Communication Signals Research Articles

Size matters: individual variation in auditory sensitivity may influence sexual selection in Pacific treefrogs (Pseudacris regilla).

The matched filter hypothesis proposes a close match between senders and receivers and is supported by several studies on variation in signal properties and sensory-processing mechanisms among species and populations. Importantly, within populations, individual variation in sensory processing may affect how receivers perceive signals. Our main goals were to characterize hearing sensitivity of Pacific treefrogs (Pseudacris regilla), assess patterns of individual variation in hearing sensitivity, and evaluate how among-individual variation in hearing sensitivity and call frequency content affect auditory processing of communication signals. Overall, males and females are most sensitive to frequencies between 2.0 and 2.5kHz, which matches the dominant frequency of the call, and have a second region of high sensitivity between 400 and 800Hz that does not match the fundamental frequency of the call. We found high levels of among-individual variation in hearing sensitivity, primarily driven by subject size. Importantly, patterns of among-individual variation in hearing differ between males and females. Cross-correlation analyses reveal that among-individual variation in hearing sensitivity may lead to differences on how receivers, particularly females, perceive male calls. Our results suggest that individual variation in sensory processing may affect signal perception and influence the evolution of sexually selected traits.

Doppler and Channel Estimation Using Superimposed Linear Frequency Modulation Preamble Signal for Underwater Acoustic Communication

Due to the relative motion between transmitters and receivers and the multipath characteristic of wideband underwater acoustic channels, Doppler and channel estimations are of great significance for an underwater acoustic (UWA) communication system. In this paper, a preamble signal based on superimposed linear frequency modulation (LFM) signals is first designed. Based on the designed preamble signal, a real-time Doppler factor estimation algorithm is proposed. The relative correlation peak shift of two LFM signals in the designed preamble signal is utilized to estimate the Doppler factor. Moreover, an enhanced channel estimation algorithm, the correlation-peak-search-based improved orthogonal matching pursuit (CPS-IOMP) algorithm, is also proposed. In the CPS-IOMP algorithm, the excellent autocorrelation characteristic of the designed preamble signal is used to estimate the channel sparsity and multipath delays, which are utilized to construct the simplified dictionary matrix. The simulation and sea trial data analysis results validated the designed preamble, the proposed Doppler estimation algorithm, and the channel estimation algorithm. The performance of the proposed Doppler factor estimation is better than that of the block estimation algorithm. Compared with the original OMP algorithm with known channel sparsity, the proposed CPS-IOMP algorithm achieves a similar estimation accuracy with a smaller computational complexity, as well as requiring no prior knowledge about the channel sparsity.

Dual Extracellular Recordings in the Mouse Hippocampus and Prefrontal Cortex.

The technique of recording local field potentials (LFPs) is an electrophysiological method used to measure the electrical activity of localized neuronal populations. It serves as a crucial tool in cognitive research, particularly in brain regions like the hippocampus and prefrontal cortex. Dual LFP recordings between these areas are of particular interest as they allow the exploration of interregional signal communication. However, methods for performing these recordings are rarely described, and most commercial recording devices are either expensive or lack adaptability to accommodate specific experimental designs. This study presents a comprehensive protocol for performing dual-electrode LFP recordings in the mouse hippocampus and the prefrontal cortex to investigate the effects of antipsychotic drugs and potassium channel modulators on LFP properties in these areas. The technique enables the measurement of LFP properties, including power spectra within each brain region and coherence between the two. Additionally, a low-cost, custom-designed recording device has been developed for these experiments. In summary, this protocol provides a means to record signals with high signal-to-noise ratios in different brain regions, facilitating the investigation of interregional information communication within the brain.

