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An integral procedure in every coherent multidimensional spectroscopy experiment is to suppress undesired background signals. For that purpose, one can employ a particular phase-matching geometry or phase cycling, a procedure that was adapted from nuclear magnetic resonance (NMR) spectroscopy. In optical multidimensional spectroscopy, phase cycling has been usually carried out in a "nested" fashion, where pulse phases are incremented sequentially with linearly spaced increments. Another phase-cycling approach that was developed for NMR spectroscopy is "cogwheel phase cycling," where all pulse phases are varied simultaneously in increments defined by so-called "winding numbers." Here we explore the concept of cogwheel phase cycling in the context of population-based coherent multidimensional spectroscopy. We derive selection rules for resolving and extracting fourth-order and higher-order nonlinear signals by cogwheel phase cycling and describe how to perform a numerical search for the winding numbers for various population-detected 2D spectroscopy experiments. We also provide an expression for a numerical search for nested phase-cycling schemes and predict the most economical schemes of both approaches for a wide range of nonlinear signals. The signal selectivity of the technique is demonstrated experimentally by acquiring rephasing and nonrephasing fourth-order signals of a laser dye by both phase-cycling approaches. We find that individual nonlinear signal contributions are, in most cases, captured with fewer steps by cogwheel phase cycling compared to nested phase cycling. [ABSTRACT FROM AUTHOR]

Multi-tone microwave signals are crucial for advanced quantum computing applications, including frequency-multiplexed qubit control and simultaneous two-qubit gate execution. However, interference among microwave signal components can cause signal amplitudes to surpass the output limits of an arbitrary waveform generator (AWG), hindering the generation of precise signals necessary for accurate qubit manipulation. To address this issue, we introduce a method that adjusts the phase of individual microwave signal components, effectively reducing interference and maintaining signal amplitude within the AWG's operational range. [ABSTRACT FROM AUTHOR]

Vibrational sum-frequency generation (VSFG) has become a powerful tool for investigating the molecular structure of surfaces and interfaces. One aspect of the technique that has been overlooked is the source and nature of the nonresonant contribution to the measured signal. If not properly accounted for, interaction between the resonant and nonresonant responses can lead to misinterpretation of the resonant signals. The nonresonant response itself also carries important information about the system under study. This Perspective reviews some of the experimental and post-processing techniques that have been developed to isolate the nonresonant response. The focus of such approaches has generally been on the resonant signal, meaning more can be done to learn about the nonresonant response. Some examples of information carried by the nonresonant response are also presented, again showing that there is more to do to understand this signal. The nonresonant sum-frequency generation response is an important component of VSFG measurement, and the VSFG community needs to learn to better understand what it is telling us about our samples. [ABSTRACT FROM AUTHOR]

Vectorcardiography (VCG) has emerged as a physiological monitoring technique to effectively represent vital signals through the electrical activity of projected signals on spatial planes. However, utilising VCG data to monitor heart disease produces enormous volumes of clinical data. Therefore, VCG data must be compressed for transmission and storage. This work presents a simple yet efficient technique for compressing VCG signals, using singular value decomposition (SVD). The SVD transformation effectively extracts the considerable signal and robust interbeat correlation in VCG cycles, leading to optimal pattern decomposition and reduced redundant data. The effectiveness of the proposed compression approach is assessed using 10 different VCG data based on different fidelity metrics, such as CR, PSNR, PRD, SSIM, MSE, and SNR. The proposed compression technique achieves an average CR of 6.55, PSNR of 38.13 dB, PRD of 4.90, SSIM of 0.966, SNR of 28.09 and MSE, 2.61 × 10−4. The results illustrate that the proposed compression technique yields a good CR for VCG data while maintaining significant diagnostic information. [ABSTRACT FROM AUTHOR]

Within cognitive neuroscience, the definition of storage in working memory (WM) has focused on the cognitive accessibility of the stored representations and the stimulus-specific neural patterns that track them. We argue that this definition may be incomplete. We propose a refined definition that acknowledges the fundamental need to track entities through time and space and to bind those representations to the surrounding context. In line with past theories, we postulate the operation of a spatiotemporal 'pointer' system that enables this tracking process. This pointer operation may be the basis of neural signals that track the number of individuated items stored in WM while generalizing across variations in both the type and number of visual features stored. Limits on the number of pointers that can be deployed may help to explain why capacity in WM is item-based rather than determined by information load. Cognitive neuroscience has converged on a definition of working memory (WM) as a capacity-limited system that maintains highly accessible representations via stimulus-specific neural patterns. We argue that this standard definition may be incomplete. We highlight the fundamental need to recognize specific instances or tokens and to bind those tokens to the surrounding context. We propose that contextual binding is supported by spatiotemporal 'pointers' and that pointers are the source of neural signals that track the number of stored items, independent of their content. These content-independent pointers may provide a productive perspective for understanding item-based capacity limits in WM and the role of WM as a gateway for long-term storage. [ABSTRACT FROM AUTHOR]

Root-deck crack, a type of subsurface damage, is one of the most concerning fracture issues on orthotropic steel decks. Therefore, the development of novel and easy-to-use subsurface damage detection technique is crucial to detect damage at an early stage to prevent the occurrence of major damage. In this paper, new methods to process the response signal of the eddy current technique (ECT) using the normalised peak and time to zero crossing of the change in induced voltage, and the peak and frequency at the peak of the normalised change in phase angle, are proposed. Based on these newly proposed methods, a probe configuration optimisation study was carried out using dynamic electromagnetic field analysis. From numerical studies, the cup-core probe promises high capability to detect damage located 10 mm below the surface of a 12 mm steel plate and maintain the sensitivity at an eccentric position. Furthermore, the newly proposed signal processing methods enable users to interpret response signals for subsurface damage detection in a more comprehensive way than conventional methods. [ABSTRACT FROM AUTHOR]

This study reported nonlinear combination of multi-photon absorption and exciton–exciton collision induced random lasing (RL) emission from zinc oxide (ZnO) excited by femtosecond laser excitation. Strong RL with signal peaks centered at 407, 412 and 417 nm while excited at 800 nm wavelength pulses was observed. The threshold of the RL peak is about 0.9 mJ/cm 2 . Unlike the conventional three-photon excited RL phenomena centered at 390 nm, the violet discrete lasing modes ranging from 407 nm to 417 nm may occur because of the excitonic stimulation. The red-shift of lasing mode signals may be attributed to exciton–exciton interaction enhanced electron–hole plasma emission. [ABSTRACT FROM AUTHOR]

