A Theoretical Combustion Kinetic Study of Unsymmetrical Dimethylhydrazine: H-Atom Abstraction and Reactions on the Potential Energy Surface of CHN Radicals.

Unsymmetrical dimethylhydrazine (UDMH) is a widely used hypergolic rocket fuel. It is one of the most commonly used fuels for attitude control engines, such as those in missiles, satellites, spacecraft, and launch vehicles. We conducted a high-level theoretical study to develop a detailed combustion kinetic mechanism for UDMH, focusing on crucial elementary reactions.

Numerical Simulation of Damage Processes in CCD Detectors Induced by Multi-Pulse Nanosecond Laser Irradiation.

This paper presents a finite element simulation of thermal damage to a CCD caused by nanosecond multi-pulse laser exposure. The temperature changes in the CCD due to the laser pulses were simulated, and the time evolution of thermal damage was studied. The impacts of different laser parameters such as spot radius, pulse width, and repetition frequency on thermal damage were evaluated.

Prediction of the Thermochemical Properties of Nitrogen-Containing Species: A Quantum Chemical Calculation and Group Additivity Approach.

With the growing demand for nitrogen-containing sustainable fuels and propellants, accurately predicting their thermochemical properties has become increasingly important. While quantum chemical calculation (QC) methods and calorimetric experiments offer high precision, they are often time-consuming and computationally intensive. In contrast, the group additivity (GA) method provides a faster alternative.

A Method for Few-Shot Radar Target Recognition Based on Multimodal Feature Fusion.

Enhancing generalization capabilities and robustness in scenarios with limited sample sizes, while simultaneously decreasing reliance on extensive and high-quality datasets, represents a significant area of inquiry within the domain of radar target recognition. This study introduces a few-shot learning framework that leverages multimodal feature fusion. We develop a cross-modal representation optimization mechanism tailored for the target recognition task by incorporating natural resonance frequency features that elucidate the target's scattering characteristics.

Design of Space Target Surveillance Constellation Based on Simulation Comparison Method.

Aiming at the requirement of space situational awareness on the full-domain and all-time coverage capability of low Earth orbit space targets and focusing on the design of a space-based space target awareness system, a space target awareness constellation design method based on simulation comparison is put forward. On the basis of systematically analyzing the distribution of space targets' orbits, the low Earth orbit space target surveillance mission mode, key indicators, and constraints of space target surveillance constellations are designed, and three space target surveillance constellation basic configurations are constructed. This paper randomly samples surveillance objects based on the stratified space target orbit distribution and selects a heterogeneous space target surveillance constellation in sun-synchronous morning-twilight orbit that meets the requirements of the surveillance mission model and capability by using simulations and comparisons.

Vogt-Koyanagi-Harada syndrome potentially associated with COVID-19 vaccination: a case report and literature review.

To investigate the potential association between COVID-19 vaccination and Vogt-Koyanagi-Harada (VKH) syndrome, offering novel insights for the diagnosis and management of vaccine-related ocular disorders. A case report combined with a literature review was conducted. A 19-year-old male developing VKH after receiving the second dose of an inactivated COVID-19 vaccine was analyzed.

Kernel-FastICA-Based Nonlinear Blind Source Separation for Anti-Jamming Satellite Communications.

Satellite communication systems, as a core component of global information infrastructure, have undergone unprecedented development. However, the open nature of satellite channels renders them vulnerable to electromagnetic interference, making anti-jamming techniques a persistent research focus in this domain. Satellite transponders contain various power-sensitive components that exhibit nonlinear characteristics under interference conditions, yet conventional anti-jamming approaches typically neglect the nonlinear distortion in transponders when suppressing interference.

Uncertainty analysis of initial orbit determination in the minimum radar admissible region.

The poor accuracy of the single solution of the initial orbit determination (IOD) affects the precise orbit determination, target matching and arc-segment correlation. This paper proposes a method for analyzing the uncertainty of the IOD results based on the Minimum Radar Admissible Region (MRAR), which describes the IOD results in the form of probability in the region bounded by the minimum admissible region. The MRAR can contain the real orbit state with a probability greater than 99.

