Dynamic Measurements Research Articles

Unveiling Magnetic States in Nanotubes: Insights from Remanent Ferromagnetic Resonance Spectroscopy

Abstract Magnetic nanotubes have garnered immense attention for their potential in high-density magnetic memory, owing to their stable flux closure configuration and fast, reproducible reversal processes. However, characterizing their magnetic configuration through straightforward methodologies remains a challenge in both scope and detail. Here, we elucidate the magnetic state details using Remanence Field Ferromagnetic Resonance Spectroscopy (RFMR) for arrays of electrodeposited nanotubes. Micromagnetic simulations revealed distinct spin configurations while coming from saturation, including the edge vortex, onion, uniform and curling states, with chirality variations depending on the preparation field direction. We identified individual spin configurations, as depicted in our micromagnetic simulations, through careful measurements of the RFMR spectra starting from both positive and negative saturation. The Observations revealed opposite RFMR spectra, indicating opposite magnetic spin configurations after removing the positive and negative saturating fields when the magnetic field was applied along (θH=00) and perpendicular (θH=900 )to the nanotube axis. We observed a mixture of the non-uniform curling states with the end vortex state (onion-like curling state) at the end of the nanotubes for the (θH=00 (900 ) ) and uniform magnetization states in the middle of the nanotubes for the θH=00 configuration. Dynamic measurements in presence of the bias field, coupled with RFMR spectra analysis, provided insights into the evolution of individual modes. Additionally, our FMR analysis indicates nucleation within the edge vortex state, which was further corroborated by micromagnetic analysis and substantiated with First Order Reversal Curve (FORC) measurements.

Weighted past and paired dynamic varentropy measures, their properties, usefulness and inferences

We introduce two uncertainty measures, say weighted past varentropy (WPVE) and weighted paired dynamic varentropy (WPDVE). Several properties of these proposed measures, including their effect under the monotone transformations are studied. An upper bound of the WPVE using the weighted past Shannon entropy and a lower bound of the WPVE are obtained. Further, the WPVE is studied for the proportional reversed hazard rate (PRHR) models. Upper and lower bounds of the WPDVE are derived. In addition, the non-parametric kernel estimates of the WPVE and WPDVE are proposed. Furthermore, the maximum likelihood estimation technique is employed to estimate WPVE and WPDVE for an exponential population. A numerical simulation is provided to observe the behaviour of the proposed estimates. A real data set is analysed, and then the estimated values of WPVE are obtained. Based on the bootstrap samples generated from the real data set, the performance of the non-parametric and parametric estimators of the WPVE and WPDVE is compared in terms of the absolute bias and mean squared error (MSE). Finally, we have reported an application of WPVE. Abbreviations RV: Random variable; PDF: Probability density function; IC: Information content; SE: Shannon entropy; VE: Varentropy; MSE: Mean squared error; RVE: Residual varentropy; CDF: Cumulative distribution function; PVE: Past varentropy; WVE: Weighted varentropy; WPSE: Weighted past Shannon entropy; WRVE: Weighted residual varentropy; WPVE: Weighted past varentropy; WPRE: Weighted past Rényi entropy; PRHR: Proportional reversed hazard rate; WPDE: Weighted paired dynamic entropy; WPDVE: Weighted paired dynamic varentropy entropy; AB: Absolute bias; CRHR: Cumulative reversed hazard rate; VPL: Variance past lifetime; MPL: Mean past lifetime; MRL: Mean residual lifetime; VRL: Variance residual lifetime; GMB-II: Gumbel-II; GXE: Generalised X-exponential; EXP: Exponential; lnL: Log-likelihood criterion; AIC: Akaikes information criterion; BIC: Bayesian information criterion; MLE: Maximum likelihood estimate

Ultraviolet Photoresponse and Electroluminescence of Exfoliated Ga2O3 Flake on p-type GaN

