Signal Transmission Process Research Articles

Development and verification of real-time hybrid model test delay compensation method for monopile-type offshore wind turbines

The real-time hybrid model (RTHM) test is adept at addressing the scale contradiction, the lack of fidelity in wind modelling in hydrodynamic testing facilities and spatial constraints inherent in conventional monopile-type offshore wind turbine (OWT) model testing methods, thus emerging as an effective avenue for conducting physical model tests of Monopile-type OWTs. This method entails the reproduction of aerodynamic loads or platform motions using loading device or vibration tables. Time delays in the physical attributes of the loading device and signal transmission processes within the system can result in error accumulation, with the potential to impact overall system stability. Moreover, time delay compensation algorithms for hybrid model test systems with force control loading can easily generate excessive noise, leading to system divergence. As a result, time delay has emerged as a technical challenge in the RTHM test. To address this issue, this paper has developed second-order and third-order polynomial extrapolation algorithms, alongside an adaptive compensation algorithm. The adaptive compensation algorithm employs the least squares method to identify parameters of the loading system, enabling it to address variations in the time delay of the experimental system caused by the nonlinearity of the loading system and changes in the physical properties of the model. The feasibility and effects of time delay compensation for various algorithms are validated through numerical simulation. Results indicate that the adaptive compensation algorithm surpasses second and third-order polynomial extrapolation compensation algorithms in terms of accuracy and compensation effectiveness. To validate the applicability of the adaptive compensation algorithm, a RTHM test was conducted. Across rotor thrust force (RotThrust) and tower top displacement, there was an average reduction of approximately 5 % and 9 % in the maximum and minimum synchronization errors, respectively. This highlights the efficacy of the delay compensation algorithm in practical applications, notably diminishing time delay errors within the experimental system. The adaptive compensation algorithm continuously adjusts and updates parameters, enhancing the adaptability of the compensation process to time-varying systems.

Terminological features of the concept of signal-to-noise ratio when processing ultra-wideband signals

Currently, when processing various signals and studying various types of receivers, there are many definitions for one of the basic characteristics of radio systems – signal-to-noise ratio (SNR). At the same time, the terminological feature of the SNR concept is that any definition within the framework of a locally solvable signal processing problem is correct. However, difficulties arise when comparing the effectiveness of one algorithm with another, when studying different signal models, or when measuring the SNR in different parts of the receiving system. Some researchers ignore this fact due to the apparent absolute clarity of this issue, which leads to incorrect comparison of various processing algorithms or the formation of obviously unrealizable requirements for the designed equipment. In each locally solved problem, the determination of SNR will be individual, and comparison of efficiency at a fixed SNR must be carried out with mandatory scaling of signal energies depending on the formulation of the problem. This paper systematizes the terminological features of the SNR concept in order to ensure uniformity of its application by researchers and engineers. The purpose of the work is to systematize the definition of SNR for various signal models and conditions for measuring this characteristic, to specify the results in terms of terminological features of UWB signal processing and to propose a model for recalculating the SNR depending on the stage of the signal transmission and reception process. The paper examines the determination of SNR at the input and output of optimal and matched filters, at the output of optimal receivers operating under conditions of various a priori uncertainties, as well as when processing various classes of signals. By determining the SNR at the output of the matched filter and the SNR at the output of the maximum likelihood receiver for a rectangular video pulse, the discrepancy between the signal energies, all other things being equal, is clearly demonstrated. A connection has been established between the SNR when processing ultra-wideband signals at the output of the optimal receiver with similar devices for processing other types of signals, as well as with the SNR at the input of the receiving system. Systematization of the terminological features of the SNR concept will allow theoretical researchers to choose SNR definitions that are as close as possible to practical applications when analyzing the effectiveness of synthesized algorithms, and will allow practicing engineers to correctly interpret the results of theoretical calculations when developing or testing radio engineering systems.

