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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]

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]

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]

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]

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]

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]

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]

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]

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]

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]

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]

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]

Semantic feature combination/parsing issue is one of the key problems in sound event classification for acoustic scene analysis, environmental sound monitoring, and urban soundscape analysis. The input audio signal in the acoustic scene classification is composed of multiple acoustic events, which usually leads to low recognition rate in complex environments. To address this issue, this paper proposes the Hierarchical-Concatenate Fusion(HCF)-TDNN model by adding HCF Module to ECAPA-TDNN model for sound event classification. In the HCF module, firstly, the audio signal is converted into two-dimensional time-frequency features for segmentation. Then, the segmented features are convolved one by one for improving the small receptive field in perceiving details. Finally, after the convolution is completed, the two adjacent parts are combined before proceeding with the next convolution for enlarging the receptive field in capturing large targets. Therefore, the improved model further enhances the scalability by emphasizing channel attention and efficient propagation and aggregation of feature information. The proposed model is trained and validated on the Urbansound8K dataset. The experimental results show that the proposed model can achieve the best classification accuracy of 95.83%, which is an approximate improvement of 5% (relatively) over the ECAPA-TDNN model. [ABSTRACT FROM AUTHOR]

Long-term single-molecule fluorescence measurements are widely used powerful tools to study the conformational dynamics of biomolecules in real time to further elucidate their conformational dynamics. Typically, thousands or even more single-molecule traces are analyzed to provide statistically meaningful information, which is labor-intensive and can introduce user bias. Recently, several deep-learning models have been developed to automatically classify single-molecule traces. In this study, we introduce DEBRIS (Deep lEarning Based fRagmentatIon approach for Single-molecule fluorescence event identification), a deep-learning model focusing on classifying local features and capable of automatically identifying steady fluorescence signals and dynamically emerging signals of different patterns. DEBRIS efficiently and accurately identifies both one-color and two-color single-molecule events, including their start and end points. By adjusting user-defined criteria, DEBRIS becomes the pioneer in using a deep learning model to accurately classify four different types of single-molecule fluorescence events using the same trained model, demonstrating its universality and ability to enrich the current toolbox. DEBRIS is a deep learning-based model that can classify local features and identify steady events and dynamically emerging events within two-color single-molecule traces of varying lengths based on user-defined criteria. [ABSTRACT FROM AUTHOR]

Previous studies have shown that pro‐social leaders cooperate, on average, more than pro‐self leaders in social dilemmas. It can, thus, be beneficial for the group to have a pro‐social leader. In this paper we analyze the consequences of a leader informing followers that they are pro‐social (or pro‐self). In doing so, we compare a setting in which the leader's type is truthfully revealed to settings where the leader can ‘hide’ or ‘lie’ about their pro‐sociality. We find that a leader saying they are pro‐social boosts efficiency, even if the signal is not fully credible. Cooperation is highest in a truth setting with a pro‐social leader. We demonstrate that these results are consistent with a belief‐based model of social preference in which the stated type of the leader changes the frame of reference for followers. [ABSTRACT FROM AUTHOR]

The cytokine interleukin 6 (IL‐6) signals via the IL‐6 α‐receptor (IL‐6Rα or IL‐6R) in complex with the gp130 β‐receptor. Cell type restricted expression of the IL‐6R limits the action of IL‐6 mainly to hepatocytes and some immune cells. Here, we show that IL‐6 also binds to the IL‐11 α receptor (IL‐11Rα or IL‐11R) and induces signaling via IL‐11R:gp130 complexes, albeit with a lower affinity compared to IL‐11. Antagonistic antibodies directed against IL‐11R, but not IL‐6R, inhibit IL‐6 signaling via IL‐11R:gp130 receptor complexes. Notably, IL‐11 did not cross‐react with IL‐6R. IL‐11R has also been identified as an alternative α receptor for the CNTF/IL‐6‐derived chimeric cytokine IC7, which has recently been shown to induce weight loss in mice. Accordingly, the effects of therapeutic monoclonal antibodies against IL‐6 or IL‐6R, which both block IL‐6 signaling, may be slightly different. These findings provide new insights into IL‐6 signaling and therefore offer new potential therapeutic intervention options in the future. [ABSTRACT FROM AUTHOR]

