960 resultados para dynamic causal modeling


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General signaling results in dynamic Tullock contests have been missing for long. The reason is the tractability of the problems. In this paper, an uninformed contestant with valuation vx competes against an informed opponent with valuation, either high vh or low vl. We show that; (i) When the hierarchy of valuations is vh ≥ vx ≥ vl, there is no pooling. Sandbagging is too costly for the high type. (ii) When the order of valuations is vx ≥ vh ≥ vl, there is no separation if vh and vl are close. Sandbagging is cheap due to the proximity of valuations. However, if vh and vx are close, there is no pooling. First period cost of pooling is high. (iii) For valuations satisfying vh ≥ vl ≥ vx, there is no separation if vh and vl are close. Bluffing in the first period is cheap for the low valuation type. Conversely, if vx and vl are close there is no pooling. Bluffing in the first stage is too costly. JEL: C72, C73, D44, D82. KEYWORDS: Signaling, Dynamic Contests, Non-existence, Sandbag Pooling, Bluff Pooling, Separating

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We study the properties of the well known Replicator Dynamics when applied to a finitely repeated version of the Prisoners' Dilemma game. We characterize the behavior of such dynamics under strongly simplifying assumptions (i.e. only 3 strategies are available) and show that the basin of attraction of defection shrinks as the number of repetitions increases. After discussing the difficulties involved in trying to relax the 'strongly simplifying assumptions' above, we approach the same model by means of simulations based on genetic algorithms. The resulting simulations describe a behavior of the system very close to the one predicted by the replicator dynamics without imposing any of the assumptions of the mathematical model. Our main conclusion is that mathematical and computational models are good complements for research in social sciences. Indeed, while computational models are extremely useful to extend the scope of the analysis to complex scenarios hard to analyze mathematically, formal models can be useful to verify and to explain the outcomes of computational models.

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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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A mathematical model is proposed to analyze the effects of acquired immunity on the transmission of schistosomiasis in the human host. From this model the prevalence curve dependent on four parameters can be obtained. These parameters were estimated fitting the data by the maximum likelihood method. The model showed a good retrieving capacity of real data from two endemic areas of schistosomiasis: Touros, Brazil (Schistosoma mansoni) and Misungwi, Tanzania (S. haematobium). Also, the average worm burden per person and the dispersion of parasite per person in the community can be obtained from the model. In this paper, the stabilizing effects of the acquired immunity assumption in the model are assessed in terms of the epidemiological variables as follows. Regarded to the prevalence curve, we calculate the confidence interval, and related to the average worm burden and the worm dispersion in the community, the sensitivity analysis (the range of the variation) of both variables with respect to their parameters is performed.

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This study compared adherence (persistence and execution) during pregnancy and postpartum in HIV-positive women having taken part in the adherence-enhancing program of the Community Pharmacy of the Department of Ambulatory Care and Community Medicine in Lausanne between 2004 and 2012. This interdisciplinary program combined electronic drug monitoring and semi-structured, repeated motivational interviews. This was a retrospective, observational study. Observation period spread over from first adherence visit after last menstruation until 6 months after childbirth. Medication-taking was recorded by electronic drug monitoring. Socio-demographic and delivery data were collected from Swiss HIV Cohort database. Adherence data, barriers and facilitators were collected from pharmacy database. Electronic data were reconciled with pill-count and interview notes in order to include reported pocket-doses. Execution was analyzed over 3-day periods by a mixed effect logistic model, separating time before and after childbirth. This model allowed us to estimate different time slopes for both periods and to show a sudden fall associated with childbirth. Twenty-five pregnant women were included. Median age was 29 (IQR: 26.5, 32.0), women were in majority black (n_17,68%) and took a cART combining protease and nucleoside reverse transcriptase inhibitors (n_24,96%). Eleven women (44%) were ART-naı¨ve at the beginning of pregnancy. Twenty women (80%) were included in the program because of pregnancy. Women were included at all stages of pregnancy. Six women (24%) stopped the program during pregnancy, 3 (12%) at delivery, 4 (16%) during postpartum and 12 (48%) stayed in program at the end of observation time. Median number of visits was 4 (3.0, 6.3) during pregnancy and 3 (0.8, 6.0) during postpartum. Execution was continuously high during pregnancy, low at beginning of postpartum and increased gradually during the 6 months of postpartum. Major barriers to adherence were medication adverse events and difficulties in daily routine. Facilitators were motivation for promoting child-health and social support. The dramatic drop and very slow increase in cART adherence during postpartum might result in viral rebound and drug resistance. Although much attention is devoted to pregnant women, interdisciplinary care should also be provided to women in the community during first trimester of postpartum to support them in sustaining cART adherence.

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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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The dissertation investigates some relevant metaphysical issues arising in the context of spacetime theories. In particular, the inquiry focuses on general relativity and canonical quantum gravity. A formal definition of spacetime theory is proposed and, against this framework, an analysis of the notions of general covariance, symmetry and background independence is performed. It is argued that many conceptual issues in general relativity and canonical quantum gravity derive from putting excessive emphasis on general covariance as an ontological prin-ciple. An original metaphysical position grounded in scientific essential- ism and causal realism (weak essentialism) is developed and defended. It is argued that, in the context of general relativity, weak essentialism supports spacetime substantivalism. It is also shown that weak essentialism escapes arguments from metaphysical underdetermination by positing a particular kind of causation, dubbed geometric. The proposed interpretive framework is then applied to Bohmian mechanics, pointing out that weak essentialism nicely fits into this theory. In the end, a possible Bohmian implementation of loop quantum gravity is considered, and such a Bohmian approach is interpreted in a geometric causal fashion. Under this interpretation, Bohmian loop quantum gravity straightforwardly commits us to an ontology of elementary extensions of space whose evolution is described by a non-local law. The causal mechanism underlying this evolution clarifies many conceptual issues related to the emergence of classical spacetime from the quantum regime. Although there is as yet no fully worked out physical theory of quantum gravity, it is argued that the proposed approach sets up a standard that proposals for a serious ontology in this field should meet.

