860 resultados para Data management and analyses


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A dynamic, mechanistic model of enteric fermentation was used to investigate the effect of type and quality of grass forage, dry matter intake (DMI) and proportion of concentrates in dietary dry matter (DM) on variation in methane (CH(4)) emission from enteric fermentation in dairy cows. The model represents substrate degradation and microbial fermentation processes in rumen and hindgut and, in particular, the effects of type of substrate fermented and of pH oil the production of individual volatile fatty acids and CH, as end-products of fermentation. Effects of type and quality of fresh and ensiled grass were evaluated by distinguishing two N fertilization rates of grassland and two stages of grass maturity. Simulation results indicated a strong impact of the amount and type of grass consumed oil CH(4) emission, with a maximum difference (across all forage types and all levels of DM 1) of 49 and 77% in g CH(4)/kg fat and protein corrected milk (FCM) for diets with a proportion of concentrates in dietary DM of 0.1 and 0.4, respectively (values ranging from 10.2 to 19.5 g CH(4)/kg FCM). The lowest emission was established for early Cut, high fertilized grass silage (GS) and high fertilized grass herbage (GH). The highest emission was found for late cut, low-fertilized GS. The N fertilization rate had the largest impact, followed by stage of grass maturity at harvesting and by the distinction between GH and GS. Emission expressed in g CH(4)/kg FCM declined oil average 14% with an increase of DMI from 14 to 18 kg/day for grass forage diets with a proportion of concentrates of 0.1, and on average 29% with an increase of DMI from 14 to 23 kg/day for diets with a proportion of concentrates of 0.4. Simulation results indicated that a high proportion of concentrates in dietary DM may lead to a further reduction of CH, emission per kg FCM mainly as a result of a higher DM I and milk yield, in comparison to low concentrate diets. Simulation results were evaluated against independent data obtained at three different laboratories in indirect calorimetry trials with COWS consuming GH mainly. The model predicted the average of observed values reasonably, but systematic deviations remained between individual laboratories and root mean squared prediction error was a proportion of 0.12 of the observed mean. Both observed and predicted emission expressed in g CH(4)/kg DM intake decreased upon an increase in dietary N:organic matter (OM) ratio. The model reproduced reasonably well the variation in measured CH, emission in cattle sheds oil Dutch dairy farms and indicated that oil average a fraction of 0.28 of the total emissions must have originated from manure under these circumstances.

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Climate-G is a large scale distributed testbed devoted to climate change research. It is an unfunded effort started in 2008 and involving a wide community both in Europe and US. The testbed is an interdisciplinary effort involving partners from several institutions and joining expertise in the field of climate change and computational science. Its main goal is to allow scientists carrying out geographical and cross-institutional data discovery, access, analysis, visualization and sharing of climate data. It represents an attempt to address, in a real environment, challenging data and metadata management issues. This paper presents a complete overview about the Climate-G testbed highlighting the most important results that have been achieved since the beginning of this project.

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A range of physiological parameters (canopy light transmission, canopy shape, leaf size, flowering and flushing intensity) were measured from the International Clone Trial, typically over the course of two years. Data were collected from six locations, these being: Brazil, Ecuador, Trinidad, Venezuela, Côte d’Ivoire and Ghana. Canopy shape varied significantly between clones, although it showed little variation between locations. Genotypic variation in leaf size was differentially affected by the growth location; such differences appeared to underlie a genotype by environment interaction in relation to canopy light transmission. Flushing data were recorded at monthly intervals over the course of a year. Within each location, a significant interaction was observed between genotype and time of year, suggesting that some genotypes respond to a greater extent than others to environmental stimuli. A similar interaction was observed for flowering data, where significant correlations were found between flowering intensity and temperature in Brazil and flowering intensity and rainfall in Côte d’Ivoire. The results demonstrate the need for local evaluation of cocoa clones and also suggest that the management practices for particular planting material may need to be fine-tuned to the location in which they are cultivated.

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Providing homeowners with real-time feedback on their electricity consumption through a dedicated display device has been shown to reduce consumption by approximately 6-10%. However, recent advances in smart grid technology have enabled larger sample sizes and more representative sample selection and recruitment methods for display trials. By analyzing these factors using data from current studies, this paper argues that a realistic, large-scale conservation effect from feedback is in the range of 3-5%. Subsequent analysis shows that providing real-time feedback may not be a cost effective strategy for reducing carbon emissions in Australia, but that it may enable additional benefits such as customer retention and peak-load shift.

