Low-frequency Components Research Articles

Pseudo-set Frequency Refinement architecture for fine-grained few-shot class-incremental learning

Few-shot class-incremental learning was introduced to solve the model adaptation problem for new incremental classes with only a few examples while still remaining effective for old data. Although recent state-of-the-art methods make some progress in improving system robustness on common datasets, they fail to work on fine-grained datasets where inter-class differences are small. The problem is mainly caused by: (1) the overlapping of new data and old data in the feature space during incremental learning, which means old samples can be falsely classified as newly introduced classes and induce catastrophic forgetting phenomena; (2) lacking discriminative feature learning ability to identify fine-grained objects. In this paper, a novel Pseudo-set Frequency Refinement (PFR) architecture is proposed to tackle these problems. We design a pseudo-set training strategy to mimic the incremental learning scenarios so that the model can better adapt to novel data in future incremental sessions. Furthermore, separate adaptation tasks are developed by utilizing frequency-based information to refine the original features and address the above challenging problems. More specifically, the high and low-frequency components of the images are employed to enrich the discriminative feature analysis ability and incremental learning ability of the model respectively. The refined features are used to perform inter-class and inter-set analyses. Extensive experiments show that the proposed method consistently outperforms the state-of-the-art methods on four fine-grained datasets.

Exploring New Frontiers: XCEEMDAN, Bidirectional LSTM, Attention Mechanism, and Spline in Stock Price Forecasting

The Attention Mechanism is acknowledged as a machine learning method proficient in managing relationships within sequential data, surpassing traditional models in this regard. However, the unique characteristics of stock data, including substantial volatility, multidimensionality, and non-linear patterns, present challenges in attaining accurate forecasts of stock prices. This research aims to tackle these hurdles by enhancing a prior model through the incorporation of an Attention Mechanism, resulting in an enhanced model. The forecasted data are standardized and prepared for analysis before undergoing signal decomposition into high and low-frequency components. Subsequently, the Attention Mechanism processes the high-frequency signals. Evaluation entails comparing the performance of the proposed model with that of the previous model using identical parameters. The findings indicate that the proposed model achieves a reduced RMSE value of 0.5708777053 compared to the previous model's average RMSE value of 0.5823726212, indicating enhanced accuracy in stock price prediction. This approach is anticipated to make a substantial contribution to the advancement of more dependable and effective stock price prediction models, addressing the limitations of prior methodologies

Analysis of DC-Link Low-Frequency Current Harmonics in Multi-Source Multi-Three-Phase Electric Drives

In a multi-source permanent magnet synchronous motor (PMSM) drive, three distinct winding structures can be implemented: multi-sector, multi-three-phase, and highly coupled. However, due to variations in the magnetic coupling between windings, their low-frequency DC-link current ripple components differ. This paper presents a method to identify the phenomena associated with each low-frequency harmonic content. Three analytical models are developed for the DC current ripple induced by unbalanced winding, counter-electromotive force (back-EMF) harmonics and aliasing effects, respectively, with the results validated through simulations. Experimental validation is conducted for highly coupled winding drives, demonstrating agreement with the analytical models and simulations. The maximum DC current ripple ratio found in the analytical model, the simulation and the experiments is less than 15%, which is deemed acceptable for motor drive applications.

Cardiohemodynamic responses and heart rate variability following an active orthostatic test among male residents of the North with different NOS3 (rs2070744) genotypes

