Communication Signals Research Articles

Dual-targeted fluorescent probe for tracking polarity and phase transition processes during lipophagy.

Eukaryotic cells regulate various cellular processes through membrane-bound and membrane-less organelles, enabling active signal communication and material exchange. Lysosomes and lipid droplets are representative organelles, contributing to cell lipophagy when their interaction and metabolism are disrupted. Our limited understanding of the interacting behaviours and physicochemical properties of different organelles during lipophagy hinders accurate diagnosis and treatment of related diseases. In this contribution, we report a fluorescent probe, PTZ, engineered for dual-targeting of lipid droplets and lysosomes. PTZ can track liquid-liquid phase separation and respond to polarity shifts through ratiometric fluorescence emission, elucidating the lipophagy process from the perspective of organelle behavior and physicochemical properties. Leveraging on the multifunctionality of PTZ, we have successfully tracked the polarity and dynamic changes of lysosomes and lipid droplets during lipophagy. Furthermore, an unknown homogeneous transition of lipid droplets and lysosomes was discovered, which provided a new perspective for understanding lipophagy processes. And this work is expected to serve as a reference for diagnosis and treatment of lipophagy-related diseases.

Sudden modulation in the UHF wireless signals probably caused by the activation of pre‑earthquake processes. Case studies for the Balkans (SE Europe)

We study the atmospheric variations of broadband wireless signal propagation intensity correlated with pre‑earthquake processes. We have maintained ground observations in the VHF range of 1.8 and 3.5 GHz in Bulgaria (Southeast Europe), close to the border with Greece and Northern Macedonia, since 2012. The signal source is 1.8 GHz –LTE broadcasting cellular communication signal and the receivers are digital HF to SHF antennae collecting the data via mobile internet. Our observations revealed phenomena associated with a natural enhancement of the intensity of the signals (no change in the transmitting level) days/hours before the seismic events, even far from the observation region. We are presenting the results for four significant earthquakes in the area: (1) M5.6 on May 22, 2012, in Bulgaria, (2) M6.9 on May 24, 2014, in the Aegean Sea, Greece, (3) M6.5 on Nov 17, 2015, Lefkada, Greece, and (4) M6.3 of May 12, 2017, in Western Türkiye. Some changes in the atmospheric boundary layer (ABL), triggered by an intensification of radon and other released gases, could lead to a change in lower atmospheric conductivity. Although the intensity modulation was observed far (> 200 km) from the epicenter areas, the anomalies were always inside the estimates of the Dobrovolsky‑Bowman area of preparation. We examined the possible correlation between magnitude and the spatial size of the earthquake preparation zone in the Lithosphere‑Atmosphere-Ionosphere coupling (LAIC) framework.

Design of industrial equipment data acquisition system based on ZYNQ

Abstract In this paper, an industrial equipment data acquisition system based on a ZYNQ chip is constructed using an AD7607 data acquisition module containing a symmetric layout. Next, four modules of signal output, data writing, caching and communication are designed. Focusing on the design of the signal processing system after analog-to-digital conversion, the D-S evidence processing algorithm is utilized to judge the obtained data independently and fuse the data based on its D-S combination rule. Finally, the industrial equipment acquisition system design is tested, and the test includes system performance, accuracy, and stability. The frequency peaks obtained by the system in this paper are all 1000.000Hz, as shown by the results. The signal peak value of 95.18mV, the NI acquisition card signal peak value of 98.33mV, and the error is only 0.89%. The signal-to-noise ratio of the sampled signal is 50.12dB, and the effective number of bits reaches 10.40 bits. The performance of the system and the accuracy and stability of data acquisition on industrial equipment are verified.

Unraveling the Complexity with Applications of Nonlinear Analysis in Signal Processing and Communication Engineering

Nonlinear analysis is an essential area of signal and communication engineering. Many different kinds of nonlinear analysis can be used in this study. Linear signal processing techniques had previously struggled to accurately capture complex data pattern and communication signals. However, the development of non-linear analysis is a game-changing advancement since it provides a solid framework for understanding and manipulating these complex and non-trivial dynamics. In order to understand the behaviour of a wide variety of signals, from financial market trends to biological and environmental data, non-linear techniques are essential in signal processing. Improved understanding of system behaviour and predictive models may result from the use of such techniques to extract complex data patterns that are not often used. Non-linear approaches also contribute to the development of image and video processing by easing the development of advanced compression, tracking, and object recognition algorithms. Non-linear analysis is crucial in communication engineering as it aids in comprehending and optimising the flow of information across various channels. A greater understanding of signal distortion is made possible by the nonlinear perspective, which makes it possible to build reliable communication systems that can withstand interference and noise. By facilitating the creation of sophisticated modulation systems, adaptive equalisation methods, and error control coding, it raises the communication networks' dependability and effectiveness. Designing complex systems that can handle the complexities of today's data and communication demands is made possible by the paradigm-shifting synergy of nonlinear analysis, signal processing, and communication engineering. This abstract highlights the role that nonlinear analysis plays in transforming various fields and highlights how it can be used to solve changing problems related to information comprehension, processing, and transmission in a technologically sophisticated world.

