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A novel framework employing deep multi-attention channels network for the autonomous detection of metastasizing cells through fluorescence microscopy

arXiv

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arXiv 2023年

作者： Mamalakis, Michail Macfarlane, Sarah C. Notley, Scott V. Gad, Annica K.B. Panoutsos, George Insigneo Institute for in-silico Medicine University of Sheffield Sheffield United Kingdom Department of Infection Immunity and Cardiovascular Disease Department of Computer science Sheffield United Kingdom Department of Psychiatry Cambridge University Cambridge United Kingdom Department of Oncology and Metabolism The Medical School University of Sheffield Sheffield United Kingdom Department of Automatic Control and Systems Engineering University of Sheffield Sheffield United Kingdom Madeira Chemistry Research Centre University of Madeira Funchal Portugal Department of Oncology-Pathology Karolinska Institutet Stockholm Sweden

We developed a transparent computational large-scale imaging-based framework that can distinguish between normal and metastasizing human cells. The method relies on fluorescence microscopy images showing the spatial organization of actin and vimentin filaments in normal and metastasizing single cells, using a combination of multiattention channels network and global explainable techniques. We test a classification between normal cells (Bj primary fibroblast), and their isogenically matched, transformed and invasive counterpart (BjTertSV40TRasV12). Manual annotation is not trivial to automate due to the intricacy of the biologically relevant features. In this research, we utilized established deep learning networks and our new multi-attention channel architecture. To increase the interpretability of the network - crucial for this application area - we developed an interpretable global explainable approach correlating the weighted geometric mean of the total cell images and their local GradCam scores. The significant results from our analysis unprecedently allowed a more detailed, and biologically relevant understanding of the cytoskeletal changes that accompany oncogenic transformation of normal to invasive and metastasizing cells. We also paved the way for a possible spatial micrometre-level biomarker for future development of diagnostic tools against metastasis (spatial distribution of vimentin). © 2023, CC BY-SA.

关键词： Cells

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Optimal intervention in transportation networks

arXiv

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arXiv 2021年

作者： Cianfanelli, Leonardo Como, Giacomo Ozdaglar, Asuman Parise, Francesca Dipartimento di Scienze Matematiche Politecnico di Torino Italy Department of Automatic Control Lund University BOX 118 LundSE-22100 Sweden Department of Electrical Engineering and Computer Science MIT United States Department of Electrical and Computer Engineering Cornell University United States

We study a network design problem (NDP) where the planner aims at selecting the optimal single-link intervention on a transportation network to minimize the travel time under Wardrop equilibrium flows. Our first result is that, if the delay functions are affine and the support of the equilibrium is not modified with interventions, the NDP may be formulated in terms of electrical quantities computed on a related resistor network. In particular, we show that the travel time variation corresponding to an intervention on a given link depends on the effective resistance between the endpoints of the link. We suggest an approach to approximate such an effective resistance by performing only local computation, and exploit it to design an efficient algorithm to solve the NDP. We discuss the optimality of this procedure in the limit of infinitely large networks, and provide a sufficient condition for its optimality. We then provide numerical simulations, showing that our algorithm achieves good performance even if the equilibrium support varies and the delay functions are *** Codes 91A14, 91A43, 91A16, 90B20 Copyright © 2021, The Authors. All rights reserved.

关键词： Travel time

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An exponential stability test for a messenger rna–micro rna ode model

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UPB Scientific Bulletin, Series A: Applied Mathematics and Physics 2020年第4期82卷 11-16页

作者： Olteanu, Mircea Ştefan, Radu Department of Mathematical Methods and Models Faculty of Applied Sciences University "Politehnica" of Bucharest Romania Department of Automatic Control and Systems Engineering Faculty of Automatic Control and Computer Science University "Politehnica" of Bucharest Romania

In this paper we obtain a numerically tractable test (sufficient condition) for the exponential stability of the unique positive equilibrium point of an ODE system. The result (Theorem 3.1) is based on Lyapunov theory and Linear Ma-trix Inequalities techniques. The ODE model is related to the messengerRNA-microRNA interaction. © 2020, Politechnica University of Bucharest. All rights reserved.

