Performance analysis tool for network analysis on team sports: a case study of FIFA Soccer World Cup 2014

The study of teammates’ interaction on team sports has been growing in the last few years. Nevertheless, no specific software has been developed so far to do this in a user-friendly manner. Therefore, the aim of this study was to introduce a software called the Performance Analysis Tool that allows the user to quickly record the teammates’ interaction and automatically generate the outputs in adjacency matrices that can then be imported by social network analysis software such as SocNetV. Moreover, it was also the aim of this study to process the data in a real-life scenario, thus the seven matches of the German national soccer team in the FIFA World Cup 2014 were used to test the software and then compute the network metrics. A dataset of 3032 passes between teammates in seven soccer matches was generated with the Performance Analysis Tool software, which permitted a study of the network structure. The analysis of variance of centrality metrics between different tactical positions was made. The two-way multivariate analysis of variance revealed that the strategic position (γ=1.305 ; F = 24.394; p = 0.001; η2p=0.652 ; large effect size) had significant main effects on the centrality measures. No statistical differences were found in the phase of competition (γ=0.003 ; F = 0.097; p = 0.907; η2p=0.003 ; very small effect size). The network approach revealed that the German national soccer team based their attacking process on positional attacks and not in counter-attack, and the midfielders were the prominent players followed by the central defenders. The Performance Analysis Tool software allowed the user to quickly identify the teammates’ interactions and extract the network data for process and analysis.info:eu-repo/semantics/publishedVersio

The Hellenic type of nondeletional hereditary persistence of fetal hemoglobin results from a novel mutation (g.-109G>T) in the HBG2 gene promoter

Nondeletional hereditary persistence of fetal hemoglobin (nd-HPFH), a rare hereditary condition resulting in elevated levels of fetal hemoglobin (Hb F) in adults, is associated with promoter mutations in the human fetal globin (HBG1 and HBG2) genes. In this paper, we report a novel type of nd-HPFH due to a HBG2 gene promoter mutation (HBG2:g.-109G>T). This mutation, located at the 3′ end of the HBG2 distal CCAAT box, was initially identified in an adult female subject of Central Greek origin and results in elevated Hb F levels (4.1%) and significantly increased Gγ-globin chain production (79.2%). Family studies and DNA analysis revealed that the HBG2:g.-109G>T mutation is also found in the family members in compound heterozygosity with the HBG2:g.-158C>T single nucleotide polymorphism or the silent HBB:g.-101C>T β-thalassemia mutation, resulting in the latter case in significantly elevated Hb F levels (14.3%). Electrophoretic mobility shift analysis revealed that the HBG2:g.-109G>T mutation abolishes a transcription factor binding site, consistent with previous observations using DNA footprinting analysis, suggesting that guanine at position HBG2/1:g.-109 is critical for NF-E3 binding. These data suggest that the HBG2:g-109G>T mutation has a functional role in increasing HBG2 transcription and is responsible for the HPFH phenotype observed in our index cases

Multifractal scaling properties of daily air temperature time series

The aim of the current research study is to examine the scaling properties of the mean daily, maximum and minimum air temperature time series of a single coastal site, located at the island of Crete in Greece. The Multifractal Detrended Fluctuation Analysis (MF-DFA) is used to examine the time series long-term correlation and the singularity spectrum to estimate the multifractality degree. The analysis reveals that the daily temperature time series exhibit a multifractal behavior, are positive long-term correlated and that their multifractal structure is insensitive to local fluctuations with large magnitudes. © 2017 Elsevier Lt

Multifractal Detrended Fluctuation Analysis of Temperature Reanalysis Data over Greece

The Multifractal Detrended Fluctuation Analysis (MF-DFA) is used to examine the scaling behavior and the multifractal characteristics of the mean daily temperature time series of the ERA-Interim reanalysis data for a domain centered over Greece. The results showed that the time series from all grid points exhibit the same behavior: they have a positive long-term correlation and their multifractal structure is insensitive to local fluctuations with a large magnitude. Special emphasis was given to the spatial distribution of the main characteristics of the multifractal spectrum: the value of the Hölder exponent, the spectral width, the asymmetry, and the truncation type of the spectra. The most interesting finding is that the spatial distribution of almost all spectral parameters is decisively determined by the land–sea distribution. The results could be useful in climate research for examining the reproducibility of the nonlinear dynamics of reanalysis datasets and model outputs