High Power Spectral Density Research Articles

Theta-gamma-coupling as predictor of working memory performance in young and elderly healthy people

The relationship between working memory (WM) and neuronal oscillations can be studied in detail using brain stimulation techniques, which provide a method for modulating these oscillations and thus influencing WM. The endogenous coupling between the amplitude of gamma oscillations and the phase of theta oscillations is crucial for cognitive control. Theta/gamma peak-coupled transcranial alternating current stimulation (TGCp-tACS) can modulate this coupling and thus influence WM performance. This study investigated the effects of TGCp-tACS on WM in older adults and compared their responses with those of younger participants from our previous work who underwent the same experimental design. Twenty-eight older subjects underwent both TGCp-tACS and sham stimulation sessions at least 72 h apart. Resting-state electroencephalography (EEG) was recorded before and after the interventions, and a WM task battery with five different WM tasks was performed during the interventions to assess various WM components. Outcomes measured included WM task performance (e.g., accuracy, reaction time (RT)) and changes in power spectral density (PSD) in different frequency bands. TGCp-tACS significantly decreased accuracy and RT on the 10- and 14-point Sternberg tasks and increased RT on the Digit Symbol Substitution Test in older adults. In contrast, younger participants showed a significant increase in accuracy only on the 14-item Sternberg task. Electrophysiological analysis revealed a decrease in delta and theta PSD and an increase in high gamma PSD in both younger and older participants after verum stimulation. In conclusion, theta-gamma coupling is essential for WM and modulation of this coupling affects WM performance. The effects of TGCp-tACS on WM vary with age due to natural brain changes. To better support older adults, the study suggests several strategies to improve cognitive function, including: Adjusting stimulation parameters, applying stimulation to two sites, conducting multiple sessions, and using brain imaging techniques for precise targeting.

Near-zero magnetic field disturbance suppression method based on adaptive filtering and quasi-proportional resonance control

The cardiac magnetic field used for magnetocardiographic (MCG) imaging must be detected in a stable near-zero magnetic field environment. In the hospital environment, there are mainly two kinds of magnetic field disturbances that affect the signal-to-noise ratio of cardiac magnetic field detection. One is the magnetic field disturbance with high power spectral density at a specific frequency, and the other is the random magnetic field disturbance with low frequency. To suppress magnetic field disturbances, this paper proposed a near-zero magnetic field disturbance suppression method that combined a PI controller with adaptive filtering and quasi-proportional resonance control (PI-APF-QPR). The magnetic field disturbance with high amplitude and specific frequency was extracted by the adaptive filter (APF) and suppressed by the quasi-proportional resonance (QPR) controller. Additionally, the low-frequency random disturbance was suppressed by the PI controller. The experimental results showed that compared with the PI controller, the peak-to-peak value of the magnetic field by the PI-APF-QPR controller was reduced by 39.1%, and the suppression ratio of the magnetic field noise by the PI-APF-QPR controller was improved by 29.5%, which verified the effectiveness of the proposed magnetic field disturbance suppression method.

Magnetic field interference suppression method based on phase-compensation vector resonance control in near-zero magnetic field environment

The traditional PI controller has limited ability to suppress magnetic field noise with high power spectral density and specific frequencies, leading to degradation in magnetocardiographic imaging quality. A phase-compensated vector resonance controller (PVRC) is proposed to suppress these disturbances. Firstly, by analyzing the coupling effect between the magnetic field and the ferromagnetic boundary of high permeability materials, the magnetic field response is divided into a first-order inertia link and a delay link. Then, the PVRC controller compensates for the phase lag of the disturbance in two stages. Additionally, the discretization method of PVRC is improved by replacing the cosine function with a Taylor series expansion to enhance response speed. The interference suppression effect of PI-PVRC is 27.5% higher than that of PI control.

