Gamification e game-based learning: uma abordagem lúdica à aprendizagem

Relatório de estágio de mestrado em Ensino de Informática

DOTA-based Ga(III) and Gd(III) chelates for medical imaging (PET, SPECT and MRI)

PhD Thesis in Sciences Specialization in Chemistry

Discrimination of Brazilian propolis according to the seasoning using chemometrics and machine learning based on UV-Vis scanning data

Propolis is a chemically complex biomass produced by honeybees (Apis mellifera) from plant resins added of salivary enzymes, beeswax, and pollen. The biological activities described for propolis were also identified for donor plants resin, but a big challenge for the standardization of the chemical composition and biological effects of propolis remains on a better understanding of the influence of seasonality on the chemical constituents of that raw material. Since propolis quality depends, among other variables, on the local flora which is strongly influenced by (a)biotic factors over the seasons, to unravel the harvest season effect on the propolis chemical profile is an issue of recognized importance. For that, fast, cheap, and robust analytical techniques seem to be the best choice for large scale quality control processes in the most demanding markets, e.g., human health applications. For that, UV-Visible (UV-Vis) scanning spectrophotometry of hydroalcoholic extracts (HE) of seventy-three propolis samples, collected over the seasons in 2014 (summer, spring, autumn, and winter) and 2015 (summer and autumn) in Southern Brazil was adopted. Further machine learning and chemometrics techniques were applied to the UV-Vis dataset aiming to gain insights as to the seasonality effect on the claimed chemical heterogeneity of propolis samples determined by changes in the flora of the geographic region under study. Descriptive and classification models were built following a chemometric approach, i.e. principal component analysis (PCA) and hierarchical clustering analysis (HCA) supported by scripts written in the R language. The UV-Vis profiles associated with chemometric analysis allowed identifying a typical pattern in propolis samples collected in the summer. Importantly, the discrimination based on PCA could be improved by using the dataset of the fingerprint region of phenolic compounds ( = 280-400m), suggesting that besides the biological activities of those secondary metabolites, they also play a relevant role for the discrimination and classification of that complex matrix through bioinformatics tools. Finally, a series of machine learning approaches, e.g., partial least square-discriminant analysis (PLS-DA), k-Nearest Neighbors (kNN), and Decision Trees showed to be complementary to PCA and HCA, allowing to obtain relevant information as to the sample discrimination.

Single-function approach to calibrating whatman n.º 42 filter paper based on suction versus water content relationships

Several suction–water-content (s-w) calibrations for the filter paper method (FPM) used for soil-suction measurement have been published. Most of the calibrations involve a bilinear function (i.e., two different equations) with an inflection point occurring at 60 kPatechniques for two different soils for the suction range of 50 kPa

Land cover classification of Lago Grande de Curuai floodplain (Amazon, Brazil) using multi-sensor and image fusion techniques

Given the limitations of different types of remote sensing images, automated land-cover classifications of the Amazon várzea may yield poor accuracy indexes. One way to improve accuracy is through the combination of images from different sensors, by either image fusion or multi-sensor classifications. Therefore, the objective of this study was to determine which classification method is more efficient in improving land cover classification accuracies for the Amazon várzea and similar wetland environments - (a) synthetically fused optical and SAR images or (b) multi-sensor classification of paired SAR and optical images. Land cover classifications based on images from a single sensor (Landsat TM or Radarsat-2) are compared with multi-sensor and image fusion classifications. Object-based image analyses (OBIA) and the J.48 data-mining algorithm were used for automated classification, and classification accuracies were assessed using the kappa index of agreement and the recently proposed allocation and quantity disagreement measures. Overall, optical-based classifications had better accuracy than SAR-based classifications. Once both datasets were combined using the multi-sensor approach, there was a 2% decrease in allocation disagreement, as the method was able to overcome part of the limitations present in both images. Accuracy decreased when image fusion methods were used, however. We therefore concluded that the multi-sensor classification method is more appropriate for classifying land cover in the Amazon várzea.

The diagnostic and prognostic role of liquid-based cytology: are we ready to monitor therapy and resistance?

Here, we evaluate the diagnostic and prognostic role of liquid-based cytology (LBC) in different body lesions, including thyroid, lung, effusions and malignant breast lesions. LBC has gained consensus after being applied to both non-gynecologic and fine-needle aspiration cytology. Although some remain sceptical regarding the diagnostic efficacy of LBC, mainly when used alone, in recent years, good results have been obtained as long as it showed a high diagnostic accuracy. Here, we discuss the additional possibility of storing material for the application of ancillary techniques (immunocytochemistry–molecular analysis) with several diagnostic and prognostic advantages, which may pave the way for the challenging evaluation of both monitoring responses to treatment and resistance to targeted therapies in thyroid, lung, breast carcinoma or malignant effusions. Furthermore, it provides the use of several molecular spots as specific targets for personalized therapy.

