Peak Frequency Research Articles

Correlations of temporomandibular joint morphology and position using cone-beam computed tomography and dynamic functional analysis in orthodontic patients: A cross-sectional study.

To correlate temporomandibular joint (TMJ) morphology and position with cone-beam computed tomography (CBCT) images, Joint Vibration Analysis (JVA), and Jaw Tracker (JT) to develop a radiation-free, dynamic method for screening and monitoring the TMJ in orthodontic patients. A total of 236 orthodontic patients without symptoms of TMJ disorders who had undergone CBCT were selected for the JVA and JT tests in this cross-sectional study. TMJ position and morphology were measured using a three-dimensional analysis software. JT measurements involved six opening-closing cycles, and JVA measurements were performed using a metronome to guide the mouth opening-closing movements of the patients. The correlations among the three measuring devices were evaluated. Abnormalities in condylar surface morphology affected the mandibular range of motion. The cut-off value results show that when various measurement groups are within a certain range, abnormalities may be observed in morphology (area under the curve, 0.81; P < 0.001). A 300/< 300 Hz ratio ≥ 0.09 suggested abnormal morphology (P < 0.05). Correlations were observed among the maximum opening velocity, maximum vertical opening position, and joint spaces in the JT measurements. Correlations were also observed between the > 300/< 300 Hz ratio, median frequency, total integral, integral < 300 Hz, and peak frequency with joint spaces in the JVA measurements. JT and JVA may serve as rapid, non-invasive, and radiation-free dynamic diagnostic tools for monitoring and screening TMJ abnormalities before and during orthodontic treatment.

A Machine-Learning-Based Method for Identifying the Failure Risk State of Fissured Sandstone under Water-Rock Interaction.

The mechanical properties of fissured sandstone will deteriorate under water-rock interaction. It is crucial to extract the precursor information of fissured sandstone instability under water-rock interaction. The potential of each acoustic emission (AE) parameter as a precursor for instability in the failure process of fissured sandstone was investigated in this study. An experimental dataset comprising 586 acoustic emission experiments was established, and subsequent classification training and testing were conducted using three machine learning (ML) models: AdaBoost, MLP, and Random Forest (RF). The primary parameters for identifying the instability risk state of fissured sandstone include acoustic emission ringing count, energy (mV·ms), centroid frequency, peak frequency, Rise Angle (RA), Average Frequency (AF), b value, and the natural/saturated state of fissured sandstone: state. To enhance data utilization, a 10-fold cross-validation method was employed during the model training process. The machine learning models were developed and designed to identify the instability risk of fissured sandstone under the natural and saturated states. The results demonstrated that the established RF model was capable of identifying fissured sandstone instability risks with an accuracy of 97.87%. Feature importance analysis revealed that state and b value exerted the most significant influence on identification results. The Spearman correlation coefficient was utilized to assess the correlation between input features. This study can provide technical support to identify the risk of instability of fissured sandstones under both natural and saturated water conditions. Based on the models developed in this study, it is possible to implement an early warning method for instability in fissured sandstone that meets realistic working conditions. Compared with the traditional empirical and formulaic methods, the machine learning method can more quickly process huge amounts of AE data and accurately identify the damage state of fissured sandstone.

Bearing fault detection using second-order moment spectrum and adaptive time-varying morphological filtering

The second-order moment spectrum is a method designed to simplify the complex shape of the spectrum, thus facilitating its interpretation for the identification and localization of defects based on peak frequency. Generally used as a final step in defect detection methods, this method offers the advantage of a more easily interpretable spectral shape. Compared to the shape of the spectrum of the vibration signal defined by the Fourier transform, which includes sidebands composed of peaks of large amplitude at different frequencies, the spectrum generated by the second-order moment spectrum method stands out for its simplicity. Starting from the mean and standard deviation of the vibration signal, the second-order moment can be defined as the power of the ratio between the standard deviation and the difference between the signal and the mean. Next, the Fourier transform is applied to express the second-order moment spectrum. The performance of the second-order moment spectrum is evaluated using the principle of comparison with the envelope spectrum obtained by the Hilbert transform. Vibration signals are analyzed using two methods: adaptive time-varying morphological filtering and second-order moment spectrum. After applying these methods to the signals from the database, we observe high-amplitude peaks at the frequencies corresponding to inner ring and ball defects. The second-order moment spectrum gives similar results to those obtained with the Hilbert transform envelope.

