A theorem regarding families of topologically non-trivial fermionic systems

We introduce a Hamiltonian for fermions on a lattice and prove a theorem regarding its topological properties. We identify the topological criterion as a $\mathbb{Z}_2-$ topological invariant $p(\textbf{k})$ (the Pfaffian polynomial). The topological invariant is not only the first Chern number, but also the sign of the Pfaffian polynomial coming from a notion of duality. Such Hamiltonian can describe non-trivial Chern insulators, single band superconductors or multiorbital superconductors. The topological features of these families are completely determined as a consequence of our theorem. Some specific model examples are explicitly worked out, with the computation of different possible topological invariants.Comment: 6 page

Margarine quality monitoring based on reflectance spectroscopy

Margarine is a term that can indicate any of a wide range of butter substitutes. Due the raw material great diversity, margarine end-product quality characteristics are expected to be highly diversified. This article proposes the use of reflectance UV-VIS-SWNIR spectroscopy to monitor the margarine end-product quality properties. The main effort in this work was the development of a fast monitoring procedure to assess the quality of the manufactured margarines. The study was performed on two margarine products: regular margarine (<80% fat) and reduced-fat margarine (<60% fat). The nine product samples were collected during the production line normal operating conditions on different days. The samples had the surface cleaned in order to remove any sign of oxidized material. Then, spectra were collected by a reflectance probe normal to the sample surface. The samples temperature was recorded (10.0± 2.0ºC) and the probe-sample distance was kept constant for all the samples. The integration time was set to 40s for the collection of the five UV/VIS spectra per samples; the three VIS/NIR spectra per sample were collected using a 10s integration time. The data analysis was performed on each product and for each spectral range independently. The spectra were normalized by its maximum intensity and the corrected for using a robust multiplicative scatter correction algorithm. A principal component analysis was performed to the pre-process spectra and the multivariate statistical process control limits were determined with bootstrap for each product/spectral range. Results show that UV-VIS-SWNIR reflectance spectroscopy provides a quick and fast assessment of these products characteristics and thus it can be used as an indication of the overall product variability with can be plotted into a multivariate control chart

Sistemas computacionais para a previsão da qualidade e segurança alimentar : evolução e sistemas complexos

Os sistemas computacionais para a previsão da qualidade e segurança alimentar assumem hoje maior relevância na prototipagem e simulação da cadeia de distribuição (e.g. gestão do armazenamento, transporte e exposição). Este artigo descreve a evolução dos sistemas de previsão até aos actuais sistemas baseados em sistemas complexos (SC), para avaliar o impacto na qualidade e segurança dos alimento

A brainstem-like modulation approach for gait transition in a quadruped robot

The ability to traverse a wide variety of terrains while walking is basically a requirement for performing useful tasks in our human centric world. In this article, we propose a bio-inspired robotic controller able to generate locomotion and to easily switch between different type of gaits. In order to improve the robot stability and response while locomoting, we adjust both the duty factor and the interlimb phase relationships, according to the velocities. We extend previous work, by applying nonlinear oscillators to generate the rhythmic locomotor movements for a quadruped robot, similarly to the biological counterparts. The generated trajectories are modulated by a drive signal, that modifies the oscillator frequency, amplitude and the coupling parameters among the oscillators, proportionally to the drive signal strength. By increasing the drive signal, locomotion can be elicited and velocity increased while switching to the appropriate gaits. This drive signal can be specified according to sensory information or set a priori. The implementation of the central pattern generator network and the activity modulation layer is shown in simulation and in an AIBO robot

Improved radial heat sink for led lamp cooling

This paper presents a numerical study concerning an improved heat sink for a light emitting diodes (LED) lamp operating under natural convection conditions. Basic geometry of the heat sink is of cylindrical nature, to be obtained from cutting an aluminum extruded bar comprising a cylindrical central core and a number of uniformly distributed radial fins. Minimum diameter of the central core is fixed and the parameters to be explored are the number of fins, their thickness, length (radial dimension) and height. Although not included in the numerical simulations, the thermal resistance due to the use of a thin thermal interface material (TIM) layer between the LED lamp back and the heat sink is taken into account in the analysis. The main objective of the heat sink is to cool the LED lamp so that the lamp maximum temperature at the contact region with the heat sink is maintained below the critical temperature given by the manufacturer. This is a crucial aspect in what concerns the expected lifetime of the LED lamp and should be achieved at the expenses of as low as possible aluminum mass. Taking these criteria in mind, a design procedure is proposed and followed in the search for the improved heat sink to cool a particular LED lamp. Results obtained with the commercial code ANSYS-CFX clearly show the relative importance of the different governing parameters on the heat sink performance and allow the choice of the better solution within the frame of dimensional constrains. Although the present results concern a particular LED lamp, the proposed methodology can be extended to other types of heat sinks for general light and/or electronic components

DC Microgrids: Benefits, Architectures, Perspectives and Challenges

One of the major paradigm shifts that will be predictably observed in the energy mix is related to distribution networks. Until now, this type of electrical grid was characterized by an AC transmission. However, a new concept is emerging, as the electrical distribution networks characterized by DC transmission are beginning to be considered as a promising solution due to technological advances. In fact, we are now witnessing a proliferation of DC equipment associated with renewable energy sources, storage systems and loads. Thus, such equipment is beginning to be considered in different contexts. In this way, taking into consideration the requirement for the fast integration of this equipment into the existing electrical network, DC networks have started to become important. On the other hand, the importance of the development of these DC networks is not only due to the fact that the amount of DC equipment is becoming huge. When compared with the classical AC transmission systems, the DC networks are considered more efficient and reliable, not having any issues regarding the reactive power and frequency control and synchronization. Although much research work has been conducted, several technical aspects have not yet been defined as standard. This uncertainty is still an obstacle to a faster transition to this type of network. There are also other aspects that still need to be a focus of study and research in order to allow this technology to become a day-to-day solution. Finally, there are also many applications in which this kind of DC microgrid can be used, but they have still not been addressed. Thus, all these aspects are considered important challenges that need to be tackled. In this context, this paper presents an overview of the existing and possible solutions for this type of microgrid, as well as the challenges that need to be faced now.info:eu-repo/semantics/publishedVersio

LogCHEM: interactive discriminative mining of chemical structure

One of the most well known successes of Inductive Logic Programming (ILP) is on Structure-Activity Relationship (SAR) problems. In such problems, ILP has proved several times to be capable of constructing expert comprehensible models that hell) to explain the activity of chemical compounds based on their structure and properties. However, despite its successes on SAR problems, ILP has severe scalability problems that prevent its application oil larger datasets. In this paper we present LogCHEM, an ILP based tool for discriminative interactive mining of chemical fragments. LogCHEM tackles ILP's scalability issues in the context of SAR applications. We show that LogCHEM benefits from the flexibility of ILP both by its ability to quickly extend the original mining model, and by its ability, to interface with external tools. Furthermore, We demonstrate that LogCHEM can be used to mine effectively large chemoinformatics datasets, namely, several datasets from EPA's DSSTox database and on a dataset based on the DTP AIDS anti-viral screen