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Simultaneous segmentation and classification of lung CT scans for COVID-19 diagnosis: a deep multi-task learning perspective

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Neural Computing and Applications 2025年第6期37卷 4185-4205页

作者： Kordnoori, Shirin Sabeti, Maliheh Mostafaei, Hamidreza Banihashemi, Saeed Seyed Agha Department of Computer Engineering North Tehran Branch Islamic Azad University Tehran Iran Department of Statistics North Tehran Branch Islamic Azad University Tehran Iran Department of Mathematics North Tehran Branch Islamic Azad University Tehran Iran

In response to the pressing need for intelligent systems to identify COVID-19 cases and detect infected areas in lung CT scan images during the ongoing pandemic, there is a growing demand for integrated solutions that can effectively handle both segmentation and classification tasks simultaneously. Such systems can provide valuable support to clinicians while enhancing diagnostic accuracy by leveraging shared features. This paper introduces a multi-task architecture designed to concurrently process lung CT scan images for both segmentation and classification tasks. The proposed approach initially employs a shared encoder–decoder architecture based on U-Net, augmented by an additional branch dedicated to classification using a perceptron. To address performance disparities between these tasks during preprocessing, a combination of binary preprocessing algorithms is introduced to establish task equilibrium. Furthermore, convolution block attention module is incorporated into the encoder levels to enhance inter-task coherence. Additionally, the application of conditional random field serves for post-processing in the segmentation task. The effectiveness of the proposed structure is evaluated across four datasets, demonstrating its superiority over previous studies and pre-trained models. The results showcase the highest classification accuracy at 98.14 ± 1.00, accompanied by a Dice index of 89.91 ± 2.00 in segmentation, alongside other relevant evaluation metrics. Furthermore, the multi-task framework is successfully applied to U-Net++ and ResUNet architectures, yielding favorable outcomes. Our proposed model provides a robust solution for accurate COVID-19 analysis, offering valuable support to medical professionals in making diagnostic and treatment decisions. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2024.

关键词： COVID-19

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Thermal analysis of chemically reactive MHD flow through rotating horizontal channel in the existence of Hall current and radiation 5

Thermal analysis of chemically reactive MHD flow through rot...

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5th National Conference on Recent Advancement in Physical Sciences, NCRAPS 2023

作者： Saboo, Ruchi Sharma, Pooja Chaudhary, Ravi Sharma, Tarun S.S. Jain Subodh P.G. Mahila Mahavidyalaya Jaipur India Department of Mathematics & Statistics Manipal University Jaipur India Department of Mathematics University of Engineering & Management Jaipur India

The current work aims to analyze the chemically reactive, MHD convective flow through the horizontal porous (Darcy’s model) channel, which rotates in its plane due to radiation and hall current existence. The flow prototype is designed, and equations are formed and the closed-form results are achieved. In addition, non-dimensional quantities (such as;shear stress, Nusselt and Sherwood numbers) are explored for concerned flow constraints. It is perceived that velocity detracts in the x and y direction with the rise in the parameter of rotation, and the temperature field decreases with the growth in radiation, heat source and Prandtl number. The concentration profile abruptly increases due to the growth in a chemical reaction. This work finds notable applications in the engineering domain. © 2024 Published under licence by IOP Publishing Ltd.

关键词： Shear stress

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Sparse Network Mean Field Games: Ring Structures and Related Topologies 63

Sparse Network Mean Field Games: Ring Structures and Related...

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63rd IEEE Conference on Decision and Control, CDC 2024

作者： Caine, Peter E. Huang, Minyi McGill University Department of Electrical and Computer Engineering MontrealQC Canada Carleton University School of Mathematics and Statistics OttawaON Canada

ISBN: (纸本)9798350316339

For sequences of networks embedded in the unit cube [0,1]m, (weak) measure limits of sequences of empirical measures of vertex densities (vertexon functions) exist, and the associated (weak) measure limits of sequences of empirical measures of edge densities (graphexon functions) in [0,1]2 m exist, regardless of the sparsity or density of the limit graphs. This paper presents an extension of Graphon Mean Field Game (GMFG) theory to the vertexon-graphexon MFG setup (denoted GXMFG). Specific second order dynamics are introduced for the inter-node influence mediated by the singular part of a network graphexon measure;this is analyzed in the particular cases of a network limit ring topology and a limit rectangular lattice topology. Existence and uniqueness results are presented for the corresponding GXMFG equations. © 2024 IEEE.