Abstract β-phase Ga2O3 (β-Ga2O3) is a promising candidate for deep ultraviolet (UV) solar-blind photodetector due to its large bandgap of 4.9 eV. A high crystal quality two-dimensional β-Ga2O3 flake on p-type GaN (p-GaN) surface was formed using a facile mechanical exfoliation and transfer method, and the heterojunction photodiode consisting of an n-type β-Ga2O3 flake on a p-type GaN substrate was fabricated. The device exhibited a distinctive rectifying current-voltage (I-V) characteristics with a rectification ratio of 4.0×105 at ±2 V. The photodetector responded to both 365 nm and 254 nm UV light irradiation with a photocurrent to dark current ratio of 5.64×10⁵% for 365 nm and 3.38×10⁵% for 254 nm UV. The rise and decay time constants for 365 nm and 254 nm deep UV exposure were obtained through dynamic time-dependent photocurrent measurements. In addition, electroluminescence of the p-type GaN/n-type Ga2O3 heterojunction diode was observed under high forward bias condition.

Abnormal Brain State in Major Depressive Disorder: A Resting-State Magnetic Resonance Study.

Background: Respective changes in resting-state linear and nonlinear measures in major depressive disorder (MDD) have been reported. However, few studies have used integrated measures of linear and nonlinear brain dynamics to explore the pathological mechanisms underlying MDD. Method: Forty-two patients with MDD and 42 sex- and age-matched healthy controls (HC) underwent resting-state functional magnetic resonance imaging to calculate multiscale entropy (MSE) and regional homogeneity (ReHo). The MSE-ReHo coupling of the whole gray matter and the MSE/ReHo ratio (the complexity of intensity homogeneity per unit time series) of each voxel were compared between the two groups. To evaluate the discriminative capacity of ratio features between patients with MDD and HC, we employed the support vector machine (SVM) learning method. Results: We observed that patients with MDD displayed increased MSE/ReHo ratio mainly in the orbitofrontal cortex, sensorimotor areas, and visual cortex. Moreover, significant correlations were observed between MSE/ReHo ratio and clinical indicators, including depression severity and cognitive function tests. The SVM model demonstrated high accuracy in differentiating patients with MDD from HC, highlighting the potential of the MSE/ReHo ratio as a diagnostic and prognostic tool. Conclusions: The aberrant MSE/ReHo ratio implicated the underlying mechanisms of depressive symptoms and cognitive impairment in patients with MDD. It may represent a critical state of the brain region, reflecting the degree of chaos and order in the brain region. Integrating linear and nonlinear combinations of brain signals holds promise for diagnosing psychiatric disorders.

Dynamic 3D Measurement Based on Camera-Pixel Mismatch Correction and Hilbert Transform

In three-dimensional (3D) measurement, the motion of objects inevitably introduces errors, posing significant challenges to high-precision 3D reconstruction. Most existing algorithms for compensating motion-induced phase errors are tailored for object motion along the camera’s principal axis (Z direction), limiting their applicability in real-world scenarios where objects often experience complex combined motions in the X/Y and Z directions. To address these challenges, we propose a universal motion error compensation algorithm that effectively corrects both pixel mismatch and phase-shift errors, ensuring accurate 3D measurements under dynamic conditions. The method involves two key steps: first, pixel mismatch errors in the camera subsystem are corrected using adjacent coarse 3D point cloud data, aligning the captured data with the actual spatial geometry. Subsequently, motion-induced phase errors, observed as sinusoidal waveforms with a frequency twice that of the projection fringe pattern, are eliminated by applying the Hilbert transform to shift the fringes by π/2. Unlike conventional approaches that address these errors separately, our method provides a systematic solution by simultaneously compensating for camera-pixel mismatch and phase-shift errors within the 3D coordinate space. This integrated approach enhances the reliability and precision of 3D reconstruction, particularly in scenarios with dynamic and multidirectional object motions. The algorithm has been experimentally validated, demonstrating its robustness and broad applicability in fields such as industrial inspection, biomedical imaging, and real-time robotics. By addressing longstanding challenges in dynamic 3D measurement, our method represents a significant advancement in achieving high-accuracy reconstructions under complex motion environments.

Monitoring Dynamic Conformations of a Single Fluorescent Molecule Inside a Protein Cavity.

