927 resultados para Multiple Change-point Analysis


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The RII beta regulatory subunit of cAMP-dependent protein kinase (PKA) contains an autophosphorylation site and a nuclear location signal, KKRK. We approached the structure-function analysis of RII beta by using site-directed mutagenesis. Ser114 (the autophosphorylation site) of human RII beta was replaced with Ala (RII beta-P) or Arg264 of KKRK was replaced with Met (RII beta-K). ras-transformed NIH 3T3 (DT) cells were transfected with expression vectors for RII beta, RII beta-P, and RII beta-K, and the effects on PKA isozyme distribution and transformation properties were analyzed. DT cells contained PKA-I and PKA-II isozymes in a 1:2 ratio. Over-expression of wild-type or mutant RII beta resulted in an increase in PKA-II and the elimination of PKA-I. Only wild-type RII beta cells demonstrated inhibition of both anchorage-dependent and -independent growth and phenotypic change. The growth inhibitory effect of RII beta overexpression was not due to suppression of ras expression but was correlated with nuclear accumulation of RII beta. DT cells demonstrated growth inhibition and phenotypic change upon treatment with 8-Cl-cAMP. RII beta-P or RII beta-K cells failed to respond to 8-Cl-cAMP. These data suggest that autophosphorylation and nuclear location signal sequences are integral parts of the growth regulatory mechanism of RII beta.

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Climate change is critically impacting the environment and economy at the local level. County governments have an opportunity to adopt climate change policies that address local environmental and economic concerns. The Colorado counties of Boulder, Gunnison, and Pitkin have all adopted some form of climate change policies. There are some components of each of these policies that are more effective in terms of economic, environmental, and community benefits. An effective climate change policy clearly states specific cost analyses, environmental impacts at the local level, the relationship between impacts and the community, and the economic benefits of policy adoption. This Capstone project addresses specific cost and energy analyses and provides a beneficial policy framework for county governments.

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In the present work, we provide a systematic analysis about all tine streams involved in the zone connecting two consecutive sections for the design of distillation columns with different thermal feed conditions, product extractions and heat additions or withdrawals. This analysis allows a better understanding of what happens on a feed or side draw (of mass or energy) stage, what compositions are or are not in equilibrium, and the impact on internal liquid and vapor flows.

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The complete characterization of rock masses implies the acquisition of information of both, the materials which compose the rock mass and the discontinuities which divide the outcrop. Recent advances in the use of remote sensing techniques – such as Light Detection and Ranging (LiDAR) – allow the accurate and dense acquisition of 3D information that can be used for the characterization of discontinuities. This work presents a novel methodology which allows the calculation of the normal spacing of persistent and non-persistent discontinuity sets using 3D point cloud datasets considering the three dimensional relationships between clusters. This approach requires that the 3D dataset has been previously classified. This implies that discontinuity sets are previously extracted, every single point is labeled with its corresponding discontinuity set and every exposed planar surface is analytically calculated. Then, for each discontinuity set the method calculates the normal spacing between an exposed plane and its nearest one considering 3D space relationship. This link between planes is obtained calculating for every point its nearest point member of the same discontinuity set, which provides its nearest plane. This allows calculating the normal spacing for every plane. Finally, the normal spacing is calculated as the mean value of all the normal spacings for each discontinuity set. The methodology is validated through three cases of study using synthetic data and 3D laser scanning datasets. The first case illustrates the fundamentals and the performance of the proposed methodology. The second and the third cases of study correspond to two rock slopes for which datasets were acquired using a 3D laser scanner. The second case study has shown that results obtained from the traditional and the proposed approaches are reasonably similar. Nevertheless, a discrepancy between both approaches has been found when the exposed planes members of a discontinuity set were hard to identify and when the planes pairing was difficult to establish during the fieldwork campaign. The third case study also has evidenced that when the number of identified exposed planes is high, the calculated normal spacing using the proposed approach is minor than those using the traditional approach.

