bluuebunny/crossref_metadata_2025_split huggingface dataset:
Wrist Motion Assessment in Tennis Players using Three-Dimensional Motion Capture and Dynamic Electromyography
Authors: Israel Jacqueline S. , Loushin Stacy R. , Tetzloff Sabine U. , Ellenbecker Todd , Kaufman Kenton R. , Kakar Sanjeev 
Published: December 2023

Abstract
Background Tennis players often present with ulnar-sided wrist pain, which may reflect repetitive stress and/or faulty mechanics. There is a role for investigating the biomechanics of tennis strokes and how they may relate to wrist pathology. The purpose of this study was to investigate whether three-dimensional motion capture technology and dynamic electromyography (EMG), when used to study groundstrokes in elite junior tennis players, reveals patterns of upper extremity motion that may correlate with the development of clinically relevant pathology.
Case Description Three-dimensional kinematic and EMG data were collected from two United States Tennis Association-ranked adolescent tennis players during groundstrokes. There were several observed differences in the two players' degree and timing of pronation/supination, ulnar/radial deviation, and flexion/extension during their strokes.
Clinical Significance Advanced motion capture technology facilitates a nuanced understanding of complex movements involved in groundstroke production. This methodology may be useful for identifying athletes who are at risk for injury and guiding rehabilitation for players experiencing pain.
Level of Evidence IV
Constituting sources is a matter of correlational claims
Authors: Pala Kiran 
Published: December 2023

AbstractThis essay delves into the essentialities of object-giving sources within the formulation of epistemic objectivity. It explores the relationship between objectivity and intentional states, particularly in the context of immediate and transcendent experiences. A key focus of this paradigm is the examination of inferences and how they are held in X’s intentional processes. These claims about inferences contribute to the perception of objectivity by highlighting the epistemological transitions of things that occur in the constitutive ideation. Additionally, the activity within X’s episteme leads to significant articulations that reflect a structural realism of experiences. The essay also introduces a convention of the experiential-intentional process so that the causality manipulations could be avoided by the precents of sources of ideation. In this instance, the central niche is occupied by transcendental reflections of intentionality, which are fundamentally founded on experiences and objectivity, and they possess a distinct rhetorical quality. They manifest as acts, propositional forms, and constituents, all of which contribute to the understanding and justification of objectivity. To establish such a framework that upholds objectivity, certain prerequisites must be met. Firstly, the framework must possess justificational resources that prevent causality manipulations. Secondly, pre-reflective sources should not inter-define causality in epistemic circumstances, although this does not exclude the emergence of causal relations, and thus this approach offers a correlational explanation. Lastly, transcendental reflections should remain compatible with the experiential-intentional process, allowing for the accommodation of subjectivity in the justification of objectivity.
Health literacy, religiosity, and political identification as predictors of vaccination conspiracy beliefs: a test of the deficit and contextual models
Authors: Pavić Željko , Kovačević Emma , Šuljok Adrijana 
Published: December 2023

AbstractThe primary focus of this paper is to investigate the influence of science literacy, particularly health literacy, on vaccine-specific conspiracy beliefs, within the broader context of vaccine hesitancy. The authors tested deficit (scientific literacy shapes science attitudes) and contextual models (contextual variables exert direct influence and influence the connection between literacy and science attitudes) in a survey research study (N = 729) in Croatia. The analytical approach included structural equation modeling with vaccination conspiracy beliefs as the outcome variable and health literacy, religiosity, and political identification as predictors. The results showed that lower health literacy and higher religiosity were related to higher vaccination conspiracy beliefs, which was not the case for political identification. In addition, the moderating effect of religiosity on the relationship between health literacy and conspiracy beliefs was confirmed. In contrast, the moderating effect of political identification was not confirmed, thus partially confirming the stronger version of the contextual model. The authors comparatively discuss the results by evoking specific socio-political characteristics of Croatian society as well as the reactions of political and religious organizations to the COVID-19 pandemic.
Influence of coaxial cable resistance on impedance measurements at low frequency and guidelines for phase determination of ac electrical signals
Authors: Chenaud Boris , Hernández Carlos , Delgard Adrien , Chaubet Christophe 
Published: November 2023