The instability and failure processes of coal-rock combinations are accompanied by the release of acoustic emission (AE) and infrared radiation (IR) signals. To investigate the characteristics of AE and IR signals during the failure process in coal-rock combinations with different ratios, and to analyze the effectiveness and applicability of the monitoring methods for these two signals in various specimen ratios. In this paper, the uniaxial compression tests were conducted on seven coal-rock combinations with different ratios by using the rock mechanics loading system and the cooperative monitoring platform of infrared and acoustic emission. The results show that (1) the AE counts for failure precursors in coal-rock combinations are positively correlated with the coal-rock ratio, whereas the AE peak counts are negatively correlated. Moreover, as the coal-rock ratio decreases, the slope of the cumulative AE count curve during the peak failure stage approaches 1. (2) During the elastic and yield stages, the maximum infrared radiation temperature (MIRT) curve fluctuates, and just before peak failure, the curve displays a distinctive "V" shape. This "V" shape becomes more pronounced as the coal-rock ratio decreases. (3) In the monitoring of damage precursors of coal-rock combinations, when the ratio of coal to rock is 1:3 or less, IR monitoring is better than AE monitoring. Conversely, when the ratio of coal to rock is greater than 1:3, AE monitoring is more suitable. Consequently, the combined monitoring of AE and IR signals can increase the reliability and precision of early warning signals for coal-rock assemblage damage precursors. [ABSTRACT FROM AUTHOR]

High dimensionality and noise have limited the new biological insights that can be discovered in scRNA-seq data. While dimensionality reduction tools have been developed to extract biological signals from the data, they often require manual determination of signal dimension, introducing user bias. Furthermore, a common data preprocessing method, log normalization, can unintentionally distort signals in the data. Here, we develop scLENS, a dimensionality reduction tool that circumvents the long-standing issues of signal distortion and manual input. Specifically, we identify the primary cause of signal distortion during log normalization and effectively address it by uniformizing cell vector lengths with L2 normalization. Furthermore, we utilize random matrix theory-based noise filtering and a signal robustness test to enable data-driven determination of the threshold for signal dimensions. Our method outperforms 11 widely used dimensionality reduction tools and performs particularly well for challenging scRNA-seq datasets with high sparsity and variability. To facilitate the use of scLENS, we provide a user-friendly package that automates accurate signal detection of scRNA-seq data without manual time-consuming tuning. Single-cell RNA sequencing data analysis is limited by noise and high dimensionality. Here, authors present scLENS, a tool that automates accurate signal detection without manual input, particularly in complex datasets. [ABSTRACT FROM AUTHOR]

Observations find that some fast radio bursts (FRBs) have extremely narrowband spectra, i.e., Δ ν / ν 0 ≪ 1. We show that, when the angular size of the emission region is larger than the Doppler beaming angle, the observed spectral width (Δ ν / ν 0) exceeds 0.58 due to the high-latitude effects for a source outside the magnetosphere, even when the spectrum in the source's comoving frame is monochromatic. The angular size of the source for magnetospheric models of FRBs can be smaller than the Doppler beaming angle, in which case this geometric effect does not influence the observed bandwidth. We discuss various propagation effects to determine if any could transform a broad-spectrum radio pulse into a narrow spectrum signal at the observer's location. We find that plasma lensing and scintillation can result in a narrow bandwidth in the observed spectrum. However, the likelihood of these phenomena being responsible for the narrow observed spectra with Δ ν / ν 0 < 0.58 in the fairly large observed sample of FRBs is exceedingly small. [ABSTRACT FROM AUTHOR]

Neurobiological investigations of perceptual decision-making have furnished the first glimpse of a flexible cognitive process at the level of single neurons. Neurons in the parietal and prefrontal cortex are thought to represent the accumulation of noisy evidence, acquired over time, leading to a decision. Neural recordings averaged over many decisions have provided support for the deterministic rise in activity to a termination bound. Critically, it is the unobserved stochastic component that is thought to confer variability in both choice and decision time. Here, we elucidate this drift-diffusion signal on individual decisions. We recorded simultaneously from hundreds of neurons in the lateral intraparietal cortex of monkeys while they made decisions about the direction of random dot motion. We show that a single scalar quantity, derived from the weighted sum of the population activity, represents a combination of deterministic drift and stochastic diffusion. Moreover, we provide direct support for the hypothesis that this drift-diffusion signal approximates the quantity responsible for the variability in choice and reaction times. The population-derived signals rely on a small subset of neurons with response fields that overlap the choice targets. These neurons represent the integral of noisy evidence. Another subset of direction-selective neurons with response fields that overlap the motion stimulus appear to represent the integrand. This parsimonious architecture would escape detection by state-space analyses, absent a clear hypothesis. [ABSTRACT FROM AUTHOR]