GLP1R and GIPR expression and signaling in pancreatic alpha cells, beta cells and delta cells

Glucagon-like peptide-1 receptor (GLP1R) and glucose-dependent insulinotropic polypeptide receptor (GIPR) are transmembrane receptors involved in insulin, glucagon and somatostatin secretion from the pancreatic islet. Therapeutic targeting of GLP1R and GIPR restores blood glucose levels in part by influencing beta cell, alpha cell and delta cell function. Despite the importance of the incretin-mimetics for diabetes therapy, our understanding of GLP1R and GIPR expression patterns and signaling within the islet remain incomplete. Here, we present the evidence for GLP1R and GIPR expression in the major islet cell types, before addressing signaling pathway(s) engaged, as well as their influence on cell survival and function. While GLP1R is largely a beta cell-specific marker within the islet, GIPR is expressed in alpha cells, beta cells, and (possibly) delta cells. GLP1R and GIPR engage Gs-coupled pathways in most settings, although the exact outcome on hormone release depends on paracrine communication and promiscuous signaling. Biased agonism away from beta-arrestin is an emerging concept for improving therapeutic efficacy, and is also relevant for GLP1R/GIPR dual agonism. Lastly, dual agonists exert multiple effects on islet function through GIPR > GLP1R imbalance, increased GLP1R surface expression and cAMP signaling, as well as beneficial alpha cell-beta cell-delta cell crosstalk.

Synthesis of electronically tunable multifunction biquad filter using voltage differencing differential input buffered amplifiers

AbstractBiquad filters are commonly used in analog circuits for various purposes in signal processing and communication applications. We synthesize an analog active biquad filter with five types of voltage‐mode filtering functions. The filter is synthesized using a parallel passive resistor‐inductor‐capacitor (RLC) network and unity‐gain voltage differencing amplifier. A voltage differencing differential input buffered amplifier (VD‐DIBA) is the main active component, and the biquad filter has a three‐input single‐output (TISO) topology. By replacing the passive inductor and resistor with VD‐DIBA‐based inductance and resistance simulators with a subtractor, the TISO voltage‐mode versatile filter is obtained from two VD‐DIBAs, one resistor, and two capacitors connected to the ground. The proposed filter can provide five types of voltage‐mode filtering functions: inverting bandpass and lowpass responses as well as noninverting band‐stop, high‐pass, and all‐pass responses. The all‐pass filter requires no additional active components. The three input voltage nodes have high impedance, and a low‐impedance output voltage node facilitates cascade connections without using additional voltage buffers. In addition, the natural frequency and quality factor can be electronically tuned. The quality factor is controlled without disturbing the passband gain and natural frequency. The proposed filter is simulated and verified experimentally in the Personal Simulation Program with Integrated Circuit Emphasis (PSPICE) and through laboratory tests employing VD‐DIBAs implemented using commercially available components.

TOR-GAN: A Transformer-Based OFDM Signals Reconstruction GAN

Reconstruction techniques for communication signals represent a significant research focus within the field of signal processing. To overcome the difficulty and low precision in reconstructing OFDM signals, we introduce a signal reconstruction technique called TOR-GAN (Transformer-Based OFDM Signal Reconstruction GAN). Reconstructing IQ sequences using a CNN and RNN presents challenges in capturing the correlations between two signals. To tackle this issue, the VIT (vision in transformer) approach was introduced into the discriminator network. The IQ signal is treated as a single-channel, two-dimensional image, divided into blocks of 2 × 2 pixels, with absolute position embedding added. The generator network maps the input noise to the same dimension as the IQ signal dimension × embedding vector dimension and adds two identical position embedding data points to the network learning. In the transformer network, prob sparse attention is employed as a replacement for multi-head attention to tackle the issue of high computational complexity. Finally, combined with the MLP structure, the transformer-based generator and discriminator are designed. The signal similarity evaluation index was constructed, and experiments showed that the reconstructed signal under QPSK and BPSK modulation had good reconstruction quality in the time-domain waveform, constellation diagram, and spectrogram at a high SNR. Compared with other reconstruction algorithms, the proposed algorithm improved the quality of the reconstructed signal while reducing the complexity of the algorithm.

