Minimize Measurement Error Research Articles

Methods for determining the physical quantities describing the vehicle movement and the driver during a road accident

The paper compares the displacement and speed courses of cars, motorbikes and motorcyclists during a road accident obtained with the use of two measurement methods. In the first method, the course of the impact recorded by a fast camera recording 1000 frames per second was used (“frame by frame” film analysis). In the second method, the courses of accelerations and angular velocities of the objects were used (numerical integration of the recorded courses). The measurements were carried out during crash tests involving a frontal-side collision of two cars or a motorcycle with a car. The results has been shown in the time interval 0-0.5 s. During this period, the following phases of the experiment are observed: vehicle collision and the process of their deformation, the separation of vehicles, the start of independent movement of both vehicles after the collision. The measurement results obtained with the use of both methods are burdened with errors resulting, among others, from limited data sampling frequency, offset errors, calibration errors and sensor noise, duration of the analyzed waveforms. The use of two of the above-mentioned measurement methods simultaneously allows to minimize measurement errors.

A Survey of Interventions for Cancer Survivors Provided by Occupational Therapy Practitioners

Purpose: Currently, there is a lack of research exploring evidence-based occupational therapy intervention practices at the activity level in survivorship care, which is important to identify for future research and clinical needs of the profession. The purpose of this study was to describe what activity level interventions OT practitioners are using and report any practice trends that might exist. Method: A cross-section design was used with non-probability purposive sampling to recruit occupational therapy practitioners working with adults living with and beyond cancer. A three-phase process for survey development and implementation was used, as recommended by the literature, for improving content validity and minimizing measurement error. Results: A total of 267 surveys were distributed and 70 surveys returned (26.20% response rate). Given the range and frequency of responses, it is suggested that occupational therapy practitioners focus on individual needs for function and participation and are not limiting practice to physical impairments. There were several areas that only a small percentage of respondents identified addressing with clients, including shopping (range 5.83-9.23%), driving and community mobility (range 5.90-9.58%), and financial management (range .74-10.20%) that typically fall into outpatient and community health practice settings. Conclusion: We reviewed current oncology intervention and referral practice trends for occupational therapy and pose several implications for advancing clinical practice in oncology. Future research into interventions not supported by literature that occupational therapists identified currently using in practice is needed.

An experimental investigation challenging the thermal collapse of sand

Currently, highly contradictory knowledge characterises the thermally induced deformation of sands and the occurrence of the thermal collapse phenomenon: a volumetric contraction of such granular materials upon heating, which has been observed in some laboratory studies as opposed to a volumetric expansion. In this context, the effects of applied stress level and relative density, which seem to account for the inconclusive findings, remain disputed. A key challenge inherent to investigations of the thermally induced deformation of sands is the requirement for tremendous measurement accuracy (i.e. trueness and precision) and the ability to minimise measurement errors. This paper addresses this challenge and the conflicts presently characterising this subject by reporting a laboratory experimental campaign that accurately and repeatedly measures the thermally induced deformation of sand for different relative densities, stress levels and particle shapes by means of temperature-controlled oedometer tests. The results of this study show a monotonic volumetric expansion of sand upon heating and contraction upon cooling, with an irreversible contractive deformation remaining after one heating–cooling cycle. Specifically, irrespective of the stress level, relative density or particle shape, no thermal collapse is observed, challenging the actual occurrence of such a phenomenon in sands.

Defining minimal detectable difference in echocardiographic measures of right ventricular function in systemic sclerosis

