Hz Amplitude Research Articles

Flexible Polymer-Based Electrodes for Detecting Depression-Related Theta Oscillations in the Medial Prefrontal Cortex

This study investigates neural activity changes in the medial prefrontal cortex (mPFC) of a lipopolysaccharide (LPS)-induced acute depression mouse model using flexible polymer multichannel electrodes, local field potential (LFP) analysis, and a convolutional neural network-long short-term memory (CNN-LSTM) classification model. LPS treatment effectively induced depressive-like behaviors, including increased immobility in the tail suspension and forced swim tests, as well as reduced sucrose preference. These behavioral outcomes validate the LPS-induced depressive phenotype, providing a foundation for neurophysiological analysis. Flexible polymer-based electrodes enabled the long-term recording of high-quality LFP and spike signals from the mPFC. Time-frequency and power spectral density (PSD) analyses revealed a significant increase in theta band (3–8 Hz) amplitude under depressive conditions. Using theta waveform features extracted via empirical mode decomposition (EMD), we classified depressive states with a CNN-LSTM model, achieving high accuracy in both training and validation sets. This study presents a novel approach for depression state recognition using flexible polymer electrodes, EMD, and CNN-LSTM modeling, suggesting that heightened theta oscillations in the mPFC may serve as a neural marker for depression. Future studies may explore theta coupling across brain regions to further elucidate neural network disruptions associated with depression.

Inverse feedforward control of piezoelectric actuators using optimized composite neural network-based Hammerstein model

This paper utilizes the optimized composite neural network (OCNN)-Hammerstein model to directly identify the dynamic inverse hysteresis effect, employing it as a feedforward controller to compensate for the rate-dependent and amplitude-dependent dynamic hysteresis of the piezoelectric actuator. The OCNN-Hammerstein model consists of an optimized composite neural network and an auto-regressive exogenous model in series. The OCNN comprises convolutional neural network layer and radial basis function neural network layer, with its hyperparameters optimized using a modified grey wolf optimizer algorithm. Compared to the existing dynamic Prandtl-Ishlinskii-Hammerstein and dynamic Bouc-Wen-Hammerstein models in the literature, the feedforward controller based on the proposed model in this paper demonstrates superior performance, with an RSME below 0.45 μm and a 74.5% reduction in relative hysteresis at the condition of 300 Hz and maximum amplitude. The feedforward controller exhibits universality across all amplitude ranges and within the 50–300 Hz frequency range, while also providing predictive compensation for dynamic hysteresis at 300–400 Hz. The feedforward controller based on the OCNN-Hammerstein model in this paper provides a crucial methodology for open-loop control of piezoelectric actuators.

Volcanic tremor associated with successive gas emission activity at a boiling pool: Analyses of seismic array and visible image data recorded at Iwo-Yama in Kirishima Volcanic complex, Japan

Volcanic tremors are often observed during volcanic activity and volcanic eruptions, and their generation processes provide clues for understanding volcanic fluid activity underground and eruption dynamics. However, tremors are characterized by continuous oscillations that mask P- and S-waves; hence few studies have precisely located the source, which is the most fundamental information for understanding the generation mechanism. In this study, we focus on volcanic tremors excited by continuous gas emissions occurring at a vent called Y2a in Iwo-Yama, the Kirishima Volcanic Complex, Japan, to clarify the source process of the tremor as well as gas emission activity. We simultaneously observed the volcanic tremor by deploying a small aperture array consisting of six seismometers and the gas emission activity by using a newly developed visual IoT system that can be operated without commercial electricity. MUSIC analysis locates the tremor at depths ranging from the ground surface to approximately 200 m beneath the Y2a and Y2b vents, which are approximately 30 m apart, for approximately four months from November 2021 to February 2022. The source locations of the tremors in the 2 Hz (1.2–2.6 Hz), 4 Hz (3–4 Hz), and 5 Hz (4–5.5 Hz) ranges show some differences and changes with time. The source location tends to become deeper when the 2 Hz amplitude is large. The infrasound generated by gas emission activity is dominant in the tremor signals, which are recognized in the wave propagation velocity with an acoustic velocity of 330 m/s when the 2 Hz amplitude is small. The visual IoT system succeeded in detecting long-term changes in the gas emission activity, and we found that the 2 Hz amplitude of tremor was well correlated with the amount of hot water in the boiling pool of Y2a, which was controlled by precipitation and evaporation during non-rainy days. From these observations, we infer that the volcanic tremor is generated by resonance of volcanic gas and hot water in a crack-like structure beneath Y2a. The resonance was triggered by the counterforces of the gas emissions in the boiling pool, and the infrasound was dominant during periods of hot water depletion in the boiling pool. Temporal changes in the source depths may be caused by changes in the fluid properties, configuration of the resonator and/or the strengths of the underground sources and infrasound. Our simultaneous observations of seismic array and visual IoT system clarify that even the continuous gas emission activity that looks stable is controlled by external sources such as precipitation.

