Frequency Interval Research Articles

Using wavelet phase coherence of heart rate variability and blood flow oscillations to compare mechanisms of action between Tai Chi mind-body exercise and brisk walking aerobic exercise

Tai Chi exercise has been demonstrated to be beneficial for health and quality of life. However, the mind–body effect of Tai Chi on modulating interactions of the cardiovascular components has not been investigated. This study aimed to differentiate the effect of Tai Chi (mind–body exercise) and brisk walking (aerobic exercise) on modulating skin blood flow oscillations (BFO) of the upper and lower limbs and heart rate variability (HRV). Bafa Wubu of Tai Chi for 15 min and brisk walking for 15 min were performed by 30 adults in two different days. Wavelet phase coherence was employed to assess the coordination between HRV and BFO before and after exercise. Two indices were proposed to quantify the coherence, i.e., the area (Aϕ) and maximal difference (dmax) between the coherence function and the threshold obtained by surrogate test. The results demonstrated that Tai Chi resulted in a significant decrease in phase coherence between HRV and BFO of the upper limb in the frequency interval 0.05–0.15 Hz (Aϕ baseline 0.1600 ± 0.0288, post-exercise 0.0486 ± 0.0220, p < 0.001; dmax baseline 0.3222 ± 0.0220, post-exercise 0.2578 ± 0.0219, p < 0.005), but not between HRV and BFO of the lower limb. Brisk walking resulted in a significant increase in phase coherence between HRV and BFO of the lower limb in the frequency interval 0.05–0.15 Hz (Aϕ baseline 0.0455 ± 0.0251, post-exercise 0.1190 ± 0.0241, p < 0.05; dmax baseline 0.2191 ± 0.0225, post-exercise 0.3103 ± 0.0208, p < 0.05) but not between HRV and BFO of the upper limb. Our finding indicates that mind–body exercise and aerobic exercise modulate cardiovascular regulations through different mechanisms of action.

Fingertip dynamic response simulated across excitation points and frequencies

Predicting how the fingertip will mechanically respond to different stimuli can help explain human haptic perception and enable improvements to actuation approaches such as ultrasonic mid-air haptics. This study addresses this goal using high-fidelity 3D finite element analyses. We compute the deformation profiles and amplitudes caused by harmonic forces applied in the normal direction at four locations: the center of the finger pad, the side of the finger, the tip of the finger, and the oblique midpoint of these three sites. The excitation frequency is swept from 2.5 to 260 Hz. The simulated frequency response functions (FRFs) obtained for displacement demonstrate that the relative magnitudes of the deformations elicited by stimulating at each of these four locations greatly depend on whether only the excitation point or the entire finger is considered. The point force that induces the smallest local deformation can even cause the largest overall deformation at certain frequency intervals. Above 225 Hz, oblique excitation produces larger mean displacement amplitudes than the other three forces due to excitation of multiple modes involving diagonal deformation. These simulation results give novel insights into the combined influence of excitation location and frequency on the fingertip dynamic response, potentially facilitating the design of future vibration feedback devices.

Interaction of sound-audition traits between eared insects and arthropodophagous bats: using a DNA approach to assess diet

Abstract Arthropod–bat interactions are often considered as a base model for studying factors underlying predator–prey coevolutionary processes. Bats developed ultrasonic echolocation to hunt, and in response some arthropods developed defense mechanisms such as ultrasonic hearing, allowing them to elude bat predators. The present study analyzes the feeding patterns of bats, focusing on sonic-auditory sensory mechanisms in predator–prey interactions. Next-generation DNA sequence data from fecal samples were used to analyze the diet of 17 bat species from Mexico. Arthropod prey taxa were classified according to their auditory traits, and echolocation data were recompiled from literature review. We: (i) classified arthropod families according to their hearing ability; (ii) estimated arthropod taxon richness and proportion in the diet of each bat species; and (iii) used multidimensional scaling, principal component analysis, and regression to analyze prey consumption patterns in relation to their auditory traits and in relation to echolocation characteristics of bats. Finally, we analyzed the relationship between foraging time and auditory characteristics of prey. Families with hearing organs correspond to the orders Lepidoptera and Orthoptera. We registered 20 families of Lepidoptera and 5 of Orthoptera—7 and 3 with hearing organs, respectively. Of these orders, families lacking ears were recorded in the diet of a few bat species. Our results support the allotonic frequency hypothesis predicting a difference in emission frequency intervals between predator and prey. However, we found that the consumption of earless moths is less frequent and is related to diurnal and twilight activity—hence, their consumption is limited to bat species foraging early. Results indicate bats feed on arthropod prey successfully despite the ultrasonic hearing ability of the prey. These results may be due to counteradaptations that allow maintenance of an asymmetric “arms race” between bats and eared insects that favors the predator.

