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Purpose: Heart rate variability (HRV) may be influenced by several factors, such as environment (hypoxia, hyperoxia, hypercapnia) or physiological demand (exercise). In this retrospective study, we tested the hypothesis that inter-beat (RR) intervals in healthy subjects exercising under various environmental stresses exhibit oscillations at the same frequency than ventilatory oscillations. Methods: Spectra from RR intervals and ventilation ( V ˙ E) were collected from 37 healthy young male subjects who participated in 5 previous studies focused on ventilatory oscillations (or periodic breathing) during exercise in hypoxia, hyperoxia and hypercapnia. Bland and Altman test and multivariate regressions were then performed to compare respective frequencies and changes in peak powers of the two signals. Results: Fast Fourier analysis of RR and V ˙ E signals showed that RR was oscillating at the same frequency than periodic breathing, i.e., ~ 0.09 Hz (11 s). During exercise, in these various conditions, the difference between minimum and maximum HRV peak power was positively correlated to the same change in ventilation peak power (P < 0.05). Low-frequency (LF) peak power was correlated to tidal volume (P < 0.01) and breathing frequency (P < 0.001). Conclusions: This study suggests that low-frequency ventilatory oscillations in hypoxia are a major contributor to the LF band power of heart rate variability. Clinical Trial Reg. no.: NCT02201875. [ABSTRACT FROM AUTHOR]

In this work, the W. Ebeling potential including the quantum effects and Monte Carlo numerical simulation have been briefly described. The limits of this potential between the classical and quantum effects were calculated. The electric microfield distribution functions in quantum plasma were calculated, mainly, using Monte Carlo (MC) and molecular dynamics (MD) simulations. To carry out this task, W. Ebeling potential, which includes quantum effects at small interspaces between various components of the plasma (ions and electrons), has been considered. All interactions (ion–ion, ion–electron) were taken into account during the calculation, which is the same idea that Hooper dealt with this issue, but considering the Coulomb or Debye potential. The results were compared with other similar works: the best classical model APEX and Sadykova with quantum effect. Most of our results have showed a near perfect agreement. Some behaviours of these functions have been deduced for different coupling parameters, quantification degrees and plasma types. [ABSTRACT FROM AUTHOR]

We compare the results of two methods used to determine the angular velocity of the Foton-12 satellite and the low-frequency component of microaccelerations onboard it. The first method is based on reconstruction of the satellite's rotational motion using the data of onboard measurements of the strength of the Earth's magnetic field. The motion (time dependence of the orientation parameters and angular velocity) was found from the condition of best approximation of the measurement data by the functions calculated along the solutions to equations of attitude motion of the satellite. The solutions found were used to calculate the quasistatic component of microaccelerations at certain points of the satellite, in particular, at the point of location of an accelerometer of the QSAM system. Filtration of the low-frequency component of the angular velocity and microacceleration from the data of measurements by a sensor of angular velocity and by the accelerometer of this system served as a second method. The filtration was made using the discrete Fourier series. A spectral analysis of the functions representing the results of determining the angular velocity and microacceleration by both methods is performed. Comparing the frequencies and amplitudes of the harmonic component of these functions allowed us to estimate the accuracy of measurements made by the QSAM system in the low-frequency range. [ABSTRACT FROM AUTHOR]

Common drive to a motor unit (MU) pool manifests as low-frequency oscillations in MU discharge rate, producing fluctuations in muscle force. The aim of the study was to examine the temporal correlation between instantaneous MU discharge rate and rectified EMG in low frequencies. Additionally, we attempted to examine whether there is a temporal correlation between the low-frequency oscillations in MU discharge rate and the first derivative of force ( dF/ dt). Healthy young subjects produced steady submaximal force with their right finger as a single task or while maintaining a pinch-grip force with the left hand as a dual task. Surface EMG and fine-wire MU potentials were recorded from the first dorsal interosseous muscle in the right hand. Surface EMG was band-pass filtered (5-1,000 Hz) and full-wave rectified. Rectified surface EMG and the instantaneous discharge rate of MUs were smoothed by a Hann-window of 400 ms duration (equivalent to 2 Hz low-pass filtering). In each of the identified MUs, the smoothed MU discharge rate was positively correlated with the rectified-and-smoothed EMG as confirmed by the distinct peak in cross-correlation function with greater values in the dual task compared with the single task. Additionally, the smoothed MU discharge rate was temporally correlated with dF/ dt more than with force and with rectified-and-smoothed EMG. The results indicated that the low-frequency component of rectified surface EMG and the first derivative of force provide temporal information on the low-frequency oscillations in the MU discharge rate. [ABSTRACT FROM AUTHOR]

The low-frequency component is investigated in the data of measurements performed onboard the Foton M-2 satellite with the three-component accelerometer TAS-3. Investigations consisted in comparison of this component with its calculated analog found from a reconstruction of the satellite’s attitude motion. The influence of the Earth’s magnetic field on the accelerometer readings is discovered by way of spectral analysis of the functions representing the results of determining the low-frequency microacceleration by two methods. After making correction for this influence, the results obtained by these two methods coincided within a root-mean-square error of less than 10−6 m/s2. [ABSTRACT FROM AUTHOR]

Based on the analysis of a 2D model composed of rectangular blocks with deformable interlayers, it is found that the earlier model of perfectly rigid blocks is only applicable if interlayers are low rigid and blocks are rigid. Otherwise, the descriptions of dynamic disturbances in such media deviate greatly. The present paper introduces a correction for this restriction, as well as analyzes the elastic properties of blocks and their contribution to the oscillation motion. [ABSTRACT FROM AUTHOR]

Abstract—A model of electroencephalogram (EEG) generation was proposed to include not only summation of postsynaptic potentials, but also fluctuations in the regulation of a constant potential level. The model explains a number of phenomena observed predominantly in the low-frequency EEG range. [ABSTRACT FROM AUTHOR]

Compared with the general urban rail transit, some of the current rapid urban rail transit can reach a maximum speed of 140 km/h when the train is running, which exceeds the speed level of the general urban rail transit. To consider the influence of different speeds and loads on the vibration of viaducts and the surrounding soil environment, this paper establishes a three-dimensional finite element model of rail-viaduct soil. The results show that: the frequency domain acceleration of each measurement point increases with the increase of train speed; except for the measurement point which is 20 m away from the centerline of the track, the frequency domain speed of each measurement point increases with the increase of train speed; the frequency domain speed under the low-frequency component of the viaduct measurement point increases with the increase of train loading, and the growth rate is obviously larger than that of the middle and high frequency bands, and the frequency domain speed of the measurement points in the site also increases with the increase of train loading, and the growth rate of the low-frequency band is obviously larger than that of the middle and high frequency bands. The frequency domain velocity at each measurement point of the site also increases with the increase of train load, and the growth rate of the low-frequency band is obviously larger than that of the middle and high-frequency bands. [ABSTRACT FROM AUTHOR]

