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arXiv 2021年

作者： Villaverde, Alejandro F. Pathirana, Dilan Fröhlich, Fabian Hasenauer, Jan Banga, Julio R. Universidade de Vigo Department of Systems Engineering & Control Vigo Galicia36310 Spain Faculty of Mathematics and Natural Sciences University of Bonn Bonn53115 Germany Institute of Computational Biology Helmholtz Zentrum München Neuherberg85764 Germany Center for Mathematics Technische Universität München Garching85748 Germany Harvard Medical School CambridgeMA02115 United States Bioprocess Engineering Group IIM-CSIC Vigo Galicia36208 Spain

Ordinary differential equation models are nowadays widely used for the mechanistic description of biological processes and their temporal evolution. These models typically have many unknown and non-measurable parameters, which have to be determined by fitting the model to experimental data. In order to perform this task, known as parameter estimation or model calibration, the modeller faces challenges such as poor parameter identifiability, lack of sufficiently informative experimental data, and the existence of local minima in the objective function landscape. These issues tend to worsen with larger model sizes, increasing the computational complexity and the number of unknown parameters. An incorrectly calibrated model is problematic because it may result in inaccurate predictions and misleading conclusions. For non-expert users, there are a large number of potential pitfalls. Here, we provide a protocol that guides the user through all the steps involved in the calibration of dynamic models. We illustrate the methodology with two models, and provide all the code required to reproduce the results and perform the same analysis on new models. Our protocol provides practitioners and researchers in biological modelling with a one-stop guide that is at the same time compact and sufficiently comprehensive to cover all aspects of the problem. © 2021, CC BY-NC-ND.

关键词： Parameter estimation

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H2 model reduction of linear network systems by moment matching and optimization

arXiv

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arXiv 2019年

作者： Necoara, I. Ionescu, T.C. Department of Automatic Control and Systems Engineering University Politehnica Bucharest Bucharest060042 Romania Department of Automatic Control and Systems Engineering University Politehnica Institute of Mathematical Statistics 050711 Romania

In this paper we study the problem of model reduction of linear network systems. We aim at computing a reduced order stable approximation of the network with the same topology and optimal w.r.t. H2-norm error approximation. Our approach is based on time-domain moment matching framework, where we optimize over families of parameterized reduced order models matching a set of moments at arbitrary interpolation points. The parameterization of the low order models is in terms of the free parameters and of the interpolation points. For this family of parameterized models we formulate an optimization-based model reduction problem with the H2-norm of error approximation as objective function while the preservation of some structural and physical properties yields the constraints. This problem is nonconvex and we write it in terms of the Gramians of a minimal realization of the error system. We propose two solutions for this problem. The first solution assumes that the error system admits a block diagonal observability Gramian, allowing for a simple convex reformulation as semidefinite programming, but at the cost of some performance loss. We also derive sufficient conditions to guarantee block diagonalization of the Gramian. The second solution employs a gradient projection method for a smooth reformulation yielding (locally) optimal interpolation points and free parameters. The potential of the methods is illustrated on several network examples. Copyright © 2019, The Authors. All rights reserved.

关键词： Linear networks

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Novel approach based on source separation for conversion of fresh urine to valuable resources in rural villages

Energy & Environmental Sustainability

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Energy & Environmental Sustainability 2025年第1期1卷

作者： Xiaomeng Zhang Longqian Xu Shiyu Tian Ke Wu Zhendong Lei Deli Wu Lin-Hui Tang Xu Wang Key Laboratory of Urban Water Supply Water Saving and Water Environment Governance in the Yangtze River Delta of Ministry of Water Resources College of Environmental Science & Engineering Tongji University Shanghai 200092 China Department of Civil and Environmental Engineering Vanderbilt University Nashville TN USA Shanghai Institute of Pollution Control and Ecological Security Shanghai 200092 China State Key Laboratory of Urban Water Resource and Environment Harbin Institute of Technology Shenzhen Shenzhen 518055 China Centre for Water Systems College of Engineering Mathematics and Physical Sciences University of Exeter Exeter EX4 4QF United Kingdom

Separation of urine and feces from wastewater at the source offers a promising strategy to alleviate resource scarcity; yet, broad implementation of this strategy in rural villages requires advanced technological systems to overcome an obstacle of benefits-burdens imbalance. Here, prior intervention of life cycle assessment (LCA) was attempted for the advance of N and P recovery technologies at proof-of-concept stage. We propose two novel nutrient recovery processes based on fresh urine: Ca 3 (PO 4 ) 2 precipitation by refined addition of Ca(OH) 2 and ion capture electrochemical system (ICES). Impurity interference in Ca–P precipitation process can be controlled through urine acidification and refined Ca(OH) 2 dosing; ICES can achieve a synchronous recovery of N and P from fresh urine. A prospective LCA revealed that the newly-proposed solutions outperform the prevailing struvite precipitation recovery process and achieve better operational eco-effectiveness, directly decreasing 80–98 % environmental burdens mainly through relieving substantial one-off chemicals input. Furthermore, a more flexible and customizable process can simplify the recovery procedures and increase the practicability for operations and subsequent applications, further amplifying the utility of the proposed source separation methodologies.

