Multiscale Information Decomposition: Exact Computation for Multivariate Gaussian Processes

Exploiting the theory of state space models, we derive the exact expressions of the information transfer, as well as redundant and synergistic transfer, for coupled Gaussian processes observed at multiple temporal scales. All of the terms, constituting the frameworks known as interaction information decomposition and partial information decomposition, can thus be analytically obtained for different time scales from the parameters of the VAR model that fits the processes. We report the application of the proposed methodology firstly to benchmark Gaussian systems, showing that this class of systems may generate patterns of information decomposition characterized by mainly redundant or synergistic information transfer persisting across multiple time scales or even by the alternating prevalence of redundant and synergistic source interaction depending on the time scale. Then, we apply our method to an important topic in neuroscience, i.e., the detection of causal interactions in human epilepsy networks, for which we show the relevance of partial information decomposition to the detection of multiscale information transfer spreading from the seizure onset zone

The role of traction in membrane curvature generation.

Curvature of biological membranes can be generated by a variety of molecular mechanisms including protein scaffolding, compositional heterogeneity, and cytoskeletal forces. These mechanisms have the net effect of generating tractions (force per unit length) on the bilayer that are translated into distinct shapes of the membrane. Here, we demonstrate how the local shape of the membrane can be used to infer the traction acting locally on the membrane. We show that buds and tubes, two common membrane deformations studied in trafficking processes, have different traction distributions along the membrane and that these tractions are specific to the molecular mechanism used to generate these shapes. Furthermore, we show that the magnitude of an axial force applied to the membrane as well as that of an effective line tension can be calculated from these tractions. Finally, we consider the sensitivity of these quantities with respect to uncertainties in material properties and follow with a discussion on sources of uncertainty in membrane shape

Rafts: scale-dependent, active lipid organization at the cell surface

Rafts have been conceptualized as lateral heterogeneities in the organization of cholesterol and sphingolipids, endowed with sorting and signaling functions. In this review we critically examine evidence for the main tenet of the 'raft hypothesis', namely lipid-dependent segregation of specific membrane components in the plasma membrane. We suggest that conventional approaches to studying raft organization wherein membranes are treated as passive, thermally equilibrated systems are unlikely to provide an adequate framework to understand the mechanisms of raft-organization in vivo. An emerging view of raft organization is that it is spatio-temporally regulated at different scales by the cell. This argues that rafts must be defined by simultaneous observation of components involved in particular functions. Recent evidence from the study of glycosylphosphatidyl inositol-anchored proteins, a common raft-marker, supports this picture in which larger scale, more stable rafts are induced from preexisting small-scale lipid-dependent structures actively maintained by cellular processes

Mean-Field-Type Games in Engineering

A mean-field-type game is a game in which the instantaneous payoffs and/or the state dynamics functions involve not only the state and the action profile but also the joint distributions of state-action pairs. This article presents some engineering applications of mean-field-type games including road traffic networks, multi-level building evacuation, millimeter wave wireless communications, distributed power networks, virus spread over networks, virtual machine resource management in cloud networks, synchronization of oscillators, energy-efficient buildings, online meeting and mobile crowdsensing.Comment: 84 pages, 24 figures, 183 references. to appear in AIMS 201

Mathematical modelling of operating cycles for road vehicles

Difficulties that commercial vehicles are facing in meeting regulation standards require ad-hoc solutions. Emissions can be dramatically lowered if the characteristics of the transport application are known in advance. To tailor the vehicle\u27s specification towards the use-case, however, a representative description of the mission, together with the surroundings, is needed.Where many conventional approaches fail, the operating cycle format (OC) has shown promising results in describing road operations in a way which is completely independent of both vehicle and driver.More specifically, the framework consists of three levels of representation. The first, called the bird\u27s eye view, serves mainly as a classification tool, and makes use of metrics and labels to completely characterise the overall application of a vehicle during its lifetime. The second description, the stochastic operating cycle (sOC), condenses the main properties of a road operation using elementary statistics. It is conceived as an intermediate representation with a higher degree of accuracy. Finally, the deterministic operating cycle (dOC) is the most detailed description of a transport mission, and collects deterministic models to be used in simulation.In previous studies, the OC format was demonstrated to work in theory, but some margins for improvement could still be identified. Furthermore, the utility and benefits deriving from the use of the OC in concrete situations was explored only partially.The main objective of this thesis consists in extending the OC representation to include stochastic models for weather and traffic, which were missing in the original formulation. The new models are built to be parsimonious and to allow ease of parametrisation and implementation starting from real data. This enables to reproduce and simulate realistic environments where a transport mission can take place, with a substantial gain in accuracy.The second purpose of this work is to showcase how the OC concept can be used in practical applications involving real customers. A case study is presented to exemplify the advantages connected with the use of the OC description in product selection, prospecting a potential reduction of fuel consumption and emission of about 10%

Graph Signal Processing: Overview, Challenges and Applications

Research in Graph Signal Processing (GSP) aims to develop tools for processing data defined on irregular graph domains. In this paper we first provide an overview of core ideas in GSP and their connection to conventional digital signal processing. We then summarize recent developments in developing basic GSP tools, including methods for sampling, filtering or graph learning. Next, we review progress in several application areas using GSP, including processing and analysis of sensor network data, biological data, and applications to image processing and machine learning. We finish by providing a brief historical perspective to highlight how concepts recently developed in GSP build on top of prior research in other areas.Comment: To appear, Proceedings of the IEE

Nested Fork-Join Queuing Networks and Their Application to Mobility Airfield Operations Analysis

A single-chain nested fork-join queuing network (FJQN) model of mobility airfield ground processing is proposed. In order to analyze the queuing network model, advances on two fronts are made. First, a general technique for decomposing nested FJQNs with probabilistic forks is proposed, which consists of incorporating feedback loops into the embedded Markov chain of the synchronization station, then using Marie\u27s Method to decompose the network. Numerical studies show this strategy to be effective, with less than two percent relative error in the approximate performance measures in most realistic cases. The second contribution is the identification of a quick, efficient method for solving for the stationary probabilities of the λn/Ck/r/N queue. Unpreconditioned Conjugate Gradient Squared is shown to be the method of choice in the context of decomposition using Marie\u27s Method, thus broadening the class of networks where the method is of practical use. The mobility airfield model is analyzed using the strategies described above, and accurate approximations of airfield performance measures are obtained in a fraction of the time needed for a simulation study. The proposed airfield modeling approach is especially effective for quick-look studies and sensitivity analysis

Wireless sensor network based monitoring system for precision agriculture in Uzbekistan

The last decades the WSN technology has been adopted by more and more scientific fields for accurate and effective monitoring of climate phenomena like air pollution, destruction phenomena like landslides, etc. It has been widely used in agriculture for field monitoring. WSN is an emerging technology, which through the research in the labs and the real deployments has been proved to be a significant and valuable tool for scientists to explore another world which is behind the various environmental phenomena using tiny sensor nodes In this article, "Expert Advisory System" was developed to improve the productivity of farmers, save their time and improve the efficiency of the crops. The system monitors real-time crop fields using wireless sensor networks and provides the necessary information to farmers via the Internet. The farmer will be required to undertake the necessary remedial action on the basis of the information received. It’s also provided that the simulation of WSN in Contiki Simulator tool. Moreover, the queing model for WSN to also considered in this work