Signal Path Research Articles

Optimized Data Transmission and Signal Processing for Telepresence Suits in Multiverse Interactions

With the rapid development of the metaverse, designing effective interfaces in virtual and augmented environments presents significant challenges. Additionally, keeping real-time sensory data flowing from users to their virtual avatars in a seamless and accurate manner is one of the biggest challenges in this domain. To this end, this article investigates a telepresence suit as an interface for interaction within the metaverse and its virtual avatars, aiming to address the complexities of signal generation, conversion, and transmission in real-time telepresence systems. We model a telepresence suit framework that systematically generates state data and transmits it to end-points, which can be either robotic avatars or virtual representations within a metaverse environment. Through a hand movement study, we successfully minimized the volume of transmitted information, reducing traffic by over 50%, which directly decreased channel load and packet delivery delay. For instance, as channel load decreases from 0.8 to 0.4, packet delivery delay is reduced by approximately half. This optimization not only enhances system responsiveness but also improves accuracy, particularly by reducing delays and errors in high-priority signal paths, enabling more precise and reliable telepresence interactions in metaverse settings.

Rate of change of torque for gear tooth damage detection

This paper presents an investigation into the applicability of a magnetoelastic rate of change of torque (ROC) sensor to condition monitoring of gearbox tooth damage, using a recirculating torque test gearbox test facility. ROC sensors have significant potential in condition monitoring of rotating machinery, due to direct signal paths between the sensors and the damaged region. To assess this, data has been collected across a wide range of operating conditions for tooth bends as small as 2.4 µm. A number of industry-standard analysis techniques have then been applied. This includes a variety of algorithms (based around time-synchronous averaging), wavelet transforms, neural network classification, shapely additive explanations (SHAP) and deep learning. It is concluded that the ROC sensor demonstrates significant potential in condition monitoring of rotating machinery, worthy of further study.

UAV-Mounted RIS-Aided Multi-Target Localization System: An Efficient Sparse-Reconstruction-Based Approach

Unmanned Aerial Vehicle (UAV) technology is increasingly gaining attention in localization systems due to its flexibility and mobility. However, traditional localization techniques often fail in complex environments where line-of-sight paths are obstructed. To address this challenge, this paper presents an innovative UAV-assisted high-precision multi-target localization system. The system utilizes UAVs equipped with Reconfigurable Intelligent Surfaces to create a reflective signal path, allowing a receiver sensor to capture these signals, creating favorable conditions for multi-target localization. Exploiting the sparsity of signals, we introduce a direct positioning algorithm that leverages Atomic Norm Minimization (ANM) to estimate the target’s location. To address the high complexity of traditional ANM methods, we propose a novel Coyote-ANM-based direct localization (CADL) approach. This method combines the coyote optimization algorithm with the alternating direction method of multipliers to achieve high-accuracy positioning with reduced computational complexity. Simulation results across various signal-to-noise ratio scenarios demonstrate that the proposed algorithm significantly improves localization accuracy, achieving lower root mean square error values and faster execution times compared to traditional methods.

Exploring Ground Reflection Effects on Received Signal Strength Indicator and Path Loss in Far-Field Air-to-Air for Unmanned Aerial Vehicle-Enabled Wireless Communication

Unmanned aerial vehicle (UAV)-enabled wireless communications are becoming increasingly important in applications such as maritime and forest rescue operations. UAV systems often depend on wireless networking and mobile edge computing (MEC) devices for effective deployment, particularly in swarm UAV-enabled MEC configurations focusing on channel modeling and path loss characteristics for air-to-air (A2A) communications. This paper examines path loss characteristics in far-field (FF) ground reflection scenarios, specifically comparing two environments: FF1 (forest floor) and FF2 (seawater floor). LoRa modules operating at 868 MHz were deployed for communication between a transmitting UAV (Tx-UAV) and a receiving UAV (Rx-UAV) to conduct this study. We investigated the received signal strength indicator (RSSI) and path loss characteristics across channel bandwidths of 125 kHz and 250 kHz and spread factors (SF) of 7, 9, and 12. Experimental results show that ground reflection has minimal impact in the FF1 scenario, whereas, in the FF2 scenario, ground reflection significantly influences communication. Therefore, in the seawater environment, a UAV-enabled LoRa MEC configuration using a 250 kHz bandwidth and an SF of 7 is recommended to minimize the effects of ground reflection.

