Carmen Hernández

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Spinal cord injury (SCI) is characterized by a total or partial loss of motor and sensory functions due to the inability of neurons to regenerate. This lack of axonal regenerative response has been associated with the induction of inhibitory proteins for regeneration, such as the Eph receptor tyrosine kinases. One member of this family, the EphA4 receptor,(More)
Functional impairment after spinal cord injury (SCI) is partially attributed to neuronal cell death, with further degeneration caused by the accompanying apoptosis of myelin-forming oligodendrocytes. The Eph receptor protein tyrosine kinase family and its cognate ligands, the ephrins, have been identified to be involved in axonal outgrowth, synapse(More)
The new SeDeM Method is proposed for testing the batch-to-batch reproducibility of the same active pharmaceutical ingredient (API) in powder form. The procedure describes the study of the galenic properties of substances in powder form in terms of the applicability of direct compression technology. Through experimental determination of the SeDeM Method(More)
In this paper we give a formal definition of the high-order Boltzmann machine (BM), and extend the well-known results on the convergence of the learning algorithm of the two-order BM. From the Bahadur-Lazarsfeld expansion we characterize the probability distribution learned by the high order BM. Likewise a criterion is given to establish the topology of the(More)
This work reports the results obtained with the application of High Order Boltzmann Machines without hidden units to construct classifiers for some problems that represent different learning paradigms. The Boltzmann Machine weight updating algorithm remains the same even when some of the units can take values in a discrete set or in a continuous interval.(More)
Mel frequency cepstral coefficients (MFCCs) are a standard tool for automatic speech recognition (ASR), but they fail to capture part of the dynamics of speech. The nonlinear nature of speech suggests that extra information provided by some nonlinear features could be especially useful when training data are scarce or when the ASR task is very complex. In(More)
Dementia is a growing concern due to the aging process of the western societies. Non-invasive detection is therefore a high priority research endeavor. In this paper we report results of classification systems applied to the feature vectors obtained by a feature extraction method computed on structural magnetic resonance imaging (sMRI) volumes for the(More)