963 resultados para MN2 MOMENTS
Resumo:
Using the treatment of Smith et al. charge distributions in and consequently the dipole moments of some aliphatic nitro compounds and oximes have been evaluated. The mesomeric moment derived as a difference between the calculated and the observed values gives a clear picture as to how the positive (+M) and the negative (-M) mesomeric effects operate in such systems.
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Dipole moment measurements have been made in the case of a few aromatic hydrocarbon picrates, the values obtained being 2·18, 2·25, 2·97 (all in Debye units) for picrates of naphthalene, acenaphthene and phenanthrene respectively and the results discussed in terms of Mulliken's theory. Measurements have also been extended to include a few salt-like heterocyclic amine picrates.
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The formal charge distributions in and the dipole moments of some organophosphines and arsines have been calculated, and the dipole moments of (p-chlorophenyl)dichlorophosphine (2.28 D) and (p-bromophenyl)dichlorophosphine (2.04 D) have been determined in benzene at 35° C. The differences between the observed and the calculated moments are explained in terms of dπ---pπ back-bonding and hyperconjugative effects in alkylhaloarsines. The mesomeric effects operating in the aromatic systems are evaluated by comparing the moments with those for the corresponding aliphatic systems. In unsaturated compounds the differences are attributed to mesomeric effects involving the expansion of arsenic valence shell.
Resumo:
The formal charge distributions in and the dipole moments of some organophosphines and arsines have been calculated, and the dipole moments of (p-chlorophenyl)dichlorophosphine (2.28 D) and (p-bromophenyl)dichlorophosphine (2.04 D) have been determined in benzene at 35° C. The differences between the observed and the calculated moments are explained in terms of dπ---pπ back-bonding and hyperconjugative effects in alkylhaloarsines. The mesomeric effects operating in the aromatic systems are evaluated by comparing the moments with those for the corresponding aliphatic systems. In unsaturated compounds the differences are attributed to mesomeric effects involving the expansion of arsenic valence shell.
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One of the most fundamental and widely accepted ideas in finance is that investors are compensated through higher returns for taking on non-diversifiable risk. Hence the quantification, modeling and prediction of risk have been, and still are one of the most prolific research areas in financial economics. It was recognized early on that there are predictable patterns in the variance of speculative prices. Later research has shown that there may also be systematic variation in the skewness and kurtosis of financial returns. Lacking in the literature so far, is an out-of-sample forecast evaluation of the potential benefits of these new more complicated models with time-varying higher moments. Such an evaluation is the topic of this dissertation. Essay 1 investigates the forecast performance of the GARCH (1,1) model when estimated with 9 different error distributions on Standard and Poor’s 500 Index Future returns. By utilizing the theory of realized variance to construct an appropriate ex post measure of variance from intra-day data it is shown that allowing for a leptokurtic error distribution leads to significant improvements in variance forecasts compared to using the normal distribution. This result holds for daily, weekly as well as monthly forecast horizons. It is also found that allowing for skewness and time variation in the higher moments of the distribution does not further improve forecasts. In Essay 2, by using 20 years of daily Standard and Poor 500 index returns, it is found that density forecasts are much improved by allowing for constant excess kurtosis but not improved by allowing for skewness. By allowing the kurtosis and skewness to be time varying the density forecasts are not further improved but on the contrary made slightly worse. In Essay 3 a new model incorporating conditional variance, skewness and kurtosis based on the Normal Inverse Gaussian (NIG) distribution is proposed. The new model and two previously used NIG models are evaluated by their Value at Risk (VaR) forecasts on a long series of daily Standard and Poor’s 500 returns. The results show that only the new model produces satisfactory VaR forecasts for both 1% and 5% VaR Taken together the results of the thesis show that kurtosis appears not to exhibit predictable time variation, whereas there is found some predictability in the skewness. However, the dynamic properties of the skewness are not completely captured by any of the models.
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A better understanding of stock price changes is important in guiding many economic activities. Since prices often do not change without good reasons, searching for related explanatory variables has involved many enthusiasts. This book seeks answers from prices per se by relating price changes to their conditional moments. This is based on the belief that prices are the products of a complex psychological and economic process and their conditional moments derive ultimately from these psychological and economic shocks. Utilizing information about conditional moments hence makes it an attractive alternative to using other selective financial variables in explaining price changes. The first paper examines the relation between the conditional mean and the conditional variance using information about moments in three types of conditional distributions; it finds that the significance of the estimated mean and variance ratio can be affected by the assumed distributions and the time variations in skewness. The second paper decomposes the conditional industry volatility into a concurrent market component and an industry specific component; it finds that market volatility is on average responsible for a rather small share of total industry volatility — 6 to 9 percent in UK and 2 to 3 percent in Germany. The third paper looks at the heteroskedasticity in stock returns through an ARCH process supplemented with a set of conditioning information variables; it finds that the heteroskedasticity in stock returns allows for several forms of heteroskedasticity that include deterministic changes in variances due to seasonal factors, random adjustments in variances due to market and macro factors, and ARCH processes with past information. The fourth paper examines the role of higher moments — especially skewness and kurtosis — in determining the expected returns; it finds that total skewness and total kurtosis are more relevant non-beta risk measures and that they are costly to be diversified due either to the possible eliminations of their desirable parts or to the unsustainability of diversification strategies based on them.