Fluorescence nanoscopy and single-molecule methods are entering the realm of structural biology, breaking new ground for dynamic structural measurements at room temperature and liquid environments. Here, single-molecule localization microscopy, polarization-dependent single-molecule excitation, and protein engineering are combined to determine the orientation of a fluorophore forming hydrogen bonds inside a protein cavity. The observed conformations are in good agreement with molecular dynamics simulations, enabling a new, more realistic interplay between experiments and simulations to identify stable conformations and the key interactions involved. Furthermore, jumps between conformations can be monitored with a precision of 3° and a time resolution of a few seconds, confirming the potential of this methodology for retrieving dynamic structural information of nanoscopic biological systems under physiologically compatible conditions.

Super-resolution ultrasound imaging of ischaemia flow: An in silico study.

Super-resolution ultrasound (SRU) is a new ultrasound imaging mode that promises to facilitate the detection of microvascular disease by providing new vascular bio-markers that are directly linked to microvascular pathophysiology, thereby augmenting current knowledge and potentially enabling new treatment. Such a capability can be developed through thorough understanding as articulated by means of mathematical models. In this study, a 2D numerical flow model is adopted for generating flow adaptation in response to ischaemia, in order to determine the ability of SRU to register the resulting flow perturbations. The flow model results demonstrate that variations in flow behaviour in response to locally induced ischaemia can be significant throughout the entire vascular bed. Measured velocities have variations that are dependent on the location of ischaemia, with median values ranging between 2-7 mms-1. Moreover, the distinction between healthy and ischaemic networks are recorded accurately in the SRU results showing excellent agreement between SRU maps and the model. Up to 7-fold spatial resolution improvement to conventional contrast ultrasound was achieved in microbubble localisation while the detection precision and recall was consistently above 98%. The microbubble tracking precision was of a similar accuracy, whereas the recall was reduced (77%) under varying ischaemic impacted flow. Further, regions with velocities up to 30 mms-1 are in excellent agreement with SRU maps, while at regions that include a proportion of higher velocities, the median velocity values are within 1.28%-3.32% of the ground-truth. In conclusion, SRU is a highly promising methodology for the direct measurement of microvascular flow dynamics and may provide a valuable tool for the understanding and subsequent modelling of behaviour in the vascular bed.

Effect of Composition and Phase Separation on Structure and Luminescence Properties of Tb3+ Doped Borosilicate Glasses

Two borosilicate glass series with different Na2O/B2O3 ratio and different phase separation probability have been doped with largely different concentrations of Tb3+. The addition of rare earth elements increases the phase separation tendency of borosilicate glasses, allowing to study the process in detail. Phase separation structures were also modified by annealing the glass samples at different temperatures and times. The occurring effects were studied by high resolution transmission electron microscopy (TEM) as well as with static and dynamic luminescence measurements. Strong effects of glass composition, doping concentration, and annealing on the intensity and shape of the luminescence spectra and the time-resolved luminescence are found and explained.

Dynamical measures of developing neuroelectric fields in emerging consciousness

Dynamical measures of developing neuroelectric fields in emerging consciousness

Unknown input uncertainty calculation using virtual input shaping and interval analysis

A triaxial accelerometer has been developed to measure and determine the uncertainty associated with unknown vibrations disturbing a small force metrology experiment. However, methodological shortcomings remain regarding the calculation of uncertainty for dynamic measurements. Therefore, this paper proposes an alternative framework to estimate the uncertainty of specific dynamic quantities of interest with a nonlinear and uncertain measuring system. The novelty of the proposed methodology lies in the use of an accurate and equivalent representation of the physical system based on a linear model, combined with an additive virtual input describing all the unknown unmodeled dynamics. Measurement models are defined considering measurement biases, and uncertainty is calculated using interval analysis tools. Such tools allow determining the feasible values of the quantities of interest to be estimated. The innovative aspects of the proposed approach are fully illustrated in simulation on the triaxial accelerometer, comparing linear and nonlinear measurement models in passive mode.

