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IDF2022-1183 The effect of multi-strain probiotics on diarrhea in patients with type 2 diabetes and metformin intolerance

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Diabetes Research and Clinical Practice 2023年 197卷 110340-110340页

作者： Nabrdalik, K. Drożdż, K. Kwiendacz, H. Skonieczna-Żydecka, K. Łoniewski, I. Kaczmarczyk, M. Nalepa, J. Holleman, F. Nieuwdorp, M. Gumprecht, J. Medical University of Silesia in Katowice Faculty of Medical Sciences in Zabrze Department of Internal Medicine Diabetology and Nephrology Zabrze Poland Pomeranian Medical University in Szczecin Department of Human Nutrition and Metabolomics Szczecin Poland Pomeranian Medical University in Szczecin Department of Biochemical Sciences Szczecin Poland Pomeranian Medical University in Szczecin Department of Clinical and Molecular Biochemistry Szczecin Poland Silesian University of Technology Faculty of Automatic Control Electronics and Computer Science Department of Algorithmics and Software Gliwice Poland Universiteit van Amsterdam- Amsterdam UMC Department of Internal Medicine Amsterdam The Netherlands Universiteit van Amsterdam Amsterdam UMC Department of Internal Medicine Section Vascular Medicine Amsterdam The Netherlands

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Nonlinear Modeling of the Subcritical Boiler-turbine System with Stochastic Differential Equations*

Nonlinear Modeling of the Subcritical Boiler-turbine System ...

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IEEE International Conference on Power Data Science (ICPDS)

作者： Ming Du Jie Xia Yonggui Qian Xiaobin Li Guoyuan Cai Rui Liu School of control and computer engineering North China Electric Power University Beijing China Huaihu Coal and Electricity Co. Ltd. Huainan Anhui Province China China Railway Beijing Bureau Group Co. Ltd. Beijing West Power Section official Beijing China

ISBN: (数字)9781728137759

ISBN: (纸本)9781728137766

With the large-scale renewable energy integrated into power system, the optimization of coordinated control system (CCS) is increasingly crucial. The dynamics of subcritical boiler-turbine system have been studied through kinds of modeling methods. But the ordinary differential equations (ODEs) are used in previous studies mainly, which can not reflect the uncertainties in this system. In this work, the uncertainties in subcritical boiler-turbine system had been analyzed and the dynamics had been described with stochastic differential equations (SDEs). Great improvements of boiler- turbine system model can be seen in the simulations. This model can be the platform to study stochastic model predictive control in CCS.

关键词： Mathematical model Load modeling Coal Boilers Turbines Analytical models

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Time Optimal Robust Fleet Management of Micro UAV Through Timed Games Formulation

Time Optimal Robust Fleet Management of Micro UAV Through Ti...

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control Technology and Applications (CCTA),

作者： Henrik Schiøler Luminita Totu Jan Dimon Kim Guldstrand Larsen Jakob Haahr Taankvist Section for Control and Automation Aalborg Universty Aalborg Denmark Department for Computer Science Aalborg Universty Aalborg Denmark Aalborg Universitet Aalborg DK

We consider the case of fleet management of a moderate number of Unmanned Aerial Vehicles (UAV or UAS) in confined space, e.g. indoor. Indoor operation of UAVs requires indoor localization capabilities as well as a sufficiently precise 3D map of the facility, whereas fleet management of multiple UAV adds an extra dimension of complexity. Additional complexity is mainly introduced by constraints ensuring collision free operation. Based on earlier work on mapping, path planning and localization we suggest fleet management through a Timed Game formulation and Winning Strategy controller synthesis using the tool Uppaal Tiga.