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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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MOTIVATION: In silico modeling of gene regulatory networks has gained some momentum recently due to increased interest in analyzing the dynamics of biological systems. This has been further facilitated by the increasing availability of experimental data on gene-gene, protein-protein and gene-protein interactions. The two dynamical properties that are often experimentally testable are perturbations and stable steady states. Although a lot of work has been done on the identification of steady states, not much work has been reported on in silico modeling of cellular differentiation processes. RESULTS: In this manuscript, we provide algorithms based on reduced ordered binary decision diagrams (ROBDDs) for Boolean modeling of gene regulatory networks. Algorithms for synchronous and asynchronous transition models have been proposed and their corresponding computational properties have been analyzed. These algorithms allow users to compute cyclic attractors of large networks that are currently not feasible using existing software. Hereby we provide a framework to analyze the effect of multiple gene perturbation protocols, and their effect on cell differentiation processes. These algorithms were validated on the T-helper model showing the correct steady state identification and Th1-Th2 cellular differentiation process. AVAILABILITY: The software binaries for Windows and Linux platforms can be downloaded from http://si2.epfl.ch/~garg/genysis.html.

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El canvi climàtic del segle XXI és una realitat, hi ha moltes evidències científiques que indiquen que l’escalfament del sistema climàtic és inequívoc. Malgrat això, també hi ha moltes incerteses respecte els impactes que pot comportar aquest canvi climàtic global. L’objectiu d’aquest projecte és estudiar la possible evolució futura de tres variables climàtiques, que són el rang de la temperatura diürna a prop de la superfície (DTR), la temperatura mitjana a prop de la superfície (MT) i la precipitació mensual (PL_mes) i valorar l’exposició que poden experimentar diferents cobertes del sòl i diferents regions biogeogràfiques del continent europeu davant d’aquests possibles patrons de canvi. Per això s’han utilitzat Models Climàtics Globals que fan projeccions de variables climàtiques que permeten preveure el possible clima futur. Mitjançant l’aplicatiu informàtic Tetyn s’han extret els paràmetres climàtics dels conjunts de dades del Tyndall Centre for Climate Change Research, del futur (TYN SC) i del passat (CRU TS). Les variables obtingudes s’han processat amb eines de sistemes d’informació geogràfica (SIG) per obtenir els patrons de canvi de les variables a cada coberta del sòl. Els resultats obtinguts mostren que hi ha una gran variabilitat, que augmenta amb el temps, entre els diferents models climàtics i escenaris considerats, que posa de manifest la incertesa associada a la modelització climàtica, a la generació d’escenaris d’emissions i a la naturalesa dinàmica i no determinista del sistema climàtic. Però en general, mostren que les glaceres seran una de les cobertes més exposades al canvi climàtic, i la mediterrània, una de les regions més vulnerables

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A factor limiting preliminary rockfall hazard mapping at regional scale is often the lack of knowledge of potential source areas. Nowadays, high resolution topographic data (LiDAR) can account for realistic landscape details even at large scale. With such fine-scale morphological variability, quantitative geomorphometric analyses become a relevant approach for delineating potential rockfall instabilities. Using digital elevation model (DEM)-based ?slope families? concept over areas of similar lithology and cliffs and screes zones available from the 1:25,000 topographic map, a susceptibility rockfall hazard map was drawn up in the canton of Vaud, Switzerland, in order to provide a relevant hazard overview. Slope surfaces over morphometrically-defined thresholds angles were considered as rockfall source zones. 3D modelling (CONEFALL) was then applied on each of the estimated source zones in order to assess the maximum runout length. Comparison with known events and other rockfall hazard assessments are in good agreement, showing that it is possible to assess rockfall activities over large areas from DEM-based parameters and topographical elements.

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Retroelements are important evolutionary forces but can be deleterious if left uncontrolled. Members of the human APOBEC3 family of cytidine deaminases can inhibit a wide range of endogenous, as well as exogenous, retroelements. These enzymes are structurally organized in one or two domains comprising a zinc-coordinating motif. APOBEC3G contains two such domains, only the C terminal of which is endowed with editing activity, while its N-terminal counterpart binds RNA, promotes homo-oligomerization, and is necessary for packaging into human immunodeficiency virus type 1 (HIV-1) virions. Here, we performed a large-scale mutagenesis-based analysis of the APOBEC3G N terminus, testing mutants for (i) inhibition of vif-defective HIV-1 infection and Alu retrotransposition, (ii) RNA binding, and (iii) oligomerization. Furthermore, in the absence of structural information on this domain, we used homology modeling to examine the positions of functionally important residues and of residues found to be under positive selection by phylogenetic analyses of primate APOBEC3G genes. Our results reveal the importance of a predicted RNA binding dimerization interface both for packaging into HIV-1 virions and inhibition of both HIV-1 infection and Alu transposition. We further found that the HIV-1-blocking activity of APOBEC3G N-terminal mutants defective for packaging can be almost entirely rescued if their virion incorporation is forced by fusion with Vpr, indicating that the corresponding region of APOBEC3G plays little role in other aspects of its action against this pathogen. Interestingly, residues forming the APOBEC3G dimer interface are highly conserved, contrasting with the rapid evolution of two neighboring surface-exposed amino acid patches, one targeted by the Vif protein of primate lentiviruses and the other of yet-undefined function.

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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.