Recent progresses of the rare earth based intermetallics and alloys for hydrogen liquefaction.

Magnetic refrigeration, utilizing the magnetocaloric effect (MCE) in magnetic solids, was considered as a high efficiency cooling technology which can be available in a wide temperature range from cryogenic to room temperature. However, large-scale magnetic refrigeration applications are still in their early stages due to the lack of suitable candidate materials with prominent magnetocaloric performance. This article briefly reviews the research development of rare earth-based magnetocaloric materials that with potential applications for hydrogen liquefaction over the past five years.

A Suppression Method for Random Errors of IFOG Based on the Decoupling of Colored Noise-Spectrum Information.

In high-precision inertial navigation systems, suppressing the random errors of a fiber-optic gyroscope is of great importance. However, the traditional rule-based autoregressive moving average modeling method, when applied in Kalman filtering considering colored noise, presents inherent disadvantages in principle, including inaccurate state equations and difficulties in state dimension expansion. To this end, the noise characteristics in the fiber-optic gyroscope signal are first deeply analyzed, a random error model form is clarified, and a new model-order determination criterion is proposed to achieve the high-precision modeling of random errors.

Fiber Optic Gyro Random Error Suppression Based on Dual Adaptive Kalman Filter.

The random error of fiber optic gyros is a critical factor affecting their measurement accuracy. However, the statistical characteristics of these errors exhibit time-varying properties, which degrade model fidelity and consequently impair the performance of random error suppression algorithms. To address these issues, this study first proposes a recursive dynamic Allan variance calculation method that effectively mitigates the poor real-time performance and spectral leakage inherent in conventional dynamic Allan variance techniques.

Thermodynamic mechanism in colored glass substrates of interference filters under continuous-wave laser irradiation.

The ablation perforation damage of double-sided coated narrow-band filters based on RG-850 colored glass under out-of-band laser irradiation is investigated. A temperature-triggered nonlinear absorption mechanism is identified where substrate absorption sharply increases beyond a critical temperature. To quantify the resulting energy deposition dynamics, the multiple reflection model is employed, revealing the absorption enhancement by partial-transmission/high-reflection coatings.

Rule-adaptive lane-changing trajectory planning method for autonomous vehicles driven by dynamic risk information.

Rapid advancements in autonomous driving technology have highlighted the challenges of ensuring vehicle safety and driving efficiency in complex dynamic traffic environments. Current approaches typically define potential risks as safety constraints for compliance and use them in trajectory planning. However, the risks predefined in these constraints are often fixed, reducing driving efficiency.

Improving the thermoelectric properties of CaCoO by reducing thermal conductivity through composite nano-ZnO.

Composite nanomaterial is a scientific solution to modulating the properties of thermoelectric materials. The thermoelectric properties of CaCoO ceramic that remain stable in high-temperature air are relatively low, and how to decouple the relationship between heat and electricity is the focus of the research. This study systematically investigates the thermoelectric transport properties of composite CaCoO@ZnO materials.

Orbital Hybridization Modulation via Ni Atom Decoration in Phosphotungstic Acid Cluster Cocatalyst for Optimized Photocatalytic Hydrogen Evolution Kinetics.

Regulating the hydrogen adsorption and desorption behavior on the cocatalyst surface can effectively improve the performance of photocatalytic hydrogen production. While platinum-group materials excel in optimizing Fermi levels and proton reduction kinetics, their practical application is hindered by economic and scalability constraints. Herein, a novel Ni atom decorated phosphotungstic acid cluster (PTA-Ni) is developed as a cocatalyst integrated with graphitic carbon nitride (GCN) for photocatalytic hydrogen evolution.

Intelligentization of Electromagnetic Functional Materials: From Design to Applications.

With advancements in radar detection and electromagnetic (EM) communication technologies, intelligentizing EM functional materials (EFMs) and endowing them with dynamic responsiveness across multi-spectral ranges, along with the ability to perceive and adapt to complex operation environments, is of significant importance. This article provides a comprehensive review of the recent progress in intelligent EFMs. It begins with the fundamentals of intelligent EFMs, with an emphasis on their EM response mechanisms and basic functions.

Advances in Structural Reliability Analysis of Solid Propellant Grain: A Comprehensive Review.