关键词： Fresh urine Source separation Phosphorus recovery Nitrogen recovery Life cycle assessment

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Identifying Causal Structure in Dynamical systems

arXiv

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arXiv 2020年

作者： Baumann, Dominik Solowjow, Friedrich Johansson, Karl H. Trimpe, Sebastian Department of Information Technology Uppsala University Uppsala Sweden Institute for Data Science in Mechanical Engineering RWTH Aachen University Aachen Germany Division of Decision and Control Systems and Digital Futures KTH Royal Institute of Technology Stockholm Sweden

Mathematical models are fundamental building blocks in the design of dynamical control systems. As control systems are becoming increasingly complex and networked, approaches for obtaining such models based on first principles reach their limits. Data-driven methods provide an alternative. However, without structural knowledge, these methods are prone to finding spurious correlations in the training data, which can hamper generalization capabilities of the obtained models. This can significantly lower control and prediction performance when the system is exposed to unknown situations. A preceding causal identification can prevent this pitfall. In this paper, we propose a method that identifies the causal structure of control systems. We design experiments based on the concept of controllability, which provides a systematic way to compute input trajectories that steer the system to specific regions in its state space. We then analyze the resulting data leveraging powerful techniques from causal inference and extend them to control systems. Further, we derive conditions that guarantee the discovery of the true causal structure of the system. Experiments on a robot arm demonstrate reliable causal identification from real-world data and enhanced generalization capabilities. Copyright © 2020, The Authors. All rights reserved.

关键词： Networked control systems

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LimeSoDa: A dataset collection for benchmarking of machine learning regressors in digital soil mapping

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Geoderma 2025年 459卷

作者： Schmidinger, Jonas Vogel, Sebastian Barkov, Viacheslav Pham, Anh-Duy Gebbers, Robin Tavakoli, Hamed Correa, Jose Tavares, Tiago R. Filippi, Patrick Jones, Edward J. Lukas, Vojtech Boenecke, Eric Ruehlmann, Joerg Schroeter, Ingmar Kramer, Eckart Paetzold, Stefan Kodaira, Masakazu Wadoux, Alexandre M.J.-C. Bragazza, Luca Metzger, Konrad Huang, Jingyi Valente, Domingos S.M. Safanelli, Jose L. Bottega, Eduardo L. Dalmolin, Ricardo S.D. Farkas, Csilla Steiger, Alexander Horst, Taciara Z. Ramirez-Lopez, Leonardo Scholten, Thomas Stumpf, Felix Rosso, Pablo Costa, Marcelo M. Zandonadi, Rodrigo S. Wetterlind, Johanna Atzmueller, Martin Osnabrück University Joint Lab Artificial Intelligence and Data Science Osnabrück Germany Department of Agromechatronics Potsdam Germany Piracicaba Brazil The University of Sydney Sydney Institute of Agriculture Sydney Australia Mendel University in Brno Department of Agrosystems and Bioclimatology Brno Czech Republic Leibniz Institute of Vegetable and Ornamental Crops Next Generation Horticultural Systems Grossbeeren Germany Eberswalde University for Sustainable Development Landscape Management and Nature Conservation Eberswalde Germany —Soil Science and Soil Ecology Bonn Germany Tokyo University of Agriculture and Technology Institute of Agriculture Tokyo Japan LISAH Univ. Montpellier AgroParisTech INRAE IRD L'Institut Agro Montpellier France Agroscope Field-Crop Systems and Plant Nutrition Nyon Switzerland University of Wisconsin-Madison Department of Soil Science Madison United States Federal University of Viçosa Department of Agricultural Engineering Viçosa Brazil Woodwell Climate Research Center Falmouth United States Academic Coordination Santa Maria Brazil Soil Department Santa Maria Brazil Division of Environment and Natural Resources Aas Norway University of Rostock Chair of Geodesy and Geoinformatics Rostock Germany Federal Technological University of Paraná Dois Vizinhos Brazil BÜCHI Labortechnik AG Data Science Department Flawil Switzerland Imperial College London Imperial College Business School London United Kingdom University of Tübingen Department of Geosciences Tübingen Germany University of Tübingen DFG Cluster of Excellence ‘Machine Learning for Science’ Germany Bern University of Applied Sciences Competence Center for Soils Zollikofen Switzerland Simulation and Data Science Müncheberg Germany Federal University of Jataí Institute of Agricultural Sciences Jatai Brazil Federal University of Mato Grosso Instute of Agricultural and Environmental Scinces Sinop Brazil Department of Soil and Environment Skara S

