992 resultados para Dynamic conditional execution
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Obedience has been thoroughly studied in social psychology, both in its positive and negative aspects. Nevertheless, in these empirical studies disobedience has been considered to be the opposite of obedience and indeed its negation. Instead, some recent studies suggest that if obedience to authority is important in ensuring the continuity of social and group life, disobedience is crucial, under some circumstances, in stopping the authority relationship from degenerating into an authoritarian relationship. In this perspective, disobedience may be conceived of as a protest undermining the legitimacy of authority, or else it can represent an instrument of the community for controlling the legitimacy of the authority's demands, becoming a factor safeguarding against authoritarianism. The aim of the present study was to empirically verify the dynamics existing between disobedience and obedience. The results show that people who attach importance to both obedience and disobedience in the relationship between the individual and society recognize the importance of democratic values and consider themselves responsible for the defence of human rights. Instead, people who only recognize the value of obedience and consider disobedience as a threat to the status quo are more authoritarian, individualistic people.
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For the execution of the scientific applications, different methods have been proposed to dynamically provide execution environments for such applications that hide the complexity of underlying distributed and heterogeneous infrastructures. Recently virtualization has emerged as a promising technology to provide such environments. Virtualization is a technology that abstracts away the details of physical hardware and provides virtualized resources for high-level scientific applications. Virtualization offers a cost-effective and flexible way to use and manage computing resources. Such an abstraction is appealing in Grid computing and Cloud computing for better matching jobs (applications) to computational resources. This work applies the virtualization concept to the Condor dynamic resource management system by using Condor Virtual Universe to harvest the existing virtual computing resources to their maximum utility. It allows existing computing resources to be dynamically provisioned at run-time by users based on application requirements instead of statically at design-time thereby lay the basis for efficient use of the available resources, thus providing way for the efficient use of the available resources.
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A high throughput method was designed to produce hyperpolarized gases by combining low-temperature dynamic nuclear polarization with a sublimation procedure. It is illustrated by applications to 129Xe nuclear magnetic resonance in xenon gas, leading to a signal enhancement of 3 to 4 orders of magnitude compared to the room-temperature thermal equilibrium signal at 7.05 T.
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MOTIVATION: Combinatorial interactions of transcription factors with cis-regulatory elements control the dynamic progression through successive cellular states and thus underpin all metazoan development. The construction of network models of cis-regulatory elements, therefore, has the potential to generate fundamental insights into cellular fate and differentiation. Haematopoiesis has long served as a model system to study mammalian differentiation, yet modelling based on experimentally informed cis-regulatory interactions has so far been restricted to pairs of interacting factors. Here, we have generated a Boolean network model based on detailed cis-regulatory functional data connecting 11 haematopoietic stem/progenitor cell (HSPC) regulator genes. RESULTS: Despite its apparent simplicity, the model exhibits surprisingly complex behaviour that we charted using strongly connected components and shortest-path analysis in its Boolean state space. This analysis of our model predicts that HSPCs display heterogeneous expression patterns and possess many intermediate states that can act as 'stepping stones' for the HSPC to achieve a final differentiated state. Importantly, an external perturbation or 'trigger' is required to exit the stem cell state, with distinct triggers characterizing maturation into the various different lineages. By focusing on intermediate states occurring during erythrocyte differentiation, from our model we predicted a novel negative regulation of Fli1 by Gata1, which we confirmed experimentally thus validating our model. In conclusion, we demonstrate that an advanced mammalian regulatory network model based on experimentally validated cis-regulatory interactions has allowed us to make novel, experimentally testable hypotheses about transcriptional mechanisms that control differentiation of mammalian stem cells. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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In the Morris water maze (MWM) task, proprioceptive information is likely to have a poor accuracy due to movement inertia. Hence, in this condition, dynamic visual information providing information on linear and angular acceleration would play a critical role in spatial navigation. To investigate this assumption we compared rat's spatial performance in the MWM and in the homing hole board (HB) tasks using a 1.5 Hz stroboscopic illumination. In the MWM, rats trained in the stroboscopic condition needed more time than those trained in a continuous light condition to reach the hidden platform. They expressed also little accuracy during the probe trial. In the HB task, in contrast, place learning remained unaffected by the stroboscopic light condition. The deficit in the MWM was thus complete, affecting both escape latency and discrimination of the reinforced area, and was thus task specific. This dissociation confirms that dynamic visual information is crucial to spatial navigation in the MWM whereas spatial navigation on solid ground is mediated by a multisensory integration, and thus less dependent on visual information.