AIM: This study explored associations between the -786TC (rs2070744) genetic polymorphism of the NOS3 gene and the main indices of systemic hemodynamics and heart rate variability following an active orthostatic test in men living in the North. MATERIAL AND METHODS: Eighty-three healthy men aged 33.5±1.5 yеаrs on average, who were permanent residents of the Magadan Region, comprised the sample. The participants underwent both resting and active orthostatic testing modes. Cardiovascular system variables were recorded using an automatic tonometer. Hemodynamic indices were then calculated. Short-term heart rate variability in frequency and spectral areas was simultaneously measured using the Varikard hardsoft complex unit. Genotyping was conducted using polymerase chain reaction. The sample was then divided into two groups: Group 1 consisted of homozygotes with the TT genotype (n=34), while Group 2 comprised carriers of the NOS3*C allele variant (genotypes TC+CC) associated with reduced nitric oxide production (n=49). RESULTS: By examining the complex vasomotor, chrono- and inotropic reactions of hemodynamic and heart rate variables during the active orthostatic test, we were able to discern unique patterns in the response of the two groups under study. Men in Group 1 demonstrated an elevated cardiac output response during orthostatic changes, while maintaining consistent vascular resistance values. This was accompanied by a shift towards sympathetic autonomic activity and an increase in the very low-frequency component of heart rate variability. In Group 2, individuals with sympathetic insufficiency and increased vascular resistance during the orthostatic test showed a 35% increase in the low-frequency component of the cardiac rhythm reflecting the importance of this indicator as a stimulator of blood pressure rhythm fluctuations mediated by baroreflex mechanisms. CONCLUSION: Our findings suggest that men lacking the NOS3*С allele variant in their genotype demonstrate more favorable responses to the active orthostatic test. This may reflect higher level of cardiovascular functional reserves. The 786TC (rs2070744) polymorphism of the NOS3 gene can be considered as a marker of cardiohemodynamic status and autonomic regulations during functional exercise, such as an active orthostatic test.

Advanced multiscale modal and frequency analysis of swirling spray flame near to lean blowout

This study provides an in-depth characterization of Jet-A1 swirled flames' dynamics using advanced decomposition techniques on high-speed OH* chemiluminescence images. Research conducted in a 300-kW combustor with global fuel-to-air ratios Φ = 0.36, 0.24, and 0.18 reveals dominant low-frequency components under ultra-lean conditions through statistical and wavelet analyses. Integrating Proper Orthogonal Decomposition (POD), Dynamic Mode Decomposition (DMD), and Multiscale Proper Orthogonal Decomposition (mPOD) enhances understanding by detailing the energy and frequency of flame modal structures. Observations show that as Φ decreases, flame size and intensity reduce, while fluctuations increase, indicating a transition towards unstable combustion dynamics. Furthermore, the frequency and intensity of burst phenomena increase, particularly in higher modes, indicating the system's approach to lean blowout (LBO). The application of nonlinear time series analysis, including autocorrelation (AFC) and phase space reconstruction, to mPOD eigenvalues, detects early warning signs of LBO. At lower Φ, the ACF reveals significant and frequent bursts, indicating high instability and intermittent behavior. Phase space reconstruction shows distorted orbits with a spiral-like structure, characteristic of substantial damping and irregular behavior near blowout conditions.

Influence of trailing edge radius of intake struts on excitation force and vibration of rotor blades

Adjusting the trailing edge radius of the intake struts may be advantageous in suppressing the vibration of compressor rotor blades. To explore the impact of the intake struts trailing edge radius on the excitation force and vibration, this study focuses on a compressor with intake struts, and fluid and vibration calculations were conducted. The study revealed that decreasing the trailing edge radius led to a reduction in separation near the strut’s trailing edge, resulting in a narrower wake and weakened mixing near the trailing edge. This caused the total pressure loss region induced by the wake to become more elongated in the low-frequency component, leading to a nonlinear decrease in total pressure amplitude with the reduction of the trailing edge radius. As the trailing edge radius decreased, the excitation force and vibration amplitude of the first-stage compressor rotor blades decreased, while the excitation force distribution showed little variation. The research findings provide insights for the design of intake struts.

Study on partial load vortex and pressure pulsation characteristics of Francis turbine

Abstract Under partial load condition of the Francis turbine, problems such as hydraulic vibration, noise, and high amplitude pressure pulsation that endanger the safe and efficient operation of the unit are inevitable during the transient process. Based on dynamic grid technology and CFD technology, unsteady numerical simulation was conducted for the closing process of the active guide vane from 54% opening to 38% opening, and the evolution characteristics of internal vortex and pressure pulsation were analyzed. The results show that there is always a vortex structure at the crown of the runner during the transition process of variable load. Because of the vortex structure, a “banded” low-pressure zone appears on the suction surface of the blade, which gradually approaches the lower ring of the runner as the vortex structure develops. The analysis of the pressure signal in the runner region shows that the pressure coefficient on the suction surface fluctuates greatly due to the influence of the distribution position of the vortex structure, and the evolution of the vortex structure from continuous to local fracture will lead to a sudden increase of the pressure coefficient. In addition, the frequency components within the runner domain include the frequency of the movable guide vanes passing through the blade and the low-frequency components caused by the evolution of eddy currents within the runner.