Bipolar and Laplacian montages are suitable for high-gamma modulation language mapping with stereoelectroencephalography.

To determine the optimal montage and vocalization conditions for high-gamma language mapping using stereoelectroencephalography. We studied 12 epilepsy patients who underwent invasive monitoring with depth electrodes and measurement of auditory-naming related high-gamma modulations. We determined the effects of electrode montage and vocalization conditions of the response on the high-gamma (60-140 Hz) amplitudes. Compared to common average reference montage, bipolar and Laplacian montages effectively reduced the degree of auditory naming-related signal deflections in the white matter during the stimulus and response phases (mixed model estimate: -21.2 to -85.4%; p < 0.001), while maintaining those at the cortical level (-4.4 to +7.8%; p = 0.614 to 0.085). They also reduced signal deflections outside the brain parenchyma during the response phase (-90.6 to -91.2%; p < 0.001). Covert responses reduced signal deflections outside the brain parenchyma during the response phase (-17.0%; p = 0.010). On depth electrode recording, bipolar and Laplacian montages are suitable for measuring auditory naming-related high-gamma modulations in gray matter. The covert response may highlight the gray matter activity. This study helps establish the practical guidelines for high-gamma language mapping using stereoelectroencephalography.

Mindfulness meditation alters neural oscillations independently of arousal

Neuroscience has identified that mindfulness meditation induces a state of relaxed alertness, characterised by changes in theta and alpha oscillations and reduced sympathetic arousal, although the underlying mechanisms remain unclear. This study aims to address this gap by examining changes in neural oscillations and arousal during mindfulness meditation using both traditional and data-driven methods. Fifty-two healthy young adults underwent electroencephalography (EEG) and skin conductance level (SCL) recordings during resting baseline and mindfulness meditation conditions, both conducted with eyes closed. The EEG data revealed a significant decrease in traditional alpha (8–13 Hz) amplitude during mindfulness meditation compared to rest. However, no significant differences were observed between conditions in traditional delta, theta, beta, or gamma amplitudes. Frequency Principal Components Analysis (fPCA) was employed as a data-driven approach, identifying six components consistent across conditions. A complex delta-theta-alpha component significantly increased during mindfulness meditation. In contrast, low alpha (~9.5 Hz) and low alpha-beta (~11 Hz) components decreased significantly during mindfulness meditation. No significant differences were observed between conditions in the delta, high alpha, and high alpha-beta components. Additionally, there were no significant differences in SCL between conditions, nor were there correlations between traditional alpha or fPCA components and SCL. These findings support the conceptualisation of mindfulness meditation as a state of relaxed alertness, characterised by changes in neural oscillations likely associated with attention and awareness. However, the observed changes do not appear to be driven by arousal.

Echoes from Sensory Entrainment in Auditory Working Memory for Pitch.

Ongoing neural oscillations reflect cycles of excitation and inhibition in local neural populations, with individual neurons being more or less likely to fire depending upon the oscillatory phase. As a result, the oscillations could determine whether or not a sound is perceived and/or whether its neural representation enters into later processing stages. While empirical support for this idea has come from sound detection studies, large gaps in knowledge still exist regarding memory for sound events. In the current study, it was investigated how sensory entrainment impacts the fidelity of working memory representations for pitch. In two separate experiments, an 8 Hz amplitude modulated (AM) entraining stimulus was presented prior to a multitone complex having an f0 between 270 and 715 Hz. This "target" sound could be presented at phases from 0 to 2π radians in relation to the previous AM. After a retention interval of 4 s (Experiment 1; n = 26) or 2 s (Experiment 2; n = 28), listeners were tasked to reproduce the target sound's pitch by moving their finger along the horizontal axis of a response pad. It was hypothesized that if entrainment modulates auditory working memory fidelity, reproductions of a target's pitch would be more accurate and precise when targets were presented in phase with the entrainment. Cosine fits of the average data for both experiments showed a significant entrainment "echo" in the accuracy of pitch matches. There was no apparent echo in the matching precision. Fitting of the individual data accuracy showed that the optimal phase was consistent across individuals, aligning near the next AM peak had the AM continued. The results show that sensory entrainment modulates auditory working memory in addition to stimulus detection, consistent with the proposal that ongoing neural oscillatory activity modulates higher-order auditory processes.