Dynamic cerebral autoregulation is preserved during orthostasis and intrathoracic pressure regulation in healthy subjects: A pilot study.

Resistance breathing may restore cardiac output (CO) and cerebral blood flow (CBF) during hypovolemia. We assessed CBF and cerebral autoregulation (CA) during tilt, resistance breathing, and paced breathing in 10 healthy subjects. Blood velocities in the internal carotid artery (ICA), middle cerebral arteries (MCA, four subjects), and aorta were measured by Doppler ultrasound in 30° and 60° semi-recumbent positions. ICA blood flow and CO were calculated. Arterial blood pressure (ABP, Finometer), and end-tidal CO2 (ETCO2) were recorded. ICA blood flow response was assessed by mixed-models regression analysis. The synchronization index (SI) for the variable pairs ABP-ICA blood velocity, ABP-MCA velocities in 0.005-0.08 Hz frequency interval was calculated as a measure of CA. Passive tilting from 30° to 60° resulted in 12% decrease in CO (p = 0.001); ICA blood flow tended to fall (p = 0.04); Resistance breathing restored CO and ICA blood flow despite a 10% ETCO2 drop. ETCO2 and CO contributed to ICA blood flow variance (adjusted R2: 0.9, p < 0.0001). The median SI was low (<0.2) indicating intact CA, confirmed by surrogate date testing. The peak SI was transiently elevated during resistance breathing in the 60° position. Resistance breathing may transiently reduce CA efficiency. Paced breathing did not restore CO or ICA blood flow.

Spatial energy evolution of focused waves generated in numerical wave tank

This paper numerically investigates the energy evolution of the focused wave and its correlation with input parameters for the wave generation. The focused wave is numerically generated based on the fully nonlinear potential wave theory which is solved by the Quasi Arbitrary Lagrangian Eulerian-Finite Element Method. The investigation is performed by dividing the generated wave energy into three categories according to their frequency intervals, i.e., the initially assigned frequency interval [f1fN], the frequencies lower (f < f1) and higher (f > fN) than the initial interval. The amount of the generated energy falling into three energy categories and the energy distribution in the initial frequency interval are analysed against amplitude parameters and frequency bands under three amplitude spectra. Four indicators are proposed to indicate the actual energy variations comparing to the initial design. It is found that for all the three frequency intervals the energies increase when the amplitude parameters increases or the given frequency shifts towards the lower frequency domain. The choice of wave amplitude spectrum plays a significant role to maintain the distribution of the energy in the design frequency range and to minimise the energies out of the design frequency range. The results from the second-order wave group theory are used to assist analyses of the mechanism of the energy evolution alongside the focused wave generation. It is found that the lower-frequency energy in the vicinity of the focusing point is dominated by the second-order difference waves, whereas the higher-frequency energy is mainly produced by the wave flap. The waves which are higher than the second-order and the complex interactions not considered by the second-order wave theory are found significantly disturbing the energy distribution in the originally assigned wave-frequency interval.

Bayesian modeling of binomial experiments in sociology: problem analysis

The article is devoted to Bayesian modeling of simple comparative binomial experiments with binary data sets (of “hit” and “miss” format) in sociology and other social sciences. The main methodological foundations of application of Bayesian approach in statistics are briefly reviewed: the use of priors in analysis, features of Bayesian statistical inference, differences in frequency and Bayesian confidence intervals, features of hypothesis testing in Bayesian statistics. A Bayesian model of a comparative binomial experiment has been constructed. It supports comparison of independent and dependent samples of binomial variables, and also allows for differences in sizes of the compared samples. The capabilities of the model, as well as the principles of the Bayesian hypothesis testing, were demonstrated on test data using PyMC and ArviZ, contemporary free packages of the Bayesian modeling and analysis. The use of these tools allows implementing direct tensor operations with the obtained posterior distributions and provides the researcher with an effective way to calculate the effect size when comparing two binomial samples without having to resort to complicated forms of calculating this parameter. The possibilities and limitations of the Bayesian approach are shown in the context of comparative analysis of the results of binomial experiments in social sciences by estimating the probability of hypotheses via finding and comparing the area of intervals of posterior distributions