Digital soil mapping (DSM) relies on a broad pool of statistical methods, yet determining the optimal method for a given context remains challenging and contentious. Benchmarking studies on multiple datasets are needed to reveal strengths and limitations of commonly used methods. Existing DSM studies usually rely on a single dataset with restricted access, leading to incomplete and potentially misleading conclusions. To address these issues, we introduce an open-access dataset collection called Precision Liming Soil Datasets (LimeSoDa). LimeSoDa consists of 31 field- and farm-scale datasets from various countries. Each dataset has three target soil properties: (1) soil organic matter or soil organic carbon, (2) clay content and (3) pH, alongside a set of features. Features are dataset-specific and were obtained by optical spectroscopy, proximal- and remote soil sensing. All datasets were aligned to a tabular format and are ready-to-use for modeling. We demonstrated the use of LimeSoDa for benchmarking by comparing the predictive performance of four learning algorithms across all datasets. This comparison included multiple linear regression (MLR), support vector regression (SVR), categorical boosting (CatBoost) and random forest (RF). The results showed that although no single algorithm was universally superior, certain algorithms performed better in specific contexts. MLR and SVR performed better on high-dimensional spectral datasets, likely due to better compatibility with principal components. In contrast, CatBoost and RF exhibited considerably better performances when applied to datasets with a moderate number ( © 2025 The Author(s)

关键词： Random forests

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LimeSoDa: A Dataset Collection for Benchmarking of Machine Learning Regressors in Digital Soil Mapping

arXiv

引用

arXiv 2025年

作者： Schmidinger, Jonas Vogel, Sebastian Barkov, Viacheslav Pham, Anh-Duy Gebbers, Robin Tavakoli, Hamed Correa, Jose Tavares, Tiago R. Filippi, Patrick Jones, Edward J. Lukas, Vojtech Boenecke, Eric Ruehlmann, Joerg Schroeter, Ingmar Kramer, Eckart Paetzold, Stefan Kodaira, Masakazu Wadoux, Alexandre M.J.-C. Bragazza, Luca Metzger, Konrad Huang, Jingyi Valente, Domingos S.M. Safanelli, Jose L. Bottega, Eduardo L. Dalmolin, Ricardo S.D. Farkas, Csilla Steiger, Alexander Horst, Taciara Z. Ramirez-Lopez, Leonardo Scholten, Thomas Stumpf, Felix Rosso, Pablo Costa, Marcelo M. Zandonadi, Rodrigo S. Wetterlind, Johanna Atzmueller, Martin Osnabrück University Joint Lab Artificial Intelligence and Data Science Osnabrück Germany Department of Agromechatronics Potsdam Germany Piracicaba Brazil The University of Sydney Sydney Institute of Agriculture Sydney Australia Mendel University in Brno Department of Agrosystems and Bioclimatology Brno Czech Republic Leibniz Institute of Vegetable and Ornamental Crops Next Generation Horticultural Systems Grossbeeren Germany Eberswalde University for Sustainable Development Landscape Management and Nature Conservation Eberswalde Germany Soil Science and Soil Ecology Bonn Germany Tokyo University of Agriculture and Technology Institute of Agriculture Tokyo Japan LISAH Univ. Montpellier AgroParisTech INRAE IRD L'Institut Agro Montpellier France Agroscope Field-Crop Systems and Plant Nutrition Nyon Switzerland University of Wisconsin-Madison Department of Soil Science Madison United States Federal University of Viçosa Department of Agricultural Engineering Viçosa Brazil Woodwell Climate Research Center Falmouth United States Academic Coordination Santa Maria Brazil Soil Department Santa Maria Brazil Division of Environment and Natural Resources Aas Norway University of Rostock Chair of Geodesy and Geoinformatics Rostock Germany Federal Technological University of Paraná Dois Vizinhos Brazil BÜCHI Labortechnik AG Data Science Department Flawil Switzerland Imperial College London Imperial College Business School London United Kingdom University of Tübingen Department of Geosciences Tübingen Germany University of Tübingen DFG Cluster of Excellence Machine Learning for Science’ Germany Bern University of Applied Sciences Competence Center for Soils Zollikofen Switzerland Simulation and Data Science Müncheberg Germany Federal University of Jataí Institute of Agricultural Sciences Jatai Brazil Federal University of Mato Grosso Instute of Agricultural and Environmental Scinces Sinop Brazil Department of Soil and Environment Skara

