948 resultados para Neural algorithm


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STUDY DESIGN:: Retrospective database- query to identify all anterior spinal approaches. OBJECTIVES:: To assess all patients with pharyngo-cutaneous fistulas after anterior cervical spine surgery. SUMMARY OF BACKGROUND DATA:: Patients treated in University of Heidelberg Spine Medical Center, Spinal Cord Injury Unit and Department of Otolaryngology (Germany), between 2005 and 2011 with the diagnosis of pharyngo-cutaneous fistulas. METHODS:: We conducted a retrospective study on 5 patients between 2005 and 2011 with PCF after ACSS, their therapy management and outcome according to radiologic data and patient charts. RESULTS:: Upon presentation 4 patients were paraplegic. 2 had PCF arising from one piriform sinus, two patients from the posterior pharyngeal wall and piriform sinus combined and one patient only from the posterior pharyngeal wall. 2 had previous unsuccessful surgical repair elsewhere and 1 had prior radiation therapy. In 3 patients speech and swallowing could be completely restored, 2 patients died. Both were paraplegic. The patients needed an average of 2-3 procedures for complete functional recovery consisting of primary closure with various vascularised regional flaps and refining laser procedures supplemented with negative pressure wound therapy where needed. CONCLUSION:: Based on our experience we are able to provide a treatment algorithm that indicates that chronic as opposed to acute fistulas require a primary surgical closure combined with a vascularised flap that should be accompanied by the immediate application of a negative pressure wound therapy. We also conclude that particularly in paraplegic patients suffering this complication the risk for a fatal outcome is substantial.

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The neuropathology of Alzheimer disease is characterized by senile plaques, neurofibrillary tangles and cell death. These hallmarks develop according to the differential vulnerability of brain networks, senile plaques accumulating preferentially in the associative cortical areas and neurofibrillary tangles in the entorhinal cortex and the hippocampus. We suggest that the main aetiological hypotheses such as the beta-amyloid cascade hypothesis or its variant, the synaptic beta-amyloid hypothesis, will have to consider neural networks not just as targets of degenerative processes but also as contributors of the disease's progression and of its phenotype. Three domains of research are highlighted in this review. First, the cerebral reserve and the redundancy of the network's elements are related to brain vulnerability. Indeed, an enriched environment appears to increase the cerebral reserve as well as the threshold of disease's onset. Second, disease's progression and memory performance cannot be explained by synaptic or neuronal loss only, but also by the presence of compensatory mechanisms, such as synaptic scaling, at the microcircuit level. Third, some phenotypes of Alzheimer disease, such as hallucinations, appear to be related to progressive dysfunction of neural networks as a result, for instance, of a decreased signal to noise ratio, involving a diminished activity of the cholinergic system. Overall, converging results from studies of biological as well as artificial neural networks lead to the conclusion that changes in neural networks contribute strongly to Alzheimer disease's progression.

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Introduction New evidence from randomized controlled and etiology of fever studies, the availability of reliable RDT for malaria, and novel technologies call for revision of the IMCI strategy. We developed a new algorithm based on (i) a systematic review of published studies assessing the safety and appropriateness of RDT and antibiotic prescription, (ii) results from a clinical and microbiological investigation of febrile children aged <5 years, (iii) international expert IMCI opinions. The aim of this study was to assess the safety of the new algorithm among patients in urban and rural areas of Tanzania.Materials and Methods The design was a controlled noninferiority study. Enrolled children aged 2-59 months with any illness were managed either by a study clinician using the new Almanach algorithm (two intervention health facilities), or clinicians using standard practice, including RDT (two control HF). At day 7 and day 14, all patients were reassessed. Patients who were ill in between or not cured at day 14 were followed until recovery or death. Primary outcome was rate of complications, secondary outcome rate of antibiotic prescriptions.Results 1062 children were recruited. Main diagnoses were URTI 26%, pneumonia 19% and gastroenteritis (9.4%). 98% (531/541) were cured at D14 in the Almanach arm and 99.6% (519/521) in controls. Rate of secondary hospitalization was 0.2% in each. One death occurred in controls. None of the complications was due to withdrawal of antibiotics or antimalarials at day 0. Rate of antibiotic use was 19% in the Almanach arm and 84% in controls.Conclusion Evidence suggests that the new algorithm, primarily aimed at the rational use of drugs, is as safe as standard practice and leads to a drastic reduction of antibiotic use. The Almanach is currently being tested for clinician adherence to proposed procedures when used on paper or a mobile phone