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OBJECTIVES: The prediction of protein structure and the precise understanding of protein folding and unfolding processes remains one of the greatest challenges in structural biology and bioinformatics. Computer simulations based on molecular dynamics (MD) are at the forefront of the effort to gain a deeper understanding of these complex processes. Currently, these MD simulations are usually on the order of tens of nanoseconds, generate a large amount of conformational data and are computationally expensive. More and more groups run such simulations and generate a myriad of data, which raises new challenges in managing and analyzing these data. Because the vast range of proteins researchers want to study and simulate, the computational effort needed to generate data, the large data volumes involved, and the different types of analyses scientists need to perform, it is desirable to provide a public repository allowing researchers to pool and share protein unfolding data. METHODS: To adequately organize, manage, and analyze the data generated by unfolding simulation studies, we designed a data warehouse system that is embedded in a grid environment to facilitate the seamless sharing of available computer resources and thus enable many groups to share complex molecular dynamics simulations on a more regular basis. RESULTS: To gain insight into the conformational fluctuations and stability of the monomeric forms of the amyloidogenic protein transthyretin (TTR), molecular dynamics unfolding simulations of the monomer of human TTR have been conducted. Trajectory data and meta-data of the wild-type (WT) protein and the highly amyloidogenic variant L55P-TTR represent the test case for the data warehouse. CONCLUSIONS: Web and grid services, especially pre-defined data mining services that can run on or 'near' the data repository of the data warehouse, are likely to play a pivotal role in the analysis of molecular dynamics unfolding data.

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Recent high-resolution radiosonde climatologies have revealed a tropopause inversion layer (TIL) in the extratropics: temperature strongly increases just above a sharp local cold point tropopause. Here, it is asked to what extent a TIL exists in current general circulation models (GCMs) and meteorological analyses. Only a weak hint of a TIL exists in NCEP/NCAR reanalysis data. In contrast, the Canadian Middle Atmosphere Model (CMAM), a comprehensive GCM, exhibits a TIL of realistic strength. However, in data assimilation mode CMAM exhibits a much weaker TIL, especially in the Southern Hemisphere where only coarse satellite data are available. The discrepancy between the analyses and the GCM is thus hypothesized to be mainly due to data assimilation acting to smooth the observed strong curvature in temperature around the tropopause. This is confirmed in the reanalysis where the stratification around the tropopause exhibits a strong discontinuity at the start of the satellite era.

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Quantity and variety of environmental antigens, age, diet, vaccine protocols, exercising practice and mucosal cytokine microenvironment are factors that influence serum immunoglobulin (Ig) levels. IgA, IgG, IgG(T) and IgM were quantified in 60 horses, which were classified into two groups, `intensive` or `relaxed`, according to sanitary standards of the facilities and physical exercise to which animals were subjected to. The `intensive` group presented lower means for all isotypes, but only IgA presented a significant (P < 0.0064) difference when compared to the `relaxed` group. This suggests that mucosal immunity found in the `intensive` group is lower when compared to the `relaxed` group. Our data suggest that athlete horses may be less poised to mount an effective mucosal immunity response to environmental challenges and should not be considered by the same perspectives as a free-ranging horse.

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We review some issues related to the implications of different missing data mechanisms on statistical inference for contingency tables and consider simulation studies to compare the results obtained under such models to those where the units with missing data are disregarded. We confirm that although, in general, analyses under the correct missing at random and missing completely at random models are more efficient even for small sample sizes, there are exceptions where they may not improve the results obtained by ignoring the partially classified data. We show that under the missing not at random (MNAR) model, estimates on the boundary of the parameter space as well as lack of identifiability of the parameters of saturated models may be associated with undesirable asymptotic properties of maximum likelihood estimators and likelihood ratio tests; even in standard cases the bias of the estimators may be low only for very large samples. We also show that the probability of a boundary solution obtained under the correct MNAR model may be large even for large samples and that, consequently, we may not always conclude that a MNAR model is misspecified because the estimate is on the boundary of the parameter space.

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Instrumentation and automation plays a vital role to managing the water industry. These systems generate vast amounts of data that must be effectively managed in order to enable intelligent decision making. Time series data management software, commonly known as data historians are used for collecting and managing real-time (time series) information. More advanced software solutions provide a data infrastructure or utility wide Operations Data Management System (ODMS) that stores, manages, calculates, displays, shares, and integrates data from multiple disparate automation and business systems that are used daily in water utilities. These ODMS solutions are proven and have the ability to manage data from smart water meters to the collaboration of data across third party corporations. This paper focuses on practical, utility successes in the water industry where utility managers are leveraging instantaneous access to data from proven, commercial off-the-shelf ODMS solutions to enable better real-time decision making. Successes include saving $650,000 / year in water loss control, safeguarding water quality, saving millions of dollars in energy management and asset management. Immediate opportunities exist to integrate the research being done in academia with these ODMS solutions in the field and to leverage these successes to utilities around the world.