BackgroundEchocardiography (2DE) is integral for screening and longitudinal evaluation of pulmonary arterial hypertension (PAH) in systemic sclerosis (SSc). In the present study, we sought to establish the reliability, repeatability, and reproducibility of 2DE parameters in SSc patients with and without PAH and to define the minimal detectable difference (MDD), the smallest change detected beyond measurement error.MethodsSSc patients without known PAH and with invasively confirmed PAH on stable therapies underwent 2DE with strain at two time points. Analysis of variance (ANOVA) and coefficients of variation (CV) were calculated to assess for repeatability, reliability, and reproducibility. Intra- and inter-observer agreement were assessed using intraclass correlation. Bland-Altman analysis explored the level of agreement between evaluations. MDD was calculated using the standard error of measurement for each parameter by cohort.ResultsANOVA demonstrated few significant differences between evaluations across groups. Global right ventricular longitudinal systolic strain (GRVLSS, 9.7%) and fractional area change (FAC, 21.3%) had the largest CV, while tricuspid annular plane excursion (TAPSE), S’ wave, and right ventricular outflow track velocity time integral (RVOT VTI) were 0.87%, 3.2%, and 6.0%, respectively. Intra- and inter-observer agreement was excellent. MDD for TAPSE, FAC, S’ wave, RVOT VTI, GRVLSS, and RVSP were 0.11 cm, 0.03%, 1.27 cm/s, 0.81 cm, 1.14%, and 6.5 mmHg, respectively.ConclusionsWe demonstrate minimal measurement error in clinically important 2DE-based measures in SSc patients with and without PAH. Defining the MDD in this population has important implications for PAH screening, assessment of therapeutic response, and sample size calculations for future clinical trials.

The Effects of Taxes, Inflation and Government Effectiveness on House Real Price in OECD Countries: A Panel Data Study

This study aims to investigate the relationship between income tax (TPI), goods and services tax (TGS) and property tax (TOP) on real house price (HRP). On the other hand, this study examines the impact of inflation and government effectiveness (GE) on HRP. As far as I know, there are few studies in the literature that have examined these relationships. There is also no study that has examined the relationship between inflation and GE as economic variables on HRP. This study is quantitative, and the research design used is panel data. This study collects data from the OECD database for 49 OECD countries from 2000 to 2019. Two estimation methods, namely Ordinary Least Square (OLS) and LSDVC, are used in this study to minimize measurement error and test five hypotheses. Since LSDVC is more suitable to solve dynamic association, endogeneity and autocorrelation problems, this study considers LSDVC results as the main result of this study. Thus, by using LSDVC, this study found only a negative relationship between GE and HRP and no relationship between taxes, inflation and HRP. This study aims to contribute to the findings of previous studies. In addition to theoretical and methodological contributions, the results of this study are useful for OECD developed and developing countries to understand the impact of various taxes, GE and inflation on HRP. The results may also provide important guidance to policy makers in developing countries who are considering the application of various types of taxes.

Evaluation of cerebral cortex viscoelastic property estimation with nonlinear inversion magnetic resonance elastography

Objective. Magnetic resonance elastography (MRE) of the brain has shown promise as a sensitive neuroimaging biomarker for neurodegenerative disorders; however, the accuracy of performing MRE of the cerebral cortex warrants investigation due to the unique challenges of studying thinner and more complex geometries. Approach. A series of realistic, whole-brain simulation experiments are performed to examine the accuracy of MRE to measure the viscoelasticity (shear stiffness, μ, and damping ratio, ξ) of cortical structures predominantly effected in aging and neurodegeneration. Variations to MRE spatial resolution and the regularization of a nonlinear inversion (NLI) approach are examined. Main results. Higher-resolution MRE displacement data (1.25 mm isotropic resolution) and NLI with a low soft prior regularization weighting provided minimal measurement error compared to other studied protocols. With the optimized protocol, an average error in μ and ξ was 3% and 11%, respectively, when compared with the known ground truth. Mid-line structures, as opposed to those on the cortical surface, generally display greater error. Varying model boundary conditions and reducing the thickness of the cortex by up to 0.67 mm (which is a realistic portrayal of neurodegenerative pathology) results in no loss in reconstruction accuracy. Significance. These experiments establish quantitative guidelines for the accuracy expected of in vivo MRE of the cortex, with the proposed method providing valid MRE measures for future investigations into cortical viscoelasticity and relationships with health, cognition, and behavior.

Precision in the measurement of lexical expertise: the selection of optimal items for a spelling assessment.