Silicon artificial neurons for uniform signal transmission and amplification

Simulating the signal transmission process in neurons is crucial in computational neuroscience. However, much of the existing researches simplifies signal transmission in a single neuron to a basic mathematical process. In this article, we introduce an all-optical silicon artificial neuron incorporating an aperiodic gold monotile structure. This structure enables the simulation of uniform signal transmission within the axon. Furthermore, we propose a III-V quantum wells protocol to achieve the amplification function of nodes of Ranvier in neurons.

Triboelectric micro-flexure-sensitive fiber electronics

Developing fiber electronics presents a practical approach for establishing multi-node distributed networks within the human body, particularly concerning triboelectric fibers. However, realizing fiber electronics for monitoring micro-physiological activities remains challenging due to the intrinsic variability and subtle amplitude of physiological signals, which differ among individuals and scenarios. Here, we propose a technical approach based on a dynamic stability model of sheath-core fibers, integrating a micro-flexure-sensitive fiber enabled by nanofiber buckling and an ion conduction mechanism. This scheme enhances the accuracy of the signal transmission process, resulting in improved sensitivity (detectable signal at ultra-low curvature of 0.1 mm−1; flexure factor >21.8% within a bending range of 10°.) and robustness of fiber under micro flexure. In addition, we also developed a scalable manufacturing process and ensured compatibility with modern weaving techniques. By combining precise micro-curvature detection, micro-flexure-sensitive fibers unlock their full potential for various subtle physiological diagnoses, particularly in monitoring fiber upper limb muscle strength for rehabilitation and training.

Discrete Impulsive Signal Observer for Fractional-Order Control Systems and Its Consumer Electronic Circuit Application

In the process of actual electronic equipment signal transmission, interference is inevitable. How to accurately estimate the device status to ensure valid signal travelling is very meaningful. This paper mainly investigates a new transmission signal estimation strategy for fractional order control systems with unknown inputs. Compared with integer order modeling, fractional order modeling can better describe and report the essential process of system signal transmission. By using the fractional order output derivative-based method and convex optimization technique, an effective discrete-time impulsive observer design algorithm is proposed to stabilize the error dynamic systems. Especially, the resulting criterion reflects well the relationship between the fractional order and the pulse signal, and then is applied on a fractional order electronic circuit. It implies that the given conclusions are of significance in signal estimation.

Bioelectric phenomena in electroacupuncture analgesia.

Pain is a complex process of electrical signal transmission. Electroacupuncture may adjust the bioelectric state of the tissues in painful sites through electrical characteristic structural units (acupoints), thereby exerting analgesic effect. The treatment of diseases with electroacupuncture results from the interaction between the external electric field and the electrical properties of acupoint tissues. Therefore, the state of biological tissues and the parameters of electroacupuncture all affect the therapeutic effect.

Triboelectric gait sensing analysis system for self‐powered IoT‐based human motion monitoring

AbstractQuantitative analysis of gait parameters, such as stride frequency and step speed, is essential for optimizing physical exercise for the human body. However, the current electronic sensors used in human motion monitoring remain constrained by factors such as battery life and accuracy. This study developed a self‐powered gait analysis system (SGAS) based on a triboelectric nanogenerator (TENG) fabricated electrospun composite nanofibers for motion monitoring and gait analysis for regulating exercise programs. The SGAS consists of a sensing module, a charging module, a data acquisition and processing module, and an Internet of Things (IoT) platform. Within the sensing module, two specialized sensing units, TENG‐S1 and TENG‐S2, are positioned at the forefoot and heel to generate synchronized signals in tandem with the user's footsteps. These signals are instrumental for real‐time step count and step speed monitoring. The output of the two TENG units is significantly improved by systematically investigating and optimizing the electrospun composite nanofibers' composition, strength, and wear resistance. Additionally, a charge amplifier circuit is implemented to process the raw voltage signal, consequently bolstering the reliability of the sensing signal. This refined data is then ready for further reading and calculation by the micro‐controller unit (MCU) during the signal transmission process. Finally, the well‐conditioned signals are wirelessly transmitted to the IoT platform for data analysis, storage, and visualization, enhancing human motion monitoring.image

Detailed role of microRNA-mediated regulation of PI3K/AKT axis in human tumors.

