Low Frequency Amplitude Research Articles

The Doppler effect induced by earthquakes: A case study of the Wenchuan MS8.0 earthquake

Seismologists have found that the first arrival frequencies of P waves at different seismic stations have different widths, that is, different periods or frequencies, and they think that this phenomenon can be used to identify whether a Doppler effect is induced by earthquakes. However, the fault rupture process of a real earthquake is so complex that it is difficult to identify a frequency shift similar to the Doppler effect. A method to identify whether a Doppler effect is induced by an earthquake is proposed here. If a seismic station is in the direction of fault rupture propagation, this station could observe a Doppler effect induced by the earthquake. The Doppler effect causes the frequency of the seismic wave to shift from low frequency to high frequency, and the high frequency amplitudes become mutually superimposed. Under the combined influences of the absorption effect, geometric spreading effect and Doppler effect, the high frequency amplitude of the seismic wave will gradually become higher than the low frequency amplitude with increasing epicentral distance. If we find that the high frequency amplitude is higher than the low frequency amplitude with increasing epicentral distance in the direction of fault rupture propagation, then there is a Doppler effect. The fault that generated the Wenchuan earthquake is a reverse fault, and its horizontal rupture propagation velocity was low. To link fault rupture propagation velocity with the Doppler effect and identify the Doppler effect more easily, we decompose three-component records into two directions: the direction of fault rupture propagation and the direction perpendicular to the fault rupture propagation along the fault plane. The initial components of the two directions are processed by wavelet transform. Several seismic stations in the direction of fault rupture propagation of the Wenchuan earthquake were selected, and it was found that with increasing epicentral distance, the high frequency amplitudes of the wavelet spectra become obviously higher than the low frequency amplitudes. It can be concluded that due to the existence of the Doppler effect, high frequency amplitudes can overcome the influences of the absorption and geometric spreading effects on seismic waves in the fault rupture propagation process.

Real-World Visual Experience Alters Baseline Brain Activity in the Resting State: A Longitudinal Study Using Expertise Model of Radiologists.

Visual experience modulates the intensity of evoked brain activity in response to training-related stimuli. Spontaneous fluctuations in the restful brain actively encode previous learning experience. However, few studies have considered how real-world visual experience alters the level of baseline brain activity in the resting state. This study aimed to investigate how short-term real-world visual experience modulates baseline neuronal activity in the resting state using the amplitude of low-frequency (<0.08 Hz) fluctuation (ALFF) and a visual expertise model of radiologists, who possess fine-level visual discrimination skill of homogeneous stimuli. In detail, a group of intern radiologists (n = 32) were recruited. The resting-state fMRI data and the behavioral data regarding their level of visual expertise in radiology and face recognition were collected before and after 1 month of training in the X-ray department in a local hospital. A machine learning analytical method, i.e., support vector machine, was used to identify subtle changes in the level of baseline brain activity. Our method led to a superb classification accuracy of 86.7% between conditions. The brain regions with highest discriminative power were the bilateral cingulate gyrus, the left superior frontal gyrus, the bilateral precentral gyrus, the bilateral superior parietal lobule, and the bilateral precuneus. To the best of our knowledge, this study is the first to investigate baseline neurodynamic alterations in response to real-world visual experience using longitudinal experimental design. These results suggest that real-world visual experience alters the resting-state brain representation in multidimensional neurobehavioral components, which are closely interrelated with high-order cognitive and low-order visual factors, i.e., attention control, working memory, memory, and visual processing. We propose that our findings are likely to help foster new insights into the neural mechanisms of visual expertise.

Feature and decision-level fusion for schizophrenia detection based on resting-state fMRI data.