A Putative NADPH Oxidase Gene in Unicellular Pathogenic Candida glabrata Is Required for Fungal ROS Production and Oxidative Stress Response.

Most previous studies on fungal NADPH oxidases (Nox) focused on multicellular fungi and highlighted the important roles of Nox-derived reactive oxygen species (ROS) in cellular differentiation and signaling communication. However, there are few reports about Nox in unicellular fungi. A novel NOX ortholog, CAGL0K05863g (named CgNOX1), in Candida glabrata was investigated in this study. Deletion of CgNOX1 led to a decrease in both intracellular and extracellular ROS production. In addition, the Cgnox1∆ mutant exhibited hypersensitivity to hydrogen peroxide and menadione. Also, the wild-type strain showed higher levels of both CgNOX1 mRNA expression and ROS production under oxidative stress. Moreover, the absence of CgNOX1 resulted in impaired ferric reductase activity. Although there was no effect on in vitro biofilm formation, the CgNOX1 mutant did not produce hepatic apoptosis, which might be mediated by fungal Nox-derived ROS during co-incubation. Together, these results indicated that the novel NOX gene plays important roles in unicellular pathogenic C. glabrata and its interaction with host cells.

Courtship behaviour reveals temporal regularity is a critical social cue in mouse communication.

While animals navigating the real world face a barrage of sensory input, their brains evolved to perceptually compress multidimensional information by selectively extracting the features relevant for survival. Notably, communication signals supporting social interactions in several mammalian species consist of acoustically complex sequences of vocalisations. However, little is known about what information listeners extract from such time-varying sensory streams. Here, we utilise female mice's natural behavioural response to male courtship songs to identify the relevant acoustic dimensions used in their social decisions. We found that females were highly sensitive to disruptions of song temporal regularity and preferentially approached playbacks of intact over rhythmically irregular versions of male songs. In contrast, female behaviour was invariant to manipulations affecting the songs' sequential organisation or the spectro-temporal structure of individual syllables. The results reveal temporal regularity as a key acoustic cue extracted by mammalian listeners from complex vocal sequences during goal-directed social behaviour.

Courtship behaviour reveals temporal regularity is a critical social cue in mouse communication

While animals navigating the real world face a barrage of sensory input, their brains evolved to perceptually compress multidimensional information by selectively extracting the features relevant for survival. Notably, communication signals supporting social interactions in several mammalian species consist of acoustically complex sequences of vocalisations. However, little is known about what information listeners extract from such time-varying sensory streams. Here, we utilise female mice’s natural behavioural response to male courtship songs to identify the relevant acoustic dimensions used in their social decisions. We found that females were highly sensitive to disruptions of song temporal regularity and preferentially approached playbacks of intact over rhythmically irregular versions of male songs. In contrast, female behaviour was invariant to manipulations affecting the songs’ sequential organisation or the spectro-temporal structure of individual syllables. The results reveal temporal regularity as a key acoustic cue extracted by mammalian listeners from complex vocal sequences during goal-directed social behaviour.

Investigation on high EMI shielding effectiveness and shielding mechanism of spherical Ti3C2Tx microfilm prepared by spray-freezing

Due to the explosive growth of the number of miniature electronic devices in the 5 G era, higher requirements have been raised for electromagnetic pollution protection materials. The production of effective electromagnetic (EM) interference (EMI) shielding materials is still challenging. In this research, Ti3C2Tx microspheres were successfully synthesized by the self-developed spray freezing technology and 43 µm-thick spherical Ti3C2Tx microfilm was prepared by vacuum filtration. The spherical film can block 5 G communication signals and its EMI shielding effectiveness (SE) is 51 dB, which is 50% higher than that of the 2D Ti3C2Tx film of approximately the same thickness. Additionally, the effects of transmitting X-band EM waves through a 43 µm-thick spherical Ti3C2Tx sheet were simulated employing Comsol Multiphsics. It is found that an annular current traveling perpendicular to the direction of electromagnetic wave propagation will be induced in the spherical Ti3C2Tx, which leads an extra larger EM loss. This discovery provides a novel avenue for the structural design of EMI shielding materials.

