852 resultados para Initial data problem


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Envenoming snakebites are thought to be a particularly important threat to public health worldwide, especially in rural areas of tropical and subtropical countries. The true magnitude of the public health threat posed by snakebites is unknown, making it difficult for public health officials to optimize prevention and treatment. The objective of this work was to conduct a systematic review of the literature to gather data on snakebite epidemiology in the Amazon region and describe a case series of snakebites from epidemiological surveillance in the State of Amazonas (1974-2012). Only 11 articles regarding snakebites were found. In the State of Amazonas, information regarding incidents involving snakes is scarce. Historical trends show an increasing number of cases after the second half of the 1980s. Snakebites predominated among adults (20-39 years old; 38%), in the male gender (78.9%) and in those living in rural areas (85.6%). The predominant snake envenomation type was bothropic. The incidence reported by the epidemiological surveillance in the State of Amazonas, reaching up to 200 cases/100,000 inhabitants in some areas, is among the highest annual snakebite incidence rates of any region in the world. The majority of the cases were reported in the rainy season with a case-fatality rate of 0.6%. Snakebite envenomation is a great disease burden in the State of Amazonas, representing a challenge for future investigations, including approaches to estimating incidence under-notification and case-fatality rates as well as the factors related to severity and disabilities.

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PURPOSE: Two groups of girls with premature breast development were studied retrospectively. We tried to identify clinical, radiological, and hormonal parameters that could distinguish between a benign, nonprogressive premature thelarche and a true precocious puberty. METHODS: The clinical outcome of 88 girls with breast enlargement before 6.1 years of age was analyzed. Taking into account the progression of their sexual maturation, we allocated the children into 2 groups: "Isolated Premature Thelarche" (n = 63) and "Precocious Puberty" (n = 25) groups. Chronological and bone ages, height and growth velocity centiles, computerized tomography of hypothalamus-pituitary area, pelvic ultrasonography, gonadotropin response to luteinizing hormone-releasing hormone stimulation as well as basal levels of luteinizing hormone, follicle-stimulating hormone, estradiol, and prolactin were studied in both groups. Statistical analysis were performed using the Student t test to compare the sample means. Fisher's exact test and chi² test were used to analyze the nonparametric variables. RESULTS: Isolated premature thelarche most frequently affected girls younger than 2 years who presented exaggerated follicle-stimulating hormone response to luteinizing hormone-releasing hormone stimulation test. The precocious puberty group had higher initial stature, accelerated growth rate and bone age, increased uterine and ovarian volumes, high spontaneous luteinizing hormone levels by immunofluorimetric assay, as well as a high luteinizing hormone response and peak luteinizing hormone/follicle-stimulating hormone ratio after luteinizing hormone-releasing hormone stimulation. CONCLUSION: At initial presentation, girls who undergo true precocious puberty present advanced bone age, increased uterine and ovarian volumes in addition to breast enlargement, as well as an luteinizing hormone-predominant response after a luteinizing hormone-releasing hormone stimulation test.

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This work presents an improved model to solve the non-emergency patients transport (NEPT) service issues given the new rules recently established in Portugal. The model follows the same principle of the Team Orienteering Problem by selecting the patients to be included in the routes attending the maximum reduction in costs when compared with individual transportation. This model establishes the best sets of patients to be transported together. The model was implemented in AMPL and a compact formulation was solved using NEOS Server. A heuristic procedure based on iteratively solving Orienteering Problems is presented, and this heuristic provides good results in terms of accuracy and computation time. Euclidean instances as well as asymmetric real data gathered from Google maps were used, and the model has a promising performance mainly with asymmetric cost matrices.

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This chapter aims at developing a taxonomic framework to classify the studies on the flexible job shop scheduling problem (FJSP). The FJSP is a generalization of the classical job shop scheduling problem (JSP), which is one of the oldest NP-hard problems. Although various solution methodologies have been developed to obtain good solutions in reasonable time for FSJPs with different objective functions and constraints, no study which systematically reviews the FJSP literature has been encountered. In the proposed taxonomy, the type of study, type of problem, objective, methodology, data characteristics, and benchmarking are the main categories. In order to verify the proposed taxonomy, a variety of papers from the literature are classified. Using this classification, several inferences are drawn and gaps in the FJSP literature are specified. With the proposed taxonomy, the aim is to develop a framework for a broad view of the FJSP literature and construct a basis for future studies.

