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Dynamic interactions in a two-species model of the mammalian predator–prey system: The influence of Allee effects, prey refuge, water resources, and moonlights

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Partial Differential Equations in applied mathematics 2024年 11卷

作者： Thirthar, Ashraf Adnan Panja, Prabir Majeed, Salam Jasim Nisar, Kottakkaran Sooppy Department of Studies and Planning University of Fallujah Department of Applied Science Haldia Institute of Technology Department of Mathematics College of Computer Science and Mathematics University of Thi-Qar Department of Mathematics College of Science and Humanities Prince Sattam bin Abdulaziz University Hourani Center for Applied Scientific Research Al-Ahliyya Amman University

In this paper, a two-species model of mammalian prey and mammalian predator has been developed. It is assumed that mammalian prey species grow logistically in the absence of the Allee effect and mammalian predator species. It is considered that the growth rate of mammalian prey species is affected by Allee. It is assumed that the consumption of mammalian prey is dependent on prey refuge, water resources, and moonlight. Different dynamical behaviours of the model, such as positivity, uniform boundedness, dissipativeness, uniform persistence, bifurcation analysis, etc., have been studied. The local stability of the model has been studied around the equilibrium points. Global stability of the model around the coexistence equilibrium point has been investigated. Transcritical bifurcation of the model with respect to the death rate of mammalian predators has been studied. Also, the existence conditions of Hopf bifurcation with respect to the conversion rate of mammalian prey has been investigated. It is observed that the increased visibility during moonlit nights can significantly impact the hunting success of mammalian predators and the survival strategies of mammalian prey. It is seen that water resources play a crucial role in shaping the dynamics between mammalian prey and predator species. It is found that a moderate increase in the Allee effect can stabilize populations by enhancing cooperation and survival at low densities, a higher rate of increase can lead to severe instability and potential population crashes Finally, some numerical simulation results have been presented to validate the analytical findings. © 2024 The Authors

关键词： Allee Bifurcation Mammalian predator Mammalian prey Moonlights Stability Water resources

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Human Activity Recognition for People with Knee Abnormality Using Surface Electromyography and Knee Angle Sensors 8

Human Activity Recognition for People with Knee Abnormality ...

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Joint 8th International Conference on Digital Arts, Media and Technology and 6th ECTI Northern Section Conference on Electrical, Electronics, computer and Telecommunications Engineering, ECTI DAMT and NCON 2023

作者： Mekruksavanich, Sakorn Jantawong, Ponnipa Hnoohom, Narit Jitpattanakul, Anuchit School of Information and Communication Technology University of Phayao Department of Computer Engineering Phayao Thailand Mahidol University Image Information and Intelligence Laboratory Faculty of Engineering Department of Computer Engineering Nakorn Pathom Thailand King Mongkut's University of Technology North Bangkok Intelligent and Nonlinear Dynamic Innovations Research Center Faculty of Applied Science Department of Mathematics Bangkok Thailand

ISBN: (纸本)9798350396546

With the onset of technological advancements, biosensors are being effectively used in a variety of contexts, including the diagnosis of diseases, the promotion of their prevention and rehabilitation, the monitoring of patient health, and human activity recognition (HAR). Recently, HAR research results have been obtained and applied in many commercial applications such as fall detection using smart watch sensors, activity classification using smart home sensors. However, previous HAR models utilizing wearable sensors primarily utilized data from healthy individuals, and such models are frequently inaccurate when applied to individuals with medical mobility impairments. In this work, surface electromyography and goniometer sensors were used to categorize various types of rehabilitation activities based on HAR models developed for individuals with knee abnormalities. To achieve the goal of our study, a deep residual network called ResNeXt was proposed to detect human activities with high performance. To investigate the classification performance of deep learning models, a 5-fold cross-validation technique was applied for both training and testing. Based on the results of our study, the combination of features extracted from the goniometer and electromyograph signals resulted in the highest F1-score (93.31%) and the best accuracy (93.52%). © 2023 IEEE.

关键词： Deep learning

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Unbiased Parameter Estimation for Partially Observed Diffusions

arXiv

引用

arXiv 2023年

作者： Awadelkarim, Elsiddig Jasra, Ajay Ruzayqat, Hamza Applied Mathematics and Computational Science Program Computer Electrical and Mathematical Sciences and Engineering Division King Abdullah University of Science and Technology Thuwal23955-6900 Saudi Arabia

In this article we consider the estimation of static parameters for partially observed diffusion process with discrete-time observations over a fixed time interval. In particular, we assume that one must time-discretize the partially observed diffusion process and work with the model with bias and consider maximizing the resulting log-likelihood. Using a novel double randomization scheme, based upon Markovian stochastic approximation we develop a new method to unbiasedly estimate the static parameters, that is, to obtain the maximum likelihood estimator with no time discretization bias. Under assumptions we prove that our estimator is unbiased and investigate the method in several numerical examples, showing that it can empirically out-perform existing unbiased *** Codes 60J22, 62M05, 65C40, 62M20 © 2023, CC BY.

