scholarly journals How recreational marathon runners hit the wall: A large-scale data analysis of late-race pacing collapse in the marathon

PLoS ONE ◽  
2021 ◽  
Vol 16 (5) ◽  
pp. e0251513
Author(s):  
Barry Smyth
Keyword(s):  
Large Scale ◽  
Marathon Runners ◽  
Male And Female ◽  
Large Scale Data ◽  
Trade Offs ◽  
Energy Stores ◽  
Before And After ◽  
Definition Of ◽  
Race Performance ◽  
Scale Data

Introduction In the marathon, how runners pace and fuel their race can have a major impact on race outcome. The phenomenon known as hitting the wall (HTW) refers to the iconic hazard of the marathon distance, in which runners experience a significant slowing of pace late in the race, typically after the 20-mile mark, and usually because of a depletion of the body’s energy stores. Aim This work investigates the occurrence of significant late-race slowing among recreational marathoners, as a proxy for runners hitting the wall, to better understand the likelihood and nature of such slowdowns, and their effect on race performance. Methods Using pacing data from more than 4 million race records, we develop a pacing-based definition of hitting the wall, by identifying runners who experience a sustained period of slowing during the latter stages of the marathon. We calculate the cost of these slowdowns relative to estimates of the recent personal-best times of runners and compare slowdowns according to runner sex, age, and ability. Results We find male runners more likely to slow significantly (hit the wall) than female runners; 28% of male runners hit the wall compared with 17% of female runners, χ2(1, N = 1, 928, 813) = 27, 693.35, p < 0.01, OR = 1.43. Such slowdowns are more frequent in the 3 years immediately before and after a recent personal-best (PB) time; for example, 36% of all runners hit the wall in the 3 years before a recent PB compared with just 23% in earlier years, χ2(1, N = 509, 444) = 8, 120.74, p < 0.01, OR = 1.31. When runners hit the wall, males slow more than females: a relative slowdown of 0.40 vs. 0.37 is noted, for male and female runners, when comparing their pace when they hit the wall to their earlier race (5km-20km) pace, with t(475, 199) = 60.19, p < 0.01, d = 0.15. And male runners slow over longer distances than female runners: 10.7km vs. 9.6km, respectively, t(475, 199) = 68.44, p < 0.01, d = 0.17. Although, notably the effect size of these differences is small. We also find the finish-time costs of hitting the wall (lost minutes) to increase with ability; r2(7) = 0.91, p < 0.01 r2(7) = 0.81, p < 0.01 for male and female runners, respectively. Conclusions While the findings from this study are consistent with qualitative results from earlier single-race or smaller-scale studies, the new insights into the risk and nature of slowdowns, based on the runner sex, age, and ability, have the potential to help runners and coaches to better understand and calibrate the risk/reward trade-offs that exist as they plan for future races.

Exploring the wall in marathon running

2020 ◽  
Vol 6 (3) ◽  
pp. 173-186
Author(s):  
Jakim Berndsen ◽  
Aonghus Lawlor ◽  
Barry Smyth
Keyword(s):  
Large Scale ◽  
Operational Definition ◽  
Data Driven ◽  
Marathon Running ◽  
Finish Line ◽  
Marathon Runners ◽  
Large Scale Data ◽  
Definition Of ◽  
Glycogen Stores ◽  
Scale Data

The wall is an iconic feature of the marathon. If runners hit the wall, usually around the 30km (20mi) mark, their pace slows dramatically, leaving them to struggle to the finish-line. While the physiology of the wall is reasonably well understood – a critical combination of fatigue and a lack of available fuel as the body’s glycogen stores become depleted – its actual impact is less well studied. In this paper we present a large-scale data-driven study of how and when recreational marathon runners hit the wall. We do this by analysing the pacing patterns of almost 60,000 runners across more than 250 races. The main contributions are: (1) an operational definition of the wall by identifying its key pacing features; and (2) and analysis of hitting the wall for runners, based on their age, gender and ability, using this definition.

scholarly journals Functional characterization of 3D protein structures informed by human genetic diversity

2019 ◽  
Vol 116 (18) ◽  
pp. 8960-8965 ◽  
Author(s):  
Michael Hicks ◽  
Istvan Bartha ◽  
Julia di Iulio ◽  
J. Craig Venter ◽  
Amalio Telenti
Keyword(s):  
Large Scale ◽  
Functional Characterization ◽  
Protein Structures ◽  
Large Scale Data ◽  
Allosteric Sites ◽  
Missense Variation ◽  
Binding Pockets ◽  
Definition Of ◽  
Scale Data

