Long-range Communication Research Articles

Contact area and tissue growth dynamics shape synthetic juxtacrine signaling patterns.

Cell-cell communication through direct contact, or juxtacrine signaling, is important in development, disease, and many areas of physiology. Synthetic forms of juxtacrine signaling can be precisely controlled and operate orthogonally to native processes, making them a powerful reductionist tool with which to address fundamental questions in cell-cell communication in vivo. Here we investigate how cell-cell contact length and tissue growth dynamics affect juxtacrine signal responses through implementing a custom synthetic gene circuit in Drosophila wing imaginal discs alongside mathematical modeling to determine synthetic Notch (synNotch) activation patterns. We find that the area of contact between cells largely determines the extent of synNotch activation, leading to the prediction that the shape of the interface between signal-sending and signal-receiving cells will impact the magnitude of the synNotch response. Notably, synNotch outputs form a graded spatial profile that extends several cell diameters from the signal source, providing evidence that the response to juxtacrine signals can persist in cells as they proliferate away from source cells, or that cells remain able to communicate directly over several cell diameters. Our model suggests the former mechanism may be sufficient, since it predicts graded outputs without diffusion or long-range cell-cell communication. Overall, we identify that cell-cell contact area together with output synthesis and decay rates likely govern the pattern of synNotch outputs in both space and time during tissue growth, insights that may have broader implications for juxtacrine signaling in general.

Single-Sample Networks Reveal Intra-Cytoband Co-Expression Hotspots in Breast Cancer Subtypes

Breast cancer is a heterogeneous disease comprising various subtypes with distinct molecular characteristics, clinical outcomes, and therapeutic responses. This heterogeneity evidences significant challenges for diagnosis, prognosis, and treatment. Traditional genomic co-expression network analyses often overlook individual-specific interactions critical for personalized medicine. In this study, we employed single-sample gene co-expression network analysis to investigate the structural and functional genomic alterations across breast cancer subtypes (Luminal A, Luminal B, Her2-enriched, and Basal-like) and compared them with normal breast tissue. We utilized RNA-Seq gene expression data to infer gene co-expression networks. The LIONESS algorithm allowed us to construct individual networks for each patient, capturing unique co-expression patterns. We focused on the top 10,000 gene interactions to ensure consistency and robustness in our analysis. Network metrics were calculated to characterize the topological properties of both aggregated and single-sample networks. Our findings reveal significant fragmentation in the co-expression networks of breast cancer subtypes, marked by a change from interchromosomal (TRANS) to intrachromosomal (CIS) interactions. This transition indicates disrupted long-range genomic communication, leading to localized genomic regulation and increased genomic instability. Single-sample analyses confirmed that these patterns are consistent at the individual level, highlighting the molecular heterogeneity of breast cancer. Despite these pronounced alterations, the proportion of CIS interactions did not significantly correlate with patient survival outcomes across subtypes, suggesting limited prognostic value. Furthermore, we identified high-degree genes and critical cytobands specific to each subtype, providing insights into subtype-specific regulatory networks and potential therapeutic targets. These genes play pivotal roles in oncogenic processes and may represent important keys for targeted interventions. The application of single-sample co-expression network analysis proves to be a powerful tool for uncovering individual-specific genomic interactions.

Action-At-A-Distance in DNA Mismatch Repair: Mechanistic Insights and Models for How DNA and Repair Proteins Facilitate Long-Range Communication

Many DNA metabolic pathways, including DNA repair, require the transmission of signals across long stretches of DNA or between DNA molecules. Solutions to this signaling challenge involve various mechanisms: protein factors can travel between these sites, loop DNA between sites, or form oligomers that bridge the spatial gaps. This review provides an overview of how these paradigms have been used to explain DNA mismatch repair, which involves several steps that require action-at-a-distance. Here, we describe these models in detail and how current data fit into these descriptions. We also outline regulation steps that remain unanswered in how the action is communicated across long distances along a DNA contour in DNA mismatch repair.