The peak-to-average power ratio (PAPR), commonly used to describe the amplitude variations of an OFDM (orthogonal frequency-division multiplex) signal, does not accurately reflect its impact on the system performance. This paper applies the mutual information as a metric to assess the effects of nonlinear PAPR reduction schemes on the performance of OFDM systems. Evaluation of the achieved mutual information shows that a significant capacity loss from clipping occurs only at high SNR (signal-to-noise ratio) and a simple compression/expansion technique is proposed to achieve close to optimal performance in this regime. The effectiveness of this method is validated through WER (word error rate) simulations with several modulation and coding schemes. [ABSTRACT FROM AUTHOR]

This article abandons the traditional Laplace transform and proposes a new method for studying fractional-order circuits, which is the Loop-By-Loop Progressive Iterative Method(LPIM). Firstly, in order to demonstrate the correctness of LPIM, the fractance circuit, which is a relatively mature and simple form in fractional-order circuits, was chosen as the research object. The output signals of fractance circuit were studied for the first time using Laplace transform and LPIM, respectively. The results showed that the conclusions obtained by LPIM were completely consistent with those obtained by Laplace transform method and existing theories, thus verifying the correctness of LPIM. Then, a brand new Fractional-Order Memory Systems (FMS) model is constructed, and based on this model, LPIM is used for the first time to simulate the output signal of Flux-Controlled Fractional-Order Memory Systems (FFMS) that has not been studied so far. The results show that when a sine signal is used as the excitation signal, the output signal of the FFMS intersects at two points, and the output signal is modulated by the frequency of the excitation signal. Finally, combining existing theories, predict the output commonalities of FMS. [ABSTRACT FROM AUTHOR]

Portable traffic signals with fixed-time signal plans are a common type of traffic control at work zones with shuttle traffic. The most-used alternatives are flagging and intelligent transport systems with traffic-actuated signals. These can provide more efficient traffic control, but existing policies often do little to encourage their practical application. This paper provides a clear and accessible overview of shuttle operations and a comparison of the main signal control types while addressing some knowledge gaps, such as whole-day operation efficiency. The relations between different variables of the signal plan and traffic flow are derived to build a theoretical framework and models for both deterministic and random arrivals to estimate delays and to find the optimal signal plan setting for a wide range of circumstances. The hypothetical scenarios are supported by a case study. Traffic and signal control data from several construction phases of a work zone with shuttle operation were gathered, processed, analysed, and used to compare different control scenarios. The results provide solid evidence for the efficiency of the dynamic systems. The magnitude of the difference is heavily affected by circumstances. The efficiency of the green signal almost doubled with the dynamic control. The case study also revealed a severe impact of road conditions (milling) on the work zone capacity. Several standards and policies are proposed based on the findings to encourage wider and more efficient adoption of traffic-actuated signals in work zones. [ABSTRACT FROM AUTHOR]

Greedy search (GS) or exhaustive search plays a crucial role in decision trees and their various extensions. We introduce an alternative splitting method called smooth sigmoid surrogate (SSS) in which the indicator threshold function used in GS is approximated by a smooth sigmoid function. This approach allows for parametric smoothing or regularization of the erratic and discrete GS process, making it more effective in identifying the true cutoff point, particularly in the presence of weak signals, as well as less prone to the inherent end-cut preference problem. Additionally, SSS provides a convenient means of evaluating the best split by referencing a parametric nonlinear model. Moreover, in many variants of recursive partitioning, SSS can be reformulated as a one-dimensional smooth optimization problem, rendering it computationally more efficient than GS. Extensive simulation studies and real data examples are provided to evaluate and demonstrate its effectiveness. [ABSTRACT FROM AUTHOR]

