Comparative Noise Analysis of Readout Circuit in Hemispherical Resonator Gyroscope.

In high-precision Hemispherical Resonator Gyroscope (HRG) control systems, readout circuit noise critically determines resonator displacement detection precision. Addressing noise issues, this paper compares the noise characteristics and contribution mechanisms of the Transimpedance Amplifier (TIA) and Charge-Sensitive Amplifier (CSA). By establishing a noise model and analyzing circuit bandwidth, the dominant role of feedback resistor thermal noise in the TIA is revealed.

Simulation-Based Two-Stage Scheduling Optimization Method for Carrier-Based Aircraft Launch and Departure Operations.

The scheduling of carrier-based aircraft departure operations is subject to stringent temporal, spatial, and resource constraints. Conventional approaches struggle to yield exact solutions or provide a comprehensive mathematical description of this complex, dynamic process. This study proposes a simulation-based optimization method, establishing a high-fidelity simulation model for aircraft departure scheduling.

Design and analysis of combined discrete-time zeroing neural network for solving time-varying nonlinear equation with robot application.

Zeroing neural network (ZNN) is viewed as an effective solution to time-varying nonlinear equation (TVNE). In this paper, a further study is shown by proposing a novel combined discrete-time ZNN (CDTZNN) model for solving TVNE. Specifically, a new difference formula, which is called the Taylor difference formula, is constructed for first-order derivative approximation by following Taylor series expansion.

Spectral-spatial wave and frequency interactive transformer for hyperspectral image classification.

Efficient extraction of spectral-spatial features is essential for accurate hyperspectral image (HSI) classification, where capturing both local texture and global semantic relationships is critical. While Convolutional Neural Networks (CNNs) and Transformers have shown strong capabilities in modeling local and global dependencies, most existing architectures operate directly on raw spectral-spatial inputs and lack explicit mechanisms for frequency-domain decomposition thereby overlooking potentially discriminative phase and frequency components. To address this limitation, we propose a Spectral-Spatial Wave and Frequency Interactive Transformer for HSI classification, which integrates frequency-aware and phase-aware token representations into a unified Transformer framework.

Intersection-Based Emergent Organizational Brokers and Their Effect on the Resilience of Emergency Response Networks: A Case Study of Two Disasters in China.

This study focuses on intersection-based emergent organizational brokers (IBEOBs), which refers to the intersection of planned and emergent organization interactions. This study attempts to identify the role and composition of IBEOBs and examine their effect on the resilience of emergency response networks. We identified the information and resource networks in two disaster environments.

Underwater Drag Reduction Applications and Fabrication of Bio-Inspired Surfaces: A Review.

As an emerging energy-saving approach, bio-inspired drag reduction technology has become a key research direction for reducing energy consumption and greenhouse gas emissions. This study introduces the latest research progress on bio-inspired microstructured surfaces in the field of underwater drag reduction, focusing on analyzing the drag reduction mechanism, preparation process, and application effect of the three major technological paths; namely, bio-inspired non-smooth surfaces, bio-inspired superhydrophobic surfaces, and bio-inspired modified coatings. Bio-inspired non-smooth surfaces can significantly reduce the wall shear stress by regulating the flow characteristics of the turbulent boundary layer through microstructure design.

Wearable Glove with Enhanced Sensitivity Based on Push-Pull Optical Fiber Sensor.

Hand motion monitoring plays a vital role in medical rehabilitation, sports training, and human-computer interaction. High-sensitivity wearable biosensors are essential for accurate gesture recognition and precise motion analysis. In this work, we propose a high-sensitivity wearable glove based on a push-pull optical fiber sensor, designed to enhance the sensitivity and accuracy of hand motion biosensing.

"Rigid-Flexible" Strategy Realizes Robust Ultralong Phosphorescence for Multifunctional Display Unit and Photoreceptor Synapse.

Amorphous materials are highly attractive for the development of ultralong room temperature phosphorescence (URTP) due to their ease of processing, scalability, and flexibility. However, the realization of stable URTP polymers remains a great challenge. Here, it is reported a robust and flexible approach to realize high-quality URTP polymers by doping the organic phosphor into the polymer matrix with both hydrophilic and hydrophobic components.

