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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]

In this study, a system for measuring the positional accuracy of industrial robots using 3D vision and networking technology has been proposed. The 3D vision system comprises a charge-coupled device (CCD) module, a reference sphere module, and a signal processing module. The reference sphere module serves as the sensing object, while the CCD module captures displacement images of the reference sphere module. The signal processing module receives and processes signals from the CCD module. It utilizes a self-developed Visual C + + interface to calculate the X, Y, Z, θx, and θy (five-degree-of-freedom, 5-DOF) positional accuracy of the industrial robot. Experimental results demonstrate that the linear accuracy (X, Y, Z) and angular accuracy (θx, θy) of the 3D vision system are approximately 3 μm and 0.15°, respectively. Additionally, a networking architecture connects the controller of the machine tool with the industrial robot to enable synchronized motion path planning. The industrial robot can be calibrated using the high-precision machine tool equipped with the 3D vision-based positional accuracy measurement system. [ABSTRACT FROM AUTHOR]

Summary: Traditional Orthogonal Multiple Access (OMA) and spectrum sharing methods struggle to provide the diverse quality of service (QoS) demands for enhanced mobile broadband (eMBB), ultra‐reliable low latency communications (uRLLC), and massive machine type communications (mMTC) leading to suboptimal performance and service quality degradation. Single‐carrier‐non‐orthogonal multiple access (SC‐NOMA) appears to be a more optimized solution. It can serve multiple users simultaneously on the same time‐frequency resources. This approach offers both enhanced spectrum efficiency and meets the QoS requirements for the coexistence of eMBB, uRLLC, and mMTC. However, SC‐NOMA has some drawbacks. Decoding a user's signal involves a complex successive interference cancellation (SIC) process that gets harder with more users causing delays and errors. Additionally, strong user signals can interfere with weaker ones, limiting the number of users per channel. In order to overcome the drawbacks associated with OMA and SC‐NOMA, this paper introduces a new method called user‐paired NOMA (hybrid NOMA). Hybrid NOMA adopts a strategic approach, employing two user pairing techniques: near‐far/far‐near (NF‐FN) and near‐near/far‐far (NN‐FF). NF‐FN pairing prioritizes users with similar signal strengths but different distances from the base station. This minimizes interference for the weaker user during SIC. NN‐FF pairing, on the other hand, groups users with similar signal strengths and proximity. This approach further simplifies SIC and minimizes potential interference altogether. The simulation results demonstrate trade‐offs between eMBB and uRLLC performance. OMA suffers with dedicated resource allocation, while SC‐NOMA balances performance but experiences interference. NN‐FF prioritizes eMBB and offers best latency, while NF‐FN prioritizes uRLLC with high spectral efficiency but suffers from higher latency. Finally, by providing a thorough grasp of how hybrid NOMA resource allocation works to improve the performance of various use cases, this research makes a significant contribution to the field of 5G spectrum optimization. [ABSTRACT FROM AUTHOR]

In this paper, an adaptive quantized output feedback event‐triggered (ET) distributed consensus control approach for an uncertain nonstrict nonlinear switched fractional‐order (FO) multi‐agent system (SFOMAS) subject to communication limitation is proposed. By relying on the common Lyapunov function method, the switch signals are arbitrarily, and no information regarding the switching instants is required. The consensus error of each agent has its own asymmetric time‐varying constraints (ATCs). By adopting the common barrier Lyapunov function (BLF), violation of these constraints is prevented. For each agent, different input nonlinearities can be considered in different modes, and the controllers need no information about their types and characteristics. The communication burden between outputs sensors and the controllers is reduced by applying uniform‐logarithmic‐hysteresis quantizers to the outputs signals. By using FO filters, which can be considered as a FO version of the dynamic surface control (DSC) method, the so‐called explosion of complexity is avoided and the discontinuity problem of FO derivatives of virtual controllers due to outputs quantization is resolved. Observers are designed to estimate the unmeasured states. Also, function approximators (FAs) are employed to approximate uncertainties. A novel lemma that correlates observer states to consensus errors and their constraints, FO filters errors, adaptive parameters and backstepping error surfaces, has been proposed to establish the observer stability. To reduce the communication burden between the controllers and actuators, relative threshold ET mechanisms have been applied to control signals. The combination problem of unmeasured states with the mentioned input constraints for SFOMASs is coped with another novel lemma. Utilizing the common Lyapunov functions (CLFs) and the backstepping technique, virtual controllers, adaptive law and control signal for each agent have been designed and boundedness of closed‐loop signals and avoidance of Zeno behavior have been proved. The effectiveness of the proposed control scheme is demonstrated through a simulation study. [ABSTRACT FROM AUTHOR]

The traditional Nussbaum‐type functions encounter challenges when extended to systems with multiple unknown control directions, as the coupling between the Nussbaum‐type function and Nussbaum‐type gain may lead to mutual elimination. To address this issue, a novel Nussbaum‐type function is introduced to handle multiple unknown control directions for stochastic systems. The stability of the proposed Nussbaum‐based design can be guaranteed using the Lyapunov analysis. To conserve computational resources, a static composite event‐triggered mechanism is integrated with intermittent feedback in the Nussbaum‐based design. In contrast to conventional event‐triggering mechanisms that depend solely on control signals, the presented design incorporates tracking errors into the event‐triggering conditions. Moreover, to further alleviate computational burdens, we further develop a dynamic composite event‐triggered mechanism. With the overall design scheme, bounded tracking errors and reduced computational burden can be ensured. Simulation examples validate the efficacy of the proposed adaptive Nussbaum composite event‐based robust control design. [ABSTRACT FROM AUTHOR]

Spoofed signal interference poses a serious threat to the security of Global Navigation Satellite Systems (GNSS). In order to effectively detect spoofing signals, this paper proposes a spoofing signal detection method based on the Transformer model in the signal capture phase. When a spoofed signal is added, the capture matrix of the receiver changes. The method takes the capture matrix near the relevant peak as the data set for training the Transformer model to improve the model's ability to recognize the features of the capture matrix, and then uses the trained model to identify the capture results and get the discriminative result of whether there is deception joining. Subsequently, the trained model is embedded into the navigation receiver, and the receiver configuration is modified so that it continuously performs signal capture over the whole data and detects spoofing signals on the capture results. The experimental results show that the spoofing signal detection method based on the Transformer model has a higher detection accuracy compared to other deep learning models. For data with different search steps, its detection accuracy can reach more than 95%. When the chip delay of the spoofed signal is greater than half a chip, the detection accuracy tends to be close to 100%. For online open-source spoofing datasets, the detection algorithm can still obtain excellent detection results. The spoofing signal detection technique based on the Transformer model is of great significance to improve the security and robustness of the navigation system and has the prospect of wide application. [ABSTRACT FROM AUTHOR]