Mental disorders, especially schizophrenia, still pose a great challenge for diagnosis in early stages. Recently, computer-aided diagnosis techniques based on resting-state functional magnetic resonance imaging (Rs-fMRI) have been developed to tackle this challenge. In this work, we investigate different decision-level and feature-level fusion schemes for discriminating between schizophrenic and normal subjects. Four types of fMRI features are investigated, namely the regional homogeneity, voxel-mirrored homotopic connectivity, fractional amplitude of low-frequency fluctuations and amplitude of low-frequency fluctuations. Data denoising and preprocessing were first applied, followed by the feature extraction module. Four different feature selection algorithms were applied, and the best discriminative features were selected using the algorithm of feature selection via concave minimization (FSV). Support vector machine classifiers were trained and tested on the COBRE dataset formed of 70 schizophrenic subjects and 70 healthy subjects. The decision-level fusion method outperformed the single-feature-type approaches and achieved a 97.85% accuracy, a 98.33% sensitivity, a 96.83% specificity. Moreover, feature-fusion scheme resulted in a 98.57% accuracy, a 99.71% sensitivity, a 97.66% specificity, and an area under the ROC curve of 0.9984. In general, decision-level and feature-level fusion schemes boosted the performance of schizophrenia detectors based on fMRI features.

A multi-folded-beam piezoelectric energy harvester for wideband energy harvesting under ultra-low harmonic acceleration

In this paper, a multi-folded-beam piezoelectric energy harvester (MFB-PEH) was proposed for low-power energy harvesting applications in wide frequency band, low frequency, and low amplitude vibration environments. The MFB-PEH consists of one traditional main beam and two new additional L-shaped wing beams, which are designed to improve the frequency bandwidth and harvest low frequency, low amplitude ambient vibration energy. Firstly, finite element method (FEM) was used to search for the optimal design that can make the operational bandwidth broader and yield the maximum power output. The experimental results reveal that the optimized MFB-PEH has three resonance frequencies in the ambient frequency range from 9 Hz to 20 Hz, which can broaden the operation bandwidth of the harvester. It is significant that the MFB-PEH device, excited at an ultra-low harmonic acceleration of 0.2 m/s2, generates a much higher output power of 29.0μW, four times higher than other multi-beam devices at the low frequency of ∼9.2 Hz. Finally, a packaged MFB-PEH was adopted to harvest the energy generated by human motion, where the MFB-PEH can generate a high voltage of 24 Vp−p when walking and 55 Vp−p when running. Our work has confirmed that the MFB-PEH is a good potential generator in wide frequency band, low frequency, and low amplitude vibration environments.

Inconsistent comparison of temperature reconstructions over the Common Era

Büntgen et al. (2020) present a new reconstruction of extra-tropical summer temperatures based on updated versions of a large number of summer temperature sensitive tree-ring width chronologies from the Northern Hemisphere (NH), which cover the full Common Era (CE). This new dataset allows the authors to draw conclusions about NH temperature history and its relation to climate forcing, marking an important contribution to our understanding of past climate changes. While we have no issues with the main conclusions of B20, here we show that their comparison with PAGES 2k reconstructions is flawed: B20′s reconstruction focused on regional, summertime temperature, while the PAGES 2k reconstruction targeted global, annual mean temperature. For their reconstruction intercomparisons, B20 rescale all six tree-ring based reconstructions to their regional observational target but fail to do this same processing step with the PAGES 2k reconstructions. This inconsistent comparison leads B20 to incorrectly conclude that the PAGES 2k reconstructions severely lack variance and are therefore unreliable. In this contribution, we present a consistent comparison of the B20 and PAGES 2k reconstructions, and we highlight the importance of careful illustrations for interpreting scientific results both in the literature and in the public discussion. Our results show that, if more accurate methods for comparisons are applied, the temperature history and low-frequency amplitudes of the different proxy selection approaches and reconstruction products are not at odds, but actually consistent with the differences between their targets over the pre-industrial CE.

Effects of Chronic Hypoxic Environment on Cognitive Function and Neuroimaging Measures in a High-Altitude Population.

