Amplitude Variability Research Articles

Aerodynamic Study of a Horizontal Axis Wind Turbine in Surge Motion Under Angular Speed and Blade Pitch Controls

Abstract Floating offshore wind turbines (FOWTs) experience dynamic conditions due to platform motion, requiring specific control strategies to mitigate loads and promote the wake diffusion improving overall wind farm efficiency. These problems can be appropriately modeled by medium-fidelity solvers, which rely on a computational fluid dynamics (CFD) resolution of the flow while avoiding its detailed resolution around the blades, preserving high-fidelity in simulating the wake at an acceptable computational cost. This work adopts a medium-fidelity actuator line model (ALM), implemented in the openfoam environment, previously validated against experiments and multifidelity models in the frame of the OC6 Phase III project. The study analyses several operating conditions during surge motion: a variable angular speed in below-rated condition, conceived to maximize the turbine efficiency, and a collective blade pitch control employable in above-rated conditions to limit surge-induced loads fluctuations. The effect of each control strategy is assessed individually through a systematic comparison with the baseline case with constant angular speed and blade pitch. Results indicate that the angular speed control succeeds in increasing the turbine power and reduces the spanwise variability of the induction factor amplitudes. Conversely, the pitch angle control reduces the force amplitude but does not alter the spanwise trend of the induction factor amplitude.

VIV mechanisms of a non-streamlined bridge deck equipped with traffic barriers

Vortex-induced vibration (VIV) has been addressed in the literature mostly for quasi-streamlined and shallow π-deck sections, typical of long-span bridges, since the latter are particularly prone to wind-induced oscillations. In contrast, although full-scale observations demonstrate that even steel-box girder bridges, usually characterized by a shorter span length if compared to suspension and cable-stayed bridges, can experience a violent VIV response, systematic studies for these bluffer cross-section geometries are less frequent. In addition, the aerodynamic optimization of non-structural additions (barriers, screens, fairings) is rarely carried out for this bridge typology. Therefore, a wind tunnel investigation is conducted on a non-streamlined box-girder sectional model (inspired by the Volgograd Bridge, Russia) equipped with two typologies of traffic barriers giving rise to a large ratio of barrier height to deck width. A realistic range of angles of attack (from −3° to 3°) are considered, and static forces, aeroelastic vibrations and wake velocity fluctuations are measured. A large and even unexpected variability in the vibration amplitude and lock-in curve pattern is found, emphasizing the possible existence of competing excitation mechanisms. Indeed, low-porosity barriers can alter the characteristics of vortex shedding, in particular creating a cavity on the upper side of the deck, which is known to foster the impinging-shear-layer instability, as in H-shaped sections. This vortex-shedding mechanism may co-exist with Kármán-vortex shedding and may be responsible for significant anticipation of the VIV onset compared to the predictions based on the Strouhal number measured during static tests. The intensity of a secondary excitation mechanism and its interaction with the dominant mechanism strongly depend on the angle of attack and is largely responsible for profound changes in the VIV bridge response, both in terms of qualitative pattern and peak amplitude. In some cases, the tracks of these competing vortex-shedding mechanisms are even clearly visible in the VIV response curves of the tested bridge model. Finally, the wind tunnel results are also reconsidered based on the quasi-steady theory, highlighting some, even qualitative, discrepancies.

Sex-differences in neuromuscular control of hip abductors during isometric submaximal tasks

