99 research outputs found
A simple and scalable receiver model in molecular communication systems
No full textThis paper shows a simple although reliable receiver model for diffusion-based molecular communication systems. Indeed, the complexity of molecular communications system, involving a massive number of interacting entities, makes scalability a fundamental property of simulators and modeling tools. A sample scenario is that of targeted drug delivery systems, which makes use of biological nanomachines close to a biological target, able to release molecules in a diseased area. The proposed model tackles the time needed for analyzing such a system by the introduction of an equivalent markovian queuing model, which reproduces the aggregate behavior of thousands of receptors spread over the receiver surface. Our results demonstrate that the proposed approach substantially matches simulation results achieved through detailed simulations of a large number of receivers by means of BiNS2 simulator, although the time taken for obtaining the results is order of magnitudes lower than the simulation time. We believe that this model is the precursor of novel models based on similar principles that allow realizing reliable simulations of body-wide systems
A simulation tool for biological nano-communication systems
No full textBiological nanonetworks is a novel interdisciplinary research area including nanotechnology, biotechnology, and ICT. In this paper, we illustrate a simulation tool designed for modeling communications at nanoscales. This tool is fully adaptable to all nano-scale bearers, used to transport information, which may range from electromagnetic waves to calcium ions. In addition, it can be easily adapted to the interested environment. In this paper, we illustrate an example of the simulator functions by modeling a portion of a lymph node, and simulating the information transfer during the humoral immune response by antibody molecules
Smart antennas for diffusion-based molecular communications
No full textDiffusion-based molecular communications are characterized by the Brownian motion of the signal molecules in their path from the transmitting nanomachine to the receiving one, which prevents directionality in the transmitted signal. In order to make diffusion-based molecular communications more reliable, we worked on the receiver side to improve the capability of receiving biological signals. Inspired by smart antennas in conventional wireless communications, we designed a directional receiver nanomachine, with the aim of increasing the average concentration of signal molecules close to its surface so as to improve the received signal strength. In more detail, we considered a spherical receiver covered by a finite number of receptors, and provided with a purely reflecting shell at a configurable distance from the receiver surface, whose shape is a spherical cap or a cylinder. The presence of the shell allows a number of signal molecules to remain trapped close to the receiver surface for a while. This phenomenon increases the probability of assimilating a signal molecule by one of the receptors deployed on the receiver surface. Through an extensive simulation campaign, we compared the received signal intensity obtained with the smart antennas with the that obtainable in standard settings. From the analysis of results, we identified the most suitable settings in terms of aperture of the shell and distance of the shell from the receiver
Endovascular Mobile Sensor Network for Detecting Circulating Tumoral Cells
No full textThis paper analyzes the communications and medical potentials arising from establishing nano-scale communications making use of the stent tubular structures in blood vessels. Most of stent implants (both bare metal and drug eluiting stents) happens in coronary arteries for supporting weak endothelial points and counteracting the obstructing effects of arthrosclerosis. Such structures have continuously inspired researchers for introducing additional functions to the mere mechanical sustain of vessels.
After a review of the current literature, we propose an original use of stents for monitoring CD47 receptors bearing cells and provide effective diagnostic and prognostic information. We can also perform the detection of different cancer markers, and then integrate this information. These monitoring functions and the event notifications makes used of nano-scale communications. Through a well established simulator of biological nano-scale communications, we will gain significant insights about the
establishment of these types of communications happening between different sections of the stent structure. The information exchanges is assumed to be collected by nano-sensors of tumor cells. The outcome of the research is the characterization of the channel transmission capabilities. When considering cost benefit of these expensive smart stents, we suggest a wider perspective where oncologists may join the team of future interventional cardiologists. Thus, our system creates a link between cancer detection, stent devices, and body area networks to P5 medicine
A simulation tool for nanoscale biological networks
No full textNanonetworking is a new interdisciplinary research area including nanotechnology, biotechnology, and ICT. In this paper, we present a novel simulation platform designed for modeling information exchange at nanoscales. This platform is adaptable to any kind of nano bearer, i.e. any mechanism used to transport information, such as electromagnetic waves or calcium ions. Moreover, it includes a set of configuration functions in order to adapt to different types of biological environments. In this paper, we provide a throughout description of the simulation libraries. In addition, we demonstrate their capabilities by modeling a section of a lymph node and the information transfer within it, which happens between antibody molecules produced by the immune system during the humoral immune response
