Deep networks are able to learn good representations of unlabelled data via a greedy layer-wise approach to training. One challenge arises in choosing the layer types to use, whether it is an autoencoder, restricted boltzmann machine, with and without sparsity regularization. The layer choice directly affects the type of representations learned. In this paper, we examine sparse autoencoders and...

Please cite this article as: Artal R, et al. Neumoencéfalo frontal sintomático secundario a displasia fibrosa sinusal. Acta Otorrinolaringol Esp. 2011;62:251--2. ∗ Corresponding author. E-mail address: [email protected] (R. Artal). with ideational slowness, motor aphasia, agraphia, acalculia and worsening of the headache. He underwent a brain CT scan, which revealed significant pneumoceph...

3D solutions of the dynamical equations in the presence of external forces are derived for a homogeneous, prestressed medium. 2D plane waves solutions are obtained from general solutions and show that there exist two types of plane waves, namely, quasi-P waves and quasi-SV waves. Expressions for slowness surfaces and apparent velocities for these waves are derived analytically as well as numeri...

BACKGROUND A 57-year-old male diagnosed with Plasmodium vivax malaria presented with a subacute onset of hand tremor, slowness, and gait difficulty. PHENOMENOLOGY A bilateral upper extremity kinetic tremor was seen, as well as a right upper extremity rigidity and body bradykinesia. EDUCATIONAL VALUE Parkinsonism and tremor are neurological manifestations that may occur in malaria as a resul...

Regional cerebral oxygen metabolism was measured before and after limbic leucotomy in a patient with Gilles de la Tourette syndrome, obsessive compulsive disorder, and obsessional slowness. The preoperative scan showed hypermetabolism in the caudate nuclei, which normalised after operation. It is proposed that the beneficial effects of this operation on both tics and obsessive compulsive behavi...

Temporal slowness is a learning principle that allows learning of invariant representations by extracting slowly varying features from quickly varying input signals. Slow feature analysis (SFA) is an efficient algorithm based on this principle and has been applied to the learning of translation, scale, and other invariances in a simple model of the visual system. Here, a theoretical analysis of...

The present study is based on the conceptual model defined by Fried which explains phenotypic frailty through the presence of the following criteria: weight loss; exhaustion; low physical activity; slowness and weakness. The aim of the present study was to identify the behaviour of phenotypic frailty and outline the profile of the frail elderly Palavras-chave: Idoso; Envelhecimento; Fragilidade...