In the field of aerospace, real-time and accurate monitoring of the milling state is of great significance for improving processing quality and processing efficiency. Relying on milling force signals to monitor tool wear state has problems such as high cost and limited size of machined parts. Aiming at the above problem, a milling cutter wear condition monitoring method based on spindle current is proposed. Firstly, based on the linear correlation between the milling force and the current increment theory, the milling experiment was carried out. The characteristic variation trend and spectral characteristics of the milling force signal and spindle current signal under the change of spindle speed, feed rate, and radial cutting width are analyzed. The cosine similarity demonstrates that the similarity of the root mean square values of the two is 0.9865, 0.9943, and 0.9421, respectively, and the changing trend of the spectral amplitude is consistent. In the iSESOL platform, a self-learning feature boundary model is built from learning data, signal interception, root mean square feature extraction, drawing boundary, and threshold judgment to monitor the wear state of the milling cutter online. Finally, the data in each wear stage are selected to verify the model, and the validity of the model is proved by setting the threshold beyond the boundary and the alarm trigger condition, in real-time, and accurately monitoring the wear state of the milling cutter online. [ABSTRACT FROM AUTHOR]

We mainly study the negligibility of haptotaxis effect on global existence, boundedness and convergence of classical solutions to a four-component chemotaxis-haptotaxis system with indirect signal production: { u t = Δ u − χ ∇ ⋅ (u ∇ v) − ξ ∇ ⋅ (u ∇ w) in Ω × (0 , ∞) , v t = Δ v − v + m in Ω × (0 , ∞) , m t = Δ m − m + u in Ω × (0 , ∞) , w t = − v w + η w (1 − w) in Ω × (0 , ∞) , in a bounded and smooth domain Ω ⊂ R n (1 ≤ n ≤ 5) with nonnegative parameters χ , ξ , η , nonnegative regular initial data (u 0 , v 0 , m 0 , w 0) and homogeneous Neumann boundary conditions. When n ≤ 3 , it is proven that solutions to the corresponding Neumann initial-boundary value problem exist globally in time for any η ≥ 0 and remain bounded for small η ≥ 0 ; when n = 4 , η = 0 and Ω is a ball centered at the origin, global boundedness of radially symmetric solutions is shown under ‖ u 0 ‖ L 1 (Ω) < (8 π) 2 χ ; and when n ∈ { 4 , 5 } , η = 0 and χ = 0 , global boundedness of solutions is shown. In either case, the global bounded w -solution component is shown to decay exponentially in W 1 , ∞ (Ω) and the global bounded (u , v , m) -solution component converges exponentially in L ∞ (Ω) to that of the corresponding indirect chemotaxis-only model for suitably small χ ≥ 0. This project incorporates a biological mechanism modeling indirect signal production in chemotaxis-haptotaxis models and our results extend the previous work of Fujie & Senba (2017) [11] on indirect chemotaxis-only system (w ≡ 0) to indirect chemotaxis-haptotaxis one, revealing that the effect of haptotaxis can be neglected even in a chemotaxis system with indirect signal production. Furthermore, our findings demonstrate that indirect chemotaxis mechanism has positive effect on boundedness and enlarges critical blow-up mass comparing to the existing result of Jin & Xiang (2021) [19] on the corresponding direct chemotaxis-haptotaxis model, providing a further understanding about this indirect mechanism in chemotaxis-haptotaxis settings. [ABSTRACT FROM AUTHOR]

ABSTRACT This article presents an anti‐disturbance constrained control scheme for the pitch channel of autonomous underwater gliders subject to internal and external disturbances, as well as actuator saturation. First, the integral control technique is employed to develop a disturbance observer to estimate the overall effect of possible uncertainties and disturbances on the nominal vehicle model, which is referred to as the mismatched lumped disturbance. Then, a disturbance rejection control law is constructed based on the disturbance observer. Following that, a straightforward anti‐windup modification is proposed to handle potential input constraints by using the tracking back calculation technique. Specifically, the difference between saturated and unsaturated control input signals is utilized to create a feedback signal that addresses the disturbance observer input, thereby alleviating system windup during actuator saturation events. Furthermore, the stability of the overall closed‐loop system is established in term of the Lyapunov stability theorem, demonstrating that the tracking error is ultimately bounded. Compared with some existing anti‐windup control schemes, the suggested approach offers intuitive design guidelines, resulting in a simple controller that can be easily implemented. Finally, the effectiveness and robustness of the proposed control scheme are verified through simulation results. [ABSTRACT FROM AUTHOR]

1D NOESY with presaturation (NOESY-presat) is the most popular water suppression method. When D2O solutions of L-phenylalanine or L-valine were measured using NOESY, the absolute concentration biases increased with longer mixing and evolution times, reaching a maximum of 54% with respect to the preparation values. At mixing and evolution times of 0 ms and 0 µs, respectively, the absolute concentration biases were reduced to less than 3%. The remaining biases were caused by the off-resonance effect, which was prevented by setting the frequency offset to an intermediate value between the analyte and internal standard 3-(trimethylsilyl)-1-propanesulfonic acid-d6 (DSS-d6) signals. Nevertheless, NOESY-presat gave maximum absolute biases of 26% and 11% for glycine and maleic acid concentrations, respectively, in three H2O/D2O (90/10 vol%) solutions. The proposed NOESY-dual-presat method reduced the absolute biases to below 4%. However, water suppression was insufficient but was improved by setting the frequency offset to the same as the presaturation offset with the H2O signal, although the absolute biases rose to 5 to 13%. Quantitative analyses using NOESY-presat and NOESY-dual-presat require careful consideration of the off-resonance effect. [ABSTRACT FROM AUTHOR]

ABSTRACT Since the microgrid lacks inertia compared to the conventional grid with synchronous generators, the microgrid is unable to address the frequency change issues resulting from the integration of large‐scale distributed generation. Due to the ability to provide virtual inertia, generalized droop control (GDC) and virtual synchronous generator (VSG) control are considered effective solutions for improving frequency regulation. However, in response to external frequency disturbances, the grid‐connected inverters may experience a significant transient active power overshoot caused by GDC and VSG. In this paper, the GDC is used as the fundamental control architecture, and then the small signal models of the GDC and VSG are compared and analyzed under various disturbances. A reduced‐order method for the GDC model is proposed to simplify the analysis of GDC. Additionally, GDC adaptive inertia (GDCAI) and adaptive inertia for operation mode switching (AIOMS) are proposed to mitigate frequency fluctuations and improve active power response. The effectiveness of the two control strategies is verified by MATLAB/Simulink simulation and StarSim hardware‐in‐the‐loop (HIL) experiment. [ABSTRACT FROM AUTHOR]