Recent works have demonstrated the great performance of forgery image forensics based on deep learning, but there is still a risk that detectors could be susceptible to unknown illegal attacks, raising growing security concerns. This paper starts from the perspective of reverse forensics and explores the vulnerabilities of current image manipulation detectors to achieve targeted attacks. We present a novel reverse decision aggregate gradient attack under low-frequency constraints (RevAggAL). Specifically, we first propose a novel pixel reverse content decision-making (PRevCDm) loss to optimize perturbation generation with a specific principle more suitable for segmenting manipulated regions. Then, we introduce the low-frequency component to constrain the perturbation into more imperceptible details, significantly avoiding the degradation of image quality. We also consider aggregating gradients on model-agnostic features to enhance the transferability of adversarial examples in black-box scenarios. We evaluate the effectiveness of our method on three representative detectors (ResFCN, MVSSNet, and OSN) with five widely used forgery datasets (COVERAGE, COLUMBIA, CASIA1, NIST 2016, and Realistic Tampering). Experimental results show that our method improves the attack success rate (ASR) while ensuring better image quality. [ABSTRACT FROM AUTHOR]

This paper proposes a multi-modal fusion algorithm for image filtering based on the guidance of local extrema maps. The image is subjected to a smoothing process using a locally extremal maps-guided image filter, and the difference from the original image forms the detail layer, while the smoothed image serves as the base layer. To preserve image details, both the base and detail layers undergo a resolution reduction process, establishing a multi-scale decomposition hierarchy. The base layer images at each level are decomposed using wavelet transform into low-frequency and high-frequency coefficients. For the low-frequency component, a region-energy fusion rule with adaptive weight allocation based on spatial and gradient information is employed, while the high-frequency component undergoes fusion using the AGPCNN fusion rule with neuron weight assignment initialized. The detail layer is fused using a weighted averaging fusion rule. Finally, the base layer images are fused through wavelet inverse transform. For the fusion of base and detail layers, a bottom layer employs the absolute maximum principle, while the top layer utilizes an average weighted fusion rule. Through subjective and objective analysis, experimental results indicate that the proposed fusion model algorithm not only effectively preserves edge and texture details but also maintains good color fidelity and spectral distortion control. Comparative analysis with eight other advanced fusion algorithms demonstrates superior fusion performance. [ABSTRACT FROM AUTHOR]

User traffic prediction is an important topic for wireless network operators. A user traffic prediction method based on Prophet and Gaussian process regression is proposed in this paper. The proposed method first employs discrete wavelet transform to decompose the user traffic time series to high-frequency component and low-frequency component. The low-frequency component bears the long-range dependence of user network traffic, while the high-frequency component reveals the gusty and irregular fluctuations of user network traffic. Then Prophet model and Gaussian process regression are applied to predict the two components respectively based on the characteristics of the two components. Experimental results demonstrate that the proposed model outperforms the existing time series prediction method. [ABSTRACT FROM AUTHOR]

Over the past few years, the use of chaotic maps have surfaced to become an important topic in the field of image encryption. The majority of chaos-based algorithms employed single or multiple rounds of confusion and diffusion. However, such algorithms increase the security and computational cost of the encryption process. On the other hand,a higher computational process is required to maintain security. To overcome this issue, a robust image encryption method using the features of two dimensional coupling map (2D-CM) and Discret Wavelet Transform(DWT) is proposed. Additionally, low-frequency component of DWT used for encryption can significantly save storage space thereby reducing computational overheads without compromising the security of the encryption. Finally, the cover image is combined with higher frequency coefficients to obtain the whole image, which will be totally secure against external attacks. The proposed encryption technique undergoes various security analyses, including Information Entropy (I en) , Correlation Coefficients (CC), Number of Pixel Change Rate (NPCR), Unified Average Change Intensity (UACI) and computational complexity and histogram analysis. The NPCR value and UACI obtained for all the images under simulation are greater than 99% and 33, respectively. Furthermore, results show that the proposed method has low correlation, high key sensitivity and sufficient key space (2 256) to withstand against external attacks. [ABSTRACT FROM AUTHOR]

Addressing the limitations of existing landslide displacement prediction models in capturing the dynamic characteristics of data changes, this study introduces a novel dynamic displacement prediction model for landslides. The proposed method combines Variational Mode Decomposition (VMD) with Sparrow Search Optimization (SSO) and Long Short-Term Memory (LSTM) techniques to formulate a comprehensive VMD–SSO–LSTM model. Through the application of VMD, the method dissects cumulative displacement and rainfall data, thereby extracting distinct components such as trend, periodicity, and fluctuation components for displacement, as well as low-frequency and high-frequency components for rainfall. Furthermore, leveraging Gray Correlational Analysis, the interrelationships between the periodic component of displacement and the low-frequency component of rainfall, as well as the fluctuation component of displacement and the high-frequency component of rainfall, are established. Building upon this foundation, the SSO–LSTM model dynamically predicts the interrelated displacement components, synthesizing the predicted values of each component to generate real-time dynamic forecasts. Simulation results underscore the effectiveness of the proposed VMD–SSO–LSTM model, indicating root-mean-square error (RMSE) and mean absolute percentage error (MAPE) values of 1.2329 mm and 0.1624%, respectively, along with a goodness of fit (R2) of 0.9969. In comparison to both back propagation (BP) prediction model and LSTM prediction model, the VMD–SSO–LSTM model exhibits heightened predictive accuracy. [ABSTRACT FROM AUTHOR]