Skilled adult readers vary in many skills related to visual word form processing such as phonological processing, vocabulary size, comprehension skill, and spelling skill (Kuperman & Van Dyke, 2011). Spelling skill in particular has received much attention because low- and high-skill spellers show different patterns of lexical processing as measured through eye movement behavior, reaction times, and word learning (Eskenazi et al., 2018; Veldre & Andrews, 2014). Researchers commonly use a spelling dictation task to measure lexical expertise; however, there is limited evidence for its psychometric properties and room for improvement in item selection (Andrews et al., 2020). The purpose of this study was to assess the precision of 110 words as measures of lexical expertise, to compare various subsets of words in a spelling dictation task, and to provide a set of words that more precisely measure lexical expertise. In Study 1, a spelling dictation task with 110 words was administered to 682 participants. In Study 2, that same task and measures of vocabulary and comprehension were administered to 786 participants. Results indicated that the set of 110 words contains many words that are imprecise measures of spelling skill. Through an iterative process of removing words with high error variance, a set of 20 words was selected that minimizes measurement error and demonstrates discriminant validity from vocabulary and comprehension ability. We recommend this set of words as a more precise measure of spelling skill, which will provide more power to detect moderating effects of lexical expertise on reading processes.

New Exponential Scoring Functions for Diet Quality Indexes Solve Problems Caused by Truncation

Diet quality indexes, including the Healthy Eating Index, assess diets based on usual dietary intakes and a scoring function. Nearly all diet quality indexes use scoring functions that have floors and ceilings, thereby truncating the scores and losing information about intakes outside the scoring range. This score truncation has 2 important impacts: 1) the index does not reflect all intakes; and 2) the assumption that measurement error in intake reporting has a neutral impact on the diet quality score cannot be upheld. Our main objective was to devise new diet quality scoring functions that eliminate truncation and its attendant problems. Seven desirable properties of a new scoring function were identified: 1) avoid truncations in component scoring to prevent information loss and to provide scoring sensitivity in the currently truncated regions; 2) reduce dependency on the accuracy of dietary standards; 3) minimize measurement error bias and subsequent misclassification; 4) relate plausibly to biological processes; 5) possess desirable mathematical and statistical properties; 6) have simple representations that are easy to calculate and add minimum artifacts of their own; and 7) otherwise closely mimic existing scoring functions. The recommended replacement for piecewise-linear scoring is a family of scoring functions based on exponentials. For components where higher intakes are better, the function is a single exponential. For components where lower intakes are better, the function is a concave-convex mirrored pair of exponentials. The proposed exponential scoring functions have all 7 desired properties. The proposed exponential scoring functions will improve the usefulness of dietary scoring indexes by eliminating truncations. Compared to existing scoring functions, the use of exponentials makes the scores more inclusive of very high and very low intakes, reduces measurement error bias, and is less sensitive to the exact placement of the scoring standards.

Development of Multiple UAV Collaborative Driving Systems for Improving Field Phenotyping.

Unmanned aerial vehicle-based remote sensing technology has recently been widely applied to crop monitoring due to the rapid development of unmanned aerial vehicles, and these technologies have considerable potential in smart agriculture applications. Field phenotyping using remote sensing is mostly performed using unmanned aerial vehicles equipped with RGB cameras or multispectral cameras. For accurate field phenotyping for precision agriculture, images taken from multiple perspectives need to be simultaneously collected, and phenotypic measurement errors may occur due to the movement of the drone and plants during flight. In this study, to minimize measurement error and improve the digital surface model, we proposed a collaborative driving system that allows multiple UAVs to simultaneously acquire images from different viewpoints. An integrated navigation system based on MAVSDK is configured for the attitude control and position control of unmanned aerial vehicles. Based on the leader–follower-based swarm driving algorithm and a long-range wireless network system, the follower drone cooperates with the leader drone to maintain a constant speed, direction, and image overlap ratio, and to maintain a rank to improve their phenotyping. A collision avoidance algorithm was developed because different UAVs can collide due to external disturbance (wind) when driving in groups while maintaining a rank. To verify and optimize the flight algorithm developed in this study in a virtual environment, a GAZEBO-based simulation environment was established. Based on the algorithm that has been verified and optimized in the previous simulation environment, some unmanned aerial vehicles were flown in the same flight path in a real field, and the simulation and the real field were compared. As a result of the comparative experiment, the simulated flight accuracy (RMSE) was 0.36 m and the actual field flight accuracy was 0.46 m, showing flight accuracy like that of a commercial program.

