Loss Of Amplitude Research Articles

Experimental Study of an Industrial Data Transmission Network in the Automatic Control System of a Wind Turbine

This article explores and optimizes network technologies for wind energy systems, focusing on the RS-485 interface to ensure reliable data transmission in extreme conditions. The study aims to address the impact of various distortions on data quality and wind turbine management. A system was proposed with two wind turbines, each equipped with a Raspberry Pi 4, connected to sensors measuring temperature, vibration, and wind speed. The research examined how data transmission rates affect signal shape, calculating the distortion coefficient. At 460,800 baud, the signal was almost completely distorted, with significant amplitude loss. The distortion coefficients were 1.84 for logic ‘1’ and 1.92 for logic ‘0’. The optimal speed to minimize distortions was found to be 19,200 baud, providing the most stable signal. Additionally, temperature significantly impacted transmission quality, highlighting the need to consider climatic conditions in system design. The findings and methods can help improve existing data transmission systems and enhance wind turbine performance.

Acoustic Wave Velocities in Bridge Steels and the Effects on Ultrasonic Testing

Ultrasonic testing is utilized to ensure weld quality during the fabrication of steel bridges by identifying discontinuities that are classified as either acceptable or rejectable. The classification of a discontinuity can be affected by differences in the acoustic properties of the material under test and the reference standard used for calibration. Differences in wave velocity affect the refracted angle and amplitude of refracted shear waves. As a result, indications can be missed or incorrectly classified, or incorrectly located in the material. The objective of this research study was to characterize the acoustic wave velocities in a sample of contemporary steels to better understand the range over which velocities may vary for common steels. To address this objective, a series of velocity measurements have been conducted for shear waves propagating through different directions in steel plates of different strengths and reported manufacturing processes. The study also examines the loss of signal amplitude that results from changes in the refracted angle of shear waves used for the inspection of welds. Beam splitting that may occur in anisotropic materials and the potential impact on signal amplitudes is also presented. It was shown in the research that relatively small differences in velocity between the material under test and the reference standard cause a loss of sensitivity of the test. Data presented in the paper documents wave velocity and anisotropic ratios for a population of contemporary bridge steels used for the fabrication of steel bridges and an assessment of how velocity differences affect the amplitude of reflected shear waves.

Development of a Semi-Autonomous Pulse and Receive Concrete Inspection System

Concrete structures are being subjected to increasing loads and used beyond their intended lifespan. When combined with operators shrinking maintenance budgets it is imperative structures are monitored for damage. Acoustic Emission (AE) and AE Tomography offer a method for damage detection and characterisation. However, they are encumbered by their equipment and setup requirements, and best used on areas where damage is already known to have occurred. An autonomous pulse catch system could be used to identify these areas. To explore the potential of such a system, seven concrete beams differentiated by their aggregate size were tested using an automated pulse and receive system. The effect of aggregate size, and pulse frequency on attenuation and wavespeed are investigated. The pulse regime consisted of narrowband pulses ranging from 30 kHz to 500 kHz. The results show that high frequency pulses experienced greater attenuation than low frequency pulses. Whilst a link appears between the size of the aggregate and the rate of attenuation of high frequency signals. A strong negative correlation between amplitude loss and pulse frequency was observed. For the specimen containing coarse aggregate, pulse velocity was constant between 100 kHz and 500 kHz, whereas specimens containing coarse aggregate experienced frequency dependant attenuation. This testing shows the significant potential for an automated pulse and receive system, which could lead to the development of an autonomous health monitoring system. In addition, the approach can be instrumental in developing large data sets, that can be used in Machine Learning processes, to develop a deeper understanding of AE signal propagation in concrete materials.

