969 resultados para Consistent term structure models
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Ecological and genetic studies of marine turtles generally support the hypothesis of natal homing, but leave open the question of the geographical scale of genetic exchange and the capacity of turtles to shift breeding sites. Here we combine analyses of mitochondrial DNA (mtDNA) variation and recapture data to assess the geographical scale of individual breeding populations and the distribution of such populations through Australasia. We conducted multiscale assessments of mtDNA variation among 714 samples from 27 green turtle rookeries and of adult female dispersal among nesting sites in eastern Australia. Many of these rookeries are on shelves that were flooded by rising sea levels less than 10 000 years (c. 450 generations) ago. Analyses of sequence variation among the mtDNA control region revealed 25 haplotypes, and their frequency distributions indicated 17 genetically distinct breeding stocks (Management Units) consisting either of individual rookeries or groups of rookeries in general that are separated by more than 500 km. The population structure inferred from mtDNA was consistent with the scale of movements observed in long-term mark-recapture studies of east Australian rookeries. Phylogenetic analysis of the haplotypes revealed five clades with significant partitioning of sequence diversity (Phi = 68.4) between Pacific Ocean and Southeast Asian/Indian Ocean rookeries. Isolation by distance was indicated for rookeries separated by up to 2000 km but explained only 12% of the genetic structure. The emerging general picture is one of dynamic population structure influenced by the capacity of females to relocate among proximal breeding sites, although this may be conditional on large population sizes as existed historically across this region.
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Predicting the various responses of different species to changes in landscape structure is a formidable challenge to landscape ecology. Based on expert knowledge and landscape ecological theory, we develop five competing a priori models for predicting the presence/absence of the Koala (Phascolarctos cinereus) in Noosa Shire, south-east Queensland (Australia). A priori predictions were nested within three levels of ecological organization: in situ (site level) habitat (< 1 ha), patch level (100 ha) and landscape level (100-1000 ha). To test the models, Koala surveys and habitat surveys (n = 245) were conducted across the habitat mosaic. After taking into account tree species preferences, the patch and landscape context, and the neighbourhood effect of adjacent present sites, we applied logistic regression and hierarchical partitioning analyses to rank the alternative models and the explanatory variables. The strongest support was for a multilevel model, with Koala presence best predicted by the proportion of the landscape occupied by high quality habitat, the neighbourhood effect, the mean nearest neighbour distance between forest patches, the density of forest patches and the density of sealed roads. When tested against independent data (n = 105) using a receiver operator characteristic curve, the multilevel model performed moderately well. The study is consistent with recent assertions that habitat loss is the major driver of population decline, however, landscape configuration and roads have an important effect that needs to be incorporated into Koala conservation strategies.
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This paper consides the problem of extracting the relationships between two time series in a non-linear non-stationary environment with Hidden Markov Models (HMMs). We describe an algorithm which is capable of identifying associations between variables. The method is applied both to synthetic data and real data. We show that HMMs are capable of modelling the oil drilling process and that they outperform existing methods.
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Methods for understanding classical disordered spin systems with interactions conforming to some idealized graphical structure are well developed. The equilibrium properties of the Sherrington-Kirkpatrick model, which has a densely connected structure, have become well understood. Many features generalize to sparse Erdös- Rényi graph structures above the percolation threshold and to Bethe lattices when appropriate boundary conditions apply. In this paper, we consider spin states subject to a combination of sparse strong interactions with weak dense interactions, which we term a composite model. The equilibrium properties are examined through the replica method, with exact analysis of the high-temperature paramagnetic, spin-glass, and ferromagnetic phases by perturbative schemes. We present results of replica symmetric variational approximations, where perturbative approaches fail at lower temperature. Results demonstrate re-entrant behaviors from spin glass to ferromagnetic phases as temperature is lowered, including transitions from replica symmetry broken to replica symmetric phases. The nature of high-temperature transitions is found to be sensitive to the connectivity profile in the sparse subgraph, with regular connectivity a discontinuous transition from the paramagnetic to ferromagnetic phases is apparent.