ObjectiveThis study aimed to investigate the effects of long-term hypoxic environment exposure on cognitive ability and neuroimaging characteristics in a highland population in China.MethodsHealth system workers in Maduo County (4,300 m above sea level) and Minhe County (1,700 m above sea level) were selected as research participants and divided into a high-altitude (HA) group and low-altitude (LA) group, respectively. Cognitive ability was assessed using the Montreal Cognitive Assessment (MoCA), Verbal Fluency Test (VFT), Symbol Digit Modalities Test (SDMT), Trail Making Test A and B (TMT), Digit Span Test (DST), and Rey Auditory Verbal Learning Test (RAVLT). All participants underwent a magnetic resonance imaging (MRI) scan, resting state functional MRI scan, and diffusion tensor imaging to clarify changes in regional gray matter (GM) volume, anisotropy index (FA), local consistency (ReHo), and low-frequency oscillation amplitude (ALFF).ResultsThe HA group had significantly lower MoCA, DST, VFT, RAVLT, and TMT scores compared to the control group. No significant differences were found in SDMT score. Furthermore, compared to the LA group, the HA group had significantly lower GM density of the left olfactory cortex, right medial orbital superior frontal gyrus, bilateral insula, left globus pallidus, and temporal lobe (left superior temporal gyrus temporal pole, bilateral middle temporal gyrus temporal pole, and right middle temporal gyrus). In terms of FA, compared with the LA group, the HA group had lower values for the corpus callosum, corpus callosum knee, bilateral radiative corona, and left internal capsule. The HA group had lower ALFF values of the left cerebellum, left putamen, left orbital inferior frontal gyrus, and left precuneus, but higher ALFF values of the left fusiform gyrus, bilateral inferior temporal gyrus, left orbital superior frontal gyrus and medial superior frontal gyrus, compared to the LA group. There was no significant group difference in ReHo values.ConclusionOur findings suggest that a chronic hypoxic environment can induce extensive cognitive impairment. Decreased GM density in multiple brain regions, damaged nerve fibers, and unbalanced neuronal activity intensity in different brain regions may be the structural and functional basis of cognitive impairment due to hypoxia.

A Position Error Correction Method for Sensorless Control of Dual Three-Phase Permanent Magnet Synchronous Machines

In this article, an online rotor position error correction method is proposed to eliminate the impact of parameter mismatch in sensorless control for dual three-phase (DTP) permanent magnet synchronous machines drives. The rotor position error production mechanism is first derived and shows that the error changes with the trend of current variation when there is a parameter mismatch. Based on this mechanism, by injecting sinusoidal current signals with low frequency and small amplitude into both sets of three-phase windings, the presence of parameter mismatch and its level can be revealed from the corresponding sinusoidal responses of the estimated speed of sensorless observers, which do not depend on the inertia of the machine. Since the amplitudes of these responses decrease as the parameter mismatch level reduces, with the help of the least mean square algorithm, the parameters can be adaptively adjusted to the actual values, and the position error can be thus corrected. Moreover, with the extra freedom of DTP machines, the detrimental effects on torque production due to current signal injections can be eliminated through adjusting the phase between the two injected signals. The effectiveness of the proposed method has been validated through simulation and experimental results.

Assessment of dynamic phase amplitude coupling using matching pursuit

BackgroundNeuronal transmission and communication are enabled by the interactions across multiple oscillatory frequencies. Phase amplitude coupling (PAC) quantifies these interactions during cognitive brain functions. PAC is defined as the modulation of the amplitude of the high frequency rhythm by the phase of the low frequency rhythm. Existing PAC measures are limited to quantifying the average coupling within a time window of interest. However, as PAC is dynamic, it is necessary to quantify time-varying PAC. Existing time-varying PAC approaches are based on using a sliding window approach. These approaches do not adapt to the signal dynamics, and thus the arbitrary selection of the window length substantially hampers PAC estimation. New methodTo address the limitations of sliding window PAC estimation approaches, in this paper, we introduce a dynamic PAC measure that relies on matching pursuit (MP). This approach decomposes the signal into time and frequency localized atoms that best describe the signal. Dynamic PAC is quantified by computing the coupling between these time and frequency localized atoms. As such, the proposed approach is data-driven and tracks the change of PAC with time. We evaluate the proposed method on both synthesized and real electroencephalogram (EEG) data. ResultsThe results from synthesized data show that the proposed method detects the coupled frequencies and the time variation of the coupling correctly with high time and frequency resolution. The analysis of EEG data revealed theta-gamma and alpha-gamma PAC during response and post-response time intervals. Comparison with existing method(s)Compared to the existing sliding window based approach, the proposed MP based dynamic PAC measure is more effective at capturing PAC within a short time window and is more robust to noise. This is because this method quantifies the low frequency phase and high frequency amplitude components from the time and frequency localized MP atoms and, as such, can capture the signal dynamics. ConclusionsWe posit that the proposed MP based data-driven approach offers a more robust and possibly more sensitive method to effectively quantify and track dynamic PAC.

