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

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

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knowledge Enhanced Coreference Resolution via Gated Attention

Knowledge Enhanced Coreference Resolution via Gated Attentio...

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2022 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2022

作者： He, Kai Mao, Bing Zhou, Xiangyu Li, Yufei Gong, Tieliang Li, Chen Wu, Jialun Xi'an Jiaotong University School of Computer Science and Technology Xi'an China Xi'an Jiaotong University Shaanxi Provincial Key Laboratory of Big Data Knowledge Engineering Xi'an China

ISBN: (纸本)9781665468190

Coreference resolution aims at linking all mentions that refer to the same entity, which are widely adopted in many biomedical and bioinformatics tasks, such as biomedical knowledge graph construction and metabolic pathway integration. Many recent studies focus on improving neural model structures. However, we argue that a practical method that integrates commonsense knowledge can further improve coreference resolution performance, because commonsense delivers extra prior knowledge for reasoning and can enhance related representations, rather than naive mention-context occurrence modeling. In this work, we propose an effective method to integrate external commonsense knowledge into a neural coreference resolution model. Specially, a gated attention mechanism is employed in our method to leverage commonsense according to different contexts. By using ConceptNet as the knowledge base in three span-ranking backbone models, the models can yield significant performance gains on used datasets. We also achieve improvements in tasks of long-term mention detection and cross-sentence coreferences after incorporating knowledge. © 2022 IEEE.

关键词： Model structures

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Glacial Lake Area Changes in High Mountain Asia during 1990-2020 Using Satellite Remote Sensing

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Research 2023年第2期2022卷 1-23页

作者： Meimei Zhang Fang Chen Huadong Guo Lu Yi Jiangyuan Zeng Bin Li International Research Center of Big Data for Sustainable Development Goals Beijing 100094China Key Laboratory of Digital Earth Science Aerospace Information Research InstituteChinese Academy of SciencesNo.9 Dengzhuang South RoadBeijing 100094China University of Chinese Academy of Sciences Beijing 100049China Key Laboratory of Coastal Environment and Resources Research of Zhejiang Province School of EngineeringWestlake UniversityHangzhou 310024China State Key Laboratory of Remote Sensing Science Aerospace Information Research InstituteChinese Academy of Sciences Beijing 100094China

Changes in a large-scale glacial lake area directly reflect the regional glacier status and climate ***,long time series of glacial lake dataset and comprehensive investigation of the spatiotemporal changes in the gla... 详细信息

关键词： glacial glacier lake

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Spatiotemporal Pattern Evolution for Vegetation Using Remote Sensing Technology: A case study of Zhoushan Island, china

Spatiotemporal Pattern Evolution for Vegetation Using Remote...

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2024 International Conference on Remote Sensing, Mapping, and Image Processing, RSMIP 2024

作者： Chen, Yankun Chen, Chao Liu, Zhisong School of Information Engineering Zhejiang Ocean University Zhoushan316022 China School of Geography Science and Geomatics Engineering Suzhou University of Science and Technology Suzhou215009 China Key Laboratory of Oceanographic Big Data Mining and Application of Zhejiang Province Zhoushan316022 China

ISBN: (纸本)9781510680012

For ecological environment protection research and regional sustainable development, vegetation, as a crucial land cover type, necessitates long-term, large-scale, and highly accurate monitoring. This paper formulates an enduring vegetation monitoring approach using Landsat satellite remote sensing imagery on the Google Earth Engine (GEE) cloud platform. By computing the Normalized Difference Vegetation Index (NDVI), we formulate a method for prolonged remote sensing monitoring of vegetation, unveiling its temporal and spatial pattern evolution. Firstly, based on Landsat remote satellite imagery and GEE, we calculated the NDVI. By leveraging the Normalized Difference Water Index (NDWI), we removed inland water bodies and outliers within the study area, enabling the precise generation of spatiotemporal NDVI distribution maps. Subsequently, the NDVI was analyzed for time trends in conjunction with grade transfer matrices. Finally, combined with Moran's I, high/low clusters, clustering and outlier, cold/hot spots, etc., the NDVI spatial pattern characteristics were analyzed. Using the Zhoushan Island in china as an example, the results indicated that: (1) The most significant changes were observed in the low NDVI area (0-0.2), which expanded from 28.84 km2 to 67.29 km2. (2) Concentrated mainly in the inland areas are the NDVI High-High clusters and the significant hot spots, while the coastal areas primarily feature NDVI Low-Low clusters and significant cold spots. © 2024 SPIE.