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This paper presents some forecasting techniques for energy demand and price prediction, one day ahead. These techniques combine wavelet transform (WT) with fixed and adaptive machine learning/time series models (multi-layer perceptron (MLP), radial basis functions, linear regression, or GARCH). To create an adaptive model, we use an extended Kalman filter or particle filter to update the parameters continuously on the test set. The adaptive GARCH model is a new contribution, broadening the applicability of GARCH methods. We empirically compared two approaches of combining the WT with prediction models: multicomponent forecasts and direct forecasts. These techniques are applied to large sets of real data (both stationary and non-stationary) from the UK energy markets, so as to provide comparative results that are statistically stronger than those previously reported. The results showed that the forecasting accuracy is significantly improved by using the WT and adaptive models. The best models on the electricity demand/gas price forecast are the adaptive MLP/GARCH with the multicomponent forecast; their MSEs are 0.02314 and 0.15384 respectively.
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The 5-HT3 receptors are members of the cys-loop family of ligand-gated ion channels. Two functional subtypes are known, the homomeric 5HT3A and the heteromeric 5HT3A/B receptors, which exhibit distinct biophysical characteristics but are difficult to differentiate pharmacologically. Atomic force microscopy has been used to determine the stoichiometry and architecture of the heteromeric 5HT3A/B receptor. Each subunit was engineered to express a unique C-terminal epitope tag, together with six sequential histidine residues to facilitate nickel affinity purification. The 5-HT3 receptors, ectopically expressed in HEK293 cells, were solubilised, purified and decorated with antibodies to the subunit specific epitope tags. Imaging of individual receptors by atomic force microscopy revealed a pentameric arrangement of subunits in the order BBABA, reading anti-clockwise when viewed from the extracellular face. Homology models for the heteromeric receptor were then constructed using both the electron microscopic structure of the nicotinic acetylcholine receptor, from Torpedo marmorata, and the X-ray crystallographic structure of the soluble acetylcholine binding protein, from Lymnaea stagnalis, as templates. These homology models were used, together with equivalent models constructed for the homomeric receptor, to interpret mutagenesis experiments designed to explore the minimal recognition differences of both the natural agonist, 5-HT, and the competitive antagonist, granisetron, for the two human receptor subtypes. The results of this work revealed that the 5-HT3B subunit residues within the ligand binding site, for both the agonist and antagonist, are accommodating to conservative mutations. They are consistent with the view that the 5-HT3A subunit provides the principal and the 5-HT38 subunit the complementary recognition interactions at the binding interface.
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Damage to insulation materials located near to a primary circuit coolant leak may compromise the operation of the emergency core cooling system (ECCS). Insulation material in the form of mineral wool fiber agglomerates (MWFA) maybe transported to the containment sump strainers, where they may block or penetrate the strainers. Though the impact of MWFA on the pressure drop across the strainers is minimal, corrosion products formed over time may also accumulate in the fiber cakes on the strainers, which can lead to a significant increase in the strainer pressure drop and result in cavitation in the ECCS. An experimental and theoretical study performed by the Helmholtz-Zentrum Dresden-Rossendorf and the Hochschule Zittau/Görlitz is investigating the phenomena that maybe observed in the containment vessel during a primary circuit coolant leak. The study entails the generation of fiber agglomerates, the determination of their transport properties in single and multi-effect experiments and the long-term effect that corrosion and erosion of the containment internals by the coolant has on the strainer pressure drop. The focus of this paper is on the verification and validation of numerical models that can predict the transport of MWFA. A number of pseudo-continuous dispersed phases of spherical wetted agglomerates represent the MWFA. The size, density, the relative viscosity of the fluid-fiber agglomerate mixture and the turbulent dispersion all affect how the fiber agglomerates are transported. In the cases described here, the size is kept constant while the density is modified. This definition affects both the terminal velocity and volume fraction of the dispersed phases. Note that the relative viscosity is only significant at high concentrations. Three single effect experiments were used to provide validation data on the transport of the fiber agglomerates under conditions of sedimentation in quiescent fluid, sedimentation in a horizontal flow and suspension in a horizontal flow. The experiments were performed in a rectangular column for the quiescent fluid and a racetrack type channel that provided a near uniform horizontal flow. The numerical models of sedimentation in the column and the racetrack channel found that the sedimentation characteristics are consistent with the experiments. For channel suspension, the heavier fibers tend to accumulate at the channel base even at high velocities, while lighter phases are more likely to be transported around the channel.