A semi-supervised method using cycle consistency and multi-perspective dilated for SAR-to-optical translation.

Synthetic aperture radar (SAR) is a powerful imaging sensor capable of operating in any weather and at any time, despite its image interpretation poses challenges. Translating SAR images to optical (S2O) can serve as a beneficial supplement for target detection, image alignment, and image fusion. The existing S2O translation employs solely unsupervised or supervised techniques.

Design of a Lorentz Force Magnetic Bearing Group Steering Law Based on an Adaptive Weighted Pseudo-Inverse Law.

Aiming at the high-precision torque output and saturation singularity avoidance problems in Lorentz force magnetic bearing (LFMB) swarms for magnetic levitation spacecraft, this study designs a manipulation law based on an adaptive weighted pseudo-inverse law. The system monitors each magnetic bearing's working state in real time using high-precision position and current sensors. As the key input for the adaptive weighted pseudo-inverse control law, the sensor data's measurement accuracy directly determines torque distribution effectiveness and attitude control precision.

Atmospheric Switching between Etching and High-Quality Fluorination of Graphene by XeF.

Fluorinated graphene (FG), a two-dimensional graphene derivative, has attracted wide attention due to its extraordinary physical and chemical properties, as well as its underlying applications. The treatment of xenon difluoride (XeF) has proved to be an effective way to achieve FG with different stoichiometric F/C ratios without graphene being etched. Here we compare the fluorination of mechanically exfoliated graphene by a home-built XeF fluorination system and a commercial Orbis XeF etching system.

Inverse Synthetic Aperture Radar Sparse Imaging Recovery Technique Based on Improved Alternating Direction Method of Multipliers.

Inverse synthetic aperture radar (ISAR) technology is widely used in the field of target recognition. This research addresses the image reconstruction error in sparse imaging for bistatic radar systems. In this paper, sparse imaging technology is studied, and a sparse imaging recovery algorithm based on an improved Alternating Direction Method of Multipliers is proposed.

Joint Task Offloading and Power Allocation for Satellite Edge Computing Networks.

Low Earth orbit (LEO) satellite networks have shown extensive application in the fields of navigation, communication services in remote areas, and disaster early warning. Inspired by multi-access edge computing (MEC) technology, satellite edge computing (SEC) technology emerges, which deploys mobile edge computing on satellites to achieve lower service latency by leveraging the advantage of satellites being closer to users. However, due to the limitations in the size and power of LEO satellites, processing computationally intensive tasks with a single satellite may overload it, reducing its lifespan and resulting in high service latency.

Transient Force Measurement and Mechanism Analysis of Nanosecond Laser Ablation of Al/Ti Alloys Using Polyvinylidene Fluoride Sensors.

This study proposes a novel calibration method for polyvinylidene fluoride (PVDF) piezoelectric sensors based on electromagnetic force. The standard force source is obtained by calibrating the original force source of the inductor coil through an electronic balance. Transient force loading waveforms and peak values of PVDF piezoelectric sensors were obtained to analyze the mechanical effects of laser ablation on Al/Ti alloys.

Bayesian Adaptive Extended Kalman-Based Orbit Determination for Optical Observation Satellites.

As the number of satellites and amount of space debris in Low-Earth orbit (LEO) increase, high-precision orbit determination is crucial for ensuring the safe operation of spacecraft and maintaining space situational awareness. However, ground-based optical observations are constrained by limited arc-segment angular data and dynamic noise interference, and the traditional Extended Kalman Filter (EKF) struggles to meet the accuracy and robustness requirements in complex orbital environments. To address these challenges, this paper proposes a Bayesian Adaptive Extended Kalman Filter (BAEKF), which synergistically optimizes track determination through dynamic noise covariance adjustment and Bayesian a posteriori probability correction.

A Lightweight Dual-Branch Complex-Valued Neural Network for Automatic Modulation Classification of Communication Signals.

Currently, deep learning has become a mainstream approach for automatic modulation classification (AMC) with its powerful feature extraction capability. Complex-valued neural networks (CVNNs) show unique advantages in the field of communication signal processing because of their ability to directly process complex data and obtain signal amplitude and phase information. However, existing models face deployment challenges due to excessive parameters and computational complexity.

