The Benefits of Sampling Sports During Childhood

Sampling may promote prolonged engagement in sport by limiting physical injuries (Fraser-Thomas et al., 2005). Overtraining injuries are a concern for young athletes who specialize in one sport and engage in high volumes of deliberate practice (Hollander, Meyers, & Leunes, 1995; Law, Côté, & Ericsson, 2007). For instance, young gymnasts who practice for over 16 hours a week have been shown to have higher incidences of back injuries (Goldstein, Berger, Windier, & Jackson, 1991). A sampling approach in child-controlled play (e.g. deliberate play) rather than highly adult-controlled practice (e.g. deliberate practice) has been proposed as a strategy to limit overuse and other sport-related injuries (Micheli, Glassman, & Klein, 2000). In summary, sampling may protect against sport attrition by limiting sport related injuries and allowing children to have early experiences in sport that are enjoyable. Psychosocial Benefits of Sampling Only a small percentage of children who participate in school sports ever become elite athletes. Therefore, the psychosocial outcomes of sport participation are particularly important to consider. Recent studies with youth between the ages of 11 to 17 have found that those who are involved in a variety of extracurricular activities (e.g. sports, volunteer, arts) score more favourably on outcome measures such as Grade Point Average (GPA; Fredricks & Eccles, 2006a) and positive peer relationships (Fredricks & Eccles, 2006b) than youth who participate in fewer activities. These patterns are thought to exist due to each extracurricular activity bringing its own distinct pattern of socialization experiences that reinforce certain behaviours and/or teach various skills (Fredricks & Eccles, 2006b; Rose-Krasnor, Bussen, Willoughby, & Chambers, 2006). This contention is corroborated by studies of children and youths' experiences in extracurricular activities indicating that youth have unique experiences in each activity that contribute to their development (Hansen, Larson, & Dworkin, 2003; Larson, Hansen, & Moneta, 2006). This has led Wilkes and Côté (2007) to propose that children who sample different activities (through their own choice or by virtue of parental direction), have a greater chance of developing the following five developmental outcomes compared to children who specialize in one activity: 1) life skills, 2) prosocial behaviour, 3) healthy identity, 4) diverse peer groups and 5) social capital.

Evaluating Misclassification Probability Using Empirical Risk

* The work is supported by RFBR, grant 04-01-00858-a

Оптимизация Оценки Вероятности Ошибочной Классификации в Дискретном Случае

* Работа выполнена при поддержке РФФИ, гранты 07-01-00331-a и 08-01-00944-a

The Benefits of Sampling Sports During Childhood

Sampling may promote prolonged engagement in sport by limiting physical injuries (Fraser-Thomas et al., 2005). Overtraining injuries are a concern for young athletes who specialize in one sport and engage in high volumes of deliberate practice (Hollander, Meyers, & Leunes, 1995; Law, Côté, & Ericsson, 2007). For instance, young gymnasts who practice for over 16 hours a week have been shown to have higher incidences of back injuries (Goldstein, Berger, Windier, & Jackson, 1991). A sampling approach in child-controlled play (e.g. deliberate play) rather than highly adult-controlled practice (e.g. deliberate practice) has been proposed as a strategy to limit overuse and other sport-related injuries (Micheli, Glassman, & Klein, 2000). In summary, sampling may protect against sport attrition by limiting sport related injuries and allowing children to have early experiences in sport that are enjoyable. Psychosocial Benefits of Sampling Only a small percentage of children who participate in school sports ever become elite athletes. Therefore, the psychosocial outcomes of sport participation are particularly important to consider. Recent studies with youth between the ages of 11 to 17 have found that those who are involved in a variety of extracurricular activities (e.g. sports, volunteer, arts) score more favourably on outcome measures such as Grade Point Average (GPA; Fredricks & Eccles, 2006a) and positive peer relationships (Fredricks & Eccles, 2006b) than youth who participate in fewer activities. These patterns are thought to exist due to each extracurricular activity bringing its own distinct pattern of socialization experiences that reinforce certain behaviours and/or teach various skills (Fredricks & Eccles, 2006b; Rose-Krasnor, Bussen, Willoughby, & Chambers, 2006). This contention is corroborated by studies of children and youths' experiences in extracurricular activities indicating that youth have unique experiences in each activity that contribute to their development (Hansen, Larson, & Dworkin, 2003; Larson, Hansen, & Moneta, 2006). This has led Wilkes and Côté (2007) to propose that children who sample different activities (through their own choice or by virtue of parental direction), have a greater chance of developing the following five developmental outcomes compared to children who specialize in one activity: 1) life skills, 2) prosocial behaviour, 3) healthy identity, 4) diverse peer groups and 5) social capital.

