Communication Signals Research Articles

Chaotic Phenomena, Sensitivity Analysis, Bifurcation Analysis, and New Abundant Solitary Wave Structures of The Two Nonlinear Dynamical Models in Industrial Optimization

In this research, we discussed the different chaotic phenomena, sensitivity analysis, and bifurcation analysis of the planer dynamical system by considering the Galilean transformation to the Lonngren wave equation (LWE) and the (2 + 1)-dimensional stochastic Nizhnik–Novikov–Veselov System (SNNVS). These two important equations have huge applications in the fields of modern physics, especially in the electric signal in data communication for LWE and the mechanical signal in a tunnel diode for SNNVS. A different chaotic nature with an additional perturbed term was also highlighted. Concerning the theory of the planer dynamical system, the bifurcation analysis incorporating phase portraits of the dynamical systems of the declared equations was performed. Additionally, a sensitivity analysis was used to monitor the sensitivity of the mentioned equations. Also, we extracted new, abundant solitary wave structures with the graphical phenomena of the mentioned nonlinear mathematical models. By conducting an expansion method on the abovementioned equations, we generated three types of soliton structures, which are rational function, trigonometric function, and hyperbolic function. By simulating the 3D, contour, and 2D graphs of these obtained solitons, we scrutinized the behavior of the waves affecting the nonlinear terms. The figures show that the solitary waves obtained from LWE are efficient in analyzing electromagnetic wave signals in the cable lines, and the solitary waves from SNNVS are essential in any stochastic system like a sound wave. Moreover, by taking some values of the parameters, we found some interesting soliton shapes, such as compaction soliton, singular periodic solution, bell-shaped soliton, anti-kink-shaped soliton, one-sided kink-shaped soliton, and some flat kink-shaped solitons, etc. This article will have a great impact on nonlinear science due to the new solitary wave structures with different complex phenomena, sensitivity analysis, and bifurcation analysis.

Fractional fourier transform and its application

The Fourier Transform (FT) is a linear transformation for the primitive function. It takes some set of functions to be an orthogonal basis. Its physical meaning is to transfer the primitive function onto each set of base functions. Because it can convert functions between the time and frequency domains, the FT is widely employed in many fields. The Fractional Fourier Transform (FrFT) is an improvement and progress based on the FT. This paper will define the FT and FrFT. Then the distinction between FrFT and FT is discussed. Finally, specific examples of its application in processing digital image are provided. FrFT is the process of transforming an image function into a series of periodic functions. The FrFT is used as a powerful mathematical tool to understand non- smooth signals, nonlinear systems and complicated phenomena, which is significant and has broad possibilities in the fields of signal processing, communication, image processing, optical imaging and quantum information processing.

The micro-ecological feature of colonies is a potential strategy for Phaeocystis globosa bloom formation

Phaeocystis globosa is among the dominant microalgae associated with harmful algal blooms. P. globosa has a polymorphic life cycle and its ecological success has been attributed to algal colony formation, however, few studies have assessed differences in microbial communities and their functional profiles between intra- and extra-colonies during P. globosa blooms. To address this, environmental and metagenomics tools were used to conduct a time-series analysis of the bacterial composition and metabolic characteristics of intra- and extra-colonies during a natural P. globosa bloom. The results show that bacterial composition, biodiversity, and network interactions differed significantly between intra- and extra-colonies. Dominant extra-colonial bacteria were Bacteroidia and Saccharimonadis, while dominant intra-colonial bacteria included Alphaproteobacteria and Gammaproteobacteria. Despite the lower richness and diversity observed in the intra-colonial bacterial community, relative to extra-colonies, the complexity and interconnectedness of the intra-colonial networks were higher. Regarding bacterial function, more functional genes were enriched in substance metabolism (polysaccharides, iron element and dimethylsulfoniopropionate) and signal communication (quorum sensing, indoleacetic acid-IAA) pathways in intra- than in extra-colonies. Conceptual model construction showed that microbial cooperative synthesis of ammonium, vitamin B12, IAA, and siderophores were strongly related to the P. globosa bloom, particularly in the intra-colonial environment. Overall, our data highlight the differences in bacterial structure and functions within and outside the colony during P. globosa blooms. These findings represent fundamental information indicating that phenotypic heterogeneity is a selective strategy that improves microbial population competitiveness and environmental adaptation, benefiting P. globosa bloom formation and persistence.

