921 resultados para 2D correlation plot
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Rindfleisch (Daniel). Album amicorum (1590-1591)
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K-(BETS)2FeBr4 is a quasi-2D charge transfer organic metal with interesting electronic and magnetic properties. It undergoes a transition to an antiferromagnetic (AF) state at ambient pressure at the Neel temperature (T^^) = 2.5 K, as well as to a superconducting (SC) state at 1.1 K [1]. The temperature dependence of the electrical resistivity shows a small decrease at T;v indicating the resistivity drops as a result of the onset of the ordering of Fe'*''" spins. A sharp drop in the resistivity at 1.1 K is due to its superconducting transition. The temperature dependence of the susceptibility indicates an antiferromagnetic spin structure with the easy axis parallel to the a-axis. The specific heat at zero-field shows a large peak at about 2.4 K, which corresponds to the antiferromagnetic transition temperature (Tat) and no anomaly is observed around the superconducting transition temperature (1.1 K) demonstrating that the magnetically ordered state is not destroyed by the appearance of another phase transition (the superconducting transition) in the 7r-electron layers [1], [2]. This work presents an investigation of how the low frequency electromagnetic response is affected by the antiferromagnetic and superconducting states, as well as the onset of strong correlation. The location of the easy axis of three samples was determined and polarized thermal reflectance measurements of these «-(BETS)2FeBr4 samples oriented with their vertical axis along the a- and c axes were then carried out using a *He refrigerator cryostat and a Martin-Puplett type polarizing interferometer at various temperatures (T = 0.5 K, 1.4 K. 1.9 K, 2.8 K) above and below the superconducting state and/or antiferromagnetic state. Comparison of the SC state to the normal state along the o- and c-axes indicates a rising thermal reflectance at low frequencies (below 10 cm"' ) which may be a manifestation of the superconducting energy gap. A dip-Hke feature is detected at low frequencies (below 15 cm"') in the thermal reflectance plots which probe the antiferromagnetic state along the two axes, and may be due to the opening of a gap in the excitation spectrum as a result of the antiferromagnetism. In another set of experiments, thermal reflectance measurements carried out along the a- and c-axes at higher temperatures (10 K-80 K) show that the reflectivity decreases with increasing temperature to 60 K (the coherence temperature) above which it increases again. Comparison of the thermal reflectance plots along the a- and c-axes at higher temperatures reveals an anisotropy between these two axes. The Hagen-Rubens thermal reflectance plots corresponding to an average over the ac-plane were calculated using experimental hterature resistivity values. Comparison of the Hagen-Rubens plots with the experimental thermal reflectance along the a- and c-axes indicates that both exhibit the general trend of a decrease in thermal reflectance with increasing frequency, however the calculated Hagen-Rubens thermal reflectance at different temperatures is much lower than the experimental curves.
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The gypsy moth, Lymantria dispar, a major defoliator of broad leaf trees, was accidentally introduced into North America in 1869. Much interest has been generated regarding the potential of using natural pathogens for biological control of this insect. One of these pathogens, a highly specific fungus, Entomophaga maimaiga, was accredited with causing major epizootics in populations of gypsy moth across the north-eastern United States in 1989 and 1990 and is thought to be spreading northwards into Canada. This study examined gypsy moth population densities in the Niagara Region. The fungus, .E.. maimaiga, was artificially introduced into one site and the resulting mortality in host populations was noted over two years. The relationship between fungal mortality, host population density and occurrence of another pathogen, the nuclear polyhedrosis virus (NPV), was assessed. Gypsy moth population density was assessed by counting egg masses in 0.01 hectare (ha) study plots in six areas, namely Louth, Queenston, Niagara-on-the-Lake, Shorthills Provincial Park, Chippawa Creek and Willoughby Marsh. High variability in density was seen among sites. Willoughby Marsh and Chippawa Creek, the sites with the greatest variability, were selected for more intensive study. The pathogenicity of E. maimaiga was established in laboratory trials. Fungal-infected gypsy moth larvae were then released into experimental plots of varying host density in Willoughby Marsh in 1992. These larvae served as the inoculum to infect field larvae. Other larvae were injected with culture medium only and released into control plots also of varying host density. Later, field larvae were collected and assessed for the presence of .E.. maimaiga and NPV. A greater proportion of larvae were infected from experimental plots than from