Scientific and Engineering Proposals for Improving the Noise Immunity of Receiving Multi-Position Signals in Channels with Variable Parameters

Introduction. An important task faced by the developers of modern telecommunication systems consists in increasing the noise immunity of signal reception in channels with variable parameters. Thus, the communication lines of DVB-T2, DVB-S, and DVB-S2/S2 standards widely apply signal structures (SS) of multi-position quadrature amplitude modulation (M-QAM). However, an analysis of scientific publications shows that the random nature of the phase change of the transformed signal constellation leads to a loss of noise immunity of the M-QAM signals. Engineering solutions for the effective reception of such signals are lacking. The proposed block diagram of a device for receiving quadrature amplitude signals and the developed operation algorithm for an amplitude-phase detector allow random phase changes to be considered and reduced.Aim. Development of scientific and engineering proposals to improve the efficiency of receiving M-QAM signals in radio channels with random phase changes.Materials and methods. The study was conducted using the methods of noise immunity research, as well as communication theory and signal theory.Results. A block diagram of a device for receiving quadrature amplitude signals and an operation algorithm for an amplitude-phase detector were proposed, which allow random phase changes to be considered and compensated for. Scientific and engineering proposals were formulated to improve the noise immunity of M-QAM reception in channels with variable parameters.Conclusion. The developed scientific and engineering proposals for increasing the noise immunity of multi-position quadrature signals in channels with variable parameters substantiate both the feasibility of using a transformed SS M-QAM with improved energy characteristics, as well as the application of the developed receiving device for processing quadrature amplitude signals and the operation algorithm of an amplitude-phase detector. The results obtained make it possible to perform demodulation with simultaneous compensation of phase distortions to increase the noise immunity of M-QAM signal reception.

Engineering the Dielectric Constants of Polymers: From Molecular to Mesoscopic Scales.

Polymers are essential components of modern-day materials and are widely used in various fields. The dielectric constant, a key physical parameter, plays a fundamental role in the light-, electricity-, and magnetism-related applications of polymers, such as dielectric and electrical insulation, battery and photovoltaic fabrication, sensing and electrical contact, and signal transmission and communication. Over the past few decades, numerous efforts have been devoted to engineering the intrinsic dielectric constant of polymers, particularly by tailoring the induced and orientational polarization modes and ferroelectric domain engineering. Investigations into these methods have guided the rational design and on-demand preparation of polymers with desired dielectric constants. This review article exhaustively summarizes the dielectric constant engineering of polymers from molecular to mesoscopic scales, with emphasis on application-driven design and on-demand polymer synthesis rooted in polymer chemistry principles. Additionally, it explores the key polymer applications that can benefit from dielectric constant regulation and outlines the future prospects of this field.

Application of Electronic Communication Signal Modulation Recognition System Based on Fourier Transform

Abstract In this paper, the weighted class fractional Fourier transform is redefined by means of the weighted superposition of state functions, and the Fourier transform is applied to dissect the intrinsic relationship between the M-WFRFT and the 4-WFRFT and to obtain the weighting coefficients of the electronic communication signals. On the basis of the WFRFT discrete algorithm, the electronic communication signal is expanded to include M a term after the M -WFRFT and the hybrid carrier modulation method based on the WFRFT is given. According to the design idea of the electronic communication system, the hardware part and software part of the electronic communication system are designed, and the electronic communication signal modulation recognition system is experimentally analyzed by using the simulation experiment method. The results show that when the signal-to-noise ratio is -8dB and the optimization algorithms are the Sgd algorithm, Sgdm algorithm, and Adam algorithm, the modulation identification accuracy of OFDM signal is 39.3%, 57.5% and 43.5%, respectively, which indicates that the Sgdm optimization algorithm is the most suitable one compared with other algorithms, and it is more effective in the modulation identification of OFDM signals at low signal-to-noise ratio. The number of scans of the three-layer multi-parameter WFRFT signal by the non-cooperative party is 6.4 × 1013 times, and the increase in the number of scans leads to an increase in the cost paid by the non-cooperative party, which confirms that the secure communication system based on three-layer weighted fractional-order Fourier transform has good resistance to parameter scanning characteristics and high confidentiality. This study further improves the a priori parameter setting of the electronic communication system and enhances its complexity, resulting in better anti-interception identification features.

