923 resultados para Kinesiology, Applied
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Objective: Tooth decay is one of the more common diseases of childhood. Several studies recommend that early preventive measures must be implemented since the first years of life and continue throughout childhood and adolescence. The aim of the this study was to present results of a preventive dental program considering oral health maintenance, dental caries experience and the prevalence of dental caries relation with follow-up compliance visits. Material end method: Intraoral and interproximal radiographic exams were performed on 171 patients participants of a preventive dental program. Data regarding age, gender, previous caries experience and the frequency at which the patients attended return visits were obtained from the records. The data were analyzed statistically by the McNemar test, with the level of significance set at 1%. Result: Clinical and radiographic examination revealed that most children participating in the program had sound teeth (77.2 and 84.8%, respectively). The past dental history of the dental caries from patients included in this study showed statistical relevance when associated with the present dental caries experience and a statistical relationship was found from the absence of compliance to clinical visits and the dental caries presence. Conclusion: The preventive strategy had a positive influence on oral health maintenance in the children examined. Previous caries experience and the lack of compliance with return visits influenced the clinical oral condition of the children during participation in the preventive program.
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This article describes the use of Artificial Intelligence (IA) techniques applied in cells of a manufacturing system. Machine Vision was used to identify pieces and their positions of two different products to be assembled in the same productive line. This information is given as input for an IA planner embedded in the manufacturing system. Therefore, initial and final states are sent automatically to the planner capable to generate assembly plans for a robotic cell, in real time.
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This study analyzes the environmental performance of the Municipal Solid Waste Management System (MSWMS) of Piedade, São Paulo, from a systemic perspective. A life cycle assessment (LCA) technique was applied according to an attributional approach to evaluate both the current operational situation and different prospective scenarios, which were devised based on the application of targets for recycling dry and wet waste suggested by the pre-draft version of the Brazilian Plan for Solid Waste. The life cycle impact assessment method EcoIndicator 99, in association with normalization and weighting procedures, was used to conduct the analysis. It was observed that the adoption of goals of 30%, 50% and 70% for recovering of the recyclable dry waste, resulted in improvement of the environmental performance of the waste management system under analysis, respectively of 10%, 15% and 20%. It was also possible to detect an evolution in the order of 54% in reducing impacts resulting from the adoption of targets for composting. LCA proved to be effective for the evaluation of the environmental performance of MSWMS-Piedade. However, for future evaluations, the attributional approach should be replaced by the methodological practice of substitution to enable the avoided burdens to be considered in estimations of the environmental performance municipal solid waste management systems.
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In order to refine the solution given by the classical logistic equation and extend its range of applications in the study of tumor dynamics, we propose and solve a generalization of this equation, using the so-called Fractional Calculus, i.e., we replace the ordinary derivative of order 1, in one version of the usual equation, by a non-integer derivative of order 0 < α < 1, and recover the classical solution as a particular case. Finally, we analyze the applicability of this model to describe the growth of cancer tumors.
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A robotic control design considering all the inherent nonlinearities of the robot engine configuration is developed. The interactions between the robot and joint motor drive mechanism are considered. The proposed control combines two strategies, one feedforward control in order to maintain the system in the desired coordinate, and feedback control system to take the system into a desired coordinate. The feedback control is obtained using State Dependent Riccati Equation (SDRE). For link positioning two cases are considered. Case 1: For control positioning, it is only used motor voltage; Case 2: For control positioning, it is used both motor voltage and torque between the links. Simulation results, including parametric uncertainties in control shows the feasibility of the proposed control for the considered system.
