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SSRN 2024年

作者： Zhang, Guangxin Wang, Minzhen Meng, Xianfa Zheng, Yan Cheng, Shichao Wang, Jian Changchun University of Architecture and Civil Engineering Sheling University Park Shuangyang District Jilin Province Changchun City China State Grid Liaoning Electric Power Co. LTD. Dalian power supply company Liaoning Province Dalian116000 China 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

In this paper, a novel method is proposed, which is suitable for shape transformation. This method is based on Lengyel-Epstein (LE) model, which is condensed from the Chlorite—Iodide—Malonic Acid (CIMA) chemical reactions. A minor adjustment to the original LE model is that $v_0-v$ replaces $u$ in the system. Five point difference scheme and seven point difference scheme are adopted to discrete the Laplace operator in two-dimensional (2D) and three-dimensional (3D) space. Meanwhile, the explicit Euler's method is considered to solve the discrete system. Through a series of numerical experiments, it is demonstrated that shape transformation can be effectively achieved in both 2D and 3D spaces using the proposed model. Additionally, we simulated the denoising process and performed image segmentation. Therefore, the modified LE model offers a novel approach applicable to a variety of tasks. © 2024, The Authors. All rights reserved.

关键词： Image segmentation

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Optimal Harvest for Predator-Prey Fishery Models with Variable Price and Marine Protected Area

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SSRN 2023年

作者： Chu, Cheng Liu, Wenjun Lv, Guangying Auger, Pierre Moussaoui, Ali School of Mathematics and Statistics Nanjing University of Information Science and Technology Nanjing210044 China Jiangsu International Joint Laboratory on System Modeling and Data Analysis Center for Applied Mathematics of Jiangsu Province Nanjing University of Information Science and Technology Nanjing210044 China UMMISCO Sorbonne Université Institut de Recherche pour le Développement IRD BondyF-93143 France Laboratoire d’Analyse Non Linéaire et Mathématiques Appliquées Department of Mathematics Faculty of Science University of Tlemcen 13000 Algeria

In this paper, we propose a predator-prey fishery model with prey harvesting, variable price and marine protected area. We assume the price changes faster than other processes such as population growth and predation, and get a slow fast ODE system. A simplified three-dimensional model is obtained by using approximate aggregation methods. The results show that there are two main scenarios, one is the depletion of fish stocks due to overfishing by fishermen, which is called a catastrophic equilibrium;and the other is a stable and sustainable fishery equilibrium. In order to avoid the extinction of fish, we consider establishing marine protected area (MPA) near fishing areas where fishermen only catch the prey. The results of the study provide the conditions for the establishment of MPA, allowing us to avoid the extinction of prey populations and establish sustainable fisheries. As another possibility, we consider increasing taxes to discourage overfishing by fishermen. In addition, when the tax revenue increases, the optimal harvest strategy is obtained. The optimal policy ensures the sustainable development of fisheries and maximizes the interests of fishermen. © 2023, The Authors. All rights reserved.

关键词： Fisheries

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Sustainable Management of Predatory Fish Affected by an Allee Effect Through Marine Protected Areas Andtaxation

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SSRN 2023年

作者： Yuan, Xiaoyue Liu, Wenjun Lv, Guangying Auger, Pierre Moussaoui, Ali School of Mathematics and Statistics Nanjing University of Information Science and Technology Nanjing210044 China Jiangsu International Joint Laboratory on System Modeling and Data Analysis Center for Applied Mathematics of Jiangsu Province Nanjing University of Information Science and Technology Nanjing210044 China UMMISCO Sorbonne Université Institut de Recherche pour le Développement IRD BondyF-93143 France Laboratoire d’Analyse Non Linéaire et Mathématiques Appliquées Department of Mathematics Faculty of Science University of Tlemcen Tlemcen13000 Algeria

In this work, we present a prey-predator model of marine community with predator harvesting in an environment made up of two sites connected by fast migrations of prey and predator. We assume that the prey grows logistically at each site, and further hypothesize that the growth of predators obeys an Allee effect in the absence of prey. The model takes into account the variation in the price of the resource under the effect of supply and demand. We use methods of aggregation of variables to derive a three-dimensional simplified model that governs prey fish biomass, predator biomass and fishing effort of the fishery. We study the effects of the installation of a marine protected area as well as taxation per unit of catch on the dynamics of the fishery in the long term. We seek conditions to avoid the extinction of species and maintain sustainable fishing activity. We carry out the analysis of the reduced model, consider the existence of positive equilibrium points, and look for the local and global stability. Our numerical simulations of the model with marine protected area show that it can protect fish stocks and notably avoid predator extinction. In addition, we consider the effect of a tax per unit of catch with the aim of limiting overfishing. We obtain the best tax policy by applying Pontryagin’s maximum principle with the aim of ensuring a good balance allowing the maintenance of the ecological community and sustainable economic development. © 2023, The Authors. All rights reserved.