Mono- and oligochromatic extreme-mass-ratio inspirals

The gravitational capture of a stellar-mass object by a supermassive black hole represents a unique probe of warped spacetime. The small object, typically a stellar-mass black hole, describes a very large number of cycles before crossing the event horizon. Because of the mass difference, we call these captures extreme-mass-ratio inspirals (EMRIs). Their merger event rate at the Galactic Center is negligible, but the amount of time spent in the early inspiral is not. Early EMRIs (E-EMRIs) spend hundreds of thousands of years in band during this phase. At very early stages, the peak of the frequency will not change during an observational time. At later stages in the evolution, it will change a bit and finally the EMRI explores a wide range of them when it is close to merger. We distinguish between “monocromatic” E-EMRIs, which do not change their (peak) frequency, oligochromatic E-EMRIs, which explore a short range and polychromatic ones, and the EMRIs which have been discussed so far in the literature. We derive the number of E-EMRIs at the Galactic Center, and we also calculate their signal-to-noise ratios (SNR) and perform a study of parameter extraction. We show that parameters such as the spin and the mass can be extracted with an error which can be as small as 10−11 and 10−5M⊙. There are between hundreds and thousands of E-EMRIs in their monochromatic stage at the Galactic Centre (GC), and tens in their oligochromatic phase. The SNR ranges from a minimum of 10 (larger likelihood) to a maximum of 106 (smaller likelihood). Moreover, we derive the contribution signal corresponding to the incoherent sum of continuous sources of oligochromatic E-EMRIs with two representatives masses, 10M⊙ and 40M⊙, and show that their curves will cover a significant part of Laser Interferometer Space Antennas (LISAs) sensitivity curve. Depending on their level of circularization, they might be detected as individual sources or form a foreground population. Published by the American Physical Society 2024

Turning up the heat: Effects of temperature on agonistic acoustic communication in the two-spotted goby (Pomatoschistus flavescens)

Acoustic communication is linked to fitness traits in many animals, but under the current scenario of global warming, sound signals can be affected by rising temperatures, particularly in ectothermic organisms such as fishes. This study examines the effect of water temperature in acoustic communication in the two-spotted goby, Pomatoschistus flavescens. To address this, we looked at the effect of different temperatures on the acoustic features of drums produced by males during territorial defence and related it with their auditory sensitivity. We also analysed the differences in acoustic features between male agonistic drums and previously reported male courtship sounds, to better understand how acoustic communication may be affected by different temperature conditions. We recorded two-spotted goby males during territorial intrusions for 10 min at 16 °C, 19 °C, and 21 °C in the laboratory. We found that agonistic drums were shorter, had fewer pulses and shorter pulse periods at higher temperature, in contrast with the peak frequency that remained unaffected. Male agonistic and mating drums (recorded in a previous study) at 16 °C only differed in pulse period, which was higher in mating drums. Hearing thresholds obtained with Auditory Evoked Potentials at 16 °C, revealed higher sensitivity below 400 Hz, matching the main energy of agonistic and mating sounds. Our findings suggest that increasing temperature could potentially affect acoustic communication in this species by reducing the duration of agonistic drums, which might hinder effective communication. Nevertheless, the impact may not be significant as there was a good match between the best hearing sensitivity and the peak frequency range of their calls, which was not influenced by temperature. As fish and other organisms are increasingly threatened by multiple anthropogenic stressors, including warming, future research should address how changes in water temperature impact acoustic communication within a more realistic multi-stressor scenario.