Adaptive Analysis of Machine Learning Algorithms on Medical Datasets for Disease Prediction

This paper aims to analyze and evaluate the performance of different classification algorithms on medical datasets and gives some tips and guidelines for choosing the right algorithm for the dataset. For this purpose, twelve medical datasets were selected from the UCI repository, including breast cancer data, chronic kidney disease, cryotherapy, hepatitis, immunotherapy, Indian Liver Patient Dataset (ILPD), liver disorders, pima diabetes, risk factors cervical cancer, statlog (heart) dataset, dermatology and lung cancer. The selected classifiers for performance evaluation are Bagging, IBK, J48, JRip, Multilayer Perceptron (MP), Naïve Bayes (NB), Support Vector Machine (SVM), ZeroR and Voting Frequency Intervals (VFI). The algorithms were implemented on datasets using the WEKA tool and 10-fold cross-validation. Experimental results and analysis for all measures were introduced to guideline researchers who seek to achieve and how to balance different measures. Additionally, challenges and future directions were presented at the end of this paper.

On a Closer Look of a Doppler Tolerant Noise Radar Waveform in Surveillance Applications.

The prevalence of Low Probability of Interception (LPI) and Low Probability of Exploitation (LPE) radars in contemporary Electronic Warfare (EW) presents an ongoing challenge to defense mechanisms, compelling constant advances in protective strategies. Noise radars are examples of LPI and LPE systems that gained substantial prominence in the past decade despite exhibiting a common drawback of limited Doppler tolerance. The Advanced Pulse Compression Noise (APCN) waveform is a stochastic radar signal proposed to amalgamate the LPI and LPE attributes of a random waveform with the Doppler tolerance feature inherent to a linear frequency modulation. In the present work, we derive closed-form expressions describing the APCN signal's ambiguity function and spectral containment that allow for a proper analysis of its detection performance and ability to remove range ambiguities as a function of its stochastic parameters. This paper also presents a more detailed address of the LPI/LPE characteristic of APCN signals claimed in previous works. We show that sophisticated Electronic Intelligence (ELINT) systems that employ Time Frequency Analysis (TFA) and image processing methods may intercept APCN and estimate important parameters of APCN waveforms, such as bandwidth, operating frequency, time duration, and pulse repetition interval. We also present a method designed to intercept and exploit the unique characteristics of the APCN waveform. Its performance is evaluated based on the probability of such an ELINT system detecting an APCN radar signal as a function of the Signal-to-Noise Ratio (SNR) in the ELINT system. We evaluated the accuracy and precision of the random variables characterizing the proposed estimators as a function of the SNR. Results indicate a probability of detection close to 1 and show good performance, even for scenarios with a SNR slightly less than -10 dB. The contributions in this work offer enhancements to noise radar capabilities while facilitating improvements in ESM systems.

Global solutions to the Kirchhoff equation with spectral gap data in the energy space

We prove that the classical hyperbolic Kirchhoff equation admits global-in-time solutions for some classes of initial data in the energy space. We also show that there are enough such solutions so that every initial datum in the energy space is the sum of two initial data for which a global-in-time solution exists. The proof relies on the notion of spectral gap data, namely initial data whose components vanish for large intervals of frequencies. We do not pass through the linearized equation, because it is not well-posed at this low level of regularity.

Indicating landslide hazard from tree rings – Ecosystem service provided by an alder forest in the hengduan Mts, Sichuan, China

Landslides are destructive geomorphological processes that cause economic and social losses. This stimulates the development of new tools related to landslide hazard. Recently, trees, their growth rings and dendrochronology have become widely used in landslide studies. Thus, this study aims to explore the potential of trees in providing landslide-monitoring ecosystem services through dendrochronology. In our opinion, establishing such an idea would help promote empirical evidence on the efficiency of tree-ring-based tools to decision-makers. We use the example of a landslide in the Moxi basin, Sichuan, China and present results of dendrochronological analysis of growth eccentricity in 48 Nepalese alder (Alnus nepalensis) trees. This analysis provided data on event timing and magnitudes, average frequency and recurrence interval for reactivation of the study landslide, as well as spatial variability of landslide active. Based on dendrochronological data we were also able to determine the current slope balance and general hazard of landslide reactivation on the study slope. Our study shows that trees and dendrochronology can provide data on the activity of landslides that can complement and improve the results of standard engineering methods. Moreover, dendrochronology itself can provide the full information needed for landslide hazard assessment, monitoring and prediction.