Adaptive virtual agent: Design and evaluation for real-time human-agent interaction

When we converse, we adapt our behaviors to our interlocutors. The adaptation can serve to indicate our engagement which can also elicit enhancement of the involvement of others. Virtual agents (or socially interactive virtual agents) that play the role of interaction partners can improve the human users’ interaction experience by displaying continuous and adaptive behaviors in real time. Virtual agents have been used in multiple domains to improve user interaction and performance. The promising results of the endowment of adaptation to agents in increasing the agents’ perception and user experience were shown in previous studies. In this paper, we develop an adaptive virtual agent that renders real-time adaptive behaviors based on the behaviors shown by its human interlocutor. The ASAP model rendering reciprocally adaptive agent behavior was employed to realize the system. The system consists of four main parts: perception of social signals, agent adaptive behavior generation, agent visualization (i.e. rendering of the agent’s verbal and nonverbal behavior), and communication of signals. To showcase the usefulness of our adaptive agent, as a proof-of-concept we choose the e-health application of cognitive behavior therapy (CBT), which identifies and rectifies biased and irrational thoughts (or automatic thoughts). Through this study, we show the importance of giving the agent reciprocal adaptation capability notably in enhancing the user experience and the effectiveness of the CBT session. We validate the importance of endowing such adaptation capability by studying the difference between agents that are reciprocally adaptive, solely expressive (with mismatched behavior), and inexpressive (in a still posture) via questionnaires and measures related to the agent perception (naturalness, human-likeliness, synchrony, and engagement) for user experience and the CBT effectiveness (mood, anxiety, stress, and cognitive change). These results highlight the value of making virtual agents adapt in real time. This could lead to agents being capable of providing more personalized and interactive experiences for a wide range of applications. Also, we have collected a new human-agent interaction (HAI) database, HAI-CBT database, which is publicly available to the research community.

Limiting the Broadcast Range of a Secreting Cell during Intercellular Signaling Using Protease-Mediated Degradation.

Synthetic biology is revolutionizing our approaches to biocomputing, diagnostics, and environmental monitoring through the use of designed genetic circuits that perform a function within a single cell. More complex functions can be performed by multiple cells that coordinate as they perform different subtasks. Cell-cell communication using molecular signals is particularly suited for aiding in this communication, but the number of molecules that can be used in different communication channels is limited. Here we investigate how proteases can limit the broadcast range of communicating cells. We find that adding barrierpepsin to Saccharomyces cerevisiae cells in two-dimensional multicellular networks that use α-factor signaling prevents cells beyond a specific radius from responding to α-factor signals. Such limiting of the broadcast range of cells could allow multiple cells to use the same signaling molecules to direct different communication processes and functions, provided that they are far enough from one another. These results suggest a means by which complex synthetic cellular networks using only a few signals for communication could be created by structuring a community of cells to create distinct broadcast environments.

Therapeutic Implications of Stem Cell Secretome

The stem cell secretome is a collective mixture of soluble and insoluble factors released by stem cells during paracrine communication and/or autocrine signaling. In addition to intracellular communication, these paracrine factors play an integral role in tissue development and generation, acting as the primary driving force in the regenerative properties of stem cells. Despite such great potential of stem cell secretome in therapeutic applications, the lack of secretome-based treatments available for the public at the time of writing is odd and puzzling. Hence, this review aims to provide insights into recent advancements in understanding the stem cell secretome, as well as discuss future possibilities and current limitations that must be overcome for the proper development of secretome-based therapies. Through utilizing the MEDLINE database from the National Library of Medicine® (NLM), we found that while there is much evidence of the therapeutic effects of secretome-based therapy, flaws involving regulations and standardization hinder it from revolutionizing regenerative medicine at present. It is cardinal to emphasize that while secretome-based therapy may be the solution for many untreatable conditions, much research is still required before it is approved for clinical practice.

The crosstalk role of CDKN2A between tumor progression and cuproptosis resistance in colorectal cancer.