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The MAP-i Doctoral Program of the Universities of Minho, Aveiro and Porto

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DNA microarrays are one of the most used technologies for gene expression measurement. However, there are several distinct microarray platforms, from different manufacturers, each with its own measurement protocol, resulting in data that can hardly be compared or directly integrated. Data integration from multiple sources aims to improve the assertiveness of statistical tests, reducing the data dimensionality problem. The integration of heterogeneous DNA microarray platforms comprehends a set of tasks that range from the re-annotation of the features used on gene expression, to data normalization and batch effect elimination. In this work, a complete methodology for gene expression data integration and application is proposed, which comprehends a transcript-based re-annotation process and several methods for batch effect attenuation. The integrated data will be used to select the best feature set and learning algorithm for a brain tumor classification case study. The integration will consider data from heterogeneous Agilent and Affymetrix platforms, collected from public gene expression databases, such as The Cancer Genome Atlas and Gene Expression Omnibus.

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Dissertação de mestrado integrado em Engenharia e Gestão de Sistemas de Informação

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Tese de Doutoramento em Estudos da Criança (Especialidade em Educação Musical)

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We study the problem of privacy-preserving proofs on authenticated data, where a party receives data from a trusted source and is requested to prove computations over the data to third parties in a correct and private way, i.e., the third party learns no information on the data but is still assured that the claimed proof is valid. Our work particularly focuses on the challenging requirement that the third party should be able to verify the validity with respect to the specific data authenticated by the source — even without having access to that source. This problem is motivated by various scenarios emerging from several application areas such as wearable computing, smart metering, or general business-to-business interactions. Furthermore, these applications also demand any meaningful solution to satisfy additional properties related to usability and scalability. In this paper, we formalize the above three-party model, discuss concrete application scenarios, and then we design, build, and evaluate ADSNARK, a nearly practical system for proving arbitrary computations over authenticated data in a privacy-preserving manner. ADSNARK improves significantly over state-of-the-art solutions for this model. For instance, compared to corresponding solutions based on Pinocchio (Oakland’13), ADSNARK achieves up to 25× improvement in proof-computation time and a 20× reduction in prover storage space.

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Football is considered nowadays one of the most popular sports. In the betting world, it has acquired an outstanding position, which moves millions of euros during the period of a single football match. The lack of profitability of football betting users has been stressed as a problem. This lack gave origin to this research proposal, which it is going to analyse the possibility of existing a way to support the users to increase their profits on their bets. Data mining models were induced with the purpose of supporting the gamblers to increase their profits in the medium/long term. Being conscience that the models can fail, the results achieved by four of the seven targets in the models are encouraging and suggest that the system can help to increase the profits. All defined targets have two possible classes to predict, for example, if there are more or less than 7.5 corners in a single game. The data mining models of the targets, more or less than 7.5 corners, 8.5 corners, 1.5 goals and 3.5 goals achieved the pre-defined thresholds. The models were implemented in a prototype, which it is a pervasive decision support system. This system was developed with the purpose to be an interface for any user, both for an expert user as to a user who has no knowledge in football games.

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Current data mining engines are difficult to use, requiring optimizations by data mining experts in order to provide optimal results. To solve this problem a new concept was devised, by maintaining the functionality of current data mining tools and adding pervasive characteristics such as invisibility and ubiquity which focus on their users, providing better ease of use and usefulness, by providing autonomous and intelligent data mining processes. This article introduces an architecture to implement a data mining engine, composed by four major components: database; Middleware (control); Middleware (processing); and interface. These components are interlinked but provide independent scaling, allowing for a system that adapts to the user’s needs. A prototype has been developed in order to test the architecture. The results are very promising and showed their functionality and the need for further improvements.

