A One-Dimensional Model For Neuronal Growth

A mathematical model for neuronal growth is presented, describing the process of axonal elongation. The main construction material is a protein called tubulin, which is produced in the soma (core body of the cell), and transported inside the axon to a structure known as the growth cone on its tip, where the construction process occurs. The concentration of tubulin is modelled by a convection-diffusion PDE along the axon and by an ODE in the small tip. The length of the axon as a function of time is given by another ODE which models the building process in the growth cone. The entire model constitutes a coupled moving-boundary problem for which a numerical method is described and investigated. Simulation are also presented with parameter values from literature in the case of the squid (Loligo pealeii)

Design ResearchScape. A visual exploration of Design Research publications

In this paper we mix methods and approaches from scientometrics, co-citation analysis and network science, in order to build a set of maps and visualizations of the Design Research field. Bringing ..

Geometric distortions in FMCW SAR images due to inaccurate knowledge of electronic radar parameters: analysis and correction by means of corner reflectors

Abstract In the last years the Frequency Modulated Continuous Wave (FMCW) technology has been playing an ever greater role in the realization of compact, light and cheap Synthetic Aperture Radar (SAR) systems to be mounted onboard small, low altitude platforms such as airplanes, helicopters and drones. To correctly focus FMCW SAR images, it is necessary to accurately know some system parameters, including the frequency sweep rate of the signal transmitted by the radar. It may happen, however, that this frequency sweep rate is not very accurately measured by the radar provider, and thus an incorrect value of this parameter is used during the SAR data focusing procedure. This may produce serious geometric distortion effects in the focused FMCW SAR images. To circumvent these problems, in this work we present a procedure that estimates the frequency sweep rate actually employed by the FMCW radar, thus providing a key information that can be then profitably used to achieve the correct focusing of the SAR data acquired by the radar system at hand. More specifically, we propose an algorithm that exploits on one side the focused SAR images corrupted by the geometric distortion effects induced by the inaccurate knowledge of this radar parameter, and on the other side the very precise in-situ measurements of the positions of a limited number of Corner Reflectors (CRs) properly deployed over the observed scene. The effectiveness of the proposed algorithm has been tested on real data acquired by an airborne X-band FMCW SAR system

Micromagnetic study of inertial spin waves in ferromagnetic nanodots

Here we report the possibility to excite ultra-short spin waves in ferromagnetic thin-films by using time-harmonic electromagnetic fields with terahertz frequency. Such ultra-fast excitation requires to include inertial effects in the description of magnetization dynamics. In this respect, we consider the inertial Landau-Lifshitz-Gilbert (iLLG) equation and develop analytical theory for exchange-dominated inertial spin waves. The theory predicts a finite limit for inertial spin wave propagation velocity, as well as spin wave spatial decay and lifetime as function of material parameters. Then, guided by the theory, we perform numerical micromagnetic simulations that demonstrate the excitation of ultra-short inertial spin waves (20 nm long) propagating at finite speed in a confined magnetic nanodot. The results are in agreement with the theory and provide the order of magnitude of quantities observable in realistic ultra-fast dynamics experiments.Comment: The following article has been accepted by Physical Review B. After it is published, it will be found at https://journals.aps.org/prb/. Revised version, 9 pages, 6 figures. Changes made in v2: added some references, minor edits and correction

SGDE: Secure Generative Data Exchange for Cross-Silo Federated Learning

Privacy regulation laws, such as GDPR, impose transparency and security as design pillars for data processing algorithms. In this context, federated learning is one of the most influential frameworks for privacy-preserving distributed machine learning, achieving astounding results in many natural language processing and computer vision tasks. Several federated learning frameworks employ differential privacy to prevent private data leakage to unauthorized parties and malicious attackers. Many studies, however, highlight the vulnerabilities of standard federated learning to poisoning and inference, thus raising concerns about potential risks for sensitive data. To address this issue, we present SGDE, a generative data exchange protocol that improves user security and machine learning performance in a cross-silo federation. The core of SGDE is to share data generators with strong differential privacy guarantees trained on private data instead of communicating explicit gradient information. These generators synthesize an arbitrarily large amount of data that retain the distinctive features of private samples but differ substantially. In this work, SGDE is tested in a cross-silo federated network on images and tabular datasets, exploiting beta-variational autoencoders as data generators. From the results, the inclusion of SGDE turns out to improve task accuracy and fairness, as well as resilience to the most influential attacks on federated learning

Analysis in k-space of Magnetization Dynamics Driven by Strong Terahertz Fields

Demagnetization in a thin film due to a terahertz pulse of magnetic field is investigated. Linearized LLG equation in the Fourier space to describe the magnetization dynamics is derived, and spin waves time evolution is studied. Finally, the demagnetization due to spin waves dynamics and recent experimental observations on similar magnetic system are compared. As a result of it, the marginal role of spin waves dynamics in loss of magnetization is established.Comment: 5 pages, 6 figure

Multiobjective Optimization of a Rotman Lens through the QLWS Minimization

We address the multiobjective optimization of a Rotman lens by means of a recently proposed method based on the minimization of a properly defined global cost function named Quantized Lexicographic Weighted Sum (QLWS). More specifically, we have considered three different objectives concurring during the optimal synthesis of the lens. First, the difference between actual and desired delay among the excitations of the array elements fed by the lens needs to be lower than a given threshold. Second, gain losses of the beams scanned by the array fed by the lens need to be lower than a given threshold. Third, lens insertion losses should be as low as possible. Exploitation of the QLWS based approach allowed us to obtain in a few minutes a Rotman lens fulfilling these three concurring objectives and to improve the starting result obtained by a commercial software