The registered dietitian in primary care: the Hamilton experience.

The Hamilton Health Service Organization Nutrition Program integrates nine registered dietitians (RDs) into the offices of 80 family physicians (FPs) at 50 sites in Hamilton, Ontario. The program is based on a shared care model, in which FPs and RDs work collaboratively to provide nutrition services aimed at prevention, treatment, and management of nutrition-related problems. In addition to their clinical role, dietitians in the program are involved in health promotion, disease prevention and early intervention strategies, interdisciplinary collaboration, building links with community services, and research. The RDs' specialized knowledge, skills, and experience allow them to provide a wide range of services that complement and augment those of the FP. This model is consistent with Canadian health care reform recommendations and offers significant benefits for both health care providers and consumers.     

基于化学成分的大米国家地理标志产品模式识别与分类研究

综合运用主成分分析(PCA)和Fisher准则两类线性判别方法对广东增城丝苗米国家地理标志产品中无机元素成分、有机组成(氨基酸、脂肪、淀粉、蛋白质等)进行模式识别与聚类研究,并采用Fisher线性判别方法建立地标产品与非地标产品间的分类模型。结果表明：Fisher线性判别用于大米地理标志产品的分类与识别简单快速,在分析数据相对复杂的情况下,可快速建立分类模型并实现地理标志产品与非地理标志样本间的鉴定与识别。     

Calculating Quantities of Ice for Cooling and Maintenance of Freshly Harvested Fish at Sea

Abstract: A new generalized model for predicting quantities of ice to cool and maintain freshly harvested fish at sea in insulated boxes is presented. The model addresses the universal need for fisherman to know in advance of going to sea just how much ice will be needed to cool down the expected day's catch to a desired temperature, maintain the catch, and to allow for losses. Illustrative predictions are presented for southern bluefin tuna (SBT) (Thunnus maccoyii) for a range of day's catch from 2000 to 8000 kg in ambient temperature ranging from 15 to 35 °C. The amount of ice needed to cool down SBT from an initial uniform harvest temperature of 28 °C to a maintenance temperature of 5 °C is shown to be the controlling contribution to total ice needed. Predictions highlight that a useful, safe rule‐of‐thumb is 1 kg of ice will be needed for each 3.5 kg of SBT. Importantly, the model is based on fundamental principles and predictive accuracy is demonstrated to be largely insensitive to a range of assumptions including volume of the void in the insulated boxes and overall coefficient of heat influx from ambient. The model can be used to predict the number of insulated boxes of defined dimension that will be needed to cool and hold the fish, ice and water for a wide range of fish species. It will be of interest to fisherman and boat owners and agents who invest in ice to preserve fish at sea. Practical Application: This research addresses the universal need for fisherman to know in advance of going to sea how much ice will be needed on‐board boats to cool down an expected day's catch to a desired temperature, maintain the catch and to allow for losses. The model is generalized and can be applied to a wide range of fish species.     

Predictive modelling of growth and measurement of enzymatic synthesis and activity by a cocktail of selected Enterobacteriaceae and Aeromonas hydrophila

The possibility was examined of developing a predictive model that would predict food spoilage by combining microbial growth (increase in cellular number) with extracellular enzymatic activity of a cocktail of five strains of Enterobacteriaceae: Escherichia coli, Enterobacter agglomerans, Klebsiella oxytoca, Klebsiella pneumoniae and Proteus vulgaris and one Aeromonas hydrophila strain. Estimations of growth and enzyme activity were made within a three-dimensional matrix of conditions: temperature 2-20 degrees C, pH value 4.0-7.5 and water activity (a(w)) 0.95-0.995. A mathematical model was constructed which predicted growth based on increases in cell number. However, although notable effects of extracellular lipases and proteases were detected, it was not possible to model enzymatic activity and prepare a combined model because the data did not follow the characteristic profile that would allow curve-fitting. Nevertheless, the model for microbial growth and information relating to enzyme activity will be made freely available in a database on the internet.     

A multi-objective optimization approach to balancing cost and traceability in bulk grain handling

This paper proposes a multi-objective optimization model that provides an effective method for minimizing traceability effort by minimizing the food safety risk caused by lot aggregation at a grain elevator. A mathematical multi-objective mixed-integer programming (MIP) model is proposed with two objective functions that allow in calculating the minimum levels of lot aggregation and minimum total cost of blending grain. Constraints on the system include customer contract specifications, availability of grain at the elevators and the blending requirements. The solutions include quantities of grain from different storage bins to be used for blending for a shipment while using the minimum number of storage bins and minimum total cost. The numerical results are presented for a corn shipment scenario to demonstrate the application of this model. Pareto optimal front is computed for the problem for simultaneous optimization of lot aggregation and cost of blending. Sensitivity analysis is conducted to analyze the application of the model under different operating conditions.     

