High Frequency Band Research Articles

Frontal alpha asymmetries and behavioral immune system: moderating role of behavioral inhibition system

Background and purpose: Behavioral immune system is a cluster of psychological mechanisms enabling detection and avoidance of pathogens in one’s immediate environment. Its presumed activation has been implicated in myriads of psychological phenomena, stemming from pathogen related disgust to more complex behaviors, such as mate choice and xenophobic cognitions. However, little is known about its biological underpinnings. The aim of this preliminary study was twofold: 1) to explore the role of another neuropsychological system governing avoidant motivations, the behavioral inhibition system, in pathogen-induced disgust and 2) to determine if frontal hemispheric asymmetries (a neural correlate of avoidant motivations) might serve as indicators of behavioral immune system activation. Materials and methods: 62 participants completed the Behavioral inhibition scale. Based on their z-scores, two extreme groups were formed: high (n=9) and low behavioral inhibition (n=9) group. After the baseline EEG recordings, participants were exposed to a set of neutral stimuli, followed by a set of pathogen disgust inducing stimuli. The frontal asymmetry (FAA) indexes (lnR-LnL) were calculated within both low (8-10 Hz) and high (11-13 Hz) alpha frequency bands on analogue pairs of frontal electrodes. Results: There were no baseline FAA differences between groups. However, compared to low behavioral inhibition group, high behavioral inhibition group showed larger shifts in FAA on frontopolar locations while watching the pathogen related disgust-inducing stimuli, as compared to neutral photographs. Conclusions: This pattern of FAA shifts suggests that high behavioral inhibition individuals attend to pathogen threat related cues more readily, i.e., have a more reactive behavioral immune system. With this preliminary study we are proposing a new line of research in order to determine if there is evidence of a calibrated response in terms of interplay between one’s immune status and pathogen treat related neural reactivity.

Hierarchical Phased-Array Antennas Coupled to Al KIDs: A Scalable Architecture for Multi-band Millimeter/Submillimeter Focal Planes

We present the optical characterization of two-scale hierarchical phased-array antenna kinetic inductance detectors (KIDs) for millimeter/submillimeter wavelengths. Our KIDs have a lumped-element architecture with parallel plate capacitors and aluminum inductors. The incoming light is received with a hierarchical phased array of slot dipole antennas, split into 4 frequency bands (between 125 GHz and 365 GHz) with on-chip lumped-element band-pass filters, and routed to different KIDs using microstriplines. Individual pixels detect light for the 3 higher-frequency bands (190–365 GHz), and the signals from four individual pixels are coherently summed to create a larger pixel detecting light for the lowest frequency band (125–175 GHz). The spectral response of the band-pass filters was measured using Fourier transform spectroscopy (FTS), the far-field beam pattern of the phased-array antennas was obtained using an infrared source mounted on a 2-axis translating stage, and the optical efficiency of the KIDs was characterized by observing loads at 294 K and 77 K. We report on the results of these three measurements.

Analyzing possible seismic velocity changes in Mexico City using seismic noise interferometry

The seismic response of the Mexico City basin has received plenty of attention as one of the most relevant cases of ground motion amplification. A recent study showed possible velocity variations of the deposits in both the lake bed and firm ground. A clear drop in seismic velocity was observed during the 2017.09.19 earthquake (Mw 7.1) in addition to more subtle seismic velocity changes related to seasonal temperature and precipitation. We use continuous seismic noise data recorded in a 29 broadband seismograph network in and around Mexico City to investigate Rayleigh wave group velocity structure and velocity changes. We estimate Green's functions (GF) between station pairs using seismic noise cross-correlation. An average estimate is computed for each of three five-day periods of recording. GFs are dominated by a Rayleigh pulse at low frequencies (between 0.1 and 0.2 Hz). Velocity changes are investigated through the comparison between GF's for different five-day periods. No velocity variations are observed. Station pairs separated at a distance smaller than 20 km also show some Rayleigh wave energy at higher frequencies, between 0.3 and 1.2 Hz. We repeated the analysis in a higher frequency band (up to 5 Hz) and show that again no velocity variation can be observed. In addition, we used horizontal-to-vertical spectral ratios computed for both earthquake and seismic noise records to identify possible non-linear effects during the 2017 earthquake. The results showed that significant non-linear effects during that event are to be discarded. Finally, we present preliminary results of a tomography of Rayleigh wave group velocity at the center of the array. Lateral structure variations below the geotechnical zonation are significant. Our data will be useful to constrain the structure of the volcanic deposits of the Transmexican Volcanic Belt (TVB).