Acoustofluidic tweezers via ring resonance.

Ring resonator (RR) devices are closed-loop waveguides where waves circulate only at the resonant frequencies. They have been used in sensor technology and optical tweezers, but controlling micron-scale particles with optical RR tweezers is challenging due to insufficient force, short working distances, and photodamage. To overcome these obstacles, an acoustofluidic RR-based tweezing method is developed to manipulate micro-sized particles that can enhance particle trapping through the resonance interaction of acoustic waves with high Q factor (>3000), more than 20 times greater than traditional acoustic transducers. Particles can be precisely manipulated within the RR by adjusting the signal phase, with trapping amplified by enlarging the connected waveguide. Rapid particle mixing is achieved when particles are placed between the waveguide and RR. The signal path is strengthened by strategically positioning the RR in a two-dimensional plane. Acoustofluidic RR tweezers have immense potential for advancing applications in biosensing, mechanobiology, lab-on-a-chip, and cell-cell communication research.

Emerging role of macrophage polarization in disease

Abstract. Macrophages, present in many human cells and play an essential duty in human body, Triggered macrophages are usually separated into 2 phenotypes, depending on a range of aspects. M1 produces a pro-inflammatory feedback, while M2 is anti-inflammatory and fixings cells. In infection, macrophages polarize to M1 to eliminate virus and then to M2 to fix tissues. Excitement of macrophage polarization regulates immune function. Macrophage polarity plays a significant role in infections, inflammatory conditions, and hatreds; its monitoring is crucial for the prevention and therapy of condition. Consequently, this evaluation summarizes the governing mechanisms of macrophage polarization, suggesting that macrophages are a heterogeneous course of cells that can rapidly change their phenotype in feedback to exterior signals. Among them, TLR4 receptor sets off pro-inflammatory actions with MyD88 and TRIF signaling pathways.Notch signaling pathway controls mobile features and may contribute in macrophage apoptosis and M1/M2 polarization.JAK/STAT signaling path manages macrophage inflammatory feedbacks and advertises M1-type pro-inflammatory feedbacks and M2-type anti-inflammatory differentiation. Exhibits the function of macrophage polarization in inflammatory conditions such as sensitive bronchial asthma, atherosclerosis, and excessive weight. The crucial duty of macrophages in illness pathogenesis and inflammatory guideline is explored.

Multi-Frequency Microwave Sensing System with Frequency Selection Method for Pulverized Coal Concentration.

The accurate measurement of pulverized coal concentration (PCC) is crucial for optimizing the production efficiency and safety of coal-fired power plants. Traditional microwave attenuation methods typically rely on a single frequency for analysis while neglecting valuable information in the frequency domain, making them susceptible to the varying sensitivity of the signal at different frequencies. To address this issue, we proposed an innovative frequency selection method based on principal component analysis (PCA) and orthogonal matching pursuit (OMP) algorithms and implemented a multi-frequency microwave sensing system for PCC measurement. This method transcended the constraints of single-frequency analysis by employing a developed hardware system to control multiple working frequencies and signal paths. It measured insertion loss data across the sensor cross-section at various frequencies and utilized PCA to reduce the dimensionality of high-dimensional full-path insertion loss data. Subsequently, the OMP algorithm was applied to select the optimal frequency signal combination based on the contribution rates of the eigenvectors, enhancing the measurement accuracy through multi-dimensional fusion. The experimental results demonstrated that the multi-frequency microwave sensing system effectively extracted features from the high-dimensional PCC samples and selected the optimal frequency combination. Filed experiments conducted on five coal mills showed that, within a common PCC range of 0-0.5 kg/kg, the system achieved a minimum mean absolute error (MAE) of 1.41% and a correlation coefficient of 0.85. These results indicate that the system could quantitatively predict PCC and promptly detect PCC fluctuations, highlighting its immediacy and reliability.