Non-linear and non-stationary signals are analyzed and processed in the time-frequency (TF) domain due to interpretation simplicity. Wigner-Ville distribution (WVD) delivers a very sharp resolution of non-stationary signals in the TF domain. However, cross-terms occur between true frequency modes due to their bilinear nature. Masked WVD reduces cross-terms by multiplying the time-frequency representation (TFR) obtained from the WVD with the TFR of the same signal obtained from another method, while S-transform (ST) is a linear signal analysis method that combines the advantages of short-time Fourier transform (STFT) and wavelet transform (WT). This paper investigated WVD masking with both original and modified STs to compare their cross-term reduction results. Moreover, additional parameters are integrated into the ST to deliver the better resolution of the ST and, consequently, more satisfactory cross-term reduction. However, these parameters must be carefully optimized by expert users in their respective application fields. [ABSTRACT FROM AUTHOR]

This study aimed to investigate the disruptive behaviors exhibited by Grade 7 students at Baltazar Nicor Valenzuela National High School, exploring the reasons behind these behaviors, the experiences they faced, how they coped with them, and their perspectives on their situations. Employing a descriptive quantitative approach using pretest and posttest methods, the study involved Grade 7 students at the school. Through in-depth interviews, observations, and survey questionnaires, it was found that the participants had significant experiences and challenges, including struggling with various disruptive behaviors among their classmates. The findings also revealed that Grade 7 students managed these challenges by ignoring their classmates and utilizing the PROJECT PSIS (Proximity control, Signal interference, Ignoring, and Student arrangement) strategy, as well as maintaining dedication and self-discipline. Ultimately, the study emphasized the need for support from parents, teachers, and the entire school community to mitigate these behaviors. [ABSTRACT FROM AUTHOR]

In this research we address the ongoing debate about the existence of the glass‐cliff phenomenon by investigating boundary conditions and mechanisms influencing its persistence and decline. Drawing on signalling theory, we hypothesize that the glass‐cliff's presence fluctuates with the clarity of signals associated with appointing women board members at various stages of quota policy implementation. In Study 1, we analyzed a dataset of 258 board appointments in German‐listed companies from 2003 to 2020. We found that women executives were more likely to be appointed following periods of declining performance during Stage 1 (pre‐quota announcement) and Stage 3 (post‐quota enforcement), but not in Stage 2 (post‐announcement, pre‐enforcement). In Study 2, an experiment with 476 respondents, we tested for changes in signal clarity as an underlying mechanism. Results indicate that signal clarity associated with appointing women following performance decline is influenced by quota policies. Signal clarity was highest during stages 1 and 3, but diminished in Stage 2. These findings support the signalling explanation for the glass‐cliff, highlighting that its occurrence is influenced by country‐level policies and emphasizing that the symbolic value of appointing women to board positions as indicators of change depends on the clarity of these signals. [ABSTRACT FROM AUTHOR]

Recently, increasing attention has been paid to exploring the unique characteristics of newly emerged organic photoelectrochemical transistors (OPECT) for biological application and neuromorphic engineering due to their effectiveness for light‐driven ionic regulation of channels interfaced with rich biochemical reactions. The observation of interesting signaling reversion is reported—the realization of dual‐directional signaling with enhanced signal resolution—enabled by porous coordination networks (PCN)‐134(Fe) in the presence of varying H2O2 concentrations, which is totally different from exiting unidirectional signaling in OPECT. The underlying mechanism of such behavior is attributed to the change in the polarity of the gate photocurrent and is explained from the perspective of potential distribution. The practical application of this device is then studied by detecting the phorbol myristate acetate (PMA)‐induced secretion of H2O2 from three kinds of human breast cells. This study features the realization of dual‐directional signaling, which is expected to catalyze a new category of OPECT operation with unknown possibilities. [ABSTRACT FROM AUTHOR]

ABSTRACT This paper presents a novel angle track converter for sinusoidal encoders. These encoders provide electronic signals in which the position is encoded in sinusoidal form. This work aims to reduce the complexity and enhance the conversion speed of the sinusoidal‐to‐angle demodulation system. Considering the periodicity of sine and cosine signals (SCSs), the full range [0,2π)$$ \left[0,2\pi \right) $$ is evenly divided into eight segments to determine the coarse angle. According to the specific coarse angle segment, the SCSs are reshaped for proceeding demodulation. Then a fine angle is derived from reshaped signals based on division and arctangent algorithm. Division operation is achieved by a capacitor digital‐to‐analog converter, dynamic comparator, and successive approximation register. The arctangent value is obtained from the division result with the compensation by a small‐size look‐up table. The new converter fabricated in 0.18‐μ$$ \upmu $$m BCD technology occupies an active area of 0.16 mm2 and consumes 1.5 mW at the sample rate 10 MHz. The measured maximum error is 1.8°, in the full range. Without analog‐to‐digital converters and no nonlinear operation unit, the proposed angle track converter has a significant advantage in cost, speed, and efficiency. [ABSTRACT FROM AUTHOR]

In this paper, we propose a novel scan driver combined with a logic circuit using amorphous indium‐gallium‐zinc‐oxide (a‐InGaZnO) thin‐film transistors (TFTs) in order to enhance the electrical stability and reduce power consumption in display panels. The latest mobile displays with high resolution and refresh rates consume more battery power, which inevitably limits portability and usability. The proposed scan driver can mask the signal by combining the output stage with a logic circuit, thereby blocking the output pulse for static images. This allows the display panel to operate in a partial driving mode depending on the display content. Due to the masking of the scan driver's output pulses, the connected pixel circuits are consistently maintained in the same state as the previous frame, leading to a lower refresh rate and reduced power consumption. Furthermore, by constructing additional control signals, the proposed scan driver can operate stably in depletion mode under a ∆VTH = −3 V. [ABSTRACT FROM AUTHOR]