Does digital innovation improve carbon productivity? A new perspective based on industrial upgrading

ABSTRACT In the era of digital economy, digital innovation is an important path to promote the improvement of carbon productivity in developing countries. Based on China’s experience, this paper systematically constructs a digital innovation measurement system, and takes the heterogeneity threshold of industrial transformation upgrading as an entry point, and adopts a non-linear dynamic panel measurement model to empirically explore the mechanism of industrial transformation upgrading threshold of digital innovation on regional carbon productivity. The results show that the current development level of China’s digital innovation is relatively low, with significant regional heterogeneity. In particular, the impact of digital innovation on regional carbon productivity is subject to the heterogeneous threshold effect of industrial transformation upgrading: the low degree of industrial transformation upgrading hinders the role of digital innovation in improving carbon productivity to some extent, and with the further improvement of industrial transformation upgrading, the enabling effect of digital innovation can be effectively brought into play to improve carbon productivity. That is, digital innovation and regional carbon productivity present ‘U-shaped’ relationship. This paper has clarified the differential‘new phenomena’ in the process of promoting carbon productivity, providing new insights for achieving ‘carbon reduction and economic promotion’ in developing countries.

Economic and Sectoral Convergence in Latin America and the Caribbean: An Analysis of Beta, Sigma, and Gamma Convergence

The purpose of this study is to examine the economic and sectoral convergence of 32 countries in Latin America and the Caribbean (LAC) region from 1980 to 2022. The economic convergence hypothesis suggests that two economies with similar structural characteristics but different per capita income levels can tend to equalize in terms of income level in the long run. Confirming economic convergence has led to the development of various methodologies, among which dynamic and static disparity measures stand out. To achieve the objective of this research, both types of measures were calculated, determining beta and sigma convergence for dynamic disparity and gamma convergence for static disparity. This was accomplished by adopting the methodological approaches proposed by Sala-I-Martin and Marchante, Ortega, and Sánchez. The results show a gradual but steady evolution towards economic and sectoral convergence in LAC region during the 1980–2022 period. However, inequalities and divergences persist, requiring less developed countries to strengthen their institutions, implement sound macroeconomic policies, and diversify their economies. These measures are essential to driving economic growth and fostering more balanced and sustainable development across the region.

Radiation Resistance Investigation of Hybrid Ultramicroporous Materials for Highly Efficient CO2/Xe and CO2/Kr Separation in Spent Nuclear Fuel Off‐Gas

AbstractRadiation‐resistant nanoporous adsorbent that can realize absolute CO2/Xe (Kr) separation without Xe and Kr loss is crucial, but yet to be achieved for accurate and reliable nuclear fuel burnup analysis. Herein, two hybrid ultramicroporous materials (NbOFFIVE‐1‐Ni and TIFSIX‐3‐Co) are presented for highly efficient CO2/Xe and CO2/Kr separation in the nuclear reprocessing off‐gas. Nearly complete CO2/Xe (Kr) molecular sieving separations are achieved in NbOFFIVE‐1‐Ni with CO2/Xe and CO2/Kr selectivities both exceeding 11 000 before and after 50 kGy irradiation. Total photon cross sections of different elements, coordination number, and crystal orbital overlap population calculation that combines atoms, chemical bonds, and crystal structure are used to analyze the radiation stability of the hybrid ultramicroporous materials. Furthermore, the dynamic breakthrough and desorption measurement confirmed the ultra‐low Xe (Kr) loss ratio (0.24% for Xe and 0.3% for Kr) of NbOFFIVE‐1‐Ni adsorbent under simulated reprocessing off‐gas separation. This work not only provides a benchmark CO2/Xe (Kr) adsorbent for reliable nuclear fuel burnup analysis but also proposes a new perspective to understand the radiation stability of hybrid ultramicroporous materials.

A new approach to off-gas analysis for shaken bioreactors showing high CTR and RQ accuracy