Mathematical SETIbacks: Open Texture in Mathematics as a New Challenge for Messaging Extra-Terrestrial Intelligence

ABSTRACT Beyond the obvious technical difficulties, human attempts to communicate with hypothetical Extra-Terrestrial Intelligences also present a number of philosophical puzzles. After all, an alien intelligence is likely the closest thing to a Wittgensteinian lion humanity could ever encounter. In this paper I advance a new challenge for the feasibility of communication with extra-terrestrials. The problem I raise is a practical problem that falls out of the history and philosophy of mathematics and the implementation of METI projects—specifically, the semiprime self-decryption schema of the Drake Pictures message strategy. The Drake Pictures strategy presumes that aliens share the concept ‘prime number’ with us, as understanding that concept is necessary to decrypt our message. However, if the concept ‘prime number’ exhibited open texture at any point in its history, it could have developed in a different direction than it did in our history. If that is so, an alien could have the concept ‘prime number’ and still not be capable of decrypting our messages. I argue that this new problem is more trenchant than previous arguments in both the philosophy and SETI literature, such as applications of the aforementioned Lion argument and other concerns about the possibility of long-range communication without the assumption of shared concepts.

Review on HF Band Vehicular Antenna with NVIS Communication

Antennas play a fundamental role in modern communication systems by facilitating signal transmission and reception across various frequency bands. Each antenna is designed for specific applications based on its operating frequency range. Whether deployed for Car-to-Car Communication or military operations, antennas serve critical functions, with information security being paramount in military contexts. Vehicular antennas typically operate within the L Band, approximately 1 to 2 GHz, relying on satellites for signal communication. However, traditional transmission through the ionosphere faces limitations, notably the skip zone, where signal reception is hindered, leading to communication failures. To address this limitation, Near Vertical Incident Skywave (NVIS) communication has been developed. NVIS utilizes antennas with very high (> 75°) radiation angles and low HF frequencies to overcome skip zone challenges. Despite existing research efforts, achieving high radiation efficiency remains a challenge, often due to improper antenna angle settings. Additionally, previous studies have overlooked the importance of narrow beam focusing, crucial for long-range communication and direction finding. This paper aims to enhance antenna performance parameters such as efficiency and gain through the adoption of specific techniques. By optimizing antenna design and configuration, we aim to improve performance for ionospheric communication, particularly in military applications involving data and voice transmission.

Design of a high power combiner in HF band

Power combiners are commonly used in power amplifiers to achieve high power, especially in long-range and medium-range wireless communication device transmission systems. This paper proposes designing and implementing a high-power two-way power combiner operating in the HF (High Frequency) band, aiming to achieve an output power of over 1 kW. The power combiner is designed, implemented, and tested in the laboratory with the following achieved parameters: insertion loss between output and input better than 3.4 dB and isolation between inputs better than 26 dB. The experimental results showed that the proposed power combiner had better performance than existing combiners on the market. Mainly, power combining efficiency is over 88%, the standing wave ratio at ports is less than 1.25, and the operating temperature of the power combiner is less than 50 °C, meeting the set requirements.

Human Astrocytes Synchronize Neural Organoid Networks.

Biological neural networks exhibit synchronized activity within and across interconnected regions of the central nervous system. Understanding how these coordinated networks are established and maintained may reveal therapeutic targets for neurodegeneration and neuromodulation. Here, we tested the influence of astrocytes upon synchronous network activity using human pluripotent stem cell-derived bioengineered neural organoids. This study revealed that astrocytes significantly increase activity within individual organoids and across long distances among numerous rapidly merged organoids via influencing synapses and bioenergetics. Treatment of amyloid protein inhibited synchronous activity during neurodegeneration, yet this can be rescued by propagating activity from neighboring networks. Altogether, this study identifies critical contributions of human astrocytes to biological neural networks and delivers a rapid, reproducible, and scalable model to investigate long-range functional communication of the nervous system in healthy and disease states.

Alpha coherence is a network signature of cognitive recovery from disorders of consciousness.

