Euphorbia paniculata Desf. subsp. paniculata en el sureste ibérico

Euphorbia paniculata Desf. subsp. paniculata in SE SpainPalabras clave. Euphorbia, Corología, Murcia, Almeria, España.Keywords. Euphorbia, Chorology, Murcia, Almeria, Spain

Exploiting Deep Neural Networks for Intention Mining

© 2020 ACM. In the current era of digital media, people are greatly interested to express themselves on online interaction which produces a huge amount of data. The user generated content may contain user\u27s emotions, opinions, daily events and specially their intent or motive behind their communication. Intention identification/mining of user\u27s reviews, that is whether a user review contains intent or not, from social media network, is an emerging area and is in great demand in various fields like online advertising, improving customer services and decision making. Until now, a lot of work has been performed by researchers on user intention identification using machine learning approaches. However, it is demanded to focus on deep neural network methods. In this research work, we have conducted experimentation on intention dataset using a deep learning method namely CNN+BILSTM. The results exhibit that the proposed model efficiently performed identification of intention sentences in user generated text with a 90% accuracy

Cross-country migration linked to people who inject drugs challenges the long-term impact of national HCV elimination programmes

To the Editor: As of 2018, the majority of Western European countries – including Spain – have lifted restrictions to therapy based on disease severity in the context of HCV infections.1 Long overdue, most national elimination programmes now also include access to care for people who inject drugs (PWID), 2 who are at the core of ongoing HCV transmission.3 Macías et al.4 have recently shown in this Journal that high viral cure rates can be achieved in this group, hereby providing evidence that targeting PWID in treatment programmes is worthwhile. However, the extent to which such national efforts can reduce the HCV burden not only depends on the uptake into care and treatment success rates, it is also determined by the relative importance of within-country transmission and virus importation from elsewhere. As the chronic nature of most HCV infections hampers reliably reconstructing contact networks from patient interviews, virus genetic data can be a valuable alternative source of information for elucidating the geographic history of virus lineages (e.g. [5], [6]). Using such data, we have recently shown that for the most prevalent subtype among PWID in Spain (40%, 7), HCV1a, infections often link to infections abroad – in recent years >50% link to Western European countries, mostly European Union (EU) member states – as opposed to other infections ..

Epidemiology of injuries in professional football: A systematic review and meta-analysis

Objective: We performed a systematic review and meta-analysis of epidemiological data of injuries in professional male football. Method: Forty-four studies have reported the incidence of injuries in football. Two reviewers independently extracted data and assessed trial quality using the STROBE statement and Newcastle Ottawa Scale. Studies were combined in a pooled analysis using a Poisson random effects regression model. Results: The overall incidence of injuries in professional male football players was 8.1 injuries/1000 hours of exposure. Match injury incidence (36 injuries/1000 hours of exposure was almost ten times higher than training injury incidence rate (3.7 injuries/1000 hours of exposure). Lower extremity injuries had the highest incidence rates (6.8 injuries/1000 hours of exposure). The most common type of injury was muscle/tendon (4.6 injuries/1000 hours of exposure), which were frequently associated with traumatic incidents. Minor injuries (1-3 days of time loss) were the most common. The incidence rate of injuries in the top 5 European professional leagues was not different to that of the professional leagues in other countries (6.8 vs. 7.6 injuries/1000 hours of exposure, respectively). Conclusions: Professional male football players have a substantial risk of sustaining injuries, especially during matches

A Bayesian Network approach to study the relationships between several neuromuscular performance measures and dynamic postural control in futsal players

