Tradução, adaptação cultural e validação do questionário Body image After Breast Cancer para a língua portuguesa do Brasil

Universidade Estadual de Campinas . Faculdade de Educação Física

Advancing Bag-of-visual-words Representations For Lesion Classification In Retinal Images.

Diabetic Retinopathy (DR) is a complication of diabetes that can lead to blindness if not readily discovered. Automated screening algorithms have the potential to improve identification of patients who need further medical attention. However, the identification of lesions must be accurate to be useful for clinical application. The bag-of-visual-words (BoVW) algorithm employs a maximum-margin classifier in a flexible framework that is able to detect the most common DR-related lesions such as microaneurysms, cotton-wool spots and hard exudates. BoVW allows to bypass the need for pre- and post-processing of the retinographic images, as well as the need of specific ad hoc techniques for identification of each type of lesion. An extensive evaluation of the BoVW model, using three large retinograph datasets (DR1, DR2 and Messidor) with different resolution and collected by different healthcare personnel, was performed. The results demonstrate that the BoVW classification approach can identify different lesions within an image without having to utilize different algorithms for each lesion reducing processing time and providing a more flexible diagnostic system. Our BoVW scheme is based on sparse low-level feature detection with a Speeded-Up Robust Features (SURF) local descriptor, and mid-level features based on semi-soft coding with max pooling. The best BoVW representation for retinal image classification was an area under the receiver operating characteristic curve (AUC-ROC) of 97.8% (exudates) and 93.5% (red lesions), applying a cross-dataset validation protocol. To assess the accuracy for detecting cases that require referral within one year, the sparse extraction technique associated with semi-soft coding and max pooling obtained an AUC of 94.2 ± 2.0%, outperforming current methods. Those results indicate that, for retinal image classification tasks in clinical practice, BoVW is equal and, in some instances, surpasses results obtained using dense detection (widely believed to be the best choice in many vision problems) for the low-level descriptors.

Temporomandibular Dysfunction Post-craniotomy: Evaluation Between Pre- And Post-operative Status.

To identify risk factors associated with post-operative temporomandibular joint dysfunction after craniotomy. The study sample included 24 patients, mean age of 37.3 ± 10 years; eligible for surgery for refractory epilepsy, evaluated according to RDC/TMD before and after surgery. The primary predictor was the time after the surgery. The primary outcome variable was maximal mouth opening. Other outcome variables were: disc displacement, bruxism, TMJ sound, TMJ pain, and pain associated to mandibular movements. Data analyses were performed using bivariate and multiple regression methods. The maximal mouth opening was significantly reduced after surgery in all patients (p = 0.03). In the multiple regression model, time of evaluation and pre-operative bruxism were significantly (p < .05) associated with an increased risk for TMD post-surgery. A significant correlation between surgery follow-up time and maximal opening mouth was found. Pre-operative bruxism was associated with increased risk for temporomandibular joint dysfunction after craniotomy.

Detection Of Explosives On The Surface Of Banknotes By Raman Hyperspectral Imaging And Independent Component Analysis.

The aim of this study was to develop a methodology using Raman hyperspectral imaging and chemometric methods for identification of pre- and post-blast explosive residues on banknote surfaces. The explosives studied were of military, commercial and propellant uses. After the acquisition of the hyperspectral imaging, independent component analysis (ICA) was applied to extract the pure spectra and the distribution of the corresponding image constituents. The performance of the methodology was evaluated by the explained variance and the lack of fit of the models, by comparing the ICA recovered spectra with the reference spectra using correlation coefficients and by the presence of rotational ambiguity in the ICA solutions. The methodology was applied to forensic samples to solve an automated teller machine explosion case. Independent component analysis proved to be a suitable method of resolving curves, achieving equivalent performance with the multivariate curve resolution with alternating least squares (MCR-ALS) method. At low concentrations, MCR-ALS presents some limitations, as it did not provide the correct solution. The detection limit of the methodology presented in this study was 50μgcm(-2).

