University of Minho

About: University of Minho is a education organization based out in Braga, Portugal. It is known for research contribution in the topics: Context (language use) & Population. The organization has 10585 authors who have published 34736 publications receiving 732436 citations. The organization is also known as: Universidade do Minho & UMinho.

Gellan gum-based hydrogels for intervertebral disc tissue-engineering applications.

Abstract: Intervertebral disc (IVD) degeneration is a challenging clinical problem that urgently demands viable nucleus pulposus (NP) implant materials. The best suited biomaterial for NP regeneration has yet to be identified, but it is believed that biodegradable hydrogel-based materials are promising candidates. In this work, we have developed ionic- and photo-crosslinked methacrylated gellan gum (GG-MA) hydrogels to be used in acellular and cellular tissue-engineering strategies for the regeneration of IVDs. The physicochemical properties of the developed hydrogels were investigated by Fourier-transform infrared spectroscopy, (1) H nuclear magnetic resonance and differential scanning calorimetry. The swelling ability and degradation rate of hydrogels were also analysed in phosphate-buffered saline solution at physiological pH for a period of 30 days. Additionally, the morphology and mechanical properties of the hydrogels were assessed under a scanning electron microscope and dynamic compression, respectively. An in vitro study was carried out to screen possible cytotoxicity of the gellan gum-based hydrogels by culturing rat lung fibroblasts (L929 cells) with hydrogel leachables up to 7 days. The results demonstrated that gellan gum was successfully methacrylated. We observed that the produced GG-MA hydrogels possess improved mechanical properties and lower water uptake ability and degradation rate as compared to gellan gum. This work also revealed that GG-MA hydrogels are non-cytotoxic in vitro, thus being promising biomaterials to be used in IVD tissue-engineering strategies.

Retinal vessel segmentation based on Fully Convolutional Neural Networks

Abstract: The retinal vascular condition is a reliable biomarker of several ophthalmologic and cardiovascular diseases, so automatic vessel segmentation may be crucial to diagnose and monitor them. In this paper, we propose a novel method that combines the multiscale analysis provided by the Stationary Wavelet Transform with a multiscale Fully Convolutional Neural Network to cope with the varying width and direction of the vessel structure in the retina. Our proposal uses rotation operations as the basis of a joint strategy for both data augmentation and prediction, which allows us to explore the information learned during training to refine the segmentation. The method was evaluated on three publicly available databases, achieving an average accuracy of 0.9576, 0.9694, and 0.9653, and average area under the ROC curve of 0.9821, 0.9905, and 0.9855 on the DRIVE, STARE, and CHASE_DB1 databases, respectively. It also appears to be robust to the training set and to the inter-rater variability, which shows its potential for real-world applications.

Social responsibility disclosure: A study of proxies for the public visibility of Portuguese banks

Abstract: This study, grounded in legitimacy theory (LT), examines social responsibility disclosure (SRD) on the Internet by Portuguese banks in 2004 and 2005. It compares these disclosures with those made in annual reports in 2003 and 2004. According to LT, companies with a higher public visibility are expected to exhibit greater concern to improve the corporate image through SRD. Size and industry affiliation are two of the most popular proxies for public visibility. By using companies from one industry this study explores size-related measures as proxies for public visibility. It analyses several size-related proxies and proposes a measure which has never been discussed in SRD studies: a spatial competition index based on the number of branches. Results suggest that the perspective adopted explains SRD by Portuguese banks and that the new measure proposed should be explored further in SRD empirical research.

Statistics of Spatial Cone-Excitation Ratios in Natural Scenes

Abstract: For some sets of surfaces, the spatial ratios of cone-photoreceptor excitations produced by light reflected from pairs of surfaces are almost invariant under illuminant changes. These sets include large populations of spectral reflectances, some of which represent individual natural surfaces but not their relative abundances in nature. The aim of this study was to determine whether spatial cone-excitation ratios are preserved under illuminant changes within the natural visual environment. A fast hyperspectral imaging system was used to obtain populations of 640,000 reflectance spectra from each of 30 natural scenes. The statistics of spatial cone-excitation ratios for randomly selected pairs of points in these scenes were determined for two extreme daylights. Almost-invariant ratios were common, suggesting that they represent a reliable property of the natural visual environment and a suitable foundation for visual color constancy.