Calling for the future of conservation: a protocol for passive acoustic monitoring of small arboreal primates

Biodiversity conservation faces challenges due to a lack of accurate information on species occurrence. Various techniques have been used to survey species diversity and estimate population density, but monitoring species over large spatial and temporal scales remains challenging. Passive acoustic monitoring (PAM) has emerged as a cost-effective and non-invasive method for monitoring biodiversity. PAM utilizes autonomous recording units (ARUs) installed in different areas and is particularly relevant for monitoring threatened species in tropical forest regions. In the case of non-human primates, PAM has proven effective in detecting endangered species, monitoring populations, studying vocal behavior, and evaluating territory use. The black lion tamarin (Leontopithecus chrysopygus), an endangered species of the Atlantic Forest, relies on acoustic signals for communication. This study proposes a PAM protocol for monitoring arboreal primates using the black lion tamarin as a model. It reviews PAM's use in primate research and emphasizes defining target vocalizations. We recommend optimal recording conditions, including distance, height, and equipment. Recordings should be positioned high above the ground, considering the arboreal nature of primates. The choice of spatial distribution, including random placement, transects, and grids, depends on the research question and objectives. Lastly, the study addresses the recording schedule, considering periods of greater species activity, such as from sunrise to sunset. In summary, this study highlights PAM's potential for monitoring arboreal primates providing recommendations for vocalizations, recording conditions, equipment, spatial distribution, and schedules, contributing to effective monitoring, and supporting conservation efforts in tropical forests.

Metasurface Glass for Wireless Communication and Energy Saving.

With the growing global energy demand and environmental issues, energy saving technologies are becoming increasingly important in the building sector. Conventional windows lack energy saving and thermal insulation capabilities, while Low emissivity glass (Low-e glass) attenuates mobile communication signals while reflecting infrared. Therefore, this paper aims to design a type of windows for the "Sub 6GHz" frequency band of 5G. These windows combine the inherent transparency of traditional glass windows with the energy saving properties of Low-e glass, while also ensuring optimal communication performance within the 5G (Sub 6G) band. The metasurface glass is fabricated and subjected to simulation-guided experiments to evaluate their reliability and practicality. The metasurface glass is rigorously assessed in terms of microwave transmission performance, infrared low emissivity performance, and energy saving and thermal insulation capabilities.

Measurement and Calibration of EMF: A Study Using Phone and GBDT for Mobile Communication Signals

AbstractElectromagnetic exposure caused by mobile communication signals has always been a cause of concern. Due to the cost and inconvenience of professional measurement equipment, researchers have turned to smartphone APPs to study and assess the electric field strength caused by mobile communication signals. However, existing cell phone‐based measurements have two weaknesses. First, no system architecture suitable for large‐scale crowdsourced testing has been proposed. Second, since smartphone sensors cannot measure electric field strength directly, existing methods for converting the received signal power of the phone and electric field strength have errors of more than 5 dB. This paper proposes a measurement and calibration method for electric field strength of mobile communication signals based on a smartphone app and gradient boosting decision tree (GBDT). This method consists of a downlink signal acquisition system based on an APP and a calibration model based on GBDT to convert received signal power into electric field strength. The experimental results show that the proposed model achieves a R2 score of 0.93 and a MAE of 0.97 dB. Compared with the existing methods, our method improves the calibration accuracy by 4 dB, enabling large‐scale, low‐cost, and high‐precision direct measurement of the electric field strength of mobile communication signals.

Development of a GSM-RC Automated Device for Measuring Mobile Communication Signal Strength and Meteorological Parameters

The automated Global System for Mobile Communication Signal Strength and Radio Climatological (GSM-RC) measuring device is an integration of different electronic sensors in a box for an in-situ measuring system. The sensor, data logging, and communication subsystems are integrated for transmitting information on meteorological parameters (MPs) and GSM signal strength level (SSL). The goal is to develop a device that could simultaneously measure MP and SSL of GSM communication systems in any location of interest. This is to reduce significant errors due to a lack of synchronization among multiple devices. To accomplish this objective, we designed an atmospheric sensing system with GSM SSL, temperature, relative humidity, and pressure sensors integrated as a GSM-RC unit. An Arduino microcontroller unit was used to wirelessly transmit the data collected by various sensors in each subsystem and stored on a micro-SD card. A statistical analysis of the SSL between the GSM-RC and the Samsung Galaxy A10s mobile reveals a correlation of roughly 0.99. The ANOVA analysis of variance demonstrates no noticeable distinction between the SSL from developed and conventional devices. The P-value is about 0.93, with α-value of 0.05. The MPs were validated with a standard Vintage Pro weather station, and the data were statistically correlated with accuracies close to unity. A field test was carried out with the device to measure the SSL through the GSM and the selected MP in Akure from January to December 2022. The findings indicate a weak and poor correlation between temperature and signal strength, while relative humidity and pressure have a positive and weak correlations with the signal strength. This implies that an increase in SSL leads to a slight decrease in temperature while the relative humidity and pressure increase slightly. Other than being affordable in terms of production and deployment, the device has also solved the problem of labour-intensiveness arising from bulkiness.

