Materiais electrocrómicos e mecaelectroquímicos: contextualização e experimentação na disciplina de química do 12º ano

Durante os últimos 1O anos, em particular, tem-se assistido à descoberta e desenvolvimento de materiais com propriedades únicas e potencialmente úteis em vários domínios da Ciência e Tecnologia. Quer seja na área das Ciências Biomédicas e do Ambiente, na área das Novas Tecnologias de Informação e Comunicação ou nas Novas Tecnologias relacionadas com sistemas de Conversão e Armazenamento de Energia Eléctrica, encontram-se inúmeros exemplos de Novos Materiais com propriedades muito interessantes, e cujas aplicações inovadoras podem revolucionar o nosso Mundo. O presente trabalho é uma proposta de contextualização e experimentação do tema "Materiais Electrocrómicos e Mecaelectroquímicos" no Programa de Química de 12° Ano, nomeadamente na terceira Unidade - Plásticos, Vidros e Novos Materiais. Neste, é apresentada uma sub-unidade que possa integrar a unidade referida. Faz-se especial referência às aplicações dos polímeros condutores, que pela sua inovação e actualidade tomam a leccionação do tema mais apelativa, interessante e facilitadora de uma literacia científica. São apresentadas experiências laboratoriais demonstrativas e elucidativas do tema em questão. Como forma de apoiar a leccionação do referido tema, é apresentada a proposta de uma animação gráfica animada em Power Point. ABSTRACT: During the past 1O years, in particular, it has witnessed to the discovery and development of materials with unique properties and potentially useful in various fields of Science and Technology. There are numerous examples of new materials in different areas, such as Biomedical, Energy and Environmental Sciences and New information and Communication Technologies, with very interesting properties, and whose innovative applications can have an outstanding impact in our world. This dissertation is a proposal of contextualization and experimentation of theme "Electrochromic Materials and Electrochemical Artificial Muscles" in the Program of Chemistry, in 12th year, particularly in the third unit - Plastics, Glass and New Materials. lt will present a sub-unit that can integrate the unit above. The definitions and some applications of the Electrochromic Materials and Electrochemical Artificial Muscles are showed. Demonstrative and illustrative laboratory experiments of the theme are proposed. ln order to support the teaching of that subject, it is presented an animated graphical presentation in Power Point.

Multi-scale analysis of active landslides using two-pass differential interferometry

Landslides are common features of the landscape of the north-central Apennine mountain range and cause frequent damage to human facilities and infrastructure. Most of these landslides move periodically with moderate velocities and, only after particular rainfall events, some accelerate abruptly. Synthetic aperture radar interferometry (InSAR) provides a particularly convenient method for studying deforming slopes. We use standard two-pass interferometry, taking advantage of the short revisit time of the Sentinel-1 satellites. In this paper we present the results of the InSAR analysis developed on several study areas in central and Northern Italian Apennines. The aims of the work described within the articles contained in this paper, concern: i) the potential of the standard two-pass interferometric technique for the recognition of active landslides; ii) the exploration of the potential related to the displacement time series resulting from a two-pass multiple time-scale InSAR analysis; iii) the evaluation of the possibility of making comparisons with climate forcing for cognitive and risk assessment purposes. Our analysis successfully identified more than 400 InSAR deformation signals (IDS) in the different study areas corresponding to active slope movements. The comparison between IDSs and thematic maps allowed us to identify the main characteristics of the slopes most prone to landslides. The analysis of displacement time series derived from monthly interferometric stacks or single 6-day interferograms allowed the establishment of landslide activity thresholds. This information, combined with the displacement time series, allowed the relationship between ground deformation and climate forcing to be successfully investigated. The InSAR data also gave access to the possibility of validating geographical warning systems and comparing the activity state of landslides with triggering probability thresholds.

