Wavelets and decision trees for target detection over sea surface using cosmo-skymed SAR data

We are investigating the combination of wavelets and decision trees to detect ships and other maritime surveillance targets from medium resolution SAR images. Wavelets have inherent advantages to extract image descriptors while decision trees are able to handle different data sources. In addition, our work aims to consider oceanic features such as ship wakes and ocean spills. In this incipient work, Haar and Cohen-Daubechies-Feauveau 9/7 wavelets obtain detailed descriptors from targets and ocean features and are inserted with other statistical parameters and wavelets into an oblique decision tree. © 2011 Springer-Verlag.

A study on automatic methods based on mathematical morphology for Martian dust devil tracks detection

This paper presents three methods for automatic detection of dust devils tracks in images of Mars. The methods are mainly based on Mathematical Morphology and results of their performance are analyzed and compared. A dataset of 21 images from the surface of Mars representative of the diversity of those track features were considered for developing, testing and evaluating our methods, confronting their outputs with ground truth images made manually. Methods 1 and 3, based on closing top-hat and path closing top-hat, respectively, showed similar mean accuracies around 90% but the time of processing was much greater for method 1 than for method 3. Method 2, based on radial closing, was the fastest but showed worse mean accuracy. Thus, this was the tiebreak factor. © 2011 Springer-Verlag.

On the Acoustic Filtering of the Pipe and Sensor in a Buried Plastic Water Pipe and its Effect on Leak Detection: An Experimental Investigation

Acoustic techniques have been used for many years to find and locate leaks in buried water distribution systems. Hydrophones and accelerometers are typically used as sensors. Although geophones could be used as well, they are not generally used for leak detection. A simple acoustic model of the pipe and the sensors has been proposed previously by some of the authors of this paper, and their model was used to explain some of the features observed in measurements. However, simultaneous measurements of a leak using all three sensor-types in controlled conditions for plastic pipes has not been reported to-date and hence they have not yet been compared directly. This paper fills that gap in knowledge. A set of measurements was made on a bespoke buried plastic water distribution pipe test rig to validate the previously reported analytical model. There is qualitative agreement between the experimental results and the model predictions in terms of the differing filtering properties of the pipe-sensor systems. A quality measure for the data is also presented, which is the ratio of the bandwidth over which the analysis is carried out divided by the centre frequency of this bandwidth. Based on this metric, the accelerometer was found to be the best sensor to use for the test rig described in this paper. However, for a system in which the distance between the sensors is large or the attenuation factor of the system is high, then it would be advantageous to use hydrophones, even though they are invasive sensors.

Feature extraction in pressure signals for leak detection in water networks

Techniques based on signal analysis for leak detection in water supply systems typically use long pressure and/or flow data series of variable length. This paper presents the feature extraction from pressure signals and their application to the identification of changes related to the onset of a leak. Example signals were acquired from an experimental laboratory circuit, and features were extracted from temporal domain and from transformed signals. Statistical analysis of features values and a classification method were applied. It was verified the feasibility of using feature vectors for distinguish data acquired in the absence or presence of a leak.

Escherichia coli from Crohn’s disease patient displays virulence features of enteroinvasive (EIEC), enterohemorragic (EHEC), and enteroaggregative (EAEC) pathotypes

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

Talent detection in taekwondo: which factors are associated with the longitudinal competitive success?

Background Several morphological and functional characteristics are associated with the performance of taekwondo (TKD) adult athletes. However, we did not find any longitudinal study associating these features to the future performance of young athletes, and thereby, identifying the best variables to use in a battery of tests to talent detection. Therefore, the aim of this study is answer the question which factors are associated with the longitudinal competitive success of TKD young athletes over five competitive years (2008 to 2012).Material &Methods: Six taekwondo athletes (13.06 +/- 1.07 years, 43.6 +/- 6.6 kg, 157.9 +/- 8.3 cm), who trained three to six hours per week, for more than three years, were assessed on 32 maturational indicators, of body composition, anthropometric and functional, using anthropometric techniques, dual energy x-ray absorptiometry, carpal radiography and contact platform. To determine the competitive ranking, the competitive results of athletes from 2008 to 2012 were analysed, and these values were correlated with the other 32 indicators for determining the Longitudinal Predictors of Performance in TKD (LPPT). Moreover, one of the athletes achieved results notably higher than the other, being medalled at Junior World Championships. Therefore, all variables were transformed into z-scores and all those in which this athlete presented superior performance in 1 z-scores were considered as LPPT. Results: The athlete of reference (the first in Longitudinal Competitive Ranking 2008-2012) distinguished, in accordance with the criteria, in nineteen LPPT indicators. The ranking was correlated with 6 LPPT parameters, including one from the maturation group of indicators and five from the functional group.Conclusion: Our results allowed us to identify several factors that are related to longitudinal competitive success in taekwondo young athletes. These factors should be considered by coaches to the proper selection of training programs, as well as for the pre-selection of young talents in competitive taekwondo. However, these results apply only to the Portuguese taekwondo adolescent athletes, being of limited generalizability.

