468 resultados para Converts


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TRPV4 ion channels function in epidermal keratinocytes and in innervating sensory neurons; however, the contribution of the channel in either cell to neurosensory function remains to be elucidated. We recently reported TRPV4 as a critical component of the keratinocyte machinery that responds to ultraviolet B (UVB) and functions critically to convert the keratinocyte into a pain-generator cell after excess UVB exposure. One key mechanism in keratinocytes was increased expression and secretion of endothelin-1, which is also a known pruritogen. Here we address the question of whether TRPV4 in skin keratinocytes functions in itch, as a particular form of "forefront" signaling in non-neural cells. Our results support this novel concept based on attenuated scratching behavior in response to histaminergic (histamine, compound 48/80, endothelin-1), not non-histaminergic (chloroquine) pruritogens in Trpv4 keratinocyte-specific and inducible knock-out mice. We demonstrate that keratinocytes rely on TRPV4 for calcium influx in response to histaminergic pruritogens. TRPV4 activation in keratinocytes evokes phosphorylation of mitogen-activated protein kinase, ERK, for histaminergic pruritogens. This finding is relevant because we observed robust anti-pruritic effects with topical applications of selective inhibitors for TRPV4 and also for MEK, the kinase upstream of ERK, suggesting that calcium influx via TRPV4 in keratinocytes leads to ERK-phosphorylation, which in turn rapidly converts the keratinocyte into an organismal itch-generator cell. In support of this concept we found that scratching behavior, evoked by direct intradermal activation of TRPV4, was critically dependent on TRPV4 expression in keratinocytes. Thus, TRPV4 functions as a pruriceptor-TRP in skin keratinocytes in histaminergic itch, a novel basic concept with translational-medical relevance.

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Activation triggers the exchange of subunits in Ca(2+)/calmodulin-dependent protein kinase II (CaMKII), an oligomeric enzyme that is critical for learning, memory, and cardiac function. The mechanism by which subunit exchange occurs remains elusive. We show that the human CaMKII holoenzyme exists in dodecameric and tetradecameric forms, and that the calmodulin (CaM)-binding element of CaMKII can bind to the hub of the holoenzyme and destabilize it to release dimers. The structures of CaMKII from two distantly diverged organisms suggest that the CaM-binding element of activated CaMKII acts as a wedge by docking at intersubunit interfaces in the hub. This converts the hub into a spiral form that can release or gain CaMKII dimers. Our data reveal a three-way competition for the CaM-binding element, whereby phosphorylation biases it towards the hub interface, away from the kinase domain and calmodulin, thus unlocking the ability of activated CaMKII holoenzymes to exchange dimers with unactivated ones.

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Activation triggers the exchange of subunits in Ca(2+)/calmodulin-dependent protein kinase II (CaMKII), an oligomeric enzyme that is critical for learning, memory, and cardiac function. The mechanism by which subunit exchange occurs remains elusive. We show that the human CaMKII holoenzyme exists in dodecameric and tetradecameric forms, and that the calmodulin (CaM)-binding element of CaMKII can bind to the hub of the holoenzyme and destabilize it to release dimers. The structures of CaMKII from two distantly diverged organisms suggest that the CaM-binding element of activated CaMKII acts as a wedge by docking at intersubunit interfaces in the hub. This converts the hub into a spiral form that can release or gain CaMKII dimers. Our data reveal a three-way competition for the CaM-binding element, whereby phosphorylation biases it towards the hub interface, away from the kinase domain and calmodulin, thus unlocking the ability of activated CaMKII holoenzymes to exchange dimers with unactivated ones.

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In this paper, we describe how the pathfinder algorithm converts relatedness ratings of concept pairs to concept maps; we also present how this algorithm has been used to develop the Concept Maps for Learning website (www.conceptmapsforlearning.com) based on the principles of effective formative assessment. The pathfinder networks, one of the network representation tools, claim to help more students memorize and recall the relations between concepts than spatial representation tools (such as Multi- Dimensional Scaling). Therefore, the pathfinder networks have been used in various studies on knowledge structures, including identifying students’ misconceptions. To accomplish this, each student’s knowledge map and the expert knowledge map are compared via the pathfinder software, and the differences between these maps are highlighted. After misconceptions are identified, the pathfinder software fails to provide any feedback on these misconceptions. To overcome this weakness, we have been developing a mobile-based concept mapping tool providing visual, textual and remedial feedback (ex. videos, website links and applets) on the concept relations. This information is then placed on the expert concept map, but not on the student’s concept map. Additionally, students are asked to note what they understand from given feedback, and given the opportunity to revise their knowledge maps after receiving various types of feedback.

