Combining non-dominance, objective-order and spread metric to extend firefly algorithm to multi-objective optimization

In this paper, we propose an extension of the firefly algorithm (FA) to multi-objective optimization. FA is a swarm intelligence optimization algorithm inspired by the flashing behavior of fireflies at night that is capable of computing global solutions to continuous optimization problems. Our proposal relies on a fitness assignment scheme that gives lower fitness values to the positions of fireflies that correspond to non-dominated points with smaller aggregation of objective function distances to the minimum values. Furthermore, FA randomness is based on the spread metric to reduce the gaps between consecutive non-dominated solutions. The obtained results from the preliminary computational experiments show that our proposal gives a dense and well distributed approximated Pareto front with a large number of points.

New control algorithm for single-phase series active power filter

This paper presents a single-phase Series Active Power Filter (Series APF) for mitigation of the load voltage harmonic content, while maintaining the voltage on the DC side regulated without the support of a voltage source. The proposed series active power filter control algorithm eliminates the additional voltage source to regulate the DC voltage, and with the adopted topology it is not used a coupling transformer to interface the series active power filter with the electrical power grid. The paper describes the control strategy which encapsulates the grid synchronization scheme, the compensation voltage calculation, the damping algorithm and the dead-time compensation. The topology and control strategy of the series active power filter have been evaluated in simulation software and simulations results are presented. Experimental results, obtained with a developed laboratorial prototype, validate the theoretical assumptions, and are within the harmonic spectrum limits imposed by the international recommendations of the IEEE-519 Standard.

MOEA/VAN: Multiobjective Evolutionary Algorithm based on Vector Angle Neighborhood

Natural selection favors the survival and reproduction of organisms that are best adapted to their environment. Selection mechanism in evolutionary algorithms mimics this process, aiming to create environmental conditions in which artificial organisms could evolve solving the problem at hand. This paper proposes a new selection scheme for evolutionary multiobjective optimization. The similarity measure that defines the concept of the neighborhood is a key feature of the proposed selection. Contrary to commonly used approaches, usually defined on the basis of distances between either individuals or weight vectors, it is suggested to consider the similarity and neighborhood based on the angle between individuals in the objective space. The smaller the angle, the more similar individuals. This notion is exploited during the mating and environmental selections. The convergence is ensured by minimizing distances from individuals to a reference point, whereas the diversity is preserved by maximizing angles between neighboring individuals. Experimental results reveal a highly competitive performance and useful characteristics of the proposed selection. Its strong diversity preserving ability allows to produce a significantly better performance on some problems when compared with stat-of-the-art algorithms.

The role of automatic shape and position recognitionin streamlining manufacturing

The main features of most components consist of simple basic functional geometries: planes, cylinders, spheres and cones. Shape and position recognition of these geometries is essential for dimensional characterization of components, and represent an important contribution in the life cycle of the product, concerning in particular the manufacturing and inspection processes of the final product. This work aims to establish an algorithm to automatically recognize such geometries, without operator intervention. Using differential geometry large volumes of data can be treated and the basic functional geometries to be dealt recognized. The original data can be obtained by rapid acquisition methods, such as 3D survey or photography, and then converted into Cartesian coordinates. The satisfaction of intrinsic decision conditions allows different geometries to be fast identified, without operator intervention. Since inspection is generally a time consuming task, this method reduces operator intervention in the process. The algorithm was first tested using geometric data generated in MATLAB and then through a set of data points acquired by measuring with a coordinate measuring machine and a 3D scan on real physical surfaces. Comparison time spent in measuring is presented to show the advantage of the method. The results validated the suitability and potential of the algorithm hereby proposed

Differential activation of the default mode network in jet lagged individuals

Long-term exposure to transmeridian flights has been shown to impact cognitive functioning. Nevertheless, the immediate effects of jet lag in the activation of specific brain networks have not been investigated. We analyzed the impact of short-term jet lag on the activation of the default mode network (DMN). A group of individuals who were on a transmeridian flight and a control group went through a functional magnetic resonance imaging acquisition. Statistical analysis was performed to test for differences in the DMN activation between groups. Participants from the jet lag group presented decreased activation in the anterior nodes of the DMN, specifically in bilateral medial prefrontal and anterior cingulate cortex. No areas of increased activation were observed for the jet lag group. These results may be suggestive of a negative impact of jet lag on important cognitive functions such as introspection, emotional regulation and decision making in a few days after individuals arrive at their destination.