A channel state information and geomagnetic fused fingerprint localisation algorithm based on multi‐input convolutional neural network

AbstractNumerous applications require indoor localisation, and one of the current research areas is how to leverage low‐cost ubiquitous signals for indoor localisation. This research designs a multi‐input convolutional neural network (Multi‐CNN) localisation approach to combine natural geomagnetic signals and universal 5G communication signals. To create the location fingerprint data, the geomagnetic three‐component data and channel state information (CSI) must first undergo independent preprocessing. Subsequently, the rebuilt CSI amplitude and geomagnetic intensity are employed for separate offline training to efficiently extract the corresponding data features. Lastly, Multi‐CNN is used to estimate the user's location online. The localisation outcomes for the conference room and hall demonstrate that the Multi‐CNN algorithm can achieve average localisation accuracies of 1.41 and 2.66 m, respectively. These are higher than the single‐input CNN algorithms by 21% and 15%, and higher than backpropagation network (BPNN) algorithm by 24% and 17%, and higher than the weighted K‐nearest neighbour algorithm by 34% and 28%. The Multi‐CNN‐based localisation approach successfully fuses the diverse data, potentially satisfying most indoor localisation applications.

Ensemble Learning Approach for Digital Communication Modulation’s Classification

This work uses artificial intelligence to create an automatic solution for the modulation's classification of various radio signals. This project is a component of a lengthy communications intelligence process that aims to find an automated method for demodulating, decoding, and deciphering communication signals. As a result, the work we did involved selecting the database required for supervised deep learning, assessing the performance of current methods on unprocessed communication signals, and suggesting a deep learning network-based method that would enable the classification of modulation types with the best possible ratio between computation time and accuracy. In order to use the current automatic classification models as a guide, we first conducted study on them. As a result, we suggested an ensemble learning strategy based on Transformer Neural Network and adjusted ResNet that takes into account the difficulty of forecasting in low Signal Noise Ratio (SNR) scenarios while also being effective at extracting multiscale characteristics from the raw I/Q sequence data. Ultimately, we produced an architecture for communication signals that is simple to work with and implement. With an accuracy of up to 95%, this solution's optimum and sturdy architecture decides the type of modulation on its own.

Generating detailed intercellular communication patterns in psoriasis at the single-cell level using social networking, pattern recognition, and manifold learning methods to optimize treatment strategies.

Psoriasis, a complex and recurrent chronic inflammatory skin disease involving various inflammatory cell types, requires effective cell communication to maintain the homeostatic balance of inflammation. However, patterns of communication at the single-cell level have not been systematically investigated. In this study, we employed social network analysis tools, pattern recognition, and manifold learning to compare molecular communication features between psoriasis cells and normal skin cells. Utilizing a process that facilitates the discovery of cell type-specific regulons, we analyzed internal regulatory networks among different cells in psoriasis. Advanced techniques for the quantitative detection of non-targeted proteins in pathological tissue sections were employed to demonstrate protein expression. Our findings revealed a synergistic interplay among the communication signals of immune cells in psoriasis. B-cells were activated, while Langerhans cells shifted into the primary signaling output mode to fulfill antigen presentation, mediating T-cell immunity. In contrast to normal skin cells, psoriasis cells shut down numerous signaling pathways, influencing the balance of skin cell renewal and differentiation. Additionally, we identified a significant number of active cell type-specific regulons of resident immune cells around the hair follicle. This study unveiled the molecular communication features of the hair follicle cell-psoriasis axis, showcasing its potential for therapeutic targeting at the single-cell level. By elucidating the pattern of immune cell communication in psoriasis and identifying new molecular features of the hair follicle cell-psoriasis axis, our findings present innovative strategies for drug targeting to enhance psoriasis treatment.

