Control of clock signals

Precision and reliability of timescales are of importance in many situations, in particular in satellite navigation systems (i.e., Galileo system). Motivated by the necessity to improve the precision and the reliability of such clock signals, we have explored the possibility to exploit control theory in clock steering methods. First of all we provide a more robust theoretical framework for the analysis of the process. Two novel control algorithms are here proposed aiming to meet metrological specifications. Numerical simulations have been performed in order to evaluate the performances of the new control systems.     

Clustering performances in the NBA according to players’ anthropometric attributes and playing experience

The aim of this study was: (i) to group basketball players into similar clusters based on a combination of anthropometric characteristics and playing experience; and (ii) explore the distribution of players (included starters and non-starters) from different levels of teams within the obtained clusters. The game-related statistics from 699 regular season balanced games were analyzed using a two-step cluster model and a discriminant analysis. The clustering process allowed identifying five different player profiles: Top height and weight (HW) with low experience, TopHW-LowE; Middle HW with middle experience, MiddleHW-MiddleE; Middle HW with top experience, MiddleHW-TopE; Low HW with low experience, LowHW-LowE; Low HW with middle experience, LowHW-MiddleE. Discriminant analysis showed that TopHW-LowE group was highlighted by two-point field goals made and missed, offensive and defensive rebounds, blocks, and personal fouls; whereas the LowHW-LowE group made fewest passes and touches. The players from weaker teams were mostly distributed in LowHW-LowE group, whereas players from stronger teams were mainly grouped in LowHW-MiddleE group; and players that participated in the finals were allocated in the MiddleHW-MiddleE group. These results provide alternative references for basketball staff concerning the process of evaluating performance.     

High-intensity endurance capacity assessment as a tool for talent identification in elite youth female soccer

ABSTRACT

Talent identification and development programmes have received broad attention in the last decades, yet evidence regarding the predictive utility of physical performance in female soccer players is limited. Using a retrospective design, we appraised the predictive value of performance-related measures in a sample of 228 youth female soccer players previously involved in residential Elite Performance Camps (age range: 12.7–15.3 years). With 10-m sprinting, 30-m sprinting, counter-movement jump height, and Yo-Yo Intermittent Recovery Test Level 1 (IR1) distance as primary predictor variables, the Akaike Information Criterion (AIC) assessed the relative quality of four penalised logistic regression models for determining future competitive international squads U17–U20 level selection. The model including Yo-Yo IR1 was the best for predicting career outcome. Predicted probabilities of future selection to the international squad increased with higher Yo-Yo IR1 distances, from 4.5% (95% confidence interval, 0.8 to 8.2%) for a distance lower than 440 m to 64.7% (95% confidence interval, 47.3 to 82.1%) for a score of 2040 m. The present study highlights the predictive utility of high-intensity endurance capacity for informing career progression in elite youth female soccer and provides reference values for staff involved in the talent development of elite youth female soccer players.     

Demand and innovation in services: The case of mobile communications

This paper aims to analyse the pricing strategies of mobile communications operators and examine the role of demand characteristics in the development of new tariff plans. In so doing, we depart from a traditional industrial organization approach to price discrimination and interpret new tariff plans as innovations. In the spirit of Schumpeter, we look at competition in this sector as depending upon this form of innovation, and we argue that, given the specific features of the industry, the development of new tariff plans is strongly related to the users’ characteristics and behaviour. Our main point is that in a context of uncertainty, demand affects firms’ innovative strategies in two ways: first, by providing information on user behaviour and by increasing the capability of market segmentation; and second, by providing the incentives to innovate. This argument is supported by an empirical analysis carried out on the basis of an original dataset which includes all the tariff plans on offer in the history of the Italian market between 1992 and 2005. We find that both a firm's installed customer base and the level of market saturation play a role in shaping firms’ innovative pricing strategies, in terms of the number and characteristics of the new tariff plans.     

Developmental Trajectories of Acculturation: Links With Family Functioning and Mental Health in Recent‐Immigrant Hispanic Adolescents

The present study was designed to examine acculturative changes, and their effects on mental health and family functioning, in recent‐immigrant Hispanic adolescents. A sample of 302 Hispanic adolescents was assessed five times over a 2½‐year period. Participants completed measures of Hispanic and U.S. practices, collectivist and individualist values, and ethnic and U.S. identity at each time point. Baseline and Time 5 levels of mental health and family functioning were also assessed. Latent class growth analyses produced two‐class solutions for practices, values, and identifications. Adolescents who increased over time in practices and values reported the most adaptive mental health and family functioning. Adolescents who did not change in any acculturation domain reported the least favorable mental health and family functioning.     

Long-term correlations in short,non-stationary time series: An application to international R&D collaborations

Within the perimeter of patent collaboration networks, the average distance of collaborations and the number of countries involved per each collaboration have been shown to have increased steadily in time. Less attention, though, has been devoted to assessing whether this growth of cross-country collaborations is stable in time. To address this scientific question we focus on the identification of long-term correlations (i.e. temporal persistence). Our data set consists of time series of yearly average collaboration radii and of cross-border links in the Euro-American subsystem of the global collaboration network for the period 1978–2014. To investigate the fundamental persistence properties of these time series, we use Detrended Fluctuation Analysis, a method that allows us to measure long-term correlations in detrended signals. Also, we devise a general and original procedure to assess the statistical significance of results for short time series. Our results, showing that long-term correlations do exist in the majority of our signals, reinforce the hypothesis of a diminishing role of geographical distance in technological collaborations. Results at national level show that a significant degree of heterogeneity in persistence parameters can be detected within Europe, irrespectively of the efforts towards the set-up of an integrated European Research Area.