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Since core-collapse supernova simulations still struggle to produce robust neutrino-driven explosions in 3D, it has been proposed that asphericities caused by convection in the progenitor might facilitate shock revival by boosting the activity of non-radial hydrodynamic instabilities in the post-shock region. We investigate this scenario in depth using 42 relativistic 2D simulations with multigroup neutrino transport to examine the effects of velocity and density perturbations in the progenitor for different perturbation geometries that obey fundamental physical constraints (like the anelastic condition). As a framework for analysing our results, we introduce semi-empirical scaling laws relating neutrino heating, average turbulent velocities in the gain region, and the shock deformation in the saturation limit of non-radial instabilities. The squared turbulent Mach number, 〈Ma2〉, reflects the violence of aspherical motions in the gain layer, and explosive runaway occurs for 〈Ma2〉 ≳ 0.3, corresponding to a reduction of the critical neutrino luminosity by ∼25∼25 per cent compared to 1D. In the light of this theory, progenitor asphericities aid shock revival mainly by creating anisotropic mass flux on to the shock: differential infall efficiently converts velocity perturbations in the progenitor into density perturbations δρ/ρ at the shock of the order of the initial convective Mach number Maprog. The anisotropic mass flux and ram pressure deform the shock and thereby amplify post-shock turbulence. Large-scale (ℓ = 2, ℓ = 1) modes prove most conducive to shock revival, whereas small-scale perturbations require unrealistically high convective Mach numbers. Initial density perturbations in the progenitor are only of the order of Ma2progMaprog2 and therefore play a subdominant role.

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The Highway Safety Manual (HSM) is the compilation of national safety research that provides quantitative methods for analyzing highway safety. The HSM presents crash modification functions related to freeway work zone characteristics such as work zone duration and length. These crash modification functions were based on freeway work zones with high traffic volumes in California. When the HSM-referenced model was calibrated for Missouri, the value was 3.78, which is not ideal since it is significantly larger than 1. Therefore, new models were developed in this study using Missouri data to capture geographical, driver behavior, and other factors in the Midwest. Also, new models for expressway and rural two-lane work zones that barely were studied in the literature were developed. A large sample of 20,837 freeway, 8,993 expressway, and 64,476 rural two-lane work zones in Missouri was analyzed to derive 15 work zone crash prediction models. The most appropriate samples of 1,546 freeway, 1,189 expressway, and 6,095 rural two-lane work zones longer than 0.1 mile and with a duration of greater than 10 days were used to make eight, four, and three models, respectively. A challenging question for practitioners is always how to use crash prediction models to make the best estimation of work zone crash count. To solve this problem, a user-friendly software tool was developed in a spreadsheet format to predict work zone crashes based on work zone characteristics. This software selects the best model, estimates the work zone crashes by severity, and converts them to monetary values using standard crash estimates. This study also included a survey of departments of transportation (DOTs), Federal Highway Administration (FHWA) representatives, and contractors to assess the current state of the practice regarding work zone safety. The survey results indicate that many agencies look at work zone safety informally using engineering judgment. Respondents indicated that they would like a tool that could help them to balance work zone safety across projects by looking at crashes and user costs.

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Provenance plays a pivotal in tracing the origin of something and determining how and why something had occurred. With the emergence of the cloud and the benefits it encompasses, there has been a rapid proliferation of services being adopted by commercial and government sectors. However, trust and security concerns for such services are on an unprecedented scale. Currently, these services expose very little internal working to their customers; this can cause accountability and compliance issues especially in the event of a fault or error, customers and providers are left to point finger at each other. Provenance-based traceability provides a mean to address part of this problem by being able to capture and query events occurred in the past to understand how and why it took place. However, due to the complexity of the cloud infrastructure, the current provenance models lack the expressibility required to describe the inner-working of a cloud service. For a complete solution, a provenance-aware policy language is also required for operators and users to define policies for compliance purpose. The current policy standards do not cater for such requirement. To address these issues, in this paper we propose a provenance (traceability) model cProv, and a provenance-aware policy language (cProvl) to capture traceability data, and express policies for validating against the model. For implementation, we have extended the XACML3.0 architecture to support provenance, and provided a translator that converts cProvl policy and request into XACML type.