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Quantitative structure-activity relationship (QSAR) analysis is a cornerstone of modern informatics. Predictive computational models of peptide-major histocompatibility complex (MHC)-binding affinity based on QSAR technology have now become important components of modern computational immunovaccinology. Historically, such approaches have been built around semiqualitative, classification methods, but these are now giving way to quantitative regression methods. We review three methods--a 2D-QSAR additive-partial least squares (PLS) and a 3D-QSAR comparative molecular similarity index analysis (CoMSIA) method--which can identify the sequence dependence of peptide-binding specificity for various class I MHC alleles from the reported binding affinities (IC50) of peptide sets. The third method is an iterative self-consistent (ISC) PLS-based additive method, which is a recently developed extension to the additive method for the affinity prediction of class II peptides. The QSAR methods presented here have established themselves as immunoinformatic techniques complementary to existing methodology, useful in the quantitative prediction of binding affinity: current methods for the in silico identification of T-cell epitopes (which form the basis of many vaccines, diagnostics, and reagents) rely on the accurate computational prediction of peptide-MHC affinity. We have reviewed various human and mouse class I and class II allele models. Studied alleles comprise HLA-A*0101, HLA-A*0201, HLA-A*0202, HLA-A*0203, HLA-A*0206, HLA-A*0301, HLA-A*1101, HLA-A*3101, HLA-A*6801, HLA-A*6802, HLA-B*3501, H2-K(k), H2-K(b), H2-D(b) HLA-DRB1*0101, HLA-DRB1*0401, HLA-DRB1*0701, I-A(b), I-A(d), I-A(k), I-A(S), I-E(d), and I-E(k). In this chapter we show a step-by-step guide into predicting the reliability and the resulting models to represent an advance on existing methods. The peptides used in this study are available from the AntiJen database (http://www.jenner.ac.uk/AntiJen). The PLS method is available commercially in the SYBYL molecular modeling software package. The resulting models, which can be used for accurate T-cell epitope prediction, will be made are freely available online at the URL http://www.jenner.ac.uk/MHCPred.
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This article investigates the attitudes to inter-firm co-operation in Hungary by analysing a special group of business networks: the business clusters. Following an overview of cluster policy, a wide range of selfproclaimed business clusters are identified. A small elite of these business networks evolves into successful, sustainable innovative business clusters. However, in the majority of cases, these consortia of interfirm co-operation are not based on a mutually satisfactory model, and as a consequence, many clusters do not survive in the longer term. The paper uses the concepts and models of social network theory in order to explain, why and under what circumstances inter-firm co-operation in clusters enhances the competitiveness of the network as a whole, or alternatively, under what circumstances the cluster remains dependent on Government subsidies. The empirical basis of the study is a thorough internet research about the Hungarian cluster movement; a questionnaire based expert survey among managers of clusters and member companies and a set of in-depth interviews among managers of self-proclaimed clusters. The last chapter analyises the applicability of social network theory in the analysis of business networks and a model involving the value chain is recommended.
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In numerous anthropological works there have been preoccupations about the relationships between Indigenous and non-Indigenous peoples. Whatever social researchers have concluded, one thing is consistent: the tendency to interpret ethnographic “data” in terms of binary oppositions. This dissertation reviews the works which have been centered upon binary oppositions, as for instance, in the case of Yucatan, between the Maya and the Dzul—the Yucatec Maya term for white males—and highlights the fact that such works have failed to recognize that within and between each “pole,” or social group there are individuals that have multiple identities, and that do not recognize themselves as belonging to a homogenized “pole.” Instead, these individuals, recognize themselves as belonging to different groups and, therefore, being aware that they have not a single identity but multiple ones. ^ Analogical anthropology is highly criticized because of its emphasis on binary oppositions, its authoritarianism, and the notion of the “Other.” In contrast, dialogical anthropology places great importance on the relationship between the individuals and the anthropologist. A relation in which both, the anthropologist and the subject, are immersed in a dialogue, because of the identification between the writer and the story that is being written. ^ However, anthropologists seem to be more interested in “dialoguing” among themselves rather than with the people that they write about. Indigenous people are relegated, they are voiceless, and, therefore, we keep treating them as “objects,” and not as individuals. This is ironic, precisely because it undermines the aim of the dialogical discourse. ^ In this context, awareness of self-identity or self-identities and the various ways in which Francisco, a good friend and the main character of this dissertation, assumes them, and the way I assume them, within multicultural contexts, leads us along the road to establish and reestablish communication. The methodology is based on four considerations: positioning, fieldwork conversations, self reflexivity and vulnerability. Hence, this dissertation constitutes an attempt to break with authoritarian models of ethnography, it is a dialogue between Francisco and me, a conversation among ourselves. A dialogue that expresses the desire of hearing our voices being echoed by each other. ^
