3,385 research outputs found
Os verbos psicológicos e a queda da preposição A no português do Brasil
No full textDissertação (mestrado) - Universidade Federal de Santa Catarina, Centro de Comunicação e Expressão.Este é um trabalho de sintaxe comparativa entre os verbos psicológicos no italiano e do PB. Trata do desaparecimento da preposição a nos DPs experienciadores em sentenças com verbos psicológicos que apresentam o tema na posição de sujeito no PB. Como Belletti & Rizzi (1988) consideramos estes verbos inacusativos e com o experienciador numa posição mais alta do que o tema. Note que os verbos têm dois argumentos. No PB, o sujeito desses verbos não reage bem a testes como o do clítico anafórico, de pro arbitrário e da passivização. No entanto, os testes evidenciam que o sujeito desses verbos não é argumento externo do verbo. Ao mesmo tempo o objeto experienciador, ao ser substituído por um quantificador universal, tem escopo sobre um WH tema, mostrando que o c-comanda. Reafirmamos que este tipo de verbo não atribui caso acusativo estrutural, mas, por outro lado, atribui caso acusativo inerente. Queremos propor que a preposição a se tornou específica para atribuir caso acusativo inerente. Como ela não é um atribuidor "forte", nos contextos em que compete com o verbo para atribuir caso ela desaparece. Quando o DP experienciador aparece deslocado à esquerda ela reaparece porque as marcas casuais se diluem e precisam ser reforçadas
L'anestesia generale causa degenerazione apoptotica nel cervello in via di sviluppo di Guinea pig e piglet.
No full textFrequent exposure of the immature brain to general anesthesia is common. The safety of this practice has recently been challenged in view of the evidence that general anesthetics could be damaging to the developing mammalian neurons. The initial reports were done in immature rats which raised the criticism regarding possibly unique vulnerability of those species, the correlation between the duration of brain development and the duration of anesthesia necessary to activate apoptosis and the importance of maintaining adequate nutritional/cardio-pulmonary homeostasis during anesthesia. Therefore we studied guinea pig whose brain growth is five-times longer than in rats and is completely prenatal phenomenon allowing anesthesia-induced neurotoxicity studies of fetal brain to be performed via anesthetizing pregnant mothers which, due to their size, we made invasive monitoring of maternal (and indirectly fetal) well-being technically feasible. Despite adequate maintenance of maternal homeostasis a single short maternal exposure (4hrs) to general anesthetic isoflurane, alone or with nitrous oxide and/or midazolam at peak of fetal synaptogenesis, induced severe neuroapoptosis in the fetal guinea pig brain which resulted in permanent loss of many neurons in vulnerable brain regions as detected in early post-natal life suggesting that anesthesia-induced neuroapoptosis can cause permanent brain damage.
We started to study also piglets whose brain growth is ten-times longer than in rats and is a prenatal and postnatal phenomenon. We anesthetized piglets 5-10 days-old, due to their large size we made invasive monitoring of their nutritional/cardio-pulmonary parameters. Despite adequate maintenance of piglet homeostasis, the preliminary data show that a single short exposure (4 hrs) to general anesthesia at the peak of synaptogenesis induced severe neuroapoptosis in newborn piglet. The anesthesia-induced developmental neuroapoptosis observed in the immature piglet brain mimics anesthesia-induced developmental neuroapoptosis observed in the immature rats and guinea pig brain
Decision Support Systems for Disease Detection and Diagnosis
No full textThe last few years have been characterized by a large amount of research activity in the field of healthcare for both the improvement of diagnostic treatments and the development of simple, efficient, and multi-tasking applications [...
A Decision Support System for Melanoma Diagnosis from Dermoscopic Images
No full textInnovative technologies in dermatology allow for the early screening of skin cancer, which results in a reduction in the mortality rate and surgical treatments. The diagnosis of melanoma is complex not only because of the number of different lesions but because of the high similarity amongst skin lesions of different nature; hence, human vision and physician experience still play a major role. The adoption of automatic systems would aid clinical assessment and make the diagnosis reproducible by eliminating inter- and intra-observer variabilities. In our paper, we describe a computer-aided system for the early diagnosis of melanoma in dermoscopic images. A soft pre-processing phase is performed so as to avoid the loss of details both in texture, colors, and contours, and color-based image segmentation is later carried out using k-means. Features linked to both geometric properties and color characteristics are used to analyze skin lesions through a support vector machine classifier. The PH2 public database is used for the assessment of the procedure’s sensitivity, specificity, and accuracy. A statistical approach is carried out to establish the impact of image quality on performance. The obtained results show remarkable achievements, so our computer-aided approach should be suitable as a Decision Support System for melanoma detection
Skin Lesion Segmentation Using Image Bit-Plane Multilayer Approach
No full textThe establishment of automatic diagnostic systems able to detect and classify skin lesions at the initial stage are getting really relevant and effective in providing support for medical personnel during clinical assessment. Image segmentation has a determinant part in computer-aided skin lesion diagnosis pipeline because it makes possible to extract and highlight information on lesion contour texture as, for example, skewness and area unevenness. However, artifacts, low contrast, indistinct boundaries, and different shapes and areas contribute to make skin lesion segmentation a challenging task. In this paper, a fully automatic computer-aided system for skin lesion segmentation in dermoscopic images is indicated. Adopting this method, noise and artifacts are initially reduced by the singular value decomposition; afterward lesion decomposition into a frame of bit-plane layers is performed. A specific procedure is implemented for redundant data reduction using simple Boolean operators. Since lesion and background are rarely homogeneous regions, the obtained segmentation region could contain some disjointed areas classified as lesion. To obtain a single zone classified as lesion avoiding spurious pixels or holes inside the image under test, mathematical morphological techniques are implemented. The performance obtained highlights the method validity
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