Search Results (993)

As part of non-terrestrial networks (NTN), the Low Earth Orbit (LEO) plays a critical role in supporting high-throughput wireless communication. However, the high-speed mobility of LEO satellites, coupled with the high density of user terminals, makes efficient user assignment crucial in maintaining overall wireless performance. The suboptimal assignment from LEO satellites to user terminals can result in frequent unnecessary handovers, rendering the user terminal unable to receive the entire downlink signal. Consequently, it reduces user rate and user satisfaction metrics. However, finding the optimum user assignment to reduce handover issues is categorized as a non-linear programming problem with a combinatorial number of possible solutions, resulting in excessive computational complexity. Therefore, this study proposes a distributed user assignment for the LEO networks. By utilizing message-passing frameworks that map the optimization problem into a graphical representation, the proposed algorithm splits the optimization problem into a local mapping issue, thereby significantly reducing computational complexity. By exchanging small messages iteratively, the proposed algorithm autonomously determines the near-optimal solution. The extensive simulation results demonstrate that the proposed algorithm significantly outperforms the conventional algorithm in terms of user rate and user satisfaction metric under various wireless parameters. Full article

Rosa bracteata J.C.Wendl. is a thorny, clump-forming or trailing perennial evergreen shrub native to China. The current analysis was designed to explore the chemical constituents and determine the in vitro antimicrobial, cytotoxic, and antioxidant properties of the essential oils (EOs) of the stems, leaves, and flowers of Rosa bracteata for the first time. The chemical composition of the essential oils obtained through hydro-distillation was characterized by means of gas chromatography–mass spectrometry (GC–MS) and gas chromatography with a flame ionization detector (GC–FID). Thirty-seven, thirty-six, and forty-two constituents were identified from leaf oil (LEO), stem oil (SEO), and flower oil (FEO), representing 96.3%, 95.9%, and 97.4% of the total oil constituents, respectively. The LEO was mainly composed of 1-pentadecene, α-cadinol, and hexadecanoic acid. However, the main identified components of SEO were (E)-nerolidol, phytol, and benzyl benzoate, and the main components of the flower oil were ethyl octanoate, octanoic acid, and α-cadinol. All of the EOs exhibited antibacterial activities against both Gram-positive and Gram-negative bacteria with MIC values ranging from 40.00 to 640.00 μg/mL. In addition, the checkerboard method demonstrates potent synergistic effects of Rosa bracteata EOs when combined with commercial antibiotics (chloramphenicol and streptomycin). In the MTT test, SEO (IC₅₀: 37.91 ± 2.10 to 51.15 ± 6.42 μg/mL) showed stronger cytotoxic activity against four cancer cell lines (MCF-7, A549, HepG2, and HCT-116) during the incubation time of 48 h in comparison to the EOs isolated from the other plant parts. Overall, these findings reveal the chemical composition and significant bioactivity of R. bracteata EOs for the first time, suggesting their potential as promising natural agents for therapeutic applications, especially in combination therapies to combat antibiotic resistance. Full article

Leveraging non-terrestrial networks for edge computing is crucial for the development of 6G, the Internet of Things, and ubiquitous digitalization. In such scenarios, diverse tasks often exhibit continuously distributed attributes, while existing research predominantly relies on qualitative thresholds for task classification, failing to accommodate quantitatively continuous task requirements. To address this issue, this paper models a multi-task scenario with continuously distributed attributes and proposes a three-tier cloud-edge collaborative offloading architecture comprising UAV-based edge nodes, LEO satellites, and ground cloud data centers. We further formulate a system cost minimization problem that integrates UAV network load balancing and satellite energy efficiency. To solve this non-convex, multi-stage optimization problem, a two-layer multi-type-agent deep reinforcement learning (TMDRL) algorithm is developed. This algorithm categorizes agents according to their functional roles in the Markov decision process and jointly optimizes task offloading and resource allocation by integrating DQN and DDPG frameworks. Simulation results demonstrate that the proposed algorithm reduces system cost by 7.82% compared to existing baseline methods. Full article