Sequence variation data of the human proteome can be used to analyze 3D protein structures to derive functional insights. We used genetic variant data from nearly 140,000 individuals to analyze 3D positional conservation in 4,715 proteins and 3,951 homology models using 860,292 missense and 465,886 synonymous variants. Sixty percent of protein structures harbor at least one intolerant 3D site as defined by significant depletion of observed over expected missense variation. Structural intolerance data correlated with deep mutational scanning functional readouts for PPARG, MAPK1/ERK2, UBE2I, SUMO1, PTEN, CALM1, CALM2, and TPK1 and with shallow mutagenesis data for 1,026 proteins. The 3D structural intolerance analysis revealed different features for ligand binding pockets and orthosteric and allosteric sites. Large-scale data on human genetic variation support a definition of functional 3D sites proteome-wide.

Hebrew Literature in the ‘World Republic of Letters’

2018 ◽  
Vol 33 (2) ◽  
pp. 1-25
Author(s):  
Yael Halevi-Wise ◽  
Madeleine Gottesman
Keyword(s):  
Large Scale ◽  
Hebrew Literature ◽  
Republic Of Letters ◽  
Large Scale Data ◽  
Cultural Experiences ◽  
The World ◽  
Modern Hebrew ◽  
Nuanced Understanding ◽  
Definition Of ◽  
Scale Data

This article charts the international reception of modern Hebrew literature over the last hundred years. It brings large-scale data on the translation of Hebrew literature into conversation with current studies on the dissemination of ‘small’ languages around the world. We pay special attention to publishing trends, genres, literary awards, and other indicators of international recognition. More broadly, we question the scope and definition of a body of literature whose ancient traces have become invisible through translation and whose international readership includes, to some extent, members of its ‘own’ nation who do not share, however, the same language, territory, or cultural experiences. Our goal is to provide a more nuanced understanding of the presence of Hebrew literature beyond its national borders.

scholarly journals Minimizing acquisition-related radiomics variability by image resampling and batch effect correction to allow for large-scale data analysis

2020 ◽  
Author(s):  
Marta Ligero ◽  
Olivia Jordi-Ollero ◽  
Kinga Bernatowicz ◽  
Alonso Garcia-Ruiz ◽  
Eric Delgado-Muñoz ◽  
...  
Keyword(s):  
Liver Metastases ◽  
Large Scale ◽  
Batch Effect ◽  
Slice Thickness ◽  
Convolution Kernel ◽  
Voxel Size ◽  
Large Scale Data ◽  
Before And After ◽  
Slice Spacing ◽  
Scale Data

Abstract Objective To identify CT-acquisition parameters accounting for radiomics variability and to develop a post-acquisition CT-image correction method to reduce variability and improve radiomics classification in both phantom and clinical applications. Methods CT-acquisition protocols were prospectively tested in a phantom. The multi-centric retrospective clinical study included CT scans of patients with colorectal/renal cancer liver metastases. Ninety-three radiomics features of first order and texture were extracted. Intraclass correlation coefficients (ICCs) between CT-acquisition protocols were evaluated to define sources of variability. Voxel size, ComBat, and singular value decomposition (SVD) compensation methods were explored for reducing the radiomics variability. The number of robust features was compared before and after correction using two-proportion z test. The radiomics classification accuracy (K-means purity) was assessed before and after ComBat- and SVD-based correction. Results Fifty-three acquisition protocols in 13 tissue densities were analyzed. Ninety-seven liver metastases from 43 patients with CT from two vendors were included. Pixel size, reconstruction slice spacing, convolution kernel, and acquisition slice thickness are relevant sources of radiomics variability with a percentage of robust features lower than 80%. Resampling to isometric voxels increased the number of robust features when images were acquired with different pixel sizes (p < 0.05). SVD-based for thickness correction and ComBat correction for thickness and combined thickness–kernel increased the number of reproducible features (p < 0.05). ComBat showed the highest improvement of radiomics-based classification in both the phantom and clinical applications (K-means purity 65.98 vs 73.20). Conclusion CT-image post-acquisition processing and radiomics normalization by means of batch effect correction allow for standardization of large-scale data analysis and improve the classification accuracy. Key Points • The voxel size (accounting for the pixel size and slice spacing), slice thickness, and convolution kernel are relevant sources of CT-radiomics variability. • Voxel size resampling increased the mean percentage of robust CT-radiomics features from 59.50 to 89.25% when comparing CT scans acquired with different pixel sizes and from 71.62 to 82.58% when the scans were acquired with different slice spacings. • ComBat batch effect correction reduced the CT-radiomics variability secondary to the slice thickness and convolution kernel, improving the capacity of CT-radiomics to differentiate tissues (in the phantom application) and the primary tumor type from liver metastases (in the clinical application).