关键词： Adversarial machine learning

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A new Chinese standard for testing of quality control in medical proton/heavy ion beam radiotherapy equipment

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Radiation Medicine and Protection 2023年第4期4卷 177-181页

作者： Jilong Yuan Xiangjie Ma Quanfu Sun Haikuan Liu Shouping Xu Yinxiangzi Sheng Xiaoyun Ma Xiangkui Mu Xinguo Liu Tao Yang Xin Zhang Hsiao-Ming Lu Jinsheng Cheng Key Laboratory of Radiological Protection and Nuclear Emergency China CDCNational Institute for Radiological ProtectionChinese Center for Disease Control and PreventionWHO Collaboration Center for Radiation and HealthBeijing 100088China Institute of Radiation Medicine Fudan UniversityShanghai 200032China National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital Chinese Academy of Medical Sciences and Peking Union Medical CollegeBeijing 100021China Department of Medical Physics Shanghai Proton and Heavy Ion Center Shanghai Engineering Research Center of Proton and Heavy Ion Radiation TherapyShanghai 201315China Heavy Ion Center of Wuwei Cancer Hospital Gansu Wuwei Academy of Medical SciencesGansu Wuwei Tumor HospitalWuwei 733000China Department of Radiation Oncology Shandong Cancer Hospital and InstituteShandong First Medical University and Shandong Academy of Medical SciencesJinan 250117China Institute of Modern Physics Chinese Academy of SciencesLanzhou 730000China Department of Radiation Oncology The First Medical Center of Chinese PLA General HospitalBeijing 100853China Varian Medical Systems China Co. LtdBeijing 100176China Hefei Ion Medical Center Hefei230088China Ion Medical Research Institute University of Science and Technology of ChinaHefei 230088China

With the development of social economy and radiotherapy technique,proton/heavy ion radiotherapy has been applied widely to clinical *** present,there are at least 29 hospitals in China at various stages of planning,construction,commissioning or clinical operation of medical proton/heavy ion beam radiotherapy *** with common radiotherapy accelerators used in conventional external beam radiotherapy,the proton/heavy ion therapy system has more stringent requirements for quality control so as to achieve an optimum therapeutic *** order to protect the health rights of patients undergoing radiotherapy,to facilitate the relevant administrative supervision departments to carry out standard-based approval and routine supervision and to promote the development of related medical undertakings,the standard for testing of quality control for medical proton/heavy ion beam radiotherapy equipment is drafted to fill the gap in this regard in China and even *** standard contains five indicators and corresponding testing methods for radiological protection and safety and 16 indicators for quality control of equipment *** standard is a mandatory standard and is based on the relevant Chinese legal requirements for the testing of radiotherapy equipment,so all the indicators listed in the standard shall be *** the drafting of the standard,the opinions from hospitals that are currently using proton/heavy ion medical accelerators for radiotherapy purpose and from the related equipment manufacturers were taken into *** draft standard was revised with reference to these opinions and the feasibility of the related quality control *** official version of the standard was released on March 7,2023,and implementation is scheduled to begin on March 1,2024.

关键词： Chinese standard Proton Heavy ion Radiotherapy Quality control

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Parity Space-Based Fault Detection by Minimum Error Minimax Probability Machine

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IFAC-PapersOnLine 2018年第24期51卷 1292-1297页

作者： Zhong, Maiying Song, Yang Xue, Ting Yang, Rui Li, Wenbo College of Electrical Engineering and Automation Shandong University of Science and Technology Qingdao266590 China School of Instrumentation Science and Opto-electronic Engineering Beihang University Beijing100191 China Institute for Automatic Control and Complex Systems University of Duisburg-Essen Duisburg47057 Germany The Beijing Institute of Control Engineering Beijing100190 China

This paper deals with the problem of parity space-based fault detection (FD) for linear discrete time systems in the framework of minimum error minimax probability machine (MEMPM). Traditional parity space-based FD is usually difficult to achieve acceptable tradeoff between missed alarm rate (MAR) and false alarm rate (FAR) without the exact stochastic properties of unknown input. To solve this problem, this paper proposes a novel method of parity space-based FD by MEMPM. Firstly, the integrated design of parity space vector, threshold, MAR and FAR is formulated as a problem of binary classification, i.e., the fault-free case and faulty case. By using the method of MEMPM, a bank of parity space vectors corresponding to different faulty scenarios and a threshold are then obtained, while an optimal trade-off between MAR and FAR is achieved in the worst-case setting. To show the effectiveness of proposed method, a satellite attitude control system subject to roll momentum wheel fault and pitch gyroscope fault is considered. © 2018