关键词： Vegetation

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Longitudinal Control for Balloon-Borne Launched Solar Powered UAVs in Near-Space

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Journal of Systems Science & Complexity 2022年第3期35卷 802-819页

作者： HU Yanpeng GUO Jin MENG Wenyue LIU Guanyu XUE Wenchao School of Automation and Electrical Engineering University of Science and Technology BeijingBeijing 100083China Key Laboratory of Knowledge Automation for Industrial Processes Ministry of EducationBeijing 100083China Institute of Engineering Thermophysics Chinese Academy of SciencesBeijing 100190China Academy of Mathematics and Systems Science Chinese Academy of SciencesBeijing 100190China

Aiming to improve the pull-up control performance in the process of releasing balloonborne solar powered UAVs(Unmanned Aerial Vehicles),this paper establishes the full flight mechanics equations with flexible modes,and proposes the control method suitable for engineering *** be specific,the authors first calculate the real aerodynamic force on horizontal stabilizer by comparing the fuselage deformation in ballooning test with that in static loading ***,considering fuselage elastic deformation,the pitching moment coefficient is obtained and the influence of airspeed and elevator angle on pitching moment coefficient and control surface efficiency are ***,the authors establish a complete flight mechanics model,including elastic structural dynamic model and rigid flight dynamic model,by comprehensively considering the aerodynamic data,the relationship between fuselage deformation and load,as well as the ballooning ***,the authors perform the numerical simulation and comparison study on control performance between rigid model and flexible ***,the authors implement model modification based on the low altitude flight test and steady-state point ***,a scaled UAV is used to complete the balloon-borne launching *** results show that the longitudinal control method can analyse the longitudinal aerodynamics and control characteristics accurately,and could be effectively utilized in the pull-up control of the balloon-borne solar powered UAV.

关键词： Aeroelastic model balloon-borne flight test flight dynamic model longitudinal control numerical simulation solar powered UAV

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RailPC: A large-scale railway point cloud semantic segmentation dataset

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CAAI Transactions on Intelligence Technology 2024年第6期9卷 1548-1560页

作者： Tengping Jiang Shiwei Li Qinyu Zhang Guangshuai Wang Zequn Zhang Fankun Zeng Peng An Xin Jin Shan Liu Yongjun Wang Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application Nanjing Normal UniversityNanjingChina Technology Innovation Center for Integrated Applications in Remote Sensing and Navigation Ministry of Natural ResourcesNanjingChina Eastern Institute of Technology(EIT) NingboChina Tianjin Key Laboratory of Rail Transit Navigation Positioning and Spatio-temporal Big Data Technology TianjinChina College of Computer Science and Engineering Northwest Normal UniversityLanzhouChina Mckelvey School of Engineering Washington University in St.LouisSt.LouisMissouriUSA School of Electronic and Information Engineering Ningbo University of TechnologyNingboChina