Solid propellant grain, as a typical polymer, are the thrust generation devices and core load-bearing components of solid rocket motor (SRM) and are also known as SRM grain. They are constantly exposed to extreme service environments such as high temperatures, high pressures, and dynamic shocks, and have a relatively high failure rate in the field use of SRM. Its life and reliability are the shortcomings that restrict the improvement of weapons and equipment capability in China at present.

An Anti-Range-Deception-Jamming Method for Networked Moving Radar Based on Trajectory Optimization.

Aiming at the problem that the anti-range-deception-jamming effect of a networked moving radar system is severely affected by the spatial distribution of each radar, an anti-range-deception-jamming method for networked moving radar based on trajectory optimization is proposed. Firstly, the anti-jamming method of networked moving radar considering the radar position error (RPE) is proposed. Then, the theoretical expression for the false target (FT) misjudgment probability of networked moving radar is deduced.

A New Method of Remaining Useful Lifetime Estimation for a Degradation Process with Random Jumps.

With the deepening of degradation, the stability and reliability of the degrading system usually becomes poor, which may lead to random jumps occurring in the degradation path. A non-homogeneous jump diffusion process model is introduced to more accurately capture this type of degradation. In this paper, the proposed degradation model is translated into a state-space model, and then the Monte Carlo simulation of the state dynamic model based on particle filtering is employed for predicting the degradation evolution and estimating the remaining useful life (RUL).

Enhancing the Elevated-Temperature Mechanical Properties of Levitation Melted NbMoTaW Refractory High-Entropy Alloys via Si Addition.

To enhance the mechanical properties of NbMoTaW refractory high-entropy alloys (RHEAs), Si was added at varying concentrations ( = 0, 0.25, and 0.5) via vacuum induction levitation melting (re-melted six times for homogeneity).

EPRSA: interference resource scheduling algorithms for air-ground communication networks.

In recent years, the rapid development of air-ground communication networks has posed challenges to traditional interference methods. However, existing research rarely involves joint air-ground distributed communication interference, and there is a lack of the ability to schedule jammers with limited energy, a limited quantity, and different types. Based on this, this paper proposes the interference link margin in the mathematical model and normalizes and quantifies the optimization objectives.

Contextual semantics graph attention network model for entity resolution.

Entity resolution technology is the process of distinguishing whether data from different knowledge bases refer to the same entity in the real world. Existing research takes entity pairs as input and makes judgments based on the characteristics of entity pairs. However, there is insufficient utilization of contextual semantics, as existing methods fail to effectively model the token-attribute associations within data sources and cross-attribute semantic hierarchical relationships, which weakens the discriminative power of key attributes.

Magic cube metamaterials.

Traditionally, magic cube configurations, which have been employed to mechanically execute diverse and unconventional structural transformations, are capable of significantly boosting versatile electromagnetic responses of reconfigurable metamaterials. However, this idea is still in the initial exploration stage and faces many constraints. Here, we propose magic cube metamaterials with features of high transparency, multi-gradient phase distribution, full polarization, and high information, which manifest 47.

An Enhanced Dynamic Model of a Spatial Parallel Mechanism Receiving Direct Constraints from the Base at Two Point-Contact Higher Kinematic Pairs.

In this paper, a biologically congruent parallel mechanism (PM) inspired by the masticatory system of human beings has been proposed to recreate complete chewing behaviours in three-dimensional space. The mechanism is featured by direct constraints from the base (DCFB) to its end effector at two higher kinematic pairs (HKPs), which greatly raise its topological complexity. Meanwhile, friction effects occur at HKPs and actuators, causing wear and then reducing motion accuracy.

Construction and efficiency analysis of an embedded system-based verification platform for edge computing.

With the profound convergence and advancement of the Internet of Things, big data analytics, and artificial intelligence technologies, edge computing-a novel computing paradigm-has garnered significant attention. While edge computing simulation platforms offer convenience for simulations and tests, the disparity between them and real-world environments remains a notable concern. These platforms often struggle to precisely mimic the interactive behaviors and physical attributes of actual devices.

Depression EEG classification based on multi-scale convolutional transformer network.

