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Nano-Micro Letters 2025年第4期17卷 130-165页

作者： Mengyao Chen Chengyu Guo Lubing Qin Lei Wang liang Qiao Kebin Chi Zhenghua Tang New Energy Research institute School of Environment and EnergySouth China University of TechnologyGuangzhou Higher Education Mega CentreGuangzhou 510006People’s Republic of China Petrochemical Research institute PetroChina Company LimitedBeijing 102206People’s Republic of China Key Laboratory of Functional inorganic Material Chemistry(Heilongjiang University) Ministry of EducationHarbin 150001People’s Republic of China

Atomically precise metal nanoclusters are an emerging type of nanomaterial which has diverse interfacial metal-ligand coordination motifs that can significantly affect their physicochemical properties and *** that,Cu nanoclusters have been gaining continuous increasing research attentions,thanks to the low cost,diversified structures,and superior catalytic performance for various *** this review,we first summarize the recent progress regarding the synthetic methods of atomically precise Cu nanoclusters and the coordination modes between Cu and several typical ligands and then discuss the catalytic applications of these Cu nanoclusters with some explicit examples to explain the atomical-level structure-performance ***,the current challenges and future research perspectives with some critical thoughts are *** hope this review can not only provide a whole picture of the current advances regarding the synthesis and catalytic applications of atomically precise Cu nanoclusters,but also points out some future research visions in this rapidly booming field.

关键词： Atomically precise Cu nanoclusters Controllable synthesis Catalytic applications Structure-performance relationship Challenges and perspectives

Development and validation of a nomogram prediction model for overall survival in patients with rectal cancer

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World Journal of Gastrointestinal Oncology 2025年第2期17卷 93-104页

作者： Ling liang Xiao-Sheng Li Ze-Jun Huang Zu-Hai Hu Qian-Jie Xu Yu-liang Yuan Wei Zhang Hai-Ke Lei Chongqing Key Laboratory of Translational Research for Cancer Metastasis and individualized Treatment Chongqing University Cancer HospitalChongqing 400030China Chongqing Cancer Multiomics Big Data Application Engineering Research Center Chongqing University Cancer HospitalChongqing 400030China Department of Health Statistics School of Public HealthChongqing Medical UniversityChongqing 400016China

BACKGROUND Rectal cancer is prevalent and associated with substantial morbidity and *** To develop a nomogram prediction model for overall survival(OS)in patients with rectal cancer by leveraging a comprehensive analysis of demographic,clinicopathological,haematological,and follow-up data to identify independent prognostic *** We conducted a prospective cohort study in China involving rectal cancer patients and applied Cox regression and least absolute shrinkage and selection operator regression to assess the significance of various variables as independent prognostic factors for *** identified factors were integrated into a nomogram model,which was evaluated for predictive accuracy via the C-index,area under the curve(AUC),calibration curve,and decision curve analysis(DCA).RESULTS Multivariate analysis revealed independent predictors of OS,including the Karnofsky performance status,age,sex,TNM stage,chemotherapy,surgery,targeted therapy,β2-microglobulin,lactate dehydrogenase,and the neutrophil-to-lymphocyte *** nomogram demonstrated a C-index of 0.80 for the training and validation cohorts,with AUC values indicating high predictive accuracy for 1-year,3-year,and 5-year *** calibration curves confirmed the model's excellent agreement with the observed survival rates,and DCA revealed the superior clinical utility of the nomogram over the TNM staging *** in this study,a novel prognostic model that accurately predicts the OS of rectal cancer patients was *** model exhibited excellent discriminatory and calibration capabilities,thus offering a reliable tool for health care professionals to estimate patient survival.

关键词： Rectal cancer Overall survival Nomogram Prognosis

DDoS Attack Autonomous Detection Model Based on Multi-Strategy integrate Zebra Optimization Algorithm

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Computers, Materials & Continua 2025年第1期82卷 645-674页

作者： Chunhui Li Xiaoying Wang Qingjie Zhang Jiaye liang Aijing Zhang School of information Engineering Institute of Disaster PreventionLangfang065201China Langfang Key Laboratory of Network Emergency Protection and Network Security Langfang065201China