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Face à la diminution des ressources énergétiques et à l’augmentation de la pollution des énergies fossiles, de très nombreuses recherches sont actuellement menées pour produire de l’énergie propre et durable et pour réduire l’utilisation des sources d’énergies fossiles caractérisées par leur production intrinsèque des gaz à effet de serre. La pile à combustible à membrane échangeuse de protons (PEMFC) est une technologie qui prend de plus en plus d’ampleur pour produire l’énergie qui s’inscrit dans un contexte de développement durable. La PEMFC est un dispositif électrochimique qui fonctionne selon le principe inverse de l’électrolyse de l’eau. Elle convertit l’énergie de la réaction chimique entre l’hydrogène et l’oxygène (ou l’air) en puissance électrique, chaleur et eau; son seul rejet dans l’atmosphère est de la vapeur d’eau. Une pile de type PEMFC est constituée d’un empilement Électrode-Membrane-Électrode (EME) où la membrane consiste en un électrolyte polymère solide séparant les deux électrodes (l’anode et la cathode). Cet ensemble est intégré entre deux plaques bipolaires (BP) qui permettent de collecter le courant électrique et de distribuer les gaz grâce à des chemins de circulation gravés sur chacune de ses deux faces. La plupart des recherches focalisent sur la PEMFC afin d’améliorer ses performances électriques et sa durabilité et aussi de réduire son coût de production. Ces recherches portent sur le développement et la caractérisation des divers éléments de ce type de pile; y compris les éléments les plus coûteux et les plus massifs, tels que les plaques bipolaires. La conception de ces plaques doit tenir compte de plusieurs paramètres : elles doivent posséder une bonne perméabilité aux gaz et doivent combiner les propriétés de résistance mécanique, de stabilité chimique et thermique ainsi qu’une conductivité électrique élevée. Elles doivent aussi permettre d’évacuer adéquatement la chaleur générée dans le cœur de la cellule. Les plaques bipolaires métalliques sont pénalisées par leur faible résistance à la corrosion et celles en graphite sont fragiles et leur coût de fabrication est élevé (dû aux phases d’usinage des canaux de cheminement des gaz). C’est pourquoi de nombreuses recherches sont orientées vers le développement d’un nouveau concept de plaques bipolaires. La voie la plus prometteuse est de remplacer les matériaux métalliques et le graphite par des composites à matrice polymère. Les plaques bipolaires composites apparaissent attrayantes en raison de leur facilité de mise en œuvre et leur faible coût de production mais nécessitent une amélioration de leurs propriétés électriques et mécaniques, d’où l’objectif principal de cette thèse dans laquelle on propose: i) un matériau nanocomposite développé par extrusion bi-vis qui est à base de polymères chargés d’additifs solides conducteurs, incluant des nanotubes de carbone. ii) fabriquer un prototype de plaque bipolaire à partir de ces matériaux en utilisant le procédé de compression à chaud avec un refroidissement contrôlé. Dans ce projet, deux polymères thermoplastiques ont été utilisés, le polyfluorure de vinylidène (PVDF) et le polyéthylène téréphtalate (PET). Les charges électriquement conductrices sélectionnées sont: le noir de carbone, le graphite et les nanotubes de carbones. La combinaison de ces charges conductrices a été aussi étudiée visant à obtenir des formulations optimisées. La conductivité électrique à travers l’épaisseur des échantillons développés ainsi que leurs propriétés mécaniques ont été soigneusement caractérisées. Les résultats ont montré que non seulement la combinaison entre les charges conductrices influence les propriétés électriques et mécaniques des prototypes développés, mais aussi la distribution de ces charges (qui de son côté dépend de leur nature, leur taille et leurs propriétés de surface), avait aidé à améliorer les propriétés visées. Il a été observé que le traitement de surface des nanotubes de carbone avait aidé à l’amélioration de la conductivité électrique et la résistance mécanique des prototypes. Le taux de cristallinité généré durant le procédé de moulage par compression des prototypes de plaques bipolaires ainsi que la cinétique de cristallisation jouent un rôle important pour l’optimisation des propriétés électriques et mécaniques visées.

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Targeted cancer therapy aims to disrupt aberrant cellular signalling pathways. Biomarkers are surrogates of pathway state, but there is limited success in translating candidate biomarkers to clinical practice due to the intrinsic complexity of pathway networks. Systems biology approaches afford better understanding of complex, dynamical interactions in signalling pathways targeted by anticancer drugs. However, adoption of dynamical modelling by clinicians and biologists is impeded by model inaccessibility. Drawing on computer games technology, we present a novel visualisation toolkit, SiViT, that converts systems biology models of cancer cell signalling into interactive simulations that can be used without specialist computational expertise. SiViT allows clinicians and biologists to directly introduce for example loss of function mutations and specific inhibitors. SiViT animates the effects of these introductions on pathway dynamics, suggesting further experiments and assessing candidate biomarker effectiveness. In a systems biology model of Her2 signalling we experimentally validated predictions using SiViT, revealing the dynamics of biomarkers of drug resistance and highlighting the role of pathway crosstalk. No model is ever complete: the iteration of real data and simulation facilitates continued evolution of more accurate, useful models. SiViT will make accessible libraries of models to support preclinical research, combinatorial strategy design and biomarker discovery.