Depression electroencephalograph (EEG) classification based on machine learning is helpful for the auxiliary diagnosis of major depression disorder (MDD). Multi-channel EEG has abundant spatial information because EEG electrodes are distributed in different brain regions. However, existing methods arrange EEG features as feature vectors, which destroys the spatial structure of the features and may affect the model's performance.

Effect of Potassium-Ion-Triggered Double Helix Aggregation on Shakedown Behavior of -Carrageenan/Polyacrylamide Hydrogel.

This study investigates the effect of potassium ion (K) concentration on double helix aggregation in -carrageenan-based hydrogels, which significantly influences their shakedown behavior. The shakedown behavior of -carrageenan/polyacrylamide (PAAm) hydrogels was characterized by the evolution of maximum stress and energy dissipation during cyclic load. The experimental results indicate that higher K concentrations significantly improve the maximum stress in the steady state, but barely influence the energy dissipation in the steady state.

A Novel Adaptive SFA-LII Based Fault Detection Method for Nonstationary Processes.

Multivariate statistical process monitoring (MSPM) methods have been widely used in industrial processes. Due to equipment aging, load changing and unknown disturbances, actual industrial processes tend to exhibit nonstationary characteristics. However, based on stationarity assumptions, traditional MSPM methods are unable to extract nonstationary features and accurately identify faults.

Matrine alleviates coronary microvascular dysfunction in ischemia with non-obstructive coronary artery disease mice induced by advanced glycation end products inhibition of the reactive oxygen species-mediated endoplasmic reticulum stress in cardiac microvascular endothelial cells.

Objective: To investigate the protective effect of matrine on coronary microvascular dysfunction (CMD) induced by advanced glycation end products (AGEs) in a mouse model of ischemia with non-obstructive coronary artery disease (INOCA), with a focus on the underlying mechanisms, particularly the endoplasmic reticulum (ER) stress protein kinase R-like ER kinase (PERK)/ nuclear factor of activated T-cells (NFAT) signaling pathway.

Methods: An INOCA model was established in mice, and CMD was induced by peritoneal injections of AGEs. Matrine was administered daily intraperitoneal injections.

Simulation of Aging and Bonding Properties of the Matrix/Filler Interface in Particle-Reinforced Composites.

To investigate the microscopic mechanism of aging-induced "dewetting" at the matrix/filler interface in Nitrate Ester Plasticized Polyether (NEPE) propellant, this study decoupled the aging process into two factors: crosslinking density evolution and nitrate ester decomposition. Molecular dynamics (MD) simulations were employed to construct all-component matrix models and matrix/filler interface models with varying aging extents. Key parameters including crosslinking density, mechanical properties, free volume fraction, diffusion coefficients of the matrix, as well as interfacial binding energy and radial distribution function (RDF) were calculated to analyze the effects of both aging factors on "debonding".

Impact of perceived severity on depression, anxiety, and insomnia among Chinese community residents during the COVID-19 lockdown.

Background: Depression, anxiety, and insomnia were found out that were significant relevance to the mental health impact of the coronavirus disease 2019 (COVID-19) lockdown.

Aim: To examine the interrelationships among perceived severity, anxiety, depression, insomnia, and sense of security in Chinese community residents during the COVID-19 lockdown period.

Methods: Participants were selected using simple random sampling from four large gated communities in Chengdu, China.

Multimodal data generative fusion method for complex system health condition estimation.

For the health management of complex systems, the high value of such systems often necessitates multimodal monitoring data, including video surveillance, internal sensors, empirical formulas, and even digital twins. Therefore, it is essential to design an effective intelligent fusion method for multimodal data. Firstly, a global monotonicity calculation method and a time series data augmentation technique are developed to address the inconsistencies arising from varying temporal lengths across different modalities.

Degradation modeling and remaining useful life prediction for electronic device under multiple stress influences.

Power driver devices have functions such as current amplification and power conversion, making them key components of electronic systems. Their degradation is affected by multiple types of stress, making it difficult to establish an accurate degradation model. To monitor the degradation state of electronic devices and predict their remaining useful life at different moments, this paper obtains the degradation data of the samples by carrying out accelerated degradation experiments of power driver devices under the influence of multiple stresses, and proposes a new multi-stress-coupled accelerated degradation model based on the Wiener process.