Multifrequency Electrical Impedance Tomography Images for Swine Pneumonia Detection Using Conductivity Differences

This article introduces a new MfEIT UDESC Mark I system, which consists of a 32-electrode setup featuring a modified Howland current source, low cost, portability, and non-radiation. The system is capable of reconstructing electrical conductivity tomographic images at a rate of 30.624 frames per second, taking about 5 min for imaging. The current source employs a 0.5 mA adjacent current application pattern with frequencies ranging from 10 kHz to 1 MHz. This article outlines the hardware, firmware, and software design specifications, which include the design of the current source, calibration procedures, and image reconstruction process. Tomographic images of conductivity were reconstructed in ex vivo healthy pig lungs and those with pneumonia, as a proof of concept for future applications in live pigs. The high spectral power density, combined with real-time system calibration provides clinical advantages in veterinary medicine. The goal is to identify lung areas affected by Mycoplasma hyopneumoniae in pigs through the analysis of electrical conductivity difference, offering a valuable tool to assist veterinarians to obtain images of respiratory diseases. The modified reconstruction method GREIT (EIDORS) was evaluated with experimental data and was compared with the Gauss–Newton and Total Variation methods, where GREIT 2D proved to be superior.

Effects of different winter paddock management of Thoroughbred weanlings and yearlings in the cold region of Japan on physiological function, endocrine function and growth.

Effects of different winter paddock management of Thoroughbred weanlings and yearlings in Hokkaido, Japan, which is extremely cold in winter, on physiological function, endocrine function and growth were investigated. They were divided into two groups; those kept outdoors for 22 hr in the paddock (22hr group) and those kept outdoors for 7 hr in daytime with walking exercise for 1 hr using the horse-walker (7hr+W group), and the changes in daily distance travelled, body temperature (BT), heart rate (HR), HR variability (HRV), endocrine function and growth parameters were compared between the two groups from November at the year of birth to January at 1 year of age. The 7hr+W group could travel almost the same distance as the 22hr group by using the horse-walker. The 22hr group had a lower rate of increase in body weight than the 7hr+W group in January. In addition, lower in BT and HR were observed, and HRV analysis showed an increase in high frequency power spectral density, indicating that parasympathetic nervous activity was dominant. And also, changes in circulating cortisol and thyroxine were not observed despite cold environment. On the other hand, the 7hr+W group had higher prolactin and insulin like growth factor than the 22hr group in January, and cortisol and thyroxine were also increased. Physiological and endocrinological findings from the present study indicate that the management of the 7hr+W group is effective in promoting growth and maintaining metabolism during the winter season.

Design and analysis of a hexagonal circular photonic crystal fibre with ultra-high negative dispersion and low confinement loss

This paper proposes a Hexagonal Circular Photonic Crystal Fiber (HC-PCF) with uniform tiny air holes around the core, obtaining ultra-high negative dispersion, high Birefringence and low confinement loss. The modal properties of the HC-PCF are investigated using the full-vectorial-Finite Element Method (FEM) with a perfectly matched layer as the boundary condition. The numerical investigations show ultra-high negative dispersion of −25503 ps/nm.km, a birefringence of 1.36×10-2, a nonlinearity of 38.34w-1km-1 and a confinement loss of 4.95×10-3 dB km-1 at the wavelength of 1550 nm. Moreover, the proposed HC-PCF exhibits a high negative dispersion and multiple Zero Dispersion within the 800 to 2000 nm wavelengths range. Specifically, the high negative dispersion, low optical Confinement Loss, and multiple Zero Dispersion Wavelengths (ZDW) give the proposed HC-PCF high Power Spectral Density (PSD). These characteristics make the proposed fibre suitable for long-range telecommunication networks and optical sensing.

