The use of a functional test battery as a noninvasive method of fatigue assessment

To assess whether a battery of performance markers, both individually and as group, would be sensitive to fatigue, a within group random cross-over design compared multiple variables during seated control and fatigue (repeated sprint cycling) conditions. Thirty-two physically active participants completed a neuromuscular fatigue questionnaire, Stroop task, postural sway, squat jump, countermovement jump, isometric mid-thigh pull and 10 s maximal sprint cycle (Sprintmax) before and after each condition (15 min, 1 h, 24 h and 48 h). In comparison to control, larger neuromuscular fatigue questionnaire total score decrements were observed 15 min (5.20 ± 4.6), 1 h (3.33 ± 3.9) and 24 h (1.83 ± 4.8) after cycling. Similarly, the fatigue condition elicited greater declines than control at 15 min and 1 h post in countermovement jump height (1.67 ± 1.90 cm and 1.04 ± 2.10 cm), flight time-contraction time ratio (0.03 ± 0.06 and 0.05 ± 0.11), and velocity (0.06 ± 0.07 m?s-1 and 0.04 ± 0.08 m?s-1). After fatigue, decrements were observed up to 48 h for average Sprintmax cadence (4-6 RPM), up to 24 h in peak Sprintmax cadence (2-5 RPM) and up to 1 h in average and peak Sprintmax power (45 ± 60Wand 58 ± 71 W). Modelling variables in a stepwise regression demonstrated that CMJ height explained 53.2% and 51.7% of 24 h and 48 h Sprintmax average power output. Based upon these data, the fatigue induced by repeated sprint cycling coincided with changes in the perception of fatigue and markers of performance during countermovement and squat jumps. Furthermore, multiple regression modelling revealed that a single variable (countermovement jump height) explained average power output. © 2019 Hughes et al.This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited

Countermovement jump and squat jump force-time curve analysis in control and fatigue conditions

This study aimed to reanalyze previously published discrete force data from countermovement jumps (CMJs) and squat jumps (SJs) using statistical parametric mapping (SPM), a statistical method that enables analysis of data in its native, complete state. Statistical parametric mapping analysis of 1-dimensional (1D) force-time curves was compared with previous zero-dimensional (0D) analysis of peak force to assess sensitivity of 1D analysis. Thirty-two subjects completed CMJs and SJs at baseline, 15 minutes, 1, 24, and 48 hours following fatigue and control conditions in a pseudo random cross-over design. Absolute (CMJABS/SJABS) and time-normalized (CMJNORM/SJNORM) force-time data were analyzed using SPM 2-way repeated measures analysis of variance with significance accepted at α = 0.05. The SPM indicated a magnitude of difference between force-time data with main effects for time (p \u3c 0.001) and interaction (p \u3c 0.001) observed in CMJABS, SJABS, and SJNORM, whereas previously published 0D analysis reported no 2-way interaction in CMJ and SJ peak force. This exploratory research demonstrates the strength of SPM to identify changes between entire movement force-time curves. Continued development and use of SPM analysis techniques could present the opportunity for refined assessment of athlete fatigue and readiness with the analysis of complete force-time curves

Verification and Validation of the General Mission Analysis Tool (GMAT)

This paper describes the processes and results of Verification and Validation (V&V) efforts for the General Mission Analysis Tool (GMAT). We describe the test program and environments, the tools used for independent test data, and comparison results. The V&V effort produced approximately 13,000 test scripts that are run as part of the nightly buildtest process. In addition, we created approximately 3000 automated GUI tests that are run every two weeks. Presenting all test results are beyond the scope of a single paper. Here we present high-level test results in most areas, and detailed test results for key areas. The final product of the V&V effort presented in this paper was GMAT version R2013a, the first Gold release of the software with completely updated documentation and greatly improved quality. Release R2013a was the staging release for flight qualification performed at Goddard Space Flight Center (GSFC) ultimately resulting in GMAT version R2013b

Voigt transmission windows in optically thick atomic vapours: a method to create single-peaked line centre filters

Cascading light through two thermal vapour cells has been shown to improve the performance of atomic filters that aim to maximise peak transmission over a minimised bandpass window. In this paper, we explore the atomic physics responsible for the operation of the second cell, which is situated in a transverse (Voigt) magnetic field and opens a narrow transmission window in an optically thick atomic vapour. By assuming transitions with Gaussian line shapes and magnetic fields sufficiently large to access the hyperfine Paschen–Back regime, the window is modelled by resolving the two transitions closest to line centre. We discuss the validity of this model and perform an experiment which demonstrates the evolution of a naturally abundant Rb transmission window as a function of magnetic field. The model results in a significant reduction in two-cell parameter space, which we use to find theoretical optimised cascaded line centre filters for Na, K, Rb and Cs across both D lines. With the exception of Cs, these all have a better figure of merit than comparable single cell filters in literature. Most noteworthy is a Rb-D2 filter which outputs >92% of light through a single peak at line centre, with maximum transmission 0.71 and a width of 330 MHz at half maximum