Alpha (8-12 Hz) frequency band oscillations are among the most informative features in electroencephalographic (EEG) assessment of patients with disorders of consciousness (DoC). Because interareal alpha synchrony is thought to facilitate long-range communication in healthy brains, coherence measures of resting-state alpha oscillations may provide insights into a patients capacity for higher-order cognition beyond channel-wise estimates of alpha power. In multi-channel EEG, global coherence methods may be used to augment standard spectral analysis methods by both estimating the strength and identifying the structure of coherent oscillatory networks. We performed global coherence analysis in 95 separate clinical EEG recordings (28 healthy controls and 33 patients with acute or chronic DoC, 25 of whom returned for follow-up) collected between two academic medical centers. We found that posterior alpha coherence is associated with recovery of higher-level cognition. We developed a measure of network organization, based on the distance between eigenvectors of the alpha cross-spectral matrix, that detects recovery of posterior alpha networks. In patients who have emerged from a minimally conscious state, we showed that coherence-based alpha networks are reconfigured prior to restoration of alpha power to resemble those seen in healthy controls. This alpha network measure performs well in classifying recovery from DoC (AUC = 0.78) compared to common representations of functional connectivity using the weighted phase lag index (AUC = 0.50 - 0.57). Lastly, we observed that activity within these alpha networks is suppressed during positive responses to task-based EEG command-following paradigms, supporting the potential utility of this biomarker to detect covert cognition. Our findings suggest that restored alpha networks may represent a sensitive early signature of cognitive recovery in patients with DoC. Therefore, network detection methods may augment the utility of EEG assessments for DoC.

Path Loss Analysis of ZigBee for Smart Meter Network Deployment in NAN

A fundamental and vital aspect of Smart Metering infrastructure is the communication technologies and techniques associated with it, especially between the Smart Meters and the Data Concentrator Unit. Among many available communication technologies, ZigBee provides a low-cost, low-power, and easy-to-deploy network solution for a Smart Meter network. There exists limited literature that discusses ZigBee as a potential communication technology for long-range networks. Hence thorough analysis is demanded on the suitability of ZigBee for smart meter deployment under different types of environmental conditions, coverage ranges, and obstacles. This work evaluates the performance of an extended ZigBee module in outdoor as well as indoor conditions in the presence of different types of obstacles. Parameters are obtained for path loss exponent and the standard deviation of the Gaussian Random variable to validate the Log Normal Shadowing model for modeling long-range ZigBee communication. The impact of obstacles on path loss is also considered. The results show that the Log Normal Shadowing model is a good approximation for the behavior of ZigBee path loss. Accordingly, the suitability of ZigBee for a Smart Meter network spanned as a Neighborhood Area Network is also assessed based on the approximated model.

Emergence of synchronized growth oscillations in filamentous fungi.

Many species of soil fungi grow in the form of branched networks that enable long-range communication and mass flow of nutrient. These networks play important roles in the soil ecosystem as a major decomposer of organic materials. While there have been investigations on the branching of the fungal networks, their long-term growth dynamics in space and time is still not very well understood. In this study, we monitor the spatio-temporal growth dynamics of the plant-promoting filamentous fungus Serendipita indica for several days in a controlled environment within a microfluidic chamber. We find that S. indica cells display synchronized growth oscillations with the onset of sporulation and at a period of 3 h. Quantifying this experimental synchronization of oscillatory dynamics, we show that the synchronization can be recapitulated by the nearest neighbour Kuramoto model with a millimetre-scale cell-cell coupling. The microfluidic set-up presented in this work may aid the future characterization of the molecular mechanisms of the cell-cell communication, which could lead to biophysical approaches for controlling fungi growth and reproductive sporulation in soil and plant health management.

Attentional Information Routing in The Human Brain.

