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International Symposium on Fusion of Mathematics and Biology, 2020

作者： Ito, Takeshi Suzuki, Takashi Murakami, Yoshinori Division of Molecular Pathology The Institute of Medical Science The University of Tokyo 4-6-1 Shirokanedai Minato-ku Tokyo108-8639 Japan Center for Mathematical Modeling and Data Science Osaka University 1-3 Machikaneyama Toyonaka Osaka560-8531 Japan

ISBN: (纸本)9789811648656

The most common driver mutations in lung adenocarcinoma occur in the EGFR gene. Gefitinib, an EGFR tyrosine kinase inhibitor, is an effective therapy for lung adenocarcinoma with EGFR mutations. However, resistant tumors inevitably arise. One of the mechanisms conferring gefitinib resistance is the amplification of the MET gene, which is observed in 5–22% of all cases. A previous study suggested that MET overexpression may cause gefitinib resistance through ErbB3, and most likely through the formation of EGFR-ErbB3 heterodimers. In this study, we focused on the dimer formation of EGFR and ErbB3 in lung adenocarcinoma cells and built a mathematical model using ordinary differential equations. To simulate the dimerization process of EGFR and ErbB3, we determined the molecular concentrations of each on the cell surface by flow cytometry and estimated unknown reaction constants by dimensional analysis. Our mathematical model would provide a quantitative understanding of dimer formation, one which cannot be obtained by a molecular biology methods. © 2021, Springer Nature Singapore Pte Ltd.

关键词： Dimerization

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Developing Measurement-Informed Methane Emissions Inventory Estimates at Midstream Compressor Stations

ACS ES&T Air

引用

ACS ES&T Air 2025年第3期2卷 358-367页

作者： Arvind P. Ravikumar Hugh Li Shuting Lydia Yang Mackenzie L. Smith Center for Energy and Environmental Systems Analysis (CEESA) The University of Texas at Austin Austin Texas 78712 United States；Energy Emissions Modeling and Data Lab The University of Texas at Austin Austin Texas 78712 United States；Department of Petroleum and Geosystems Engineering The University of Texas at Austin Austin Texas 78712 United States Department of Systems Engineering Harrisburg University of Science and Technology Harrisburg Pennsylvania 17101 United States Center for Energy and Environmental Systems Analysis (CEESA) The University of Texas at Austin Austin Texas 78712 United States；Energy Emissions Modeling and Data Lab The University of Texas at Austin Austin Texas 78712 United States Champion X The Woodlands Texas 77381 United States

Natural gas transmissions and storage compressor stations account for the largest share of anthropogenic methane (CH4) emissions in New York State (NYS). Yet, NYS’s CH4emissions inventory is based on measurements that are a decade old and potentially unlikely to be representative of NYS operations. Here, we present results from a comprehensive, multiscale aerial CH4measurement campaign across all NYS transmission and storage compressor stations. We find a skewed emissions distribution, with 20% of stations accounting for 74% of total CH4emissions. Emissions at engine-driven compressor stations are, on average, 3–4× higher than emissions at turbine-driven compressor stations, thus demonstrating the need for separate emissions factors for engine- and turbine-drive compressor stations. Overall, measurement-informed emissions inventory from midstream transmission and storage compressor stations in NYS is 72% and 69% lower than the current NYS inventory, respectively. We estimate updated emissions factors of 464 [95% CI: 162–920] metric ton (MT) CH4/station/yr and 139 [97, 191] MT CH4/station/yr for engine- and turbine-based transmission compressor stations, respectively. Similarly, we estimate an updated emissions factor of 413 [164, 733] MT CH4/station/yr for engine-based storage compressor stations. These updated emissions factors, along with improved activity data, enable effective reconciliation of NYS inventory with measured *** study reports on the first large-scale measurement of methane emissions from midstream compressor stations in New York and provides a scalable approach to reconcile and update official emission inventories.

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An Efficient Model based on Machine Learning Algorithms for Virtual Machines Classification in Cloud Computing Environment

An Efficient Model based on Machine Learning Algorithms for ...

