High Frequency Band Research Articles

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.

Study on Sound Absorption Properties of Polyvinyl Chloride (PVC) Film Multicavity Structure Materials

Since the development of industry, sound absorption and noise reduction have gradually become an urgent problem to be solved. Lightweight polymer film materials are very effective in response to sound waves, and sound waves can easily cause vibration of the film, which can convert sound energy into vibration and film friction to achieve sound absorption. The application conditions of the film material are very harsh, that is, a support body is required to fix the film and the film needs to be tensioned. The film is very thin and easy to damage. The idea of this research is to transform the film into a bubble structure and use a large number of film bubbles to form a cavity structure material. As a unit of the sound absorption structure, bubbles can avoid damage to the film. In this paper, commercial polyvinyl chloride film bubble materials are used to prepare two kinds of film multicavity structure materials, and the sound absorption performance of this film multicavity structure material is studied. The research results show that this film multicavity structure material has very excellent broadband sound absorption performance, which changes the narrow band sound absorption properties of the usual film single cavity. The average sound absorption coefficient can reach 0.84 in frequency range from 500 Hz to 6400 Hz. This structural material has a single peak sound absorption curve at the middle and low frequency bands, which is the characteristic of resonance sound absorption. And at the middle and high frequency bands, it exhibits the characteristics of broadband sound absorption. The film multicavity structure material has both cavity sound absorption and broadband sound absorption characteristics.

Ensemble classifiers fed by functional connectivity during cognitive processing differentiate Parkinson’s disease even being under medication

Brain–computer interface technologies, as a type of human-computer interaction, provide a control ability on machines and intelligent systems via human brain functions without needing physical contact. Moreover, it has a considerable contribution to the detection of cognitive state changes, which gives a clue for neurodegenerative diseases, including Parkinson’s disease (PD), in recent years. Although various studies implemented different machine learning models with several EEG features to detect PD and receive remarkable performances, there is a lack of knowledge on how brain connectivity during a cognitive task contributes to the differentiation of PD, even being under medication. To fill this gap, this study used three ensemble classifiers, which were fed by functional connectivity through cognitive response coherence (CRC) with varying selected features in different frequency bands upon application of the 3-Stimulation auditory oddball paradigm to differentiate PD medication ON and OFF and healthy controls (HC). The results revealed that the most remarkable performances were exhibited in slow frequency bands (delta and theta) in comparison to high frequency and wide range bands, especially in terms of target sounds. Moreover, in the delta band, target CRC distinguishes all groups from each other with accuracy rates of 80% for HC vs PD-OFF, 80% for HC vs PD-ON, and 81% for PD-ON vs PD-OFF. In the theta band, again target sounds were the most distinctive stimuli to classify HCxPD-OFF (80% accuracy), HCxPD-ON (80.5% accuracy) with quite good performances, and PD-ONxPD-OFF (76% accuracy) with acceptable performance. Besides, this study achieved a state-of-the-art performance with an accuracy of 87.5% in classifying PD-ONxPD-OFF via CRC of standard sounds in the delta band. Overall, the findings revealed that brain connectivity contributes to identifying PD and HC as well as the medication state of PD, especially in the slow frequency bands.

Propagation characteristics of obliquely incident THz waves in inhomogeneous fully ionized dusty plasma using the scattering matrix method

The scattering matrix method is applied to investigate the propagation characteristics of obliquely incident terahertz (THz) waves in inhomogeneous fully ionized dusty plasma. The propagation coefficients of THz waves are analyzed with different physical parameters in the case of parabolic electron density distribution. The results show that the transmissivity of lower frequency THz waves have a noticeable variation with the change of physical parameters. However, the transmissivity values can rapidly approach 1 in higher frequency band. We notice that there is a critical value fc≈0.045 THz. When f&amp;gt;fc, the transmissivity increases as the dust particles density and radius increase. However, it is somewhat opposite when f&amp;lt;fc. Significantly, the THz waves exhibit a greater propensity for penetrating fully ionized dusty plasma compared with the weakly ionized dusty plasma. To a certain degree, the investigation results provide new ideas for addressing the issue of “blackout”.

Advanced Algorithms for Configuring Discrete Antenna Tuning Units of High Frequency Band Using a Quick Search Method for the Points’ Geometric Proximity

Advanced Algorithms for Configuring Discrete Antenna Tuning Units of High Frequency Band Using a Quick Search Method for the Points’ Geometric Proximity

The distance to CRL 618 through its radio expansion parallax

ABSTRACT CRL 618 is a post-Asymptotic Giant Branch star that has started to ionize its ejecta. Its central H ii region has been observed over the last 40 yr and has steadily increased in flux density at radio wavelengths. In this paper, we present data that we obtained with the Very Large Array in its highest frequency band (43 GHz) in 2011 and compare these with archival data in the same frequency band from 1998. By applying the so-called expansion-parallax method, we are able to estimate an expansion rate of 4.0 ± 0.4 mas yr−1 along the major axis of the nebula and derive a distance of 1.1 ± 0.2 kpc. Within errors, this distance estimation is in good agreement with the value of ∼900 pc derived from the expansion of the optical lobes.