Declining neighborhood simulated annealing algorithm to robust fixture synthesis in a point-set domain

Fixture synthesis addresses the problem of fixture-elements placement on the workpiece surfaces. This article presents a novel variant of the simulated annealing (SA) algorithm called declining neighborhood simulated annealing (DNSA) specifically developed for the problem of fixture synthesis. The objective is to minimize measurement errors in the machined features induced by the misalignment at locators-workpiece contact points. The algorithm systematically evaluates different fixture layouts to reach a sufficient approximation of the most robust layout. For each iteration, a set of previously accepted candidates are exploited to direct the search toward the optimal region. Throughout the progress of the algorithm, the search space is reduced and the new candidates are designated according to a declining probability density function (PDF). To assure best performance, the DNSA parameters are configured using the Technique for Order Preference by Similarity to Ideal Solution (TOPOSIS). Moreover, the parameters are set to auto-adapt the complexity of a given input based on a Shanon entropy index. The optimization process is carried out automatically in the computer-aided design (CAD) environment NX; a computer code was developed for this purpose using the application programming interface (API) NXOpen. Benchmark examples from industrial partner and literature demonstrate satisfactory results.

Accurate internal deformation measurement of an indentation test using micro-CT and self-adaptive digital volume correlation.

Mechanical indentation testing is a widely used technique for determining local mechanical properties of materials. Accurate measurement of internal deformation in the indentation test is necessary for further study of material properties. Therefore, an in situ experimental measurement strategy combining micro-CT imaging and self-adaptive digital volume correlation (SA-DVC) is proposed. Unlike conventional DVC, SA-DVC can automatically identify the optimal subvolume size for each calculation point, which can effectively minimize measurement errors. The efficacy of the proposed method is first verified by the simulated indentation experiment. Then, it is used to analyze the deformation of epoxy resin composite in a real indentation experiment. Measurement results indicate that the proposed method can estimate three-dimensional displacement and strain fields with enhanced accuracy, and further application of the obtained measurement results on material parameter identification and stress field reconstruction is expected.

Reliability, minimal detectable change and measurement errors in knee extension muscle strength measurement using a hand-held dynamometer in young children.

[Purpose] Few studies have assessed the reliability of muscle strength measurement using a hand-held dynamometer, specifically in Japanese young children. This study aims to investigate the reliability, minimal detectable change and measurement error in knee extension muscle strength measurements in young children using a hand-held dynamometer. [Participants and Methods] The study participants comprised 36 kindergarten-enrolled children of 3–6 years age. An experienced physiotherapist measured their isometric knee extension strength. Appropriate orientation and practices were performed prior to measurement. The same physiotherapist took the muscle measurements twice; and the maximum value was used as the muscle strength value. The measurements were repeated at intervals of approximately 30 min to verify reproducibility. [Results] The initial isometric knee extension strength was 10.6 ± 3.3 kgf and the Intra-class correlation coefficient (1,1) was 0.765. The standard error of measurement was 1.6 kgf and the minimal detectable change was 4.4 kgf. No significant systematic errors were observed. [Conclusion] Isometric knee extension strength measurement using a hand-held dynamometer in young children has good reliability with a low risk of systematic errors.