Experimental Study of Magnetron’s Power-Pulled Characteristic to Realize a Quasi-Dual-Frequency Microwave Output

This article presents experimental evidence demonstrating the feasibility of implementing a quasi-dual-frequency microwave signal generator using a 1 kW commercial magnetron. The injection-pulled magnetron may generate quasi-dual-frequency output with nearly identical amplitudes by injecting signal at specific powers and frequencies out of the Adler locking band. This generator offers the advantage of developing a large-power and tunable quasi-dual-frequency signal at low cost and with simple implementation. In the present study, a tunable quasi-dual-frequency signal with a frequency interval ranging from 0.48 MHz to 13.74 MHz is generated experimentally. Furthermore, the effects of anode voltage ripples on the dual-frequency outputs are experimentally investigated. An empirical relationship between the frequency interval and injection ratio is obtained and presented. In addition, neither the output power nor the efficiency of the magnetron in the dual-frequency mode decreases. This research is promising for improving microwave heating uniformity in large-scale industrial applications.

Assessing the impact of climate change on landslide recurrence intervals in Nakhon Si Thammarat Province, Thailand, using CMIP6 climate models

Climate variability and climate change may influence the frequency and recurrence interval of landslides. Precipitation, as a main triggering factor of landslides, may be influenced by climate variability and climate change. Changes in precipitation may directly affect landslide frequency and recurrence intervals. Considering the influence of climate variability and climate change, the partial duration series method and critical rainfall threshold are combined with the simulated precipitation of Phase 6 of the Coupled Model Intercomparison Project (CMIP6) general circulation models (GCMs) to predict changes in future landslide recurrence intervals in Nakhon Si Thammarat Province, Thailand. The analytical results predicted changes in the landslide frequency over the next 20 years (2023 to 2042). SSP1–2.6 and SSP2–4.5 are adopted as future socioeconomic development scenarios. According to the predictions, the results showed that the return period of landslide occurrence in the future will be shorter than the return period of landslide occurrence in the historical period; moreover, the landslide recurrence interval will fluctuate greatly. The Nakhon Si Thammarat DWR meteorological station shows the most fluctuation in landslide recurrence intervals for SSP1–2.6. In addition, the Nakhon Si Thammarat meteorological Station experiences a significant decrease of approximately 35% in landslide recurrence intervals under SSP1–2.6. For SSP2–4.5, the Nakhon Si Thammarat meteorological station shows the most fluctuation in landslide return period. In addition, the Nakhon Si Thammarat meteorological station observed a decline in landslide recurrence intervals, with a reduction of approximately 40%. Hence, the frequency of landslides may increase in the future. A comparison between SSP1–2.6 and SSP2–4.5 revealed that SSP2–4.5 yielded lower landslide return periods.

Influence of two collection frequency intervals on sperm quality of standard and miniature bull Terriers during short breeding periods: A clinical field study.