Signal detection

Acoustic emission (AE) occurring in concrete fracture process is a combination of concrete fracture at local material level and the propagation of induced elastic waves at structural level. Simulation of the fracture-induced AE in concrete needs a model that is able to address the fracture behavior and the wave propagation at the same time. However, to date, no available modelling tools can simulate the whole fracture-induced AE process. Among others, the lattice models have the potential to achieve the simulation of the whole fracture-induced AE process. However, the lattice models are currently restricted to statistical analysis of AE events in fracture process. This paper investigates the feasibility and limitation of lattice model for the simulation of elastic wave propagation process. Several simulation cases are performed considering the propagation of both plane waves and point-source waves. The simulation results, in terms of wave velocity and geometric spreading loss of wave amplitudes, agree well with the analytical solutions. This study represents the first step for the simulation of complete fracture-induced AE waves in concrete.

A high-efficiency Q-compensated pure-viscoacoustic reverse time migration for tilted transversely isotropic media

The attenuation and anisotropy characteristics of real earth media give rise to amplitude loss and phase dispersion during seismic wave propagation. To address these effects on seismic imaging, viscoacoustic anisotropic wave equations expressed by the fractional Laplacian have been derived. However, the huge computational expense associated with multiple Fast Fourier transforms for solving these wave equations makes them unsuitable for industrial applications, especially in three dimensions. Therefore, we first derived a cost-effective pure-viscoacoustic wave equation expressed by the memory-variable in tilted transversely isotropic (TTI) media, based on the standard linear solid model. The newly derived wave equation featuring decoupled amplitude dissipation and phase dispersion terms, can be easily solved using the finite-difference method (FDM). Computational efficiency analyses demonstrate that wavefields simulated by our newly derived wave equation are more efficient compared to the previous pure-viscoacoustic TTI wave equations. The decoupling characteristics of the phase dispersion and amplitude dissipation of the proposed wave equation are illustrated in numerical tests. Additionally, we extend the newly derived wave equation to implement Q-compensated reverse time migration (RTM) in attenuating TTI media. Synthetic examples and field data test demonstrate that the proposed Q-compensated TTI RTM effectively migrate the effects of anisotropy and attenuation, providing high-quality imaging results.

Dysfunctional lens syndrome: a literature review

Introduction. The term “Dysfunctional Lens Syndrome” (DLS) refers to age-related changes in the lens, including early cataracts and presbyopia, that do not significantly reduce visual acuity. This syndrome is characterized by a decrease in accommodative amplitude, an increase in light scattering, and a reduction in contrast sensitivity. With rising life expectancy, the prevalence of DLS is increasing, necessitating a more in-depth study of the pathogenic mechanisms underlying the syndrome and the refinement of its diagnostic criteria to establish standards for treatment correction. Aim: to summarize information on the pathogenesis of DLS, the potential for staging the syndrome using objective examination methods, and to provide treatment recommendations. Materials and methods. A bibliographic study of scientific publications was conducted using the Pubmed, ScienceDirect, and Cyberleninka databases. Literature sources were searched using the following keywords: dysfunctional lens syndrome (DLS), presbyopia correction, cataract, age-related lens changes. A total of 32 publications, primarily from the last 10 years, were included in the study from more than 100 viewed sources. Results. The DLS encompasses a wide range of conditions, from early stages characterized by a loss of accommodative amplitude and minor refractive anomalies to later stages involving a decrease in visual acuity and quality due to increased light scattering and aberrations. Currently, the evaluation of age-related lens changes involves assessing visual acuity and determining the degree of lens opacification using slit-lamp examination. Additionally, objective instrumental methods, such as optical coherence tomography and Scheimpflug imaging, can be used to assess the degree of lens opacification. Various methods are employed for the correction and treatment of DLS, ranging from glasses and contact lenses to surgical interventions, such as lens extraction and intraocular lens implantation. Research is also ongoing into drugs aimed at slowing the progression of lens changes. Conclusion. The term “Dysfunctional Lens Syndrome” is currently used to describe early cataracts and presbyopia, where the reduction in visual acuity is still minor, but patients experience visual complaints due to age-related lens changes. Further research is necessary to develop and standardize diagnostic criteria and to evaluate the effectiveness of new treatment methods and interventions in order to create the most effective and adequate approach to correcting DLS and alleviating the associated visual complaints.