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The paper deals with the development and application of the methodology for automatic mapping of pollution/contamination data. General Regression Neural Network (GRNN) is considered in detail and is proposed as an efficient tool to solve this problem. The automatic tuning of isotropic and an anisotropic GRNN model using cross-validation procedure is presented. Results are compared with k-nearest-neighbours interpolation algorithm using independent validation data set. Quality of mapping is controlled by the analysis of raw data and the residuals using variography. Maps of probabilities of exceeding a given decision level and ?thick? isoline visualization of the uncertainties are presented as examples of decision-oriented mapping. Real case study is based on mapping of radioactively contaminated territories.

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Este trabajo presenta un Algoritmo Genético (GA) del problema de secuenciar unidades en una línea de producción. Se tiene en cuenta la posibilidad de cambiar la secuencia de piezas mediante estaciones con acceso a un almacén intermedio o centralizado. El acceso al almacén además está restringido, debido al tamaño de las piezas.AbstractThis paper presents a Genetic Algorithm (GA) for the problem of sequencing in a mixed model non-permutation flowshop. Resequencingis permitted where stations have access to intermittent or centralized resequencing buffers. The access to a buffer is restricted by the number of available buffer places and the physical size of the products.

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In natural settings the same sound source is often heard repeatedly, with variations in spectro-temporal and spatial characteristics. We investigated how such repetitions influence sound representations and in particular how auditory cortices keep track of recently vs. often heard objects. A set of 40 environmental sounds was presented twice, i.e. as prime and as repeat, while subjects categorized the corresponding sound sources as living vs. non-living. Electrical neuroimaging analyses were applied to auditory evoked potentials (AEPs) comparing primes vs. repeats (effect of presentation) and the four experimental sections. Dynamic analysis of distributed source estimations revealed i) a significant main effect of presentation within the left temporal convexity at 164-215ms post-stimulus onset; and ii) a significant main effect of section in the right temporo-parietal junction at 166-213ms. A 3-way repeated measures ANOVA (hemisphere×presentation×section) applied to neural activity of the above clusters during the common time window confirmed the specificity of the left hemisphere for the effect of presentation, but not that of the right hemisphere for the effect of section. In conclusion, spatio-temporal dynamics of neural activity encode the temporal history of exposure to sound objects. Rapidly occurring plastic changes within the semantic representations of the left hemisphere keep track of objects heard a few seconds before, independent of the more general sound exposure history. Progressively occurring and more long-lasting plastic changes occurring predominantly within right hemispheric networks, which are known to code for perceptual, semantic and spatial aspects of sound objects, keep track of multiple exposures.

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Glucose homeostasis requires the tight regulation of glucose utilization by liver, muscle and white or brown fat, and glucose production and release in the blood by liver. The major goal of maintaining glycemia at ∼ 5 mM is to ensure a sufficient flux of glucose to the brain, which depends mostly on this nutrient as a source of metabolic energy. This homeostatic process is controlled by hormones, mainly glucagon and insulin, and by autonomic nervous activities that control the metabolic state of liver, muscle and fat tissue but also the secretory activity of the endocrine pancreas. Activation or inhibition of the sympathetic or parasympathetic branches of the autonomic nervous systems are controlled by glucose-excited or glucose-inhibited neurons located at different anatomical sites, mainly in the brainstem and the hypothalamus. Activation of these neurons by hyper- or hypoglycemia represents a critical aspect of the control of glucose homeostasis, and loss of glucose sensing by these cells as well as by pancreatic β-cells is a hallmark of type 2 diabetes. In this article, aspects of the brain-endocrine pancreas axis are reviewed, highlighting the importance of central glucose sensing in the control of counterregulation to hypoglycemia but also mentioning the role of the neural control in β-cell mass and function. Overall, the conclusions of these studies is that impaired glucose homeostasis, such as associated with type 2 diabetes, but also defective counterregulation to hypoglycemia, may be caused by initial defects in glucose sensing.

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Due to the large number of characteristics, there is a need to extract the most relevant characteristicsfrom the input data, so that the amount of information lost in this way is minimal, and the classification realized with the projected data set is relevant with respect to the original data. In order to achieve this feature extraction, different statistical techniques, as well as the principal components analysis (PCA) may be used. This thesis describes an extension of principal components analysis (PCA) allowing the extraction ofa finite number of relevant features from high-dimensional fuzzy data and noisy data. PCA finds linear combinations of the original measurement variables that describe the significant variation in the data. The comparisonof the two proposed methods was produced by using postoperative patient data. Experiment results demonstrate the ability of using the proposed two methods in complex data. Fuzzy PCA was used in the classificationproblem. The classification was applied by using the similarity classifier algorithm where total similarity measures weights are optimized with differential evolution algorithm. This thesis presents the comparison of the classification results based on the obtained data from the fuzzy PCA.