Previous studies have shown that deep learning is very effective in detecting known ***,when facing unknown attacks,models such as Deep Neural Networks(DNN)combined with Long Short-Term Memory(LSTM),Convolutional Neural Networks(CNN)combined with LSTM,and so on are built by simple stacking,which has the problems of feature loss,low efficiency,and low ***,this paper proposes an autonomous detectionmodel for Distributed Denial of Service attacks,Multi-Scale Convolutional Neural Network-Bidirectional Gated Recurrent Units-Single Headed Attention(MSCNN-BiGRU-SHA),which is based on a Multistrategy integrated Zebra Optimization Algorithm(Mi-ZOA).The model undergoes training and testing with the CiCDDoS2019 dataset,and its performance is evaluated on a new GiNKS2023 *** hyperparameters for Conv_filter and GRU_unit are optimized using the Multi-strategy integrated Zebra Optimization Algorithm(MiZOA).The experimental results show that the test accuracy of the MSCNN-BiGRU-SHA model based on the MiZOA proposed in this paper is as high as 0.9971 in the CiCDDoS 2019 *** evaluation accuracy of the new dataset GiNKS2023 created in this paper is *** to the MSCNN-BiGRU-SHA model based on the Zebra Optimization Algorithm(ZOA),the detection accuracy on the GiNKS2023 dataset has improved by 5.81%,precisionhas increasedby 1.35%,the recallhas improvedby 9%,and theF1scorehas increasedby 5.55%.Compared to the MSCNN-BiGRU-SHA models developed using Grid Search,Random Search,and Bayesian Optimization,the MSCNN-BiGRU-SHA model optimized with the Mi-ZOA exhibits better performance in terms of accuracy,precision,recall,and F1 score.

关键词： Distributed denial of service attack intrusion detection deep learning zebra optimization algorithm multi-strategy integrated zebra optimization algorithm

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 UniversityXi’an 710049ShaanxiChina Shaanxi Key Laboratory of intelligent Robots School of Mechanical EngineeringXi’an Jiaotong UniversityXi’an 710049ShaanxiChina Department of Electrical Engineering and Automation Luoyang Institute of Science and TechnologyLuoyang 471023HenanChina School of Mechanical Engineering Hangzhou Dianzi UniversityHangzhou 310018ZhejiangChina

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

New perspectives on DNA methylation modifications in ocular diseases

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international Journal of Ophthalmology(English edition) 2025年第2期18卷 340-350页

作者： Fei-Fei Zong Da-Dong Jia Guang-Kun Huang Meng Pan Hao Hu Shi-Yi Song liang Xiao Ru-Weng Wang liang liang The First College of Clinical Medical Science China Three Gorges UniversityDepartment of PathologyYichang Central People’s HospitalYichang 443003Hubei ProvinceChina The Second People’s Hospital of China Three Gorges University the Second People’s Hospital of YichangYichang 443000Hubei ProvinceChina Department of Ophthalmology the First Affiliated Hospital of Kunming Medical UniversityKunming 650032Yunnan ProvinceChina Shaanxi University of Chinese Medicine Basic Medical CollegeXianyang 712046Shaanxi ProvinceChina

The methylation of DNA is a prevalent epigenetic modification that plays a crucial role in the pathological progression of ocular *** methylation can regulate gene expression,thereby affecting cell function and signal *** diseases are a kind of complex diseases,and their pathogenesis involves many factors such as genetic,environmental and individual *** addition,inflammation,oxidative stress and lipid metabolism,which abnormal DNA methylation is closely related to,are also considered to be major factors in eye *** current understanding of DNA methylation in eye diseases is becoming more complex and *** addition to the simple suppression of gene expression by hypermethylation,factors such as hypomethylation or demethylation,DNA methylation in non-promoter regions,interactions with other epigenetic modifications,and dynamic changes in DNA methylation must also be ***,although some genes are at abnormal methylation levels,their expression is not significantly changed,which indirectly reflects the complexity of gene *** review aims to summarize and compare some relevant studies,and provide with new ideas and methods for the prevention and treatment of different eye diseases,such as glaucoma,retinoblastoma,and diabetic retinopathy.

关键词： DNA methylation modification epigenetic glaucoma retinoblastoma diabetic retinopathy methylase inhibitors

Ultrahigh Energy and Power Density in Ni-Zn Aqueous Battery via Superoxide-Activated Three-Electron Transfer

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Nano-Micro Letters 2025年第4期17卷 63-76页

作者： Yixue Duan Bolong Li Kai Yang Zheng Gong Xuqiao Peng liang He Derek Ho School of Mechanical Engineering State Key Laboratory of Intelligent Construction and Healthy Operation and Maintenance of Deep Underground EngineeringSichuan UniversityChengdu 610065People’s Republic of China Department of Materials Science and Engineering City University of Hong KongKowloonHong Kong 999077People’s Republic of China Hong Kong Centre for Cerebro-Cardiovascular Health Engineering Hong Kong Science ParkHong Kong 999077People’s Republic of China School of Mechanical Engineering Sichuan UniversityChengdu 610065People’s Republic of China

