1,720,959 research outputs found
Sport-terapia nell'anziano: studio preliminare alla ricerca della dose minima anti-invecchiamento
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Blood parameters and Biathlon performance
No full textBackground: Biathlon is a sport that combines cross-country skiing with rifle shooting. There is no well-described model of performance is this multi-sport event.
This study aimed to identify the parameters influencing biathlon performance. In addition, the study aimed to search for a relationship between performance and measured blood parameters and to determine whether higher haemoglobin concentration [Hb] was associated with improved performance.
Methods: Eighty-three male biathletes underwent pre-competition blood sampling in selected World Cup competitions. For all athletes (n=83) and for a subgroup of top-athletes (n=37), performance parameters identified were related to final standings by univariate and multiple regression analyses and, subsequently, to blood parameters measured on the same day. In athletes tested twice with different [Hb], performance corresponding to competitions with lower and higher [Hb] was compared.
Results: Among the parameters considered, the percent variation for both groups in best skiing time and percent of missed targets were independent determinants of performance (R2=0.853, 0.834, respectively) and were not correlated to blood parameters. In athletes with two samples, despite significantly different [Hb], no corresponding changes in performance were observed.
Conclusion: In this study, the determinants of biathlon performance were identified. A relationship between measured blood parameters was not found, and the individual [Hb] variations observed were not associated with improved performance
Searching for a tool to improve the anti-Doping action: the Project AR.I.E.T.T.A. (Artificial Intelligence Evoking Target Testing In Antidoping)
No full textBackground: Substances and methods used to increase the oxygen blood transport and the athlete's performance can be detected but the screening phase performed by International Federations remains a critical issue. The project AR.IE.T.T.A. aimed to develop a software able to analyze athletes’ haematological and performance profile and to point out those reflecting an abnormal pattern. Methods: 120 Athletes belonging to the International Biathlon Union gave their written informed consent to the study. The haematological and performance data, previously collected were used to develop the AR.I.E.T.T.A. software. Results: The software includes the following sections: 1) Log-in 2) Data-Entry: data can be loaded, stored and grouped 3) Analysis: data can be analysed, validated scores calculated, parameters displayed simultaneously as statistics, table/graphs, individual or subpopulation profiles 4) Screening: an immediate evaluation of the risk score of the present sample and/or the athlete under study can be obtained. The risk score is calculated combining different parameters, absolute values and inter-intra-individual variations considered concurrently with different weights. Conclusions: AR.I.E.T.T.A. software enables a quick evaluation of blood results, favouring surveillance programs and timely target testing controls on athletes by the International Federations. Future studies aiming to validate the risk score and to improve the diagnostic phase will enable an upgrade of the system
Performance and blood monitoring in sports: the artificial intelligence evoking target testing in antidoping (AR.I.E.T.T.A.) project
No full textAIM: Substances and methods used to increase oxygen blood transport and physical performance can be detected in the blood, but the screening of the athletes to be tested remains a critical issue for the International Federations. This project, AR.I.E.T.T.A., aimed to develop a software capable of analysing athletes' hematological and performance profiles to detect abnormal patterns.
METHODS: One-hundred eighty athletes belonging to the International Biathlon Union gave written informed consent to have their hematological data, previously collected according to anti-doping rules, used to develop the AR.I.E.T.T.A. software.
RESULTS: Software was developed with the included sections: 1) log-in; 2) data-entry: where data are loaded, stored and grouped; 3) analysis: where data are analysed, validated scores are calculated, and parameters are simultaneously displayed as statistics, tables and graphs, and individual or subpopulation profiles; 4) screening: where an immediate evaluation of the risk score of the present sample and/or the athlete under study is obtained. The sample risk score or AR.I.E.T.T.A. score is calculated by a simple computational system combining different parameters (absolute values and intra-individual variations) considered concurrently. The AR.I.E.T.T.A. score is obtained by the sum of the deviation units derived from each parameter, considering the shift of the present value from the reference values, based on the number of standard deviations.
CONCLUSION: AR.I.E.T.T.A. enables a quick evaluation of blood results assisting surveillance programs and perform timely target testing controls on athletes by the International Federations. Future studies aiming to validate the AR.I.E.T.T.A. score and improve the diagnostic accuracy will improve the system
“Artificial Intelligence Evoking Target Testing in Antidoping” (AR.I.E.T.T.A.)
No full textDifferent substances and methods can be used to increase the oxygen carrying capacity of blood, thereby improving an athlete's ability to perform. Doping control procedures are expensive and the problem always exists of who we should test, by what criteria and when. Research groups have been developing criteria to detect these substances and methods (blood doping, human recombinant erythropoietin, oxygen carriers, the off/on model) International federations, including Biathlon, currently choose athletes based on random selection, standings, high hemoglobin and/or hematocrit and/or reticulocyte counts, off model scores, etc. There is currently no accurate integrated way to combine all variables (individual performance change and laboratory values), to estimate which athletes should be selected at the optimal time for anti-doping tests.This project aims to develop an intelligent system which is able to identify those athletes whose haematological and multiple variables reflect a pattern consistent with the use of banned substances or methods. These athletes could then be chosen at the optimal time for target testing. The focus of this project is the creation of a software program that will consider haematological values abnormal not only on the basis of high values, but also on the basis of raw data considered concurrently (haematological data in relation to the reference population, intraindividual haematological variations including abnormal low data, performance variations, ranking, nation). This system will produce classes of results associated to a diagnostic probability, useful for targeted selection for both in and out of competition controls. The system aims to be fast (analysing multiple data simultaneously), unpredictable and self-learning (the new informations will be automatically included to improve the knowledge). The project aims to provide a strong deterrent against doping, reducing the risk of evasion by manipulation, and to be cost-effective, ensuring that anti-doping budgets are spent in an evidence based fashion
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
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