABSTRACT

In this article, we report on the lack of reliability of explicit user feedback and its interpretation in the light of system evaluation. It is known, that given feedback strongly depends on the situational context. But also when many contextual factors are held constant, user feedback still proves to be unreliable. This impacts the evaluation of predictive algorithms since it is not clear whether a deviation between a user response and its corresponding prediction can be seen as a flaw by the system or just as usual ‘human uncertainty’. As a result, the perspective on the evaluation of adaptive systems basically changes. The main goal of this article is to demonstrate that simply increasing the amount of explicit feedback is not the key to sustainable system design innovation, as long as that information is not appropriately evaluated. To this end, we will exploit a novel probabilistic approach of processing user feedback and identify biasing effects on accuracy metrics, error probabilities for system rankings as well as natural limitations of evaluation. Finally, we will discuss possible solution strategies and give advice for handling explicit user feedback that is associated with uncertainty.     

New doctors ranking system based on VIKOR method

Nowadays, we can use different websites that help us make decisions about various aspects of our lives. However, privacy protection prevents websites from providing personalised guidelines to users. We propose a novel doctor‐ranking system (DRS) based on multi‐criteria group decision‐making (MCGDM) method to address the problems of privacy protection. The following aspects differentiate our proposed DRS model from previous works: (a) textual information reviews are used to identify user preferences and complementary criteria, (b) criteria weights are determined by term frequency inverse document frequency (TF‐IDF) instead of Delphi method or expert opinion, (c) intuitionistic fuzzy sets (IFSs) are used to replace sentiment analysis to express subjective user criteria, and (d) VIsekriterijumsko KOmpromisno Rangiranjie (VIKOR) method for MCGDM with IFSs is used to solve the doctor‐ranking problem. We apply our proposed model to datasets from Haodf.com to compare the performance of our method with that of sentiment analysis and technique for order performance by similarity to ideal solution (TOPSIS) methods. The experimental results show that our method provides accurate ranking and increases the reliability of DRS.     

Investigation of solar energy utilization for production of hydrogen and sustainable chemical fertilizer: A case study

Renewable energies play a vital role in the economic and social development and progress of many countries. As one of the most significant sources of renewable energy, solar energy has been used due to its availability in many regions. Generating electricity for hydrogen production is one of the applications of solar energy. In petrochemical complexes, hydrogen is often used for producing fertilizers, especially urea fertilizers. The present study aims at investigating five major Iranian petrochemical complexes in terms of their suitability for the construction of a solar plant to produce electrolysis‐based green chemical fertilizers. To this end, a multicriteria decision‐making model is proposed, which includes the fuzzy analytic hierarchy process (AHP) and extended TODIM method of multicriteria decision making (including crisp, interval, and fuzzy numbers). The present research investigates 10 criteria for prioritizing petrochemical complexes, classified into four general categories, namely, climatic, geographic, environmental, and probability of natural disaster occurrence categories. Having calculated the weight of the criteria using the fuzzy AHP method, the alternatives are prioritized using the extended TODIM method. The methods of simple additive weighting (SAW), Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), and VIKOR were then used for validation of the results. Results showed that the Shiraz Petrochemical Complex has the highest priority and Khorasan Petrochemical Complex has the lowest priority for producing green fertilizer via solar energy–assisted water electrolysis. By using the solar system, Shiraz Petrochemical Complex can emit over 1900 tons less pollutants in the environment per day and provides up to 8% of its annual total production through clean energy.     

Risk-based approach to developing a national residue sampling plan for testing under European Union regulation for veterinary medicinal products and coccidiostat feed additives in domestic animal production

A ranking system for veterinary medicinal products and coccidiostat feed additives has been developed as a tool to be applied in a risk-based approach to the residue testing programme for foods of animal origin in the Irish National Residue Control Plan (NRCP). Three characteristics of substances that may occur as residues in food are included in the developed risk ranking system: Potency, as measured by the acceptable daily intake assigned by the European Medicines Agency Committee for Medicinal Products for Veterinary Use, to each substance; Usage, as measured by the three factors of Number of Doses, use on Individual animals or for Group treatment, and Withdrawal Period; and Residue Occurrence, as measured by the number of Non-Compliant Samples in the NRCP. For both Number of Doses and Non-Compliant Samples, data for the 5-year period 2008–12 have been used. The risk ranking system for substances was developed for beef cattle, sheep and goats, pigs, chickens and dairy cattle using a scoring system applied to the various parameters described above to give an overall score based on the following equation: Potency × Usage (Number of Doses + Individual/Group Use + Withdrawal Period) × Residue Occurrence. Applying this risk ranking system, the following substances are ranked very highly: antimicrobials such as amoxicillin (for all species except pigs), marbofloxacillin (for beef cattle), oxytetracycline (for all species except chickens), sulfadiazine with trimethoprim (for pigs and chickens) and tilmicosin (for chickens); antiparasitic drugs, such as the benzimidazoles triclabendazole (for beef and dairy cattle), fenbendazole/oxfendazole (for sheep/goats and dairy cattle) and albendazole (for dairy cattle), the avermectin ivermectin (for beef cattle), and anti-fluke drugs closantel and rafoxanide (for sheep/goats); the anticoccidials monensin, narasin, nicarbazin and toltrazuril (for chickens). The risk ranking system described is a relatively simple system designed to provide a reliable basis for selecting the veterinary medicinal products and coccidiostat feed additives that might be prioritised for residue testing.