Abstract
Background and purpose We evaluated two methods to identify mesial temporal sclerosis (MTS): visual inspection by experienced epilepsy neuroradiologists based on structural magnetic resonance imaging sequences and automated hippocampal volumetry provided by a processing pipeline based on the FMRIB Software Library. Methods This retrospective study included patients from the epilepsy monitoring unit database of our institution. All patients underwent brain magnetic resonance imaging in 1.5T and 3T scanners with protocols that included thin coronal T2, T1 and fluid-attenuated inversion recovery and isometric T1 acquisitions. Two neuroradiologists with experience in epilepsy and blinded to clinical data evaluated magnetic resonance images for the diagnosis of MTS. The diagnosis of MTS based on an automated method included the calculation of a volumetric asymmetry index between the two hippocampi of each patient and a threshold value to define the presence of MTS obtained through statistical tests (receiver operating characteristics curve). Hippocampi were segmented for volumetric quantification using the FIRST tool and fslstats from the FMRIB Software Library. Results The final cohort included 19 patients with unilateral MTS (14 left side): 14 women and a mean age of 43.4 ± 10.4 years. Neuroradiologists had a sensitivity of 100% and specificity of 73.3% to detect MTS (gold standard, k = 0.755). Automated hippocampal volumetry had a sensitivity of 84.2% and specificity of 86.7% (k = 0.704). Combined, these methods had a sensitivity of 84.2% and a specificity of 100% (k = 0.825). Conclusions Automated volumetry of the hippocampus could play an important role in temporal lobe epilepsy evaluation, namely on confirmation of unilateral MTS diagnosis in patients with radiological suggestive findings. © SAGE Publications.

Abstract
Online recommender systems often deal with continuous, potentially fast and unbounded flows of data. Ensemble methods for recommender systems have been used in the past in batch algorithms, however they have never been studied with incremental algorithms that learn from data streams. We evaluate online bagging with an incremental matrix factorization algorithm for top-N recommendation with positiveonly user feedback, often known as binary ratings. Our results show that online bagging is able to improve accuracy up to 35% over the baseline, with small computational overhead.

Abstract
Social entrepreneurship is emerging as an innovative approach for dealing with complex social and environmental needs, and is an important lever for the development of a sustainable society. Social entrepreneurship and related concepts have had a growing attention in the academy, giving rise to dissimilar approaches in the United States of America and in Western Europe. Despite the importance of the Third Sector in Portugal, it has been difficult to set ideal definitions for social entrepreneurship, social entrepreneur and social enterprises. By means of a qualitative study involving four Portuguese social ventures, this chapter identifies contemporary socio-cultural and economic factors that foster social innovation and intervention in Portugal, and contributes to understand the role of social entrepreneur in this context.

Abstract
The Multi-Layer Stream Mapping (MSM) methodology addresses current challenges regarding the applicability of Lean Thinking concepts in the domain of sustainability assessment tools. Therefore, MSM aims to assess the overall performance of a production system, while evaluating the productivity and efficiency of resource utilization as well as evaluate the costs related to missuses and inefficiencies and other process and domains variables. This paper highlights the benefits arising from the application of the MSM methodology in a real industrial case regarding the injection moulding process, namely fostering the quantification of the efficiency of different resources streams, for its improvement, for the several production processes involved. So, it is explained how MSM can contribute for a more sustainable production system with a continuously increasing productivity.

Abstract
Discount and Outlet E-commerce Platforms (DOEP) are technologies with more and more influence in people's lives, and the literature on this subject is still somewhat scarce in relation to the proportion these platforms have today, in the context of e-commerce. In this study, the research team aims to characterize the variables that have the greatest relative importance in DOEP adoption, with the use of 25 experts related to IT and e-commerce in general. For this, a succinct literature analysis is done, in order to aggregate all the constructs that may influence the adoption of this technology. The contribution is distributed in the form of practical and theoretical implications, as well as future lines of action for possible investigations.

Abstract
Several methods have been proposed for performing schedulability analysis for both uni-processor and multi-processor real-time systems. Very few of these works use the power of formal logic to write unambiguous specifications and to allow the usage of theorem provers for building the proofs of interest with greater correctness guarantees. In this paper we address this challenge by: 1) defining a formal language that allows to specify periodic resource models; 2) describe a transformational approach to reasoning about timing properties of resource models by transforming the latter specifications into a satisfiability modulo theories problem.