Accurate Fitting Procedure Research Articles

Direct Comb Vernier Spectroscopy for Fractional Isotopic Ratio Determinations.

Accurate isotopic composition analysis of the greenhouse-gasses emitted in the atmosphere is an important step to mitigate global climate warnings. Optical frequency comb–based spectroscopic techniques have shown ideal performance to accomplish the simultaneous monitoring of the different isotope substituted species of such gases. The capabilities of one such technique, namely, direct comb Vernier spectroscopy, to determine the fractional isotopic ratio composition are discussed. This technique combines interferometric filtering of the comb source in a Fabry–Perot that contains the sample gas, with a high resolution dispersion spectrometer to resolve the spectral content of each interacting frequency inside of the Fabry–Perot. Following this methodology, simultaneous spectra of ro-vibrational transitions of CO and CO molecules are recorded and analyzed with an accurate fitting procedure. Fractional isotopic ratio C/C at 3% of precision is measured for a sample of CO gas, showing the potentialities of the technique for all isotopic-related applications of this important pollutant.

Localising Temperature Risk

On the temperature derivative market, modeling temperature volatility is an important issue for pricing and hedging. In order to apply pricing tools of financial mathematics, one needs to isolate a Gaussian risk factor. A conventional model for temperature dynamics is a stochastic model with seasonality and inter temporal autocorrelation. Empirical work based on seasonality and autocorrelation correction reveals that the obtained residuals are heteroscedastic with a periodic pattern. The object of this research is to estimate this heteroscedastic function so that after scale normalisation a pure standardised Gaussian variable appears. Earlier work investigated this temperature risk in different locations and showed that neither parametric component functions nor a local linear smoother with constant smoothing parameter are flexible enough to generally describe the volatility process well. Therefore, we consider a local adaptive modeling approach to find at each time point, an optimal smoothing parameter to locally estimate the seasonality and volatility. Our approach provides a more flexible and accurate fitting procedure of localised temperature risk process by achieving excellent normal risk factors.

Localizing Temperature Risk

ABSTRACTOn the temperature derivative market, modeling temperature volatility is an important issue for pricing and hedging. To apply the pricing tools of financial mathematics, one needs to isolate a Gaussian risk factor. A conventional model for temperature dynamics is a stochastic model with seasonality and intertemporal autocorrelation. Empirical work based on seasonality and autocorrelation correction reveals that the obtained residuals are heteroscedastic with a periodic pattern. The object of this research is to estimate this heteroscedastic function so that, after scale normalization, a pure standardized Gaussian variable appears. Earlier works investigated temperature risk in different locations and showed that neither parametric component functions nor a local linear smoother with constant smoothing parameter are flexible enough to generally describe the variance process well. Therefore, we consider a local adaptive modeling approach to find, at each time point, an optimal smoothing parameter to locally estimate the seasonality and volatility. Our approach provides a more flexible and accurate fitting procedure for localized temperature risk by achieving nearly normal risk factors. We also employ our model to forecast the temperaturein different cities and compare it to a model developed in 2005 by Campbell and Diebold. Supplementary materials for this article are available online.

Volatility linkages between energy and agricultural commodity prices

We investigate price and volatility risk originating in linkages between energy and agricultural commodity prices in Germany and study their dynamics over time. We propose an econometric approach to quantify the volatility and correlation risk structure, which has a large impact for investment and hedging strategies of market participants as well as for policy makers. Volatilities and their short and long run linkages are analyzed using an asymmetric dynamic conditional correlation GARCH model as well as a multivariate multiplicative volatility model. Our approach provides a flexible and accurate fitting procedure for volatility and correlation risk. We find that in the long run prices move together and preserve an equilibrium, while correlations are mostly positive with persistent market shocks. Our results reveal that concerns about biodiesel being the cause of high and volatile agricultural commodity prices are rather unjustified.