引用

Innovative Research in Applied science, Engineering and Technology (IRASET),Conference on

作者： Abdelhadi Amahrouch Mehdi Bouhamidi Youssef Saadi Said El Kafhali Faculty of Sciences and Techniques Data Science for Sustainable Earth Laboratory Sultan Moulay Slimane University Beni Mellal Morocco Laboratory of Industrial and Human Automation Mechanics and Computer Science Polytechnic University Hauts-de-France France Faculty of Sciences and Techniques Computer Networks Modeling and Mobility Laboratory Hassan First University of Settat Settat Morocco

ISBN: (数字)9798350309508

ISBN: (纸本)9798350309515

In cloud computing, virtual machines consolidation (VMC) techniques are commonly used to improve resource utilization and reduce energy consumption. Task scheduling in cloud systems is a crucial aspect of VMC as it involves mapping clients' requirements to the appropriate computing resources such as Virtual Machines (VMs) or Physical Machines (PMs). The cloud provider must ensure that tasks are executed efficiently using the available shared computing resources while maintaining the quality of service (QoS) and minimizing the carbon footprint. Therefore, a good VM migration based on the customer's needs and IT resource capacity is required to maintain the best performance of the cloud system. In this work, we introduce an approach that leverage machine learning-based algorithms for VMs classification based on their latency sensitivity to facilitate subsequent migration into a suitable PM for better VMC. These algorithms categorize VMs into two groups: potentially inter-active machines (exhibiting periodic behavior on a daily scale) and latency-insensitive machines (for example, batch workloads, development, and test workloads). Our model demonstrated robust performance, achieving an accuracy of around 83%, thus establishing itself as the most proficient classifier in this study.

关键词： Cloud computing Machine learning algorithms Sensitivity Processor scheduling Computational modeling Quality of service Virtual machining

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Agglomeration triggered by the effect of the number of regions: A model in NEG with a quadratic subutility

arXiv

引用

arXiv 2021年

作者： Ohtake, Kensuke Center for Mathematical Modeling and Data Science Osaka University Osaka Toyonaka560-8531 Japan

We extend the mathematical model proposed by Ottaviano-Tabuchi-Thisse (2002) to a multi-regional case and investigate the stability of the homogeneous stationary solution of the model in a one-dimensional periodic space. When the number of regions is two and three, the homogeneous stationary solution is stable under sufficiently high transport cost. On the other hand, when the number of regions is a multiple of four, the homogeneous stationary solution is unstable under any values of the transport cost. Copyright © 2021, The Authors. All rights reserved.

关键词： Differential equations

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INTERPOLATORY H2-OPTIMALITY CONDITIONS FOR STRUCTURED LINEAR TIME-INVARIANT SYSTEMS

arXiv

引用

arXiv 2023年

作者： Mlinarić, Petar Benner, Peter Gugercin, Serkan Department of Mathematics Virginia Tech BlacksburgVA24061 United States Computational Methods in Systems and Control Theory Max Planck Institute for Dynamics of Complex Technical Systems Magdeburg39106 Germany Department of Mathematics Division of Computational Modeling and Data Analytics Academy of Data Science Virginia Tech BlacksburgVA24061 United States

Interpolatory necessary optimality conditions for H2-optimal reduced-order modeling of unstructured linear time-invariant (LTI) systems are well-known. Based on previous work on L2-optimal reduced-order modeling of stationary parametric problems, in this paper we develop and investigate optimality conditions for H2-optimal reduced-order modeling of structured LTI systems, in particular, for second-order, port-Hamiltonian, and time-delay systems. Under certain diagonalizability assumptions, we show that across all these different structured settings, bitangential Hermite interpolation is the common form for optimality, thus proving a unifying optimality framework for structured reduced-order modeling. Copyright © 2023, The Authors. All rights reserved.

关键词： Linear time-invariant system

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Graph Linear Canonical Transform Based on CM-CC-CM Decomposition

arXiv

引用

arXiv 2024年

作者： Li, Na Zhang, Zhichao Han, Jie Chen, Yunjie Cao, Chunzheng School of Mathematics and Statistics Nanjing University of Information Science and Technology Nanjing210044 China Center for Applied Mathematics of Jiangsu Province Nanjing University of Information Science and Technology Nanjing210044 China Jiangsu International Joint Laboratory on System Modeling and Data Analysis Nanjing University of Information Science and Technology Nanjing210044 China School of Remote Sensing and Geomatics Engineering Nanjing University of Information Science and Technology Nanjing210044 China