O efeito da deposição salina nas características das escorrências rodoviárias em zonas costeiras

Tese de Doutoramento em Engenharia Civil.

Flexible gastrointestinal motility pressure sensors based on aluminum thin-film strain-gauge arrays

This paper reports on an innovative approach to measuring intraluminal pressure in the upper gastrointestinal (GI) tract, especially monitoring GI motility and peristaltic movements. The proposed approach relies on thin-film aluminum strain gauges deposited on top of a Kapton membrane, which in turn lies on top of an SU-8 diaphragm-like structure. This structure enables the Kapton membrane to bend when pressure is applied, thereby affecting the strain gauges and effectively changing their electrical resistance. The sensor, with an area of 3.4 mm2, is fabricated using photolithography and standard microfabrication techniques (wet etching). It features a linear response (R2 = 0.9987) and an overall sensitivity of 2.6 mV mmHg−1. Additionally, its topology allows a high integration capability. The strain gauges’ responses to pressure were studied and the fabrication process optimized to achieve high sensitivity, linearity, and reproducibility. The sequential acquisition of the different signals is carried out by a microcontroller, with a 10-bit ADC and a sample rate of 250 Hz. The pressure signals are then presented in a user-friendly interface, developed using the Integrated Development Environment software, QtCreator IDE, for better visualization by physicians.

Development of a novel aptamer-based multi-sensor device for the detection of osteopontin

Doctoral Dissertation for PhD degree in Chemical and Biological Engineering

Verificación Formal de Sistemas basada Formal Software Verification based on Automated Analysisen Análisis Automático.

Identificación y caracterización del problema. Uno de los problemas más importantes asociados con la construcción de software es la corrección del mismo. En busca de proveer garantías del correcto funcionamiento del software, han surgido una variedad de técnicas de desarrollo con sólidas bases matemáticas y lógicas conocidas como métodos formales. Debido a su naturaleza, la aplicación de métodos formales requiere gran experiencia y conocimientos, sobre todo en lo concerniente a matemáticas y lógica, por lo cual su aplicación resulta costosa en la práctica. Esto ha provocado que su principal aplicación se limite a sistemas críticos, es decir, sistemas cuyo mal funcionamiento puede causar daños de magnitud, aunque los beneficios que sus técnicas proveen son relevantes a todo tipo de software. Poder trasladar los beneficios de los métodos formales a contextos de desarrollo de software más amplios que los sistemas críticos tendría un alto impacto en la productividad en tales contextos. Hipótesis. Contar con herramientas de análisis automático es un elemento de gran importancia. Ejemplos de esto son varias herramientas potentes de análisis basadas en métodos formales, cuya aplicación apunta directamente a código fuente. En la amplia mayoría de estas herramientas, la brecha entre las nociones a las cuales están acostumbrados los desarrolladores y aquellas necesarias para la aplicación de estas herramientas de análisis formal sigue siendo demasiado amplia. Muchas herramientas utilizan lenguajes de aserciones que escapan a los conocimientos y las costumbres usuales de los desarrolladores. Además, en muchos casos la salida brindada por la herramienta de análisis requiere cierto manejo del método formal subyacente. Este problema puede aliviarse mediante la producción de herramientas adecuadas. Otro problema intrínseco a las técnicas automáticas de análisis es cómo se comportan las mismas a medida que el tamaño y complejidad de los elementos a analizar crece (escalabilidad). Esta limitación es ampliamente conocida y es considerada crítica en la aplicabilidad de métodos formales de análisis en la práctica. Una forma de atacar este problema es el aprovechamiento de información y características de dominios específicos de aplicación. Planteo de objetivos. Este proyecto apunta a la construcción de herramientas de análisis formal para contribuir a la calidad, en cuanto a su corrección funcional, de especificaciones, modelos o código, en el contexto del desarrollo de software. Más precisamente, se busca, por un lado, identificar ambientes específicos en los cuales ciertas técnicas de análisis automático, como el análisis basado en SMT o SAT solving, o el model checking, puedan llevarse a niveles de escalabilidad superiores a los conocidos para estas técnicas en ámbitos generales. Se intentará implementar las adaptaciones a las técnicas elegidas en herramientas que permitan su uso a desarrolladores familiarizados con el contexto de aplicación, pero no necesariamente conocedores de los métodos o técnicas subyacentes. Materiales y métodos a utilizar. Los materiales a emplear serán bibliografía relevante al área y equipamiento informático. Métodos. Se emplearán los métodos propios de la matemática discreta, la lógica y la ingeniería de software. Resultados esperados. Uno de los resultados esperados del proyecto es la individualización de ámbitos específicos de aplicación de métodos formales de análisis. Se espera que como resultado del desarrollo del proyecto surjan herramientas de análisis cuyo nivel de usabilidad sea adecuado para su aplicación por parte de desarrolladores sin formación específica en los métodos formales utilizados. Importancia del proyecto. El principal impacto de este proyecto será la contribución a la aplicación práctica de técnicas formales de análisis en diferentes etapas del desarrollo de software, con la finalidad de incrementar su calidad y confiabilidad. A crucial factor for software quality is correcteness. Traditionally, formal approaches to software development concentrate on functional correctness, and tackle this problem basically by being based on well defined notations founded on solid mathematical grounds. This makes formal methods better suited for analysis, due to their precise semantics, but they are usually more complex, and require familiarity and experience with the manipulation of mathematical definitions. So, their acceptance by software engineers is rather restricted, and formal methods applications have been confined to critical systems. Nevertheless, it is obvious that the advantages that formal methods provide apply to any kind of software system. It is accepted that appropriate software tool support for formal analysis is essential, if one seeks providing support for software development based on formal methods. Indeed, some of the relatively recent sucesses of formal methods are accompanied by good quality tools that automate powerful analysis mechanisms, and are even integrated in widely used development environments. Still, most of these tools either concentrate on code analysis, and in many cases are still far from being simple enough to be employed by software engineers without experience in formal methods. Another important problem for the adoption of tool support for formal methods is scalability. Automated software analysis is intrinsically complex, and thus techniques do not scale well in the general case. In this project, we will attempt to identify particular modelling, design, specification or coding activities in software development processes where to apply automated formal analysis techniques. By focusing in very specific application domains, we expect to find characteristics that might be exploited to increase the scalability of the corresponding analyses, compared to the general case.