In this paper, a theoretical investigation of electromagnetically induced transparency (EIT) using Laguerre–Gaussian (LG) beams has been carried out for the three canonical atom-laser coupled systems (e.g. Λ -, V-, and Ξ -type) in 8 7 Rb atom. The required optical Bloch equations (OBEs) are derived for each system. The OBEs are analytically solved in steady-state condition under the weak probe field approximation. We have used the iterative perturbative technique to obtain the probe coherence term. The probe response w.r.t. probe detuning for different orders of the orbital angular momentum (OAM) number of both the pump and probe LG beams has been studied. We have also studied the effect of the OAM number on probe response in both Doppler-free and Doppler-broadened mediums. It has been observed that the EIT signal is squeezed for nonzero OAM number of the pump beam with arbitrary OAM number of the probe beam. It is found that for higher-order OAM number, the EIT signal is further squeezed. The modification of the EIT signal is attributed because of the spatial-dependent Rabi frequency. Our study demonstrates that the dynamic of the probe field inside an atomic medium may be controlled by tuning the OAM number of the LG beam. [ABSTRACT FROM AUTHOR]

In this Afterword I engage with each article in this special issue by highlighting some of their main points and placing them in conversation with scholarship in my substantive interests. In doing so, I signal the expansive potential of each contribution as I see it from my scholarly corner. I elucidate the generative potential of this collection and underscore the fruitfulness of adopting the critical lens to state-created categorization that threads the articles for the field of immigration studies in general. [ABSTRACT FROM AUTHOR]

Switched affine systems (SASs) are a special class of switched systems. The existing works about SASs predominantly focuses on steady-state performance. There exist limited attention given to transient performance, particularly the transient performance induced by switchings. The inappropriate switchings can induce severe signal jumps, degrade the steady-state performance of the system, and even lead to instability. The bumpless transfer control (BTC) represents an effective strategy for mitigating signal jumps. However, the existing BTC methods are primarily designed for general switched systems, and these approaches are often not applicable to SASs. This article is focussed on the issue of $ H_{\infty } $ H ∞ BTC for SASs under unmodeled disturbances. Firstly, an affine term (AT) related to $ H_{\infty } $ H ∞ bumpless transfer (BT) performance definition is introduced for the SAS to characterise the alleviation level of the bumps in the control input signal at switching points. Secondly, a criterion is established to enable the solvability of the $ H_{\infty } $ H ∞ BTC problem for the SAS. Thirdly, an $ H_{\infty } $ H ∞ BT controller and a switching signal are co-designed to drive the SAS to satisfy the $ H_{\infty } $ H ∞ BT performance which may not be shared by the subsystems. Finally, a turbofan engine model example is implemented to illustrate the availability and rationality of the suggested $ H_{\infty } $ H ∞ BTC scheme. [ABSTRACT FROM AUTHOR]

In this article, a transient road signals simulation strategy in a Stewart platform is presented. Real world road signals are transient signals and thus the accurate simulation of its frequency, amplitude and damping components is key for further simulation of comfort. This simulation strategy combines a kinematic model and a transient signal reconstruction strategy using an autoregressive method. First, the developed experimental kinematic model on a Stewart platform is presented. Then, the procedure to simulate real-world transient road signals in the driving simulator is explained. Finally, the developed strategy has been validated under real road signals combined in the 6 degrees-of-freedom to prove the accuracy between the real world experimental measured signal and the simulated signal in the hexapod. The final goal of the presented transient road signals simulation strategy is to perform further vehicle dynamics and ride and comfort studies in the simulation phase using electric Stewart platforms. [ABSTRACT FROM AUTHOR]

The spatial distribution of signals in X-ray diffraction (XRD) may be very narrow, posing challenges in obtaining high angular resolution results through traditional methods. This article explores multi-frame super-resolution algorithms from the field of image processing, selecting and refining the best suited to the requirements of the crystal truncation rod (CTR) test. Consequently, a new algorithm with a corresponding methodology is proposed. This approach is subsequently applied to characterize the CTR signal of SrTiO3 single-crystal samples, effectively enhancing the clarity of blurry and rough CTR cross-section signals. The resolution with this method surpasses that obtained using the pixel size alone, which is beneficial for characterizing weak signals. By combining data in three dimensions, a significantly enhanced three-dimensional CTR signal is obtained. This method enables the extraction of otherwise difficult-to-obtain information and can be conveniently integrated into subsequent theoretical work. Moreover, these methods hold potential for application in other techniques that require improved resolution under similar conditions. [ABSTRACT FROM AUTHOR]

The key aim of compressed sensing (CS) is to stably reconstruct a $ k $-sparse signal $ \mathbf{x} $ from some measurements $ \mathbf{y} $ in $ \mathbf{y = Ax+v} $, where $ \mathbf{v} $ is a noise vector. Recently, in order to promote sparsity, $ \frac{\ell_{1}}{\ell_{p}} $-minimization have been proposed in CS. In this paper, we consider two cases of $ \mathbf{v} $ (i.e., $ \|\mathbf{v}\|_{2} \le \varepsilon $ and $ \|\mathbf{A}^{T}\mathbf{v}\|_{\infty} $) and establish sufficient conditions based on mutual coherence for recovering $ k $-sparse signal $ \mathbf{x} $ by using $ \frac{\ell_{1}}{\ell_{p}} $-minimization method with $ p>1 $. [ABSTRACT FROM AUTHOR]

This paper concerns the homogeneous Neumann initial-boundary value problem for a two-species attraction-repulsion system with nonlinear signal production and logistic-type source. Under appropriate regularity assumptions on the initial data, using different methods we present the global existence and uniform boundedness of positive classical solutions in any dimensions for the parabolic-elliptic-parabolic-elliptic system and the fully parabolic system. Moreover, by constructing the appropriate energy functional, we further establish the global stabilities of nonnegative spatially homogeneous equilibria for a special case of the fully parabolic attraction-repulsion system. These results partially generalize and improve the previously known ones. [ABSTRACT FROM AUTHOR]