Event classification, seismicity, and eruption forecasting at Great Sitkin Volcano, Alaska: 1999–2023

The frequency content of volcanogenic seismicity is often used to classify events and their spatial and temporal progression is then used to map subsurface volcanic processes. The progression of volcano-seismic events and associated source processes also plays a critical role in eruption forecasting. Here we develop and evaluate a computerized methodology for characterizing volcano-seismic event types using Frequency Index and Average Peak Frequency. We apply and test this technique at Great Sitkin Volcano, Alaska, classifying over 9000 hypocenters between 1999 and 2023. This 24-year time span covers periods of seismic quiescence, earthquake activity on nearby tectonic (bookshelf) faults, precursory unrest from 2016 to 2021, and the explosive onset in May 2021 of the ongoing effusive eruption. We use the spatial and temporal evolution of classified event types to map the active volcanic and tectonic processes, develop a conceptual model of the subsurface magmatic system, and perform a retrospective analysis of eruption forecasts at Great Sitkin Volcano between 2016 and the present. The classification and progression of hypocenters suggests the subsurface Great Sitkin Volcano magmatic system consists of a mid- to lower- crustal source zone between 10 and 40 km depth and an upper crustal magma storage area between −1 and 10 km depth (hypocenter depth is referenced to sea level and negative depths reflect height above sea level). The earliest precursors occurred in July 2016 and consisted of deep long-period and volcano-tectonic earthquakes at mid-crustal depths suggesting the subsequent unrest and eruption were triggered by a deeper intrusion of magma. This mid-crustal seismic activity was immediately followed by the onset upper-crustal long-period events and volcano-tectonic earthquakes VTs suggesting a strong linkage between the shallow and deeper portions of the magmatic system. The upper crustal area was likely capped by the 1974 lava dome until the magmatic explosion on May 26, 2021.

Plummer-Vinson syndrome: Clinical, therapeutic and evolutionary aspects: a Moroccan case series

Plummer Vinson syndrome (PVS) is a rare entity characterized mainly by upper dysphagia, irondeficiency anemia, and the presence of an esophageal ring on endoscopic examination. We conducted a retrospective study over a period of 18 years describing the epidemiological and clinical profile, endoscopic management and the medium and long-term evolution. A total of 96 patients were enrolled, with a median age of 41,5 years and a clear female predominance (19/77). dysphagia was present in almost all our patients (97,9%), and an anemic syndrome in half the cases (52%). Female gender was significantly associated with PVS occurrence (p=0.002). The frequency of the disease was significantly higher after the age of 30 years with a peak in frequency in the 4th decade (p&lt;0.034). Upper endoscopy found a membranous ring located in the cervical area in all cases. 1 patient had, in addition to the plummer vinson ring, a lower esophageal membranous called Schatzki ring with a small sliding hiatal hernia. PVS was associated with other autoimmune diseases mostly represented by celiac disease and autoimmune thyroiditis. Treatment was based on iron supplementation followed by endoscopic dilatation with Savary dilators in 91,6% (n=88) and balloons for 8,3% of cases (n=8). long-term outcome was favorable in 79.1% of patients with no clinical recurrence. 20,8% patients relapsed after a median of 29,2 months [2-72 months] requiring a second dilation. PVS was complicated by squamous cell carcinoma in 5,2% (n=5).

Passive Seismology: Lightweight and Rapid Detection of Arctic Subsea and Sub‐Aquatic Permafrost

AbstractLow sea levels during the last Ice Age exposed millions of square kilometers of Arctic shelves which have been subsequently submerged, creating subsea permafrost. In onshore settings, permafrost can also exist beneath water bodies such as coastal lagoons, rivers, and thermokarst lakes. We explored passive seismology as a method for mapping unfrozen sediment thickness above subsea and sub‐aquatic permafrost. We present passive seismic data collected with the Mobile Ocean Bottom Seismic Instrument (MOBSI) from the Beaufort Sea near Tuktoyaktuk in Canada, Ivashkina Lagoon on the Bykovsky Peninsula, as well as a lake and river in the Lena Delta, Siberia, Russia. We use borehole data and frost probe measurements to identify permafrost‐related H/V measurement peaks and calibrate shear wave velocities for frequency‐to‐depth conversion. We employ the shortest path and maximum signal amplitude to connect peaks and generate geological profiles. The MOBSI detected the ice‐bonded permafrost table beneath the Beaufort Sea, as well as beneath a Siberian lake and lagoon. At Tuktoyaktuk, an ocean bottom seismometer revealed a 5% scatter about the peak frequency for three‐minute time windows and over 8 hr of recording time. With peak frequencies ranging from 4.9 ± 0.2 Hz to 27.6 ± 1.4 Hz, the depth to subsea permafrost ranged from 1.4 ± 0.1 m bsl at the shoreline to 14.0 ± 0.4 m bsl 240 m offshore. Given an accurate shear wave velocity, our findings highlight that MOBSI deployment times as short as 3 min are adequate for detecting Arctic subsea and sub‐aquatic permafrost.