A Tempered Fractional Kinetic Transport Theory for Energetic Particle Interaction with Quasi-two-dimensional Turbulence in the Large-scale Solar Wind

Observational evidence is accumulating that turbulence in the solar wind is intermittent (non-Gaussian) because of the strong presence of a quasi-two-dimensional (quasi-2D), low-frequency turbulence component containing nonpropagating, closed, small-scale magnetic flux ropes with open meandering field lines in between. le Roux & Zank showed how one can derive fractional focused and Parker-type transport equations that model large-scale anomalous transport in the solar wind as the outcome of energetic particle interaction with quasi-2D turbulence. In this follow-up paper this theory is developed further to address certain limitations. (i) The second moment of the Lévy probability distribution function (PDF) specified in the theory for the particle step size is infinite, indicating unphysical transport. (ii) The expected transition of energetic particle transport from anomalous to normal diffusion beyond a certain critical transport distance was not included. (iii) The competition between anomalous diffusion and advection is not properly sustained at late times. Shortcomings (i) and (ii) are addressed by introducing an exponentially truncated Lévy PDF for the energetic particle step size in the theory, resulting in revised tempered fractional focused and Parker-type transport equations featuring tempered fractional derivatives that enable modeling of tempered Lévy flights. Furthermore, these equations are cast in a tempered fractional telegrapher form to investigate whether the fractional wave equation part of the equation can restore causality in unscattered particle transport during early times and in Lévy flights during intermediate times (Lévy walks). They are also transformed into a tempered fractional Fokker–Planck form to overcome limitation (iii).

Study on the design of short blade offset for the long and short blade runner of 1000 MW hydraulic turbine units

Abstract For such complex rotating machinery as hydraulic turbine, the hydraulic operation characteristics of the hydraulic turbine unit are significantly impacted by the short blade of the runner used as the splitter blade. To find the optimum position of the short blade, the study object is the 1000 MW hydraulic turbine, selects three circumferential offset positions of the short blade for numerical simulation calculation, obtains the runner flow pattern at different offsets, and explores the impact on the short blade offset on the vortex and pressure pulsation in the runner. The results show that the counterclockwise offset of the short blade will improve the flow pattern of the runner, reduce the scale of vortex in the runner and enhance the efficiency of the hydraulic turbine. The counterclockwise offset will increase the interference while decreasing the pressure pulsation in the vaneless region, at the runner’s inlet, and downstream of the short blade. When the offset δ=0.6, the peak-valley difference of pressure fluctuation in the vaneless zone is the smallest, accounting for only 1.38 % of the rated head. The main frequency of the vaneless zone gradually changes from 15fn to 30fn , and the main frequency of the runner inlet and the short blade downstream is 24fn . Due to the different weakening effects of short blades on the interference, low-frequency pulsation components of 4fn and 8fn appear.

Flow-induced vibrations of a twistable two-tandem cylinder system across varied gap ratios