To address the challenges of low accuracy in indoor positioning caused by factors such as signal interference and visual distortions, this paper proposes a novel method that integrates ultra-wideband (UWB) technology with visual positioning. In the UWB positioning module, the powerful feature-extraction ability of the graph convolutional network (GCN) is used to integrate the features of adjacent positioning points and improve positioning accuracy. In the visual positioning module, the residual results learned from the bidirectional gate recurrent unit (Bi-GRU) network are compensated into the mathematical visual positioning model's solution results to improve the positioning results' continuity. Finally, the two positioning coordinates are fused based on particle filter (PF) to obtain the final positioning results and improve the accuracy. The experimental results show that the positioning accuracy of the proposed UWB positioning method based on a GCN is less than 0.72 m in a single UWB positioning, and the positioning accuracy is improved by 55% compared with the Chan–Taylor algorithm. The proposed visual positioning method based on Bi-GRU and residual fitting has a positioning accuracy of 0.42 m, 71% higher than the Zhang Zhengyou visual positioning algorithm. In the fusion experiment, 80% of the positioning accuracy is within 0.24 m, and the maximum error is 0.66 m. Compared with the single UWB and visual positioning, the positioning accuracy is improved by 56% and 52%, respectively, effectively enhancing indoor pedestrian positioning accuracy. [ABSTRACT FROM AUTHOR]

This paper focuses on the direction-of-arrival (DOA) estimation for noncircular coherently distributed (CD) sources with nested arrays. Usually, for point sources, sparse arrays have the potential to improve the estimation performance of algorithms by obtaining more degrees of freedom. However, algorithms have to be reconsidered for CD sources with sparse arrays and many problems arise. One thorny problem is the disappearance of displacement invariance of the virtual array manifold constructed by the virtualization technique. To deal with this issue, a nested array processing method for CD sources transmitting noncircular signals is proposed in this paper. Firstly, we construct the virtual sum-and-difference co-array by leveraging the noncircular quality of signals with a nested array. Then, an approximation is made to degrade CD sources into point sources. In this way, spatial smoothing techniques can be applied to restore the rank. Finally, in order to reduce the complexity, we modify the reduced-dimension MUSIC to estimate DOAs through a one-dimensional peak-searching procedure. The simulation results prove the superiority of our algorithm against other competitors. [ABSTRACT FROM AUTHOR]

With the acceleration of global population aging, the elderly have an increasing demand for home care and nursing institutions, and the significance of health prevention and management of the elderly has become increasingly prominent. In this context, we propose a biometric recognition method for multi-modal biomedical signals. This article focuses on three key signals that can be picked up by wearable devices: ECG, PPG, and breath (RESP). The RESP signal is introduced into the existing two-mode signal identification for multi-mode identification. Firstly, the features of the signal in the time–frequency domain are extracted. To represent deep features in a low-dimensional feature space and expedite authentication tasks, PCA and LDA are employed for dimensionality reduction. MCCA is used for feature fusion, and SVM is used for identification. The accuracy and performance of the system were evaluated using both public data sets and self-collected data sets, with an accuracy of more than 99.5%. The experimental data fully show that this method significantly improves the accuracy of identity recognition. In the future, combined with the signal monitoring function of wearable devices, it can quickly identify individual elderly people with abnormal conditions, provide safer and more efficient medical services for the elderly, and relieve the pressure on medical resources. [ABSTRACT FROM AUTHOR]

In this paper, a signal conditioner intended for use in variable impedance sensors is presented. First, an inductive linear displacement sensor design is described, and the signal conditioner discrete realization is presented. Second, based on this system's requirements, the integrated conditioner is proposed. The conditioner comprises an amplifier, a tunable band-pass filter, and a precision high-frequency AC-DC converter. It is designed in a low-cost AMS 0.35 µm CMOS process. The presented conditioner measures the sensor's impedance magnitude by using a simplified variation of the sensor voltage and current vector measurement. It can be used for the real-time measurement of fast sensors, having small output impedance. The post-layout simulation results show that the integrated conditioner has an inductance measurement range from 10 nH to 550 nH with a nonlinearity of 1.2%. The operating frequency in this case was 8 MHz, but the circuit can be easily adjusted to different operating frequencies (due to the tunable filter). The designed IC area is 500 × 330 μm2, and the total power consumption is 93.8 mW. [ABSTRACT FROM AUTHOR]

