Emerging infectious disease dynamics with compliance and isolation resource constraints [0.03%]
符合性和隔离资源约束下的新兴传染病动力学模型研究
Xinru Li,Ning Wang,Shengqiang Liu
Xinru Li
The effectiveness of isolation strategies against emerging infectious diseases (EIDs) is critically undermined by two interacting factors: Limited resource capacity and imperfect public compliance, yet their combined impact remains poorly q...
Artificial Intelligence for Hydraulic Engineering: Predicting discharge coefficients in trapezoidal side weirs [0.03%]
人工智能在水利领域的应用：预测梯形侧槽的流量系数
Mehdi Fuladipanah,Saleema Panda,Namal Rathnayake et al.
Mehdi Fuladipanah et al.
Accurately predicting the discharge coefficient (Cd) is fundamental to the hydraulic design and performance of side weirs. In this study, we introduced a novel artificial intelligence (AI) framework to enhance the prediction accuracy of Cd ...
A mathematical model of Clostridioides difficile transmission in long-term care facilities [0.03%]
长期护理机构中艰难梭菌传播的数学模型
Priscilla Doran,Natsuka Hayashida,Kristen Joyner et al.
Priscilla Doran et al.
Clostridioides difficile, also known as C. difficile, is a prevalent cause of infectious diarrhea in United States healthcare facilities. Spread through the fecal-oral route and often through contact with spores on contaminated surfaces, C....
A detailed analysis of the spatial dynamics of a food-chain model with Allee and fear effect [0.03%]
具有Allee效应和恐惧效应的食物链模型的时空动力学分析
Swati Mishra,Anal Chatterjee,Ranjit Kumar Upadhyay et al.
Swati Mishra et al.
We investigate the spatiotemporal dynamics of a tri-trophic food chain model incorporating a strong Allee effect on the prey and a fear effect on the middle predator. The model's well-posedness is established through the positivity and boun...
An accessible approach to density estimation neural networks with data preprocessing [0.03%]
一种具有数据预处理的密度估计神经网络方法
Bosi Hou,Jonathan E Rubin
Bosi Hou
Density estimation neural networks (DENNs) represent a form of artificial neural network designed to provide an efficient approach to the Bayesian estimation of a probability density on a model parameter space, conditioned on an empirical o...
Environmental variability and fish stock dynamics: a stochastic model of Mahi Mahi abundance [0.03%]
环境变化与渔业资源动力学：一种关于鲯鳅种群丰度的随机模型
Erika Johanna Martínez-Salinas,Andrés Ríos-Gutiérrez,Viswanathan Arunachalam et al.
Erika Johanna Martínez-Salinas et al.
Climatic factors exert a substantial influence on both biotic and abiotic components of marine ecosystems, significantly affecting the abundance and spatial distribution of fish species. In this study, we introduced a stochastic modeling fr...
A compartmental epidemic model with age stratification for insurance premium calculation [0.03%]
一个用于保险费率计算的分隔式年龄结构流行病模型
Shirali Kadyrov,Gauhar Kayumova,Asilbek Yallaboyev et al.
Shirali Kadyrov et al.
This paper develops a mathematical framework for life and health insurance premium calculation under epidemic conditions, incorporating age-structured population dynamics and disease compartments. We proposed a compartmental epidemic model ...
Recent advances in ODEs modeling of tumor-immune responses: a focus on delay effects [0.03%]
肿瘤免疫反应的ODE模型新进展：重点关注时滞效应
John A Arredondo,Andrés Rivera
John A Arredondo
This review examines recent developments in modeling the interaction between tumor cells and the immune system, with a specific focus on the application of delay differential equations (DDEs). The models serve as crucial tools to simulate a...
Adaptive Neuro-Symbolic framework with dynamic contextual reasoning: A novel framework for semantic understanding [0.03%]
一种具有动态上下文推理的自适应神经符号框架：一种语义理解的新框架
Idowu Paul Okuwobi,Jingyuan Liu,Olayinka Susan Raji et al.
Idowu Paul Okuwobi et al.
Despite significant advances in image processing, achieving human-like semantic understanding and explainability remains a formidable challenge. Current deep learning models excel at feature extraction but lack the ability to reason about r...
Few-shot learning for rare skin disease classification via adaptive distribution calibration [0.03%]
自适应分布校准的少样本学习皮肤罕见病分类方法
Yin Wen,Yingbo Wu,Zhigao Zeng et al.
Yin Wen et al.
The classification of rare skin diseases faces significant data scarcity challenges due to the difficulty in acquiring clinical samples and the high cost of annotation, which severely hinders the training of deep neural network-based models...