We present an experimental study on ac measurements at low frequencies (below 1 MHz) when the coaxial cables used for the measurement are resistive, as in cryogenic conditions. More precisely, we are interested in admittance or impedance measurements and the accurate determination of the phase. Our experiments were completed using an auto-balancing bridge impedance analyzer and various standard coaxial cables, as well as their serial combinations. We characterize the experimental setup, and then, we analyze and measure the phase shift introduced in impedance measurements by lead resistance. Using basic equations for electrical signal propagation in coaxial cables, we calculate phase shift in the whole frequency range and explain our data in the low frequency limit of our model. We propose a quantitative criterion to determine whether the experimental context is appropriate. If not, we show that by using an original calibration procedure, the imaginary part can be accurately recovered, avoiding artifacts. The calibration procedure can be applied to any ac voltage or current measurement, whatever the detection technique is, with known accuracy.
Electrical microparticle acceleration by high-speed membrane deformation
Authors: Ichihara D. , Takata R. 
Published: December 2023

In this study, we conducted experiments to explore the potential of a low-power exploding foil initiator for accelerating microparticles through high-speed membrane deformation. This involved the use of a conductive layer with a conversion section known as a “bridge,” which was positioned between the substrate and the cover layer. The application of pulsed electrical energy led to Joule heating at the bridge, while the vaporized gas generated impulsive loading, resulting in the deformation of the cover layer. According to the principles of energy conservation, 8.7% of the electrical input energy was converted into kinetic energy for the membrane. This deformation process achieved a velocity of 800 m/s, with a corresponding strain rate of 1.6 × 107 s−1. The applied impulse predominantly induced extension stresses in the cover layer rather than bending stresses. Under these conditions, a 17.5-µm radius polylactic acid bead was propelled and subsequently captured by a silicone gel layer, resembling human dermic skin. Considering factors such as particle clustering and deceleration due to air resistance during supersonic flight, assuming a normal incident angle, it was estimated that approximately half of the ejected particles could reach the human dermic layer, located 200 µm beneath the skin surface. These findings suggest that pulse discharge is a promising method for inducing high-speed membrane deformation, and the electrical microparticle accelerator holds potential for applications in needle-free drug delivery.
Simulation for the test mass charging rate in the Tianqin orbit
Authors: Lei Chi , Su Wei , Hong Wei , Li Honggang , Zhao Menghao , Chen Bingxue , Chu Liangyu , Li Qingqing , Bai Yanzheng , Zhou Zebing 
Published: November 2023

Abstract
For the purpose of detecting gravitational waves from space, high-energy particles will infiltrate the satellite’s structure and accumulate charges on the test mass, consequently diminishing detection performance. Present investigations into the charging rate of the test mass typically rely on the particle distribution of Earth orbit. However, the influence of the Earth’s magnetosphere needs to be considered for the Tianqin detector because of its geocentric orbit. In this paper, artificial neural network is used to fuse satellite data and the galactic cosmic rays model to give the distribution of high-energy particles in the Tianqin orbit. And then, the charging rate is estimated by Monte Carlo simulation. The simulation results show that the flux of hundreds of MeV particles is a little higher than that in Earth orbit, which lead to

3
−
4

e s−1 higher than LISA, i.e. the charging rate of approximately 43 e s−1 during periods of solar minimum and 19 e s−1 during periods of solar maximum. These findings hold substantial implications for guiding the design of the charge management system.
Anti-reflection metasurface synergizing plasma and lattice modes: an efficient route to wideband electromagnetic transparency under extreme angles
Authors: Li Tiefu , Ma Jiachen , Chu Zuntian , Yan Mingbao , Jiang Jinming , Wang Jiafu , Feng Cunqian , Han Yajuan , Qu Shaobo 
Published: November 2023

