922 resultados para Methods of application


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

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This study investigated the effect of two anti-pronation taping techniques on vertical navicular height, an indicator of foot pronation, after its application and 20 min of exercise. The taping techniques were: the low dye (LD) and low dye with the addition of calcaneal slings and reverse sixes (LDCR). A repeated measures study was used. It found that LDCR was superior to LD and control immediately after application and exercise. LD was better than control immediately after application but not after exercise. These findings provide practical directions to clinicians regularly using anti-pronation taping techniques.

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Antioxidant enzymes are involved in important processes of cell detoxification during oxidative stress and have, therefore, been used as biomarkers in algae. Nevertheless, their limited use in fluvial biofilms may be due to the complexity of such communities. Here, a comparison between different extraction methods was performed to obtain a reliable method for catalase extraction from fluvial biofilms. Homogenization followed by glass bead disruption appeared to be the best compromise for catalase extraction. This method was then applied to a field study in a metal-polluted stream (Riou Mort, France). The most polluted sites were characterized by a catalase activity 4–6 times lower than in the low-polluted site. Results of the comparison process and its application are promising for the use of catalase activity as an early warning biomarker of toxicity using biofilms in the laboratory and in the field

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Study on variable stars is an important topic of modern astrophysics. After the invention of powerful telescopes and high resolving powered CCD’s, the variable star data is accumulating in the order of peta-bytes. The huge amount of data need lot of automated methods as well as human experts. This thesis is devoted to the data analysis on variable star’s astronomical time series data and hence belong to the inter-disciplinary topic, Astrostatistics. For an observer on earth, stars that have a change in apparent brightness over time are called variable stars. The variation in brightness may be regular (periodic), quasi periodic (semi-periodic) or irregular manner (aperiodic) and are caused by various reasons. In some cases, the variation is due to some internal thermo-nuclear processes, which are generally known as intrinsic vari- ables and in some other cases, it is due to some external processes, like eclipse or rotation, which are known as extrinsic variables. Intrinsic variables can be further grouped into pulsating variables, eruptive variables and flare stars. Extrinsic variables are grouped into eclipsing binary stars and chromospheri- cal stars. Pulsating variables can again classified into Cepheid, RR Lyrae, RV Tauri, Delta Scuti, Mira etc. The eruptive or cataclysmic variables are novae, supernovae, etc., which rarely occurs and are not periodic phenomena. Most of the other variations are periodic in nature. Variable stars can be observed through many ways such as photometry, spectrophotometry and spectroscopy. The sequence of photometric observa- xiv tions on variable stars produces time series data, which contains time, magni- tude and error. The plot between variable star’s apparent magnitude and time are known as light curve. If the time series data is folded on a period, the plot between apparent magnitude and phase is known as phased light curve. The unique shape of phased light curve is a characteristic of each type of variable star. One way to identify the type of variable star and to classify them is by visually looking at the phased light curve by an expert. For last several years, automated algorithms are used to classify a group of variable stars, with the help of computers. Research on variable stars can be divided into different stages like observa- tion, data reduction, data analysis, modeling and classification. The modeling on variable stars helps to determine the short-term and long-term behaviour and to construct theoretical models (for eg:- Wilson-Devinney model for eclips- ing binaries) and to derive stellar properties like mass, radius, luminosity, tem- perature, internal and external structure, chemical composition and evolution. The classification requires the determination of the basic parameters like pe- riod, amplitude and phase and also some other derived parameters. Out of these, period is the most important parameter since the wrong periods can lead to sparse light curves and misleading information. Time series analysis is a method of applying mathematical and statistical tests to data, to quantify the variation, understand the nature of time-varying phenomena, to gain physical understanding of the system and to predict future behavior of the system. Astronomical time series usually suffer from unevenly spaced time instants, varying error conditions and possibility of big gaps. This is due to daily varying daylight and the weather conditions for ground based observations and observations from space may suffer from the impact of cosmic ray particles. Many large scale astronomical surveys such as MACHO, OGLE, EROS, xv ROTSE, PLANET, Hipparcos, MISAO, NSVS, ASAS, Pan-STARRS, Ke- pler,ESA, Gaia, LSST, CRTS provide variable star’s time series data, even though their primary intention is not variable star observation. Center for Astrostatistics, Pennsylvania State University is established to help the astro- nomical community with the aid of statistical tools for harvesting and analysing archival data. Most of these surveys releases the data to the public for further analysis. There exist many period search algorithms through astronomical time se- ries analysis, which can be classified into parametric (assume some underlying distribution for data) and non-parametric (do not assume any statistical model like Gaussian etc.,) methods. Many of the parametric methods are based on variations of discrete Fourier transforms like Generalised Lomb-Scargle peri- odogram (GLSP) by Zechmeister(2009), Significant Spectrum (SigSpec) by Reegen(2007) etc. Non-parametric methods include Phase Dispersion Minimi- sation (PDM) by Stellingwerf(1978) and Cubic spline method by Akerlof(1994) etc. Even though most of the methods can be brought under automation, any of the method stated above could not fully recover the true periods. The wrong detection of period can be due to several reasons such as power leakage to other frequencies which is due to finite total interval, finite sampling interval and finite amount of data. Another problem is aliasing, which is due to the influence of regular sampling. Also spurious periods appear due to long gaps and power flow to harmonic frequencies is an inherent problem of Fourier methods. Hence obtaining the exact period of variable star from it’s time series data is still a difficult problem, in case of huge databases, when subjected to automation. As Matthew Templeton, AAVSO, states “Variable star data analysis is not always straightforward; large-scale, automated analysis design is non-trivial”. Derekas et al. 2007, Deb et.al. 2010 states “The processing of xvi huge amount of data in these databases is quite challenging, even when looking at seemingly small issues such as period determination and classification”. It will be beneficial for the variable star astronomical community, if basic parameters, such as period, amplitude and phase are obtained more accurately, when huge time series databases are subjected to automation. In the present thesis work, the theories of four popular period search methods are studied, the strength and weakness of these methods are evaluated by applying it on two survey databases and finally a modified form of cubic spline method is intro- duced to confirm the exact period of variable star. For the classification of new variable stars discovered and entering them in the “General Catalogue of Vari- able Stars” or other databases like “Variable Star Index“, the characteristics of the variability has to be quantified in term of variable star parameters.