Broadband supercontinuum generation in cascaded tapered liquid core fiber

Most recent broad supercontinuum sources have used nonlinear fibers with small core diameters, resulting in low coupling efficiency, limiting power level launching into the fiber, and low spectral power density. In this work, we numerically investigate tapered liquid-core fibers for supercontinuum generation that have a potential for both high coupling efficiency (with a standard SMF-28 fiber) and high nonlinear effects. Carbon disulfide is selected to fill into the fibers because of its high nonlinear refractive index and high transparency from the visible to the mid-infrared range. We consider cascaded fibers including SMF-28 and the tapered liquid-core fibers for all-normal and anomalous dispersion supercontinuum generation pumped by C-band femtosecond lasers (1560 nm, 90 fs). In such a case, we obtain all-normal dispersion supercontinuum generation with flat-top, broad bandwidth (1.0–2.5μm) via an input peak power of 27 kW. By changing the core diameter of the tapered fiber, we also yield anomalous dispersion supercontinuum generation with broad spectral bandwidth (1.0–3.3μm). In addition, the use of the cascaded tapered fibers is possible to mitigate fiber damage (via thermal effects of a high-power laser on the selected liquids) and increase stability of output supercontinuum spectra. In this context, supercontinuum generation in the cascaded fibers by using a picosecond laser with high average power (≈ 800 mW) is considered towards applications requiring high spectral power density (e.g., multiphoton imaging techniques).

Supercontinuum generation in chalcogenide photonic crystal fiber infiltrated with liquid

Chalcogenide fibers have attracted much attention for multi-octave spanning supercontinuum generation in the mid-infrared range. However, readily optimizing the dispersion characteristics as well as other mode properties is still problematic because it is difficult to fabricate chalcogenide fibers with sophisticated structures. In this work, we numerically investigate the liquid infiltration as a post-processing method to optimize the dispersion shapes, so that the nonlinear dynamics and spectro-temporal properties of supercontinuum generation are efficiently controlled. In particular, water, carbon disulfide (CS2), carbon tetrachloride (CCl4), and bromoform (CHBr3) are selected to fill into all cladding air holes of As38Se62 fibers for dispersion engineering. By pumping a femtosecond laser at 4.5 μm, pulse duration of 250 fs, and pulse energy of 0.1 nJ (peak power of 0.4 kW), the unfilled and CCl4-filled fibers provide soliton-induced supercontinuum generation with a spectral bandwidth of 2.5–6.5 μm and 2.0–5.5 μm, respectively. Whilst, CHBr3-filled fiber offers all-normal dispersion supercontinuum generation with high coherence and spectral bandwidth of 2.2–5.2 μm. In contrast, unfortunately, CS2 and water-filled fibers have complex dispersion shapes and provide narrow bandwidth supercontinua. We also thoroughly numerically investigate the tapered fibers, which assure both high coupling efficiency with laser sources and high nonlinearity, for broad mid-infrared supercontinuum generation. The results point out that liquid-filled tapered fibers can provide both anomalous and all-normal dispersion SC generation with an octave-spanning bandwidth via the same value of input peak power (0.4 kW). With a large core diameter (12 μm) at the input and output fiber ends, the tapered fibers have a potential to couple with high-power laser pulses without fiber damage, therefore, they can provide supercontinuum spectra with broad bandwidth and high spectral power density for practical applications in sensing, gas detection, and LIDAR.

A multiwavelet-based sparse time-varying autoregressive modeling for motor imagery EEG classification

Brain-computer Interface (BCI) system based on motor imagery (MI) heavily relies on electroencephalography (EEG) recognition with high accuracy. However, modeling and classification of MI EEG signals remains a challenging task due to the non-linear and non-stationary characteristics of the signals. In this paper, a new time-varying modeling framework combining multiwavelet basis functions and regularized orthogonal forward regression (ROFR) algorithm is proposed for the characterization and classification of MI EEG signals. Firstly, the time-varying coefficients of the time-varying autoregressive (TVAR) model are precisely approximated with the multiwavelet basis functions. Then a powerful ROFR algorithm is employed to dramatically alleviate the redundant model structure and accurately recover the relevant time-varying model parameters to obtain high resolution power spectral density (PSD) features. Finally, the features are sent to different classifiers for the classification task. To effectively improve the accuracy of classification, a principal component analysis (PCA) algorithm is utilized to determine the best feature subset and Bayesian optimization algorithm is performed to obtain the optimal parameters of the classifier. The proposed method achieves satisfactory classification accuracy on the public BCI Competition II Dataset III, which proves that this method potentially improves the recognition accuracy of MI EEG signals, and has great significance for the construction of BCI system based on MI.