Semantic segmentation in the context of 3D point clouds for the railway environment holds a significant economic value,but its development is severely hindered by the lack of suitable and specific ***,the models trained on existing urban road point cloud datasets demonstrate poor generalisation on railway data due to a large domain gap caused by non-overlapping special/rare categories,for example,rail track,track bed *** harness the potential of supervised learning methods in the domain of 3D railway semantic segmentation,we introduce RailPC,a new point cloud *** provides a large-scale dataset with rich annotations for semantic segmentation in the railway ***,RailPC contains twice the number of annotated points compared to the largest available mobile laser scanning(MLS)point cloud dataset and is the first railway-specific 3D dataset for semantic *** covers a total of nearly 25 km railway in two different scenes(urban and mountain),with 3 billion points that are finely labelled as 16 most typical classes with respect to railway,and the data acquisition process is completed in china by MLS *** extensive experimentation,we evaluate the performance of advanced scene understanding methods on the annotated dataset and present a synthetic analysis of semantic segmentation *** on our findings,we establish some critical challenges towards railway-scale point cloud semantic *** dataset is available at https://***/NNU-GISA/GISA-RailPC,and we will continuously update it based on community feedback.

关键词： data benchmark MLS point clouds railway scene semantic segmentation

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An effective scheme for top-k frequent itemset mining under differential privacy conditions

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Science china(Information Sciences) 2020年第5期63卷 200-202页

作者： Wenjuan LIANG Hong CHEN Jing ZHANG Dan ZHAO Cuiping LI Key Lab of Data Engineering and Knowledge Engineering of MOE Renmin University of China College of Computer and Information Engineering Henan University

Dear editor,Frequent itemset mining (FIM) is important in many data mining applications [1], such as web log mining and trend analysis. However, if the data are sensitive (e.g., web browsing history), directly releasing frequent itemsets and their support may breach user privacy. The protection of user privacy while obtaining statistical information is im-

关键词： An effective scheme for top-k frequent itemset mining under differential privacy conditions

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A preliminary study on the volcanic intrusive complex type beryllium metallogenic belt from the southeast coast of china

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Science china Earth Sciences 2022年第8期65卷 1586-1600页

作者： Can RAO Rucheng WANG Fuyuan WU Xudong CHE Xiaofeng LI Qi WANG Zhiqi ZHANG Runqiu WU Key Laboratory of Geoscience Big Data and Deep Resource of Zhejiang Province School of Earth SciencesZhejiang UniversityHangzhou310027China State Key Laboratory for Mineral Deposits Research School of Earth Sciences and EngineeringNanjing UniversityNanjing210023China State Key Laboratory of Lithosphere Evolution Institute of Geology and GeophysicsChinese Academy of SciencesBeijing100029China

Beryllium(Be)is one of the unsubstitutable key metals in strategic emerging industries and national defense industries,mainly originating from volcanogenic Be ***,volcanogenic Be deposits have become important research objects of key metal deposits,with a focus on their occurrence,metallogenic mechanism,and resource *** the southeast coast of china,the Late Mesozoic volcanic intrusive complex has a good Be metallogenic background,and strong Be mineralization occurs in some *** geological investigation and analyses of samples from Southeast Zhejiang as well as Northeast and Southeast Fujian indicate that Be mineralization in the southeast coast of china is closely related to the hydrothermal processes in the volcanic intrusive *** Southeast Zhejiang,Be ore in the Qingtian area mainly occurs in granite porphyry,with the Be content reaching 939 ppm,while strong Be mineralization from Zhangji rhyolite porphyry in the Pingyang area contains up to 11400 ppm *** Xiapu County,Northeastern Fujian,the Dawan Be deposit is characterized by constituents of helvite and *** Pinghe County,Southeastern Fujian,the Fulishi Be ore is a quartz vein beryl-type *** results suggest that the volcanic intrusive complex area in the southeast coast of china has a wide range of Be mineralization and better Be metallogenic potential,and it is expected to become an important Be metallogenic belt in ***,we should thoroughly investigate the Be resources of granite porphyry,rhyolite porphyry,quartz porphyry,and quartz vein in this volcanic rock area,which can provide a theoretical basis for the exploration and guiding prospecting of volcanic intrusive complex Be deposits.

