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Reliability of running gait variability measures calculated from inertial measurement units
Changes to the variability within biomechanical signals may reflect a change in the health of the human system. However, for running gait variability measures calculated from wearable device data, it is unknown whether a between-day difference reflects a shift in system dynamics reflective of a change in human health or is a result of poor between-day reliability of the measurement device or the biomechanical signal. This study investigated the reliability of stride time and sacral acceleration variability measures calculated from inertial measurement units (IMUs). Nineteen runners completed six treadmill running trials on two occasions seven days apart. Stride time and sacral acceleration signals were obtained using IMUs. Stride time variability and complexity were calculated using the coefficient of variation (CV) and detrended fluctuation analysis (DFA), respectively. Sacral acceleration regularity was quantified using sample entropy with a range of input parameters m (vector length) and r (similarity threshold). Between-day reliability was assessed using the intraclass correlation coefficient (ICC), standard error of measurement (SEM) and minimum detectable change. Stride time CV displayed moderate relative reliability (ICC = 0.672), but with a large absolute minimum detectable change = 0.525 %, whilst stride time DFA-α displayed poor relative reliability (ICC = 0.457) and yielded large minimum detectable changes (≥ 0.208). Sample entropy displayed good relative reliability in mediolateral and resultant sacral acceleration signals for certain combinations of the parameters m and r, although again with large minimum detectable changes. Researchers should be cognisant of these reliability metrics when interpreting changes in running gait variability measures in clinical contexts.
Journal Article
Avoiding data pitfalls : how to steer clear of common blunders when working with data and presenting analysis and visualizations
\"Avoiding Data Pitfalls is a useful resource that points out common data viz. mistakes so that users can avoid making them and notice them when they are made by others. Working with data is so common now, but the vast majority of \"data workers\" were trained in another technical field like engineering or science. Most were not explicitly taught how to successfully work with today's tools and the types of data at their disposal. This book will provide illustrative examples of common mistakes, first outlining how we often think about data and the \"data-reality gap,\" before walking the reader through each step of successful data visualization, from calculating and analyzing data to eventually presenting it in a way that is both clear and effective. The author will detail common data viz. blunders like cluttered design and ineffective use of color so that the reader can differentiate between a poor presentation and something truly representative and useful\"-- Provided by publisher.
Book
Atypical Combinations and Scientific Impact
Novelty is an essential feature of creative ideas, yet the building blocks of new ideas are often embodied in existing knowledge. From this perspective, balancing atypical knowledge with conventional knowledge may be critical to the link between innovativeness and impact. Our analysis of 17.9 million papers spanning all scientific fields suggests that science follows a nearly universal pattern: The highest-impact science is primarily grounded in exceptionally conventional combinations of prior work yet simultaneously features an intrusion of unusual combinations. Papers of this type were twice as likely to be highly cited works. Novel combinations of prior work are rare, yet teams are 37.7% more likely than solo authors to insert novel combinations into familiar knowledge domains.
Journal Article
Lonely boy : tales from a Sex Pistol
The Sex Pistols transformed twentieth-century culture and kick-started a social revolution. On the 40th anniversary of punk, Jones takes readers on his journey from the Kings Road of the early '70s through the years of the Sex Pistols and punk rock. He delves into the details of his self-imposed exile in New York and Los Angeles, where he battled alcohol, heroin, and sex addiction but eventually emerged to gain fresh acclaim as an actor and radio host.
BOOK
Anthropometric and Physical Qualities of Elite Male Youth Rugby League Players
Rugby league is a collision team sport played at junior and senior levels worldwide, whereby players require highly developed anthropometric and physical qualities (i.e. speed, change-of-direction speed, aerobic capacity, muscular strength and power). Within junior levels, professional clubs and national governing bodies implement talent identification and development programmes to support the development of youth (i.e. 13–20 years) rugby league players into professional athletes. This review presents and critically appraises the anthropometric and physical qualities of elite male youth rugby league players aged between 13 and 20 years, by age category, playing standard and playing position. Height, body mass, body composition, linear speed, change-of-direction speed, aerobic capacity, muscular strength and power characteristics are presented and demonstrate that qualities develop with age and differentiate between playing standard and playing position. This highlights the importance of anthropometric and physical qualities for the identification and development of youth rugby league players. However, factors such as maturity status, variability in development, longitudinal monitoring and career attainment should be considered to help understand, identify and develop the physical qualities of youth players. Further extensive research is required into the anthropometric and physical qualities of youth rugby league players, specifically considering national standardised testing batteries, links between physical qualities and match performance, together with intervention studies, to inform the physical development of youth rugby league players for talent identification and development purposes.