Gonad development in females of fiddler crab Uca rapax (Crustacea, Brachyura, Ocypodidae) using macro and microscopic techniques

The morphology of the ovaries in Uca rapax (Smith, 1870) was described based on macroscopic and microscopic analysis. Females were collected in Itamambuca mangrove, Ubatuba, state of São Paulo, Brazil. In the laboratory, 18 females had their ovaries removed and prepared for histology. Each gonad developmental stage was previously determined based on external and macroscopic morphology and afterwards each stage was microscopically described. The ovaries of U. rapax showed a pronounced macroscopic differentiation in size and coloration with the maturation of the gonad, with six ovarian developmental stages: immature, rudimentary, developing, developed, advanced and spent. During the vitellogenesis, the amount of oocytes in secondary stage increases in the ovary, resulting in a change in coloration of the gonad. Oogonias, primary oocytes, secondary oocytes and follicular cells were histologically described and measured. In female’s ovaries of U. rapax the modifications observed in the oocytes during the process of gonad maturation are similar to descriptions of gonads of other females of brachyuran crustaceans. The similarities are specially found in the morphological changes in the reproductive cells, and also in the presence and arrange of follicle cells during the process of ovary maturation. When external morphological characteristics of the gonads were compared to histological descriptions, it was possible to observe modifications that characterize the process in different developmental stages throughout the ovarian cycle and, consequently, the macroscopic classification of gonad stages agree with the modifications of the reproductive cells.

Development of CBCT-based prostate setup correction strategies and impact of rectal distension.

BACKGROUND: Cone-beam computed tomography (CBCT) image-guided radiotherapy (IGRT) systems are widely used tools to verify and correct the target position before each fraction, allowing to maximize treatment accuracy and precision. In this study, we evaluate automatic three-dimensional intensity-based rigid registration (RR) methods for prostate setup correction using CBCT scans and study the impact of rectal distension on registration quality. METHODS: We retrospectively analyzed 115 CBCT scans of 10 prostate patients. CT-to-CBCT registration was performed using (a) global RR, (b) bony RR, or (c) bony RR refined by a local prostate RR using the CT clinical target volume (CTV) expanded with 1-to-20-mm varying margins. After propagation of the manual CT contours, automatic CBCT contours were generated. For evaluation, a radiation oncologist manually delineated the CTV on the CBCT scans. The propagated and manual CBCT contours were compared using the Dice similarity and a measure based on the bidirectional local distance (BLD). We also conducted a blind visual assessment of the quality of the propagated segmentations. Moreover, we automatically quantified rectal distension between the CT and CBCT scans without using the manual CBCT contours and we investigated its correlation with the registration failures. To improve the registration quality, the air in the rectum was replaced with soft tissue using a filter. The results with and without filtering were compared. RESULTS: The statistical analysis of the Dice coefficients and the BLD values resulted in highly significant differences (p<10(-6)) for the 5-mm and 8-mm local RRs vs the global, bony and 1-mm local RRs. The 8-mm local RR provided the best compromise between accuracy and robustness (Dice median of 0.814 and 97% of success with filtering the air in the rectum). We observed that all failures were due to high rectal distension. Moreover, the visual assessment confirmed the superiority of the 8-mm local RR over the bony RR. CONCLUSION: The most successful CT-to-CBCT RR method proved to be the 8-mm local RR. We have shown the correlation between its registration failures and rectal distension. Furthermore, we have provided a simple (easily applicable in routine) and automatic method to quantify rectal distension and to predict registration failure using only the manual CT contours.