Numerical studies on the radiation of micro-pressure wave noise at the tunnel exits

To effectively control the micro-pressure wave noise radiating from tunnel exits, numerical simulations were conducted to investigate the generation and propagation of such noise at the exits of high-speed metro tunnels. Large-eddy simulation was employed to obtain the near-field unsteady flow field data at the tunnel exit. The Ffowcs Williams–Hawkings (FW–H) acoustic analogy was used to predict the types of sound sources for micro-pressure wave noise. The unsteady flow field data were also utilized for finite element method acoustic analysis to calculate the far-field radiation of micro-pressure wave noise. The accuracy of the numerical methods was verified through moving model tests. The results indicate that dipole noise dominates within the micro-pressure wave noise. The tunnel's inner wall contributes most to the dipole sound sources. Dipole noise radiates outward in the form of semi-ellipsoidal waves, with energy mainly concentrated below 20 Hz and a peak frequency of 4 Hz. Furthermore, the decay of dipole noise in the direction of the tunnel exit follows a similar exponential decay pattern to that of an explosion shock wave. When the train speed exceeds 400 km/h, the human ear can distinctly perceive the sonic booms at the tunnel exit.

ComBat models for harmonization of resting-state EEG features in multisite studies

ObjectivePooling multisite resting-state electroencephalography (rsEEG) datasets may introduce bias due to batch effects (i.e., cross-site differences in the rsEEG related to scanner/sample characteristics). The Combining Batches (ComBat) models, introduced for microarray expression and adapted for neuroimaging, can control for batch effects while preserving the variability of biological covariates. We aim to evaluate four ComBat harmonization methods in a pooled sample from five independent rsEEG datasets of young and old adults. MethodsRsEEG signals (n = 374) were automatically preprocessed. Oscillatory and aperiodic rsEEG features were extracted in sensor space. Features were harmonized using neuroCombat (standard ComBat used in neuroimaging), neuroHarmonize (variant with nonlinear adjustment of covariates), OPNested-GMM (variant based on Gaussian Mixture Models to fit bimodal feature distributions), and HarmonizR (variant based on resampling to handle missing feature values). Relationships between rsEEG features and age were explored before and after harmonizing batch effects. ResultsBatch effects were identified in rsEEG features. All ComBat methods reduced batch effects and features’ dispersion; HarmonizR and OPNested-GMM ComBat achieved the greatest performance. Harmonized Beta power, individual Alpha peak frequency, Aperiodic exponent, and offset in posterior electrodes showed significant relations with age. All ComBat models maintained the direction of observed relationships while increasing the effect size. ConclusionsComBat models, particularly HarmonizeR and OPNested-GMM ComBat, effectively control for batch effects in rsEEG spectral features. SignificanceThis workflow can be used in multisite studies to harmonize batch effects in sensor-space rsEEG spectral features while preserving biological associations.

Abnormal brain-heart electrophysiology in mild and severe orthostatic hypotension.

This study investigated the changes in cardiocerebral electrophysiology in patients with mild orthostatic hypotension (MOH) and severe orthostatic hypotension (SOH) and their relationship with the severity of orthostatic hypotension, psychiatric symptoms, and cognitive dysfunction. This study included 72 nonorthostatic hypotension (NOH), 17 with MOH, and 11 with SOH. Seated resting-state heart rate variability (HRV) and quantitative electroencephalogram parameters were synchronized and recorded. HRV measures in the time and frequency domains were analyzed, along with the peak frequency and power of the brain waves. Abnormal neuronal activity was found in FP1 in patients with MOH, whereas it was more widespread in FP1, FP2, and O2 in patients with SOH (P < 0.05). Cardiac and cerebral electrophysiological abnormalities were significantly associated with orthostatic hypotension severity, psychiatric symptoms, and cognitive dysfunction. Abnormal EEG activity in patients are mainly manifested in the prefrontal and occipital lobes, especially in patients with SOH. These results may help patients to better understand the mechanisms underlying orthostatic hypotension severity and psychiatric and cognitive impairment in orthostatic hypotension.

