993 resultados para Near-Duplicate Detection


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Conventional molecular techniques for detection and characterization of relevant nucleic acid (i.e. DNA) sequences are, nowadays, cumbersome, expensive and with reduced portability. The main objective of this dissertation consisted in the optimization and validation of a fast and low-cost colorimetric nanodiagnostic methodology for the detection of single nucleotide polymorphisms (SNPs). This was done considering SNPs associated to obesity of commercial interest for STAB VIDA, and subsequent evaluation of other clinically relevant targets. Also, integration of this methodology into a microfluidic platform envisaging portability and application on points-of-care (POC) was achieved. To warrant success in pursuing these objectives, the experimental work was divided in four sections: i) genetic association of SNPs to obesity in the Portuguese population; ii) optimization and validation of the non-cross-linking approach for complete genotype characterization of these SNPs; iii) incorporation into a microfluidic platform; and iv) translation to other relevant commercial targets. FTO dbSNP rs#:9939609 carriers had higher body mass index (BMI), total body fat mass, waist perimeter and 2.5 times higher risk to obesity. AuNPs functionalized with thiolated oligonucleotides (Au-nanoprobes) were used via the non-cross-linking to validate a diagnostics approach against the gold standard technique - Sanger Sequencing - with high levels of sensitivity (87.50%) and specificity (91.67%). A proof-of-concept POC microfluidic device was assembled towards incorporation of the molecular detection strategy. In conclusion a successful framework was developed and validated for the detection of SNPs with commercial interest for STAB VIDA, towards future translation into a POC device.

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The Santa Tenesinha region in northeaster Mato Grosso has a varied vegetation which is principally hammock pantanal. The flat clayey alluvial ground between the hummocks is coveted with a continuous non-cerrado ground cover dominated by grasses but which harbors sedges and a lange herb flora. No woody plants grow in it. The tops of the 10-20m wide, slightly elliptical hummocks, 1.5-2 m high, 10-40 per hectare, are covered with cerrado plants: herbs, semlshrubs, thin- and thick-stemmed shrubs and low trees. For 4-5 months during the latter part of the rainy season, the regional water table rises to the surface and the ground between the hummocks becomes saturated or floods up to 1.5-2 m deep. The tops of the hummocks almost always remain above high water level. In the dry season the surface soil dries out completely. This alternation of saturation or shallow flooding and dryness, prevents woody plant, growth between the hummocks, and except for a few tolerant species, also prevents woody plant. growth on the lower part of the hummochs. The gallery forests in the pantanal are seasonally flooded more deeply but their soil does not dry out so thonoughly in the dry season so woody plant growth is not prevented.

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Abundances of msmall terrestrial mammals were estimated in 10 and 100-ha, isolated and non-isolated primary forest reserves near, Manaus, Brazil between October 1983 and March 1984. The smalt mammal abundance pattern In a 10 ha reserve isolated fan appoximately three years differed significantly from that in othen reserves, primarily due to higher capture rates of Marmosa cinerea, Rhipidomys mastacalis, and Onyzomys paricola in the isolated reserve. Viet type and re-invasion potential may be important factors the small mammal communities in forest patches. Variation the small mammal community among othen reserves was pnimanlty due to variatton In the abundances of Proechimys and 0. capito. At least pant of this vantation was attributable to temporal efects, but variation due to reserve effects also was suggested. Small mammals were much more abundant in the reserves during the present study than in 1982.

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Ship tracking systems allow Maritime Organizations that are concerned with the Safety at Sea to obtain information on the current location and route of merchant vessels. Thanks to Space technology in recent years the geographical coverage of the ship tracking platforms has increased significantly, from radar based near-shore traffic monitoring towards a worldwide picture of the maritime traffic situation. The long-range tracking systems currently in operations allow the storage of ship position data over many years: a valuable source of knowledge about the shipping routes between different ocean regions. The outcome of this Master project is a software prototype for the estimation of the most operated shipping route between any two geographical locations. The analysis is based on the historical ship positions acquired with long-range tracking systems. The proposed approach makes use of a Genetic Algorithm applied on a training set of relevant ship positions extracted from the long-term storage tracking database of the European Maritime Safety Agency (EMSA). The analysis of some representative shipping routes is presented and the quality of the results and their operational applications are assessed by a Maritime Safety expert.