The degree of correlation between the sounds received by the ears significantly influences the spatial perception of a sound image. Audio signal decorrelation is, therefore, a commonly used tool in various spatial audio rendering applications. In this paper, we propose a multi-channel extension of a previously proposed decorrelation method based on generative adversarial networks. A separate generator network is employed for each output channel. All generator networks are optimized jointly to obtain a multi-channel output signal with the desired properties. The training objective includes a number of individual loss terms to control both the input-output and the inter-channel correlation as well as the quality of the individual output channels. The proposed approach is trained on music signals and evaluated both objectively and through formal listening tests. Thereby, a comparison with two classical signal processing-based multi-channel decorrelators is performed. Additionally, the influence of the number of output channels, the individual loss term weightings, and the employed training data on the proposed method's performance is investigated. [ABSTRACT FROM AUTHOR]

Smartphone-based location estimation technology is becoming increasingly important across various fields. Accurate location estimation plays a critical role in life-saving efforts during emergency rescue situations, where rapid response is essential. Traditional methods such as GPS often face limitations in indoors or in densely built environments, where signals may be obstructed or reflected, leading to inaccuracies. Similarly, fingerprinting-based methods rely heavily on existing infrastructure and exhibit signal variability, making them less reliable in dynamic, real-world conditions. In this study, we analyzed the strengths and weaknesses of different types of wireless signal data and proposed a new deep learning-based method for location estimation that comprehensively integrates these data sources. The core of our research is the introduction of a 'matching-map image' conversion technique that efficiently integrates LTE, WiFi, and BLE signals. These generated matching-map images were applied to a deep learning model, enabling highly accurate and stable location estimates even in challenging emergency rescue situations. In real-world experiments, our method, utilizing multi-source data, achieved a positioning success rate of 85.27%, which meets the US FCC's E911 standards for location accuracy and reliability across various conditions and environments. This makes the proposed approach particularly well-suited for emergency applications, where both accuracy and speed are critical. [ABSTRACT FROM AUTHOR]

The underground detection environment in coal mines is complex, with numerous interference sources. Traditional ground-penetrating radar (GPR) methods suffer from limited detection range, high noise levels, and weak deep signals, making it extremely difficult to accurately identify geological structures without stable feature feedback. During research, it was found that the detection energy of the same target significantly changes with the antenna direction. Based on this phenomenon, this paper proposes a geological radar advanced detection method using spatial scanning. This method overcomes constraints imposed by the underground coal mine environment on detection equipment, enhancing both detection range and accuracy compared to traditional approaches. Experiments using this method revealed pea-shaped response characteristics of planar geological structures in radar images, and the mechanisms behind their formation were analyzed. Additionally, this paper studied the changes in response characteristics under changes in target inclination, providing a basis for understanding the spatial distribution of geological structures. Finally, application experiments in underground coal mine environments explored the practical potential of this method. Results indicate that, compared to drilling data, this method achieves identification accuracies of 91.88%, 90.42%, and 78.72% for the depth and spatial extent of geological structures, providing effective technical support for coal mining operations. [ABSTRACT FROM AUTHOR]

The BeiDou Navigation Satellite System (BDS-3) has officially provided services worldwide since July 2020. BDS-3 has added new signals for B1C, B2a and B2b based on old BDS-2 B1I and B3I signals, which brings opportunities for achieving high-precision time transfer. In this research, the BDS-3/BDS-2 combined penta-frequency common-view (CV) single-differenced (SD) precise time transfer model is established with B1I, B3I, B2I, B1C, B2a and B2b signals, including dual-, triple-, quad- and penta-frequency (abbreviated as DF, TF, QF and PF) ionosphere-free (IF) combination CV SD models. Taking four long baseline time links (from 637.6 km to 1331.6 km) as examples, the accuracy and frequency stability of the BDS-3/BDS-2 combined DF, TF, QF and PF SD time transfer models were evaluated. The experimental results show that the frequency stability of the TF, QF and PF SD models were improved by 2.5%, 5.3% and 8.5%, on average, over the DF SD model. Compared with the traditional DF (B1I/B3I IF combination) SD model, the standard deviation (STD) of the multi-frequency SD model was reduced by 5.9%, on average, and the frequency stability was improved by 4.0% on average, which had the most apparent effect on the improvement of short-term frequency stability. Specifically, the DF1 (B1C and B2a DF IF combination), TF1 (B1C, B2a and B2b TF IF combination), QF1 (B1C, B1I, B2a and B2b QF IF combination) and PF4 (B1C, B1I, B2a, B2b and B3I PF IF combination) SD models had better performance in timing, and the PF4 SD model had the best performance. Considering that the PF4 (one PF signal IF combination) SD model does not require an estimated inter-frequency bias and that its noise factor is minor compared with the PF1 (four DF signal IF combination), PF2 (three TF signal IF combination) and PF3 (two QF signal IF combination) SD models, we recommend the PF4 SD model for multi-frequency time transfer and the use of the PF2, PF2 or PF3 SD model to supplement the PF4 SD model in cases of penta-frequency observation loss. [ABSTRACT FROM AUTHOR]

Many data analysis methods actually combine optimization of several criteria. In this paper, a framework is offered for categorizing such multi‐criteria methods. In particular, it categorizes multiset and three‐way analysis methods as well as penalized methods and combinations thereof. The framework aims to stimulate critical evaluation of methods and reflection on the purpose of methods and, by signaling gaps, to help the development of new data analysis methods. [ABSTRACT FROM AUTHOR]

This work presents a methodology for controlling a quadrotor vehicle in both regulation and trajectory tracking tasks when the system is affected by endogenous and exogenous disturbances. In the proposed approach, the quadrotor is driven by a second-order variable-gain sliding mode controller (VG-SMC), which includes a state-dependent variable-gain that allows enhancing the controller performance against disturbances. Besides, the proposed controller achieves finite-time convergence of the position and orientation error signals and their time derivatives. The performance of the closed-loop system is assessed by comparing it with a standard sliding mode controller whose control objective is to track two optimal smooth reference signals. The comparison between both controllers considers the undisturbed and the perturbed cases. Numerical simulations and experimental results demonstrate that the proposed VG-SMC controller provides better overall closed-loop results than those obtained by a fixed-gain sliding mode controller, despite the presence of disturbances. [ABSTRACT FROM AUTHOR]

