UMA NOVA CARTOGRAFIA COGNITIVA PARA O ENSINO DA COMUNICAÇÃO

O trabalho proposto é a montar um projeto exploratório funcional que parta da cartografia cognitiva, que é definida como a arte, teoria e técnica de construir mapas do conhecimento, visando com esta cartografia a sua aplicabilidade na estruturação de um conjunto de cursos/saberes da área da Comunicação. Assemelhado ao conceito de mapas conceituais, ou cognitivos, representam o conhecimento organizado e são compostos por conceitos. Este mapas foram desenvolvido a partir da década de setenta por vários pesquisadores. A tese experimento foi montada tendo como base os softwares de relacionamento por temas e interesses dentro de um ambiente de interatividade tridimensional , montado no conceito de arvore do conhecimento relacional. Esta experiência é construída em ambiente tridimensional com uso de softwares 3D que rodam como aplicativos de engines de vídeo games, que são motores gráficos. A base de dados e a interatividade de textos e tarefas é realizada sob a plataforma do MediaWiki, que é o software aberto que roda a Wikipédia. A plataforma de mapas roda dentro de um software MindJet MindManager e do CMAPS. As vídeo conferências são administradas pelo FlashMeeting, de Web conferência. A maioria deles são softwares abertos. Todos operando em sistemas presenciais ou de modulação EAD. A base conceitual está estruturada dentro de uma visão de educação disruptiva, que lança um novo modelo educacional baseado em mapas, visto dentro de uma abordagem de um mundo de múltiplas telas, um mundo da era hiper, um mundo hipermoderno, que tem como base uma cultura da era tecnológica, numa renovação dos conceitos de Cultura, agora revigorados à luz das novas tecnologias e da nova sociedade interligada em rede.

Structural and chemical basis for anticancer activity of a series of 'beta'-tubulin ligands: molecular modeling and 3D QSAR studies

An important approach to cancer therapy is the design of small molecule modulators that interfere with microtubule dynamics through their specific binding to the ²-subunit of tubulin. In the present work, comparative molecular field analysis (CoMFA) studies were conducted on a series of discodermolide analogs with antimitotic properties. Significant correlation coefficients were obtained (CoMFA(i), q² =0.68, r²=0.94; CoMFA(ii), q² = 0.63, r²= 0.91), indicating the good internal and external consistency of the models generated using two independent structural alignment strategies. The models were externally validated employing a test set, and the predicted values were in good agreement with the experimental results. The final QSAR models and the 3D contour maps provided important insights into the chemical and structural basis involved in the molecular recognition process of this family of discodermolide analogs, and should be useful for the design of new specific ²-tubulin modulators with potent anticancer activity.

Spectrum simulation of rough and nanostructured targets from their 2D and 3D image by Monte Carlo methods

Corteo is a program that implements Monte Carlo (MC) method to simulate ion beam analysis (IBA) spectra of several techniques by following the ions trajectory until a sufficiently large fraction of them reach the detector to generate a spectrum. Hence, it fully accounts for effects such as multiple scattering (MS). Here, a version of Corteo is presented where the target can be a 2D or 3D image. This image can be derived from micrographs where the different compounds are identified, therefore bringing extra information into the solution of an IBA spectrum, and potentially significantly constraining the solution. The image intrinsically includes many details such as the actual surface or interfacial roughness, or actual nanostructures shape and distribution. This can for example lead to the unambiguous identification of structures stoichiometry in a layer, or at least to better constraints on their composition. Because MC computes in details the trajectory of the ions, it simulates accurately many of its aspects such as ions coming back into the target after leaving it (re-entry), as well as going through a variety of nanostructures shapes and orientations. We show how, for example, as the ions angle of incidence becomes shallower than the inclination distribution of a rough surface, this process tends to make the effective roughness smaller in a comparable 1D simulation (i.e. narrower thickness distribution in a comparable slab simulation). Also, in ordered nanostructures, target re-entry can lead to replications of a peak in a spectrum. In addition, bitmap description of the target can be used to simulate depth profiles such as those resulting from ion implantation, diffusion, and intermixing. Other improvements to Corteo include the possibility to interpolate the cross-section in angle-energy tables, and the generation of energy-depth maps.

