A5057970006- Particle physics theoretical and experimental studies
- Quantum Chromodynamics and Particle Interactions
- High-Energy Particle Collisions Research
- Dark Matter and Cosmic Phenomena
- Neutrino Physics Research
- Computational Physics and Python Applications
- Black Holes and Theoretical Physics
- Atomic and Subatomic Physics Research
- Nuclear physics research studies
- Medical Imaging Techniques and Applications
- Particle Accelerators and Free-Electron Lasers
- Particle Detector Development and Performance
- Cosmology and Gravitation Theories
- Energy Load and Power Forecasting
- Scientific Research and Discoveries
- EEG and Brain-Computer Interfaces
- Muscle activation and electromyography studies
- Advanced NMR Techniques and Applications
- Stock Market Forecasting Methods
- Advancements in Battery Materials
- Advanced Algorithms and Applications
- Spectroscopy and Chemometric Analyses
- Spectroscopy Techniques in Biomedical and Chemical Research
- Atomic and Molecular Physics
- Advanced Algebra and Geometry
Shandong University
2021-2025
Nanjing University of Chinese Medicine
2024-2025
Shandong First Medical University
2025
Shandong Tumor Hospital
2025
Guizhou University
2025
South China Normal University
2023-2025
South China Agricultural University
2025
Huanghe Science and Technology College
2024
Shanghai Maritime University
2024
Xuchang University
2024
Abstract Lithium metal is the most promising high‐energy‐density anode. However, it incompatible with high‐voltage cathodes in ether solvents due to their narrow electrochemical window. Herein, fluoroethylene carbonate (FEC) co‐solvent introduced regulate Li + solvation structures solvents, including cyclic (1,3‐dioxolane [DOL]) and linear glymes different chain lengths (1,2‐dimethoxyethane [DME], diglyme [G 2 ] triglyme 3 ]). The apparently effects of on ability interaction strength FEC are...
The grid-connected inverter with virtual synchronous generator (VSG) control technology can improve the friendliness of a distributed power supply to grid. However, its low-voltage ridethrough (LVRT) capability is insufficient, which results in difficulties limiting current and provide reactive support. A new LVRT strategy based on smooth switching proposed this paper. In strategy, voltage source mode VSG transformed into limit output support through proportional resonance algorithm under...
Stock market volatility has a significant impact on many economic and financial activities in the world. Forecasting stock price movement plays an important role setting investment strategy or determining right timing for trading. However, movements are noisy, nonlinear, chaotic. It is difficult to forecast trends improving return investment. Here, we proposed novel improved particle swarm optimization (IPSO) long-short term memory (LSTM) hybrid model forecasting. An adaptive mutation factor...
Abstract Antibiotic residues have become a significant challenge in food safety, threatening both ecosystem integrity and human health. To combat this problem, we developed an innovative photo‐powered, self‐powered aptasensor that employs novel carbon‐doped three‐dimensional graphitic carbon nitride (3D‐CN) combined with metal‐organic framework composed of N‐doped copper(I) oxide‐carbon (Cu 2 O@C) skeletons. The 3D‐CN serves as the photoanode, offering stable photocurrent production due to...
Abstract The von Neumann bottleneck has long been a significant obstacle to the advancement of era intelligent computing. Neuromorphic devices are considered promising solution overcome this bottleneck. These draw inspiration from information processing and computing capabilities neurons in human brain. Nevertheless, biomimetic synaptic used neural network encounter challenges, including high nonlinearity regulation, limited abundance state conductance, restrictions unidirectional...
Exploring the changes in plant functional traits and their relationship with environment karst climax communities across different latitudes can enhance our understanding of how these respond to environmental gradients. In this study, we focus on Guizhou Province, China. We selected three sample sites located at varying analyzed variations latitudes. Additionally, examined between factors, integrating species characteristics community structure into analysis. The results indicated that (1)...
This paper explores methods for optimizing product pricing and replenishment strategies in fresh supermarkets through advanced data analysis techniques. The initial processing involves merging cleaning, with a focus on statistical visual of sales distribution across products categories. Descriptive statistics are derived using line charts, bar pie charts based yearly, quarterly, monthly data. article analyzes relationships within the employing Kruskal-Wallis test, Spearman correlation...
In order to optimize diets for Bengal tiger cubs and improve their health condition survival rates, we conducted microbiota metabolomics analyses on fecal samples from fed goat dog milk replacer formulae. The results showed that there were significant differences in microorganisms metabolites between the two groups. At phylum level, major components of microbial composition feces Firmicutes, Actinobacteriota, Proteobacteria, Bacteroidota Fusobacteriota. addition, abundance gut varied...
Chrysanthemum tea is popular because of its health benefits, although different varieties vary in effectiveness and role. The rapid identification the variety critical for consumers industry. This study employed near-infrared (NIR) spectroscopy combination with feature extraction methods to characterize chrysanthemum varieties. To improve recognition accuracy, a fuzzy improved pseudoinverse linear discriminant analysis (FIPLDA) algorithm was extract information from NIR spectra that were...
The prediction of stock market fluctuations is crucial for decision-making in various financial fields. Deep learning algorithms have demonstrated outstanding performance index prediction. Recent research has also highlighted the potential Transformer model enhancing accuracy. However, faces challenges multi-step forecasting, including limitations inference speed long sequence and inadequacy traditional loss functions to capture characteristics noisy, nonlinear history data. To address these...
Abstract Discrete wavelet transform (WT) followed by principal component analysis (PCA) has been a powerful approach for the of biomedical signals. Wavelet coefficients at various scales and channels were usually transformed into one-dimensional array, causing issues such as curse dimensionality dilemma small sample size problem. In addition, lack time-shift invariance WT can be modeled noise degrades classifier performance. this study, we present stationary wavelet-based two-directional...
The traditional Chinese medicine (TCM) formulation Shengqiyichang Decoction (SQYCD) has been reported to stimulate host immunity, and it administered for the treatment of colorectal cancer (CRC). Here, we applied network bioinformatics analyses elucidate mechanisms by which SQYCD ameliorates CRC validated its modes action via
Abstract We experimentally demonstrated the phenomenon of period-multiplying pulses in self-mode-locking Nd:YVO 4 laser. With a fixed cavity length 50 mm and input mirrors resonator with radii curvature 100 mm, 200 500 mode-locked pulse periods times, 6 times 10 fundamental period are observed respectively. Besides, by tilting angle output mirror to control spatial distribution transverse modes, switching between period-multiplication state its harmonic self-locking can be achieved....
Abstract Resource-constrained problems for technology-based applications/services are common due to pervasive utilization and in-definite user/demand densities. Traditional resource allocation methods consume high time make it difficult predict the possible solutions from collection of resources. Various range through optimizations provided addressing issues that, however, result in imbalanced solutions. This article assimilates genetic algorithm (GA) fuzzy clustering process introduces...
Cyclin Dependent Kinase 1 (CDK1) plays a crucial role in cell cycle regulation, and dysregulation of its activity has been implicated various cancers. Although several CDK1 inhibitors are currently clinical trials, none have yet approved for therapeutic use. This research utilized deep learning techniques, specifically Recurrent Neural Networks with Long Short-Term Memory (LSTM), to generate potential inhibitors. Molecular docking, evaluation molecular properties, dynamics simulations were...