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Modification of conventional peak shapes to accurately represent spectral asymmetry: High-Resolution X-ray photoelectron spectra of [C 4 C 1 Pyrr][NTf 2 ] and [C 8 C 1 Im][NTf 2 ] ionic liquids
X-ray photoelectron spectroscopy (XPS) is one of the most widely used techniques for surface characterization. Analysis of XPS data is challenging and requires the analyst to fit the data with synthetic line shapes to reach physically meaningful interpretations. Experimental spectral envelopes, however, are complex and display asymmetric features that are often ignored or attributed to additional chemical components. The high-resolution XPS spectra of [C 4 C 1 Pyrr][NTf 2 ] and [C 8 C 1 Im][NTf 2 ] all exhibit a degree of asymmetry which is systematically observed at the higher binding energy side of photoemission envelopes. Here, we present the development of a refined fitting procedure for XPS spectra of these ionic liquid-based systems which include (a) Shirley background offset necessary to account for the insulator-like region and (b) spectral asymmetry in C 1s and N 1s regions. Further, Shirley and trapezoid components are applied to compensate for inelastic scattering taking place during electron transitions as high as 7.8 eV above the start of the fitting region in C 1s high-resolution spectrum. To demonstrate the fitness of this model, we present an analysis of a 2:1 mixture of [C 4 C 1 Pyrr][NTf 2 ]: [C 8 C 1 Im][NTf 2 ].
Identification of crystal plasticity model parameters by multi-objective optimization integrating microstructural evolution and mechanical data
Crystal plasticity models evolve a polycrystalline yield surface using meso-scale descriptions of deformation mechanisms. The activation of deformation mechanisms is governed by crystallography and a set of model parameters, which are typically calibrated through the fitting of mechanical data such as stress–strain curves and elastic lattice strains. Microstructural data such as phase fractions and texture evolution are used for verifying crystal plasticity parameters. In this study, we use a multi-objective genetic algorithm to identify hardening parameters from flow stress curves with an option to incorporate texture into the optimization approach. Robust, generalized objective functions are developed and used to identify sets of parameters pertaining to dislocation density-based hardening laws in visco-plastic and elasto-plastic self-consistent (VPSC and EPSC) homogenization models. First, the parameters are identified for pure Nb directly from texture using an objective function based on generalized spherical harmonics. Since texture evolution is driven by the relative contribution of active slip systems, the parameters governing the evolution of slip resistance ratios can be recovered from fitting discrete textures at a series of strains. Next, a comprehensive set of load reversal data for dual phase (DP) 780 steel is used to fit a hardening law and a back-stress law in EPSC. Finally, parameters pertaining to a complex hardening law for the evolution of slip and twinning in pure α-Ti are identified. Remarkably, using texture as an objective in combination with stress–strain objectives constrains the model of Ti to fully reproduce not only stress–strain and texture evolution but also hierarchical twinning measurements as a function of initial grain size and texture. Furthermore, given an appropriate model fit to representative experimental texture evolution, underlying twin volume fractions contributing to texture evolution can be predicted.
Tight-binding study of beryllium
In this work, we have applied the Naval Research Laboratory Tight-binding (NRL-TB) Method to the hcp alkaline-earth metal Beryllium. This approach consists of fitting to energy band and total energy data generated by the Linearized Augmented Plane Wave (LAPW) for the fcc, bcc, sc, and hcp structures as a function of volume. First, we found that using the Generalized Gradient Approximation (GGA) for the input data secures a better agreement to experimental volumes than the LDA. Second, we found that including small volumes to the fit is needed to get TB parameters that are transferable enough to successfully predict the energies of structures that were not fitted, and to perform molecular dynamics (MD) simulations. The non-orthogonal Hamiltonian obtained, is successful in correctly predicting the hcp lattice as the ground state of Be and finding eight other structures, that were not fitted to LAPW, positioned at higher energies. In addition, the NRL-TB produces accurate energy bands, densities of states, elastic constants, the Bain path and several quantities derived from MD simulations.