In Low Earth Orbit (LEO) satellite communication systems, providing reliable data transmission for ultra-high-speed mobile terminals faces severe challenges from dramatic Doppler effects and fast time-varying channels. Orthogonal Time Frequency Space (OTFS) modulation is a promising technique for high-mobility Low Earth Orbit (LEO) satellite communications, but its performance is often limited by inaccurate Channel State Information (CSI) prediction and suboptimal resource allocation, particularly in dynamic channels with coupled parameters like SNR, Doppler, and delay. To address these limitations, this paper proposes an adaptive OTFS frame configuration scheme based on multi-domain channel prediction. We utilize a Long Short-Term Memory (LSTM) network to jointly predict multi-dimensional channel parameters by leveraging their temporal correlations. Based on these predictions, the OTFS transmitter performs two key optimizations: dynamically adjusting the pilot guard bands in the Delay-Doppler domain to reallocate guard resources to data symbols, thereby improving spectral efficiency while maintaining channel estimation accuracy; and performing optimal power allocation based on predicted sub-channel SNRs to minimize the system’s Bit Error Rate (BER). The simulation results show that our proposed scheme reduces the required SNR for a BER of $1\times {10}^{-3}$ by approximately 1.5 dB and improves spectral efficiency by 10.5% compared to baseline methods, demonstrating its robustness and superiority in high-mobility satellite communication scenarios. Full article

Universal Stress Protein (USP) plays crucial roles in plant stress adaptation, yet their evolutionary dynamics, regulatory mechanisms, and functional diversification in rice (Oryza sativa) remain poorly understood. This study aimed to conduct a genome-wide identification and characterization of the OsUSP gene family to elucidate its role in abiotic stress responses using integrated bioinformatics approaches. Here, we identified 46 OsUSP genes that are unevenly distributed across 11 rice chromosomes and exhibit significant divergence in protein length, molecular weight, and subcellular localization. Phylogenetic analysis classified OsUSPs into three subfamilies, with conserved motif and domain architectures within groups but distinct structural variations across subfamilies. Evolutionary analysis revealed strong collinearity between rice and other monocots, which suggests functional conservation in grasses, whereas limited synteny with dicots indicates lineage-specific divergence. Cis-regulatory element analysis showed enrichment in ABA, MeJA, drought, and hypoxia response motifs, implicating OsUSPs in hormonal and stress signaling. Expression profiling indicated tissue-specific patterns, with subfamily III genes broadly expressed, while subfamily II members were anther-enriched. Stress response profiling revealed that 24 OsUSPs were significantly induced, while LOC_Os02g54590 and LOC_Os05g37970 emerged as particularly notable due to their broad-spectrum responsiveness, being upregulated under all tested stress conditions. Protein–protein interaction (PPI) analysis indicated that OsUSP proteins potentially interact with Leo1/TPR-domain proteins and are involved in stress response and phosphorylation signaling pathways. This study yields key insights into OsUSP-mediated stress adaptation in rice and pinpoints promising candidate genes to facilitate the breeding of climate-resilient rice. Full article

Poultry meat, due to its high content of polyunsaturated fatty acids, is particularly susceptible to lipid oxidation, which affects its quality and shelf life. Optimizing meat composition, including fatty acid profile and antioxidant activity, is essential for consumer health. The study aimed to evaluate the effect of supplementing hydrogel capsules containing immobilized lavender essential oil (HE group) and capsules without immobilized essential oil (H group) on the oxidative stability, fatty acid profile, and mineral composition of broiler chicken breast muscles. The study results showed that supplementation with the lavender oil hydrogel (HE) significantly reduced total superoxide dismutase (SOD) and CuZn-SOD activity in breast muscles. Although TBARS values did not show significant differences, the reduced SOD activity may indicate decreased free radical production or more effective action of other antioxidant mechanisms. The fatty acid profile was significantly altered, with a lower content of saturated fatty acids (SFAs) observed in the HE group. Significant changes were also observed in the mineral composition of the muscles. The HE group had a higher sodium content and lower copper and iron levels compared to the control group. These changes may indicate an effect of the hydrogel and essential oil on mineral metabolism and bioavailability. The study suggests that hydrogels with immobilized lavender essential oil (LEO) may positively affect poultry meat quality by improving its fatty acid profile and oxidative stability, although these mechanisms require further research and confirmation. Full article