P-220-Escherichia coli displaying virulence features of multiple diarrheogenic pathotypes detected in a Crohn's disease patient

Background: The number of Escherichia coli in the gut of Crohn's disease (CD) patients is higher than that of normal subjects, but the virulence potential of these bacteria is not fully known. Previous studies have shown that these E. coli are closely related to extraintestinal pathogenic categories (ExPEC), are able to invade epithelial cells, and usually do not produce exotoxins. We report here the detection, in a CD patient, of an E. coli which belongs to a classical enteropathogenic (EPEC) serotype and displays virulence markers of enteroinvasive (EIEC), enteroaggregative (EAEC) and enterohemorrhagic (EHEC) pathotypes. Methods: The E. coli strain was isolated, in 2009, by classical bacteriological procedures from a 56 year old woman who underwent ileo-terminal resection 1 year before, due to intestinal obstruction. The bacterial characterization was carried out by in vitro adhesion and invasion assays to cultured epithelial cells and macrophages and screening by PCR to identify virulence genetic markers of diarrheogenic E. coli (DEC) and to detect one of the gene combinations which define the phylogroups of the E. coli reference (EcoR) collection. The strain was also tested for the ability to produce biofilm and shiga cytotoxins and had its whole genome sequenced by Ion Torrent Sequencing Technology. Results: The studied strain, which was detected both in ileum biopsies and the stools of the patient, displayed the aggregative adherence (AA) phenotype to Hep-2 cells and an ability to enter Caco-2 cells 3x as high as that of EIEC reference strain and 89% of that of the prototype AIEC LF82 strain. Although it could invade cultured macrophages, the strain was unable to replicate inside these cells. PCR screening revealed the presence of eae, aggR and stx1. Tests with bacterial culture supernatants in Vero cells demonstrating cytotoxicity suggested the production of Stx1. In addition, the strain revealed to be a strong biofilm producer, belonged to the B2 EcoR phylogroup, to the O126:H27 serogroup and to the multilocus sequencing type (MLST) ST3057. The 2 later features were deduced from the whole genome sequence of the strain. Conclusions: The characterization of this E. coli isolate from a CD patient revealed a combination of virulence markers of distinct DEC pathotypes, namely eae and stx1 of EHEC, AA, aggR and biofilm formation of EAEC, and invasiveness of EIEC. These features along with its serotype and phylogroup identity seem to suggest a potential to be involved in CD, an observation which should be tested with additional studies.

A subpixel edge detector applied to aortic dissection detection

[EN] The aortic dissection is a disease that can cause a deadly situation, even with a correct treatment. It consists in a rupture of a layer of the aortic artery wall, causing a blood flow inside this rupture, called dissection. The aim of this paper is to contribute to its diagnosis, detecting the dissection edges inside the aorta. A subpixel accuracy edge detector based on the hypothesis of partial volume effect is used, where the intensity of an edge pixel is the sum of the contribution of each color weighted by its relative area inside the pixel. The method uses a floating window centred on the edge pixel and computes the edge features. The accuracy of our method is evaluated on synthetic images of different hickness and noise levels, obtaining an edge detection with a maximal mean error lower than 16 percent of a pixel.

From "wet biology" to statistical analysis of structural features with bioinformatics tools

Many new Escherichia coli outer membrane proteins have recently been identified by proteomics techniques. However, poorly expressed proteins and proteins expressed only under certain conditions may escape detection when wild-type cells are grown under standard conditions. Here, we have taken a complementary approach where candidate outer membrane proteins have been identified by bioinformatics prediction, cloned and overexpressed, and finally localized by cell fractionation experiments. Out of eight predicted outer membrane proteins, we have confirmed the outer membrane localization for five—YftM, YaiO, YfaZ, CsgF, and YliI—and also provide preliminary data indicating that a sixth—YfaL—may be an outer membrane autotransporter.