BackgroundOne key focus in the literature is the need to better understand how males and females perform neuromuscular control, which requires consideration of muscle morphology, as it may change neural drive during force production. Although previous studies focused on muscles around the knee and ankle, it is crucial to explore the behavior of other muscles, such as the hip abductors, since many lower limb conditions more common in females have been associated with alterations in hip muscles. Research questionsAre electromyography (EMG) variables (amplitude and low- and high frequency bands) of hip abductors during submaximal isometric tasks different between males and females? How is muscle size associated with EMG responses during these tasks? MethodsThirty-six participants (males, n = 18; females, n = 18) had muscle and subcutaneous thickness of gluteus medius (GMed) and tensor fascia latae (TFL) measured. They then performed an estimated one-repetition maximum (1RM) test in a side-lying hip abduction exercise, followed by two 10-s submaximal tasks: (i) side-lying hip abduction with 50 % 1RM and (ii) with 20 % 1RM. GMed and TFL EMG amplitude and frequency bands (low and high frequency components) were analyzed. ResultsFemales had higher GMed EMG amplitude, lower low-frequency, and higher high-frequency components than males in both tasks (p = 0.001–0.040). No differences were observed in TFL EMG variables. Greater GMed thickness was associated with lower amplitudes in the 50 % 1RM task (r = − 0.35; p = 0.03), while greater TFL thickness was associated with lower low-frequency [20 % 1RM: r = − 0.70; p = 0.002; 50 %-1RM: r = − 0.65; p = 0.005] and higher high-frequency components [20 % 1RM: r = 0.74; p = 0.001; 50 %-1RM: r = 0.76; p < 0.001] only in females. SignificanceMales and females employ different neuromuscular control strategies, which vary among the synergists for hip abduction.

Vortex-Induced Vibration Performance Analysis of Long-Span Sea-Crossing Bridges Using Unsupervised Clustering

Vortex-induced vibration is a type of wind-induced vibration occurring frequently in large-span sea-crossing bridges under relatively low wind speeds, posing a threat to the structural fatigue performance and driving comfort. Identifying the instantaneous occurrence moments of vortex-induced vibration is a prerequisite for establishing a data-driven prediction model for vortex-induced vibration, and it is of great significance for the monitoring and early warning of vortex-induced vibration performance in bridges. To automatically detect the occurrence moments of vortex-induced vibration and establish a correlation model between vortex-induced vibration amplitude and environmental factors, this study proposes a fuzzy C-means clustering-based classification method. In order to detect the occurrence moments of vortex-induced vibration more finely, only short-term or even instantaneous structural vibration indicators were selected and transformed for distribution as clustering features. The entire detection process could be carried out unsupervised, reducing the manual cost of obtaining vortex-induced vibration information from massive monitoring data. Finally, actual vortex-induced vibration test data from a certain overseas bridge was utilized to verify the feasibility of this method. Based on the classification results, the correlation between vortex-induced vibration amplitude and environmental variables was determined, providing valuable guidance for predicting vortex-induced vibration amplitudes.

Damage Analysis of High-Speed Railway Bridge-Track System with Unequal Pier Heights Under Near-Fault Earthquake Based on FK-FE Method

ABSTRACT Canyons have a significant influence on near-fault earthquakes, and near-fault earthquakes exhibit strong amplitude and large spatial variability. In turn, this causes the damage and deformation of the high-speed railway (HSR) bridge-track system with unequal pier heights, which affects the normal service of the unequal pier heights bridge and the safe running of the train. This study investigates the damage and deformation of HSR bridge-track systems with unequal pier height in canyon areas under near-fault seismic based on FK (frequency wavenumber)-FE (finite element) method. It aims to offer suggestions for seismic design in canyon regions of HSR unequal pier height bridges. First, a finite fault kinematic hybrid source model and a canyon site model were established, and the FK-FE hybrid method was employed to simulate the three-dimensional (3D) site motion considering the full process of the seismic source-propagation medium-complex site (SSPC). Then, the influence of near-fault earthquakes and the canyon topography on the spatial distribution of near-fault ground motions were analyzed, and the non-uniform near-fault seismic excitation at the bottom of each pier considering the canyon topography effect was obtained. Finally, a nonlinear dynamic FE model of the HSR bridge-track system was established, and its damage patterns and mechanism in canyon near-fault earthquakes were analyzed. The results indicate that near-fault earthquakes in the canyon exhibit significant vertical and sliding effects with significant spatial variability and the FK-FE method can provide more accurate ground motion input. The seismic damage to HSR bridge-track systems increases as the fault distance decreases, and topography effects further aggravates seismic damage to HSR bridges. Moreover, vulnerable areas in the track system are often found at girder ends. Therefore, for HSR bridges in canyon regions, seismic input needs to comprehensively consider the effects of near-fault earthquakes and topography, with post-earthquake focus on damage assessment at girder ends.