Joint estimation of biogeochemical model parameters from multiple experiments: A bayesian approach applied to mercury methylation
Here, to characterize complex biogeochemical systems, results from multiple experiments, where each targets a specific subprocess, are commonly combined. The resulting datasets are interpreted through the calibration of biogeochemical models for process inference and predictions. Commonly used calibration approaches of fitting datasets from individual experiments to subprocess models one at a time is prone to missing information shared between datasets and incomplete uncertainty propagation. We propose a Bayesian joint-fitting scheme addressing the above-mentioned concerns by jointly fitting all the available datasets, thus calibrating the entire biogeochemical model in one go using Markov Chain Monte Carlo (MCMC). The identification of null spaces in the parameter distributions from MCMC guided the simplification of certain subprocess models. For example, fast kinetic sorption was replaced by equilibrium sorption, and Monod demethylation was replaced by first-order demethylation. Joint fitting of datasets resulted in complete uncertainty propagation with parameter estimates informed by all available data.
Experimental density and PC-SAFT modeling of Krytox (R) (perfluoropolyether) at pressures to 275 MPa and temperatures to 533 K
Density data from 298 to 533 K and to 275 MPa are reported for Krytox® GPL 102, a poly(perfluoropropyl ether) (PFPE) with a CF3-branched fluoropropylether repeat group. The Tait equation fit to each density isotherm have mean absolute percent deviations (MAPD) between 0.11 and 0.30% with standard deviations (SD) not exceeding 0.20%. The perturbed-chain statistical associating fluid theory (PC-SAFT) fit to the density data has an MAPD of 0.67% and an SD of 0.67%. Likewise the PC-SAFT fit to previously reported density data of Demnum®, a PFPE with an n-fluoropropylether repeat group, has an MAPD of 0.22% and a SD of 0.21% for Demnum® S-20 and an MAPD of 0.27% with a SD of 0.14% for Demnum® S-65. The trends exhibited by the PC-SAFT pure component parameters obtained from the fits of these three PFPEs are similar to those reported for linear and branched hydrocarbons with the same number of carbons.
Validation of Normal Tissue Complication Probability Predictions in Individual Patient: Late Rectal Toxicity
Purpose: To perform validation of risk predictions for late rectal toxicity (LRT) in prostate cancer obtained using a new approach to synthesize published normal tissue complication data. Methods and Materials: A published study survey was performed to identify the dose-response relationships for LRT derived from nonoverlapping patient populations. To avoid mixing models based on different symptoms, the emphasis was placed on rectal bleeding. The selected models were used to compute the risk estimates of grade 2+ and grade 3+ LRT for an independent validation cohort composed of 269 prostate cancer patients with known toxicity outcomes. Risk estimates from single studies were combined to produce consolidated risk estimates. An agreement between the actuarial toxicity incidence 3 years after radiation therapy completion and single-study or consolidated risk estimates was evaluated using the concordance correlation coefficient. Goodness of fit for the consolidated risk estimates was assessed using the Hosmer-Lemeshow test. Results: A total of 16 studies of grade 2+ and 5 studies of grade 3+ LRT met the inclusion criteria. The consolidated risk estimates of grade 2+ and 3+ LRT were constructed using 3 studies each. For grade 2+ LRT, the concordance correlation coefficient for the consolidated risk estimates was 0.537 compared with 0.431 for the best-fit single study. For grade 3+ LRT, the concordance correlation coefficient for the consolidated risk estimates was 0.477 compared with 0.448 for the best-fit single study. No evidence was found for a lack of fit for the consolidated risk estimates using the Hosmer-Lemeshow test (P=.531 and P=.397 for grade 2+ and 3+ LRT, respectively). Conclusions: In a large cohort of prostate cancer patients, selected sets of consolidated risk estimates were found to be more accurate predictors of LRT than risk estimates derived from any single study.
