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Imbalanced rock burst assessment using variational autoencoder-enhanced gradient boosting algorithms and explainability

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Underground Space 2024年第4期17卷 226-245页

作者： Shan Lin zenglong liang Miao Dong Hongwei Guo Hong Zheng Key Laboratory of Urban Security and Disaster Engineering Ministry of EducationBeijing University of TechnologyBeijing 100124China Department of Civil and Environmental Engineering The Hong Kong Polytechnic University(PolyU)Hung HomKowloon 999077Hong KongChina

We conducted a study to evaluate the potential and robustness of gradient boosting algorithms in rock burst assessment,established a variational autoencoder(VAE)to address the imbalance rock burst dataset,and proposed a multilevel explainable artificial intelligence(XAI)tailored for tree-based ensemble *** collected 537 data from real-world rock burst records and selected four critical features contributing to rock burst ***,we employed data visualization to gain insight into the data’s structure and performed correlation analysis to explore the data distribution and feature ***,we set up a VAE model to generate samples for the minority class due to the imbalanced class *** conjunction with the VAE,we compared and evaluated six state-of-theart ensemble models,including gradient boosting algorithms and the classical logistic regression model,for rock burst *** results indicated that gradient boosting algorithms outperformed the classical single models,and the VAE-classifier outperformed the original classifier,with the VAE-NGBoost model yielding the most favorable *** to other resampling methods combined with NGBoost for imbalanced datasets,such as synthetic minority oversampling technique(SMOTE),SMOTE-edited nearest neighbours(SMOTE-ENN),and SMOTE-tomek links(SMOTE-Tomek),the VAE-NGBoost model yielded the best ***,we developed a multilevel XAI model using feature sensitivity analysis,Tree Shapley Additive exPlanations(Tree SHAP),and Anchor to provide an in-depth exploration of the decision-making mechanics of VAE-NGBoost,further enhancing the accountability of treebased ensemble models in predicting rock burst occurrences.

关键词： Gradient boosting VAE Ensemble learning Explainable artificial intelligence(XAI) Rock burst

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Interpretable gradient boosting based ensemble learning and African vultures optimization algorithm optimization for estimating deflection induced by excavation

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FRONTIERS OF STRUCTURAL AND CIVIL ENGINEERING 2024年第11期18卷 1698-1712页

作者： liang, zenglong Lin, Shan Dong, Miao Cao, Xitailang Guo, Hongwei Zheng, Hong Beijing Univ Technol Key Lab Urban Secur & Disaster Engn Minist Educ Beijing 100124 Peoples R China Hong Kong Polytech Univ PolyU Dept Civil & Environm Engn Hong Kong 999077 Peoples R China

Intelligent construction has become an inevitable trend in the development of the construction industry. In the excavation project, using machine learning methods for early warning can improve construction efficiency and quality and reduce the chances of damage in the excavation process. An interpretable gradient boosting based ensemble learning framework enhanced by the African Vultures Optimization Algorithm (AVOA) was proposed and evaluated in estimating the diaphragm wall deflections induced by excavation. We investigated and compared the performance of machine learning models in predicting deflections induced by excavation based on a database generated by finite element simulations. First, we exploratively analyzed these data to discover the relationship between features. We used several state-of-the-art intelligent models based on gradient boosting and several simple models for model selection. The hyperparameters for all models in evaluation are optimized using AVOA, and then the optimized models are assembled into a unified framework for fairness assessment. The comprehensive evaluation results show that the AVOA-CatBoost built in this paper performs well (RMSE = 1.84, MAE = 1.18, R2 = 0.9993) and cross-validation (RMSE = 2.65 +/- 1.54, MAE = 1.17 +/- 0.23, R2 = 0.998 +/- 0.002). In the end, in order to improve the transparency and usefulness of the model, we constructed an interpretable model from both global and local perspectives.

