917 resultados para Probabilistic constraints


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The logic PJ is a probabilistic logic defined by adding (noniterated) probability operators to the basic justification logic J. In this paper we establish upper and lower bounds for the complexity of the derivability problem in the logic PJ. The main result of the paper is that the complexity of the derivability problem in PJ remains the same as the complexity of the derivability problem in the underlying logic J, which is π[p/2] -complete. This implies that the probability operators do not increase the complexity of the logic, although they arguably enrich the expressiveness of the language.

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We present a probabilistic justification logic, PPJ, to study rational belief, degrees of belief and justifications. We establish soundness and completeness for PPJ and show that its satisfiability problem is decidable. In the last part we use PPJ to provide a solution to the lottery paradox.

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Several theories assume that successful team coordination is partly based on knowledge that helps anticipating individual contributions necessary in a situational task. It has been argued that a more ecological perspective needs to be considered in contexts evolving dynamically and unpredictably. In football, defensive plays are usually coordinated according to strategic concepts spanning all members and large areas of the playfield. On the other hand, fewer people are involved in offensive plays as these are less projectable and strongly constrained by ecological characteristics. The aim of this study is to test the effects of ecological constraints and player knowledge on decision making in offensive game scenarios. It is hypothesized that both knowledge about team members and situational constraints will influence decisional processes. Effects of situational constraints are expected to be of higher magnitude. Two teams playing in the fourth league of the Swiss Football Federation participate in the study. Forty customized game scenarios were developed based on the coaches’ information about player positions and game strategies. Each player was shown in ball possession four times. Participants were asked to take the perspective of the player on the ball and to choose a passing destination and a recipient. Participants then rated domain specific strengths (e.g., technical skills, game intelligence) of each of their teammates. Multilevel models for categorical dependent variables (team members) will be specified. Player knowledge (rated skills) and ecological constraints (operationalized as each players’ proximity and availability for ball reception) are included as predictor variables. Data are currently being collected. Results will yield effects of parameters that are stable across situations as well as of variable parameters that are bound to situational context. These will enable insight into the degree to which ecological constraints and more enduring team knowledge are involved in decisional processes aimed at coordinating interpersonal action.

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The Ivrea–Verbano Zone (IVZ), northern Italy, exposes an attenuated section through the Permian lower crust that records high-temperature metamorphism under lower crustal conditions and a protracted history of extension and exhumation associated partly with the Jurassic opening of the Alpine Tethys ocean. This study presents SHRIMP U–Pb geochronology of rutile from seven granulite facies metapelites from the base of the IVZ, collected from locations spanning ~35 km along the strike of Paleozoic fabrics. Rutile crystallised during Permian high-temperature metamorphism and anatexis, yet all samples give Jurassic rutile U–Pb ages that record cooling through 650–550 °C. Rutile age distributions are dominated by a peak at ~160 Ma, with a subordinate peak at ~175 Ma. Both ~160 and ~175 Ma age populations show excellent agreement between samples, indicating that the two distinctive cooling stages they record were synchronous on a regional scale. The ~175 Ma population is interpreted to record cooling in the footwall of rift-related faults and shear zones, for which widespread activity in the Lower Jurassic has been documented along the western margin of the Adriatic plate. The ~160 Ma age population postdates the activity of all known rift-related structures within the Adriatic margin, but coincides with extensive gabbroic magmatism and exhumation of sub-continental mantle to the floor of the Alpine Tethys, west of the Ivrea Zone. We propose that this ~160 Ma early post-rift age population records regional cooling following episodic heating of the distal Adriatic margin, likely related to extreme lithospheric thinning and associated advection of the asthenosphere to shallow levels. The partial preservation of the ~175 Ma age cluster suggests that the post-rift (~160 Ma) heating pulse was of short duration. The regional consistency of the data presented here, which is in contrast to many other thermochronometers in the IVZ, demonstrates the value of the rutile U–Pb technique for probing the thermal evolution of high-grade metamorphic terrains. In the IVZ, a significant decoupling between Zr-in-rutile temperatures and U–Pb ages of rutile is observed, with the two systems recording events ~120 Ma apart.