Incorporating Cancer Stem Cells in Radiation Therapy Treatment Response Modeling and the Implication in Glioblastoma Multiforme Treatment Resistance
Purpose: To perform a preliminary exploration with a simplistic mathematical cancer stem cell (CSC) interaction model to determine whether the tumor-intrinsic heterogeneity and dynamic equilibrium between CSCs and differentiated cancer cells (DCCs) can better explain radiation therapy treatment response with a dual-compartment linear-quadratic (DLQ) model. Methods and Materials: The radiosensitivity parameters of CSCs and DCCs for cancer cell lines including glioblastoma multiforme (GBM), non–small cell lung cancer, melanoma, osteosarcoma, and prostate, cervical, and breast cancer were determined by performing robust least-square fitting using the DLQ model on published clonogenic survival data. Fitting performance was compared with the single-compartment LQ (SLQ) and universal survival curve models. The fitting results were then used in an ordinary differential equation describing the kinetics of DCCs and CSCs in response to 2- to 14.3-Gy fractionated treatments. The total dose to achieve tumor control and the fraction size that achieved the least normal biological equivalent dose were calculated. Results: Smaller cell survival fitting errors were observed using DLQ, with the exception of melanoma, which had a low α/β = 0.16 in SLQ. Ordinary differential equation simulation indicated lower normal tissue biological equivalent dose to achieve the same tumor control with a hypofractionated approach for 4 cell lines for the DLQ model, in contrast to SLQ, which favored 2 Gy per fraction for all cells except melanoma. The DLQ model indicated greater tumor radioresistance than SLQ, but the radioresistance was overcome by hypofractionation, other than the GBM cells, which responded poorly to all fractionations. Conclusion: The distinct radiosensitivity and dynamics between CSCs and DCCs in radiation therapy response could perhaps be one possible explanation for the heterogeneous intertumor response to hypofractionation and in some cases superior outcome from stereotactic ablative radiation therapy. The DLQ model also predicted the remarkable GBM radioresistance, a result that is highly consistent with clinical observations. The radioresistance putatively stemmed from accelerated DCC regrowth that rapidly restored compartmental equilibrium between CSCs and DCCs.
Local and Global Function Model of the Liver
Purpose: To develop a local and global function model in the liver based on regional and organ function measurements to support individualized adaptive radiation therapy (RT). Methods and Materials: A local and global model for liver function was developed to include both functional volume and the effect of functional variation of subunits. Adopting the assumption of parallel architecture in the liver, the global function was composed of a sum of local function probabilities of subunits, varying between 0 and 1. The model was fit to 59 datasets of liver regional and organ function measures from 23 patients obtained before, during, and 1 month after RT. The local function probabilities of subunits were modeled by a sigmoid function in relating to MRI-derived portal venous perfusion values. The global function was fitted to a logarithm of an indocyanine green retention rate at 15 minutes (an overall liver function measure). Cross-validation was performed by leave-m-out tests. The model was further evaluated by fitting to the data divided according to whether the patients had hepatocellular carcinoma (HCC) or not. Results: The liver function model showed that (1) a perfusion value of 68.6 mL/(100 g · min) yielded a local function probability of 0.5; (2) the probability reached 0.9 at a perfusion value of 98 mL/(100 g · min); and (3) at a probability of 0.03 [corresponding perfusion of 38 mL/(100 g · min)] or lower, the contribution to global function was lost. Cross-validations showed that the model parameters were stable. The model fitted to the data from the patients with HCC indicated that the same amount of portal venous perfusion was translated into less local function probability than in the patients with non-HCC tumors. Conclusions: The developed liver function model could provide a means to better assess individual and regional dose-responses of hepatic functions, and provide guidance for individualized treatment planning of RT.
