Vision in Futsal Players: Coordination and Reaction Time

Background: Coordination and reaction time are relevant aspects of a sport’s competitive performance within teams. The aim of this study was to explore if a group of futsal players, in a laboratory context, would present better results from actions where vision is prevalent compared to a control group without contact with futsal or any other sport. Methods: The digital system of the COI- SV software was used; six tests were selected, related to coordination (“Eye/hand coordination”; “Coordination and identification”) and reaction time (“Anticipation Time”; “Peripheral response”; “reaction time”; “Visual memory”). Results: Of all the tests performed, only in the anticipation time test did the futsal players obtain better results than the control group. The average time of the failures was lower in relation to the control group. In the others, no differences were found between the two groups. Conclusions: The futsal players did not perform better than the control group in most of the tests carried out, except in the “anticipation time”. Therefore, visual training maybe necessary to improve visual skills and sports performance.

Forecasting groundwater pumping cap in an overexploited Mediterranean aquifer using seasonal meteorological forecasts from Copernicus Climate Change Service

<p>The Requena-Utiel aquifer in the Jucar River Basin (Mediterranean Spain) is mined mainly for the irrigation of vineyards (Denominación de Origen Utiel-Requena), and some olive and nut trees. It has been recently declared as in bad quantitative status by the Jucar River Basin Agency (Confederación Hidrográfica del Júcar, CHJ). Among the measures taken to control water abstraction, a pumping cap for the irrigation season (May-September) has been agreed between the CHJ and the groundwater user association. This limit depends on the cumulative precipitation from December to April (classifying the year in wet, normal or dry), although that irrigation amount is in any case below the crop requirements. Consequently, predicting the type of year beforehand is a piece of valuable information for the water users in order to optimally schedule groundwater pumping and foresee crop production.</p><p>This study analyses the ability of seasonal meteorological forecasts from the Copernicus Climate Change Service (C3S) to anticipate the type of year in the agricultural areas of the Requena Utiel aquifer considering different periods ahead. The following seasonal forecasting services were used: ECMWF SEAS5, UKMO GloSEA5, MétéoFrance System, DWD GCFS, and CMCC SPS. Seasonal forecasts issued between November 1<sup>st</sup> and April 1<sup>st</sup> were downloaded and post-processed using a month-dependent linear scaling against historical records. Once post-processed, the skill of seasonal forecasts to predict the type of year has been evaluated for the 1995-2015 period, depending on the anticipation time.</p><p>Results show that, on a broader view, the type of year cannot be safely anticipated before April 1<sup>st</sup>. However, we have identified that, for particular types of year and forecasting services, the anticipation time can be enlarged (e.g predicting wet years in December). Furthermore, we have found a direct relationship between the strength of the signal (number of ensemble members that predict the same type of year) and the forecasting skill, meaning that seasonal forecasts showing a strong signal, if properly identified, could offer valuable information months in advance to the beginning of the irrigation season.</p><p><em>Acknowledgements:</em></p><p>This study has received funding from the eGROUNDWATER project (GA n. 1921), part of the PRIMA programme supported by the European Union’s Horizon 2020 research and innovation programme. It has been also supported by the ADAPTAMED project (RTI2018-101483-B-I00), funded by the Ministerio de Economia y Competitividad (MINECO) of Spain and with EU FEDER funds.</p>

Ionosonde and satellite data analysis in relation to the M5.9 April 6, 2009 L’Aquila (Italy) earthquake

<p>A combined ground-satellite study of the ionospheric response to the preparation phase of the M5.9 crustal earthquake occurred in L’Aquila (Italy) on April 6, 2009 is here presented. Ionospheric anomalies based on ionosonde observations of the altitude and blanketing frequency of the E-sporadic (Es) layer (<em>h</em>’Es and <em>f</em><sub>b</sub>Es, respectively) and of the critical frequency <em>f</em><sub>o</sub>F2 of the F2 layer are considered. For our analysis we make use of data from the Rome ionospheric observatory, located 90 km away from the earthquake epicentre, looking for anomalies up to a couple of months before the mainshock occurrence. Specifically, the variations for 2-3 hours of these parameters with respect to the past 27-day hourly running median are studied in relation to: (a) the ongoing geomagnetic activity during and several hours before the detection of the anomalies, as described by the values of the global a<sub>p</sub> and the auroral AE geomagnetic indices; (b) the earlier-obtained empirical relations for the seismic-ionospheric disturbances relating the earthquake magnitude with the epicentral distance and the anticipation time of the found anomalies. In addition, ionospheric anomalies in the electron density measured over the earthquake preparation region by the CHAllenging Minisatellite Payload (CHAMP) satellite at altitudes of about 320 km are studied in relation to the ionosonde-derived anomalies during the whole period preceding the mainshock occurrence.</p>