关键词： RNA

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2D nanomaterials for realization of flexible and wearable gas sensors: A review

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Chemosphere 2024年 352卷 141234页

作者： Pawar, Krishna Kiran Kumar, Ashok Mirzaei, Ali Kumar, Mahesh Kim, Hyoun Woo Kim, Sang Sub Division of Materials Science and Engineering Hanyang University Seoul 04763 South Korea The Research Institute of Industrial Science Hanyang University Seoul 04763 South Korea School of Nanoscience and Technology Shivaji University Kolhapur 416004 India Department of Electrical Engineering Indian Institute of Technology Jodhpur 342030 India Department of Materials Science and Engineering Shiraz University of Technology Shiraz 715557-13876 Iran Department of Cybernetics Nanotechnology and Data Processing Faculty of Automatic Control Electronics and Computer Science Silesian University of Technology Akademicka 16 Gliwice 44-100 Poland Department of Materials Science and Engineering Inha University Incheon 22212 South Korea

Gas sensors are extensively employed for monitoring and detection of hazardous gases and vapors. Many of them are produced on rigid substrates, but flexible and wearable gas sensors are needed for intriguing usage including the internet of things (IoT) and medical devices. The materials with the greatest potential for the fabrication of flexible and wearable gas sensing devices are two-dimensional (2D) semiconducting nanomaterials, which consist of graphene and its substitutes, transition metal dichalcogenides, and MXenes. These types of materials have good mechanical flexibility, high charge carrier mobility, a large area of surface, an abundance of defects and dangling bonds, and, in certain instances adequate transparency and ease of synthesis. In this review, we have addressed the different 2D nonmaterial properties for gas sensing in the context of fabrication of flexible/wearable gas sensors. We have discussed the sensing performance of flexible/wearable gas sensors in various forms such as pristine, composite and noble metal decorated. We believe that content of this review paper is greatly useful for the researchers working in the research area of fabrication of flexible/wearable gas sensors. © 2024 Elsevier Ltd

关键词： 2D nanomaterials Flexible/wearable gas sensor Graphene MXenes Sensing mechanism TMDs Toxic gas

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Distributed control of Descriptor Networks: A Convex Procedure for Augmented Sparsity

arXiv

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arXiv 2021年

作者： Sperilă, Andrei Oară, Cristian Ciubotaru, Bogdan D. Sabău, Şerban Faculty of Automatic Control and Computers "Politehnica" University of Bucharest Sector 6 060042 Romania Electrical and Computer Engineering Department Stevens Institute of Technology HobokenNJ07030 United States

For networks of systems, with possibly improper transfer function matrices, we present a design framework which enables H∞ control, while imposing sparsity constraints on the controller’s coprime factors. We propose a convex and iterative optimization procedure with guaranteed convergence to obtain distributed controllers. By exploiting the robustness-oriented nature of our proposed approach, we provide the means to obtain sparse representations of our control laws that may not be directly supported by the network’s nominal model. © 2021, CC BY.

关键词： Convex optimization

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Study of the Influence of Rolling Modes on the Operation of Interconnected Electric Drives of a Rolling Mill

Study of the Influence of Rolling Modes on the Operation of ...