Damage Mechanism and Wave Attenuation Induced by Blasting in Jointed Rock

This work uses a combination of simulations performed via numerical models and field observations studied the attenuation of deep-hole blasting stress waves and the evolution mechanism of cracks in a jointed rock mass. First, we conclude that the larger the joint angle is, the larger is the transmission coefficient and smaller is the fractal dimension. Second, the time difference between the peak stress difference and the maximum principal stress on both sides of the blasting hole in the horizontal direction of the rock mass with joints is relatively large, but there is no significant difference in the vertical direction. Finally, an unjointed-rock-mass model and multiple parallel joint model are established to explore the attenuation of stress waves and damage effect of multiple joint rock mass, it is concluded that the larger the angle, the smaller is the particle peak velocity and amplitude attenuation, and as the number of stress waves passing through the joints increases, the amplitude gradually decreases and the high-frequency amplitude decreases more significantly than the low-frequency amplitude. The research conclusions of this paper further reveal the damage mechanism induced by a blasting stress wave on jointed rock masses and the law of stress wave propagation and attenuation.

Visual expertise modulates baseline brain activity: a preliminary resting-state fMRI study using expertise model of radiologists

Backgroundvisual expertise and experience modulate evoked brain activity in response to training-related stimuli. However, few studies have considered how the visual experience is represented in the resting state brain activity. This study tried to investigate the way visual experience, i.e., visual recognition expertise, modulates baseline brain neuronal activity in the resting state using the model of radiologists.MethodsThe amplitude of low-frequency (< 0.08 Hz) fluctuation (ALFF) was used as the metric of baseline brain activity and a visual expertise model of radiologists to investigated this question. The visual recognition skill enables them to accurately identify pathological information in medical images. After the behavior measurement, a cohort group of radiology interns (n = 22) and a group of matched layperson (n = 22) were selected for inclusion in the study. The resting state functional magnetic resonance imaging (fMRI) scans were performed for all of the subjects.ResultsHigher ALFF in the right fusiform gyrus and the left orbitofrontal cortex were observed, and the ALFF in the fusiform gyrus was correlated with the intern radiologists’ behavioral expertise(all results corrected for multiple comparisons).ConclusionsVisual experience modulates the baseline brain activity in both high-level visual cortex and high-order cognitive cortex, indicating the engagement of both top-down and bottom-up facilitation. We provide a novel perspective to how visual experience modulated cortical brain activity by introducing the resting state changes. Also, we propose that our current study may provide novel ideas for the development of new training protocols in medical school.

Dynamics of chugging phenomenon induced by subsonic and supersonic steam–air jet condensation in water flow

Chugging, a typical unstable flow pattern caused by steam-water direct contact condensation, should be paid more attention in engineering applications due to its accompanying low-frequency and high amplitude pressure pulse. In this paper, it was experimentally found that both subsonic and supersonic steam–air jet condensation could trigger chugging in a confined channel. As for such conditions, the chugging-caused pressure pulses all had two dominant frequencies with different amplitudes, and the one with larger amplitude was mainly distributed in the low-frequency zone of 15–45 Hz and 30–50 Hz. The brilliant image of steam-water phase interface captured by a high-speed camera showed that the mechanism of chugging was the sharp and low-frequency stretching and shrinking of the phase interface because of the periodic aggregation and dissipation of air layer. The subsonic steam–air jet condensation could trigger chugging only with a small amount of air, which therefore should be prevented as far as possible in engineering. However, for supersonic steam–air jet condensation, chugging could be triggered as soon as the air mass fraction reached a critical value because the incoming flow had severely damage effect on the air layer. By considering the steam mass flux, condensation driven potential, water Reynolds number and air mass fraction, the correlations of dominant frequency of chugging for subsonic and supersonic steam–air jet condensation were given, with deviations in the range of ± 20% and 15%, respectively.