Effect of Swing Amplitude on Microstructure and Properties of TC4 Titanium Alloy in Laser Welding

The welding of TC4 titanium alloy sheets with a thickness of 1 mm was successfully accomplished by a swinging laser. The microstructure and mechanical properties of the welding seam under different swing amplitudes were studied. In this paper, the microstructure, phase composition, mechanical properties, and fracture morphology of the weld with swing frequency of 50 Hz and different swing amplitudes (0.2 mm, 1 mm, 2 mm, and 3 mm) were tested and analyzed. The results show that basket-weave microstructures are present in the fusion zone of welds under different oscillation amplitudes, but the morphology of martensite within the basket-weave differs. The weld microstructure is mainly composed of acicular α′ martensite, initial α phase, secondary α phase, and residual β phase. The hardness of the weld is higher than that of the base metal, and the overall hardness decreases from the weld center to the base metal. When the oscillation amplitude A = 1 mm, the weld microstructure has the smallest average grain size, the highest microhardness (388.86 HV), the largest tensile strength (1115.4 MPa), and quasi-cleavage fracture occurs. At an oscillation amplitude of A = 2 mm, the tensile specimen achieves the maximum elongation of 14%, with ductile fracture as the dominant mechanism.

Enhancing mixing efficiency of a circular electroosmotic micromixer with cross-reciprocal electrodes

Enhancing mixing efficiency in microscale processes for sensitive biomedical, pharmaceutical, and chemical applications is crucial, particularly when operating under low-velocity constraints. This study presents a comprehensive investigation into the impact of various factors on microfluidic mixing within a circular mixing chamber micromixer, utilizing electroosmotic principles. The governing equations are solved numerically using the finite element technique-based solver. This research examines the effects of microchamber diameter (D), inlet velocity (uo), alternating current (AC) voltage amplitude (ϕo), and AC frequency (f) on fluid mixing dynamics. Several key findings are noted from this study. The reduction of the circular microchamber diameter decreases the linear distance between cross-reciprocally placed microelectrodes, resulting in increased electroosmosis force and mixing efficiency. The voltage amplitude within the specified range shows increased mixing efficiency when fluid species are combined at appropriate velocity and AC frequency. The highest mixing efficiency of 98.84% is achieved with the following parameters: flow velocity (uo) of 150 μm/s, AC frequency of 4 Hz, voltage amplitude of 500 mV, and microchamber diameter of 20 μm. At a frequency of 12 Hz and voltage amplitude of 500 mV, the mixing efficiency exceeds 94.66% across a wide range of input velocities (100–200 μm/s), enabling versatile control in microfluidic devices. The nonlinear interaction between electroosmotic flow and microchamber geometry significantly contributes to this enhanced mixing efficiency. These results demonstrate the potential for optimizing microfluidic mixing processes through careful parameter tuning, particularly in applications requiring high efficiency at low flow rates. Thus, this study provides valuable insights for designing more effective microfluidic systems in various scientific and industrial fields.

Harvesting vibration energy by quad-stable piezoelectric cantilever beam: Modeling, fabrication and testing

The combination of beams with piezoelectric patches has become a prevalent energy harvesting tool due to its ease of use. Typical energy harvesting systems are usually linear, and their efficiency is not satisfying due to low-frequency bandwidth. In this paper, a quad-stable piezoelectric vibration energy harvester is analyzed both numerically and experimentally. The primary purpose of this investigation is to analyze the static and dynamic characteristics of a proposed quad-stable system to consider its potential for application in broadband energy harvesting comprehensively. The harvester system consists of a slotted cantilever beam, a piezoelectric patch, a pair of tip-mass blocks, and a double-sided clip. The cantilever beam is subjected to pre-displacement constraints made by a mutual self-constraint at the free end of it. The nonlinear behaviors of the harvester system, including snap-through and softening phenomena, are analyzed using the assumed modes and finite element method (FEM). The harvester's vibration equation is solved numerically and through an FE model which is made by an in-house finite element software. A prototype is designed and fabricated to validate the mathematical model and FE simulation. The experimental force-displacement diagram of the harvester displays distinct discontinuities, reflecting abrupt transitions occurring while switching its stable states. The prototype dynamics are analyzed by harmonic base excitation with different amplitude levels in two conditions, including the presence and absence of the piezoelectric patch. The results obtained from the mathematical and FEM model demonstrate a satisfactory correlation with the experimental data. Furthermore, the experimental data reveal the occurrence of the snap-through phenomenon, accompanied by a significant widening of the frequency bandwidth at relatively high amplitude levels. The system has the ability to provide an average output electrical power of 0.288 mW for an electrical resistance of 3.262 kΩ at the excitation frequency of 12.695 Hz and base acceleration amplitude of 3g.