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Antioxidant enzymes are involved in important processes of cell detoxification during oxidative stress and have, therefore, been used as biomarkers in algae. Nevertheless, their limited use in fluvial biofilms may be due to the complexity of such communities. Here, a comparison between different extraction methods was performed to obtain a reliable method for catalase extraction from fluvial biofilms. Homogenization followed by glass bead disruption appeared to be the best compromise for catalase extraction. This method was then applied to a field study in a metal-polluted stream (Riou Mort, France). The most polluted sites were characterized by a catalase activity 4–6 times lower than in the low-polluted site. Results of the comparison process and its application are promising for the use of catalase activity as an early warning biomarker of toxicity using biofilms in the laboratory and in the field

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This paper presents findings of our study on peer-reviewed papers published in the International Conference on Persuasive Technology from 2006 to 2010. The study indicated that out of 44 systems reviewed, 23 were reported to be successful, 2 to be unsuccessful and 19 did not specify whether or not it was successful. 56 different techniques were mentioned and it was observed that most designers use ad hoc definitions for techniques or methods used in design. Hence we propose the need for research to establish unambiguous definitions of techniques and methods in the field.

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Nesse artigo, tem-se o interesse em avaliar diferentes estratégias de estimação de parâmetros para um modelo de regressão linear múltipla. Para a estimação dos parâmetros do modelo foram utilizados dados de um ensaio clínico em que o interesse foi verificar se o ensaio mecânico da propriedade de força máxima (EM-FM) está associada com a massa femoral, com o diâmetro femoral e com o grupo experimental de ratas ovariectomizadas da raça Rattus norvegicus albinus, variedade Wistar. Para a estimação dos parâmetros do modelo serão comparadas três metodologias: a metodologia clássica, baseada no método dos mínimos quadrados; a metodologia Bayesiana, baseada no teorema de Bayes; e o método Bootstrap, baseado em processos de reamostragem.

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

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This is a report on the influence of the methods of postharvest application of CaCl2 in several concentrations, on the maintenance of the firmness of the sweet passion fruit (Passiflora alata Dryander). The fruits, picked in the pre-climateric stage, were selected desinfection with thiabendazol and submitted to CaCl2 in concentrations of 0% (control), 1%, 2%, 3% or 4% with two methods: immersion (for 2 h) and infiltration under vacuum and pressure (- 25 vacuum kPa, for 1 minute and, + 25 pressure kPa, for 1 min). All fruits were stored under refrigeration (9 degreesC, 85-90% RH), for 30 d. The fruits were evaluated for texture every 3 d. From the results, it is concluded that application of CaCl2 by infiltration favored the maintenance of fruit consistency during the first 18 days of storage. Fruits treated with 1% and 2% of CaCl2 were firmer than the others.

