Adição de metionina protegida da degrabilidade ruminal em rações para cordeiros alimentados com dois níveis de ptoteína não degradável no rúmen: degrabilidade ruminal da matéria seca1.

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Forest stand type and forest diversity affect on above ground carbon biomass in Ontario's boreal forest

Biomass is a renewable organic material that is the living and recently dead organic material synthesized by plants and other organisms (Battles 2015). Quantifying forests and determining their value is an increasingly important concept in modern forestry. Forests are often quantified by estimating their total above ground biomass in forest ecosystems (Drake et al. 2003). This is significant as in the urban United states alone, trees store approximately 700 million tonnes of carbon with an estimated value of 14.3 billion dollars. Understanding factors that increase a forest's biomass will have direct and indirect environmental and economic impacts (Nowak and Crane 2002). Climate change is currently one of the largest threats to human health (Martens 1999). Greenhouse gases, a major cause of climate change, continue to rise. As a result, there are increasing levels of atmospheric carbon dioxide, methane, chlorofluorocarbons, nitrous oxide, and tropospheric ozone which contributes to rising global temperatures (Novak and Crane 2002). Forests absorb atmospheric carbon and store it in plant tissues, which are approximately 50% carbon, helping to mitigate greenhouse gasses emitted by atmospheric carbon (Drake et al. 2003, Novak and Crane 2002). [...

Statistical trend analysis and extreme distribution of significant wave height from 1958 to 1999 – an application to the Italian Seas

The study is a statistical analysis of sea states timeseries derived using the wave model WAM forced by the ERA-40 dataset in selected areas near the Italian coasts. For the period 1 January 1958 to 31 December 1999 the analysis yields: (i) the existence of a negative trend in the annual- and winter-averaged sea state heights; (ii) the existence of a turning-point in late 80's in the annual-averaged trend of sea state heights at a site in the Northern Adriatic Sea; (iii) the overall absence of a significant trend in the annual-averaged mean durations of sea states over thresholds; (iv) the assessment of the extreme values on a time-scale of thousand years. The analysis uses two methods to obtain samples of extremes from the independent sea states: the <i>r-largest annual maxima</i> and the <i>peak-over-threshold</i>. The two methods show statistical differences in retrieving the return values and more generally in describing the significant wave field. The <i>r-largest annual maxima</i> method provides more reliable predictions of the extreme values especially for small return periods (<100 years). Finally, the study statistically proves the existence of decadal negative trends in the significant wave heights and by this it conveys useful information on the wave climatology of the Italian seas during the second half of the 20th century

Predicting Isoform-Selective Carbonic Anhydrase Inhibitors via Machine Learning and Rationalizing Structural Features Important for Selectivity

Carbonic anhydrases (CAs) catalyze the physiological hydration of carbon dioxide and are among the most intensely studied pharmaceutical target enzymes. A hallmark of CA inhibition is the complexation of the catalytic zinc cation in the active site. Human (h) CA isoforms belonging to different families are implicated in a wide range of diseases and of very high interest for therapeutic intervention. Given the conserved catalytic mechanisms and high similarity of many hCA isoforms, a major challenge for CA-based therapy is achieving inhibitor selectivity for hCA isoforms that are associated with specific pathologies over other widely distributed isoforms such as hCA I or hCA II that are of critical relevance for the integrity of many physiological processes. To address this challenge, we have attempted to predict compounds that are selective for isoform hCA IX, which is a tumor-associated protein and implicated in metastasis, over hCA II on the basis of a carefully curated data set of selective and nonselective inhibitors. Machine learning achieved surprisingly high accuracy in predicting hCA IX-selective inhibitors. The results were further investigated, and compound features determining successful predictions were identified. These features were then studied on the basis of X-ray structures of hCA isoform-inhibitor complexes and found to include substructures that explain compound selectivity. Our findings lend credence to selectivity predictions and indicate that the machine learning models derived herein have considerable potential to aid in the identification of new hCA IX-selective compounds