With the rapid development of national infrastructure projects, there has been a significant increase in intersecting lines in transportation construction. As a result, rotating bridges are increasingly used in engineering projects that span existing railway lines. In order to study the spatial response characteristics and vibration wave transmission mechanisms of the rotating bridge structure under the loading of existing railway trains, field experiments and numerical analyses were conducted. The response characteristics of these bridges were investigated under different types and speeds of adjacent existing lines. A comprehensive methodology has been proposed, integrating the time domain spectrum and the Hilbert–Huang Transform (HHT) energy spectrum for signal processing and vibration analysis. The analysis was carried out using MATLAB 2018a software. This methodology was applied to analyze the test data. The results show that significant resonance phenomenon occurs in the girders of the rotating bridge under the loading of trains on the existing line. The low-frequency component f1 (2–5 Hz) is the primary factor contributing to the amplification of the acceleration response in the rotating bridge, while f3 (10–13 Hz) plays a secondary role. The frequency distribution characteristics of vibration waves caused by train loads on the existing line have a significant influence on the acceleration response of the rotating bridge's girders. The predominant frequency of vibration waves at each measuring point along the transmission path shows a trend of decreasing → increasing → decreasing. The impact on the rotating bridge structure of vibration waves generated by low-speed freight trains on existing railways is greater. The research findings are of great importance for studying the dynamic response of rotating bridges adjacent to existing railway lines. [ABSTRACT FROM AUTHOR]

High spatial resolution multispectral (HMS) images can provide sufficient information for researchers to analyze the potential disasters in the living environment. However, an original multispectral (MS) image is with low-space-resolution and high-spectrum-resolution, while an original panchromatic (PAN) image has the opposite property. Pansharpening aims at obtaining HMS image by retaining spectrum of the MS image and injecting details of the PAN image simultaneously. In this paper, we present a new pansharpening method. First, we use a bilateral filter (BF) to obtain the low-frequency-component (LFC) of PAN and MS images, respectively. Then the high-frequency-component (HFC) of PAN and MS images are readily obtained. Second, an adaptive intensity-hue-saturation (AIHS) based method is applied to generate the HFC of intensity. Finally, a dual-scale guided image filter (GIF) is utilized to calculate the difference between HFC of intensity and PAN to get the detail images. And then, these detail images are injected into the original MS image to achieve the HMS image. The proposed method is applied into testing various satellite data sets, and performs better effect on both visual quality and objective indictors than the existing methods. [ABSTRACT FROM AUTHOR]

We study spectral properties of fluorescent radiation from a two-level quantum system with broken inversion spatial symmetry, which can be implemented as a model of a one-electron two-level atom whose electric dipole moment operator has permanent unequal diagonal matrix elements. We consider the case of the excitation of this system by a bichromatic laser field consisting of a high-frequency resonance component with the frequency coinciding with the atomic transition frequency and a low-frequency component whose frequency coincides with the Rabi frequency of the high-frequency component. We show that by changing the intensity of the low-frequency component, we can efficiently control spectral properties of the fluorescent radiation of the system in the high-frequency range. We discuss possible methods for the experimental detection and practical use of the effects under study. [ABSTRACT FROM AUTHOR]

The spectrogram, based on a short-time Fourier transform, can visualize the time-dependent frequency spectrum of waves and is easy to compute. This time-frequency analysis method provides crucial information about waves generated by moving vessels and has been utilized to analyze Kelvin ship waves and internal waves. To further study the internal waves induced by a submerged body, an experiment is conducted for the towed and self-propelled SUBOFF model in a stratified fluid. The internal wave elevation signals are captured using electronic conductivity probes. Comparing with the calculation results of theoretical model, the high-frequency component of internal waves is identified. The high-frequency component has the exact same characteristics in both the towed and self-propelled model experiment and is consistent with the theoretical results for all Froude numbers. Therefore, this component is composed mainly of lee waves. Through spectral characteristics identification, a low-frequency component is discovered in the spectrogram in addition to the lee wave component. The intensity of the low-frequency component is tightly related to the vortex structure behind the submerged body. The vortex structure depends on the net momentum imparted by the submerged body. Therefore, this component is composed mainly of wake waves induced by the vortex structure. [ABSTRACT FROM AUTHOR]

Porosity is a key parameter in calculating the velocity of gas hydrate bearing sediments and quantifying the amount of gas hydrate. The variation of porosity is affected by many factors. The influences of different factors on porosity are distinct. The purpose of this paper is to analyze the main factors that affect the overall and local change of porosity in marine sediments where gas hydrate was sampled. Porosity logs were collected from ODP Leg 164, Blake Ridge, ODP Leg 204, Hydrate Ridge, and IODP expedition 311, Cascadia Margin. Based on the characteristic of porosity variation in depth, porosity was divided into three components: low frequency component, middle frequency component, and high frequency component. The factors influencing each component were discussed. From the analysis, we observed that the porosity of unconsolidated sediment was very high, and the decreasing trend of low frequency component versus depth was affected by compaction. In addition, the initial porosity and slope of low frequency component variation were affected by the content of fine grain and geothermal gradient respectively. The middle component could reflect the variation of lithology, which was affected by the content variation of different sized grains and gas hydrate. The high frequency component was affected by the frequent change of grain size. The existence of volcanic ash-rich sand caused a high value to the high frequency component. The results are applicable to porosity evaluation in gas hydrate bearing sediments. [ABSTRACT FROM AUTHOR]

The purposes of this study were to clarify if force fluctuations during steady multi-muscle contractions have a temporal correlation with a low-frequency component of rectified surface EMG (rEMG) in the involved muscles and collection of that component across muscles allows for the reconstruction of force fluctuations across a wide range of contraction intensities. Healthy young men (n = 15) exerted steady isometric plantarflexion force at 5–60% of maximal force. Surface EMG was recorded from the medial and lateral gastrocnemii, soleus, peroneus longus, abductor hallucis, and tibialis anterior muscles. The cross-correlation function (CCF) between plantarflexion force fluctuations and low-pass filtered rEMG in each muscle was calculated for 8 s. To reconstruct force fluctuations from rEMGs, the product of rEMG and an identified constant factor were summed across muscles with time-lag compensation for electro-mechanical delay. A distinct peak of the CCF was found between plantarflexion force fluctuations and rEMG in most cases except for the tibialis anterior. The CCF peak was greatest in the medial gastrocnemius and soleus. Reconstructed force from rEMGs was temporally correlated with measured force fluctuations across contraction intensities (average CCF peak: r = 0.65). The results indicate that individual surface rEMG has a low-frequency component that is temporally correlated with net force fluctuations during steady multi-muscle contractions and contributes to the reconstruction of force fluctuations across a wide range of contraction intensities. It suggests a potential applicability of individual surface EMGs for identifying the contributing muscles to controlling or disturbing isometric steady force in multi-muscle contractions. [ABSTRACT FROM AUTHOR]

Full-scale experiments in biharmonic uniaxial loading of low-modulus highly filled viscoelastic polymer-based composites were performed, and the hysteresis of the dynamic elastic modulus was obtained by changing the low-frequency component of the biharmonic loading. The effect of amplitude of the high-frequency component of the biharmonic loading law on the dynamic mechanical properties of the viscoelastic low-modulus composites is investigated. Relationships for the dynamic modulus and the loss angle at different parameters of the biharmonic loading law are found. [ABSTRACT FROM AUTHOR]