Separating Surface Reflectance from Volume Reflectance in Medical Hyperspectral Imaging.

Hyperspectral imaging has shown great promise for diagnostic applications, particularly in cancer surgery. However, non-bulk tissue-related spectral variations complicate the data analysis. Common techniques, such as standard normal variate normalization, often lead to a loss of amplitude and scattering information. This study investigates a novel approach to address these spectral variations in hyperspectral images of optical phantoms and excised human breast tissue. Our method separates surface and volume reflectance, hypothesizing that spectral variability arises from significant variations in surface reflectance across pixels. An illumination setup was developed to measure samples with a hyperspectral camera from different axial positions but with identical zenith angles. This configuration, combined with a novel data analysis approach, allows for the estimation and separation of surface reflectance for each direction and volume reflectance across all directions. Validated with optical phantoms, our method achieved an 83% reduction in spectral variability. Its functionality was further demonstrated in excised human breast tissue. Our method effectively addresses variations caused by surface reflectance or glare while conserving surface reflectance information, which may enhance sample analysis and evaluation. It benefits samples with unknown refractive index spectra and can be easily adapted and applied across a wide range of fields where hyperspectral imaging is used.

Does an improvement in cord-level intraoperative neuromonitoring data lead to a reduced risk for postoperative neurologic deficit in spine deformity surgery?

To determine if an improvement in cord-level intraoperative neuromonitoring (IONM) data following data loss results in a reduced risk for new postoperative motor deficit in pediatric and adult spinal deformity surgery. A consecutive series of 1106 patients underwent spine surgery from 2015 to 2023 by a single surgeon. Cord alerts were defined by Somatosensory-Evoked Potentials (SSEP; warning criteria: 10% increase in latency or > 50% loss in amplitude) and Motor-Evoked Potentials (MEP; warning criteria: 75% loss in amplitude without return to acceptable limits after stimulation up 100V above baseline level). Timing of IONM loss and recovery, interventions, and baseline/postoperative day 1 (POD1) lower extremity motor scores were analyzed. IONM Cord loss was noted in 4.8% (53/11,06) of patients and 34% (18/53) with cord alerts had a POD1 deficit compared to preoperative motor exam. MEP and SSEP loss attributed to 98.1% (52/53) and 39.6% (21/53) of cord alerts, respectively. Abnormal descending neurogenic-evoked potential (DNEP) was seen in 85.7% (12/14) and detected 91.7% (11/12) with POD1 deficit. Abnormal wake-up test (WUT) was seen in 38.5% (5/13) and detected 100% (5/5) with POD1 deficit. Most cord alerts occurred during a three-column osteotomy (N = 23/53, 43%); decompression (N = 12), compression (N = 7), exposure (N = 4), and rod placement (N = 14). Interventions were performed in all 53 patients with cord loss and included removing rods/less correction (N = 11), increasing mean arterial pressure alone (N = 10), and further decompression with three-column osteotomy (N = 9). After intervention, IONM data improved in 45(84.9%) patients (Full improvement: N = 28; Partial improvement: 17). For those with full and partial IONM improvement, the POD1 deficit was 10.7% (3/28) and 41.2% (7/17), respectively. For those without any IONM improvement (15.1%, 8/53), 100% (8/8) had a POD1 deficit, P < 0.001. A full or partial improvement in IONM data loss after intraoperative intervention was significantly associated with a lower risk for POD1 deficit with an absolute risk reduction of 89.3% and 58.8%, respectively. All patients without IONM improvement had a POD1 neurologic deficit.