The Amsterdam Foot Model: a clinically informed multi-segment foot model developed to minimize measurement errors in foot kinematics

BackgroundFoot and ankle joint kinematics are measured during clinical gait analyses with marker-based multi-segment foot models. To improve on existing models, measurement errors due to soft tissue artifacts (STAs) and marker misplacements should be reduced. Therefore, the aim of this study is to define a clinically informed, universally applicable multi-segment foot model, which is developed to minimize these measurement errors.MethodsThe Amsterdam foot model (AFM) is a follow-up of existing multi-segment foot models. It was developed by consulting a clinical expert panel and optimizing marker locations and segment definitions to minimize measurement errors. Evaluation of the model was performed in three steps. First, kinematic errors due to STAs were evaluated and compared to two frequently used foot models, i.e. the Oxford and Rizzoli foot models (OFM, RFM). Previously collected computed tomography data was used of 15 asymptomatic feet with markers attached, to determine the joint angles with and without STAs taken into account. Second, the sensitivity to marker misplacements was determined for AFM and compared to OFM and RFM using static standing trials of 19 asymptomatic subjects in which each marker was virtually replaced in multiple directions. Third, a preliminary inter- and intra-tester repeatability analysis was performed by acquiring 3D gait analysis data of 15 healthy subjects, who were equipped by two testers for two sessions. Repeatability of all kinematic parameters was assessed through analysis of the standard deviation (σ) and standard error of measurement (SEM).ResultsThe AFM was defined and all calculation methods were provided. Errors in joint angles due to STAs were in general similar or smaller in AFM (≤2.9°) compared to OFM (≤4.0°) and RFM (≤6.7°). AFM was also more robust to marker misplacement than OFM and RFM, as a large sensitivity of kinematic parameters to marker misplacement (i.e. > 1.0°/mm) was found only two times for AFM as opposed to six times for OFM and five times for RFM. The average intra-tester repeatability of AFM angles was σ:2.2[0.9°], SEM:3.3 ± 0.9° and the inter-tester repeatability was σ:3.1[2.1°], SEM:5.2 ± 2.3°.ConclusionsMeasurement errors of AFM are smaller compared to two widely-used multi-segment foot models. This qualifies AFM as a follow-up to existing foot models, which should be evaluated further in a range of clinical application areas.

Digital image correlation at long working distances: The influence of diffraction limits

Digital Image Correlation (DIC) is an optical measurement technique that can easily be adapted for high magnification applications. These high magnifications involve competing phenomena which must be balanced to produce the highest quality measurements. When out-of-plane displacements cause the specimen under investigation to move out of the depth of field, poor focus negatively affects the measurement. As a result, it is often recommended to reduce aperture size to improve the depth of field. However, smaller aperture sizes can also cause poor focus as the diffraction limit of light causes larger Airy disks, particularly at longer working distances. This work investigates the competing effects of both depth of field and Airy disk size in three test cases: higher magnification and shorter working distance, lower magnification and shorter working distance, and lower magnification and longer working distance. Different aperture sizes are found to change which effect dominates, and a recommendation for selecting the aperture setting to minimize measurement error from both phenomena is made.

Temporal variability in automatically-collected liveweight data affects estimation of dry matter intake of dairy cows

Daily liveweight monitoring can be done using an automated weighing system. However, liveweight of dairy cows is extremely variable between and within individual cows and days due to various factors. Large variation in daily liveweight changes can be seen when measured at different times of the day, and that may affect the estimation of daily energy required by cows, and directly affect the estimation of dry matter intake. The objectives of the present study were to quantify the variation in cow’s liveweight automatically recorded in the morning and afternoon, and subsequently demonstrate the differences in estimates of dry matter intake. Morning and afternoon liveweight data from 64 primiparous and multiparous lactating Holstein-Friesian cows were used in this study. Two analyses were performed, without (raw) and with smoothing liveweight data using a spline function to minimize measurement errors and reduce the variability in liveweight over time. Dry matter intake for individual animals was estimated using back-calculation of the energy requirement from liveweight, liveweight change, milk production and milk composition. Results showed that, on average, cows were significantly heavier in the afternoon (Mean ± SD = 614.3 ± 78.20 kg) compared to morning (593.2 ± 76.08 kg; P < 0.01). In terms of variability, the residual standard deviation indicated that the afternoon liveweight had more fluctuations (P < 0.01) over the time compared to those recorded in the morning. The estimation of both individual liveweight change and dry matter intake using morning and afternoon liveweight in their raw form showed unrealistic values ranging from −110.0 to +96.0 and −337.57 to + 399.74 kg/day, respectively. The smoothing of automatically-collected liveweight data substantially reduced the variability of liveweight, liveweight change and dry matter intake. The estimated dry matter intake ranged between 1 and 5% of liveweight/day when calculated using adjusted liveweight values. Based on the residual standard deviation for estimated dry matter intake, we concluded that a single liveweight measurement per cow in the morning is adequate to adjust the automatically-collected liveweight to reduce variability in the estimated intake.