Cuproptosis is a type of cell death characterized by excessive copper-lipid reactions in the tricarboxylic acid cycle, resulting in protein toxicity stress and cell death. Although known as a cuproptosis inhibitor through CRISPR-Cas9 screening, the role of cyclin-dependent kinase inhibitor 2A (CDKN2A) in cuproptosis resistance and its connection to tumor development remains unclear. In this study, we combined single-cell sequencing, spatial transcriptomics, pathological image analysis, TCGA multi-omics analysis and in vitro experimental validation to comprehensively investigate CDKN2A distribution, expression, epigenetic modification, regulation and genomic features in colorectal cancer cells. We further explored the associations between CDKN2A and cellular pathway, immune infiltration and spatial signal communication. Our findings showed an increasing trend in cuproptosis in the trajectory of tumor progression, accompanied by an upward trend of CDKN2A. CDKN2A underwent transcriptional activation by MEF2D and via the SNHG7/miR-133b axis, upregulating glycolysis, copper metabolism and copper ion efflux. CDKN2A likely drives epithelial-mesenchymal transition (EMT) and progression by activating Wnt signaling. CDKN2A is associated with high genomic instability and sensitivity to radiation and chemotherapy. Tumor regions expressing CDKN2A exhibit distinctive SPP1+ tumor-associated macrophage (TAM) infiltration and MMP7 enrichment, along with unique signaling crosstalk with adjacent areas. CDKN2A mediates cuproptosis resistance through regulating glycolysis and copper homeostasis, accompanied by a malignant phenotype and pro-tumor niche. Radiation and chemotherapy are expected to potentially serve as therapeutic approaches for cuproptosis-resistant colorectal cancer with high CDKN2A expression.

Spatiotemporal Cooperative Spectrum Sensing of Random Arrival of Primary Signals for Cognitive UAV Communications

Spatiotemporal Cooperative Spectrum Sensing of Random Arrival of Primary Signals for Cognitive UAV Communications

Real-Time Object Detection from UAV Inspection Videos by Combining YOLOv5s and DeepStream.

The high-altitude real-time inspection of unmanned aerial vehicles (UAVs) has always been a very challenging task. Because high-altitude inspections are susceptible to interference from different weather conditions, interference from communication signals and a larger field of view result in a smaller object area to be identified. We adopted a method that combines a UAV system scheduling platform with artificial intelligence object detection to implement the UAV automatic inspection technology. We trained the YOLOv5s model on five different categories of vehicle data sets, in which mAP50 and mAP50-95 reached 93.2% and 71.7%, respectively. The YOLOv5s model size is only 13.76 MB, and the detection speed of a single inspection photo reaches 11.26 ms. It is a relatively lightweight model and is suitable for deployment on edge devices for real-time detection. In the original DeepStream framework, we set up the http communication protocol to start quickly to enable different users to call and use it at the same time. In addition, asynchronous sending of alarm frame interception function was added and the auxiliary services were set up to quickly resume video streaming after interruption. We deployed the trained YOLOv5s model on the improved DeepStream framework to implement automatic UAV inspection.

Automatic classification of multi-carrier modulation signal using STFT spectrogram and deep CNN

In the realm of communication systems, categorizing Multi-Carrier Modulation (MCM) signals without cooperative communication poses a significant technical challenge. In this paper, we introduce a novel approach for accurately categorizing five distinct MCM signals, including Orthogonal Frequency Division Multiplexing (OFDM), Filter Bank Multicarrier (FBMC), Filtered Orthogonal Frequency Division Multiplexing (FOFDM), Windowed Orthogonal Frequency Division Multiplexing (WOLA), and Universal Filtered Multicarrier (UFMC). Each signal is considered with two types of subcarrier waveforms, Quadrature Amplitude Modulation 16 (QAM16) and Quadrature Amplitude Modulation 64 (QAM64), resulting in a total of 10 unique MCM signals for classification. Our proposed methodology leverages Short-Time Fourier Transform (STFT) spectrograms for feature extraction at the frontend, while at the backend, we employ three variants of Convolutional Neural Network (CNN) models; CNN, CNN with Dropout (CNN_d), CNN with both Dropout and L1 Regularization (CNN_dL1) and one deep CNN model; Xception, individually. We aim to provide an efficient and reliable means of categorizing MCM signals, with practical applications in signal processing and communication systems. Extensive simulations demonstrate the effectiveness of our approach, achieving remarkable accuracies. Notably, the Xception model exhibits the highest accuracy among the four models considered. Specifically, we attain an accuracy of 98% at 10 dB SNR using the Xception model. These results underscore the efficacy of our proposed methodology and highlight the potential for its deployment in real-world scenarios.

