Altered resting-state sensorimotor network in patients with obsessive-compulsive disorder: An EEG study.

Uncovering the Cognitive Mechanisms of Risk Decision-Making among ICU Nurses in Complex Clinical Contexts.

Effects of swLORETA Z-score neurofeedback in Z-coherence of the fronto-limbic circuit in patients with major depressive disorder.

Sleep biomarkers of sudden unexpected death in epilepsy: Data from the Kv1.1 mouse model.

The transition from analog to digital television broadcasting in Indonesia improves picture and sound quality; however, signal reception in rural areas remains a challenge due to long distances from transmitters and unfavorable topography. Conventional antennas and signal boosters have not provided optimal performance. This study aims to design a vertical linear antenna array with a stacking configuration to enhance digital television signal reception in the Ultra High Frequency (UHF) band. The antenna design was carried out through theoretical calculations, simulation, and optimization using CST Studio Suite 2019. The analyzed parameters include return loss, VSWR, gain, bandwidth, and radiation pattern. Simulation and testing results show that the antenna achieves a return loss below −10 dB, VSWR less than 2, gain above 10 dBi, and a unidirectional radiation pattern. The proposed antenna effectively improves digital television reception quality in rural areas.

Developing effective Brain-Computer Interfaces (BCIs) based on Imagined Speech (IS) is a significant challenge, largely due to high inter-subject variability in neural patterns. This study introduces a novel analytical framework to address this issue by integrating functional, effective, and complex network analyses with a more naturalistic sentence-level experimental protocol. Our findings confirm that while IS connectivity networks are characterized by considerable variability across individuals, our methodology successfully identifies a core set of stable pathways that persist across subjects. Specifically, we identified three principal pathways: a motor-language network in the left hemisphere driven by delta-band activity (CL→FR,CR consistent in 60% of subjects), a right-hemisphere network relayed to motor planning areas via gamma-band activity (TR→CL in 40% of subjects), and a top-down visual-spatial network involving parietal regions (POL→CR in 60% of subjects). In parallel, complex network analysis reveals the gamma frequency band to be the most functionally integrated and robust spectral signature, exhibiting significantly higher mean connectivity strength compared to all other bands (e.g., p=0.0015 vs. beta) and appearing consistently in 6/10 subjects. By distinguishing these stable neural markers from subject-specific activity, this work provides more reliable EEG-based signatures for the future development of advanced speech BCIs.

Novel damage identification of frame structure based on energy intensity ratio of sensitive frequency band

Inductance and capacitance parasitic prediction thanks to data analysis applied to Si and SiC MOSFET wide frequency band characterization

Deep learning based treatment remission prediction to transcranial direct current stimulation in bipolar depression using EEG power spectral density.

Incipient bearing fault diagnosis based on optical fiber sensor and feature-informed geometric partition entropy guided informative frequency band extraction

Abstract Spectral amplitude modulation (SAM) can effectively enhance the features of different signal components due to its superior spectral line editing capabilities. However, noise and interference cannot be separated by the SAM equalization effect. Therefore, this paper proposes a method named variable differential spectrum amplitude modulation (VDSAM) to optimize the amplitude modulation process. By designing differential spectral amplitude modulation assisted by the modulation Gini index, the optimal differential demodulation order is selected, and bearing fault information within the frequency band is enhanced by frequency correlation. Constructing a variational filtering framework based on spectral envelope and an adaptive resonant band identification method can increase the accuracy of feature extraction under multi-band unknown strong interference. The feasibility of the proposed method is verified using simulation data and experimental signals, with comparisons against other widely used methods confirming its prominent superiority.