The regulation of signal transmission and biological processes, such as cell proliferation, apoptosis, metabolism, migration, and angiogenesis are greatly influenced by the PI3K/AKT signaling pathway. Highly conserved endogenous non-protein-coding RNAs known as microRNAs (miRNAs) have the ability to regulate gene expression by inhibiting mRNA translation or mRNA degradation. MiRNAs serve key role in PI3K/AKT pathway as upstream or downstream target, and aberrant activation of this pathway contributes to the development of cancers. A growing body of research shows that miRNAs can control the PI3K/AKT pathway to control the biological processes within cells. The expression of genes linked to cancers can be controlled by the miRNA/PI3K/AKT axis, which in turn controls the development of cancer. There is also a strong correlation between the expression of miRNAs linked to the PI3K/AKT pathway and numerous clinical traits. Moreover, PI3K/AKT pathway-associated miRNAs are potential biomarkers for cancer diagnosis, therapy, and prognostic evaluation. The role and clinical applications of the PI3K/AKT pathway and miRNA/PI3K/AKT axis in the emergence of cancers are reviewed in this article.

Dual-dispersive spectral linear polarization imager based on coded-aperture

Spectral and polarization detections can increase the dimension of data acquisition and enhance the capabilities of target detection systems under complicated circumstances. A spectral linear polarization imager that combines double-disperser coded aperture imaging technology with a division of focal plane polarization detector is proposed in this paper to acquire spectral and polarization information simultaneously. First, the principles and mathematical model of the system are presented, where the proposed mathematical model considers the transformations among different coordinate systems and signal transmission processes, which is realistic and provides guidance for the calibration process. Then, targeting the detection and reconstruction methods based on the Hadamard transform, the loading approach of the coded aperture and the necessity of merging micro-mirror units are analyzed. Finally, according to the actual detection demands, the proposed system can achieve measurements and reconstructions at different spectral resolutions by loading 7th- and 15th-order cyclic S-matrix templates in real-time at the coded template. The results show the Pearson correlation coefficient and the root-mean-square error between the degree of linear polarization values acquired through proposed and reference systems are 0.9975 and 0.0238, respectively. Experimental results also demonstrate that although 15th-order cyclic S-matrix template can result a higher spectral resolution compared with 7th-order cyclic S-matrix template, it decreases the accuracy of the reconstructed results, indicating a trade-off between spectral resolution and accuracy in actual detections.

Activation of TRPV1 Channels Inhibits the Release of Acetylcholine and Improves Muscle Contractility in Mice.

TRPV1 represents a non-selective transient receptor potential cation channel found not only in sensory neurons, but also in motor nerve endings and in skeletal muscle fibers. However, the role of TRPV1 in the functioning of the neuromuscular junction has not yet been fully established. In this study, the Levator Auris Longus muscle preparations were used to assess the effect of pharmacological activation of TRPV1 channels on neuromuscular transmission. The presence of TRPV1 channels in the nerve terminal and in the muscle fiber was confirmed by immunohistochemistry. It was verified by electrophysiology that the TRPV1 channel agonist capsaicin inhibits the acetylcholine release, and this effect was completely absent after preliminary application of the TRPV1 channel blocker SB 366791. Nerve stimulation revealed an increase of amplitude of isometric tetanic contractions upon application of capsaicin which was also eliminated after preliminary application of SB 366791. Similar data were obtained during direct muscle stimulation. Thus, pharmacological activation of TRPV1 channels affects the functioning of both the pre- and postsynaptic compartment of the neuromuscular junction. A moderate decrease in the amount of acetylcholine released from the motor nerve allows to maintain a reserve pool of the mediator to ensure a longer signal transmission process, and an increase in the force of muscle contraction, in its turn, also implies more effective physiological muscle activity in response to prolonged stimulation. This assumption is supported by the fact that when muscle was indirect stimulated with a fatigue protocol, muscle fatigue was attenuated in the presence of capsaicin.