Neurofeedback Training in Children with ADHD: A Systematic Review of Personalization and Methodological Features Facilitating Training Conditions.

Objective. Current research on the effectiveness of neurofeedback (NFB) in children with attention-deficit/hyperactivity disorder (ADHD) is divided. Personalized NFB (pNFB), using pre-recorded individual electroencephalogram (EEG) features, is hypothesized to provide more reliable results. Our paper reviews available evidence on pNFB effectiveness and its methodological quality. Additionally, it explores whether other methodological features implying personalization are related to successful NFB. Methods. We conducted a systematic literature review on PubMed, PSYNDEX, PsycInfo and PsycArticles until November, 30, 2023. Studies that focused on pNFB in children with ADHD were selected, deviant studies excluded. Quality ratings by independent raters using Loney's1 criteria were conducted. Pooled effect sizes for NFB effects and methodological features were calculated. Results. Three of 109 studies included personalization and were reviewed in the full-text. In two studies, theta/beta-NFB was personalized using individual alpha peak frequencies (iAPF), whereas in one study, individual beta rhythms were trained. All three studies demonstrated significant short- and long-term improvements in ADHD symptoms, as assessed by questionnaires and objective performance tests, when compared to standard protocols (SP), sham-NFB, and control conditions. Twelve of 111 studies reported methodological features consistently related to NFB effectiveness. These features, including self-control instructions, feedback animations, timing of feedback presentation, behavioral performance, pre-recorded individual ERP-components and stimulant medication dosage, can be used to personalize NFB and enhance training success. Conclusion. Personalizing NFB with iAPF appears promising based on the existing -albeit small- body of research. Future NFB studies should include iAPF and other personalized features facilitating implementation consistently associated with treatment success.

Optical properties of cylindrical topological photonic crystal heterostructures

This paper uses a modified transfer matrix method to investigate the optical properties of a cylindrical topological photonic crystal heterostructure composed of two cylindrical photonic crystals. Topological photonic crystals are novel structures with topological edge states capable of field confinement and robust propagation. Numerical results showed that when the sum of the phases of the reflection coefficients of the two cylindrical photonic crystals is zero, a topological edge state occurs inside their overlapping band gaps. In the linear regime, the peak frequency of the topological edge states undergoes a redshift as the incidence angle increases. An increase in the incidence angle leads to a decrease (increase) in the Full width at half maximum of the E-polarized (H-polarized) topological edge states. As the incidence angle increases, the frequency separation between the E-polarized and H-polarized topological edge states increases, causing the cylindrical heterostructure to work as a polarizer. The performance of the cylindrical topological photonic crystal heterostructure as a polarizer is evaluated in the linear and nonlinear regimes. We showed that the peak frequency of the topological edge states undergoes a redshift irrespective of their polarization state as the intensity of the input light increases. We found that the structure has a good performance in the nonlinear regime due to the higher displacement in E-polarized topological edge states compared to H-polarized topological edge states. The findings of this paper might be beneficial in the construction of polarization-maintaining optical fiber, which has specific applications in telecommunications, fiber optic sensing, interferometry, and quantum key distribution.

Measuring Vibrations of Subway Tunnel Structures with Cracks

In a study conducted in a metro tunnel, acceleration and displacement sensors were strategically placed along steel rails, track beds, and tunnel walls to capture real-time dynamic responses during train operations. Data were analyzed in the time and frequency domains, focusing on vibration levels and one-third octave bands. The results indicated that peak vibration acceleration significantly decreases from steel rails to tunnel walls, with different vibration frequencies observed at various locations: steel rails (200 Hz–1400 Hz), track beds, and tunnel walls (70 Hz–400 Hz). Cracks notably increase peak acceleration, vibration levels, peak frequency, and steel rail displacement but do not alter the overall vibration trends. Tunnel wall responses show the highest sensitivity to cracks, with a 300% increase in peak frequency, followed by track beds (100%) and steel rails (70%). Vibration levels under one-third octave band processing increased by 12.4% for tunnel walls, 8.8% for track beds, and 2.2% for steel rails. Cracks also caused steel rails’ vertical and lateral displacement to rise by 112% and 53%, respectively. These findings provide valuable insights for vibration reduction and crack repair in long-term subway operations.

