Test Procedure Research Articles

Orthostatic testing for heart rate and heart rate variability monitoring in exercise science and practice.

Orthostatic testing, involving the transition from different body positions (e.g., from lying or sitting position to an upright or standing position), offers valuable insights into the autonomic nervous system (ANS) functioning and cardiovascular regulation reflected through complex adjustments in, e.g., measures of heart rate (HR) and heart rate variability (HRV). This narrative review explores the intricate physiological mechanisms underlying orthostatic stress responses and evaluates its significance for exercise science and sports practice. Into this matter, active orthostatic testing (e.g., active standing up) challenges the cardiovascular autonomic function in a different way than a passive tilt test. It is well documented that there is a transient reduction in blood pressure while standing up, leading to a reflex increase in HR and peripheral vasoconstriction. After that acute response systolic and diastolic blood pressures are usually slightly increased compared to supine lying body position. The ANS response to standing is initiated by instantaneous cardiac vagal withdrawal, followed by sympathetic activation and vagal reactivation over the first 25-30 heartbeats. Thus, HR increases immediately upon standing, peaking after 15-20 beats, and is less marked during passive tilting due to the lack of muscular activity. Standing also decreases vagally related HRV indices compared to the supine position. In overtrained endurance athletes, both parasympathetic and sympathetic activity are attenuated in supine and standing positions. Their response to standing is lower than in non-overtrained athletes, with a tendency for further decreased HRV as a sign of pronounced vagal withdrawal and, in some cases, decreased sympathetic excitability, indicating a potential overtraining state. However, as a significant main characteristic, it could be noted that additional pathophysiological conditions consist in a reduced responsiveness or counter-regulation of neural drive in ANS according to an excitatory stimulus, such as an orthostatic challenge. Hence, especially active orthostatic testing could provide additional information about HR(V) reactivity and recovery giving valuable insights into athletes' training status, fatigue levels, and adaptability to workload. Measuring while standing might also counteract the issue of parasympathetic saturation as a common phenomenon especially in well-trained endurance athletes. Data interpretation should be made within intra-individual data history in trend analysis accounting for inter-individual variations in acute responses during testing due to life and physical training stressors. Therefore, additional measures (e.g., psychometrical scales) are required to provide context for HR and HRV analysis interpretation. However, incidence of orthostatic intolerance should be evaluated on an individual level and must be taken into account when considering to implement orthostatic testing in specific subpopulations. Recommendations for standardized testing procedures and interpretation guidelines are developed with the overall aim of enhancing training and recovery strategies. Despite promising study findings in the above-mentioned applied fields, further research, thorough method comparison studies, and systematic reviews are needed to assess the overall perspective of orthostatic testing for training monitoring and fine-tuning of different populations in exercise science and training.

Suitability of Test Procedures for Determining the Compatibility of Seal Materials with Ionic Hydraulic Fluids

The compatibility of seal materials with the working fluid is crucial for the flawless, energy-saving, environmentally sustainable, and safe operation of any technical system. This is especially true for hydraulic systems operating under high operating pressure. The problem of materials compatibility comes into play when either a new type of seal material or a new type of fluid comes into use. The paper discusses the research findings regarding material compatibility testing of new high-tech ionic hydraulic fluids with commonly used seal materials. Due to the completely different chemical composition of these new fluids compared to the classical mineral-based oil, for these fluids, there are no standardized testing procedures. In these cases, we can only lean on the Standards that apply to classical fluids, which can lead to incorrect results. In the forefront of the paper is the discrepancy between the results obtained by the standardized test, and the test under real operating conditions. FKM, an excellent material for seals, proved to be the most suitable in the case of using ionic hydraulic fluid, according to a standardized test. However, it failed in the comparison test under real operating conditions, as the cylinder leaked. NBR seals proved to be a better solution.

Precise Tool to Target Positioning Widgets (TOTTA) in Spatial Environments: A Systematic Review.