Radar emitter signal deinterleaving based on pulse description words (PDWs) is a challenging task in the field of electronic warfare because of the parameter sparsity and uncertainty of PDWs. In this paper, a modulation-hypothesis-augmented Transformer model is proposed to identify emitters from a single PDW with an end-to-end manner. Firstly, the pulse features are enriched by the modulation hypothesis mechanism to generate I/Q complex signals from PDWs. Secondly, a multiple-parameter embedding method is proposed to expand the signal discriminative features and to enhance the identification capability of emitters. Moreover, a novel Transformer deep learning model, named PulseFormer and composed of spectral convolution, multi-layer perceptron, and self-attention based basic blocks, is proposed for discriminative feature extraction, emitter identification, and signal deinterleaving. Experimental results on synthesized PDW dataset show that the proposed method performs better on emitter signal deinterleaving in complex environments without relying on the pulse repetition interval (PRI). Compared with other deep learning methods, the PulseFormer performs better in noisy environments. [ABSTRACT FROM AUTHOR]

A well-known technique to enhance the signal to noise ratio (SNR) of repetitive signals is to average them. The coherent parts of the signal add up constructively while the incoherent parts are averaged out. The prerequisite is that the signals are acquired under conditions of high repeatability, i.e., the signals must be sufficiently similar. In the present technical note, we describe an efficient method for maintaining signal similarity by ensuring spatial and temporal proximity of laser waveform signals obtained by a sensor operated from an airborne platform. The method makes use of a few auxiliary parameters such as laser pulse repetition rate, mirror rotation rate, platform altitude and flight speed. The method can be extended to be operated in real time. [ABSTRACT FROM AUTHOR]

Human perception is often based on the integration of multiple sensory cues, where more statistically reliable cues are considered to have stronger influence on the percept. For example, in three-dimensional shape perception, binocular disparity is considered the most reliable cue at close distances, while pictorial cues like shading are considered less reliable. In three within-subject experiments, we instead show that shading can override disparity, a result that cannot be explained by its measured reliability, cue vetoing or cue promotion. Observers judged the shape of a disparity surface that was combined with different shading patterns. In all tests, shading altered the perceived shape specified by a strong disparity signal in a way that could not be predicted by standard accounts of three-dimensional perception. We find an example of unaccounted for cue cooperation, where shading becomes strong when it interacts with disparity. [ABSTRACT FROM AUTHOR]

This study analyses the interference effect in a visible light‐non‐orthogonal multiple access (VL‐NOMA) network that considers the signal power parameters performance for near and far users. The light‐emitting diode (LED) as a carrier transmits signals, and we investigate the interference effect. The interference effect challenge is a result of unaligned signal power parameters, thereby producing noise or echo during the signal transmission. The signal power parameters are successfully aligned, and NOMA techniques are deployed, which improves the signal performance in terms of bit‐error rate (BER), achieved data rate, and signal‐to‐interference plus noise ratio (SINR). Furthermore, the deployed NOMA techniques, such as power allocations (PA) to assign the signals appropriately, then superposition coding (SC) encodes the entire signal, and successive interference cancellation (SIC) cancels the interference within the signals. The signal behavior of the aligned and the unaligned signal power parameters performance are used to investigate the interference effect. We observed that unaligned signal power parameters reduce the signal performance of achieved data rate, BER, and SINR. Further, the aligned signal power parameter with NOMA techniques improves the signal performance. Moreover, in the aligned signal power scenario of NOMA, the near user performed better than the far user. [ABSTRACT FROM AUTHOR]

The complex network governing self-renewal in epidermal stem cells (EPSCs) is only partially defined. FOXM1 is one of the main players in this network, but the upstream signals regulating its activity remain to be elucidated. In this study, we identify cyclin-dependent kinase 1 (CDK1) as the principal kinase controlling FOXM1 activity in human primary keratinocytes. Mass spectrometry identified CDK1 as a key hub in a stem cell-associated protein network, showing its upregulation and interaction with essential self renewal-related markers. CDK1 phosphorylates FOXM1 at specific residues, stabilizing the protein and enhancing its nuclear localization and transcriptional activity, promoting self-renewal. Additionally, FOXM1 binds to the CDK1 promoter, inducing its expression. We identify the CDK1-FOXM1 feedforward loop as a critical axis sustaining EPSCs during in vitro cultivation. Understanding the upstream regulators of FOXM1 activity offers new insights into the biochemical mechanisms underlying self-renewal and differentiation in human primary keratinocytes. [ABSTRACT FROM AUTHOR]