3D representation of the urban evolution of Braga using the cityengine tool

The morphological evolution of the city of Braga has been the subject of several studies focusing on different urban areas in different periods. Using the accumulated knowledge provided by the available archaeological, historical and iconographic data of Braga, from the Roman times to the nineteenth century, we intend to present a working methodology for 3D representation of urban areas and its evolution, using the CityEngine ESRI tool. Different types of graphic and cartographic data will be integrated in an archaeological information system for the characterization of urban buildings. Linking this information system to the rules of characterization of urban spaces through the CityEngine tool, we can create the 3D urban spaces and their changes. The building characterization rules include several parameters of architectural elements that can be dynamically changed according the latest information. This methodology will be applied to the best known areas within of the city allowing the creation of different and dynamic layouts. Considerations about the concepts, challenges and constraints of using the CityEngine tool for recording and representing urban evolution knowledge will be discussed.

Reconstructing historical forest cover change in the Lower Amazon floodplains using the LandTrendr algorithm

ABSTRACTThe Amazon várzeas are an important component of the Amazon biome, but anthropic and climatic impacts have been leading to forest loss and interruption of essential ecosystem functions and services. The objectives of this study were to evaluate the capability of the Landsat-based Detection of Trends in Disturbance and Recovery (LandTrendr) algorithm to characterize changes in várzeaforest cover in the Lower Amazon, and to analyze the potential of spectral and temporal attributes to classify forest loss as either natural or anthropogenic. We used a time series of 37 Landsat TM and ETM+ images acquired between 1984 and 2009. We used the LandTrendr algorithm to detect forest cover change and the attributes of "start year", "magnitude", and "duration" of the changes, as well as "NDVI at the end of series". Detection was restricted to areas identified as having forest cover at the start and/or end of the time series. We used the Support Vector Machine (SVM) algorithm to classify the extracted attributes, differentiating between anthropogenic and natural forest loss. Detection reliability was consistently high for change events along the Amazon River channel, but variable for changes within the floodplain. Spectral-temporal trajectories faithfully represented the nature of changes in floodplain forest cover, corroborating field observations. We estimated anthropogenic forest losses to be larger (1.071 ha) than natural losses (884 ha), with a global classification accuracy of 94%. We conclude that the LandTrendr algorithm is a reliable tool for studies of forest dynamics throughout the floodplain.

Measurement of differential J/psi production cross sections and forward-backward ratios in p plus Pb collisions with the ATLAS detector

Measurements of differential cross sections for J/ψ production in p+Pb collisions at sNN−−−−√=5.02 TeV at the CERN Large Hadron Collider with the ATLAS detector are presented. The data set used corresponds to an integrated luminosity of 28.1 nb−1. The J/ψ mesons are reconstructed in the dimuon decay channel over the transverse momentum range 8differential cross section for production of nonprompt J/ψ is compared to a FONLL calculation that does not include nuclear effects. Forward-backward production ratios are presented and compared to theoretical predictions. These results complement previously published results by covering a region of higher transverse momentum and more central rapidity. They thus constrain the kinematic dependence of nuclear modifications of charmonium and b-quark production in p+Pb collisions.

Microstructural evolution of Au/TiO2 nanocomposite films: The influence of Au concentration and thermal annealing

Nanocomposite thin films consisting of a dielectric matrix, such as titanium oxide (TiO2), with embedded gold (Au) nanoparticles were prepared and will be analysed and discussed in detail in the present work. The evolution of morphological and structural features was studied for a wide range of Au concentrations and for annealing treatments in air, for temperatures ranging from 200 to 800 °C. Major findings revealed that for low Au atomic concentrations (at.%), there are only traces of clustering, and just for relatively high annealing temperatures, T ≥ 500 °C. Furthermore, the number of Au nanoparticles is extremely low, even for the highest annealing temperature, T = 800 °C. It is noteworthy that the TiO2 matrix also crystallizes in the anatase phase for annealing temperatures above 300 °C. For intermediate Au contents (5 at.% ≤ CAu ≤ 15 at.%), the formation of gold nanoclusters was much more evident, beginning at lower annealing temperatures (T ≥ 200 °C) with sizes ranging from 2 to 25 nm as the temperature increased. A change in the matrix crystallization from anatase to rutile was also observed in this intermediate range of compositions. For the highest Au concentrations (> 20 at.%), the films tended to form relatively larger clusters, with sizes above 20 nm (for T ≥ 400 °C). It is demonstrated that the structural and morphological characteristics of the films are strongly affected by the annealing temperature, as well as by the particular amounts, size and distribution of the Au nanoparticles dispersed in the TiO2 matrix.