关键词： Automata Games Unmanned aerial vehicles Uncertainty Path planning Schedules Clocks

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Lyapunov Function Synthesis - Infeasibility and Farkas’ Lemma

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IFAC-PapersOnLine 2017年第1期50卷 1667-1672页

作者： Leth T. Sloth C. Wisniewski R. Sankaranarayanan S. Department of Electrical Engineering Section of Automation & Control University of Aalborg Aalborg East 9220 Denmark Department of Computer Science University of Colorado Boulder CO United States

In this paper we prove the convergence of an algorithm synthesising continuous piecewise-polynomial Lyapunov functions for polynomial vector fields defined on simplices. We subsequently modify the algorithm to sub-divide locally by utilizing information from infeasible linear problems. We prove that this modification does not destroy the convergence of the algorithm. Both methods are accompanied by examples. © 2017

关键词： Algorithmic design Lyapunov methods Stability of nonlinear systems

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New method for the stability analysis of neutral systems with time-varying structured uncertainties

New method for the stability analysis of neutral systems wit...

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第37届中国控制会议

作者： Liming Ding Dajiang He Xianwu Mi Jun Shu Leiping Chen Fazhong Hou Dengfeng Xiao College of Electrical and Information Engineering Huaihua University Key Laboratory of Intelligent Control Technology for Wuling-Mountain Ecological Agriculture in Hunan Province Teaching and Research Section for Computer in Department of Public Courses Huaihua University of Medicine School of Information and Electrical Engineering Hunan University of Science and Technology

This study investigates the delay-dependent stability problem for neutral systems with mixed *** from previous works,this paper employs the free-weighting matrix(FWM) approach and integral inequality approach to estimate the derivative of LKF ***,a new integral inequality based the Wirtinger inequality is *** improved inequality is right used to cope with the terms ∫x(s)ds which are generated by using the free-weighting matrix ***,by integrating the newly integral inequality with free-weighting matrix approach,some less conservative stability criteria are *** examples demonstrate the effectiveness of the method and its advantage over existing methods.

关键词： free-weighting matrix（FWM） integral inequality Stabilization Linear matrix inequality（LMI） neutral systems

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System Properties of Implicit Passive Electrical Networks Descriptions

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IFAC-PapersOnLine 2017年第1期50卷 9242-9247页

作者： Karcanias N. Livada M. Leventides J. Systems and Control Research Centre School of Mathematics Computer Sciences & Engineering City University London Northampton Square London EC1V 0HB United Kingdom University of Athens Department of Economics Section of Mathematics and Informatics Pezmazoglou 8 Athens Greece

Redesigning systems by changing elements, topology, organization, augmenting the system by the addition of subsystems, or removing parts, is a major challenge for systems and control theory. A special case is the redesign of passive electric networks which aims to change the natural dynamics of the network (natural frequencies) by the above operations leading to a modification of the network. This requires changing the system to achieve the desirable natural frequencies and involves the selection of alternative values for dynamic elements and non-dynamic elements within a fixed interconnection topology and/or alteration of the interconnection topology and possible evolution of the network (increase of elements, branches). The use of state-space or transfer function models does not provide a suitable framework for the study of this problem, since every time such changes are introduced, a new state space or transfer function model has to be recalculated. The use of impedance and admittance modeling, provides a suitable framework for the study of network properties under the process of re-engineering transformations. This paper deals with the fundamental system properties of the impedance-admittance network description which provide the appropriate framework for network re-engineering. We identify the natural topologies expressing the structured transformations linked to the impedance-graph, admittance graph-topology of the network and examine issues such as network regularity, number of finite frequencies and provide characterization of them in terms of the basic network matrices. The implicit network representation introduced provides a natural framework for expressing the different types of re-engineering transformations which can be used for the study of the natural frequencies assignment. © 2017

关键词： linear networks Linear systems structured systems system models system theory

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A Grassmann Matrix Approach for the Computation of Degenerate Solutions for Output Feedback Laws

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IFAC-PapersOnLine 2017年第1期50卷 10839-10844页

作者： Leventides J. Meintanis I. Karcanias N. University of Athens Department of Economics Section of Mathematics and Informatics Pezmazoglou 8 Athens Greece Systems and Control Research Centre School of Mathematics Computer Sciences and Engineering City University of London Northampton Square London EC1V 0HB United Kingdom