Determination Of Detergent And Dispensant Additives In Gasoline By Ring-oven And Near Infrared Hypespectral Imaging.

A method using the ring-oven technique for pre-concentration in filter paper discs and near infrared hyperspectral imaging is proposed to identify four detergent and dispersant additives, and to determine their concentration in gasoline. Different approaches were used to select the best image data processing in order to gather the relevant spectral information. This was attained by selecting the pixels of the region of interest (ROI), using a pre-calculated threshold value of the PCA scores arranged as histograms, to select the spectra set; summing up the selected spectra to achieve representativeness; and compensating for the superimposed filter paper spectral information, also supported by scores histograms for each individual sample. The best classification model was achieved using linear discriminant analysis and genetic algorithm (LDA/GA), whose correct classification rate in the external validation set was 92%. Previous classification of the type of additive present in the gasoline is necessary to define the PLS model required for its quantitative determination. Considering that two of the additives studied present high spectral similarity, a PLS regression model was constructed to predict their content in gasoline, while two additional models were used for the remaining additives. The results for the external validation of these regression models showed a mean percentage error of prediction varying from 5 to 15%.

Association Between Parity, Pre-pregnancy Body Mass Index And Gestational Weight Gain.

To analyze the relationship between parity, pre-pregnancy body mass index (BMI), and gestational weight gain (GWG). This observational controlled study was conducted from November 2013 to April 2014, with postpartum women who started antenatal care up to 14 weeks and had full-term births. Data were collected from medical records and antenatal cards. Descriptive and bivariate analyses were performed. The significance level was 5%. Data were collected from 130 primiparous and 160 multiparous women. At the beginning of prenatal care, 54.62% of the primiparous were eutrophic, while the majority of multiparous were overweight or obese (62.51%). Multiparas are two times more likely to be obese at the beginning of their pregnancies, when compared to primiparas. The average pre-pregnancy weight and final pregnancy weight was significantly higher in multiparous, however, the mean GWG was higher among primiparous. We found an inverse correlation between parity and the total GWG, but initial BMI was significantly higher in multiparas. Nevertheless, monitoring of the GWG through actions that promote a healthier lifestyle is needed, regardless of parity and nutritional status, in order to prevent excessive GWG and postpartum weight retention and consequently inadequate pre-pregnancy nutritional status in future pregnancies.

A comunicação corporal na pre-escola : caminhos e descaminhos

Universidade Estadual de Campinas . Faculdade de Educação Física

Crescimento e desempenho motor em pre-escolares de Itapira SP : um enfoque bio-social-cultural

Universidade Estadual de Campinas. Faculdade de Educação Física

A criança pre-escolar em Ilhabela : crescimento e atividade motora

Universidade Estadual de Campinas . Faculdade de Educação Física

Validação da Body Appreciation Scale (BAS), Life Satisfaction Index for the Third Age (LSITA) e do Aging Perception Questionnaire (APQ) para a língua portuguesa no Brasil : um estudo em idosos brasileiros

Universidade Estadual de Campinas . Faculdade de Educação Física

Tradução, adaptação transcultural e validação do "Body Image Avoidance Questionnaire (BIAQ)" e do "Body Checking Questionnaire (BCQ)" para lingua portuguesa no Brasil

Universidade Estadual de Campinas . Faculdade de Educação Física

Desenvolvimento da consciencia corporal : uma experiencia da Educação Fisica na idade pre-escolar

Universidade Estadual de Campinas . Faculdade de Educação Física

As expressões simbolicas nas atividades ludicas com crianças na pre-escola

Universidade Estadual de Campinas. Faculdade de Educação Física

Mudanças nas variaveis de aptidão fisica numa equipe de futebol da 1ª divisão do campeonato nacional durante uma pre-temporada

Universidade Estadual de Campinas . Faculdade de Educação Física