关键词： Fisheries

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Heterogeneous bacterial swarms with mixed lengths

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Physical Review E 2021年第3期103卷 032413-032413页

作者： Shlomit Peled Shawn D. Ryan Sebastian Heidenreich Markus Bär Gil Ariel Avraham Be'er Zuckerberg Institute for Water Research The Jacob Blaustein Institutes for Desert Research Ben-Gurion University of the Negev Sede Boqer Campus 84990 Midreshet Ben-Gurion Israel Department of Mathematics and Statistics Cleveland State University Cleveland Ohio 44115 USA Center for Applied Data Analysis and Modeling Cleveland State University Cleveland Ohio 44115 USA Department of Mathematical Modelling and Data Analysis Physikalisch-Technische Bundesanstalt Braunschweig und Berlin Abbestrasse 2-12 D-10587 Berlin Germany Department of Mathematics Bar-Ilan University Ramat Gan 52900 Israel Department of Physics Ben-Gurion University of the Negev 84105 Beer-Sheva Israel

Heterogeneous systems of active matter exhibit a range of complex emergent dynamical patterns. In particular, it is difficult to predict the properties of the mixed system based on its constituents. These considerations are particularly significant for understanding realistic bacterial swarms, which typically develop heterogeneities even when grown from a single cell. Here, mixed swarms of cells with different aspect ratios are studied both experimentally and in simulations. In contrast with previous theory, there is no macroscopic phase segregation. However, locally, long cells act as nucleation cites, around which aggregates of short, rapidly moving cells can form, resulting in enhanced swarming speeds. On the other hand, high fractions of long cells form a bottleneck for efficient swarming. Our results suggest a physical advantage for the spontaneous heterogeneity of bacterial swarm populations.

关键词： Biological complexity Biological movement Cell growth Cell locomotion Cell migration Collective behavior Swimming Bacteria

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Non-invasive Cardiac Output Monitoring in Congenital Heart Disease

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Current Treatment Options in Pediatrics 2023年第4期9卷 247-259页

作者： Tandon, Animesh Bhattacharya, Sarnab Morca, Ayse Inan, Omer T Munther, Daniel S Ryan, Shawn D Latifi, Samir Q Lu, Nanshu Lasa, Javier J Marino, Bradley S Baloglu, Orkun Department of Heart Vascular and Thoracic Division of Cardiology and Cardiovascular Medicine Children’s Institute Cleveland Clinic Children’s Cleveland OH United States Cleveland Clinic Children’s Center for Artificial Intelligence (C4AI) Department of Heart Vascular and Thoracic Children’s Institute Cleveland Clinic Children’s Cleveland OH United States Department of Pediatrics Cleveland Clinic Lerner College of Medicine of Case Western Reserve University Cleveland OH United States Department of Biomedical Engineering Cleveland Clinic Lerner Research Institute and Case School of Engineering at Case Western Reserve University Cleveland OH United States Department of Electrical and Computer Engineering The University of Texas at Austin Austin 78712 TX United States Department of Integrated Hospital Care Division of Critical Care Children’s Institute Cleveland Clinic Children’s Cleveland OH United States School of Electrical and Computer Engineering Georgia Institute of Technology Atlanta GA United States Department of Mathematics and Statistics Cleveland State University Cleveland 44115 OH United States Center for Applied Data Analysis and Modeling Cleveland State University Cleveland 44115 OH United States Department of Aerospace Engineering and Engineering Mechanics Texas Materials Institute The University of Texas at Austin Austin 78712 TX United States Department of Biomedical Engineering The University of Texas at Austin Austin 78712 TX United States Department of Mechanical Engineering Texas Materials Institute The University of Texas at Austin Austin 78712 TX United States Divisions of Cardiology and Critical Care Department of Pediatrics Children’s Medical Center UT Southwestern Medical Center Dallas TX United States