关键词： Parameter estimation

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Direct System Identification of Dynamical Networks with Partial Measurements: a Maximum Likelihood Approach

arXiv

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arXiv 2023年

作者： da Mata, João Victor Galvão Hansson, Anders Andersen, Martin S. Department of Applied Mathematics and Computer Science Technical University of Denmark Denmark Department of Electrical Engineering Linköping University Sweden

This paper introduces a novel direct approach to system identification of dynamic networks with missing data based on maximum likelihood estimation. Dynamic networks generally present a singular probability density function, which poses a challenge in the estimation of their parameters. By leveraging knowledge about the network’s interconnections, we show that it is possible to transform the problem into a more tractable form by applying linear transformations. This results in a nonsingular probability density function, enabling the application of maximum likelihood estimation techniques. Our preliminary numerical results suggest that when combined with global optimization algorithms or a suitable initialization strategy, we are able to obtain a good estimate of the dynamics of the internal systems. © 2023, CC BY.

关键词： Maximum likelihood estimation

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An Exploratory Computational Approach for Elucidating a Nonstructural Protein Interaction in Dengue Virus 2

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Procedia computer science 2024年 245卷 470-479页

作者： Alam Ahmad Hidayat Rudi Nirwantono Bens Pardamean Mathematics Department School of Computer Science Bina Nusantara University Indonesia 11480 Biotechnology Department Faculty of Engineering Bina Nusantara University Indonesia 11480 Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta Indonesia 11480 Computer Science Department BINUS Graduate Program Bina Nusantara University Jakarta Indonesia 11480

As the dengue infection still impacts hundreds of millions of people globally, unprecedented efforts in dengue drug development have been more progressive in recent decades. Computational methods provide a fast, sustainable, and efficient screening of active compounds and newly created drug molecules, including those specifically targeting nonstructural proteins (NS) of dengue viruses. In this work, protein modeling for the NS proteins of DENV-2/16681 strain was performed using a template-based homology modeling for the NS3 protein and an Artificial Intelligence (AI)-based prediction via AlphaFold for the NS4B protein. Moreover, the protein-protein interaction between the two structures was predicted using the HADDOCK server, which employs information about active and passive residues of the interaction interface to guide the docking process. After the modeling and its respective refinement process, the predicted structures of NS3 and NS4B improved their steric clashing scoring from MolProbity assessment. The refined models were then docked, and the resulting docking pose was analyzed to extract the interacting residues based on the polar contacts within the interface of the two proteins. Our result presents a preliminary study to create a dataset related to in silico molecular interactions of the NS3-NS4B interaction of different DENV types. It is helpful for building a computational pipeline for elucidating protein-ligand problems in dengue drug screenings.

关键词： bioinformatics computational biology dengue protein docking structural biology

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New developments in MatCont: delay equation importer and Lyapunov exponents

arXiv

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arXiv 2025年

作者： Liessi, Davide Santi, Enrico Vermiglio, Rossana Thakur, Mayank Meijer, Hil G.E. Scarabel, Francesca CDLab – Computational Dynamics Laboratory Department of Mathematics Computer Science and Physics University of Udine Italy Department of Applied Mathematics University of Twente Netherlands School of Mathematics University of Leeds United Kingdom CDLab – Computational Dynamics Laboratory University of Udine Italy

MatCont is a powerful toolbox for numerical bifurcation analysis focussing on smooth ODEs. A user can study equilibria, periodic and connecting orbits, and their stability and bifurcations. Here, we report on additional features in version 7p6. The first is a delay equation importer enabling MatCont users to study a much larger class of models, namely delay equations with finite delay (including delay differential and renewal equations). This importer translates the delay equation into a system of ODEs using a pseudospectral approximation with an order specified by the user. We also implemented Lyapunov exponent computations, event functions for Poincaré maps, and enhanced homoclinic continuation. We demonstrate these features with test cases, such as the Mackey–Glass equation and a renewal equation, and provide additional examples in online tutorials. © 2025, CC BY.

关键词： Bifurcation (mathematics)

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Solutions of fractional differential models by using Sumudu transform method and its hybrid

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Partial Differential Equations in applied mathematics 2024年 11卷

作者： Aibinu, Mathew O. Mahomed, Fazal M. Jorgensen, Palle E. School of Computer Science and Applied Mathematics University of the Witwatersrand Department of Mathematics University of Iowa Mathematics and Statistics University of Regina National Institute for Theoretical and Computational Sciences (NITheCS)

This paper presents the Sumudu transform method and its hybrid for the construction of solutions of differential equations, both with integer-order and fractional derivatives. The paper discusses the construction of solutions of fractional differential equations with varying delay proportional to the independent variable by using two methods. The paper considers the mathematical model for the decay of Iodine 135 as an application of fractional differential equations in nuclear physics. The application indicates that fractional differential equations with variable delay proportional to the independent variable are a useful tool for the modeling of many anomalous phenomena in nature and in the theory of complex systems. © 2024 The Author(s)