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In the instrumental records of daily precipitation, we often encounter one or more periods in which values below some threshold were not registered. Such periods, besides lacking small values, also have a large number of dry days. Their cumulative distribution function is shifted to the right in relation to that for other portions of the record having more reliable observations. Such problems are examined in this work, based mostly on the two-sample Kolmogorov–Smirnov (KS) test, where the portion of the series with more number of dry days is compared with the portion with less number of dry days. Another relatively common problem in daily rainfall data is the prevalence of integers either throughout the period of record or in some part of it, likely resulting from truncation during data compilation prior to archiving or by coarse rounding of daily readings by observers. This problem is identified by simple calculation of the proportion of integers in the series, taking the expected proportion as 10%. The above two procedures were applied to the daily rainfall data sets from the European Climate Assessment (ECA), Southeast Asian Climate Assessment (SACA), and Brazilian Water Resources Agency (BRA). Taking the statistic D of the KS test >0.15 and the corresponding p-value <0.001 as the condition to classify a given series as suspicious, the proportions of the ECA, SACA, and BRA series falling into this category are, respectively, 34.5%, 54.3%, and 62.5%. With relation to coarse rounding problem, the proportions of series exceeding twice the 10% reference level are 3%, 60%, and 43% for the ECA, SACA, and BRA data sets, respectively. A simple way to visualize the two problems addressed here is by plotting the time series of daily rainfall for a limited range, for instance, 0–10 mm day−1.
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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
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In the search for productivity increase, industry has invested on the development of intelligent, flexible and self-adjusting method, capable of controlling processes through the assistance of autonomous systems, independently whether they are hardware or software. Notwithstanding, simulating conventional computational techniques is rather challenging, regarding the complexity and non-linearity of the production systems. Compared to traditional models, the approach with Artificial Neural Networks (ANN) performs well as noise suppression and treatment of non-linear data. Therefore, the challenges in the wood industry justify the use of ANN as a tool for process improvement and, consequently, add value to the final product. Furthermore, Artificial Intelligence techniques such as Neuro-Fuzzy Networks (NFNs) have proven effective, since NFNs combine the ability to learn from previous examples and generalize the acquired information from the ANNs with the capacity of Fuzzy Logic to transform linguistic variables in rules.
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Conselho Nacional de Desenvolvimento Cientifico e Tecnológico (CNPq)
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This study evaluated the genetic erosion risk factors and the strategic points for the conservation of Lychnophora ericoides population in “Paraíso Perdido” farm, Serra da Canastra (20° 37’ 54” S; 46° 19’ 37” W; 833 m height) in São João Batista do Glória City, Minas Gerais State, Brazil. The number of young and adult plants, the soil and the phenology were evaluated in two sample areas of 125 m2. Information about the species utilization was obtained with local informants. Data on the region were obtained through literature review, in loco evaluation, GPS and geo-referenced map. In addition, local use of the plant for mixtures of drug was evaluated. According to the results obtained, the soil of the population is lithic with a weathered portion of frank-sandy texture, very acidic and dystrophic. The population density is 0.16 individuals/m2, 0.078 young/adult plant. The predominant phenophase was fruiting (100% plants) followed by flowering (21.62% plants). The local community uses the leaves of the plant in the form of hydroalcoholic extracts, as anti-inflammatory. Based on the evaluated parameters, the population is at 73% risk of genetic erosion. The detected key points were the development of activities including the participation of the local community for habitat protection as well as germplasm collection, seedlings production and reintroduction, together with environmental education, supervision, and reduction in the propensity for fire.
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Most authors struggle to pick a title that adequately conveys all of the material covered in a book. When I first saw Applied Spatial Data Analysis with R, I expected a review of spatial statistical models and their applications in packages (libraries) from the CRAN site of R. The authors’ title is not misleading, but I was very pleasantly surprised by how deep the word “applied” is here. The first half of the book essentially covers how R handles spatial data. To some statisticians this may be boring. Do you want, or need, to know the difference between S3 and S4 classes, how spatial objects in R are organized, and how various methods work on the spatial objects? A few years ago I would have said “no,” especially to the “want” part. Just let me slap my EXCEL spreadsheet into R and run some spatial functions on it. Unfortunately, the world is not so simple, and ultimately we want to minimize effort to get all of our spatial analyses accomplished. The first half of this book certainly convinced me that some extra effort in organizing my data into certain spatial class structures makes the analysis easier and less subject to mistakes. I also admit that I found it very interesting and I learned a lot.