Broadening of the Divertor Heat Flux Profile in High Confinement Tokamak Fusion Plasmas with Edge Pedestals Limited by Turbulence in DIII-D.

Multimachine empirical scaling predicts an extremely narrow heat exhaust layer in future high magnetic field tokamaks, producing high power densities that require mitigation. In the experiments presented, the width of this exhaust layer is nearly doubled using actuators to increase turbulent transport in the plasma edge. This is achieved in low collisionality, high confinement edge pedestals with their gradients limited by turbulent transport instead of large-scale, coherent instabilities. The exhaust heat flux profile width and divertor leg diffusive spreading both double as a high frequency band of turbulent fluctuations propagating in the electron diamagnetic direction doubles in amplitude. The results are quantitatively reproduced in electromagnetic XGC particle-in-cell simulations which show the heat flux carried by electrons emerges to broaden the heat flux profile, directly supported by Langmuir probe measurements.

Chronic intracranial recordings in the globus pallidus reveal circadian rhythms in Parkinson’s disease

Circadian rhythms have been shown in the subthalamic nucleus (STN) in Parkinson’s disease (PD), but only a few studies have focused on the globus pallidus internus (GPi). This retrospective study investigates GPi circadian rhythms in a large cohort of subjects with PD (130 recordings from 93 subjects) with GPi activity chronically recorded in their home environment. We found a significant change in GPi activity between daytime and nighttime in most subjects (82.4%), with a reduction in GPi activity at nighttime in 56.2% of recordings and an increase in activity in 26.2%. GPi activity in higher frequency bands ( > 20 Hz) was more likely to decrease at night and in patients taking extended-release levodopa medication. Our results suggest that circadian fluctuations in the GPi vary across individuals and that increased power at night might be due to the reemergence of pathological neural activity. These findings should be considered to ensure successful implementation of adaptive neurostimulation paradigms in the real-world.

MCML-BF: A Metal-Column Embedded Microstrip Line Transmission Structure with Bias Feeders for Beam-Scanning Leakage Antenna Design.

This article proposes a novel fixed-frequency beam scanning leakage antenna based on a liquid crystal metamaterial (LCM) and adopting a metal column embedded microstrip line (MCML) transmission structure. Based on the microstrip line (ML) transmission structure, it was observed that by adding two rows of metal columns in the dielectric substrate, electromagnetic waves can be more effectively transmitted to reduce dissipation, and attenuation loss can be lowered to improve energy radiation efficiency. This antenna couples TEM mode electromagnetic waves into free space by periodically arranging 72 complementary split ring resonators (CSRRs). The LC layer is encapsulated in the transmission medium between the ML and the metal grounding plate. The simulation results show that the antenna can achieve a 106° continuous beam turning from reverse -52° to forward 54° at a frequency of 38 GHz with the holographic principle. In practical applications, beam scanning is achieved by applying a DC bias voltage to the LC layer to adjust the LC dielectric constant. We designed a sector-blocking bias feeder structure to minimize the impact of RF signals on the DC source and avoid the effect of DC bias on antenna radiation. Further comparative experiments revealed that the bias feeder can significantly diminish the influence between the two sources, thereby reducing the impact of bias voltage introduced by LC layer feeding on antenna performance. Compared with existing approaches, the antenna array simultaneously combines the advantages of high frequency band, high gain, wide beam scanning range, and low loss.

Full-Term and Preterm Newborns Differ More Significantly in Photoplethysmographic Waveform Variability than Heart Rate Variability.