Calculator tool for determining greenhouse gas emissions for biosolids processing and end use

A greenhouse gas (GHG) calculator tool (Biosolids Emissions Assessment Model, BEAM) was developed for the Canadian Council of Ministers of the Environment to allow municipalities to estimate GHG emissions from biosolids management. The tool was developed using data from peer reviewed literature and municipalities. GHG emissions from biosolids processing through final end use/disposal were modeled. Emissions from nine existing programs in Canada were estimated using the model. The program that involved dewatering followed by combustion resulted in the highest GHG emissions (Mg CO(2)e 100 Mg(-1) biosolids (dry wt.). The programs that had digestion followed by land application resulted in the lowest emissions (-26 and -23 Mg CO(2)e 100 Mg(-1) biosolids (dry wt.). Transportation had relatively minor effects on overall emissions. The greatest areas of uncertainty in the model include N(2)O emissions from land application and biosolids processing. The model suggests that targeted use of biosolids and optimizing processes to avoid CH(4) and N(2)O emissions can result in significant GHG savings.     

Statistical and Thurstonian models for the A-not A protocol with and without sureness

The A-not A protocol with sureness produce multinomial observations that are traditionally analyzed with statistical methods for contingency tables or by calculation of an R-index. In this paper it is shown that the Thurstonian model for the A-not A protocol can be written as a cumulative link model including the binormal unequal variances model. The model is extended to allow for explanatory variables and we illustrate how consumer differences can be modeled within the Thurstonian framework on a consumer study of packet soup conducted by Unilever. The extension also allows several test-product variations to be analyzed in the same model providing additional insight and reduced experimental costs. The effects of explanatory variables on the Thurstonian delta, the sensitivity (AUC), the ROC curve and the response category thresholds are discussed in detail. All statistical methods are implemented in the free R-package ordinal (http://www.cran.r-project.org/package=ordinal/).     

近红外光谱的预处理对羊肉TVB-N模型的影响

为研究能否通过对算法参数的调整和算法的组合来减弱甚至消除便携式近红外仪和样品组织结构等对样品光谱信息的影响,提高模型的预测准确性和稳健性,实现现场快速无损检测生鲜羊肉挥发性盐基氮(total volatile basic nitrogen,TVB-N)的目的。本研究应用不同参数组合的单一算法和不同算法组合对样品的光谱信息进行预处理并建模,从模型的预测准确性和稳健性2个方面探讨算法参数和算法组合对模型性能的影响,找出针对检测生鲜羊肉中TVB-N含量的最佳预处理方法。结果表明,不同的算法参数和算法组合对模型性能的影响差别很大,对样品的近红外光谱信息进行差分求导(窗口数为6,求导阶次为1)后,模型性能最佳。模型的校正标准差和验证标准差分别为1.21和1.31,校正标准差和验证标准差的比值为1.08小于1.2,主成分数为10,校正集相关系数和验证及相关系数分别为0.94和0.92。说明通过对算法参数的调整和对算法的组合可以有效提高模型性能,满足应用便携式近红外仪现场快速无损检测生鲜羊肉TVB-N含量的要求。     

Woven fabric design and analysis in 3D virtual reality. Part 1: computer aided design and modeling of interlaced structures

A computer model is developed that enables geometric models for woven fabric structures in three dimensions, which would allow engineers to simulate new textile forms in virtual reality and to study the effects of the process parameters on the textile structure. Mathematical models and algorithms for the generation and manipulation of 3D single and multi-layer fabrics are developed.     

C₆₀ oxide as a key component of aqueous C₆₀ colloidal suspensions

Stable aqueous fullerene colloidal suspensions (nC(60)) are demonstrated to rely on the [6,6]-closed epoxide derivative of the fullerene (C(60)O) for stability. This derivative is present, though often unrecognized, in small quantities in nearly all C(60) starting materials due to a reaction with air. The low-yield formation of nC(60) from organic solvent solutions results from a preferential partitioning and thus enrichment of C(60)O in the colloidal particles. This partitioning is significantly retarded in the nC(60) synthesis method that does not involve organic solvent solutions: long-term stirring in water. Instead, this method relies on trace levels of ozone in the ambient atmosphere to produce sufficient C(60)O at the surfaces of the nC(60) particles to allow stable suspension in water. Controlled-atmosphere syntheses, deliberate C(60)O enrichment, light scattering measurements, and extraction followed by HPLC analysis and UV-visible absorption spectroscopy support the above model of nC(60) formation and stabilization.     