Purpose: To develop a single‐shot SNR‐efficient distortion‐free multi‐echo imaging technique for dynamic imaging applications. Methods: Echo planar time‐resolved imaging (EPTI) was first introduced as a multi‐shot technique for distortion‐free multi‐echo imaging. This work aims to develop single‐shot EPTI (ss‐EPTI) to achieve improved robustness to motion/physiological noise, increased temporal resolution, and higher SNR efficiency. A new spatiotemporal encoding that enables reduced phase‐encoding blips and minimized echo spacing under the single‐shot regime was developed, which improves sampling efficiency and enhances spatiotemporal correlation in the k‐TE space for improved reconstruction. A continuous readout with minimized deadtime was employed to optimize SNR efficiency. Moreover, k‐TE partial Fourier and simultaneous multi‐slice acquisition were integrated for further acceleration. Results: ss‐EPTI provided distortion‐free imaging with densely sampled multi‐echo images at standard resolutions (e.g., ˜1.25 to 3 mm) in a single‐shot. Improved SNR efficiency was observed in ss‐EPTI due to improved motion/physiological‐noise robustness and efficient continuous readout. Its ability to eliminate dynamic distortions—geometric changes across dynamics due to field changes induced by physiological variations or eddy currents—further improved the data's temporal stability. For multi‐echo fMRI, ss‐EPTI's multi‐echo images recovered signal dropout in short‐T2*$$ {\mathrm{T}}_2^{\ast } $$ regions and provided TE‐dependent functional information to distinguish non‐BOLD noise for further tSNR improvement. For diffusion MRI, it achieved shortened TEs for improved SNR and provided images free from both B0‐induced and diffusion‐encoding‐dependent eddy‐current‐induced distortions with multi‐TE diffusion metrics. Conclusion: ss‐EPTI provides SNR‐efficient distortion‐free multi‐echo imaging with comparable temporal resolutions to ss‐EPI, offering a new acquisition tool for dynamic imaging. [ABSTRACT FROM AUTHOR]

This paper presents two searches for supersymmetry through the direct production of pairs of higgsinos decaying into final states with leptons and (b-) jets. The analyses are performed using 139fb−1 of the 13TeV proton–proton collision data collected with the ATLAS detector. The methods used to estimate the Standard Model and detector backgrounds are discussed, as well as their shortcomings. Finally, results in selected signal regions, and some exclusion limits, are presented, illustrating the significant improvement over the previous exclusion limits. [ABSTRACT FROM AUTHOR]

This paper explores the experimental search potential for sbottom pair production in an R-parity conserving scenario at the LHC Run-3 and HL-LHC. The sbottom decays with a 100% BR via a chargino, b̃1→tχ̃1±, which subsequently decays to a W boson and a neutralino, χ̃1±→Wχ̃10, also with a 100% BR. The study follows the ATLAS object definitions and event selection criteria from [ATLAS Collab., J. High Energy Phys. 06, 046 (2020), arXiv:1909.08457 [hep-ex]], focusing on Rpc2L1b and Rpc2L2b signal regions defined with same-sign leptons and at least one b-tagged jet. Projected exclusion limits are presented in the b̃1–χ̃10 mass plane for three center-of-mass energies (13, 13.6 and 14TeV) and three integrated luminosity scenarios (139, 300 and 3000fb−1). [ABSTRACT FROM AUTHOR]

Network models are widely applied to describe connectivity and flow in diverse systems. In contrast, the fact that many connected systems move through space as the result of dynamic restructuring has received little attention. Therefore, we introduce the concept of 'traveling networks', and we analyze a tree-based model where the leaves are stochastically manipulated to grow, branch, and retract. We derive how these restructuring rates determine key attributes of network structure and motion, enabling a compact understanding of higher-level network behaviors such as multiscale search. These networks self-organize to the critical point between exponential growth and decay, allowing them to detect and respond to environmental signals with high sensitivity. Finally, we demonstrate how the traveling network concept applies to real-world systems, such as slime molds, the actin cytoskeleton, and human organizations, exemplifying how restructuring rules and rates in general can select for versatile search strategies in real or abstract spaces. Complex networks are relevant to wide range of areas, from biology to social sciences and economics, however the aspect that networks can move through space has not been elaborated. The authors propose a concept of traveling networks that can dynamically restructure themselves in space and perform search tasks. [ABSTRACT FROM AUTHOR]

Some authors argue that filled pauses serve a communicative function in speech. The current study aims to test this function by analyzing the difference in filler-use in a self-directed and social speech condition. Additionally, the influence of Autism Spectrum Disorder (ASD) traits and stress on the difference in filler-use between the two conditions were examined. In the first condition, participants described a series of different tangrams to themselves. In the second condition, participants described tangrams to another participant. More words and filled pauses were used when talking to someone else, but there were no more filled pauses per word. This suggests that filled pauses do not primarily serve as communicative signals. Instead they indicate that at least to some extent, they appear involuntary and automatically as a result of errors in the language production system. Furthermore, no significant correlation was found between the score on the ASD questionnaire or stress and the difference in fillers used in both speech conditions. Future research should consider experimental designs that more clearly differentiate between the presence or absence of a communicative goal, as the context of a monologue may still provide speakers with reasons to use communicative signals. [ABSTRACT FROM AUTHOR]

The integration of distributed generation (DG) in microgrids has brought the challenge of islanding detection, where a portion of the grid operates independently due to disconnection from the main utility. Traditional islanding detection methods often struggle to balance detection speed, reliability, and non-detection zones (NDZ). This paper presents a novel modified passive islanding detection strategy based on a mathematical morphological filter (MMF) with a sliding window method-based median filter (SWMBMF), designed to address these challenges in microgrid systems. The measured noisy voltage signal at point of common coupling (PCC)/DGs-terminal is initially estimated via SWMBMF by continuously monitoring the signals with minimal latency. Then, the MMF is utilized to process the estimated voltage to compute the voltage residuals index (VRI). Moreover, the VRI are compared with pre-specified threshold setting to detect islanding conditions, VRI also effectively distinguishes between normal and islanding conditions. Comprehensive MATLAB/Simulink 2023b simulations demonstrate the robustness of the proposed strategy under various islanding scenarios and grid disturbances, proving its effectiveness in ensuring the stability and reliability of microgrid operations. The proposed method demonstrates an impressive accuracy of 99%, successfully identifying islanding events within 5 ms. This rapid detection enhances grid reliability and minimizes risks associated with delayed islanding detection. The proposed scheme has negligible non detection zone (NDZ). [ABSTRACT FROM AUTHOR]