In recent years, diversified measurements reflect the system dynamics from a more comprehensive perspective in system modeling and analysis, such as scalars, waveform signals, images, and structured point clouds. To handle such multimodal structured high-dimensional (SHD) data, combining a large amount of data from multiple sites is necessary (i) to reduce the inherent population bias from a single site and (ii) to increase the model accuracy. However, impeded by data management policies and storage costs, data could not be easily shared or directly exchanged among different sites. Instead of simplifying or facilitating the data query process, we propose a federated multiple tensor-on-tensor regression (FedMTOT) framework to train the individual system model locally using (i) its own data and (ii) data features (not data itself) from other sites. Specifically, federated computation is executed based on alternating direction method of multipliers (ADMM) to satisfy data-sharing requirements, while the individual model at each site can still benefit from feature knowledge from other sites to improve its own model accuracy. Finally, two simulations and two case studies validate the superiority of the proposed FedMTOT framework. [ABSTRACT FROM AUTHOR]

We demonstrate an all-fiber oscillator with high optical-to-optical efficiency using laser diodes working at 915nm as the pump sources to reduce the demand for thermal management. When the output power of the bidirectional pumped oscillator is 1.16kW, the optical-to-optical efficiency is as high as 75.4%. In this working state, the output characteristics of the oscillator are observed. The Raman suppression ratio is 41.23dB and the beam quality factor Mx2 = 1.14, My2 = 1.29. Analyzing the time trajectory of the highest power output, there are no significant characteristic peaks in the time domain signal and the frequency domain signal, which indicates that the oscillator has good stability.Improving the output characteristics of the 915nm pumping lasers has a positive significance for the application of non-strict ambient temperature control. [ABSTRACT FROM AUTHOR]

Existing unconventional intersection designs can enhance the capacity of intersections to deal with repaid pressure on urban commuting, whereas they force vehicles to multi-stop and reorganize, resulting in safety risks and high fuel consumption. This paper proposes the Intermittent Lane Intersection (ILI) that combines the advantages of variable lane intersection and CTE (Combining the tandem control and exit lanes for left-turn control). An integrated optimization model is established to obtain the optimal geometric and signal control parameters, and a homothermic genetic algorithm is used to solve the model. Then, the application of ILI in different traffic demands of the Tianfu Third Street intersection is analyzed. Compared with the benchmark design (TI, CTE, and CTE with signal coordinated control), ILI can effectively reduce intersection delay, fuel consumption, and parking times. Additionally, ILI has great application superiority when the traffic arrival rate is [1500,1700] and the left-turn ratio is [0.40,0.60]. [ABSTRACT FROM AUTHOR]

Neuronal information processing depends on converting membrane depolarizations into compartmentalized biochemical signals that can modify neuronal activity and structure. However, our understanding of how neurons translate electrical signals into specific biochemical responses remains limited, especially in the soma where gene expression and ion channel function are crucial for neuronal activity. Here, I emphasize the importance of physically compartmentalizing action potential‐triggered biochemical reactions within the soma. Emerging evidence suggests that somatic endoplasmic reticulum–plasma membrane (ER‐PM) junctions are specialized organelles that coordinate electrical and biochemical signaling. The juxtaposition of ion channels and signaling proteins at a prominent subset of these sites enables compartmentalized calcium and cAMP‐dependent protein kinase (PKA) signaling. I explore the hypothesis that these PKA‐containing ER‐PM junctions serve as critical sites for translating membrane depolarizations into PKA signals and identify key gaps in knowledge of the assembly, regulation, and neurobiological functions of this somatic signaling system. [ABSTRACT FROM AUTHOR]

Drawing upon empirical evidence this article explains that, as the US-China Great Power Competition intensifies, New Zealand – a small state in the South Pacific – has shifted its view of Beijing from a potential security partner to a revisionist actor challenging the regional status quo and the international rules-based order that Wellington repeatedly declares is critical to its long-term security. China's rise and assertive behaviour is placing structural pressure on New Zealand to react and altered its threat assessment of Beijing. This article reveals this by detailing New Zealand's balancing strategy in the security domain vis-a-vis China from 2010. This includes an initial phase of pre-balancing through deepened ties with Washington, then transition to active balancing via acquisition of advanced aircraft, space co-operation, joint naval manoeuvres, and initiatives in the Pacific. A suite of new strategy documents released by the New Zealand government in August 2023 - and statements made by the new conservative National Party-led coalition government in 2024 - signals that balancing is set to continue and portends the rejuvenation of the NZ Defence Force (which has been neglected and under-resourced in recent times). New Zealand's potential membership of Pillar 2 of the AUKUS security pact is considered, and how Wellington is presently managing its relationships with the US and China within a broader asymmetric hedging strategy. The article concludes that if China's behaviour demonstrably changes, so too may Wellington's assessment of the China threat and, therefore, Wellington's response. It also outlines area where additional research could prove fruitful. [ABSTRACT FROM AUTHOR]

The use of high‐pitched auditory signals by species communicating alongside noisy streams has been often considered an adaptation, yet studies testing this hypothesis have yielded inconclusive results. The major challenge has been to quantify the proportion of across‐species signal variation that could be attributed to either common history (phylogenetic load) or adaptation. We further advance in this approach by comparing the phylogenetic load between different components of anuran calls. Because stream noise allegedly represents a stronger selective pressure for call frequency than for call temporal traits, we predicted a weaker phylogenetic signal in call frequency, particularly in the taxa that breed alongside streams. We first built a phylogenetic hypothesis using four mitochondrial genes on each of three clades: the genus Hyloscirtus and the family Centrolenidae, which call alongside streams and the subfamily Phyllomedusinae, known to call at lentic water bodies. In parallel, we compiled data on the advertisement calls of 154 species and used them to calculate Blomberg's K values as a proxy for the phylogenetic load (signal) of the call traits. The phylogenetic signal was weaker in spectral than in temporal call traits within the Hyloscirtus calls and weak or absent in both spectral and temporal components of Phyllomedusine calls. Against our expectations, the phylogenetic signal was strong in call frequency, but absent in call temporal components of the centrolenid calls. Our results support uncoupled evolution between spectral and temporal components of anuran calls. They also indicate that the selective role of abiotic noise varies among taxa and that other factors must be invoked to fully understand among‐species variation in advertisement calls. [ABSTRACT FROM AUTHOR]

The paper presents evidence on the relationship concerning military spending among Southeast Mediterranean countries (Greece – Turkey, Israel – Egypt, Israel – Turkey) over the period 1962–2020. We account for the presence of nonlinearities in the bilateral relationships of defence spending by applying Threshold Autoregressive methodologies and utilize kink regression analysis to detect the existence of a country's military spending threshold that signals a threat to another country of the region. Our empirical results show: First, there is a nonlinear strategic interaction between the countries examined, in the sense that their defence spending policy is cointegrated. Second, there is no arms race among the countries examined, but only unilateral effects. Third, there is consistent evidence of a possible military spending equilibrium, in the absence of friction between the countries involved (peace threshold). Our findings have important policy implications as they indicate, first, that each country in the region should not determine its level of military spending considering only operational factors, but also considering the signaling of its military spending on its neighboring countries and, second, that there is space for peaceful solutions regarding disputes in the Southeast Mediterranean region. [ABSTRACT FROM AUTHOR]