关键词： African vultures optimization algorithm gradient boosting ensemble learning interpretable model wall deflection prediction

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千米立井揭煤施工

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建井技术 2017年第3期38卷 8-10,45页

作者：梁增龙中煤第五建设有限公司江苏徐州221140

淮南潘三矿千米立井深部施工中,需揭穿4-1突出煤层。揭煤前,采用前探释放抽排技术,在距煤层顶板不同法距位置,进行多次探放,使瓦斯含量降到安全范围内,最后顺利通过。简要介绍了揭煤前期准备工作、揭煤施工工艺及揭煤施工安全技术措施。

关键词：千米立井突出煤层揭煤施工防突措施

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“Slope-adsorption & plateau-pore filling” mechanism unlocking the potential of hard carbon anodes for “fast-charging & large-sized”batteries

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Science China Materials 2025年第1期 309-311页

作者： Tian liang Xiaoming Zhu Hubei Key Laboratory of Radiation Chemistry and Functional Materials School of Nuclear Technology and Chemistry & Biology Hubei University of Science and Technology

To date, there has been no report on fast-charging and Ahlevel sodium-ion batteries (SIBs) by utilizing thick hard carbon anodes that demonstrate prolonged cycling life and high areal capacity at high rates. Further, the relationship among the complex structure of hard carbon, storage mechanism, and fastcharging performance in alkali-metal ion batteries has been a subject of ongoing debate [1,2].

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The dopaminergic system and Alzheimer's disease

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Neural Regeneration Research 2025年第9期20卷 2495-2512页

作者： Yuhan Zhang Yuan liang Yixue Gu International Medical College Chongqing Medical UniversityChongqingChina College of Pharmacy Chongqing Medical UniversityChongqingChina Department of Neurology The First Affiliated Hospital of Chongqing Medical UniversityChongqing Key Laboratory of NeurologyChongqingChina

Alzheimer's disease is a common neurodegenerative disorder in older *** its prevalence,its pathogenesis remains unclea *** addition to the most widely accepted causes,which in clude excessive amyloid-beta aggregation,tau hyperphosphorylation,and deficiency of the neurotransmitter acetylcholine,numerous studies have shown that the dopaminergic system is also closely associated with the occurrence and development of this *** is a crucial catecholaminergic neurotransmitter in the human ***-associated treatments,such as drugs that target dopamine receptor D and dopamine analogs,can improve cognitive function and alleviate psychiatric symptoms as well as ameliorate other clinical *** r,therapeutics targeting the dopaminergic system are associated with various adverse reactions,such as addiction and exacerbation of cognitive *** review summarizes the role of the dopaminergic system in the pathology of Alzheimer's disease,focusing on currently available dopamine-based therapies for this disorder and the common side effects associated with dopamine-related *** aim of this review is to provide insights into the potential connections between the dopaminergic system and Alzheimer's disease,thus helping to clarify the mechanisms underlying the condition and exploring more effective therapeutic options.

关键词： adverse drug reaction Alzheimer's disease catecholamine dopamine receptor dopamine receptor heterodimers dopaminergic system neurodegenerative disease neurotransmitter signaling pathways traditional Chinese medicine treatment

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Joint Probabilistic Scheduling and Resource Allocation for Wireless Networked Control Systems

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IEEE/CAA Journal of Automatica Sinica 2025年第1期 258-260页

作者： Meng Zheng Lei Zhang Wei liang IEEE the State Key Laboratory of Robotics and the Key Laboratory of Networked Control Systems Shenyang Institute of Automation Chinese Academy of Sciences the University of Chinese Academy of Sciences

Dear Editor,This letter presents a joint probabilistic scheduling and resource allocation method(PSRA) for 5G-based wireless networked control systems(WNCSs). As a control-aware optimization method, PSRA minimizes the linear quadratic Gaussian(LQG) control cost of WNCSs by optimizing the activation probability of subsystems, the number of uplink repetitions, and the durations of uplink and downlink phases. Simulation results show that PSRA achieves smaller LQG control costs than existing works.

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Epigenetic regulation of the inflammatory response in stroke

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Neural Regeneration Research 2025年第11期20卷 3045-3062页

作者： Jingyi liang Fei Yang Zixiao Li Qian Li School of Basic Medical Sciences Capital Medical UniversityBeijingChina Department of Neurobiology School of Basic Medical SciencesCapital Medical UniversityBeijingChina Laboratory for Clinical Medicine Beijing Key Laboratory of Neural Regeneration and RepairCapital Medical UniversityBeijingChina Department of Neurology Beijing Tiantan HospitalCapital Medical UniversityBeijingChina China National Clinical Research Center for Neurological Diseases Beijing Tiantan HospitalCapital Medical UniversityBeijingChina National Center for Healthcare Quality Management in Neurological Diseases Beijing Tiantan HospitalCapital Medical UniversityBeijingChina Chinese Institute for Brain Research BeijingChina Research Unit of Artificial Intelligence in Cerebrovascular Disease Chinese Academy of Medical SciencesBeijingChina Beijing Engineering Research Center of Digital Healthcare for Neurological Diseases BeijingChina Department of Biochemistry and Molecular Biology School of Basic Medical SciencesCapital Medical UniversityBeijingChina Beijing Key Laboratory of Cancer Invasion and Metastasis Research Capital Medical UniversityBeijingChina