Applications of molecular communications to medicine: A survey
No full textIn recent years, progresses in nanotechnology have established the foundations for implementing nanomachines capable of carrying out simple but significant tasks. Under this stimulus, researchers have been proposing various solutions for realizing nanoscale communications, considering both electromagnetic and biological communications. Their aim is to extend the capabilities of nanodevices, so as to enable the execution of more complex tasks by means of mutual coordination, achievable through communications. However, although most of these proposals show how devices can communicate at the nanoscales, they leave in the background specific applications of these new technologies. Thus, this paper shows an overview of the actual and potential applications that can rely on a specific class of such communications techniques, commonly referred to as molecular communications. In particular, we focus on health-related applications. This decision is due to the rapidly increasing interests of research communities and companies to minimally invasive, biocompatible, and targeted health-care solutions. Molecular communication techniques have actually the potentials of becoming the main technology for implementing advanced medical solution. Hence, in this paper we provide a taxonomy of potential applications, illustrate them in some detail, along with the existing open challenges for them to be actually deployed, and draw future perspectives
Effect of Aging, Disease Versus Health Conditions in the Design of Nano-communications in Blood Vessels
No full textThis chapter illustrates the analysis of a nano-communication system, implemented in blood vessels, designed for detecting tumor cells. This system may be used for diagnostic purposes in the early stage of a disease or to check any relapse of a previous disease already treated.
The tumor detection happens through revealing tumor biomarkers, such as the CD47 protein, on the cell surface. Once a biomarker has been revealed, a molecular communication system distribute the information to a number of nano-machines having a size allowing them to flow through the vessel at the maximum speed of the bloodstream. The final information detection is extra-body, and based on a smart probe, which triggers a decision tree computing which aims to find is any tumor is present and the most likely location. Effects of aging and serious disease, such as the diabetes, are highlighted
Digital Media and Knowledge Production Within Social Movements: Insights From the Transition Movement in Italy
No full textsponsorship: The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This article grounds in research activites carried out in the period 2016-2017 within the framework of the project "MAKERS- Movements as knowledge producers and learning spaces in the digital age" funded by the Scuola Normale Superiore. (Scuola Normale Superiore)status: Publishe
Adaptive Reference Governor for DC–DC Converters Based on Model Predictive Control
No full textIn this article, we propose a time-varying model predictive control (MPC)-based scheme to enhance the dynamic performance of dc–dc converters. The proposed approach employs MPC as a reference governor (RG), addressing industrial certification constraints that may limit modifications to the low-level controller. To accommodate the computational limitations of conventional control boards, we introduce a highly efficient real-time optimization algorithm for solving equality-constrained quadratic programming (QP) problems. The algorithm is based on a tailored QR factorization that outperforms well-known linear algebra libraries, and it is shown to be superior to condensing with state elimination. Furthermore, we implement an efficient recursive least-squares (RLS) method to provide a linear-time varying model for the adaptive MPC-based RG. No information regarding the topology of the converter nor the structure of the low-level controller is required for such adaptation, making the proposed method self-tuning and eliminating the need for prior identification steps. The proposed control scheme has been tested on various simulated and real dc–dc converters, demonstrating its computational and memory efficiency, as well as its versatility across different converter topologies
Fixed-size LS-SVM LPV System Identification for Large Datasets
No full textIn this paper, we propose an efficient method for handling large datasets in linear parameter-varying (LPV) model identification. The method is based on least-squares support vector machine (LS-SVM) identification in the primal space. To make the identification computationally feasible, even for very large datasets, we propose estimating a finite-dimensional feature map. To achieve this, we propose a two-step method to reduce the computational effort. First, we define the training set as a fixed-size subsample of the entire dataset, considering collision entropy for subset selection. The second step involves approximating the feature map through the eigenvalue decomposition of the kernel matrices. This paper considers both autoregressive with exogenous input (ARX) and state-space (SS) model forms. By comparing the problem formulation in the primal and dual spaces in terms of accuracy and computational complexity, the main advantage of the proposed technique is the reduction in space and time complexity during the training stage, making it preferable for handling very large datasets. To validate our proposed primal approach, we apply it to estimate LPV models using provided inputs, outputs, and scheduling signals for two nonlinear benchmarks: the parallel Wiener-Hammerstein system and the Silverbox system. The performances of our proposed approach are compared with the dual LS-SVM approach and the kernel principal component regression
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