Features of cardiovascular autonomic regulation in infants are poorly studied compared with adults. However, the clinical significance of autonomic dysfunction in infants is very high. The goal of our research was to study the temporal and frequency-dependent features, as well as low-frequency synchronization in cardiovascular autonomic regulation in full-term vs. preterm newborns, based on the analysis of their heart rate variability (HRV) and photoplethysmographic waveform variability (PPGV). The study included three groups of newborns: 64 full-term newborns (with a gestational age at birth of 37-40 weeks) with a physiological course of the neonatal adaptation; 23 full-term newborns (with a gestational age at birth of 37-40 weeks) with a pathological course of the neonatal adaptation; and 17 preterm newborns (with a postconceptional age of 34 weeks or more). We conducted spectral analysis of HRV and PPGV, along with an assessment of the synchronization strength between low-frequency oscillations in HRV and in PPGV (synchronization index). We employed several options for the boundaries of the high-frequency (HF) band: 0.15-0.40 Hz, 0.2-2 Hz, 0.15-0.8 Hz, and 0.24-1.04 Hz. Preterm newborns had higher heart rate, RMSSD, and PNN50 values relative to both groups of full-term newborns. Values of SDNN index and synchronization index (S index) were similar in all groups of newborns. Differences in frequency domain indices of HRV between groups of newborns depended on the considered options of HF band boundaries. Values of frequency domain indices of PPGV demonstrated similar differences between groups, regardless of the boundaries of considered options of HF bands and the location of PPG signal recording (forehead or leg). An increase in sympathetic influences on peripheral blood flow and a decrease in respiratory influences were observed along the following gradient: healthy full-term newborns → preterm newborns → full-term newborns with pathology. Differences in frequency domain indices of autonomic regulation between the studied groups of newborns depended on the boundaries of the considered options of the HF band. Frequency domain indices of PPGV revealed significantly more pronounced differences between groups of newborns than analogous HRV indicators. An increase in sympathetic influences on peripheral blood flow and a decrease in respiratory influences were observed along the following gradient: healthy full-term newborns → preterm newborns → full-term newborns with pathology.

Binary image embedding and restoration in speech signal

AbstractIn this paper, we propose a method of embedding images into a speech signal. An image is embedded in the high frequency band above 16 kHz of the speech signal to be difficult to perceive for humans. In the proposed method, the image is embedded after being binarized by the error diffusion method. When the image is embedded, we apply an iterative phase restoration method to avoid noise generation. We also investigate a compensation method for an extracted image whose quality degrades due to transmission channel characteristics. Simulation and real‐environmental experiments showed that the proposed method significantly improved the quality of the extracted image on the receiver side.

Broad‐range, high‐linearity, and fast‐response pressure sensing enabled by nanomechanical resonators based on 2D non‐layered material: β‐In2S3

AbstractTwo‐dimensional (2D) non‐layered materials, along with their unique surface properties, offer intriguing prospects for sensing applications. Introducing mechanical degrees of freedom is expected to enrich the sensing performances of 2D non‐layered devices, such as high frequency, high tunability, and large dynamic range, which could lead to new types of high performance nanosensors. Here, we demonstrate 2D non‐layered nanomechanical resonant sensors based on β‐In2S3, where the devices exhibit robust nanomechanical vibrations up to the very high frequency (VHF) band. We show that such device can operate as pressure sensor with broad range (from 10−3 Torr to atmospheric pressure), high linearity (with a nonlinearity factor as low as 0.0071), and fast response (with an intrinsic response time less than 1 μs). We further unveil the frequency scaling law in these β‐In2S3 nanomechanical sensors and successfully extract both the Young's modulus and pretension for the crystal. Our work paves the way towards future wafer‐scale design and integrated sensors based on 2D non‐layered materials.image

Laser-assisted screen-printing of graphene folded reflectarray antenna for millimeter-wave applications