Survival curves of Listeria monocytogenes in chorizos modeled with artificial neural networks

Using artificial neural networks (ANNs), a highly accurate model was developed to simulate survival curves of Listeria monocytogenes in chorizos as affected by the initial water activity (a(w0)) of the sausage formulation, temperature (T), and air inflow velocity (F) where the sausages are stored. The ANN-based survival model (R(2)=0.970) outperformed the regression-based cubic model (R(2)=0.851), and as such was used to derive other models (using regression) that allow prediction of the times needed to drop count by 1, 2, 3, and 4 logs (i.e., nD-values, n=1, 2, 3, 4). The nD-value regression models almost perfectly predicted the various times derived from a number of simulated survival curves exhibiting a wide variety of the operating conditions (R(2)=0.990-0.995). The nD-values were found to decrease with decreasing a(w0), and increasing T and F. The influence of a(w0) on nD-values seems to become more significant at some critical value of a(w0), below which the variation is negligible (0.93 for 1D-value, 0.90 for 2D-value, and <0.85 for 3D- and 4D-values). There is greater influence of storage T and F on 3D- and 4D-values than on 1D- and 2D-values.     

A stochastic regression approach to analyzing thermodynamic uncertainty in chemical speciation modeling

Chemical speciation modeling is a vital tool for assessing the bioavailability of inorganic species, yet significant uncertainties in thermodynamic parameters and model form limit its potential for decision-making. In this paper we present a novel method for the quantification of thermodynamic parameter uncertainty and ionic strength correction model uncertainty using Bayesian Markov Chain Monte Carlo (MCMC) estimation methods. These methods allow for the inclusion of correlation modeling, which has not been present in previous work. The MCMC simulations are used to model a natural river water to determine the uncertainty in the calculated environmental speciation of ethylenediamenetetraacetate, a chelating agent that has attracted considerable environmental interest. The results indicate that incorporating correlation among related thermodynamic parameters into the uncertainty model is necessary to correctly quantify the overall system uncertainty. This result indicates the superiority of MCMC estimation methods overtraditional Monte Carlo methods when available data are used to estimate parameter uncertainty in systems with closely related model parameters.     

Short communication: Calculating analytical reliabilities for single-step predictions

It has been shown that single-step genomic BLUP (ssGBLUP) can be reformulated, resulting in an equivalent SNP model that includes the explicit imputation of gene contents of all ungenotyped animals in the pedigree. This reformulation reveals the underlying mechanism enabling ungenotyped animals to contribute information to genotyped animals via estimates of marker effects and consequently to the reliability of genomic predictions, a key feature generally associated with the single-step approach. Irrespective of which BLUP formulation is used for genomic prediction, with increasing numbers of genotyped animals, the marker-oriented model is recommended when calculating the reliabilities of genomic predictions. This approach has the advantage of a manageable and stable size of the model matrix that needs to be inverted to calculate analytical prediction error variances of marker effects, an advantage that also holds for prediction with the single-step model. However, when including imputed genotypes in the design matrix of marker effects, an additional imputation residual term has to be considered to account for the prediction error of imputation. We summarize some of the theoretical aspects associated with the calculation of analytical reliabilities of single-step predictions. Derivations are based on the equivalent reformulation of ssGBLUP as a marker-oriented model and the calculation of prediction error variances of marker effects. We propose 2 approximations that allow for a substantial reduction of the complexity of the matrix operations involved, while retaining most of the relevant information required for reliability calculations. We additionally provide a general framework for an implementation of single-step reliability approximation using standard animal model reliabilities as a starting point. Finally, we demonstrate the effectiveness of the proposed approach using a small example extracted from data of the routine evaluation on dual-purpose Fleckvieh (Simmental) cattle.     

Simulation model for moving food packages in microwave heating processes using conformal FDTD method

A numeric model was developed to couple electromagnetic (EM) and thermal field calculations in packaged foods moving in pressurized 915 MHz microwave (MW) cavities with circulating water at above 120 °C. This model employed a commercial EM package with a customized heat transfer sub-model to solve EM field and thermal field equations. Both methods applied finite-difference time-domain (FDTD) method. An interface was built to facilitate the communication between electromagnetic and thermal models to incorporate the coupling feature which is unique to microwave heating process. Special numerical strategies were implemented to simulate the movement of food packages. The simulation model was validated with a pilot-scale microwave system using direct temperature measurement data and indirect color patterns in whey protein gels via formation of the thermally induced chemical marker M-2. Good agreements were observed. Four cases were studied to investigate the influence of power input and package gaps on heating uniformity. These applications demonstrated the flexibility of the model to allow its usage for system and process optimization.     