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BACKGROUND: The ambition of most molecular biologists is the understanding of the intricate network of molecular interactions that control biological systems. As scientists uncover the components and the connectivity of these networks, it becomes possible to study their dynamical behavior as a whole and discover what is the specific role of each of their components. Since the behavior of a network is by no means intuitive, it becomes necessary to use computational models to understand its behavior and to be able to make predictions about it. Unfortunately, most current computational models describe small networks due to the scarcity of kinetic data available. To overcome this problem, we previously published a methodology to convert a signaling network into a dynamical system, even in the total absence of kinetic information. In this paper we present a software implementation of such methodology. RESULTS: We developed SQUAD, a software for the dynamic simulation of signaling networks using the standardized qualitative dynamical systems approach. SQUAD converts the network into a discrete dynamical system, and it uses a binary decision diagram algorithm to identify all the steady states of the system. Then, the software creates a continuous dynamical system and localizes its steady states which are located near the steady states of the discrete system. The software permits to make simulations on the continuous system, allowing for the modification of several parameters. Importantly, SQUAD includes a framework for perturbing networks in a manner similar to what is performed in experimental laboratory protocols, for example by activating receptors or knocking out molecular components. Using this software we have been able to successfully reproduce the behavior of the regulatory network implicated in T-helper cell differentiation. CONCLUSION: The simulation of regulatory networks aims at predicting the behavior of a whole system when subject to stimuli, such as drugs, or determine the role of specific components within the network. The predictions can then be used to interpret and/or drive laboratory experiments. SQUAD provides a user-friendly graphical interface, accessible to both computational and experimental biologists for the fast qualitative simulation of large regulatory networks for which kinetic data is not necessarily available.
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AIMS/HYPOTHESIS: betaTC-tet (H2(k)) is a conditional insulinoma cell line derived from transgenic mice expressing a tetracycline-regulated oncogene. Transgenic expression of several proteins implicated in the apoptotic pathways increase the resistance of betaTC-tet cells in vitro. We tested in vivo the sensitivity of the cells to rejection and the protective effect of genetic alterations in NOD mice. METHODS: betaTC-tet cells and genetically engineered lines expressing Bcl-2 (CDM3D), a dominant negative mutant of MyD88 or SOCS-1 were transplanted in diabetic female NOD mice or in male NOD mice with diabetes induced by high-dose streptozotocin. Survival of functional cell grafts in NOD-scid mice was also analyzed after transfer of splenocytes from diabetic NOD mice. Autoreactive T-cell hybridomas and splenocytes from diabetic NOD mice were stimulated by betaTC-tet cells. RESULTS: betaTC-tet cells and genetically engineered cell lines were all similarly rejected in diabetic NOD mice and in NOD-scid mice after splenocyte transfer. In 3- to 6-week-old male NOD mice treated with high-dose streptozotocin, the cells temporarily survived, in contrast with C57BL/6 mice treated with high-dose streptozotocin (indefinite survival) and untreated 3- to 6-week-old male NOD mice (rejection). The protective effect of high-dose streptozotocin was lost in older male NOD mice. betaTC-tet cells did not stimulate autoreactive T-cell hybridomas, but induced IL-2 secretion by splenocytes from diabetic NOD mice. CONCLUSION/INTERPRETATION: The autoimmune process seems to play an important role in the destruction of betaTC-tet cells in NOD mice. Genetic manipulations intended at increasing the resistance of beta cells were inefficient. Similar approaches should be tested in vivo as well as in vitro. High dose streptozotocin influences immune rejection and should be used with caution.