Antennas operating at high frequency bands are sought after for applications in 5G, satellite, radar, and other communication systems. Graphene, a two-dimensional material known for its exceptional conductivity, mechanical strength, and chemical stability, is anticipated to serve as a viable substitute for copper in antenna applications. However, researches on graphene antennas at millimeter-wave and higher frequencies are mainly limited to theory and simulation, due to the fabrication challenges of achieving high-precision graphene patterns. Herein, we present the design and fabrication of a graphene folded reflectarray antenna (FRA) operating at millimeter-wave. The FRA is fabricated using screen-printing of graphene ink on an RT5880 substrate, followed by laser engraving for precise patterning. The main reflector has 918 patch units, and the polarizing grids have line widths and spacings of 100 μm. Measurements demonstrate that the antenna has a realized peak gain of 21.37 dBi at 37.5 GHz. The radiation patterns show a 3 dB beamwidth of 6° and 4° in the E-plane and H-plane respectively, with cross-polarization more than −18 dB. The laser-assisted screen-printing method provides a feasible strategy for the precision manufacture of graphene communication devices.

Research on Atmospheric Attenuation Compensation Technology of High-Frequency Band Microwave in Long-Distance Transmission

With the rapid development of wireless communication technology, high-frequency band microwaves (e.g., millimeter-wave and terahertz wave) show great potential in the field of high-speed data transmission due to their huge bandwidth resources. However, high-frequency band microwaves are seriously affected by atmospheric attenuation during transmission, especially at long distances, and this attenuation significantly reduces the signal strength and quality. Therefore, the study of accurate modeling of atmospheric attenuation as well as effective compensation techniques is crucial for improving the performance of long-distance transmission of high-frequency band microwaves.

Omnidirectional circularly polarized base station antenna with high gain and wide band

Omnidirectional circularly polarized base station antenna with high gain and wide band

Examining Cryptocurrency Dynamics with Asian Equity Indices and Commodities: A Wavelet Coherence Analysis

A wide range of interest has been shown in this field by investors and decision-makers due to the correlation between cryptocurrencies, Asian stock indexes, and commodities in the global financial market through partitioning the data and applying the wavelet analysis approach to analyze the described movement of various variables. Moreover, this study seeks to provide information to fintech financiers and policymakers as well about the examined variables. Time-series data was obtained from 01st January 2019 to 31st December 2023 and analyzed from multiple internet sources about commodities, Asian Stock indices, and cryptocurrency prices. To find specific patterns and trends in a certain area, research used the wavelet approach to analyze the data and separate each series into a separate frequency band. The findings showed that there is a highly significant relationship among commodities, Asian stock indexes, and cryptocurrency in different frequency bands. On the other hand, a negative correlation was found in low frequency bands between the prices of commodities and cryptocurrency, whilst a positive correlation was found in high frequency bands between cryptocurrency and Asian Stock indices.

A miniaturized dual band pass frequency selective surface insensitive to oblique angles and polarizations of wave

Abstract A Dualband Pass Frequency Selective Structure (DPSFSS) with miniaturized elements is proposed in this article. The miniaturized elements induce high inductance and capacitance values. The meandered line concept is used which extensively increases inductance of the dipole element. Very large capacitance is obtained between two meandered elements which have wide common area perpendicular to electric field for wave propagating in Z-direction. Two pass band poles and two zeros are obtained by perpendicular arrangement of meandered patterns on two sides of the substrate. Orthogonal arrangement of patterns ensure polarization symmetry (polarization insensitive) for Transverse Electric (TE) and Transverse Magnetic (TM) modes of exciting wave. Two pass band pole frequencies are positioned at 1.84 GHz and 4.53 GHz with low Insertion Losses (IL) of 0.67 dB and 1 dB, respectively. The lower and higher frequency bands have factional bandwidths of 41 % and 46 %, respectively. The transmission nulls occupy 2.8 GHz and 6.58 GHz frequencies. The structure is miniaturized to 0.032λ 0 × 0.032λ 0 dimensions with respect to lowest resonance residing at 1.83 GHz. The low IL at both pass bands is realized despite of using a lossy FR-4 material that can be improved to less than 0.5 dB at both the bands using less lossy materials such as F4BME or RO4003C. The proposed DPSFSS design is elaborated using Equivalent Circuit Model (ECM) and Surface Current Distribution (SCD). Measurements are performed on fabricated DPSFSS prototype and it is observed that the measured results coincide well with the simulated response. Angle stability of the DPSFSS is excellent and no unwanted resonances are observed at oblique angles upto 80° for dual polarizations of wave.

