Thermal skin reference values in healthy late pregnancy

Digital thermal imaging has been employed in medicine for over 50 years. However, its use has been focused on vascular, musculoskeletal and neurological conditions, while other potential applications,such as obstetrics, have been much less explored. This paper presents a study conducted during 2011 at the Hospital of Braga on a group of healthy pregnant women in the last third of gestation. The analysis focused on characterizing typical pregnant women steady temperature profiles in specific defined regions of interest (ROI), and determining if the thermal symmetry values for late pregnant healthy women are in line with the values for non-pregnant healthy women. A temperature distribution pattern was found in the defined ROI. The obtained thermal symmetry value had a maximum of 0.370.2 1C, and there was no evidence for the influence of age (p40.05) in the observed group. The influence of the BMI requires further investigation since one ROI (P2 right) presented a p¼0.059, close to the threshold of statistical evidence in the influence of BMI. The study group presented symmetry values in line with non-pregnant reference values, but the profiles in temperature distribution are different. Assumptions can therefore now be used with higher confidence when assessing abnormalities in specific pathologic states during pregnancy using the defined ROI. This work represents a first contribution towards establishing guidelines for future research in this specific field of study.

Travel preferences of the residents of Guimarães: a revised model of push and pull motives

The historic center of the Portuguese city of Guimarães is a world heritage site (UNESCO) since 2001, having hosted the European Capital of Culture (ECOC) in 2012. In this sense, Guimarães has made a major effort in promoting tourism, positioning itself as an urban and cultural tourism destination. The present paper has two objectives. The first, to examine if an existing push and pull motivation model finds statistical support with regard to the population of the municipality of Guimarães, a cultural tourism destination. The second, to study the role that important socio-demographic variables, such as gender, age, and education, play in determining travel motivations of residents from this municipality. Insight on tourism motivation may be an important policy tool for tourism planners and managers in the development of products and marketing strategies. The empirical analysis is undertaken based on questionnaires administered in 2012 to residents of Guimarães. The present study shows that gender, age and education make a difference with regard to travel motivations.

Variations of the soft tissue thicknesses external to the ribs in Pectus Excavatum patients

Background: Surgical repair of pectus excavatum (PE) has become more popular due to improvements in the minimally invasive Nuss procedure. The pre-surgical assessment of PE patients requires Computerized Tomography (CT), as the malformation characteristics vary from patient to patient. Objective: This work aims to characterize soft tissue thickness (STT) external to the ribs among PE patients. It also presents a comparative analysis between the anterior chest wall surface before and after surgical correction. Methods: Through surrounding tissue segmentation in CT data, STT values were calculated at different lines along the thoracic wall, with a reference point in the intersection of coronal and median planes. The comparative analysis between the two 3D anterior chest surfaces sets a surgical correction influence area (SCIA) and a volume of interest (VOI) based on image processing algorithms, 3D surface algorithms, and registration methods. Results: There are always variations between left and right side STTs (2.54±2.05 mm and 2.95±2.97 mm for female and male patients, respectively). STTs are dependent on age, sex, and body mass index of each patient. On female patients, breast tissue induces additional errors in bar manual

Predicting the mechanical behavior of amorphous polymeric materials under strain through multi-scale simulation

Polymeric materials have become the reference material for high reliability and performance applications. However, their performance in service conditions is difficult to predict, due in large part to their inherent complex morphology, which leads to non-linear and anisotropic behavior, highly dependent on the thermomechanical environment under which it is processed. In this work, a multiscale approach is proposed to investigate the mechanical properties of polymeric-based material under strain. To achieve a better understanding of phenomena occurring at the smaller scales, the coupling of a finite element method (FEM) and molecular dynamics (MD) modeling, in an iterative procedure, was employed, enabling the prediction of the macroscopic constitutive response. As the mechanical response can be related to the local microstructure, which in turn depends on the nano-scale structure, this multiscale approach computes the stress-strain relationship at every analysis point of the macro-structure by detailed modeling of the underlying micro- and meso-scale deformation phenomena. The proposed multiscale approach can enable prediction of properties at the macroscale while taking into consideration phenomena that occur at the mesoscale, thus offering an increased potential accuracy compared to traditional methods.

Variations of the soft tissue thicknesses external to the ribs in pectus excavatum patients

Background: Surgical repair of pectus excavatum (PE) has become more popular due to improvements in the minimally invasive Nuss procedure. The pre-surgical assessment of PE patients requires Computerized Tomography (CT), as the malformation characteristics vary from patient to patient. Objective: This work aims to characterize soft tissue thickness (STT) external to the ribs among PE patients. It also presents a comparative analysis between the anterior chest wall surface before and after surgical correction. Methods: Through surrounding tissue segmentation in CT data, STT values were calculated at different lines along the thoracic wall, with a reference point in the intersection of coronal and median planes. The comparative analysis between the two 3D anterior chest surfaces sets a surgical correction influence area (SCIA) and a volume of interest (VOI) based on image processing algorithms, 3D surface algorithms, and registration methods. Results: There are always variations between left and right side STTs (2.54±2.05 mm and 2.95±2.97 mm for female and male patients, respectively). STTs are dependent on age, sex, and body mass index of each patient. On female patients, breast tissue induces additional errors in bar manual

Computer-aided recognition of dental implants in X-ray images

Dental implant recognition in patients without available records is a time-consuming and not straightforward task. The traditional method is a complete user-dependent process, where the expert compares a 2D X-ray image of the dental implant with a generic database. Due to the high number of implants available and the similarity between them, automatic/semi-automatic frameworks to aide implant model detection are essential. In this study, a novel computer-aided framework for dental implant recognition is suggested. The proposed method relies on image processing concepts, namely: (i) a segmentation strategy for semi-automatic implant delineation; and (ii) a machine learning approach for implant model recognition. Although the segmentation technique is the main focus of the current study, preliminary details of the machine learning approach are also reported. Two different scenarios are used to validate the framework: (1) comparison of the semi-automatic contours against implant’s manual contours of 125 X-ray images; and (2) classification of 11 known implants using a large reference database of 601 implants. Regarding experiment 1, 0.97±0.01, 2.24±0.85 pixels and 11.12±6 pixels of dice metric, mean absolute distance and Hausdorff distance were obtained, respectively. In experiment 2, 91% of the implants were successfully recognized while reducing the reference database to 5% of its original size. Overall, the segmentation technique achieved accurate implant contours. Although the preliminary classification results prove the concept of the current work, more features and an extended database should be used in a future work.