Recent advances in functional PET (fPET) enable modeling of metabolic processes with second-level temporal resolution, opening applications such as imaging molecular connectivity comparable to fMRI. However, high-temporal fPET is more noise-sensitive, making meaningful signal extraction challenging. We developed a component-based preprocessing method adapted from fMRI, which models structured noise with tissue-specific regressors and removes low-frequency uptake trends (CompCor). This approach was applied to 20 high-temporal [18F]FDG-fPET scans from a long-axial PET/CT system (1 s frames) and 16 scans from a PET/MR scanner (3 s frames). Filtering methods were compared across frequency bands, and their effects on metabolic connectivity (M-MC) assessed. Connectivity was strongly influenced by filter strategy and scanner type. CompCor produced more consistent, structured networks than standard bandpass filters. Intermediate frequency bands (0.01-0.1 Hz) gave the most reliable connectivity across PET/CT and PET/MR (r = 0.89), while high-sensitivity PET/CT also revealed structured patterns at 0.1-0.2 Hz. Compared to fMRI, fPET networks appeared more spatially cohesive but less differentiated. In sum, high-temporal [18F]FDG-fPET enables high within-scan reliability estimation of resting-state M-MC when paired with appropriate denoising, opening a new avenue in molecular imaging. Scanner characteristics and preprocessing critically affect signal quality, while our physiologically informed pipeline improves comparability across systems and studies.

EEG-based emotion recognition is a crucial task with significant implications for mental health monitoring, affective computing, and clinical decision support. While Graph Neural Networks (GNNs) have shown promise in modeling the complex spatio-temporal dynamics of EEG signals, existing methods fall short by only considering pairwise spatial dependencies and neglecting critical higher-order associations among functionally related brain regions. Moreover, these approaches often fail to achieve frequency-specific temporal learning, leading to suboptimal results. To overcome these limitations, we propose the Sub-band Embedded Spatio-Temporal Network (SESTN), a novel framework that jointly models multi-frequency spatial and temporal dependencies. In SESTN, EEG features are first projected into sub-band embedding spaces, enabling finer-grained frequency-specific representation. Our approach then uses neurophysiological priors to construct weighted hyperedges, capturing intra-regional spatial relationships more effectively. A multi-head, Mamba-based temporal module is subsequently utilized to extract frequency-specific temporal dynamics. Finally, a graph convolutional fusion strategy integrates these features across different frequency bands. Extensive experiments on two widely used EEG emotion recognition datasets, SEED and SEED-IV, demonstrate that SESTN significantly improves classification performance in both subject-dependent and subject-independent scenarios. These results underscore SESTN's potential as a robust and effective framework for real-world biomedical applications, particularly in affective state monitoring and mental health assessment.

Abstract The terahertz metamaterials and metasurfaces with strong optical chirality are vital in a wide range of applications, such as chirality detection, bimolecular sensing and terahertz communication. Here, we proposed a metal spiral metasurface (MSM) that can achieve strong circular dichroism with high circular polarization extinction ratio in terahertz region. The designed metasurface can support two kinds of electric resonance modes, which can be used to control the polarization and phase of light at dual frequency bands. The chiroptical responses of structure are enhanced by lowering symmetry of MSM and the thin-film interference effects. The simulation results demonstrate that the left-hand and right-hand circularly polarized light waves can be selectively converted into linearly polarized light waves with transmission efficiency up to 80% at dual frequency bands. The amplitude of the circular dichroism is up to 0.8 and the circular polarization extinction ratio is larger than 90 at each frequency band. Moreover, the sign of CD in each frequency band can be controlled and flipped by simply varying the rotation angle of spiral metasurface. The studied results have potential applications in terahertz communication, polarization imaging, and biomedical diagnosis.

Stereo-electroencephalography guided radiofrequency thermocoagulation (RF-TC) aims at changing epileptogenic networks to achieve therapeutic purpose. However, the functional connectivity mechanism of RF-TC remains unknown. We sought to determine the effects of RF-TC on functional connectivity and the relationship between these variations and the clinical outcome. For this retrospective cohort study, we analyzed resting-state stereoelectroencephalography (SEEG) data segments to assess functional connectivity across sampling areas in seventeen epilepsy patients. We analyzed the variance of functional connectivity and graph theory indicators and assessed the relationship between variation and clinical response to RF-TC. We found decreased functional connectivity both within and between epileptogenic zone in alpha band (p < 0.05) after RF-TC. We also discovered the alteration of most graph theory properties in the alpha band. Moreover, within connectivity and betweenness were significantly decreased in alpha band in the non-improvement group (p < 0.05), while clustering coefficient showed opposite change in the improvement group (p < 0.05). Eventually, compared to improvement group, we discovered a greater decrease of within connectivity of alpha band in the epileptogenic zone (p < 0.01). The research on network changes after radiofrequency thermocoagulation (RF-TC) is still an evolving field. Our research results indicate that significant changes occurred in functional connectivity and network characteristics in specific frequency bands and brain regions after RF-TC. Notably, the reduction in the internal connectivity within the alpha frequency band of the epileptic lesion not only provides early electrophysiological feedback for RF-TC, but also serves as a potential indicator for evaluating clinical response and prognosis.

