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Articles by Xiaoping Lu
Tianwen-2 mission target asteroid (469219) Kamoʻoalewa probably develops an Itokawa-compositional but more space-weathered surface
Abstract China’s ongoing Tianwen-2 mission will return samples from a small, rapidly spinning Earth quasi-satellite (469219) Kamoʻoalewa. Previous studies linked Kamoʻoalewa to lunar composition and origin. Here, we propose another scenario. We reanalyze the reflectance spectrum of Kamoʻoalewa and obtain an absorption band center at 1.001 ± 0.028 μm (error is 1σ), consistent with LL chondrites.
IGF2BP3 Knockdown Induces Ferroptosis by Inhibiting Autophagy-Mediated EMC2 Degradation in Ovarian Cancer
Xiaoping Lu and Jinping Ni were contributed equally to the article. X.Lu, J.Ni, C.Qian, et al., “IGF2BP3 Knockdown Induces Ferroptosis by Inhibiting Autophagy-Mediated EMC2 Degradation in Ovarian Cancer,” Journal of Biochemical and Molecular Toxicology40 (2026): e70801. https://doi.org/10.1002/jbt.70801. Conflicts of Interest The authors declare no conflicts of interest.
scRNA+TCR-seq reveals the proportion and characteristics of dual TCR Treg cells in mouse lymphoid and non-lymphoid tissues
eLife Assessment This study reanalyzed previously published scRNA-seq and TCR-seq data to examine the proportion and characteristics of dual-TCR-expressing Treg cells in mice, presenting some useful insights into TCR diversity and immune regulation. However, the evidence is incomplete, particularly with respect to data interpretation, statistical rigor, and the functionality of dual -TCR Treg cells. The study is potentially of interest to immunologists studying T-cell biology.
A Self-Rewarding Mechanism in Deep Reinforcement Learning for Trading Strategy Optimization
4.5. Experimental Results 4.5.1. Comparison with Baselines To assess the effectiveness of the proposed method, we conducted a comparative evaluation of the SRDDQN model against various baseline models across six different datasets. The experimental results demonstrate that the SRDDQN model significantly outperforms the other models on four major financial metrics: CR, AR, SR, and MDD, as shown in Table 3.
DDAM-Net: A Difference-Directed Multi-Scale Attention Mechanism Network for Cultivated Land Change Detection
All articles published by MDPI are made immediately available worldwide under an open access license. No special permission is required to reuse all or part of the article published by MDPI, including figures and tables. For articles published under an open access Creative Common CC BY license, any part of the article may be reused without permission provided that the original article is clearly cited. For more information, please refer to https://www.mdpi.com/openaccess.
Extraction of Maize Distribution Information Based on Critical Fertility Periods and Active-Passive Remote Sensing
All articles published by MDPI are made immediately available worldwide under an open access license. No special permission is required to reuse all or part of the article published by MDPI, including figures and tables. For articles published under an open access Creative Common CC BY license, any part of the article may be reused without permission provided that the original article is clearly cited. For more information, please refer to https://www.mdpi.com/openaccess.
Agronomy | Free Full-Text | Application of the Reconstructed Solar-Induced Chlorophyll Fluorescence by Machine Learning in Agricultural Drought Monitoring of Henan Province, China from 2010 to 2022
All articles published by MDPI are made immediately available worldwide under an open access license. No special permission is required to reuse all or part of the article published by MDPI, including figures and tables. For articles published under an open access Creative Common CC BY license, any part of the article may be reused without permission provided that the original article is clearly cited. For more information, please refer to https://www.mdpi.com/openaccess.
Yield Prediction of Winter Wheat at Different Growth Stages Based on Machine Learning
All articles published by MDPI are made immediately available worldwide under an open access license. No special permission is required to reuse all or part of the article published by MDPI, including figures and tables. For articles published under an open access Creative Common CC BY license, any part of the article may be reused without permission provided that the original article is clearly cited. For more information, please refer to https://www.mdpi.com/openaccess.
MambaSR: Arbitrary-Scale Super-Resolution Integrating Mamba with Fast Fourier Convolution Blocks
All articles published by MDPI are made immediately available worldwide under an open access license. No special permission is required to reuse all or part of the article published by MDPI, including figures and tables. For articles published under an open access Creative Common CC BY license, any part of the article may be reused without permission provided that the original article is clearly cited. For more information, please refer to https://www.mdpi.com/openaccess.
Inversion Method for Monitoring Daily Variations in Terrestrial Water Storage Changes in the Yellow River Basin Based on GNSS
All articles published by MDPI are made immediately available worldwide under an open access license. No special permission is required to reuse all or part of the article published by MDPI, including figures and tables. For articles published under an open access Creative Common CC BY license, any part of the article may be reused without permission provided that the original article is clearly cited. For more information, please refer to https://www.mdpi.com/openaccess.
Constructing a Machine Learning Model for Rapid Urban Flooding Forecast in Sloping Cities along the Yangtze River: A Case Study in Jiujiang
1. Introduction In recent years, big data methods have gradually been applied to urban flooding, stormwater management, and other related fields [1,2,3,4]. The integration of multi-source information, such as satellite radar and precipitation data, along with extensive data mining and intelligent analytical methods, has become the focal point of high-precision information identification in the hydrological field.
R-DDQN: Optimizing Algorithmic Trading Strategies Using a Reward Network in a Double DQN
1. Introduction With the rapid development of modern artificial intelligence (AI) techniques, modern machine learning is gaining more attention from scholars. In particular, the remarkable pace of development in deep learning has been evident since the introduction of various representative neural network architectures, which have led to significant achievements in the domains of CV [1,2,3], NLP [4,5,6], and time series analysis [7,8,9,10].
DADE-DQN: Dual Action and Dual Environment Deep Q-Network for Enhancing Stock Trading Strategy
1. Introduction The primary objective of investing in financial assets is usually to optimize returns while effectively managing risk. This objective revolves around striking a balance between risk and returns to achieve sustainable long-term investment returns. However, traditional methods typically involve human traders who analyze market data and trends, evaluate price fluctuations, and execute buy and sell trades based on their decisions.
Inversion of Wheat Leaf Area Index by Multivariate Red-Edge Spectral Vegetation Index
Open AccessArticle by Xiaoxuan Wang 1, Guosheng Cai 1,*, Xiaoping Lu 1, Zenan Yang 1, Xiangjun Zhang 2 and Qinggang Zhang 1 1 Key Laboratory of Spatio-Temporal Information and Ecological Restoration of Mines of Natural Resources of the People’s Republic of China, Henan Polytechnic University, Jiaozuo 454003, China 2 Institute of Remote Sensing and Surveying and Mapping, Zhengzhou 450000, China * Author to whom correspondence should be addressed.
Using time series vector features for annual cultivated land mapping: A trial in northern Henan, China
Satellite data Sentinel-2 is a polar-orbit, high-resolution, multi-spectral imaging mission for terrestrial monitoring. It consists of two satellites, Sentinel-2A and Sentinel-2B, which are each equipped with a multi-spectral imager (MSI). Sentinel-2 satellite data includes data for 13 spectral bands, ranging from visible and near-infrared light to short-wave infrared light, with a ground resolution of up to 10 m (Table 1).
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