Cooperative communication and distributed detection in wireless sensor networks

Recent progress in microelectronic and wireless communications have enabled the development of low cost, low power, multifunctional sensors, which has allowed the birth of new type of networks named wireless sensor networks (WSNs). The main features of such networks are: the nodes can be positioned randomly over a given field with a high density; each node operates both like sensor (for collection of environmental data) as well as transceiver (for transmission of information to the data retrieval); the nodes have limited energy resources. The use of wireless communications and the small size of nodes, make this type of networks suitable for a large number of applications. For example, sensor nodes can be used to monitor a high risk region, as near a volcano; in a hospital they could be used to monitor physical conditions of patients. For each of these possible application scenarios, it is necessary to guarantee a trade-off between energy consumptions and communication reliability. The thesis investigates the use of WSNs in two possible scenarios and for each of them suggests a solution that permits to solve relating problems considering the trade-off introduced. The first scenario considers a network with a high number of nodes deployed in a given geographical area without detailed planning that have to transmit data toward a coordinator node, named sink, that we assume to be located onboard an unmanned aerial vehicle (UAV). This is a practical example of reachback communication, characterized by the high density of nodes that have to transmit data reliably and efficiently towards a far receiver. It is considered that each node transmits a common shared message directly to the receiver onboard the UAV whenever it receives a broadcast message (triggered for example by the vehicle). We assume that the communication channels between the local nodes and the receiver are subject to fading and noise. The receiver onboard the UAV must be able to fuse the weak and noisy signals in a coherent way to receive the data reliably. It is proposed a cooperative diversity concept as an effective solution to the reachback problem. In particular, it is considered a spread spectrum (SS) transmission scheme in conjunction with a fusion center that can exploit cooperative diversity, without requiring stringent synchronization between nodes. The idea consists of simultaneous transmission of the common message among the nodes and a Rake reception at the fusion center. The proposed solution is mainly motivated by two goals: the necessity to have simple nodes (to this aim we move the computational complexity to the receiver onboard the UAV), and the importance to guarantee high levels of energy efficiency of the network, thus increasing the network lifetime. The proposed scheme is analyzed in order to better understand the effectiveness of the approach presented. The performance metrics considered are both the theoretical limit on the maximum amount of data that can be collected by the receiver, as well as the error probability with a given modulation scheme. Since we deal with a WSN, both of these performance are evaluated taking into consideration the energy efficiency of the network. The second scenario considers the use of a chain network for the detection of fires by using nodes that have a double function of sensors and routers. The first one is relative to the monitoring of a temperature parameter that allows to take a local binary decision of target (fire) absent/present. The second one considers that each node receives a decision made by the previous node of the chain, compares this with that deriving by the observation of the phenomenon, and transmits the final result to the next node. The chain ends at the sink node that transmits the received decision to the user. In this network the goals are to limit throughput in each sensor-to-sensor link and minimize probability of error at the last stage of the chain. This is a typical scenario of distributed detection. To obtain good performance it is necessary to define some fusion rules for each node to summarize local observations and decisions of the previous nodes, to get a final decision that it is transmitted to the next node. WSNs have been studied also under a practical point of view, describing both the main characteristics of IEEE802:15:4 standard and two commercial WSN platforms. By using a commercial WSN platform it is realized an agricultural application that has been tested in a six months on-field experimentation.

Development of oil spill detection techniques for satellite optical sensors and their application to monitor oil spill discharge in Mediterranean sea

Satellite remote sensing has proved to be an effective support in timely detection and monitoring of marine oil pollution, mainly due to illegal ship discharges. In this context, we have developed a new methodology and technique for optical oil spill detection, which make use of MODIS L2 and MERIS L1B satellite top of atmosphere (TOA) reflectance imagery, for the first time in a highly automated way. The main idea was combining wide swaths and short revisit times of optical sensors with SAR observations, generally used in oil spill monitoring. This arises from the necessity to overcome the SAR reduced coverage and long revisit time of the monitoring area. This can be done now, given the MODIS and MERIS higher spatial resolution with respect to older sensors (250-300 m vs. 1 km), which consents the identification of smaller spills deriving from illicit discharge at sea. The procedure to obtain identifiable spills in optical reflectance images involves removal of oceanic and atmospheric natural variability, in order to enhance oil-water contrast; image clustering, which purpose is to segment the oil spill eventually presents in the image; finally, the application of a set of criteria for the elimination of those features which look like spills (look-alikes). The final result is a classification of oil spill candidate regions by means of a score based on the above criteria.