Deep learning for retrieving omni-directional ocean wave spectra from spaceborne synthetic aperture radar

Synthetic Aperture Radar (SAR) is a unique remote sensing instrument imaging ocean surface waves in two dimensions with high spatial resolution regardless of sunlight and weather conditions. However, due to the nonlinear imaging process, the ocean wave spectra cannot be retrieved directly from SAR data. The emergence of deep learning (DL) techniques provides a new paradigm for addressing this challenge. In this paper, a deep-learning-based model, called Wave-Spec-CNN, is proposed for retrieving omni-directional ocean wave spectra from SAR data. This model is constructed using approximately 21,000 collocations of Sentinel-1 Interferometric Wide swath mode images matched with global in-situ buoy data. The model adapts the convolution neural network (CNN) to accommodate the multi-valued nature of omni-directional ocean wave spectra, enhances performance by integrating a calibration branch and further incorporates physical characteristics into the training process. The results demonstrate consistency with buoy measurements for significant wave height (SWH) in the range of 0.5 m to 6 m, yielding a root-mean-square error (RMSE) of 0.51 m on the validation dataset, comparable to traditional physical-based methods. In terms of mean wave period (MWP) and peak frequency (PF), the achieved RMSEs are of 1.24 s and 0.03 Hz, respectively. The retrieved omni-directional ocean wave spectra also allow to separate swell and windsea components for respective comparisons with those derived by in-situ buoy data. The RMSEs of respective SWH comparisons are of 0.46 m and 0.42 m. This research represents an initial endeavor into utilizing DL for the long-standing challenge of SAR inversion for ocean wave spectra, as well as providing valuable insights for employing DL in multi-parameter inversion tasks in remote sensing.

Single-pulse Gamma-Ray Bursts Have Prevalent Hard-to-soft Spectral Evolution

We analyze the spectral evolution of 62 bright Fermi gamma-ray bursts with large enough signal-to-noise to allow for time-resolved spectral analysis. We develop a new algorithm to test for single-pulse morphology that is insensitive to the specific shape of pulses. Instead, it only checks whether or not there are multiple, isolated, or statistical significant peaks in the light curve. In addition, we carry out a citizen science test to assess light-curve morphology and spectral evolution. We find that, no matter the adopted assessment method, bursts characterized by single-peaked prompt emission light curves have a greater tendency to also have a consistently decaying peak energy or hard-to-soft spectral evolution. This contrasts with the behavior of multipeaked bursts, for which the tendency is to have a peak frequency that is not monotonically decreasing. We discuss this finding in the theoretical framework of internal/external shocks and find it to be consistent with at least some single-pulse bursts associated with particularly high-density environments.

Fracture properties and acoustic emission characteristics of manufactured sand recycled fine aggregate concrete

To promote the application of recycled fine aggregates, fracture characteristics of concrete beams containing manufactured sand (MS) and recycled fine aggregate (RFA) were investigated. The fracture properties and acoustic emission (AE) characteristics of manufactured sand recycled fine aggregate concrete (MSRFAC) with 0 %, 25 %, 50 %, 75 % and 100 % RFA replacement rates were evaluated by three-point bending test of single-sided notched beams. The fracture mechanisms of MSRFAC beams were explored using AE and digital image correlation (DIC) techniques, and fracture process zone (FPZ) was qualitatively and quantitatively analyzed. The results indicated that the critical nominal stiffness, initial fracture toughness, fracture energy and characteristic length of MSRFAC decreased significantly with the increase of RFA replacement rate, up to 20.2 %, 37.7 %, 22.8 %, and 26.6 %, respectively, while the unstable fracture toughness was insensitive to the variation of RFA. Moreover, the AE activity, the tensile crack, large-scale crack, high amplitude, and high peak frequency in MSRFAC increased with increasing RFA replacement rate. According to the FPZ characteristics of MSRFAC, its FPZ length increased with the increase of RFA replacement rate, while the FPZ width decreased with the increase of RFA replacement rate. The critical FPZ lengths of MSRFAC with different RFA replacement rates were about 20.2–30.0 mm, and the maximum FPZ widths were about 26.0–36.7 mm. The RFA weakened the friction mechanism and interlocking effect between aggregates of MSRFAC, resulting in a faster FPZ propagation rate and smaller damage width of MSRFAC than normal manufactured sand concrete.