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From May to December, 1992 we studied the earthworm activity, as part of the ECOFIT Program at Surrão ( 30km from Boa Vista), verifying the duration of the activity and quantifying it through the casts deposited on the soil surface. Three transects were stablished: a 100m long in the savanna, a 40m in the transitional area and 100m long in the forest. Specimens were collected monthly along the transects according to the method proposed by TSBF and the casts were collected from the squares previously placed on the transects. Two earthworm species were found in the three areas: Pontoscolex roraìmensis and Pontoscolex corethrurus. The first species depositing its casts on the soil surface. Rainy season wich usually occurs from April to August, determined the duration of activity for the two species (however, 1992 was atypical in that rainy season, only started in May). P. roraìmensis produced casts in the three areas from May to August followed by aestivation. In the savanna, P. corethrurus started aestivation in the same period as P. roraìmensis but remained active until November in the two other areas. P. roraìmensiswas found up 50m from the forest border, being associated to the presence of Curatella americana and Byrsonima sp, two typical savanna bushes.

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Over a seven year period from 1991 to 1997, 22 species of tiger beetles, representing nine genera, were recorded near Manaus, Brazil. In the Whitewaterfloodplains along the Rio Solimões-Amazonas (Ilha de Marchantaria), three diurnal species inhabit inundation forests and six species (two diurnal, four nocturnal) live in open areas. Data on their natural history and adaptation to living conditions in floodplains are presented. Fifteen species were located on non-flooded uplands (Reserva Florestal A. Ducke). Five diurnal species inhabit the forest floor, two species are canopy dwellers, and eight species (seven diurnal, one nocturnal) live in open areas on whitesand or laterite. Only one species, Pentacomia lacordairei, was found in both floodplain and upland forests. A key to the larvae of tiger beetle genera located near Manaus is presented.

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The spatial and temporal distribution of a guild of eight diurnal tiger beetle species was studied on a 105 m long transect near the field station of the Reserva Florestal A. Ducke near Manaus (AM), Brazil. The transect followed a path that included both shaded and an open areas. Five of the species, restricted to primary forest, occurrred only in shaded areas of the transect, and three species occurred in open areas. Of all eight species only two of the open habitat species showed no clear seasonality in adult activity. In six species the activity of adults was limited to the rainy season. The most pronounced annual rhythm was found in Pentacomia ventralis, an open habitat species. Activity of adults was limited to October/November. First in-star larvae appeared shortly thereafter. Larval development mainly took place from January to May. The third instar larva entered a dormancy which lasted up to 10 months, and which enabled the synchronisation of emerging adults with annual seasons.

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Imaging techniques are the standard method for assessment of fracture healing processes. However, these methods are perhaps not entirely reliable for early detection of complications, the most frequent of these being delayed union and non-union. A prompt diagnosis of such disorders could prevent prolonged patient distress and disability. Efforts should be directed towards the development of new technologies for improving accuracy in diagnosing complications following bone fractures. The variation in the levels of bone turnover markers (BTMs) have been assessed with regard to there ability to predict impaired fracture healing at an early stage, nevertheless the conclusions of some studies are not consensual. In this article the authors have revised the potential of BTMs as early predictors of prognosis in adult patients presenting traumatic bone fractures but who did not suffer from osteopenia or postmenopausal osteoporosis. The available information from the different studies performed in this field was systematized in order to highlight the most promising BTMs for the assessment of fracture healing outcome.

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Nowadays, road accidents are a major public health problem, which increase is forecasted if road safety is not treated properly, dying about 1.2 million people every year around the globe. In 2012, Portugal recorded 573 fatalities in road accidents, on site, revealing the largest decreasing of the European Union for 2011, along with Denmark. Beyond the impact caused by fatalities, it was calculated that the economic and social costs of road accidents weighted about 1.17% of the Portuguese gross domestic product in 2010. Visual Analytics allows the combination of data analysis techniques with interactive visualizations, which facilitates the process of knowledge discovery in sets of large and complex data, while the Geovisual Analytics facilitates the exploration of space-time data through maps with different variables and parameters that are under analysis. In Portugal, the identification of road accident accumulation zones, in this work named black spots, has been restricted to annual fixed windows. In this work, it is presented a dynamic approach based on Visual Analytics techniques that is able to identify the displacement of black spots on sliding windows of 12 months. Moreover, with the use of different parameterizations in the formula usually used to detect black spots, it is possible to identify zones that are almost becoming black spots. Through the proposed visualizations, the study and identification of countermeasures to this social and economic problem can gain new grounds and thus the decision- making process is supported and improved.

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Due to advances in information technology (e.g., digital video cameras, ubiquitous sensors), the automatic detection of human behaviors from video is a very recent research topic. In this paper, we perform a systematic and recent literature review on this topic, from 2000 to 2014, covering a selection of 193 papers that were searched from six major scientific publishers. The selected papers were classified into three main subjects: detection techniques, datasets and applications. The detection techniques were divided into four categories (initialization, tracking, pose estimation and recognition). The list of datasets includes eight examples (e.g., Hollywood action). Finally, several application areas were identified, including human detection, abnormal activity detection, action recognition, player modeling and pedestrian detection. Our analysis provides a road map to guide future research for designing automatic visual human behavior detection systems.