First analysis of the rotationally-resolved ν 2 and 2 ν 2 - ν 2 bands of sulfur dioxide, 33 S 16 O 2
A Fourier transform spectrum of sulfur dioxide 33S16O2 has been recorded in the 18.3 µm spectral region at a resolution of 0.002 cm-1 using a Bruker IFS 125HR spectrometer leading to the observation of the ν2 and 2ν2- ν2 vibrational bands of the 33S16O2 molecule. The corresponding upper state ro-vibrational levels were fit using Watson-type Hamiltonians. In this way it was possible to reproduce the upper state ro-vibrational levels to within the experimental uncertainty; i.e., ~0.20 x 10-3 cm-1. Very accurate rotational and centrifugal distortion constants were derived from the fit together with the following band centers: ν0 (ν2) =515.659089(50) cm-1, ν0 (2ν2) = 1030.697723(20) cm-1.
High-resolution infrared spectroscopy of the asymmetric NO stretch band of jet-cooled nitromethane and assignment of the lowest four torsional states
A high-throughput CW slit-jet apparatus coupled to a high-resolution FTIR was used to record the asymmetric NO stretch band of nitromethane. The b-type band, including torsionally excited states with m ≤ 3, has been assigned for Ka" ≤ 10, J" ≤ 20. The ground state combination differences derived from these assigned levels were fit with the RAM36 program to give an RMS deviation of 0.0006 cm-1. The band origin is 1583.0 (+/- 0.1) cm-1 and the torsional level spacing is nearly identical to that in the ground state. The upper state levels are split into multiplets by perturbations. A subset of the available upper state combination differences for m = 0, Ka' ≤ 7, J' ≤ 10 were fit with the same program, but with rather poorer precision (0.01 cm-1) than for the ground state.
Line shape parameters of air-broadened water vapor transitions in the nu(1) and nu(3) spectral region
A Bruker IFS-120HR Fourier transform spectrometer located at the Pacific Northwest Laboratory (PNNL) in Richland, Washington was used to record a series of spectra of pure H2O and air-broadened H2O in the regions of the ¦1 and ¦3 bands (3450-4000 cm-1) at different pressures, mperatures and volume mixing ratios of H2O in air. 18 high-resolution, high signal- to-noise (S/N) ratio absorption spectra were recorded at T = 268, 296 and 353 K using two temperature-controlled absorption cells with path lengths of 9.906(1) and 19.95(1) cm. The resolution of the spectra recorded with the 9.906 cm and 19.95 cm absorption cells was 0.006 and 0.008 cm-1, respectively. A multispectrum nonlinear least squares fitting technique was employed to fit all the eighteen spectra simultaneously to retrieve 313 accurate line positions, 315 intensities, 229 Lorentz air-broadened half- width and 213 air-shift coefficients and their temperature dependences (136 for air-broadened width and 128 for air-shift coefficients, respectively). Room temperature self-broadened half-width coefficients for 209 transitions and self-shift coefficients for 106 transitions were also measured. Line mixing coefficients were experimentally determined for isolated sets of 10 transition pairs for H2O-air and 8 transition pairs for H2O-H2O using the off-diagonal relaxation matrix element formalism, and 85 quadratic speed dependence parameters were measured. Modified Complex Robert-Bonamy (MCRB) calculations of self-, and air-broadened (from N2- and O2-broadening) half-width and air-shift coefficients, and temperature dependence exponents of air-broadened half-width coefficients are made. The measurements and calculations are compared with each other and with similar parameters reported in the literature.