control plots indicating that the experimental augmentation had been successful. There was no relationship between host density and the proportion of infected larvae in either experimental or control plots. In 1992, 86% of larvae were positive for NPV. Presence and intensity of NPV infection was independent of fungal presence, plot type or interaction of these two factors. Sampling was carried out in the summer of 1993, the year after the introduction, to evaluate the persistence of the pathogen in the environment. Almost 50% of all larvae were infected with the fungus. There was no difference between control and experimental plots. Data collected from Willoughby Marsh indicated that there was no correlation between the proportion of larvae infected with the fungus and host population density in either experimental or control plots. About 10% of larvae collected from a nearby site, Chippawa Creek, were also positive for .E.. maimaiga suggesting that low levels of .E.. maimaiga probably occurred naturally in the area. In 1993, 9.6% of larvae were positive for NPV. Again, presence or absence of NPV infection was independent of fungal presence plot type or interaction of these two factors. In conclusion, gypsy moth population densities were highly variable between and within sites in the Niagara Region. The introduction of the pathogenic fungus, .E.. maimaiga, into Willoughby Marsh in 1992 was successful and the fungus was again evident in 1993. There was no evidence for existence of a relationship between fungal mortality and gypsy moth density or occurrence of NPV. The results from this study are discussed with respect to the use of .E.. maimaiga in gypsy moth management programs.
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The cr ystal structure of the compound 2-benzoylethylidene-3-(2,4- dibromophenyl)-2,3-dihydro-5-phenyl-l,3,4-thiadiazole* C23H16Br2NZOS (BRMEO) has been determined by using three dimensiona l x-ray diffraction data. The crys tal form is monoclinic, space group P21/c, a = 17.492(4), o -.t' 0 R 0 b =: 16.979(1), c = 14.962(1) A, "X. =o= 90 ',= 106.46(1) , z = 8, graphite-monochromatized Mo~ rad iation, Jl= 0.710J3~, D = 1.62g/cc and o D = 1.65g/cc. The data were col lected on ~ Nonius CAD-4 c diffractometer. The following atoms were made anisotropic: Br, S, N, 0, C7, and C14-C16 for each i ndependent molecu le ; the rest were left isotropic. For 3112 independent refl ec tions with F > 6G\F), R == 0.057. The compound has two independent molecules within the asymmetric unit. Two different conformers were observed which pack well together. /l The S---O interaction distances of 2.493(6) and 2 . 478(7) A were observed for molecules A and B respectively. These values are consistent with earlier findings for 2-benzoylmethylene-3-(2,4-dibromophenyl)- ~~ 2,3-dihydro-5-phenyl-l,3,4-thiadiazole C22H14Br2N20S (BRPHO) and 2-benzoylpropylidene-3-(2,4-dibromophenyl)-2,3-dihydroiii ,'r 5-phenyl-l,3,4-thiadiazole C24H18Br2N20S (BRPETO ) where S---O distances are l ess than the van der Waals (3.251\) but greater than those expected for () a single bond (1.50A). From the results and the literature it appears obvious that the energy/reaction coordinate pathway has a minimum between the end structures (the mono- and bicyclic compounds). * See reference (21) for nomenclature.
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Chapman Family burial plot, Forest Lawn, Glendale, California. "La Carita" statue.
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Cellular stress resistance has been shown to be highly correlated with longevity. However, the mechanisms conferring this stress resistance have yet to be identified. Maintenance of protein homeostasis is a critical component of cellular maintenance and stress resistance. Superior protein homeostasis capacities may thus underlie the greater stress resistance observed in longer-lived animals; however, little vertebrate data have been provided supporting this idea. I used two different experimental approaches to test the associations of protein homeostasis capacities with stress resistance and lifespan: 1) a comparison between a large set of vertebrate species with varying body masses and lifespans and 2) a comparison of long-lived Snell dwarf mice and their normal littermates. Protein homeostasis mechanisms including protein degradation activity, protein repair activity and molecular chaperone levels were examined. These measurements were performed in liver, heart and brain tissues, and isolated myoblasts. My results indicated that neither protein degradation nor protein repair were upregulated in association with enhanced stress resistance and longevity in an inter-species and intraspecies context. Furthermore, my results did show that there is a positive correlation between molecular chaperone levels and maximum lifespan (MLSP). However, there was no elevation of chaperone levels in the long-lived Snell dwarf mouse, indicating there are other mechanisms linked to their increased lifespan. Therefore, these results suggest that molecular chaperones are involved in increasing animal lifespan in an interspecies context.