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The urokinase plasminogen activator (uPA) system (uPAS) comprises the uPA, its cell membrane receptor (uPAR) and two specific inhibitors, the plasminogen activator inhibitor 1 (PAI-1) and 2 (PAI-2). The uPA converts the plasminogen in the serine protease plasmin, involved in a number of physiopathological processes requiring basement membrane (BM) or extracellular matrix (ECM) remodelling, including tumor progression and metastasis. The tumor-promoting role of PAS is not limited to the degradation of ECM and BM required for local diffusion and spread to distant sites of malignant cells, but widens to tumor cell proliferation, adhesion and migration, intravasation, growth at the metastatic site and neoangiogenesis. The relevance of uPAS in cancer progression has been confirmed by several studies which documented an increased expression of uPA, uPAR and PAI-1 in different human malignancies, and a positive correlation between the levels of one or more of them and a poor prognosis. For these reasons, the uPAS components have aroused considerable interest as suitable targets for anticancer therapy, and several pharmacological approaches aimed at inhibiting the uPA and/or uPAR expression or function in preclinical and clinical settings have been described. In the present manuscript, we will first glance at uPAS biological functions in human cancer progression and its clinical significance in terms of prognosis and therapy. We will then review the main findings regarding expression and function of uPAS components in thyroid cancer tissues along with the experimental and clinical evidence suggesting its potential value as molecular prognostic marker and therapeutic target in thyroid cancer patients.

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The blast furnace is the main ironmaking production unit in the world which converts iron ore with coke and hot blast into liquid iron, hot metal, which is used for steelmaking. The furnace acts as a counter-current reactor charged with layers of raw material of very different gas permeability. The arrangement of these layers, or burden distribution, is the most important factor influencing the gas flow conditions inside the furnace, which dictate the efficiency of the heat transfer and reduction processes. For proper control the furnace operators should know the overall conditions in the furnace and be able to predict how control actions affect the state of the furnace. However, due to high temperatures and pressure, hostile atmosphere and mechanical wear it is very difficult to measure internal variables. Instead, the operators have to rely extensively on measurements obtained at the boundaries of the furnace and make their decisions on the basis of heuristic rules and results from mathematical models. It is particularly difficult to understand the distribution of the burden materials because of the complex behavior of the particulate materials during charging. The aim of this doctoral thesis is to clarify some aspects of burden distribution and to develop tools that can aid the decision-making process in the control of the burden and gas distribution in the blast furnace. A relatively simple mathematical model was created for simulation of the distribution of the burden material with a bell-less top charging system. The model developed is fast and it can therefore be used by the operators to gain understanding of the formation of layers for different charging programs. The results were verified by findings from charging experiments using a small-scale charging rig at the laboratory. A basic gas flow model was developed which utilized the results of the burden distribution model to estimate the gas permeability of the upper part of the blast furnace. This combined formulation for gas and burden distribution made it possible to implement a search for the best combination of charging parameters to achieve a target gas temperature distribution. As this mathematical task is discontinuous and non-differentiable, a genetic algorithm was applied to solve the optimization problem. It was demonstrated that the method was able to evolve optimal charging programs that fulfilled the target conditions. Even though the burden distribution model provides information about the layer structure, it neglects some effects which influence the results, such as mixed layer formation and coke collapse. A more accurate numerical method for studying particle mechanics, the Discrete Element Method (DEM), was used to study some aspects of the charging process more closely. Model charging programs were simulated using DEM and compared with the results from small-scale experiments. The mixed layer was defined and the voidage of mixed layers was estimated. The mixed layer was found to have about 12% less voidage than layers of the individual burden components. Finally, a model for predicting the extent of coke collapse when heavier pellets are charged over a layer of lighter coke particles was formulated based on slope stability theory, and was used to update the coke layer distribution after charging in the mathematical model. In designing this revision, results from DEM simulations and charging experiments for some charging programs were used. The findings from the coke collapse analysis can be used to design charging programs with more stable coke layers.