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Timber frame buildings are well known as an efficient seismic resistant structure popular all over the world not only due to their seismic performance, but also to their low cost and the strength they offer. These constructions still exist today and it is important to be able to preserve them, so a better knowledge on their behaviour is sought. Furthermore, historic technologies could be used even in modern constructions to build seismic resistant buildings using more natural materials with lesser costs. A great rehabilitation effort is being carried out on this type of buildings, as their neglect has led to decay or their change in use and alterations to the structure has led to the need to retrofit such buildings; only recently studies on their behaviour have become available and only a few of them address the issue of possible strengthening techniques for this kind of walls. In this scope, an innovative retrofitting technique (near surface mounted steel flat bars) is proposed and validated on traditional timber frame walls based on an extensive experimental program. The results of the static cyclic tests on distinct wall typologies retrofitted with the NSM technique are herein presented and discussed in detail. The main features on deformation, lateral stiffness, lateral resistance and seismic performance indexes are analysed

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The Internet of Things (IoT) is a concept that can foster the emergence of innovative applications. In order to minimize parents’s concerns about their children’s safety, this paper presents the design of a smart Internet of Things system for identifying dangerous situations. The system will be based on real time collection and analysis of physiological signals monitored by non-invasive and non-intrusive sensors, Frequency IDentification (RFID) tags and a Global Positioning System (GPS) to determine when a child is in danger. The assumption of a state of danger is made taking into account the validation of a certain number of biometric reactions to some specific situations and according to a self-learning algorithm developed for this architecture. The results of the analysis of data collected and the location of the child will be able in real time to child’s care holders in a web application.

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Polymer based scintillator composites have been fabricated by combining poly(vinylidene fluoride) (PVDF) and Gd2O3:Eu nanoparticles (50nm). PVDF has been used since it is a flexible and stable binder matrix and highly resistance to thermal and light deterioration. Gd2O3:Eu has been selected as scintillator material due to its wide band gap, high density and suitable visible light yield. The structural, mechanical, thermal and electrical characteristics of the composites were studied as a function of filler content, together with their performance as scintillator material. The introduction of Gd2O3:Eu nanoparticles into the PVDF matrix does not influence the morphology of the polymer or the degree of crystallinity. On the other hand, an increase of the Young´s modulus with respect to PVDF matrix is observed for filler contents of 0.1-0.75 wt.%. The introduction of Gd2O3:Eu into the PVDF matrix increases dielectric constant and DC electrical conductivity as well as the visible light yield in the nanocomposite, being this increase dependent upon Gd2O3:Eu content and X-ray input power. In this way, Gd2O3:Eu/PVDF composites shows suitable characteristics to be used as X-ray radiation transducers, in particular for large area applications.

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Schizophrenia stands for a long-lasting state of mental uncertainty that may bring to an end the relation among behavior, thought, and emotion; that is, it may lead to unreliable perception, not suitable actions and feelings, and a sense of mental fragmentation. Indeed, its diagnosis is done over a large period of time; continuos signs of the disturbance persist for at least 6 (six) months. Once detected, the psychiatrist diagnosis is made through the clinical interview and a series of psychic tests, addressed mainly to avoid the diagnosis of other mental states or diseases. Undeniably, the main problem with identifying schizophrenia is the difficulty to distinguish its symptoms from those associated to different untidiness or roles. Therefore, this work will focus on the development of a diagnostic support system, in terms of its knowledge representation and reasoning procedures, based on a blended of Logic Programming and Artificial Neural Networks approaches to computing, taking advantage of a novel approach to knowledge representation and reasoning, which aims to solve the problems associated in the handling (i.e., to stand for and reason) of defective information.

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About 90% of breast cancers do not cause or are capable of producing death if detected at an early stage and treated properly. Indeed, it is still not known a specific cause for the illness. It may be not only a beginning, but also a set of associations that will determine the onset of the disease. Undeniably, there are some factors that seem to be associated with the boosted risk of the malady. Pondering the present study, different breast cancer risk assessment models where considered. It is our intention to develop a hybrid decision support system under a formal framework based on Logic Programming for knowledge representation and reasoning, complemented with an approach to computing centered on Artificial Neural Networks, to evaluate the risk of developing breast cancer and the respective Degree-of-Confidence that one has on such a happening.