Stroke is classified as ischemic or hemorrhagic,and there are few effective treatments for either *** mechanisms play a critical role in secondary brain injury following a stroke,which manifests as cytokine release,blood–brain barrier disruption,neuronal cell death,and ultimately behavioral *** the inflammatory response has been shown to mitigate this cascade of events in experimental stroke ***,in clinical trials of anti-inflammatory agents,longterm immunosuppression has not demonstrated significant clinical benefits for *** may be attributable to the dichotomous roles of inflammation in both tissue injury and repair,as well as the complex pathophysiologic inflammatory processes in *** acute harmful inflammatory responses or inducing a phenotypic shift from a pro-inflammatory to an anti-inflammatory state at specific time points after a stroke are alternative and promising therapeutic *** agents that can modulate inflammation requires a detailed understanding of the inflammatory processes of ***,epigenetic reprogramming plays a crucial role in modulating post-stroke inflammation and can potentially be exploited for stroke *** this review,we summarize current findings on the epigenetic regulation of the inflammatory response in stroke,focusing on key signaling pathways including nuclear factor-kappa B,Janus kinase/signal transducer and activator of transcription,and mitogen-activated protein kinase as well as inflammasome *** also discuss promising molecular targets for stroke *** evidence to date indicates that therapeutic targeting of the epigenetic regulation of inflammation can shift the balance from inflammation-induced tissue injury to repair following stroke,leading to improved post-stroke outcomes.

关键词： DNA methylation histone modification intracerebral hemorrhage ischemic stroke neuroinflammation neuroprotection non-coding RNA RNA methylation subarachnoid hemorrhage treatment

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Multi-model ensemble learning for battery state-of-health estimation:Recent advances and perspectives

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Journal of Energy Chemistry 2025年第1期100卷 739-759页

作者： Chuanping Lin Jun Xu Delong Jiang Jiayang Hou Ying liang Zhongyue Zou Xuesong Mei State Key Laboratory for Manufacturing Systems Engineering Xi'an Jiaotong University Shaanxi Key Laboratory of Intelligent Robots School of Mechanical Engineering Xi'an Jiaotong University Department of Electrical Engineering and Automation Luoyang Institute of Science and Technology School of Mechanical Engineering Hangzhou Dianzi University

The burgeoning market for lithium-ion batteries has stimulated a growing need for more reliable battery performance monitoring. Accurate state-of-health(SOH) estimation is critical for ensuring battery operational performance. Despite numerous data-driven methods reported in existing research for battery SOH estimation, these methods often exhibit inconsistent performance across different application scenarios. To address this issue and overcome the performance limitations of individual data-driven models,integrating multiple models for SOH estimation has received considerable attention. Ensemble learning(EL) typically leverages the strengths of multiple base models to achieve more robust and accurate outputs. However, the lack of a clear review of current research hinders the further development of ensemble methods in SOH estimation. Therefore, this paper comprehensively reviews multi-model ensemble learning methods for battery SOH estimation. First, existing ensemble methods are systematically categorized into 6 classes based on their combination strategies. Different realizations and underlying connections are meticulously analyzed for each category of EL methods, highlighting distinctions, innovations, and typical applications. Subsequently, these ensemble methods are comprehensively compared in terms of base models, combination strategies, and publication trends. Evaluations across 6 dimensions underscore the outstanding performance of stacking-based ensemble methods. Following this, these ensemble methods are further inspected from the perspectives of weighted ensemble and diversity, aiming to inspire potential approaches for enhancing ensemble performance. Moreover, addressing challenges such as base model selection, measuring model robustness and uncertainty, and interpretability of ensemble models in practical applications is emphasized. Finally, future research prospects are outlined, specifically noting that deep learning ensemble is poised to advance ens