TOTTA outlines the spatial position and rotation guidance of a real/virtual tool (TO) towards a real/virtual target (TA), which is a key task in Mixed reality applications. The task error can have critical consequences regarding safety, performance, and quality, such as surgical implantology or industrial maintenance scenarios. The TOTTA problem lacks a dedicated study and it is scattered in different domains with isolated designs. This work contributes to a systematic review of the TOTTA visual widgets, studying 70 unique designs from 24 papers. TOTTA is commonly guided by the visual overlap -an intuitive, pre-attentive "collimation" feedback- of simple shaped widgets: Box, 3D Axes, 3D Model, 2D Crosshair, Globe, Tetrahedron, Line, Plane. Our research discovers that TO and TA are often represented with the same shape. They are distinguished by topological elements (e.g., edges/vertices/faces), colors, transparency levels, and added. shapes, widget quantity, and size. Meanwhile some designs provide continuous "during manipulation feedback" relative to the distance between TO and TA by text, dynamic color, sonification, and amplified graphical visualization. Some approaches trigger discrete "TA reached feedback" such as color alteration, added sound, TA shape change, and added text. We found the lack of golden standards, including in testing procedures, as current ones are limited to partial sets with different and incomparable setups (different target configurations, avatar, background, etc.). We also found a bias in participants: right-handed, young male, non-color impaired.

A Novel Approach for Testing Fractional Cointegration in Panel Data Models with Fixed Effects

Fractional cointegration in time series data has been explored by several authors, but panel data applications have been largely neglected. A previous study of ours discovered that the Chen and Hurvich fractional cointegration test for time series was fairly robust to a moderate degree of heterogeneity across sections of the six tests considered. Therefore, this paper advances a customized version of the Chen and Hurvich methodology to detect cointegrating connections in panels with unobserved fixed effects. Specifically, we develop a test statistic that accommodates variation in the long-term cointegrating vectors and fractional cointegration parameters across observational units. The behavior of our proposed test is examined through extensive Monte Carlo experiments under various data-generating processes and circumstances. The findings reveal that our modified test performs quite well comparatively and can successfully identify fractional cointegrating relationships in panels, even in the presence of idiosyncratic disturbances unique to each cross-sectional unit. Furthermore, the proposed modified test procedure established the presence of long-run equilibrium between the exchange rate and labor wage of 36 countries’ agricultural markets.

A comparison between a proposed preconsolidated presheared flush (P.P.F) testing procedure and flush procedure to measure the drained residual strength

A comparison between a proposed preconsolidated presheared flush (P.P.F) testing procedure and flush procedure to measure the drained residual strength

Multivariate normality tests with two-step monotone missing data: a critical review with emphasis on the different methods of handling missing values

Two-step monotone missing data is a special case of missing data that attracted the attention of researchers since it not only appears frequently in applications but also since under the hypothesis of multivariate normality a unique and explicit solution to the likelihood equations exists. This importance prompted Yamada et al. [Kurtosis tests for multivariate normality with monotone incomplete data. Test. 2015;24:532–557. doi: 10.1007/s11749-014-0423-1] and Kurita and Seo [Multivariate normality test based on kurtosis with two-step monotone missing data. J Multivar Anal. 2022;188:104–824. doi: 10.1016/j.jmva.2021.104824] to propose four procedures in total for testing multivariate normality with two-step monotone missing data. The aim of this paper is twofold. On the one, to compare, for the first time, the performance of the four aforementioned multivariate normality tests via a Monte Carlo study. The second aim of the paper is to compare the performance of the four existing testing procedures with the respective procedures derived as a combination of 12 popular methods for handling incomplete data and 6 multivariate normality tests for complete data. We show that in several cases the tests proposed by Yamada et al. [Kurtosis tests for multivariate normality with monotone incomplete data. Test. 2015;24:532–557. doi: 10.1007/s11749-014-0423-1] and Kurita and Seo [Multivariate normality test based on kurtosis with two-step monotone missing data. J Multivar Anal. 2022;188:104–824. doi: 10.1016/j.jmva.2021.104824] are unable to achieve the nominal significance level. At the same time, no single procedure was found to be the most powerful in all situations of multivariate alternatives considered. As a consequence, the use of specific combinations of methods of handling missing data and testing multivariate normality with complete data is recommended.

Postural Stability in Children with Cerebral Palsy.