Two way workable microchanneled hydrogel suture to diagnose, treat and monitor the infarcted heart

During myocardial infarction, microcirculation disturbance in the ischemic area can cause necrosis and formation of fibrotic tissue, potentially leading to malignant arrhythmia and myocardial remodeling. Here, we report a microchanneled hydrogel suture for two-way signal communication, pumping drugs on demand, and cardiac repair. After myocardial infarction, our hydrogel suture monitors abnormal electrocardiogram through the mobile device and triggers nitric oxide on demand via the hydrogel sutures’ microchannels, thereby inhibiting inflammation, promoting microvascular remodeling, and improving the left ventricular ejection fraction in rats and minipigs by more than 60% and 50%, respectively. This work proposes a suture for bidirectional communication that acts as a cardio-patch to repair myocardial infarction, that remotely monitors the heart, and can deliver drugs on demand.

Design and implementation of intelligent‐oriented electronic communication power monitoring system

AbstractIn order to improve the monitoring effect of electronic communication power supply, this paper applies the intelligent communication signal processing method to the monitoring system, and deeply analyzes the basic principle of OTA. Moreover, from the perspective of improving linearity, a signal attenuation OTA is designed in this paper, and its linearity has been greatly improved. In addition, this paper designs a cross‐coupled POTA that can not only ensure high linearity but also achieve tunable translinearity. The tunable POTA circuit has simple structure, wide linear input range, tunable translinearity and easy implementation, and can meet its performance requirements in FPAA arrays. Through data analysis, it can be seen that the intelligent‐oriented electronic communication power monitoring system proposed in this paper has a good data monitoring effect. This study provides an effective approach for the development of electronic communication power monitoring technology, improves the signal processing efficiency of electronic communication power monitoring, and also provides some reference for the improvement of signal strength in electronic communication technology.

Anti-Gravity System Based on Magnetic Levitation Technology

This paper presents a design of an anti-gravity system based on magnetic levitation technology. The system utilizes the force generated by magnetic principles to counteract gravity and achieve object suspension and control. The design objective is to achieve portable maglev technology for everyday use. Specific requirements include adjustable speed range, endurance time, effective suspension range, mass, control mode, safety, magnetic field strength, suspension stability, altitude control precision, resistance to strong magnetic field interference, and portability. The system structure includes suspension device, magnetic field generator, sensor, and control system. Control strategies such as PID control, fuzzy control, and sliding mode control can be employed, and signal communication can be achieved through Bluetooth, Wi-Fi, or fiber optic communication. By selecting and designing appropriate control strategies and integrating suspension, magnetic field generator, and sensor components, the anti-gravity system based on magnetic levitation technology can achieve height control and suspension stability.

The function of sphingolipids in membrane trafficking and cell signaling in plants, in comparison with yeast and animal cells

Sphingolipids are essential membrane components involved in a wide range of cellular, developmental and signaling processes. Sphingolipids are so essential that knock-out mutation often leads to lethality. In recent years, conditional or weak allele mutants as well as the broadening of the pharmacological catalog allowed to decipher sphingolipid function more precisely in a less invasive way. This review intends to provide a discussion and point of view on the function of sphingolipids with a main focus on endomembrane trafficking, Golgi-mediated protein sorting, cell polarity, cell-to-cell communication and cell signaling at the plasma membrane. While our main angle is the plant field research, we will constantly refer to and compare with the advances made in the yeast and animal field. In this review, we will emphasize the role of sphingolipids not only as a membrane component, but also as a key player at a center of homeostatic regulatory networks involving direct or indirect interaction with other lipids, proteins and ion fluxes.

LncRNA Profiling of Exosomes and Its Communication Role in Regulating Silica-Stimulated Macrophage Apoptosis and Fibroblast Activation.