Quantifying consistency of Event Related Potentials across subjects based on single-trial topographic analysis

Introduction: Non-invasive brain imaging techniques often contrast experimental conditions across a cohort of participants, obfuscating distinctions in individual performance and brain mechanisms that are better characterised by the inter-trial variability. To overcome such limitations, we developed topographic analysis methods for single-trial EEG data [1]. So far this was typically based on time-frequency analysis of single-electrode data or single independent components. The method's efficacy is demonstrated for event-related responses to environmental sounds, hitherto studied at an average event-related potential (ERP) level. Methods: Nine healthy subjects participated to the experiment. Auditory meaningful sounds of common objects were used for a target detection task [2]. On each block, subjects were asked to discriminate target sounds, which were living or man-made auditory objects. Continuous 64-channel EEG was acquired during the task. Two datasets were considered for each subject including single-trial of the two conditions, living and man-made. The analysis comprised two steps. In the first part, a mixture of Gaussians analysis [3] provided representative topographies for each subject. In the second step, conditional probabilities for each Gaussian provided statistical inference on the structure of these topographies across trials, time, and experimental conditions. Similar analysis was conducted at group-level. Results: Results show that the occurrence of each map is structured in time and consistent across trials both at the single-subject and at group level. Conducting separate analyses of ERPs at single-subject and group levels, we could quantify the consistency of identified topographies and their time course of activation within and across participants as well as experimental conditions. A general agreement was found with previous analysis at average ERP level. Conclusions: This novel approach to single-trial analysis promises to have impact on several domains. In clinical research, it gives the possibility to statistically evaluate single-subject data, an essential tool for analysing patients with specific deficits and impairments and their deviation from normative standards. In cognitive neuroscience, it provides a novel tool for understanding behaviour and brain activity interdependencies at both single-subject and at group levels. In basic neurophysiology, it provides a new representation of ERPs and promises to cast light on the mechanisms of its generation and inter-individual variability.

Model based fault diagnosis with application to an automotive engine

Report for the scientific sojourn at the University of Linköping between April to July 2007. Monitoring of the air intake system of an automotive engine is important to meet emission related legislative diagnosis requirements. During the research the problem of fault detection in the air intake system was stated as a constraint satisfaction problem over continuous domains with a big number of variables and constraints. This problem was solved using Interval-based Consistency Techniques. Interval-based consistency techniques are shown to be particularly efficient for checking the consistency of the Analytical Redundancy Relations (ARRs), dealing with uncertain measurements and parameters, and using experimental data. All experiments were performed on a four-cylinder turbo-charged spark-ignited SAAB engine located in the research laboratory at Vehicular System Group - University of Linköping.

Corticosterone shifts reproductive behaviour towards self-maintenance in the barn owl and is linked to melanin-based coloration in females.

Trade-offs between the benefits of current reproduction and the costs to future reproduction and survival are widely recognized. However, such trade-offs might only be detected when resources become limited to the point where investment in one activity jeopardizes investment in others. The resolution of the trade-off between reproduction and self-maintenance is mediated by hormones such as glucocorticoids which direct behaviour and physiology towards self-maintenance under stressful situations. We investigated this trade-off in male and female barn owls in relation to the degree of heritable melanin-based coloration, a trait that reflects the ability to cope with various sources of stress in nestlings. We increased circulating corticosterone in breeding adults by implanting a corticosterone-releasing-pellet, using birds implanted with a placebo-pellet as controls. In males, elevated corticosterone reduced the activity (i.e. reduced home-range size and distance covered within the home-range) independently of coloration, while we could not detect any effect on hunting efficiency. The effect of experimentally elevated corticosterone on female behaviour was correlated with their melanin-based coloration. Corticosterone (cort-) induced an increase in brooding behaviour in small-spotted females, while this hormone had no detectable effect in large-spotted females. Cort-females with small eumelanic spots showed the normal body-mass loss during the early nestling period, while large spotted cort-females did not lose body mass. This indicates that corticosterone induced a shift towards self-maintenance in males independently on their plumage, whereas in females this shift was observed only in large-spotted females.