Recently, UWB-based technology providing centimeter-level accuracy has been developed and widely utilized in indoor real-time location tracking systems. However, location accuracy varies due to factors such as frequency interference, collisions, reflected signals, and whether line-of-sight (LOS) conditions are met, and it can be challenging to ensure high accuracy in specific environments. Fortunately, when anchor positions are fixed, the locations of large obstacles such as columns or furniture remain relatively stable, leading to similar patterns of positioning bias at specific points. This study proposes an algorithm that corrects inaccurate positioning to more closely reflect the actual location based on bias and deviation maps generated using natural neighbor interpolation. Initially, positioning bias and deviations at specific points are sampled, and bias and deviation maps are created using natural neighbor interpolation. During location tracking, the algorithm detects candidate clusters and determines the centroid to estimate the actual location by applying the bias and deviation maps to the measured positions derived through trilateration. To validate the proposed algorithm, experiments were conducted in a non-LOS (NLOS) indoor environment. The results demonstrate that the proposed algorithm can reduce the positioning bias of a UWB-based RTLS by approximately 71.34% compared to an uncalibrated system. [ABSTRACT FROM AUTHOR]

Plants are able to perceive diverse environmental factors and form an appropriate systemic functional response. Systemic responses are induced by stimulus-specific long-distance signals that carry information about the stimulus. Variation potential is proposed as a candidate for the role of such a signal. Here, we focus on the mechanisms that determine the specificity of the variation potential under the action of different local stimuli. Local stimuli such as heating, burning and wounding cause variation potential, the parameters of which differ depending on the type of stimulus. It was found that the stimulus-specific features of the hydraulic signal monitored by changes in leaf thickness and variation potential, such as a greater amplitude upon heating and burning and a significant amplitude decrement upon burning and wounding, were similar. The main features of these signals are the greater amplitude upon heating and burning, and a significant amplitude decrement upon burning and wounding. Together with the temporal correspondence of signal propagation, this evidence indicates a role for the hydraulic signal in the induction of stimulus-specific variation potential. Experiments using mechanosensitive channel inhibitors have demonstrated that the hydraulic signal contributes more to the induction of the variation potential in the case of rapidly growing stimuli, such as burning and wounding, than in the case of gradual heating. For thermal stimuli (gradual heating and burning), a greater contribution, compared to wounding, of the chemical signal related to reactive oxygen species to the induction of the variation potential was demonstrated. Thus, the specificity of the parameters of the variation potential is determined by the different contributions of hydraulic and chemical signals. [ABSTRACT FROM AUTHOR]

N-methyl-D-aspartate (NMDA) receptors are ionotropic glutamate receptors involved in learning and memory. NMDA receptors primarily comprise two GluN1 and two GluN2 subunits. The GluN2 subunit dictates biophysical receptor properties, including the extent of receptor activation and desensitization. GluN2A- and GluN2D-containing receptors represent two functional extremes. To uncover the conformational basis of their functional divergence, we utilize single-molecule fluorescence resonance energy transfer to probe the extracellular domains of these receptor subtypes under resting and ligand-bound conditions. We find that the conformational profile of the GluN2 amino-terminal domain correlates with the disparate functions of GluN2A- and GluN2D-containing receptors. Changes at the pre-transmembrane segments inversely correlate with those observed at the amino-terminal domain, confirming direct allosteric communication between these domains. Additionally, binding of a positive allosteric modulator at the transmembrane domain shifts the conformational profile of the amino-terminal domain towards the active state, revealing a bidirectional allosteric pathway between extracellular and transmembrane domains. NMDA receptors convert chemical signals into electrical signals in the brain, and function is fine-tuned by the subunit composition. Here the authors use smFRET to uncover a bi-directional communication pathway between different parts of the receptor. [ABSTRACT FROM AUTHOR]

