900 resultados para Difference method for differences
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The space and time discretization inherent to all FDTD schemesintroduce non-physical dispersion errors, i.e. deviations ofthe speed of sound from the theoretical value predicted bythe governing Euler differential equations. A generalmethodologyfor computing this dispersion error via straightforwardnumerical simulations of the FDTD schemes is presented.The method is shown to provide remarkable accuraciesof the order of 1/1000 in a wide variety of twodimensionalfinite difference schemes.
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Over the last 10 years, diffusion-weighted imaging (DWI) has become an important tool to investigate white matter (WM) anomalies in schizophrenia. Despite technological improvement and the exponential use of this technique, discrepancies remain and little is known about optimal parameters to apply for diffusion weighting during image acquisition. Specifically, high b-value diffusion-weighted imaging known to be more sensitive to slow diffusion is not widely used, even though subtle myelin alterations as thought to happen in schizophrenia are likely to affect slow-diffusing protons. Schizophrenia patients and healthy controls were scanned with a high b-value (4000s/mm(2)) protocol. Apparent diffusion coefficient (ADC) measures turned out to be very sensitive in detecting differences between schizophrenia patients and healthy volunteers even in a relatively small sample. We speculate that this is related to the sensitivity of high b-value imaging to the slow-diffusing compartment believed to reflect mainly the intra-axonal and myelin bound water pool. We also compared these results to a low b-value imaging experiment performed on the same population in the same scanning session. Even though the acquisition protocols are not strictly comparable, we noticed important differences in sensitivities in the favor of high b-value imaging, warranting further exploration.
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Human biomonitoring is a widely used method in the assessment of occupational exposure to chemical substances and recommended biological limits are published periodically for interpretation and decision-making. However, it is increasingly recognized that a large variability is associated with biological monitoring, making interpretation less efficient than assumed. In order to improve the applicability of biological monitoring, specific factors responsible for this variability should be identified and their contribution quantified. Among these factors, age and sex are easily identifiable, and present knowledge about pharmaceutical chemicals suggests that they play an important role on the toxicokinetics of occupational chemical agents, and therefore on the biological monitoring results.The aim of the present research project was to assess the influence of age and sex on biological indicators corresponding to organic solvents. This has been done experimentally and by toxicokinetic computer simulation. Another purpose was to explore the effect of selected CYP2E1 polymorphisms on the toxicokinetic profile.Age differences were identified by numerical simulations using a general toxicokinetic model from a previous study which was applied to 14 chemicals, representing 21 specific biological entities, with, among others, toluene, phenol, lead and mercury. These models were runn with the modified parameters, indicating in some cases important differences due to age. The expected changes are mostly of the order of 10-20 %, but differences up to 50 % were observed in some cases. These differences appear to depend on the chemical and on the biological entity considered.Sex differences were quantified by controlled human exposures, which were carried out in a 12 m3 exposure chamber for three organic solvents separately: methyl ethyl ketone, 1-methoxy-2-propanol and 1,1,1-trichloroethane. The human volunteer groups were composed 12 of ten young men and fifteen young women, the latter subdivided into those with and without hormonal contraceptive. They were exposed during six hours at rest and at half of the threshold limit value. The kinetics of the parent compounds (organic volatiles) and their metabolite(s) were followed in blood, urine and expired air over time. Analyses of the solvent and their metabolites were performed by using headspace gas chromatography, CYP2E1 genotypes by using PCR-based RFLP methods. Experimental data were used to calibrate the toxicokinetic models developed for the three solvents. The results obtained for the different biomarkers of exposure mainly showed an effect on the urinary levels of several biomarkers among women due to the use of hormonal contraceptive, with an increase of about 50 % in the metabolism rate. The results also showed a difference due to the genotype CYP2E1*6, when exposed to methyl ethyl ketone, with a tendency to increase CYP2E1 activity when volunteers were carriers of the mutant allele. Simulations showed that it is possible to use simple toxicokinetic tools in order to predict internal exposure when exposed to organic solvents. Our study suggests that not only physiological differences but also exogenous sex hormones could influence CYP2E1 enzyme activity. The variability among the urinary biological indicators levels gives evidence of an interindividual susceptibility, an aspect that should have its place in the approaches for setting limits of occupational exposure.
