Performing edge detection by difference of Gaussians using q-Gaussian kernels

In image processing, edge detection is a valuable tool to perform the extraction of features from an image. This detection reduces the amount of information to be processed, since the redundant information (considered less relevant) can be unconsidered. The technique of edge detection consists of determining the points of a digital image whose intensity changes sharply. This changes are due to the discontinuities of the orientation on a surface for example. A well known method of edge detection is the Difference of Gaussians (DoG). The method consists of subtracting two Gaussians, where a kernel has a standard deviation smaller than the previous one. The convolution between the subtraction of kernels and the input image results in the edge detection of this image. This paper introduces a method of extracting edges using DoG with kernels based on the q-Gaussian probability distribution, derived from the q-statistic proposed by Constantino Tsallis. To demonstrate the method's potential, we compare the introduced method with the traditional DoG using Gaussians kernels. The results showed that the proposed method can extract edges with more accurate details.Comment: 5 pages, 5 figures, IC-MSQUARE 201

What are patents revealing?

Metzger, P., Mendonça, S., Silva, J. A., & Damásio, B. (2023). Battery innovation and the Circular Economy: What are patents revealing? Renewable Energy, 209(June), 516-532. https://doi.org/10.1016/j.renene.2023.03.132---Funding: Bruno Damásio and Philipp Metzger acknowledge the financial support provided by Fundac̨ão para a Ciência e a Tecnologia, Portugal (FCT) under the project UIDB/04152/2020 — Centro de Investigação em Gestão de Informação (MagIC). Sandro Mendonça acknowledges support by FCT, Portugal, by the Business Research Unit (BRU-IUL) and by UECE-REM (Research Unit on Complexity and Economics). BRU-IUL also benefited from grants UID/GES/00315/2013, UIDB/00315/2020; UIDB/05069/2020; PTDC/EGE-ECO/30690/2017 and is part of the project PTDC/EGE-ECO/30690/2017. José Silva acknowledges FCT support under the project UIDB/50019/2020–IDL.This analysis of over 90,000 secondary battery innovations (measured by international patent families) provides a comprehensive account of the long-run progress of a knowledge base with a key role in the transition to a transformative, closed-loop, Circular Economy. Innovation accelerated globally from 2000 to 2019, a sustained dynamic mostly originating in Asia. Patterns of less toxicity and more diversity in technological trajectories are detected and found to bear evidence of pro-circularity. We find a number of emergent technological trajectories, such as solid-state, lithium-sulfur, redox-flow and sodium-ion batteries, each one with a different potential to push ahead the circularity pathway, and which allow for the detection of country clusters. Through a methodology that can be of interest for further research, we examine the extent to which batteries have circular characteristics.publishersversionpublishe

An efficient adaptive data-link-layer architecture for LoRa networks

LoRa is one of the most popular low-power wireless network technologies for implementation of the Internet of Things, with the advantage of providing long-range communication, but lower data rates, when compared with technologies such as Zigbee or Bluetooth. LoRa is a single-channel physical layer technology on top of which LoRaWAN implements a more complex multi-channel network with enhanced functionalities, such as adaptive data rate. However, LoRaWAN relies on expensive hardware to support these functionalities. This paper proposes a LoRa data-link-layer architecture based on a multi-layer star network topology that adapts relevant LoRa parameters for each end node dynamically taking into account its link distance and quality in order to balance communication range and energy consumption. The developed solution is comprised of multiple components, including a LoRa parameter calculator to help the user to configure the network parameters, a contention-free MAC protocol to avoid collisions, and an adaptive spreading factor and transmission power mechanism. These components work together to ensure a more efficient use of the chosen ISM band and end node resources, but with low-cost implementation and operation requirements.This research was funded by FEDER through COMPETE2020—Programa Operacional Competitividade e Internacionalização (POCI) grant number POCI-01-0145-FEDER-028247 and by FCT—Fundação para a Ciência e Tecnologia within the R&D Units Project Scope: UIDB/00319/202

Development and characterization of PLA nanoparticles as carriers for topical delivery

Nanoparticles are seen today as one of the best approaches for the delivery of drugs into the skin. Poly (Lactic Acid) (PLA) is biocompatible and biodegradable and already approved for clinical use. Thus, this work aimed to study the effect of several parameters on the properties of PLA nanoparticles (PLA-NPs) intended for topical delivery. The yield of nanoparticles formation and entrapment efficiencies of lipophilic and hydrophilic model compounds in PLA-NPs were assessed. We evaluated the effects of mechanical stirring, solvent composition and presence of tri-bloc polymers on the protocol for the production of PLA-NPs. The best protocol provided a monodispersed population of non-cytotoxic spherical particles of !150 nm and a yield of nanoparticles formation of !90%. This formulation also proved to be efficient in the encapsulation of lipophilic and hydrophilic model compounds (>80%). The best protocol for the production of PLA-NPs includes a nanoprecipitation step, which is easily up scalable

Dynamics of Serial Manipulators using Dual Quaternion Algebra

This paper presents two approaches to obtain the dynamical equations of serial manipulators using dual quaternion algebra. The first one is based on the recursive Newton-Euler formulation and uses twists and wrenches instead of 3D vectors, which simplifies the classic procedure by removing the necessity of exhaustive geometrical analyses since wrenches and twists are propagated through high-level algebraic operations. Furthermore, the proposed formulation works for arbitrary types of joints and does not impose any particular convention for the propagation of twists. The second approach, based on Gauss's Principle of Least Constraint (GPLC), takes into account elements of the dual quaternion algebra and provides a linear relationship between twists derivatives and joint accelerations, which can be particularly useful in robot control. Differently from other approaches based on the GPLC, which have representational singularities or require constraints, our method does not have those drawbacks. We present a thorough methodology to obtain the computational cost of both algorithms and compared them with their classic counterparts. Although our current formulations are more computationally expensive, they are more general than their counterparts in the state of the art. Simulation results showed that both methods are as accurate as the classic recursive Newton-Euler algorithm.Comment: Submitted for publication (currently under review