On the dielectric relaxation of biological cell suspensions: The effect of the membrane electrical conductivity

Due to the mismatch of the electrical parameters (the permittivity ϵ' and the electrical conductivity σ) of the membrane of a biological cell with the ones of the cytosol and the extracellular medium, biological cell suspensions are the site, under the influence of an external electric field, of large dielectric relaxations in the radiowave frequency range. However, a point still remains controversial, i.e., whether or not the value of membrane conductivity σ(s) might be extracted from the de-convolution of the dielectric spectra or otherwise if it would be more reasonable to assign to the membrane conductivity a value equal to zero. This point is not to be considered with superficiality since it concerns an a priori choice which ultimately influences the values of the electrical parameters deduced from this technique. As far as this point is concerned, the opinion of the researchers in this field diverges. We believe that, at least within certain limits, the membrane conductivity can be deduced from the shape of the relaxation spectra. We substantiate this thesis with two different examples concerning the first a suspension of human normal erythrocyte cells and the second a suspension of human lymphocyte cells. In both cases, by means of an accurate fitting procedure based on the Levenberg-Marquardt method for complex functions, we can evaluate the membrane conductivity σ(s) with its associated uncertainty. The knowledge of the membrane electrical conductivity will favor the investigation of different ion transport mechanisms across the cell membrane.

Genetic algorithm for shift-uncertainty correction in 1-D NMR-based metabolite identifications and quantifications

The analysis of metabolic processes is becoming increasingly important to our understanding of complex biological systems and disease states. Nuclear magnetic resonance spectroscopy (NMR) is a particularly relevant technology in this respect, since the NMR signals provide a quantitative measure of the metabolite concentrations. However, due to the complexity of the spectra typical of biological samples, the demands of clinical and high-throughput analysis will only be fully met by a system capable of reliable, automatic processing of the spectra. An initial step in this direction has been taken by Targeted Profiling (TP), employing a set of known and predicted metabolite signatures fitted against the signal. However, an accurate fitting procedure for (1)H NMR data is complicated by shift uncertainties in the peak systems caused by measurement imperfections. These uncertainties have a large impact on the accuracy of identification and quantification and currently require compensation by very time consuming manual interactions. Here, we present an approach, termed Extended Targeted Profiling (ETP), that estimates shift uncertainties based on a genetic algorithm (GA) combined with a least squares optimization (LSQO). The estimated shifts are used to correct the known metabolite signatures leading to significantly improved identification and quantification. In this way, use of the automated system significantly reduces the effort normally associated with manual processing and paves the way for reliable, high-throughput analysis of complex NMR spectra. The results indicate that using simultaneous shift uncertainty correction and least squares fitting significantly improves the identification and quantification results for (1)H NMR data in comparison to the standard targeted profiling approach and compares favorably with the results obtained by manual expert analysis. Preservation of the functional structure of the NMR spectra makes this approach more realistic than simple binning strategies.

XXZ-like phase in the F-AF anisotropic Heisenberg chain

By means of the Density Matrix Renormalization Group technique, we have studied the region where XXZ-like behavior is most likely to emerge within the phase diagram of the F-AF anisotropic extended (J-J’) Heisenberg chain. We have analyzed, in great detail, the equal-time two-spin correlation functions, both in- and out-of- plane, as functions of the distance (and momentum). Then, we have extracted, through an accurate fitting procedure, the exponents of the asymptotic power-law decay of the spatial correlations. We have used the exact solution of XXZ model (J’ = 0) to benchmark our results, which clearly show the expected agreement. A critical value of J’ has been found where the relevant power-law decay exponent is independent of the in-plane nearest-neighbor coupling.