The recovery of decreased executive attention in Tibetan migrants at high-altitude.

Attention is one of the basic cognitive functions sensitive to high altitude, and most studies have focussed on exposure times of approximately 3 years; however, it is unclear how attention changes in migrants who have lived and worked at high altitude for nearly 20 years. We explored the dynamics of attentional networks and neurophysiological mechanisms in migrants over 3-20 years using the Attentional Network Test combined with Electrocardiograph and Electroencephalography and found a consistent quadratic correlation between exposure and executive control efficiency, P3 amplitude and heart rate variability (HRV), with a decrease followed by an increase/relative stability, with approximately 10 years being the breakpoint. However, neither linear nor quadratic trajectories were observed for the alerting and orienting network. Mediation analysis revealed that the P3 amplitude mediated the decrease and increase in executive control efficiency with exposure time depends on the breakpoint. Correlations between HRV and executive control efficiency and P3 amplitude suggest that U-shaped changes in executive control in migrants may be related to body homeostasis maintained by the autonomic nervous system, and that P3 amplitude may serve as a neurophysiological marker of migrants' adaptation/recovery from high-altitude exposure.

The impact of receiver arrays on suppressing seismic speckle scattering noise caused by the meter-scale near-surface heterogeneity

Managing seismic scattering noise in geophysical surveying, especially from near-surface heterogeneity, presents significant challenges. We revisit the role of receiver arrays in mitigating such noise in regions with near-surface meter-scale heterogeneity. Moving beyond traditional approaches that focus on suppressing coherent noise from near-surface arrivals and random ambient noise, our research highlights the substantial impact of speckle scattering noise. This noise, resulting from near-ballistic scattering on small-scale heterogeneities, introduces considerable trace-to-trace variability in phase and amplitude, complicating data processing. By integrating a novel model of random multiplicative noise with sophisticated statistical techniques, we determine the efficacy of array stacking in significantly reducing this type of noise and decreasing the dispersion of phase and amplitudes. Our analytical and numerical analyses reveal a notable trend: the reduction in phase and amplitude spread amplifies with the array size. A key finding of our study is the identification of a [Formula: see text] law for phase spread reduction, analogous yet distinct from the well-known [Formula: see text] law observed in amplitude attenuation of additive ambient noise. In our context, this law implies that the standard deviation of residual phase disturbances diminishes in proportion to [Formula: see text], where N denotes the array size. This insight holds particular significance for smaller arrays, such as those with nine receivers commonly used in desert environments.

Joint ALMA/X-ray monitoring of the radio-quiet type 1 active galactic nucleus IC 4329A

The origin of a compact millimeter (mm, 100–250 GHz) emission in radio-quiet active galactic nuclei (RQ AGN) remains debated. Recent studies propose a connection with self-absorbed synchrotron emission from the accretion disk X-ray corona. We present the first joint ALMA (∼100 GHz) and X-ray (NICER/XMM-Newton/Swift; 2–10 keV) observations of the unobscured RQ AGN, IC 4329A (z = 0.016). The time-averaged mm-to-X-ray flux ratio aligns with recently established trends for larger samples, but with a tighter scatter (∼0.1 dex) compared to previous studies. However, there is no significant correlation on timescales of less than 20 days. The compact mm emission exhibits a spectral index of −0.23 ± 0.18, remains unresolved with a 13 pc upper limit, and shows no jet signatures. Notably, the mm flux density varies significantly (by factor of 3) within four days, exceeding the contemporaneous X-ray variability and showing the largest mm variations ever detected in RQ AGN over daily timescales. The high amplitude variability rules out scenarios of heated dust and thermal free–free emission, pointing toward a synchrotron origin for the mm radiation in a source of ∼1 light day (∼120 gravitational radii) size. While the exact source is not yet certain, an X-ray corona scenario emerges as the most plausible compared to a scaled-down jet or outflow-driven shocks.

