992 resultados para Implicit Function


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We formulate and interpret several multi-modal registration methods in the context of a unified statistical and information theoretic framework. A unified interpretation clarifies the implicit assumptions of each method yielding a better understanding of their relative strengths and weaknesses. Additionally, we discuss a generative statistical model from which we derive a novel analysis tool, the "auto-information function", as a means of assessing and exploiting the common spatial dependencies inherent in multi-modal imagery. We analytically derive useful properties of the "auto-information" as well as verify them empirically on multi-modal imagery. Among the useful aspects of the "auto-information function" is that it can be computed from imaging modalities independently and it allows one to decompose the search space of registration problems.

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Nonlinear multivariate statistical techniques on fast computers offer the potential to capture more of the dynamics of the high dimensional, noisy systems underlying financial markets than traditional models, while making fewer restrictive assumptions. This thesis presents a collection of practical techniques to address important estimation and confidence issues for Radial Basis Function networks arising from such a data driven approach, including efficient methods for parameter estimation and pruning, a pointwise prediction error estimator, and a methodology for controlling the "data mining'' problem. Novel applications in the finance area are described, including customized, adaptive option pricing and stock price prediction.

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Polycystic Ovary Syndrome (PCOS) is a complex disorder encompassing reproductive and metabolic dysfunction. Ovarian hyperandrogenism is an endocrine hallmark of human PCOS. In animal models, PCOS-like abnormalities can be recreated by in utero over-exposure to androgenic steroid hormones. This thesis investigated pancreatic and adrenal development and function in a unique model of PCOS. Fetal sheep were directly exposed (day 62 and day 82 of gestation) to steroidal excesses - androgen excess (testosterone propionate - TP), estrogen excess (diethylstilbestrol - DES) or glucocorticoid excess (dexamethasone - DEX). At d90 gestation there was elevated expression of genes involved in β- cell development and function: PDX-1 (P<0.001), and INS (P<0.05), INSR (P<0.05) driven by androgenic excess only in the female fetal pancreas. β- cell numbers (P<0.001) and in vitro insulin secretion (P<0.05) were also elevated in androgen exposed female fetuses. There was a significant increase in insulin secreting β-cell numbers (P<0.001) and in vivo insulin secretion (glucose stimulated) (P<0.01) in adult female offspring, specifically associated with prenatal androgen excess. At d90 gestation, female fetal adrenal gene expression was perturbed by fetal estrogenic exposure. Male fetal adrenal gene expression was altered more dramatically by fetal glucocorticoid exposure. In female adult offspring from androgen exposed pregnancies there was increased adrenal steroidogenic gene expression and in vivo testosterone secretion (P<0.01). This highlights that the adrenal glands may contribute towards excess androgen secretion in PCOS, but such effects might be secondary to other metabolic alterations driven by prenatal androgen exposure, such as excess insulin secretion Thus there may be dialogue between the pancreas and adrenal gland, programmed during early life, with implications for adult health Given both hyperinsulinaemia and hyperandrogenism are common features in PCOS, we suggest that their origins may be at least partially due to altered fetal steroidal environments, specifically excess androgenic stimulation

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This chapter examines the role of the advanced nurse practitioner (ANP) within the domains of practice identified by the Royal College of Nursing (2002) as the teaching and coaching function. (Note that this is referred to by the NMC as the education function. It approaches the analysis against the backdrop of three policy documents: The Expert Patient: a new approach to chronic disease management for the 21st century(DoH 2001), Choosing Health: making healthy choices easier (DoH 2004), Our health, our care, our say (DoH 2006). It draws into the frame the experiences of ANP students as they work with patients, clients and carers, with the intention of enabling health and managing illness. It uses examples from a range of everyday practice setting to illustrate the inherent challenges of the teaching and coaching function of the ANP, at the same time as recognising its significance if patients, clients and carers are to be enabled to make choices that might optimize their well-being. Before this, however, some statistics are presented to focus thinking on why education is an invaluable component of advanced nursing practice.