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We investigated whether a pure perceptual stream is sufficient for probabilistic sequence learning to occur within a single session or whether correlated streams are necessary, whether learning is affected by the transition probability between sequence elements, and how the sequence length influences learning. In each of three experiments, we used six horizontally arranged stimulus displays which consisted of randomly ordered bigrams xo and ox. The probability of the next possible target location out of two was either .50/.50 or .75/.25 and was marked by an underline. In Experiment 1, a left vs. right key response was required for the x of a marked bigram in the pure perceptual learning condition and a response key press corresponding to the marked bigram location (out of 6) was required in the correlated streams condition (i.e., the ring, middle, or index finger of the left and right hand, respectively). The same probabilistic 3-element sequence was used in both conditions. Learning occurred only in the correlated streams condition. In Experiment 2, we investigated whether sequence length affected learning correlated sequences by contrasting the 3-elements sequence with a 6-elements sequence. Significant sequence learning occurred in all conditions. In Experiment 3, we removed a potential confound, that is, the sequence of hand changes. Under these conditions, learning occurred for the 3-element sequence only and transition probability did not affect the amount of learning. Together, these results indicate that correlated streams are necessary for probabilistic sequence learning within a single session and that sequence length can reduce the chances for learning to occur.

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Aims. We present an inversion method based on Bayesian analysis to constrain the interior structure of terrestrial exoplanets, in the form of chemical composition of the mantle and core size. Specifically, we identify what parts of the interior structure of terrestrial exoplanets can be determined from observations of mass, radius, and stellar elemental abundances. Methods. We perform a full probabilistic inverse analysis to formally account for observational and model uncertainties and obtain confidence regions of interior structure models. This enables us to characterize how model variability depends on data and associated uncertainties. Results. We test our method on terrestrial solar system planets and find that our model predictions are consistent with independent estimates. Furthermore, we apply our method to synthetic exoplanets up to 10 Earth masses and up to 1.7 Earth radii, and to exoplanet Kepler-36b. Importantly, the inversion strategy proposed here provides a framework for understanding the level of precision required to characterize the interior of exoplanets. Conclusions. Our main conclusions are (1) observations of mass and radius are sufficient to constrain core size; (2) stellar elemental abundances (Fe, Si, Mg) are principal constraints to reduce degeneracy in interior structure models and to constrain mantle composition; (3) the inherent degeneracy in determining interior structure from mass and radius observations does not only depend on measurement accuracies, but also on the actual size and density of the exoplanet. We argue that precise observations of stellar elemental abundances are central in order to place constraints on planetary bulk composition and to reduce model degeneracy. We provide a general methodology of analyzing interior structures of exoplanets that may help to understand how interior models are distributed among star systems. The methodology we propose is sufficiently general to allow its future extension to more complex internal structures including hydrogen- and water-rich exoplanets.

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Context. One of the main aims of the ESA Rosetta mission is to study the origin of the solar system by exploring comet 67P/Churyumov-Gerasimenko at close range. Aims. In this paper we discuss the origin and evolution of comet 67P/Churyumov-Gerasimenko in relation to that of comets in general and in the framework of current solar system formation models. Methods. We use data from the OSIRIS scientific cameras as basic constraints. In particular, we discuss the overall bi-lobate shape and the presence of key geological features, such as layers and fractures. We also treat the problem of collisional evolution of comet nuclei by a particle-in-a-box calculation for an estimate of the probability of survival for 67P/Churyumov-Gerasimenko during the early epochs of the solar system. Results. We argue that the two lobes of the 67P/Churyumov-Gerasimenko nucleus are derived from two distinct objects that have formed a contact binary via a gentle merger. The lobes are separate bodies, though sufficiently similar to have formed in the same environment. An estimate of the collisional rate in the primordial, trans-planetary disk shows that most comets of similar size to 67P/Churyumov-Gerasimenko are likely collisional fragments, although survival of primordial planetesimals cannot be excluded. Conclusions. A collisional origin of the contact binary is suggested, and the low bulk density of the aggregate and abundance of volatile species show that a very gentle merger must have occurred. We thus consider two main scenarios: the primordial accretion of planetesimals, and the re-accretion of fragments after an energetic impact onto a larger parent body. We point to the primordial signatures exhibited by 67P/Churyumov-Gerasimenko and other comet nuclei as critical tests of the collisional evolution.