Wet oxidation lumped kinetic model for wastewater organic burden biodegradability prediction

In many cases, treatment of wastewaters requires a combination of processes that very often includes biological treatment. Wet oxidation (WO) in combination with biotreatment has been successfully used for the treatment of refractory wastes. Therefore, information about the biodegradability of wastewater solutes and particulates after wet oxidation is very important. The present work proposes a model that can describe the oxidation process via organic concentration characteristics such as chemical oxygen demand (COD), biochemical oxygen demand (BOD), and immediately available BOD (IA BOD) and so can allow the prediction of biodegradability (i.e., BOD/COD ratio). The reaction mechanism includes the destruction of nonbiodegradable substances bytwo pathways: oxidation to carbon dioxide and water and oxidation to larger biodegradable compounds with their further degradation to smaller ones measured via IA BOD. The destruction of small biodegradable compounds to end products is also included in the model. The experiments were performed at different temperatures (170-200 degrees C) and partial oxygen pressures (0.5-1.5 MPa) in a batch stainless steel high-pressure autoclave. The model of concentrated thermomechanical pulp circulation water was selected for the experiments. The proposed model correlates with the experimental data well and it is compared with other WO models in the literature.     

Shelf life prediction of bread sticks using oxidation indices: a validation study

ABSTRACT:  The aim of this study was to apply the protocol for the shelf life prediction of bakery products proposed by Calligaris and others (2007a) on bread sticks. The methodology comprises 4 steps: (1) evaluation of the physical properties of fat; (2) performing the accelerated shelf life test; (3) evaluation of sensory acceptance limit and the relevant chemical index limit; (4) setting up the shelf life prediction model. The results allow validating the shelf life prediction methodology proposed. In fact, the peroxide number was found to be a representative index of the quality depletion of bread sticks during their shelf life. In addition, once again by accounting for the changes in the fat physical state, it is possible to set up a modified Arrhenius equation able to describe the temperature dependence of peroxide formation. Finally, a mathematical model to simply and quickly calculate the shelf life of bread sticks has been developed.     

A mixture-enthalpy fixed-grid model for temperature evolution and heterocyclic-amine formation in a frying beef patty

The ideal cooking process would heat food to a sufficient temperature throughout to kill bacteria without heating the food to temperatures that promote formation of toxic or carcinogenic compounds. Experimentally validated computer models have an important role to play in designing cooking processes since they allow rapid evaluations of different conditions without the confounding effects of experimental variation. In this paper we derive a mathematical model governing the heat and water transport in a cylindrical pan-fried beef patty. The continuum temperature model stems from a mixture-enthalpy formulation that accommodates the liquid and vapor states of water along with fat and protein. The governing equations were spatially discretized with Legendre spectral finite elements. All but two of the model properties were taken from the literature, with the remaining two determined through a comparison of numerical and physical experiments. These parameters were shown to produce solutions in agreement with a different set of experimental results. The model was used to calculate the formation of heterocyclic-amine (HA) compounds (known DNA mutagens and carcinogens). Results provide an explanation based on patty temperature for previous experimental studies showing that frequent patty flipping yields a dramatic reduction in HAs.     

A review of the kinetics of degradation of inosine monophosphate in some species of fish during chilled storage

A literature search was made for data on the concentrations of inosine monophosphate (IMP) and its degradation products, inosine (Ino) and hypoxanthine (Hx), in the flesh of vertebrate fish during storage in ice. Twenty‐one publications containing data for forty‐five species were selected for review. A mathematical model was developed for analysing the data by assuming that the kinetics of degradation of IMP could be modelled as consecutive first order reactions. The model was fitted to the data and in about half of the cases examined in the review the data suggested that IMP and degradation products were lost by leaching and the kinetic model was extended to allow for this loss. In all of the cases reviewed the mathematical model was a good fit to the experimental data and the reaction rates for the reactions are tabulated in the paper. In all species the concentration of IMP decreased as a first order reaction, but for thirteen of the species examined the enzyme model of IMP to Ino to Hx did not fit the data in that either Ino or Hx did not accumulate in the muscle. There were only a few examples of replications of storage trials within species and comparison of the outcomes of these replications suggested that season or, in the case of farmed fish, genetic stock or cultural practices might influence initial IMP concentrations or reaction rates.