Theta oscillations linked to auditory informativeness and context disambiguation.

Accurate predictions and the processing of prediction error signals can be important for efficient interaction with the auditory environment. In a reanalysis of data from Simal et al. (2021), who found that informative tones elicited increased N1 and P2 event-related potential components, we sought to identify electrophysiological indicators in the time-frequency domain associated with disambiguation of the hearing context and prediction of forthcoming stimulation. Participants heard two isochronous sequences of pure tones separated by a silent retention interval. A sequence could contain one, three, or five tones. Fifteen participants heard the three load conditions randomly intermixed. In this case, when sequence length was unknown, the second and fourth tone during encoding contained information allowing the prediction of another tone. Other participants heard the sequences blocked by sequence length, and the second and fourth tone of the sequences provided no new information (and hence were not informative). We used wavelet analysis and Hilbert transform methods to analyse the oscillatory activity related to tone informativeness. We found a significant increase in theta (4-7 Hz) amplitude following a tone that was informative and allowed prediction, in comparison with a tone that carried no predictive information. Previous work suggests increased theta amplitude is linked with task switching and an increase in cognitive control. We suggest informative tones recruit higher-level control processes involved in prediction of upcoming auditory events.

Towards ASSR-based hearing assessment using natural sounds

Objective. The auditory steady-state response (ASSR) allows estimation of hearing thresholds. The ASSR can be estimated from electroencephalography (EEG) recordings from electrodes positioned on both the scalp and within the ear (ear-EEG). Ear-EEG can potentially be integrated into hearing aids, which would enable automatic fitting of the hearing device in daily life. The conventional stimuli for ASSR-based hearing assessment, such as pure tones and chirps, are monotonous and tiresome, making them inconvenient for repeated use in everyday situations. In this study we investigate the use of natural speech sounds for ASSR estimation. Approach. EEG was recorded from 22 normal hearing subjects from both scalp and ear electrodes. Subjects were stimulated monaurally with 180 min of speech stimulus modified by applying a 40 Hz amplitude modulation (AM) to an octave frequency sub-band centered at 1 kHz. Each 50 ms sub-interval in the AM sub-band was scaled to match one of 10 pre-defined levels (0–45 dB sensation level, 5 dB steps). The apparent latency for the ASSR was estimated as the maximum average cross-correlation between the envelope of the AM sub-band and the recorded EEG and was used to align the EEG signal with the audio signal. The EEG was then split up into sub-epochs of 50 ms length and sorted according to the stimulation level. ASSR was estimated for each level for both scalp- and ear-EEG. Main results. Significant ASSRs with increasing amplitude as a function of presentation level were recorded from both scalp and ear electrode configurations. Significance. Utilizing natural sounds in ASSR estimation offers the potential for electrophysiological hearing assessment that are more comfortable and less fatiguing compared to existing ASSR methods. Combined with ear-EEG, this approach may allow convenient hearing threshold estimation in everyday life, utilizing ambient sounds. Additionally, it may facilitate both initial fitting and subsequent adjustments of hearing aids outside of clinical settings.