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In this study, different methods of cutting fluid application are used in turning of a difficult-to-machine steel (SAE EV-8). Initially, a semisynthetic cutting fluid was applied using a conventional method (i.e. overhead flood cooling), minimum quantity of cutting fluid, and pulverization. A lubricant of vegetable oil (minimum quantity of lubricant) was also applied using the minimum quantity method. Thereafter, a cutting fluid jet under high pressure (3.0 MPa) was singly applied in the following regions: chip-tool interface, top surface of the chip (between workpiece and chip) and tool-workpiece contact. Moreover, two other methods were used: an interflow between conventional application and chip-tool interface jet (combined method) and, finally, three jets simultaneously applied. In order to carry out these tests, it was necessary to set up a high-pressure system using a piston pump for generating a cutting fluid jet, a venturi for fluid application (minimum quantity of cutting fluid and minimum quantity of lubricant) and a nozzle for cutting fluid pulverization. The output variables analyzed included tool life, surface roughness, cutting tool temperature, cutting force, chip form, chip compression rate and machined specimen microstructure. Among the results, it can be observed that the tool life increases and the cutting force decreases with the application of cutting fluid jet, mainly when it is directed to the chip-tool interface. Excluding the methods involving jet fluid, the conventional method seems to be more efficient than other methods of low pressure, such as minimum quantity of volume and pulverization, when considering just the cutting tool wear. © 2013 IMechE.

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Different methods of cutting fluid application are used on turning of a difficult-tomachine steel (SAE EV-8). A semi-synthetic cutting fluid was applied using a conventional method, minimum quantity of cutting fluid (MQCF), and pulverization. By the minimum quantity method was also applied a lubricant of vegetable oil (MQL). Thereafter, a cutting fluid jet under high pressure (3.0 MPa) was singly applied in the following regions: chip-tool interface; top surface of the chip; and tool-workpiece contact. Two other methods were used: an interflow between conventional application and chip-tool interface jet and, finally, three jets simultaneously applied. In order to carry out these tests, it was necessary to set up a high pressure system using a piston pump for generating a cutting fluid jet, a Venturi for fluid application (MQCF and MQL), and a nozzle for cutting fluid pulverization. The output variables analyzed included tool life, surface roughness, cutting tool temperature, cutting force, chip form, chip compression rate and machined specimen microstructure. It can be observed that the tool life increases and the cutting force decreases with the application of cutting fluid jet, mainly when it is directed to the chip-tool interface. Excluding the methods involving jet fluid, the conventional method seems to be more efficient than other methods of low pressure. © (2013) Trans Tech Publications, Switzerland.

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In this work, new tools in atmospheric pollutant sampling and analysis were applied in order to go deeper in source apportionment study. The project was developed mainly by the study of atmospheric emission sources in a suburban area influenced by a municipal solid waste incinerator (MSWI), a medium-sized coastal tourist town and a motorway. Two main research lines were followed. For what concerns the first line, the potentiality of the use of PM samplers coupled with a wind select sensor was assessed. Results showed that they may be a valid support in source apportionment studies. However, meteorological and territorial conditions could strongly affect the results. Moreover, new markers were investigated, particularly focusing on the processes of biomass burning. OC revealed a good biomass combustion process indicator, as well as all determined organic compounds. Among metals, lead and aluminium are well related to the biomass combustion. Surprisingly PM was not enriched of potassium during bonfire event. The second research line consists on the application of Positive Matrix factorization (PMF), a new statistical tool in data analysis. This new technique was applied to datasets which refer to different time resolution data. PMF application to atmospheric deposition fluxes identified six main sources affecting the area. The incinerator’s relative contribution seemed to be negligible. PMF analysis was then applied to PM2.5 collected with samplers coupled with a wind select sensor. The higher number of determined environmental indicators allowed to obtain more detailed results on the sources affecting the area. Vehicular traffic revealed the source of greatest concern for the study area. Also in this case, incinerator’s relative contribution seemed to be negligible. Finally, the application of PMF analysis to hourly aerosol data demonstrated that the higher the temporal resolution of the data was, the more the source profiles were close to the real one.