Amplitude Of Component Research Articles

The neural mechanisms of the impact of emoji spatial metaphors on emotional perception

Metaphors play a crucial role in language, thinking, and communication. Emoji, as modern metaphors, carry rich meanings and significantly impact emotional expression. While spatial metaphors in emotional lexicons are confirmed, empirical evidence for spatial metaphors in emoji is scarce, and their neural mechanisms are largely unexplored. This study used a spatial Stroop task to investigate emoji spatial metaphors and their effects on emotional perception and neural mechanisms. The results showed that when the positive emoji were in the upper visual field, compared with the middle and lower visual field, the ability to perceive positive emotions was significantly enhanced; Conversely, when the negative emotion emoji was in the lower visual field, the perception of negative emotion was significantly enhanced compared to the middle visual field. EEG data indicate that inconsistencies between Emoji spatial positions and emotional valence lead to increased amplitudes of the Late Positive Component (LPC), revealing heightened neural activity.

FFS-Net: Fourier-based segmentation of colon cancer glands using frequency and spatial edge interaction

The morphological features of glands provide a reliable basis for pathologists to diagnose colon cancer correctly. Currently, most methods are limited in their ability to address blurred edges, adhesions, and morphological differences in glands when working in the spatial domain. In this study, a new perspective is proposed to segment glands by utilizing the interaction between Fourier and spatial domain features. Specifically, a Fourier transform is used to analyze the frequency characteristics of pathological images in which the phase component is related to image structural information and the amplitude component contains image intensity information. A Fourier-based colon cancer gland segmentation network (FFS-Net) is proposed, which gradually constructs feature representations in both the spatial and frequency domains through spatial frequency edge interactions. This network comprises spatial subnetworks, frequency subnetworks, and an edge phase fusion module (EPFM). To alleviate the interference of complex background information in feature discrimination, the spatial subnetwork collects high-frequency contour information regarding the glands. Then, the EPFM completes the spatial-frequency feature interaction to add edge-related constraints to the extracted features, enhance edge representation, and obtain global features from the frequency domain, thereby, addressing significant differences in gland morphology. Finally, learnable Gabor filters are introduced to enhance edge texture detail information in the frequency subnetwork, which further improves the segmentation of glands exhibiting blurred edges. The experimental results demonstrate that FFS-Net’s performance on two representative datasets was competitive and highly interpretable.

Posterior short ciliary arteries ischemia following embolization of anterior ethmoid artery to treat dural arteriovenous fistulas: a case report

BackgroundThe Onyx™ Liquid Embolic System is a non-adhesive liquid embolic agent, which has been proved by the US FDA for embolization of lesions in the peripheral and neurovasculature since 2005. We reported a case of ischemic optic neuropathy after using Onyx-18 to embolize the anterior ethmoid arteries that feeding dural arteriovenous fistulas (DAVF).Case presentationA 57-year-old Asian male presented with anterior cranial fossa DAVF underwent embolotherapy by delivering Onyx-18 through a microcatheter into the anterior ethmoid arteries under angiography guidance. The interventional procedure was successful and no clear evidence was found pointing to untargeted occlusive embolus. But after the surgery the patient experienced delayed painless vision loss in the right eye (RE). The fundoscopy showed unilateral papilledema with pale optic disc in RE, accompanied by significant edema and thickening in the retinal nerve fiber layer (RNFL) of macula. The fundus fluorescence angiography showed that most of the optic disc in RE had postponed or absent fluorescence filling. Visual evoked potential (VEP) confirmed that the amplitude of the P100 component was decreased in RE without significant prolongation of the latency. The patient was diagnosed with anterior ischemic optic neuropathy, but immediate pulse steroid therapy failed to rescue his vision.ConclusionPreoperative evaluation of the patient’s hemodynamic status and fundus examination are essential for assessing the risk of ischemic ocular complications, and the non-adhesive liquid embolic agent Onyx-18 should be used cautiously during endovascular embolization of intracranial artery.

Rolling bearing fault diagnosis method based on SSA-IWT-EMD

Aiming at the problem of insufficient wavelet threshold noise reduction and unclear extraction of characteristic frequency of EMD decomposition, a rolling bearing fault diagnosis method based on SSA-IWT-EMD is proposed. Two adjustment factors are introduced to propose an improved threshold function (IWT), which overcomes the shortcomings of traditional soft and hard thresholds, and the sparrow search optimization algorithm (SSA) is used to globally optimize its parameters to achieve rolling bearing signal noise reduction. A comprehensive index P is proposed to select and reconstruct the components generated by empirical mode decomposition (EMD) to highlight the fault characteristic information of the signal. Envelope spectrum analysis is used to realize bearing fault diagnosis. Simulation and measurement results verify the effectiveness of the proposed method; at the same time, compared with the method of selecting components with a single index and the literature method, it is shown that the comprehensive index P and the proposed method have stronger noise reduction and feature extraction capabilities, and the envelope spectrum amplitude and frequency doubling components are more obvious, which can better realize the fault diagnosis of rolling bearings.