Resource-Constrained Specific Emitter Identification Based on Efficient Design and Network Compression.

Specific emitter identification (SEI) methods based on deep learning (DL) have effectively addressed complex, multi-dimensional signal recognition tasks by leveraging deep neural networks. However, this advancement introduces challenges such as model parameter redundancy and high feature dimensionality, which pose limitations for resource-constrained (RC) edge devices, especially in Internet of Things (IoT) applications. To tackle these problems, we propose an RC-SEI method based on efficient design and model compression.

SSDDPM: A single SAR image generation method based on denoising diffusion probabilistic model.

The limited availability of high-quality SAR images severely affects the accuracy and robustness of target detection, classification, and segmentation. To solve this problem, a novel image generation method based on a diffusion model is introduced that requires only one training sample to generate a realistic SAR image. We propose a single-scale architecture to avoid image noise accumulation.

A novel broadband reflectarray antenna employing equivalent magnetic dipole elements.

In this paper, a planar reflectarray antenna employing equivalent magnetic dipole (EMD) elements is proposed. An H-shaped patch and two coupling T-shaped patches are employed as the EMD element, in which the electric current intrinsically flows on the central H-shaped patch while the equivalent magnetic current with orthogonal direction can be ingeniously excited in the meanwhile due to the adjacent patch gaps. Compared with conventional magnetoelectric dipoles, the single-layer EMD element eliminates the vertically metallized via structure and generates an equivalent magnetic dipole with the help of displacement current rather than toroidal current, providing benefits including reduced complexity and enhanced bandwidth.

Dual-Polarized Metasurface-Integrated Antenna for Integrated Imaging of LWIR Camera and SAR.

The integrated imaging of LWIR cameras and SAR is one of the important directions of multi-sensor integration. In order to reduce the structural complexity of LWIR cameras and SAR-integrated imaging antenna, a dual-polarized metasurface-integrated antenna (MIA) is designed in this paper. It is composed of a microwave metasurface antenna and an optical metalens, and the metalens is embedded in the center of the metasurface antenna.

A MEMS grating modulator with a tunable sinusoidal grating for large-scale extendable apertures.

Microelectromechanical system (MEMS) grating modulators enable versatile beam steering functions through the electrostatic actuation of movable ribbons. These modulators operate at ultrahigh frequencies in the hundred kHz range, and their micromirror-free configuration simplifies the fabrication process and reduces costs compared to micromirror-based modulators. However, these modulators are limited in their optical efficiency and aperture.

DCLTV: An Improved Dual-Condition Diffusion Model for Laser-Visible Image Translation.

Laser active imaging systems can remedy the shortcomings of visible light imaging systems in difficult imaging circumstances, thereby attaining clear images. However, laser images exhibit significant modal discrepancy in contrast to the visible image, impeding human perception and computer processing. Consequently, it is necessary to translate laser images to visible images across modalities.

Theoretical insights on the double ESIPT mechanism and fluorescence properties of HBIo chromophore.

2-{[3-(1H-benzoimidazol-2-yl)-2-hydroxy-5-methylbenzylidene] amino}-benzoic acid (HBIo) based on proton transfer can serve as the fluorescent probe for detecting heavy metal ions. The excited-state intramolecular proton transfer (ESIPT) reaction mechanism of the HBIo chromophore with an intramolecular asymmetric double hydrogen bond in different solvents are investigated. The reaction barrier of the ESIPT along hydrogen bond O1-H2···N3 is higher than that of ESIPT along O4-H5···N6, which indicates that the double ESIPT is a stepwise process.

MalHAPGNN: An Enhanced Call Graph-Based Malware Detection Framework Using Hierarchical Attention Pooling Graph Neural Network.

While deep learning techniques have been extensively employed in malware detection, there is a notable challenge in effectively embedding malware features. Current neural network methods primarily capture superficial characteristics, lacking in-depth semantic exploration of functions and failing to preserve structural information at the file level. Motivated by the aforementioned challenges, this paper introduces MalHAPGNN, a novel framework for malware detection that leverages a hierarchical attention pooling graph neural network based on enhanced call graphs.