This paper presents a simulation study on the flow-induced vibrations (FIVs) of a two-tandem cylinder system with three degrees of freedom, encompassing in-flow, cross-flow, and torsional motions at a Reynolds number of 150. We specifically focus on investigating the impact of gap ratios (G*) between the cylinders, considering values of 0.5, 2, and 3. The ratio of torsional natural frequency to translational natural frequency was maintained at 12.5, while the mass ratio between the cylinder system and the fluid was set to 2. Our findings reveal a notable sensitivity of the FIV responses to the gap ratio between the cylinders. It was observed that the cylinder system's vibrations can undergo locking phenomena at both the translational and torsional natural frequencies, with maximal cross-flow amplitudes occurring within the torsional locked region. Particularly, at G* = 0.5, the maximal cross-flow amplitude reached approximately 21.4 times that of the cylinder system without torsional vibration, posing potential risks of fatigue failure in offshore equipment. Conversely, at G* = 2, an unusual ultra-low frequency was detected in the in-flow vibration. This phenomenon significantly magnified the FIV of the cylinder system, despite the absence of frequency locking. Furthermore, at G* = 3, we observed an expanded range of vibrations with ultra-low frequency compared to G* = 2. Our analysis identified the differential development speed of the shear layers around the upstream and downstream cylinders as a key factor contributing to varying vortex shedding frequencies. This discrepancy led to periodic changes in the vortex shedding mode of the cylinder system over time, thereby introducing low-frequency components into the flow-induced vibration. These insights deepen our understanding of the complex dynamics governing the FIV of tandem cylinder systems, which holds implications for the design and maintenance of offshore structures.

Chronic inhibition of angiotensin converting enzyme lowers blood pressure in spontaneously hypertensive rats by attenuation of sympathetic tone: The role of enhanced baroreflex sensitivity

Spontaneously hypertensive rats (SHR) are characterized by sympathetic hyperactivity and insufficient parasympathetic activity, and their high blood pressure (BP) can be lowered by long-term inhibition of the renin-angiotensin system. The aim of our study was to determine the influence of chronic inhibition of angiotensin converting enzyme (ACE) by captopril on cardiovascular regulation by the sympathetic and parasympathetic nervous system. Implanted radiotelemetric probes or arterial cannulas were used to measure mean arterial pressure (MAP), heart rate (HR), and arterial baroreflex in adult SHR and Wistar-Kyoto (WKY) rats under basal or stress conditions. MAP and the low-frequency component of systolic blood pressure variability (LF-SBPV, marker of sympathetic activity) were greater in SHR than in WKY rats. Under basal conditions chronic captopril treatment reduced both parameters more effectively in SHR, and the same was true during acute restraint stress. HR was similar in control rats of both strains, but WKY rats showed greater heart rate variability (HRV), indicating higher parasympathetic activity. Captopril administration increased HR in both strains, whereas HRV was decreased only in WKY. Chronic captopril treatment improved the impaired baroreflex-HR control in SHR by increasing the sensitivity but not the capacity of vagal arm of arterial baroreflex. Captopril treatment attenuated BP changes elicited by dimethylphenylpiperazinium (DMPP, agonist of nicotinic acetylcholine receptors), especially in SHR, indicating that sympathetic nerve transmission is facilitated by angiotensin II more in hypertensive than in normotensive animals. Thus, chronic ACE inhibition improves baroreflex sensitivity and lowers BP through both central and peripheral attenuation of sympathetic tone.

A comparative study on hydrocarbon detection using cepstrum–based methods

Amplitude anomaly caused by a high–frequency component is attenuated more rapidly than a low–frequency component for a seismic trace in sediments susceptible to gas influence and is always used as a direct indicator of hydrocarbons. Recently, cepstrum–based hydrocarbon detection methods have become an important exploration pathway for detecting amplitude anomalies in the gas–bearing formation more sensitively and accurately. In this study, we compared three cepstrum–based hydrocarbon detection methods. We compared their fluid identification abilities in gas reservoirs and the noise robustness. They were further compared with the traditional absorption coefficient estimation method. We also indicate how the choice of the selection of the sliding–window length influences the performance of the three cepstrum–based hydrocarbon detection methods. Model test results and real data applications show that for thick gas reservoirs, the hydrocarbon detection methods using the Berthil–based cepstrum and the wavelet–based cepstrum can better discriminate the upper and lower interfaces than the hydrocarbon detection method using the Fourier–based cepstrum. For thin gas reservoirs, the hydrocarbon detection method using the wavelet–based cepstrum can identify the lower interface of the gas–bearing reservoir more obviously than the upper interface. The hydrocarbon detection method using the Berthil cepstrum cannot identify the upper and lower interfaces of the gas–bearing reservoir, but it shows higher temporal and spatial resolution compared to the hydrocarbon detection method using the Fourier–based cepstrum. For noise robustness, the hydrocarbon detection method using the wavelet–based cepstrum has the strongest noise robustness property, and the hydrocarbon detection method using the Fourier–based cepstrum is the most sensitive method to the noise. For time–consumption, the hydrocarbon detection method using the wavelet–based cepstrum is the most time–consuming, and the hydrocarbon detection method using the Fourier–based cepstrum is the fastest.