EEG band power and phase‐amplitude coupling in patients with Dravet syndrome

AbstractObjectiveDravet syndrome (DS) is an epileptic encephalopathy caused by haploinsufficiency of the SCN1A gene. SCN1A gene deficiency limits the firing rates of fast‐spiking inhibitory interneurons, which should reflect in abnormal aggregate network oscillatory electroencephalography (EEG) activity that can be measured by spectral power and phase‐amplitude coupling (PAC) analysis. In this retrospective pilot study, we tested whether spectral EEG frequency band power and PAC metrics distinguish children with DS from age‐matched controls, an early step toward establishing EEG markers of target engagement by gene or drug therapy.MethodsEEG data were collected from patients with DS (N = 6) and age‐matched control pediatric participants (N = 11) and analyzed for cumulative spectral power and PAC and classification capacity of these metrics, by logistic regression analysis. For this initial spectral and PAC analysis, we focused on sleep EEG, where myogenic artifact is minimal and where δ–γ and θ–γ coupling is otherwise expected to be robust.ResultsCumulative δ (1– &lt;4 Hz) and θ (4–7 Hz) power was significantly reduced in the DS group, compared with age‐matched controls (p = 0.001 and p = 0.02, respectively). The δ power was a stronger classifier of separating DS from controls than θ power, with 87% and 83% accuracy, respectively. The γ power trended toward significant reduction (p = 0.08) in the DS group. We found significantly lower PAC between 1–2 Hz phase and 63–80 Hz amplitude in patients with DS compared with the age‐matched controls (p = 0.003), with 78% classification accuracy between groups for PAC.InterpretationIn this pilot study assessing EEG patterns during sleep, we found lower δ–θ power and PAC in patients with DS versus controls, which may reflect abnormal aggregate macroscale network communication patterns resulting from SCN1A deficiency. These measures may be useful metrics of therapeutic target engagement, particularly if the therapy restores the underlying DS pathophysiology. The sorting capacity of these metrics distinguished patients with DS from patients without DS and may in turn facilitate near‐future development of disease and therapy target engagement biomarkers in this syndrome.

Closed-loop auditory stimulation of slow-wave sleep in chronic insomnia: a pilot study.

Insomnia is a prevalent and disabling condition whose treatment is not always effective. This pilot study explores the feasibility and effects of closed-loop auditory stimulation (CLAS) as a potential non-invasive intervention to improve sleep, its subjective quality, and memory consolidation in patients with insomnia. A total of 27 patients with chronic insomnia underwent a crossover, sham-controlled study with 2 nights of either CLAS or sham stimulation. Polysomnography was used to record sleep parameters, while questionnaires and a word-pair memory task were administered to assess subjective sleep quality and memory consolidation. The initial analyses included 17 patients who completed the study, met the inclusion criteria, and received CLAS. From those, 10 (58%) received only a small number of stimuli. In the remaining seven (41%) patients with sufficient CLAS, we evaluated the acute and whole-night effect on sleep. CLAS led to a significant immediate increase in slow oscillation (0.5-1 Hz) amplitude and activity, and reduced delta (1-4 Hz) and sigma/sleep spindle (12-15 Hz) activity during slow-wave sleep across the whole night. All these fundamental sleep rhythms are implicated in sleep-dependent memory consolidation. Yet, CLAS did not change sleep-dependent memory consolidation or sleep macrostructure characteristics, number of arousals, or subjective perception of sleep quality. Results showed CLAS to be feasible in patients with insomnia. However, a high variance in the efficacy of our automated stimulation approach suggests that further research is needed to optimise stimulation protocols to better unlock potential CLAS benefits for sleep structure and subjective sleep quality in such clinical settings.

Detection of principal and higher harmonic frequencies using stochastic resonance phenomenon in PBTTT-C14-based organic field-effect transistor

Stochastic resonance (SR) is an intriguing phenomenon in which noise, typically considered a detrimental aspect of electronic communication systems, assumes a beneficial role in the detection of undetectable signals. The SR phenomenon for detecting low-intensity optical signals using PBTTT-C14-based organic field-effect transistors (OFETs) is being reported. In this discourse, we explicate the sensing of an undetectable periodic optical signal with a frequency of 5 Hz, using a PBTTT-C14-based OFETs in the presence of a finite and optimal quantity of Gaussian noise (noise bandwidth of 1 Hz and noise amplitude of 2.0, 4.0, 6.0, and 7.5 V). The detection of higher harmonics for optical signals using the SR phenomenon has not been hitherto explored for OFETs. This report presents a noteworthy finding elucidating the detection of the principal frequency and also higher harmonics of the optical signal. This simplistic methodology for examining the SR phenomenon holds great promise in identifying its robust utility in diverse real-world contexts.

Sport-related concussion alters cerebral hemodynamic activity during controlled respiration.