Purpose of review: Cardiac output (CO) is a fundamental physiological parameter that measures the volume of blood that is pumped by the heart per unit of time, and helps define how oxygen is delivered to the tissues of the human body. In this paper, we discuss current methods of continuous CO monitoring while defining low CO syndrome (LCOS) and how analytical tools may help improve CO management in the subpopulation of patients with congenital heart disease (CHD). Recent findings: Non-invasive methods of measuring CO have become increasingly available in recent years. Advantages of non-invasive over invasive techniques include decreased risk of procedural complications, decreased exposure to sedative and/or anesthetic agents, and increased patient comfort. Pediatric patient populations are particularly sensitive to the risks and complications of invasive techniques given the relative size of current technologies to pediatric vascular and cardiac dimensions. Summary: Novel device technologies, combined with emerging analytical techniques, may help improve measurement of CO in children and those with CHD, and allow earlier detection of LCOS. © 2023, The Author(s).

关键词： Cardiac index Cardiac output Congenital heart disease Non-invasive continuous cardiac output monitoring

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Brain MRIs classification based on 2D SWD-MF-DFA

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Journal of Neuroscience Methods 2025年 421卷 110468页

作者： Wang, Jing Wu, Xinpei Wang, Haozhe Wang, Jian School of Mathematics and Statistics Nanjing University of Information Science and Technology Nanjing 210044 China Reading Academy Nanjing University of Information Science and Technology Nanjing 210044 China Center for Applied Mathematics of Jiangsu Province Nanjing University of Information Science and Technology Nanjing 210044 China Jiangsu International Joint Laboratory on System Modeling and Data Analysis Nanjing University of Information Science and Technology Nanjing 210044 China

Background: To improve imaging classification accuracy, we modify the traditional 2D multifractal trend fluctuation analysis (MF-DFA) method to better preserve local feature values. Inspired by MF-DFA, we develop a novel method for extracting eigenvalues, enhancing the precision of imaging analysis. New method: In this paper, we propose an enhanced algorithm building upon the traditional 2D MF-DFA. Our approach introduces a 2D sliding window (SWD) technique for feature value extraction. Initially, the local generalized Hurst index of the imaging is derived using the SWD algorithm, based on MF-DFA principles. Subsequently, the generalized Hurst index is recalculated for the digital matrix formed by these local Hurst indexes. These vectors are then input into a support vector machine (SVM) for classification. This methodology seeks to refine the traditional 2D MF-DFA by more effectively preserving local feature values in imaging. Results: The classification accuracy of the SWD eigenvalue extraction method based on 2D MF-DFA reaches 91.54%. Comparison with existing methods: We employ brain magnetic resonance imaging (MRI) data sets to evaluate the efficacy of both the conventional 2D MF-DFA method and our proposed feature value extraction technique. Both methods are applied alongside a SVM for classification. The findings reveal that the conventional 2D MF-DFA method yields a classification accuracy of 59.40%, while our SWD feature value extraction method attains a classification accuracy of 91.54%. Conclusion: This substantial performance enhancement underscores the superiority of the SWD approach over the conventional method. © 2025 Elsevier B.V.

关键词： 2D MF-DFA 2D SWD MRI SVM

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Anthropogenic emission is the main contributor to the rise of atmospheric methane during 1993-2017

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National Science Review 2022年第5期9卷 154-166页

作者：张臻 Benjamin Poulter Sara Knox Ann Stavert Gavin McNicol Etienne Fluet-Chouinard Aryeh Feinberg 赵园红 Philippe Bousquet Josep G.Canadell Anita Ganesan Gustaf Hugelius George Hurtt Robert B.Jackson Prabir K.Patra Marielle Saunois Lena H?glund-Isaksson 黄春林 Abhishek Chatterjee 李新 Department of Geographical Sciences University of Maryland Biospheric Sciences Laboratory NASA Goddard Space Flight Center Department of Geography University of British Columbia Global Carbon Project CSIRO Oceans and Atmosphere Department of Earth and Environmental Sciences University of Illinois Chicago Department of Earth System Science Stanford University Institute for Data Systems and Society Massachusetts Institute of Technology College of Oceanic and Atmospheric Sciences Ocean University of China Laboratoire des Sciences du Climat et de l’Environment LSCE-IPSL (CEA-CNRS-UVSQ)Université Paris-Saclay School of Geographical Sciences University of Bristol Department of Physical Geography and Bolin Centre for Climate Research Stockholm University Woods Institute for the Environment and Precourt Institute for Energy Stanford University Research Institute for Global Change JAMSTEC International Institute for Applied Systems Analysis (IIASA) Northwest Institute of Eco-Environment and Resources Chinese Academy of Sciences Global Modeling and Assimilation Office NASA Goddard Space Flight Center Universities Space Research Association Institute of Tibetan Plateau Research Chinese Academy of Sciences