Brain-wide communication supports behaviors that require coordination between sensory and associative regions. However, how large-scale brain networks route sensory information at fast timescales to guide upcoming actions remains unclear. Using spiking neural networks and human intracranial electrophysiology during spatial attention tasks, where participants detected a target at cued locations, we show that high-frequency activity bursts (HFAb) serve as information-carrying events, facilitating fast and long-range communications. HFAbs emerged as bouts of neural population spiking and were coordinated brain-wide through low-frequency rhythms. At the network-level, HFAb coordination identified distinct cue- and target-activated subnetworks. HFAbs following the cue onset in cue-subnetworks predicted successful target detection and preceded the information in target-subnetworks following target onset. Our findings suggest HFAbs as a neural mechanism for fast brain-wide information routing that supports attentional performance.

Effects of solar radiation on the performance of long-distance atmosphere-ocean laser communication links

We investigated the effect of solar radiation noise on the performance of a long-range atmosphere-ocean laser communication system. To model an inhomogeneous channel in the atmosphere-ocean system, a Monte Carlo (MC) simulation method was utilized in combination with measured underwater chlorophyll profiles. We conducted field measurements to accurately assess the effects of background noise, specifically solar radiation at different underwater depths and times. The influence of different scenarios on the system's signal-to-noise ratio (SNR) was then scrutinized based on the detector type. Additionally, a comprehensive analytical model was proposed for diverse background light noises, enabling the exploration of the effects of solar noise and Photomultiplier Tube (PMT) on the communication link's performance in terms of Pulse Position Modulation (PPM) demodulation symbol error rate (SER). The results indicate that expanding the receiver's field of view (FOV) from 1° to 15° can enhance the system's communication depth by 11 m, while increasing the receiver's radius from 1 cm to 20 cm can elevate the communication depth by 37 m. Moreover, the study investigates the impact of transmit power and the multi-aperture receiving technique on communication depth, providing valuable insights for designing atmosphere-ocean laser communication links and offering robust support for the practical implementation of the Free-Space Optical (FSO) - Underwater Optical Communication (UWOC) system.

Photonics-aided exceeding 200-Gb/s wireless data transmission over outdoor long-range 2 × 2 MIMO THz links at 300 GHz

Outdoor long-range terahertz (THz) communications often come at the expense of transmission rate. Moreover, the practicability of the single polarization optical/THz link, which is commonly used in the previous long-range THz demonstrations based on photonics, is extremely limited by the following two fatal defects. One is relying on active polarization control, and the other is not supporting the transparent bridging of optical polarization division multiplexed (PDM) signals for mature coherent optical communication networks. In this work, a large-capacity photonics-aided THz wireless communication system based on the outdoor long-range 2 × 2 multiple-input multiple-output (MIMO) links has been successfully demonstrated. We first build the 200-m 2 × 2 MIMO THz wireless links at the 300 GHz band. The cascaded linear and nonlinear equalizers are proposed which can significantly improve the transmission performance of 100- and 200-Gb/s PDM quadrature phase shift keying (QPSK) signals. Then an interesting 2 × 2 MIMO structure which can provide certain diversity reception gain under 200-m long-range wireless delivery using the same polarization scheme is also presented and further compared with the orthogonal polarization scheme. Since each THz receiver simultaneously receives data from both the two THz transmitters for this MIMO links, an improvement over 6 dB in receiving sensitivity and one order of magnitude in bit error ratio performance under low signal-to-noise ratio conditions can be achieved. Finally, based on the proposed cascaded equalizers and novel 2 × 2 MIMO structure, we successfully demonstrate a record-breaking 58-Gbaud (232-Gb/s) PDM-QPSK signal transmission over 200-m 2 × 2 MIMO THz wireless links. This is an important attempt for the photonics-aided THz wireless communication systems to achieve 2 × 2 MIMO transmission over a long wireless distance in the outdoors. Furthermore, attaining over 200 Gb/s at a wireless distance of 200 m also represents a key milestone for the long-range and large-capacity THz wireless communication systems.