Purpose This study aims to address the reliability issue of fatigue fracture in internal metal interconnects of flexible vector hydrophones due to strain concentration when deployed on curved surfaces. The core objective is to propose a full semi-circular arc periodic serpentine interconnect structure and to systematically investigate its bending resistance and acoustic sensing performance. The goal is to fill the research gap on serpentine interconnects in the field of flexible hydrophones and to provide theoretical and technical support for complex curved surface applications. Design/methodology/approach This research used a systematic approach combining theoretical modeling, simulation analysis and process optimization. First, a mechanical model for linear and serpentine interconnects was established to theoretically reveal the low-stress mechanism of the serpentine structure. Second, a finite element model coupling solid mechanics and pressure acoustics was built using COMSOL multiphysics to simulate the stress, characteristic frequency, directivity and bending resistance of the flexible hydrophone and its serpentine interconnects. Furthermore, an innovative microfabrication process was developed, using transfer printing to achieve high-performance integration of single-crystal silicon piezoresistors onto the flexible substrate, with process reliability ensured by a multiindex collaborative judgment method. Finally, the piezoresistive effect of the sensitive unit was validated through quasi-static pressure resistance tests. Findings The research yielded the following key findings: regarding mechanical performance, simulations showed that at a bending radius of 8 mm, the maximum von Mises stress of the serpentine interconnect was 688 MPa, which is 31% lower than that of the linear wire, significantly enhancing the fatigue life. Regarding acoustic performance, the flexible hydrophone achieved a sensitivity of −179.75 dB, an 18.75 dB improvement over traditional hydrophones, exhibited good directivity, and had an effective working frequency band of 20–543 Hz. Regarding process and electrical performance, the optimized transfer printing process increased the yield by 35%. The measured piezoresistive coefficient of the sensitive unit reached 3.53 × 10–10 Pa-1, approximately 4.92 times that of traditional bulk silicon, demonstrating that this structure greatly enhances mechanical reliability while maintaining excellent electrical performance. Originality/value The originality and value of this research are reflected in three aspects: first, it proposes a novel full semi-circular arc periodic serpentine interconnect structure without straight segments, specifically addressing the stress concentration problem in high-curvature surface applications. Second, it constructs a dedicated mechanical model for this serpentine interconnect, clarifying the relationship between its stress and geometric parameters, thus providing clear guidance for design. Third, it systematically introduces the serpentine interconnect into the field of flexible vector hydrophones and solves the process challenges of integrating it with the bionic sensitive structure, filling a research gap in this area. This study provides a valuable solution and design basis for developing highly reliable flexible electronic devices suitable for dynamic bending environments.

Spreading depolarizations (SDs) are key drivers of secondary brain injury, yet existing bedside monitoring methods that use electrocorticography (ECoG) analyze electrodes and frequency bands separately, thereby obscuring the joint spatiotemporal patterns of SDs. Therefore, this paper introduces a multi-scale signal-image fusion framework that for the first time enables SDmonitoring as a joint multi-modal multi-band spectral image-based analysis. The ECoG signal is converted into a persistent spectral de-weighted spectrogram (PSd-Spec) and joined with multi-band features, through Transformer-CNN jointly empowered blocks: Multi-Channel and Band Transformer Block (MCBTB) and Multi-Scale Adaptive Fusion (MSAF). The network extracts short- and long-range dynamics in a multi-scale time window, while an attention-driven channel weighting module adaptively models the spatial propagation of the electrode strips. On 500h of neuro-ICU recordings, the proposed approach achieved 92.6% accuracy, 84.9% sensitivity. Relative to the best single-modality base line, performance improved by at least 18%, and SD onset was identified on average of 8 min before expert observation. The results suggest that multi-scale fusion of spectral images with ECoG signals yields a clinically actionable early-warning approach and extends quantitative imaging methods to intracranial electrophysiology.