In-plane electrodynamics of the superconductivity inBi2Sr2CaCu2O8+δ: Energy scales and spectral weight distribution

The in-plane infrared and visible $(3\phantom{\rule{0.3em}{0ex}}\mathrm{meV}--3\phantom{\rule{0.3em}{0ex}}\mathrm{eV})$ reflectivity of ${\mathrm{Bi}}_{2}{\mathrm{Sr}}_{2}\mathrm{Ca}{\mathrm{Cu}}_{2}{\mathrm{O}}_{8+\ensuremath{\delta}}$ (Bi-2212) thin films is measured between $300\phantom{\rule{0.3em}{0ex}}\mathrm{K}$ and $10\phantom{\rule{0.3em}{0ex}}\mathrm{K}$ for different doping levels with unprecedented accuracy. The optical conductivity is derived through an accurate fitting procedure. We study the transfer of spectral weight from finite energy into the superfluid as the system becomes superconducting. In the overdoped regime, the superfluid develops at the expense of states lying below $60\phantom{\rule{0.3em}{0ex}}\mathrm{meV}$, which is a conventional energy of the order of a few times the superconducting gap. In the underdoped regime, spectral weight is removed from up to $2\phantom{\rule{0.3em}{0ex}}\mathrm{eV}$, far beyond any conventional scale. The intraband spectral weight change between the normal and superconducting state, if analyzed in terms of a change of kinetic energy, is $\ensuremath{\sim}1\phantom{\rule{0.3em}{0ex}}\mathrm{meV}$. Compared to the condensation energy, this figure addresses the issue of a kinetic-energy driven mechanism.

Physical Parameters of Southern B- and Be-Type Stars

In this paper we present new results on stellar fundamental parameters for early B and Be field stars observed in the southern hemisphere: effective temperature, superficial gravity, and projected stellar rotation velocity. The estimation of their projected rotation velocities is made by two successive methods. We first obtain an initial value based on Fourier transforms of the He I λ4471 line for 34 B and Be field stars with magnitudes in the range 0.5 ≤ mv ≤ 10, followed by a more accurate fitting procedure of observed lines with non-LTE model line profiles. This procedure yields stellar rotation velocity estimates that are in agreement with those of the literature. We derive also Teff and log g values by fitting equivalent widths and profiles of NLTE model spectra to the observed ones. Finally, we give estimates of stellar ages, masses, and bolometric luminosities derived from interpolations in the evolutionary tracks calculated by Schaller.

Monitoring of Cell Surface Movement at the Erythrocyte’s Edge By Scanning Phase Contrast.Microscopy

We explored the ability of a novel method of nano-scale movement detection to analyze the effects of chemical crosslinking and thiol reduction on the fluctuations of the human erythrocyte membrane. The method employs line images of light intensity distribution across the red blood cell, obtained by laser scanning phase contrast microscope. The essential feature of these images is a noiseless region corresponding to edge scene. This enables- one to carry out very accurate fitting procedure between the theoretical intensity distribution and the experimental one. One of the free parameters of fitting is the edge position. Measuring line scan intensity distributions with a certain sampling rate and defining the edge positions in consequent moments of time, yields the time-dependent displacement of cell's edge with up to nanometer scale precision.The significant feature of the suggested procedure is that it implicitly takes into account the halo effect.

Model for the above-threshold characteristics and threshold voltage in polycrystalline silicon transistors

A new theory of polycrystalline silicon thin-film transistors is proposed, based on a continuous trap state density. Three different regimes are predicted: subthreshold, transitional, and crystallinelike. Two characteristic voltages are identified: the threshold voltage, corresponding to the condition of equal trapped and free charge concentration at the oxide/semiconductor interface and the on-voltage, corresponding to the condition of equal trapped and free charge in the whole space-charge region. In the case of an exponential distribution of gap states, approximated analytical expressions can be deduced and a simple accurate fitting procedure is presented. A very good agreement with the experiment is obtained, confirming the importance of taking into account the detailed energy dependence of the trap distribution.

Extrapolated equation of state for rare gases at high temperatures and densities

An equation of state for argon, krypton and xenon has been established to obtain high temperature and high density p- V- T data. The equation is based on a perturbated hard sphere model using a Lennard-Jones (12-7) potential. Second and higher order terms in the calculation of the compressibility factor have been obtained by an accurate fitting procedure of the experimental data. p- V isotherms have been extrapolated up to densities near to the close packing, in the temperature range above 300 K. The results are compared with the Rowlinson equation and with empirically extrapolated tables.