Abstract
All-angle wideband electromagnetic (EM) transparency for dual polarizations is desired for many practical applications. Conventionally, surface-mount anti-reflection materials or films are usually used to reduce the reflection and thus enhance transparency. In this paper, we propose to achieve wideband EM transparency under extreme angles for both TE- and TM-polarizations using embedded anti-reflection metasurface. The metasurface is composed of a pair of long and short metallic strips, which can introduce both plasma and lattice modes into the original half-wave wall. The plasma mode can create an angle-stable transmission peak at a lower frequency while the lattice mode renders a transmission peak under extreme angles at a higher frequency due to scattering cancellation between short strips and the substrate. By synergizing the plasma, half-wave, and lattice modes consecutively, wide-band transparency can be achieved under extreme angles for TE polarization. Due to the anisotropy of the metasurface, wideband transparency under TM-polarization is maintained. This finally enables us to obtain wideband EM transparency for dual polarizations under extreme angles. More importantly, the metasurface can also be customized to operate best under any given incident angle. Prototypes were designed, fabricated, and measured. Both the simulation and experiment results verify our method. This work provides an efficient route to wideband EM transparency under extreme angles and may find wide applications in communication, radar, and others.
Deep particle diffusometry: convolutional neural networks for particle diffusometry in the presence of flow and thermal gradients
Authors: Sardana Pranshul , Wereley Steven T 
Published: November 2023

Abstract
Diffusion coefficient measurement is a helpful tool in revealing various properties of a fluid such as viscosity and temperature. However, determining the diffusion coefficient often requires specialized equipment. Particle-based techniques allow the use of conventional cameras to determine flow properties without any specialized measurement devices. However, the performance of existing methods such as single-particle and correlation-based measurements degrade drastically in the presence of real-world scenarios such as flow and thermal gradients. This work introduces a new method of estimating diffusion coefficient in the presence of flow and thermal gradients named deep particle diffusometry (DPD). The technique uses temporally averaged particle images as inputs and uses convolutional neural networks to predict the underlying diffusion coefficient. The results show that a high fit coefficient R
2 value of 0.99 was achieved with no or known fluid flow conditions and an R
2 value of 0.95 was achieved if the fluid had an arbitrary flow. Next, the generalization ability of the network was shown by training the DPD models on no gradient datasets and testing on datasets with a diffusion coefficient gradient. The networks maintained comparably high R
2 values of 0.96. Next, the DPD models were tested against three conventional methods on various simulated datasets, showing their superior performance in situations where an arbitrary flow was present along with diffusion. Finally, the networks were tested on experimental data and the predictions were compared with conventional methods which resulted in R2 values of 0.97 under the no-flow condition. The results show that the proposed method provides performance similar to existing methods on datasets with no flow or with a known flow and can surpass their performance on datasets that have an arbitrary flow.
Time-resolved electrostatic force microscopy under base-bias-level control
Authors: Sato Jo , Ishibashi Ryota , Takahashi Takuji 
Published: November 2023

Abstract
We propose a base-bias-level control method, in which the contact potential difference is always compensated in a similar way to Kelvin probe force microscopy, applicable to time-resolved electrostatic force microscopy using the pump–probe method. We experimentally acquired temporal waveforms of the electrostatic force signal on two SiO2/n-type Si samples, one of which was as-grown and the other was treated by forming gas annealing. Consequently, the effectiveness of the proposed method was confirmed.
Embedded measurement of process monitoring in melt-cast explosive based on distributed optical fiber sensing and numerical verification
Authors: Deng Pengfei , Sun Jie , Guo Penglin , Fu Tao 
Published: November 2023

Abstract
The solidification sequence during the solidification of fusion-cast explosives is an important parameter for the optimization of the manufacturing process, which can be analyzed by using numerical simulation experiments. However, the numerical simulations are not totally reliable due to the inherent errors in the algorithms and parameters. To address this issue, a measurement method is proposed to monitor the solidification process based on the embedded method of distributed fiber optic sensing. And a method is developed to identify the solid–liquid phase change interface region, which can be effectively demodulated and analyzed for sensing data. The experimental results were verified by using numerical simulations based on casting simulation software and compared. It can be found that the total solidification time and pattern of both are relatively consistent. However, some of the solidification characteristics in the numerical simulation are lack of precision due to the inaccuracy of the heat transfer parameters.
Experimental study on acoustic signal characteristic analysis and time delay estimation of pipeline leakage in boilers
Authors: Luo Pei , Yang Wenkai , Sun Mingyang , Shen Guoqing , Zhang Shiping 
Published: November 2023