Credibility signals represent a wide range of heuristics typically used by journalists and fact-checkers to assess the veracity of online content. Automating the extraction of credibility signals presents significant challenges due to the necessity of training high-accuracy, signal-specific extractors, coupled with the lack of sufficiently large annotated datasets. This paper introduces Pastel (Prompted weAk Supervision wiTh crEdibility signaLs), a weakly supervised approach that leverages large language models (LLMs) to extract credibility signals from web content, and subsequently combines them to predict the veracity of content without relying on human supervision. We validate our approach using four article-level misinformation detection datasets, demonstrating that Pastel outperforms zero-shot veracity detection by 38.3% and achieves 86.7% of the performance of the state-of-the-art system trained with human supervision. Moreover, in cross-domain settings where training and testing datasets originate from different domains, Pastel significantly outperforms the state-of-the-art supervised model by 63%. We further study the association between credibility signals and veracity, and perform an ablation study showing the impact of each signal on model performance. Our findings reveal that 12 out of the 19 proposed signals exhibit strong associations with veracity across all datasets, while some signals show domain-specific strengths. [ABSTRACT FROM AUTHOR]

Time angle of arrival (AoA) and time difference of arrival (TDOA) are two widely used methods for solving dynamic signal source localization (DSSL) problems, where the position of a moving target is determined by measuring the angle and time difference of the signal's arrival, respectively. In robotic manipulator applications, accurate and real-time joint information is crucial for tasks such as trajectory tracking and visual servoing. However, signal propagation and acquisition are susceptible to noise interference, which poses challenges for real-time systems. To address this issue, a noise-immune zeroing neural dynamics (NIZND) model is proposed. The NIZND model is a brain-inspired algorithm that incorporates an integral term and an activation function into the traditional zeroing neural dynamics (ZND) model, designed to effectively mitigate noise interference during localization tasks. Theoretical analysis confirms that the proposed NIZND model exhibits global convergence and high precision under noisy conditions. Simulation experiments demonstrate the robustness and effectiveness of the NIZND model in comparison to traditional DSSL-solving schemes and in a trajectory tracking scheme for robotic manipulators. The NIZND model offers a promising solution to the challenge of accurate localization in noisy environments, ensuring both high precision and effective noise suppression. The experimental results highlight its superiority in real-time applications where noise interference is prevalent. [ABSTRACT FROM AUTHOR]

In 2020, BDS-3 began broadcasting high-precision positioning correction products through B2b signals, effectively addressing the limitations of ground-based augmentation. However, challenges such as the "south wall effect" from geostationary orbit (GEO) satellites, issues of data (IOD) mismatch, and signal priority conflicts often result in interruptions and anomalies during real-time positioning with the B2b service. This paper proposes a continuous B2b-PPP (B2b signal-based Precise Point Positioning) model that incorporates signal-in-space range error (SISRE) residuals and predictions for B2b orbits and clock corrections to achieve seamless, high-precision continuous positioning. In our experiments, we first analyze the characteristics of B2b SISRE for both BDS-3 and GPS. We then evaluate the positioning accuracy of several models, B2b-PPP, EB2b-PPP, PB2b-PPP, EB2bS-PPP, and PB2bS-PPP, through simulated and real dynamic experiments. Here, 'E' indicates the direct utilization of the previous observation corrections from B2b before the signal interruption, 'P' represents B2b prediction products, and 'S' signifies the incorporation of the SISRE residuals. The results show that EB2b-PPP exhibits significant deviations as early as 10 min into a B2b signal interruption. Both PB2b-PPP and EB2bS-PPP demonstrate comparable performances, with PB2bS-PPP emerging as the most effective method. Notably, in real dynamic experiments, PB2bS-PPP maintains positioning accuracy in the E/N directions like B2b-PPP, even after 40 min of signal interruption, ensuring continuous and stable positioning upon signal restoration. This achievement significantly enhances the capability for high-precision continuous positioning based on B2b signals. [ABSTRACT FROM AUTHOR]

The design of conventional digital predistortion (DPD) requires an analogue-to-digital converter (ADC) with a sampling frequency that is multiple times the signal bandwidth, which is extremely challenging for sub-Nyquist sampling systems with undersampled signals. To address this, this paper proposes a neural network (NN)-assisted wideband power amplifier (PA) DPD method for sub-Nyquist sampling systems, wherein a dual-stage architecture is designed to handle the ambiguity caused by subsampled communications signals. In the first stage, the time-delayed polynomial reconstruction method is employed to estimate the wideband DPD nonlinearity coarsely with the undersampled signals with limited pilots. In the second stage, an NN-based DPD method is proposed for the virtual training of the DPD, which learns the up-sampled DPD behavior by taking advantage of the pre-estimated DPD model and the input data signals, which reduces the length of the training sequence significantly and refines the DPD behavior efficiently. Simulation results demonstrate the efficacy of the proposed method in tackling the wideband PA nonlinearity and its ability to outperform the conventional method in terms of power spectrum, error vector magnitude, and bit error rate. [ABSTRACT FROM AUTHOR]

In the process of unconventional oil and gas production, a large number of microseismic signals are generated. These signals are received by geophones deployed on the ground or in wells and used for safety monitoring. The moving-coil geophone is a commonly used geophone, which is widely used for collecting vibration signals. However, the current conventional moving-coil geophones have certain limitations in terms of frequency band range and cannot fully meet the low-frequency requirements of microseismic signals. We studied the structure and material properties of moving-coil geophones to understand the factors that affect their frequency band. In this paper, we use finite element analysis method to perform structural analysis on a 10 Hz moving-coil geophone, and we combine modal analysis and excitation response analysis to obtain its operating frequency range of 10.63–200.68 Hz. We then discuss the effect of the vibrating components of a moving-coil geophone on its operating frequency range. The material properties of the spring sheet mainly affect the natural frequency of the first-order mode (natural frequency, the lower limit of the operating frequency of the geophone), and the material properties of the lead spring mainly affect the natural frequency of the second-order mode (spurious frequency, the upper limit of the operating frequency of the geophone). By analyzing the sensitivity of the material properties of the vibration system parts and selecting more suitable spring sheets and lead spring materials, a lower natural frequency and a higher spurious frequency can be obtained, thereby achieving the purpose of broadening the operating frequency range of the geophone, which is expected to provide help in actual production. [ABSTRACT FROM AUTHOR]