Applying ensemble empirical mode decomposition (EEMD) to the study of global food price volatility, this article decomposes an original food price series into a set of intrinsic mode functions, from high to low frequency, and a residual, which provides an explanation of how different factors contribute to each component of food price volatility. A time series analysis complements the EEMD investigation and reveals that the low-frequency component contributes more than 49% to food price volatility; notable events or food trade policies are the primary reasons for such changes. The high-frequency component is determined mainly by small events and regular market adjustments for economic growth. In the long term, food prices are determined by an intrinsic trend, triggered by economic development throughout the world. Distinct factors are involved in explaining the low and high frequencies of food prices, which makes food price volatility a complicated story to tell. [ABSTRACT FROM AUTHOR]

The removal of fog or haze from video frames and images has been a major focus in the area of computer vision since fog has a detrimental effect on monitoring and surveillance systems, as well as on the recognition of scene objects and other applications. Numerous defogging strategies have been presented thus far, including those based on the "colour-line model", polarization, "anisotropic diffusion", and the "dark channel prior" (DCP). Nevertheless, when the scene counters a thick fog and sky regions, these approaches fail to provide high-quality output. The authors suggest a novel haze/fog removal approach that uses tetrolet transformation to decompose a foggy image into low- and high-frequency components based on their structural information and dual dictionary learning-based residual frequency extractor to extract additional residual image information. DCP operation is performed on the low-frequency component to recover more fog-free information while sharpening the tetrolet coefficients extracts finer details. The inverse transformed image is then added to the residual high-frequency image component and post-processed using contrast limited adaptive histogram equalization to balance the contrast. Lastly, S and V channel gain regulator optimizes the contrast-enhanced image's colour and intensity. Compared to current methodologies, the suggested method significantly improves the overall picture quality. Quantitative and qualitative data support the statements. [ABSTRACT FROM AUTHOR]

The input of seismic wave with different frequency has a significant impact on loess slope instability. On the basis of field investigation and experiments, the particle flow software PFC2D was used to explore the effect of seismic frequency spectrum on slope instability through the process of calibrating soil microscopic parameters, model establishment, seismic wave input and other processes. The results show that: 1. The low-frequency component of the input wave is the main frequency band that causes the slope instability, the slope has amplifying effect on the low-frequency input wave, and the slope has a "filtering" effect on the high-frequency input wave; 2. The instability of the slope will cause an increase in frequency components above 10 Hz; 3. The special structure of the slope is one of the main reasons for the instability of the slope. This result has theoretical and practical significance for earthquake landslide prevention and monitoring and early warning. [ABSTRACT FROM AUTHOR]

We analyze multidecadal temperature fluctuations of the Atlantic Ocean and their influence on Northern Europe, focusing on the Baltic Sea, without a priori assuming a linear relationship of this teleconnection. Instead, we use the method of low-frequency component analysis to identify modes of multidecadal variability in the Baltic Sea temperature signal and relate this signal to the Atlantic climate variability. Disentangling the seasonal impact reveals that a large fraction of the variability in Baltic Sea winter temperatures is related to multidecadal temperature fluctuations in the North Atlantic, known as Atlantic Multidecadal Variability (AMV). The strong winter response can be linked to the interaction between the North Atlantic Oscillation and the AMV and is maintained by oceanic inertia. In contrast, the AMV does not influence the Baltic Sea's summer and spring water temperatures. [ABSTRACT FROM AUTHOR]

The two characteristics of near-fault ground motions, i.e., the forward directivity effect and permanent displacement effect, result in long period and large velocity pulse in the velocity time history and large step pulse in the displacement time history. Considering the two effects, a simple expression of continuous function for equivalent velocity pulse time history is presented in this paper. The equivalent pulse model, in which the pulse period, peak velocity and pulse shape are described by five parameters, is highly advantageous to fit and simulate the pulse-type velocity time history. The equivalent pulse model comprises only one low-frequency component while the high-frequency component of a pulse-type earthquake record cannot be considered. Based on 28 records of 11 earthquakes, the pulse frequency of pulse-type records is generally less than 1 Hz. Therefore the low-frequency component and high-frequency component are simulated respectively and combined them together to generate a pulse-type ground motion. [ABSTRACT FROM AUTHOR]

Bearing fault diagnosis is essential for reducing equipment operating and maintenance costs. We propose a bearing fault diagnosis method that combines hierarchical symbolic fuzzy entropy (HSFE) and sparse Bayesian extreme learning machine (SBELM). Multiscale symbolic fuzzy entropy (MSFE) is a recently proposed fault diagnosis method. Compared with multiscale sample entropy (MSE), multiscale permutation entropy (MPE), and multiscale fuzzy entropy (MFE), MSFE has high noise resistance and computational efficiency. The multiscale analysis method using the average operator can only extract information in the low frequency component, but cannot use the feature information in the high frequency component. Aiming at this defect, symbolic fuzzy entropy is formed by combining the hierarchical decomposition with the symbolic fuzzy entropy. Hierarchical decomposition uses average and difference operators to decompose the sequence, which can extract the fault information of high-frequency and low-frequency components at the same time. Then, the extracted fault information is efficiently identified and classified using the SBELM. The effectiveness and superiority of the HSFE method are verified by simulation signals and experimental vibration signals. At the same time, experimental comparisons were carried out using MPE, HPE, MSE, HSE, MSFE and HSFE. The experimental results indicate that the HSFE method has the best effect on the identification of rotating machinery fault types. [ABSTRACT FROM AUTHOR]

Image security is an essential aspect of research in network transmission. To improve the security of image encryption, a two-dimensional Fibonacci combined with cubic and sine map (2D-FCSM) is designed. Through a series of randomness tests, the proposed map is shown to have a wide range of chaotic and hyperchaotic properties. Besides, a pseudo-wavelet transform (PWT) decomposition method is proposed. The method extracts the main information of the image by resampling and preprocessing to reduce the amount of operational data and improve the efficiency. Further, an efficient image encryption algorithm is designed using 2D-FCSM and PWT. Firstly, the image is decomposed using the PWT, and then, pseudo-random sequences are generated by the 2D-FCSM for pixel-level processing of the low-frequency component and block-level processing of the detail components. The experimental results show that the proposed algorithm has desirable encryption effect, strong security and high encryption efficiency. [ABSTRACT FROM AUTHOR]

