966 resultados para Functional Capacity Classification


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Most of the modem developments with classification trees are aimed at improving their predictive capacity. This article considers a curiously neglected aspect of classification trees, namely the reliability of predictions that come from a given classification tree. In the sense that a node of a tree represents a point in the predictor space in the limit, the aim of this article is the development of localized assessment of the reliability of prediction rules. A classification tree may be used either to provide a probability forecast, where for each node the membership probabilities for each class constitutes the prediction, or a true classification where each new observation is predictively assigned to a unique class. Correspondingly, two types of reliability measure will be derived-namely, prediction reliability and classification reliability. We use bootstrapping methods as the main tool to construct these measures. We also provide a suite of graphical displays by which they may be easily appreciated. In addition to providing some estimate of the reliability of specific forecasts of each type, these measures can also be used to guide future data collection to improve the effectiveness of the tree model. The motivating example we give has a binary response, namely the presence or absence of a species of Eucalypt, Eucalyptus cloeziana, at a given sampling location in response to a suite of environmental covariates, (although the methods are not restricted to binary response data).

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Methodological criticisms of research undertaken in the area of paediatric burns are widespread. To date, quasi-experimental research designs have most frequently been used to examine the impact of impairments such as scarring and reduced ran e of motion on functional outcomes. Predominantly, these studies have utilised a narrow definition of functioning (e.g. school attendance) to determine a child's level of participation in activities post-burn injury. Until recently, there had been little attempt to develop and/or test a theoretical model of functional outcome with these children. Using a conceptual model of functional outcome based oil the International Classification of Functioning, Disability and Health, this review paper outlines the current state of the research literature and presents explanatory case study methodology as an alternative research design to further advance the Study of functional outcome post-burn injury. (C) 2004 Elsevier Ltd and ISBI. All rights reserved.

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We present new simulation results for the packing of single-center and three-center models of carbon dioxide at high pressure in carbon slit pores. The former shows a series of packing transitions that are well described by our density functional theory model developed earlier. In contrast, these transitions are absent for the three-center model. Analysis of the simulation results shows that alternations of flat-lying molecules and rotated molecules can occur as the pore width is increased. The presence or absence of quadrupoles has negligible effect on these high-density structures.

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Scorpion toxins are common experimental tools for studies of biochemical and pharmacological properties of ion channels. The number of functionally annotated scorpion toxins is steadily growing, but the number of identified toxin sequences is increasing at much faster pace. With an estimated 100,000 different variants, bioinformatic analysis of scorpion toxins is becoming a necessary tool for their systematic functional analysis. Here, we report a bioinformatics-driven system involving scorpion toxin structural classification, functional annotation, database technology, sequence comparison, nearest neighbour analysis, and decision rules which produces highly accurate predictions of scorpion toxin functional properties. (c) 2005 Elsevier Inc. All rights reserved.

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The process of adsorption of two dissociating and two non-dissociating aromatic compounds from dilute aqueous solutions on an untreated commercially available activated carbon (B.D.H.) was investigated systematically. All adsorption experiments were carried out in pH controlled aqueous solutions. The experimental isotherms were fitted into four different models (Langmuir homogenous Models, Langmuir binary Model, Langmuir-Freundlich single model and Langmuir-Freundlich double model). Variation of the model parameters with the solution pH was studied and used to gain further insight into the adsorption process. The relationship between the model parameters and the solution pH and pK(a) was used to predict the adsorption capacity in molecular and ionic form of solutes in other solution. A relationship was sought to predict the effect of pH on the adsorption systems and for estimating the maximum adsorption capacity of carbon at any pH where the solute is ionized reasonably well. N-2 and CO2 adsorption were used to characterize the carbon. X-ray Photoelectron Spectroscopy (XPS) measurement was used for surface elemental analysis of the activated carbon.

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beta-turns are important topological motifs for biological recognition of proteins and peptides. Organic molecules that sample the side chain positions of beta-turns have shown broad binding capacity to multiple different receptors, for example benzodiazepines. beta-turns have traditionally been classified into various types based on the backbone dihedral angles (phi 2, psi 2, phi 3 and psi 3). Indeed, 57-68% of beta-turns are currently classified into 8 different backbone families (Type I, Type II, Type I', Type II', Type VIII, Type VIa1, Type VIa2 and Type VIb and Type IV which represents unclassified beta-turns). Although this classification of beta-turns has been useful, the resulting beta-turn types are not ideal for the design of beta-turn mimetics as they do not reflect topological features of the recognition elements, the side chains. To overcome this, we have extracted beta-turns from a data set of non-homologous and high-resolution protein crystal structures. The side chain positions, as defined by C-alpha-C-beta vectors, of these turns have been clustered using the kth nearest neighbor clustering and filtered nearest centroid sorting algorithms. Nine clusters were obtained that cluster 90% of the data, and the average intra-cluster RMSD of the four C-alpha-C-beta vectors is 0.36. The nine clusters therefore represent the topology of the side chain scaffold architecture of the vast majority of beta-turns. The mean structures of the nine clusters are useful for the development of beta-turn mimetics and as biological descriptors for focusing combinatorial chemistry towards biologically relevant topological space.