Clustering and Classification of Time Series Sound Data

This scientific article addresses two critical tasks in data analysis—time series classification and clustering, particularly focusing on heart sound recordings. One of the main challenges in analyzing time series lies in the difficulty of comparing different series due to their variability in length, shape, and amplitude. Various algorithms were employed to tackle these tasks, including the Long Short-Term Memory (LSTM), KNN, recurrent neural network for classification and the K-means and DBSCAN methods for clustering. The study emphasizes the effectiveness of these methods in solving classification and clustering problems involving time series data containing heart sound recordings. The results indicate that LSTM is a powerful tool for time series classification due to its ability to retain contextual information over time. In contrast, KNN demonstrated high accuracy and speed in classification, though its limitations became apparent with larger datasets. For clustering tasks, the K-means method proved to be more effective than DBSCAN, showing higher clustering quality based on metrics such as silhouette score, Rand score, and others. The data used in this research were obtained from the UCR Time Series Archive, which includes heart sound recordings from various categories: normal sounds, murmurs, additional heart sounds, artifacts, and extra systolic rhythms. The analysis of results demonstrated that the chosen classification and clustering methods could be effectively used for diagnosing heart diseases. Furthermore, this research opens up new opportunities for further improvement in data processing and analysis methods, particularly in developing new medical diagnostic tools. Thus, this work illustrates the effectiveness of machine learning algorithms for time series analysis and their significance in improving cardiovascular disease diagnosis.

Modeling the TESS Light Curve of Ap Si Star MX TrA

The TESS light curve of the silicon Ap star MX TrA was modeled using the observational surface distribution of silicon, iron, helium, and chromium obtained previously with the Doppler Imaging technique. The theoretical light curve was calculated using a grid of synthetic fluxes from line-by-line stellar atmosphere models with individual chemical abundances. The observational TESS light curve was fitted by a synthetic one with an accuracy better than 0.001 mag. The influence of Si and Fe abundance stratification on the amplitude of variability was estimated. Also, the wavelength dependence of the photometric amplitude and phase of the maximum light was modeled showing the typical Ap Si star behavior with increased amplitude and anti-phase variability in far ultraviolet caused by the flux redistribution.

CircadiPy: An open-source toolkit for analyzing chronobiology time series

BackgroundChronobiology is the scientific field focused on studying periodicity in biological processes. In mammals, most physiological variables exhibit circadian rhythmicity, such as metabolism, body temperature, locomotor activity, and sleep. The biological rhythmicity can be statistically evaluated by examining the time series and extracting parameters that correlate to the period of oscillation, its amplitude, phase displacement, and overall variability. New methodWe have developed a library called CircadiPy, which encapsulates methods for chronobiological analysis and data inspection, serving as an open-access toolkit for the analysis and interpretation of chronobiological data. The package was designed to be flexible, comprehensive and scalable in order to assist research dealing with processes affected or influenced by rhythmicity. ResultsThe results demonstrate the toolkit's capability to guide users in analyzing chronobiological data collected from various recording sources, while also providing precise parameters related to the circadian rhythmicity. Comparison with existing methodsThe analysis methodology from this proposed library offers an opportunity to inspect and obtain chronobiological parameters in a straightforward and cost-free manner, in contrast to commercial tools. ConclusionsMoreover, being an open-source tool, it empowers the community with the opportunity to contribute with new functions, analysis methods, and graphical visualizations given the simplified computational method of time series data analysis using an easy and comprehensive pipeline within a single Python object.