Background/Objectives: The skin is a protective barrier against pathogens such as herpes simplex virus type 1 (HSV-1), which causes recurrent and highly prevalent skin infections worldwide. The increasing resistance of HSV-1 to conventional treatments has driven the search for new therapeutic alternatives. In this context, the essential oil of Lippia graveolens (EOL) has demonstrated promising antiviral activity; however, its high volatility limits direct skin application. To overcome this, polymeric nanoparticles (NPs) loaded with EOL were developed to improve its availability and antiviral efficacy. Methods: Nanoformulations were prepared by nanoprecipitation, and their antiviral activity against HSV-1 was evaluated using the plaque reduction assay. The effect of the nanoformulations on skin barrier integrity was assessed using an ex vivo porcine skin model and non-invasive techniques. Results: The NP-EOL exhibited physicochemical properties favorable for skin deposition, including a particle size around 200 nm, a polydispersity index of ≤ 0.2, and negative zeta potential. Moreover, NP-EOL showed 1.85-fold higher antiviral activity against HSV-1 compared with free EOL, while also reducing cytotoxicity in Vero cells. Conclusions: Results demonstrated that the NPs promoted skin hydration without altering pH or transepidermal water loss, suggesting they do not disrupt skin homeostasis. This study supports the potential of NP-based systems as effective topical delivery vehicles for EOL, representing a promising therapeutic alternative against HSV-1 skin infections. Full article

The harsh conditions of the space environment necessitate advanced materials capable of withstanding extreme temperature fluctuations and ultraviolet (UV) radiation. While epoxy-based composites are widely utilized in aerospace due to their favorable strength-to-weight ratio, they are prone to degradation, especially under prolonged high-energy UV-C exposure. This study investigated the mechanical and chemical stability of epoxy composites reinforced with nanosilica at 0, 2, 5, and 10 wt% before and after UV-C irradiation. Dynamic mechanical analysis (DMA) revealed that increased nanosilica content enhanced the storage modulus below the glass transition temperature (Tg) but reduced both Tg and the damping factor. Following UV-C exposure, all samples showed a decrease in storage modulus and Tg; however, composites with higher nanosilica content maintained better property retention. Frequency sweeps corroborated these findings, indicating improved instantaneous modulus but accelerated relaxation with increased nanosilica. Fourier-transform infrared (FTIR) spectroscopy of UV-C-exposed samples demonstrated significant oxidation and carboxylic group formation in neat epoxy, contrasting with minimal spectral changes in nanosilica-modified composites, signifying improved chemical resistance. Overall, nanosilica incorporation substantially enhances the thermomechanical and oxidative stability of epoxy composites under simulated space conditions, highlighting their potential for more durable performance in low Earth orbit applications. Full article

Low-Earth-Orbit Satellite Internet (LEO SI), with its capability for seamless global coverage, is a key solution for connecting IoT devices in areas beyond terrestrial network reach, playing a vital role in building a future ubiquitous IoT system. Inspired by the IEEE 802.15.4 Improved Adaptive Backoff Algorithm (I-ABA), this paper proposes an Attack-Aware Adaptive Backoff Indicator (AA-BI) mechanism to enhance the security and robustness of the two-step random access process in LEO SI. The mechanism constructs a composite threat intensity indicator that incorporates collision probability, Denial-of-Service (DoS) attack strength, and replay attack intensity. This quantified threat level is smoothly mapped to a dynamic backoff window to achieve adaptive backoff adjustment. Simulation results demonstrate that, with 200 pieces of user equipment (UE), the AA-BI mechanism significantly improves the access success rate (ASR) and jamming resistance rate (JRR) under various attack scenarios compared to the I-ABA and Binary Exponential Backoff (BEB) algorithms. Notably, under high-attack conditions, AA-BI improves ASR by up to 25.1% and 56.6% over I-ABA and BEB, respectively. Moreover, under high-load conditions with 800 users, AA-BI still maintains superior performance, achieving an ASR of 0.42 and a JRR of 0.68, thereby effectively ensuring the access performance and reliability of satellite Internet in malicious environments. Full article