Purpose: The purpose of this study was to analyse the relationship between several parameters of neuromuscular performance with dynamic postural control using a Bayesian Network Classifiers (BN) based analysis. Methods: The y-balance test (measure of dynamic postural control), isokinetic (concentric and eccentric) knee flexion and extension strength, isometric hip abduction and adduction strength, lower extremity joint range of motion (ROM) and core stability were assessed in 44 elite male futsal players. A feature selection process was carried out before building a BN (using the Tabu search algorithm) for each leg. The BN models built were used to make belief updating processes to study the individual and concurrent contributions of the selected parameters of neuromuscular performance on dynamic postural control. Results: The BNs generated using the selected features by the algorithms correlation attribute evaluator and chi squared reported the highest evaluation criteria (area under the receiver operating characteristic curve [AUC]) for the dominant (AUC = 0.899) and non-dominant (AUC = 0.879) legs, respectively. Conclusions: The BNs demonstrated that performance achieved in the y-balance test appears to be widely influenced by hip and knee flexion and ankle dorsiflexion ROM measures in the sagittal plane, as well as by measures of static but mainly dynamic core stability in the frontal plane. Therefore, training interventions aimed at improving or maintaining dynamic postural control in elite male futsal players should include, among other things, exercises that produce ROM scores equal or higher than 127º of hip flexion, 132.5º of knee flexion as well as 34º and 30.5º of ankle dorsiflexion with the knee flexed and extended, respectively. Likewise, these training interventions should also include exercises to maintain or improve both the static and dynamic (medial-lateral plane) core stability so that futsal players can achieve medial radial error values lower than 6.69 and 8.79 mm, respectively

Comprehensive profile of hip, knee and ankle ranges of motion in professional football players

BACKGROUND: Limited ranges of motion (ROM) has been considered as a primary risk factor for some football injuries, but only a few studies have analysed differences in lower extremity joints. The main purposes were (a) to describe the lower extremity ROM profile in professional football players; and (b) to examine differences between goalkeepers and outfield players. METHODS: 82 professional male football players from 4 teams were measured in the 2013 pre-season. Measures of passive hip (flexion with knee flexed [PHFKF] and extended [PHFKE], extension [PHE], abduction [PHA], external [PHER] and internal [PHIR] rotation), knee (flexion [PKF]) and ankle (dorsiflexion with knee flexed [ADFKF] and extended [ADFKE]) ROMs were taken. Magnitude-based inferences exploring differences between player position and limb were made. RESULTS: 46% of all participants showed restricted PHFKE and/or around 30% showed restricted ADFKF ROM values. Contrarily, most players reported normal PHFKF, PHE, PHIR and PHER as well as PKF ROM scores with percentage values close to 100%. Bilateral meaningful differences for PHA, PHIR and PHER were found in approximately 30% of outfield players and goalkeepers. Statistical analysis found trivial differences between players for PHFKE, PHE, PHIR, PHER, ADFKE and ADFKF. However, moderate differences between players were found for PHFKF, PHA and PKF, with goalkeepers demonstrating higher values than outfield players. CONCLUSIONS: The findings of this study reinforce the necessity of prescribing exercises aimed at improving PHFKE and ADFKF ROM within everyday football training routines. In addition, as some bilateral deficits were observed, unilateral training should be considered where appropriate

A preventive model for muscle injuries: a novel approach based on learning algorithms

Introduction: The application of contemporary statistical approaches coming from Machine Learning and Data Mining environments to build more robust predictive models to identify athletes at high risk of injury might support injury prevention strategies of the future. Purpose: The purpose was to analyse and compare the behaviour of numerous machine learning methods in order to select the best performing injury risk factor model to identify athlete at risk of lower extremity muscle injuries (MUSINJ). Study Design: Prospective Cohort study. Methods: A total of 132 male professional soccer and handball players underwent a pre-season screening evaluation which included personal, psychological and neuromuscular measures. Furthermore, injury surveillance was employed to capture all the MUSINJ occurring in the 2013/2014 seasons. The predictive ability of several models built by applying a range of learning techniques were analysed and compared. Results: There were 32 MUSINJ over the follow up period, 21 (65.6%) of which corresponded to the hamstrings, three to the quadriceps (9.3%), four to the adductors (12.5%) and four to the triceps surae (12.5%). A total of 13 injures occurred during training and 19 during competition. Three players were injured twice during the observation period so the first injury was used leaving 29 MUSINJ that were used to develop the predictive models. The model generated by the SmooteBoost technique with a cost-sensitive ADTree as the base classifier reported the best evaluation criteria (area under the receiver operating characteristic curve score = 0.747, true positive rate = 65.9%, true negative rate = 79.1) and hence was considered the best for predicting MUSINJ. Conclusions: The prediction model showed moderate accuracy for identifying professional soccer and handball players at risk of MUSINJ. Therefore, the model developed might help in the decision-making process for injury prevention