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Magnesium and its alloys have shown a great potential in effective hydrogen storage due to their advantages of high volumetric/ gravimetric hydrogen storage capacity and low cost. However, the use of these materials in fuel cells for automotive applications at the present time is limited by high hydrogenation temperature and sluggish sorption kinetics. This paper presents the recent results of design and development of magnesium-based nanocomposites demonstrating the catalytic effects of carbon nanotubes and transition metals on hydrogen adsorption in these materials. The results are promising for the application of magnesium materials for hydrogen storage, with significantly reduced absorption temperatures and enhanced ab/desorption kinetics. High level Density Functional Theory calculations support the analysis of the hydrogenation mechanisms by revealing the detailed atomic and molecular interactions that underpin the catalytic roles of incorporated carbon and titanium, providing clear guidance for further design and development of such materials with better hydrogen storage properties.

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We recently established that fibroblast growth factor (FGF)-1 promotes adipogenesis of primary human preadipocytes (phPA). In the current report, we have characterized the adipogenic effects of FGF-1 in phPA and also in a human PA strain derived from an individual with Simpson-Golabi-Behmel syndrome (SGBS PA), which exhibit an intrinsic capacity to differentiate with high efficiency. In further studies, we compared these models with the well-characterized murine 3T3-L1 preadipocyte cell line (3T3-L1 PA). FGF-1 up-regulated the adipogenic program in phPA, with increased expression of peroxisome proliferator-activated receptor-gamma in confluent PA prior to induction of differentiation and increased expression of adipocyte markers during differentiation. Moreover, phPA differentiated in the presence of FGF-1 were more insulin responsive and secreted increased levels of adiponectin. FGF-1 treatment of SGBS PA further enhanced differentiation. For the most part, the adipogenic program in phPA paralleled that observed in 3T3-L1 PA; however, we found no evidence of mitotic clonal expansion in the phPA. Finally, we investigated a role for extracellular regulated kinase 1/2 (ERK 1/2) in adipogenesis of phPA. FGF-1 induced robust phosphorylation of ERK1/2 in early differentiation and inhibition of ERK1/2 activity significantly reduced phPA differentiation. These data suggest that FGF-1 treated phPA represent a valuable in vitro model for the study of adipogenesis and insulin action and indicate that ERK1/2 activation is necessary for human adipogenesis in the absence of mitotic clonal expansion.

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The G-protein coupled receptors--or GPCRs--comprise simultaneously one of the largest and one of the most multi-functional protein families known to modern-day molecular bioscience. From a drug discovery and pharmaceutical industry perspective, the GPCRs constitute one of the most commercially and economically important groups of proteins known. The GPCRs undertake numerous vital metabolic functions and interact with a hugely diverse range of small and large ligands. Many different methodologies have been developed to efficiently and accurately classify the GPCRs. These range from motif-based techniques to machine learning as well as a variety of alignment-free techniques based on the physiochemical properties of sequences. We review here the available methodologies for the classification of GPCRs. Part of this work focuses on how we have tried to build the intrinsically hierarchical nature of sequence relations, implicit within the family, into an adaptive approach to classification. Importantly, we also allude to some of the key innate problems in developing an effective approach to classifying the GPCRs: the lack of sequence similarity between the six classes that comprise the GPCR family and the low sequence similarity to other family members evinced by many newly revealed members of the family.

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This thesis deals with the problem of Information Systems design for Corporate Management. It shows that the results of applying current approaches to Management Information Systems and Corporate Modelling fully justify a fresh look to the problem. The thesis develops an approach to design based on Cybernetic principles and theories. It looks at Management as an informational process and discusses the relevance of regulation theory to its practice. The work proceeds around the concept of change and its effects on the organization's stability and survival. The idea of looking at organizations as viable systems is discussed and a design to enhance survival capacity is developed. It takes Ashby's theory of adaptation and developments on ultra-stability as a theoretical framework and considering conditions for learning and foresight deduces that a design should include three basic components: A dynamic model of the organization- environment relationships; a method to spot significant changes in the value of the essential variables and in a certain set of parameters; and a Controller able to conceive and change the other two elements and to make choices among alternative policies. Further considerations of the conditions for rapid adaptation in organisms composed of many parts, and the law of Requisite Variety determine that successful adaptive behaviour requires certain functional organization. Beer's model of viable organizations is put in relation to Ashby's theory of adaptation and regulation. The use of the Ultra-stable system as abstract unit of analysis permits developing a rigorous taxonomy of change; it starts distinguishing between change with in behaviour and change of behaviour to complete the classification with organizational change. It relates these changes to the logical categories of learning connecting the topic of Information System design with that of organizational learning.