BackgroundShake flasks are essential tools in biotechnological development due to their cost efficiency and ease of use. However, a significant challenge is the miniaturization of process analytical tools to maximize information output from each cultivation. This study aimed to develop a respiration activity online measurement system via off-gas analysis, named “Transfer rate Online Measurement” (TOM), for determining the oxygen transfer rate (OTR), carbon dioxide transfer rate (CTR), and the respiration quotient (RQ) in surface-aerated bioreactors, primarily targeting shake flasks.ResultsSensors for off-gas analysis were placed in a bypass system that avoids the shaking of the electronics and sensors. An electrochemical oxygen sensor and an infrared CO2 sensor were used. The bypass system was combined with the established method of recurrent dynamic measurement phases, evaluating the decrease in oxygen and the increase in CO2 during stopped aeration. The newly developed measurement system showed high accuracy, precision and reproducibility among individual flasks, especially regarding CTR measurement. The system was compared with state-of-the-art RAMOS technology (Respiration Activity Monitoring System, see explanation below) and calibrated with a non-biological model system. The accuracy of RQ measurement was +-4% for the tested range (8% filling volume, OTR and CTR: 0–56 mmol/L/h), allowing for the determination of metabolic switches and quantitative analysis of metabolites. At ambient CO2 levels, a CTR resolution of less than 0.01 mmol/L/h was possible. The system was applied to the microbial model systems S. cerevisiae, G. oxydans, and E. coli. Physiological states, such as growth vs. protein production, could be revealed, and quantitative analysis of metabolites was performed, putting focus on RQ measurements.ConclusionsThe developed TOM system showcases a novel approach to measuring OTR, CTR, and RQ in shaken bioreactors. It offers a robust and accurate solution for respiration activity analysis. Due to its flexible design and tunable accuracy, it enables measurement in various applications and different shake flasks.

Construction of the dynamic measurement algorithm for well inclination and azimuth in strapdown stable platform

Construction of the dynamic measurement algorithm for well inclination and azimuth in strapdown stable platform

Beyond support: exploring the dynamic and static biomechanical changes induced by preventive ankle taping: a novel cross-sectional study.

In sports, 80% of all ankle injuries are sprains of the external compartment. Functional bandages are usually used preventively, specially in individuals with a history of lateral ankle injuries. To this day, the actual benefits of such taping remain unknown as important modifications are introduced in the ankle biomechanics. The aim of the present study is to describe the biomechanical processes underlying these effects, such as modification during stance times, balance, contact surface and maximum and average pressures in the rearfoot, forefoot and midfoot, using a sprain preventive taping for the external ankle compartment. An observational, analytic, cross-sectional study was designed. Data from static and dynamic plantar pressures with a pressure platform and balance data assessed with the Y Balance Test (YBT) were analysed in 50 participants (age = 21.00±2.34 years, weight = 71.11±13.12 kg, height = 1.75±00.9 m, BMI = 22.94±2.50 kg/m2, foot size = 41.60±3.00) with and without preventive functional taping for lateral ankle sprain (LAS). A statistically significant decrease in YBT was observed in the taped participants toward anterior (p=0.001) and posterolateral (p=0.005) motion. On the static measures at the pressure platform, an increase in peak pressure at the midfoot (p=0.001), a decrease in the maximum pressure in the forefoot (p=0.003) and a decrease in the contact surface in the rearfoot (p=0.003) were recorded. Dynamic measures at the pressure platform analysis showed a statistically significant decrease in contact surface at the rearfoot (p=0.001), an increase in mean pressure in both the midfoot (p=0.044) and forefoot (p=0.001) and a significant decrease in velocity in the forefoot (p=0.003). In conclusion, we observed that ankle taping led to increased peak pressures in the midfoot and decreased maximum pressures in the forefoot, indicating a shift in load distribution within the plantar surface. Simultaneously, a significant reduction in the velocity at the forefoot during dynamic tasks suggests that taping may alter natural gait dynamics, potentially affecting movement efficiency and stride characteristics. In addition, the application of ankle taping significantly altered balance, as evidenced by a decrease of YBT scores anterior and posterolateral directions. Prophylactic taping in patients with no prior history of LAS is not recommended.

Challenging the skin pigmentation bias in tissue oximetry via time-domain near-infrared spectroscopy

Recently, skin pigmentation has been shown to affect the performance of pulse oximeters and other light-based techniques like photo-acoustic imaging, tissue oximetry, and continuous wave near-infrared spectroscopy. Evaluating the robustness to changes in skin pigmentation is therefore essential for the proper use of optical technologies in the clinical scenario. We conducted systematic time-domain near-infrared spectroscopy measurements on calibrated tissue phantoms and in vivo on volunteers during static and dynamic (i.e., arterial occlusion) measurements. To simulate varying melanosome volume fractions in the skin, we inserted, between the target sample and the measurement probe, thin tissue phantoms made of silicone and nigrosine (skin phantoms). Additionally, we conducted an extensive measurement campaign on a large cohort of pediatric subjects, covering the full spectrum of skin pigmentation. Our findings consistently demonstrate that skin pigmentation has a negligible effect on time-domain near-infrared spectroscopy results, underscoring the reliability and potential of this emerging technology in diverse clinical settings.