Every day, we encounter far more information than we could possibly remember. Thus, our memory systems must organize and prioritize the details from an experience that can adaptively guide the storage and retrieval of specific episodic events. Prior work has shown that shifts in internal goal states can function as event boundaries, chunking experiences into distinct and memorable episodes. In addition, at short delays, memory for contextual information at boundaries has been shown to be enhanced compared with items within each event. However, it remains unclear if these memory enhancements are limited to features that signal a meaningful transition between events. To determine how changes in dynamic goal states influence the organization and content of long-term memory, we designed a 2-day experiment in which participants viewed a series of black-and-white objects surrounded by a color border on a two-by-two grid. The location of the object on the grid determined which of two tasks participants performed on a given trial. To examine if distinct types of goal shifts modulate the effects of event segmentation, we changed the border color, the task, or both after every four items in a sequence. We found that goal shifts influenced temporal memory in a manner consistent with the formation of distinct events. However, for subjective memory representations in particular, these effects differed by the type of event boundary. Furthermore, to examine if goal shifts lead to the prioritization of goal-relevant features in longer lasting memories, we tested source memory for each object's color and grid location both immediately and after a 24-hr delay. On the immediate test, boundaries enhanced the memory for all concurrent source features compared with nonboundary items, but only if those boundaries involved a goal shift. In contrast, after a delay, the source memory was selectively enhanced for the feature relevant to the goal shift. These findings suggest that goals can adaptively structure memories by prioritizing contextual features that define a unique episode in memory. [ABSTRACT FROM AUTHOR]

Combining computed diffusion-weighted imaging (DWI) with readout-segmented echo-planar-imaging may shorten acquisition time and improve imaging quality. This study aimed to compare computed vs. acquired DWI qualitatively and quantitatively in visualizing scrotal or testicular lesions. We retrospectively enrolled 57 consecutive men who underwent scrotal MRI. Four computed DWI sets (cDWI 800 , cDWI 1000 , cDWI 1200 , and cDWI 1400) were generated from acquired DWI with two lower b-values (150 and 600 s/mm2). Acquired DWI (DWI 800 and DWI 1000) and computed DWI were compared through qualitative (susceptibility artifact, signal loss artifact, anatomic clarity, and lesion conspicuity) and quantitative assessment (signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and lesion-to-testicular parenchyma contrast ratio (CR)). Computed DWI was prone to signal loss artifact and slightly lower assessment scores in terms of anatomic clarity and lesion conspicuity, comparing with acquired DWI. The SNR of computed and acquired DWI decreased with increasing b value. Under the same b-values (800 and 1,000 s/mm2), there was no difference in the median SNR and CR between computed and acquired DWI. The median CR of cDWI 1400 was significantly higher than that of the other DWI sets excepting cDWI 1200 (P =1.000). The median CNR tended to be lower for computed vs. acquired DWI, while no significant difference (P =0.233). Computed and acquired DWI were nearly equivalent in both qualitative and quantitative evaluations at the b values of 800 and 1,000 s/mm2. Computed DWI could enhance the contrast of scrotal or testicular lesions. • Computed vs. acquired DWI are equivalent at the b values of 800 and 1,000 s/mm2. • Computed DWI could enhance the contrast of scrotal or testicular lesions. • Computed DWI can serve visual aid to radiologists without increasing scan time. [ABSTRACT FROM AUTHOR]

In this paper, the problem of reliable bumpless transfer control for switched systems with actuator faults is investigated. A switching law and a class of reliable controllers via output feedback are constructed such that the bumpless transfer performance and H ∞ reliable property of the closed-loop systems are guaranteed. The switching process is divided into two stages, that is, dwell time and state-dependent switching stages. In the dwell time stage, a low bound of the time of the activated subsystem is introduced to restrict the frequent switching and suppress the system bumps. This guarantees the bumpless transfer performance of systems. In the second stage, only the measurable controller states are used to generate the switching signals, which upgrades the feasibility in the frame of output feedback. Finally, to ensure the H ∞ reliable property, the proposed controllers are time-varying, which work in the different switching stages. A simulation example is given to demonstrate the effectiveness of the proposed control scheme. [ABSTRACT FROM AUTHOR]

Chain-scaling fractional-order memristors (fracmemristors) refers to the concept of implementing them in circuits. Despite its advantages, a few issues that require urgent attention remain, including the effect of input signals on its instantaneous valid frequency range, failure to find the corresponding time-domain electrical characteristic expression of the fracmemristor, and the use of several memristor emulators in circuit schematics. Accordingly, a simple circuit for implementing a chain-scaling fracmemristor (CSF) within a fixed valid frequency range is proposed in this paper. First, a CSF circuit configuration with a fixed valid frequency range is described. Subsequently, a simple circuit schematic of an incremental/decremental CSF is presented, and the corresponding time-domain electrical characteristic expressions of the fracmemristor are obtained. Finally, rich theoretical analysis results are obtained along with the CSF circuit implementation. The accuracy of the theoretical analysis is verified experimentally. In this study, we developed a method to achieve a CSF with a fixed valid frequency range through the replacement of all the capacitors with memcapacitors, which also facilitated the design of circuit schematics. [ABSTRACT FROM AUTHOR]

In this paper, we study several tighter uncertainty principles (UPs) for the non-isotropic angular Stockwell transform (NAST). By employing the polar coordinate representation of signal functions, we establish the tighter Heisenberg-Weyl UPs in spatial and directional settings, the tighter concentration Heisenberg-Weyl UP of position and scale concentration, as well as the tighter local-type Heisenberg-Weyl UP for the NAST. Quantitative and qualitative analysis indicates that our results give rise to a new understanding for the NAST with more precise lower bounds so as to offer more valuable insights for signal processing and image analysis. [ABSTRACT FROM AUTHOR]