Background: A lack of postural control is one of the key problems in children with cerebral palsy (CP). The goals of the present study were to assess static postural stability in children with mild CP using a force platform compared to that of typically developing peers and to identify differences in static stability between children with hemiplegic and diplegic CP. Methods: This study included 45 children with hemiplegic CP and 45 children with well-functioning diplegic CP (Gross Motor Function Classification System; GMFCS scores between I and II) who were patients of local paediatric rehabilitation centres. The testing procedure included two interrelated parts: (1) the analysis of the body weight distribution and (2) the posturometric test (the centre of pressure; CoP measurements) using the force platform. Results: The results of the present study show that children with CP, compared to their TD peers, demonstrated significantly higher values for all of the analysed indexes of postural stability. The obtained results indicate differences in disorders of static postural stability between children with hemiplegic and diplegic CP. Compared to their TD peers, children with hemiplegic CP showed greater body weight asymmetry between the affected and unaffected sides of the body and greater CoP sway in the medial-lateral direction. In contrast, children with diplegic CP exhibited greater CoP displacements in the anterior-posterior direction. Conclusions: The findings of the present study show that (1) children with CP have increased static postural instability compared to their TD peers and (2) children with diplegic CP exhibit weaker mediolateral stability in standing, whereas children with hemiplegic CP show reduced anterior-posterior stability.

Natural killer (NK) cells-related gene signature reveals the immune environment heterogeneity in hepatocellular carcinoma based on single cell analysis

The early diagnosis of liver cancer is crucial for the treatment and depends on the coordinated use of several test procedures. Early diagnosis is crucial for precision therapy in the treatment of the hepatocellular carcinoma (HCC). Therefore, in this study, the NK cell-related gene prediction model was used to provide the basis for precision therapy at the gene level and a novel basis for the treatment of patients with liver cancer. Natural killer (NK) cells have innate abilities to recognize and destroy tumor cells and thus play a crucial function as the “innate counterpart” of cytotoxic T cells. The natural killer (NK) cells is well recognized as a prospective approach for tumor immunotherapy in treating patients with HCC. In this research, we used publicly available databases to collect bioinformatics data of scRNA-seq and RNA-seq from HCC patients. To determine the NK cell-related genes (NKRGs)-based risk profile for HCC, we isolated T and natural killer (NK) cells and subjected them to analysis. Uniform Manifold Approximation and Projection plots were created to show the degree of expression of each marker gene and the distribution of distinct clusters. The connection between the immunotherapy response and the NKRGs-based signature was further analyzed, and the NKRGs-based signature was established. Eventually, a nomogram was developed using the model and clinical features to precisely predict the likelihood of survival. The prognosis of HCC can be accurately predicted using the NKRGs-based prognostic signature, and thorough characterization of the NKRGs signature of HCC may help to interpret the response of HCC to immunotherapy and propose a novel tumor treatment perspective.

The Optimal Experimental Design for Exponentiated Frech’et Lifetime Products

In many manufacturing industries, the lifetime performance index CL is utilized to assess the manufacturing process performance for products following some lifetime distributions and subjecting them to progressive type I interval censoring. This paper aims to explore the sampling design required to achieve a specified level of significance and test power for products with lifetimes following the Exponentiated Frech’et distribution. Since lifetime distribution is an asymmetrical probability distribution, this investigation is related to the topic of asymmetrical probability distributions and applications in various fields. When the termination time is fixed but the number of intervals is variable, the optimal number of inspection intervals and sample sizes yielding the minimized total experimental costs are determined and tabulated. When the termination time is varying, the optimal number of inspection intervals, sample sizes, and equal interval lengths achieving the minimum total experimental costs are determined and tabulated. Optimal parameter values are displayed in tabular form for feasible applications for users. Additionally, a practical example is provided to illustrate how this sampling design can be used to collect data by using the optimal setup of parameters, followed by a testing procedure to assess the capability of the production process.