High sensitivity flexible piezoelectric nanogenerator based on multi‐layer piezoelectric composite fiber for human motion energy harvesting

AbstractIn this study, a piezoelectric nanogenerator (PENG) based on multilayer composite fiber had good and stable piezoelectric output performance, which could realize biomechanical energy collection and human movement monitoring. The polyvinylidene fluoride‐hexafluoryl propylene (P(VDF‐HFP)) composite fiber doped with MXene was used as a promising piezoelectric functional layer (MPFP). By electrospinning, P(VDF‐HFP) composite fiber was constructed by alternating electrospinning with polyurethane (TPU) nanofibers layer by layer. The adoption of MXene as a functional filler promoted the transformation of P(VDF‐HFP) from α to piezoelectric β‐crystal, the piezoelectric β‐crystal content of P(VDF‐HFP) increased, and the dielectric properties and polarization levels were enhanced. At the same time, the multi‐layer structure design improved the piezoelectric sensitivity and mechanical properties of the composite fiber, and the composite fiber was more flexible and had longer tensile strain. With excellent dielectric and mechanical properties, 3MPFP/TPU/3MPFP/TPU multilayer composite fibers showed piezoelectric sensitivity of 10.88 V/kPa. Under the action of palm pressing, the PENG generated an open circuit voltage of 25 V, and the voltage signal of the device under different motion forms had specific characteristics such as peak value, frequency, and shape, which could be used to realize the analysis of human motion forms. This study provided an efficient, simple, and creative new idea for the application of flexible energy storage electronic devices, PENGs, and piezoelectric sensors.

Acoustic emission characteristics of coal and limestone failure based on MFCC

Fractures in the rock surrounding karst caves can result in substantial surface subsidence, especially in mining areas with abundant carbonate rocks. Acoustic emission (AE) is a crucial signal associated with rock fracture mechanics and lithology. This study aimed to distinguish the AE features between coal and limestone using the MFCC-based method and universal AE analysis method in conjunction with uniaxial compression tests. The results indicated that the MFCC-4–6 of AE could distinguish between coal and limestone prior to rock failure. The MFCC-1–6 of limestone exhibited a tail-like pattern change on the stress sawtooth and a step-like pattern change after reaching peak stress. The fluctuation degree of MFCC-2–5 exhibited an initial transition from small to large, followed by a subsequent transition from large to small, reaching its maximum value during the elastic deformation stage. Additionally, the power law distribution index of AE energy in the magnitude range of 102–104 for coal was larger than that for limestone. The AE events in coal were mainly characterized by shear fractures, while limestone exhibited more tension fractures than coal, as indicated by the AF/RA analysis. Furthermore, the lower the AE peak frequency, the larger the scale of fracturing in coal and limestone. These findings are valuable for ground control and early warning of rock failure.

On the effects of wind and operating conditions on mooring line tensions for floating offshore wind turbine

The present work addresses a significant topic in the current understanding of the structural dynamic behavior of mooring lines for floating offshore wind turbines (FOWT) in operating condition and aims to contribute to the ongoing efforts to enhance the performance and reliability of floating offshore wind energy systems. The present paper investigates the impact of operating conditions on mooring line tension for FOWT. A numerical model of a spar-type FOWT developed in Orcaflex, validated with experimental data, was employed to perform dynamic analyses and to calculate the most probable maximum tension values for scenarios involving wave-only and combined wind-wave actions under various operating conditions. Results indicate that the peak frequency of oscillations is primarily influenced by wave frequency and remain unchanged in operating conditions, but the significant variability in the structure’s displacement response leads to a notable fluctuation in tensions within the mooring lines. Specifically, higher tensions are observed in the upwind region while lower tensions are evident in the downwind area. However, for prolonged periods it becomes apparent that operating conditions induce high tension levels across all mooring lines, while also exerting a damping contribution related to wave-induced effects. The study underscores that the primary detrimental factor affecting mooring lines in operating conditions is the widening of the operating tension range.