Electrochemical-Memristor-Based Artificial Neurons and Synapses-Fundamentals, Applications, and Challenges.

Artificial neurons and synapses are considered essential for the progress of the future brain-inspired computing, based on beyond von Neumann architectures. Here, a discussion on the common electrochemical fundamentals of biological and artificial cells is provided, focusing on their similarities with the redox-based memristive devices. The driving forces behind the functionalities and the ways to control them by an electrochemical-materials approach are presented. Factors such as the chemical symmetry of the electrodes, doping of the solid electrolyte, concentration gradients, and excess surface energy are discussed as essential to understand, predict, and design artificial neurons and synapses. A variety of two- and three-terminal memristive devices and memristive architectures are presented and their application for solving various problems is shown. The work provides an overview of the current understandings on the complex processes of neural signal generation and transmission in both biological and artificial cells and presents the state-of-the-art applications, including signal transmission between biological and artificial cells. This example is showcasing the possibility for creating bioelectronic interfaces and integrating artificial circuits in biological systems. Prospectives and challenges of the modern technology toward low-power, high-information-density circuits are highlighted.

Design and Simulation of a Hierarchical Parallel Distributed Processing Model for Orientation Selection Based on Primary Visual Cortex.

The study of the human visual system not only helps to understand the mechanism of the visual system but also helps to develop visual aid systems to help the visually impaired. As the systematic study of neural signal processing mechanisms in early biological vision continues, the hierarchical structure of the visual system is gradually being dissected, bringing the possibility of building brain-like computational models from a bionic perspective. In this paper, we follow the objective facts of neurobiology and propose a parallel distributed processing computational model of primary visual cortex orientation selection with reference to the complex process of visual signal processing and transmission between the retina to the primary visual cortex, the hierarchical receptive field structure between cells in each layer, and the very fine-grained parallel distributed characteristics of cortical visual computation, which allow for high speed and efficiency. We approach the design from a brain-like chip perspective, map our network model on the field programmable gate array (FPGA), and perform simulation experiments. The results verify the possibility of implementing our proposed model with programmable devices, which can be applied to small wearable devices with low power consumption and low latency.

Image Mapping Accuracy Evaluation Using UAV with Standalone, Differential (RTK), and PPP GNSS Positioning Techniques in an Abandoned Mine Site.

Global navigation satellite systems (GNSSs) provide a common positioning method that utilizes satellite signals to determine the spatial location of a receiver. However, there are several error factors in standalone GNSS positioning due to instrumental, procedural, and environmental factors that arise during the signal transmission process, and the final positioning error can be up to several meters or greater in length. Thus, real-time kinematic (RTK) correction and post-mission precise point positioning (PPP) processing technologies are proposed to improve accuracy and accomplish precise position measurements. To evaluate the geolocation accuracy of mosaicked UAV images of an abandoned mine site, we compared each orthomosaic image and digital elevation model obtained using standalone GNSS positioning, differential (RTK) GNSS positioning, and post-mission PPP processing techniques. In the three types of error evaluation measure (i.e., relative camera location error, ground control points-based absolute image mapping error, and volumetric difference of mine tailings), we found that the RTK GNSS positioning method obtained the best performance in terms of the relative camera location error and the absolute image mapping error evaluations, and the PPP post-processing correction effectively reduced the error (69.5% of the average total relative camera location error and 59.3% of the average total absolute image mapping error) relative to the standalone GNSS positioning method. Although differential (RTK) GNSS positioning is widely used in positioning applications that require very high accuracy, post-mission PPP processing can also be used in various fields in which it is either not feasible to operate expensive equipment to receive RTK GNSS signals or network RTK services are unavailable.