In this work, we investigate a contraction-type method for solving monotone variational inclusion problems in real Hilbert spaces. We obtain strong convergence theorems for two algorithms with a self-adaptive step size for solving monotone variational inclusions. The advantage of our algorithms is that we do not require a cocoercivity assumption nor do we need to know the Lipschitz-type constant of the single-valued operator. Moreover, a convergence rate is derived in the case where one of the operators is maximally and strongly monotone, and the other is monotone and Lipschitz continuous. The performance of our proposed methods is illustrated by numerical experiments regarding signal recovery. Our results improve and extend some known results, and our experiments show that our proposed algorithms are efficient and outperform other algorithms which are available in the literature. [ABSTRACT FROM AUTHOR]

Psychological vital assessments are required for monitoring health conditions and observing body reactions toward diseases and medications. Wearable sensors play a vital role in sensing body vitals and presenting them as signals for computer-based analysis. The problem relies on the signal decoding due to its input stream that turns out to be discrete/ continuous. Therefore for addressing the above specific issue, this article introduces MV-DUO (Multi-Variate Discrete Unified Optimization) method. This method addresses the above problem from a multi-variate perspective by sensing differential signals across healthy and unhealthy conditions. The healthy and unhealthy conditions are trained using neural learning by augmenting/ ceasing external vital data. The unification is performed using single-point artificial ecosystem-based optimization for identifying discrete sequences collaborated with continuous signals. The single-point reference is grouped based on the maximum continuity fitness observed under various sensing intervals. In this process, the non-grouped sequences are identified as unhealthy or discrete for which additional detection training and classification are required. Considerably the changes between successive sensing intervals are used for variations detection from unified high-fitness groups. Those grouped instances are used for training new vital changes observed at distinct intervals. This improves detection accuracy under controlled errors. For the varying sensing intervals, the proposed method achieves 14.13% high accuracy, 8.29% high grouping rate, 10.77% less error, and 10.07% less detection time. [ABSTRACT FROM AUTHOR]

A graph G is q-Ramsey for a q -tuple of graphs (H 1 , ... , H q) if for every q -coloring of the edges of G there exists a monochromatic copy of H i in color i for some i ∈ [ q ]. Over the last few decades, researchers have investigated a number of questions related to this notion, aiming to understand the properties of graphs that are q -Ramsey for a fixed tuple. Among the tools developed while studying questions of this type are gadget graphs, called signal senders and determiners, which have proven invaluable for building Ramsey graphs with certain properties. However, until now these gadgets have been shown to exist and used mainly in the two-color setting or in the symmetric multicolor setting, and our knowledge about their existence for multicolor asymmetric tuples is extremely limited. In this paper, we construct such gadgets for any tuple of cliques. We then use these gadgets to generalize three classical theorems in this area to the asymmetric multicolor setting. [ABSTRACT FROM AUTHOR]

Due to the important strategic position of Pumped Storage Power Plants (PSPP) in global energy upgrading, conducting in-depth research on the various operating conditions of pump turbine units is important for their safe and stable operation. This study sought to clarify the gas–liquid phase motion and the nonlinear chaotic characteristics of the process of exhaust and pressurization in pump mode; with the simplified objective model proposed here, a visualization of the process is achieved using data-driven methods, and the nonlinear characteristics of gas–liquid phase motion during the process are theoretically demonstrated. A method that combines data-driven and chaotic analysis is proposed to qualitatively and quantitatively analyze the force and torque time- series signals of the runner under different exhaust rates. The results indicate that the chaotic characteristics of the force signals and torque signals of the runner are not in a single linear relationship with the exhaust rates. Therefore, this research also provides guidance on exhaust rates with the aim of informing actual engineering practice, the purpose of which is to reduce the vibration amplitude caused by repetitive torque and improve the stability of the unit operations. [ABSTRACT FROM AUTHOR]

Blade crack detection is the key to ensuring the smooth and safe operation of centrifugal fans. However, a single vibration signal is difficult to fully reflect the health state of the blade and is susceptible to noise interference in the industrial field, which makes it difficult to detect blade cracks. Therefore, a two-level fusion model of vibro-acoustic signals is proposed for blade crack detection of centrifugal fans. Firstly, based on the designed correlated degree of cyclostationarity fusion rule, the data-level fusion of multi-source homogeneous vibro-acoustic signals is completed, and the fused signals with more obvious fault features are obtained. Then, a one-dimensional feature pyramid network is proposed to extract the vibro-acoustic features and generate initial decisions. Finally, a basic probability assignment acquisition method based on the precision of the initial classifiers and a weighted average method based on the Pignistic probability distance are proposed to minimize the conflict between multi-source evidence, and the Dempster-Shafer evidence theory method is used to obtain the blade crack detection results. The effectiveness of the proposed method is verified by the centrifugal fan blade crack detection experiments. Compared with other related methods, the proposed method has better detection performance and stronger robustness. [ABSTRACT FROM AUTHOR]

Semantic text matching plays a vital role in diverse domains, such as information retrieval, question answering, and recommendation. However, longer texts present challenges, including noise, long-range dependency, and cross-sentence inference. Graph-based approaches have shown effectiveness in addressing these challenges, but traditional graph structures struggle to model complex higher-order relationships in long-form texts. To overcome this limitation, we propose HyperMatch, a hypergraph-based method for long-form text matching. HyperMatch leverages hypergraph modeling to capture high-order relationships and enhance matching performance. Our approach involves constructing a keyword graph using document keywords as nodes, connecting sentences to nodes based on inclusion relationships, creating a hypergraph based on sentence similarity across nodes, and utilizing hypergraph convolutional networks to aggregate matching signals. Extensive experiments on benchmark datasets demonstrate the superiority of our model over state-of-the-art long-form text matching approaches. [ABSTRACT FROM AUTHOR]

Interaction between heterogeneous, nanometer-sized building blocks (NSBBs) is fascinating from viewpoints of both structures and functions. We report the co-assembly of fullerene C60 and a chiral silver nanocluster (Ag6), which yields C60 nanoarchitecture decorated with a small amount of Ag6. While Ag6 exhibits circular dichroism (CD) signal mainly in the ultraviolet (UV) region, the signal of the C60-Ag6 hybrid extends to visible region (over 700 nm). Up to five pairs of CD signals were distinguished, which match well with the absorption of the C60 crystal. The successful chirality transfer from the guest of Ag6 to C60-dominated supramolecular system indicates that the "sergeants and soldiers" effect is valid in architectonics of NSBBs. In addition, the doping of Ag6 leads to pronounced nonlinear optical response, paving a new way for the development of chiral optical materials. [ABSTRACT FROM AUTHOR]

