University of Electronic Science and Technology of China

Recent Advances in Infrared‐to‐Visible Upconversion Photodetectors: From Multi‐Dimensional Innovations to Future Perspectives

ABSTRACT Thin‐film infrared‐to‐visible upconversion photodetectors (UCDs) have emerged as a cost‐effective, pixel‐less paradigm for infrared (IR) visualization. This review first elucidates mainstream upconversion modalities, device configurations, and the physical principles of...

A Comparative Study of Machine-Learning Methods for Early Classification from Sparse Astronomical Light Curves

The booming data volume of modern time-domain surveys demands fast, robust early classification of sparsely sampled light curves, as newly discovered transients typically have only a handful of observations. We compare classifiers for extremely sparse light curves (3–30 observati...

Interlayer charge-transfer states in SnS2/InSe Van der Waals heterostructures realizing mid-infrared photodetection

Abstract Two-dimensional (2D) van der Waals (vdWs) heterostructures offer a versatile platform where engineered interlayer coupling enables optical processes beyond those of individual materials. Their atomically sharp interfaces support charge-transfer states, directional carrie...

A Novel Multi-Scale Dual-Modality CNN Approach Leveraging Light and Dark Fingerprints for RSS-Based Indoor Positioning

Traditional indoor localization using received signal strength (RSS) fingerprinting commonly uses measured RSS values as location-related inputs. This paper investigates a paired light–dark representation of an RSS fingerprint image and a cross-modality multi-scale fusion model f...

Prescribed‐Time Adaptive Dynamic Surface Control for Non‐Strict‐Feedback Nonlinear Systems

ABSTRACT In this paper, we investigate the practical prescribed‐time (PPT) tracking control problem for a class of nonlinear non‐strict‐feedback systems with arbitrarily bounded initial states. A radial basis function neural network (RBFNN) is employed to approximate unknown and...

MetaMamba: Meta-learning with mamba for few-shot vegetation species classification using UAV-based hyperspectral imagery in desert rangeland

Effective monitoring of desert rangeland ecosystems is of crucial significance to regional ecological security. Unmanned aerial vehicle (UAV) hyperspectral remote sensing provides an effective means for the fine identification of vegetation species. However, in practical applicat...

High‐Energy, 4‐kW Peak‐Power, Single‐Frequency Nanosecond Fiber Amplifier at 2.7 µm

ABSTRACT Single‐frequency (SF) pulsed lasers in the mid‐infrared (MIR) spectral region are highly demanded for applications in spectroscopy, LIDAR, and nonlinear frequency conversion, yet scaling their pulse energy and peak power while maintaining robust SF operation remains chal...

Fast Generation of Feasible Unit Commitment Schedules Based on Standardized Net-Load Trajectory Similarity and Historical Schedule Transfer

High penetration of wind and photovoltaic generation reshapes power system net-load profiles and increases the computational burden of repeatedly solving security-constrained unit commitment problems under multiple renewable scenarios. This paper proposes a fast schedule generati...

Single-cell and spatial transcriptomics reveal glycolytic remodeling and ENO1-associated metabolic vulnerability in hepatoblastoma

Hepatoblastoma (HB) is the most common malignant liver tumor in children; however, the contribution of glycolytic metabolic reprogramming to HB development and progression remains incompletely characterized. We integrated single-cell RNA sequencing and spatial transcriptomic data...

Development of a Two Stage Pipeline for Robust Pulmonary Nodule Detection in Consecutive CT Slices

Background/Objectives: Current pulmonary nodule detection systems often neglect the spatiotemporal continuity inherent in computed tomography (CT) sequences within a single scan. They treat individual slices as independent images and lack mechanisms to recover missed detections....

An Improved Informed-RRT* Algorithm Based on Risk-Density-Aware Corridor Sampling and Improvement-Bound Rejection for Path Planning

Sampling-based path planning is widely used in autonomous navigation, but Informed-RRT* still relies mainly on geometric ellipsoidal sampling and does not explicitly evaluate local obstacle risk, which can lead to invalid expansion, redundant nodes, and slow convergence. This pap...

Comparative study of ensemble-based uncertainty quantification methods for neural network interatomic potentials

Abstract Machine learning interatomic potentials (MLIPs) enable atomistic simulations with near first-principles accuracy at substantially reduced computational cost, making them powerful tools for large-scale materials modeling. The accuracy of MLIPs is typically validated on a...

Geometric frustration and strain-engineered magnetic phase transitions in the pentagonal FeS 2 monolayer

Two-dimensional pentagonal materials have recently emerged as a promising platform for exploring novel magnetic phenomena. Using first-principles calculations, we systematically investigate the strain-tunable optical and magnetic properties of $\mathrm{penta}\text{\ensuremath{-}}...

An Integrated Fault Localization and Diagnosis Method for NPP Temperature Sensor Systems Based on Abnormal Feature-GCN

Temperature sensor systems are critical for nuclear power plant (NPP) condition monitoring, whose reliability underpins unit safety and stability. Fault localization and diagnosis are essential to sustain their stable service. Conventional Principal Component Analysis (PCA) and G...

Mechanical Programming of PEGDA‐ β ‐CD Polyrotaxane‐Based Hydrogels via Host–Guest Molecular Recognition

ABSTRACT Polyrotaxane‐based hydrogels with mechanically interlocked structures offer unique opportunities for designing biomaterials with tunable mechanical properties in tissue engineering. However, the polyrotaxane structure based on poly(ethylene glycol) (PEG) and β ‐cyclodext...

FSC-BiMamba: A Dual-Branch Bidirectional Mamba Network for Frontal Sparse-Channel EEG Depression Detection

Background: Major depressive disorder (MDD) is a common psychiatric disorder. Electroencephalography (EEG) provides physiological information for depression detection, but many existing methods rely on dense multichannel recordings, limiting their use in lightweight EEG screening...

R-MCTS: Retrospective Offline Correction for Multi-Agent LLM Task Planning

We present R-MCTS, a retrospective (offline) correction framework for LLM-based multi-agent embodied task planning: failed trajectories are recorded, a lightweight scorer estimates action quality from recorded data alone, a Monte Carlo Tree Search rooted at the failure point prop...

Development of a core competency evaluation indicator system for weight management nurses: a Delphi and analytic hierarchy process study

Weight management services increasingly require nurses to contribute to risk assessment, behavioural support, multidisciplinary coordination and long-term follow-up. However, there is limited consensus on the competencies required for nurses working in this emerging field. This s...

Efficient Colon Cancer Immunogene Therapy by Hydrogel Ball Loaded With Two Types of Cell Membrane‐Coated Nanoparticles

ABSTRACT Biomimetic technology has high potential for enhancing cancer immunogene therapy. Cell membrane‐coated nanoparticles (CMNPs) obtain extra targeting, recognition, and signaling transduction functions. However, a single kind of CMNPs is limited when facing complicated tumo...

A privacy-preserving data augmentation approach for credit card fraud detection

Abstract Credit card fraud costs credit card companies billions of dollars annually. Privacy concerns prevent most banks from sharing transaction data. Federated Learning enables multiple companies to train a unified model while preserving the privacy of sensitive data. The scarc...