Design of an Anti-interference long-range acoustic Communication System Based on optimal length segment coding

Abstract With the increased demand for unmanned vehicles in marine development, the development of underwater acoustic communication technology has received much attention. One of the key technologies in the research of long-range underwater acoustic communication technology is the use of underwater acoustic channels for efficient and stable data transmission. The harsh environment of the underwater acoustic channel has a significant impact on the rate and quality of underwater acoustic communication, making it a challenging research direction to achieve high-speed and reliable telecommunication systems underwater. In this paper, a high-speed remote command-based communication system is investigated, and a long-range acoustic communication system with good adaptability to sudden and continuous interference is designed based on a remote unmanned platform. A method for encoding the communication message in segments of optimal length is proposed in this paper. This coding method can enhance the anti-sudden interference capability of the communication system which has a certain degree of communication confidentiality, and the performance of this anti-interference communication system is verified by laboratory tests and field tests. The verification results show that the proposed telecommunication system based on optimal length segment coding has better performance in anti-sudden interference and continuous interference, which can make the communication system performance more stable and increase the success rate of command-based communication significantly.

Komodo Dragon Mlipir Algorithm-based CNN Model for Detection of Illegal Tree Cutting in Smart IoT Forest Area

Introduction: Trees and woods are vital to preventing climate change and protecting our planet. Sadly, they are constantly being destroyed due to human activities like deforestation, fires, etc. Method: This research presents and examines an outline for using audio event categorisation to automatically detect unlawful tree-cutting activity in forests. To monitor large swaths of forest, the research team proposes using ultra-low-power, minor devices incorporating edgecomputing microcontrollers and long-range wireless communication. An efficient and accurate audio classification solution based on multi-layer perceptron (MLP) and modified convolutional neural networks (M-CNN) is projected and tailored for cutting. The Komodo Dragon Mlipir Algorithm (KDMA) is used to pick the best weight for the CNN. Result: Compared to earlier efforts, the suggested system uses a computing technique to recognise deforestation-related hazards. Various preprocessing methods have been evaluated, with special attention paid to the trade-off between classification precision and computer resources, memory, and power use. Conclusion: Additionally, there have been long-range communication trials performed in natural settings. The experimental consequences demonstrate that the suggested method can notice and apprise tree-cutting occurrences through smart IoT for efficient and lucrative forest nursing.

Vehicle Safety Application through the Integration of Flood Detection and Safe Overtaking in Vehicular Communication

Road safety in Malaysia is a major concern due to frequent floods and accidents caused by overtaking. These issues result in significant injuries and losses. In this paper, we introduce a new system called the Safe Driving Tool (SDT). The SDT integrates a Flood Detection System (FDS) and a Vehicle Overtaking System (VOS) using Long-Range (LoRa) communication technology. The FDS continuously monitors water levels in flood-prone areas. It alerts drivers about potential hazards through vehicle-to-infrastructure (V2I) communication. Simultaneously, the VOS enables safe overtaking maneuvers. It does this by exchanging information with nearby vehicles through vehicle-to-vehicle (V2V) communication. Through testing and experimentation, we have shown that the SDT system effectively reduces accident risks and losses associated with floods and overtaking. The system's performance under various conditions confirms the reliability and effectiveness of LoRa communication technology in enhancing vehicular safety. This study represents a significant advancement in road safety. It combines flood detection and overtaking assistance into a single unified system, addressing two major causes of road accidents in Malaysia. The integration of V2I and V2V communication provides a comprehensive solution that improves driver awareness and decision-making. This ultimately leads to safer driving environments and enhanced driver convenience. Doi: 10.28991/CEJ-2024-010-09-015 Full Text: PDF

State-specific Regulation of Electrical Stimulation in the Intralaminar Thalamus of Macaque Monkeys: Network and Transcriptional Insights into Arousal.