SFDiff: Diffusion model with sufficient spatial‐Fourier frequency information interaction for low‐light image enhancement

AbstractDiffusion models are increasingly applied in low‐light image enhancement tasks due to their exceptional capability to model data distributions, but most current methods focus only on the original pixel space and neglect the potential of Fourier frequency information. In this article, SFDiff is proposed, a novel low‐light image enhancement method that integrates Fourier frequency information into the diffusion process. Specifically, Fourier transforms are applied at both the image and feature levels to separately enhance the amplitude and phase components, which restores global illumination degradation and positional information. Then a Spatial‐Frequency Fusion (SFF) block is used to fully integrate and interact with the information across spatial and frequency domains. Since illumination degradation is primarily manifested in the amplitude component, a loss function based on maximum likelihood learning is employed to constrain the amplitude component at each step of the sampling process, ensuring that the reverse process maintains an optimal trajectory. Owing to the streamlined network design and the fact that the Fourier transform requires no extra parameters, SFDiff achieves a reduction in parameters of over compared to several state‐of‐the‐art (SOTA) diffusion models and delivers high‐quality enhancement results on multiple real‐world datasets. The code is available at https://github.com/MrWan001/SFDiff.

Study of transient pressure and fluctuation characteristics in a centrifugal pump using the delayed detached-eddy simulation method

This study employed OpenFOAM, the delayed detached-eddy simulation (DDES) turbulence model, and structured grids to develop numerical models for three centrifugal pumps with twisted blades. The internal pressure field, velocity field, forces, and fluctuation characteristics of the centrifugal pumps are comprehensively analyzed under various operating conditions. The findings indicate that the pressure is relatively higher in the flow passages near the volute tongue and the outlet within the impeller. Regions of high relative velocity (slip velocity) are mainly found on the suction side of the blades, indicating that the design of the blade suction side affects the fluid outward slip performance. As the flow rate increases, the forces and force fluctuation amplitudes of each pump component also rise. Conversely, as the rotational speed increases, the force on the blades or impeller gradually increases while the fluctuation amplitude decreases. In the stationary domain, the force on the volute gradually decreases while the fluctuation amplitude of this force increases. The shape of the volute tongue influences the rate at which pressure inside the volute is converted to outlet pressure. The power spectral density (PSD) of pressure fluctuations is smallest at the nominal flow rate, displaying a clear and distinct axial frequency pattern without complex low-frequency fluctuations. Under low flow and high-speed conditions, the PSD at the axial frequency is relatively small, whereas the pressure PSD at other low frequencies is relatively large. This indicates instability in the flow under these conditions.

Non-additivity of the functional properties of individual P450 species and its manifestation in the effects of alcohol consumption on the metabolism of ketamine and amitriptyline

To explore functional interconnections between multiple P450 enzymes and their manifestation in alcohol-induced changes in drug metabolism, we implemented a high-throughput study of correlations between the composition of the P450 pool and the substrate saturation profiles (SSP) of amitriptyline and ketamine demethylation in a series of 23 individual human liver microsomes preparations from donors with a known history of alcohol consumption. The SSPs were approximated with linear combinations of three Michaelis-Menten equations with globally optimized KM (substrate affinity) values. This analysis revealed a strong correlation between the rate of ketamine metabolism and alcohol exposure. For both substrates, alcohol consumption caused a significant increase in the role of the low-affinity enzymes. The amplitudes of the kinetic components and the total rate were further analyzed for correlations with the abundance of 11 major P450 enzymes assessed by global proteomics. The maximal rate of metabolism of both substrates correlated with the abundance of CYP3A4, their predicted principal metabolizer. However, except for CYP2D6 and CYP2E1, responsible for the low-affinity metabolism of ketamine and amitriptyline, respectively, none of the other potent metabolizers of the drugs revealed a positive correlation. Instead, in the case of ketamine, we observed negative correlations with the abundances of CYP1A2, CYP2C9, and CYP3A5. For amitriptyline, the data suggest inhibitory effects of CYP1A2 and CYP2A6. Our results demonstrate the importance of functional interactions between multiple P450 species and their decisive role in the effects of alcohol exposure on drug metabolism.