Portable microwave radiometer for wearable devices

This paper presents a new circuit of the miniature microwave radiometer for wearable devices, which can be used to monitor the core body temperature (CBT) of internal human tissues continuously 24/7. The measurement results of the proposed device, as opposed to the known miniature wearable radiometers, remain unchanged when the impedance of the examined area varies. We have derived an analytical expression for radiometer measurement error based on parameters of device components. This formula allows accuracies to be estimated and optimal parameters of the circuit to be selected to minimise measurement error at a design stage. It is shown that measurement error is independent of the antenna reflection coefficient and the temperature of the radiometer front-end. A prototype of the single-channel miniature radiometer has 32 х 25 х 14 mm3 dimensions and USB interface communication with PC. A 28-hour run of the device has shown that it is highly stable, and a maximum drift in temperature is 0.15 ̊C. Operating frequency range was 3400-4100 MHz, supply voltage - 5V; power supply of the radiometer in measurement mode is 210 mA; time constant of the radiometer without being averaged is 0.6 sec, at the same time, standard deviation δ = 0.17 ̊С, with further averaging during 4 sec δ=0.052 ̊С, with averaging during 30 sec δ =0.017 ̊C; when there were input reflections R2=0.25, an error in measuring brightness temperature shifted by 0.2 ̊ C; with 10 ̊C variations in ambient temperature the shift was 0.15 ̊C. Introduction of self-contained power supply and wireless communication with smartphone have made it possible to use the proposed radiometer as a wearable device to monitor the temperature of internal tissues and CBT during human activities.

Test-Retest Reliability of the Timed Up and Go Test in Subjects with Parkinson's Disease: Implications for Longitudinal Assessments.

Despite the frequent use of the Timed Up and Go (TUG) test in clinical trials, evaluation of longitudinal test-retest reliability is generally lacking and still inconclusive for patients with Parkinson's disease (PD). We aimed to further investigate long-term reliability and sensitivity of the TUG test among this population. Furthermore, we explored alternative assessment strategies of the test aimed at elucidating whether the inclusion or combination of timed trials may have potential implications on outcome measure. Relative and absolute reliability of the TUG performance were obtained in forty-three subjects with PD over three timed trials in two different testing sessions separated by a two-months period. Our results reported excellent intra-session and moderate inter-session reliability coefficients. The use of different assessment strategies of the TUG was found to have an important impact on outcome measure, highlighting the averaging of several timed trials in each testing session as a recommended alternative to minimize measurement error and increase reliability in longitudinal assessments. Nevertheless, beyond acceptable reliability, poor trial-to-trial stability of the measure appears to exist, since the ranges of expected variability upon retesting were wide and the incidence of spurious statistical effects was not negligible, especially in longitudinal repeated testing. Limitations may exist in the interpretation of the TUG outputs as part of longitudinal assessments aimed at evaluating treatment effectiveness in PD population. Researchers and practitioners should be aware of these concerns to prevent possible misrepresentations of functional ability in patients for a particular intervention.

Curiosity helps: Growth in need for cognition bidirectionally predicts future reduction in anxiety and depression symptoms across 10 years

