检索结果-内蒙古大学图书馆

SSRN 2022年

作者： Chang, Qingqing He, Honglin Ren, Xiaoli Zhang, Li Feng, Lili Lv, Yan Zhang, Mengyu Xu, Qian Liu, Weihua Zhang, Yonghong Wang, Tianxiang Key Laboratory of Ecosystem Network Observation and Modeling Institute of Geographic Sciences and Natural Resources Research Chinese Academy of Sciences Beijing100101 China National Ecological Science Data Center Beijing100101 China University of Chinese Academy of Sciences Beijing100049 China College of Resources and Environment University of Chinese Academy of Sciences Beijing100049 China State Key Laboratory of Grassland Agro-ecosystems School of Ecology Lanzhou University Gansu Lanzhou730000 China

Increasingly drastic global change is expected to cause hydroclimatic changes, which will influence vegetation productivity and pose a threat to the terrestrial carbon sink. Asymmetry represents an imbalance between vegetation growth and loss of growth during dry and wet periods, respectively. However, the mechanisms of asymmetric plant responses to hydrological changes remain poorly understood. Here, we examined the spatiotemporal patterns of asymmetric responses of vegetation productivity across terrestrial ecosystems in China. We analyzed several observational and satellite-based datasets of plant productivity and several reanalyzed datasets of hydroclimatic variables from 2001 to 2020, and used a random forest model to assess the importance of hydroclimatic variables for these responses. Our results showed that the productivity of >50% of China’s vegetated areas showed a more positive asymmetry (2.3 ± 9.4%) over the study period, which were distributed broadly in northwest China (mainly grasslands and sparse vegetation ecosystems). Negative asymmetries were most common in forest ecosystems in northeast China. We demonstrated that one-third of vegetated areas tended to exhibit significant changes in asymmetry during 2001–2020. The trend towards stronger positive asymmetry (0.95% yr-1) was higher than that towards stronger negative asymmetry (-0.55% yr-1), which is beneficial for the carbon sink. We further showed that in China, soil moisture was a more important driver of spatiotemporal changes on asymmetric productivity than precipitation. We identified thresholds of surface soil moisture (20–30%) and root-zone soil moisture (200–350 mm) that were associated with changes in asymmetry. Our findings highlight the necessity of considering the dynamic responses of vegetation to hydrological factors in order to fully understand the physiological growth processes of plants and avoid the possible loss of productivity due to future climate change. © 2022, The Authors. A

关键词： Productivity

来源：评论

学校读者我要写书评

暂无评论

The Most Probable Transition Paths of Stochastic Dynamical Systems: A Sufficient and Necessary Characterization

arXiv

引用

arXiv 2021年

作者： Huang, Yuanfei Huang, Qiao Duan, Jinqiao School of Mathematics and Statistics Center for Mathematical Sciences Hubei Key Laboratory of Engineering Modeling and Scientific Computing Huazhong University of Science and Technology Wuhan430074 China Department of Statistics and Data Science National University of Singapore 6 Science Drive 2 Singapore117546 Singapore School of Data Science City University of Hong Kong Kowloon Hong Kong Department of Mathematics Faculty of Sciences University of Lisbon Campo Grande Edifício C6 LisboaPT-1749-016 Portugal Division of Mathematical Sciences School of Physical and Mathematical Sciences Nanyang Technological University 21 Nanyang Link Singapore637371 Singapore The Dongguan Key Laboratory for Data Science and Intelligent Medicine Department of Mathematics Department of Physics Great Bay University Guangdong Dongguan523000 China

The most probable transition paths of a stochastic dynamical system are the global minimizers of the Onsager–Machlup action functional and can be described by a necessary but not sufficient condition, the Euler–Lagrange equation (a second-order differential equation with initial-terminal conditions) from a variational principle. This work is devoted to showing a sufficient and necessary characterization for the most probable transition paths of stochastic dynamical systems with Brownian noise. We prove that, under appropriate conditions, the most probable transition paths are completely determined by a first-order ordinary differential equation. The equivalence is established by showing that the Onsager–Machlup action functional of the original system can be derived from the corresponding Markovian bridge process. For linear stochastic systems and the nonlinear Hongler’s model, the first-order differential equations determining the most probable transition paths are shown analytically to imply the Euler–Lagrange equations of the Onsager–Machlup functional. For general nonlinear systems, the determining first-order differential equations can be approximated, in a short time or for the small noise case. Some numerical experiments are presented to illustrate our results. Copyright © 2021, The Authors. All rights reserved.