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The business environment context points at the necessity of new forms of management for the sustainable competitiveness of organizations through time. Coopetition is characterized as an alternative in the interaction of different actors, which compete and cooperate simultaneously, in the pursuit of common goals. This dual relation, within a gain-increasing perspective, converts competitors into partners and fosters competitiveness, especially that of organizations within a specific sector. The field of competitive intelligence has, in its turn, assisted organizations, individually, in the systematization of information valuable to decision-making processes, which benefits competitiveness. It follows that it is possible to combine coopetition and competitive intelligence in a systematized process of sectorial intelligence for coopetitive relations. The general aim of this study is, therefore, to put forth a model of sectorial coopetitive intelligence. The methodological outlining of the study is characterized as a mixed approach (quantitative and qualitative methods), of an applied nature, of exploratory and descriptive aims. The Coordination of the Strategic Roadmapping Project for the Future of Paraná's Industry is the selected object of investigation. Protocols have been designed to collect primary and secondary data. In the collection of the primary ata, online questionary were sent to the sectors selected for examination. A total of 149 answers to the online questionary were obtained, and interviews were performed with all embers of the technical team of the Coordination, in a total of five interviewees. After the collection, all the data were tabulated, analyzed and validated by means of focal groups with the same five members of the Coordination technical team, and interviews were performed with a representative of each of the four sectors selected, in a total of nine participants in the validation. The results allowed the systematization of a sectorial coopetitive intelligence model called ICoops. This model is characterized by five stages, namely, planning, collection, nalysis, project development, dissemination and evaluation. Each stage is detailed in inputs, activities and outputs. The results suggest that sectorial coopetition is motivated mainly by knowledge sharing, technological development, investment in R&D, innovation, chain integration and resource complementation. The importance of a neutral institution has been recognized as a facilitator and incentive to the approximation of organizations. Among the main difficulties are the financing of the projects, the adhesion of new members, the lack of tools for the analysis of information and the dissemination of the actions.

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This paper reports some experiments in using SVG (Scalable Vector Graphics), rather than the browser default of (X)HTML/CSS, as a potential Web-based rendering technology, in an attempt to create an approach that integrates the structural and display aspects of a Web document in a single XML-compliant envelope. Although the syntax of SVG is XML based, the semantics of the primitive graphic operations more closely resemble those of page description languages such as PostScript or PDF. The principal usage of SVG, so far, is for inserting complex graphic material into Web pages that are predominantly controlled via (X)HTML and CSS. The conversion of structured and unstructured PDF into SVG is discussed. It is found that unstructured PDF converts into pages of SVG with few problems, but difficulties arise when one attempts to map the structural components of a Tagged PDF into an XML skeleton underlying the corresponding SVG. These difficulties are not fundamentally syntactic; they arise largely because browsers are innately bound to (X)HTML/CSS as their default rendering model. Some suggestions are made for ways in which SVG could be more totally integrated into browser functionality, with the possibility that future browsers might be able to use SVG as their default rendering paradigm.

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Strigolactones are a group of plant compounds of diverse but related chemical structures. They have similar bioactivity across a broad range of plant species, act to optimize plant growth and development, and promote soil microbe interactions. Carlactone, a common precursor to strigolactones, is produced by conserved enzymes found in a number of diverse species. Versions of the MORE AXILLARY GROWTH1 (MAX1) cytochrome P450 from rice and Arabidopsis thaliana make specific subsets of strigolactones from carlactone. However, the diversity of natural strigolactones suggests that additional enzymes are involved and remain to be discovered. Here, we use an innovative method that has revealed a missing enzyme involved in strigolactone metabolism. By using a transcriptomics approach involving a range of treatments that modify strigolactone biosynthesis gene expression coupled with reverse genetics, we identified LATERAL BRANCHING OXIDOREDUCTASE (LBO), a gene encoding an oxidoreductase-like enzyme of the 2-oxoglutarate and Fe(II)-dependent dioxygenase superfamily. Arabidopsis lbo mutants exhibited increased shoot branching, but the lbo mutation did not enhance the max mutant phenotype. Grafting indicated that LBO is required for a graft-transmissible signal that, in turn, requires a product of MAX1. Mutant lbo backgrounds showed reduced responses to carlactone, the substrate of MAX1, and methyl carlactonoate (MeCLA), a product downstream of MAX1. Furthermore, lbo mutants contained increased amounts of these compounds, and the LBO protein specifically converts MeCLA to an unidentified strigolactone-like compound. Thus, LBO function may be important in the later steps of strigolactone biosynthesis to inhibit shoot branching in Arabidopsis and other seed plants.

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This paper will address questions of identity that male Muslim converts in São Paulo, Brazil face after adopting Islam. Specifically, it will analyze how they place their religion into notions of what it means to be Brazilian. Furthermore, this paper will show how many of these converts use Islam as a way to reconstruct their personal identities. Finally, it will argue that by becoming Muslims, they embrace a transnational religious identity. This paper will seek to show how conversion to Islam in São Paulo can significantly influence how individuals articulate notions of Brazilian national identity and belonging to the nation.