A machine learning approach for estimating the drift velocities of equatorial plasma bubbles based on All-Sky Imager and GNSS observations

Equatorial Plasma Bubbles (EPBs) are zones characterized by fluctuations in plasma densities which form in the low-latitude ionosphere primarily during the post-sunset. They subject radio signals to amplitude and phase variabilities, affecting the functioning of technological systems that utilize the Global Navigation Satellite Systems (GNSS) signals for navigation. Thus, understanding EPB occurrence patterns and morphological features is vital for mitigating their effects. In this work, we employed two GNSS receivers and an All-Sky Imager (ASI) to conduct simultaneous observations on the morphology of EPBs over Brazil. The main objectives of the study were (1) to develop a Random Forest (RF) machine-learning model to estimate and predict the zonal drift velocities of EPBs, and (2) to compare the model predictions with actual EPB drifts inferred from the two instruments, as well as zonal neutral wind speeds obtained from the Horizontal Wind Model (HWM-14). In the model development, we utilized reliable EPB drift measurements made during geomagnetically quiet days between 2013 and 2017 in Brazil. The model predicted the velocities based on parameters including the day of the year, universal time, critical frequency of the F2 layer (foF2), solar and interplanetary indices. The correlation coefficients of 0.98 and 0.96 and RMSE values of 10.61 m/s and 10.06 m/s were obtained upon training and validation correspondingly. We evaluated the accuracy of the model in predicting EPB drifts on two geomagnetically quiet nights where an average correlation coefficient of 0.89 and an RMSE of 15.74 m/s were obtained. The predicted drifts, the zonal neutral wind velocities, and the GNSS and ASI velocity measurements were put into context for validation purposes. Overall, the velocities were comparable and ranged between ∼100 m/s and ∼30 m/s from the hours of 00 UT to 05 UT. The results confirmed the accuracy and applicability of the model, revealing the ionosphere-thermosphere coupling influence on the nocturnal propagation of EPBs under the full activation of the F region dynamo.

Seasonal Dependency of the Solar Cycle, QBO, and ENSO Effects on the Interannual Variability of the Wind DW1 in the MLT Region

AbstractThe migrating diurnal tide (DW1) is derived by fitting Hough Mode Extensions to the TIMED/TIDI near‐global wind measurements within the mesosphere and lower thermosphere between 85 and 100 km from 2004 to 2014. The tidal amplitude peaks around the equinoxes with a large interannual variability of up to 50%. The correlation coefficients between the tidal amplitude variability and the solar cycle as represented by F10.7, stratospheric Quasi‐Biennial Oscillation (QBO), and El Niño‐Southern Oscillation (ENSO) are calculated every 10 days revealing seasonal dependencies. The interannual variability is positively correlated with QBO from spring to fall, maximizing around the equinoxes; anti‐correlated to the solar cycle in early winter; and anti‐correlated to ENSO in early winter and slightly in March. Multivariate linear regressions are performed to quantitatively analyze the linear relationships between the DW1 amplitude and those factors. The fittings perform best with the QBO at 30 and 50 hPa both being considered. The contribution of QBO peaks around January and October may be related to the polar vortex modulated by QBO in the northern and southern hemispheres, respectively. The correlation between the DW1 amplitude and ENSO is negative with time lags &lt;∼5 months during early winter and spring.

Short‐Term to Inter‐Annual Variability of the Non‐Migrating Tide DE3 From MIGHTI, SABER, and TIDI: Potential Tropospheric Sources and Ionospheric Impacts