R & D of prototype iTOF-MRPC at CEE

The cooling storage ring (CSR) external-target experiment (CEE) is a spectrometer running at the Heavy Ion Research Facility (HIRFL) at Lanzhou. The CEE is the first large-scale nuclear physics experimental device by China to operate in the fixed-target mode with an energy of ∼1 GeV. The purpose of the CEE is to study the properties of dense nuclear matter. CEE uses a multi-gap resistive plate chamber (MRPC) as its internal time-of-flight (iTOF) detector for the identification of final-state particles. An iTOF-MRPC prototype with 24 gaps was designed to meet the requirements of CEE, and the readout electronics of the prototype use the FPGA-based time digitization technology. Using cosmic ray tests, the time resolution of the iTOF prototype was found to be approximately 30 ps. In order to further understand how to improve the time resolution of MRPC, ANSYS HFSS was used to simulate the signal transmission process in MRPC. The main factors affecting the timing performance of the MRPC and, accordingly, the optimization scheme are presented.

The Formation of Reputation in CSR Disclosure: The Role of Signal Transmission and Sensemaking Processes of Stakeholders

A growing number of companies are issuing corporate social responsibility (CSR) reports to publicize their commitment to sustainable development. However, skepticism remains among stakeholders about firms’ CSR information, which could hinder the success of worldwide CSR campaigns. Our paper examines mechanisms of how CSR disclosure resonates with stakeholders and influences their attitudes towards firms. Extending the current knowledge of CSR signaling effects, this paper provides a framework illustrating the interplay between CSR signaling properties and readers’ sensemaking processes, thereby predicting how corporate reputation is shaped through CSR communication. In order to test our theoretical hypotheses, a survey was conducted on 53 firms with 1521 respondents. The results show that the better the readers’ comprehension of a CSR report is, the stronger the signals of authenticity and corporate social performance (CSP) they perceive, the better the report value and value fit are recognized, and eventually, the more trust they hold for the firm. The relationship between comprehension of CSR reports and trust is partially mediated by the signaling-sensemaking process. Our research contributes to the literature on micro-foundations of strategic CSR by applying signaling theory in the context of CSR disclosure. The research findings have practical implications for firms’ CSR disclosure strategies.

Time delay effect reduction on the wireless networked control system using an optimized FOPI-FOPD controller

Wireless Networked Control System (WNCS) is made up of an actuator, sensor, and controller that communicates through a wireless network rather than typical point-to-point cable connections. Lower maintenance costs, greater flexibility, and increased safety are the main WNCS advantages, so as a result, it has attracted a lot of researchers. Nevertheless, time delays and packet losses in wireless data transmission are classified as complicated problems, which impair WNCS output accuracy and may influence the overall system stability. Integer-Order PI-PD (PI-PD) and Fractional-Order PI-PD (FOPI-FOPD) controllers are proposed to reduce the impact of the control signal transmission's time delay and improve system performance. Matlab Simulink and True-time simulator are used to simulate the WNCS, and ZigBee protocol is used in transceiving the control signal between the controller and the system. Rotary Inverted Pendulum (RIP) acted as the controller's objective. The Grey Wolf Optimization (GWO) technique is utilized to evaluate the best controller parameters. Xbee S2 modules are used to implement the signal transmission process over ZigBee protocol. The FOPI-FOPD controller outperforms the PI-PD controller in the simulation and experimental results in decreasing the influence of time delay on system stability

Fatiguing freestyle swimming modifies miRNA profiles of circulating extracellular vesicles in athletes

Extracellular vesicles (EVs) are secreted by various tissues and cells under normal physiological or pathological conditions. Exercise-induced EVs may be involved in the adaptation of exercise-induced fatigue. The 1500-m freestyle is the longest pool-based swimming event in the Olympic Games, and there is a paucity of information regarding changes in the miRNA profiles of circulating EVs after a single session of fatiguing swimming. In this study, 13 male freestyle swimmers conducted a fatiguing 1500-m freestyle swimming session at the speed of their best previously recorded swimming performance. Fasting venous blood was collected before and after the swimming session for analysis. 70 miRNAs from the circulating EVs were found to be differentially expressed after the fatiguing 1500-m freestyle swimming session, among which 45 and 25 miRNAs were up-regulated and down-regulated, respectively. As for the target genes of five miRNAs (miR-144-3p, miR-145-3p, miR-509-5p, miR-891b, and miR-890) with the largest expression-fold variation, their functional enrichment analysis demonstrated that the target genes were involved in the regulation of long-term potentiation (LTP), vascular endothelial growth factor (VEGF), glutathione metabolism pathway, dopaminergic synapse, signal transmission, and other biological processes. In summary, these findings reveal that a single session of fatiguing swimming modifies the miRNAs profiles of the circulating EVs, especially miR-144-3p, miR-145-3p, miR-509-5p, miR-891b, and miR-890, which clarifies new mechanisms for the adaptation to a single session of fatiguing exercise from the perspective of EV-miRNAs.