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The consumption capital asset pricing model is the standard economic model used to capture stock market behavior. However, empirical tests have pointed out to its inability to account quantitatively for the high average rate of return and volatility of stocks over time for plausible parameter values. Recent research has suggested that the consumption of stockholders is more strongly correlated with the performance of the stock market than the consumption of non-stockholders. We model two types of agents, non-stockholders with standard preferences and stock holders with preferences that incorporate elements of the prospect theory developed by Kahneman and Tversky (1979). In addition to consumption, stockholders consider fluctuations in their financial wealth explicitly when making decisions. Data from the Panel Study of Income Dynamics are used to calibrate the labor income processes of the two types of agents. Each agent faces idiosyncratic shocks to his labor income as well as aggregate shocks to the per-share dividend but markets are incomplete and agents cannot hedge consumption risks completely. In addition, consumers face both borrowing and short-sale constraints. Our results show that in equilibrium, agents hold different portfolios. Our model is able to generate a time-varying risk premium of about 5.5% while maintaining a low risk free rate, thus suggesting a plausible explanation for the equity premium puzzle reported by Mehra and Prescott (1985).

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Coastal managers require reliable spatial data on the extent and timing of potential coastal inundation, particularly in a changing climate. Most sea level rise (SLR) vulnerability assessments are undertaken using the easily implemented bathtub approach, where areas adjacent to the sea and below a given elevation are mapped using a deterministic line dividing potentially inundated from dry areas. This method only requires elevation data usually in the form of a digital elevation model (DEM). However, inherent errors in the DEM and spatial analysis of the bathtub model propagate into the inundation mapping. The aim of this study was to assess the impacts of spatially variable and spatially correlated elevation errors in high-spatial resolution DEMs for mapping coastal inundation. Elevation errors were best modelled using regression-kriging. This geostatistical model takes the spatial correlation in elevation errors into account, which has a significant impact on analyses that include spatial interactions, such as inundation modelling. The spatial variability of elevation errors was partially explained by land cover and terrain variables. Elevation errors were simulated using sequential Gaussian simulation, a Monte Carlo probabilistic approach. 1,000 error simulations were added to the original DEM and reclassified using a hydrologically correct bathtub method. The probability of inundation to a scenario combining a 1 in 100 year storm event over a 1 m SLR was calculated by counting the proportion of times from the 1,000 simulations that a location was inundated. This probabilistic approach can be used in a risk-aversive decision making process by planning for scenarios with different probabilities of occurrence. For example, results showed that when considering a 1% probability exceedance, the inundated area was approximately 11% larger than mapped using the deterministic bathtub approach. The probabilistic approach provides visually intuitive maps that convey uncertainties inherent to spatial data and analysis.

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The large discrepancy between field and laboratory measurements of mineral reaction rates is a long-standing problem in earth sciences, often attributed to factors extrinsic to the mineral itself. Nevertheless, differences in reaction rate are also observed within laboratory measurements, raising the possibility of intrinsic variations as well. Critical insight is available from analysis of the relationship between the reaction rate and its distribution over the mineral surface. This analysis recognizes the fundamental variance of the rate. The resulting anisotropic rate distributions are completely obscured by the common practice of surface area normalization. In a simple experiment using a single crystal and its polycrystalline counterpart, we demonstrate the sensitivity of dissolution rate to grain size, results that undermine the use of "classical" rate constants. Comparison of selected published crystal surface step retreat velocities (Jordan and Rammensee, 1998) as well as large single crystal dissolution data (Busenberg and Plummer, 1986) provide further evidence of this fundamental variability. Our key finding highlights the unsubstantiated use of a single-valued "mean" rate or rate constant as a function of environmental conditions. Reactivity predictions and long-term reservoir stability calculations based on laboratory measurements are thus not directly applicable to natural settings without a probabilistic approach. Such a probabilistic approach must incorporate both the variation of surface energy as a general range (intrinsic variation) as well as constraints to this variation owing to the heterogeneity of complex material (e.g., density of domain borders). We suggest the introduction of surface energy spectra (or the resulting rate spectra) containing information about the probability of existing rate ranges and the critical modes of surface energy.