Wire rope isolator identification and dynamic modeling for small amplitude vibrations

Wire rope isolators are used in variety of applications to protect sensitive equipment from vibration. The nonlinear hysteretic behavior of steel wires provides advantages when compared to linear vibration isolators. This study proposes an amplitude dependent stiffness and damping model for low amplitude vibrations under axial loading, where the parameters can be determined with an experimental procedure. Comprehensive experimental results of forced vibration tests with varying loading, frequency and preload were considered in the model identification. Amplitude dependent stiffness and loss energy models were determined from the test data, and the effect of the preload and loading frequency on the model parameters were studied. It is shown, that the effect of preload and frequency is not evidently clear, while the effect of vibration amplitude is more significant. The mathematical model was further verified against measurements from base excitation loading. The proposed model can be used to study the effectiveness of the selected wire rope isolator configurations in chosen application, and to effectively perform dynamic design studies.

Influence of loss function and electron dose on ptychography of 2D materials using the Wirtinger flow

Iterative phase retrieval is based on minimising a loss function as a measure of the consistency of an initial guess and underlying experimental data. Under ideal experimental conditions, real data contains Poissonian noise due to counting statistics. In this work, we use the Wirtinger Flow concept in combination with four common loss functions, being the L1 loss, the mean-squared error (MSE), the amplitude loss and the Poisson loss. Since only the latter reflects the counting statistics as an asymmetric Poisson distribution correctly, our simulation study focuses on two main cases. Firstly, high-dose momentum-resolved scanning transmission electron microscopy (STEM) of an MoS2 monolayer is considered for phase retrieval. In this case, it is found that the four losses perform differently with respect to chemical sensitivity and frequency transfer, which we interprete in terms of the substantially different signal level in the bright and dark field part of diffraction patterns. Remedies are discussed using further simulations, addressing the use of virtual ring detectors for the dark field, or restricting loss calculation to the bright field. Secondly, a dose series is presented down to 100 electrons per diffraction pattern. It is found that all losses yield qualitatively reasonable structural data in the phase, whereas only MSE and Poisson loss range at the correct amplitude level. Chemical contrast is, in general, reliably obtained using the Poisson concept, which also provides the most continuous spatial frequency transfer as to the reconstructed object transmission function.

HF/HR VSP acquisition, processing, and interpretation in the deviated section of the high angle geothermal borehole of Grigny GGR5, targeting intra Dogger thin, porous beds.

Defining 5m thin, or even thinner, porous reservoir beds was the feasibility objective assigned to the High Frequency/High Resolution (HF/HR) look ahead VSP survey to be recorded in the deviated section of a geothermal production well drilled down to the top of the carbonate Dogger aquifer in the Paris basin, around 1500m in vertical depth, with a landing angle of 65°. The idea was to predict the depth of the first porous bed(s) to be drilled at high angle, and to determine the minimal DLS (Dog Leg Severity) to be applied by the driller after setting a production casing at the top Dogger level and changing the drilling fluid composition, so as to avoid directional drilling with sharp angles. A 50-100m vertical depth range was targeted for the acoustic impedance to be predicted below the top Dogger carbonate aquifer. Besides, a Pilot Hole (PH) was drilled prior to the high angle leg to assess with full reliability the depth of productive thin beds to be subsequently drilled at high angle. These actions were undertaken within a global R&amp;D project named “SISMOSUB” aiming reservoir characterisation, conducted by the reservoir and drilling engineers of GEOFLUID/GPCIP, in a partnership with IFPEN, and partially financed by ADEME (French Agency for Ecological Transition). High Frequency (HF) VSP still represents a frontier seismic domain to investigate, for which technical difficulties are piling up: First, the surface fix source needs to be extremely repeatable and preferably deliver an increased amount of HF energy to compensate somehow for the higher loss of seismic amplitudes with high frequency. Second, downhole receiver tool or toolstring may not present constant vector fidelity of 3 component reception over the whole recording frequency range, mainly in high frequency, due to mechanical coupling characteristics of the VSP tool hardware and the open borehole ruggedness; in cased hole, the mechanical coupling of the VSP tool to the formation is insured by a good cementing quality between casing and borehole wall. Third, the physics of the seismic attenuation is not fully understood and depends on several factors, mainly viscoelasticity and heterogeneity, potentially variable in depth and laterally to the wellbore. Additionally, the geometrical spreading represents the main factor of amplitude decay, independent from frequency, and can be estimated at processing stage. Surprisingly, the VSP image produced underneath the deviated hole section evidenced a faulted structure. A remarkable abrupt amplitude loss of high frequencies above 120Hz occurs where the direct P-wave ray crosses one of the confirmed minor faults before reaching Total Depth (TD); secondary downgoing arrivals appear locally in depth, mainly in the high frequencies, which are not strictly parallel to the first P-wave arrival...