The Formation of 2D Holograms of a Noise Source and Bearing Estimation by a Vector Scalar Receiver in the High-Frequency Band

The holographic signal-processing method for a single vector scalar receiver (VSR) in the high-frequency band in shallow water is developed in the paper. The aim of this paper is to present the results of the theoretical analysis, numerical modeling, and experimental verification of holographic signal processing for a noise source by the VSR. The developed method is based on the formation of the 2D interferogram and 2D hologram of a noise source in a shallow-water waveguide. The 2D interferograms and 2D holograms for different channels of the VSR (P sound pressure and VX and VY vibration velocity components) are considered. It is shown that the 2D interferogram consists of parallel interference fingers in the presence of a moving noise source. As a result, the 2D hologram contains focal points located on a straight line, and the angular distribution of the holograms has the main extreme value. It is shown in the paper that the holographic signal-processing method allows detecting the source, estimating the source bearing, and filtering the useful signal from the noise. The results of the source detection, source bearing estimation, and noise filtering are presented within the framework of experimental data processing and numerical modeling.

The role of visual spatial frequencies in newborns' processing of dynamic facial expressions of emotion.

Evidence on newborns' discrimination of emotional facial expressions is scarce, and the question of what is the nature of the visual information that newborns rely on to perform such discrimination remains open. Here, we manipulated the spatial frequency (SF) content of the stimuli by selectively removing low spatial frequency (LSF) and high spatial frequency bands using newborn-appropriate cutoffs to investigate what information newborns use when preferring and discriminating between dynamic displays showing happy and fearful expressions unfolding over time. Using a preferential looking paradigm, in Study 1 (N = 63, 59% females, 92% White), we showed that newborns looked longer to happy over fearful expressions in unfiltered (broad spatial frequency) and high-pass (high spatial frequency > 0.6 cycles per degree [cpd]) faces but not in low-pass (LSF < 0.5 cpd) faces. In Study 2 (N = 22, 59% females, 91% White), newborns tested in a visual habituation paradigm showed successful discrimination of the two LSF emotions. Results show that newborns can discriminate between dynamic images of happy and fearful facial expressions containing either extreme low SF (< 0.5 cpd) information or higher SF (> 0.6 cpd) bandwidth. Their preference for the happy expression was present for intact and high-pass filtered faces but not for low-pass faces. This SF effect is tentatively driven by an enhancement of attentional response to the LSF fearful face, whereas the response to the happy face is unaffected by the SF manipulation. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Data Classification and Parameter Estimations with Deep Learning to the Simulated Time-domain High-frequency Gravitational Waves Detections

Abstract High-frequency Gravitational wave (HFGW) detection is a great challenge, as its signal is significantly weak, compared with the relevant background noise in the same frequency band. Therefore, besides designing and running the feasible installation for the experimental weak-signal detection, developing various effective approaches to process the big detected data for extracting the information 1about the GWs is also particularly important. In this paper, we focus on the simulated time-domain detected data of the electromagnetic response of the GWs in high frequency band, typically such as Gigahertzs. Specifically, we develop an effective deep learning method to implement the classification of the simulated detection data, which includes the strong electromagnetic background noise in the same frequency band, for the parameter estimations of the HFGWs. The simulatively detected data is generated by the transverse first-order electromagnetic responses of the HFGWs passing through a high stationary magnetic field biased &amp;#xD;by a high frequency Gaussian beam. We propose a convolutional neural network (CNN) model to implement the classification of the simulated detection data, whose accuracy can reach more than 90%. With these data being served as the positive sample datasets, the physical parameters of the simulatively detected HFGWs can be effectively estimated by matching the sample datasets with the &amp;#xD;noise-free template library one by one. The confidence levels of these extracted parameters can reach to 95% in the corresponding confidence interval. By the multiple data experiments, the effectiveness and reliability of the proposed data processing method is verified. Hopefully, the proposed method could be generalized to the big data processing for the experimental HFGWs detections, in &amp;#xD;future.