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This research evaluated (a) the correlation between math anxiety, math attitudes, and achievement in math and (b) comparison among these variables in terms of gender among grade 9 students in a high school located in southern Ontario. Data were compiled from participant responses to the Attitudes Toward Math Inventory (ATMI) and the Math Anxiety Rating Scale for Adolescents (MARS-A), and achievement data were gathered from participants’ grade 9 academic math course marks and the EQAO Grade 9 Assessment of Mathematics. Nonparametric tests were conducted to determine whether there were relationships between the variables and to explore whether gender differences in anxiety, attitudes, and achievement existed for this sample. Results indicated that math anxiety was not related to math achievement but was a strong correlate of attitudes toward math. A strong positive relationship was found between math attitudes and achievement in math. Specifically, self-confidence in math, enjoyment of math, value of math, and motivation were all positive correlates of achievement in math. Also, results for gender comparisons were nonsignificant, indicating that gender differences in math anxiety, math attitudes, and math achievement scores were not prevalent in this group of grade 9 students. Therefore, attitudes toward math were considered to be a stronger predictor of performance than math anxiety or gender for this group.
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This paper proposes finite-sample procedures for testing the SURE specification in multi-equation regression models, i.e. whether the disturbances in different equations are contemporaneously uncorrelated or not. We apply the technique of Monte Carlo (MC) tests [Dwass (1957), Barnard (1963)] to obtain exact tests based on standard LR and LM zero correlation tests. We also suggest a MC quasi-LR (QLR) test based on feasible generalized least squares (FGLS). We show that the latter statistics are pivotal under the null, which provides the justification for applying MC tests. Furthermore, we extend the exact independence test proposed by Harvey and Phillips (1982) to the multi-equation framework. Specifically, we introduce several induced tests based on a set of simultaneous Harvey/Phillips-type tests and suggest a simulation-based solution to the associated combination problem. The properties of the proposed tests are studied in a Monte Carlo experiment which shows that standard asymptotic tests exhibit important size distortions, while MC tests achieve complete size control and display good power. Moreover, MC-QLR tests performed best in terms of power, a result of interest from the point of view of simulation-based tests. The power of the MC induced tests improves appreciably in comparison to standard Bonferroni tests and, in certain cases, outperforms the likelihood-based MC tests. The tests are applied to data used by Fischer (1993) to analyze the macroeconomic determinants of growth.
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Several Authors Have Discussed Recently the Limited Dependent Variable Regression Model with Serial Correlation Between Residuals. the Pseudo-Maximum Likelihood Estimators Obtained by Ignoring Serial Correlation Altogether, Have Been Shown to Be Consistent. We Present Alternative Pseudo-Maximum Likelihood Estimators Which Are Obtained by Ignoring Serial Correlation Only Selectively. Monte Carlo Experiments on a Model with First Order Serial Correlation Suggest That Our Alternative Estimators Have Substantially Lower Mean-Squared Errors in Medium Size and Small Samples, Especially When the Serial Correlation Coefficient Is High. the Same Experiments Also Suggest That the True Level of the Confidence Intervals Established with Our Estimators by Assuming Asymptotic Normality, Is Somewhat Lower Than the Intended Level. Although the Paper Focuses on Models with Only First Order Serial Correlation, the Generalization of the Proposed Approach to Serial Correlation of Higher Order Is Also Discussed Briefly.
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We consider the problem of testing whether the observations X1, ..., Xn of a time series are independent with unspecified (possibly nonidentical) distributions symmetric about a common known median. Various bounds on the distributions of serial correlation coefficients are proposed: exponential bounds, Eaton-type bounds, Chebyshev bounds and Berry-Esséen-Zolotarev bounds. The bounds are exact in finite samples, distribution-free and easy to compute. The performance of the bounds is evaluated and compared with traditional serial dependence tests in a simulation experiment. The procedures proposed are applied to U.S. data on interest rates (commercial paper rate).