AbstractUpward propagating waves of lower atmospheric origin play an important role in coupling terrestrial weather with space weather on daily to inter‐annual timescales. Quantifying their short‐term (&lt;30 days) variability is a difficult challenge because simultaneous observations at multiple local times are needed to sample diurnal cycles. This study demonstrates and validates a short‐term estimation method of the DE3 non‐migrating tide at the equator and then applies the technique to three independent data sets: MIGHTI, SABER, and TIDI. We find that daily DE3 estimates from SABER, MIGHTI, and TIDI at equator agree well with correlation coefficients ranging between 0.76 and 0.85. The daily DE3 amplitude variability is typically ∼7 m/s in zonal winds and ∼3 K in temperature. We also find that daily MLT variations and F‐region ionospheric DE3 from COSMIC‐2 Global Ionospheric Specification (GIS) show a correlation of 0.55–0.65, suggesting that not all ionospheric variability can be attributed to the E‐region dynamo; however, increasing correlation with increasing time‐scale suggests that lower atmospheric variability has pronounced impact on the ionosphere on intra‐seasonal scales. We find that the MLT and the F‐region ionosphere exhibit strong coherent intra‐seasonal oscillations (residual amplitudes upto 50%–60%); their coherency with the MJO in 2020 suggests a possible modulation of the upward propagating DE3 tide related to this major tropical tropospheric weather pattern. In addition, we find stratospheric QBO signatures in the MLT DE3 on inter‐annual scales. This study offers fresh observational insights into the pivotal role of tropospheric weather in shaping variability in the coupled thermosphere‐ionosphere system.

Improvements in Therapy Experience With Evoked Compound Action Potential Controlled, Closed-Loop Spinal Cord Stimulation—Primary Outcome of the ECHO-MAC Randomized Clinical Trial

Spinal cord stimulation (SCS) is a well-established treatment for chronic neuropathic pain. However, over- or underdelivery of the SCS may occur because the spacing between the stimulating electrodes and the spinal cord is not fixed; spacing changes with motion and postural shifts may result in variable delivery of the SCS dose and, in turn, a suboptimal therapy experience for the patient. The evoked compound action potential (ECAP)—a measure of neural activation—may be used as a control signal to adapt SCS parameters in real time to compensate for this variability. In this prospective, multicenter, randomized, single-blind, crossover trial, reduction in overstimulation intensity was used as a perceptual measure to evaluate a novel ECAP-controlled, closed-loop (CL) SCS algorithm relative to traditional open-loop (OL) SCS. The primary outcome used a Likert scale to assess sensation during activities of daily living with CL versus OL SCS. Of the 42 subjects in the intent-to-treat analysis set, 97.6% had a reduction in sensation with CL versus OL SCS. The primary objective was met as the lower confidence limit (87.4%) exceeded the performance goal of 50% (P < .001). A total of 88.1% (37/42) of subjects preferred CL and 11.9% (5/42) preferred OL SCS. SCS dose consistency during CL SCS was demonstrated by the reduced variability in ECAP amplitude with CL SCS (standard deviation: 8.72 µV) relative to OL SCS (standard deviation: 19.95 µV). Together, these results demonstrate that the ECAP-controlled, CL algorithm reduces or eliminates unwanted sensation, and thereby provides a more preferred and consistent SCS experience. PerspectivePatients with chronic pain need durable and dependable options for pain relief. SCS is an important therapy option, and new technology advancements could improve long-term therapy use. CL SCS offers a preferred and more consistent therapy experience for patients that could lead to increased therapy utilization and reliable therapy outcomes.

The clinical utility of the prone hip extension test in the diagnosis of motor control impairments associated with low back pain: A cross-sectional study using motion capture and electromyography

BackgroundThe prone hip extension test is used as a clinical tool to diagnose specific motor control impairments that have been identified in individuals with chronic low back pain. However, conventional protocols for performing the test are subjective and lack evidence for their effectiveness. The objective of the current study was to quantify lumbopelvic motion and muscle activation during this test and identify which motor control patterns best distinguish individuals with low back pain from asymptomatic controls. Methods18 individuals with sub-acute or chronic low back pain and 32 asymptomatic controls performed the prone hip extension test while a 3D motion capture system measured lumbar and pelvic movement patterns and an electromyography system measured the muscle activation patterns of the paraspinal, gluteus maximus, and hamstring muscles. A three-stage statistical analysis was performed, the final stage being a stepwise logistic regression analysis aimed at identifying the movement and muscle activation pattern variables that best distinguished the two groups. FindingsThe final regression model included three lumbar kinematic variables and several electromyographic amplitude variables for the gluteus maximus and hamstring muscles during right-sided prone hip extension. The final model correctly classified 86.7 % of the control group and 83.3 % of the low back pain group. InterpretationThe subject of asymmetrical gluteus maximus and hamstring muscle activation appears to be a potentially interesting area for future research on the utility of the prone hip extension test as a clinical tool in diagnosing motor control impairments associated with low back pain.