Dynamic and Static Amplitude of Low-Frequency Fluctuation Is a Potential Biomarker for Predicting Prognosis of Degenerative Cervical Myelopathy Patients: A Preliminary Resting-State fMRI Study.

ObjectiveThe aim of this study was to explore the clinical value of the static amplitude of low-frequency fluctuation (sALFF) and dynamic amplitude of low-frequency fluctuation (dALFF) in the identification of brain functional alterations in degenerative cervical myelopathy (DCM) patients.MethodsVoxel-wise sALFF and dALFF of 47 DCM patients and 44 healthy controls were calculated using resting-state fMRI data, and an intergroup comparison was performed. The mean of sALFF or dALFF data were extracted within the resultant clusters and the correlation analysis of these data with the clinical measures was performed. Furthermore, whole-brain-wise and region-wise multivariate pattern analyses (MVPAs) were performed to classify DCM patients and healthy controls. sALFF and dALFF were used to predict the prognosis of DCM patients.ResultsThe findings showed that (1) DCM patients exhibited higher sALFF within the left thalamus and putamen compared with that of the healthy controls. DCM patients also exhibited lower dALFF within bilateral postcentral gyrus compared with the healthy controls; (2) No significant correlations were observed between brain alterations and clinical measures through univariate correlation analysis; (3) sALFF (91%) and dALFF (95%) exhibited high accuracy in classifying the DCM patients and healthy controls; (4) Region-wise MVPA further revealed brain regions in which functional patterns were associated with prognosis in DCM patients. These regions were mainly located at the frontal lobe and temporal lobe.ConclusionIn summary, sALFF and dALFF can be used to accurately reveal brain functional alterations in DCM patients. Furthermore, the multivariate approach is a more sensitive method in exploring neuropathology and establishing a prognostic biomarker for DCM compared with the conventional univariate method.

Self-referenced electro-optic response measurement of dual-parallel Mach-Zehnder modulators employing single-tone level control and low-frequency bias swing.

A self-referenced method is proposed to characterize the electro-optic frequency response of dual-parallel Mach-Zehnder modulators (DPMZMs) based on single-tone level control and low-frequency bias swing. The single-tone driving signal and the low-frequency bias signal of the DPMZM mix with each other after photodetection, and a low-frequency beat note is generated in the electrical domain. The functional relationship between the desired low-frequency amplitude and the single-tone driving level is investigated and established, from which the modulation depth and half-wave voltage are extracted with the help of regression analysis. We experimentally demonstrate the feasibility of the proposed method and compare it with the conventional ones to check the consistency. The self-referenced method features single-tone modulation and low-frequency detection for measuring high-speed DPMZMs, which avoids the use of a broadband photodetector (PD) and the influence of the uneven response of the PD.

Investigation of vortex motion mechanism of synthetic jet in a cross flow

To investigate the mechanism of vortex motion, a pitched synthetic jet is arranged on the bottom of a cross flow and simulated by incompressible Naiver–Stokes equations with large eddy simulation. The Liutex vector identification method is utilized to quantitatively study the rotation strength and the core size of the vortex structures according to various driving frequencies (St = 0.25, 0.5, 0.75, 1.0) and amplitudes (A0 = 1.0, 1.5, 2.0, 2.5) of the synthetic jet during 21 periods. The results show that both the frequency and the amplitude play a significant role in the vortex generation mechanism of the synthetic jet. However, the amplitude makes a positive contribution to the rotation strength and the vortex core size, while the frequency makes a negative contribution. The vortex motion mechanism of a synthetic jet in a cross flow can be summarized as follows: low frequency and small amplitude favor the primary clockwise vortex, while high frequency and large amplitude motivate the anticlockwise vortex generation.