Automatic induction of lexical features

This thesis concerns artificially intelligent natural language processing systems that are capable of learning the properties of lexical items (properties like verbal valency or inflectional class membership) autonomously while they are fulfilling their tasks for which they have been deployed in the first place. Many of these tasks require a deep analysis of language input, which can be characterized as a mapping of utterances in a given input C to a set S of linguistically motivated structures with the help of linguistic information encoded in a grammar G and a lexicon L: G + L + C → S (1) The idea that underlies intelligent lexical acquisition systems is to modify this schematic formula in such a way that the system is able to exploit the information encoded in S to create a new, improved version of the lexicon: G + L + S → L' (2) Moreover, the thesis claims that a system can only be considered intelligent if it does not just make maximum usage of the learning opportunities in C, but if it is also able to revise falsely acquired lexical knowledge. So, one of the central elements in this work is the formulation of a couple of criteria for intelligent lexical acquisition systems subsumed under one paradigm: the Learn-Alpha design rule. The thesis describes the design and quality of a prototype for such a system, whose acquisition components have been developed from scratch and built on top of one of the state-of-the-art Head-driven Phrase Structure Grammar (HPSG) processing systems. The quality of this prototype is investigated in a series of experiments, in which the system is fed with extracts of a large English corpus. While the idea of using machine-readable language input to automatically acquire lexical knowledge is not new, we are not aware of a system that fulfills Learn-Alpha and is able to deal with large corpora. To instance four major challenges of constructing such a system, it should be mentioned that a) the high number of possible structural descriptions caused by highly underspeci ed lexical entries demands for a parser with a very effective ambiguity management system, b) the automatic construction of concise lexical entries out of a bulk of observed lexical facts requires a special technique of data alignment, c) the reliability of these entries depends on the system's decision on whether it has seen 'enough' input and d) general properties of language might render some lexical features indeterminable if the system tries to acquire them with a too high precision. The cornerstone of this dissertation is the motivation and development of a general theory of automatic lexical acquisition that is applicable to every language and independent of any particular theory of grammar or lexicon. This work is divided into five chapters. The introductory chapter first contrasts three different and mutually incompatible approaches to (artificial) lexical acquisition: cue-based queries, head-lexicalized probabilistic context free grammars and learning by unification. Then the postulation of the Learn-Alpha design rule is presented. The second chapter outlines the theory that underlies Learn-Alpha and exposes all the related notions and concepts required for a proper understanding of artificial lexical acquisition. Chapter 3 develops the prototyped acquisition method, called ANALYZE-LEARN-REDUCE, a framework which implements Learn-Alpha. The fourth chapter presents the design and results of a bootstrapping experiment conducted on this prototype: lexeme detection, learning of verbal valency, categorization into nominal count/mass classes, selection of prepositions and sentential complements, among others. The thesis concludes with a review of the conclusions and motivation for further improvements as well as proposals for future research on the automatic induction of lexical features.

Software tools and efficient algorithms for the feature detection, feature tracking, event localization, and visualization of large sets of atmospheric data