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The increasing interest aroused by more advanced forecasting techniques, together with the requirement for more accurate forecasts of tourismdemand at the destination level due to the constant growth of world tourism, has lead us to evaluate the forecasting performance of neural modelling relative to that of time seriesmethods at a regional level. Seasonality and volatility are important features of tourism data, which makes it a particularly favourable context in which to compare the forecasting performance of linear models to that of nonlinear alternative approaches. Pre-processed official statistical data of overnight stays and tourist arrivals fromall the different countries of origin to Catalonia from 2001 to 2009 is used in the study. When comparing the forecasting accuracy of the different techniques for different time horizons, autoregressive integrated moving average models outperform self-exciting threshold autoregressions and artificial neural network models, especially for shorter horizons. These results suggest that the there is a trade-off between the degree of pre-processing and the accuracy of the forecasts obtained with neural networks, which are more suitable in the presence of nonlinearity in the data. In spite of the significant differences between countries, which can be explained by different patterns of consumer behaviour,we also find that forecasts of tourist arrivals aremore accurate than forecasts of overnight stays.

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Cortical electrical stimulation mapping was used to study neural substrates of the function of writing in the temporoparietal cortex. We identified the sites involved in oral language (sentence reading and naming) and writing from dictation, in order to spare these areas during removal of brain tumours in 30 patients (23 in the left, and 7 in the right hemisphere). Electrostimulation of the cortex impaired writing ability in 62 restricted cortical areas (.25 cm2). These were found in left temporoparietal lobes and were mostly located along the superior temporal gyrus (Brodmann's areas 22 and 42). Stimulation of right temporoparietal lobes in right-handed patients produced no writing impairments. However there was a high variability of location between individuals. Stimulation resulted in combined symptoms (affecting oral language and writing) in fourteen patients, whereas in eight other patients, stimulation-induced pure agraphia symptoms with no oral language disturbance in twelve of the identified areas. Each detected area affected writing in a different way. We detected the various different stages of the auditory-to-motor pathway of writing from dictation: either through comprehension of the dictated sentences (word deafness areas), lexico-semantic retrieval, or phonologic processing. In group analysis, barycentres of all different types of writing interferences reveal a hierarchical functional organization along the superior temporal gyrus from initial word recognition to lexico-semantic and phonologic processes along the ventral and the dorsal comprehension pathways, supporting the previously described auditory-to-motor process. The left posterior Sylvian region supports different aspects of writing function that are extremely specialized and localized, sometimes being segregated in a way that could account for the occurrence of pure agraphia that has long-been described in cases of damage to this region.

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Ochratoxin A (OTA), a fungal contaminant of basic food commodities, is known to be highly cytotoxic, but the pathways underlying adverse effects at subcytotoxic concentrations remain to be elucidated. Recent reports indicate that OTA affects cell cycle regulation. Therefore, 3D brain cell cultures were used to study OTA effects on mitotically active neural stem/progenitor cells, comparing highly differentiated cultures with their immature counterparts. Changes in the rate of DNA synthesis were related to early changes in the mRNA expression of neural stem/progenitor cell markers. OTA at 10nM, a concentration below the cytotoxic level, was ineffective in immature cultures, whereas in mature cultures it significantly decreased the rate of DNA synthesis together with the mRNA expression of key transcriptional regulators such as Sox2, Mash1, Hes5, and Gli1; the cell cycle activator cyclin D2; the phenotypic markers nestin, doublecortin, and PDGFRα. These effects were largely prevented by Sonic hedgehog (Shh) peptide (500ngml(-1)) administration, indicating that OTA impaired the Shh pathway and the Sox2 regulatory transcription factor critical for stem cell self-renewal. Similar adverse effects of OTA in vivo might perturb the regulation of stem cell proliferation in the adult brain and in other organs exhibiting homeostatic and/or regenerative cell proliferation.

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Adaptació de l'algorisme de Kumar per resoldre sistemes d'equacions amb matrius de Toeplitz sobre els reals a cossos finits en un temps 0 (n log n).