Waveform inversion with structural regularizing constraint based on gradient decomposition

Abstract Full waveform inversion (FWI) can simultaneously update low-to-medium wavenumber velocity components and high-wavenumber velocity components. However, if seismic data lack large-offset data and effective low-frequency components, FWI updates will be dominated by high-wavenumber velocity perturbation. Meanwhile, providing that the initial model is inaccurate, inversion will have the problem of local minima. In this study, FWI is developed with structural regularizing constraint based on gradient decomposition (RGDFWI). By correlating the separated forward wavefield and backward wavefield with specific propagating direction, FWI gradient is decomposed into tomography-mode gradient and migration-mode gradient. We propose an optimized strategy taking full advantage of the two modes of FWI gradient. On the one hand, we use tomography-mode gradient to enhance low-to-medium wavenumber updates. On the other hand, we use migration-mode gradient to apply structural regularizing constraint by estimating structure dip and adding sparsity constraint in Seislet domain. During the inversion process, high-wavenumber structural information constrains and guides low-wavenumber model updates. The results of two numerical tests, Marmousi model test and Overthrust model test, validate the optimized strategy, which can produce a better initial velocity model for FWI. The inversion finally generates a high-precision and high-resolution velocity model.

Apple-and-pin drawings by blind novices show occluded features: region theory

Abstract Sighted children drawing an apple with a pin through it show the hidden parts of the pin. That is, not only is the pin shown running towards the apple and out the other side, it is also shown inside the apple, without a single break, and so the sketch depicts the occluded parts of the pin. Several investigators have offered theories of the observation. We report here on tangible raised-line drawings by young blind people who are novices at drawing. They also include occluded segments of the pin. To explain the drawings we use the John Willats region theory. In this account, enclosed regions represent the volumes of 3D objects. According to region theory, what is in the interior of an object should be shown in the drawing even if it cannot be seen or touched. As a result, since occluded parts of the pin are inside the apple, blind children, like sighted children, include them in their drawings. In region theory, for both the blind and the sighted, long lines on a 2D pictorial surface represent elongated objects in the scene and regions on the surface represent 3D objects and their contents. The basis of region theory may be that sensory information for pins and lines has high-frequency components, and for apples and regions has lower-frequency components.

Research on the Attenuation Characteristics of Frequency Domain Parameters in Different Rock Medium

Abstract This study examines the frequency attenuation characteristics of elastic waves in marble, granite, and red sandstone through laboratory tests and numerical simulations based on ABAQUS software on eight rock samples. The correlation between the distance of the decay of the peak frequency and the petrophysical and mechanical parameters is also analyzed. The results show that elastic waves undergo stepwise attenuation of their peak frequency during laboratory attenuation tests. This finding was confirmed by numerical simulations. As elastic waves propagate through a rock medium, the amplitude of the high-frequency peak area near the excitation frequency decreases rapidly, while the proportion of low-frequency signals increases. As the propagation continues, the signal spectrum is dominated by low-frequency components, resulting in a stepwise attenuation of the peak frequency. It has been observed that the step decay distance of the peak frequency of elastic waves varies with the degree of particle bonding, which can be used to characterize the attenuation properties of elastic waves in a medium.