The Parameter Identification of Structure with TMD considering Seismic Soil-Structure Interaction

Parameter identification is of great significance for the postearthquake performance evaluation of structure equipped with tuned mass damper (TMD). However, the soil-structure interaction (SSI) effects have not been considered in the parameter identification of structure with TMD yet, which influence the dynamic characteristics and seismic responses of structures. This paper aims at proposing a framework for identifying the physical parameters of soil-structure-TMD system. Firstly, the accelerated particle swarm optimization (APSO) algorithm is combined with the search space reduction (SSR) method. Then, the frequency response function and transmissibility function are adopted for output-input and input-only cases, respectively, and a simplified mechanical model for soil-structure-TMD system is employed. Next, the measured responses are used to identify the physical parameters of structure with TMD considering SSI effects. Finally, the effectiveness of the proposed identification method is investigated, and the influences of frequency band and noise pollution on the identification performance are discussed. The results show that the proposed strategy can identify the system physical parameters accurately and quickly. It is worth noting that high frequency bands and noise pollution may lead to estimation error, especially for output-only case.

Modal acoustic emission-based circumferential crack feature extractions for pipeline welds with L-shaped flexible sensor array

ABSTRACT The collection and analysis of acoustic emission (AE) from weld circumferential cracks are crucial for ensuring pipeline safety. However, the unclear propagation characteristics and mode features of AE present challenges in array design and mode identification. In this manuscript, a novel mode feature extraction method for circumferential crack AE signals is proposed. This method involves three primary steps: firstly, a L-shaped flexible sensor array is designed to capture raw AE signals from both axial and circumferential directions. Next, the collected signals are filtered and evaluated to extract effective multi-mode components through the Kalman filtering and recursive plot (RP). Finally, the time–frequency features and mode types are extracted through combining the Hilbert-Huang transform (HHT) and dispersion curves. Results indicate that during the crack growths, both axial and circumferential direction AE signals contain multi-mode components, specifically L(0,1), F(1,1) and F(1,2) modes, with durations spanning 30–500 μs. Additionally, the axial modes predominantly occur within 200–300 kHz range, whereas the circumferential modes span both low and high frequency bands, specifically 40–50 kHz and 200–300 kHz, respectively. Modes across different frequencies indicate distinct structural behaviours, including crack growths and plastic deformations. The proposed method provides attempts for the pipe weld AE monitoring and multi-mode analysis.

Decoding kinematic information from beta-band motor rhythms of speech motor cortex: a methodological/analytic approach using concurrent speech movement tracking and magnetoencephalography.

Articulography and functional neuroimaging are two major tools for studying the neurobiology of speech production. Until now, however, it has generally not been feasible to use both in the same experimental setup because of technical incompatibilities between the two methodologies. Here we describe results from a novel articulography system dubbed Magneto-articulography for the Assessment of Speech Kinematics (MASK), which is technically compatible with magnetoencephalography (MEG) brain scanning systems. In the present paper we describe our methodological and analytic approach for extracting brain motor activities related to key kinematic and coordination event parameters derived from time-registered MASK tracking measurements. Data were collected from 10 healthy adults with tracking coils on the tongue, lips, and jaw. Analyses targeted the gestural landmarks of reiterated utterances/ipa/ and /api/, produced at normal and faster rates. The results show that (1) Speech sensorimotor cortex can be reliably located in peri-rolandic regions of the left hemisphere; (2) mu (8-12 Hz) and beta band (13-30 Hz) neuromotor oscillations are present in the speech signals and contain information structures that are independent of those present in higher-frequency bands; and (3) hypotheses concerning the information content of speech motor rhythms can be systematically evaluated with multivariate pattern analytic techniques. These results show that MASK provides the capability, for deriving subject-specific articulatory parameters, based on well-established and robust motor control parameters, in the same experimental setup as the MEG brain recordings and in temporal and spatial co-register with the brain data. The analytic approach described here provides new capabilities for testing hypotheses concerning the types of kinematic information that are encoded and processed within specific components of the speech neuromotor system.