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1H NMR spin-lattice relaxation time (T1) measurements have been carried out with various sugars, viz. methyl alpha-D-glucopyranoside (alpha-MeGluP), methyl beta-D-lucopyranoside (beta-MeGluP), methyl alpha--annopyranoside (alpha-MeManP), maltose (4-O-alpha-D-glucopyranosyl--glucose), nigerose (3-O-alpha-D-glucopyranosyl-D-glucose), p-nitrophenyl alpha-maltoside (PNP-alpha-maltoside) and p-nitrophenyl beta-maltoside (PNP-beta-maltoside) to determine the distances of sugar protons from Mn2+ in concanavalin A (Con A). With a rotational correlation time of 1.58 x 10(-10) s determined, distances were calculated using Solomon-Bloembergen equation. The data obtained indicated differences in disposition of different groups in the binding site of Con A. An average value of about 10 A was obtained for the distances of sugar protons from Mn2+ in Con A. In the case of mono and disaccharides, the non-reducing end sugar unit was found to be closer to Mn2+ than the reducing end one.
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We show that the characteristic Mn2+ d emission color from Mn2+-doped CdS nanocrystals can be tuned over as much as 40 nm, in contrast to what should be expected from such a nearly localized d-d transition. This is achieved surprisingly by a fine-tuning of the host particle diameter from 1.9 to 2.6 nm, thereby changing the overall emission color from red to yellow. Systematic experiments in conjunction with state-of-the-art ab initio calculations with full geometry optimization establish that Mn2+ ions residing at surface/subsurface regions have a distorted tetrahedral coordination resulting in a larger ligand field splitting. Consequently, these near-surface Mn2+ species exhibit a lower Mn2+ d emission energy, compared to those residing at the core of the nanocrystal with an undisturbed tetrahedral coordination. The origin of the tunability of the observed Mn2+ emission is the variation of emission contributions arising from Mn2+ doped at the core, subsurface, and surface of the host. Our findings provide a unique and easy method to identify the location of an emitting Mn2+ ion in the nanocrystal, which would be otherwise very difficult to decipher.
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Single crystals of calcium hydrazine carboxylate, monohydrate have been studied by ESR of Mn2+ doped in the calcium sites. X-band ESR indicated a large crystal field splitting necessitating experiments at Q band. The analysis shows two magnetically inequivalent (but chemically equivalent) sites with g(xx) = 2.0042+/-0.0038, g(yy) = 2.0076 +/-00029, g(zz) =2.0314+/-0.001, A(zz) = 0.0099+/-0.0002 cm(-1), A(xx) = 0.0099+/-0.0002 cm(-1), A(yy) = 0.0082+/-0.0002cm(-1), D = 3/2D(zz) = 0.0558+/-0.0006cm(-1), and E = 1/2(D-xx-D-yy) = 0.0127+/-0.0002 cm(-1).One of the principal components of the crystal field, (D-zz), is found to be along the Ca<->Ca direction in the structure and a second one, (D-xx), along the perpendicular to the plane of the triangle formed by three neighbouring calciums. The A tensor is found to have an orientation different from that of the g and D tensors reflecting the low symmetry of the Ca2+ sites.
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In this paper, we show a method of obtaining general and orthogonal moments, specifically Legendre and Zernicke moments, from the Radon Transform data of a two-dimensional function. The regular or geometric moments are first evaluated directly from the projection data and the orthogonal moments are derived from these regular moments.
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Genetic Algorithms are efficient and robust search methods that are being employed in a plethora of applications with extremely large search spaces. The directed search mechanism employed in Genetic Algorithms performs a simultaneous and balanced, exploration of new regions in the search space and exploitation of already discovered regions.This paper introduces the notion of fitness moments for analyzing the working of Genetic Algorithms (GAs). We show that the fitness moments in any generation may be predicted from those of the initial population. Since a knowledge of the fitness moments allows us to estimate the fitness distribution of strings, this approach provides for a method of characterizing the dynamics of GAs. In particular the average fitness and fitness variance of the population in any generation may be predicted. We introduce the technique of fitness-based disruption of solutions for improving the performance of GAs. Using fitness moments, we demonstrate the advantages of using fitness-based disruption. We also present experimental results comparing the performance of a standard GA and GAs (CDGA and AGA) that incorporate the principle of fitness-based disruption. The experimental evidence clearly demonstrates the power of fitness based disruption.
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This paper presents recursive algorithms for fast computation of Legendre and Zernike moments of a grey-level image intensity distribution. For a binary image, a contour integration method is developed for the evaluation of Legendre moments using only the boundary information. A method for recursive calculation of Zernike polynomial coefficients is also given. A square-to-circular image transformation scheme is introduced to minimize the computation involved in Zernike moment functions. The recursive formulae can also be used in inverse moment transforms to reconstruct the original image from moments. The mathematical framework of the algorithms is given in detail, and illustrated with binary and grey-level images.
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Probably the most informative description of the ground slate of a magnetic molecular species is provided by the spin density map. Such a map may be experimentally obtained from polarized neutron diffraction (PND) data or theoretically calculated using quantum chemical approaches. Density functional theory (DFT) methods have been proved to be well-adapted for this. Spin distributions in one-dimensional compounds may also be computed using the density matrix renormalization group (DMRG) formalism. These three approaches, PND, DFT, and DMRG, have been utilized to obtain new insights on the ground state of two antiferromagnetically coupled Mn2+Cu2+ compounds, namely [Mn(Me-6-[14]ane-N-4)Cu(oxpn)](CF3SO3)(2) and MnCu(pba)(H2O)(3) . 2H(2)O, with Me-6-[14]ane-N-4 = (+/-)-5,7,7,12,14,14-hexamethyl-1,4,8,11-tetraazacyclotetradecane, oxpn = N,N'-bis(3-aminopropyl)oxamido and pba = 1,3-propylenebis(oxamato). Three problems in particular have been investigated: the spin distribution in the mononuclear precursors [Cu(oxpn)] and [Cu(pba)](2-), the spin density maps in the two Mn2+Cu2+ compounds, and the evolution of the spin distributions on the Mn2+ and Cu2+ sites when passing from a pair to a one-dimensional ferrimagnet.