Modeling Growth and Reduction of Microorganisms in Foods as Functions of Temperature and Time

Food safety objectives (FSOs) are established in order to minimize the risk of foodborne illnesses to consumers, but these have not yet been incorporated into regulatory policy. An FSO states the maximum frequency and/or concentration of a microbiological hazard in a food at the time of consumption that provides an acceptable level of protection to the public and leads to a performance criterion for industry. However, in order to be implemented as a regulation, this criterion has to be achievable by the affected industry. In order to determine an FSO, the steps to produce and store that food need to be known, especially where they have an impact on contamination, growth, and destruction. This article uses existing models for growth of Listeria monocytogenes in conjunction with calculations of FSOs to approximate the outcome of more than one introduction of the foodborne organism throughout the food-processing path from the farm to the consumer. Most models for the growth and reduction of foodborne illnesses are logarithmic in nature, which fits the nature of the growth of microorganisms, spanning many orders of magnitude. However, these logarithmic models are normally limited to a single introduction step and a single reduction step. The model presented as part of this research addresses more than one introduction of food contamination, each of which can be separated by a substantial amount of time. The advantage of treating the problem this way is the accommodation of multiple introductions of foodborne pathogens over a range of time durations and conditions.     

People as partners: Facilitating people's participation in public–private partnerships for solid waste management

Cities in developing countries are facing a double dilemma. On one hand, the urban population is growing rapidly, causing a huge increase in demand for waste management services. On the other hand, the traditional public sector is failing to respond to the increased demand for service. The public sector is constrained by resource and institutional limitations. It is often proposed that the solution lies in private sector participation. It is expected that the private sector, with its dynamism and flexibility, may fill in the service delivery gaps by forming partnership with the public sector. However, a third tier—the people—is often overlooked in the service delivery framework. Citizens can contribute significantly to service delivery. They can support the private sector with payment of service charges. But more importantly, they can play an active role in improving accountability and service quality of both public and private sector. This radical shift in people's role, from passive service receivers to active service partners, however, may not occur endogenously. External help from facilitating agencies may enable the public and private sector to form partnership with people for better service delivery. This article examines the role of facilitating agencies in developing tripartite partnership for solid waste management service in Bangladesh. The key lessons learned are: a number of obstacles prevented spontaneous partnership among the public sector, private sector and people; facilitating agencies were able to overcome the obstacles to form partnership of the three; and, the tripartite arrangement resulted in higher accountability and better service delivery.     

Using unlabelled data to update classification rules with applications in food authenticity studies

Summary.  An authentic food is one that is what it purports to be. Food processors and consumers need to be assured that, when they pay for a specific product or ingredient, they are receiving exactly what they pay for. Classification methods are an important tool in food authenticity studies where they are used to assign food samples of unknown type to known types. A classification method is developed where the classification rule is estimated by using both the labelled and the unlabelled data, in contrast with many classical methods which use only the labelled data for estimation. This methodology models the data as arising from a Gaussian mixture model with parsimonious covariance structure, as is done in model-based clustering. A missing data formulation of the mixture model is used and the models are fitted by using the EM and classification EM algorithms. The methods are applied to the analysis of spectra of food-stuffs recorded over the visible and near infra-red wavelength range in food authenticity studies. A comparison of the performance of model-based discriminant analysis and the method of classification proposed is given. The classification method proposed is shown to yield very good misclassification rates. The correct classification rate was observed to be as much as 15% higher than the correct classification rate for model-based discriminant analysis.     

A Review of the High-Level Nuclear Waste Repository Siting Analysis

We critique two 1986 Department of Energy reports concerning the selection of sites for characterization as the nation's first high-level nuclear waste repository. We find that the multiattribute utility analysis of the five nominated sites was well done, although we express concern about the assessed probabilities, question the construction of two important attribute scales, and disagree with some of the value tradeoffs that were used. In contrast, we find the logic of the recommendations report to be weak and unconvincing.     

Attitudes Toward Managing Hazardous Waste: What Should Be Cleaned Up and Who Should Pay for It?

