Abstract
This study presents and applies a quantitative metric, based on entire time series of measured surface electromyography (sEMG) from selected lower limb muscles to validate multibody dynamics (MBD) estimated action of the same subject muscles during modified gait, stiff knee gait (SKG) and slow running (SR) in relation to normal gait (NG). MBD is being increasingly applied for estimation of internal actions according to difficulty of its direct measurements under natural conditions of movement and the importance of this estimation for prevention, diagnosis and treatment planning of specific subject skeletal and neuromuscular diseases. Inverse kinematics and inverse dynamics from position and force data have been used to estimate internal joint force moments, with muscle grouping and optimization techniques applied along with musculoskeletal model for estimation of muscle action. Nevertheless kinematic and kinetic input data of human movement must be accurate and employed model for simulation must be personalized to subject, task and moment of application. Also the results provided by the simulation with the musculoskeletal model must be compared with measured results for validation. Comparative analysis of kinematic and kinetic input data of human lower limbs is performed during modified gait modes and a personalized musculoskeletal model employed for MBD estimation of muscle actions and compare estimated muscle actions with measured sEMG of selected muscles on different gait modes, SKG and SR in relation to those registered at NG. The results from quantitative metrics followed qualitative agreement from visual inspection with better agreement between processed sEMG and MBD muscle estimated activity on phase metric than at magnitude, and combined metric presenting overall better agreement at NG and SKG than at SR, pointing to higher ability of the model to predict muscle force patterns in agreement with measured sEMG activity at NG and SKG than at SR and the need to improve model predictions for SR. Applied technique presents as a reproducible quantitative metric based on entire time series, both magnitude and phase, overcoming qualitative and subjective comparing by the observer, reducing time consuming and allowing increase at the number of automatic validation of MBD muscle action estimation.

Abstract
Public transport networks were, in the past, mainly designed to maximize the efficiency of commuting trips. However, with such perspective there are considerable risks to marginalize some specific population groups (e.g. disabled, elderly, children, pregnant, people in poverty). For enhancing social inclusion and improving the accessibility of more vulnerable citizens, such networks are often redesigned and adjusted. Nevertheless, even with such adjustments, it is sometimes difficult to provide efficient services that fully address the real needs and capabilities of travelers, partially because of the failure in following the fast technological and demanding changes of modern societies. Taking in mind these challenges, we have developed a conceptual model to support knowledge sharing and decision-making in urban mobility, and to improve the way travel information is addressed. The multi-user integrated platform proposed in this work is supported by the idea that information from different channels must be centralized, organized, managed and properly distributed. This idea is grounded in two main principles: (i) past and real-time information from a wide range of sources is combined for knowledge extraction, and such knowledge is going to be used not only to allow travelers to better plan their trips, but also to help transport providers to develop services adapted to the needs and preferences of their customers; and (ii) information is provided in a personalized way taking into account socio-economical differences between groups of travelers. (C) 2017 The Authors. Published by Elsevier B.V.

Abstract
This work aims to understand, formalize and explore the scientific challenges of using unstructured text data from different Web sources for Online Reputation Monitoring. We here present TexRep, an adaptable text mining framework specifically tailored for Online Reputation Monitoring that can be reused in multiple application scenarios, from politics to finance. This framework is able to collect texts from online media, such as Twitter, and identify entities of interest and classify sentiment polarity and intensity. The framework supports multiple data aggregation methods, as well as visualization and modeling techniques that can be used for both descriptive analytics, such as analyze how political polls evolve over time, and predictive analytics, such as predict elections. We here present case studies that illustrate and validate TexRep for Online Reputation Monitoring. In particular, we provide an evaluation of TexRep Entity Filtering and Sentiment Analysis modules using well known external benchmarks. We also present an illustrative example of TexRep application in the political domain.

Abstract
This paper presents a solar power forecasting scheme, which uses spatial and temporal time series data along with a photovoltaic (PV) power conversion model. The PV conversion model uses the forecast of three different variables, namely, irradiance on the tilted plane, ambient temperature, and wind speed, in order to estimate the power produced by a PV plant at the grid connection terminals. The forecast values are obtained using a spatio-temporal method that uses the data recorded from a target meteorological station as well as data of its surrounding stations. The proposed forecasting method exploits the sparsity of correlations between time series data in a collection of stations. The performance of both the PV conversion model and the spatio-temporal algorithm is evaluated using high-resolution real data recorded in various locations in Italy. Comparison with other benchmark methods illustrates that the proposed method significantly improves the solar power forecasts, particularly over short-term horizons.

Abstract
IntroductionBreast cosmesis is an important endpoint of breast conserving therapy (BCT), but a gold standard method of its evaluation is not yet established. The St. George and Wollongong Randomised Breast Boost trial used five different methods of cosmetic assessment, including both subjective and objective, to comprehensively evaluate the cosmetic outcome of the trial patients. This current study analyses the level of concordance between these methods in an attempt to determine a possible standard in the evaluation of breast cosmesis. MethodsPatients attending follow-up clinic reviews at 5years post breast radiotherapy were evaluated. Patients completed a cosmesis and functional assessment questionnaire, assessing clinicians completed an EORTC (European Organization for Research and Treatment of Cancer) cosmetic rating questionnaire and photographs were obtained. The photographs were later assessed by a panel of five experts, as well as analysed using the objective pBRA (relative Breast Retraction Assessment) and the BCCT.core (Breast Cancer Conservative Treatment.cosmetic results) computer software. Scores were dichotomised to excellent/good and fair/poor. Pairwise comparisons between all methods, except pBRA, were carried out using overall agreement calculations and kappa scores. pBRA scores were compared on a continuous scale with each of the other dichotomised scores obtained by the other four methods. ResultsOf 513 St George patients alive at 5years, 385 (75%) attended St George for follow-up and consented to photography. Results showed that assessment by physicians in clinic and patient self-assessment were more favourable regarding overall cosmetic outcome than evaluation of photographs by the panel or the BCCT.core software. Excellent/good scores by clinician-live and patient self-assessments were 93% and 94% respectively (agreement 89%), as compared to 75% and 74% only by BCCT.core and panel assessments respectively (agreement 83%, kappa 0.57). For the pBRA measurements, there was a statistically significant difference (P <0.001) between scores for excellent/good versus fair/poor cosmesis by all four methods. The range of median pBRA measurements for fair/poor scores was 13.4-14.8 and for excellent/good scores was 8.0-9.4. ConclusionIncorporating both BCCT.core assessment and patient self-assessment could potentially provide the basis of a gold standard method of breast cosmetic evaluation. BCCT.core represents an easy, time efficient, reproducible, cost effective and reliable method, however, it lacks the functional and psychosocial elements of cosmesis that only patient self-reported outcomes can provide.

Abstract
This article addresses the developments ongoing in SENSIBLE, an H2020 funded project focused on energy storage and energy management, which demonstration occurs in Évora-Portugal, Nottingham, UK and Nuremberg, Germany. Currently, the presented work focuses on the developments necessary to make possible islanding operation in low-voltage grids, where new assets like storage and new automation and protection schemes are necessary to guaranty safety and reliability of low-voltage grids. These developments are a result of the ongoing works under one of SENSIBLE use cases which demonstrations occurs in a small village in Évora district in Portugal.