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Advanced Technology (KhPIWeek), IEEE KhPI Week on

作者： Valerii Tytiuk Alexey Kalinin Valeriy Druzhinin Victor Busher Oleksii Chornyi Dmytro Halushko Department of Electromechanics Kryvyi Rih National University Kryvyi Rih Ukraine Department of Informative computer systems Abylkas Saginov Karaganda Technical University NPJSC Karaganda The Republic of Kazakhstan Department of Power Engineering Karaganda Industrial University NPJSC Temirtau The Republic of Kazakhstan Dept. of Electrical Engineering and Electronics National University “Odessa Maritime Academy” Odessa Ukraine Institute of Electromechanics Energy Saving and Automatic Control Systems Kremenchuk Mykhailo Ostrogradskyi National University Kremenchuk Ukraine Dept. of Electrical Engineering Ukrainian State University of Science and Technologies Dnipro Ukraine

The paper is devoted to study of the influence of rolling modes on the performance of powerful interconnected electric drives of a hot rolling mill under the action of an electromagnetic coupling circuit between the electric drives of the roughing and finishing groups. The action of the electromagnetic coupling circuit manifests itself in the form of the influence of impact loads of synchronous electric drives on the angular velocity of direct current electric drives of the finishing group of the mill. The parameters of the electromagnetic coupling circuit are determined by the power supply scheme and equipment parameters. Values of impact loads applied to a synchronous motor depend on the rolling process parameters, in particular, the chemical composition of the rolled steel and the temperature of the ingot. The paper presents the results of calculating the rolling power for various rolling mode parameters. Using mathematical modeling in Simulink, numerical estimates of the influence of rolling modes on the magnitude of the voltage drop in the power supply unit and the drop in the angular velocity of the electric drive of the finishing group were obtained on the example of a wide-strip hot rolling mill 1700 of ArcelorMittal Temirtau JSC.

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TextBenDS: A generic textual data benchmark for distributed systems

arXiv

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arXiv 2021年

作者： Truicǎ, Ciprian-Octavian Apostol, Elena Darmont, Jérôme Assent, Ira Computer Science and Engineering Department Faculty of Automatic Control and Computers University Politehnica of Bucharest Bucharest Romania Department of Computer Science Aarhus University Aarhus Denmark Université de Lyon ERIC Lyon 2 EA 3083 France DIGIT Department of Computer Science Aarhus University Denmark

Extracting top-k keywords and documents using weighting schemes are popular techniques employed in text mining and machine learning for different analysis and retrieval tasks. The weights are usually computed in the data preprocessing step, as they are costly to update and keep track of all the modifications performed on the dataset. Furthermore, computation errors are introduced when analyzing only subsets of the dataset. Therefore, in a Big Data context, it is crucial to lower the runtime of computing weighting schemes, without hindering the analysis process and the accuracy of the machine learning algorithms. To address this requirement for the task of top-k keywords and documents, it is customary to design benchmarks that compare weighting schemes within various configurations of distributed frameworks and database management systems. Thus, we propose a generic document-oriented benchmark for storing textual data and constructing weighting schemes (TextBenDS). Our benchmark offers a generic data model designed with a multidimensional approach for storing text documents. We also propose using aggregation queries with various complexities and selectivities for constructing term weighting schemes, that are utilized in extracting top-k keywords and documents. We evaluate the computing performance of the queries on several distributed environments set within the Apache Hadoop ecosystem. Our experimental results provide interesting insights. As an example, MongoDB proves to have the best overall performance, while Spark's execution time remains almost the same, regardless of the weighting schemes. Copyright © 2021, The Authors. All rights reserved.

关键词： Machine learning

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Lockdown interventions in SIR models: Is the reproduction number the right control variable?

arXiv

引用

arXiv 2021年

作者： Cianfanelli, Leonardo Parise, Francesca Acemoglu, Daron Como, Giacomo Ozdaglar, Asuman Dipartimento di Scienze Matematiche Politecnico di Torino Italy Department of Electrical and Computer Engineering Cornell University United States Department of Economics Massachusetts Institute of Technology MIT United States Department of Automatic Control Lund University Sweden Department of Electrical Engineering and Computer Science MIT United States