Coil Formation and Biomimetic Performance Characterization of Twisted Coiled Polymer Artificial Muscles

A biological muscle's force is nonlinearly constrained by its current state (force, length, and speed) and state history. To investigate if artificial muscles can mimic (i.e. biomimetic) the complete mechanical state spectrum of biological muscles, this study uses a novel method to characterize twisted coiled polymer actuators (TCPAs) mechanically. Thus, comprehensive and reproducible test procedures are established to verify artificial muscle biomimetics regarding stress, strain, and strain rate combinations intrinsic to biological muscle. A rheometer performs novel high‐precision mechanical characterization methods to comprehensively verify biomimetic performance. Sample twist level, torque, length, force, and temperature are controlled and measured during twist‐induced coiling, heatsetting/annealing, and mechanical testing. TCPAs are formed from linear low‐density polyethylene monofilament. Linear low‐density polyethylene (LLDPE) TCPAs generate larger stresses than biological muscle through the entire spectrum of strains—contracting more than 40%, exerting more than 0.3 MPa at rest length, and withstanding tension of 8 MPa without damage. Thus, the LLDPE TCPAs attain biological muscle performance statically, but additional tests are required to assess this dynamically. The mechanical performance of LLDPE TCPAs enables biomimetic actuation with an intelligent control and measurement system. Their high‐throughput textile manufacturability positions them for advanced biomechatronic applications—including prosthetics and exoskeletons.

Infant Mortality, Education and Financial Development: Evidence from World Level Data Using Heterogeneous Panel Granger Causality Analysis

Education and financial development are crucial factors in achieving better health, including the reduction of infant mortality. This article investigates the causal relationship between education, financial development and infant mortality rate using annual data for 81 countries for the period 1980–2015 and employing the Emirmahmutoglu and Rose (2011) Granger causality test procedure for heterogeneous mixed panels. The results show that, individually and jointly, education and financial development Granger cause infant mortality in some countries across the major regions of the world. This suggests that improved education and a developed financial system are likely to reduce the infant mortality rate. JEL Codes: C33; E25; I

Modeling the output from a commercial chemical process using regression models from survival analysis

This article is concerned with the modeling of the gas output of a commercial chemical plant using the coal sources as predictor variables. We consider the use of two models to incorporate these predictors; the Cox proportional hazards and accelerated failure time regression models. These models are chosen for their simplicity and for the ease with which the effects of explanatory variables can be interpreted. The contribution of this article lies therein that these models are used in the current context for the first time. We show, using both graphical and formal hypothesis testing procedures that these models (with a Weibull baseline distribution) fit observed gas production data well. We provide a discussion of the interpretation of the estimated model parameters and we comment on how these estimates can be of substantial practical value. The large scale of production from the chemical plant in question ensures that potential cost savings and increases in production associated with more accurate models are of great practical importance.

The effect of ankle-foot orthoses on gait characteristics in people with Charcot-Marie-Tooth disease: A systematic review and meta-analysis.

Ankle-foot orthoses (AFOs) are commonly prescribed for people with Charcot-Marie-Tooth disease (CMT) to improve gait efficiency and reduce the occurrence of tripping and falls. The aim of this study was to systematically review evidence on the effects of AFOs on gait kinematics and kinetics and postural stability/balance in people with CMT. Studies were identified from electronic databases and screened for inclusion online using Rayyan. Data from all eligible studies were extracted into a standardised Excel spreadsheet. Methodological quality was assessed using the Joanna Briggs Institute Critical Appraisal Checklists. Where available, continuous outcomes were pooled to estimate standardised mean differences in random-effects meta-analyses. A total of 15 studies were included with variable methodological quality. Sample sizes ranged from 1 to 32 with significant variability in participant characteristics, AFO designs and testing procedures. Data from eight studies were available for meta-analysis. Although AFOs impacted walking velocity, stride length, step length, cadence, ankle dorsiflexion, plantarflexion, knee and hip flexion and ankle plantarflexion and dorsiflexion moments, the effect sizes were small-to-moderate and non-significant. There were insufficient data available for pooled analyses of outcomes related to postural stability/balance. Although AFOs positively affect a number of gait and balance parameters, the small participant numbers, variability in participant characteristics, AFO designs and testing procedures adopted by the available studies resulted in the absence of statistically significant effects when data were pooled. The results from this review also highlight the importance of device customisation based on the individual needs of people with CMT and their degree of gait impairment.

