On the reduction of the degree of linear differential operators

Let L be a linear differential operator with coefficients in some differential field k of characteristic zero with algebraically closed field of constants. Let k^a be the algebraic closure of k. For a solution y, Ly=0, we determine the linear differential operator of minimal degree M and coefficients in k^a, such that My=0. This result is then applied to some Picard-Fuchs equations which appear in the study of perturbations of plane polynomial vector fields of Lotka-Volterra type

Sparse 3D Point-cloud Map Upsampling and Noise Removal as a vSLAM Post-processing Step: Experimental Evaluation

The monocular vision-based simultaneous localization and mapping (vSLAM) is one of the most challenging problem in mobile robotics and computer vision. In this work we study the post-processing techniques applied to sparse 3D point-cloud maps, obtained by feature-based vSLAM algorithms. Map post-processing is split into 2 major steps: 1) noise and outlier removal and 2) upsampling. We evaluate different combinations of known algorithms for outlier removing and upsampling on datasets of real indoor and outdoor environments and identify the most promising combination. We further use it to convert a point-cloud map, obtained by the real UAV performing indoor flight to 3D voxel grid (octo-map) potentially suitable for path planning.Comment: 10 pages, 4 figures, camera-ready version of paper for "The 3rd International Conference on Interactive Collaborative Robotics (ICR 2018)

Radio Frequency Identification and Privacy Law: An Integrative Approach

The indiscriminate nature of Radio Frequency Identification (RFID)1 technology creates unique privacy issues.2 Currently privacy standards for the type of information gathered through RFID and the use of that information do not exist.3 With few exceptions, compatible readers may legally access from a remote location RFID devices and the information these devices contain. After gathering information, the legal uses of that information are innumerable in terms of aggregation and re-use

Stark Effect of Interactive Electron-hole pairs in Spherical Semiconductor Quantum Dots

We present a theoretical variational approach, based on the effective mass approximation (EMA), to study the quantum-confinement Stark effects for spherical semiconducting quantum dots in the strong confinement regime of interactive electron-hole pair and limiting weak electric field. The respective roles of the Coulomb potential and the polarization energy are investigated in details. Under reasonable physical assumptions, analytical calculations can be performed. They clearly indicate that the Stark shift is a quadratic function of the electric field amplitude in the regime of study. The resulting numerical values are found to be in good agreement with experimental data over a significant domain of validity

The memristive artificial neuron high level architecture for biologically inspired robotic systems

© 2017 IEEE. In this paper we propose a new hardware architecture for the implementation of an artificial neuron based on organic memristive elements and operational amplifiers. This architecture is proposed as a possible solution for the integration and deployment of the cluster based bio- realistic simulation of a mammalian brain into a robotic system. Originally, this simulation has been developed through a neuro-biologically inspired cognitive architecture (NeuCogAr) re-implementing basic emotional states or affects in a computational system. This way, the dopamine, serotonin and noradrenaline pathways developed in NeuCogAr are synthesized through hardware memristors suitable for the implementation of basic emotional states or affects on a biologically inspired robotic system

Replacement of Contentious Inputs in Organic Farming Systems (RELACS) – a comprehensive Horizon 2020 project

Organic farmers adhere to high standards in producing quality food while protecting the environment. However, organic farming needs to improve continuously to keep meeting its ambitious objectives. The project ‘Replacement of Contentious Inputs in Organic Farming Systems’ (RELACS) will foster the development and adoption of cost-efficient and environmentally safe tools and technologies to further reduce the use of external inputs on organic farms across Europe as well as in Non EU Mediterranean countries. Project partners will provide scientific support to develop fair and implementable EU rules to improve current practices in organic farming. Farm advisory networks in 11 European countries will reach out to farmers to ensure effective dissemination and adoption of the tools and techniques

Structure factor of polymers interacting via a short range repulsive potential: application to hairy wormlike micelles

We use the Random Phase Approximation (RPA) to compute the structure factor, S(q), of a solution of chains interacting through a soft and short range repulsive potential V. Above a threshold polymer concentration, whose magnitude is essentially controlled by the range of the potential, S(q) exhibits a peak whose position depends on the concentration. We take advantage of the close analogy between polymers and wormlike micelles and apply our model, using a Gaussian function for V, to quantitatively analyze experimental small angle neutron scattering profiles of semi-dilute solutions of hairy wormlike micelles. These samples, which consist in surfactant self-assembled flexible cylinders decorated by amphiphilic copolymer, provide indeed an appropriate experimental model system to study the structure of sterically interacting polymer solutions

Modeling inhibitory and excitatory synapse learning in the memristive neuron model

© 2017 by SCITEPRESS - Science and Technology Publications, Lda. All Rights Reserved. In this paper we present the results of simulation of exitatory Hebbian and inhibitory "sombrero" learning of a hardware architecture based on organic memristive elements and operational amplifiers implementing an artificial neuron we recently proposed. This is a first step towards the deployment on robots of a bioplausible simulation, currently developed in the neuro-biologically inspired cognitive architecture (NeuCogAr) implementing basic emotional states or affects in a computational system, in the context of our "Robot dream" project. The long term goal is to re-implement dopamine, serotonin and noradrenaline pathways of NeuCogAr in a memristive hardware

Modeling Inhibitory and Excitatory Synapse Learning in the Memristive Neuron Model

© 2017 by SCITEPRESS - Science and Technology Publications, Lda. All Rights Reserved. In this paper we present the results of simulation of exitatory Hebbian and inhibitory "sombrero" learning of a hardware architecture based on organic memristive elements and operational amplifiers implementing an artificial neuron we recently proposed. This is a first step towards the deployment on robots of a bioplausible simulation, currently developed in the neuro-biologically inspired cognitive architecture (NeuCogAr) implementing basic emotional states or affects in a computational system, in the context of our "Robot dream" project. The long term goal is to re-implement dopamine, serotonin and noradrenaline pathways of NeuCogAr in a memristive hardware