Alpha-power in electroencephalography as good outcome predictor for out-of-hospital cardiac arrest survivors

This study aimed to investigate the utility of quantitative EEG biomarkers for predicting good neurologic outcomes in OHCA survivors treated with targeted temperature management (TTM) using power spectral density (PSD), event-related spectral perturbation (ERSP), and spectral entropy (SE). This observational registry-based study was conducted at a tertiary care hospital in Korea using data of adult nontraumatic comatose OHCA survivors who underwent standard EEG and treated with TTM between 2010 and 2018. Good neurological outcome at 1 month (Cerebral Performance Category scores 1 and 2) was the primary outcome. The linear mixed model analysis was performed for PSD, ESRP, and SE values of all and each frequency band. Thirteen of the 54 comatose OHCA survivors with TTM and EEG were excluded due to poor EEG quality or periodic/rhythmic pattern, and EEG data of 41 patients were used for analysis. The median time to EEG was 21 h, and the rate of the good neurologic outcome at 1 month was 52.5%. The good neurologic outcome group was significantly younger and showed higher PSD and ERSP and lower SE features for each frequency than the poor outcome group. After age adjustment, only the alpha-PSD was significantly higher in the good neurologic outcome group (1.13 ± 1.11 vs. 0.09 ± 0.09, p = 0.031) and had best performance with 0.903 of the area under the curve for predicting good neurologic outcome. Alpha-PSD best predicts good neurologic outcome in OHCA survivors and is an early biomarker for prognostication. Larger studies are needed to conclusively confirm these findings.

TECHNOLOGY ENSURING THE RELIABILITY OF INFORMATION ON THE BASIS OF CONCATENATED CODING

Wireless Data Media (WDM) provide data exchange between subscribers who can perform a single tasks in the conditions of active electronic influence. That is why it is important an indicator that characterizes the effectiveness of such WDM is the ability to ensure a given reliability of information reception in the conditions exposure to interference of various origins, including intentional, which characterized by high power spectral density. Effective the direction of counteraction to disturbances is application in WDM of technologies of expansion signal spectrum and code constructions. The purpose of the research is to increase effectiveness of WDM in the conditions of influence of disturbances through ensuring reliability information through the development of methods based on adaptive coding and their using. To develop technology to ensure the reliability of information in WDM on the basis of adaptation of code constructions methods of the theory of management were used, coding, decision making, adaptive systems, optimization, communication, simulation, noise-tolerant coding theory, information theory. The results of the research permit: to ensure reliability of information of departmental radio communication systems under impact of intentional jamming; to quantify reliability of information of departmental radio communication systems under impact of intentional jamming; to choose control parameters in selecting an operating mode of radio communication equipment; on the basis of the developed results to design components of modem equipment for means of departmental radio communication. The results of the study should be used by industrial and research organizations in order to ensure the reliability of adaptive programmed radio stations in conditions of intentional interference.

A recommendation prediction method based on the estimation of PSD of sampled signals on graph

In recommendation system, the rating prediction is a very challenging problem. In this paper, we model users (items) and their relationships as a weighted undirected graph, and propose a rating prediction model based on graph signal reconstruction. Different from the existing reconstruction model, the proposed model takes into account the frequency structure of the signal itself, and tends to protect the frequency contents with higher power spectral density (PSD) and impose large penalties on those with lower PSD when reconstructing a signal. Furthermore, based on the assumption of the stationarity of the graph signal, we propose a method to estimate the PSD of a stationarity stochastic graph signal directly from some sampled signals without its any other complete implementation. Related theoretical analysis is also given. Finally, a rating prediction algorithm based on the graph signal reconstruction is derived. Experimental results show that the proposed model leads a significant improvement of the predictive accuracy.

Impulsive Noise Suppressing Method in Power Line Communication System Using Sparse Iterative Covariance Estimation

AbstractPower line communication (PLC) is severely affected by impulsive noise, especially asynchronous impulsive noise with high power spectral density and short duration. This paper presents an asynchronous impulsive noise suppression method in PLC system. Based on the component of the asynchronous impulsive noise and the background noise extracted from the received signal by using a null subcarrier matrix, a sparse iterative covariance estimation method is proposed. A optimization problem for estimating impulsive noise power is formed based on a minimum covariance matrix fitting criterion, and the impulsive noise power is then obtained by an iterative algorithm. After that, the impulsive noise is estimated by using the linear minimum mean square estimate method and subtracted from the received signal. Finally, simulation results show that the proposed method can achieve better performance in terms of bit error rate, and has lower computational complexity.