Long-term silica particle exposure leads to interstitial pulmonary inflammation and fibrosis, called silicosis. Silica-activated macrophages secrete a wide range of cytokines resulting in persistent inflammation. In addition, silica-stimulated activation of fibroblast is another checkpoint in the progression of silicosis. The pathogenesis after silica exposure is complex, involving intercellular communication and intracellular signaling pathway transduction, which was ignored previously. Exosomes are noteworthy because of their crucial role in intercellular communication by delivering bioactive substances, such as lncRNA. However, the expression profile of exosomal lncRNA in silicosis has not been reported yet. In this study, exosomes were isolated from the peripheral serum of silicosis patients or healthy donors. The exosomal lncRNAs were profiled using high-throughput sequencing technology. Target genes were predicted, and functional annotation was performed using differentially expressed lncRNAs. Eight aberrant expressed exosomal lncRNAs were considered to play a key role in the process of silicosis according to the OPLS-DA. Furthermore, the increased expression of lncRNA MSTRG.43085.16 was testified in vitro. Its target gene PARP1 was critical in regulating apoptosis based on bioinformatics analysis. In addition, the effects of exosomes on macrophage apoptosis and fibroblast activation were checked based on a co-cultured system. Our findings suggested that upregulation of lncRNA MSTRG.43085.16 could regulate silica-induced macrophage apoptosis through elevating PARP1 expression, and promote fibroblast activation, implying that the exosomal lncRNA MSTRG.43085.16 might have potential as a biomarker for the early diagnosis of silicosis.

Listening to your partner: serotonin increases male responsiveness to female vocal signals in mice.

The context surrounding vocal communication can have a strong influence on how vocal signals are perceived. The serotonergic system is well-positioned for modulating the perception of communication signals according to context, because serotonergic neurons are responsive to social context, influence social behavior, and innervate auditory regions. Animals like lab mice can be excellent models for exploring how serotonin affects the primary neural systems involved in vocal perception, including within central auditory regions like the inferior colliculus (IC). Within the IC, serotonergic activity reflects not only the presence of a conspecific, but also the valence of a given social interaction. To assess whether serotonin can influence the perception of vocal signals in male mice, we manipulated serotonin systemically with an injection of its precursor 5-HTP, and locally in the IC with an infusion of fenfluramine, a serotonin reuptake blocker. Mice then participated in a behavioral assay in which males suppress their ultrasonic vocalizations (USVs) in response to the playback of female broadband vocalizations (BBVs), used in defensive aggression by females when interacting with males. Both 5-HTP and fenfluramine increased the suppression of USVs during BBV playback relative to controls. 5-HTP additionally decreased the baseline production of a specific type of USV and male investigation, but neither drug treatment strongly affected male digging or grooming. These findings show that serotonin modifies behavioral responses to vocal signals in mice, in part by acting in auditory brain regions, and suggest that mouse vocal behavior can serve as a useful model for exploring the mechanisms of context in human communication.

Peale's dolphins (Lagenorhynchus australis) are acoustic mergers between dolphins and porpoises

Most dolphin species produce broadband clicks for echolocation (i.e., biosonar pulses), and whistles and burst-pulsed calls for communication purposes. A few dolphin species in the southern hemisphere are reported to only produce clicks of a more narrowband high-frequency (NBHF) type, very similar to the clicks produced by porpoises. Here, we use underwater acoustic recordings of Peale's dolphins (Lagenorhynchus australis) in the Falkland Islands to show that they also can produce broadband clicks and tonal whistle sounds similar to other whistling odontocete species in addition to NBHF clicks. Whistles and broadband clicks co-occurred in seven out of twelve acoustic encounters with Peale's dolphins. The co-occurrence of whistles and broadband signals, which were predominately burst-pulses, produced by Peale's dolphins in this study points to a probable function as communication signals. Furthermore, the measured frequency and time parameters of Peale's dolphin whistles were comparable with whistles recorded from four additional species in the Lagenorhynchus genus in various parts of their ranges. This is the only species of Lagenorhynchus recorded to date that can relax acoustic crypsis in a similar manner as Heaviside's (Cephalorhynchus heavisidii), Commerson's (C. commersonii), and Hector's (C. hectori) dolphins. Our findings make it likely that additional NBHF species have the ability to generate both pulsed signal types and whistles, and further challenges the acoustic classification of NBHF species.