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Moving objects database systems are the most challenging sub-category among Spatio-Temporal database systems. A database system that updates in real-time the location information of GPS-equipped moving vehicles has to meet even stricter requirements. Currently existing data storage models and indexing mechanisms work well only when the number of moving objects in the system is relatively small. This dissertation research aimed at the real-time tracking and history retrieval of massive numbers of vehicles moving on road networks. A total solution has been provided for the real-time update of the vehicles' location and motion information, range queries on current and history data, and prediction of vehicles' movement in the near future. ^ To achieve these goals, a new approach called Segmented Time Associated to Partitioned Space (STAPS) was first proposed in this dissertation for building and manipulating the indexing structures for moving objects databases. ^ Applying the STAPS approach, an indexing structure of associating a time interval tree to each road segment was developed for real-time database systems of vehicles moving on road networks. The indexing structure uses affordable storage to support real-time data updates and efficient query processing. The data update and query processing performance it provides is consistent without restrictions such as a time window or assuming linear moving trajectories. ^ An application system design based on distributed system architecture with centralized organization was developed to maximally support the proposed data and indexing structures. The suggested system architecture is highly scalable and flexible. Finally, based on a real-world application model of vehicles moving in region-wide, main issues on the implementation of such a system were addressed. ^
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An oligotrophic phosphorus (P) limited seagrass ecosystem in Florida Bay was experimentally fertilized in a unique way. Perches were installed to encourage seabirds to roost and deliver an external source of nutrients via defecation. Two treatments were examined: (1) a chronic 23-year fertilization and (2) an earlier 28-month fertilization that was discontinued when the chronic treatment was initiated. Because of the low mobility of P in carbonate sediments, we hypothesized long-term changes to ecosystem structure and function in both treatments. Structural changes in the chronic treatment included a shift in the dominant seagrass species from Thalassia testudinum to Halodule wrightii, large increases in epiphytic biomass and sediment chlorophyll-a, and a decline in species richness. Functional changes included increased benthic metabolism and quantum efficiency. Initial changes in the 28-month fertilization were similar, but after 23 years of nutrient depuration T. testudinum has reestablished itself as the dominant species. However, P remains elevated in the sediment and H. wrightii has maintained a presence. Functionally the discontinued treatment remains altered. Biomass exceeds that in the chronic treatment and indices of productivity, elevated relative to control, are not different from the chronic fertilization. Cessation of nutrient loading has resulted in a superficial return to the pre-disturbance character of the community, but due to the nature of P cycles functional changes persist.
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Models of community regulation commonly incorporate gradients of disturbance inversely related to the role of biotic interactions in regulating intermediate trophic levels. Higher trophic-level organisms are predicted to be more strongly limited by intermediate levels of disturbance than are the organisms they consume. We used a manipulation of the frequency of hydrological disturbance in an intervention analysis to examine its effects on small-fish communities in the Everglades, USA. From 1978 to 2002, we monitored fishes at one long-hydroperiod (average 350 days) and at one short-hydroperiod (average 259 days; monitoring started here in 1985) site. At a third site, managers intervened in 1985 to diminish the frequency and duration of marsh drying. By the late 1990s, the successional dynamics of density and relative abundance at the intervention site converged on those of the long-hydroperiod site. Community change was manifested over 3 to 5 years following a dry-down if a site remained inundated; the number of days since the most recent drying event and length of the preceding dry period were useful for predicting population dynamics. Community dissimilarity was positively correlated with the time since last dry. Community dynamics resulted from change in the relative abundance of three groups of species linked by life-history responses to drought. Drought frequency and intensity covaried in response to hydrological manipulation at the landscape scale; community-level successional dynamics converged on a relatively small range of species compositions when drought return-time extended beyond 4 years. The density of small fishes increased with diminution of drought frequency, consistent with disturbance-limited community structure; less-frequent drying than experienced in this study (i.e., longer return times) yields predator-dominated regulation of small-fish communities in some parts of the Everglades.