Novel printed passive ultra high frequency radio frequency identification antenna using meander technique

&lt;p&gt;In this paper, a novel radio frequency identification (RFID) antenna using a meander technique associated with a slotted patch is studied for RFID applications in the ultra high frequency (UHF) band [867.5-868 MHz]. The proposed RFID antenna is designed on a Kapton substrate with dielectric constant 3.5 and loss of 0.0027. It consists of two opposite meander line antennas of 8 turns each one and interconnected to ALIEH H3 microchip associated to two slotted patch’s with a global size 105×25×0.1 mm&lt;sup&gt;3&lt;/sup&gt;. The proposed RFID antenna is designed and simulated using CST MWS as an electromagnetic solver. The results of the simulation show a return loss of -22.64 dB at 868 MHz, a reading distance of around 5 m, and a simulated input impedance of the antenna are 31.72+j109.68 Ω at the operating frequency 868 MHz.&lt;/p&gt;

Polarization Insensitive and Thin Metamaterial Absorber Performed in High-Frequency 5G Bands

A variety of fascinating applications, including 5G communication devices, high-speed data transfer, and large-scale Internet of Things (IoT), make life easier with 5G technology. Despite the 5G’s superior features, the percentage of electromagnetic (EM) waves in the environment execute a significant increase, unpleasantly. Broadband metamaterial absorbers are an appealing alternative to gather these unwanted signals. This study aims to numerically investigate a broadband metamaterial absorber (MMA) in the 5G high-frequency spectral range with the metasurface formed with coupled resistors. In addition, the 24.25-27.5GHz frequency range, one of the high-frequency 5G bands used by selected countries such as the European Union and China, was preferred. The minor aim of this study is that the usage of coupled elements as resistors may have the ability to increase the absorption bandwidth and magnitude. Comprehensive simulations were performed using the finite integration technique (FIT) utilized by the CST Microwave Studio program to investigate the absorber performance and other relevant parameters. The unit cell design is created metal-substrate-metal structures as asymmetric, single-layer, and easy to implement. The absorption responses are investigated according to the oblique incidence angle, polarization angle for TE &amp;amp;TM modes. The suggested MMA provided an absorbency response above 87.6% in the frequency range 24.20-27.30GHz under normal incidence. Moreover, to comprehend the physical mechanism on absorption, the top and bottom surfaces of the absorber's electric field and surface current distributions are assessed. The designed MMA resulting in relatively high performance and polarization insensitive is helpful for electromagnetic interference (EMI) shielding of 5G signals in the FR2/mmWave frequency regime.

A spaceborne broadband circularly polarized conformal antenna for UHF band applications

AbstractA Spaceborne broadband circularly polarized conformal antenna for ultra high frequency band is presented. The antenna mounted on the outer surface of the circular arc spherical cone satellite works in 390–450 MHz frequency band, and has the characteristics of broadband, light miniature. The measured results for the antenna demonstrate an impedance bandwidth of 32.5% from 360 to 500 MHz, an axial ratio bandwidth of 27.2% from 380 to 500 MHz, and a peak gain of 6.7 dBic. The antenna form can be applied to the field of broadband circularly polarized conformal antenna on satellite and missile, and has a wide application prospect.

Intertidal Soundscapes of Hardened and Living Shorelines: A Case Study of Habitat Enhancement

Abstract Organisms, such as fishes and invertebrates and including their larval stages, listen to underwater soundscapes to detect information about nearby habitats. Such soundscapes may be influenced by habitat degradation or enhancement, which can lead to acoustically mediated feedback loops affecting the overall ecosystem. Despite the importance of underwater sounds on ecological functioning, there have been limited studies documenting soundscapes of intertidal ecosystems and few, if any, of living shoreline soundscapes. Living shorelines would especially benefit from acoustically mediated effects for objectives like encouraging fish and invertebrate settlement. This case study used a Before‐After‐Control‐Impact design to sample soundscapes and nekton (i.e., fishes and mobile macroinvertebrates) at a living shoreline construction and a nearby hardened shoreline in Cedar Key, FL (USA). Diel soundscape patterns and acoustic attenuation at the two sites were also described a year following the living shoreline construction. In the acoustic sampling, the high frequency bands of both shorelines were dominated by invertebrate sounds that were influenced by season, site and time of day, while the low frequency band of the living shoreline was often dominated by a loud anthropogenic sound. About a year after the living shoreline installation—despite similar measured acoustic attenuation at both sites—the living shoreline featured louder sound pressure levels compared to the hardened shoreline, which may be particularly beneficial for promoting foundational species and other organism settlement. These results demonstrate that Gulf of Mexico intertidal habitats may have soundscape differences even within close proximity and that living shorelines may enhance acoustic characteristics in ways beneficial to continued shoreline development. This represents an important step in better understanding the relationships between habitat structures, nekton communities, and their associated soundscapes as well as the application of passive acoustic monitoring to improve coastal management and conservation.

Radial Distribution of Electron Quasi-thermal Noise in the Outer Heliosphere

Voyager 1 and 2 are only the two spacecraft that have arrived and passed through the heliospheric boundaries. Based on the plasma data from the Voyager 2 spacecraft, the electron quasi-thermal noise (QTN) is investigated by using of the electron population model consisting of a core with Maxwellian distribution and a halo with kappa distribution. The power spectra of the electron QTN is calculated at different heliocentric distances from 1 to 110 au. The parametric dependence of the QTN power spectra and the effective Debye length on the model parameters, such as the density ratio and temperature ratio of the halo to the core, kappa index and the antenna length, are discussed further. The results show that the electron QTN spectrum consists of a plateau in the low frequency band f < f pt , a prominent peak at the plasma frequency f pt , and a rapid decreasing part in the high frequency band f > f pt . The QTN plateau level basically falls down outwards until the termination shock crossing at about 84 au, after which the plateau rebounds a little near the heliopause. Although the model parameters can be very variable, the QTN plateau level does not present more than the double change in a fairly wide range of the model parameters. The presented results can be useful for future deep-space explorations in the heliosphere and can provide valuable references for the design of onboard detectors.