Automatic segmentation and classification of human intestinal parasites from microscopy images

Human intestinal parasites constitute a problem in most tropical countries, causing death or physical and mental disorders. Their diagnosis usually relies on the visual analysis of microscopy images, with error rates that may range from moderate to high. The problem has been addressed via computational image analysis, but only for a few species and images free of fecal impurities. In routine, fecal impurities are a real challenge for automatic image analysis. We have circumvented this problem by a method that can segment and classify, from bright field microscopy images with fecal impurities, the 15 most common species of protozoan cysts, helminth eggs, and larvae in Brazil. Our approach exploits ellipse matching and image foresting transform for image segmentation, multiple object descriptors and their optimum combination by genetic programming for object representation, and the optimum-path forest classifier for object recognition. The results indicate that our method is a promising approach toward the fully automation of the enteroparasitosis diagnosis. © 2012 IEEE.

Motherhood wage penalties and labour market segmentation: Evidence from Argentina

Includes bibliography.

Informality and labour market segmentation: the case of Argentina

The document evaluates the presence of segmentation in the Argentinean labour market. The analysis is centred on the comparison of the earnings of formal and informal workers. Two different approaches to the definition of informality are used. The existence of a formal premium is tested using dynamic data and semiparametric techniques. The period analysed is 1996-2006 for all urban surveyed areas. Our results support the segmentation hypothesis for the Argentine urban labour market: workers with similar probabilities of entering/exiting across sectors obtain different earnings.

Diet Seasonality and Feeding Preferences of Brachycephalus pitanga (Anura: Brachycephalidae)

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Image segmentation through combined methods: watershed transform, unsupervised distance learning and normalized cut

Research on image processing has shown that combining segmentation methods may lead to a solid approach to extract semantic information from different sort of images. Within this context, the Normalized Cut (NCut) is usually used as a final partitioning tool for graphs modeled in some chosen method. This work explores the Watershed Transform as a modeling tool, using different criteria of the hierarchical Watershed to convert an image into an adjacency graph. The Watershed is combined with an unsupervised distance learning step that redistributes the graph weights and redefines the Similarity matrix, before the final segmentation step using NCut. Adopting the Berkeley Segmentation Data Set and Benchmark as a background, our goal is to compare the results obtained for this method with previous work to validate its performance.

Botanical Preferences of Africanized Bees (Apis mellifera) on the Coast and in the Atlantic Forest of Sergipe, Brazil

Pollen analysis in honey can be used as an alternative method to research into flowers visited by bees in an area. This study aimed to indentify the main floral families in honey from apiaries in the Atlantic Forest and Sergipe state coast. Honey samples from these apiaries were studied, as well as plants that grow around them, which can be used as a source of foraging for bees. The palynological technique was used to compare the pollen content of honey samples with the pollen grains from leaves of plants found in the vicinity of the apiaries to assess whether they had been visited by bees. The results of studies in both sites were similar in terms of incompatibility of families found in the apiary vicinity and honey. Thus, it was possible to observe that in honey samples from the coast and in the remaining Atlantic forest, the number of families was greater than the number of families found in the apiary vicinity, which highlights the diversity of plants visited by bees and a possible expansion of the visited area for food search. This diversity suggests an adaptive foraging behavior to plant resources available in the environment, which may facilitate the pollination of these botanical families and consequently improve their genetic quality.

Fuzzy Connectedness Image Segmentation in Graph Cut Formulation: A Linear-Time Algorithm and a Comparative Analysis

A deep theoretical analysis of the graph cut image segmentation framework presented in this paper simultaneously translates into important contributions in several directions. The most important practical contribution of this work is a full theoretical description, and implementation, of a novel powerful segmentation algorithm, GC(max). The output of GC(max) coincides with a version of a segmentation algorithm known as Iterative Relative Fuzzy Connectedness, IRFC. However, GC(max) is considerably faster than the classic IRFC algorithm, which we prove theoretically and show experimentally. Specifically, we prove that, in the worst case scenario, the GC(max) algorithm runs in linear time with respect to the variable M=|C|+|Z|, where |C| is the image scene size and |Z| is the size of the allowable range, Z, of the associated weight/affinity function. For most implementations, Z is identical to the set of allowable image intensity values, and its size can be treated as small with respect to |C|, meaning that O(M)=O(|C|). In such a situation, GC(max) runs in linear time with respect to the image size |C|. We show that the output of GC(max) constitutes a solution of a graph cut energy minimization problem, in which the energy is defined as the a"" (a) norm ayenF (P) ayen(a) of the map F (P) that associates, with every element e from the boundary of an object P, its weight w(e). This formulation brings IRFC algorithms to the realm of the graph cut energy minimizers, with energy functions ayenF (P) ayen (q) for qa[1,a]. Of these, the best known minimization problem is for the energy ayenF (P) ayen(1), which is solved by the classic min-cut/max-flow algorithm, referred to often as the Graph Cut algorithm. We notice that a minimization problem for ayenF (P) ayen (q) , qa[1,a), is identical to that for ayenF (P) ayen(1), when the original weight function w is replaced by w (q) . Thus, any algorithm GC(sum) solving the ayenF (P) ayen(1) minimization problem, solves also one for ayenF (P) ayen (q) with qa[1,a), so just two algorithms, GC(sum) and GC(max), are enough to solve all ayenF (P) ayen (q) -minimization problems. We also show that, for any fixed weight assignment, the solutions of the ayenF (P) ayen (q) -minimization problems converge to a solution of the ayenF (P) ayen(a)-minimization problem (ayenF (P) ayen(a)=lim (q -> a)ayenF (P) ayen (q) is not enough to deduce that). An experimental comparison of the performance of GC(max) and GC(sum) algorithms is included. This concentrates on comparing the actual (as opposed to provable worst scenario) algorithms' running time, as well as the influence of the choice of the seeds on the output.