关键词： Network topology

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Physical aspects of magnetized Jeffrey nanomaterial flow with irreversibility analysis

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Chinese Physics B 2022年第8期31卷 485-493页

作者： Fazal Haq Muhammad Ijaz Khan Sami Ullah Khan Khadijah M Abualnaja M A El-Shorbagy Department of Mathematics Karakoram International University Main CampusGilgit 15100Pakistan Department of Mathematics and Statistics Riphah International University I-14Islamabad 44000Pakistan Department of Mechanics and Engineering Science Peking UniversityBeijing 100871China Department of Mathematics COMSATS University IslamabadSahiwal 57000Pakistan Department of Mathematics and Statistics College of ScienceTaif UniversityP.O.Box 11099Taif 21944Saudi Arabia Department of Mathematics College of Science and Humanities in Al-KharjPrince Sattam bin Abdulaziz UniversityAl-Kharj 11942Saudi Arabia Department of Basic Engineering Science Faculty of EngineeringMenoufia UniversityShebin El-Kom 32511Egypt

This research presents the applications of entropy generation phenomenon in incompressible flow of Jeffrey nanofluid in the presence of distinct thermal features. The novel aspects of various features, such as Joule heating, porous medium,dissipation features, and radiative mechanism are addressed. In order to improve thermal transportation systems based on nanomaterials, convective boundary conditions are introduced. The thermal viscoelastic nanofluid model is expressed in terms of differential equations. The problem is presented via nonlinear differential equations for which analytical expressions are obtained by using the homotopy analysis method(HAM). The accuracy of solution is ensured. The effective outcomes of all physical parameters associated with the flow model are carefully examined and underlined through various curves. The observations summarized from current analysis reveal that the presence of a permeability parameter offers resistance to the flow. A monotonic decrement in local Nusselt number is noted with Hartmann number and Prandtl ***, entropy generation and Bejan number increases with radiation parameter and fluid parameter.

关键词： Jeffrey nonmaterial entropy generation magnetohydrodynamics(MHD) Bejan number porous medium Brownian motion

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Explainable Conformer Network for Detection of COVID-19 Pneumonia from Chest CT Scan: From Concepts toward Clinical Explainability

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Computers, Materials & Continua 2024年第1期78卷 1171-1187页

作者： Mohamed Abdel-Basset Hossam Hawash Mohamed Abouhawwash S.S.Askar Alshaimaa A.Tantawy Faculty of Computers and Informatics Zagazig UniversityZagazig44519Egypt Department of Computational Mathematics Scienceand Engineering(CMSE)Michigan State UniversityEast LansingMI48824USA Department of Mathematics Faculty of ScienceMansoura UniversityMansoura35516Egypt Department of Statistics and Operations Research College of ScienceKing Saud UniversityP.O.Box 2455Riyadh11451Saudi Arabia

The early implementation of treatment therapies necessitates the swift and precise identification of COVID-19 pneumonia by the analysis of chest CT *** study aims to investigate the indispensable need for precise and interpretable diagnostic tools for improving clinical decision-making for COVID-19 *** paper proposes a novel deep learning approach,called Conformer Network,for explainable discrimination of viral pneumonia depending on the lung Region of Infections(ROI)within a single modality radiographic CT ***,an efficient U-shaped transformer network is integrated for lung image ***,a robust transfer learning technique is introduced to design a robust feature extractor based on pre-trained lightweight Big Transfer(BiT-L)and finetuned on medical data to effectively learn the patterns of infection in the input ***,this work presents a visual explanation method to guarantee clinical explainability for decisions made by Conformer *** evaluation of real-world CT data demonstrated that the diagnostic accuracy of ourmodel outperforms cutting-edge studies with statistical *** Conformer Network achieves 97.40% of detection accuracy under cross-validation *** model not only achieves high sensitivity and specificity but also affords visualizations of salient features contributing to each classification decision,enhancing the overall transparency and trustworthiness of our *** findings provide obvious implications for the ability of our model to empower clinical staff by generating transparent intuitions about the features driving diagnostic decisions.

