998 resultados para psychotherapeutic processes


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This splitting techniques for MARKOV chains developed by NUMMELIN (1978a) and ATHREYA and NEY (1978b) are used to derive an imbedded renewal process in WOLD's point process with MARKOV-correlated intervals. This leads to a simple proof of renewal theorems for such processes. In particular, a key renewal theorem is proved, from which analogues to both BLACKWELL's and BREIMAN's forms of the renewal theorem can be deduced.

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Pseudo-marginal methods such as the grouped independence Metropolis-Hastings (GIMH) and Markov chain within Metropolis (MCWM) algorithms have been introduced in the literature as an approach to perform Bayesian inference in latent variable models. These methods replace intractable likelihood calculations with unbiased estimates within Markov chain Monte Carlo algorithms. The GIMH method has the posterior of interest as its limiting distribution, but suffers from poor mixing if it is too computationally intensive to obtain high-precision likelihood estimates. The MCWM algorithm has better mixing properties, but less theoretical support. In this paper we propose to use Gaussian processes (GP) to accelerate the GIMH method, whilst using a short pilot run of MCWM to train the GP. Our new method, GP-GIMH, is illustrated on simulated data from a stochastic volatility and a gene network model.

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This special issue of Continental Shelf Research contains 20 papers giving research results produced as part of Australia's Torres Strait Co-operative Research Centre (CRC) Program, which was funded over a three-year period during 2003-2006. Marine biophysical, fisheries, socioeconomic-cultural and extension research in the Torres Strait region of northeastern Australia was carried out to meet three aims: 1) support the sustainable development of marine resources and minimize impacts of resource use in Torres Strait; 2) enhance the conservation of the marine environment and the social, cultural and economic well being of all stakeholders, particularly the Torres Strait peoples; and 3) contribute to effective policy formulation and management decision making. Subjects covered, including commercial and traditional fisheries management, impacts of anthropogenic sediment inputs on seagrass meadows and communication of science results to local communities, have broad applications to other similar environments.

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Overprocessing waste occurs in a business process when effort is spent in a way that does not add value to the customer nor to the business. Previous studies have identied a recurrent overprocessing pattern in business processes with so-called "knockout checks", meaning activities that classify a case into "accepted" or "rejected", such that if the case is accepted it proceeds forward, while if rejected, it is cancelled and all work performed in the case is considered unnecessary. Thus, when a knockout check rejects a case, the effort spent in other (previous) checks becomes overprocessing waste. Traditional process redesign methods propose to order knockout checks according to their mean effort and rejection rate. This paper presents a more fine-grained approach where knockout checks are ordered at runtime based on predictive machine learning models. Experiments on two real-life processes show that this predictive approach outperforms traditional methods while incurring minimal runtime overhead.

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The authors identify and track processes that have resulted in the detection of six tropical weeds targeted for eradication. The habitats and distributions of these species make detection by field officers and members of the public more likely than targeted searches. The eradication program is increasing the scope of detection processes by conducting and documenting activities to improve weed recognition amongst public, government and industry stakeholders.

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Despite biocontrol research spanning over 100 years, the hybrid weed, commonly referred to as Lantana camara, is not under adequate control. Host specificity and varietal preference of released agents, climatic suitability of a region for released agents, number of agents introduced and range or area of infestation appear to play a role in limiting biocontrol success. At least one of 41 species of mainly leaf- or flower-feeding insects has been introduced, or spread, to 41 of the 70 countries or regions where lantana occurs. Over half (26) of these species have established, achieving varying levels of herbivory and presumably some degree of control. Accurate taxonomy of the plant and adaptation of potential agents to the host plant are some of the better predictors of at least establishment success. Retrospective analysis of the hosts of introduced biocontrol agents for L. camara show that a greater proportion of agents that were collected from L. camara or Lantana urticifolia established, than agents that were collected from other species of Lantana. Of the introduced agents that had established and were oligophagous, 18 out of 22 established. The proportion of species establishing, declined with the number of species introduced. However, there was no trend when oceanic islands were treated separately from mainland areas and the result is likely an artefact of how introductions have changed over time. A calculated index of the degree of herbivory due to agents known to have caused some damage per country, was not related to land area infested with lantana for mainlands nor for oceanic islands. However, the degree of herbivory is much higher on islands than mainlands. This difference between island and mainland situations may reflect population dynamics in patchy or metapopulation landscapes. Basic systematic studies of the host remain crucial to successful biocontrol, especially of hybrid weeds like L. camara. Potential biocontrol agents should be monophages collected from the most closely related species to the target weed or be phytophages that attack several species of lantana. Suitable agents should be released in the most ideal ecoclimatic area. Since collection of biocontrol agents has been limited to a fraction of the known number of phytophagous species available, biocontrol may be improved by targeting insects that feed on stems and roots, as well as the agents that feed on leaves and flowers.