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The aim of this study was to analyze the effects of short-term resistance training on the body composition profile and muscle function in a group of Anorexia Nervosa restricting type (AN-R) patients. The sample consisted of AN-R female adolescents (12.8 ± 0.6 years) allocated into the control and intervention groups (n¼18 each). Body composition and relative strength were assessed at baseline, after 8 weeks and 4 weeks following the intervention. Body mass index (BMI) increased throughout the study (p = 0.011). Significant skeletal muscle mass (SMM) gains were found in the intervention group (p = 0.045, d = 0.6) that correlated to the change in BMI (r = 0.51, p < 0.031). Meanwhile, fat mass (FM) gains were significant in the control group (p = 0.047, d = 0.6) and correlated (r > 0.60) with change in BMI in both the groups. Significant relative strength increases (p < 0.001) were found in the intervention group and were sustained over time.

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King, R. D. and Wise, P. H. and Clare, A. (2004) Confirmation of Data Mining Based Predictions of Protein Function. Bioinformatics 20(7), 1110-1118

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Clare, A. and King R.D. (2003) Predicting gene function in Saccharomyces cerevisiae. 2nd European Conference on Computational Biology (ECCB '03). (published as a journal supplement in Bioinformatics 19: ii42-ii49)

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Q. Meng and M. H Lee, Automated cross-modal mapping in robotic eye/hand systems using plastic radial basis function networks, Connection Science, 19(1), pp 25-52, 2007.

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Q. Meng and M.H. Lee, 'Error-driven active learning in growing radial basis function networks for early robot learning', 2006 IEEE International Conference on Robotics and Automation (IEEE ICRA 2006), 2984-90, Orlando, Florida, USA.

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The interest in the study of ventricular function has grown considerably in the last decades. In this review, we analyse the extreme values of ventricular function as obtained with Doppler echocardiography. We mainly focus on the parameters that have been used throughout the history of Doppler echocardiography to assess left ventricular (LV) systolic and diastolic function. The ‘athlete's heart’ would be the highest expression of ventricular function whereas its lowest expression is represented by the failing heart, independently from the original aetiology leading to this condition. There are, however, morphological similarities (dilation and hypertrophy) between the athlete's and the failing heart, which emerge as physiological and pathophysiological adaptations, respectively. The introduction of new assessment techniques, specifically speckle tracking, may provide new insight into the properties that determine ventricular filling, specifically left ventricular twisting. The concept of ventricular function must be always considered, although it may not be always possible to distinguish the normal heart of sedentary individuals from that of highly trained hearts based solely on echocardiographic or basic studies.

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This commentary links Humphrey and Sui’s proposed Self-attention Network (SAN) to the memory advantage associated with self-relevant information (i.e., the self-reference effect). Articulating this link elucidates the functional quality of the SAN in ensuring that information of potential importance to self is not lost. This adaptive system for self-processing mirrors the cognitive response to threat stimuli, which also elicit attentional biases and produce characteristically enhanced, episodic representations in memory. Understanding the link between the SAN and memory is key to comprehending more broadly the operation of the self in cognition.

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Musculoskeletal ageing is associated with profound morphological and functional changes that increase fall risk and disease incidence and is characterised by age-related reductions in motor unit number and atrophy of muscle fibres, particularly type II fibres. Decrements in functional strength and power are relatively modest until the 6th decade, after which the rate of loss exponentially accelerates, particularly beyond the 8th decade of life. Physical activity is a therapeutic modality that can significantly attenuate age-related decline. The underlying signature of ageing, as manifested by perturbed redox homeostasis, leads to a blunting of acute and chronic redox regulated exercise adaptations. Impaired redox regulated exercise adaptations are mechanistically related to altered exercise-induced reactive oxygen and nitrogen species generation and a resultant failure to properly activate redox regulated signaling cascades. Despite the aforementioned specific impairment in redox signaling, exercise induces a plethora of beneficial effects, irrespective of age. There is, therefore, strong evidence for promoting regular physical exercise, especially progressive resistance training as a lifelong habitual practice.