Aqueous Ni-Zn microbatteries are safe,reliable and inexpensive but notoriously suffer from inadequate energy and power ***,we present a novel mechanism of superoxide-activated Ni substrate that realizes the redox reaction featuring three-electron transfers(Ni↔Ni3+).The superoxide activates the direct redox reaction between Ni substrate and KNiO_(2)by lowering the reaction Gibbs free energy,supported by in-situ Raman and density functional theory *** prepared chronopotentiostatic superoxidation-activated Ni(CPS-Ni)electrodes exhibit an ultrahigh capacity of 3.21 mAh cm^(-2)at the current density of 5 mA cm^(-2),nearly 8 times that of traditional one-electron processes *** under the ultrahigh 200 mA cm^(-2)current density,the CPS-Ni electrodes show 86.4%capacity retention with a Columbic efficiency of 99.2%after 10,000 *** CPS-Ni||Zn microbattery achieves an exceptional energy density of 6.88 mWh cm^(-2)and power density of 339.56 mW cm^(-2).Device demonstration shows that the power source can continuously operate for more than 7 days in powering the sensing and computation intensive practical application of photoplethysmographic waveform *** work paves the way to the development of multi-electron transfer mechanisms for advanced aqueous Ni-Zn batteries with high capacity and long lifetime.

关键词： Superoxide Multiple electron transfer Ni aqueous battery AioT power source Wearable health monitoring

interpretable Machine Learning-Based Spring Algal Bloom Forecast Model for the Coastal Waters of Zhejiang

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Journal of Ocean University of China 2025年第1期24卷 1-12页

作者： HUANG Guoqiang BAO Min ZHANG Zhao GU Dongming liang Liansong TAO Bangyi State Key Laboratory of Satellite Ocean Environment Dynamics Second Institute of OceanographyMinistry of Natural ResourceHangzhou 310012China Wenzhou Marine Center Ministry of Natural ResourcesWenzhou 325000China Observation and Research Station of Yangtze River Delta Marine Ecosystems Ministry of Natural ResourcesZhoushan 316000China Key Laboratory of Marine Ecological Monitoring and Restoration Technologies Ministry of Natural ResourceShanghai 201206China

The 2016–2022 monitoring data from three ecological buoys in the Wenzhou coastal region of Zhejiang Province and the dataset European Centre for Medium-Range Weather Forecasts were examined to clarify the elaborate relationship between variations in ecological parameters during spring algal bloom incidents and the associated changes in temperature and wind fields in this study.A long short-term memory recurrent neural network was employed,and a predictive model for spring algal bloom in this region was *** model integrated various inputs,including temperature,wind speed,and other pertinent variables,and chlorophyll concentration served as the primary output *** model training used chlorophyll concentration data,which were supplemented by reanalysis and forecast temperature and wind field *** model demonstrated proficiency in forecasting next-day chlorophyll concentrations and assessing the likelihood of spring algal bloom occurrences using a defined chlorophyll concentration *** historical validation from 2016 to 2019 corroborated the model's accuracy with an 81.71%probability of correct prediction,which was further proven by its precise prediction of two spring algal bloom incidents in late April 2023 and early May *** interpretable machine learning-based model for spring algal bloom prediction,displaying effective forecasting with limited data,was established through the detailed analysis of the spring algal bloom mechanism and the careful selection of input *** insights gained from this study offer valuable contributions to the development of early warning systems for spring algal bloom in the Wenzhou coastal area of Zhejiang Province.

关键词： spring algal bloom forecast LSTM interpretable

Vector meson’s spin alignments in high energy reactions

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Science China(Physics,Mechanics & Astronomy) 2025年第1期68卷 1-16页

作者： Jin-Hui Chen Zuo-Tang liang Yu-Gang Ma Xin-Li Sheng Qun Wang Key Laboratory of Nuclear Physics and ion-beam Application(MoE) Institute of Modern PhysicsFudan UniversityShanghai 200433China institute of Frontier and interdisciplinary Science Key Laboratory of Particle Physics and Particle Irradiation(MOE)Shandong UniversityQingdao 266237China iNFN-Firenze Sesto Fiorentino FI 50019Italy Department of Modern Physics University of Science and Technology of ChinaHefei 230026China School of Mechanics and Physics Anhui University of Science and TechnologyHuainan 232001China