Multispectrum analysis of air-broadened spectra in the ν 3 Q branch of 12CH4
In this paper, we report experimental measurements of spectral line shape parameters (air-broadened width, shift, and line mixing coefficients) for several transitions in the ν 3 Q branch of methane in the 3000–3023 cm -1 region. 13 high-resolution, room temperature laboratory spectra of pure methane and air-broadened methane recorded with two different Fourier transform spectrometers are fitted. 12 of these spectra were acquired at 0.01 cm -1 resolution with the McMath-Pierce FTS at the National Solar Observatory on Kitt Peak, and one higher-resolution (~0.0011 cm-1) low pressure methane spectrum was obtained with the Bruker IFS-120HR FTS at the Pacific Northwest National Laboratory, in Richland, Washington. All the spectra were obtained using high purity natural samples of CH 4 and lean mixtures of the same natural CH 4 in dry air. For the 12 spectra recorded at Kitt Peak, three different absorption cells (L= 5, 25 and 150 cm) were used while the methane spectrum at PNNL was obtained using a 19.95 cm long absorption cell. For the analysis, an interactive multispectrum nonlinear least squares fitting software was employed where all the 13 spectra were fitted simultaneously. An accurate and self-consistent set of line parameters were determined by constraining a few of those for severely blended transitions. Line mixing was measured for fourteen transition pairs for the CH 4 -air collision system. Lastly, a constant speed dependence parameter, consistent with measured speed dependence values obtained in other methane bands, was applied to all the transitions included in the fitted region. The present measurements are compared to values reported in the literature.
Non-model-based damage identification of plates using principal, mean and Gaussian curvature mode shapes
Mode shapes (MSs) have been extensively used to identify structural damage. This paper presents a new non-model-based method that uses principal, mean and Gaussian curvature MSs (CMSs) to identify damage in plates; the method is applicable and robust to MSs associated with low and high elastic modes on dense and coarse measurement grids. A multi-scale discrete differential-geometry scheme is proposed to calculate principal, mean and Gaussian CMSs associated with a MS of a plate, which can alleviate adverse effects of measurement noise on calculating the CMSs. Principal, mean and Gaussian CMSs of a damaged plate and those of an undamaged one are used to yield four curvature damage indices (CDIs), including Maximum-CDIs, Minimum-CDIs, Mean-CDIs and Gaussian-CDIs. Damage can be identified near regions with consistently higher values of the CDIs. It is shown that a MS of an undamaged plate can be well approximated using a polynomial with a properly determined order that fits a MS of a damaged one, provided that the undamaged plate has a smooth geometry and is made of material that has no stiffness and mass discontinuities. New fitting and convergence indices are proposed to quantify the level of approximation of a MS from a polynomial fit to that of a damaged plate and to determine the proper order of the polynomial fit, respectively. A MS of an aluminum plate with damage in the form of a machined thickness reduction area was measured to experimentally investigate the effectiveness of the proposed CDIs in damage identification; the damage on the plate was successfully identified.
A comparison of small-field tissue phantom ratio data generation methods for an Elekta Agility 6 MV photon beam
Tissue-phantom ratios (TPRs) are a common dosimetric quantity used to describe the change in dose with depth in tissue. These can be challenging and time consuming to measure. The conversion of percentage depth dose (PDD) data using standard formulae is widely employed as an alternative method in generating TPR. However, the applicability of these formulae for small fields has been questioned in the literature. Functional representation has also been proposed for small-field TPR production. This article compares measured TPR data for small 6 MV photon fields against that generated by conversion of PDD using standard formulae to assess the efficacy of the conversion data. By functionally fitting the measured TPR data for square fields greater than 4 cm in length, the TPR curves for smaller fields are generated and compared with measurements. TPRs and PDDs were measured in a water tank for a range of square field sizes. The PDDs were converted to TPRs using standard formulae. TPRs for fields of 4 × 4 cm{sup 2} and larger were used to create functional fits. The parameterization coefficients were used to construct extrapolated TPR curves for 1 × 1 cm{sup 2}, 2 × 2-cm{sup 2}, and 3 × 3-cm{sup 2} fields. The TPR data generated using standard formulae were in excellent agreement with direct TPR measurements. The TPR data for 1 × 1-cm{sup 2}, 2 × 2-cm{sup 2}, and 3 × 3-cm{sup 2} fields created by extrapolation of the larger field functional fits gave inaccurate initial results. The corresponding mean differences for the 3 fields were 4.0%, 2.0%, and 0.9%. Generation of TPR data using a standard PDD-conversion methodology has been shown to give good agreement with our directly measured data for small fields. However, extrapolation of TPR data using the functional fit to fields of 4 × 4 cm{sup 2} or larger resulted in generation of TPR curves that did not compare well with the measured data.