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BACKGROUND:In the current climate of high-throughput computational biology, the inference of a protein's function from related measurements, such as protein-protein interaction relations, has become a canonical task. Most existing technologies pursue this task as a classification problem, on a term-by-term basis, for each term in a database, such as the Gene Ontology (GO) database, a popular rigorous vocabulary for biological functions. However, ontology structures are essentially hierarchies, with certain top to bottom annotation rules which protein function predictions should in principle follow. Currently, the most common approach to imposing these hierarchical constraints on network-based classifiers is through the use of transitive closure to predictions.RESULTS:We propose a probabilistic framework to integrate information in relational data, in the form of a protein-protein interaction network, and a hierarchically structured database of terms, in the form of the GO database, for the purpose of protein function prediction. At the heart of our framework is a factorization of local neighborhood information in the protein-protein interaction network across successive ancestral terms in the GO hierarchy. We introduce a classifier within this framework, with computationally efficient implementation, that produces GO-term predictions that naturally obey a hierarchical 'true-path' consistency from root to leaves, without the need for further post-processing.CONCLUSION:A cross-validation study, using data from the yeast Saccharomyces cerevisiae, shows our method offers substantial improvements over both standard 'guilt-by-association' (i.e., Nearest-Neighbor) and more refined Markov random field methods, whether in their original form or when post-processed to artificially impose 'true-path' consistency. Further analysis of the results indicates that these improvements are associated with increased predictive capabilities (i.e., increased positive predictive value), and that this increase is consistent uniformly with GO-term depth. Additional in silico validation on a collection of new annotations recently added to GO confirms the advantages suggested by the cross-validation study. Taken as a whole, our results show that a hierarchical approach to network-based protein function prediction, that exploits the ontological structure of protein annotation databases in a principled manner, can offer substantial advantages over the successive application of 'flat' network-based methods.

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Growth/differentiation factor 5 (GDF5) and glial cell line-derived neurotrophic factor (GDNF) are neurotrophic factors that promote the survival of midbrain dopaminergic neurons in vitro and in vivo. Both factors have potent neurotrophic and neuroprotective effects in rat models of Parkinson's disease (PD), and may represent promising new therapies for PD. The aim of the present study was to investigate the endogenous expression and function of GDF5 and GDNF in the nigrostriatal dopaminergic system during development and in rat models of PD. Examination of the temporal expression patterns of endogenous GDF5, GDNF, and their respective receptors, in the developing and adult nigrostriatal dopaminergic system suggest that these factors play important roles in promoting the survival and maturation of midbrain dopaminergic neurons during the period of postnatal programmed cell death. The relative levels of GDF5 and GDNF mRNAs in the midbrain and striatum, and their individual temporal expression patterns during development, suggest that their modes of actions are quite distinct in vivo. Furthermore, the sustained expression of GDF5, GDNF, and their receptors into adulthood suggest roles for these factors in the continued support and maintenance of mature nigrostriatal dopaminergic neurons. The present study found that endogenous GDF5, GDNF, and their receptors are differentially expressed in two 6-hydroxydopamine-induced lesion adult rat models of PD. In both terminal and axonal lesion models of PD, GDF5 mRNA levels in the striatum increased at 10 days post-lesion, while GDNF mRNA levels in the nigrostriatal system decreased at 10 and 28 days post-lesion. Thus, despite the fact that exogenous GDF5 and GDNF have similar effects on midbrain dopaminergic neurons in vitro and in vivo, their endogenous responses to a neurotoxic injury are quite distinct. These results highlight the importance of studying the temporal dynamic changes in neurotrophic factor expression during development and in animal models of PD.