997 resultados para Problem Resolution


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Eighty-Sixth General Assembly Senate Code of Ethics (Senate Resolution 4-Adopted 2-4-2015)Every legislator owes a duty to uphold the integrity and honor of the general assembly, to encourage respect for the law and for the general assembly and the members thereof, and to observe the legislative code of ethics.

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Eighty-Sixth General Assembly House Rules (House Resolution 4-Adopted 2-3-2015)

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Eighty-Sixth General Assembly Joint Rules Governing Lobbyists (House Concurrent Resolution 7) House Adopted 2-3-2015, Senate Adopted 2-4-2015

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Forensic scientists face increasingly complex inference problems for evaluating likelihood ratios (LRs) for an appropriate pair of propositions. Up to now, scientists and statisticians have derived LR formulae using an algebraic approach. However, this approach reaches its limits when addressing cases with an increasing number of variables and dependence relationships between these variables. In this study, we suggest using a graphical approach, based on the construction of Bayesian networks (BNs). We first construct a BN that captures the problem, and then deduce the expression for calculating the LR from this model to compare it with existing LR formulae. We illustrate this idea by applying it to the evaluation of an activity level LR in the context of the two-trace transfer problem. Our approach allows us to relax assumptions made in previous LR developments, produce a new LR formula for the two-trace transfer problem and generalize this scenario to n traces.

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Eighty-Sixth General Assembly House Rules (House Resolution 4-Adopted 2-3-2015)

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We present a spatiotemporal adaptive multiscale algorithm, which is based on the Multiscale Finite Volume method. The algorithm offers a very efficient framework to deal with multiphysics problems and to couple regions with different spatial resolution. We employ the method to simulate two-phase flow through porous media. At the fine scale, we consider a pore-scale description of the flow based on the Volume Of Fluid method. In order to construct a global problem that describes the coarse-scale behavior, the equations are averaged numerically with respect to auxiliary control volumes, and a Darcy-like coarse-scale model is obtained. The space adaptivity is based on the idea that a fine-scale description is only required in the front region, whereas the resolution can be coarsened elsewhere. Temporal adaptivity relies on the fact that the fine-scale and the coarse-scale problems can be solved with different temporal resolution (longer time steps can be used at the coarse scale). By simulating drainage under unstable flow conditions, we show that the method is able to capture the coarse-scale behavior outside the front region and to reproduce complex fluid patterns in the front region.

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Many early Iowa Portland Cement Concrete (PCC) pavements provided good performance without deterioration for more than 50 years. In the late 1950's, Iowa was faced with severe PCC pavement deterioration called D cracking due to crushed limestone containing a bad pore system. Selective quarrying solved the problem. In 1990, cracking deterioration was identified on a three year old US 20 pavement in central Iowa. The coarse aggregate was a crushed limestone with an excellent history of performance in PCC pavement. Examination of cores showed very few cracks through the coarse aggregate particles. The cracks were predominately confined to the matrix. A high resolution, low vacuum Hitachi Scanning Electron Microscope (SEM) with an energy dispersion detector was used to investigate the deterioration. Subsequent evaluation identified very little concentration of silica gel (silicon-Si), but did identify substantial amounts of sulfur-s and aluminum-Al (assumed to be ettringite) in the air voids. Some of these voids have cracks radiating from them leading us to conclude that the ettringite filled voids were a center of pressure causing the crack. The ettringite in the voids, after being subjected to sodium chloride (NaCl) brine, initially swells and then dissolves. The research has led to the conclusion that the premature deterioration may be due to ettringite and may have been mistakenly identified as Alkali-Silica reactivity (ASR).