Combined mechanistic and machine learning method for construction of oil reservoir permeability map consistent with well test measurements

We introduce a novel method for estimating the spatial distribution of absolute permeability in oil reservoirs, consistent with well logging and well test measurements. The primary objective is to create a permeability map, incorporating the well test interpretation results and achieving hydrodynamic similarity to the actual permeability distribution around each well. This enhancement aims to improve the accuracy of reservoir modeling outcomes in reproducing real data. We utilize Nadaraya-Watson kernel regression to parameterize the two-dimensional spatial distribution of rock permeability. The kernel regression parameters are optimized by minimizing the discrepancies between actual and predicted values of permeability at well locations, the integral permeability of the reservoir domain around each well, and skin factors. This inverse optimization problem is addressed by repeatedly solving forward problems, where an artificial neural network (ANN) predicts the integral permeability of the formation surrounding a well and skin factor. The ANN is trained on a physics-based dataset generated through a synthetic well test procedure, which includes the numerical modeling of the bottomhole pressure decline curve in a reservoir simulator and its interpretation using a semi-analytical reservoir model. The proposed method is tested on the “Egg Model”, a synthetic reservoir with significant heterogeneity due to highly permeable channels. The permeability map created by our approach demonstrates hydrodynamic similarity to the original map. Numerical reservoir simulations, corresponding to the constructed and original permeability maps, yield comparable pore pressure and water saturation distributions at the end of the simulation period. Additionally, we observe a notable match in flow rates and total volumes of produced oil, water, and injected water between simulations. The developed approach outperforms kriging in terms of numerical reservoir modeling outcomes. This research advances existing geostatistical interpolation techniques by fusing well logging and well test data to build the reservoir permeability map through an optimization framework coupled with machine learning. Unlike traditional variogram-based geostatistical simulation algorithms, our method provides a permeability distribution that is hydrodynamically similar to the actual one, enhancing initial guess in the history matching process. The novel incorporation of well test interpretation results into the permeability map represents a significant improvement over existing methods, offering an innovative approach that can benefit the petroleum industry. We also provide recommendations for further developing the proposed algorithm to account for geological realism.

Statistical Fractal Analysis in testing the Hypotheses with imprecise data

A new statistical hypothesis testing procedure using fractal analysis, incorporating the concept of lacunarity for interval population parameters when the sample data are real intervals, is introduced. The decision rules for accepting or rejecting the null and alternative hypotheses are provided, along with testing procedures and numerical examples. Additionally, the proposed tests are extended to statistical hypotheses involving fuzzy data samples with lacunarity.

Potential of near-infrared spectroscopy (NIRS) for prediction of acrylamide formation in French fries in the potato breeding process

Breeding goals of potatoes for deep-frying purposes include high starch contents, good suitability for long-term storage, and low tendency to form reducing sugars as acrylamide precursors. Due to the extensive number of samples, an accurate analysis of acrylamide in French fries and its precursors in tubers is difficult to implement in the breeding process. Therefore, this study aimed to evaluate the suitability of NIRS measurements after minimal sample processing for the prediction of reducing sugar contents in the tubers or acrylamide contents in French fries. An external validation with more than 650 samples consisting of 194 potato genotypes resulted in a prediction accuracy of 51 % for acrylamide and 76 % for reducing sugar content. RPD values of less than 1.5 for acrylamide and between 1.64 and 2.23 for reducing sugar prediction rendered low medium to medium model quality. Nevertheless, acrylamide prediction models based on NIRS measurement of mashed tubers categorised over 80 % of unknown samples correctly as being below or above the European threshold value, indicating suitability as rapid test procedure in the breeding process.

Stress and Temperature Dependence of Irradiation Creep in Zircaloy-4 Studied Using Proton Irradiation