Adversarial training for signal modulation classification based on Ulam stability theory

The modulation classification of radar, communication, and other radiation source signals under complex electromagnetic conditions is an important task in the field of military electronic countermeasures. Deep learning is an important tool for automatic modulation classification (AMC) tasks. However, AMC models based on deep neural networks are easily attacked by adversarial methods such as gradient attacks, and even under small perturbations, the model may exhibit significant differences in prediction. To address adversarial attacks, we proposed a Ulam stability adversarial training method, which could improve the robust accuracy and the natural accuracy of the adversarial training model. We introduced a class of Jensen type Ulam stability theorem, which transforms the Jensen condition into a special class of stability preserving regularization terms for adversarial training models, enhancing the model's adversarial robustness. More importantly, our method provided a framework for improving the stability of adversarial training, which can be combined with existing adversarial training methods to effectively enhance their adversarial defense capabilities. In the experimental section, we compared four types of adversarial training methods on three types of modulation recognition datasets, and the results showed that Ulam adversarial training improved robust accuracy by an average of 4.8% and natural accuracy by an average of 2.2% on three datasets. The difference between the best and final accuracies of the models decreased by an average of 4.5%.

Cu-doped KTN crystal with controllable, reversible, and fast photochromic properties: A superior electro-optical material for improving beam deflection performance

Improving the deflection performance of a beam deflector is urgently required to acquire optical signals for space laser communication and change the attitude and position of space targets and spacecraft. In this work, a Cu-doped potassium tantalate niobate (Cu-KTN) single crystal with fast photochromic and increased beam deflection properties is synthesized using the top-seeded solution growth method. When a Cu-KTN single crystal is irradiated with 405 nm light or ultraviolet (UV) light, the color changes from pale green to reddish brown. After light irradiation, the color gradually returns to yellowish green. Decolorization is accelerated under irradiation with green light or long-wavelength light, and the color changes to pale green. The origin of reversible photochromism reveals the fast valence change of Cu ions. In addition, ion doping improves the beam deflection angle of the secondary electro-optical effect of Cu-KTN (4.3 mrad, 1000 V) crystal compared with pure KTN (3.2 mrad, 1000 V). This study successfully synthesizes Cu-KTN single crystals with photochromic uses and establishes a new route for beam deflectors with significant deflection angles.

Species variation in steroid hormone-related gene expression contributes to species diversity in sexually dimorphic communication in electric fishes

Sexually dimorphic behaviors are often regulated by gonadal steroid hormones. Species diversity in behavioral sex differences may arise as expression of genes mediating steroid action in brain regions controlling these behaviors evolves. The electric communication signals of apteronotid knifefishes are an excellent model for comparatively studying neuroendocrine regulation of sexually dimorphic behavior. These fish produce and detect weak electric organ discharges (EODs) for electrolocation and communication. EOD frequency (EODf), controlled by the medullary pacemaker nucleus (Pn), is sexually dimorphic and regulated by androgens and estrogens in some species, but is sexually monomorphic and unaffected by hormones in other species. We quantified expression of genes for steroid receptors, metabolizing enzymes, and cofactors in the Pn of two species with sexually dimorphic EODf (Apteronotus albifrons and Apteronotus leptorhynchus) and two species with sexually monomorphic EODf (“Apteronotus” bonapartii and Parapteronotus hasemani). The “A.” bonapartii Pn expressed lower levels of androgen receptor (AR) genes than the Pn of species with sexually dimorphic EODf. In contrast, the P. hasemani Pn robustly expressed AR genes, but expressed lower levels of genes for 5α-reductases, which convert androgens to more potent metabolites, and higher levels of genes for 17β-hydroxysteroid dehydrogenases that oxidize androgens and estrogens to less potent forms. These findings suggest that sexual monomorphism of EODf arose convergently via two different mechanisms. In “A.” bonapartii, reduced Pn expression of ARs likely results in insensitivity of EODf to androgens, whereas in P. hasemani, gonadal steroids may be metabolically inactivated in the Pn, reducing their potential to influence EODf.