The quality of canine sperm can be influenced by many factors, such as breed, body weight, age, ejaculatory frequency, nutrition, and environment. In the UK, it is common practice for standard Bull Terriers (SBT) and miniature Bull Terriers (MBT) to require male donors during a short breeding period. The aim of this study was to evaluate the effect of semen collection frequency on ejaculate volume and nine sperm parameters in SBT and MBT males, considering age and body condition score (BCS). Ejaculates from six adult SBTs and four MBTs were collected 5 times at two consecutive intervals (Time Series [TS]1, 24 h vs. TS2, 48 h), 1 week apart. Ejaculate volume, concentration, total output, viability (live sperm), subjective total motility, vigor, and total morphological defects, including head, midpiece, and tail defects of sperm, were evaluated. A multivariable mixed linear model for repeated measures was used to analyze the effects of semen collection frequency, age, breed, and BCS on ejaculate volume and sperm parameters. Semen collection frequency, age, and, to a lesser extent, breed, and BCS significantly affected sperm parameters. Semen collection frequency affected all sperm parameters (p < 0.05) but not ejaculate volume (p > 0.05). Total sperm output, sperm vigor, total motility, and tail defects decreased (p < 0.05) at the end of TS1. However, sperm parameters remained relatively constant (p > 0.05) in TS2 between semen collection sessions. Overall, poorer sperm parameters were observed in older dogs (aged 5-8 years) than in younger dogs (aged 4 years). MBT produced less (p < 0.001) ejaculate volume (3.2 ± 0.2 mL vs. 4.3 ± 0.2 mL: Least Squares Mean ± Standard Error of Mean), lower total sperm output (221.8 ± 19.2 × 106 vs. 348.6 ± 19.2 × 106) and lower total morphological defects (25.0 ± 1.1% vs. 31.3 ± 0.9%), and a higher percentage of live sperm (77.0 ± 1.4% vs. 71.7 ± 1.1%) than SBT. In addition, a BCS of 4 positively influenced (p < 0.05) viability, vigor, and total sperm motility. Despite differences in age, breed, and BCS, better sperm parameter values were observed in all semen collection sessions. However, intensive semen collection (TS1) appears to be less effective in maintaining good sperm quality. For breeding or artificial insemination purposes, a 48-h interval between collection sessions is recommended for both breeds. The results of this study could be used to further optimize assisted reproductive technologies in both breeds.

Unipolar optical transitions in nanoclusters of ellipsoidal geometry

The quantum states of an ellipsoidal nanocluster of a heterophase system InAs/GaAs are studied using an exact analytical approach, in contrast to the generally accepted theoretical model based on the adiabatic approximation. It is shown that the spectrum of a nanoobject is formed from local groups, consisting of discrete levels, separated by terahertz frequency intervals. A double random degeneration of certain spectrum states is revealed. Allowed mid-infrared (IR) optical transitions between different spectral states are analyzed. The role of dimensional parameters and features of the shape of a nanoobject in the characteristics of unipolar transitions is assessed. The absorption spectrum for the transition in the lower part of the substructure spectrum is calculated.

Photonics-based wideband multi-format tunable radar jamming signal generator

A photonics-based radar jamming signal generator is proposed in this paper. By adjusting a polarization controller, interrupted-sampling repeater jamming (ISRJ), comb spectrum modulation jamming (CSMJ), ISRJ and CSMJ composite jamming can be respectively generated after photoelectric conversion. We have experimentally verified the generation of ISRJ signals with duty cycles of 50% and 25%, the generation of CSMJ signals with comb spectrum frequency intervals of 5 MHz and 10 MHz, and the generation of their composite jamming signals in the Ku band. Additionally, the ISRJ and CSMJ composite jamming effect of radar signals in the Ka band has been tested. After matched filtering processing, multiple false targets are produced and the total number of jamming targets can be up to 25, demonstrating significant jamming effects. The proposed structure can generate multi-format jamming signals without using digital radio frequency memory, which is suitable for producing high-frequency and large-bandwidth jamming signals. It can be applied in electronic countermeasure systems.

Heart Rate Variability Monitoring Based on Doppler Radar Using Deep Learning.

The potential of microwave Doppler radar in non-contact vital sign detection is significant; however, prevailing radar-based heart rate (HR) and heart rate variability (HRV) monitoring technologies often necessitate data lengths surpassing 10 s, leading to increased detection latency and inaccurate HRV estimates. To address this problem, this paper introduces a novel network integrating a frequency representation module and a residual in residual module for the precise estimation and tracking of HR from concise time series, followed by HRV monitoring. The network adeptly transforms radar signals from the time domain to the frequency domain, yielding high-resolution spectrum representation within specified frequency intervals. This significantly reduces latency and improves HRV estimation accuracy by using data that are only 4 s in length. This study uses simulation data, Frequency-Modulated Continuous-Wave radar-measured data, and Continuous-Wave radar data to validate the model. Experimental results show that despite the shortened data length, the average heart rate measurement accuracy of the algorithm remains above 95% with no loss of estimation accuracy. This study contributes an efficient heart rate variability estimation algorithm to the domain of non-contact vital sign detection, offering significant practical application value.