Anointing variation across wild capuchin populations: a review of material preferences, bout frequency and anointing sociality in Cebus and Sapajus

The frequency of anointing bouts and the materials used for self- and social anointing vary across capuchin species in captivity, but there is little published data on capuchin anointing in the wild. Here we present previously unpublished data on anointing behaviors from capuchin monkey populations at ten different field sites and incorporate these data into a review of the anointing literature for captive and wild capuchins. Using a comparative phylogenetic framework, we test four hypotheses derived primarily from captive literature for variation in anointing between wild untufted capuchins (Cebus) and tufted capuchins (Sapajus), including that (1) the frequency of anointing is higher in Cebus, (2) Cebus uses a higher proportion of plant species to insect species for anointing compared with Sapajus, (3) anointing material diversity is higher in Cebus, and (4) social indices of anointing are higher in Cebus. We found that wild Cebus anoints more with plant parts, including fruits, whereas wild Sapajus anoints more with ants and other arthropods. Cebus capucinus in particular uses more plant species per site for anointing compared with other capuchins and may specialize in anointing as an activity independent from foraging, whereas most other capuchin species tend to eat the substances they use for anointing. In agreement with captive studies, we found evidence that wild Cebus anoints at a significantly higher frequency than Sapajus. However, contrary to the captive literature, we found no difference in the range of sociality for anointing between Cebus and Sapajus in the wild. We review anointing in the context of other Neotropical primate rubbing behaviors and consider the evidence for anointing as self-medication; as a mechanism for enhanced sociality; and as a behavioral response to chemical stimuli. Am. J. Primatol. 74:299314, 2012. (c) 2011 Wiley Periodicals, Inc.

Conformational preferences for some 3-(4 '-substituted phenylsulfonyl)-1-methyl-2-piperidones through spectroscopic and theoretical studies

The analysis of the infrared (IR) carbonyl band of some 3-(4'-substituted phenylsulfonyl)-1-methyl-2-piperidones 1-5 bearing as substituents: OMe 1, Me 2, H 3, Cl 4 and NO2 5, supported by B3LY13/6-31G(d,p) calculations along with NBO analysis (for 1, 3 and 5) and X-ray diffraction (for 5), indicated the existence of three stable conformations i.e. quasi-axial (q-ax), syn-clinal (s-cl) and quasi-equatorial (q-eq). In the gas phase, the q-ax conformer is calculated as the most stable (ca. 88%) and the least polar, the s-cl conformer is less stable (ca. 12%) but more polar, and the q-eq conformer is the least stable (ca. 1%) and the most polar of the three conformers evaluated. The sum of the most important orbital interactions from NBO analysis and the trend of the electrostatic interactions accounts for the relative populations as well as for the v(CO) frequencies of the q-ax. s-cl and q-eq conformers calculated in the gas phase. The unique IR v(CO) band in CCl4 may be ascribed to the most stable q-ax conformer. The more intense (60%) high frequency doublet component in CHCl3 may be assigned to the summing up of the least stable q-eq and the less stable s-cl conformers, as their frequencies are almost coincident. The occurrence of only a single v(CO) band in both CH2Cl2 and CH3CN supports the fact that the v(CO) band of the two more polar conformers appear as a single band. Additional support to this rationalization is given by the single point PCM method, which showed a progressive increase of the q-eq + s-cl/q-ax population ratio going from the gas phase to CCl4, to CHCl3, to CH2Cl2 and to CN3CN. X-ray single crystal analysis of 5 indicates that this compound displays a quasi-axial geometry with respect to the [O=C-CH-S] moiety, and that the 2-piperidone ring assumes a slightly distorted half-chair conformation. In the crystal packing, molecules of 5 are arranged into supramolecular layers linked through C-H center dot center dot center dot O interactions along with it pi center dot center dot center dot pi interactions between adjacent benzene rings. (C) 2012 Elsevier B.V. All rights reserved.