Impact of the gap distance between two adjacent external windshields of a high-speed train on surrounding flow characteristics: an IDDES study

The external windshield is a key component in high-speed trains for drag reduction. However, the installation gap between external windshields, which is intended for improving curve-passing ability, could lead to strong aerodynamic instability in train-end area and therefore significant operating risk for train. This study aims to advance this field based on detailed numerical simulation, investigating the related flow features in this area, particularly from a time-dependent perspective. Flow field around external windshields with different installation gaps (10, 20 and 30 mm) is resolved based on Improved Delayed Detached Eddy Simulation (IDDES). The aerodynamic forces on different windshield components, turbulent flow fields around the train-end area, and corresponding low-dimensional modes are analyzed. The results show that the difference in the external windshield gap can significantly affect the related aerodynamic forces, with the 20 mm case having the highest time-averaged values. The aerodynamic spectrum shows primary, secondary and tertiary peak frequencies with a relatively high power spectral density (PSD). Decreasing the gap distance generally increases the overall PSD in the Strouhal number ranges considered, particularly for the secondary and tertiary peaks. The load forms and their energy distributions under different external windshield gaps are obtained through the proper orthogonal decomposition analysis.

Advances in mid-infrared spectroscopy enabled by supercontinuum laser sources.

Supercontinuum sources are all-fiber pulsed laser-driven systems that provide high power spectral densities within ultra-broadband spectral ranges. The tailored process of generating broadband, bright, and spectrally flat supercontinua-through a complex interplay of linear and non-linear processes-has been recently pushed further towards longer wavelengths and has evolved enough to enter the field of mid-infrared (mid-IR) spectroscopy. In this work, we review the current state and perspectives of this technology that offers laser-like emission properties and instantaneous broadband spectral coverage comparable to thermal emitters. We aim to go beyond a literature review. Thus, we first discuss the basic principles of supercontinuum sources and then provide an experimental part focusing on the quantification and analysis of intrinsic emission properties such as typical power spectral densities, brightness levels, spectral stability, and beam quality (to the best of the authors' knowledge, the M2 factor for a mid-IR supercontinuum source is characterized for the first time). On this basis, we identify key competitive advantages of these alternative emitters for mid-IR spectroscopy over state-of-the-art technologies such as thermal sources or quantum cascade lasers. The specific features of supercontinuum radiation open up prospects of improving well-established techniques in mid-IR spectroscopy and trigger developments of novel analytical methods and instrumentation. The review concludes with a structured summary of recent advances and applications in various routine mid-IR spectroscopy scenarios that have benefited from the use of supercontinuum sources.

Narrow linewidth fiber laser oscillator based on fiber bragg grating with high power spectral density

In this paper, we present a thorough study on an all-fiber narrow-linewidth FBG-based laser oscillator. Having established a theoretical model, the spectrum broadening characteristics of the narrow-linewidth FBG-based oscillator were analyzed based on multiple factors. During the experiment, using optimized structural parameters according to theoretical analyses, a backward pumped laser oscillator achieved an output power of 192.4 W and a spectral 3-dB bandwidth of 33.7 pm, corresponding to a power spectral density of 5.7 W/pm. To the best of our knowledge, this is the highest PSD reported to date by an all-fiber FBG-based laser oscillator.

A reconstruction method for graph signals based on the power spectral density estimation

Graph signal reconstruction is a classic problem of graph signal processing. The ultimate goal of signal reconstruction is to obtain an estimate as close as possible to the original signals. Most of existing reconstruction models are based on assumption of signal smoothness. This paper proposes a new reconstruction model based on signal power spectral density estimation. The basic idea is to suppress those graph frequency components with low power spectral density when reconstructing a signal, while preserving those graph frequency contents with high power spectral density. Therefore, the reconstructed signals can well maintain the frequency structures of the original signals. Under the stationarity assumption of stochastic graph signals, we further propose a method to estimate the power spectral density directly from the sampled signals. Experimental results show that the proposed power spectral density estimation algorithm works well even when the proportion of labeled vertices is extremely low, and is robust to the PSD of signals itself and the various structures of graphs. Compared with traditional models based on smoothness assumption, the proposed reconstruction model can significantly improve the reconstruction performance.