The geological structure and stratum lithology have important roles in the seismic stability of complex slopes; however, their roles complicate engineering construction. Four three-dimensional, layered granite slope models with infinite boundaries were modeled via the finite element method. The seismic response characteristics of slopes are systematically analyzed in the time–frequency domain. A frequency-domain analysis method of complex slopes, including modal and spectrum conjoint analysis, is proposed. Modal analysis can directly display the main vibration modes of slopes. The combination of modal and spectral analysis can clarify the inherent characteristics of slopes and reveal the interaction mechanism between the inherent frequency of slopes and their dynamic characteristics. The results illustrate that structural planes have significant effects on the propagation characteristics of waves within rock masses, and complex refraction/reflection phenomena occur near these discontinuities, thus leading to different dynamic response characteristics in the slope. Layered slopes have an apparent magnification effect of slope surface and altitude. The directions of seismic excitation and structural plane types affect the dynamic response of slopes. Horizontal waves mainly affect the middle and upper parts of high-steep slopes, while vertical waves have an obvious influence on the slope crest. Additionally, Fourier spectral analysis shows that structural planes have filtering effects on high-frequency waves. Combined with modal analysis, this finding further explains that the high-frequency section of waves mainly triggers local deformation of slopes, while the low-frequency component controls their overall deformation. The instability regions and evolution process of slopes were predicted based on time–frequency conjoint analysis. [ABSTRACT FROM AUTHOR]

The excess pore water pressure generated under the combined vertical and horizontal earthquake excitations is generally greater than that under the unidirectional excitation, which may further affect the dynamic response of soil-pile-superstructure-quay wall (SPSQ) system. This study conducted a coupled effective-stress analysis for the response of SPSQ system to liquefaction-induced lateral displacement under horizontal and vertical earthquake excitations. To accurately describe the lateral displacement behind the quay wall, the liquefaction behavior of soils was described by a modified generalized plasticity model with parameters properly determined from laboratory tests. The numerical model of the SPSQ system was validated against the previously reported centrifuge model tests. The results show that the earthquake excitation with abundant low-frequency component causes greater residual lateral displacements of pile cap (ux,RC) and quay wall (ux,RQ) than that with abundant high-frequency component. The ux,RC and ux,RQ tend to increase as the peak vertical acceleration increases for both vertical and inclined piles. Increasing the fixity of the quay wall significantly reduces the influence of vertical ground motion on the ux,RC and ux,RQ. The polarity reversal of the vertical ground motion also has a significant effect on the ux,RC and ux,RQ and should be considered in the analyses. In addition, the lateral displacement of liquefied ground causes an amount of rotation of the cap of the inclined pile, probably leading to the potential shear failure at the head of piles. Special consideration should be given to the earthquake-induced shear force at deeper location because the shear force could be significantly greater than that at the head of both inclined and vertical piles in certain cases. [ABSTRACT FROM AUTHOR]

Amphibians have inner ears with two sensory papillae tuned to different frequency ranges of airborne sounds. In frogs, male advertisement calls possess distinct spectral components that match the tuning of one or both sensory papillae. Female preferences for the spectral content of advertisement calls can depend on signal amplitude and can vary among closely related lineages. In this study of Cope's gray tree frog (Hyla chrysoscelis), we investigated the amplitude dependence of female preferences for the spectral content of male advertisement calls, which have a "bimodal" spectrum with separate low-frequency (1.25 kHz) and high-frequency (2.5 kHz) components. In two-alternative choice tests, females generally preferred synthetic calls with bimodal spectra over "unimodal" calls having only one of the two spectral components. They also preferred unimodal calls with a high-frequency component over one with the low-frequency component. With few exceptions, preferences were largely independent of amplitude across both a 30 dB range of overall signal amplitude and an 11 dB range in the relative amplitudes of the two spectral components. We discuss these results in the context of evolutionary lability in female preferences for the spectral content of advertisement calls in North American tree frogs in the genus Hyla. [ABSTRACT FROM AUTHOR]

Abstract—Problems of transport-noise monitoring have been considered. The existing approaches to transport-noise monitoring have a number of disadvantages. The influence of noise from transport and other sources on public health was estimated. The results showed there to be a reliable, statistically significant dependence of the increase in illness among the population on acoustical pollution. A new system of transport-noise monitoring was suggested and approved in the conditions of Russia's Samara oblast. This system has a number of advantages for acoustic research. The acoustic characteristics of separate vehicles and their spectral values were investigated as well. Analysis of our measurement results of the transport noise from cars of different kinds shows that the most significant noise values are observed within a low-frequency range. Thus, when reducing transport noise down to appropriate hygienic values, special attention should be paid to reduction of the low-frequency component of noise. [ABSTRACT FROM AUTHOR]

The effects of septoplasty and sinus lifting simulation in rats on changes in the frequency domain of heart rate variability were compared. In the early postoperative period, the low-frequency component increases, and the high-frequency component decreases. The VLF range also increased. This indicates an increase in the activity of the sympathetic nervous system and a shift in metabolism under the influence of post-surgical inflammation. [ABSTRACT FROM AUTHOR]

Purpose: Patients with chronic chagasic cardiomyopathy with preserved ventricular function present with autonomic imbalance. This study evaluated the effects of exercise training (ET) in restoring peripheral and cardiac autonomic control and skeletal muscle phenotype in patients with subclinical chronic chagasic cardiomyopathy. Methods: This controlled trial (NCT02295215) included 24 chronic chagasic cardiomyopathy patients who were randomized www.random.org/lists/ into two groups: those who underwent exercise training (n = 12) and those who continued their usual activities (n = 12). Eight patients completed the exercise training protocol, and 10 patients were clinically followed up for 4 months. Muscular sympathetic nerve activity was measured by microneurography and muscle blood flow (MBF) using venous occlusion plethysmography. The low-frequency component of heart rate variability in normalized units (LFnuHR) reflects sympathetic activity in the heart, and the low-frequency component of systolic blood pressure variability in normalized units reflects sympathetic activity in the vessels. The infusion of vasoactive drugs (phenylephrine and sodium nitroprusside) was used to evaluate cardiac baroreflex sensitivity, and a vastus lateralis muscle biopsy was performed to evaluate atrogin-1 and MuRF-1 gene expression. Results: The baroreflex sensitivity for increases (p = 0.002) and decreases (p = 0.02) in systolic blood pressure increased in the ET group. Muscle blood flow also increased only in the ET group (p = 0.004). Only the ET group had reduced resting muscular sympathetic nerve activity levels (p = 0.008) and sympathetic activity in the heart (LFnu; p = 0.004) and vessels (p = 0.04) after 4 months. Regarding skeletal muscle, after 4 months, participants in the exercise training group presented with lower atrogin-1 gene expression than participants who continued their activities as usual (p = 0.001). The reduction in muscular sympathetic nerve activity was positively associated with reduced atrogin-1 (r = 0.86; p = 0.02) and MuRF-1 gene expression (r = 0.64; p = 0.06); it was negatively associated with improved baroreflex sensitivity both for increases (r = –0.72; p = 0.020) and decreases (r = –0.82; p = 0.001) in blood pressure. Conclusions: ET improved cardiac and peripheral autonomic function in patients with subclinical chagasic cardiomyopathy. ET reduced MSNA and sympathetic activity in the heart and vessels and increased cardiac parasympathetic tone and baroreflex sensitivity. Regarding peripheral muscle, after 4 months, patients who underwent exercise training had an increased cross-sectional area of type I fibers and oxidative metabolism of muscle fibers, and decreased atrogin-1 gene expression, compared to participants who continued their activities as usual. In addition, the reduction in MSNA was associated with improved cardiac baroreflex sensitivity, reduced sympathetic cardiovascular tone, and reduced atrogin-1 and MuRF-1 gene expression. Trial registration: ID: NCT02295215. Registered in June 2013. [ABSTRACT FROM AUTHOR]