关键词： Dynamical systems

来源：评论

学校读者我要写书评

暂无评论

Ecology in the digital world of Wikipedia

arXiv

引用

arXiv 2021年

作者： Ogushi, Fumiko Kertész, János Kaski, Kimmo Shimada, Takashi Center for Mathematical Modeling and Data Science Osaka University Toyonaka Osaka560-8531 Japan Department of Network and Data Science Central European University Quellenstrasse 51 Vienna1100 Austria Department of Computer Science Aalto University School of Science P. O. Box 15500 Espoo Finland Alan Turing Institute British Library 96 Euston Road LondonNW1 2DB United States Mathematics and Infomatics Center University of Tokyo 7-3-1 Hongo Bunkyo-ku Tokyo113-8656 Japan Department of Systems Innovation Graduate School of Engineering University of Tokyo

Wikipedia, a paradigmatic example of online knowledge space is organized in a collaborative, bottom-up way with voluntary contributions, yet it maintains a level of reliability comparable to that of traditional encyclopedias. The lack of selected professional writers and editors makes the judgement about quality and trustworthiness of the articles a real challenge. Here we show that a self-consistent metrics for the network defined by the edit records captures well the character of editors’ activity and the articles’ level of complexity. Using our metrics, one can better identify the human-labeled high-quality articles, e.g., "featured" ones, and differentiate them from the popular and controversial articles. Furthermore, the dynamics of the editor-article system is also well captured by the metrics, revealing the evolutionary pathways of articles and diverse roles of editors. We demonstrate that the collective effort of the editors indeed drives to the direction of article improvement. © 2021, CC BY.

关键词：

来源：评论

学校读者我要写书评

暂无评论

A Machine Learning Approach for Deriving Atmospheric Temperatures and Typhoon Warm Cores From FY-3E MWTS-3 Observations

Journal of Geophysical Research: Machine Learning and Comput...

引用

Journal of Geophysical Research: Machine Learning and Computation 2024年第3期1卷

作者： Zeyi Niu Xiaolei Zou Shanghai Typhoon Institute and Key Laboratory of Numerical Modeling for Tropical Cyclone of the China Meteorological Administration Shanghai China Department of Atmospheric and Oceanic Sciences and Institute of Atmospheric Sciences Fudan University Shanghai China Joint Center of Data Assimilation for Research and Application Nanjing University of Information and Science & Technology Nanjing China

Machine learning has gained an increasing popularity in the fields of satellite retrieval and numerical weather modeling. In this study, machine-learning (ML) neural-network (NN) models are utilized to retrieve atmospheric temperatures from observations of brightness temperature from the Microwave Temperature Sounder-3 (MWTS-3) onboard the China's first dawn-dusk polar-orbiting satellite Fengyun (FY)-3E, with the ERA5 reanalysis serving as training data sets. The root mean square errors of the ML-retrieved temperatures at all pressure levels are smaller than those obtained by a previously used traditional linear regression method compared to the ERA5 reanalysis over global oceans as well as radiosonde observations over land. Less than a 1-week period of training data is usually sufficient for an ML NN model to converge in less than 50–100 iterations. The shortest time period of training data is 3-days right before the testing data period. While the horizontal patterns and temporal evolutions of the ML-retrieved warm cores of Typhoon Malakas (2022) and Typhoon Haikui (2023) in the upper troposphere compared favorably with those obtained by traditional regression methods as well as the ERA5 reanalysis in the testing periods. The vertical structures of ML-retrieved warm cores extend further down to the middle and lower troposphere while those from the traditional regression method are confined in the upper troposphere. A comparison among ML results with additional training data sets across different seasons confirms the above conclusion. Neural networks retrieve atmospheric temperatures from FY-3E's MWTS-3, outperforming traditional methods For Typhoon Malakas, machine learning reveals detailed warm core structures, especially in middle- and lower-levels troposphere This study indicates that the outputs of NN models combine the characteristics of input MWTS-3 observations and the ERA5 reanalysis This study applies a machine learning neural network method to retrieve at

关键词： FY-3E MWTS-3 typhoon warm core machine learning

来源：评论

学校读者我要写书评

暂无评论

A model for the transportation and distribution of jellyfish Rhopilema esculentum for stock enhancement in the Liaodong Bay, China

引用

Acta Oceanologica Sinica 2019年第1期38卷 90-101页

作者： Liping Yin Xiujuan Shan Chang Zhao Xianshi Jin Guansuo Wang Fangli Qiao First Institute of Oceanography Ministry of Natural Resources Laboratory for Regional Oceanography and Numerical Modeling Pilot National Laboratory for Marine Science and Technology (Qingdao) Key Laboratory of Marine Science and Numerical Modelling Ministry of Natural Resources Yellow Sea Fisheries Research Institute Chinese Academy of Fishery Sciences Laboratory for Marine Fisheries Science and Food Production Processes Pilot Qingdao National Laboratory for Marine Science and Technology (Qingdao) Key Laboratory of Data Analysis and Applications Ministry of Natural Resources