Quantitative assessment of intertarget position variations based on 4D-CT and 4D-CBCT simulations in single-isocenter multitarget lung stereotactic body radiation therapy

BackgroundIn single-isocenter multitarget stereotactic body radiotherapy (SBRT), geometric miss risks arise from uncertainties in intertarget position. However, its assessment is inadequate, and may be interfered by the reconstructed tumor position errors (RPEs) during simulated CT and cone beam CT (CBCT) acquisition. This study aimed to quantify intertarget position variations and assess factors influencing it.MethodsWe analyzed data from 14 patients with 100 tumor pairs treated with single-isocenter SBRT. Intertarget position variation was measured using 4D-CT simulation to assess the intertarget position variations (ΔD) during routine treatment process. Additionally, a homologous 4D-CBCT simulation provided RPE-free comparison to determine the impact of RPEs, and isolating purely tumor motion induced ΔD to evaluate potential contributing factors.ResultsThe median ΔD was 4.3 mm (4D-CT) and 3.4 mm (4D-CBCT). Variations exceeding 5 mm and 10 mm were observed in 31.1% and 5.5% (4D-CT) and 20.4% and 3.4% (4D-CBCT) of fractions, respectively. RPEs necessitated an additional 1–2 mm safety margin. Intertarget distance and breathing amplitude variability showed weak correlations with variation (Rs = 0.33 and 0.31). The ΔD differed significantly by locations (upper vs. lower lobe and right vs. Left lung). Notably, left lung tumor pairs exhibited the highest risk.ConclusionsThis study provide a reliable way to assess intertarget position variation by using both 4D-CT and 4D-CBCT simulation. Consequently, single-isocenter SBRT for multiple lung tumors carries high risk of geometric miss. Tumor motion and RPE constitute a substantial portion of intertarget position variation, requiring correspondent strategies to minimize the intertarget uncertainties.

A high security coding and anti-counterfeiting method based on the nonlinear magnetization response of superparamagnetic nanomaterials

Traditional coding methods based on graphics and digital or magnetic labels have gradually decreased their anti-counterfeiting because of market popularity. This paper presents a new magnetic anti-counterfeiting coding method. This method uses a high-performance coding material, which, along with small changes to the material itself and the particle size of the superparamagnetic nanomaterials, results in a large difference in the nonlinear magnetization response. This method, which adopts 12-site coding and establishes a screening model by measuring the voltage amplitude of 12-site variables, can code different kinds of products, establishing long-term stable coding and decoding means. Through the anti-counterfeiting experiment of wine, the experiment results show that the authenticity of the coded products can be verified using the self-developed magnetic encoding and decoding system. The new coding technology can verify the anti-counterfeiting of 9000 products, with a single detection accuracy of 97% and a detection time of less than one minute. Moreover, this coding method completely depends on the production batch of the superparamagnetic nanomaterials, which is difficult to imitate, and it provides a new coding anti-counterfeiting technology for related industries with a wide range of potential applications.

Gait Analysis and Magnetic Resonance Imaging Characteristics in Patients with Isolated Rapid Eye Movement Sleep Behavior Disorder.