IntroductionDecreased motivational tendency to seek out, engage in, and enjoy investing in complex cognitive processes in a sustained manner (need for cognition; NFC) may be a predictor and consequence of heightened anxiety and depression symptoms (ADS). However, the majority of investigations on this topic have been cross-sectional, which hinders causal inferences. MethodsThe current study thus determined the within-person relations between NFC and ADS by using random intercept cross-lagged panel model (RI-CLPM) and bivariate dual latent change score (BLCS) approaches to separate between- and within-person effects. RI-CLPM and BLCS also present with advantages of adjusting for regression to the mean, baseline scores, autoregressive and lagged effects, and minimizing measurement error. Community-dwelling adults (n = 6750) completed the Mental Health Inventory-5 and trait-level NFC scales approximately every one year across 10 years. ResultsRI-CLPM showed that within persons, lower level of NFC predicted higher future level of ADS, and vice versa (d = -0.852 to -0.498). Likewise, BLCS demonstrated that within persons, smaller change in NFC forecasted larger subsequent increase in ADS, and conversely (d = -0.631 to -0.519). Findings remained after adjusting for socio-demographic covariates. ConclusionConsistent with theories, findings suggested that the within-person level-to-future level and change-to-future change relations among NFC and ADS were bi-directional and negative, with moderate-to-large effect sizes. Targeting NFC may treat or prevent the emergence of depression and anxiety disorders. Such efforts may include augmenting or personalizing evidence-based cognitive-behavioral therapeutic strategies for individuals with or at-risk for heightened ADS.

Laminar-Turbulent Transition Localization in Thermographic Flow Visualization by Means of Principal Component Analysis

Thermographic flow visualization is a contactless, non-invasive technique to visualize the boundary layer flow on wind turbine rotor blades, to assess the aerodynamic condition and consequently the efficiency of the entire wind turbine. In applications on wind turbines in operation, the distinguishability between the laminar and turbulent flow regime cannot be easily increased artificially and solely depends on the energy input from the sun. State-of-the-art image processing methods are able to increase the contrast slightly but are not able to reduce systematic gradients in the image or need excessive a priori knowledge. In order to cope with a low-contrast measurement condition and to increase the distinguishability between the flow regimes, an enhanced image processing by means of the feature extraction method, principal component analysis, is introduced. The image processing is applied to an image series of thermographic flow visualizations of a steady flow situation in a wind tunnel experiment on a cylinder and DU96W180 airfoil measurement object without artificially increasing the thermal contrast between the flow regimes. The resulting feature images, based on the temporal temperature fluctuations in the images, are evaluated with regard to the global distinguishability between the laminar and turbulent flow regime as well as the achievable measurement error of an automatic localization of the local flow transition between the flow regimes. By applying the principal component analysis, systematic temperature gradients within the flow regimes as well as image artefacts such as reflections are reduced, leading to an increased contrast-to-noise ratio by a factor of 7.5. Additionally, the gradient between the laminar and turbulent flow regime is increased, leading to a minimal measurement error of the laminar-turbulent transition localization. The systematic error was reduced by 4% and the random error by 5.3% of the chord length. As a result, the principal component analysis is proven to be a valuable complementary tool to the classical image processing method in flow visualizations. After noise-reducing methods such as the temporal averaging and subsequent assessment of the spatial expansion of the boundary layer flow surface, the PCA is able to increase the laminar-turbulent flow regime distinguishability and reduce the systematic and random error of the flow transition localization in applications where no artificial increase in the contrast is possible. The enhancement of contrast increases the independence from the amount of solar energy input required for a flow evaluation, and the reduced errors of the flow transition localization enables a more precise assessment of the aerodynamic condition of the rotor blade.

New Frontiers of Body Composition in Sport.

The body composition phenotype of an athlete displays the complex interaction among genotype, physiological and metabolic demands of a sport, diet, and physical training. Observational studies dominate the literature and describe the sport-specific physique characteristics (size, shape, and composition) of adult athletes by gender and levels of competition. Limited data reveal how body composition measurements can benefit an athlete. Thus, the objective is to identify purposeful measurements of body composition, notably fat and lean muscle masses, and determine their impact on the health and performance of athletes. Areas of interest include relationships among total and regional body composition measurements, muscle function, sport-specific performance, risk of injury, return to sport after injury, and identification of activity-induced fluid shifts. Discussion includes the application of specific uses of dual X-ray absorptiometry and bioelectrical impedance including an emphasis on the need to minimize measurement errors and standardize protocols, and highlights opportunities for future research. This focus on functional body composition can benefit the health and optimize the performance of an athlete.