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Amino-N is preserved because of the scarcity and nutritional importance of protein. Excretion requires its conversion to ammonia, later incorporated into urea. Under conditions of excess dietary energy, the body cannot easily dispose of the excess amino-N against the evolutively adapted schemes that prevent its wastage; thus ammonia and glutamine formation (and urea excretion) are decreased. High lipid (and energy) availability limits the utilisation of glucose, and high glucose spares the production of ammonium from amino acids, limiting the synthesis of glutamine and its utilisation by the intestine and kidney. The amino acid composition of the diet affects the production of ammonium depending on its composition and the individual amino acid catabolic pathways. Surplus amino acids enhance protein synthesis and growth, and the synthesis of non-protein-N-containing compounds. But these outlets are not enough; consequently, less-conventional mechanisms are activated, such as increased synthesis of NO∙ followed by higher nitrite (and nitrate) excretion and changes in the microbiota. There is also a significant production of N(2) gas, through unknown mechanisms. Health consequences of amino-N surplus are difficult to fathom because of the sparse data available, but it can be speculated that the effects may be negative, largely because the fundamental N homeostasis is stretched out of normalcy, forcing the N removal through pathways unprepared for that task. The unreliable results of hyperproteic diets, and part of the dysregulation found in the metabolic syndrome may be an unwanted consequence of this N disposal conflict.

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Contemporary coronary magnetic resonance angiography techniques suffer from signal-to-noise ratio (SNR) constraints. We propose a method to enhance SNR in gradient echo coronary magnetic resonance angiography by using sensitivity encoding (SENSE). While the use of sensitivity encoding to improve SNR seems counterintuitive, it can be exploited by reducing the number of radiofrequency excitations during the acquisition window while lowering the signal readout bandwidth, therefore improving the radiofrequency receive to radiofrequency transmit duty cycle. Under certain conditions, this leads to improved SNR. The use of sensitivity encoding for improved SNR in three-dimensional coronary magnetic resonance angiography is investigated using numerical simulations and an in vitro and an in vivo study. A maximum 55% SNR enhancement for coronary magnetic resonance angiography was found both in vitro and in vivo, which is well consistent with the numerical simulations. This method is most suitable for spoiled gradient echo coronary magnetic resonance angiography in which a high temporal and spatial resolution is required.

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In this paper, mixed spectral-structural kernel machines are proposed for the classification of very-high resolution images. The simultaneous use of multispectral and structural features (computed using morphological filters) allows a significant increase in classification accuracy of remote sensing images. Subsequently, weighted summation kernel support vector machines are proposed and applied in order to take into account the multiscale nature of the scene considered. Such classifiers use the Mercer property of kernel matrices to compute a new kernel matrix accounting simultaneously for two scale parameters. Tests on a Zurich QuickBird image show the relevance of the proposed method : using the mixed spectral-structural features, the classification accuracy increases of about 5%, achieving a Kappa index of 0.97. The multikernel approach proposed provide an overall accuracy of 98.90% with related Kappa index of 0.985.

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The objective of this work was to evaluate sampling density on the prediction accuracy of soil orders, with high spatial resolution, in a viticultural zone of Serra Gaúcha, Southern Brazil. A digital elevation model (DEM), a cartographic base, a conventional soil map, and the Idrisi software were used. Seven predictor variables were calculated and read along with soil classes in randomly distributed points, with sampling densities of 0.5, 1, 1.5, 2, and 4 points per hectare. Data were used to train a decision tree (Gini) and three artificial neural networks: adaptive resonance theory, fuzzy ARTMap; self‑organizing map, SOM; and multi‑layer perceptron, MLP. Estimated maps were compared with the conventional soil map to calculate omission and commission errors, overall accuracy, and quantity and allocation disagreement. The decision tree was less sensitive to sampling density and had the highest accuracy and consistence. The SOM was the less sensitive and most consistent network. The MLP had a critical minimum and showed high inconsistency, whereas fuzzy ARTMap was more sensitive and less accurate. Results indicate that sampling densities used in conventional soil surveys can serve as a reference to predict soil orders in Serra Gaúcha.

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A new fast MR-venography approach using a high resolution True-FISP imaging sequence was investigated in 20 patients suffering from 23 deep vein thromboses. Diagnosis was proven by x-ray venography, CT or ultrasound examination. The presented technique allowed for clear thrombus visualization with a high contrast to the surrounding blood pool even in calf veins. Acquisition time was less than 10 minutes for imaging the pelvis and the legs. No contrast media was needed. The presented high resolution True-FISP MR-venography is a promising non-invasive, fast MR-venography approach for detection of deep venous thrombosis.

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Peer-reviewed