Fault Classification and Diagnosis Approach Using FFT-CNN for FPGA-Based CORDIC Processor

Within the realm of digital signal processing and communication systems, FPGA-based CORDIC (Coordinate Rotation Digital Computer) processors play pivotal roles, applied in trigonometric calculations and vector operations. However, soft errors have become one of the major threats in high-reliability FPGA-based applications, potentially degrading performance and causing system failures. This paper proposes a fault classification and diagnosis method for FPGA-based CORDIC processors, leveraging Fast Fourier Transform (FFT) and Convolutional Neural Networks (CNNs). The approach involves constructing fault classification datasets, optimizing features extraction through FFT to shorten the time of diagnosis and improve the diagnostic accuracy, and employing CNNs for training and testing of faults diagnosis. Different CNN architectures are tested to explore and construct the optimal fault classifier. Experimental results encompassing simulation and implementation demonstrate the improved accuracy and efficiency in fault classification and diagnosis. The proposed method provides fault prediction with an accuracy of more than 98.6% and holds the potential to enhance the reliability and performance of FPGA-based CORDIC circuit systems, surpassing traditional fault diagnosis methods such as Sum of Square (SoS).

Versatile Neuromorphic Modulation and Biosensing based on N-type Small-molecule Organic Mixed Ionic-Electronic Conductors.

The ion/chemical-based modulation feature of organic mixed ionic-electronic conductors (OMIECs) are critical to advancing next generation bio-integrated neuromorphic hardware. Despite achievements with polymeric OMIECs in organic electrochemical neuronal synapse (OENS). However, small molecule OMIECs based OENS has not yet been realized. Here, for the first time, we demonstrate an effective materials design concept of combining n-type fused all-acceptor small molecule OMIECs with subtle side chain optimization that enables robustly and flexibly modulating versatile synaptic behavior and sensing neurotransmitter in solid or aqueous electrolyte, operating in accumulation modes. By judicious tuning the ending side chains, the linear oligoether and butyl chain derivative gNR-Bu exhibits higher recognition accuracy for a model artificial neural network (ANN) simulation, higher steady conductance states and more outstanding ambient stability, which is superior to the state-of-art n-type OMIECs based OENS. These superior artificial synapse characteristics of gNR-Bu can be attributed to its higher crystallinity with stronger ion bonding capacities. More impressively, we unprecedentedly realized n-type small-molecule OMIECs based OENS as a neuromorphic biosensor enabling to respond synaptic communication signals of dopamine even at sub-μM level in aqueous electrolyte. This work may open a new path of small-molecule ion-electron conductors for next-generation ANN and bioelectronics.

Versatile Neuromorphic Modulation and Biosensing based on N‐type Small‐molecule Organic Mixed Ionic‐Electronic Conductors

AbstractThe ion/chemical‐based modulation feature of organic mixed ionic‐electronic conductors (OMIECs) are critical to advancing next generation bio‐integrated neuromorphic hardware. Despite achievements with polymeric OMIECs in organic electrochemical neuronal synapse (OENS). However, small molecule OMIECs based OENS has not yet been realized. Here, for the first time, we demonstrate an effective materials design concept of combining n‐type fused all‐acceptor small molecule OMIECs with subtle side chain optimization that enables robustly and flexibly modulating versatile synaptic behavior and sensing neurotransmitter in solid or aqueous electrolyte, operating in accumulation modes. By judicious tuning the ending side chains, the linear oligoether and butyl chain derivative gNR‐Bu exhibits higher recognition accuracy for a model artificial neural network (ANN) simulation, higher steady conductance states and more outstanding ambient stability, which is superior to the state‐of‐art n‐type OMIECs based OENS. These superior artificial synapse characteristics of gNR‐Bu can be attributed to its higher crystallinity with stronger ion bonding capacities. More impressively, we unprecedentedly realized n‐type small‐molecule OMIECs based OENS as a neuromorphic biosensor enabling to respond synaptic communication signals of dopamine even at sub‐μM level in aqueous electrolyte. This work may open a new path of small‐molecule ion‐electron conductors for next‐generation ANN and bioelectronics.