关键词： Volcanogenic Be deposit Beryllium resources Be-bearing minerals Beryllium metallogenic belt Southeast coast of china

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High Mixing Entropy Enhanced Energy States in Metallic Glasses

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Chinese Physics Letters 2022年第4期39卷 36-40页

作者： Juntao Huo Kangyuan Li Bowen Zang Meng Gao Li-Min Wang Baoan Sun Maozhi Li Lijian Song Jun-Qiang Wang Wei-Hua Wang CAS Key Laboratory of Magnetic Materials and Devices and Zhejiang Province Key Laboratory of Magnetic Materials and Application TechnologyNingbo Institute of Materials Technology&EngineeringChinese Academy of SciencesNingbo 315201China Department of Physics Renmin University of ChinaBeijing 100872China State Key Lab of Metastable Materials Science and Technology and College of Materials Science and EngineeringYanshan UniversityQinhuangdao 066004China Institute of Physics Chinese Academy of SciencesBeijing 100190China

Owing to the nonequilibrium nature,the energy state of metallic glasses(MGs)can vary a lot and has a critical influence on the physical *** new methods to modulate the energy state of glasses and studying its relationship with properties have attracted great ***,we systematically investigate the energy state,mixing entropy and physical properties of Zr–Ti–Cu–Ni–Be multicomponent high entropy MGs by experiments and *** find that the energy state increases along with the increase of mixing *** yield strength and thermal stability of MGs are also enhanced by high mixing *** results may open a new door on regulation of energy states and thus physical properties of MGs.

关键词： properties glasses mixing

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An Encoder-Based Framework for Privacy-Preserving Machine Learning 24th

An Encoder-Based Framework for Privacy-Preserving Machine L...

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24th International Conference on Algorithms and Architectures for Parallel Processing, ICA3PP 2024

作者： Wu, Jiayun Ren, Wei Zhang, Xianchao Zheng, Xianghan School of Computer Science China University of Geosciences Wuhan430074 China State Key Laboratory of Geo-Information Engineering and Key Laboratory of Surveying and Mapping Science and Geospatial Information Technology of MNR CASM Beijing China Ministry of Education Chengdu China Key Laboratory of Medical Electronics and Digital Health of Zhejiang Province Jiaxing University Jiaxing China Engineering Research Center of Intelligent Human Health Situation Awareness of Zhejiang Province Jiaxing University Jiaxing China College of Computer and Big Data Fuzhou University Fujian Fuzhou China School of Information and Intelligent Engineering Sanya College Hainan China

ISBN: (纸本)9789819615506

As a data-driven science, machine learning requires vast amounts of training data and computational resources. However, for highly privacy-sensitive data, it is crucial to protect the privacy of the data during both the training and utilization of machine learning models. In this paper, we propose a privacy-preserving machine learning approach using autoencoders and differential privacy mechanisms to safeguard data privacy while minimizing the impact on data availability. Specifically, we augment logistic regression and ResNet18 models with different architectures of autoencoders to perform data encryption? without compromising the machine learning tasks. Additionally, we employ differential privacy mechanisms to introduce gradient perturbations in the encoding part of the autoencoder, enhancing the algorithm’s security and further protecting data privacy. We also design the cosine similarity between the encoded and original data as a metric for evaluating data privacy, considering model performance, privacy budget, and data privacy collectively to balance data availability and privacy. Extensive experiments conducted on MNIST, CIFAR-10, PathMNIST, and BloodMNIST datasets demonstrate that for simple logistic regression models handling easily classifiable datasets, employing simple autoencoder structures can enhance classification accuracy, with significant performance impact after adding differential privacy. For ResNet18, utilizing convolutional autoencoders for data encryption generally has minimal impact on model classification performance and can even improve accuracy in most cases. Adding differential privacy has minor effects on model classification performance. Selecting appropriate model structures and privacy budgets for different usage scenarios can ensure both data availability and privacy. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Adversarial machine learning

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