High-resolution stratigraphy and seismic site characterization of late Quaternary paleovalley systems (Adriatic coastal plain, Italy)

In highly urbanized coastal lowlands, effective site characterization is crucial for assessing seismic risk. It requires a comprehensive stratigraphic analysis of the shallow subsurface, coupled with the precise assessment of the geophysical properties of buried deposits. In this context, late Quaternary paleovalley systems, shallowly buried fluvial incisions formed during the Late Pleistocene sea-level fall and filled during the Holocene sea-level rise, are crucial for understanding seismic amplification due to their soft sediment infill and sharp lithologic contrasts. In this research, we conducted high-resolution stratigraphic analyses of two regions, the Pescara and Manfredonia areas along the Adriatic coastline of Italy, to delineate the geometries and facies architecture of two paleovalley systems. Furthermore, we carried out geophysical investigations to characterize the study areas and perform seismic response analyses. We tested the microtremor-based horizontal-to-vertical spectral ratio as a mapping tool to reconstruct the buried paleovalley geometries. We evaluated the relationship between geological and geophysical data and identified the stratigraphic surfaces responsible for the observed resonances. To perform seismic response analysis of the Pescara paleovalley system, we integrated the stratigraphic framework with microtremor and shear wave velocity measurements. The seismic response analysis highlights strong seismic amplifications in frequency ranges that can interact with a wide variety of building types. Additionally, we explored the applicability of artificial intelligence in performing facies analysis from borehole images. We used a robust dataset of high-resolution digital images from continuous sediment cores of Holocene age to outline a novel, deep-learning-based approach for performing automatic semantic segmentation directly on core images, leveraging the power of convolutional neural networks. We propose an automated model to rapidly characterize sediment cores, reproducing the sedimentologist's interpretation, and providing guidance for stratigraphic correlation and subsurface reconstructions.

Non-line-of-sight localization with frequency-selective metasurfaces

An emerging technology, that Smart Radio Environments rely on to improve wireless link quality, are Reconfigurable Intelligent Surfaces (RISs). A RIS, in general, can be understood as a thin layer of EM composite material, typically mounted on the walls or ceilings of buildings, which can be reconfigured even after its deployment in the network. RISs made by composing artificial materials in an engineered way, in order to obtain unconventional characteristics, are called metasurfaces. Through the programming of the RIS, it is possible to control and/or modify the radio waves that affect it, thus shaping the radio environment. To overcome the limitations of RISs, the metaprism represents an alternative: it is a passive and non-reconfigurable frequency-selective metasurface that acts as a metamirror to improve the efficiency of the wireless link. In particular, using an OFDM (Orthogonal Frequency-Division Multiplexing) signaling it is possible to control the reflection of the signal, suitably selecting the sub-carrier assigned to each user, without having to interact with the metaprism or having to estimate the CSI. This thesis investigates how OFDM signaling and metaprism can be used for localization purposes, especially to extend the coverage area at low cost, in a scenario where the user is in NLoS (Non-line-of-sight) conditions with respect to the base station, both single antenna. In particular, the paper concerns the design of the analytical model and the corresponding Matlab implementation of a Maximum Likelihood (ML) estimator able to estimate the unknown position, behind an obstacle, from which a generic user transmits to a base station, exploiting the metaprism.

Visual Navigation In The Neotropical Ant Odontomachus Hastatus (formicidae, Ponerinae), A Predominantly Nocturnal, Canopy-dwelling Predator Of The Atlantic Rainforest.

The arboreal ant Odontomachus hastatus nests among roots of epiphytic bromeliads in the sandy forest at Cardoso Island (Brazil). Crepuscular and nocturnal foragers travel up to 8m to search for arthropod prey in the canopy, where silhouettes of leaves and branches potentially provide directional information. We investigated the relevance of visual cues (canopy, horizon patterns) during navigation in O. hastatus. Laboratory experiments using a captive ant colony and a round foraging arena revealed that an artificial canopy pattern above the ants and horizon visual marks are effective orientation cues for homing O. hastatus. On the other hand, foragers that were only given a tridimensional landmark (cylinder) or chemical marks were unable to home correctly. Navigation by visual cues in O. hastatus is in accordance with other diurnal arboreal ants. Nocturnal luminosity (moon, stars) is apparently sufficient to produce contrasting silhouettes from the canopy and surrounding vegetation, thus providing orientation cues. Contrary to the plain floor of the round arena, chemical cues may be important for marking bifurcated arboreal routes. This experimental demonstration of the use of visual cues by a predominantly nocturnal arboreal ant provides important information for comparative studies on the evolution of spatial orientation behavior in ants. This article is part of a Special Issue entitled: Neotropical Behaviour.