Involvement of muscarinic acetylcholine receptor-mediated cholinergic neurotransmission in TMS–EEG responses

The combination of transcranial magnetic stimulation and electroencephalography (TMS–EEG) is emerging as a valuable tool for investigating brain functions in health and disease. However, the detailed neural mechanisms underlying TMS–EEG responses, including TMS-evoked EEG potentials (TEPs) and TMS-induced EEG oscillations (TIOs), remain largely unknown. Combining TMS–EEG with pharmacological interventions provides a unique opportunity to elucidate the roles of specific receptor-mediated neurotransmissions in these responses. Here, we investigated the involvement of muscarinic acetylcholine receptor (mAChR)-mediated cholinergic neurotransmission in TMS–EEG responses by evaluating the effects of mAChR antagonists on TEPs and TIOs in twenty-four healthy participants using a randomized, placebo-controlled crossover design. TEPs and TIOs were measured before and after administering a single oral dose of scopolamine (a non-selective mAChR antagonist), biperiden (an M1 mAChR antagonist), or placebo, with TMS targeting the left medial prefrontal cortex (mPFC), angular gyrus (AG), and supplementary motor area (SMA). The results indicated that mAChR-mediated cholinergic neurotransmission played a role in TEPs, but not TIOs, in a target-specific manner. Specifically, scopolamine significantly increased the amplitude of a local TEP component between approximately 40 and 63 ms post-stimulus when TMS was applied to the SMA, but not the mPFC or AG. Biperiden produced a similar but less pronounced effect. Importantly, the effects of these mAChR antagonists on TEPs were independent of those on sensory-evoked EEG potentials caused by TMS-associated sensory stimulation. These findings expand our understanding of TMS–EEG physiology, providing insights for its application in physiological and clinical research.

Angular analysis of B→K*e+e− in the low- q2 region with new electron identification at Belle

We perform an angular analysis of the B→K*e+e− decay for the dielectron mass squared, q2, range of 0.0008–1.1200 GeV2/c4 using the full Belle dataset in the K*0→K+π− and K*+→KS0π+ channels, incorporating new methods of electron identification to improve the statistical power of the dataset. This analysis is sensitive to contributions from right-handed currents from physics beyond the Standard Model by constraining the Wilson coefficients C7(′). We perform a fit to the B→K*e+e− differential decay rate and measure the imaginary component of the transversality amplitude to be ATIm=−1.27±0.52±0.12, and the K* transverse asymmetry to be AT(2)=0.52±0.53±0.11, with FL and ATRe fixed to the Standard Model values. The resulting constraints on the value of C7′ are consistent with the Standard Model within a 2σ confidence interval. Published by the American Physical Society 2024

Bringing Patients Out of The Gloom: Examining The Effects of Patient Power and Affect Labeling on Emotional Experience Reflected in Emotional Judgement

ObjectiveNegative emotions are common among patients in medical settings. It is important to investigate impacts of patient power and affect labeling on emotional experience in patients. MethodsBehavioral judgments and event-related potentials (ERPs) were recorded while participants with high or low patient power made emotional judgments (positive, negative) about neutral faces, as well as investigating how affect labeling (affect labeling, viewing) influenced emotional judgments about neutral faces in participants with low patient power. ResultsIndividuals with low patient power made more and faster negative emotion judgements. A larger late positive component (LPC) amplitude was found in negative emotion judgments for individuals with low patient power, a component related to allocation of attentional resources to motivationally salient stimuli. Affect labeling elicit less and slower negative emotion judgments in individuals with low patient power. ConclusionsThese results suggest that low patient power triggers negative emotion, which can be reduced by affect labeling. Practice implicationsThe current findings provide valuable insights into reducing negative emotions in patients, fostering promising targets for training for medical professionals and education for patients aiming to ensure more humanistic and higher-quality care delivery.