Isolated rapid eye movement sleep behavioral disorder (iRBD) can precede neurodegenerative diseases. There is an urgent need for biomarkers to aid early intervention and neuroprotection. The aim is to assess quantitative motor, cognitive, and brain magnetic resonance imaging (MRI) characteristics in iRBD patients. Thirty-eight polysomnography-confirmed iRBD patients and 28 age- and sex-matched healthy controls underwent clinical, cognitive, and motor functional evaluations, along with brain MRI. Motor tasks included nine-hole peg test, five-times-sit-to-stand test, timed-up-and-go test, and 4-meter walking test with and without cognitive dual task. Quantitative spatiotemporal gait parameters were obtained using an optoelectronic system. Brain MRI analysis included functional connectivity (FC) of the main resting-state networks, gray matter (GM) volume using voxel-based morphometry, cortical thickness, and deep GM and brainstem volumes using FMRIB's Integrated Registration and Segmentation Tool and FreeSurfer. iRBD patients relative to healthy subjects exhibited a poorer performance during the nine-hole peg test and five-times-sit-to-stand test, and greater asymmetry of arm-swing amplitude and stride length variability during dual-task gait. Dual task significantly worsened the walking performance of iRBD patients more than healthy controls. iRBD patients exhibited nonmotor symptoms, and memory, abstract reasoning, and visuospatial deficits. iRBD patients exhibited decreased FC of pallidum and putamen within the basal ganglia network and occipital and temporal areas within the visuo-associative network, and a reduced volume of the supramarginal gyrus. Brain functional alterations correlated with gait changes. Subtle motor and nonmotor alterations were identified in iRBD patients, alongside brain structural and functional MRI changes. These findings may represent early signs of neurodegeneration and contribute to the development of predictive models for progression to parkinsonism. © 2024 The Author(s). Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Rest-Activity Rhythm Differences in Acute Rehabilitation Between Poststroke Patients and Non-Brain Disease Controls: Comparative Study.

Circadian rhythm disruptions are a common concern for poststroke patients undergoing rehabilitation and might negatively impact their functional outcomes. Our research aimed to uncover unique patterns and disruptions specific to poststroke rehabilitation patients and identify potential differences in specific rest-activity rhythm indicators when compared to inpatient controls with non-brain-related lesions, such as patients with spinal cord injuries. We obtained a 7-day recording with a wearable actigraphy device from 25 poststroke patients (n=9, 36% women; median age 56, IQR 46-71) and 25 age- and gender-matched inpatient control participants (n=15, 60% women; median age 57, IQR 46.5-68.5). To assess circadian rhythm, we used a nonparametric method to calculate key rest-activity rhythm indicators-relative amplitude, interdaily stability, and intradaily variability. Relative amplitude, quantifying rest-activity rhythm amplitude while considering daily variations and unbalanced amplitudes, was calculated as the ratio of the difference between the most active 10 continuous hours and the least active 5 continuous hours to the sum of these 10 and 5 continuous hours. We also examined the clinical correlations between rest-activity rhythm indicators and delirium screening tools, such as the 4 A's Test and the Barthel Index, which assess delirium and activities of daily living. Patients who had a stroke had higher least active 5-hour values compared to the control group (median 4.29, IQR 2.88-6.49 vs median 1.84, IQR 0.67-4.34; P=.008). The most active 10-hour values showed no significant differences between the groups (stroke group: median 38.92, IQR 14.60-40.87; control group: median 31.18, IQR 18.02-46.84; P=.93). The stroke group presented a lower relative amplitude compared to the control group (median 0.74, IQR 0.57-0.85 vs median 0.88, IQR 0.71-0.96; P=.009). Further analysis revealed no significant differences in other rest-activity rhythm metrics between the two groups. Among the patients who had a stroke, a negative correlation was observed between the 4 A's Test scores and relative amplitude (ρ=-0.41; P=.045). Across all participants, positive correlations emerged between the Barthel Index scores and both interdaily stability (ρ=0.34; P=.02) and the most active 10-hour value (ρ=0.42; P=.002). This study highlights the relevance of circadian rhythm disruptions in poststroke rehabilitation and provides insights into potential diagnostic and prognostic implications for rest-activity rhythm indicators as digital biomarkers.