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Selected AbstractsImplementation of quality control methods (physico-chemical, microbiological and sensory) in conjunction with multivariate analysis towards fish authenticityINTERNATIONAL JOURNAL OF FOOD SCIENCE & TECHNOLOGY, Issue 3 2005Ioannis S. Arvanitoyannis Summary Nowadays authenticity of foods and fish in particular has become of crucial importance because of high number of adulteration cases. Authenticity control has gained ground thanks to the development of several rapid physico-chemical and microbiological methods aiming at distinguishing one species from another based on solid scientific evidence. It has been proven that despite the precision and accuracy of robust analytical and protein and DNA-based techniques, detection of authenticity could not be claimed without resorting to multivariate analysis. This review summarizes both the most advanced and state of the art used techniques for detecting fish and seafood authenticity (both in terms of species and geographical origin). Another issue reported in this review is the preservation of fish and seafood through the implementation of old and novel techniques (ice, modified atmosphere packaging). Several informative tables were included in this paper referring to the employed quality control and sensory analysis methods and multivariate analysis for fish and seafood. [source] CURRENT-STATUS SURVIVAL ANALYSIS METHODOLOGY APPLIED TO ESTIMATING SENSORY SHELF LIFE OF READY-TO-EAT LETTUCE (LACTUCA SATIVA)JOURNAL OF SENSORY STUDIES, Issue 2 2008MABEL ARANEDA ABSTRACT The objective of the present work was to develop a method for predicting sensory shelf life for situations in which each consumer evaluates only one sample corresponding to one storage time. This type of data is known as current-status data in survival analysis statistics. The methodology was applied to estimate the sensory shelf life of ready-to-eat lettuce (Lactuca sativa var. capitata cv."Alpha"). For each of six storage times, 50,52 consumers answered yes or no to whether they would normally consume the presented sample. The results were satisfactory, showing that the methodology can be applied when necessary. The Weibull model was found adequate to model the data. Estimated shelf lives ± 95% confidence intervals were 11.3 ± 1.2 days and 15.5 ± 0.9 days for a 25% and a 50% consumer rejection probability, respectively. PRACTICAL APPLICATIONS When considering shelf-life evaluations by consumers, the first idea is to have each consumer evaluate six or seven samples with different storage times in a single session. To do this, a reverse storage design is necessary, and in the case of a product such as lettuce, it would lead to different batches being confused with storage times. The methodology proposed in this article avoids this problem by having each consumer evaluate a single sample. Another issue with consumers tasting several samples in a single session is how representative this situation is of real consumption. The present methodology allows for a consumer to take home, e.g., a bottle of beer with an established storage time, and later collecting the information as to whether they found the beer acceptable or not. This is a situation much closer to real consumption. [source] Robust ship scheduling with multiple time windowsNAVAL RESEARCH LOGISTICS: AN INTERNATIONAL JOURNAL, Issue 6 2002Marielle Christiansen We present a ship scheduling problem concerned with the pickup and delivery of bulk cargoes within given time windows. As the ports are closed for service at night and during weekends, the wide time windows can be regarded as multiple time windows. Another issue is that the loading/discharging times of cargoes may take several days. This means that a ship will stay idle much of the time in port, and the total time at port will depend on the ship's arrival time. Ship scheduling is associated with uncertainty due to bad weather at sea and unpredictable service times in ports. Our objective is to make robust schedules that are less likely to result in ships staying idle in ports during the weekend, and impose penalty costs for arrivals at risky times (i.e., close to weekends). A set partitioning approach is proposed to solve the problem. The columns correspond to feasible ship schedules that are found a priori. They are generated taking the uncertainty and multiple time windows into account. The computational results show that we can increase the robustness of the schedules at the sacrifice of increased transportation costs. © 2002 Wiley Periodicals, Inc. Naval Research Logistics 49: 611,625, 2002; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/nav.10033 [source] Science and Religion: Philosophical IssuesPHILOSOPHY COMPASS (ELECTRONIC), Issue 1 2008Alan G. Padgett An overview of several philosophical issues that arise from the recent growth of interest in the relationships between science (especially natural science) and theology (especially Christian thought). The interactions between theology and science are complex, and often highly contextual in nature. This makes simple typologies of their interaction rather dubious. There are some similarities between religion and science, including the difficulty of defining them. Concerns about the use and meaning of language, and issues of realism and anti-realism, are found in both areas of thought. Epistemology is important to both areas, and there is increasing acceptance of differing epistemologies not only in religion and science, but also within the various scientific disciplines. One central issue is the question of legitimate influence between science and theology given their aims and methods. Another issue surrounds the question of naturalism in natural science. Also important to note is the variety of god-concepts at work in the current dialogue between science and theology. [source] Key issues with implementing LOPAPROCESS SAFETY PROGRESS, Issue 2 2010William Bill Bridges Abstract This article writen by one of the originators of LOPA, focuses on problems observed with LOPA. One the biggest issues is that organizations use LOPA without following the rules for LOPA, especially the rules related to maintaining, testing, and record-keeping for each independent protection layer (IPL) and for each "optimized" initiating event (IE). Another issue is that many companies and analysts overuse LOPA. The LOPA book authors expected the number of scenarios going to LOPA (after a HAZOP/PHA) would be 1 to 10% (max) of those uncovered in a qualitative analysis (maybe after 100 HAZOP nodes, you would do 1,10 LOPA). A PHA team would recommend (or use) LOPA only if the scenario was too complex for the PHA/HAZOP team. It appears that most companies are using LOPA for every scenario that has a severe consequence; this result in doing LOPA on much more than 10% of the scenarios. Many times, there is weak definition of the consequence that is being avoided, so an independent layer of protection does not always match up well with the consequence. LOPA is also overworked when it is used. Many of us on the original LOPA book authorship considered LOPA a single analyst job, after a PHA/HAZOP. Instead, the trend appears to be that companies (or perhaps their consultants) make LOPA part of the PHA (in situ), therefore involving the whole PHA team. LOPA is used in PHA team settings, which distracts PHA teams from their primary task of brainstorming to identify the accident scenarios that can occur. This article focuses on preventing these problems and also summarizes the many benefits LOPA has produced for the industry. © 2010 American Institute of Chemical Engineers Process Saf Prog, 2010 [source] A Bayesian Hierarchical Model for Classification with Selection of Functional PredictorsBIOMETRICS, Issue 2 2010Hongxiao Zhu Summary In functional data classification, functional observations are often contaminated by various systematic effects, such as random batch effects caused by device artifacts, or fixed effects caused by sample-related factors. These effects may lead to classification bias and thus should not be neglected. Another issue of concern is the selection of functions when predictors consist of multiple functions, some of which may be redundant. The above issues arise in a real data application where we use fluorescence spectroscopy to detect cervical precancer. In this article, we propose a Bayesian hierarchical model that takes into account random batch effects and selects effective functions among multiple functional predictors. Fixed effects or predictors in nonfunctional form are also included in the model. The dimension of the functional data is reduced through orthonormal basis expansion or functional principal components. For posterior sampling, we use a hybrid Metropolis,Hastings/Gibbs sampler, which suffers slow mixing. An evolutionary Monte Carlo algorithm is applied to improve the mixing. Simulation and real data application show that the proposed model provides accurate selection of functional predictors as well as good classification. [source] | |||||||||||||