A numerical model for jellyfish Rhopilema esculentum stock enhancement is developed for the first time. The model is based on an operational ocean circulation-surface wave coupled forecasting system for the seas off China and adjacent areas and uses a Lagrangian particle-tracking scheme to track the trajectories of released jellyfish. The Jellyfish are modeled as particles with diel vertical migration and are passively drifted by the current and dispersion due to the sub-grid processes. A comparison between the simulation and survey results demonstrate that the model can capture the primary distribution patterns of the released jellyfish. The model results show that the ocean current and indirect wind impact are the main drivers controlling the jellyfish transport. A connectivity matrix between the release sites and fishing grounds indicates the top of the bay is better than the eastern and western coasts for jellyfish fishing. The matrix also shows that only 45% and 27% of the jellyfish released from Wafangdian(WFD) can enter the fishing ground in 2008 and 2010; thus, the site near WFD is not an advisable location for jellyfish release. A Lagrangian probability density function based on a nine-year tracing experiment validates the results and further provides a "climatology" distribution of the released *** experiments are conducted to examine the sensitivity of the model to random walk schemes and to release conditions. The model requires a random walk but is insensitive to the random walk scheme. The experiments with different habitat depths show that if the jellyfish are fixed on the bottom of the water, most of them will be transported to the center, or even out of the bay, by the bottom circulation.

关键词： Liaodong Bay Jellyfish Rhopilema esculentum distribution and connectivity Lagrangian particle tracking current

来源：评论

学校读者我要写书评

暂无评论

Improving Policy-Oriented Agent-Based modeling with History Matching: A Case Study

arXiv

引用

arXiv 2024年

作者： O’Gara, David Kerr, Cliff C. Klein, Daniel J. Binois, Mickaël Garnett, Roman Hammond, Ross A. Division of Computational and Data Sciences Washington University in St. Louis St. LouisMO United States Institute for Disease Modeling Bill & Melinda Gates Foundation SeattleWA United States Acumes Team Université Côte d’Azur Inria Sophia Antipolis France Department of Computer Science McKelvey School of Engineering Washington University in St. Louis St. LouisMO United States Public Health Brown School Washington University in St. Louis St. LouisMO United States Center on Social Dynamics and Policy Brookings Institution WashingtonDC United States The Santa Fe Institute Santa FeNM United States

Advances in computing power and data availability have led to growing sophistication in mechanistic mathematical models of social dynamics. Increasingly these models are used to inform real-world policy decision-making, often with significant time sensitivity. One such modeling approach is agent-based modeling, which offers particular strengths for capturing spatial and behavioral realism, and for in-silico experiments (varying input parameters and assumptions to explore their downstream impact on key outcomes). To be useful in the real-world, these models must be able to qualitatively or quantitatively capture observed empirical phenomena, forming the starting point for subsequent experimentation. Computational constraints often form a significant hurdle to timely calibration and policy analysis in high-resolution agent-based models. In this paper, we present a technical solution to address this bottleneck, substantially increasing efficiency and thus widening the range of utility for policy models. We illustrate our approach with a case study using a previously published and widely used epidemiological model. © 2024, CC BY.

关键词： Digital elevation model

来源：评论

学校读者我要写书评

暂无评论

Constrained multi-objective optimization of process design parameters in settings with scarce data: an application to adhesive bonding

arXiv

引用

arXiv 2021年

作者： Morales-Hernández, Alejandro Gonzalez, Sebastian Rojas Van Nieuwenhuyse, Inneke Couckuyt, Ivo Jordens, Jeroen Witters, Maarten Van Doninck, Bart Flanders Make@UHasselt and Data Science Institute Hasselt University Agoralaan Diepenbeek3590 Belgium Computational Mathematics Faculty of Sciences Hasselt University Agoralaan Diepenbeek3590 Belgium Surrogate Modeling Lab Ghent University-IMEC Technologiepark-Zwijnaarde Ghent9052 Belgium CoDesignS Flanders Make Oude Diestersebaan Lommel3920 Belgium

Adhesive joints are increasingly used in industry for a wide variety of applications because of their favorable characteristics such as high strength-to-weight ratio, design flexibility, limited stress concentrations, planar force transfer, good damage tolerance, and fatigue resistance. Finding the optimal process parameters for an adhesive bonding process is challenging: the optimization is inherently multi-objective (aiming to maximize break strength while minimizing cost), constrained (the process should not result in any visual damage to the materials, and stress tests should not result in failures that are adhesion-related), and uncertain (testing the same process parameters several times may lead to different break strengths). Real-life physical experiments in the lab are expensive to perform. Traditional evolutionary approaches (such as genetic algorithms) are then ill-suited to solve the problem, due to the prohibitive amount of experiments required for evaluation. Although Bayesian optimization-based algorithms are preferred to solve such expensive problems, few methods consider the optimization of more than one (noisy) objective and several constraints at the same time. In this research, we successfully applied specific machine learning techniques (Gaussian Process Regression) to emulate the objective and constraint functions based on a limited amount of experimental data. The techniques are embedded in a Bayesian optimization algorithm, which succeeds in detecting Pareto-optimal process settings in a highly efficient way (i.e., requiring a limited number of physical experiments). © 2021, CC BY-NC-ND.

