We present here a method for analyzing the neighborhoods of all the vertices in a large graph. We first give an algorithm for characterizing a simple undirected graph that relies on enumeration of small induced subgraphs. We make a step further in this direction by identifying not only subgraphs but also the positions occupied by the different vertices of the graph. We are thus able to compute the roles played by the vertices of the graph, roles found according to a new definition that we introduce. We apply this method to the neighborhood of each vertex in a 2.7M vertices, 6M edges mobile phone graph. We analyze how the contacts of each person are connected to each other and the positions they occupy in the neighborhood network. Then we compare their quantity of communication (duration and frequency) to their positions, finding that the two are not independent. We finally interpret and explain the results using social studies on phone communications. 1

This study investigates travel behavior and psychosocial factors that influence it during the COVID-19 pandemic. In a cross-sectional study, using an online survey, we examined changes in travel behavior and preferences after lifting travel restrictions, and how these changes were influenced by exposure to COVID-19, COVID-19 travel-related risk and severity, personality, fear of travel, coping, and self-efficacy appraisals in the Romanian population. Our results showed that participants traveled less in the pandemic year than the year before—especially group and foreign travel—yet more participants reported individual traveling in their home county during the pandemic period. Distinct types of exposure to COVID-19 risk, as well as cognitive and affective factors, were related to travel behavior and preferences. However, fun-seeking personality was the only major predictor of travel intention, while fear of travel was the only predictor of travel avoidance. Instead, people traveled more cautiously when they perceived more risk of infection at the destination, and had higher levels of fear of travel, but also a high sense of efficacy in controlling the infection and problem-solving capacity. The results suggest that specific information about COVID-19, coping mechanisms, fear of travel, and neuropsychological personality traits may affect travel behavior in the pandemic period.

The aim of the study was to determine the effects of proprioceptive training (PT) on balance, strength, agility and dribbling in adolescent soccer players. In this research, we included an experimental (n = 48) and a control (n = 48) group (CG) with 14 years old players. The experimental group (EG) participated in an 8 week PT program, with four 30 minute sessions per week. The experimental program included 12 bosu ball exercises to improve balance, stability and strength which were grouped into two subprograms: the first not using the soccer ball, the second subprogram using the soccer ball. The subprograms were implemented alternately during 16 proprioceptive training sessions, on two types of firm and foam surfaces. Pre- and post-tests included the static balance [Balance Error Scoring System (BESS)], vertical, horizontal, and lateral jumping, and the completion of agility (“arrowhead”) and dribbling (“short dribbling”) tests. Regarding the total BESS score, the CG has demonstrated progress between the pre- and the post-test, with 0.780 ± 0.895, fewer errors, while the EG had 5.828 ± 1.017 fewer errors. The difference between the two groups was of 5.148 fewer errors for the EG who had practiced the proposed program of proprioceptive training. The highest difference registered between the pre- and the post-test was at the test “single-leg forward jump with the right leg”, with a result of 1.083 ± 0.459 cm for the CG and of 3.916 ± 0. 761 cm for the EG. Through the analysis of average differences between the pre- and the post-tests, we observe that, regarding the “Agility right side test”, the EG has progressed with 0.382 s in comparison with the CG; regarding the “Agility left side test”, the EG has progressed with 0.233 s compared to the CG; regarding the “Agility right and left side test”, the EG has progressed with 0.196 s compared to the CG; in the “Short dribbling test”, the EG has progressed with 0.174 s compared to the CG. The highest progress was made at the “Agility right side test”, of 0.402 s for the EG, while the CG registered 0.120 s. Most of the results in all tests for both experimental groups show an effect size ranging from small to medium. The progress made by the experimental group in all tests was statistically significant, while in the control group the progress was mostly statistically insignificant for p < 0.05. The results suggest that a PT program performed at about 14 years of age could be successfully implemented in the training regime of soccer players to improve components of fitness along with dribbling skills. The results of the study revealed that sports training on the foam surfaces determined a superior progress of the development of proprioception compared to the increased training on the firm surfaces.

International audienceHere we propose a set of dynamical measures to detect causality effects on communication datasets. Using appropriate comparison models, we are able to enumerate patterns containing causality relationships. This approach is illustrated on a large cellphone call dataset: we show that specific patterns such as short chain-like trees and directed loops are more frequent in real networks than in comparison models at short time scales. We argue that these patterns - which involve a node and its close neighborhood - constitute indirect evidence of active spreading of information only at a local level. This suggests that mobile phone networks are used almost exclusively to communicate information to a closed group of individuals. Furthermore, our study reveals that the bursty activity of the callers promotes larger patterns at small time scales

Snow avalanches are one of the most devastating natural hazards in the highlands that often cause human casualties and economic losses. The complex process of modeling terrain susceptibility requires the application of modern methods and software. The prediction of avalanches in this study is based on the use of geographic information systems (GIS), remote sensing, and multicriteria analysis—analytic hierarchy process (AHP) on the territory of the Šar Mountains (Serbia). Five indicators (lithological, geomorphological, hydrological, vegetation, and climatic) were processed, where 14 criteria were analyzed. The results showed that approximately 20% of the investigated area is highly susceptible to avalanches and that 24% of the area has a medium susceptibility. Based on the results, settlements where avalanche protection measures should be applied have been singled out. The obtained data can will help local self-governments, emergency management services, and mountaineering services to mitigate human and material losses from the snow avalanches. This is the first research in the Republic of Serbia that deals with GIS-AHP spatial modeling of snow avalanches, and methodology and criteria used in this study can be tested in other high mountainous regions.