Numerical analysis of the effects of pores on propagating guided waves

The present numerical study aims to analyze the effect of pores on propagating guided waves while outlining the relevance of pore formation and its significance to structural properties. The primary focus of this study was on the pores present in planar carbon fiber-reinforced polymer (CFRP) parts. The wavefield data were generated by applying the elastodynamic finite integration technique (EFIT) solver AE3D, allowing for a systematic analysis based on fully controllable configurations and noise-free data. An isotropic material model was used to simplify the modeling of the anisotropic CFRP by assuming the averaged quasi-isotropic properties of the CFRP in all directions. More than 220 specimens containing single pores or four basic configurations of pore accumulations were modeled and analyzed in terms of their effect on the out-of-plane component of the propagating guided waves. Analysis of the guided wavefield data focused on the direction-dependent maximum amplitude differences and deviations in the wavefield energy. Mode- and wavenumber-specific amplitude loss along the centerline was analyzed using a matrix pencil algorithm. Finally, principal component analysis (PCA) was conducted to examine deviations caused by the presence of pores. Analysis of the wavefield effects of the pores for each specific configuration showed good differentiation between the considered pore volume groups. At the same time, the effects of the pores were shown to be significantly dependent on the pore configuration in terms of orientation and morphological properties. Associated with this, the intersecting outcome ranges for different pore volume groups were evident when all the pore configurations were considered simultaneously.

Pulse-echo ultrasound attenuation tomography

Objective. We present the first fully two-dimensional attenuation imaging technique developed for pulse-echo ultrasound systems. Unlike state-of-the-art techniques, which use line-by-line acquisitions, our method uses steered emissions to constrain attenuation values at each location with multiple crossing wave paths, essential to resolve the spatial variations of this tissue property. Approach. At every location, we compute normalized cross-correlations between the beamformed images that are obtained from emissions at different steering angles. We demonstrate that their log-amplitudes provide the changes between attenuation-induced amplitude losses undergone by the different incident waves. This allows us to formulate a linear tomographic problem, which we efficiently solve via a Tikhonov-regularized least-squares approach. Main results. The performance of our tomography technique is first validated in numerical examples and then experimentally demonstrated in custom-made tissue-mimicking phantoms with inclusions of varying size, echogenicity, and attenuation. We show that this technique is particularly good at resolving lateral variations in tissue attenuation and remains accurate in media with varying echogenicity. Significance. Based on a similar principle, this method can be easily combined with computed ultrasound tomography in echo mode for speed-of-sound imaging, paving the way towards a multi-modal ultrasound tomography framework characterizing multiple acoustic tissue properties simultaneously.

A Frequency Domain Methodology for Quantitative Evaluation of Diffuse Wavefield With Applications to Seismic Imaging

AbstractAmbient Noise Imaging (ANI) of subsurface structures relies on seismic interferometry of diffuse seismic wavefields. However, the lack of effective methods to quantify and identify highly diffuse waves hampers applications of ANI, particularly in evaluating seismic attenuation and monitoring structural changes with high temporal resolution. Conventional ANI approaches require data normalization, which effectively suppresses the non‐diffuse component with large amplitude but also results in significant loss of amplitude and phase information in the continuous seismic records. In this study, we propose a frequency domain method to quantitatively evaluate the degree of diffuseness of seismic wavefields by analyzing their statistical characteristics of modal amplitudes for stationarity and randomness. Tests on synthetic waveform and field nodal records show that the proposed method can effectively distinguish between diffuse and non‐diffuse waveforms for either single‐ or three‐component data. As an application, we identify a 60‐s‐long diffuse coda of a local M 2.2 earthquake recorded by a dense nodal array on the San Jacinto Fault Zone, and successfully extract high‐quality dispersion curve and Q‐value without performing data normalization. These results are consistent with those obtained by conventional methods that assess the correlation between coherency and the Green's function, and by modeling ballistic waves generated by road traffic. Our proposed method can advance the imaging of subsurface velocity and attenuation structures as well as monitoring temporal changes for scientific studies and engineering applications.