Search for Higgs Boson Production Beyond the Standard Model Using the Razor Kinematic Variables in pp Collisions at √s=8 TeV and Optimization of Higgs Boson Identification Using a Quantum Annealer

In the first part of this thesis we search for beyond the Standard Model physics through the search for anomalous production of the Higgs boson using the razor kinematic variables. We search for anomalous Higgs boson production using proton-proton collisions at center of mass energy √s=8 TeV collected by the Compact Muon Solenoid experiment at the Large Hadron Collider corresponding to an integrated luminosity of 19.8 fb^-1.

In the second part we present a novel method for using a quantum annealer to train a classifier to recognize events containing a Higgs boson decaying to two photons. We train that classifier using simulated proton-proton collisions at √s=8 TeV producing either a Standard Model Higgs boson decaying to two photons or a non-resonant Standard Model process that produces a two photon final state.

The production mechanisms of the Higgs boson are precisely predicted by the Standard Model based on its association with the mechanism of electroweak symmetry breaking. We measure the yield of Higgs bosons decaying to two photons in kinematic regions predicted to have very little contribution from a Standard Model Higgs boson and search for an excess of events, which would be evidence of either non-standard production or non-standard properties of the Higgs boson. We divide the events into disjoint categories based on kinematic properties and the presence of additional b-quarks produced in the collisions. In each of these disjoint categories, we use the razor kinematic variables to characterize events with topological configurations incompatible with typical configurations found from standard model production of the Higgs boson.

We observe an excess of events with di-photon invariant mass compatible with the Higgs boson mass and localized in a small region of the razor plane. We observe 5 events with a predicted background of 0.54 ± 0.28, which observation has a p-value of 10^-3 and a local significance of 3.35σ. This background prediction comes from 0.48 predicted non-resonant background events and 0.07 predicted SM higgs boson events. We proceed to investigate the properties of this excess, finding that it provides a very compelling peak in the di-photon invariant mass distribution and is physically separated in the razor plane from predicted background. Using another method of measuring the background and significance of the excess, we find a 2.5σ deviation from the Standard Model hypothesis over a broader range of the razor plane.

In the second part of the thesis we transform the problem of training a classifier to distinguish events with a Higgs boson decaying to two photons from events with other sources of photon pairs into the Hamiltonian of a spin system, the ground state of which is the best classifier. We then use a quantum annealer to find the ground state of this Hamiltonian and train the classifier. We find that we are able to do this successfully in less than 400 annealing runs for a problem of median difficulty at the largest problem size considered. The networks trained in this manner exhibit good classification performance, competitive with the more complicated machine learning techniques, and are highly resistant to overtraining. We also find that the nature of the training gives access to additional solutions that can be used to improve the classification performance by up to 1.2% in some regions.

New trends in food science: the use of nutraceuticals as an antiinflammatory therapeutic tool in exercise

Prolonged high-intensity training seems to result in increased systemic inflammation, which might explain muscle injury, delayed onset muscle soreness, and overtraining syndrome in athletes. Furthermore, an impaired immune function caused by strenuous exercise leads to the development of upper respiratory tract infections in athletes. Nutraceuticals might help counteract these performance-lowering effects. The use of nanotechnology is an interesting alternative to supply athletes with nutraceuticals, as many of these substances are insoluble in water and are poorly absorbed in the digestive tract. The present chapter starts with a brief review of the effects of exercise on immunity, followed by an analysis on how nutraceuticals such as omega-3 fatty acids, glutamine, BCAAs, or phytochemicals can counteract negative effects of strenuous exercise in athletes. Finally, how nanostructured delivery systems can constitute a new trend in enhancing bioavailability and optimizing the action of nutraceuticals will be discussed, using the example of food beverages.