Extending XQuery with pattern matching over XML, HTML and JSON, and its usage for data mining

2014 ◽  
Author(s):  
Benito van der Zander
Keyword(s):  
Data Mining ◽  
Programming Languages ◽  
Pattern Matching ◽  
Large Scale ◽  
General Pattern ◽  
Real Thing ◽  
Functional Programming Languages ◽  
Large Scale Data ◽  
Definition Of ◽  
Scale Data

Pattern matching in a broad sense is a common feature of modern functional programming languages, answering the question, if one complex structured object has a form that is the same as another complex structured object, for some definition of “the same”. In XQuery path expressions, switch, and typeswitch statements are often described as performing pattern matching, but these are merely impoverished flavors of matching when compared to the real thing. We describe a syntax for general pattern matching based on regular expressions for XML/HTML/JSONiq trees, how these patterns are matched against input data, and how this pattern matching can be integrated into the syntax and semantics of the XQuery language. At the end we summarize real-world experience using it for large-scale data mining of library webcatalogs.

scholarly journals A method of identifying and analyzing Outgoing Long-wave Radiation anomalies before earthquake

2018 ◽  
Vol 189 ◽  
pp. 11001 ◽  
Author(s):  
Xiaoying Jiang ◽  
Xiangzeng Kong ◽  
Gongde Guo
Keyword(s):  
Large Scale ◽  
Wave Radiation ◽  
Outgoing Long Wave Radiation ◽  
Large Scale Data ◽  
Long Wave ◽  
Geological Conditions ◽  
Before And After ◽  
Large Earthquakes ◽  
Scale Data ◽  
Long Wave Radiation

A large amount of anomalous information will appear before the earthquake, but it is difficult to identify and analyze valuable anomalous information from large-scale data. To solve this problem, this paper presents a method of pre-earthquake Outgoing Long-wave Radiation (OLR) anomaly identification and analysis based on quantum walking algorithm. The National Oceanic and Atmospheric Administration (NOAA) data are used to process and analyze the OLR data before and after the 6 major earthquakes in 2017 in western China.The results show that different degrees of thermal infrared anomalies have appeared before and after these large earthquakes. In this paper, we also analyze and discuss the similarities and differences of these changes by combining geological conditions and other factors.

scholarly journals Applying Collocation Analysis to Chinese Discourse: A Case Study of Causal Connectives

Lingua Sinica ◽  
2020 ◽  
Vol 6 (1) ◽  
pp. 1-24
Author(s):  
Yipu Wei ◽  
Dirk Speelman ◽  
Jacqueline Evers-Vermeul
Keyword(s):  
Large Scale ◽  
Methodological Issues ◽  
Large Scale Data ◽  
Manual Analysis ◽  
Discourse Relations ◽  
Discourse Studies ◽  
Definition Of ◽  
Scale Data ◽  
Selection Of

Abstract Collocation analysis can be used to extract meaningful linguistic information from large-scale corpus data. This paper reviews the methodological issues one may encounter when performing collocation analysis for discourse studies on Chinese. We propose four crucial aspects to consider in such analyses: (i) the definition of collocates according to various parameters; (ii) the choice of analysis and association measures; (iii) the definition of the search span; and (iv) the selection of corpora for analysis. To illustrate how these aspects can be addressed when applying a Chinese collocation analysis, we conducted a case study of two Chinese causal connectives: yushi ‘that is why’ and yin’er ‘as a result’. The distinctive collocation analysis shows how these two connectives differ in volitionality, an important dimension of discourse relations. The study also demonstrates that collocation analysis, as an explorative approach based on large-scale data, can provide valuable converging evidence for corpus-based studies that have been conducted with laborious manual analysis on limited datasets.

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