The paper is concerned with the improvement of the overall sensitivity properties of a method to design feedback laws for multivariable linear systems which can be applied to the whole family of determinantal type frequency assignment problems, expressed by a unified description, the so-called Determinantal Assignment Problem (DAP). By using the exterior algebra/algebraic geometry framework, DAP is reduced to a linear problem (zero assignment of polynomial combinants) and a standard problem of multilinear algebra (decomposability of multivectors) which is characterized by the set of Quadratic Plücker Relations (QPR) that define the Grassmann variety of P. This design method is based on the notion of degenerate compensator, which are the solutions that indicate the boundaries of the control design and they provide the means for linearising asymptotically the nonlinear nature of the problems and hence are used as the starting points to generate linearized feedback laws. A new algorithmic approach is introduced for the computation and the selection of degenerate solutions (decomposable vectors) which allows the computation of static and dynamic feedback laws with reduced sensitivity (and hence more robust solutions). This approach is based on alternative, linear algebra type criterion for decomposability of multivectors to that defined by the QPRs, in terms of the properties of structured matrices, referred to as Grassmann Matrices. The overall problem is transformed to a nonlinear maximization problem where the objective function is expressed via the Grassmann Matrices and the first order conditions for optimality are reduced to a nonlinear eigenvalue-eigenvector problem. Hence, an iterative method similar to the power method for finding the largest modulus eigenvalue and the corresponding eigenvector is proposed as a solution for the above problem. © 2017

关键词： Frequency assignment Linear multivariable systems Linear systems Output feedback control (linear case)

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Long-term exposure to low ambient air pollution concentrations and mortality among 28 million people: results from seven large European cohorts within the ELAPSE project

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The Lancet Planetary Health 2022年第1期6卷 e9-e18页

作者： Stafoggia, Massimo Oftedal, Bente Chen, Jie Rodopoulou, Sophia Renzi, Matteo Atkinson, Richard W Bauwelinck, Mariska Klompmaker, Jochem O Mehta, Amar Vienneau, Danielle Andersen, Zorana J Bellander, Tom Brandt, Jørgen Cesaroni, Giulia de Hoogh, Kees Fecht, Daniela Gulliver, John Hertel, Ole Hoffmann, Barbara Hvidtfeldt, Ulla A Jöckel, Karl-Heinz Jørgensen, Jeanette T Katsouyanni, Klea Ketzel, Matthias Kristoffersen, Doris Tove Lager, Anton Leander, Karin Liu, Shuo Ljungman, Petter L S Nagel, Gabriele Pershagen, Göran Peters, Annette Raaschou-Nielsen, Ole Rizzuto, Debora Schramm, Sara Schwarze, Per E Severi, Gianluca Sigsgaard, Torben Strak, Maciek van der Schouw, Yvonne T Verschuren, Monique Weinmayr, Gudrun Wolf, Kathrin Zitt, Emanuel Samoli, Evangelia Forastiere, Francesco Brunekreef, Bert Hoek, Gerard Janssen, Nicole A H Department of Epidemiology Lazio Region Health Service ASL Roma 1 Rome Italy Institute of Environmental Medicine Karolinska Institutet Stockholm Sweden Department of Global Public Health Karolinska Institutet Stockholm Sweden Department of Environmental Health Norwegian Institute of Public Health Oslo Norway Division for Infection Control and Environmental Health Norwegian Institute of Public Health Oslo Norway Institute for Risk Assessment Sciences Utrecht University Utrecht Netherlands Department of Hygiene Epidemiology and Medical Statistics Medical School National and Kapodistrian University of Athens Athens Greece Population Health Research Institute St George's University of London London UK United Kingdom Interface Demography–Department of Sociology Vrije Universiteit Brussel Brussels Belgium National Institute for Public Health and the Environment Bilthoven Netherlands Harvard T H Chan School of Public Health Boston MA United States Section of Epidemiology Department of Public Health University of Copenhagen Copenhagen Denmark Section of Environmental Health Department of Public Health University of Copenhagen Copenhagen Denmark Swiss Tropical and Public Health Institute Basel Switzerland University of Basel Basel Switzerland Centre for Occupational and Environmental Medicine Region Stockholm Stockholm Sweden Department of Environmental Science Aarhus University Roskilde Denmark Department of Bioscience Aarhus University Roskilde Denmark iClimate Aarhus University Interdisciplinary Centre for Climate Change Aarhus Denmark School of Public Health Faculty of Medicine Imperial College London London UK United Kingdom Centre for Environmental Health and Sustainability and School of Geography Geology and the Environment University of Leicester Leicester UK United Kingdom Institute for Occupational Social and Environmental Medicine Centre for Health and Society Medical Faculty Heinrich Heine University Düsseldorf Düsseldorf Germany Danis