A lightweight reversible multi-mode physical unclonable function

Physical Unclonable Function (PUF), a hardware security primitive capable of generating unique fingerprints for chips, is crucial for Internet of Things (IoT) security. However, substantial hardware overhead, low reliability, and high power consumption have hindered the broad application of PUFs in lightweight IoT devices. This paper proposes a solution by leveraging the reversible logic paradigm in PUF design. Specifically, a Multi-Mode (M2) PUF is introduced and is based on configurable ring oscillators and transient effect rings. By configuring signal paths and internal delays, the M2 PUF efficiently generates numerous Challenge-Response Pairs (CRPs) with minimal hardware resources. Implemented on Xilinx Spartan-6 and Xilinx Virtex-7 FPGA platforms, it requires only 1.6 % of the hardware resources to generate a 1-bit response, significantly lower than existing state-of-the-art PUF solutions. The performance metrics for uniqueness, average native reliability, and reliability under different voltage conditions are impressive, registering at 48.23 %, 98.44 %, and 96.08 %, respectively. This structure represents an ideal solution for lightweight PUF design.

Limits to dynamic range in GHz-THz single-dish planetary spectra

Abstract When bright solar-system objects are observed by GHz-THz regime telescopes, off-axis signals bounce around locally and re-enter the signal path with a time delay, causing sinusoidal ripples in output spectra. Ripples that are unstable over time are challenging to remove. A typical detection limit for planetary spectral lines is a fraction ∼10−3 of continuum signal, restricting searches for minor atmospheric trace-gases. Modern wideband spectra of Venus demonstrate a plethora of effects, at three example telescopes spanning nearly a factor-of-50 in frequency. Characterisation of instrumental effects as families of pure sine-waves via Fourier-analysis is shown to improve dynamic-range by factors of a few. An example upper limit on sulphuric acid (H2SO4) vapour in Venus’ mesosphere, from fully-automated data-cleaning of a 3.5 GHz band containing 10 line components, goes as deep as the best previously-published limit. The most challenging cases are searches for single lines of width comparable to ripple periods. Traditional polynomial-fitting approaches can be deployed to test for false positives, to demonstrate robustness at a level of zero ”fake lines” in >1000 comparisons. Fourier-based data-cleaning avoids subjectivity and can be fully automated, and synthetic spectra can be injected before processing to test to what degree signals are lost in cleaning. An ideal robustness strategy is mitigation at the data-acquisition stage, e.g. using slow drifts in target-velocity with respect to the telescope to isolate a planetary line from a quasi-static instrumental ripple pattern.

On the accuracy of distance estimates by propagation time of sound signals on the arctic shelf

As part of numerical modeling, estimates are made of the accuracy of determining the distance between underwater sources and sound receivers located at a distance of several kilometers from each other in the Kara Sea in the autumn. It is assumed that the main source of possible errors in determining the distance is the lack of accurate data on the vertical profile of the sound speed along the propagation path of acoustic signals. Data from September and November were analyzed, in the interval between which significant changes in the profile take place, when the vertical gradient of sound speed changes from negative to positive values. Characteristic values of sound speed variations were obtained by statistical processing of hydrological data taken from the World Ocean Database. The results obtained are important for analyzing the capabilities of underwater acoustic navigation.

Fucoidan from Stichopus chloronotus relieved DSS induced ulcerative colitis through inhibiting intestinal barrier disruption and oxidative stress.