POSE ESTIMATION AND 3D RECONSTRUCTION USING SENSOR FUSION

A camera maps 3-dimensional (3D) world space to a 2-dimensional (2D) image space. In the process it loses the depth information, i.e., the distance from the camera focal point to the imaged objects. It is impossible to recover this information from a single image. However, by using two or more images from different viewing angles this information can be recovered, which in turn can be used to obtain the pose (position and orientation) of the camera. Using this pose, a 3D reconstruction of imaged objects in the world can be computed. Numerous algorithms have been proposed and implemented to solve the above problem; these algorithms are commonly called Structure from Motion (SfM). State-of-the-art SfM techniques have been shown to give promising results. However, unlike a Global Positioning System (GPS) or an Inertial Measurement Unit (IMU) which directly give the position and orientation respectively, the camera system estimates it after implementing SfM as mentioned above. This makes the pose obtained from a camera highly sensitive to the images captured and other effects, such as low lighting conditions, poor focus or improper viewing angles. In some applications, for example, an Unmanned Aerial Vehicle (UAV) inspecting a bridge or a robot mapping an environment using Simultaneous Localization and Mapping (SLAM), it is often difficult to capture images with ideal conditions. This report examines the use of SfM methods in such applications and the role of combining multiple sensors, viz., sensor fusion, to achieve more accurate and usable position and reconstruction information. This project investigates the role of sensor fusion in accurately estimating the pose of a camera for the application of 3D reconstruction of a scene. The first set of experiments is conducted in a motion capture room. These results are assumed as ground truth in order to evaluate the strengths and weaknesses of each sensor and to map their coordinate systems. Then a number of scenarios are targeted where SfM fails. The pose estimates obtained from SfM are replaced by those obtained from other sensors and the 3D reconstruction is completed. Quantitative and qualitative comparisons are made between the 3D reconstruction obtained by using only a camera versus that obtained by using the camera along with a LIDAR and/or an IMU. Additionally, the project also works towards the performance issue faced while handling large data sets of high-resolution images by implementing the system on the Superior high performance computing cluster at Michigan Technological University.

Generation of self-similar Gaussian time series by means of the DWT and DWPT variance maps

Due to the several kinds of services that use the Internet and data networks infra-structures, the present networks are characterized by the diversity of types of traffic that have statistical properties as complex temporal correlation and non-gaussian distribution. The networks complex temporal correlation may be characterized by the Short Range Dependence (SRD) and the Long Range Dependence - (LRD). Models as the fGN (Fractional Gaussian Noise) may capture the LRD but not the SRD. This work presents two methods for traffic generation that synthesize approximate realizations of the self-similar fGN with SRD random process. The first one employs the IDWT (Inverse Discrete Wavelet Transform) and the second the IDWPT (Inverse Discrete Wavelet Packet Transform). It has been developed the variance map concept that allows to associate the LRD and SRD behaviors directly to the wavelet transform coefficients. The developed methods are extremely flexible and allow the generation of Gaussian time series with complex statistical behaviors.

Rational Design and 3D-Pharmacophore Mapping of 5 `-Thiourea-Substituted alpha-Thymidine Analogues as Mycobacterial TMPK Inhibitors

Thymidine monophosphate kinase (TMPK) has emerged as an attractive target for developing inhibitors of Mycobacterium tuberculosis growth. In this study the receptor-independent (RI) 4D-QSAR formalism has been used to develop QSAR models and corresponding 3D-pharmacophores for a set of 5`-thiourea-substituted alpha-thymidine inhibitors. Models were developed for the entire training set and for a subset of the training set consisting of the most potent inhibitors. The optimized (RI) 4D-QSAR models are statistically significant (r(2) = 0.90, q(2) = 0.83 entire set, r(2) = 0.86, q(2) = 0.80 high potency subset) and also possess good predictivity based on test set predictions. The most and least potent inhibitors, in their respective postulated active conformations derived from the models, were docked in the active site of the TMPK crystallographic structure. There is a solid consistency between the 3D-pharmacophore sites defined by the QSAR models and interactions with binding site residues. This model identifies new regions of the inhibitors that contain pharmacophore sites, such as the sugar-pyrimidine ring structure and the region of the 5`-arylthiourea moiety. These new regions of the ligands can be further explored and possibly exploited to identify new, novel, and, perhaps, better antituberculosis inhibitors of TMPKmt. Furthermore, the 3D-pharmacophores defined by these models can be used as a starting point for future receptor-dependent antituberculosis drug design as well as to elucidate candidate sites for substituent addition to optimize ADMET properties of analog inhibitors.