Analysis of Influence of Digitization Process on the Error Characteristics of FOCT

All-fiber optical current transformers have a large dynamic range and fast response speed, which can meet the test requirements of complex electrical signals for a high proportion of new energy grid-connected operations. At present, the main problems are that the key components are easily affected by the complex environment of the substation, and the error stability is poor. In this paper, by analyzing the structure of all-fiber optical current transformers, the signal transmission process and closed-loop system model are established. Based on the method of numerical simulation, the influence of the digital conversion process and digital transmission process on the measurement accuracy of FOCT is analyzed, and the corresponding improvement strategy is proposed to improve the stability of the measurement error of all-fiber optical current transformers.

Semi-analytical approximation of time-fractional telegraph equation via natural transform in Caputo derivative

Abstract In the present research study, time-fractional hyperbolic telegraph equations are solved iteratively using natural transform in one, two, and three dimensions. The fractional derivative is considered in the Caputo sense. These equations serve as a model for the wave theory process of signal processing and transmission of electric impulses. To evaluate the validity and effectiveness of the suggested strategy, a graphical comparison of approximated and exact findings is performed. Convergence analysis of the approximations utilising L ∞ {L}_{\infty } has been done using tables. The suggested approach may successfully and without errors solve a wide variety of ordinary differential equations, partial differential equations (PDEs), fractional PDEs, and fractional hyperbolic telegraph equations.

Dynamic and systemic regulatory mechanisms in rainbow trout (Oncorhynchus mykiss) in response to acute hypoxia and reoxygenation stress

Hypoxia frequently occurs in natural aquatic systems and aquaculture environments due to extreme climate fluctuations, high-density farming, environmental pollution and global warming, resulting in serious ecological damage and enormous economic losses. Rainbow trout (Oncorhynchus mykiss), a key economic fish species worldwide, is extremely sensitive to hypoxia. However, the regulatory mechanisms in response to environmental hypoxia and reoxygenation stress remain unknown. Herein, rainbow trout liver transcriptomes and biochemical parameters were investigated in response to hypoxia for different durations (3, 12 and 24 h), reoxygenation (hypoxia for 24 h followed by reoxygenation for 3 h) and normoxia to highlight dynamic changes in molecular regulation and oxidative stress. In RNA-seq analysis, 5906 differentially expressed genes, two significantly expressed gene sets (profiles 10 and 12) and two hypoxia specific modules (MEgreen and MEturquoise) were screened by differential expression analysis, short time-series expression miner (STEM) and weighted gene co-expression network analysis (WGCNA), respectively. The intersection of the above analyses further identified several key hub genes related to hypoxia, including hif-1α, epo, igfbp1, ddit4, pck1, g6pc, cyp1a1 and dusp1. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses revealed different metabolic strategies at different stress stages; signal transmission and protein synthesis process were strongly influenced by hypoxia. The immune system was inhibited, and a switch from programmed to pathological cell death was observed from hypoxia for 12 h to 24 h. After reoxygenation for 3 h, mitochondrial oxidative phosphorylation was strongly activated to provide more cellular ATP. Enzymatic and non-enzymatic antioxidant systems clearly coordinate to alleviate oxidative stress injury caused by hypoxia. This study reveals dynamic and systemic regulatory mechanisms in rainbow trout liver, and lays a foundation for further study on the molecular mechanisms governing responses to environmental hypoxia and reoxygenation stress.