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Analytical solutions of partial differential equation (PDE) models describing reactive transport phenomena in saturated porous media are often used as screening tools to provide insight into contaminant fate and transport processes. While many practical modelling scenarios involve spatially variable coefficients, such as spatially variable flow velocity, v(x), or spatially variable decay rate, k(x), most analytical models deal with constant coefficients. Here we present a framework for constructing exact solutions of PDE models of reactive transport. Our approach is relevant for advection-dominant problems, and is based on a regular perturbation technique. We present a description of the solution technique for a range of one-dimensional scenarios involving constant and variable coefficients, and we show that the solutions compare well with numerical approximations. Our general approach applies to a range of initial conditions and various forms of v(x) and k(x). Instead of simply documenting specific solutions for particular cases, we present a symbolic worksheet, as supplementary material, which enables the solution to be evaluated for different choices of the initial condition, v(x) and k(x). We also discuss how the technique generalizes to apply to models of coupled multispecies reactive transport as well as higher dimensional problems.

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Over the last two decades, there has been an increasing awareness of, and interest in, the use of spatial moment techniques to provide insight into a range of biological and ecological processes. Models that incorporate spatial moments can be viewed as extensions of mean-field models. These mean-field models often consist of systems of classical ordinary differential equations and partial differential equations, whose derivation, at some point, hinges on the simplifying assumption that individuals in the underlying stochastic process encounter each other at a rate that is proportional to the average abundance of individuals. This assumption has several implications, the most striking of which is that mean-field models essentially neglect any impact of the spatial structure of individuals in the system. Moment dynamics models extend traditional mean-field descriptions by accounting for the dynamics of pairs, triples and higher n-tuples of individuals. This means that moment dynamics models can, to some extent, account for how the spatial structure affects the dynamics of the system in question.

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This article presents a method for checking the conformance between an event log capturing the actual execution of a business process, and a model capturing its expected or normative execution. Given a business process model and an event log, the method returns a set of statements in natural language describing the behavior allowed by the process model but not observed in the log and vice versa. The method relies on a unified representation of process models and event logs based on a well-known model of concurrency, namely event structures. Specifically, the problem of conformance checking is approached by folding the input event log into an event structure, unfolding the process model into another event structure, and comparing the two event structures via an error-correcting synchronized product. Each behavioral difference detected in the synchronized product is then verbalized as a natural language statement. An empirical evaluation shows that the proposed method scales up to real-life datasets while producing more concise and higher-level difference descriptions than state-of-the-art conformance checking methods.

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Summary Poor land condition resulting from unsustainable grazing practices can reduce enterprise profitability and increase water, sediment and associated nutrient runoff from properties and catchments. This paper presents the results of a 6 year field study that used a series of hillslope flume experiments to evaluate the impact of improved grazing land management (GLM) on hillslope runoff and sediment yields. The study was carried out on a commercial grazing property in a catchment draining to the Burdekin River in northern Australia. During this study average ground cover on hillslopes increased from ~35% to ~75%, although average biomass and litter levels are still relatively low for this landscape type (~60 increasing to 1100 kg of dry matter per hectare). Pasture recovery was greatest on the upper and middle parts of hillslopes. Areas that did not respond to the improved grazing management had <10% cover and were on the lower slopes associated with the location of sodic soil and the initiation of gullies. Comparison of ground cover changes and soil conditions with adjacent properties suggest that grazing management, and not just improved rainfall conditions, were responsible for the improvements in ground cover in this study. The ground cover improvements resulted in progressively lower runoff coefficients for the first event in each wet season, however, runoff coefficients were not reduced at the annual time scale. The hillslope annual sediment yields declined by ~70% on two out of three hillslopes, although where bare patches (with <10% cover) were connected to gullies and streams, annual sediment yields increased in response to higher rainfall in latter years of the study. It appears that bare patches are the primary source areas for both runoff and erosion on these hillslopes. Achieving further reductions in runoff and erosion in these landscapes may require management practices that improve ground cover and biomass in bare areas, particularly when they are located adjacent to concentrated drainage lines.

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Models are abstractions of reality that have predetermined limits (often not consciously thought through) on what problem domains the models can be used to explore. These limits are determined by the range of observed data used to construct and validate the model. However, it is important to remember that operating the model beyond these limits, one of the reasons for building the model in the first place, potentially brings unwanted behaviour and thus reduces the usefulness of the model. Our experience with the Agricultural Production Systems Simulator (APSIM), a farming systems model, has led us to adapt techniques from the disciplines of modelling and software development to create a model development process. This process is simple, easy to follow, and brings a much higher level of stability to the development effort, which then delivers a much more useful model. A major part of the process relies on having a range of detailed model tests (unit, simulation, sensibility, validation) that exercise a model at various levels (sub-model, model and simulation). To underline the usefulness of testing, we examine several case studies where simulated output can be compared with simple relationships. For example, output is compared with crop water use efficiency relationships gleaned from the literature to check that the model reproduces the expected function. Similarly, another case study attempts to reproduce generalised hydrological relationships found in the literature. This paper then describes a simple model development process (using version control, automated testing and differencing tools), that will enhance the reliability and usefulness of a model.

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We report here that the structural origin of an easily reversible Ge15Te83Si2 glass can be a promising candidate for phase change random access memories. In situ Raman scattering studies on Ge15Te83Si2 sample, undertaken during the amorphous set and reset processes, indicate that the degree of disorder in the glass is reduced from off to set state. It is also found that the local structure of the sample under reset condition is similar to that in the amorphous off state. Electron microscopic studies on switched samples indicate the formation of nanometric sized particles of c-SiTe2 structure. ©2009 American Institute of Physics

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Abstract is not available.