In order to deal with the pseudo-Gibbs phenomenon and noise interference in the image enhancement, a novel remote sensing image enhancement technique based on unsharp masking and non-subsampled shearlet transform (NSST) is proposed in this paper. The steps of the proposed model are described as follows: Firstly, the input image is decomposed into one low-frequency component and several high-frequency components by the NSST transform; Secondly, the weighted guided image filter is performed on the low-frequency component to improve the contrast of the image, and the hard thresholding is used to suppress the noise of the high-frequency components; Thirdly, the inverse non-subsampled shearlet transform is utilized to reconstruct the image; Finally, the unsharp masking model is performed on the reconstructed image, and the final enhanced image is obtained. Experimental results and comparison analysis demonstrate that the proposed framework outperforms others in terms of remote sensing image enhancement. [ABSTRACT FROM AUTHOR]

The Internet of Medical Things (IoMT) has included a new layer for development and smart infrastructure growth in the medical field. Besides, the medical data on IoMT systems are constantly expanding due to the rising peripherals in the health system. This paper introduces a new fusion technique in the shearlet domain to improve existing methods, which may provide medical image fusion in the IoMT system. In this paper, firstly low and high frequencies NSST coefficients are obtained of both input images. Over the low frequency component, a new Multi local extrema (MLE) based decomposition is performed to get more detail features (Coarse and detail layers). Over these MLE features saliency based weighted average is performed using co-occurrence filter to get the enhanced low frequency NSST Coefficients. These enhanced low frequency NSST Coefficients of both input images are fused using the proposed weighted function. In high frequency NSST Coefficients, local type-2 fuzzy entropy-based fusion is performed. Finally, inverse NSST is performed to get the final fused image. The experimental results are evaluated and compared with existing methods by visually and also by performance metrics. After a critical analysis, it was found that the results of the proposed method give better outcomes compared to similar and recent existing schemes. [ABSTRACT FROM AUTHOR]

We examined whether the recovery from fatigue could be facilitated by viewing the children's faces. Seventeen healthy mothers with child or children over 6 years old participated in our experiment. After performing a 2-back task for 40 min, they viewed the pictures of children's and adult's faces in the target and control conditions, respectively. The target and control conditions were performed on the separate days in a two-crossover design. Neural activity caused by viewing the children's faces was recorded using magnetoencephalography and electrocardiography was performed to assess the index of heart rate variability (low-frequency component power/high-frequency component power ratio, LF/HF) reflecting fatigue. The subjective level of mental fatigue sensation and LF/HF ratio was decreased after viewing the children's faces and the overactivation of the visual cortex caused by performing the 2-back task, assessed by the alteration of alpha band power in the visual cortex, was attenuated by viewing the children's faces, suggesting that viewing the children's faces affected the time course of mental fatigue after performing the 2-back task. [ABSTRACT FROM AUTHOR]

In this study a heart-beat-interval counterbased a low-power PPG microsystem is proposed for accurate assessment of the mental stress. The designed microsystem incorporates a new low power PPG sensing readout with a Time-to-digital converter for the long-time continuous heart-beat-interval estimation. Further the analog front-end circuit is implemented in the integrated chip having an area of 1.4 mm2 and fabricated using the TSMC 0.18 µm process. Measured linear sensing range of the designed readout is 20 nA to 110 µA. With the 1.8 V standard supply, measurement results show that the power consumption of the PPG readout circuit is 52.2 µW, while the total measured power consumption of the designed chip is 100.2 µW. To evaluate the performance of the proposed microsystem in mental stress assessment, the designed circuit is integrated with OLED-OPD sensor and then applied to the wrist of two healthy subjects under different stressors, (e.g., laughing, solving a mathematical problem, hearing loud audio/sound, and moving neck). The statistical analysis of the detected PPG signal and measured on-chip-heart rate interval in time domain shows that the mean value of peak-to-peak interval, entropy, and stress-induced vascular index increases during the stress. In addition, in the frequency domain analysis of the heart rate variability (HRV) shows that the ratio of the low frequency component to the high frequency component is increased during the stress. Thus, the indices of HRV measured directly from the designed readout system can serve effectively as indication of heart rate variability and mental stress. [ABSTRACT FROM AUTHOR]

Pulse-like ground motions may have only a distinct strong pulse or multiple pulses within the velocity time-history. These intrinsic pulses are hidden in low-frequency components that can impose extreme seismic demands on structures. This study presents a simple approach based on the empirical Fourier decomposition (EFD) to extract the intrinsic pulses of pulse-like ground motions. Based on the proposed approach, first, the original ground velocity is decomposed into several Fourier spectrum components (FSCs) via the EFD method. Among these FSCs, the significant low-frequency components are identified based on a proposed relative energy indicator (Ere). Ere is defined as the ratio of the Fourier square amplitude of the FSC to that of the original ground velocity. Next, pulse component is obtained by superimposing the minimum number of significant low-frequency components so that their total energy is above than 70% of the original ground velocity energy. Finally, the strong pulse is extracted from the pulse component by the peak point method. Results obtained by the EFD decomposed method are compared to those obtained from wavelet method for 91 pulse-like ground motions. The results show that the proposed method can extract the intrinsic pulses of pulse-like ground motions with reasonable accuracy. The proposed approach is further applied for classification of near-fault pulse-like ground motions in a dataset of ground motion records. According to the classification results, ground motions with a relative energy value greater than 0.30 can be characterized as pulse-like. Highlights: • The intrinsic pulses of pulse like ground motions are extracted based on the empirical Fourier decomposition (EFD) technique. • The Fourier component with the high relative energy can be considered as significant low-frequency component. • Ground motions with Ep values above 0.30 are considered as pulse-like ground motions. [ABSTRACT FROM AUTHOR]