Performance optimization of spatial diversity antenna using hybrid combination for terrestrial optical wireless communication

The coherent laser signals of optical wireless communication suffer dramatic intensity fluctuations due to the atmospheric turbulence effect. A larger receiver aperture could only increase the average laser intensity without adaptive optics. Adaptive optics and wavefront reconstruction are popular in laser wireless transmission systems. Still, the alternative spatial diversity receivers are more convenient and economical to mitigate the irradiance scintillation, in which the antenna array combines multiple signals in digital signal processing or analog laser beams coherent combination. We provide channels correlated spatial diversity models and compare the performances of digital and optical combinations. In addition, reception experiments with a 19-aperture optical combination for horizontal 2 km transmission showed a ten times increase in average optical intensity and decreased scintillation index to 16 %. The large-scale spatial diversity receivers of 64-aperture that adopt hybrid optical and digital combinations are proposed to reduce the complexity of digital processing or cascaded optical combination structure.

Retracted: Research on Spectrum Feature Identification of Indoor Multimodal Communication Signal

Retracted: Research on Spectrum Feature Identification of Indoor Multimodal Communication Signal

A NavCom Signal Authentication Scheme Based on Twice Two-Way Satellite Time Transfer

Low Earth Orbit (LEO) satellite communication systems typically achieve identity authentication through the encryption and decryption of two-way information, which requires complex key management systems. In contrast, the integration of navigation and communication (NavCom) signals provides novel opportunities for physical observation and authentication solutions due to its measurement functions. This paper introduces a novel signal authentication scheme based on twice two-way satellite time transfer (TWSTT) for LEO satellite systems. It leverages the non-mutated nature of the clock difference to ascertain the legitimacy of the signal by measuring the clock difference of signals at different instances. Unlike traditional authentication methods, this approach directly exploits the temporal and spatial characteristics of the signal, negating the necessity for intricate authorization key systems. Additionally, it adeptly tackles the challenges posed by spoofing interference. The performance analysis indicates that this scheme can achieve a high detection probability for the repeater spoofing signal in the low carrier-to-noise ratio conditions.

Slot-Waveguide Based All-Optical RF Spectrum Analyzer

All-optical radio-frequency spectrum analyzers (AORFSAs) with ultrabroad bandwidth break the electronic bottleneck and provide an efficient frequency analysis means for ultrafast optical signals in communications, signal generation and processing systems. Here, we propose and experimentally demonstrate an AORFSA built on the cross-phase modulation effect in a 50 cm long CMOS-compatible photonic slot-waveguide. The waveguide has a 100 nm thick thin-film core of fused silica that is sandwiched by two 750 nm thick cladding layers of high-index doped silica, which shows optimized dispersion and comparable nonlinear characteristics. The measured 3 dB bandwidth of the proposed slot-waveguide-based AORFSA has a three-fold increase over the conventional channel waveguide having the same dimension and length. The sensitivity and wavelength- and polarization-dependence properties are investigated, confirming the proposed waveguide as a versatile platform for frequency analysis of ultrafast optical signals, such as Kerr microcombs with hundreds of GHz or even THz mode spacing.

Coordination of marine multi robot systems with communication constraints

This article focuses on the coordination and communication aspects of multi-robot systems (MRS) and explores what, how and when robots should coordinate and communicate in marine environment. It includes a comparative analysis of MRS coordination under communication constraints in aerial, terrestrial, and marine environments. In the light of the gaps identified in the current MRS literature, we focus on how to tackle the inherent communication constraints presents in marine environments. Thus, a review of Marine Multi-Robot systems (MMRS) is presented, proposing a taxonomy that classifies them according to how they communicate and coordinate. In this line, the classification of different communication strategies found in the literature has received significant attention. Additionally, a MMRS coordination approach is proposed where a heterogeneous group of marine vehicles must explore an unknown area maximizing communication. The proposed approach uses a real characterization of the acoustic communication signal quality as input to the decision making process. To validate its effectiveness, our approach has been subjected to a series of highly realistic experiments.

Prototypical Network with Residual Attention for Modulation Classification of Wireless Communication Signals

Automatic modulation classification (AMC) based on data-driven deep learning (DL) can achieve excellent classification performance. However, in the field of electronic countermeasures, it is difficult to extract salient features from wireless communication signals under scarce samples. Aiming at the problem of modulation classification under scarce samples, this paper proposes a few-shot learning method using prototypical network (PN) with residual attention (RA), namely PNRA, to achieve the AMC. Firstly, the RA is utilized to extract the feature vector of wireless communication signals. Subsequently, the feature vector is mapped to a new feature space. Finally, the PN is utilized to measure the Euclidean distance between the feature vector of the query point and each prototype in this space, determining the type of the signals. In comparison to mainstream few-shot learning (FSL) methods, the proposed PNRA can achieve effective and robust AMC under the data-hungry condition.