The graph linear canonical transform (GLCT) is presented as an extension of the graph Fourier transform (GFT) and the graph fractional Fourier transform (GFrFT), offering more flexibility as an effective tool for graph signal processing. In this paper, we introduce a GLCT based on chirp multiplication-chirp convolution-chirp multiplication decomposition (CM-CCCM- GLCT), which irrelevant to sampling periods and without oversampling operation. Various properties and special cases of the CM-CC-CM-GLCT are derived and discussed. In terms of computational complexity, additivity, and reversibility, we compare the CM-CC-CM-GLCT and the GLCT based on the central discrete dilated Hermite function (CDDHFs-GLCT). Theoretical analysis demonstrates that the computational complexity of the CM-CC-CM-GLCT is significantly reduced. Simulation results indicate that the CM-CC-CM-GLCT achieves similar additivity to the CDDHFs-GLCT. Notably, the CM-CC-CM-GLCT exhibits better reversibility. Copyright © 2024, The Authors. All rights reserved.

关键词： Chirp modulation

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Generalized Convolution and Product Theorems Associated With the Free Metaplectic Transformation and Their Applications

SSRN

引用

SSRN 2023年

作者： Cui, Manjun Zhang, Zhichao School of Mathematics and Statistics Nanjing University of Information Science and Technology Nanjing210044 China Center for Applied Mathematics of Jiangsu Province Nanjing University of Information Science and Technology Nanjing210044 China Jiangsu International Joint Laboratory on System Modeling and Data Analysis Nanjing University of Information Science and Technology Nanjing210044 China

Convolution theorems for the free metaplectic transformation (FMT) have great significance in the fields of fractional domain non-stationary signal processing theory and method. The existing results have found many applications in high-dimensional non-stationary signal sampling and filtering. However, a widely accepted closed-form expression has not yet been established. In this paper, we introduce the definitions of generalized convolution and product operators in the FMT domain, and use them to formulate the generalized convolution and product theorems for the FMT. The derived results include particular cases the existing convolution and product theorems for the FMT and also the convolution and product theorems for the Fourier transform, the fractional Fourier transform, and the linear canonical transform. We employ the generalized convolution theorem for the FMT in designing an optimal filter in the FMT domain. We also validate the correctness and effectiveness of the theoretical analysis through numerical experiments, demonstrating the superiority of the proposed optimal filtering method over the conventional ones. © 2023, The Authors. All rights reserved.

关键词： Convolution

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The Warm Arctic-Cold Eurasia Pattern and Its Key Region in Winter in CMIP6 Model Simulations

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Advances in Atmospheric sciences 2023年第12期40卷 2138-2153,I0002-I0006页

作者： Liang ZHAO Yunwen LIU Yihui DING Qingquan LI Wei DONG Xinyong SHEN Wei CHENG Haoxin YAO Ziniu XIAO State Key Laboratory of Numerical Modeling for Atmosphere Sciences and Geophysical Fluid Dynamics(LASG) Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing 100029China Key Laboratory of Meteorological Disaster Ministry of Education/Joint International Research Laboratory of Climate and Environment Change/Collaborative Innovation Center on Forecast and Evaluation of Meteorological DisastersNanjing University of Information Science and TechnologyNanjing 210044China Neijiang Meteorological Bureau Neijiang 641000China China Meteorological Administration National Climate CenterBeijing 100081China Key Laboratory of Geoscience Big Data and Deep Resource of Zhejiang Province School of Earth SciencesZhejiang UniversityHangzhou 310058China Southern Marine Science and Engineering Guangdong Laboratory(Zhuhai) Zhuhai 519082China Beijing Institute of the Applied Meteorology Beijing 100029China

An enhanced Warm Arctic-Cold Eurasia(WACE)pattern has been a notable feature in recent winters of the Northern ***,divergent results between model and observational studies of the WACE still *** study evaluates the performance of 39 climate models participating in the Coupled Model Intercomparison Project Phase 6(CMIP6)in simulating the WACE pattern in winter of 1980-2014 and explores the key factors causing the differences in the simulation capability among the *** results show that the multimodel ensemble(MME)can better simulate the spatial distribution of the WACE pattern than most single *** that can/cannot simulate both the climatology and the standard deviation of the Eurasian winter surface air temperature well,especially the latter,usually can/cannot simulate the WACE pattern *** mainly results from the different abilities of the models to simulate the range and intensity of the warm anomaly in the Barents Sea-Kara seas(BKS)*** analysis shows that a good performance of the models in the BKS area is usually related to their ability to simulate location and persistence of Ural blocking(UB),which can transport heat to the BKS region,causing the warm Arctic,and strengthen the westerly trough downstream,cooling central ***,simulation of UB is key and significantly affects the model’s performance in simulating the WACE.

