923 resultados para Structure-Mapping Theory
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In this paper necessary and sufficient conditions for a vector to be the fine structure of a balanced ternary design with block size 3, index 3 and rho(2) = 1 and 2 are determined with one unresolved case.
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This paper describes algorithms that can identify patterns of brain structure and function associated with Alzheimer's disease, schizophrenia, normal aging, and abnormal brain development based on imaging data collected in large human populations. Extraordinary information can be discovered with these techniques: dynamic brain maps reveal how the brain grows in childhood, how it changes in disease, and how it responds to medication. Genetic brain maps can reveal genetic influences on brain structure, shedding light on the nature-nurture debate, and the mechanisms underlying inherited neurobehavioral disorders. Recently, we created time-lapse movies of brain structure for a variety of diseases. These identify complex, shifting patterns of brain structural deficits, revealing where, and at what rate, the path of brain deterioration in illness deviates from normal. Statistical criteria can then identify situations in which these changes are abnormally accelerated, or when medication or other interventions slow them. In this paper, we focus on describing our approaches to map structural changes in the cortex. These methods have already been used to reveal the profile of brain anomalies in studies of dementia, epilepsy, depression, childhood and adult-onset schizophrenia, bipolar disorder, attention-deficit/ hyperactivity disorder, fetal alcohol syndrome, Tourette syndrome, Williams syndrome, and in methamphetamine abusers. Specifically, we describe an image analysis pipeline known as cortical pattern matching that helps compare and pool cortical data over time and across subjects. Statistics are then defined to identify brain structural differences between groups, including localized alterations in cortical thickness, gray matter density (GMD), and asymmetries in cortical organization. Subtle features, not seen in individual brain scans, often emerge when population-based brain data are averaged in this way. Illustrative examples are presented to show the profound effects of development and various diseases on the human cortex. Dynamically spreading waves of gray matter loss are tracked in dementia and schizophrenia, and these sequences are related to normally occurring changes in healthy subjects of various ages. (C) 2004 Published by Elsevier Inc.
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Smoothing the potential energy surface for structure optimization is a general and commonly applied strategy. We propose a combination of soft-core potential energy functions and a variation of the diffusion equation method to smooth potential energy surfaces, which is applicable to complex systems such as protein structures; The performance of the method was demonstrated by comparison with simulated annealing using the refinement of the undecapeptide Cyclosporin A as a test case. Simulations were repeated many times using different initial conditions and structures since the methods are heuristic and results are only meaningful in a statistical sense.
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Functional magnetic resonance imaging (fMRI) is currently one of the most widely used methods for studying human brain function in vivo. Although many different approaches to fMRI analysis are available, the most widely used methods employ so called ""mass-univariate"" modeling of responses in a voxel-by-voxel fashion to construct activation maps. However, it is well known that many brain processes involve networks of interacting regions and for this reason multivariate analyses might seem to be attractive alternatives to univariate approaches. The current paper focuses on one multivariate application of statistical learning theory: the statistical discrimination maps (SDM) based on support vector machine, and seeks to establish some possible interpretations when the results differ from univariate `approaches. In fact, when there are changes not only on the activation level of two conditions but also on functional connectivity, SDM seems more informative. We addressed this question using both simulations and applications to real data. We have shown that the combined use of univariate approaches and SDM yields significant new insights into brain activations not available using univariate methods alone. In the application to a visual working memory fMRI data, we demonstrated that the interaction among brain regions play a role in SDM`s power to detect discriminative voxels. (C) 2008 Elsevier B.V. All rights reserved.
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Objective: To compare the volume of the hippocampus and parahippocampal gyrus in elderly individuals with and without depressive disorders, and to determine whether the volumes of these regions correlate with scores on memory tests. Method: Clinical and demographic differences, as well as differences in regional gray matter volumes, were assessed in 48 elderly patients with depressive disorders and 31 control subjects. Brain (structural MRI) scans were processed using statistical parametric mapping and voxel-based morphometry. Cognitive tests were administered to subjects in both groups. Results: There were no between-group gray matter volume differences in the hippocampus or parahippocampal gyrus. In the elderly depressed group only, the volume of the left parahippocampal gyrus correlated with scores on the delayed naming portion of the visual verbal learning test. There were also significant direct correlations in depressed subjects between the volumes of the left hippocampus, right and left parahippocampal gyrus and immediate recall scores on verbal episodic memory tests and visual learning tests. In the control group, there were direct correlations only between overall cognitive performance (as assessed with the MMSE) and the volume of right hippocampus, and between the total score on the visual verbal learning test and the volume of the right and left parahippocampal gyrus. Conclusions: These findings highlight different patterns of relationship between cognitive performance and volumes of medial temporal structures in depressed individuals and healthy elderly subjects. The direct correlation between delayed visual verbal memory recall scores with left parahippocampal volumes specifically in elderly depressed individuals provides support to the view that depression in elderly populations may be a risk factor for dementia. (C) 2009 Elsevier Inc. All rights reserved.