Atmospheric methane（CH4） concentrations have shown a puzzling resumption in growth since 2007 following a period of stabilization from 2000 to *** hypotheses have been proposed to explain the temporal variations in CH4growth,and attribute the rise of atmospheric CH4either to increases in emissions from fossil fuel activities,agriculture and natural wetlands,or to a decrease in the atmospheric chemical ***,we use a comprehensive ensemble of CH4source estimates and isotopic δ13C-CH4source signature data to show that the resumption of CH4growth is most likely due to increased anthropogenic *** emission scenarios that have the fewest biases with respect to isotopic composition suggest that the agriculture,landfill and waste sectors were responsible for 53±13% of the renewed growth over the period 2007-2017 compared to 2000-2006;industrial fossil fuel sources explained an additional 34 ±24%,and wetland sources contributed the least at 13 ±9%.The hypothesis that a large increase in emissions from natural wetlands drove the decrease in atmospheric δ13C-CH4values cannot be reconciled with current process-based wetland *** finding suggests the need for increased wetland measurements to better understand the contemporary and future role of wetlands in the rise of atmospheric methane and climate *** findings highlight the predominant role of anthropogenic activities in driving the growth of atmospheric CH4concentrations.

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Anthropogenic emission is the main contributor to the rise of atmospheric methane during 1993-2017

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国家科学评论（英文版） 2022年第5期9卷 149-161页

作者： Zhen Zhang Benjamin Poulter Sara Knox Ann Stavert Gavin McNicol Etienne Fluet-Chouinard Aryeh Feinberg Yuanhong Zhao Philippe Bousquet Josep G.Canadell Anita Ganesan Gustaf Hugelius George Hurtt Robert B.Jackson Prabir K.Patra Marielle Saunois Lena H?glund-lsaksson Chunlin Huang Abhishek Chatterjee Xin Li Department of Geographical Sciences University of MarylandCollege ParkMD 20742USA Biospheric Sciences Laboratory NASA Goddard Space Flight CenterGreenbeltMD 20771USA Department of Geography University of British ColumbiaVancouver V6T 1Z2Canada Global Carbon Project CSIRO Oceans and AtmosphereCanberraACT 2601Australia Department of Earth and Environmental Sciences University of Illinois ChicagoChicagoIL 60607USA Department of Earth System Science Stanford UniversityStanfordCA 94305USA Institute for Data Systems and SocietyMassachusetts Institute of TechnologyCambridgeMA 02139USA College of Oceanic and Atmospheric Sciences Ocean University of ChinaQingdao 266000China Laboratoire des Sciences du Climat et de I'Environment LSCE-IPSL(CEA-CNRS-UVSQ)Université Paris-SaclayGif-sur-Yvette 91191France School of Geographical Sciences University of BristolBristol BS8 1RLUK Department of Physical Geography and Bolin Centre for Climate Research Stockholm UniversityStockholm SE-10691Sweden Department of Earth System Science Stanford UniversityStanfordCA 94305USA Woods Institute for the Environment and Precourt Institute for Energy Stanford UniversityStanfordCA 94305USA Research Institute for Global Change JAMSTECYokohama 236-0001Japan International Institute for Applied Systems Analysis(IIASA) Laxenburg A-2361Austria Northwest Institute of Eco-Environment and Resources Chinese Academy of SciencesLanzhou 730000China Global Modeling and Assimilation Office NASA Goddard Space Flight CenterGreenbeltMD 20771USA Universities Space Research Association ColumbiaMD 21046USA Institute of Tibetan Plateau Research Chinese Academy of SciencesBeijing 100101China

Atmospheric methane(CH4)concentrations have shown a puzzling resumption in growth since 2007 following a period of stabilization from 2000 to *** hypotheses have been proposed to explain the temporal variations in CH4 growth,and attribute the rise of atmospheric CH4 either to increases in emissions from fossil fuel activities,agriculture and natural wetlands,or to a decrease in the atmospheric chemical ***,we use a comprehensive ensemble of CH4 source estimates and isotopic δ13C-CH4 source signature data to show that the resumption of CH4 growth is most likely due to increased anthropogenic *** emission scenarios that have the fewest biases with respect to isotopic composition suggest that the agriculture,landfill and waste sectors were responsible for 53±13％of the renewed growth over the period 2007-2017 compared to 2000-2006;industrial fossil fuel sources explained an additional 34±24％,and wetland sources contributed the least at 13±9％.The hypothesis that a large increase in emissions from natural wetlands drove the decrease in atmospheric δ13C-CH4 values cannot be reconciled with current process-based wetland CH4 *** finding suggests the need for increased wetland measurements to better understand the contemporary and future role of wetlands in the rise of atmospheric methane and climate *** findings highlight the predominant role of anthropogenic activities in driving the growth of atmospheric CH4 concentrations.