Using deep learning to screen OCTA images for hypertension to reduce the risk of serious complications.

Background: As a disease with high global incidence, hypertension is known to cause systemic vasculopathy. Ophthalmic vessels are the only vascular structures that can be directly observed in a non-invasive manner. We aim to investigate the changes in ocular microvessels in hypertension using deep learning on optical coherence tomography angiography (OCTA) images.

Simulation approach for common female cancers: a brief review.

Simulation approach involves the use of computers and mathematical models to simulate real systems for experimentation or tests that evaluate the behavior and performance of a system or predict the results of various hypothetical scenarios. Due to its rapid development in the context of cancer, we introduce commonly used cancer simulation approach, and review the application of these approach in common cancers of women, such as breast, cervical, ovarian and endometrial cancers, to provide new ideas and directions for cancer study as well as clinical treatment.

Enhanced Encoding Module of AisNet with Charge Features: An Application to the S2 Data Set.

This research introduces a charge-enhanced encoding module within the AisNet multifeature fusion framework, demonstrating superior force error accuracy and cross-model transferability, and achieving in state-of-the-art performance on the S2 dataset. Compared with the original AisNet, the addition of the Coulomb matrix enables AisNet-C with ternary features to maintain its leading performance in all feature dimensions. Through t-SNE and PCA analysis, long-range Coulomb interaction effectively enhances global environmental resolution, forming a synergistic relationship with other features.

Characteristics of a new UT-type prefabricated joint for rectangular steel tubes under combined axial-moment loading.

This study proposes a UT-type prefabricated joint incorporating adjustable sleeves (±5 mm tolerance) and an energy-dissipating segment to address the practical demands for construction tolerance management and plasticity assurance. Through systematic static and cyclic loading tests, the paper examines the mechanical behavior of UT-type joints under the combined axial force and bending moment. The results demonstrate that axial force significantly influences joint performance.

A multi-spectral radiation thermometry method based on MGACO-RFR emissivity model identification under the background of high temperature.

Multi-spectral radiation thermometry is extensively applied in high-temperature fields. Currently, multi-spectral radiation thermometry technology still faces issues such as inaccurate identification of target emissivity models due to high-temperature background reflection and significant temperature measurement errors. This paper proposes a multi-spectral radiation thermometry method based on a Mixed Genetic Algorithm and Ant Colony Optimization Random Forest (MGACO-RFR) for emissivity model identification.

Prediction model for postoperative pulmonary complications after thoracoscopic surgery with machine learning algorithms and SHapley Additive exPlanations.

Background: Postoperative pulmonary complications (PPCs) are common and have a negative impact on postoperative morbidity and mortality, with associated medical resource use and cost care plan. Management of preoperative and intraoperative risk factors has been shown to reduce the occurrence of PPCs. Therefore, this study aimed to develop a risk prediction model for PPCs based on explainable machine learning (ML) methods and evaluate its predictive performance in order to enhance the prevention and intervention for PPCs.

A characteristic non-reflective boundary for low Mach number flow-induced noise.

Characteristic boundary conditions are widely used to simulate compressible flow-induced noise. This study extends the application to incompressible flow-induced noise by introducing a low Mach number characteristic boundary condition (LMCBC) to eliminate sound wave reflections at boundaries. This boundary condition is derived from the second type of acoustic perturbation equations (APE-2) and implemented within the open-source software OpenFOAM (OpenCFD Ltd, Bracknell, Berkshire, UK).

Bioactivity-guided isolation of benzocoumarin and quinonoid compounds from and their anti-inflammatory activity in .

The bioactivity-guided isolation was performed to explore bioactive components from 75% ethanol extract of . The structures of ten compounds, including one new benzocoumarin type compound () and nine known quinonoids (-), were determined by means of analysis of comprehensive spectroscopic data. Anti-inflammatory activity evaluation revealed that compounds - could inhibit overproduction of NO induced by LPS, and compounds - and - exhibited the inhibitory ration more than 50% at 30 M, especially compound exhibited the strongest inhibitive efficiency with 80.

High-mechanical properties, anti-freezing, and self-regeneration zwitterionic poly (ionic liquid) hydrogel reinforced by cellulose nanofibers for strain sensor applications.