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Declarative memory impairments are common in patients with bipolar illness, suggesting underlying hippocampal pathology. However, hippocampal volume deficits are rarely observed in bipolar disorder. Here we used surface-based anatomic mapping to examine hippocampal anatomy in bipolar patients treated with lithium relative to matched control subjects and unmedicated patients with bipolar disorder. High-resolution brain magnetic resonance images were acquired from 33 patients with bipolar disorder ( 21 treated with lithium and 12 unmedicated), and 62 demographically matched healthy control subjects. Three-dimensional parametric mesh models were created from manual tracings of the hippocampal formation. Total hippocampal volume was significantly larger in lithium-treated bipolar patients compared with healthy controls (by 10.3%; p=0.001) and unmedicated bipolar patients ( by 13.9%; p=0.003). Statistical mapping results, confirmed by permutation testing, revealed localized deficits in the right hippocampus, in regions corresponding primarily to cornu ammonis vertical bar subfields, in unmedicated bipolar patients, as compared to both normal controls (p=0.01), and in lithium-treated bipolar patients (p=0.03). These findings demonstrate the sensitivity of these anatomic mapping methods for detecting subtle alterations in hippocampal structure in bipolar disorder. The observed reduction in subregions of the hippocampus in unmedicated bipolar patients suggests a possible neural correlate for memory deficits frequently reported in this illness. Moreover, increased hippocampal volume in lithium-treated bipolar patients may reflect postulated neurotrophic effects of this agent, a possibility warranting further study in longitudinal investigations.
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We present a mathematical framework that combines extinction-colonization dynamics with the dynamics of patch succession. We draw an analogy between the epidemiological categorization of individuals (infected, susceptible, latent and resistant) and the patch structure of a spatially heterogeneous landscape (occupied-suitable, empty-suitable, occupied-unsuitable and empty-unsuitable). This approach allows one to consider life-history attributes that influence persistence in patchy environments (e.g., longevity, colonization ability) in concert with extrinsic processes (e.g., disturbances, succession) that lead to spatial heterogeneity in patch suitability. It also allows the incorporation of seed banks and other dormant life forms, thus broadening patch occupancy dynamics to include sink habitats. We use the model to investigate how equilibrium patch occupancy is influenced by four critical parameters: colonization rate? extinction rate, disturbance frequency and the rate of habitat succession. This analysis leads to general predictions about how the temporal scaling of patch succession and extinction-colonization dynamics influences long-term persistence. We apply the model to herbaceous, early-successional species that inhabit open patches created by periodic disturbances. We predict the minimum disturbance frequency required far viable management of such species in the Florida scrub ecosystem. (C) 2001 Academic Press.
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The collection of spatial information to quantify changes to the state and condition of the environment is a fundamental component of conservation or sustainable utilization of tropical and subtropical forests, Age is an important structural attribute of old-growth forests influencing biological diversity in Australia eucalypt forests. Aerial photograph interpretation has traditionally been used for mapping the age and structure of forest stands. However this method is subjective and is not able to accurately capture fine to landscape scale variation necessary for ecological studies. Identification and mapping of fine to landscape scale vegetative structural attributes will allow the compilation of information associated with Montreal Process indicators lb and ld, which seek to determine linkages between age structure and the diversity and abundance of forest fauna populations. This project integrated measurements of structural attributes derived from a canopy-height elevation model with results from a geometrical-optical/spectral mixture analysis model to map forest age structure at a landscape scale. The availability of multiple-scale data allows the transfer of high-resolution attributes to landscape scale monitoring. Multispectral image data were obtained from a DMSV (Digital Multi-Spectral Video) sensor over St Mary's State Forest in Southeast Queensland, Australia. Local scene variance levels for different forest tapes calculated from the DMSV data were used to optimize the tree density and canopy size output in a geometric-optical model applied to a Landsat Thematic Mapper (TU) data set. Airborne laser scanner data obtained over the project area were used to calibrate a digital filter to extract tree heights from a digital elevation model that was derived from scanned colour stereopairs. The modelled estimates of tree height, crown size, and tree density were used to produce a decision-tree classification of forest successional stage at a landscape scale. The results obtained (72% accuracy), were limited in validation, but demonstrate potential for using the multi-scale methodology to provide spatial information for forestry policy objectives (ie., monitoring forest age structure).
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This paper deals with non-Markovian behavior in atomic systems coupled to a structured reservoir of quantum electromagnetic field modes, with particular relevance to atoms interacting with the field in high-Q cavities or photonic band-gap materials. In cases such as the former, we show that the pseudomode theory for single-quantum reservoir excitations can be obtained by applying the Fano diagonalization method to a system in which the atomic transitions are coupled to a discrete set of (cavity) quasimodes, which in turn are coupled to a continuum set of (external) quasimodes with slowly varying coupling constants and continuum mode density. Each pseudomode can be identified with a discrete quasimode, which gives structure to the actual reservoir of true modes via the expressions for the equivalent atom-true mode coupling constants. The quasimode theory enables cases of multiple excitation of the reservoir to now be treated via Markovian master equations for the atom-discrete quasimode system. Applications of the theory to one, two, and many discrete quasimodes are made. For a simple photonic band-gap model, where the reservoir structure is associated with the true mode density rather than the coupling constants, the single quantum excitation case appears to be equivalent to a case with two discrete quasimodes.