Bilayer segmentation of live video in uncontrolled environments for background substitution: an overview and main challenges

Bilayer segmentation of live video in uncontrolled environments is an essential task for home applications in which the original background of the scene must be replaced, as in videochats or traditional videoconference. The main challenge in such conditions is overcome all difficulties in problem-situations (e. g., illumination change, distract events such as element moving in the background and camera shake) that may occur while the video is being captured. This paper presents a survey of segmentation methods for background substitution applications, describes the main concepts and identifies events that may cause errors. Our analysis shows that although robust methods rely on specific devices (multiple cameras or sensors to generate depth maps) which aid the process. In order to achieve the same results using conventional devices (monocular video cameras), most current research relies on energy minimization frameworks, in which temporal and spacial information are probabilistically combined with those of color and contrast.

Pattern-based segmentation of digital documents: model and implementation

This thesis proposes a new document model, according to which any document can be segmented in some independent components and transformed in a pattern-based projection, that only uses a very small set of objects and composition rules. The point is that such a normalized document expresses the same fundamental information of the original one, in a simple, clear and unambiguous way. The central part of my work consists of discussing that model, investigating how a digital document can be segmented, and how a segmented version can be used to implement advanced tools of conversion. I present seven patterns which are versatile enough to capture the most relevant documents’ structures, and whose minimality and rigour make that implementation possible. The abstract model is then instantiated into an actual markup language, called IML. IML is a general and extensible language, which basically adopts an XHTML syntax, able to capture a posteriori the only content of a digital document. It is compared with other languages and proposals, in order to clarify its role and objectives. Finally, I present some systems built upon these ideas. These applications are evaluated in terms of users’ advantages, workflow improvements and impact over the overall quality of the output. In particular, they cover heterogeneous content management processes: from web editing to collaboration (IsaWiki and WikiFactory), from e-learning (IsaLearning) to professional printing (IsaPress).

Reasoning with incomplete and imprecise preferences

Preferences are present in many real life situations but it is often difficult to quantify them giving a precise value. Sometimes preference values may be missing because of privacy reasons or because they are expensive to obtain or to produce. In some other situations the user of an automated system may have a vague idea of whats he wants. In this thesis we considered the general formalism of soft constraints, where preferences play a crucial role and we extended such a framework to handle both incomplete and imprecise preferences. In particular we provided new theoretical frameworks to handle such kinds of preferences. By admitting missing or imprecise preferences, solving a soft constraint problem becomes a different task. In fact, the new goal is to find solutions which are the best ones independently of the precise value the each preference may have. With this in mind we defined two notions of optimality: the possibly optimal solutions and the necessary optimal solutions, which are optimal no matter we assign a precise value to a missing or imprecise preference. We provided several algorithms, bases on both systematic and local search approaches, to find such kind of solutions. Moreover, we also studied the impact of our techniques also in a specific class of problems (the stable marriage problems) where imprecision and incompleteness have a specific meaning and up to now have been tackled with different techniques. In the context of the classical stable marriage problem we developed a fair method to randomly generate stable marriages of a given problem instance. Furthermore, we adapted our techniques to solve stable marriage problems with ties and incomplete lists, which are known to be NP-hard, obtaining good results both in terms of size of the returned marriage and in terms of steps need to find a solution.

Automated Segmentation and Non-Rigid Registration for the Quantitative Evaluation of Myocardial Perfusion from Magnetic Resonance Images

Myocardial perfusion quantification by means of Contrast-Enhanced Cardiac Magnetic Resonance images relies on time consuming frame-by-frame manual tracing of regions of interest. In this Thesis, a novel automated technique for myocardial segmentation and non-rigid registration as a basis for perfusion quantification is presented. The proposed technique is based on three steps: reference frame selection, myocardial segmentation and non-rigid registration. In the first step, the reference frame in which both endo- and epicardial segmentation will be performed is chosen. Endocardial segmentation is achieved by means of a statistical region-based level-set technique followed by a curvature-based regularization motion. Epicardial segmentation is achieved by means of an edge-based level-set technique followed again by a regularization motion. To take into account the changes in position, size and shape of myocardium throughout the sequence due to out of plane respiratory motion, a non-rigid registration algorithm is required. The proposed non-rigid registration scheme consists in a novel multiscale extension of the normalized cross-correlation algorithm in combination with level-set methods. The myocardium is then divided into standard segments. Contrast enhancement curves are computed measuring the mean pixel intensity of each segment over time, and perfusion indices are extracted from each curve. The overall approach has been tested on synthetic and real datasets. For validation purposes, the sequences have been manually traced by an experienced interpreter, and contrast enhancement curves as well as perfusion indices have been computed. Comparisons between automatically extracted and manually obtained contours and enhancement curves showed high inter-technique agreement. Comparisons of perfusion indices computed using both approaches against quantitative coronary angiography and visual interpretation demonstrated that the two technique have similar diagnostic accuracy. In conclusion, the proposed technique allows fast, automated and accurate measurement of intra-myocardial contrast dynamics, and may thus address the strong clinical need for quantitative evaluation of myocardial perfusion.