An effective procedure to design the layout of standard and enhanced mode-S multilateration systems for airport surveillance

In this paper, an effective procedure to emplace standard and enhanced mode-S multilateration stations for airport surveillance is studied and developed. This procedure is based on meta-heuristic optimization techniques, such as genetic algorithm (GA), and is intended to obtain useful parameters for an optimal system configuration that provides acceptable performance levels. Furthermore, the procedure developed here is able to evaluate and improve previous system designs, as well as possible system enhancements. Additionally, the design strategies to be used along with the procedure proposed here are fully described. Parameters such as the number of stations, the system geometry, the kind of measurements to be used, and the system accuracy are obtained taking into account the basic requirements such as the Line of Sight, the probability of detection, and the accuracy levels. © Cambridge University Press and the European Microwave Association, 2012

Inability of immunohistochemistry to predict clinical outcomes of endometrial cancer patients

Gossett DR, Alo P, Bristow RE, Galati M, Kyshtoobayeva A, Fruehauf J, Montz FJ. Inability of immunohistochemistry to predict clinical outcomes of endometrial cancer patients. Introduction: Despite optimal surgery, some patients with early endometrial carcinoma develop recurrence and die of disease. A number of immunohistochemical (IHC)-identified cell products (markers) have been proposed as predictors of recurrence. This study characterizes a large series of endometrial carcinomas with previously described markers as well as markers that have not been investigated in endometrial carcinoma. Patients and methods: Women who had undergone surgery for endometrial carcinoma were identified and specimens accessed. Tissue blocks were evaluated for ten IHC markers. Results were correlated with last known clinical status. Results: Mean follow-up was 43 months; complete data were available on 117 patients. Two women died of other causes; of the remaining 115, eight died of disease and six were alive with recurrence at last follow-up (12%). Vascular endothelial growth factor staining independently predicted recurrence and death. However, in multivariate analyses, only FIGO stage predicted outcome. Discussion: Our goal was to identify markers to predict which women with endometrial carcinoma were likely to have disease recurrence. We evaluated cell-cycle regulatory proteins, growth factors, hormone receptors, and angiogenic factors, but did not identify any marker that independently predicted outcome in multivariate analysis. This may reflect the few negative outcomes in our population.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/72601/1/j.1048-891x.2004.014028.x.pd

Phonon Dynamics and Multipolar Isomorphic Transition in beta-pyrochlore KOs2O6

We investigate with a microscopic model anharmonic K-cation oscillation observed by neutron experiments in beta-pyrochlore superconductor KOs2O6, which also shows a mysterious first-order structural transition at Tp=7.5 K. We have identified a set of microscopic model parameters that successfully reproduce the observed temperature dependence and the superconducting transition temperature. Considering changes in the parameters at Tp, we can explain puzzling experimental results about electron-phonon coupling and neutron data. Our analysis demonstrates that the first-order transition is multipolar transition driven by the octupolar component of K-cation oscillations. The octupole moment does not change the symmetry and is characteristic to noncentrosymmetric K-cation potential.Comment: 5 pages, 4 figures, submitted to J. Phys. Soc. Jp

A new triclinic modification of the pyrochlore-type KOs2O6 superconductor

A new modification of KOs2O6, the representative of a new structural type (Pearson symbol aP18, a=5.5668(1)A, b=6.4519(2)A, c=7.2356(2)A, space group P-1, no.2) was synthesized employing high pressure technique. Its structure was determined by single-crystal X-ray diffraction. The structure can be described as two OsO6 octahedral chains relating to each other through inversion and forming big voids with K atoms inside. Quantum chemical calculations were performed on the novel compound and structurally related cubic compound. High-pressure X-ray study showed that cubic KOs2O6 phase was stable up to 32.5(2) GPa at room temperature.Comment: 23 pages, 9 figures,6 tables. Accepted for J. Solid State Che