This paper presents an innovative end-to-end framework for conformal antenna array design and beam steering in Low Earth Orbit (LEO) satellite-based IoT communication systems. We propose a multi-stage learning architecture that integrates machine learning (ML) for antenna parameter prediction with reinforcement learning (RL) for adaptive beam steering. The ML module predicts optimal geometric and material parameters for conformal antenna arrays based on mission-specific performance requirements such as frequency, gain, coverage angle, and satellite constraints with an accuracy of 99%. These predictions are then passed to a Deep Q-Network (DQN)-based offline RL model, which learns beamforming strategies to maximize gain toward dynamic ground terminals, without requiring real-time interaction. To enable this, a synthetic dataset grounded in statistical principles and a static dataset is generated using CST Studio Suite and COMSOL Multiphysics simulations, capturing the electromagnetic behavior of various conformal geometries. The results from both the machine learning and reinforcement learning models show that the predicted antenna designs and beam steering angles closely align with simulation benchmarks. Our approach demonstrates the potential of combining data-driven ensemble models with offline reinforcement learning for scalable, efficient, and autonomous antenna synthesis in resource-constrained space environments. Full article

Grid point approaches for LEO mega-constellation coverage analysis become computationally prohibitive for constellations exceeding 10³ satellites due to exponential complexity growth. This paper presents the Mercator projection superposition (MPS) approach, which transforms coverage evaluation into a two-dimensional image-processing paradigm by projecting the satellite coverage onto Mercator maps. MPS decouples computational complexity from satellite count, enabling analysis of constellations exceeding 10⁴ satellites. Validation against grid point approaches shows ≤1.2% error with 60× speed improvement for 103-scale constellations without parallel computation. The method establishes that instantaneous coverage rates reliably approximate periodic rates within 0.04% precision for early-stage constellation design. Analysis of Starlink-based configurations identifies optimal principles governing mega-constellation coverage, with particular emphasis on configuration and orbital parameter relationships. These findings enable rapid design iteration and optimization for future mega-constellation development. Full article

This paper presents the final implemented design and performance evaluation of the ground-based C-band Cheia radar system, developed to enhance Romania’s contribution to the EU Space Surveillance and Tracking (EU SST) network. All data used for performance analysis are real-time, real-life measurements of true spatial test objects orbiting Earth. The radar is based on two decommissioned 32 m satellite communication antennas already present at the Cheia Satellite Communication Center, that were retrofitted for radar operation in a quasi-monostatic architecture. A Linear Frequency Modulated Continuous Wave (LFMCW) Radar design was implemented, using low transmitted power (2.5 kW) and advanced software-defined signal processing for detection and tracking of Low Earth Orbit (LEO) targets. System validation involved dry-run acceptance tests and calibration campaigns with known reference satellites. The radar demonstrated accurate measurements of range, Doppler velocity, and angular coordinates, with the capability to detect objects with radar cross-sections as low as 0.03 m² at slant ranges up to 1200 km. Tracking of medium and large Radar Cross Section (RCS) targets remained robust under both fair and adverse weather conditions. This work highlights the feasibility of re-purposing legacy satellite infrastructure for SST applications. The Cheia radar provides a cost-effective, EUSST-compliant performance solution using primarily commercial off-the-shelf components. The system strengthens the EU SST network while demonstrating the advantages of LFMCW radar architectures in electromagnetically congested environments. Full article