Methodology for Real-Time Torque Estimation in a Ship Propulsion Digital Twin

Abstract The safe operation of ships requires the condition of propulsion components to be maintained. Digital twins are a promising alternative for intelligent monitoring of these complex systems. Digital twins require models which ensure that the digital representation is able to mimic the behavior of the physical system. Alternate modeling solutions must be found when intellectual property restrictions or lack of available information limit the usability of physics-based models. This paper considers such a case where a system model of the propulsion system requires a real-time capable model of the propeller hydrodynamic torque. The creation of a data-driven hydrodynamic torque model based on full-scale, operational measurements is discussed. The described method focuses on the significant challenges associated with data cleaning and preparation while also evaluating whether well-known machine learning methods are suited for this application. The methods use speed-over-ground, heading, course, rotational speed, and propeller pitch as inputs. The outputs of the models are the single quadrant propeller torque coefficient and the amplitude of harmonic torsional excitation. These outputs are then combined to create a holistic prediction of the torque. Results indicate that both a polynomial least-squares fit and a shallow neural network predict the mean and the amplitude of harmonic components of the torque well. This prediction can be used to isolate the hydrodynamic torque when more than one torque source is present or to simulate what-if scenarios in a digital twin environment.

Ventilatory and Perceived Ergogenic Effects of Mandibular Forward Repositioning During Running at Maximal Oxygen Uptake Intensity.

Cardoso, F, Costa, MJ, Colaço, P, Vilas-Boas, JP, Pinho, JC, Pyne, DB, and Fernandes, RJ. Ventilatory and perceived ergogenic effects of mandibular forward repositioning during running at maximal oxygen uptake intensity. J Strength Cond Res XX(X): 000-000, 2024-Wearing an intraoral dental splint may enhance ventilatory function and exercise performance. Nineteen runners performed on a 400-m outdoor track: (a) an incremental protocol to assess the velocity at maximal oxygen uptake (vV̇ o2 max) and (b) 2 square wave bouts wearing 2 intraoral splints (with and without mandibular forward repositioning). The time until exhaustion at vV̇ o2 max (TLimv V̇ o2 max), ventilatory variables, oxygen uptake (V̇ o2 ) kinetics, energetic profiling, perceived exertion and kinematics, were all measured. Ventilatory data were assessed breath-by-breath and perceived exertion evaluated using the Borg 6-20-point scale at the end of TLimv V̇ o2 max bouts. Images were recorded by video cameras (120 Hz) and kinematic measures retrieved using Kinovea. A paired t test was computed for comparison of splints ( p ≤ 0.05). With (vs. without) mandibular forward repositioning, runners increased their TLimv V̇ o2 max by ∼6% ( p = 0.03), coupled with higher ventilation (151 ± 22 vs. 147 ± 23 L·min -1 , p = 0.04), end-tidal oxygen tension (114.3 ± 3.7 vs. 112.9 ± 3.9 mm Hg, p = 0.003), and lower inspiratory time (0.526 ± 0.083 vs. 0.540 ± 0.090 seconds, p = 0.02), despite similar V̇ o2 kinetics (e.g., 49.0 ± 8.7 vs. 47.7 ± 8.6 ml∙kg∙min -1 of fast component amplitude) being observed. The energy expenditure was ∼8% higher ( p = 0.03) with the mandible forward, coupled with lower perceived exertion scores ( p = 0.04). Mandibular forward repositioning was effective in acutely improving running performance at vV̇ o2 max with ergogenic effects on ventilatory and perceived variables.

Which ERP components are effective in measuring cognitive load in multimedia learning? A meta-analysis based on relevant studies.

The open and generative nature of multimedia learning environments tends to cause cognitive overload in learners, and cognitive load is difficult for researchers to observe objectively because of its implicit and complex nature. Event-related potentials (ERP), a method of studying potential changes associated with specific events or stimuli by recording the electroencephalogram (EEG), has become an important method of measuring cognitive load in cognitive psychology. Although many studies have relied on ERP output measurements to compare different levels of cognitive load in multimedia learning, the results of the effect of cognitive load on ERP have been inconsistent. In this study, we used a meta-analysis of evidence-based research to quantitatively analyze 17 experimental studies to quantitatively evaluate which ERP component (amplitude) is most sensitive to cognitive load. Forty five effect sizes from 26 studies involving 360 participants were calculated. (1) The results of the studies analyzed in subgroups indicated high level effect sizes for P300 and P200 (2) Analyses of moderating variables for signal acquisition did not find that different methods of signal acquisition had a significant effect on the measurement of cognitive load (3) Analyses of moderating variables for task design found that a task system with feedback was more convenient for the measurement of cognitive load, and that designing for 3 levels of cognitive load was more convenient for the measurement of cognitive load than for 2 levels of cognitive load. (4) Analyses of continuous moderating variables for subject characteristics did not find significant effects of age, gender, or sample size on the results.

Noninvasive Method Using Mechanical Extensometer for the Estimation of Intracranial Compliance by Repeated Measures Agreement Analysis.