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The Iterative Closest Point algorithm (ICP) is commonly used in engineering applications to solve the rigid registration problem of partially overlapped point sets which are pre-aligned with a coarse estimate of their relative positions. This iterative algorithm is applied in many areas such as the medicine for volumetric reconstruction of tomography data, in robotics to reconstruct surfaces or scenes using range sensor information, in industrial systems for quality control of manufactured objects or even in biology to study the structure and folding of proteins. One of the algorithm’s main problems is its high computational complexity (quadratic in the number of points with the non-optimized original variant) in a context where high density point sets, acquired by high resolution scanners, are processed. Many variants have been proposed in the literature whose goal is the performance improvement either by reducing the number of points or the required iterations or even enhancing the complexity of the most expensive phase: the closest neighbor search. In spite of decreasing its complexity, some of the variants tend to have a negative impact on the final registration precision or the convergence domain thus limiting the possible application scenarios. The goal of this work is the improvement of the algorithm’s computational cost so that a wider range of computationally demanding problems from among the ones described before can be addressed. For that purpose, an experimental and mathematical convergence analysis and validation of point-to-point distance metrics has been performed taking into account those distances with lower computational cost than the Euclidean one, which is used as the de facto standard for the algorithm’s implementations in the literature. In that analysis, the functioning of the algorithm in diverse topological spaces, characterized by different metrics, has been studied to check the convergence, efficacy and cost of the method in order to determine the one which offers the best results. Given that the distance calculation represents a significant part of the whole set of computations performed by the algorithm, it is expected that any reduction of that operation affects significantly and positively the overall performance of the method. As a result, a performance improvement has been achieved by the application of those reduced cost metrics whose quality in terms of convergence and error has been analyzed and validated experimentally as comparable with respect to the Euclidean distance using a heterogeneous set of objects, scenarios and initial situations.

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.bin files should be opened using CloudCompare

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Supplementary Material: J.A. REYES-LABARTA, M.D. SERRANO and A. MARCILLA. ANALYSIS OF THE CONNECTING ZONE BETWEEN CONSECUTIVE SECTIONS IN DISTILLATION COLUMNS COVERING MULTIPLE FEEDS, PRODUCTS AND HEAT TRANSFER STAGES. Latin American Applied Research an International Journal of Chemical Engineering. 2014, vol. 44(4), 307-312 (http://www.laar.uns.edu.ar/indexes/artic_v4404/44_04_307.pdf)

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The March 2014 European Council could enter the history books as a turning point, not only in the EU’s relations with Russia but also in its role as a foreign policy actor. Events in Ukraine inevitably dominated the Summit, with EU leaders adopting a balanced approach aimed at achieving three key objectives – de-escalation, containment/deterrence and cooperation – based on political and economic support for Ukraine, increased but limited pressure on Russia, and moves to strengthen ties with other EU neighbours. The Summit also discussed a range of economic and environmental policy issues, with the situation in Ukraine casting a long shadow over the discussion on energy policy, but failed to reach agreement on the EU’s climate goals to 2030, or to put more flesh on the bones of calls for a European “industrial renaissance”. However, two other developments were particularly significant: the creation of the second pillar of the future banking union, establishing a single regime for winding down failing banks; and changes to the savings tax directive, bringing years of negotiation to an end.

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This paper examines the functioning of energy efficiency standards and labeling policies for air conditioners in Japan. The results of our empirical analysis suggest that consumers respond more to label information, which benchmarks the energy efficiency performance of each product to a pre-specified target, than to direct performance measures. This finding provides justification for the setting, and regular updating, of target standards as well as their use in calculating relative performance measures. We also find, through graphical analysis, that air conditioner manufacturers face a tradeoff between energy efficiency and product compactness when they develop their products. This tradeoff, combined with the semi-regular upward revision of minimum energy efficiency standards, has led to the growth in indoor unit size of air conditioners in recent years. In the face of this phenomenon, regulatory rules were revised so that manufacturers could adhere to less stringent standards if the indoor unit size of their product remains below a certain size. Our demand estimates provide no evidence that larger indoor unit size causes disutility to consumers. It is therefore possible that the regulatory change was not warranted from a consumer welfare point of view.

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Multiple sclerosis (MS) is a prevalent neurological disease of complex etiology. Here, we describe the characterization of a multi-incident MS family that nominated a rare missense variant (p.G420D) in plasminogen (PLG) as a putative genetic risk factor for MS. Genotyping of PLG p.G420D (rs139071351) in 2160 MS patients, and 886 controls from Canada, identified 10 additional probands, two sporadic patients and one control with the variant. Segregation in families harboring the rs139071351 variant, identified p.G420D in 26 out of 30 family members diagnosed with MS, 14 unaffected parents, and 12 out of 30 family members not diagnosed with disease. Despite considerably reduced penetrance, linkage analysis supports cosegregation of PLG p.G420D and disease. Genotyping of PLG p.G420D in 14446 patients, and 8797 controls from Canada, France, Spain, Germany, Belgium, and Austria failed to identify significant association with disease (P = 0.117), despite an overall higher prevalence in patients (OR = 1.32; 95% CI = 0.93-1.87). To assess whether additional rare variants have an effect on MS risk, we sequenced PLG in 293 probands, and genotyped all rare variants in cases and controls. This analysis identified nine rare missense variants, and although three of them were exclusively observed in MS patients, segregation does not support pathogenicity. PLG is a plausible biological candidate for MS owing to its involvement in immune system response, blood-brain barrier permeability, and myelin degradation. Moreover, components of its activation cascade have been shown to present increased activity or expression in MS patients compared to controls; further studies are needed to clarify whether PLG is involved in MS susceptibility.

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Bibliographical footnotes.