Resolving the relaxation complexity of vitrimers: Time-temperature superpositions of a time-temperature non-equivalent system

Vitrimers are polymer networks that, thanks to covalent bond exchange, combine desirable properties of thermoplastic and thermosets, such as flowability and insolubility. For this reason, vitrimers are considered to be good candidates for a number of innovative applications from self-healing soft robots to hard reprocessable materials. All these applications are related to the unusual thermomechanical behavior of vitrimers, consequence of the non-trivial interplay between the polymer network dynamics and the thermally activated chemical link exchange. Here we use solid-state rheology to investigate the properties of a recently developed epoxy-based vitrimer. The rheological analysis demonstrates that the mechanical spectrum is composed of two relaxation processes with distinct activation energies that are associated with glass dynamics and covalent bond exchange, respectively. This makes the material thermo-rheologically complex and time temperature equivalence does not apply. Nonetheless, thanks to mechanical spectral analysis in a wide range of stiffness, time and temperature, we are able to depict the time-temperature-relaxation landscape in an enough precise way to account for the two dynamical processes and recombine them to predict the mechanical moduli in a wide interval of frequencies (21 decades), from low temperatures (close to room temperature) to high temperatures (above the glass transition temperature).

Optical cavity spectroscopy using heterodyne detection with optical feedback laser frequency locking.

We demonstrate an accurate high sensitivity method for cavity spectroscopy. We measure the frequency intervals of transverse electromagnetic modes relative to a fundamental mode in a high finesse optical resonator, and attribute their mode numbers unambiguously. A laser is frequency locked to a fundamental T E M 00 cavity mode by optical feedback, and phase modulation is used to obtain frequency side bands, which may come to resonance with other transverse cavity modes as the radio-frequency of the modulation is tuned. At these resonances, transmission of the side bands is sensitively detected by heterodyning with the carrier. We also analyze the transverse spatial profile of the heterodyne signal for identification of mode numbers. The adjustment of the Gaussian cavity model to the measured frequency intervals yields values of cavity length, mirror radius of curvature, and mirror ellipticity, with high precision to the ppm level.

Enhancing moisture detection in coal gravels: A deep learning-based adaptive microwave spectra fusion method

The accurate and effective detection of moisture in coal gravels is crucial. Conventional air oven-drying method suffers from prolonged processing times and their disruptive nature. This paper proposes a deep learning-based adaptive fusion method for multiple microwave spectra to non-destructively detect the moisture content of coal gravels. First, a purpose-built free-space measurement platform is employed to acquire microwave spectra of coal samples, encompassing the magnitude and phase spectra of reflection coefficients (S11) and transmission coefficients (S21). Subsequently, a Monte-Carlo cross-validation-based method is adopted to detect and eliminate outliers in the spectra. Furthermore, a novel feature extraction module is proposed, enhancing the traditional U-shaped network using residual learning (ResNet) and the convolutional block attention module (CBAM) to extract and reconstruct subtle spectral features. Inspired by the high-level data fusion, an adaptive spectra fusion method is then introduced that can autonomously balance the contributions between different spectra. The experimental results underscore the advantages of the proposed method, with narrow frequency intervals between 2.50–3.25 GHz, 3.75–4.00 GHz, and 4.75–5.00 GHz exhibiting superior detection accuracy compared to the entire frequency band, achieving R2 = 0.9034, MAE = 1.0254, RMSE = 1.2948 and RPIQ = 6.0630.

Fractional-order lead networks to avoid limit cycle in control loops with dead zone and plant servo system

Abstract The fractional-order controllers (FOCs) have recently had a significant impact on control applications. However, they still need further research for feedback systems with hard nonlinearities, such as dead zones. The above compelling evidence motivates the design of a new robust FOC to avoid limit cycles caused by dead zones in the control loops. The proposed FOC consists of the cascade of two shifted in frequency, fractional-order lead networks. They provide high-value and sufficiently flat phase leads in sufficiently large frequency intervals. In this way, the linear part of the control loop can be easily shaped to achieve avoidance of limit cycles. The article applies classical concepts, such as the Nyquist plot and describing function method, to derive guidelines for designing the free parameters of the FOC. Moreover, a realization algorithm and a parameter setting procedure make the new FOC easily implementable in engineering practice.