Low-Intensity Light Detection with a High Detectivity Using 2D-Sb2Se3 Nanoflakes on 1D-ZnO Nanorods as Heterojunction Photodetectors.

Multifunctional photodetectors (PDs) with broadband responsivity (R) and specific detectivity (D*) at low light intensities are gaining significant attention. Thus, we report a bilayer PD creatively fabricated by layering two-dimensional (2D) Sb2Se3 nanoflakes (NFs) on one-dimensional (1D) ZnO nanorods (NRs) using simple thermal transfer and hydrothermal processes. The unique coupling of these two layers of materials in a nanostructured form, such as 2D-Sb2Se3 NFs/1D-ZnO NRs, provides an effective large surface area, robust charge transport paths, and light-trapping effects that enhance light harvesting. Furthermore, the combination of both layers can effectively facilitate photoactivity owing to proper band alignment. The as-fabricated device demonstrated superior overall performance in terms of a suitable bandwidth, good R, and high D* under low-intensity light, unlike the single-layered 1D-ZnO NRs and 2D-Sb2Se3 NF structures alone, which had poor detectivity or response in the measured spectral range. The PD demonstrated a spectral photoresponse ranging from ultraviolet (UV) to visible (220-628 nm) light at intensities as low as 0.15 mW·cm-2. The PD yielded a D* value of 3.15 × 1013 Jones (220 nm), which reached up to 5.95 × 1013 Jones in the visible light region (628 nm) at a 3 V bias. This study demonstrated that the 2D-Sb2Se3 NFs/1D-ZnO NRs PD has excellent potential for low-intensity light detection with a broad bandwidth, which is useful for signal communications and optoelectronic systems.

Implementation of companding scheme for performance enhancement of optical OFDM structure

Abstract Due to its great spectral efficiency and resistance to multi-path fading, OFDM, or orthogonal frequency division multiplexing, is commonly utilized in optical communication systems. However, because of nonlinear distortions in optical components, OFDM signals are prone to a high peak-to-average power ratio (PAPR), which can severely impair bit error rate (BER) performance. This paper introduces a companding scheme to address high PAPR in optical OFDM systems and improve BER performance. The proposed scheme uses a nonlinear transformation to compress signal peaks and expand valleys, effectively reducing PAPR. Specifically, we investigate the µ-law companding technique, known for its simplicity and effectiveness in handling the active range of OFDM signals in optical communication. The companded signals are transmitted through an optical link and demodulated at the receiver. Simulation results show that the µ-law companding technique substantially reduces PAPR, leading to a significant improvement in BER performance. The companding process maintains signal integrity and spectral efficiency with minimal computational complexity and implementation cost. By mitigating nonlinearities introduced by optical components, this companding scheme enhances the overall reliability and efficiency of the optical OFDM system. An SNR gain of 2 dB–3 dB was achieved at a BER of 10−3.

Modeling the reactive oxygen species (ROS) wave in Chlamydomonas reinhardtii colonies

Reactive oxygen species (ROS) play a crucial role as signaling molecules in both plant and animal cells, enabling rapid responses to various stimuli. Among the many cellular mechanisms used to generate and transduce ROS signals, ROS-induced-ROS release (RIRR) is emerging as an important pathway involved in the responses of various multicellular and unicellular organisms to environmental stresses. In RIRR, one cellular compartment, organelle, or cell generates or releases ROS, triggering an increased ROS production and release by another compartment, organelle, or cell, thereby giving rise to a fast propagating ROS wave. This RIRR-based signal relay has been demonstrated to facilitate mitochondria-to-mitochondria communication in animal cells and long-distance systemic signaling in plants in response to biotic and abiotic stresses. More recently, it has been discovered that different unicellular microorganism communities also exhibit a RIRR cell-to-cell signaling process triggered by a localized stress treatment. However, the precise mechanism underlying the propagation of the ROS signal among cells within these unicellular communities remained elusive. In this study, we employed a reaction-diffusion model incorporating the RIRR mechanism to analyze the propagation of ROS-mediated signals. By effectively balancing production and scavenging processes, our model successfully reproduces the experimental ROS signal velocities observed in unicellular green algae (Chlamydomonas reinhardtii) colonies grown on agar plates, furthering our understanding of intercellular ROS communication.

