Nursing home food services linked with risk of malnutrition.

PURPOSE: Links between food service characteristics and residents' risk of malnutrition were examined. METHODS: Cognitively intact residents meeting inclusion criteria and living in one of 38 participating nursing homes were randomly sampled. The final sample consisted of 132 residents, who were screened for risk of malnutrition and completed a face-to-face interview questionnaire about dining experiences. Additional data came from participants' medical charts, and each institution's food service manager completed a written questionnaire. Frequencies and logistic regressions were used to describe the sample and to examine relationships between risk of malnutrition and food service characteristics. RESULTS: Overall, 37.4% of participants were at risk of malnutrition. Food service factors, including food packages, lids, and dishes that were difficult to manipulate (b=0.285, p=0.009), bulk food-delivery systems (b=1.329, p=0.036), overall food satisfaction (b=0.253, p=0.044), menu cycle length (b=-2.162, p=0.003), and porcelain dishes (b=-0.345, p=0.052), all were significantly associated with risk of malnutrition. CONCLUSIONS: Our findings clearly show a need for nursing homes to modify certain aspects of food service that may increase the risk of malnutrition among cognitively intact residents.     

A Study of Interspeaker Variability in Speaker Verification

We propose a new approach to the problem of estimating the hyperparameters which define the interspeaker variability model in joint factor analysis. We tested the proposed estimation technique on the NIST 2006 speaker recognition evaluation data and obtained 10%-15% reductions in error rates on the core condition and the extended data condition (as measured both by equal error rates and the NIST detection cost function). We show that when a large joint factor analysis model is trained in this way and tested on the core condition, the extended data condition and the cross-channel condition, it is capable of performing at least as well as fusions of multiple systems of other types. (The comparisons are based on the best results on these tasks that have been reported in the literature.) In the case of the cross-channel condition, a factor analysis model with 300 speaker factors and 200 channel factors can achieve equal error rates of less than 3.0%. This is a substantial improvement over the best results that have previously been reported on this task.     

Reduction by cefodizime of the pulmonary inflammatory response induced by heat-killed Streptococcus pneumoniae in mice

It has recently become apparent that overwhelming inflammatory reactions contribute to the high mortality rate associated with pneumococcal infection in immunocompetent hosts. Cefodizime (CEF) is an antibiotic that seems to be endowed with immunomodulating properties. To investigate the influence of CEF on the pulmonary inflammatory response induced by Streptococcus pneumoniae, we infected mice with repeated intranasal inoculations of 10(7) CFU of heat-killed fluorescein isothiocyanate-labeled bacteria, which are insensitive to the killing properties of the drug. CEF downregulated but did not abolish the strong polymorphonuclear leukocyte (PMN) recruitment induced by S. pneumoniae. PMN recruitment was not primarily mediated by leukotriene B4 in this model. The drug did not interfere with intrinsic mechanisms of phagocytosis by PMNs and alveolar macrophages. CEF totally abrogated the pneumococcus-induced tumor necrosis factor alpha (TNF-alpha) and interleukin-6 (IL-6) secretion in bronchoalveolar lavage fluid. The drug also prevented IL-6 release in lung homogenates and partly inhibited TNF-alpha, but it did not interfere with IL-1alpha secretion in the lungs of infected mice. The fractional and selective downregulation of inflammatory cells and cytokines by CEF suggests cell-specific and intracellular specific mechanisms of interaction of the drug. The immunomodulatory properties of CEF may help restrain excessive inflammatory reactions, thus contributing to the reported good clinical efficacy of the drug against lower respiratory tract infections.     

A reliability based maintenance policy; a case study

Reliability centered maintenance (RCM) incorporates sound guidance for managers who wish to attain high standards of maintenance at their operating plants. Since the amount and type of maintenance which is applied depend strongly on the machine or components age (DFR, CFR or IFR), on its replacement cost as well as on the cost and safety consequences of system failure, a careful analysis of the system components based on their reliability data should be done in order to optimize the maintenance program. This paper describes the methodology which was used at an aluminum plant in order to select critical machines and to develop an optimal maintenance policy based on reliability data of each machine, safety consequences of system failure, lead time and repair time, and components criticality.     