Abstract
Acoustic signal detection technology has significant advantages in detecting the leakage and bursting of heat exchange pipes in boilers. To address the current lack of sound signal data for steam medium leakages and the problem of large errors in the complex sound field environment of power plants, we performed an innovative experimental comparative analysis of leakage acoustic signals under a dual medium of compressed air and steam to provide a reference for detecting leakage acoustic signals. During the experiment, the time and frequency domains were analyzed by changing the pressure of the leakage pipeline and aperture of the leakage hole, and the spectrogram and power spectrum of the leakage acoustic signal were obtained using fast Fourier transform and autocorrelation analysis. The results showed that the signal value of the leakage medium increased with increasing pipeline pressure and leakage aperture and that the energy of the steam leakage acoustic signal was greater than that of compressed air under the same pressure and aperture because of its larger specific heat capacity. In addition, the complete empirical mode decomposition of adaptive noise (CEEMDAN) algorithm was introduced into the denoising decomposition of the leakage sound signal in the furnace, and the average error of the time delay value of the leakage acoustic signal calculated using the CEEMDAN algorithm was observed to be within 5%.
Is muscle localized phase angle an indicator of muscle power and strength in young women?
Authors: Oliveira Núbia Maria , Fukuoka Aryanne Hydeko , Matias Catarina Nunes , Guerra-Júnior Gil , Gonçalves Ezequiel Moreira 
Published: November 2023

Abstract

Objective. This study aimed to investigate the capacity of the bioelectrical muscle localized phase angle (ML-PhA) as an indicator of muscle power and strength compared to whole body PhA (WB-PhA). Approach. This study assessed 30 young women (22.1 ± 3.2 years) for muscle power and strength using the Wingate test and isokinetic dynamometer, respectively. Bioimpedance analysis at 50 kHz was employed to assess WB-PhA and ML-PhA. Lean soft tissue (LST) and fat mass (FM) were quantified using dual x-ray absorptiometry. Performance values were stratified into tertiles for comparisons. Regression and mediation analysis were used to test WB-PhA and ML-PhA as performance predictors. Main results. Women in the second tertile of maximum muscle power demonstrated higher ML-PhA values than those in first tertile (13.6° ± 1.5° versus 11.5° ± 1.5°, p = 0.031). WB-PhA was a predictor of maximum muscle power even after adjusting for LST and FM (β = 0.40, p = 0.039). ML-PhA alone predicted average muscle power (β = 0.47, p = 0.008). FM percentage was negatively related to ML-PhA and average muscle power, and it mediated their relationship (b = 0.14; bias-corrected and accelerated 95% confidence interval: 0.007–0.269). Significance. PhA values among tertiles demonstrated no differences and no correlation for strength variables. The results revealed that both WB and ML-PhA may be markers of muscle power in active young women.
Cross-subject emotion recognition using hierarchical feature optimization and support vector machine with multi-kernel collaboration
Authors: Pan Lizheng , Tang Ziqin , Wang Shunchao , Song Aiguo 
Published: November 2023