Intracranial compliance refers to the relationship between changes in volume and the resultant changes in intracranial pressure (ICP). This study aimed to assess the agreement of a noninvasive ICP waveform device for the estimation of compliance compared with invasive ICP monitoring employing three distinct methods. We conducted a retrospective analysis of ICP waveform morphology recorded through both invasive (external ventricular drain) and noninvasive (mechanical extensometer) methods in adult patients with acute brain injury admitted to a neurointensive care unit between August 2021 and August 2022. Compliance was calculated as the amplitude of the fundamental component of cerebral arterial blood volume (estimated with concurrent Transcranial Doppler [TCD] recordings), divided by the amplitude of the fundamental component of the invasive and noninvasive ICP waveforms. Subsequently, we assessed the agreement between invasive and noninvasive intracranial compliance by repeated measures correlation coefficient analysis using three methods: TCD-derived, P2/P1 ratio, and time-to-peak (TTP). A linear mixed-effects model was used to compute the concordance correlation coefficient, total deviation index, and coefficient of individual agreement. Coverage probability plot was calculated to estimate the percent of observations within different cut points for each of the three methods. A total of 21 patients were identified for this study. Repeated measures correlation analysis showed a strong correlation (R = 0.982, 95% confidence interval [0.980-0.984], p < 0.0001) between log-transformed noninvasive and invasive compliance. Agreement statistics for TCD, P2/P1 ratio, and TTP indicated that although the concordance correlation coefficient was highest for log(TCD) values, TTP and P2:P1 ratio measures had better agreement with total deviation index and coverage probability plot analyses. Repeated measures correlations suggest that ICP waveform analyses may offer a more accurate estimate of compliance than TCD-derived methods for noninvasive ICP monitoring. Further validations studies are warranted to confidently establish this method as an indicator of intracranial compliance.

Classification of complex power quality disturbances under noisy environment using Root-Music and least square techniques

In this paper, a hybrid classification approach for single and complex power quality disturbances is proposed. This approach combines the Root-Music and least square techniques. Firstly, the frequencies are extracted by the Root-Music technique, including those of harmonic components. Afterward, the amplitude components are extracted using the least square technique. Once frequency and amplitude components are extracted, the waveform distortion of voltage is analyzed using the known criteria of total harmonic distortion. The value of this criterion allows for pre-classifying the disturbance into one of two classes. Then, the value of the extracted amplitudes of signals allows the identification of the corresponding disturbance. The classifier performances are validated by several tests using real power and synthetic data. The achieved results prove the effectiveness of the classifier compared to recent state-of-the-art techniques, especially in highly noisy environments. These results show that the proposed classifier leads to the highest classification accuracy of 100% at 20 dB, compared to those of other classifiers. Furthermore, this classifier demonstrates high classification accuracy even under challenging conditions with a high noise level of 10 dB.

Sensitivity of Frequency Domain Near Infrared Spectroscopy for Neurovascular Structure Detection in Biotissue Volume: Numerical Modeling Results.

Through numerical modeling, it has been determined that near infrared spectroscopy with a frequency domain approach can detect neurovascular structures with diameters from 0.5 mm at source-detector distances of 5-8 mm, depending on optical parameters and technical implementation of the method. Among the five classical machine learning methods considered, quadratic discriminant analysis is the most effective for detection. Furthermore, it has been demonstrated that the use of a photomultiplier tube and the registration of both amplitude and phase signal components exhibit the highest sensitivity. Spectroscopy can rival modern ultrasound for detecting arterial vessels. A cross-shaped probe configuration improves sensitivity, and the ratio of reduced scattering coefficient values at different wavelengths is informative for blood-filled vessel detection. These findings are consistent with and significantly extend previous experimental in vivo and in situ studies and could be valuable for intraoperative diagnostic tasks, particularly in neurosurgery.

Optical atompilz: Propagation-invariant strongly longitudinally polarized toroidal pulses

Recent advancements in optical, terahertz, and microwave systems have unveiled non-transverse optical toroidal pulses characterized by skyrmionic topologies, fractal-like singularities, space-time nonseparability, and anapole-exciting ability. Despite this, the longitudinally polarized fields of canonical toroidal pulses notably lag behind their transverse counterparts in magnitude. Interestingly, although mushroom-cloud-like toroidal vortices with strong longitudinal fields are common in nature, they remain unexplored in the realm of electromagnetics. Here, we present strongly longitudinally polarized toroidal pulses (SLPTPs), which boast a longitudinal component amplitude exceeding that of the transverse component by over tenfold. This unique polarization property endows SLPTPs with robust propagation characteristics, showcasing nondiffracting behavior. The propagation-invariant strongly longitudinally polarized field holds promise for pioneering light–matter interactions, far-field superresolution microscopy, and high-capacity wireless communication utilizing three polarizations.