Effect of body composition methodology on heritability estimation of body fatness

Heritability estimates of human body fatness vary widely and the contribution of body composition methodology to this variability is unknown. The effect of body composition methodology on estimations of genetic and environmental contributions to body fatness variation was examined in 78 adult male and female monozygotic twin pairs reared apart or together. Body composition was assessed by six methods - body mass index (BMI), dual energy x-ray absorptiometry (DXA), underwater weighing (UWW), total body water (TBW), bioelectric impedance (BIA), and skinfold thickness. Body fatness was expressed as percent body fat, fat mass, and fat mass/height2 to assess the effect of body fatness expression on heritability estimates. Model-fitting multivariate analyses were used to assess the genetic and environmental components of variance. Mean BMI was 24.5 kg/m2 (range of 17.8-43.4 kg/m2). There was a significant effect of body composition methodology (p<0.001) on heritability estimates, with UWW giving the highest estimate (69%) and BIA giving the lowest estimate (47%) for fat mass/height2. Expression of body fatness as percent body fat resulted in significantly higher heritability estimates (on average 10.3% higher) compared to expression as fat mass/height2 (p=0.015). DXA and TBW methods expressing body fatness as fat mass/height2 gave the least biased heritability assessments, based on the small contribution of specific genetic factors to their genetic variance. A model combining DXA and TBW methods resulted in a relatively low FM/ht2 heritability estimate of 60%, and significant contributions of common and unique environmental factors (22% and 18%, respectively). The body fatness heritability estimate of 60% indicates a smaller contribution of genetic variance to total variance than many previous studies using less powerful research designs have indicated. The results also highlight the importance of environmental factors and possibly genotype by environmental interactions in the etiology of weight gain and the obesity epidemic.R01 AR046124 - NIAMS NIH HHS; R01 MH065322 - NIMH NIH HHS; T32 HL069772 - NHLBI NIH HHS; R21 DK078867 - NIDDK NIH HHS; R37 DA018673 - NIDA NIH HHS; R01 DK076092 - NIDDK NIH HHS; R01 DK079003 - NIDDK NIH HHS; F32 DK009747 - NIDDK NIH HHS; R01 DA018673 - NIDA NIH HH

Determination of a complex crystal structure in the absence of single crystals : analysis of powder X-ray diffraction data, guided by solid-state NMR and periodic DFT calculations, reveals a new 2′-deoxyguanosine structural motif

Derivatives of guanine exhibit diverse supramolecular chemistry, with a variety of distinct hydrogen-bonding motifs reported in the solid state, including ribbons and quartets, which resemble the G-quadruplex found in nucleic acids with sequences rich in guanine. Reflecting this diversity, the solid-state structural properties of 3′,5′-bis-O-decanoyl-2′-deoxyguanosine, reported in this paper, reveal a hydrogen-bonded guanine ribbon motif that has not been observed previously for 2′-deoxyguanosine derivatives. In this case, structure determination was carried out directly from powder XRD data, representing one of the most challenging organic molecular structures (a 90-atom molecule) that has been solved to date by this technique. While specific challenges were encountered in the structure determination process, a successful outcome was achieved by augmenting the powder XRD analysis with information derived from solid-state NMR data and with dispersion-corrected periodic DFT calculations for structure optimization. The synergy of experimental and computational methodologies demonstrated in the present work is likely to be an essential feature of strategies to further expand the application of powder XRD as a technique for structure determination of organic molecular materials of even greater complexity in the future

py4DSTEM: a software package for multimodal analysis of four-dimensional scanning transmission electron microscopy datasets

Scanning transmission electron microscopy (STEM) allows for imaging, diffraction, and spectroscopy of materials on length scales ranging from microns to atoms. By using a high-speed, direct electron detector, it is now possible to record a full 2D image of the diffracted electron beam at each probe position, typically a 2D grid of probe positions. These 4D-STEM datasets are rich in information, including signatures of the local structure, orientation, deformation, electromagnetic fields and other sample-dependent properties. However, extracting this information requires complex analysis pipelines, from data wrangling to calibration to analysis to visualization, all while maintaining robustness against imaging distortions and artifacts. In this paper, we present py4DSTEM, an analysis toolkit for measuring material properties from 4D-STEM datasets, written in the Python language and released with an open source license. We describe the algorithmic steps for dataset calibration and various 4D-STEM property measurements in detail, and present results from several experimental datasets. We have also implemented a simple and universal file format appropriate for electron microscopy data in py4DSTEM, which uses the open source HDF5 standard. We hope this tool will benefit the research community, helps to move the developing standards for data and computational methods in electron microscopy, and invite the community to contribute to this ongoing, fully open-source project