Journal Article
Source code
\"Jake Gyllenhaal headlines this sci-fi time-travel thriller directed by Moon's Duncan Jones from a script by Ben Ripley. A bomb explodes on a Chicago train, derailing the locomotive and killing hundreds. In an attempt to identify the bomber and prevent another, larger attack on downtown Chicago, Captain Colter Stevens (Gyllenhaal) agrees to take part in a clandestine government experiment dubbed \"Source Code,\" which allows him to enter the body of a male passenger during the eight minutes before the man is killed. But during his first trip back, Capt. Stevens fails to gather enough clues to prevent the second attack. With time quickly running out, he repeats the mission ad nauseam in a desperate race to head off one of the most deadly terrorist attacks ever to take place on American soil\"--Allmovie.com, viewed August 29, 2017.
DVD
The Challenge of Applying and Undertaking Research in Female Sport
In recent years there has been an exponential rise in the professionalism and success of female sports. Practitioners (e.g., sport science professionals) aim to apply evidence-informed approaches to optimise athlete performance and well-being. Evidence-informed practices should be derived from research literature. Given the lack of research on elite female athletes, this is challenging at present. This limits the ability to adopt an evidence-informed approach when working in female sports, and as such, we are likely failing to maximize the performance potential of female athletes. This article discusses the challenges of applying an evidence base derived from male athletes to female athletes. A conceptual framework is presented, which depicts the need to question the current (male) evidence base due to the differences of the “female athlete” and the “female sporting environment,” which pose a number of challenges for practitioners working in the field. Until a comparable applied sport science research evidence base is established in female athletes, evidence-informed approaches will remain a challenge for those working in female sport.
Journal Article
Welcome to the punch
Three years ago, master criminal Jacob Sternwood escaped London during a daring robbery that left detective Max Lewinsky physically and emotionally scarred. When a failed heist puts Sternwood's son in a hospital, the fugitive is forced to come out of hiding, giving Max his second chance to get the one criminal who got away. But as Max returns to the pursuit of his arch-nemesis, he begins to uncover evidence of a vast conspiracy that may put him in even greater danger than his personal vendetta.
DVD
Avoiding Data Pitfalls
Avoid data blunders and create truly useful visualizations
Avoiding Data Pitfalls is a reputation-saving handbook for those who work with data, designed to help you avoid the all-too-common blunders that occur in data analysis, visualization, and presentation. Plenty of data tools exist, along with plenty of books that tell you how to use them—but unless you truly understand how to work with data, each of these tools can ultimately mislead and cause costly mistakes. This book walks you step by step through the full data visualization process, from calculation and analysis through accurate, useful presentation. Common blunders are explored in depth to show you how they arise, how they have become so common, and how you can avoid them from the outset. Then and only then can you take advantage of the wealth of tools that are out there—in the hands of someone who knows what they're doing, the right tools can cut down on the time, labor, and myriad decisions that go into each and every data presentation.
Workers in almost every industry are now commonly expected to effectively analyze and present data, even with little or no formal training. There are many pitfalls—some might say chasms —in the process, and no one wants to be the source of a data error that costs money or even lives. This book provides a full walk-through of the process to help you ensure a truly useful result.
* Delve into the \"data-reality gap\" that grows with our dependence on data
* Learn how the right tools can streamline the visualization process
* Avoid common mistakes in data analysis, visualization, and presentation
* Create and present clear, accurate, effective data visualizations
To err is human, but in today's data-driven world, the stakes can be high and the mistakes costly. Don't rely on \"catching\" mistakes, avoid them from the outset with the expert instruction in Avoiding Data Pitfalls.
eBook