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Observation-based reconstructions of sea surface temperature from relatively stable periods in the past, such as the Last Glacial Maximum, represent an important means of constraining climate sensitivity and evaluating model simulations. The first quantitative global reconstruction of sea surface temperatures during the Last Glacial Maximum was developed by the Climate Long-Range Investigation, Mapping and Prediction (CLIMAP) project in the 1970s and 1980s. Since that time, several shortcomings of that earlier effort have become apparent. Here we present an updated synthesis of sea surface temperatures during the Last Glacial Maximum, rigorously defined as the period between 23 and 19 thousand years before present, from the Multiproxy Approach for the Reconstruction of the Glacial Ocean Surface (MARGO) project. We integrate microfossil and geochemical reconstructions of surface temperatures and include assessments of the reliability of individual records. Our reconstruction reveals the presence of large longitudinal gradients in sea surface temperature in all of the ocean basins, in contrast to the simulations of the Last Glacial Maximum climate available at present.

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Lake Baikal, the world's most voluminous freshwater lake, has experienced unprecedented warming during the last decades. A uniquely diverse amphipod fauna inhabits the littoral zone and can serve as a model system to identify the role of thermal tolerance under climate change. This study aimed to identify sublethal thermal constraints in two of the most abundant endemic Baikal amphipods, Eulimnogammarus verrucosus and Eulimnogammarus cyaneus, and Gammarus lacustris, a ubiquitous gammarid of the Holarctic. As the latter is only found in some shallow isolated bays of the lake, we further addressed the question whether rising temperatures could promote the widespread invasion of this non-endemic species into the littoral zone. Animals were exposed to gradual temperature increases (4 week, 0.8 °C/d; 24 h, 1 °C/h) starting from the reported annual mean temperature of the Baikal littoral (6 °C). Within the framework of oxygen- and capacity-limited thermal tolerance (OCLTT), we used a nonlinear regression approach to determine the points at which the changing temperature-dependence of relevant physiological processes indicates the onset of limitation. Limitations in ventilation representing the first limits of thermal tolerance (pejus (= "getting worse") temperatures (Tp)) were recorded at 10.6 (95% confidence interval; 9.5, 11.7), 19.1 (17.9, 20.2), and 21.1 (19.8, 22.4) °C in E. verrucosus, E. cyaneus, and G. lacustris, respectively. Field observations revealed that E. verrucosus retreated from the upper littoral to deeper and cooler waters once its Tp was surpassed, identifying Tp as the ecological thermal boundary. Constraints in oxygen consumption at higher than critical temperatures (Tc) led to an exponential increase in mortality in all species. Exposure to short-term warming resulted in higher threshold values, consistent with a time dependence of thermal tolerance. In conclusion, species-specific limits to oxygen supply capacity are likely key in the onset of constraining (beyond pejus) and then life-threatening (beyond critical) conditions. Ecological consequences of these limits are mediated through behavioral plasticity in E. verrucosus. However, similar upper thermal limits in E. cyaneus (endemic, Baikal) and G. lacustris (ubiquitous, Holarctic) indicate that the potential invader G. lacustris would not necessarily benefit from rising temperatures. Secondary effects of increasing temperatures remain to be investigated.

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The selection of metrics for ecosystem restoration programs is critical for improving the quality of monitoring programs and characterizing project success. Moreover it is oftentimes very difficult to balance the importance of multiple ecological, social, and economical metrics. Metric selection process is a complex and must simultaneously take into account monitoring data, environmental models, socio-economic considerations, and stakeholder interests. We propose multicriteria decision analysis (MCDA) methods, broadly defined, for the selection of optimal sets of metrics to enhance evaluation of ecosystem restoration alternatives. Two MCDA methods, a multiattribute utility analysis (MAUT), and a probabilistic multicriteria acceptability analysis (ProMAA), are applied and compared for a hypothetical case study of a river restoration involving multiple stakeholders. Overall, the MCDA results in a systematic, unbiased, and transparent solution, informing restoration alternatives evaluation. The two methods provide comparable results in terms of selected metrics. However, because ProMAA can consider probability distributions for weights and utility values of metrics for each criteria, it is suggested as the best option if data uncertainty is high. Despite the increase in complexity in the metric selection process, MCDA improves upon the current ad-hoc decision practice based on the consultations with stakeholders and experts, and encourages transparent and quantitative aggregation of data and judgement, increasing the transparency of decision making in restoration projects. We believe that MCDA can enhance the overall sustainability of ecosystem by enhancing both ecological and societal needs.