Navigation assistance for wayfinding in the virtual environments: taxonomy and a survey

Efficient Navigation is essential for the user-acceptance of the Virtual Environments (VEs), but it is also inherently, a difficult task to perform. Resulting research in the area provides users with great variety of navigation assistance in VEs however it is still known to be inadequate, complex and suffers through many limitations. In this paper we discuss the task of navigation in the virtual environments and record the wayfinding assistance currently available for the VEs. The paper introduces taxonomy of navigation and categorizes the aids on basis of the functions performed. The paper provides views on current work performed in the area of non-speech auditory aids. Further we conclude by providing views on the important areas that require further investigation and research.

JSEG-based image segmentation in computer vision for agricultural mobile robot navigation

This project aims to apply image processing techniques in computer vision featuring an omnidirectional vision system to agricultural mobile robots (AMR) used for trajectory navigation problems, as well as localization matters. To carry through this task, computational methods based on the JSEG algorithm were used to provide the classification and the characterization of such problems, together with Artificial Neural Networks (ANN) for pattern recognition. Therefore, it was possible to run simulations and carry out analyses of the performance of JSEG image segmentation technique through Matlab/Octave platforms, along with the application of customized Back-propagation algorithm and statistical methods in a Simulink environment. Having the aforementioned procedures been done, it was practicable to classify and also characterize the HSV space color segments, not to mention allow the recognition of patterns in which reasonably accurate results were obtained.

ANN statistical image recognition method for computer vision in agricultural mobile robot navigation

The main application area in this project, is to deploy image processing and segmentation techniques in computer vision through an omnidirectional vision system to agricultural mobile robots (AMR) used for trajectory navigation problems, as well as localization matters. Thereby, computational methods based on the JSEG algorithm were used to provide the classification and the characterization of such problems, together with Artificial Neural Networks (ANN) for image recognition. Hence, it was possible to run simulations and carry out analyses of the performance of JSEG image segmentation technique through Matlab/Octave computational platforms, along with the application of customized Back-propagation Multilayer Perceptron (MLP) algorithm and statistical methods as structured heuristics methods in a Simulink environment. Having the aforementioned procedures been done, it was practicable to classify and also characterize the HSV space color segments, not to mention allow the recognition of segmented images in which reasonably accurate results were obtained. © 2010 IEEE.

Pattern recognition structured heuristics methods for image processing in mobile robot navigation

In this project, the main focus is to apply image processing techniques in computer vision through an omnidirectional vision system to agricultural mobile robots (AMR) used for trajectory navigation problems, as well as localization matters. To carry through this task, computational methods based on the JSEG algorithm were used to provide the classification and the characterization of such problems, together with Artificial Neural Networks (ANN) for pattern recognition. Therefore, it was possible to run simulations and carry out analyses of the performance of JSEG image segmentation technique through Matlab/Octave platforms, along with the application of customized Back-propagation algorithm and statistical methods as structured heuristics methods in a Simulink environment. Having the aforementioned procedures been done, it was practicable to classify and also characterize the HSV space color segments, not to mention allow the recognition of patterns in which reasonably accurate results were obtained. ©2010 IEEE.

Comparing support vector machines and artificial neural networks in the recognition of steering angle for driving of mobile robots through paths in plantations

The use of mobile robots turns out to be interesting in activities where the action of human specialist is difficult or dangerous. Mobile robots are often used for the exploration in areas of difficult access, such as rescue operations and space missions, to avoid human experts exposition to risky situations. Mobile robots are also used in agriculture for planting tasks as well as for keeping the application of pesticides within minimal amounts to mitigate environmental pollution. In this paper we present the development of a system to control the navigation of an autonomous mobile robot through tracks in plantations. Track images are used to control robot direction by pre-processing them to extract image features. Such features are then submitted to a support vector machine and an artificial neural network in order to find out the most appropriate route. A comparison of the two approaches was performed to ascertain the one presenting the best outcome. The overall goal of the project to which this work is connected is to develop a real time robot control system to be embedded into a hardware platform. In this paper we report the software implementation of a support vector machine and of an artificial neural network, which so far presented respectively around 93% and 90% accuracy in predicting the appropriate route. (C) 2013 The Authors. Published by Elsevier B.V. Selection and peer review under responsibility of the organizers of the 2013 International Conference on Computational Science

A connected view of the whole internal navigation of the United States; natural and artificial, present and prospective: corrected and improved from the edition of 1826, and much enlarged, from authentic materials, down to the present time. With a sheet map, and numerous engraved profiles ... The map ... is projected, on a reduced scale, from Tanner's ... map of the United States ...