The global spin alignment of vector mesons has been observed by the STAR collaboration at the Relativistic Heavy ion Collider(RHiC)at Brookhaven National Laboratory(BNL).it provides a unique opportunity to probe the correlation between the po-larized quark and antiquark in the strongly coupled quark-gluon plasma(sQGP)produced in relativistic heavy ion collisions,opening a new window to explore the properties of *** addition,spin alignments of vector mesons have also been observed in other high-energy particle collisions such as e^(+)e^(−)annihilations at high energies where hadron production is dominated by quark fragmentation *** results obtained are quite different from those obtained in heavy ion collisions where quark coalescence/combination mechanism dominates suggesting strong dependence on hadronization *** comprehensive studies in different hadronization processes are *** this article,we present a brief review of theoretical and experimen-tal advances in the study of vector meson’s spin alignments in a variety of high-energy particle collisions,with emphasis on hadronization mechanisms.

关键词： vector meson spin alignment global polarization relativistic heavy ion collisions fragmentation

BEV-Locator:an end-to-end visual semantic localization network using multi-view images

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Science China(information Sciences) 2025年第2期68卷 134-150页

作者： Zhihuang ZHANG Meng XU Wenqiang ZHOU Tao PENG liang Li Stefan POSLAD School of Vehicle and Mobility Tsinghua University School of information Technology & Management University of International Business and Economics Qcraft inc. School of Electronic Engineering and Computer Science Queen Mary University of London

Accurate localization ability is fundamental in autonomous driving. Traditional visual localization frameworks approach the semantic map-matching problem with geometric models, which rely on complex parameter tuning and thus hinder large-scale deployment. in this paper, we propose BEV-Locator: an end-to-end visual semantic localization neural network using multi-view camera images. Specifically, a visual BEV(bird-eye-view) encoder extracts and flattens the multi-view images into BEV space. While the semantic map features are structurally embedded as map query sequences. Then a cross-model transformer associates the BEV features and semantic map queries. The localization information of ego-car is recursively queried out by cross-attention modules. Finally, the ego pose can be inferred by decoding the transformer outputs. This end-to-end model speaks to its broad applicability across different driving environments, including high-speed scenarios. We evaluate the proposed method in large-scale nuScenes and Qcraft datasets. The experimental results show that the BEV-Locator is capable of estimating the vehicle poses under versatile scenarios, which effectively associates the cross-model information from multi-view images and global semantic maps. The experiments report satisfactory accuracy with mean absolute errors of 0.052 m, 0.135 m and 0.251° in lateral, longitudinal translation and heading angle degree.

关键词： visual localization semantic map bird-eye-view transformer pose estimation

insight into catalytic performance and reaction mechanism for toluene total oxidation over Cu-Ce supported catalyst

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Journal of Environmental Sciences 2025年第3期149卷 476-487页

作者： Xuan liang Jin Zhang Juntai Tian Zenghua Xie Yue Liu Peng Liu Daiqi Ye School of Environment and Energy South China University of TechnologyGuangzhou 510006China National Engineering Laboratory for VOCs Pollution Control Technology and Equipment Guangzhou 510006China Guangdong Provincial Key Laboratory of Atmospheric Environment and Pollution Control South China University of TechnologyGuangzhou 510006China Guangdong Provincial Engineering and Technology Research Centre for Environmental Risk Prevention and Emergency Disposal South China University of TechnologyGuangzhou 510006China

Herein,three supported catalysts,CuO/Al_(2)O_(3),CeO_(2)/Al_(2)O_(3),and CuO-CeO_(2)/Al_(2)O_(3),were synthesized by the convenient impregnation method to reveal the effect of CeO_(2)addition on catalytic performance and reaction mechanism for toluene *** with CuO/Al_(2)O_(3),the T_(50)and T_(90)(the temperatures at 50%and 90%toluene conversion,respectively)of CuO-CeO_(2)/Al_(2)O_(3)were reduced by 33 and 39°C,respectively.N_(2)adsorptiondesorption experiment,XRD,SEM,EDS mapping,Raman,EPR,H_(2)-TPR,O_(2)-TPD,XPS,NH_(3)-TPD,Toluene-TPD,and in-situ DRiFTS were conducted to characterize these *** excellent catalytic performance of CuO-CeO_(2)/Al_(2)O_(3)could be attributed to its strong coppercerium interaction and high oxygen vacancies ***,in-situ DRiFTS proved that CuO-CeO_(2)/Al_(2)O_(3)promoted the conversion of toluene to benzoate and accelerated the deep degradation path of *** work provided valuable insights into the development of efficient and economical catalysts for volatile organic compounds.

关键词： Cu-Ce supported catalyst Copper-cerium interaction Oxygen vacancies Toluene oxidation Reaction mechanism