We demonstrate a novel injection-locking effect in oscillators, which is obtained in both the time and frequency domains. The "temporal-locked" oscillator generates an ultra-low phase noise continuous-wave (CW) signal, accompanied by an ordered train of short phase pulses with precise timing, where both signals are phase-locked to an external sinusoidal source. Remarkably, even when the cavity delay drifts, the period of the temporal-locked pulses remains constant. Furthermore, the instantaneous phase and the timing of the minimum and maximum amplitudes within part of the pulse remain approximately constant. These unexpected results stem from the nonlinear effect of strong injection on the waveform of the phase pulses. In particular, this effect leads to the self-adaptation of the instantaneous frequency to delay variations, thereby preserving the periodicity of the pulses. We theoretically show that a simple and general setup can accurately model the pulse propagation within the cavity. We experimentally demonstrate the effect in an optoelectronic oscillator (OEO). The pulse timing inherits the stability of the external CW source. The combination of an ultra-low phase noise CW signal with precisely timed pulses is important for various applications that require accurate measurements in both the time and frequency domains. [ABSTRACT FROM AUTHOR]

For electronics to be wearable, contactless charging and overall deformability are necessary pre-conditions. However, the current heterogeneous integration based on different active materials and separate manufacturing often leads to mechanical mismatch. Here, we report an ultrastretchable all-in-one integrated MXene-based microsystem comprising wireless coils, micro-supercapacitors (MSCs) and strain sensors. The seamless configuration without any connecting interface dramatically improves the structural integrity of the microsystem, and a pre-crumpled structure endows it with superior stretchability. Attributed to these, our MSCs can be wirelessly charged in ~20 s under various types of deformation and are capable of powering strain sensors, responding rapidly to body motion signals. Moreover, the MSCs display a high specific capacitance of 76.82 F cm–3, and superb mechanical stability with 98.5% capacitance retention after biaxial stretching 1000 cycles from 0% to 500% areal strain. Therefore, this work sheds new insights into design and implementation of skin-attachable wireless microelectronics. The authors report a stretchable and integrated energy harvest-storage-application skin-adherent microsystem, by utilizing an all-in-one MXene film simultaneously as micro-supercapacitors, wireless receiver coils and strain sensors. [ABSTRACT FROM AUTHOR]

In this paper, a detailed investigation of deep learning-based speaker detection and localization (SDL) with higher-order Ambisonics signals is conducted. Different spherical harmonic (SH) input features such as the higher-order pseudointensity vector (HO-PIV), relative harmonic coefficients (RHCs), and the spatially-localized pseudointensity vector (SL-PIV), a feature proposed for the first time as an input feature for deep learning-based SDL, are examined using first- to fourth-order SH signals. The trained neural networks, optimized with a single loss function for the combined tasks of detection and localization, are then evaluated in detail for overall SDL performance as well as their performance in the sub-tasks of detection and, particularly, localization. The results are further analyzed in dependence on room reverberation, signal-to-interference ratio (SIR), as well as the number and distances between multiple simultaneously active speakers, utilizing both simulated and measured data. The findings indicate an overall improvement in SDL performance up to third-order Ambisonics for all investigated features, while using fourth-order signals does not yield any further improvement or sometimes even delivers worse results. Notably, the HO-PIV and the SL-PIV, both extensions of the first-order pseudointensity vector (FO-PIV), have proven to be suitable input features. In particular the newly proposed SL-PIV has been found to be the best of the investigated features on third- and fourth-order Ambisonics signals, especially in the most demanding scenarios on measured data, with multiple, closely located speakers and poor SIR. [ABSTRACT FROM AUTHOR]

Background: Identifying bacterial taxa associated with disease phenotypes or clinical treatments over time is critical for understanding the underlying biological mechanism. Association testing for microbiome data is already challenging due to its complex distribution that involves sparsity, over-dispersion, heavy tails, etc. The longitudinal nature of the data adds another layer of complexity - one needs to account for the within-subject correlations to avoid biased results. Existing longitudinal differential abundance approaches usually depend on strong parametric assumptions, such as zero-inflated normal or negative binomial. However, the complex microbiome data frequently violate these distributional assumptions, leading to inflated false discovery rates. In addition, the existing methods are mostly mean-based, unable to identify heterogeneous associations such as tail events or subgroup effects, which could be important biomedical signals. Methods: We propose a zero-inflated quantile approach for longitudinal (ZINQ-L) microbiome differential abundance test. A mixed-effects quantile rank-score-based test was proposed for hypothesis testing, which consists of a test in mixed-effects logistic model for the presence-absence status of the investigated taxon, and a series of mixed-effects quantile rank-score tests adjusted for zero inflation given its presence. As a regression method with minimal distributional assumptions, it is robust to the complex microbiome data, controlling false discovery rate, and is flexible to adjust for important covariates. Its comprehensive examination of the abundance distribution enables the identification of heterogeneous associations, improving the testing power. Results: Extensive simulation studies and an application to a real kidney transplant microbiome study demonstrate the improved power of ZINQ-L in detecting true signals while controlling false discovery rates. Conclusion: ZINQ-L is a zero-inflated quantile-based approach for detecting individual taxa associated with outcomes or exposures in longitudinal microbiome studies, providing a robust and powerful option to improve and complement the existing methods in the field. [ABSTRACT FROM AUTHOR]

The relationship between the multifractal of the resting-state functional magnetic resonance imaging (rs-fMRI) and its parameters still needs to be discovered. So, the primary purpose of this study is to evaluate the effects of repetition time (TR) on rs-fMRI signals, and the relationship between multifractal and session. Our findings revealed that the larger the TR, the more scattered the analysis results of multifractal, and the multifractal increase with the TR between Youths and Adults except for the degree of multifractal. However, it is worth noting that when TR = 1.4 s, the average degree of multifractal is generally greater than TR = 0.645 s and TR = 2.5 s. Furthermore, the reliability decreases with the increase in session numbers, increases with rs-fMRI data length increase, and is higher for the short intervals than long ones. Besides, with the rise in the number of sessions, when the data length is ≥400, the intraclass correlation coefficient (ICC) > 0.5 of the Hurst exponent (HE); when the data length is equal to 808, the ICC > 0.4 of the maximum gradient, and the spectrum width of ICC < 0.3. With the increase of the session interval, when the data length is ≥200, the ICC > 0.4 of the HE; when the rs-fMRI data length is equal to 808, the ICC ≈ 0.4 of the maximum gradient, and the spectrum width and degree of multifractal of ICC < 0.3. The results are of great significance for understanding the relationship between nonlinear dynamic characteristics and parameters of rs-fMRI. [ABSTRACT FROM AUTHOR]