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We address the important bioinformatics problem of predicting protein function from a protein's primary sequence. We consider the functional classification of G-Protein-Coupled Receptors (GPCRs), whose functions are specified in a class hierarchy. We tackle this task using a novel top-down hierarchical classification system where, for each node in the class hierarchy, the predictor attributes to be used in that node and the classifier to be applied to the selected attributes are chosen in a data-driven manner. Compared with a previous hierarchical classification system selecting classifiers only, our new system significantly reduced processing time without significantly sacrificing predictive accuracy.

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Despite the large body of research regarding the role of memory in OCD, the results are described as mixed at best (Hermans et al., 2008). For example, inconsistent findings have been reported with respect to basic capacity, intact verbal, and generally affected visuospatial memory. We suggest that this is due to the traditional pursuit of OCD memory impairment as one of the general capacity and/or domain specificity (visuospatial vs. verbal). In contrast, we conclude from our experiments (i.e., Harkin & Kessler, 2009, 2011; Harkin, Rutherford, & Kessler, 2011) and recent literature (e.g., Greisberg & McKay, 2003) that OCD memory impairment is secondary to executive dysfunction, and more specifically we identify three common factors (EBL: Executive-functioning efficiency, Binding complexity, and memory Load) that we generalize to 58 experimental findings from 46 OCD memory studies. As a result we explain otherwise inconsistent research – e.g., intact vs. deficient verbal memory – that are difficult to reconcile within a capacity or domain specific perspective. We conclude by discussing the relationship between our account and others', which in most cases is complementary rather than contradictory.

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Damaged, aged or unwanted cells are removed from the body by an active process known as apoptosis. This highly orchestrated programme results in the exposure of 'flags' at the dying cell surface and the release of attractive signals to recruit phagocytes. Together these changes ensure efficient phagocytic removal of dying cells and prevention of inflammatory and autoimmune disorders. Extracellular vesicles (EV) are released from a variety of cells (both viable and apoptotic) and they serve as a novel means of intercellular communication. They range in size: 70-100nm ('exosomes') through 100-1000nm ('microparticles') to large vesicles released from dying cells ('apoptotic bodies'). Release of apoptotic cell-derived extracellular vesicles (acdEV) of less than 1000nm is an important mechanism by which phagocytes are attracted to sites of cell death. Using a variety of approaches we characterize the release, physical characteristics and function of acdEV. Using fluorescence microscopy we demonstrate release of ICAM-3 on acdEV from dying leukocytes and, through the use of resistive pulse technology (qNano, IZON Science), we accurately size and quantitate acdEV release. The function of acdEV is revealed through the use of both horizontal chemotaxis assays (Dunn chambers) and vertical transwell migration assays (Cell-IQ, CM Technologies). These assays reveal potent chemoattractive capacity of acdEV and associated ICAM-3. Additionally we demonstrate an additional novel function of acdEV as anti-inflammatory immune-modulators. These data support an integrated approach to the physical and functional analyses of EV.

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Virus-specific CD8+ T cells are known to play an important role in the control of HIV infection. In this study we investigated whether there may be qualitative differences in the CD8+ T cell response in HIV-1- and HIV-2-infected individuals that contribute to the relatively efficient control of the latter infection. A molecular comparison of global TCR heterogeneity showed a more oligoclonal pattern of CD8 cells in HIV-1- than HIV-2-infected patients. This was reflected in restricted and conserved TCR usage by CD8+ T cells recognizing individual HLA-A2- and HLA-B57-restricted viral epitopes in HIV-1, with limited plasticity in their response to amino acid substitutions within these epitopes. The more diverse TCR usage observed for HIV-2-specific CD8 T cells was associated with an enhanced potential for CD8+ expansion and IFN- production on cross-recognition of variant epitopes. Our data suggest a mechanism that could account for any possible cross-protection that may be mediated by HIV-2-specific CD8+ T cells against HIV-1 infection. Furthermore, they have implications for HIV vaccine development, demonstrating an association between a polyclonal, virus-specific CD8+ T cell response and an enhanced capacity to tolerate substitutions within T cell epitopes.

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Relation between dermatoglyphic signs and temperaments types is considered. An algorithm for papillary patterns classification and Izenk’s two factors model are used for establishment relationship asymmetry signs with psychic functional state of human’s organism.