Machine learning-based time-lapse 1D seismic full-waveform inversion with efficient training data generation in a carbon capture and storage monitoring

Machine learning (ML)-based time-lapse and seismic full-waveform inversion has recently gained attention in carbon capture and storage (CCS) research because of its potential to overcome the limitations of theory-based inversion and its excellent imaging performance for CO2 plumes. We propose a ML-based time-lapse 1D inversion method with efficient training data generation. The proposed method exploits time-lapse seismic data to infer time-lapse velocity changes and uses a 1D inversion strategy to enable the UNet3+ model to learn the general characteristics of velocity changes between baseline and monitoring phases. Our proposed method quickly generates various 1D velocity models and rapidly provides numerous near-offset data by using 1D ray-based modeling method. This allows us to overcome a challenge in constructing of 2D velocity models based on limited geological assumptions and forward modeling to generate seismic gathers, which requires massive computational resources. However, because 2D effects such as diffraction caused by the CO2 plume only affect the monitoring data, inaccurate predictions in the 1D inversion occurred near the plume, following the diffraction trajectory. We corrected this effect using a diffraction removal process for 2D target data, thereby improving the prediction accuracy of the ML model. The ML model was trained with a large amount of training data generated using the proposed method and validated on 2D target data with three different CO2 injection plume shapes obtained from a modified Marmousi2 velocity model. As a result, information about the CO2 plume was reasonably delineated, although the magnitude of the time-lapse velocity change near the plume boundary was reduced by small amplitude losses during the diffraction removal process. Our results suggest that the proposed method is a powerful tool for CCS monitoring, which requires forward modeling for each iterative survey.

Research on noise reduction and data mining techniques for pavement dynamic response signals

Purpose This study aims to ensure reliable analysis of dynamic responses in asphalt pavement structures. It investigates noise reduction and data mining techniques for pavement dynamic response signals. Design/methodology/approach The paper conducts time-frequency analysis on signals of pavement dynamic response initially. It also uses two common noise reduction methods, namely, low-pass filtering and wavelet decomposition reconstruction, to evaluate their effectiveness in reducing noise in these signals. Furthermore, as these signals are generated in response to vehicle loading, they contain a substantial amount of data and are prone to environmental interference, potentially resulting in outliers. Hence, it becomes crucial to extract dynamic strain response features (e.g. peaks and peak intervals) in real-time and efficiently. Findings The study introduces an improved density-based spatial clustering of applications with Noise (DBSCAN) algorithm for identifying outliers in denoised data. The results demonstrate that low-pass filtering is highly effective in reducing noise in pavement dynamic response signals within specified frequency ranges. The improved DBSCAN algorithm effectively identifies outliers in these signals through testing. Furthermore, the peak detection process, using the enhanced findpeaks function, consistently achieves excellent performance in identifying peak values, even when complex multi-axle heavy-duty truck strain signals are present. Originality/value The authors identified a suitable frequency domain range for low-pass filtering in asphalt road dynamic response signals, revealing minimal amplitude loss and effective strain information reflection between road layers. Furthermore, the authors introduced the DBSCAN-based anomaly data detection method and enhancements to the Matlab findpeaks function, enabling the detection of anomalies in road sensor data and automated peak identification.