Intestinal barrier disruption and oxidative stress are the major pathological features during the ulcerative colitis (UC). The present research aimed to explore the amelioration property of fucoidan of Stichopus chloronotus (FucSc) against dextran sulfate sodium (DSS) resulted UC. The findings from our study suggest that treating with Fuc-Sc improved the integrity of the Caco-2 monolayer through raising its TEER value, reducing LDH release, promoting the tight junction proteins (TJs) in Caco-2 cells, and shielding the cells from decreases of these proteins caused by H2O2. Besides, Fuc-Sc activated Nrf2/HO-1 pathway to facilitate the antioxidant activities of Caco-2 cells under oxidative stress through elevating the SOD and GSH, and reducing LDH and MDA. Furthermore, oral administration of Fuc-Sc attenuated DSS resulted body weights decrease, DAI score increase, colon length decrease, and structural damage of colon tissue. Fuc-Sc also promoted the barrier function and suppressed oxidative injury via activation of Nrf2/HO-1 signal path. Collectively, this research provided the theoretical foundation for fucoidan as a promising functional food for colitis.

Employing stable isotopes to reveal temporal trajectories of water travelling through the soil–plant-atmosphere continuum

The spatiotemporal patterns of water travelling through the soil–plant-atmosphere continuum (SPAC) have received much attention due to the frequency of extreme weather and water scarcity. However, the interconnections and transboundary transport of specific compartments within the hydrologic cycle are poorly understood. We portrayed the propagation paths of water isotope signals by analyzing isotopes of precipitation, soil water, and xylem water. The isotope sine curves analysis method was improved to quantify water transfer efficiency, mean transmission time from precipitation to soil (MTT1), mean transmission time from soil to trees (MTT2), mean residence time within soil (MRTSW), and mean residence time within tree xylems (MRTXY). The temporal trajectory of water traveling through SPAC was depicted, and its influencing factors and intrinsic mechanisms were explored. Our results showed that (1) water isotopes were blocked when crossing water pools (precipitation, soil water, and xylem water) and the transfer efficiency was progressively weaker (85.5 %→13.5 %). (2) The MTT1 was significantly and positively correlated with soil porosity (Spearman correlation coefficient, 0.551). Its spatiotemporal pattern (0.8–15.9d) indicated that the transport and mixing of soil water involved two modes: displacement flow and bypass flow. The MTT2 (−13.2d–4.3d) of Platycadus orientalis was in general smaller than that of Quercus variabilis (−4.7d–11.5d). (3) The MRT (35.2d–343.8d) was influenced by a combination of soil physicochemical properties, root distribution, and tree morphological traits. Our study shows that connectivity between pools is better reflected with transfer efficiency. Comparing MTT and MRT of P. orientalis and Q. variabilis, tree hydrodynamic processes were quantified, and P. orientalis was more sensitive to seasonal moisture variability. Additionally, our study improved the understanding of the “black box” within the hydrological interface of plant-soil interactions.

Delayed response of the coastal sedimentary record to the southward shift of the Huanghe (Yellow River) course during AD1128–1855

The sediment source-to-sink process is an important topic in marine sedimentology. However, how sedimentary signals evolve along source-to-sink path remains less clear. This study focuses on the southward shift of the Huanghe River course between AD 1128 and 1855, and the manifestation and variation of sedimentary signals in a natural diffusion system were investigated through sedimentological analysis of three spatially adjacent regions, the abandoned Huanghe Delta, the central coast of Jiangsu, and the Changjiang Delta. Laboratory analyses including Optically Stimulated Luminescence (OSL), geochemical element analysis, and grain size analysis, were conducted. The results show that sedimentary signals manifest in various forms, primarily manifested in two ways: grain size refinement and sedimentation rate acceleration. The fining of grain size is most pronounced in the abandoned Huanghe delta, followed by the central coast of Jiangsu, and is least pronounced in the Changjiang subaqueous delta. The response of the coastal system to the event was delayed by approximately 0–100, 100–300, and 300–500 years for the abandoned Huanghe Delta, the central coast of Jiangsu, and the Changjiang River Delta, respectively. These findings indicate that sediment transport processes exhibit sedimentary signal attenuation and response lag. This study not only highlights the variation along the source-sink path of coastal sedimentary signals but also illuminates the sedimentary record of drastic changes in sediment flux, which will help study the source-to-sink process given the variable changes in sedimentary fluxes.