关键词： Multiobjective optimization

来源：评论

学校读者我要写书评

暂无评论

BreastCare application: Moroccan Breast cancer diagnosis through deep learning-based image segmentation and classification

引用

Intelligence-Based Medicine 2025年 11卷 100254-100254页

作者： Erragzi, Nouhaila Zrira, Nabila Lanjeri, Safae Omor, Youssef Jimi, Anwar Benmiloud, Ibtissam Sebihi, Rajaa Latib, Rachida Ngote, Nabil Khan, Haris Ahmad Nawaz, Shah LPHE-Modeling and Simulations Faculty of Science Mohammed V University in Rabat Morocco LISTD Laboratory National Superior School of Mines Rabat Morocco Radiology Department National Institute of Oncology University of Medicine and Pharmacy of Rabat Morocco ADOS Team LISTD Laboratory National Superior School of Mines Rabat Morocco Data Science Crop Protection Development Syngenta Netherlands Johannes Kepler University Linz Austria

Breast cancer remains a critical health problem worldwide. Increasing survival rates requires early detection. Accurate classification and segmentation are crucial for effective diagnosis and treatment. Although breast imaging modalities offer many advantages for the diagnosis of breast cancer, the interpretation of breast ultrasound images has always been a vital issue for physicians and radiologists due to misdiagnosis. Moreover, detecting cancer at an early stage increases the chances of survival. This article presents two approaches: Attention-DenseUNet for the segmentation task and EfficientNetB7 for the classification task using public datasets: BUSI, UDIAT, BUSC, BUSIS, and STUHospital. These models are proposed in the context of Computer-Aided Diagnosis (CAD) for breast cancer detection. In the first study, we obtained an impressive Dice coefficient for all datasets, with scores of 88.93%, 95.35%, 92.79%, 93.29%, and 94.24%, respectively. In the classification task, we achieved a high accuracy using only four public datasets that include the two classes benign and malignant: BUSI, UDIAT, BUSC, and BUSIS, with an accuracy of 97%, 100%, 99%, and 94%, respectively. Generally, the results show that our proposed methods are considerably better than other state-of-the-art methods, which will undoubtedly help improve cancer diagnosis and reduce the number of false positives. Finally, we used the suggested approaches to create “Moroccan BreastCare”, an advanced breast cancer segmentation and classification software that automatically processes, segments, and classifies breast ultrasound images. © 2025 The Authors

关键词： Application Breast ultrasound images Classification Deep learning Image pre-processing Segmentation

来源：评论

学校读者我要写书评

暂无评论

Correction to: Pointwise agglomeration in continuous racetrack model

引用

Portuguese Economic Journal 2021年第2期21卷 237-237页

作者： Ohtake, Kensuke Yagi, Atsushi Center for Mathematical Modeling and Data Science Osaka University Toyonaka Japan Graduate School of Information Science and Technology Osaka University Suita Japan

Incorrect equation 1.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Financial Instruments Generation via Tokenization into Commodity

Financial Instruments Generation via Tokenization into Commo...

引用

Blockchain, Robotics and AI for Networking Security Conference (BRAINS)

作者： Vyacheslav Davydov Yury Yanovich Moscow Institute of Electronics and Mathematics National Research University Higher School of Economics 123458 Moscow Russia Center for Computational and Data-Intensive Science and Engineering Skolkovo Institute of Science and Technology (Skoltech) 121205 Moscow Russia Laboratory of Data Mining and Predictive Modeling Institute for Information Transmission Problems (IITP RAS) 127051 Moscow Russia

ISBN: (数字)9781728170916

ISBN: (纸本)9781728170923

The diversification is a classic approach to reduce investor risks. Blockchain and smart contracts allow tokenizing heterogeneous assets into a commodity and open a new tool for it. The authors describe how to apply the approach to the various finance cases from peer-to-peer lending to real estate and leases, and theoretically estimate minimum token package size to ensure the given reliability parameter.

关键词： commodities LEASING REAL PROPERTY diversification packet size lease token peer to peer EQUIPMENT contract

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：