Sport-related concussion (SRC) is known to disrupt neurohemodynamic activity, cardiac function, and blood pressure (BP) autoregulation. This study aims to observe changes in cerebrovascular and cardiovascular responses during controlled respiration after sustaining an SRC. University varsity athletes (n = 81) completed a preseason physiological assessment and were followed up within 5 days of sustaining an SRC. During preseason and follow-up assessments, participants' continuous beat-to-beat BP was collected by finger photoplethysmography, and right prefrontal cortex oxygenation was collected using near-infrared spectroscopy (NIRS). Participants completed 5 min of seated rest and 5 min of a 6-breaths per minute controlled breathing protocol (5 s inhale and 5 s exhale; 0.10 Hz). Wavelet transformation was applied to the NIRS and BP signals, separating them into respiratory (0.10-0.6 Hz) and cardiac (0.6-2 Hz) frequency intervals. Of the 81 participants, 74 had a usable BP signal, 43 had usable NIRS signals, and 28 had both usable BP and NIRS signals. Wavelet amplitudes were calculated and coherence between NIRS and BP on the 28 participants were assessed. There was a significant (P < 0.05) decrease in oxygenated hemoglobin amplitude from 0.062 to 0.054 Hz and hemoglobin difference amplitude from 0.059 to 0.051 Hz, both at the respiratory (0.10-0.6 Hz) frequency interval, from preseason to acute SRC, respectively. Therefore, during controlled respiration, there was a reduction in intensity at the respiratory band, suggesting a protective, reduced respiratory contribution to cerebral hemodynamic activity following acute SRC.NEW & NOTEWORTHY This study investigated cerebral hemodynamic activity following sport-related concussion. Prefrontal cortex oxygenation was assessed by near-infrared spectroscopy (NIRS) during a controlled breathing protocol. Wavelet transformation of the NIRS signals showed significant decreases in HbO2 and HbD amplitude at the respiratory frequency interval (0.10-0.6 HZ) from preseason baseline to acute concussion. These results suggest a decreased respiratory contribution to cerebral hemodynamic activity following acute concussion.

The comparative analysis of the Ex and Hz fields sensitivity generated by electric dipole sources

Abstract In the controlled source audio-frequency magnetotelluric method, orthogonal electric and magnetic fields are commonly measured to determine the Cagniard apparent resistivity. However, in the near-field zone, the Cagniard resistivity is severely distorted, which is unrelated to underground structures. The Ex and Hz amplitudes in a homogeneous half-space monotonically vary in resistivity, and a numerical algorithm could achieve high-precision apparent resistivity without distortion for all frequencies. On this basis, the main focus of this investigation is on the comparative analysis of the sensitivity for the Exfield, Hzfield, and Cagniard apparent resistivity to conductive and resistivity targets via synthetic models. The achieved results confirm that the Ex field could exhibit a more enhanced sensitivity for the resistive objects, whereas the Hz field could more effectively identify the conductive target. Besides, the static effect often distorts the electromagnetic data, which rigorously influences their application. The influence of the static effect on both the Exand Hzfields is also examined in detail. The apparent resistivity based on the Exfield and Cagniard apparent resistivity is significantly affected by the static effect, which can mask deep anomalous blocks. However, the apparent resistivity based on the Hz field is almost unaffected by the static effect. Finally, a more efficient observation approach is provided for both the insulating and conductive targets.

Studies of the acoustic activity of white whales (in captive conditions and the possibility of their signals using to control behavior of fish in fishing process

The purpose of the work: identification of acoustic activity of belugas in conditions of aviary keeping and justification of the possibility of using their signals in fishing.The material of research was digital audio recordings of hydroacoustic signals of belugas collected from 2016 to 2018.Methods used: analysis of hydroacoustic data, visualization of the daily acoustic activity of belugas in different seasons, identification of stereotypes of acoustic behavior and characteristic signals in captive conditions and during fish hunting. Novelty: for the first time a substantiation for the possibility of using signals of one of the species of toothed whales — belugas registered in the captive conditions, to influence on the behavior of hydrobionts and solve practical problems of fishing and fish protection is given.Results: the highest acoustic activity of white whales is observed during the day and noticeably decreases at night with increase and decrease in the morning and evening hours. Maximum acoustic activity precedes the feeding of dolphins.The most common tones are those containing the fundamental frequency and harmonics. Characteristic features of the sounds are high variability of duration from 0.25 to 2.5 s, pronounced frequency components in the 500–2500 Hz spectrum zones, amplitude and frequency modulation, sound pressure levels of the signal up to 500 Pa /1 m.Acoustic activity of belugas during fish hunting and in the period preceding feeding in captive conditions, stereotypical. Typical are low-frequency frequency-modulated calls and whistles in the hearing range of fish, as well as a curtain of air bubbles and body and tail slaps. Possible ways of using beluga whale signals to increase the efficiency of fishing are proposed.Practical significance: the results of the study open up the possibility of using the signals of belugas to remotely control the movement of fish, create artificial concentrations and deterrent of hydrobionts in the intended areas.