Conventional thermospheric density models are limited in their ability to capture solar-geomagnetic coupling dynamics and lack probabilistic uncertainty estimates. We present MSIS-UN (NRLMSISE-00 with Uncertainty Quantification), an innovative framework integrating sparse principal component analysis (sPCA) with heteroscedastic neural networks. Our methodology leverages multi-satellite density measurements from the CHAMP, GRACE, and SWARM missions, coupled with MSIS-00-derived exospheric temperature (tinf) data. The technical approach features three key innovations: (1) spherical harmonic decomposition of T∞ using spatiotemporally orthogonal basis functions, (2) sPCA-based extraction of dominant modes from sparse orbital sampling data, and (3) neural network prediction of temporal coefficients with built-in uncertainty quantification. This integrated framework significantly enhances the temperature calculation module in MSIS-00 while providing probabilistic density estimates. Validation against SWARM-C measurements demonstrates superior performance, reducing mean absolute error (MAE) during quiet periods from MSIS-00’s 44.1% to 23.7%, with uncertainty bounds (1σ) achieving an MAE of 8.4%. The model’s dynamic confidence intervals enable rigorous probabilistic risk assessment for LEO satellite collision avoidance systems, representing a paradigm shift from deterministic to probabilistic modeling of thermospheric density. Full article

Small satellites or CubeSats orbiting in low Earth orbit (LEO) have become increasingly popular in Earth Observation missions, where high-resolution imaging is essential. Due to the lower mass of these spacecrafts, they are more sensitive to vibrations, and image quality can be particularly negatively affected by micro-vibrations. These vibrations originate from on-board subsystems, such as the Attitude Determination and Control System (ADCS), which uses reaction wheels to change the orientation of the satellite. The main goal of our research was to analyze these micro-vibrations so that the acquired data could be used for post-correction of camera images. Obuda University, as a participant in a research project, was tasked with designing and building a micro-vibration measuring device for the LEO CubeSat called WREN-1. In the first phase of the project, the satellite was launched into orbit, and test data were collected and analyzed. The results are presented in this article. Based on the data obtained in this way, the next step will be to analyze the images taken at the same time as the vibration measurements and to search for a correlation between the image quality and the vibrations. Based on the results of the entire project, it could be possible to improve the image quality of the onboard cameras of microsatellites. Full article

We present the design and analysis of three CMOS 4-way power splitters operating in the K/Ka-band (18–27 GHz/27–40 GHz) for low Earth orbit (LEO) satellite communications and 26.5–29.5/37–40 GHz 5G radio applications. The first power splitter (PS1) consists of a two-way power splitter using circular double-helical transmission lines (DH-TLs) cascaded with two two-way power splitters using noninverting circular sole-helical coupled-TL (SH-CL). The second power splitter (PS2) consists of a two-way power splitter using circular DH-TLs cascaded with two two-way power splitters using inverting circular SH-CL. The third power splitter (PS3) consists of three two-way power splitters using DH-TLs. For each two-way power splitter, a parallel input capacitor is included to satisfy the requirement for two equivalent quarter-wavelength (λ/4) TLs, ensuring a low input reflection coefficient. λ/10-DH-TL-based-double-λ/4-TLs, λ/12-noninverting-SH-CL-based-double-λ/4-TLs, and λ/9-inverting-SH-CL-based-double-λ/4-TLs are utilized to attain compact chip size and low amplitude inequality (AI) and phase deviation (PD). Prominent results are attained. For instance, the chip size of PS1 is 0.057 mm². At 33 GHz, PS1 attains S₁₁ of −16 dB, S₂₂ of −21.2 dB, S₃₃ of −19.7 dB, S₂₃ of −15.3 dB, S₂₁ of −7.862 dB, S₃₁ of −7.803 dB, AI₂₃ of −0.059 dB, and PD₂₃ of 0.197°. The chip size of PS2 is 0.071 mm². At 33 GHz, PS2 attains S₁₁ of −13.5 dB, S₂₂ of −16.1 dB, S₃₃ of −16.7 dB, S₂₃ of −34.8 dB, S₂₁ of −8.1 dB, S₃₁ of −8.146 dB, AI₂₃ of 0.046 dB, and PD₂₃ of −0.581°. To the authors’ knowledge, the overall performance of PS1, PS2, and PS3 ranks among the best published in the literature for K- and Ka-band four-way power splitters. Full article