A novel zwitterionic poly (ionic liquid) hydrogel was constructed through the room-temperature in situ polymerization of acrylamide (Am), 3-(1-vinyl-3-imidazolio) propanesulfonate (ZILs), cellulose nanofibers (CNFs) and lithium chloride (LiCl). The synergistic effects in the network (i.e.

Spatio-Temporal Geographic Networks for Value Co-Creation and Technology Transfer in China with Patent Data.

With the increasing complexity of technology, cross-regional joint patent applications and patent transfers have become a prominent component of knowledge activities, attracting substantial attention of academic researchers. To examine the state and distribution characteristics of inter-city knowledge flows, this study utilizes patent data from the China National Intellectual Property Administration database and conducts in-depth data exploration to construct two urban knowledge networks (UKN). Specifically, over 1.

Reconfiguration planning and structure parameter design of a reconfigurable cable-driven lower limb rehabilitation robot.

Reconfigurable cable-driven parallel robots (RCDPRs) have attracted much attention as a novel type of cable-driven robot that can change their cable anchor position. The reconfigurable cable-driven lower limb rehabilitation robot (RCDLR) employs RCDPRs in lower limb rehabilitation to achieve multiple training modes. This paper investigates the reconfiguration planning and structural parameter design of the RCDLR.

Prediction of compressor aerodynamic noise based on transfer learning Random Forest.

Aerodynamic noise is an important evaluation indicator for high-pressure ratio centrifugal compressors. However, using traditional numerical methods to predict aerodynamic noise requires significant computational resources and time, making it challenging to quickly assess the aerodynamic noise of compressors. This study proposes a transfer learning-based method for predicting the aerodynamic noise of centrifugal compressors.

Multifunctional terahertz device with angular resilience for biomedical sensing and polarization conversion.

The demand for high-performance devices capable of both electromagnetic wave manipulation and biomedical detection has intensified with the growth of terahertz technologies. However, most existing devices are designed for a single function, either polarization control or biosensing which limits their utility in integrated systems. Addressing this challenge, we introduce a cost-effective terahertz device that seamlessly integrates broadband cross polarization transformation with precise refractive index sensing, all within a fabrication-friendly structure.

Temperature-field multiscale regulated 3D PVA-PPy conductive hydrogel for enhanced bio-electrocatalytic performance.

Microbial fuel cells (MFCs) have been proven to be a green technology for solving energy crises, but their low power density limits their large-scale practical applications. In this paper, a three-dimensional porous composite hydrogel polyvinyl alcohol/polypyrrole (PVA/PPy) with good biocompatibility was prepared by temperature-field regulation via alternating cycles between low temperature (- 20 °C) and room temperature (25 °C) and used as the anode in MFC. The three-dimensional network structure of PPy nanospheres compressed by ice crystal stress exhibited excellent charge conduction capability and ion transport performance, which significantly improved the interfacial charge transfer efficiency of PVA/PPy-5 bioanode.

Plasticity-based design and static performance of UT-type joint for construction error adaptation.

To solve the problem of insufficient development of prefabricated rectangular hollow section (RHS) beam-column joints, a new type of prefabricated joint (UT-type joint) is proposed in this paper. The problem of construction error is effectively solved using a unique structural design, and the plastic energy dissipation section is introduced based on the concept of plastic controllability. This research mainly includes three aspects: (1) a new type of beam-column loading test device is designed, and a static loading test of the UT-type joint is carried out to evaluate the static performance of the joint; (2) through finite element simulation, the static performances of UT-type joints and traditional RHS joints are compared; and (3) based on the existing specifications and simulation results, a simplified design method for UT-type joints is proposed.

A Module-Level Polygenic Risk Score-Based NetWAS Framework for Identifying AD Genetic Modules Mediated by Amygdala: An ADNI Study.

Network-based GWAS (NetWAS) has advanced brain imaging research by identifying genetic modules associated with brain alterations. However, how imaging risk genes exert functions in brain diseases, particularly their mediation through imaging quantitative traits (iQTs), remains underexplored. We propose a module-level polygenic risk score (MPRS)-based NetWAS framework to uncover genetic modules associated with Alzheimer's disease (AD) through the mediation of an iQT, using amygdala density as a case study.