Background: Long-term exposure to ambient air pollution has been associated with premature mortality, but associations at concentrations lower than current annual limit values are uncertain. We analysed associations between low-level air pollution and mortality within the multicentre study Effects of Low-Level Air Pollution: A Study in Europe (ELAPSE). Methods: In this multicentre longitudinal study, we analysed seven population-based cohorts of adults (age ≥30 years) within ELAPSE, from Belgium, Denmark, England, the Netherlands, Norway, Rome (Italy), and Switzerland (enrolled in 2000–11;follow-up until 2011–17). Mortality registries were used to extract the underlying cause of death for deceased individuals. Annual average concentrations of fine particulate matter (PM_2·5), nitrogen dioxide (NO₂), black carbon, and tropospheric warm-season ozone (O₃) from Europe-wide land use regression models at 100 m spatial resolution were assigned to baseline residential addresses. We applied cohort-specific Cox proportional hazard models with adjustment for area-level and individual-level covariates to evaluate associations with non-accidental mortality, as the main outcome, and with cardiovascular, non-malignant respiratory, and lung cancer mortality. Subset analyses of participants living at low pollutant concentrations (as per predefined values) and natural splines were used to investigate the concentration-response function. Cohort-specific effect estimates were pooled in a random-effects meta-analysis. Findings: We analysed 28 153 138 participants contributing 257 859 621 person-years of observation, during which 3 593 741 deaths from non-accidental causes occurred. We found significant positive associations between non-accidental mortality and PM_2·5, NO₂, and black carbon, with a hazard ratio (HR) of 1·053 (95% CI 1·021–1·085) per 5 μg/m³ increment in PM_2·5, 1·044 (1·019–1·069) per 10 μg/m³

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Ten quick tips for deep learning in biology

arXiv

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arXiv 2021年

作者： Lee, Benjamin D. Gitter, Anthony Greene, Casey S. Raschka, Sebastian Maguire, Finlay Titus, Alexander J. Kessler, Michael D. Lee, Alexandra J. Chevrette, Marc G. Stewart, Paul Allen Britto-Borges, Thiago Cofer, Evan M. Yu, Kun-Hsing Carmona, Juan Jose Fertig, Elana J. Kalinin, Alexandr A. Signal, Beth Lengerich, Benjamin J. Triche, Timothy J. Boca, Simina M. In-Q-Tel Labs School of Engineering and Applied Sciences Harvard University Department of Genetics Harvard Medical School United States Department of Biostatistics and Medical Informatics University of Wisconsin-Madison MadisonWI United States Morgridge Institute for Research MadisonWI United States Department of Systems Pharmacology and Translational Therapeutics Perelman School of Medicine University of Pennsylvania PhiladelphiaPA United States Department of Biochemistry and Molecular Genetics University of Colorado School of Medicine AuroraCO United States Center for Health AI University of Colorado School of Medicine AuroraCO United States Department of Statistics University of Wisconsin Madison United States Faculty of Computer Science Dalhousie University Canada University of New Hampshire Bioeconomy.XYZ United States Department of Oncology Johns Hopkins University United States Institute for Genome Sciences University of Maryland School of Medicine United States Genomics and Computational Biology Graduate Program University of Pennsylvania United States Department of Systems Pharmacology and Translational Therapeutics University of Pennsylvania United States Wisconsin Institute for Discovery Department of Plant Pathology University of Wisconsin-Madison United States Department of Biostatistics and Bioinformatics Moffitt Cancer Center TampaFL United States Section of Bioinformatics and Systems Cardiology Klaus Tschira Institute for Integrative Computational Cardiology University Hospital Heidelberg Germany University Hospital Heidelberg Germany Lewis-Sigler Institute for Integrative Genomics Princeton University PrincetonNJ United States Graduate Program in Quantitative and Computational Biology Princeton University PrincetonNJ United States Department of Biomedical Informatics Harvard Medical School United States Department of Pathology Brigham and Women's Hospital United States Philips Healthcare CambridgeMA United States Philips Research