关键词： Decay Delay Fractional derivatives Model Sumudu transform

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An Enhanced Levenberg-Marquardt Method via Gram Reduction 39

An Enhanced Levenberg-Marquardt Method via Gram Reduction

引用

39th Annual AAAI Conference on Artificial Intelligence, AAAI 2025

作者： Liu, Chengchang Luo, Luo Lui, John C.S. Department of Computer Science and Engineering The Chinese University of Hong Kong Hong Kong School of Data Science Fudan University China Shanghai Key Laboratory for Contemporary Applied Mathematics China

ISBN: (纸本)157735897X

This paper studies the problem of solving the system of nonlinear equations. We propose the Gram-reduced Levenberg-Marquardt method, which reuses the Gram matrix. Our method has a global convergence guarantee without relying on any step of line-search or solving sub-problems. We show that our method takes a smaller computational complexity than existing Levenberg-Marquardt methods to find the stationary point of the square norm of the equations. We also show that the proposed method enjoys a local superlinear convergence rate under the non-degenerate assumption. Experiments are conducted on real-world applications in scientific computing and machine learning, which validate the efficiency of our method. Copyright © 2025, Association for the Advancement of Artificial Intelligence (***). All rights reserved.

关键词： e-science

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AI-Powered Code Reviews: Leveraging Large Language Models

AI-Powered Code Reviews: Leveraging Large Language Models

引用

Signal Processing and Advance Research in Computing (SPARC), International Conference on

作者： Md Shain Shahid Chowdhury Md Naseef Ur Rahman Chowdhury Fariha Ferdous Neha Ahshanul Haque Department of Computer Science Utah State University Logan UT USA Department of Computer Science New Mexico Tech Socorro NM USA Department of Applied Mathematics University of Dhaka Dhaka Bangladesh Department of Computer Sceince New Mexico Tech Socorro New Mexico USA

ISBN: (数字)9798350385205

ISBN: (纸本)9798350385212

As the complexity and volume of software development continue to grow, the need for efficient and thorough code review processes becomes increasingly critical. This paper explores the integration of Large Language Models (LLMs), such as ChatGPT and Bard, into code review workflows to enhance software quality and security. By leveraging the natural language processing capabilities of LLMs, we aim to streamline the identification of code issues, detect potential security vulnerabilities, and provide developers with actionable feedback. Through a comprehensive analysis of current literature, case studies, and experimental data, this study evaluates the impact of AI-assisted code reviews on developer productivity and code quality. We also address the challenges and limitations of relying on LLMs, including context comprehension and potential biases. Our findings suggest that while LLMs offer significant advantages in automating and improving code reviews, they should complement rather than replace human expertise. This paper provides insights into best practices for integrating LLMs into development workflows, ultimately contributing to more robust and secure software systems.

关键词： Ethics Technological innovation Codes Reviews Large language models Collaboration Software quality Software systems Security Software development management

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Multi-Level Feature Distillation of Joint Teachers Trained on Distinct Image Datasets

Multi-Level Feature Distillation of Joint Teachers Trained o...

引用

IEEE Workshop on Applications of computer Vision (WACV)

作者： Adrian Iordache Bogdan Alexe Radu Tudor Ionescu Department of Computer Science University of Bucharest Bucharest Romania “Gheorghe Mihoc - Caius Iacob” Institute of Mathematical Statistics and Applied Mathematics of the Romanian Academy Bucharest Romania

ISBN: (数字)9798331510831

ISBN: (纸本)9798331510848

We propose a novel teacher-student framework to distill knowledge from multiple teachers trained on distinct datasets. Each teacher is first trained from scratch on its own dataset. Then, the teachers are combined into a joint architecture, which fuses the features of all teachers at multiple representation levels. The joint teacher architecture is fine-tuned on samples from all datasets, thus gathering useful generic information from all data samples. Finally, we employ a multi-level feature distillation procedure to transfer the knowledge to a student model for each of the considered datasets. We conduct image classification experiments on seven benchmarks, and action recognition experiments on three benchmarks. To illustrate the power of our feature distillation procedure, the student architectures are chosen to be identical to those of the individual teachers. To demonstrate the flexibility of our approach, we combine teachers with distinct architectures. We show that our novel Multi-Level Feature Distillation (MLFD) can significantly surpass equivalent architectures that are either trained on individual datasets, or jointly trained on all datasets at once. Furthermore, we confirm that each step of the proposed training procedure is well motivated by a comprehensive ablation study. We publicly release our code at https://***/AdrianIordache/MLFD.

关键词： Training Convolutional codes Image segmentation Image recognition computer architecture Object detection Benchmark testing Transformers Natural language processing Image classification

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