The recent COVID-19 pandemic highlighted the need of non-pharmaceutical interventions in the first stages of a pandemic. Among these, lockdown policies proved unavoidable yet extremely costly from an economic perspective. To better understand the tradeoffs between economic and epidemic costs of lockdown interventions, we here focus on a simple SIR epidemic model and study lockdowns as solutions to an optimal control problem. We first show numerically that the optimal lockdown policy exhibits a phase transition from suppression to mitigation as the time horizon grows, i.e., if the horizon is short the optimal strategy is to impose severe lockdown to avoid diffusion of the infection, whereas if the horizon is long the optimal control steers the system to herd immunity to reduce economic loss. We then consider two alternative policies, motivated by government responses to the COVID-19 pandemic, where lockdown levels are selected to either stabilize the reproduction number (i.e., "flatten the curve") or the fraction of infected (i.e., containing the number of hospitalizations). We compute analytically the performance of these two feedback policies and compare them to the optimal control. Interestingly, we show that in the limit of infinite horizon stabilizing the number of infected is preferable to controlling the reproduction number, and in fact yields close to optimal performance. Copyright © 2021, The Authors. All rights reserved.

关键词： Optimal control systems

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Generalization Analysis of Machine Learning Algorithms via the Worst-Case Data-Generating Probability Measure

arXiv

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arXiv 2023年

作者： Zou, Xinying Perlaza, Samir M. Esnaola, Iñaki Altman, Eitan INRIA Centre Inria d'Université Côte d'Azur Sophia Antipolis06902 France Department of Electrical and Computer Engineering Princeton University PrincetonNJ08544 United States GAATI Laboratory Université de la Polynésie Française Faaa98702 French Polynesia Department of Automatic Control and Systems Engineering University of Sheffield SheffieldS1 3JD United Kingdom Laboratoire d'Informatique d'Avignon Université d'Avignon France

In this paper, the worst-case probability measure over the data is introduced as a tool for characterizing the generalization capabilities of machine learning algorithms. More specifically, the worst-case probability measure is a Gibbs probability measure and the unique solution to the maximization of the expected loss under a relative entropy constraint with respect to a reference probability measure. Fundamental generalization metrics, such as the sensitivity of the expected loss, the sensitivity of the empirical risk, and the generalization gap are shown to have closed-form expressions involving the worst-case data-generating probability measure. Existing results for the Gibbs algorithm, such as characterizing the generalization gap as a sum of mutual information and lautum information, up to a constant factor, are recovered. A novel parallel is established between the worst-case data-generating probability measure and the Gibbs algorithm. Specifically, the Gibbs probability measure is identified as a fundamental commonality of the model space and the data space for machine learning algorithms. © 2023, CC BY.

关键词： Learning algorithms

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Optimization of Methodology for Identifying Partial Discharges in Insulating Liquids through Optical Radiation Analysis Using Machine Learning

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IEEE Transactions on Instrumentation and Measurement 2025年 74卷

作者： Koziol, Michal Boczar, Tomasz Jancarczyk, Daniel Bernas, Marcin Opole University of Technology Faculty of Electrical Engineering Automatic Control and Informatics Opole45-758 Poland University of Bielsko-Biala Department of Computer Science and Automatics Bielsko-Biala43-309 Poland

The emission of optical radiation is associated with electrical discharges in high-voltage power systems. Detecting, measuring, and analyzing this radiation can enable the identification of the type of electrical discharge and the determination of its source. The article presents the results of measurements and analysis of optical spectra in the context of their application for recognizing different forms of electrical discharges in selected insulating liquids. Optical radiation in the ultraviolet, visible light, and near-infrared range, emitted by electrical discharges in insulating liquids commonly used in electrical engineering, such as mineral oil, natural ester, and synthetic ester, was analyzed. As part of the research, an innovative methodology for measuring and analyzing optical radiation emitted by electrical discharges was proposed, utilizing machine learning tools for precise analysis and interpretation of measurement data. The research results enrich current knowledge with new parameters and measurement indicators, representing another stage in the development of diagnostic methods that can be used to build expert systems and new diagnostic techniques for high-voltage insulation systems. © 1963-2012 IEEE.

关键词： Electric insulation

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