92 research outputs found

    Modeling Nonconfined Density Currents Using 3D Hydrodynamic Models

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    Density currents generated by marine brine discharges, e.g., from desalination plants, can have a negative impact on marine ecosystems. It is therefore important to accurately predict their behavior. Predictions are often made using computational hydrodynamic models, which should be validated using field or laboratory measurements. This paper focuses on the setup and validation of three-dimensional (3D) models for estimating the transport and mixing processes that occur in these types of flows. Through a comprehensive sensitivity analysis based on the reproduction of several laboratory-generated density currents, a set of recommendations are made regarding the modeling aspects, including the domain discretization, the treatment of momentum at the density current source, the hydrostatic hypothesis and the selection of turbulence closure models. Finally, the proposed numerical model setup is validated using different experimental data showing good agreement in terms of the main variables considered: errors of less than 1.3% for dilution and of 6% for velocity. This study serves as a first step toward the full validation of these 3D hydrodynamic models for the simulation of field-scale density currents.This study was partially funded by the Ministry of Economy and Competitiveness (MINECO) under research project TRA2011-28900 (PLVMA3D). B. PĂ©rez-DĂ­az would like to thank MINECO for providing funding under the FPI Program (research fellowship, reference number BES-2012-053693) and the Coasts and Ocean Group of HRWallingford for their assistance with numerical tasks

    Relationships between milk coagulation property traits analyzed with different methodologies.

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    Milk coagulation properties (MCP) analysis is performed using a wide range of methodologies in different countries and laboratories, using different instruments, coagulant activity in the milk, and type of coagulant. This makes it difficult to compare results and data from different research. The aims of this study were to propose a method for the transformation of values of rennet coagulation time (RCT) and curd firmness (a(30)) and to predict the noncoagulation (NC) probability of milk samples analyzed using different methodologies. Individual milk samples were collected during the morning milking in October 2010 from each of 165 Holstein-Friesian dairy cows in 2 freestall barns in Italy, and sent to 3 laboratories for MCP analysis. For each laboratory, MCP analysis was performed using a different methodology: A, with a computerized renneting meter instrument using 0.051 international milk clotting units (IMCU)/mL of coagulant activity; B, with a Lattodinamografo (Foss-Italia, Padova, Italy) using 0.051 IMCU/mL of coagulant activity; and C, with an Optigraph (Ysebaert, Frépillon, France) using 0.120 IMCU/mL of coagulant activity. The relationships between MCP traits were analyzed with correlation and regression analyses for each pair of methodologies. For each MCP trait, 2 regression models were applied: model 1 was a single regression model, where the dependent and independent variables were the same MCP trait determined by 2 different methodologies; in model 2, both a(30) and RCT were included as independent variables. The NC probabilities for laboratories with the highest number of NC samples were predicted based on the RCT and a(30) values measured in the laboratories with lower number of NC samples using logistic regression and receiver operating characteristic analysis. The percentages of NC samples were 4.2, 11.5, and 0.6% for A, B, and C, respectively. The transformation of MCP traits was more precise with model 1 for RCT (R(2): 0.77-0.82) than for a(30) (R(2): 0.28-0.63). The application of model 2 was needed when the C measurements were transformed into the other scales. The analyses of NC probabilities of milk samples showed that NC samples from one methodology were well distinguishable (with an accuracy of 0.972-0.996) based on the rennet coagulation time measured with the other methodology. A standard definition for MCP traits analysis is needed to enable reliable comparisons between MCP traits recorded in different laboratories and in different animal populations and breeds

    Clones with finitely many relative R-classes

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    For each clone C on a set A there is an associated equivalence relation analogous to Green's R-relation, which relates two operations on A iff each one is a substitution instance of the other using operations from C. We study the clones for which there are only finitely many relative R-classes.Comment: 41 pages; proofs improved, examples adde

    Application des recommandations dans la prise en charge du cancer de l’endomĂštre en pratique clinique. Étude rĂ©trospective bretonne

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    National audienceObjective - To assess the use of French Cancer Institute recommendations for the diagnosis and treatment of endometrial cancer. Methods - Retrospective observational study involving 137 patients with endometrial cancer between 2011 and 2013. Results - Both MRI and pathological assessment with correct report as recommended were used for 66.4% of patients with endometrial cancer. For patients with correct preoperative assessment, 44.9% of patients were uncorrectly classified and upgraded on final pathological analysis of hysterectomy concerning lymph node involvement risk. These patients did not have confident surgical assessment, according this risk. Conclusion - To improve relevance of preoperative assessment in endometrial cancer, radiological and pathological expertise is required. However, even performed optimally, preoperative assessment does not allow correct risk stratification of lymph node involvement in endometrial cancer. This ineffective stratification leads to propose sentinel lymph node biopsy with hysterectomy in case of preoperative low risk endometrial cancer assessment

    Seasonal variations of Saanen goat milk composition and the impact of climatic conditions

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    The aim of this research was to investigate the effect of climatic conditions and their impact on seasonal variations of physico-chemical characteristics of Saanen goat milk produced over a period of 4 years. Lactation period (early, mid and late) and year were considered as factors that influence physico-chemical composition of milk. Pearson's coefficient of correlation was calculated between the physico-chemical characteristics of milk (fat, proteins, lactose, non-fat dry matter, density, freezing point, pH, titrable acidity) and climatic condition parameters (air temperature, temperature humidity index-THI, solar radiation duration, relative humidity). Results showed that all physico-chemical characteristics of Saanen goat milk varied significantly throughout the lactation period and years. The decrease of fat, protein, non-fat dry matter and lactose content in goat milk during the mid-lactation period was more pronounced than was previously reported in the literature. The highest values for these characteristics were recorded in the late lactation period. Observed variations were explained by negative correlation between THI and the physico-chemical characteristics of Saanen goat milk. This indicated that Saanen goats were very prone to heat stress, which implied the decrease of physico-chemical characteristics during hot summers

    The structure of the lantibiotic lacticin 481 produced by Lactococcus lactis:location of the thioether bridges

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    AbstractThe lantibiotic lacticin 481 is a bacteriocin produced by Lactococcus lactis ssp. lactis. This polypeptide contains 27 amino acids, including the unusual residues dehydrobutyrine and the thioether-bridging lanthionine and 3-methyllanthionine. Lacticin 481 belongs to a structurally distinct group of lantibiotics, which also include streptococcin A-FF22, salivaricin A and variacin. Here we report the first complete structure of this type of lantibiotic. The exact location of the thioether bridges in lacticin 481 was determined by a combination of peptide chemistry, mass spectrometry and NMR spectroscopy, showing connections between residues 9 and 14, 11 and 25, and 18 and 26
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