In space gravitational wave detection, the phase information of interfering signals is read out by a phasemeter, typically output sampling at a MHz frequency. To transmit the phase information between space and ground, it must be downsampled; however, spectral aliasing during downsampling will affect the performance of the phasemeter.This paper presents a four-module cascaded downsampling filter (FCDF) with detailed module parameter design. On-board experiments conducted in a phasemeter environment demonstrate that the FCDF achieves a passband attenuation of less than 8.68 × 10 − 6 dB and a stopband attenuation exceeding 160 dB, enabling downsampling from 80 MHz to 3.4 Hz. Additionally, the FCDF offers improved low-frequency noise suppression, which can enhance phasemeter performance. [ABSTRACT FROM AUTHOR]

Most adhesion G protein-coupled receptors (GPCRs) undergo autoproteolytic cleavage during receptor biosynthesis, resulting in noncovalently bound N-terminal fragments (NTFs) and C-terminal fragments (CTFs) that remain associated during receptor trafficking to the plasma membrane. While substantial evidence supports increased G protein signaling when just the CTF is expressed, there is an ongoing debate about whether NTF removal is required to initiate signaling in the context of the WT receptor. Here, we use adhesion GPCR latrophilin-3 (ADGRL3) as a model receptor to investigate tethered agonist (TA)-mediated activation. First, we show that extending the N terminus of the TA in ADGRL3 CTF disrupts G protein signaling. This suggests that if the TA is not fully exposed, it is unlikely to interact with the orthosteric pocket in an optimal manner for G protein activation. Second, we show that when full-length ADGRL3 is expressed in heterologous cells, approximately 5% of the receptor population spontaneously sheds its NTF. We hypothesized that the signaling activity observed for full-length ADGRL3 is largely because of this shedding, which exposes the native TA. To test this hypothesis, we used a full-length cleavage-deficient ADGRL3 mutant. Compared with WT receptor, this mutant lost ~80% of its signaling through Ga13 and showed a much lower level of spontaneous NTF shedding, approximately 20% of that observed for WT receptor. This loss of spontaneous NTF shedding likely explains its diminished signaling activity. These findings suggest that TA-mediated signal transduction by fulllength ADGRL3 requires removal of its NTF. [ABSTRACT FROM AUTHOR]

Cellular adaptation to external signals is essential for biological functions, and it is an important field of interest in systems biology. This study examines the impact of cooperativity on the adaptation response of the Incoherent Feedforward Loop (IFFL) network motif to various signal profiles. Through comprehensive simulations, we studied how the IFFL motif responds to constant and pulse-type signals under varying levels of cooperativity. The results of our study demonstrate that positive cooperativity generally enhances the system's ability to adapt to different signal profiles. Nevertheless, given specific signal profiles, higher levels of cooperativity may decrease the system's adaptability. On the other hand, the adaptive response breaks down for negative cooperativity. For constant signals, increased positive cooperativity leads to a response with higher amplitude, and it accelerates the response time but delays the return time required to settle back down to the pre-stimulus state. Upon signal cessation, high positive cooperativity not only slows the system's response and return times but, in some cases, can lead to a complete temporary halt in response. For the pulse-like signal, cooperativity increases the maximum amplitude of the oscillatory response. These insights highlight the delicate balance between cooperativity and signal profile in cellular adaptation mechanisms involving the IFFL network motif. [ABSTRACT FROM AUTHOR]

Humans achieve skilled actions by continuously correcting for motor errors or perceptual misjudgments, a process called sensorimotor adaptation. This can occur with the actor both detecting (explicitly) and not detecting the error (implicitly). We investigated how the magnitude of a perturbation and the corresponding error signal each contribute to the detection of a size perturbation during interaction with real-world objects. Participants grasped cuboids of different lengths in a mirror-setup allowing us to present different sizes for seen and felt cuboids, respectively. Visuo-haptic size mismatches (perturbations) were introduced either abruptly or followed a sinusoidal schedule. These schedules dissociated the error signal from the visuo-haptic mismatch: Participants could fully adapt their grip and reduce the error when a perturbation was introduced abruptly and then stayed the same, but not with a constantly changing sinusoidal perturbation. We compared participants' performance in a two-alternative forced choice (2AFC) task where participants judged these mismatches, and modelled error-correction in grasping movements by looking at changes in maximum grip apertures, measured using motion tracking. We found similar mismatch-detection performance with sinusoidal perturbation schedules and the first trial after an abrupt change, but decreasing performance over further trials for the latter. This is consistent with the idea that reduced error signals following adaptation make it harder to detect perturbations. Error-correction parameters indicated stronger error-correction in abruptly introduced perturbations. However, we saw no correlation between error-correction and overall mismatch-detection performance. This emphasizes the distinct contributions of the perturbation magnitude and the error signal in helping participants detect sensory perturbations. [ABSTRACT FROM AUTHOR]

The Indo-Pacific region has emerged as a critical geopolitical platform. Can major powers and regional states avoid conflict? This article explores the concept of status signalling to better understand the region. Status signalling aims to demonstrate a state's preferred ranking in international society. By applying this concept to new empirical domains, the article shows how status signalling offers fresh insights into regional trends. As an example of strategic spinning, the emergence of the Indo-Pacific reshapes strategic thinking and diplomatic practice in the 21st century. While countries may engage in military posturing to signal their preferred status, the rising competition in the region is not always a zero-sum game. Countries can signal status by providing international public goods in non-military domains. The United States and China need to find ways to handle the potential problem of status dilemmas. Meanwhile, all countries should prudently manage competing expectations from multiple audiences. [ABSTRACT FROM AUTHOR]