Analysis of calibration data for the uranium active neutron coincidence counting collar with attention to errors in the measured neutron coincidence rate
The declared linear density of 238 U and 235 U in fresh low enriched uranium light water reactor fuel assemblies can be verified for nuclear safeguards purposes using a neutron coincidence counter collar in passive and active mode, respectively. The active mode calibration of the Uranium Neutron Collar - Light water reactor fuel (UNCL) instrument is normally performed using a non-linear fitting technique. The fitting technique relates the measured neutron coincidence rate (the predictor) to the linear density of 235 U (the response) in order to estimate model parameters of the nonlinear Parte equation, which traditionally is used to model the calibration data. Alternatively, following a simple data transformation, the fitting can also be performed using standard linear fitting methods. This article compares performance of the nonlinear technique to the linear technique, using a range of possible error variance magnitudes in the measured neutron coincidence rate. We develop the required formalism and then apply the traditional (nonlinear) and alternative approaches (linear) to the same experimental and corresponding simulated representative datasets. Here, we find that, in this context, because of the magnitude of the errors in the predictor, it is preferable not to transform to a linear model, and it is preferable not to adjust for the errors in the predictor when inferring the model parameters.
Thermalization of nuclear matter in heavy-ion collisions at Fermi energies
We analyze the time evolution of the kinetic properties of nuclear matter produced in heavy-ion collisions at Fermi energies. The collision system is simulated using Constrained Molecular Dynamics (CoMD) transport calculations whose output is the isospin, position, and momentum of the nucleons. Focusing on central 35 A·MeV 40 Ca+ 40 Ca collisions we utilize this information to extract localized momentum distributions in volume elements of 8 fm 3 and time steps of 5 fm/$c$. We then parameterize the single-particle momentum distributions with thermally motivated fit functions in the local rest frame of each cell. While the transverse-momentum distributions are well reproduced by thermal ones, the longitudinal ones carry a marked imprint of the initial nuclear motion which we capture by introducing a centroid motion into our fit functions. In particular, we find that Fermi distributions yield significantly better fits than Boltzmann ones, a consequence of the Pauli blocking implemented in CoMD. From the fits we extract the time dependence of the thermodynamic and collective properties of the excited nuclear medium. We find that the transverse temperature gradually rises to about 6 MeV, which is accompanied by a dissipation of the initial centroid motion of the incoming nuclei which vanishes at about 100 fm/c after initial impact. In conclusion, we are therefore able to track the transition of beam energy into random kinetic energy for nucleons, suggesting a three-dimensional equilibration of energy in the late stages of the collision.
Dark Matter implications of DAMA/LIBRA-phase2 results
Recently, the DAMA/LIBRA collaboration released updated results from their search for the annual modulation signal from Dark Matter (DM) scattering in the detector. Besides approximately doubling the exposure of the DAMA/LIBRA data set, the updated photomultiplier tubes of the experiment allow a lower recoil energy threshold of 1 keV electron equivalent compared to the previous threshold of 2 keV electron equivalent. We study the compatibility of the observed modulation signal with DM scattering. Due to a conspiracy of multiple effects, the new data at low recoil energies is very powerful for testing the DM hypothesis. We find that canonical (isospin conserving) spin-independent DM-nucleon interactions are no longer a good fit to the observed modulation signal in the standard halo model. The canonical spin-independent case is disfavored by the new data, with best fit points of a DM mass of ~ 8 GeV , disfavored by 5.2 σ , or a mass of ~ 54 GeV , disfavored by 2.5 σ . Allowing for isospin violating spin independent interactions, we find a region with a good fit to the data with suppressed effective couplings to iodine for DM masses of ~ 10 GeV . We also consider spin-dependent DM-nucleon interactions, which yield good fits for similar DM masses of ~ 10 GeV or ~ 45 GeV .