Light‐fueled self‐oscillation of liquid crystal polymer network: Effect of photostabilizers

AbstractThe quest for harnessing light‐induced oscillatory motion, inspired by natural oscillations, has become a focus of scientific attention. Researchers are exploring the use of liquid crystal network (LCN) polymers and their integration with compatible materials as soft actuators. Of particular interest is the utilization of photostabilizers, which play a pivotal role in preserving the polymer against photodegradation. For this, three distinct derivatives of Tinuvin were chosen to explore their influence on the light‐fueled oscillatory motion of LCN polymers when exposed to polarized light to examine the impact of molecular orientation on the resultant motion. The research includes a comprehensive analysis of morphology, FT‐IR spectra, and elastic modulus assessments. The findings indicate that the Tinuvin derivatives along with light polarization have an impact on the resulting oscillatory characteristics. The findings include oscillation frequencies spanning from 8.95 to 14.96 Hz and oscillation amplitudes ranging from 0.47 to 1.73 mm. The dipole moment of Tinuvin types influences the oscillation frequency by altering the elastic modulus of the LCN, while its impact on surface roughness and structural configuration affects the resulting oscillation amplitude. Notably, the highest oscillation frequency is observed when all oriented molecules within the LCN respond to 45° polarized light. Investigating the impact of utilized photostabilizers on the polymer structural configuration was although possible through the examination of related FT‐IR specra.

PORTABLE DVOR RECEIVER DESIGN USING RTL-SDR R820T2 WITH PYTHON PROGRAMMING LANGUAGE

The navigation equipment currently in use in Indonesia for flight is DVOR. The PIR (Portable ILS/DVOR Receiver) equipment must be subject to periodic ground check procedures using to ensure that the equipment is in good working condition. The PIR currently in use is manufactured by the manufacturer of DVOR equipment. As a result, the design of a portable DVOR receiver is underway, along with the measurement and evaluation of its performance, using the RTL-SDR R820T2 device in combination with the Python programming language. This design implements the waterfall method as its technique. The output of the portable DVOR receiver that employs RTL-SDR takes the form of 30 Hz amplitude modulation percentage. The portable DVOR receiver using RTL SDR, which features a positive-intrinsicnegative (PIR) manufacturer, exhibits an average deviation of 0.25% for the 30 Hz amplitude modulation percentage. According to these findings, the design tool functions sufficiently well.

Oscillatory beta dynamics inform biomarker-driven treatment optimization for Parkinson's disease.

Parkinson's disease (PD) is a neurodegenerative disorder characterized by loss of dopaminergic neurons and dysregulation of the basal ganglia. Cardinal motor symptoms include bradykinesia, rigidity, and tremor. Deep brain stimulation (DBS) of select subcortical nuclei is standard of care for medication-refractory PD. Conventional open-loop DBS delivers continuous stimulation with fixed parameters that do not account for a patient's dynamic activity state or medication cycle. In comparison, closed-loop DBS, or adaptive DBS (aDBS), adjusts stimulation based on biomarker feedback that correlates with clinical state. Recent work has identified several neurophysiological biomarkers in local field potential recordings from PD patients, the most promising of which are 1) elevated beta (∼13-30 Hz) power in the subthalamic nucleus (STN), 2) increased beta synchrony throughout basal ganglia-thalamocortical circuits, notably observed as coupling between the STN beta phase and cortical broadband gamma (∼50-200 Hz) amplitude, and 3) prolonged beta bursts in the STN and cortex. In this review, we highlight relevant frequency and time domain features of STN beta measured in PD patients and summarize how spectral beta power, oscillatory beta synchrony, phase-amplitude coupling, and temporal beta bursting inform PD pathology, neurosurgical targeting, and DBS therapy. We then review how STN beta dynamics inform predictive, biomarker-driven aDBS approaches for optimizing PD treatment. We therefore provide clinically useful and actionable insight that can be applied toward aDBS implementation for PD.