Explore the vast range of titles available.

This paper investigates the mathematical modeling and the stability of multi-lane traffic in the microscopic scale, studying a model based on two interaction terms. To do this we propose simple lane changing conditions and we study the stability of the steady states starting from the model in the one-lane case and extending the results to the generic multi-lane case with the careful design of the lane changing rules. We compare the results with numerical tests, that confirm the predictions of the linear stability analysis and also show that the model is able to reproduce stop & go waves, a typical feature of congested traffic.

The mathematical modeling and the stability analysis of multi-lane traffic in the macroscopic scale is considered. We propose a new first order model derived from microscopic dynamics with lane changing, leading to a coupled system of hyperbolic balance laws. The macroscopic limit is derived without assuming ad hoc space and time scalings. The analysis of the stability of the equilibria of the model is discussed. The proposed numerical tests confirm the theoretical findings between the macroscopic and microscopic modeling, and the results of the stability analysis.

This paper presents a mathematical model for opinion dynamics in popularity-adaptive social networks, where both opinion spreading and the evolution of social media contacts depend on agents' popularity and the prominence of their views. While previous approaches accounted for the influence of popularity on opinion dynamics, we introduce a novel feedback mechanism in which opinion affects the formation of contacts. Within a kinetic modeling framework, we describe the evolution of the coupled dynamics of opinions and network structure, incorporating a class of control laws in order to promote interactions with popular individuals and amplify dominant opinions. Such control strategies are introduced to influence both opinion formation and connectivity, representing interventions such as awareness campaigns or moderation policies. Numerical results show how control strategies can mitigate polarization, foster consensus, or guide opinion distributions in dynamically evolving networks.

This paper presents a mathematical model for opinion dynamics in popularity-adaptive social networks, where both opinion spreading and the evolution of social media contacts depend on agents' popularity and the prominence of their views. While previous approaches accounted for the influence of popularity on opinion dynamics, we introduce a novel feedback mechanism in which opinion affects the formation of contacts. Within a kinetic modeling framework, we describe the evolution of the coupled dynamics of opinions and network structure, incorporating a class of control laws in order to promote interactions with popular individuals and amplify dominant opinions. Such control strategies are introduced to influence both opinion formation and connectivity, representing interventions such as awareness campaigns or moderation policies. Numerical results show how control strategies can mitigate polarization, foster consensus, or guide opinion distributions in dynamically evolving networks.

This study addresses multilane vehicular traffic modelling, focusing on the transition between microscopic (individual vehicle-based) to macroscopic (aggregate flow-based) descriptions. While previous research on multilane traffic has largely focused on first-order models, we derive two new multilane second-order macroscopic models by applying a microscopic-to-macroscopic limit to the multilane Bando-Follow-the-Leader model. The resulting models incorporate lane-changing through source terms in a hyperbolic system of balance laws. We propose several numerical experiments showing that the models can reproduce complex traffic phenomena, including congestion propagation, non-equilibrium effects, and asymmetric lane usage. Leveraging experimental datasets from real-world highways, we further construct lane-specific empirical fundamental diagrams and compare them with their simulated counterparts, showing that our models can faithfully capture critical density values and characteristic lane-dependent patterns, thus offering a robust and generalizable tool for realistic traffic flow analysis

We study a leader-follower system of interacting particles subject to feedback control and derive its mean-field limits through a two-step passage: first to a micro-macro system coupling leader particles with a follower fluid, and then to a fully continuum macro-macro system. For each limiting procedure, we establish quantitative stability and convergence estimates based on modulated energy methods and Wasserstein distances. These results provide a rigorous foundation for the hierarchical reduction of controlled multi-agent systems. Numerical simulations are presented, including examples with interaction potentials beyond the analytical class considered, to demonstrate the dynamics and support the theoretical results.

Cognitive disorders represent a leading cause of disability in the aging population, of which dementia has the highest global burden. Early signs of dementia such as slow gait and memory complaints are known to present well before the overt manifestation of the disease. Motoric cognitive risk (MCR) syndrome characterized by the simultaneous presence of gait disturbances and memory complaints in older subjects has been proposed to study the close interactions between the physical and cognitive domains as well as a possible approach to identify individuals at increased risk of dementia. In addition, studies have shown MCR as a predictor of other negative outcomes in older adults, including disability, falls and death. However, the concept of MCR is still in its early stage and approach to the syndrome is still not well established. This review aims to put together the various aspects of MCR syndrome including its pathophysiology, diagnosis, epidemiology, and relationship with other geriatric conditions.

Literature has suggested that changes in brain flow circulation occur in patients with multiple sclerosis. In this study, digital subtraction angiography (DSA) was used to measure the absolute CCT value in MS patients and to correlate its value to age at disease onset and duration, and to expand disability status scale (EDSS). DSA assessment was performed on eighty MS patients and on a control group of forty-four age-matched patients. CCT in MS and control groups was calculated by analyzing the angiographic images. Lesion and brain volumes were calculated in a representative group of MS patients. Statistical correlations among CCT and disease duration, age at disease onset, lesion load, brain volumes and EDSS were considered. A significant difference between CCT in MS patients (mean = 4.9s; sd = 1.27 s) and control group (mean = 2.8s; sd = 0.51 s) was demonstrated. No significant statistical correlation was found between CCT and the other parameters in all MS patients. Significantly increased CCT value in MS patients suggests the presence of microvascular dysfunctions, which do not depend on clinical and MRI findings. Hemodynamic changes may not be exclusively the result of a late chronic inflammatory process.

In the development process of actual cars it is more and more important to be able to evaluate in a detailed and fast way the impact, on the fuel consumption, of components and management strategies of the auxiliary systems. For these reasons, there is the need to develop and test specific tools. One of the most consuming subsystem is the Air Conditioning system: to be able to integrate it in a dynamic simulation model is going to be of outmost importance in the near future, since it is most likely that in some countries (see incoming California legislation) vehicle fuel consumption will be measured with the A/C system \"ON\". FIAT Auto and Centra Ricerche FIAT have jointly developed a simulation tool, DrivEM, that integrates three dedicated simulation models: Drivetrain© for vehicle performance & fuel consumption, SACS for air conditioning systems and BILELCO for electrical system analysis. DrivEM 1.0 allows to estimate the impact on fuel consumption both for A/C system under a whatever ambient conditions using and for electrical power loads needs. One of the key feature of the approach is that the majority of data, needed as input, do not require experimental tests, but can be derived from suppliers datasheet or from the basic characteristics of the vehicle. This allows to use this tool since the early stage of the development process of the vehicle itself. The simulation of vehicle performances with air conditioning and electrical system on has been validated with experimental tests in a test bench with climatic chambers. The accuracy of the comparison between measurement and simulation is within 5%.