A new method of intraoperative assessment of the dynamics of cortical blood flow using imaging photoplethysmography

Background. Intraoperative assessment of changes in cerebral blood flow is an important component of objective quality control of surgical treatment of cerebral artery aneurysms. Various techniques have been tried to solve this task, but they all have their drawbacks, which forces us to look for new ways of blood flow monitoring. We propose to use the technology of imaging photoplethysmography (IPPG) – a technically simple, contactless, safe and cheap optical method for assessing the perfusion of biological tissues.Aim. To demonstrate the possibility of using IPPG to assess the dynamics of cerebral blood flow parameters during aneurysm clipping surgery, as well as to identify early changes in blood supply to the cerebral cortex.Materials and methods. The study was carried out during six surgeries of clipping aneurysms of the anterior part of the Willis’s circle, both in the acute stage of rupture (n = 1) and in a planned manner (n = 5). The IPPG system, which is an LED illuminator in a single unit with a digital video camera, was located on a tripod 25 cm from the intervention zone. During each operation, two one-minute recordings of the illuminated surface of the cerebral cortex were performed: after dissection of the dura mater and before its suturing at the end of the main stage of the intervention. To improve the measurement accuracy, video frames of the studied area were recorded synchronously with the registration of an electrocardiogram. After recording, two IPPG parameters were calculated and compared: the amplitude of the pulsatile component and the pulse wave transit time. Thereafter, the obtained data were compared with the results of computed tomography. Statistical analysis was performed using pairwise comparison tests in the GraphPad Prism software package.Results. Clipping of cerebral vessel aneurysms are accompanied by significant changes in the parameters of cerebral blood flow. Analysis of the data for all patients revealed significant differences in IPPG parameters before and after surgery, namely, statistically significant increase in amplitude of the pulsatile component (n = 3) and decrease in pulse wave transit time (n = 5). The absence of significant changes in both parameters was found only in one patient who had mechanical damage in the cortex in the region of video recording.Conclusion. The IPPG system is capable to quantify changes in blood supply to the cortex during surgical treatment of cerebral artery aneurysms and to identify areas with either increased or decreased blood supply. In-depth studies are required to obtain additional markers of the postoperative state of cerebral blood flow.

Distraction impact of concurrent conversation on event-related potential based brain-computer interfaces

Objective.This study investigates the impact of conversation on the performance of visual event-related potential (ERP)-based brain-computer interfaces (BCIs), considering distractions in real life environment. The research aims to understand how cognitive distractions from speaking and listening activities affect ERP-BCI performance.Approach.The experiment employs a dual-task paradigm where participants control a smart light using visual ERP-BCIs while simultaneously conducting speaking or listening tasks.Main results.The findings reveal that speaking notably degrades BCI accuracy and the amplitude of ERP components, while increases the latency variability of ERP components and occipital alpha power. In contrast, listening and simple syllable repetition tasks have a lesser impact on these variables. The results suggest that speaking activity significantly distracts visual attentional processes critical for BCI operationSignificance. This study highlights the need to take distractions by daily conversation into account of the design and implementation of ERP-BCIs.

Self correction technique for amplitude and phase errors of underwater acoustic arrays based on variable decibel Bayesian inference

Abstract Direction of arrival (DOA) estimation of underwater targets is an important research direction in the field of underwater acoustic array signal processing. Due to factors such as assembly errors and component aging, amplitude and phase errors between each channel of the array are common, resulting in distortion of the array flow pattern matrix. At the same time, the non-uniform distribution of noise intensity at the positions of each array element further increases the difficulty of DOA for underwater targets. Based on the characteristics of sparse spatial distribution of underwater targets, this paper uses the flexibility of hyperparametric modeling to construct an array observation signal graph model. On this basis, the effects of amplitude and phase errors and non-uniform noise on the array model are added, and a comprehensive observation model with clear distribution types of amplitude and phase errors, signals, and noise is established. The variational Bayesian inference theory is used to obtain closed solutions of various variables and parameters, so as to achieve joint estimation of target azimuth and error parameters. Simulation results and sea trial data processing results show that the algorithm can achieve amplitude and phase error self correction while completing DOA estimation in the absence of prior information on the number of sources.