Experimental research on the evolutionary characteristics of acoustic signals for concrete cracking under uniaxial compression

In this study, the evolutionary characteristics of the acoustic emission (AE), microseismic (MS), and sound signals released during concrete fracture in terms of their amplitude, b value, activity level, and frequency spectrum were investigated. The results indicated that the b values are all characterised by a continuous decline immediately before concrete failure, accompanied by the appearance of low-frequency signals with high amplitudes. The occurrence of these two phenomena can be used as precursor information for the subsequent concrete failure. Nevertheless, there are significant differences among the three signal types. Frequency ranges of these acoustic signals and hierarchical characteristics of the concrete fracturing result in different signal activeness, which can be evidenced by the following order of the initial stress of activeness: sound (85% σpeak), MS (70% σpeak), and AE (57% σpeak). Diversities in signal acquisitions modes lead to differences near the failure stage. A quiescent period of AE, characterized by only a few signals with low frequency and high amplitude, was observed immediately before concrete failure, whereas MS and sound were distributed in various frequency bands without quiescent periods. These differences indicated that the three types of signals have different sensitivities and applicability. A reliable concrete fracturing analysis and prediction can be achieved by the integrated usage of the three types of acoustic techniques.

Suppression of Cavitation Surge in Turbopump With Inducer by Reduced-Diameter Suction Pipe With Swirl Brake

Abstract Downsizing and high power density of turbopumps is achieved by increasing their rotational speed. Cavitation often becomes a problem while the influence of cavitation will be generally relieved by employing an inducer before the impeller. For general-use turbopumps with an inducer, instability-free operation, as well as high suction performance is required in a wide flow rate range including extremely low flow rate. However, the cavitation surge phenomenon with low frequency and large amplitude is often to be a serious problem even with inducer when operated at very low flow rates. In this study, a reduced-diameter suction pipe (RSP) equipped with swirl brake (SB) was proposed for a suppression device of the inlet backflow as well as of the cavitation surge through removing the swirling velocity component. The effectiveness of this device was investigated by computational fluid dynamics (CFD) and experiments. First, several geometries of RSP with SB were examined by CFD, and it was found that the extension of inlet backflow was stopped at this device provided that the swirl brake had a sufficient radial or axial length. Then, one of the proposed RSP with SB was manufactured, and the experimental evaluation of the effectiveness of this device was conducted. It seemed that RSP with SB could well prevent the extension of inlet backflow. The cavitation surge was completely suppressed even at extremely low flow rates. As a result, the suction performance was also improved at low flow rates.

Study on Energy Dissipation Mechanism of an Impact Damper System

Abstract The objective of this paper is to investigate how higher damping is achieved by energy dissipation as high-frequency vibration due to the addition of impact mass. In an impact damper system, collision between primary and impact masses cause an exchange of momentum resulting in dissipation of energy. A numerical model is developed to study the dynamic behavior of an impact damper system using a multi-degree-of-freedom (MDOF) system with augmented Lagrangian multiplier contact algorithm. Mathematical modeling and numerical simulations are carried out using ansysfea package. Studies are carried out for various mass ratios subjecting the system to low-frequency high amplitude excitation. Time responses obtained from numerical simulations at fundamental mode when the system is excited in the vicinity of its fundamental frequency are validated by comparing with experimental results. Magnification factor evaluated from numerical simulation results is comparable with those obtained from experimental data. The transient response obtained from numerical simulations is used to study the behavior of first three modes of the system excited in vicinity of its fundamental frequency. It is inferred that dissipation of energy is a main reason for achieving higher damping for an impact damper system in addition to being transformed to heat, sound, and/or those required to deform a body.

Natural infant-directed speech facilitates neural tracking of prosody

Infants prefer to be addressed with infant-directed speech (IDS). IDS benefits language acquisition through amplified low-frequency amplitude modulations. It has been reported that this amplification increases electrophysiological tracking of IDS compared to adult-directed speech (ADS). It is still unknown which particular frequency band triggers this effect. Here, we compare tracking at the rates of syllables and prosodic stress, which are both critical to word segmentation and recognition. In mother-infant dyads (n=30), mothers described novel objects to their 9-month-olds while infants’ EEG was recorded. For IDS, mothers were instructed to speak to their children as they typically do, while for ADS, mothers described the objects as if speaking with an adult. Phonetic analyses confirmed that pitch features were more prototypically infant-directed in the IDS-condition compared to the ADS-condition. Neural tracking of speech was assessed by speech-brain coherence, which measures the synchronization between speech envelope and EEG. Results revealed significant speech-brain coherence at both syllabic and prosodic stress rates, indicating that infants track speech in IDS and ADS at both rates. We found significantly higher speech-brain coherence for IDS compared to ADS in the prosodic stress rate but not the syllabic rate. This indicates that the IDS benefit arises primarily from enhanced prosodic stress. Thus, neural tracking is sensitive to parents’ speech adaptations during natural interactions, possibly facilitating higher-level inferential processes such as word segmentation from continuous speech.