关键词： Lithium-ion battery State-of-health estimation Data-driven Machine learning Ensemble learning Ensemble diversity

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Unraveling post-growth mechanisms of monolayer CsPbBr3 nanocubes:Laser-enhanced transformations and cathodoluminescence-electron microscopy correlations

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Journal of Energy Chemistry 2025年第1期100卷 146-156页

作者： Mingxing Li Xiaoge Wang Xiaofan Cao Zhiqun He Chunjun liang Mingxing Chen Jing Ju Fangtian You Key Laboratory of Luminescence and Optical Information Ministry of Education Institute of Optoelectronic Technology Beijing Jiaotong University Beijing National Laboratory for Molecular Sciences (BNLMS) College of Chemistry and Molecular Engineering Peking University

Lead-halide perovskite nanoparticles（LHP NPs） are highly promising materials for next-generation displays and solid-state lighting due to their exceptional optical properties. However, their inherent instability presents a significant challenge. Recent advances have demonstrated that optoelectronic devices based on monolayer nanoparticle films exhibit both high luminescence efficiency and long-term *** research demonstrates that mobility limitations and anisotropic alignments in CsPbBr3nanocube monolayer films are key to their stabilization, hindering spontaneous growth through face-to-face fusion and resulting in the formation of connecting necks in a diagonal direction. Introducing laser irradiation confirmed this by significantly accelerating nanocubes growth, increasing mobility, and enhancing local structural ordering, leading to larger and more regularly shaped nanosheets. Fourier transform infrared spectroscopy and energy dispersive spectroscopy line-scan analyses indicated that laser irradiation did not disrupt the ligand structure. Transmission electron microscopy and correlative cathodoluminescence electron microscopy revealed the effects of post-growth and heterogeneous structures, including enhanced luminescence and inhomogeneous intensity in the nanosheets. These findings deepen the understanding of the post-growth mechanism of monolayer nanoparticles and the structure-emission correlation and highlight the unique role of laser irradiation in directing the formation of well-defined and regular nanostructures.

关键词： Post-growth mechanism Heterogeneous structure Single-particle spectroscopy Laser irradiation

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Potassium and calcium channels in different nerve cells act as therapeutic targets in neurological disorders

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Neural Regeneration Research 2025年第5期20卷 1258-1276页

作者： Qing Qiu Mengting Yang Danfeng Gong Haiying liang Tingting Chen Department of Pharmacology School of PharmacyNantong UniversityNantongJiangsu ProvinceChina Jiangsu Province Key Laboratory of Inflammation and Molecular Drug Target NantongJiangsu ProvinceChina Department of Pharmacy Longyan First Affiliated Hospital of Fujian Medical UniversityLongyanFujian ProvinceChina

The central nervous system, information integration center of the body, is mainly composed of neurons and glial cells. The neuron is one of the most basic and important structural and functional units of the central nervous system, with sensory stimulation and excitation conduction functions. Astrocytes and microglia belong to the glial cell family, which is the main source of cytokines and represents the main defense system of the central nervous system. Nerve cells undergo neurotransmission or gliotransmission, which regulates neuronal activity via the ion channels, receptors, or transporters expressed on nerve cell membranes. Ion channels, composed of large transmembrane proteins, play crucial roles in maintaining nerve cell homeostasis. These channels are also important for control of the membrane potential and in the secretion of neurotransmitters. A variety of cellular functions and life activities, including functional regulation of the central nervous system, the generation and conduction of nerve excitation, the occurrence of receptor potential, heart pulsation, smooth muscle peristalsis, skeletal muscle contraction, and hormone secretion, are closely related to ion channels associated with passive transmembrane transport. Two types of ion channels in the central nervous system, potassium channels and calcium channels, are closely related to various neurological disorders, including Alzheimer's disease, Parkinson's disease, and epilepsy. Accordingly, various drugs that can affect these ion channels have been explored deeply to provide new directions for the treatment of these neurological disorders. In this review, we focus on the functions of potassium and calcium ion channels in different nerve cells and their involvement in neurological disorders such as Parkinson's disease, Alzheimer's disease, depression, epilepsy, autism, and rare disorders. We also describe several clinical drugs that target potassium or calcium channels in nerve cells and could be u

关键词： astrocytes calcium channels central nervous system extracellular ion concentration microglia neurological disorders neurons potassium channels

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