A 23–29 GHz GaN Low-Noise Amplifier with Drain-to-Source Coupling Feedback

In this paper, a four-stage gallium nitride (GaN) low noise amplifier (LNA) using coupled-line (CL) feedback in a 0.15-μm GaN-on-SiC process is proposed. The electromagnetic coupling feedback between the drain and source of each transistor is employed to generate an additional signal path for neutralization, which enhances gain and improves stability performance. A series transmission line-capacitor-transmission line (TL-C-TL) network is introduced between stages of the LNA for wider band interstage matching. The measured results show that the designed LNA achieves a 3-dB bandwidth of 23.6 to 29.8 GHz, a peak gain of 23.7 dB at 25.8 GHz, and a minimum noise figure (NF) of 2.2 dB at 27.8 GHz. The output-referred 1-dB compression point (OP1dB) is 13 dBm. The total power consumption of the LNA is 200 mW.

Location of 5G base station antenna in substation taking into account path loss and RF radiation

Aiming at the engineering problem that 5G base station antenna is difficult to locate efficiently in complex electromagnetic environment, a two-stage positioning method of 5G base station antenna substation is proposed, which considers signal path loss and antenna RF radiation. Firstly, the path loss solution model of the 5G base station antenna signal in the substation is established, and the RF radiation solution model generated by the coupling excitation of 5G high-frequency electromagnetic wave and the metal shell of the electrical equipment is constructed based on the big element physical optics method. Secondly, combining the advantages of particle swarm optimization (PSO) and interior point algorithm, the antenna positioning method considering path loss and RF radiation is constructed. Among them, in the first stage, the minimum loss of 5G signal path in the substation is taken as the goal, and the antenna stations in the substation are searched globally to get the optimal pre-selected position. In the second stage, the antenna position is calibrated according to the pre-selected position, so that the interference of RF radiation is minimized, and the final position is output. Finally, a 500 kV 5G substation in Henan Province was taken as the simulation object. Compared with the original scheme, the simulation results ensured the minimum 5G path loss in the substation and took into account the electromagnetic compatibility of the equipment in the substation. The effectiveness of the location strategy for maintaining the safe operation of the substation is verified, and it can provide a reference for the 5G base station antenna positioning project of the substation.

A Novel Ultrasonic Leak Detection System in Nuclear Power Plants Using Rigid Guide Tubes with FCOG and SNR.

Leak detection in nuclear reactor coolant systems is crucial for maintaining the safety and operational integrity of nuclear power plants. Traditional leak detection methods, such as acoustic emission sensors and spectroscopy, face challenges in sensitivity, response time, and accurate leak localization, particularly in complex piping systems. In this study, we propose a novel leak detection approach that incorporates a rigid guide tube into the insulation layer surrounding reactor coolant pipes and combines this with an advanced detection criterion based on Frequency Center of Gravity shifts and Signal-to-Noise Ratio analysis. This dual-method strategy significantly improves the sensitivity and accuracy of leak detection by providing a stable transmission path for ultrasonic signals and enabling robust signal analysis. The rigid guide tube-based system, along with the integrated criteria, addresses several limitations of existing technologies, including the detection of minor leaks and the complexity of installation and maintenance. By enhancing the early detection of leaks and enabling precise localization, this approach contributes to increased reactor safety, reduced downtime, and lower operational costs. Experimental evaluations demonstrate the system's effectiveness, focusing on its potential as a valuable addition to the current array of nuclear power plant maintenance technologies. Future research will focus on optimizing key parameters, such as the threshold frequency shift (Δf) and the number of randomly selected frequencies (N), using machine learning techniques to further enhance the system's accuracy and reliability in various reactor environments.