ABSTRACT We present a new set of Rayleigh-wave detection algorithms (a module) that we derive from two competing, approximate models for elliptically polarized seismic data. This module processes three-component seismograms with sliding windows to output estimates of test statistics and source back azimuths that it can combine from multiple frequency bands. The module automatically adjusts declaration thresholds to maintain a fixed false alarm rate against noise and adapts its sliding window lengths to include a fixed number of waveform cycles per frequency band. We demonstrate these capabilities against real Rayleigh waves that are sourced from airborne explosions in Ukraine. The module shows reliable detection rates against explosions and reasonable estimates of source back azimuths at computational costs akin to those of power detectors. Performance curves show that the detection module exceeds a 0.80 true positive detection rate against a real, ∼75 kg Trinitrotoluene yield equivalent source at ranges of 25 km. Back-azimuthal estimates achieve mean errors of ∼3° with median absolute deviations of ∼10°. Our module thereby demonstrates a capability to automatically detect and directionally locate airborne explosions from three-component seismic data, simultaneously. Plain Language Summary: Rayleigh waves are a type of seismic surface wave that moves each point on the ground in the shape of an ellipse. This article develops and tests a new set of algorithms, or a module, to detect such Rayleigh waves with sensors that record ground motion in the east, north, and vertical directions. Our module operates like the scan feature of traditional car radios, but against seismic data. During its “scan” operation, our module consistently tests a fixed number of waveform cycles for Rayleigh-wave motion and adjusts its sensitivity to falsely trigger fewer than a set number of times per year. Our module also estimates the direction from which the source of this motion came. We test our module against data that we predict from airborne explosion simulations and from real explosions recorded in Ukraine. We thereby detect real events with the energy of about 75 kg of Trinitrotoluene explosive from 25 km away, about 80 out of 100 times. We also correctly estimate the direction back to the source within about 10°. Our article and its supplemental material provide the mathematics, physics, and some data required to understand and use this module.

ABSTRACT As information technology evolves, millimeter‑wave frequencies have become essential for ultra‑high‑speed wireless links. However, improving mmWave signal coverage and using spectrum resources efficiently remain challenging. To address these challenges, a spectrum fusion‐enabled millimeter‐wave intelligent metasurface system is proposed for assisting wireless communication, in which low‑frequency signals are used to establish sensing links for precise target localization, while high‑frequency millimeter‑wave signals are dynamically manipulated by the metasurface to enable user‑tracking communication. By decoupling the sensing and communication functions across different frequency bands, the system can effectively mitigate spectrum congestion and enhance the performance of dynamic wireless link. Simulation and experimental results demonstrate that the programmable metasurface, operating at 52.8 GHz, enables robust user‐tracking communication over an angular range of ±60°, while maintaining low and stable EVM values, indicating consistent modulation quality. These results highlight the advantages of leveraging low‑frequency sensing to assist high‑frequency communication. The proposed intelligent system architecture provides a novel and resource‑efficient solution for next‐generation wireless networks.

Abstract The current planned space-based gravitational-wave detectors require a bidirectional optical connection, referred to as Backlink, between two adjacent optical benches to provide a mutual phase reference for the local interferometric measurements. However, if the Backlink shows asymmetry between the two propagation directions, the effective optical pathlengths of the counter-propagating beams can introduce a differential phase noise, called non-reciprocity, into the main interferometric measurement that will limit the achievable accuracy in time-delay interferometry (TDI) post-processing. Hence, it is important to understand the properties of the Backlink to ensure that it will not compromise the interferometric detection. The Three-Backlink Experiment (3BL), which consists of an optical test facility with two rotatable benches, was designed under the Laser Interferometer Space Antenna (LISA) framework to study the performance of three Backlink configurations: two fiber-based and one free-beam scheme. In this paper, we report recent experimental results from the 3BL. We describe the commissioning and the subsequent noise mitigation. We achieve a setup noise floor below 1 pm/√Hz across most of the LISA measurement band, and provide an understanding of the current technical limitations. With this low-noise baseline, we measured the performance of the three Backlink implementations under non-rotational conditions. We show that all three Backlinks reach sub-picometer non-reciprocity levels across most of the frequency band, with the remaining part dominated by the mentioned testbed noise. This enabled us to conduct a preliminary study of the Backlink inherent noise, where we placed emphasis on the investigation of the backscatter noise intrinsic to a straightforward fiber-based Backlink, as this is the current baseline for LISA.