关键词： greenhouse gas carbon cycle climate mitigation wetland methane isotope

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Influence of PEG on the clustering of active janus colloids

arXiv

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arXiv 2021年

作者： Kalil, Mohammed A. Baumgartner, Nicky R. Issa, Marola W. Ryan, Shawn D. Wirth, Christopher L. Department of Chemical and Biomedical Engineering Washkewicz College of Engineering Cleveland State University 2121 Euclid Avenue ClevelandOH44115 United States Department of Mathematics and Statistics College of Science and Health Professions Cleveland State University 2121 Euclid Avenue ClevelandOH44115 United States Department of Chemical and Biomolecular Engineering Case School of Engineering Case Western Reserve University ClevelandOH44106 United States Center for Applied Data Analysis and Modeling Cleveland State University ClevelandOH44115 United States

Micrometer scale "colloidal" particles that propel in a deterministic fashion in response to local environmental cues are useful analogs to self-propelling entities found in nature. Both natural and synthetic active colloidal systems are often near boundaries or are located in crowded environments. Herein, we describe experiments in which we measured the influence of hydrogen peroxide concentration and dispersed polyethylene glycol (PEG) on the clustering behavior of 5 μm catalytic active Janus particles at low concentration. We found the extent to which clustering occurred in ensembles of active Janus particles grew with hydrogen peroxide concentration in the absence of PEG. Once PEG was added, clustering was slightly enhanced at low PEG volume fractions, but was reduced at higher PEG volumes fractions. The region in which clustering was mitigated at higher PEG volume fractions corresponded to the region in which propulsion was previously found to be quenched. Complementary agent based simulations showed that clustering grew with nominal speed. These data support the hypothesis that growth of living crystals is enhanced with increases in propulsion speed, but the addition of PEG will tend to mitigate cluster formation as a consequence of quenched propulsion at these conditions. Copyright © 2021, The Authors. All rights reserved.

关键词： Computational methods

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A systematic review of challenges and proposed solutions in modeling multimodal data

arXiv

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arXiv 2025年

作者： Farhadizadeh, Maryam Weymann, Maria Blaß, Michael Kraus, Johann Gundler, Christopher Walter, Sebastian Hempen, Noah Binder, Harald Binder, Nadine Institute of General Practice/Family Medicine Faculty of Medicine Medical Center University of Freiburg Elsässer Straße 2M Freiburg79110 Germany Freiburg Center for Data Analysis Modeling and AI University of Freiburg Ernst-Zermelo-Str. 1 Freiburg79104 Germany Institute of Medical Biometry and Statistics Faculty of Medicine Medical Center University of Freiburg Stefan-Meier-Straße 26 Freiburg79104 Germany Institute for Applied Medical Informatics University Medical Center Hamburg-Eppendorf Martinistraße 52 Hamburg20251 Germany Institute of Medical Systems Biology Ulm University Helmholtzstraße 16 Ulm89081 Germany Department of Computer Science Faculty of Engineering University of Freiburg Georges-Köhler-Allee 051 Freiburg79110 Germany

Multimodal data modeling has emerged as a powerful approach in clinical research, enabling the integration of diverse data types such as imaging, genomics, wearable sensors, and electronic health records. Despite its potential to improve diagnostic accuracy and support personalized care, modeling such heterogeneous data presents significant technical challenges. This systematic review synthesizes findings from 69 studies to identify common obstacles, including missing modalities, limited sample sizes, dimensionality imbalance, interpretability issues, and finding the optimal fusion techniques. We highlight recent methodological advances, such as transfer learning, generative models, attention mechanisms, and neural architecture search that offer promising solutions. By mapping current trends and innovations, this review provides a comprehensive overview of the field and offers practical insights to guide future research and development in multimodal modeling for medical applications. © 2025, CC BY.

关键词： Clinical research

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