Long-range thalamocortical communication is central to anesthesia-induced loss of consciousness and its reversal. However, isolating the specific neural networks connecting thalamic nuclei with various cortical regions for state-specific anesthesia regulation is challenging, with the biological underpinnings still largely unknown. Here, simultaneous electroencephalogram-fuctional magnetic resonance imaging(EEG-fMRI) and deep brain stimulation are applied to the intralaminar thalamus in macaques under finely-tuned propofol anesthesia. This approach led to the identification of an intralaminar-driven network responsible for rapid arousal during slow-wave oscillations. A network-based RNA-sequencing analysis is conducted of region-, layer-, and cell-specific gene expression data from independent transcriptomic atlases and identifies 2489 genes preferentially expressed within this arousal network, notably enriched in potassium channels and excitatory, parvalbumin-expressing neurons, and oligodendrocytes. Comparison with human RNA-sequencing data highlights conserved molecular and cellular architectures that enable the matching of homologous genes, protein interactions, and cell types across primates, providing novel insight into network-focused transcriptional signatures of arousal.

Development of a cloud-based IoT system for livestock health monitoring using AWS and python

The agriculture industry is currently facing significant challenges in effectively monitoring the health of livestock. Traditional methods of health monitoring are often labor-intensive, inefficient, and insufficiently responsive to the needs of modern farming. As the number of IoT devices in agriculture proliferates, issues of scalability and computational load have become prominent, necessitating efficient and scalable solutions. This research introduces a cloud-based architecture aimed at enhancing livestock health monitoring. This system is designed to track critical health indicators such as movement patterns, body temperature, and heart rate, utilizing AWS for robust data handling and Python for data processing and real-time analytics. The proposed system incorporates Narrow Band IoT (Nb IoT) technology, which is optimized for low-bandwidth, long-range communication, making it suitable for rural and remote farming locations. The architecture's scalability allows for the effective management of varying numbers of IoT devices, which is essential for adapting to changing herd sizes and farm scales. Preliminary experiments conducted to assess the system's performance have demonstrated its durability and effectiveness, indicating a successful integration of AWS IoT Cloud services with the deployed IoT devices. Furthermore, the study explores the implementation of predictive analytics to facilitate proactive health management in livestock. By predicting potential health issues before they become apparent, the system can offer significant improvements in animal welfare and farm efficiency. The integration of cloud computing and IoT not only meets the growing technological needs of modern agriculture but also sets a new benchmark in the development of sustainable farming practices. The findings from this research could have broad implications for the future of livestock management, potentially leading to widespread adoption of technology-driven health monitoring systems in agriculture. This would help in optimizing the health management of livestock globally, thereby enhancing productivity and sustainability in the agricultural sector.

Integration of LoRa-enabled IoT infrastructure for advanced campus safety systems in Taiwan

Amid rising concerns about campus safety in Taiwan, particularly with the global trend towards smart cities, integrating the Internet of Things (IoT) into institutional security frameworks has become pivotal. The paper discusses the implementation of using iBeacons and Long Range (LoRa) technology to locating the student position and ensure his safety in the school campus. It uses Internet of Things (IoT) approach in real time to monitor and locate the student presence in the school compound. This paper unveils an innovative design for a campus security system that harnesses the LoRa technology. In the system, the students are equipped with devices containing Bluetooth Low Energy (BLE) beacons to capture and transmit real-time location data. The system response time to locating student in abnormal locations such as cornered and concealed areas is about one second. By extending this system to cover all individuals on campus, a closely monitored environment and areas is enabled that significantly bolstering the security measures. This not only furnishes a dynamic protective layer for educational institutions but also serves as a proactive deterrent against potential security breaches. Ultimately, this research underscores the transformative potential of merging IoT with campus security to ushering in a new era of student safety. LoRa technology offers advantages in battery life, cost-effectiveness, deployment flexibility, and network coverage etc. Therefore, this paper ultimately provides a method of how to utilize the LoRa technology to develop a campus security system. Unlike artificial intelligence (AI)-based image recognition, which raises concerns about privacy and human rights; the features of LoRa’s long-range communication and low power consumption make it a more suitable choice.

Modeling of Medium- and Long-Range Electromagnetic Communication Channel for Underwater Wireless Sensor Networks

Modeling of Medium- and Long-Range Electromagnetic Communication Channel for Underwater Wireless Sensor Networks