关键词： warm Arctic-cold Eurasia pattern Arctic amplification CMIP6 simulation evaluation extreme climate blocking highs

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Adaptive Statistical Spatial Downscaling of Precipitation Supported by High-Resolution Atmospheric Simulation data for Mountainous Areas of Nepal

引用

Journal of Meteorological Research 2023年第4期37卷 508-520页

作者： Hua YANG Kun YANG Jun QIN Baohong DING Yaozhi JIANG Yingying CHEN Xu ZHOU Yan WANG Shankar SHARMA National Tibetan Plateau Data Center State Key Laboratory of Tibetan Plateau Earth SystemEnvironment and ResourcesInstitute of Tibetan Plateau ResearchChinese Academy of SciencesBeijing 100101 University of Chinese Academy of Sciences Beijing 100049 Ministry of Education Key Laboratory for Earth System Modeling Department of Earth System ScienceInstitute for Global Change StudiesTsinghua UniversityBeijing 100084 State Key Laboratory of Resources and Environmental Information System Institute of Geographic Sciences and Natural Resources ResearchChinese Academy of SciencesBeijing 100101 Key Laboratory of Land Surface Pattern and Simulation Institute of Geographic Sciences and Natural Resources ResearchChinese Academy of SciencesBeijing 100101

In complex terrain regions, it is very challenging to obtain high accuracy and resolution precipitation data that are required in land hydrological studies. In this study, an adaptive precipitation downscaling method is proposed based on the statistical downscaling model MicroMet. A key input parameter in the MicroMet is the precipitation adjustment factor(PAF) that shows the elevation dependence of precipitation. Its value is estimated conventionally based on station observations and suffers sparse stations in high altitudes. This study proposes to estimate the PAF value and its spatial variability with precipitation data from high-resolution atmospheric simulations and tests the idea in Nepal of South Himalayas, where rainfall stations are relatively dense. The result shows that MicroMet performs the best with the PAF value estimated from the simulation data at the scale of approximately 1.5 degrees. Not only the value at this scale is qualitatively consistent with early knowledge obtained from intensive observations, but also the downscaling performance with this value is better than or comparable to that with the PAF estimated from dense station data. Finally, it is shown that the PAF estimation, although critical, cannot replace the importance of increasing input station density for downscaling.

关键词： precipitation statistical downscaling precipitation adjustment factor adaptive estimation high resolution dynamical downscaling

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Linn: A Lightweight Image Hiding Method Based on Invertible Neural Network

SSRN

引用

SSRN 2024年

作者： Cheng, Dapeng Zhu, Minghui Mao, Yanyan Gao, Xiaolian Jing, Wanting Kong, Yue Li, Jinjiang School of Computer Science and Technology Shandong Technology and Business University Shandong Yantai264005 China Yantai Key Laboratory of Big Data Modeling and Intelligent Computingy Shandong Yantai264005 China School of Information and Electronic Engineering Shandong Technology and Business University Shandong Yantai264005 China

Image steganography aims to conceal a secret image within a cover image, allowing only those who are informed can recover it. Compared to ordinary steganography, image steganography not only demands the recovered secret image to closely resemble the original image while keeping the stego image well concealed, but also requires a larger capacity. Existing image hiding methods based on invertible neural network have met this requirement, but they generally have a large number of parameters, the complexity of the model is high. In this paper, we propose a lightweight image hiding framework based on invertible neural network called LINN. This framework incorporates the idea of residuals, aiming to minimize the network depth while ensuring image quality. Additionally, it incorporates a spatial attention module, enabling adaptive identiffcation of regions more suitable for concealing secret images. We also try to ensure that the spatial domain and frequency domain of the original image and the image processed by the model are consistent through loss function. Experimental results demonstrate that the method proposed in this paper has stronger generalization ability and a smaller number of parameters, and the image quality generated is better than that generated by other existing methods, while having higher security. © 2024, The Authors. All rights reserved.

关键词： Image quality

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