A self-supported structure hybrid triboelectric/piezoelectric nanogenerator for bio-mechanical energy harvesting and pressure sensing

Recently, nanogenerators (NGs) based on triboelectric effect and piezoelectric effect have attracted worldwide attention. However, the development of NGs still faces many challenges, including reasonable structural design, multi-functional application, etc. Here, we reported a novel self-supported structure hybrid triboelectric/piezoelectric nanogenerator (TPNG) to harvest low-frequency and low amplitude mechanical energy through friction and deformation. The result of the experiment confirmed that the triboelectric part (size: 4 cm × 3 cm) of TPNG can achieve the maximum output power of 1.32 mW, and the piezoelectric section (size: 8 cm × 3 cm) of TPNG can arrive at 4.14 μW. Moreover, the triboelectric transferred charges and piezoelectric transferred charges of TPNG can get to 52.5 nC and 54 nC, respectively. In addition, all preparation materials are common commercial materials, which contributes to low-cost and large-scale production. The electrical energy produced by the TPNG device can drive 19 commercial light-emitting diodes (LEDs) and electronic calculators. The TPNG device can also serve as a self-powered sensor to reflect the change of pressure. This design realizes the integration of triboelectric devices and piezoelectric devices and will promote the development of self-powered flexible sensors.

Intrinsic Brain Activity Alterations in Patients With Mild Cognitive Impairment-to-Normal Reversion: A Resting-State Functional Magnetic Resonance Imaging Study From Voxel to Whole-Brain Level.

Mild cognitive impairment (MCI) reversion refers to patients with MCI who revert from MCI to a normal cognitive state. Exploring the underlying neuromechanism of MCI reverters may contribute to providing new insights into the pathogenesis of Alzheimer’s disease and developing therapeutic interventions. Information on patients with MCI and healthy controls (HCs) was collected from the Alzheimer’s Disease Neuroimaging Initiative database. We redefined MCI reverters as patients with MCI whose logical memory scores changed from MCI to normal levels using the logical memory criteria. We explored intrinsic brain activity alterations in MCI reverters from voxel, regional, and whole-brain levels by comparing resting-state functional magnetic resonance imaging metrics of the amplitude of low-frequency of fluctuation (ALFF), the fractional amplitude of low-frequency fluctuation (fALFF), percent amplitude of fluctuation (PerAF), regional homogeneity (ReHo), and degree centrality (DC) between MCI reverters and HCs. Finally, partial correlation analyses were conducted between cognitive scale scores and resting-state functional magnetic resonance imaging metrics of brain regions, revealing significant group differences. Thirty-two patients with MCI from the Alzheimer’s Disease Neuroimaging Initiative database were identified as reverters. Thirty-seven age-, sex-, and education-matched healthy individuals were also enrolled. At the voxel level, compared with the HCs, MCI reverters had increased ALFF, fALFF, and PerAF in the frontal gyrus (including the bilateral orbital inferior frontal gyrus and left middle frontal gyrus), increased PerAF in the left fusiform gyrus, and decreased ALFF and fALFF in the right inferior cerebellum. Regarding regional and whole-brain levels, MCI reverters showed increased ReHo in the left fusiform gyrus and right median cingulate and paracingulate gyri; increased DC in the left inferior temporal gyrus and left medial superior frontal; decreased DC in the right inferior cerebellum and bilateral insular gyrus relative to HCs. Furthermore, significant correlations were found between cognitive performance and neuroimaging changes. These findings suggest that MCI reverters show significant intrinsic brain activity changes compared with HCs, potentially related to the cognitive reversion of patients with MCI. These results enhance our understanding of the underlying neuromechanism of MCI reverters and may contribute to further exploration of Alzheimer’s disease.