Predicting >10 MeV SEP Events from Solar Flare and Radio Burst Data

The prediction of solar energetic particle (SEP) events or solar radiation storms is one of the most important problems in the space weather field. These events may have adverse effects on technology infrastructures and humans in space; they may also irradiate passengers and flight crews in commercial aircraft flying at polar latitudes. This paper explores the use of ≥ M2 solar flares and radio burst observations as proxies for predicting >10 MeV SEP events on Earth. These observations are manifestations of the parent event at the sun associated with the SEP event. As a consequence of processing data at the beginning of the physical process that leads to the radiation storm, the model may provide its predictions with large anticipation. The main advantage of the present approach is that the model analyzes solar data that are updated every 30 min and, as such, it may be operational; however, a disadvantage is that those SEP events associated with strong well-connected flares cannot be predicted. For the period from November 1997 to February 2014, we obtained a probability of detection of 70.2%, a false alarm ratio of 40.2%, and an average anticipation time of 9 h 52 min. In this study, the prediction model was built using decision trees, an interpretable machine learning technique. This approach leads to outputs and results comparable to those derived by the Empirical model for Solar Proton Event Real Time Alert (ESPERTA) model. The obtained decision tree shows that the best criteria to differentiate pre-SEP scenarios and non-pre-SEP scenarios are the peak and integrated flux for soft X-ray flares and the radio type III bursts.

Precipitation Nowcasting using Deep Neural Network

<p>Precipitation nowcasting is the prediction of the future precipitation rate in a given geographical region with an anticipation time of a few hours at most. It is of great importance for weather forecast users, for activitites ranging from outdoor activities and sports competitions to airport traffic management. In contrast to long-term precipitation forecasts which are traditionally obtained from numerical weather prediction models, precipitation nowcasting needs to be very fast. It is therefore more challenging to obtain because of this time constraint. Recently, many machine learning based methods had been proposed. In this work, we develop an original deep learning approach. We formulate precipitation nowcasting issue as a video prediction problem where both input and prediction target are image sequences. The proposed model combines a Long Short-Term Memory network (LSTM) with a convolutional encoder-decoder network (U-net). Experiments show that our method captures spatiotemporal correlations and yields meaningful forecasts</p>

An extended continuum model with consideration of the self-anticipative effect

Drivers would adjust the speeds in response to not only the external environment, but also the anticipated traffic condition. In this paper, we propose a new continuum model considering the driver’s self-anticipative effect. Such effect is mainly reflected by the difference between the current speed and optimal speed within the anticipation time step. By applying the linear stability theory, the stability condition of the new model is obtained. Through the nonlinear analysis method, the KdV–Burgers equation of the model is provided. The solution describes the evolution of density waves near the neutral stability region. The simulation example verifies that the self-anticipative effect of the driver contributes to suppressing traffic congestion and reducing exhaust emissions effectively. We thus suggest that the traffic flow stability could be improved in an ad hoc manner.

Falling in Place: Geoscience, Disaster, and Cultural Heritage at the Frank Slide, Canada’s Deadliest Rockslide

Grounded in a case study of the Frank Slide, Canada’s Deadliest Rockslide, this article introduces a new perspective on disaster sites as socio-cultural entities by way of correlating the specific technicality of scientific research and management of disaster sites with a broader conceptual framework from within the social sciences and spatial theories. Heritage sites such as the Frank Slide are often understood as protected places that benefit the image of a sovereign nation (i.e., a “place-myth”). It is often assumed that heritage sites need protection from natural elements and from human interference. But the case of the Frank Slide is different, insofar as (a) it is a heritage site made out of the remnants of a terrifying disaster and (b) it is predicted to be further damaged when its ensuing rockslide follows (sometime between now and 5,000 years). This makes the case of the Frank Slide an intriguing one for an interdisciplinary study, since it is made up of various overlapping temporalities belonging to the measurement-time of scientific monitoring, commodity-time of the tourism industry, myth-time of national identity, duration-time of cultural memory, and the anticipation-time of further disaster. The analysis considers how these disparate activities contribute to the vitalization, devitalization, and revitalization of place, in such a way that challenges the “dark tourism” paradigm that has come to frame disaster sites. This article thus proposes a unique synthesis between these times and practices contained within them in order to elucidate and explore how various overlapping temporalities make up the visible and invisible materials of a place.