A compact dual‐band bandpass filter based on coupled stub‐loaded square ring resonators by using transversal signal‐interaction concepts

AbstractIn this paper, a novel dual‐band wideband bandpass filter (BPF) based on transversal signal‐interaction concepts with a wide upper stopband is proposed and investigated. The designed specification of two passbands can be managed and satisfied based on the independent controllable fractional bandwidth of the two passbands and the centered frequencies. The centered frequencies of dual‐band BPF are, respectively, 0.79 GHz (ƒ1) and 1.24 GHz (ƒ2) with 3 dB fraction bandwidths of 26.54% and 11.3%. Two transmission paths consisting of coupled stub‐loaded square ring resonators and anti‐coupled shorted lines are used to realize signal cancellation of multiple transmission path signal transmission from Port 1 to Port 2. Eleven transmission zeros (TZs) modify harmonic suppression up to 10 ƒ1 with stopband rejection higher than 15 dB. Butterworth lumped notch network and step impedance resonator (SIR) are also utilized to improve the selectivity and harmonic suppression. A compact filter with a circuit size of 0.08λg × 0.08λg is implemented and tested. Good agreement between simulation and measured results verifies the reliability of the designing scheme.

Explainable fault diagnosis method for process flow based on data augmentation with system graph relationship

The main objective of process industrial systems is to ensure safe operation. Signal fluctuations resulting from equipment failures and variable abnormalities can progressively propagate over the entire system, potentially resulting in fault conditions. However, the sporadic occurrence of fault conditions leads to a scarcity of data samples for diagnosis models. A fault diagnosis method for process flow based on data augmentation with system graph relationships is proposed. Propagation paths of fault signals are generated through graph relationships of systems. Simultaneously, the data of multiple nodes in paths is transformed to generate augmentation samples. To ensure comprehensive learning of the information included in augmentation samples, a large number of samples are generated for pre-training based on real-world data from a system. The explainability analysis method is used to analyze the focus area of diagnostic networks on samples with and without augmentation. The experimental results demonstrate that the proposed method can substantially improve diagnostic accuracy and explainability, hence offering advantages for diagnosis tasks in small sample cases.

SNR analysis of a multi-channel temporal correlation scheme in quantum-enhanced target detection.

In lossy and noisy environments, quantum-enhanced target detection based on temporal quantum correlation encounters low signal-to-noise ratio (SNR), resulting in poor detection performance. To address these challenges, we propose a multi-channel temporal correlation scheme. In this scheme, signal photons from multiple independent entangled sources illuminate the target and arrive at the same detector. Coincidences are obtained by correlation measurements of the entangled photons on one signal path and different reference paths. We then propose a weighted average processing method for fusing the coincidences to obtain higher SNR. The relationship between the SNR and the number of sources is analyzed for different background noise levels. It is shown that the SNR increases as the number of sources increases, but eventually approaches a limit. Experimental results verify the correction of our theoretical analysis.

Segmented propagation model for the paths and travel times of surface duct leaky signals.

In the deep ocean environment with a surface duct, sound propagating within the duct leaks into the geometric shadow zone below it. However, the propagation paths and time of these leaky parts have not been fully characterized. This paper investigates the mechanism of surface duct leaky (SDL) signals based on normal mode theory. It reveals that SDL signals are caused by specific modes with grazing angles close to zero at the bottom of the surface duct. Combining the theory of diffracted sound rays, the study proposes a Segmented Propagation model (SPM) for SDL signals. The propagation paths of SDL signals are divided into three segments: S1, which extends from the source to the surface duct; S2, the segment propagating within the surface duct; and S3, the segment leading from the surface duct to the receiver. The proposed SPM describes the propagation mechanism of SDL signals and allows for precise calculation of their propagation time. Experimental data from the western Pacific are used to verify the SPM.