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Asian soybean rust is a formidable threat to soybean (Glycine max) production in many areas of the world, including the United States. Only five sources of resistance have been identified (Resistance to Phakopsora pachyrhizi1 [Rpp1], Rpp2, Rpp3, Rpp4, and Rpp5). Rpp4 was previously identified in the resistant genotype PI459025B and mapped within 2 centimorgans of Satt288 on soybean chromosome 18 (linkage group G). Using simple sequence repeat markers, we developed a bacterial artificial chromosome contig for the Rpp4 locus in the susceptible cv Williams82 (Wm82). Sequencing within this region identified three Rpp4 candidate disease resistance genes (Rpp4C1-Rpp4C3 [Wm82]) with greatest similarity to the lettuce (Lactuca sativa) RGC2 family of coiled coil-nucleotide binding site-leucine rich repeat disease resistance genes. Constructs containing regions of the Wm82 Rpp4 candidate genes were used for virus-induced gene silencing experiments to silence resistance in PI459025B, confirming that orthologous genes confer resistance. Using primers developed from conserved sequences in the Wm82 Rpp4 candidate genes, we identified five Rpp4 candidate genes (Rpp4C1-Rpp4C5 [PI459025B]) from the resistant genotype. Additional markers developed from the Wm82 Rpp4 bacterial artificial chromosome contig further defined the region containing Rpp4 and eliminated Rpp4C1 (PI459025B) and Rpp4C3 (PI459025B) as candidate genes. Sequencing of reverse transcription-polymerase chain reaction products revealed that Rpp4C4 (PI459025B) was highly expressed in the resistant genotype, while expression of the other candidate genes was nearly undetectable. These data support Rpp4C4 (PI459025B) as the single candidate gene for Rpp4-mediated resistance to Asian soybean rust.

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The main objective of this study is to verify the influence of Environmental Management (EM) on Operational Performance (OP) in Brazilian automotive companies, analyzing whether Lean Manufacturing (LM) and Human Resources (HR) interfere in the greening of these companies. Therefore, a conceptual framework listing these concepts was proposed, and three research hypotheses were presented. A questionnaire was elaborated based on this theoretical background and sent to respondents occupying the highest positions in the production/operations areas of Brazilian automotive companies. The data, collected from 75 companies, were analyzed using structural equation modeling. The main results are as follows: (a) the model tested revealed an adequate goodness of fit, showing that overall, the relations proposed between EM and OP and between HR, LM and EM tend to be statistically valid; (b) EM tends to influence OP in a positive and statistically weak manner; (c) LM has a greater influence on EM when compared to the influence HR has over EM; (d) HR has a positive relationship over EM, but the statistical significance of this relationship is less than that of the other evaluated relationships. The originality of this paper lies in its gathering the concepts of EM, LM, HR and OP in a single study, as they generally tend not to be treated jointly. This paper also provided valid empirical evidence for a littlestudied context: the Brazilian automotive sector. © 2012 Elsevier Ltd. All rights reserved.

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The aimed of this article is to measure risk factors on health and milk production on organic and conventional dairy goats in Brazil. Two experimental groups (organic and conventional) were evaluated simultaneously. The study design was completely randomized. The organic herd consisted of 25 goats and 15 kids. In the conventional production system, a dairy herd comprising 40 goats and 20 kids participated in the study. Data on milk production and health management were available from January 2007 to December 2009. The abortion rate in the conventional system was 5% (2/40) whereas in organic system no abortion was diagnosed (0/25). The mortality rate at weaning in the conventional system was 5% (2/40) and in the organic system was 8% (2/25). Milk production was lower (2.20 kg/day) in organic than conventional system (2.66 kg/day). Goats and kids in organic farm had a higher FEC (386±104 and 900±204, respectively) (p<0.05) than those in conventional farm (245±132 and 634±212, respectively). In addition, Saanen kids had higher FEC (p<0.001) than goats. Treatment with antiparasitic drugs was higher in conventional system (50%) than organic system (1.3%).

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Spermiogenesis and sperm ultrastructure from 21 species of Moenkhausia and others related genera are described. To evaluate the phylogenetic signals, 18 unordered characters were utilized in implied weighting analysis through the program TNT 1.1. Four variations of spermiogenesis were found. In the earliest spermatids, the nucleus can be positioned lateral, eccentric, strongly eccentric or nearly medial in relation to the distal centriole. The nuclear rotation can be present or absent. These spermiogenesis processes are related or intermediate to Type I and Type III. Taking into account the degrees of nuclear rotation during the spermiogenesis and other characteristics, distinct forms of spermatozoa are observed among the species analyzed. The phylogenetic analysis yielded a single most parsimonious tree with fit value 2.70000 and the topology obtained founds Moenkhausia as non-monophyletic. However, some hypothesis of relationships previously proposed viz the clade 20, which contains the type species Moenkhausia xinguensis, is recovered herein. This clade is supported by five synapomorphies, and it allows the supposition that these species constitute a monophyletic group. The whole topology is presented and discussed. © 2012 The Authors. Acta Zoologica © 2012 The Royal Swedish Academy of Sciences.