The Indo-Pacific is a laboratory of foreign policy signaling. It has seen a plethora of novel diplomatic phrasings and formats emerging in the recent past – from the adoption of the Indo-Pacific terminology itself, to a series of strategy papers from regional as well as extra-regional governments to varying multilateral naval exercises. Playing host to the rivalry between the US and China that is set to define 21st century world politics, it is not surprising that both major Asian and external powers have intensified their foreign policy signaling towards and within the Indo-Pacific region. What is more puzzling is the simultaneity of often very public signals and their vagueness. In fact, a multipolar Asia replete with interdependencies from safe sea lanes to infrastructure investments and arms supplies is one that is full of ambiguous signaling – raising questions about the reasons for this as well as its consequences and effectiveness. The introduction of this special issue highlights this central feature of signalling in the Indo-Pacific. Moreover, with reference to the rich signalling literature it suggests an understanding of foreign policy signalling outside immediate crises as communication that is costly, public, and intentional for the contributing authors to work with. [ABSTRACT FROM AUTHOR]

Over the past decade, the government of the Republic of Korea showed a puzzling attitude towards foreign policy signalling. Seoul did not demand costly signals from Beijing and Pyongyang to ascertain their cooperative intents. Moreover, Seoul showed eagerness to unilaterally send the rivals costly signals to convey its intention to cooperate. We aim to explain Seoul's engagement in unreciprocated costly signalling that diverges from mainstream theoretical expectations. We argue that the unreciprocated signalling stemmed from Seoul's belief that Beijing and Pyongyang might not know its own cooperative intent, whereas the latter two countries' cooperative intents were already sufficiently clear to Seoul. Therefore, Seoul reasoned that sending costly signals was crucial to convince Beijing and Pyongyang of its trustworthiness whereas such signals from the rivals were unnecessary. To support this argument, we draw on interviews with senior Republic of Korea officials, along with primary and secondary documents available in Korean and English. [ABSTRACT FROM AUTHOR]

When signalling in the Indo-Pacific, India must manage several contradictory imperatives. Signals of resolve that explicitly frame China as a threat or order challenger can raise tensions with this more powerful neighbour. Yet, given India's strategic resourcing needs, some indication of resolve is necessary in order to project 'like-mindedness' with strategic partners – especially the United States – who seek to counter-balance China. Meanwhile, signals of reassurance to the United States and its allies may read as signals of resolve towards China in and of themselves, and/or lead to rhetorical entrapment into alliance-like relations that erode India's strategic autonomy. Since signalling is both purposeful and socially contingent, these complexities are reflected in India's discursive signalling strategy. We argue that India often signals via a mode of indirect speech known as implicature. When states implicate, they convey meaning beyond what is explicitly said, while depriving recipients of the rhetorical material to evidence resolve or reassurance. As a signalling strategy, implicature aims to avoid breaches in India's distinctive social relationships with China and the United States. Signalling through implicature thus manifests as a mode of social hedging, intended to widen the choices of secondary states in the polarised signalling arena of the Indo-Pacific. [ABSTRACT FROM AUTHOR]

Freedom-of-navigation operations (FONOPs) led by the United States have become a prominent policy tool in the South China Sea. These operations, however, have caused much confusion and consternation in the region despite the limited legal purpose that they officially serve. Why? This article departs from existing research by examining FONOPs as a form of signalling. Utilising an original dataset on US FONOPs in the South China Sea, we explain why and how FONOPs are ambiguous signals. Because of the nature of FONOPs using warships, the complexities in the maritime environment, and the irregularity of FONOPs, serious sender–receiver gaps emerge in the South China Sea regarding whether FONOPs signal resolve, coercive intent, and/or intentions to check certain states' broader ambitions. Our analysis reveals that some signalling interpretations of FONOPs in the region are more plausible than others, thus helping to reduce the signalling ambiguity of these operations. [ABSTRACT FROM AUTHOR]

Amid growing strategic competition, regional powers have intensified their engagement with Pacific Island Countries. This article examines Australia's 'Pacific Step-up', a signature foreign policy initiative of the Scott Morrison government (2018–2022), from a signalling perspective. Through the Step-up, Australia sought to affirm its resolve to be partner of choice for Pacific Island Countries. This was not cheap talk but led Canberra to invest substantially in its ties with the region. Despite this and significant prior Australian engagement leading to a bilateral security pact, Solomon Islands' government signed an additional security agreement with China in 2022. How can we explain this sender–receiver gap? I argue that close attention to the agency of domestic actors on the receiver side and the context in which such agency occurs – in this case, an extended history of insecurity in the Pacific country – provides us with analytical leverage when examining concrete instances of signalling. [ABSTRACT FROM AUTHOR]

This paper deals with applying the sliding Fast Fourier Transform analysis to detect voltage dips and swells in modern distribution networks. Significant odd and even voltage harmonics appear during voltage dips and swells, and they can be used to detect these events. Since the voltage waveshape during the dips and swells have the same harmonic content, the separation of these events can be done by calculating the angles of the voltage harmonics at the moment of the event. In the case of voltage swells phase angles of the 1st and the higher order harmonics have the same polarity, while in the case of voltage dips phase angles of the 1st and of the higher order harmonics have the opposite polarity. The presented approach is verified by analyzing mathematical signals and signals measured in real distribution networks with renewable sources. The limitation of the analyzed method is that the amplitude of voltage variation during the dip or swell in a real distribution network cannot be reliably associated with the calculated values of voltage harmonics. This limitation can be overcome by considering the value of 1st voltage harmonic, or RMS voltage value calculated for one cycle or half cycle of the voltage wave. [ABSTRACT FROM AUTHOR]

Politicians' ability to provide national security to the public is deeply enmeshed in conceptions of the state and of leadership. This article incorporates securitization, feminist, and political communication theories to consider whether gendered and militarized conceptions of national security have different effects for politicians who are women and those who are men. Although scholarship suggests that signaling military bona fides—such as invoking one's veteran status—can help politicians claim that certain policies are a matter of national security, we consider whether this ability will be gendered. Relying on two national studies, we find results that are contrary to our original predictions. First, we find that military bona fides do help women be seen as leaders. However, we do not find evidence that bona fides increase the "authority" to identify and address national security threats for any politicians. [ABSTRACT FROM AUTHOR]