During unilateral contractions, muscular activation can be detected in both active and resting limbs. In healthy populations, the latter is referred to as physiological mirror activity (pMA). The study of pMA holds implications for clinical applications as well as the understanding of bilateral motor control. However, the underlying mechanisms of pMA remain to be fully resolved. A commonality of prevailing explanatory approaches is the concept of shared neural input. With this study, we, therefore, aimed to investigate neural input in the form of multiple analyses of surface electromyography (sEMG) recordings in the frequency domain. For this purpose, 14 healthy, right-handed males aged 18–35 years were recruited. All participants performed a pinch-force task with the dominant hand in a blockwise manner. In total, 9 blocks of 5 contractions each were completed at 80% of maximum force output. Muscle activity was recorded via sEMG of the first dorsal interosseous muscle of the active and resting hand. We analyzed (1) spectral features as well as (2) intermuscular coherence (IMC). Our results demonstrate a blockwise increase in median frequency, mean frequency, and peak frequency in both hands. Frequency ratio analyses revealed a higher low-frequency component in the resting hand. Although we were able to demonstrate IMC on an individual level, results varied greatly and grand-averaged IMC failed to reach significance. Taken together, our findings imply an overlap of spectral properties between active and passive hands during repeated unilateral contractions. Combined with evidence from previous studies, this suggests a common neural origin between active and resting hands during unilateral contractions possibly resulting from a reduction in interhemispheric inhibition due to high force demands. Nevertheless, the exploratory nature of this study necessitates the classification of our results through follow-up studies. [ABSTRACT FROM AUTHOR]

We propose an optimization algorithm to speed up the computation of a high-frequency geoid based on the surface integral of Stokes's formula. Stokes's integral computes high-frequency geoid undulations from the terrestrial gravity data. The global geopotential model (GGM) provides the respective low-frequency component of the geoid solution. The combination of high and low-frequency geoid solutions with the associated corrections represents the final geoid model. However, the practical implementation of Stokes's integration is time-consuming over dense gravity grids and needs to be optimized efficiently. Therefore, the vectorization techniques and relational operators have been utilized in Matlab®; and Octave to the loops and conditional statements. The efficiency of the presented algorithm is evaluated and tested on different gravity grids and capsize values before and after the optimization. The total run time (TRT) of the original and modified Stokes's integral is employed to assess the efficiency of the algorithm. Finally, our algorithm shows high performance in all tested scenarios. It reduces the TRT by 7 times on 1 arc-min resolution grid with varying capsize values from 0.25∘ to 1.5∘. [ABSTRACT FROM AUTHOR]

To investigate the distributing disciplinarian of ground motion parameters on the earth fissure site during strong earthquakes, a series of shaking table tests were designed and conducted based on 1:15 scaled models. Test results showed significant differences in the ground motion parameters (including ground motion intensity indices, spectrum characteristics and strong motion duration) between the hanging-wall and footwall caused by the earth fissure. Acceleration response, displacement response and Arias Intensity response on both sides of earth fissure indicated that the earth fissure site on the hanging-wall was destroyed more seriously. The distributing disciplinarian of amplification factors showed clear "hanging-wall and footwall effects", which were more remarkable nearby the fissure zones. The low-frequency component of the seismic wave was richer after selectively filtering in the soil medium. By comparing the predominant period and mean period of the hanging-wall and footwall, it was found that vibration frequency on the hanging-wall was greater than that on the footwall. Minimum values of strong motion duration were recorded on the hanging-wall close to the fissure and increased from the fissure to both sides. [ABSTRACT FROM AUTHOR]

Measuring and controlling external force from the environment and human beings are essential to realize the future application of the robot systems for medical, nursing, and personal support systems. This paper proposes a friction and noise suppression for force control system based on the integration of the reaction torque observer and force (torque) sensor information. The proposed method performs external force estimation by integrating the low-frequency component information of the force sensor and the high-frequency component of the force information estimated by reaction torque observer (RTOB). By using the low-frequency component of the force sensor, the effect of static friction can be suppressed, and the high-frequency part of RTOB can be used to attenuate the noise component. As a result, the performance of the force control system can be enhanced. The proposed method is evaluated through the experiments of the force control and bilateral control as a position/force hybrid control. [ABSTRACT FROM AUTHOR]

A technique and an algorithm of digital surface image processing are proposed to increase the validity of real-time detection of small size defects. The algorithm is implemented in the MATLAB programming environment. The technique is based on segmentation of the high-frequency component of surface texture because small size defects are especially pronounced in this component. The high-frequency component, in particular roughness, is extracted by means of wavelet transform for frequency components separation and homomorphic filtration for compensation of low-frequency distortion caused by nonuniform illumination of test surface. Segmentation of the high-frequency texture component consists in formation of a binary image using the texture descriptors derived from the gray-level co-occurrence matrix as the segmentation threshold. The proposed technique and algorithm are approved in applications to defect detection for a simulated surface, for real ground surface of hardened steel, and for surfaces of carbon fiber reinforced plastic composite. Extraction efficiency of the high-frequency component of surface texture is shown. It is found that texture descriptors, "contrast' and "energy," can be applied as segmentation thresholds for defect extraction/determination on the ground (anisotropic) surface while segmentation of an image of a plastic composite (isotropic) surface is effective just with "energy" as a threshold. The proposed technique can be applied for simultaneously real-time monitoring the surface texture and detecting the small size defect in machine vision systems during production and operation of tribosystems. [ABSTRACT FROM AUTHOR]