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Generación dinámica de interfaces web basadas en ficheros descriptivos XML para el control de la parametrización compleja y ejecución de programas por línea de comandos. La necesidad surge con la aplicación mlcoalsim, utilizada por investigadores de la UAB, cuya parametrización requiere la edición manual de un fichero de texto la sintaxis del cual es complicada y pesada. Con la generación de interfaces web se pretende ayudar a los usuarios en la correcta parametrización y ejecución de aplicaciones como mlcoalsim.
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The goal of this paper is to study the frequency of new product introductions in monopoly markets where demand is subject to transitory saturation. We focus on those types of goods for which consumers purchase at most one unit of each variety, but repeat purchases in the same product category. The model considers infinitely-lived, forward-looking consumers and firms. We show that the share of potential surplus that a monopolist is able to appropriate increases with the frequency of introduction of new products and the intensity of transitory saturation. If the latter is sufficiently strong then the rate of introduction of new products is higher than socially desirable (excessive dynamic product diversity.)
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In fear conditioning, an animal learns to associate an unconditioned stimulus (US), such as a shock, and a conditioned stimulus (CS), such as a tone, so that the presentation of the CS alone can trigger conditioned responses. Recent research on the lateral amygdala has shown that following cued fear conditioning, only a subset of higher-excitable neurons are recruited in the memory trace. Their selective deletion after fear conditioning results in a selective erasure of the fearful memory. I hypothesize that the recruitment of highly excitable neurons depends on responsiveness to stimuli, intrinsic excitability and local connectivity. In addition, I hypothesize that neurons recruited for an initial memory also participate in subsequent memories, and that changes in neuronal excitability affect secondary fear learning. To address these hypotheses, I will show that A) a rat can learn to associate two successive short-term fearful memories; B) neuronal populations in the LA are competitively recruited in the memory traces depending on individual neuronal advantages, as well as advantages granted by the local network. By performing two successive cued fear conditioning experiments, I found that rats were able to learn and extinguish the two successive short-term memories, when tested 1 hour after learning for each memory. These rats were equipped with a system of stable extracellular recordings that I developed, which allowed to monitor neuronal activity during fear learning. 233 individual putative pyramidal neurons could modulate their firing rate in response to the conditioned tone (conditioned neurons) and/or non- conditioned tones (generalizing neurons). Out of these recorded putative pyramidal neurons 86 (37%) neurons were conditioned to one or both tones. More precisely, one population of neurons encoded for a shared memory while another group of neurons likely encoded the memories' new features. Notably, in spite of a successful behavioral extinction, the firing rate of those conditioned neurons in response to the conditioned tone remained unchanged throughout memory testing. Furthermore, by analyzing the pre-conditioning characteristics of the conditioned neurons, I determined that it was possible to predict neuronal recruitment based on three factors: 1) initial sensitivity to auditory inputs, with tone-sensitive neurons being more easily recruited than tone- insensitive neurons; 2) baseline excitability levels, with more highly excitable neurons being more likely to become conditioned; and 3) the number of afferent connections received from local neurons, with neurons destined to become conditioned receiving more connections than non-conditioned neurons. - En conditionnement de la peur, un animal apprend à associer un stimulus inconditionnel (SI), tel un choc électrique, et un stimulus conditionné (SC), comme un son, de sorte que la présentation du SC seul suffit pour déclencher des réflexes conditionnés. Des recherches récentes sur l'amygdale latérale (AL) ont montré que, suite au conditionnement à la peur, seul un sous-ensemble de neurones plus excitables sont recrutés pour constituer la trace mnésique. Pour apprendre à associer deux sons au même SI, je fais l'hypothèse que les neurones entrent en compétition afin d'être sélectionnés lors du recrutement pour coder la trace mnésique. Ce recrutement dépendrait d'un part à une activation facilité des neurones ainsi qu'une activation facilité de réseaux de neurones locaux. En outre, je fais l'hypothèse que l'activation de ces réseaux de l'AL, en soi, est suffisante pour induire une mémoire