Purification, characterization and amino acid sequencing of divergicin M35: a novel class IIa bacteriocin produced by Carnobacterium divergens M35

Carnobacterium divergens M35, isolated from a commercial sample of frozen smoked mussels, produces a new bacteriocin, divergicin M35, a class IIa bacteriocin. Divergicin M35 is sensitive to pronase-E, alpha-chymotrypsin and proteinase K, but not to trypsin and withstands thermal treatments up to 121 degrees C for 30 min. Divergicin M35 was extracted from the culture supernatant of C. divergens M35 using an SP-Sepharose cation-exchange column, desalted and purified on a C18 Sep-Pack column and further purified by reverse phase-high pressure liquid chromatography. This procedure allowed the recovery of 10% of the bacteriocin present in the culture supernatant with purity higher than 99%. Divergicin M35 had a molecular mass of 4518.75 Da as determined by mass spectrometry, a pI value of 8.3 and positive net charge (+3). The amino acid sequence of divergicin M35 was found to consist of 43 amino acid with four cysteine residues (Cys10, 15, 25, 43) and showed 80.5% homology with divercin V41 (80.5%) and 80.0% with bavaricin MN. Divergicin M35 showed powerful antilisterial activity, especially against Listeria monocytogenes and was also active against carnobacteria but not against strains of Lactococcus, Lactobacillus, Enterococcus, Bifidobacteria and Escherichia. Divergicin M35 production began in late exponential phase and reached a maximum activity of 65,000 AU/ml in early stationary phase. Initial broth pH, Tween 80 and acetate did not affect C. divergens M35 growth or divergicin production. This bacteriocin may be a potential tool for inhibiting L. monocytogenes in seafood products that do not usually undergo an adequate heat treatment.     

DAILY AVERAGED 2D WATER TEMPERATURE MODEL FOR THE ST. LAWRENCE RIVER

A daily averaged two‐dimensional water temperature model has been developed for the freshwater part of the St. Lawrence River, between Lake St. Louis and Trois‐Rivières (Québec, Canada). The model was first calibrated and validated for the area of Lake St. Pierre, a natural enlargement of the river subject to strong lateral and longitudinal thermal variations. Forecasts from the Global Environmental Multiscale model were used in preference to observations from meteorological stations for model inputs, both to increase the spatial resolution and ultimately to allow the water temperature model to be used in predictive mode. The resulting model provided daily water temperature estimates with an overall root mean square error (RMSE) of 1.18 °C and a Nash–Sutcliffe coefficient of 0.44. Comparisons between Landsat images and simulations demonstrated that the model not only simulated accurate water temperature values but also showed the adequacy of the model in general. It not only simulated local water temperature relatively accurately but also provided a good representation of the spatial water temperature patterns within the study area. The error varied between deep and shallow water areas. In deeper water, the overall RMSE is 0.41 °C, and the modified Nash coefficient rises up to 0.92. Because shallow water areas are subject to greater variations, longer, more spatially dense data sets will be needed to refine the hydrodynamic and thermal budget models for those specific areas. Copyright © 2013 John Wiley & Sons, Ltd.     

A method to consider replaced pipes in modeling of sewer pipe deterioration

Statistical models that predict the deterioration of sewer pipes are useful for planning financial resources required for sewer renewal. Usually, data that are available to calibrate these models solely concern pipes that are still in place, leading to underestimated deterioration rates. A new method is proposed to consider possible past replacement of pipes in the statistical modeling of their deterioration. The proposed method considers the aging of pipes, simulated with a Cox model, and their probability to be replaced separately. Application to a synthetic sewer network, for which it was assumed that information regarding all pipe replacements over the lifetime of the network was available, showed that the proposed method allows for improved predictions of the sewer deterioration model, when compared to predictions of a model calibrated without considering the information about replaced pipes.     

Optimal control of an aluminum casting furnace: Part I. The control model

This is a series of two articles on the control of an aluminum casting furnace to bring a mass of liquid aluminum from a known initial temperature to a desired final temperature in a given time with minimal fuel cost. An analytic model of the furnace already exists but is too complex for control purposes. Here in Part I, a simplified nonlinear control model is derived from the analytic model. In Part II, an optimization of the fuel flow is performed on the control model using Pontryagin’s maximum principle. The first article shows that despite the complexity of the analytic model, a tenth-order nonlinear control model with good representativity can be obtained. The second article shows that the maximum principle applied to this problem leads to a solution with optimal fuel cost. If modeling industrial processes is a complex problem in itself, obtaining a control model therefrom is just as delicate. This series of articles proposes an approach that works for the casting furnace and is indeed applicable to other industrial processes as well. In the existing analytic model, the casting furnace is treated as two one-dimensional conducting media (metal and refractories), while its chamber is seen as a well-stirred reactor. In this article, a control model is derived therefrom by a statistical method. The analytic model is run several times to obtain a set of predicted data on which a least-squares approximation is performed to determine the best parameter values to be used for the control model equations. The conduction equations in the two media are linear. The expressions for heat generation in the chamber and for radiative-convective heat transfer from the chamber to the two media are nonlinear and are kept to ensure maximum representativity. The result is a highly representative tenth-order control model, the degree of representativity being assessed by comparing the temperature outputs and the energy balances obtained from the analytic model with those obtained from the control model.