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Airports worldwide are at a disadvantage when it comes to being able to spot birds and warn aircrews about the location of flocks either on the ground or close to the airfield. Birds simply cannot be easily seen during the day and are nearly invisible targets for planes at night or during low visibility. Thermal imaging (infrared) devices can be used to allow ground and tower personnel to pinpoint bird locations day or night, thus giving the airport operators the ability to launch countermeasures or simply warn the aircrews. This technology is available now, though it has been predominately isolated to medical and military system modifications. The cost of these devices has dropped significantly in recent years as technology, capability, and availability have continued to increase. Davison Army Airfield (DAAF), which is located about 20 miles south of Ronald Reagan National Airport in Washington, DC, is the transient home to many bird species including an abundance of ducks, seagulls, pigeons, and migrating Canadian geese. Over the past few years, DAAF implemented a variety of measures in an attempt to control the bird hazards on the airfield. Unfortunately, when it came to controlling these birds on or near our runways and aircraft movement areas we were more reactive than proactive. We would do airfield checks several times an hour to detect and deter any birds in these areas. The deterrents used included vehicle/human presence, pyrotechnics, and the periodic use of a trained border collie. At the time, we felt like we were doing all we could to reduce the threat to aircraft and human life. It was not until a near fatal accident in October 1998, when we truly realized how dangerous our operating environment really was to aircraft at or near the airfield. It was at this time, we had a C-12 (twin-engine passenger plane) land on our primary runway at night. The tower cleared the aircraft to land, and upon touchdown to the runway the aircraft collided with a flock of geese. Neither the tower nor the crew of the aircraft saw the geese because they were obscured in the darkness. The end result was 12 dead geese and $374,000 damage to the C-12. Fortunately, there were no human fatalities, but it was painfully clear we needed to improve our method of clearing the runway at night and during low visibility conditions. It was through this realization that we ventured to the U.S. Army Communications and Electronics Command for ideas on ways to deal with our threat. It was through a sub-organization within this command, Night Vision Labs, that we realized the possibilities of modifying thermal imagery and infrared technology to detecting wildlife on airports.
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“Specifically, issues of race, gender, disability, status, etc. provide a new context in which to judge the reasonableness of an individual’s actions.”
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The centrifuge technique was used to investigate the influence of particle size, applied compression, and substrate material (stainless steel, glass, Teflon, and poly(vinyl chloride)) on particle-surface adhesion force. For this purpose, phosphatic rock (rho(p) = 3090 kg/m(3)) and manioc starch particles (rho(p) = 1480 kg/m(3)) were used as test particles. A microcentrifuge that reached a maximum rotation speed of 14 000 rpm and which contained specially designed centrifuge tubes was used in the adhesion force measurements. The curves showed that the adhesion force profile followed a normal log distribution. The adhesion force increased linearly with particle size and with the increase of each increment of compression force. The manioc starch particles presented greater adhesion forces than the phosphatic rock particles for all particle sizes studied. The glass substrate showed a higher adherence than the other materials, probably due to its smoother topographic surface roughness in relation to the other substrata.
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Risks of the introduction of highly pathogenic avian influenza (HPAI) H5N1 through migratory birds to the main wintering site for wild birds in southern Brazil and its consequences were assessed. Likelihoods were estimated by a qualitative scale ranging from negligible to high. Northern migrants that breed in Alaska and regularly migrate to South America (primary Charadriiformes) can have contact with birds from affected areas in Asia. The likelihood of the introduction of HPAI H5N1 through migratory birds was found to be very low as it is a probability conditioned to successful transmission in breeding areas and the probabilities of an infected bird migrating and shedding the virus as far as southern Brazil. The probability of wild species becoming exposed to H5N1-infected birds is high as they nest with northern migrants from Alaska, whereas for backyard poultry it is moderate to high depending on proximity to wetlands and the presence of species that could increase the likelihood of contact with wild birds such as domestic duck. The magnitude of the biological and economic consequences of successful transmission to poultry or wild birds would be low to severe depending on the probability of the occurrence of outbreak scenarios described. As a result, the risk estimate is greater than negligible, and HPAI H5N1 prevention strategy in the region should always be carefully considered by the veterinary services in Brazil.