effrayante. Pour répondre à ces hypothèses, je vais montrer que A) selon un processus de mémoire à court terme, un rat peut apprendre à associer deux mémoires effrayantes apprises successivement; B) des populations neuronales dans l'AL sont compétitivement recrutées dans les traces mnésiques en fonction des avantages neuronaux individuels, ainsi que les avantages consentis par le réseau local. En effectuant deux expériences successives de conditionnement à la peur, des rats étaient capables d'apprendre, ainsi que de subir un processus d'extinction, pour les deux souvenirs effrayants. La mesure de l'efficacité du conditionnement à la peur a été effectuée 1 heure après l'apprentissage pour chaque souvenir. Ces rats ont été équipés d'un système d'enregistrements extracellulaires stables que j'ai développé, ce qui a permis de suivre l'activité neuronale pendant l'apprentissage de la peur. 233 neurones pyramidaux individuels pouvaient moduler leur taux d'activité en réponse au son conditionné (neurones conditionnés) et/ou au son non conditionné (neurones généralisant). Sur les 233 neurones pyramidaux putatifs enregistrés 86 (37%) d'entre eux ont été conditionnés à un ou deux tons. Plus précisément, une population de neurones code conjointement pour un souvenir partagé, alors qu'un groupe de neurones différent code pour de nouvelles caractéristiques de nouveaux souvenirs. En particulier, en dépit d'une extinction du comportement réussie, le taux de décharge de ces neurones conditionné en réponse à la tonalité conditionnée est resté inchangée tout au long de la mesure d'apprentissage. En outre, en analysant les caractéristiques de pré-conditionnement des neurones conditionnés, j'ai déterminé qu'il était possible de prévoir le recrutement neuronal basé sur trois facteurs : 1) la sensibilité initiale aux entrées auditives, avec les neurones sensibles aux sons étant plus facilement recrutés que les neurones ne répondant pas aux stimuli auditifs; 2) les niveaux d'excitabilité des neurones, avec les neurones plus facilement excitables étant plus susceptibles d'être conditionnés au son ; et 3) le nombre de connexions reçues, puisque les neurones conditionné reçoivent plus de connexions que les neurones non-conditionnés. Enfin, nous avons constaté qu'il était possible de remplacer de façon satisfaisante le SI lors d'un conditionnement à la peur par des injections bilatérales de bicuculline, un antagoniste des récepteurs de l'acide y-Aminobutirique.
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A parts based model is a parametrization of an object class using a collection of landmarks following the object structure. The matching of parts based models is one of the problems where pairwise Conditional Random Fields have been successfully applied. The main reason of their effectiveness is tractable inference and learning due to the simplicity of involved graphs, usually trees. However, these models do not consider possible patterns of statistics among sets of landmarks, and thus they sufffer from using too myopic information. To overcome this limitation, we propoese a novel structure based on a hierarchical Conditional Random Fields, which we explain in the first part of this memory. We build a hierarchy of combinations of landmarks, where matching is performed taking into account the whole hierarchy. To preserve tractable inference we effectively sample the label set. We test our method on facial feature selection and human pose estimation on two challenging datasets: Buffy and MultiPIE. In the second part of this memory, we present a novel approach to multiple kernel combination that relies on stacked classification. This method can be used to evaluate the landmarks of the parts-based model approach. Our method is based on combining responses of a set of independent classifiers for each individual kernel. Unlike earlier approaches that linearly combine kernel responses, our approach uses them as inputs to another set of classifiers. We will show that we outperform state-of-the-art methods on most of the standard benchmark datasets.
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El consumo energético es un aspecto cada vez más importante en el diseño de microprocesadores. Este trabajo experimenta con una técnica de control del consumo, el escalado dinámico de tensión y frecuencia (DVFS, siglas en inglés), para determinar cuan efectiva es la misma en la ejecución de programas con diferentes cargas de trabajo, intensivas en cómputo o memoria. Además, se ha extendido la experimentación a varios núcleos de ejecución, permitiendo comprobar en que medida las características de la ejecución en una arquitectura multicore afecta al desempeño de dicha técnica.
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L'objectiu final d'aquest projecte és realitzar un Sistema Traçador d' Errors, però potser mésimportant és l'objectiu d'aprendre noves tecnologies, que sovint estan a disposició de l'usuari però l'usuari les desconeix.