Predicting well-connected SEP events from observations of solar soft X-rays and near-relativistic electrons

This paper studies the use of electron data from the Electron Proton Alpha Monitor (EPAM) on board the Advanced Composition Explorer (ACE) in the UMASEP (University of Málaga Solar particle Event Predictor) scheme [Núñez, Space Weather 9 (2011) S07003; Núñez, Space Weather 13 (2015)] for predicting well-connected >10 MeV Solar Energetic Proton (SEP) events. In this study, the identification of magnetic connection to a solar particle source is done by correlating Geostationary Operational Environmental Satellites (GOES) Soft X-Ray (SXR) fluxes with ACE EPAM electrons fluxes with energies of 0.175–0.375 MeV. The forecasting performance of this model, called Well-Connected Prediction with electrons (WCP-electrons), was evaluated for a 16-year period from November 2001 to October 2017. This performance is compared with that of the component of current real-time tool UMASEP-10, called here WCP-protons model, which predicts the same type of events by correlating GOES SXR with differential proton fluxes with energies of 9–500 MeV. For the aforementioned period, the WCP-electrons model obtained a Probability of Detection (POD) of 50.0%, a False Alarm Ratio (FAR) of 39% and an Average Warning Time (AWT) of 1 h 44 min. The WCP-protons model obtained a POD of 78.0%, a FAR of 22% and an AWT of 1 h 3 min. These results show that the use of ACE EPAM electron data in the UMASEP scheme obtained a better anticipation time (additional 41 min on average) but a lower performance in terms of POD and FAR. We also analyzed the use of a combined model, composed of WCP-electrons and WCP-protons, working in parallel (i.e. the combined model issues a forecast when any of the individual models emits a forecast). The combined model obtained the best POD (84%), and a FAR and AWT (34.4% and 1 h 34 min, respectively) which is in between those of the individual models.

Perceptual and Motor Components at Young Football Players

The purpose of this study was to determine some perceptual and motor components level of young football players and to investigate the relationships between perceptual and motor components. Thirty-eight (38) selected football players from different division of Turkey whose mean age was 13.50±.42 years, height 150.00±5.60 cm and body weight 40.00±4.75 kg were tested as voluntarily in this study. This study was conducted in the Riva Orhan Saka Facility of the Turkish Football Federation. The findings indicated that statistically significant relations were observed between visual reaction time and anticipation time and also between sit-ups and sprint time, reaction time and agility times. On the other hands, there is no significant relation was found in other parameters.These findings may be useful for trainer and physical education teachers in the selection process and talent identification and preparing sport education programs.

Investigation of the Anticipation Time in Forehand and Backhand Strokes of Badminton Players

The purpose of this study was to examine if there was a difference between forehand and backhand coincidence-anticipation timing (CAT) performance of badminton players. Badminton players participating in the study are in the age range of 18-23 ( = 20.25, SS = 1.48) and 12 top athletes who regularly participated in Super League competitions in Turkey were selected (4 female and 8 male).Those athletes were determined by using the Purposive Sampling method. Participants were 12 elit badminton players (4 female and 8 male) whose ages ranged from 18 to 23 years ( = 20.25, SS = 1.48). CAT performances were measured with modified Bassin Anticipation Timer (BAT) device. Stimulus speed used for this study was set at 4 m / s. Participants were informed about the test protocol and they performed 3 trials with a racket to familiarize BAT device. Then, participants performed 20 trials for forehand and 20 trials for backhand strokes, 40 trials in total. Collected data were transformed to absolute error (AE) and variable error (VE) scores. Independent sample t-test was employed to calculate statistical data, and the significance level was set as 0.05. Results showed that there were significant differences between forehand and backhand strokes in terms of absolute and variable error scores of participants (p<0,05). As a conclusion, CAT performance of badminton players is effected during forehand and backhand strokes. CAT forehand stroke scores are better than the backhand stroke scores.