Physical fatigue can be assessed using heart rate variability (HRV). We measured HRV at rest and in a fatigued state using impulse-radio ultra wideband (IR-UWB) radar in a noncontact fashion and compared the measurements with those obtained using electrocardiography (ECG) to assess the reliability and validity of the radar measurements. HRV was measured in 15 subjects using radar and ECG simultaneously before (rest for 10 min before exercise) and after a 20-min exercise session (fatigue level 1 for 0–9 min; fatigue level 2 for 10–19 min; recovery for ≥ 20 min after exercise). HRV was analysed in the frequency domain, including the low-frequency component (LF), high-frequency component (HF) and LF/HF ratio. The LF/HF ratio measured using radar highly agreed with that measured using ECG during rest (ICC = 0.807), fatigue-1 (ICC = 0.712), fatigue-2 (ICC = 0.741) and recovery (ICC = 0.764) in analyses using intraclass correlation coefficients (ICCs). The change pattern in the LH/HF ratios during the experiment was similar between radar and ECG. The subject's body fat percentage was linearly associated with the time to recovery from physical fatigue (R2 = 0.96, p < 0.001). Our results demonstrated that fatigue and rest states can be distinguished accurately based on HRV measurements using IR-UWB radar in a noncontact fashion. [ABSTRACT FROM AUTHOR]

Infraslow activity (ISA) is a biomarker that has recently become of interest in the characterization of seizure recordings. Recent data from a small number of studies have suggested that the epileptogenic zone may be identified by the presence of ISA. Investigation of low frequency activity in clinical seizure recordings, however, has been hampered by technical limitations. EEG systems necessarily include a high-pass filter early in the measurement chain to remove large artifactual drifts that can saturate recording elements such as the amplifier. This filter, unfortunately, attenuates legitimately seizure-related low frequencies, making ISA difficult to study in clinical EEG recordings. In this study, we present a deconvolution-based digital inverse filter that allows recovery of attenuated low frequency activity in intracranial recordings of temporal lobe epilepsy patients. First, we show that the unit impulse response (UIR) of an EEG system can be characterized by differentiation of the system's step response. As proof of method, we present several examples that show that the low frequency component of a high-pass filtered signal can be restored by deconvolution with the UIR. We then demonstrate that this method can be applied to biologically relevant signals including clinical EEG recordings obtained from seizure patients. Finally, we discuss how this method can be applied to study ISA to identify and assess the seizure onset zone. [ABSTRACT FROM AUTHOR]

An optical watermarking method is presented based on computational ghost imaging and multiple logistic maps. Instead of directly embedding an original watermark into the host image, the object image considered as the watermark is encoded to a series of bucket values using computational ghost imaging in the beginning. The host image is decomposed into four components using a single-level discrete wavelet transform. Then, all or part of bucket values is fused with the low-frequency coefficients of the host image. After applying the corresponding inverse wavelet transform, the watermarked host image can be obtained with high imperceptibility. In this process, a sequence generated with a logistic map is used to scramble bucket values, and another sequence is used to randomly select the fusion positions in the low-frequency component. In this way, the security level of the proposed method can be greatly enhanced when initial values and bifurcation parameters of multiple logistic maps are considered secret keys. Optical experiments are performed to verify the validity of the proposed watermarking method and the robustness resisting against various attacks such as noise and occlusion attack. [ABSTRACT FROM AUTHOR]

With the advancement of multimedia technology and coming of big data era, the size of image data is significantly increased. However, the traditional image encryption methods cannot solve the emerging problems of efficient compression. To settle with this challenge, an effective content-adaptive image compression and encryption method based on compressive sensing and double random phase encoding (DRPE) is proposed in this paper. The original image is converted to one low-frequency part and three high-frequency parts by DWT and then permutated by sorting-based chaotic sequences. Afterward, a novel measurement matrix optimization algorithm based on adaptive step size is presented to measure the high-frequency components. To enhance the security of the scheme, the DRPE, quantization, and diffusion are successively performed on the complex matrix composed of the shuffled low-frequency component and three measurement value matrices to obtain the cipher image. Logistic-Sine chaotic system is utilized to produce the chaotic keystreams for the encryption process, and its system parameter and initial value are determined by the information entropy of the plain image and external key parameters, so that the proposed cipher can withstand known-plaintext and chosen-plaintext attacks effectively. Numerical experiments demonstrate the effectiveness of the proposed image compression and encryption algorithm. [ABSTRACT FROM AUTHOR]

Behavioral and electrophysiological experiments were conducted to examine whether frequency-modulated electrocommunication signals are detected by the ampullary electroreceptor system in Eigenmannia. First, frequency-modulated electric organ discharges were found to contain a low-frequency component that could be detected by the ampullary system. Second, fish were successfully trained to distinguish a frequency-modulated signal, which contained a low-frequency component as in natural signals, from an artificial signal in which the low-frequency component was eliminated but still modulated in frequency. Subsequently, the trained fish responded without reinforcement to a low-frequency sinusoidal signal which mimicked the low-frequency component in the frequency-modulated signal, suggesting that the fish used the ampullary system to detect frequency modulation. Finally, physiological recording from ampullary afferent fibers demonstrated that they respond to frequency-modulated signals as predicted from the signal's low-frequency component. Electrophysiological study also showed that detection of frequency modulation by the ampullary system is immune to the presence of other constant electric organ discharges. [ABSTRACT FROM AUTHOR]

Due to the prolonged inflammatory process induced by infection of the novel severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), indices of autonomic nervous system dysfunction may persist long after viral shedding. Previous studies showed significant changes in HRV parameters in severe (including fatal) infection of SARS-CoV-2. However, few studies have comprehensively examined HRV in individuals who previously presented as asymptomatic or mildly symptomatic cases of COVID-19. In this study, we examined HRV in asymptomatic or mildly symptomatic individuals 5–7 weeks following positive confirmation of SARS-CoV-2 infection. Sixty-five ECG Holter recordings from young (mean age 22.6 ± 3.4 years), physically fit male subjects 4–6 weeks after the second negative test (considered to be the start of recovery) and twenty-six control male subjects (mean age 23.2 ± 2.9 years) were considered in the study. Night-time RR time series were extracted from ECG signals. Selected linear as well as nonlinear HRV parameters were calculated. We found significant differences in Porta's symbolic analysis parameters V0 and V2 (p < 0.001), α2 (p < 0.001), very low-frequency component (VLF; p = 0.022) and respiratory peak (from the PRSA method; p = 0.012). These differences may be caused by the changes of activity of the parasympathetic autonomic nervous system as well as by the coupling of respiratory rhythm with heart rate due to an increase in pulmonary arterial vascular resistance. The results suggest that the differences with the control group in the HRV parameters, that reflect the functional state of the autonomic nervous system, are measurable after a few weeks from the beginning of the recovery even in the post-COVID group—a young and physically active population. We indicate HRV sensitive markers which may be used in long-term monitoring of patients after recovery. [ABSTRACT FROM AUTHOR]