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Background Analysing the observed differences for incidence or mortality of a particular disease between two different situations (such as time points, geographical areas, gender or other social characteristics) can be useful both for scientific or administrative purposes. From an epidemiological and public health point of view, it is of great interest to assess the effect of demographic factors in these observed differences in order to elucidate the effect of the risk of developing a disease or dying from it. The method proposed by Bashir and Estève, which splits the observed variation into three components: risk, population structure and population size is a common choice at practice. Results A web-based application, called RiskDiff has been implemented (available at http://rht.iconcologia.net/riskdiff.htm webcite), to perform this kind of statistical analyses, providing text and graphical summaries. Code from the implemented functions in R is also provided. An application to cancer mortality data from Catalonia is used for illustration. Conclusions Combining epidemiological with demographical factors is crucial for analysing incidence or mortality from a disease, especially if the population pyramids show substantial differences. The tool implemented may serve to promote and divulgate the use of this method to give advice for epidemiologic interpretation and decision making in public health.
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Abstract: Fifty-five bursa of Fabricius (BF) were evaluated by optical microscopy for three different avian histopathologists (H1, H3 and H4) to determine the degree of lymphoid depletion. One histologist evaluated the same slides at two different times (H1 and H2) with four-months interval between the observations. The same BFs were evaluated using the system of Digital Lymphocyte Depletion Evaluation (ADDL), being performed by three differents operators of the system, not histopathologists. The results showed was a significant difference between the histopathologists and between the scores established by the same expert (H1 and H2). However, there were not significant differences between the scores with the ADDL system, obtained using ADDL. The results make clear the fragility of the subjective lymphocyte depletion score classification by the traditional histologic method, while the ADDL system proves to be more appropriated for the assessment of the lymphoid loss in the BF.
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Pressure-driven and temperature-driven transitions of two thermoresponsive polymers, poly(N-isopropylacrylamide) (pNIPAM) and poly(N-vinylisobutyramide) (pNVIBA)), in both a soluble linear polymer form and a cross-linked hydro-gel form, were examined by a dynamic light-scattering method and direct microscopic observation, respectively. Their behavior was compared with that of protein systems. Changes in some characteristic parameters in the time-intensity correlation functions of dynamic light-scattering measurement of aqueous solutions of pNIPAM at various pressures and temperatures showed no essential differences during temperature and pressure scanning and, as a whole, the motions of polymers in aqueous solutions were similar in two types of transitions until chain shrinkage occurred. The gels (cross-linked polymer gels) prepared from the thermoresponsive polymers also showed similar volume transitions responding to the pressure and temperature increase. In temperature transitions, however, gels showed drastic volume shrinkage with loss of transparency, while pressure-induced transition showed a slow recovery of transparency while keeping the size, after first transient drastic volume shrinkage with loss of transparency. At a temperature slightly higher than the transition under atmospheric temperature, so-called reentry of the volume change and recovery of the transparency were observed during the pressure-increasing process, which implies much smaller aggregation or non-aggregated collapsed polymer chains in the gel at higher pressures, indicating a certain mechanistic difference of the dehydration processes induced by temperature and pressure.
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Recent Ontario legislation by the Ministry of Education has targeted a goal of 50 percent as the minimum objective for representation by women in positions of responsibility by the year 2000. As a result,those few women currently in the field of Educational Administration have become a focus for researchers. The intent of this research is to contribute to the current knowledge and understanding of women principals in the leadership role. In-depth interviews with four experienced female principals were conducted centering on their perceptions and experiences on a wide range of issues that included: gender characteristics and impact on role, perceived differences as a result of gender characteristics, decision making, curriculum leadership, communication, the perception of others, and the advantages and disadvantages of being a woman in the role. Narrative profiles were constructed for each participant and analyzed. A description for each woman emerged by an analysis of common patterns and themes in the participants' narratives. Results revealed that the participants were able to identify and to describe particular gender traits that they perceived had impact on their role. Moreover the participants regarded their gender characteristics as facilitating and enhancing the performance of their role. Common patterns for all the participants emerged from the data that conveyed a strong feminine imagery of mother and espoused the idea of school as home, and staff and students as family. Leadership ii styles demonstrated an emphasis on collaborative decision making, open communication, and apparent difficulty and ambiguity arising from the role of Curriculum leader. The results of this study also indicate that personal metaphors ascribed and embedded in the narratives are significant in conceptualizing and interpreting the administrative role.