Evolution of the functional properties of titanium–silver thin films for biomedical applications: Influence of in-vacuum annealing

In this work, the thermal stability of TiAgx thin films, deposited by magnetron sputtering, was evaluated, envisaging their application in biomedical devices, namely as electrodes for biosignal acquisition. Based on the composition and microstructural characterization, a set of four representative TiAgx thin films was selected in order to infer whether they are thermally stable in terms of functional properties. In order to achieve this purpose, the structural and morphological evolution of the films with annealing temperature was correlated with their electrical, mechanical and thermal properties. Two distinct zones were identified and two samples from each zone were extensively analysed. In the first zone (zone I), Ti was the main component (Ti-rich zone) while in the second, zone II, the Ag content was more significant. The selected samples were annealed in vacuum at four different temperatures up to 500 oC. For the samples produced within zone I, small microstructural changes were observed due to the recrystallization of the Ti structure and grain size increment. Also, no significant changes were observed with annealing temperature regarding the f l ’ functional properties, being thermally stable up to 500 oC. For higher Ag contents (zone II) the energy supplied by thermal treatments was sufficient to activate the crystallization of Ti-Ag intermetallic phases. A strong increase of the grain size of these phases was also reported. The structural and morphological organization proved to be determinant for the physical responses of the TiAgx system. The hardness and Y g’s modulus were significantly improved with the formation of the intermetallic phases. The silver addition and annealing treatments also played an important role in the electrical conductivity of the films, which was once again improved by the formation of Ti-Ag phases. The thermal diffusivity of the films was practically unchanged with the heat-treatment. This set of results shows that this intermetallic-like thin film system has good thermal stability up to high temperatures (as high as 500 oC), which in case of the highest Ag content zone is particularly evident for electrical and mechanical properties, showing an important improvement. Hardness increases about three times, while resistivity values become half of those from the lowest Ag contents zone. These set of characteristics are consistent with the targeted applications, namely in terms of biomedical sensing devices.

Silicon nanowire arrays coupled with cobalt phosphide spheres as low-cost photocathodes for efficient solar hydrogen evolution

We demonstrate the first example of silicon nanowire array photocathodes coupled with hollow spheres of the emerging earth-abundant cobalt phosphide catalysts. Compared to bare silicon nanowire arrays, the hybrid electrodes exhibit significantly improved photoelectrochemical performance toward the solar-driven H2 evolution reaction.

High-level of viral genomic diversity in cervical cancers: a Brazilian study on human papillomavirus type 16

Invasive cervical cancer (ICC) is the third most frequent cancer among women worldwide and is associated with persistent infection by carcinogenic human papillomaviruses (HPVs). The combination of large populations of viral progeny and decades of sustained infection may allow for the generation of intra-patient diversity, in spite of the assumedly low mutation rates of PVs. While the natural history of chronic HPVs infections has been comprehensively described, within-host viral diversity remains largely unexplored. In this study we have applied next generation sequencing to the analysis of intra-host genetic diversity in ten ICC and one condyloma cases associated to single HPV16 infection. We retrieved from all cases near full-length genomic sequences. All samples analyzed contained polymorphic sites, ranging from 3 to 125 polymorphic positions per genome, and the median probability of a viral genome picked at random to be identical to the consensus sequence in the lesion was only 40%. We have also identified two independent putative duplication events in two samples, spanning the L2 and the L1 gene, respectively. Finally, we have identified with good support a chimera of human and viral DNA. We propose that viral diversity generated during HPVs chronic infection may be fueled by innate and adaptive immune pressures. Further research will be needed to understand the dynamics of viral DNA variability, differentially in benign and malignant lesions, as well as in tissues with differential intensity of immune surveillance. Finally, the impact of intralesion viral diversity on the long-term oncogenic potential may deserve closer attention.

Evolution of the gene regulatory network controlling flower dorsoventral asymmetry

Tese de Doutoramento em Biologia de Plantas.

Embedding, evolution, and validation of model-driven spreadsheets

This paper proposes and validates a model-driven software engineering technique for spreadsheets. The technique that we envision builds on the embedding of spreadsheet models under a widely used spreadsheet system. This means that we enable the creation and evolution of spreadsheet models under a spreadsheet system. More precisely, we embed ClassSheets, a visual language with a syntax similar to the one offered by common spreadsheets, that was created with the aim of specifying spreadsheets. Our embedding allows models and their conforming instances to be developed under the same environment. In practice, this convenient environment enhances evolution steps at the model level while the corresponding instance is automatically co-evolved.Finally,wehave designed and conducted an empirical study with human users in order to assess our technique in production environments. The results of this study are promising and suggest that productivity gains are realizable under our model-driven spreadsheet development setting.

Differential predictors of acute post-surgical pain intensity after abdominal hysterectomy and major joint arthroplasty

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