关键词： Deep learning COVID-19 multi-modal medical image fusion diagnostic image fusion

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Mathematical Dynamics of Meningococcal Meningitis: Examining Carrier Diagnosis and Prophylaxis Treatment

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International Journal of Applied and Computational mathematics 2025年第2期11卷 1-29页

作者： Mustapha, Umar Tasiu Muhammad, Aliyu Iliyasu Yusuf, Abdullahi Althobaiti, Nesreen Aliyu, Aliyu Isa Andrawus, James Department of Mathematics Federal University Dutse Jigawa 7156 Nigeria Department of Mathematics Firat University Elazig Turkey Department of Mathematics Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Saveetha University Tamil Nadu Chennai 602105 India Faculty of Engineering and Natural Sciences Istanbul Okan University Istanbul Turkey Department of Mathematics and Statistics College of Science Taif University Taif 11099 Saudi Arabia Operational Research Centre in Healthcare Near East University TRNC Nicosia Turkey

Meningococcal meningitis remains a persistent public health challenge with widespread implications. This paper delves into the sometimes-underrated carrier class, comprising approximately 10% of the population, recognized as the primary source of the overall disease transmission. The challenge lies in the complex task of identifying these asymptomatic carriers in real-world scenarios, as they appear healthy, thus diminishing their incentive for treatment. This study underscores the necessity of proactive measures for individuals who have come into contact with a meningitis patient, emphasizing the importance of meningitis testing or CDC-recommended chemoprophylaxis treatment. In this study, we design a dynamic of Meningococcal Meningitis outbreak, incorporating vaccination, undiagnosed carriers and hospitalisation. We compute basic reproduction number using the generalised next-generation matrix approach and the analysis shows that, the model is globally asymptotically stable for both the DFE and Endemic equilibria. Further analysis indicates the possibility of a backward bifurcation for the system when R0<1. The findings of sensitivity analysis suggest that public health campaigns should prioritize increasing awareness about the significance of diagnosis for carriers of meningococcal meningitis and prophylaxis treatment. This measure will have a significant effect and substantially reduce the spread of the disease. Optimal control analysis shows that, the awareness campaign plays a significant role in controlling the spread of the disease in the community. © The Author(s), under exclusive licence to Springer Nature India Private Limited 2025.

关键词： Basic reproduction number Chemoprophylaxis Diagnosed carriers Meningococcal meningitis Undiagnosed carriers

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Wave energy extraction by an OWC device in the presence of a porous bottom

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Energy Reports 2024年 11卷 5602-5618页

作者： Naik, Nikita Kushwaha, Aman Kumar Behera, Harekrushna Tsai, Chia-Cheng Department of Mathematics SRM Institute of Science and Technology Kattankulathur Chennai603203 India Department of Mathematics Indian Institute of Technology Indore Indore453552 India Center of Excellence for Ocean Engineering National Taiwan Ocean University Keelung202301 Taiwan Bachelor Degree Program in Ocean Engineering and Technology National Taiwan Ocean University Keelung202301 Taiwan

The present study explores the effects of a porous bed on an oscillating water column (OWC) device under the assumptions of the linearized water wave theory and small-amplitude of the surface waves. The velocity potentials in each region have been determined by using the far-field and boundary conditions. To tackle the physical problem, two different mathematical techniques have been employed: the boundary element method (BEM) and the matched eigenfunction expansion method (EEM). The findings of the study are validated by the existing literature. The outcomes of the numerical results and analytical results are in good agreement. It is noted that as the width of the chamber increases, there is an increase in radiation conductance and a decrease in radiation susceptance. The zero efficiencies are observed multiple times as the width of the OWC device increases with respect to the dimensionless wavenumber. Moreover, the study reveals that full efficiency can be obtained by an OWC device over a porous bed for certain wave and structural parameters as obtained in the presence of an impermeable bottom. The proposed model can help to design and develop a successful OWC device. © 2024

关键词： Boundary element method

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Fully-Decoupled and Second-Order Time-Accurate Scheme for the Cahn–Hilliard Ohta–Kawaski Phase-Field Model of Diblock Copolymer Melt Confined in Hele–Shaw Cell

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Communications in mathematics and statistics 2024年第3期12卷 479-504页