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An unsuitable patient flow as well as prolonged waiting lists in the emergency room of a maternity unit, regarding gynecology and obstetrics care, can affect the mother and child’s health, leading to adverse events and consequences regarding their safety and satisfaction. Predicting the patients’ waiting time in the emergency room is a means to avoid this problem. This study aims to predict the pre-triage waiting time in the emergency care of gynecology and obstetrics of Centro Materno Infantil do Norte (CMIN), the maternal and perinatal care unit of Centro Hospitalar of Oporto, situated in the north of Portugal. Data mining techniques were induced using information collected from the information systems and technologies available in CMIN. The models developed presented good results reaching accuracy and specificity values of approximately 74% and 94%, respectively. Additionally, the number of patients and triage professionals working in the emergency room, as well as some temporal variables were identified as direct enhancers to the pre-triage waiting time. The imp lementation of the attained knowledge in the decision support system and business intelligence platform, deployed in CMIN, leads to the optimization of the patient flow through the emergency room and improving the quality of services.

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OBJECTIVE - To investigate the initial energy level required for electrical cardioversion of atrial fibrillation (AF). METHODS - We studied patients undergoing electrical cardioversion in the 1st Multicenter Trial of SOCESP. Patients were divided into 2 groups according to the initial energy level of electrical cardioversion: 100J and > or = 150J. We compared the efficacy of the initial and final shock of the procedure, the number of shocks administered, and the cumulative energy levels. RESULTS - Eight-six patients underwent electrical cardioversion. In 53 patients (62%), cardioversion was started with 100J, and in 33 patients (38%), cardioversion was started with > or = 150J. Groups did not differ regarding clinical features and therapeutical interventions. A tendency existed towards greater efficacy of the initial shock in patients who received > or = 150J (61% vs. 42% in the 100J group, p=0.08). The number of shocks was smaller in the > or = 150J group (1.5±0.7 vs. 2.1±1.3, p=0.04). No difference existed regarding the final efficacy of electrical cardioversion and total cumulative energy levels in both groups. In the subgroup of patients with recent-onset AF (<=48h), the cumulative energy level was lower in the 100J group (240±227J vs. 324±225J, p=0.03). CONCLUSION - Patients who were given initial energy of > or = 150J received fewer counter shocks with a tendency toward greater success than those patients who were given 100J; however, in patients with recent-onset AF, the average cumulative energy level was lower in the 100J group. These data suggest that electrical cardioversion should be initiated with energy levels > or = 150J in patients with chronic AF.

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Finfish pots have emerged as a “responsible” gear, when used in combination with conservational and technical measures to sustain fisheries. Previous trials in Irish waters have offered no published reported data and so three designs tested in the current study provide new information on this gear. The most successful traps in terms of fish catch were rigid steel framed rectangular pots used to target Conger eel. Although commercial yield was low (0.2 per trap haul), potential existed for a viable pot fishery. Deployment and storage of Norwegian floating pots was conducted with relative ease but performance in the water was poor resulting in loss of gear. Catch returns were notable even though effort was restricted as mega-faunal by-catch was a problem, which lead to ending this trial. From these initial trials it was evident that catch rates were low compared to established Norwegian fisheries (3.6 cod per pot), which resulted in the utilisation of pots, already established in the crustacean fishery, to find species readily accessible to pot capture. Although fished and designed differently, these gears provided an opportunity to establish the benefits of pot fishing to fish quality and to determine the effects on by-catch. The fishing effects of three catching methods (pots, angling and trawl) and the effects of air exposure on the physiological status of a common by-catch, the lesser spotted dogfish Scyliorhinus canícula (L.) were examined using a range of physiological biomarkers (plasma catecholamine, glucose, lactate, muscle pH and muscle lactate). Physiological responses of fish to an emersion stress regime resulted in a significant metabolic disturbance in groups, but may not have weakened the overall health of these fish, as signified in the revival of some metabolites. Plasma glucose and lactate concentrations did not however recovery to baseline levels indicating that to achieve an accurate profile, responses should be determined by a suite of biomarkers. Responses did not demonstrate that samples from the pots were significantly less stressed than for the other two methods; angling and trawling, which are in contrast to many other studies. Employment of finfish potting therefore in Irish waters needs further consideration before further promotion as a more responsible method to supplement or replace established techniques.