Nonergodicity in Load and Recovery:Group Results Do Not Generalize to Individuals

PURPOSE: The study of load and recovery gained significant interest in the last decades, given its important value in decreasing the likelihood of injuries and improving performance. So far, findings are typically reported on the group level, whereas practitioners are most often interested in applications at the individual level. Hence, the aim of the present research is to examine to what extent group-level statistics can be generalized to individual athletes, which is referred to as the "ergodicity issue." Nonergodicity may have serious consequences for the way we should analyze, and work with, load and recovery measures in the sports field. METHODS: The authors collected load, that is, rating of perceived exertion × training duration, and total quality of recovery data among youth male players of a professional football club. This data were collected daily across 2 seasons and analyzed on both the group and the individual level. RESULTS: Group- and individual-level analysis resulted in different statistical outcomes, particularly with regard to load. Specifically, SDs within individuals were up to 7.63 times larger than SDs between individuals. In addition, at either level, the authors observed different correlations between load and recovery. CONCLUSIONS: The results suggest that the process of load and recovery in athletes is nonergodic, which has important implications for the sports field. Recommendations for training programs of individual athletes may be suboptimal, or even erroneous, when guided by group-level outcomes. The utilization of individual-level analysis is key to ensure the optimal balance of individual load and recovery

Measurement of the solar neutrino capture rate with gallium metal

The solar neutrino capture rate measured by the Russian-American Gallium Experiment (SAGE) on metallic gallium during the period January 1990 through December 1997 is 67.2 (+7.2-7.0) (+3.5-3.0) SNU, where the uncertainties are statistical and systematic, respectively. This represents only about half of the predicted Standard Solar Model rate of 129 SNU. All the experimental procedures, including extraction of germanium from gallium, counting of 71Ge, and data analysis are discussed in detail.Comment: 34 pages including 14 figures, Revtex, slightly shortene

Enhanced brightness of a laser-driven X-ray and particle source by microstructured surfaces of silicon targets

The production of intense X-ray and particle sources is one of the most remarkable aspects of high energy laser interaction with a solid target. Wide application of these laser-driven secondary sources requires a high yield, which is partially limited by the amount of laser energy absorbed by the target. Here, we report on the enhancement of laser absorption and X-ray and particle flux by target surface modifications. In comparison to targets with flat front surfaces, our experiments show exceptional laser-to-target performance for our novel cone-shaped silicon microstructures. The structures are manufactured via laser-induced surface structuring. Spectral and spatial studies of reflectance and X-ray generation reveal significant increases of the silicon Kα line and a boost of the overall X-ray intensity, while the amount of reflected light decreases. Also, the proton and electron yields are enhanced, but both temperatures remain comparable to those of flat foil targets. We support the experimental findings with 2D particle in cell simulations to identify the mechanisms responsible for the strong enhancement. Our results demonstrate how custom surface structures can be used to engineer high power laser-plasma sources for future applications

Parkinson’s disease mouse models in translational research

Animal models with high predictive power are a prerequisite for translational research. The closer the similarity of a model to Parkinson’s disease (PD), the higher is the predictive value for clinical trials. An ideal PD model should present behavioral signs and pathology that resemble the human disease. The increasing understanding of PD stratification and etiology, however, complicates the choice of adequate animal models for preclinical studies. An ultimate mouse model, relevant to address all PD-related questions, is yet to be developed. However, many of the existing models are useful in answering specific questions. An appropriate model should be chosen after considering both the context of the research and the model properties. This review addresses the validity, strengths, and limitations of current PD mouse models for translational research

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe

Laser-driven acceleration by microstructured silicon targets

<p>Diagnostic data from a high power laser plasma experiment realised at the Central Laser Facility, UK. Target Area Petawatt with the VULCAN OPCPA laser system was used, to compare microstructured silicon targets (produced at the Detektor- & Targetlabor at the Institut für Kernphysik, Technische Universität Darmstadt, Germany) with flat silicon foils. This spreadsheet shows the laser parameters together with the diagnostic data for 1053nm reflection from target, 527nm emission from target, characteristic X-ray, electron and ion spectra.</p

How everything is connected:Mapping performance determinants of athletes in personalized networks

Research in the field of sports performance has mostly been conducted (a) at a single point, or at most, a few points in time; (b) on the group level; and (c) as a causal chain of monodisciplinary predictor and outcome variables. In the present study, we argue and demonstrate that the next important step should be to monitor, analyze, and visualize the dynamic and individual-specific interactions of multidisciplinary determinants of sports performance. We, therefore, applied a recently developed analytical method, that is, (time-varying) vector-autoregressive (TV-VAR) modeling, which is particularly suited to capture the intra-individual interactions and changes of multidisciplinary determinants. We first measured critical psychological (e.g., confidence, motivation) and physiological (e.g., load, recovery) variables of youth male players from a professional soccer club on a daily basis across one season. Next, we assessed the temporal dynamics (i.e., autoregressive and cross-lagged effects) of those variables and visualized the findings in changing network graphs. We highlight the results of two players, showing how multidisciplinary key determinants of sports performance dynamically evolve across a season in individual-specific ways. For instance, the results of player 1 revealed a stable network across the season in which self-efficacy was the strongest predictor of other determinants. The network of player 2, however, revealed changing effects over time, more overall relations, and no central determinant. These new insights improve our understanding of how key determinants of sports performance are dynamically related in individual athletes. Accordingly, they may allow practitioners to develop and implement athlete-specific interventions at the right time. Future studies may apply (TV-)VAR models to study patterns in the networks of individual athletes in periods of performance gains and losses, injuries, or health problems. Funding source: ZonMw (Dutch organization for health research and innovation)