Dynamic wall shear stress measurement using event-based 3d particle tracking

We describe the implementation of a 3d Lagrangian particle tracking (LPT) system based on event-based vision (EBV) and demonstrate its application for the near-wall characterization of a turbulent boundary layer (TBL) in air. The viscous sublayer of the TBL is illuminated by a thin light sheet that grazes the surface of a thin glass window inserted into the wind tunnel wall. The data simultaneously captured by three synchronized event cameras are used to reconstruct the 3d particle tracks within 400μm of the wall on a field of view of 12.0mm×7.5mm. The velocity and position of particles within the viscous sublayer permit the estimation of the local vector of the unsteady wall shear stress (WSS) under the assumption of linearity between particle velocity and WSS. Thereby, time-evolving maps of the unsteady WSS and higher-order statistics are obtained that are in agreement with DNS data at matching Reynolds number. Near-wall particle acceleration provides the rate of change of the WSS which exhibits fully symmetric log-normal superstatistics. Two-point correlations of the randomly spaced WSS data are obtained by a bin-averaging approach and reveal information on the spacing of near-wall streaks. The employed compact EBV hardware coupled with suited LPT tracking algorithms provides data quality on par with currently used, considerably more expensive, high-speed framing cameras.

Heart Rate Variability Estimation Based on RFID Tag-Pair in Dynamic Environments

With the rapid development of smart health care, accurate heart rate variability (HRV) estimation for the early detection of diseases has become a hot research topic. Advanced work uses the wireless signal to estimate the heartbeat in a contact-free way, which usually cannot separate multiple users or work in a dynamic environment. In this article, we propose a lightweight heartbeat-sensing method based on RFID tag pairs, which focuses on HRV extraction in a more general sensing scenario. Based on the tag-pair design, we build a novel heartbeat and respiration model to describe the signal relationship between the two tags from the time and space domains. Based on the model, we propose a Calibrated Temporal-Spatial IQ-Shaping-based signal cancellation algorithm to cancel the respiration and extract the heartbeat. To remove the interference in dynamic measurement, we build an IQ-based signal model via a Principal Component Analysis-based interference estimation. To reduce the statistical error in HRV extraction, we further design a neural network to predict the HRV index. We have implemented a system prototype in a real environment with COTS RFID devices. Extensive experiments show that our system can achieve a median RMSSD error of 7.51 ms, which satisfies the medical demand in HRV measurement.

Large-Space Laser Tracking Attitude Combination Measurement Using Backpropagation Algorithm Based on Neighborhood Search

Large-space high-precision attitude dynamic measurement technology has urgent application needs in large equipment manufacturing fields, such as aerospace, rail transportation, automobiles, and ships. In this paper, taking laser tracking equipment as the base station, a backpropagation algorithm based on neighborhood search is proposed, which is applied to the fusion of multi-source information for solving the dynamic attitude angle. This paper firstly established a mathematical model of laser tracking attitude dynamic measurement based on IMU and CCD multi-sensor, designed a 6-11-3 back propagation network structure and algorithm flow, and realized the prediction of attitude angle through model training. Secondly, the method based on neighborhood search realizes the determination of the optimal training target value of the model, of which the MSE has a 34% reduction compared to the IMU determination method. Finally, the experimental platform is set up with the precision rotary table as the motion carrier to verify the effectiveness of the research method in this paper. The experimental results show that with the neighborhood-based backpropagation algorithm, the measurement results have a higher data update rate and a certain inhibition effect on the error accumulation of IMU. The absolute value of the system angle error can be less than 0.4° within 8 m and 0–50°, with an angle update rate of 100 Hz. The research method in this paper can be applied to the dynamic measurement of laser tracking attitude angles, which provides a new reference for the angle measurement method based on the fusion of multi-source information.