Abstract

Objective. Due to individual differences, it is greatly challenging to realize the multiple types of emotion identification across subjects. Approach. In this research, a hierarchical feature optimization method is proposed in order to represent emotional states effectively based on peripheral physiological signals. Firstly, sparse learning combined with binary search is employed to achieve feature selection of single signals. Then an improved fast correlation-based filter is proposed to implement fusion optimization of multi-channel signal features. Aiming at overcoming the limitations of the support vector machine (SVM), which uses a single kernel function to make decisions, the multi-kernel function collaboration strategy is proposed to improve the classification performance of SVM. Main results. The effectiveness of the proposed method is verified on the DEAP dataset. Experimental results show that the proposed method presents a competitive performance for four cross-subject types of emotion identification with an accuracy of 84% (group 1) and 85.07% (group 2). Significance. The proposed model with hierarchical feature optimization and SVM with multi-kernel function collaboration demonstrates superior emotion recognition accuracy compared to state-of-the-art techniques. In addition, the analysis based on DEAP dataset composition characteristics presents a novel perspective to explore the emotion recognition issue more objectively and comprehensively.
Availability and reactivity of N2(v) for NH3 synthesis by plasma catalysis
Authors: Bayer Brian N , Raskar Sai , Adamovich Igor V , Bruggeman Peter J , Bhan Aditya 
Published: November 2023

Abstract
Production of vibrationally excited N2 (N2(v)) in atmospheric pressure nonthermal plasma and loss of N2(v) by gas-phase reactions and reactions on catalytic surfaces are analyzed to examine the role of N2(v) in NH3 formation by plasma catalysis. Vibrational state-to-state kinetic models complemented with molecular beam mass spectrometry (MBMS) measurements demonstrate that N2(v> 0) is produced with densities 100× greater than the density of N radicals by a radiofrequency atmospheric pressure plasma jet. The experimentally measured loss of N2(v) corresponds with a state-to-state kinetic model that describes loss of N2(v) by surface-mediated vibrational relaxation without consideration of reactions that convert N2(v) to NH3 over the catalyst surface. Rate constants for vibrational relaxation of N2(v) on catalyst surfaces exceed upper bounds on proposed rate constants for NH3 formation reactions from N2(v) over Fe when v < 9, Ni when v < 18, and Ag when v < 39, which indicates that only higher vibrational levels can possibly contribute to catalytic NH3 formation faster than they undergo vibrational relaxation on the surface. Densities of N2(v> 8), vibrational levels that can possibly react over Fe to form NH3 faster than they undergo vibrational relaxation, are less than or similar to N densities at the inlet of the catalyst bed and measured NH3 formation for the investigated conditions in this work, while densities of N2(v> 17) and N2(v> 38) are orders of magnitude below the N density at the inlet of the catalyst bed and the measured NH3 formation. The loss of N2(v) by vibrational relaxation on the surface limits the ability of N2(v) to contribute to catalytic NH3 formation and explains why N2(v) does not produce NH3 in quantities that are comparable to NH3 formation from N even though N2(v > 0) is more abundantly produced by the plasma.
Advancements in wearable ammonia sensors using polypyrrole/MWCNT coated yarn
Authors: Maity Debasis , Rajendra Kumar Ramasamy Thangavelu 
Published: November 2023

Abstract
In this study, we utilized a dip coating method to modify insulating yarn with polypyrrole and multiwall carbon nanotubes (MWCNTs) to convert it into a conductive yarn. The resulting fabricated conducting yarn underwent thorough characterization through scanning electron microscope, x-ray diffraction pattern, and thermal gravimetric analysis. Subsequently, we examined the ammonia sensing properties of the modified yarn at various stages of its development. Our findings revealed that the combination of MWCNTs followed by polypyrrole modification significantly enhanced the ammonia sensing capabilities compared to using MWCNTs or polypyrrole-coated yarn individually. Specifically, the MWCNTs followed by polypyrrole modified yarn demonstrated an excellent sensing response, remarkable repeatability (up to 24 continuous cycles), quick response time (11 ± 2 s), and recovery time (34 ± 5 s). Additionally, the sensor exhibited good linearity in detecting ammonia vapor concentrations within the range of 20–100 ppm. We also assessed the sensor’s performance with diverse vapors at room temperature, revealing its high selectivity for ammonia. Furthermore, the sensor’s response correlated linearly with yarn length. Remarkably, it demonstrated minimal sensitivity to humidity and exceptional stability over fifty days. These results have the potential to lead to the development of wearable room temperature ammonia sensors, suitable for use in agricultural and industrial chemistry, as well as in environmental, automotive, and medical applications.