作者： Junying Cao Jun Zhang Xiaofeng Yang School of Data Science and Information Engineering Guizhou Minzu UniversityGuiyang 550025People’s Republic of China Guizhou Key Laboratory of Big Data Statistics Analysis Computational Mathematics Research CenterGuizhou University of Finance and EconomicsGuiyang 550025People’s Republic of China Department of Mathematics University of South CarolinaColumbiaSCUSA

In this work,we consider numerical approximations of the phase-field model of diblock copolymer melt confined in Hele–Shaw cell,which is a very complicated coupled nonlinear system consisting of the Darcy equations and the Cahn–Hilliard type equations with the Ohta–Kawaski *** the combination of a novel explicit-Invariant Energy Quadratization approach and the projection method,we develop the first full decoupling,energy stable,and second-order time-accurate numerical *** introduction of two auxiliary variables and the design of two auxiliary ODEs play a vital role in obtaining the full decoupling structure while maintaining energy *** scheme is also linear and unconditional energy stable,and the practical implementation efficiency is also very high because it only needs to solve a few elliptic equations with constant coefficients at each time *** strictly prove that the scheme satisfies the unconditional energy stability and give a detailed implementation *** experiments further verify the convergence rate,energy stability,and effectiveness of the developed algorithm.

关键词： Phase-field Explicit-IEQ Darcy Decoupled Energy Stability Diblock copolymer melt

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Data-Driven Learning of the Generalized Langevin Equation with State-Dependent Memory

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Physical Review Letters 2024年第7期133卷 077301-077301页

作者： Pei Ge Zhongqiang Zhang Huan Lei Department of Computational Mathematics Science and Engineering Department of Mathematical Sciences Department of Statistics and Probability

We present a data-driven method to learn stochastic reduced models of complex systems that retain a state-dependent memory beyond the standard generalized Langevin equation with a homogeneous kernel. The constructed model naturally encodes the heterogeneous energy dissipation by jointly learning a set of state features and the non-Markovian coupling among the features. Numerical results demonstrate the limitation of the standard generalized Langevin equation and the essential role of the broadly overlooked state-dependency nature in predicting molecule kinetics related to conformation relaxation and transition.

关键词： Coarse graining Machine learning Multiscale modeling

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Paradoxical roles of inhibitory autapse and excitatory synapse in formation of counterintuitive anticipated synchronization

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Chinese Physics B 2023年第8期32卷 499-509页

作者：丁学利古华光李玉叶贾雁兵 Department of Public Basic Education Fuyang Institute of TechnologyFuyang 236031China School of Aerospace Engineering and Applied Mechanics Tongji UniversityShanghai 200092China College of Mathematics and Computer Science Chifeng UniversityChifeng 024000China School of Mathematics and Statistics Henan University of Science and TechnologyLuoyang 471000China

Different from the common delayed synchronization(DS)in which response appears after stimulation,anticipated synchronization(AS)in unidirectionally coupled neurons denotes a counterintuitive phenomenon in which response of the receiver neuron appears before stimulation of the sender neuron,showing an interesting function of brain to anticipate the *** dynamical mechanism for the AS remains unclear due to complex dynamics of inhibitory and excitatory *** this article,the paradoxical roles of excitatory synapse and inhibitory autapse in the formation of AS are ***,in addition to the common roles such that inhibitory modulation delays and excitatory modulation advances spike,paradoxical roles of excitatory stimulation to delay spike via type-II phase response and of inhibitory autapse to advance spike are obtained in suitable parameter regions,extending the dynamics and functions of the excitatory and inhibitory ***,AS is related to the paradoxical roles of the excitatory and inhibitory modulations,presenting deep understandings to the *** autapse induces spike of the receiver neuron advanced to appear before that of the sender neuron at first,and then excitatory synapse plays a delay role to prevent the spike further advanced,resulting in the AS as the advance and delay effects realize a dynamic ***,inhibitory autapse with strong advance,middle advance,and weak advance and delay effects induce phase drift(spike of the receiver neuron advances continuously),AS,and DS,respectively,presenting comprehensive relationships between AS and other *** results present potential measures to modulate AS related to brain function.

关键词： anticipated synchronization inhibitory autapse excitatory synapse paradoxical firing

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