Machine learning is a modern approach to problem-solving and task automation. In particular, machine learning is concerned with the development and applications of algorithms that can recognize patterns in data and use them for predictive modeling. Artificial neural networks are a particular class of machine learning algorithms and models that evolved into what is now described as deep learning. Given the computational advances made in the last decade, deep learning can now be applied to massive data sets and in innumerable contexts. Therefore, deep learning has become its own subfield of machine learning. In the context of biological research, it has been increasingly used to derive novel insights from high-dimensional biological data. To make the biological applications of deep learning more accessible to scientists who have some experience with machine learning, we solicited input from a community of researchers with varied biological and deep learning interests. These individuals collaboratively contributed to this manuscript's writing using the GitHub version control platform and the Manubot manuscript generation toolset. The goal was to articulate a practical, accessible, and concise set of guidelines and suggestions to follow when using deep learning. In the course of our discussions, several themes became clear: the importance of understanding and applying machine learning fundamentals as a baseline for utilizing deep learning, the necessity for extensive model comparisons with careful evaluation, and the need for critical thought in interpreting results generated by deep learning, among others. © 2021, CC BY.

关键词： Learning algorithms

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Evaluation of the simple safe site selection (S4) hazard detection algorithm using helicopter field test data

Evaluation of the simple safe site selection (S4) hazard det...

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AIAA Guidance, Navigation, and control Conference, 2017

作者： Luna, Michael E. Almeida, Eduardo Spiers, Gary Villalpando, Carlos Y. Johnson, Andrew E. Trawny, Nikolas Guidance & Control Operations Group Jet Propulsion Laboratory California Institute of Technology PasadenaCA91109 United States Maritime & Aerial Perception Systems Group Jet Propulsion Laboratory California Institute of Technology PasadenaCA91109 United States Optics Section Staff Jet Propulsion Laboratory California Institute of Technology PasadenaCA91109 United States Advanced Computer Systems & Technologies Group Jet Propulsion Laboratory California Institute of Technology PasadenaCA91109 United States Guidance & Control Section Staff Jet Propulsion Laboratory California Institute of Technology PasadenaCA91109 United States GN&C Hardware and Testbed Development Group Jet Propulsion Laboratory California Institute of Technology PasadenaCA91109 United States

ISBN: (数字)9781624104503

ISBN: (纸本)9781624104503

Small scale terrain hazards, such as rocks, slopes, and craters, can pose significant risk to landing spacecraft and rover or payload deployment. Onboard Hazard Detection and Avoidance (HDA) systems scan and analyze the landing area for these hazards in real time during descent, and divert the spacecraft to the safest touchdown site. The computationally efficient Simple Safe Site Selection (S4) algorithm combined with a ash LIDAR is an HDA system geared towards small robotic spacecraft. Rather than creating and analyzing a digital elevation map (DEM) from potentially many overlapping range images, S4 operates directly on a single ash LIDAR image. Extending prior work that has analyzed S4 performance for Mars landing using extensive simulations, this paper evaluates S4 performance using actual ash LIDAR images of an artificial hazard field acquired during a 2014 helicopter field test in Death Valley, CA. In particular, we describe LIDAR characterization and calibration, creation of ground truth elevation and safety maps, creation of ground truth sensor poses, actual S4 algorithm processing, and performance analysis. The results show that the safety cost images produced by S4 are remarkably close to the ground truth safety map (computed offline by an HDA algorithm developed under the Autonomous Landing and Hazard Avoidance (ALHAT) project) at significantly reduced computational cost, confirming S4 as a viable candidate algorithm for onboard spacecraft HDA. © 2017, American Institute of Aeronautics and Astronautics Inc, AIAA. All rights reserved.

关键词： Optical radar

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