Three-dimensional structure of RTD-1, a cyclic antimicrobial defensin from rhesus macaque leukocytes
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Most mammalian defensins are cationic peptides of 29-42 amino acids long, stabilized by three disulfide bonds. However, recently Tang et al. (1999, Science 286, 498-502) reported the isolation of a new defensin type found in the leukocytes of rhesus macaques. In contrast to all the other defensins found so far, rhesus theta defensin-1 (RTD-1) is composed of just 18 amino acids with the backbone cyclized through peptide bonds. Antibacterial activities of both the native cyclic peptide and a linear form were examined, showing that the cyclic form was 3-fold more active than the open chain analogue [Tang et al. (1999) Science 286, 498-502]. To elucidate the three-dimensional structure of RTD-1 and its open chain analogue, both peptides were synthesized using solid-phase peptide synthesis and tert-butyloxycarbonyl chemistry. The structures of both peptides in aqueous solution were determined from two-dimensional H-1 NMR data recorded at 500 and 750 MHz. Structural constraints consisting of interproton distances and dihedral angles were used as input for simulated-annealing calculations and water refinement with the program CNS. RTD-1 and its open chain analogue oRTD-1 adopt very similar structures in water. Both comprise an extended beta -hairpin structure with turns at one or both ends. The turns are well defined within themselves and seem to be flexible with respect to the extended regions of the molecules. Although the two strands of the beta -sheet are connected by three disulfide bonds, this region displays a degree of flexibility. The structural similarity of RTD-1 and its open chain analogue oRTD-1, as well as their comparable degree of flexibility, support the theory that the additional charges at the termini of the open chain analogue rather than overall differences in structure or flexibility are the cause for oRTD-1's lower antimicrobial activity. In contrast to numerous other antimicrobial peptides, RTD-1 does not display any amphiphilic character, even though surface models of RTD-1 exhibit a certain clustering of positive charges. Some amide protons of RTD-1 that should be solvent-exposed in monomeric beta -sheet structures show low-temperature coefficients, suggesting the possible presence of weak intermolecular hydrogen bonds.
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A new parafermionic algebra associated with the homogeneous space A(2)((2))/U(1) and its corresponding Z-algebra have been recently proposed. In this paper, we give a free boson representation of the A(2)((2)) parafermion algebra in terms of seven free fields. Free field realizations of the parafermionic energy-momentum tensor and screening currents are also obtained. A new algebraic structure is discovered, which contains a W-algebra type primary field with spin two. (C) 2002 Published by Elsevier Science B.V.
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Novel current density mapping (CDM) schemes are developed for the design of new actively shielded, clinical magnetic resonance imaging (MRI) magnets. This is an extended inverse method in which the entire potential solution space for the superconductors has been considered, rather than single current density layers. The solution provides an insight into the required superconducting coil pattern for a desired magnet configuration. This information is then used as an initial set of parameters for the magnet structure, and a previously developed hybrid numerical optimization technique is used to obtain the final geometry of the magnet. The CDM scheme is applied to the design of compact symmetric, asymmetric, and open architecture 1.0-1.5 T MRI magnet systems of novel geometry and utility. A new symmetric 1.0-T system that is just I m in length with a full 50-cm diameter of the active, or sensitive, volume (DSV) is detailed, as well as an asymmetric system in which a 50-cm DSV begins just 14 cm from the end of the coil structure. Finally a 1.0-T open magnet system with a full 50-cm DSV is presented. These new designs provide clinically useful homogeneous regions and have appropriately restricted stray fields but, in some of the designs, the DSV is much closer to the end of the magnet system than in conventional designs. These new designs have the potential to reduce patient claustrophobia and improve physician access to patients undergoing scans. (C) 2002 Wiley Periodicals, Inc.
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In computer simulations of smooth dynamical systems, the original phase space is replaced by machine arithmetic, which is a finite set. The resulting spatially discretized dynamical systems do not inherit all functional properties of the original systems, such as surjectivity and existence of absolutely continuous invariant measures. This can lead to computational collapse to fixed points or short cycles. The paper studies loss of such properties in spatial discretizations of dynamical systems induced by unimodal mappings of the unit interval. The problem reduces to studying set-valued negative semitrajectories of the discretized system. As the grid is refined, the asymptotic behavior of the cardinality structure of the semitrajectories follows probabilistic laws corresponding to a branching process. The transition probabilities of this process are explicitly calculated. These results are illustrated by the example of the discretized logistic mapping.