Wavelet Ridges in EEG Diagnostic Features Extraction: Epilepsy Long-Time Monitoring and Rehabilitation after Traumatic Brain Injury.

Interchannel EEG synchronization, as well as its violation, is an important diagnostic sign of a number of diseases. In particular, during an epileptic seizure, such synchronization occurs starting from some pairs of channels up to many pairs in a generalized seizure. Additionally, for example, after traumatic brain injury, the destruction of interneuronal connections occurs, which leads to a violation of interchannel synchronization when performing motor or cognitive tests. Within the framework of a unified approach to the analysis of interchannel EEG synchronization using the ridges of wavelet spectra, two problems were solved. First, the segmentation of the initial data of long-term monitoring of scalp EEG with various artifacts into fragments suspicious of epileptic seizures in order to reduce the total duration of the fragments analyzed by the doctor. Second, assessments of recovery after rehabilitation of cognitive functions in patients with moderate traumatic brain injury. In the first task, the initial EEG was segmented into fragments in which at least two channels were synchronized, and by the adaptive threshold method into fragments with a high value of the EEG power spectral density. Overlapping in time synchronized fragments with fragments of high spectral power density was determined. As a result, the total duration of the fragments for analysis by the doctor was reduced by more than 60 times. In the second task, the network of phase-related EEG channels was determined during the cognitive test before and after rehabilitation. Calculation-logical and spatial-pattern cognitive tests were used. The positive dynamics of rehabilitation was determined during the initialization of interhemispheric connections and connections in the frontal cortex of the brain.

Low and High Broadband Spectral Models of Atmospheric Pressure Fluctuation

AbstractThis paper presents new low and high power spectral density models for pressure fluctuations at the Earth’s surface over the frequency range of (10−5 – 8) Hz. Previously proposed models often included limitations, such as a much narrower frequency range, the inclusion of erroneous and non-calibrated data or recorded data not deconvolved from the measurement system responses. The progress recently made with response modeling and field calibration of pressure fluctuation measurement systems now allows to propose more realistic power spectral density models over an extremely large frequency band. This paper describes how the data were selected, processed, and analyzed to obtain the final global models. In addition, the intermediate results allow the characterization of several atmospheric mechanisms, such as gravity wave saturation, limits of the buoyancy and acoustic cut-off frequencies or wind turbulence modes. The two proposed low and high power spectral density models are planned to be used for a wide range of applications, including assessing the quality of measured pressure fluctuations, verifying the validity of modeled pressure fluctuations and supporting the design, testing and calibration of a new generation of measurement systems. The models presented in this paper are made available to the scientific community.

Fatigue strain signal reconstruction technique based on selected wavelet decomposition levels of an automobile coil spring

This study aims to assess the fatigue life analysis of strain signals with the implementation of a reconstruction of the signals of the discrete wavelet transform (DWT) decomposition technique. The process involves the time and frequency information used in fatigue life analysis. Strain signals, also known as original signals, were measured based on different road conditions. The DWT method was applied to the original signals to assess the time–frequency domain characteristics. As a result, 14 decomposition signals were obtained and the fatigue life of each signal was evaluated. The decomposition signals contained lower fatigue life, which is below 108 cycles determined at levels 6 to 9. The reconstructed signals were obtained based on these selected levels. The frequency information obtained from the power spectral density (PSD) shows the elimination of high frequency, with low PSD amplitude in the reconstructed signal. The frequency range with high PSD amplitude obtained from this reconstructed signal at 20 Hz was the same as the original signal. Good fatigue life correlation between the reconstructed and original signals enable the prediction of similar fatigue life values, which are at 107 and 105 cycles for the highway and bumpy road conditions, respectively. It can be concluded that the implementation of this technique was able to provide good agreement of strain signals in fatigue life analysis.