These days, as the application of permanent magnet synchronous machines (PMSMs) and drive systems becomes popular, the reliability issue of PMSMs gains more and more attention. To improve the reliability of PMSMs, fault detection is one of the practical techniques that enables the early interference and mitigation of the faults and subsequently reduces the impact of the faults. In this paper, the state-of-the-art fault detection methods of PMSMs are systematically reviewed. Three typical faults, i.e., the inter-turn short-circuit fault, the PM partial demagnetization fault, and the eccentricity fault, are included. The existing methods are firstly classified into signal-, model-, and data-based methods, while the focus of this paper is laid on the signal sources and the signatures utilized in these methods. Based on this perspective, this paper intends to provide a new insight into the inherent commonalities and differences among these detection methods and thus inspire further innovation. Furthermore, comparison is conducted between methods based on different signatures. Finally, some issues in the existing methods are discussed, and future work is highlighted. [ABSTRACT FROM AUTHOR]

Wind turbine gearbox fault diagnosis is critical to guarantee working efficiency and operational safety. However, the current diagnostic methods face enormous restrictions in handling nonlinear noise signals and intricate compound fault patterns. Herein, a compound fault diagnosis method based on modified signal quality coefficient (MSQC) and versatile residual shrinkage network (VRSN) is proposed to resolve these issues. In detail, the MSQC is designed to remove the noise components irrelevant to wind turbine operation status, and it has the ability to balance the denoised effect and signal fidelity. The VRSN is constructed for compound fault diagnosis, and it consists of two heterogeneous residual shrinkage networks. The former is designed to count the number of faults, and the latter is adopted to identify the single or compound fault pattern. Finally, a self-built wind turbine gearbox compound fault test rig is adopted to verify the proposed method's effectiveness. The results demonstrate that the proposed method is competitive in terms of compound fault diagnosis accuracy. [ABSTRACT FROM AUTHOR]

Spoofing detection is critical for GNSS security. To address the issues of low detection rates and insufficient coverage in traditional methods, this study proposes an eye diagram detection method based on the multiscale Canny algorithm with minimum misjudgment probability (EDDM-MSC-MMP). Unlike conventional correlation peak distortion detection techniques, the proposed method uses the MSC-MMP algorithm to perform multiscale edge extraction from the eye diagram generated from the receiver's correlation values. It then calculates the image threshold using minimum misjudgment probability to ensure the accuracy of the eye diagram's edges. This enables the accurate detection of subtle changes in the eye diagram, leading to the better identification of spoofing signals. The results show that the MSC-MMP outperforms traditional edge extraction algorithms by over 0.072 in terms of the optimal dataset scale F score (ODS-F). Compared to signal quality monitoring (SQM) and Carrier-to-Noise Ratio methods, the EDDM-MSC-MMP method increases spoofing detection coverage by over 60%, achieving the highest detection rate in the TEXBAT dataset. Overall, the EDDM-MSC-MMP method improves the reliability and coverage of spoofing detection, providing an effective solution for GNSS spoofing detection. [ABSTRACT FROM AUTHOR]

In recent years, the analysis of signal properties (especially biomedical signals) has become an important research direction. One interesting feature of signals is their potential to be chaotic. This article concerns the issues of classification of real signals or synthetic ones in the context of detecting chaotic properties. In previous works, datasets of synthetic signals were created based on well-known chaotic and non-chaotic dynamical systems. They were published and used to train classifiers. This paper extends the previous studies and proposes a method for obtaining/extracting signals to force classifiers to learn to detect chaos. The proposed method allows the generation of groups of signals with similar initial conditions. The property of chaotic dynamical systems was used here, which consists of the strong dependence of the signal courses on a small change in the initial conditions. This method is based on reconstructing multidimensional phase space and data clustering. An additional goal of the work is to create referential datasets with so-called refined signals using the described method and to make them publicly available. The usefulness of the new datasets was confirmed during a simple experiment with the usage of the LSTM neural network. [ABSTRACT FROM AUTHOR]

The development of optical methods for surface vibration measurements is currently of great interest. We propose a modified tandem low-coherence technique that utilizes the phase information of the low-coherence signal to detect surface vibrations. The resolution of this scheme is less than 1 nm for a 20 kHz bandwidth. The proposed technique is not just limited to measurements of surface vibrations, but it can also be used for interferometric fiber-optic sensors. [ABSTRACT FROM AUTHOR]

Fetal electrocardiogram (FECG) signals directly reflect the electrical activity of the fetal heart, enabling the assessment of fetal cardiac health. To effectively separate and extract FECG signals from maternal abdominal electrocardiogram (ECG) signals, this study proposed a W-shaped parallel network, termed Attention R2W-Net, which consisted of two Attention R2U-Nets. In the encoder and decoder, recurrent residual modules were used to replace feedforward convolutional layers, significantly enhancing feature representation and improving noise suppression. Additionally, attention gates were used to replace skip connections, enabling precise correction of low-resolution features using deep features and further improving model performance. The decoders at both ends of the network were utilized to reconstruct FECG and MECG signals, respectively. The algorithm was validated using simulated and real datasets, achieving F1 scores of 99.17%, 98.03%, and 97.08% on the ADFECGDB, PCDB, and NIFECGDB datasets, respectively, demonstrating superior performance in both subjective visual effects and objective evaluation metrics. Attention R2W-Net's ability to extract robustly and accurately FECG signals, even in complex noisy environments, make it a reliable tool for FECG extraction. The proposed method's efficiency and accuracy highlight its potential for widespread clinical application, contributing to improved early diagnosis of fetal cardiac abnormalities. [ABSTRACT FROM AUTHOR]

Chip rate estimation for direct-sequence spread spectrum (DSSS) signals plays a crucial role in signal detection and interference identification in non-cooperative wireless communication systems. However, accurate chip rate estimation is difficult in low signal-to-noise ratio (SNR) environments due to the influence of noise and channel fading. To address this problem, an improved chip rate estimation method, based on a time-reassigned multisynchrosqueezing transform energy squeeze, for DSSS signals is proposed for low SNR conditions. In this method, we explain how to choose an appropriate wavelet function and concentrate the wavelet coefficients on the energy ridge by reordering time details. This enhances the time resolution of the signal energy, reduces noise interference, and improves the accuracy of chip rate estimation for DSSS signals. To validate the proposed method, we compared the effects of different information code lengths, spread spectrum code lengths, spread spectrum code sequences, and modulation schemes on chip rate estimation performance with traditional methods. Additionally, we applied the method to real DSSS signal data to demonstrate its feasibility. Simulation examples and measurements demonstrate the reliability of the proposed method in low SNR environments. [ABSTRACT FROM AUTHOR]