Semi-supervised approach using Transductive SVM for internal leakage detection in two-stage hydraulic cylinder

Abstract Hydraulic cylinders with higher stages of extraction are extensively used in earthmoving and heavy machines due to their longer stroke, shorter retracted length and high-end performance. The rigorous and long hours of operations make cylinders prone to internal leakage, which visually remains unnoticeable This manuscript presents the conceptualization and realization of a newly developed 210 bar high-pressure hydraulic test rig actuated by a two-stage hydraulic cylinder. Experiments have been carried out to acquire pressure signals for two different leakage conditions (3 and 5% for moderate and severe leakage respectively) in the ramp wave motion of the cylinder. A decline in the working pressure and the piston velocity by approximately 10 and 45% for these leakage conditions respectively is noted. The time-frequency analysis infers these signals contain low-frequency components. For the automated leakage detection, a new iterative probability-based, transductive semi-supervised Support Vector Machine (TS-SVM) is proposed capable of learning with limited datasets in several iterations. TS-SVM classifies the internal leakage with 100% accuracy in 4 iterations and utilises only 64% of the total training data.

MFMSNet: A Multi-frequency and Multi-scale Interactive CNN-Transformer Hybrid Network for breast ultrasound image segmentation

Breast tumor segmentation in ultrasound images is fundamental for quantitative analysis and plays a crucial role in the diagnosis and treatment of breast cancer. Recently, existing methods have mainly focused on spatial domain implementations, with less attention to the frequency domain. In this paper, we propose a Multi-frequency and Multi-scale Interactive CNN-Transformer Hybrid Network (MFMSNet). Specifically, we utilize Octave convolutions instead of conventional convolutions to effectively separate high-frequency and low-frequency components while reducing computational complexity. Introducing the Multi-frequency Transformer block (MF-Trans) enables efficient interaction between high-frequency and low-frequency information, thereby capturing long-range dependencies. Additionally, we incorporate Multi-scale interactive fusion module (MSIF) to merge high-frequency feature maps of different sizes, enhancing the emphasis on tumor edges by integrating local contextual information. Experimental results demonstrate the superiority of our MFMSNet over seven state-of-the-art methods on two publicly available breast ultrasound datasets and one thyroid ultrasound dataset. In the evaluation of MFMSNet, tests were conducted on the BUSI, BUI, and DDTI datasets, comprising 130 images (BUSI), 47 images (BUI), and 128 images (DDTI) in the respective test sets. Employing a five-fold cross-validation approach, the obtained dice coefficients are as follows: 83.42 % (BUSI), 90.79 % (BUI), and 79.96 % (DDTI). The code is available at https://github.com/wrc990616/MFMSNet.

Image inpainting based on GAN-driven structure- and texture-aware learning with application to object removal

In this paper, a novel deep learning-based image inpainting framework consisting of restoring image structure and reconstructing image details from corrupted images is proposed. Most image inpainting methods in the literature aim at restoring image details, outlines, and colors, simultaneously, which may suffer from blurring, deformation, and unreasonable content recovery due to interference among various information. To solve these problems, a two-stage image inpainting deep neural network based on GAN (generative adversarial network) architecture is proposed. The proposed inpainting framework consists of two modules: (1) the first stage, called the structure-aware learning stage, aims at learning a GAN-based structure restoration network, focusing on recovering the low-frequency image component, including colors and outlines of the missing regions of the input corrupted image; and (2) the second stage, called the texture-aware learning stage, aims at learning a GAN-based detail refinement network, focusing on rebuilding the high-frequency image details and texture information. In particular, we also propose to remove details from the training images to better train the structure restoration network to avoid inadequate image structure recovery induced by richer image textures, where the detail reconstruction task is left to the second stage. This strategy achieves to balance the workload between the two stages and the image quality can be progressively enhanced through the two stages. Experimental results have shown that the proposed deep inpainting framework quantitatively and qualitatively achieves state-of-the-art performance on the well-known datasets, including the CelebA, Places2, and ImageNet datasets, compared with existing deep learning-based image inpainting approaches. More specifically, in terms of the two well-known image quality assessment metrics, PSNR (peak signal-to-noise ratio) and SSIM (structural similarity), the improvement percentage of the proposed method, compared with the baseline approach, respectively, ranges from 3.23 % to 11.12 %, and 1.95 % to 13.39 %. The improvements have been shown to stably and significantly outperform the compared state-of-the-art methods in most types of inpainting mask. We also show that the proposed method is applicable to image editing in object removal from a single image.