Driver-to-Driver Communication Skills: Contributing Factors to Traffic Accidents on South African Roads?

Road traffic accidents are associated with different factors, such as nonsignalised road networks, inexperienced drivers, a lack of communication skills, distraction, and the visual or cognitive impairment of road users, which have led to this increase in traffic accidents. Understanding these factors in alignment with road user communication skills can provide solutions that can reduce traffic fatalities. Road users’ communication is predominantly formal in nature; informal means of communication also exist but are not given proper attention during the driving training and licence testing processes. Therefore, this study investigated the communication skills between drivers as a factor contributing to traffic accidents in South African cities. Consequently, 16 traffic scenarios of communication between drivers were simulated using PTV Vissim 2022 and Blender 3.0 software, and a semistructured interview questionnaire was used to collect data from South African road users. The questionnaire was further used to evaluate the confidence level of road users concerning informal communication. The data were analysed via regression analysis to establish the relationship between traffic accidents and miscommunication between drivers. The information gathered and analysed from this study helps us to understand the informal communication types between drivers and establish where communication loss exists, which could potentially lead to a traffic accident. The results also show that the misinterpretation of communication signals can present the possibility of a traffic safety risk.

Single-Source VLCP System Based on Solar Cell Array Receiver and Right-Angled Tetrahedron Trilateration VLP (RATT-VLP) Algorithm

A significant deployment limitation for visible light communication and positioning (VLCP) systems in energy- and light-source-restricted scenarios is the reliance of photodetectors (PDs) on external power supplies, compromising sustainability and complicating receiver charging. Solar cells (SCs), capable of harvesting and converting environmental light into electrical energy, offer a promising alternative. Consequently, we first propose an indoor VLCP system that utilizes an SC array as the receiver, alongside a right-angled tetrahedron trilateration visible light positioning (RATT-VLP) algorithm based on a single light source and multiple receivers. The proposed system uses an SC array in place of PDs, utilizing binary phase shift keying (BPSK) signals for simultaneous communication and positioning. In experiments, we verified the system’s error-free communication rate of 1.21 kbps and average positioning error of 3.40 cm in a 30 cm × 30 cm area, indicating that the system can simultaneously satisfy low-speed communication and accurate positioning applications. This provides a viable foundation for further research on SC-based VLCP systems, facilitating potential applications in environments like underwater wireless communication, positioning, and storage tank inspection.

Guest Editorial: Introduction to the Special Issue on Electromagnetic Signal and Information Theory for Communications

Guest Editorial: Introduction to the Special Issue on Electromagnetic Signal and Information Theory for Communications

The role of pannexin/purinergic signaling in intervascular communication from capillaries during skeletal muscle contraction in male Golden hamsters.

We sought to determine the physiological relevance of pannexin/purinergic-dependent signaling in mediating conducted vasodilation elicited by capillary stimulation through skeletal muscle contraction. Using hamster cremaster muscle and intravital microscopy we stimulated capillaries through local muscle contraction while observing the associated upstream arteriole. Capillaries were stimulated with muscle contraction at low and high contraction (6 and 60CPM) and stimulus frequencies (4 and 40 Hz) in the absence and presence of pannexin blocker mefloquine (MEF; 10-5 M), purinergic receptor antagonist suramin (SUR 10-5 M) and gap-junction uncoupler halothane (HALO, 0.07%) applied between the capillary stimulation site and the upstream arteriolar observation site. Conducted vasodilations elicited at 6CPM were inhibited by HALO while vasodilations at 60CPM were inhibited by MEF and SUR. The conducted response elicited at 4 Hz was inhibited by MEF while the vasodilation at 40 Hz was unaffected by any blocker. Therefore, upstream vasodilations resulting from capillary stimulation via muscle contraction are dependent upon a pannexin/purinergic-dependent pathway that appears to be stimulation parameter-dependent. Our data highlight a physiological importance of the pannexin/purinergic pathway in facilitating communication between capillaries and upstream arteriolar microvasculature and, consequently, indicating that this pathway may play a crucial role in regulating blood flow in response to skeletal muscle contraction.