This paper describes a series of experiments conducted to investigate the in-situ irradiation creep behavior of Zircaloy-4 using proton irradiations as a surrogate to neutrons. The first series of experiments investigated the impact of the initial irradiation-induced defect evolution during the 0 – 0.1 dpa regime on the subsequent in-situ steady-state behavior derived from experimentation. These experiments were conducted at a constant applied load of 85 MPa, a constant damage rate of 1.58 × 10−6 dpa/s, and were repeated at both 250°C and 350°C. We also examined the use of a ‘conditioning-irradiation’ step prior to the creep tests on the results derived from subsequent in-situ proton irradiation creep experiments. By extension, we aim to further develop and refine optimum testing procedures when using proton irradiations to investigate the in-situ creep behavior of nuclear materials. The second stage of in-situ proton irradiation experiments were conducted on two Recrystallized (RX) Zircaloy-4 samples in order to investigate the temperature and stress dependence of irradiation creep. One sample was held at a constant load while the temperature was varied in the range of 275 – 350°C, and the other was held at a constant temperature while stress was varied in the range of 65 – 105 MPa. The associated strains and creep rates were measured at each interval and used to determine an activation temperature of 5000±1700 K and a stress sensitivity exponent of 4.3±0.8 for RX Zr-4 over the given temperature and stress ranges. A discussion of potential deformation mechanisms based on competition between bulk diffusion through the lattice and point defect diffusion enabling dislocation climb and glide is given: the relatively high stress dependence suggested the latter is more likely however further investigations will be required to improve the mechanistic understanding. The results presented in this manuscript, including activation temperature, stress sensitivity, and associated creep rates, determined through proton irradiation investigations are closely comparable to those determined from neutron irradiation experiments found in the literature for similar zirconium alloys at similar temperatures and stresses. Coupled with the primary-secondary creep behavior investigations presented, this demonstrates the usefulness of this approach to estimate neutron-irradiation equivalent creep behavior using in-situ proton irradiation.

Research on Silage Corn Forage Quality Grading Based on Hyperspectroscopy

Corn silage is the main feed in the diet of dairy cows and other ruminant livestock. Silage corn feed is very susceptible to spoilage and corruption due to the influence of aerobic secondary fermentation during the silage process. At present, silage quality testing of corn feed mainly relies on the combination of sensory evaluation and laboratory measurement. The sensory review method is difficult to achieve precision and objectivity, while the laboratory determination method has problems such as cumbersome testing procedures, time-consuming, high cost, and damage to samples. In this study, the external sensory quality grading model for different qualities of silage corn feed was established using hyperspectral data. To explore the feasibility of using hyperspectral data for external sensory quality grading of corn silage, a hyperspectral system was used to collect spectral data of 200 corn silage samples in the 380–1004 nm band, and the samples were classified into four grades: excellent, fair, medium, and spoiled according to the German Agricultural Association (DLG) standard for sensory evaluation of silage samples. Three algorithms were used to preprocess the fodder hyperspectral data, including multiplicative scatter correction (MSC), standard normal variate (SNV), and S–G convolutional smoothing. To reduce the redundancy of the spectral data, variable combination population analysis (VCPA) and competitive adaptive reweighted sampling (CARS) were used for feature wavelength selection, and linear discriminant analysis (LDA) algorithm was used for data dimensionality reduction, constructing random forest classification (RFC), convolutional neural networks (CNN) and support vector machines (SVM) models. The best classification model was derived based on the comparison of the model results. The results show that SNV-LDA-SVM is the optimal algorithm combination, where the accuracy of the calibration set is 99.375% and the accuracy of the prediction set is 100%. In summary, combined with hyperspectral technology, the constructed model can realize the accurate discrimination of the external sensory quality of silage corn feed, which provides a reliable and effective new non-destructive testing method for silage corn feed quality detection.

Are made and missed different? An analysis of field goal attempts of professional basketball players via depth based testing procedure

Are made and missed different? An analysis of field goal attempts of professional basketball players via depth based testing procedure

Inference about a Common Mean Vector from Several Independent Multinormal Populations with Unequal and Unknown Dispersion Matrices

This paper addresses the problem of making inferences about a common mean vector from several independent multivariate normal populations with unknown and unequal dispersion matrices. We propose an unbiased estimator of the common mean vector, along with its asymptotic estimated variance, which can be used to test hypotheses and construct confidence ellipsoids, both of which are valid for large samples. Additionally, we discuss an approximate method based on generalized p-values. The paper also presents exact test procedures and methods for constructing exact confidence sets for the common mean vector, with a comparison of the local power of these exact tests. The performance of the proposed methods is demonstrated through a simulation study and an application to data from the Current Population Survey (CPS) Annual Social and Economic (ASEC) Supplement 2021 conducted by the U.S. Census Bureau for the Bureau of Labor Statistics.