Data sets describing the state of the earth's atmosphere are of great importance in the atmospheric sciences. Over the last decades, the quality and sheer amount of the available data increased significantly, resulting in a rising demand for new tools capable of handling and analysing these large, multidimensional sets of atmospheric data. The interdisciplinary work presented in this thesis covers the development and the application of practical software tools and efficient algorithms from the field of computer science, aiming at the goal of enabling atmospheric scientists to analyse and to gain new insights from these large data sets. For this purpose, our tools combine novel techniques with well-established methods from different areas such as scientific visualization and data segmentation. In this thesis, three practical tools are presented. Two of these tools are software systems (Insight and IWAL) for different types of processing and interactive visualization of data, the third tool is an efficient algorithm for data segmentation implemented as part of Insight.Insight is a toolkit for the interactive, three-dimensional visualization and processing of large sets of atmospheric data, originally developed as a testing environment for the novel segmentation algorithm. It provides a dynamic system for combining at runtime data from different sources, a variety of different data processing algorithms, and several visualization techniques. Its modular architecture and flexible scripting support led to additional applications of the software, from which two examples are presented: the usage of Insight as a WMS (web map service) server, and the automatic production of a sequence of images for the visualization of cyclone simulations. The core application of Insight is the provision of the novel segmentation algorithm for the efficient detection and tracking of 3D features in large sets of atmospheric data, as well as for the precise localization of the occurring genesis, lysis, merging and splitting events. Data segmentation usually leads to a significant reduction of the size of the considered data. This enables a practical visualization of the data, statistical analyses of the features and their events, and the manual or automatic detection of interesting situations for subsequent detailed investigation. The concepts of the novel algorithm, its technical realization, and several extensions for avoiding under- and over-segmentation are discussed. As example applications, this thesis covers the setup and the results of the segmentation of upper-tropospheric jet streams and cyclones as full 3D objects. Finally, IWAL is presented, which is a web application for providing an easy interactive access to meteorological data visualizations, primarily aimed at students. As a web application, the needs to retrieve all input data sets and to install and handle complex visualization tools on a local machine are avoided. The main challenge in the provision of customizable visualizations to large numbers of simultaneous users was to find an acceptable trade-off between the available visualization options and the performance of the application. Besides the implementational details, benchmarks and the results of a user survey are presented.

Endocarditis due to Tropheryma whipplei: rapid detection, limited genetic diversity, and long-term clinical outcome in a local experience

The characteristic features of Whipple's disease include abdominal pain, diarrhoea, wasting, and arthralgias, with the causative agent, Tropheryma whipplei, being detected mainly in intestinal biopsies. PCR technology has led to the identification of T. whipplei in specimens from various other locations, including the central nervous system and the heart. T. whipplei is now recognized as one of the causes of culture-negative endocarditis, and endocarditis can be the only manifestation of the infection with T. whipplei. Although it is considered a rare disease, the true incidence of endocarditis due to T. whipplei is not clearly established. With the increasing use of molecular methods, it is likely that T. whipplei will be more frequently identified. Questions also remain about the genetic variability of T. whipplei strains, optimal diagnostic procedures and therapeutic options. In the present study, we provide clinical data on four new patients with documented endocarditis due to T. whipplei in the context of the available published literature. There was no clinical involvement of the gastrointestinal tract. Genetic analysis of the T. whipplei strains with DNA isolated from the excised heart valves revealed little to no genetic variability. In a selected case, we describe acridine orange staining for early detection of the disease, prompting early adaptation of the antibiotic therapy. We provide long-term follow-up data on the patients. In our hands, an initial 2-week course of intravenous antibiotics followed by cotrimoxazole for at least 1 year was a suitable treatment option for T. whipplei endocarditis.

Sensitive and selective detection of free FXIII activation peptide: a potential marker of acute thrombotic events

Coagulation factor XIII (FXIII) stabilizes fibrin fibers and is therefore a major player in the maintenance of hemostasis. FXIII is activated by thrombin resulting in cleavage and release of the FXIII activation peptide (AP-FXIII). The objective of this study was to characterize the released AP-FXIII and determine specific features that may be used for its specific detection. We analyzed the structure of bound AP-FXIII within the FXIII A-subunit and interactions of AP-FXIII by hydrogen bonds with both FXIII A-subunit monomers. We optimized our previously developed AP-FXIII ELISA by using 2 monoclonal antibodies. We determined high binding affinities between the antibodies and free AP-FXIII and demonstrated specific binding by epitope mapping analyses with surface plasmon resonance and enzyme-linked immunosorbent assay. Because the structure of free AP-FXIII had been characterized so far by molecular modeling only, we performed structural analysis by nuclear magnetic resonance. Recombinant AP-FXIII was largely flexible both in plasma and water, differing significantly from the rigid structure in the bound state. We suggest that the recognized epitope is either occluded in the noncleaved form or possesses a structure that does not allow binding to the antibodies. On the basis of our findings, we propose AP-FXIII as a possible new marker for acute thrombotic events.