Hazardous waste policy in the United States uses a liability-based approach, including strict, retroactive, and joint and several liability. To assess attitudes toward these basic principles of liability, and toward priorities for clean-up of wastes, a questionnaire was mailed to legislators, judges, executives of oil and chemical companies, environmentalists, and economists. The questionnaire consisted of abstract, simplified cases, which contrasted basic principles rather than dealing with real-world scenarios. Subjects were asked how they would allocate clean-up costs between companies and government as a function of such factors as adherence to standards, adoption of best available technology (BAT), and influence of penalties on future behavior. Most subjects felt that, if the company followed government standards or used the best available technology (BAT), it should pay for only a portion of the clean-up cost, with the government paying the rest. In general, responses did not support the principles underlying current law–strict, retroactive, and joint-and-several liability. Most subjects were more interested in polluters paying for damages than in deterrence or future benefit–even to the extent that they would have "harmless" waste sites cleaned up. A bias was found toward complete clean-up of some sites, or "zero risk." Different groups of subjects gave similar answers, although more committed environmentalists were more willing to make companies pay and to clean up waste regardless of the cost.     

社会学视域中的电子废弃物回收再利用问题——以呼和浩特市为例

随着社会经济的发展,我国电子废弃物的产生量和废弃量呈现逐年递增的趋势,如何有效地变废为宝及减少电子废弃物对环境的污染,引起了人们越来越多的关注。将呼和浩特市作为一个研究案例,分析其电子废弃物回收再利用的主要现状及影响,并尝试从环境社会学的角度提出能够促进电子废弃物合理、高效回收再利用的建议。     

华中抗日根据地建设廉洁政治之实践与启示

抗日战争时期,华中抗日根据地根据党中央提出的＂建立廉洁政府＂的政治纲领,进一步建立与健全法律制度,加强干部队伍的思想、作风建设,实行以法治为基础的综合治理,为党的反腐倡廉建设积累了丰富的经验,与贪污腐败的国民党政权形成了鲜明的对比。     

凉山彝区幼儿园本土课程资源的开发与利用研究 ——以凉山彝区“一村一幼”辅导员的玩教具制作为例

针对凉山彝区幼儿园本土课程资源的开发与利用,重点阐述了玩教具制作的重要意义及五大领域玩教具制作的主要原 则、方法与途径,目的在于充分调动辅导员的主观能动性,利用本土资源及安全无害的废旧材料制作出适合本地幼儿的玩教 具,满足彝区幼儿园玩教具缺乏的需要,从而提升其教育教学质量,助力彝区脱贫奔康。     

生态文明视域下农村生活垃圾的防治——基于四川省巴中市平昌县的调研数据

基于对四川省平昌县农村生活垃圾污染现状的调研,分析农村生活垃圾对自然环境、农产品质量、居民身体健康的影响。调研结果显示,当前农村生活垃圾污染防治存在的问题主要是：农村居民环境保护意识差、农村环境保护法律法规制度不健全、环境执法监管部门监督缺失、农村环境卫生基础设施建设严重滞后等。为了有效防治农村生活垃圾污染,推进农村生态文明体系建设,需要充分发挥制度优势加强生态文明理念宣传教育,促使农村居民养成绿色消费的生活习惯,完善农村环境保护法律法规体系,发挥村委会对农村环境保护的监督作用,加快农村环境保护基础设施建设,大力发展生态农业经济等。     

New Prediction Interval and Band in the Nonlinear Regression Model: Application to Predictive Modeling in Foods

This article is concerned with the proposal of a new prediction interval and band for the nonlinear regression model. The construction principle of this interval and band is based on an exact (the meaning of the term “exact” will be given later) confidence region for parameters of the nonlinear regression model. This region, fully described in Vila and Gauchi (2007 Vila , J.-P. , Gauchi , J.-P. ( 2007 ). Optimal designs based on exact confidence regions for parameter estimation of a nonlinear regression model . Journal of Statistical Planning and Inference 137 ( 9 ): 2935 – 2953 .[Crossref], [Web of Science ®] , [Google Scholar]), provides a rigorous justification for the new prediction interval and band that we propose. This new band is then compared to the classical bands (which are asymptotic and thus approximate for small n), and also to the band based on the bootstrap resampling method. The comparison of these bands is undertaken with simulated and real data from predictive modeling in food science.