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This study was undertaken to investigate any textual differences and similarities within essays written with a word processing program and an e-mail editor by non-native writers. It arose from many contradictions and a paucity of empirical research within the field of second language learning and electronic technology. To further explore these contradictory observations, 3 classes of intermediate level ESL (English as a Second Language) students v^ote 6 essays, alternating between a word processing program and an e-mail editor. Prior to the data collection, students read brief texts and responded to questions that focused upon three formal topics: immigration, economics, and multiculturalism. Data were examined for (a) the differences in the frequency counts of 12 cohesive devices, (b) sentence complexity, which focused upon the occurrences of simple and complex sentences, (c) the number of words within the writings, (d) the method of contextualization preferred by writers, and (e) any variations in the final grades of the students' texts that resulted from holistic rating. Results of analysis indicated that there were no statistically significant differences in the frequency counts of the linguistic features. Sentence complexity did not vary within the off-line and on-line essays. The average number of words found within the off-line essays was approximately 20% greater than within on-line essays. Contextualization methods were not different within word-processed or e-mailed essays. Finally, there was no difference in the quality of the texts when holistically rated.
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Organic fertilizers based on seaweed extract potentially have beneficial effects on many crop plants. Herewe investigate the impact of organic fertilizer on Rosmarinus officinalis measured by both yield and oilquality. Plants grown in a temperature-controlled greenhouse with a natural photoperiod and a controlledirrigation system were treated with seaweed fertilizer and an inorganic fertilizer of matching mineralcomposition but with no organic content. Treatments were either by spraying on to the foliage or wateringdirect to the compost. The essential oil was extracted by hydro-distillation with a Clevenger apparatusand analysed by gas-chromatography mass-spectrometry (GC–MS) and NMR. The chemical composi-tions of the plants were compared, and qualitative differences were found between fertilizer treatmentsand application methods. Thus sprayed seaweed fertilizer showed a significantly higher percentage of�-pinene, �-phellandrene, �-terpinene (monoterpenes) and 3-methylenecycloheptene than other treat-ments. Italicene, �-bisabolol (sesquiterpenes), �-thujene, and E-isocitral (monoterpenes) occurred insignificantly higher percentages for plants watered with the seaweed extract. Each was significantly dif-ferent to the inorganic fertilizer and to controls. The seaweed treatments caused a significant increasein oil amount and leaf area as compared with both inorganic treatments and the control regardless ofapplication method.
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P>This study aimed to verify the effect of modified section method and laser-welding on the accuracy of fit of ill-fitting commercially pure titanium (cp Ti) and Ni-Cr alloy one-piece cast frameworks. Two sets of similar implant-supported frameworks were constructed. Both groups of six 3-unit implant-supported fixed partial dentures were cast as one-piece [I: Ni-Cr (control) and II: cp Ti] and evaluated for passive fitting in an optical microscope with both screws tightened and with only one screw tightened. All frameworks were then sectioned in the diagonal axis at the pontic region (III: Ni-Cr and IV: cp Ti). Sectioned frameworks were positioned in the matrix (10-Ncm torque) and laser-welded. Passive fitting was evaluated for the second time. Data were submitted to anova and Tukey-Kramer honestly significant difference tests (P < 0 center dot 05). With both screws tightened, one-piece cp Ti group II showed significantly higher misfit values (27 center dot 57 +/- 5 center dot 06 mu m) than other groups (I: 11 center dot 19 +/- 2 center dot 54 mu m, III: 12 center dot 88 +/- 2 center dot 93 mu m, IV: 13 center dot 77 +/- 1 center dot 51 mu m) (P < 0 center dot 05). In the single-screw-tightened test, with readings on the opposite side to the tightened side, Ni-Cr cast as one-piece (I: 58 center dot 66 +/- 14 center dot 30 mu m) was significantly different from cp Ti group after diagonal section (IV: 27 center dot 51 +/- 8 center dot 28 mu m) (P < 0 center dot 05). On the tightened side, no significant differences were found between groups (P > 0 center dot 05). Results showed that diagonally sectioning ill-fitting cp Ti frameworks lowers misfit levels of prosthetic implant-supported frameworks and also improves passivity levels of the same frameworks when compared to one-piece cast structures.