Multidimensional Q‐compensated reverse time migration using a high‐efficient decoupled viscoacoustic wave equation

AbstractSeismic waves propagating through attenuating media induce amplitude loss and phase dispersion. Neglecting the attenuation effects during seismic processing results in the imaging profiles with weakened energy, mispositioned interfaces and reduced resolution. To obtain high‐quality imaging results, Q‐compensated reverse time migration is developed. The kernel of the Q‐compensated reverse time migration algorithm is a viscoacoustic wave equation with decoupled amplitude loss and phase dispersion terms. However, the majority of current decoupled viscoacoustic wave equations are solved using the computationally expensive pseudo‐spectral method. To enhance computational efficiency, we initiate our approach from the dispersion relation of a single standard linear solid model. Subsequently, we derive a novel decoupled viscoacoustic wave equation by separating the amplitude loss and phase dispersion terms, previously coupled in the memory variable. The newly derived decoupled viscoacoustic wave equation can be efficiently solved using the finite‐difference method. Then, we reverse the sign of the amplitude loss term of the newly derived viscoacoustic wave equation to implement high‐efficient Q‐compensated reverse time migration based on the finite‐difference method. In addition, we design a regularization term to suppress the high‐frequency noise for stabilizing the wavefield extrapolation. Forward modelling tests validate the decoupled amplitude loss and phase dispersion characteristics of the newly derived viscoacoustic wave equation. Numerical examples in both two‐dimensional and three‐dimensional confirm the effectiveness of the Q‐compensated reverse time migration based on the finite‐difference algorithm in mitigating the attenuation effects in subsurface media and providing high‐quality imaging results.

Age-related decline in hearing and emotional prosody processing: A multi-feature oddball study

This study investigated how age and hearing loss contributed to the challenges in perceiving emotional prosody in speech. A multi-feature oddball paradigm was employed to assess mismatch negativity (MMN) and P3a responses to three deviant prosodies (happy, angry and sad) against the standard neutral prosody in spoken words. The participants were 22 adults in the age range of 18 to 70 with various degrees of hearing loss as assessed with pure tone audiometry. Linear mixed effects models revealed heightened MMN response to angry voice and strongest P3a response to happy voice among the three deviants. There was a significant positive correlation between age and MMN amplitude for the angry prosody. Significant correlations were also observed between hearing loss and MMN amplitude in response to both angry and happy stimuli. In addition, negative correlations were found between P3a amplitude and hearing loss as well as aging for happy stimuli. However, aging and hearing loss did not significantly affect the processing of sadness in this paradigm. These findings showed category-sensitive age-related decline in emotional prosody processing. The intricate correlations patterns among age, hearing loss, MMN, and P3a responses called for further exploration of broader implications in cognitive aging.

A versatile design method applied to reconfigurable metasurfaces

This paper introduces a versatile design method for reconfigurable metasurfaces based on the Pancharatnam–Berry phase theory. Unlike traditional reconfigurable metasurfaces that require designing independent surfaces for specific applications, leading to a significant time investment for designers to learn and create, this study proposes a foundational, invariant metasurface. By selectively metallizing holes or inserting metal cylinders, it achieves nine available functionalities. Regardless of the chosen operating function, the metasurface demonstrates high efficiency at 8.2 GHz, with amplitude loss less than 1 dB. Additionally, when operating in phase modulation mode, the design provides a 360° phase adjustment range and a 30° phase step. A prototype containing 31×31 units (425.6×425.6mm2) has been fabricated and tested under function 7 (TM and RHCP transmission phase modulation). Measurement results confirm the metasurface’s capability for polarization conversion and phase modulation at the frequency of 8.2 GHz.

A digital prediction compensation for DR improvement in CT DSM with digital noise coupling

AbstractThis paper presents a prediction‐based dynamic range (DR) compensation technique in continuous‐time (CT) delta ‐sigma modulator (DSM) with digital‐domain noise coupling (DNC) structure. A digital prediction technique is proposed to address the issue of maximum stable amplitude (MSA) loss caused by DNC. The proposed prediction method has been shown to significantly extend the MSA of CT DSM with DNC. Moreover, through the extension of MSA, the DR and SNDR is significantly improved. A CTDSM with proposed compensation achieves a SNDR of 85.1dB at ‐1dBFS and a DR of 89dB.