Assessing cardiovascular stress based on heart rate variability in female shift workers: a multiscale-multifractal analysis approach.

Sleep-wake cycle disruption caused by shift work may lead to cardiovascular stress, which is observed as an alteration in the behavior of heart rate variability (HRV). In particular, HRV exhibits complex patterns over different time scales that help to understand the regulatory mechanisms of the autonomic nervous system, and changes in the fractality of HRV may be associated with pathological conditions, including cardiovascular disease, diabetes, or even psychological stress. The main purpose of this study is to evaluate the multifractal-multiscale structure of HRV during sleep in healthy shift and non-shift workers to identify conditions of cardiovascular stress that may be associated with shift work. The whole-sleep HRV signal was analyzed from female participants: eleven healthy shift workers and seven non-shift workers. The HRV signal was decomposed into intrinsic mode functions (IMFs) using the empirical mode decomposition method, and then the IMFs were analyzed using the multiscale-multifractal detrended fluctuation analysis (MMF-DFA) method. The MMF-DFA was applied to estimate the self-similarity coefficients, α(q, τ), considering moment orders (q) between -5 and +5 and scales (τ) between 8 and 2,048 s. Additionally, to describe the multifractality at each τ in a simple way, a multifractal index, MFI(τ), was computed. Compared to non-shift workers, shift workers presented an increase in the scaling exponent, α(q, τ), at short scales (τ < 64 s) with q < 0 in the high-frequency component (IMF1, 0.15-0.4 Hz) and low-frequency components (IMF2-IMF3, 0.04-0.15 Hz), and with q> 0 in the very low frequencies (IMF4, < 0.04 Hz). In addition, at large scales (τ> 1,024 s), a decrease in α(q, τ) was observed in IMF3, suggesting an alteration in the multifractal dynamic. MFI(τ) showed an increase at small scales and a decrease at large scales in IMFs of shift workers. This study helps to recognize the multifractality of HRV during sleep, beyond simply looking at indices based on means and variances. This analysis helps to identify that shift workers show alterations in fractal properties, mainly on short scales. These findings suggest a disturbance in the autonomic nervous system induced by the cardiovascular stress of shift work.

Shaking table tests on seismic performance of a five-story reinforced concrete frame structure with MoS2 sliding bearings and steel dampers

The seismic performance of friction isolated structure is greatly affected by the friction coefficient, and the combination of low friction material and limit device is an available option. Via the Motion State module simulating the friction conditions and the Bouc Wen model describing the restoring characteristic of the steel dampers, a single-degree-of-freedom model was established to investigate the influence of the friction coefficient and limit stiffness on the isolation effect. Then, for the evaluation of the seismic performance of the proposed isolation system with molybdenum disulfide (MoS2) sliding bearings and steel dampers, the shaking table tests of a 1/5 scaled five-story reinforced concrete frame structure model, subjected to three ground motions with different peak ground acceleration, were implemented to obtain the isolation layer drift, absolute acceleration, inter-story shear and damage energy of the structure under the testing conditions of free sliding, limited sliding, multi-dimensional seismic excitation, and top additional layer sliding. It is found that the ideal friction coefficient for sliding isolated structure is 0.03–0.07, and the corresponding reasonable elastic stiffness of steel dampers is (0.2–0.5) Ks that is the stiffness of the structural standard story, and the proposed MoS2 sliding bearing presents remarkable low-friction characteristic with a friction coefficient of 0.04–0.05. The appropriate steel dampers can reduce the isolation layer drift without obviously increasing the acceleration. The low-frequency components in the ground motion significantly increase the isolation layer drift, while the high-frequency components cause the superstructure acceleration to show a K-shaped distribution along the height. Moreover, the proposed isolated system can be effectively used for structural protection under multi-dimensional earthquakes, the sliding additional layer on the roof can be considered as the second defense line in the structural seismic design, and the seismic energy the superstructure bears can directly estimate the seismic isolation effect that is consistent with the analysis result of dynamic response.