关键词： Fault detection Alarm systems Attitude control Digital control systems Discrete time control systems Economic and social effects Error detection Finite difference method Image resolution Probability Stochastic systems Vector spaces Alarm rate False alarm rate Linear discrete time systems Minimax probability machine Missed alarm rates (MAR) Parity spaces Satellite attitude control systems Stochastic properties

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Wide-angle giant photonic spin Hall effect

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Physical Review B 2022年第7期106卷 075409-075409页

作者： Zhihao Chen Yu Chen Yaodong Wu Xinxing Zhou Handong Sun Tony Low Hongsheng Chen Xiao Lin Key Laboratory of Low-Dimensional Quantum Structures and Quantum Control of Ministry of Education Synergetic Innovation Center for Quantum Effects and Applications School of Physics and Electronics Hunan Normal University Changsha 410081 China International Collaborative Laboratory of 2D Materials for Optoelectronics Science and Technology Engineering Technology Research Center for 2D Material Information Function Devices and Systems of Guangdong Province Institute of Microscale Optoelectronics Shenzhen University Shenzhen 518060 China Division of Physics and Applied Physics School of Physical and Mathematical Sciences Nanyang Technological University Singapore 637371 Singapore Centre for Disruptive Photonic Technologies (CDPT) School of Physical and Mathematical Sciences Nanyang Technological University Singapore 637371 Singapore Department of Electrical and Computer Engineering University of Minnesota Minneapolis Minnesota 55455 USA Interdisciplinary Center for Quantum Information State Key Laboratory of Modern Optical Instrumentation ZJU-Hangzhou Global Scientific and Technological Innovation Center College of Information Science and Electronic Engineering Zhejiang University Hangzhou 310027 China International Joint Innovation Center ZJU-UIUC Institute The Electromagnetics Academy at Zhejiang University Zhejiang University Haining 314400 China

The photonic spin Hall effect is a manifestation of the spin-orbit interaction of light and can be measured by a transverse shift δ of photons with opposite spins. The precise measurement of transverse shifts can enable many spin-related applications, such as precise metrology and optical sensing. However, this transverse shift is generally small (i.e., δ/λ<10−1, where λ is the wavelength), which impedes its precise measurement. To date, proposals to generate a giant spin Hall effect (namely, with δ/λ>102) have severe limitations, particularly its occurrence only over a narrow angular cone (with a width of Δθ<1∘). Here we propose a universal scheme to realize the wide-angle giant photonic spin Hall effect with Δθ>70∘ by exploiting the interface between free space and uniaxial epsilon-near-zero media. The underlying mechanism is ascribed to the almost-perfect polarization splitting between s and p polarized waves at the designed interface. Remarkably, this almost-perfect polarization splitting does not resort to the interference effect and is insensitive to the incident angle, which then gives rise to the wide-angle giant photonic spin Hall effect.

关键词： Light-matter interaction Photonics Spin Hall effect Spin-orbit coupling

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A Stochastic Inventory Model with Two Queues and a Flexible Server

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International Journal of Applied and Computational Mathematics 2019年第1期5卷 1-27页

作者： Jeganathan, K. Melikov, A.Z. Padmasekaran, S. Kingsly, S. Jehoashan Lakshmi, K. Prasanna Ramanujan Institute for Advanced Study in Mathematics University of Madras Chennai India Institute of Control Systems National Academy of Sciences Baku Azerbaijan Department of Mathematics Periyar University Salem India Department of Mathematics Adhiyamaan College of Engineering Hosur India Department of Mathematics with Computer Applications Ethiraj College for Women Chennai India

This paper focusses on a perishable inventory model with two stations, namely, station 1 and station 2 with two dedicated servers and one flexible server, where service rates are different with respect to stations and servers. By using matrix analysis method, the joint stationary distribution of the number of customers in station 1 and station 2, the status of the servers and the inventory level under steady state are investigated. Some significant measures of the system performance are obtained. Finally, some intrinsic numerical examples are given. © 2019, Springer Nature India Private Limited.

关键词： (s, Q) policy Additional service Balking and multiple vacations Continuous review Flexible server Heterogeneous servers Perishable commodity

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