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Differences-in-Differences (DID) is one of the most widely used identification strategies in applied economics. However, how to draw inferences in DID models when there are few treated groups remains an open question. We show that the usual inference methods used in DID models might not perform well when there are few treated groups and errors are heteroskedastic. In particular, we show that when there is variation in the number of observations per group, inference methods designed to work when there are few treated groups tend to (under-) over-reject the null hypothesis when the treated groups are (large) small relative to the control groups. This happens because larger groups tend to have lower variance, generating heteroskedasticity in the group x time aggregate DID model. We provide evidence from Monte Carlo simulations and from placebo DID regressions with the American Community Survey (ACS) and the Current Population Survey (CPS) datasets to show that this problem is relevant even in datasets with large numbers of observations per group. We then derive an alternative inference method that provides accurate hypothesis testing in situations where there are few treated groups (or even just one) and many control groups in the presence of heteroskedasticity. Our method assumes that we can model the heteroskedasticity of a linear combination of the errors. We show that this assumption can be satisfied without imposing strong assumptions on the errors in common DID applications. With many pre-treatment periods, we show that this assumption can be relaxed. Instead, we provide an alternative inference method that relies on strict stationarity and ergodicity of the time series. Finally, we consider two recent alternatives to DID when there are many pre-treatment periods. We extend our inference methods to linear factor models when there are few treated groups. We also derive conditions under which a permutation test for the synthetic control estimator proposed by Abadie et al. (2010) is robust to heteroskedasticity and propose a modification on the test statistic that provided a better heteroskedasticity correction in our simulations.
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Differences-in-Differences (DID) is one of the most widely used identification strategies in applied economics. However, how to draw inferences in DID models when there are few treated groups remains an open question. We show that the usual inference methods used in DID models might not perform well when there are few treated groups and errors are heteroskedastic. In particular, we show that when there is variation in the number of observations per group, inference methods designed to work when there are few treated groups tend to (under-) over-reject the null hypothesis when the treated groups are (large) small relative to the control groups. This happens because larger groups tend to have lower variance, generating heteroskedasticity in the group x time aggregate DID model. We provide evidence from Monte Carlo simulations and from placebo DID regressions with the American Community Survey (ACS) and the Current Population Survey (CPS) datasets to show that this problem is relevant even in datasets with large numbers of observations per group. We then derive an alternative inference method that provides accurate hypothesis testing in situations where there are few treated groups (or even just one) and many control groups in the presence of heteroskedasticity. Our method assumes that we know how the heteroskedasticity is generated, which is the case when it is generated by variation in the number of observations per group. With many pre-treatment periods, we show that this assumption can be relaxed. Instead, we provide an alternative application of our method that relies on assumptions about stationarity and convergence of the moments of the time series. Finally, we consider two recent alternatives to DID when there are many pre-treatment groups. We extend our inference method to linear factor models when there are few treated groups. We also propose a permutation test for the synthetic control estimator that provided a better heteroskedasticity correction in our simulations than the test suggested by Abadie et al. (2010).
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The zircon mineral is widely studied in geochronology. In the case of the fission track method (FTM), the age is determined by the density of fission tracks at the zircon surface, which can be observed with an optical microscope after an appropriate chemical treatment (etching). The etching must be isotropic at the zircon grain surface to be used in the FTM, which leads those zircon grains whose etching is anisotropic to be discarded. The only reason for this discarding is the nonuniform morphology of the surface grain seen by optical microscopy, that is, no further physicochemical analysis is performed. In this work, combining micro-Raman and scanning electron microscopy (SEM) to study the etching anisotropy, it was shown that zircon grains that present at least one area at the surface where the density of fission track is uniform can be used in the FTM. The micro-Raman showed characteristic spectra of the standard zircon sample either from the areas where there are tracks or from where there are not. The only difference found was in the Raman bandwidths, which were broader for the areas with higher density of fission tracks. This suggests simply a decrease in the relative percentage of the crystalline/amorphous phases at these areas. The SEM/energy dispersive spectrometry (EDX) showed that there were no significant differences in the principal chemical composition at the areas with and without fission tracks. Copyright (c) 2008 John Wiley & Sons, Ltd.
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)