Unidirectional spin Hall magnetoresistance (USMR) has emerged as a promising candidate for magnetoresistive random-access memory (MRAM) technology. However, the realization of high signal-to-noise output signal in USMR devices has remained a challenge, primarily due to the limited USMR effect at room temperature. In this study, we report a large USMR effect in FeNi/Pt/Bi₂Se₃ trilayers through interfacial engineering with Pt to optimize the spin current transmission efficiency and electron-magnon scattering. Our devices exhibit a USMR value that is an order of magnitude higher than previously reported systems, reaching 30.6 ppm/MA/cm² at room temperature. First-principles calculations and experimental observations suggest that the Pt layer not only preserves the spin-momentum locked topological surface states in Bi₂Se₃ at the Fermi-level but also generates additional Rashba surface states within the Pt itself to enhance the effective SOT efficiency. Furthermore, we demonstrate that the two-terminal USMR-MRAM devices show robust output performance with 2nd harmonic resistance variation around 0.11 Ω/mA. Remarkably, the performance of these devices further improves at elevated temperatures, highlighting their potential for reliable operation in a wide range of environmental conditions. Our findings pave the way for future advancements in high-performance, energy-efficient spintronic memory devices. Unidirectional spin Hall magnetoresistance refers to an asymmetric resistance response, which allows for the readout of the magnetic state from two terminal devices. Here, Zhang et al demonstrate a large unidirectional spin hall magnetoresistance FeNi/Pt/Bi₂Se₃ trilayers and present a robust random-access magnetoresistance device. [ABSTRACT FROM AUTHOR]

Magnetic flux leakage (MFL) testing is widely used for acquiring MFL signals to detect pipeline defects, and data-driven approaches have been effectively investigated for MFL defect identification. However, with the increasing complexity of pipeline defects, current methods are constrained by the incomplete information from single modal data, which fail to meet detection requirements. Moreover, the incorporation of multimodal MFL data results in feature redundancy. Therefore, the multi-modality hierarchical attention networks (MMHAN) are proposed for defect identification. Firstly, stacked residual blocks with cross-level attention module (CLAM) and multiscale 1D-CNNs with multiscale attention module are utilized to extract multiscale defect features. Secondly, the multi-modality feature enhancement attention module (MMFEAM) is developed to enhance critical defect features by leveraging correlations among multimodal features. Lastly, the multi-modality feature fusion attention module (MMFFAM) is designed to dynamically integrate multimodal features deeply, utilizing the consistency and complementarity of multimodal information. Extensive experiments were conducted on multimodal pipeline datasets to assess the proposed MMHAN. The experimental results demonstrate that MMHAN achieves a higher identification accuracy, validating its exceptional performance. [ABSTRACT FROM AUTHOR]

It is essential to enhance the speech signal's clarity and quality in order to maintain the message's content. By boosting the noisy voice signal, the speech signal quality can be raised. Two techniques are presented in this study to significantly minimize the additive background noise. In order to minimize non-stationary additive noise concerning the speech signal, the first approach employs modified multiband spectral subtraction. With this technique, spectral subtraction is carried out based on the signal to noise ratio (SNR) values in various noisy speech frames. When the noisy signal and noise signal are somewhat correlated, a second method is used to minimize the cross spectral components. These techniques are used to get over the drawbacks of the fundamental spectrum subtraction method. To improve the noisy speech signal, both techniques are combined. [ABSTRACT FROM AUTHOR]

RF power amplifier (RF PA) finds its application in almost all the areas of electronics, mobile communication being identified as a major area. The paper performs a comparative efficiency analysis of RF power amplifiers operating with a fixed bias and an envelope tracking bias. Simulations are performed using Keysight advanced design system (ADS) tool. A class a RF PA operating at a 12 dB gain is fixed for the work. 16 QAM LTE signal operating at 5 MHz input frequency, with a peak to average power ratio (PAPR) of 6.0 dB is used as input signal. An envelope simulation at 2.5 GHz is performed on the RF power amplifier. Simulation result shows an improvement of 12% in power added efficiency (PAE) at 6 dB back-off and 6.422% in mean PAE while using envelope tracking power amplifiers, compared to RF PA with fixed supply. Envelope tracking power amplifiers reduced AM/AM distortions also by a factor of 0.248. The results obtained are much better than that obtained using a conventional RF PA with fixed bias. RF PA being the most power dissipative block in a mobile handset, improving its efficiency contributes directly to a great improvement in the battery lifetime of mobile phones. The major challenges faced by envelope tracking PA (ETPA) designers in achieving this efficiency improvement is also delineated in the paper. [ABSTRACT FROM AUTHOR]

A method of expanding the operating range of the amplifier is presented, which allows reducing the coefficient of nonlinear distortions of the calibration signal to 0.003%. The structural diagram of the analog-digital amplifier of the input signal to the output, which provides minimal nonlinear distortion of the output signal, is given. The principle of operation of the amplifier is described. The input scaling amplifier and output highvolt digital-to-analog converter transmission coefficients dependens diagrams on the input signal amplitude are given. The results of experimental studies of the metrological characteristics of the experimental sample of the amplifier are given. References 10, figures 2. [ABSTRACT FROM AUTHOR]

This paper studies the general principal-agent framework in which the principal aims to implement his first-best action that is monotone in the unknown state. The principal privately selects a signal structure of the agent whose payoff depends on the principal's action, the state, and the privately known type. The agent privately observes the generated signal and reports it to the principal, who takes action. We show that by randomizing between two perfectly informative signal structures, the principal can elicit perfect information from the agent about the state and implement his first-best action regardless of the agent's type. As to the economic application, we consider the bilateral trade model with non-quasilinear preferences and private multi-dimensional information of the buyer, and show that the seller can extract full surplus by privately designing the buyer's signal structures. [ABSTRACT FROM AUTHOR]

For continuous‐time complex‐valued neural networks, this paper addresses the state‐feedback stabilization issue via dynamic event‐triggered protocol. Aiming at random parameters' switching, semi‐Markov jump model surpasses the Markov jump model in terms of its generality, enabling us to effectively capture the occurrence of random abrupt alterations in both the structure and parameters of complex‐valued neural networks. To optimize packet transmission, a new dynamic event‐based protocol is introduced to judge whether the previous signal transmission continues. The design of this protocol takes into full consideration the imaginary part characteristics of the system, while also integrating the system modes and dynamic variables. Utilizing an appropriate Lyapunov functional that contains auxiliary internal dynamical variables, the desired stability is proposed. Eventually, the effectiveness of theoretical findings is ultimately validated through two numerical simulations. [ABSTRACT FROM AUTHOR]