INTENSITY-MODULATED AND 3D-CONFORMAL RADIOTHERAPY FOR WHOLE-VENTRICULAR IRRADIATION AS COMPARED WITH CONVENTIONAL WHOLE-BRAIN IRRADIATION IN THE MANAGEMENT OF LOCALIZED CENTRAL NERVOUS SYSTEM GERM CELL TUMORS

Purpose: To compare the sparing potential of cerebral hemispheres with intensity-modulated radiotherapy (IMRT) and three-dimensional conformal radiotherapy (3D-CRT) for whole-ventricular irradiation (WVI) and conventional whole-brain irradiation (WBI) in the management of localized central nervous system germ cell tumors (CNSGCTs). Methods and Materials: Ten cases of patients with localized CNSGCTs and submitted to WVI by use of IMRT with or without a ""boost"" to the primary lesion were selected. For comparison purposes, similar treatment plans were produced by use of 3D-CRT (WVI with or without boost) and WBI (opposed lateral fields with or without boost), and cerebral hemisphere sparing was evaluated at dose levels ranging from 2 Gy to 40 Gy. Results: The median prescription dose for WVI was 30.6 Gy (range, 25.2-37.5 Gy), and that for the boost was 16.5 Gy (range, 0-23.4 Gy). Mean irradiated cerebral hemisphere volumes were lower for WVI with IMRT than for 3D-CRT and were lower for WVI with 3D-CRT than for WBI. Intensity-modulated radiotherapy was associated with the lowest irradiated volumes, with reductions of 7.5%, 12.2%, and 9.0% at dose levels., compared with 3D-CRT. Intensity-modulated radiotherapy provided of 20, 30, and 40 Gy, respectively statistically significant reductions of median irradiated volumes at all dose levels (p = 0.002 or less). However, estimated radiation doses to peripheral areas of the body were 1.9 times higher with IMRT than with 3D-CRT. Conclusions: Although IMRT is associated with increased radiation doses to peripheral areas of the body, its use can spare a significant amount of normal central nervous system tissue compared with 3D-CRT or WBI in the setting of CNSGCT treatment. (C) 2010 Elsevier Inc.

Automatic segmentation and 3D feature extraction of protein aggregates in Caenorhabditis Elegans

In the last years, it has become increasingly clear that neurodegenerative diseases involve protein aggregation, a process often used as disease progression readout and to develop therapeutic strategies. This work presents an image processing tool to automatic segment, classify and quantify these aggregates and the whole 3D body of the nematode Caenorhabditis Elegans. A total of 150 data set images, containing different slices, were captured with a confocal microscope from animals of distinct genetic conditions. Because of the animals’ transparency, most of the slices pixels appeared dark, hampering their body volume direct reconstruction. Therefore, for each data set, all slices were stacked in one single 2D image in order to determine a volume approximation. The gradient of this image was input to an anisotropic diffusion algorithm that uses the Tukey’s biweight as edge-stopping function. The image histogram median of this outcome was used to dynamically determine a thresholding level, which allows the determination of a smoothed exterior contour of the worm and the medial axis of the worm body from thinning its skeleton. Based on this exterior contour diameter and the medial animal axis, random 3D points were then calculated to produce a volume mesh approximation. The protein aggregations were subsequently segmented based on an iso-value and blended with the resulting volume mesh. The results obtained were consistent with qualitative observations in literature, allowing non-biased, reliable and high throughput protein aggregates quantification. This may lead to a significant improvement on neurodegenerative diseases treatment planning and interventions prevention

Amygdala activation in response to 2D and 3D emotion-inducing stimuli

Studying changes in brain activation according to the valence of emotion-inducing stimuli is essential in the research on emotions. Due to the ecological potential of virtual reality, it is also important to examine whether brain activation in response to emotional stimuli can be modulated by the three-dimensional (3D) properties of the images. This study uses functional Magnetic Resonance Imaging to compare differences between 3D and standard (2D) visual stimuli in the activation of emotion-related brain areas. The stimuli were organized in three virtual-reality scenarios, each with a different emotional valence (pleasant, unpleasant and neutral). The scenarios were presented in a pseudo-randomized order in the two visualization modes to twelve healthy males. Data were analyzed through a GLM-based fixed effects procedure. Unpleasant and neutral stimuli activated the right amygdala more strongly when presented in 3D than in 2D. These results suggest that 3D stimuli, when used as “building blocks” for virtual environments, can induce increased emotional loading, as shown here through neuroimaging.

Comparison of Methods and Co-Registration Maps of EEG and fMRI in Occipital Lobe Epilepsy

Clinically childhood occipital lobe epilepsy (OLE) manifests itself with distinct syndromes. The traditional EEG recordings have not been able to overcome the difficulty in correlating the ictal clinical symptoms to the onset in particular areas of the occipital lobes. To understand these syndromes it is important to map with more precision the epileptogenic cortical regions in OLE. Experimentally, we studied three idiopathic childhood OLE patients with EEG source analysis and with the simultaneous acquisition of EEG and fMRI, to map the BOLD effect associated with EEG spikes. The spatial overlap between the EEG and BOLD results was not very good, but the fMRI suggested localizations more consistent with the ictal clinical manifestations of each type of epileptic syndrome. Since our first results show that by associating the BOLD effect with interictal spikes the epileptogenic areas are mapped to localizations different from those calculated from EEG sources and that by using different EEG/fMRI processing methods our results differ to some extent, it is very important to compare the different methods of processing the localization of activation and develop a good methodology for obtaining co-registration maps of high resolution EEG with BOLD localizations.