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Resonance studies of artificial earth satellites

Orbit determination from artificial satellite observations is a key process in obtaining information about the Earth and its environment. A study of the perturbations experienced by these satellites enables knowledge to be gained of the upper atmosphere, the gravity field, ocean tides, solid-Earth tides and solar radiation. The gravity field is expressed as a double infinite series of associated Legendre functions (tesseral harmonics). In contemporary global gravity field models the overall geoid is well determined. An independent check on these gravity field harmonics of a particular order may be made by analysis of satellites that pass through resonance of that order. For such satellites the perturbations of the orbital elements close to resonance are analysed to derive lumped harmonic coefficients. The orbital parameters of 1984-106A have been determined at 43 epochs, during which time the satellite was close to 14th order resonance. Analysis of the inclination and eccentricity yielded 6 lumped harmonic coefficients of order 14 whilst analysis of the mean motion yielded additional pairs of lumped harmonics of orders 14, 28 and 42, with the 14th order harmonics superseding those obtained from analysis of the inclination. This thesis concentrates in detail on the theoretical changes of a near-circular satellite orbit perturbed by the Earth's gravity field under the influence of minimal air-drag whilst in resonance with the Earth. The satellite 1984-106A experienced the interesting property of being temporarily trapped with respect to a secondary resonance parameter due to the low air-drag in 1987. This prompted the theoretical investigation of such a phenomenon. Expressions obtained for the resonance parameter led to the determination of 8 lumped harmonic coefficients, coincidental to those already obtained. All the derived lumped harmonic values arc used to test the accuracy of contemporary gravity field models and the underlying theory in this thesis.

Pitfalls of artificial grouping and stratification of scientific journals based on their Impact Factor: a case study in Brazilian Zoology

The present contribution explores the impact of the QUALIS metric system for academic evaluation implemented by CAPES (Coordination for the Development of Personnel in Higher Education) upon Brazilian Zoological research. The QUALIS system is based on the grouping and ranking of scientific journals according to their Impact Factor (IF). We examined two main points implied by this system, namely: 1) its reliability as a guideline for authors; 2) if Zoology possesses the same publication profile as Botany and Oceanography, three fields of knowledge grouped by CAPES under the subarea "BOZ" for purposes of evaluation. Additionally, we tested CAPES' recent suggestion that the area of Ecology would represent a fourth field of research compatible with the former three. Our results indicate that this system of classification is inappropriate as a guideline for publication improvement, with approximately one third of the journals changing their strata between years. We also demonstrate that the citation profile of Zoology is distinct from those of Botany and Oceanography. Finally, we show that Ecology shows an IF that is significantly different from those of Botany, Oceanography, and Zoology, and that grouping these fields together would be particularly detrimental to Zoology. We conclude that the use of only one parameter of analysis for the stratification of journals, i.e., the Impact Factor calculated for a comparatively small number of journals, fails to evaluate with accuracy the pattern of publication present in Zoology, Botany, and Oceanography. While such simplified procedure might appeals to our sense of objectivity, it dismisses any real attempt to evaluate with clarity the merit embedded in at least three very distinct aspects of scientific practice, namely: productivity, quality, and specificity.

Evaluation of follicular lymphoid depletion in the Bursa of Fabricius: an alternative methodology using digital image analysis and artificial neural networks

Fifty Bursa of Fabricius (BF) were examined by conventional optical microscopy and digital images were acquired and processed using Matlab® 6.5 software. The Artificial Neuronal Network (ANN) was generated using Neuroshell® Classifier software and the optical and digital data were compared. The ANN was able to make a comparable classification of digital and optical scores. The use of ANN was able to classify correctly the majority of the follicles, reaching sensibility and specificity of 89% and 96%, respectively. When the follicles were scored and grouped in a binary fashion the sensibility increased to 90% and obtained the maximum value for the specificity of 92%. These results demonstrate that the use of digital image analysis and ANN is a useful tool for the pathological classification of the BF lymphoid depletion. In addition it provides objective results that allow measuring the dimension of the error in the diagnosis and classification therefore making comparison between databases feasible.

Detection of Ureaplasma diversum in bovine semen straws for artificial insemination

Fundacao de Amparo a Pesquisa do Estado de Sao Paulo (FAPESP)[06/56855-0]