Communication allows members of a collective to share information about their environment. Advanced collective systems, such as multicellular organisms and social insect colonies, vary in whether they use communication at all and, if they do, in what types of signals they use, but the origins of these differences are poorly understood. Here, we develop a theoretical framework to investigate the evolution and diversity of communication strategies under collective-level selection. We find that whether communication can evolve depends on a collective's external environment: communication only evolves in sufficiently stable environments, where the costs of sensing are high enough to disfavour independent sensing but not so high that the optimal strategy is to ignore the environment altogether. Moreover, we find that the evolution of diverse signalling strategies—including those relying on prolonged signalling (e.g. honeybee waggle dance), persistence of signals in the environment (e.g. ant trail pheromones) and brief but frequent communicative interactions (e.g. ant antennal contacts)—can be explained theoretically in terms of the interplay between the demands of the environment and internal constraints on the signal. Altogether, we provide a general framework for comparing communication strategies found in nature and uncover simple ecological principles that may contribute to their diversity. [ABSTRACT FROM AUTHOR]

One of the remaining issues regarding the Anthropocene is the lack of stratigraphic evidence indicating when the cumulative human pressure from the early Holocene began to fundamentally change the Earth system. Herein, we compile anthropogenic fingerprints from various high-precision-dated proxy records for 137 global sites to determine the age of the unprecedented surge in these records over the last 7700 y. The cumulative number of fingerprints revealed an unprecedented surge in diverse anthropogenic fingerprints starting in 1952 ± 3 CE, corresponding to the onset of the Great Acceleration. Notably, the period from 1953 to 1958 CE saw a nearly simultaneous surge in fingerprints across all regions, including Antarctica, the Arctic, East Asia, Europe, North America, and Oceania. This synchronous upsurge reflects the moment when human impacts led to rapid transformations in various natural processes and cycles, with humans becoming a geological force capable of inscribing abundant and diverse anthropogenic fingerprints in global strata. Following this global fingerprint explosion, profound planetary-scale changes, including deviations from the established natural climatic conditions, begin. This unprecedented surge in anthropogenic signals worldwide suggests that human influences started to match many natural forces controlling the processes and cycles and overwhelm some of the functioning of the Earth system around 1952. [ABSTRACT FROM AUTHOR]

It has become an interesting topic for modern radar possessing capabilities of polarimetric measurement, high‐resolution imaging, and good delay‐Doppler resolution. The linear frequency modulation (LFM) scheme is widely used in radar systems as it can achieve both high Doppler tolerance and resolution. Based on the LFM scheme, a novel waveform is proposed, namely, the orthogonal double V‐linear frequency modulation (ODV‐LFM), which exhibits the capability to mitigate the influence of delay‐Doppler coupling and reduces the risk of false targets and ghosts in multiple‐target scenes. Based on the ODV‐LFM signal, a simultaneous polarimetric measurement method is proposed to obtain fully polarimetric information of the target. According to the unique chirp rate characteristic of the ODV‐LFM signal, the pointwise linear and non‐linear processing methods are proposed to enhance delay‐Doppler resolution, suppress sidelobes, and achieve high‐resolution imaging without substantially compromising the signal detection performance. Finally, simulated experiments are conducted to demonstrate the superiority of the proposed waveform and methods. [ABSTRACT FROM AUTHOR]

Mid-frequency transmissions (1.5 to 7.5 kHz) from a towed source to a drifting array one convergence zone away demonstrate smoothly varying phase. Calculations of the strength and diffraction parameters Φ and Λ for a representative background environment predict partially saturated propagation. For a single convergence zone path, the evolving phase rate due to the changing internal wave field corresponds to a narrowband coherent integration time, defined by the length of a discrete Fourier transform that likely captures the signal, from ∼370 s at 10 kHz to ∼1370 s at 1 kHz in the absence of source motion. Simulated propagation with a split-step parabolic equation solver through a sound speed field with thermocline fine structure and a Garrett-Munk internal wave displacement field provides a full wave picture that is consistent with the statistical predictions. Experimental data from the Philippine Sea demonstrates signal phase that is highly correlated with source tow body vertical excursions, measured by a pressure sensor, that couple into horizontal motion. The received signal can be integrated for up to 128 s at 5.5 kHz, with the upper limit thought to be due to non-uniform source motion rather than ocean dynamics. [ABSTRACT FROM AUTHOR]