A Comparison of Radiation Dose Between Standard and 3D Angiography in Congenital Heart Disease

Background: The use of three-dimensional rotational angiography (3D-RA) to assess patients with congenital heart diseases appears to be a promising technique despite the scarce literature available. Objectives: The objective of this study was to describe our initial experience with 3D-RA and to compare its radiation dose to that of standard two-dimensional angiography (2D-SA). Methods: Between September 2011 and April 2012, 18 patients underwent simultaneous 3D-RA and 2D-SA during diagnostic cardiac catheterization. Radiation dose was assessed using the dose-area-product (DAP). Results: The median patient age and weight were 12.5 years and 47.5 Kg, respectively. The median DAP of each 3D-RA acquisition was 1093µGy.m2 and 190µGy.m2 for each 2D-SA acquisition (p<0.01). In patients weighing more than 45Kg (n=7), this difference was attenuated but still significant (1525 µGy.m2 vs.413µGy.m2, p=0.01). No difference was found between one 3D-RA and three 2D-SA (1525µGy.m2 vs.1238 µGy.m2, p = 0.575) in this population. This difference was significantly higher in patients weighing less than 45Kg (n=9) (713µGy.m2 vs.81µGy.m2, P = 0.008), even when comparing one 3D-RA with three 2D-SA (242µGy.m2, respectively, p<0.008). 3D-RA was extremely useful for the assessment of conduits of univentricular hearts, tortuous branches of the pulmonary artery, and aorta relative to 2D-SA acquisitions. Conclusions: The radiation dose of 3D-RA used in our institution was higher than those previously reported in the literature and this difference was more evident in children. This type of assessment is of paramount importance when starting to perform 3D-RA.

Extraction of topological structures in 2D and 3D vector fields

feature extraction, feature tracking, vector field visualization

Model-based Segmentation and Fusion of 3D Computed Tomography and 3D Ultrasound of the Eye for Radiotherapy Planning

Computed Tomography (CT) represents the standard imaging modality for tumor volume delineation for radiotherapy treatment planning of retinoblastoma despite some inherent limitations. CT scan is very useful in providing information on physical density for dose calculation and morphological volumetric information but presents a low sensitivity in assessing the tumor viability. On the other hand, 3D ultrasound (US) allows a highly accurate definition of the tumor volume thanks to its high spatial resolution but it is not currently integrated in the treatment planning but used only for diagnosis and follow-up. Our ultimate goal is an automatic segmentation of gross tumor volume (GTV) in the 3D US, the segmentation of the organs at risk (OAR) in the CT and the registration of both modalities. In this paper, we present some preliminary results in this direction. We present 3D active contour-based segmentation of the eye ball and the lens in CT images; the presented approach incorporates the prior knowledge of the anatomy by using a 3D geometrical eye model. The automated segmentation results are validated by comparing with manual segmentations. Then, we present two approaches for the fusion of 3D CT and US images: (i) landmark-based transformation, and (ii) object-based transformation that makes use of eye ball contour information on CT and US images.

Quantitative analysis of crystal/grain sizes and their distributions in 2D and 3D

We review methods to estimate the average crystal (grain) size and the crystal (grain) size distribution in solid rocks. Average grain sizes often provide the base for stress estimates or rheological calculations requiring the quantification of grain sizes in a rock's microstructure. The primary data for grain size data are either 1D (i.e. line intercept methods), 2D (area analysis) or 3D (e.g., computed tomography, serial sectioning). These data have been used for different data treatments over the years, whereas several studies assume a certain probability function (e.g., logarithm, square root) to calculate statistical parameters as the mean, median, mode or the skewness of a crystal size distribution. The finally calculated average grain sizes have to be compatible between the different grain size estimation approaches in order to be properly applied, for example, in paleo-piezometers or grain size sensitive flow laws. Such compatibility is tested for different data treatments using one- and two-dimensional measurements. We propose an empirical conversion matrix for different datasets. These conversion factors provide the option to make different datasets compatible with each other, although the primary calculations were obtained in different ways. In order to present an average grain size, we propose to use the area-weighted and volume-weighted mean in the case of unimodal grain size distributions, respectively, for 2D and 3D measurements. The shape of the crystal size distribution is important for studies of nucleation and growth of minerals. The shape of the crystal size distribution of garnet populations is compared between different 2D and 3D measurements, which are serial sectioning and computed tomography. The comparison of different direct measured 3D data; stereological data and direct presented 20 data show the problems of the quality of the smallest grain sizes and the overestimation of small grain sizes in stereological tools, depending on the type of CSD. (C) 2011 Published by Elsevier Ltd.