Long-Term Validation and Variability of the Shortwave and Longwave Radiation Data of the GEWEX Surface Radiation Budget (SRB) Project

In this investigation, we make systematic Surface Radiation Budget-Baseline Surface Radiation Network (SRB-BSRN), Surface Radiation Data Centre (SRB-WRDC) and Surface Radiation Budget-Global Energy Balance Archive (SRB-GEBA) comparisons for both shortwave and longwave daily and monthly mean radiation fluxes at the Earth's surface. We first have an overview of all the comparable pairs of data in scatter or scatter density plots. Then we show the time series of the SRB data at grids in which there are ground sites where longterm records of data are available for comparison. An overall very good agreement between the SRB data and ground observations is found. To see the variability of the SRB data during the 21.5 years, we computed the global mean and its linear trend. No appreciable trend is detected at the 5% level. The empirical orthogonal functions (EOF) of the SRB deseasonalized shortwave downward flux are computed over the Pacific region, and the first EOF coefficient is found to be correlated with the ENSO Index at a high value of coefficient of 0.7083

Elimination Theory for Nonlinear Parameter Estimation

The work presented here exploits elimination theory (solving systems of polynomial equations in several variables) [1][2] to perform nonlinear parameter identification. In particular show how this technique can be used to estimate the rotor time constant and the stator resistance values of an induction machine. Although the example here is restricted to an induction machine, parameter estimation is applicable to many practical engineering problems. In [3], L. Ljung has outlined many of the challenges of nonlinear system identification as well as its particular importance for biological systems. In these types of problems, the model developed for analysis is typically a nonlinear state space model with unknown parameter values. The typical situation is that only a few of the state variables are measurable requiring that the system be reformulated as a nonlinear input-output model. In turn, resulting the nonlinear input-output model is almost always nonlinear in the parameters. Towards that end, differential algebra tools for analysis of nonlinear systems have been developed by Michel Fliess [4][5] and Diop [6]. Moreover, Ollivier [7] as well as Ljung and Glad [8] have developed the use of the characteristic set of an ideal as a tool for identification problems. The use of these differential algebraic methods for system identification have also been considered in [9], [10]. The focus of their research has been the determination of a priori identifiability of a given system model. However, as stated in [10], the development of an efficient algorithm using these differential algebraic techniques is still unknown. Here, in contrast, a method for which one can actually numerically obtain the numerical value of the parameters is presented. We also point out that [11] has also done work applying elimination theory to systems problems

Fetal Hemoglobin is Associated with Peripheral Oxygen Saturation in Sickle Cell Disease in Tanzania.

Fetal hemoglobin (HbF) and peripheral hemoglobin oxygen saturation (SpO2) both predict clinical severity in sickle cell disease (SCD), while reticulocytosis is associated with vasculopathy, but there are few data on mechanisms. HbF, SpO2 and routine clinical and laboratory measures were available in a Tanzanian cohort of 1175 SCD individuals aged≥5years and the association with SpO2 (as response variable transformed to a Poisson distribution) was assessed by negative binomial model with age and sex as covariates. Increase in HbF was associated with increased SpO2 (rate ratio, RR=1.19; 95% confidence intervals [CI] 1.04, 1.37 per natural log unit of HbF; p=0.0004). In univariable analysis, SpO2 was inversely associated with age, reticulocyte count, and log (total bilirubin) and directly with pulse, SBP, hemoglobin, and log(HbF). In multivariable regression log(HbF) (RR 1.191; 95%CI 1.04, 1.37; p=0.013), pulse (RR 1.01; 95%CI 1.00, 1.01; p=0.026), SBP (RR 1.008; 95%CI 1.00, 1.02; p=0.014), and hemoglobin (1.120; 95%CI 1.05, 1.19; p=0.001) were positively and independently associated with SpO2 while reticulocyte count (RR 0.985; 95%CI 0.97, 0.99; p=0.019) was independently inversely associated with SpO2. In SCD, improving SpO2, in part through cardiovascular compensation and associated with reduced reticulocytosis, may be a mechanism by which HbF reduces disease severity

Modified iterative versus Laplacian Landau gauge in compact U(1) theory

Compact U(1) theory in 4 dimensions is used to compare the modified iterative and the Laplacian fixing to lattice Landau gauge in a controlled setting, since in the Coulomb phase the lattice theory must reproduce the perturbative prediction. It turns out that on either side of the phase transition clear differences show up and in the Coulomb phase the ability to remove double Dirac sheets proves vital on a small lattice.Comment: 14 pages, 8 figures containing 23 graphs, v2: 2 figures removed, 2 references adde

Measurement of the (90,91,92,93,94,96)Zr(n,gamma) and (139)La(n,gamma) cross sections at n_TOF

Open AccessNeutron capture cross sections of Zr and La isotopes have important implications in the field of nuclear astrophysics as well as in the nuclear technology. In particular the Zr isotopes play a key role for the determination of the neutron density in the He burning zone of the Red Giant star, while the (139)La is important to monitor the s-process abundances from Ba up to Ph. Zr is also largely used as structural materials of traditional and advanced nuclear reactors. The nuclear resonance parameters and the cross section of (90,91,92,93,94,96)Zr and (139)La have been measured at the n_TOF facility at CERN. Based on these data the capture resonance strength and the Maxwellian-averaged cross section were calculated

New measurement of neutron capture resonances of 209Bi

The neutron capture cross section of Bi209 has been measured at the CERN n TOF facility by employing the pulse-height-weighting technique. Improvements over previous measurements are mainly because of an optimized detection system, which led to a practically negligible neutron sensitivity. Additional experimental sources of systematic error, such as the electronic threshold in the detectors, summing of gamma-rays, internal electron conversion, and the isomeric state in bismuth, have been taken into account. Gamma-ray absorption effects inside the sample have been corrected by employing a nonpolynomial weighting function. Because Bi209 is the last stable isotope in the reaction path of the stellar s-process, the Maxwellian averaged capture cross section is important for the recycling of the reaction flow by alpha-decays. In the relevant stellar range of thermal energies between kT=5 and 8 keV our new capture rate is about 16% higher than the presently accepted value used for nucleosynthesis calculations. At this low temperature an important part of the heavy Pb-Bi isotopes are supposed to be synthesized by the s-process in the He shells of low mass, thermally pulsing asymptotic giant branch stars. With the improved set of cross sections we obtain an s-process fraction of 19(3)% of the solar bismuth abundance, resulting in an r-process residual of 81(3)%. The present (n,gamma) cross-section measurement is also of relevance for the design of accelerator driven systems based on a liquid metal Pb/Bi spallation target.Comment: 10 pages, 5figures, recently published in Phys. Rev.

Measurements of high-energy neutron-induced fission of (nat)Pb and (209)Bi

This is an Open Access article distributed under the terms of the Creative Commons Attribution-Noncommercial License 3.0, which permits unrestricted use, distribution, and reproduction in any noncommercial medium, provided the original work is properly citedThe CERN Neutron Time-Of-Flight (n_TOF) facility is well suited to measure low cross sections as those of neutron-induced fission in subactinides. The cross section ratios of (nat)Pb and (209)Bi relative to (235)U and (238)U were measured using PPAC detectors and a fragment coincidence method that allows us to identify the fission events. The present experiment provides first results for neutron-induced fission up to 1 GeV. Good agreement is found with previous experimental data below 200 MeV. The comparison with proton-induced fission indicates that the limiting regime where neutron-induced and proton-induced fission reach equal cross sections is close to 1 GeV

Measurement of the neutron capture cross section of the s-only isotope 204Pb from 1 eV to 440 keV

The neutron capture cross section of 204Pb has been measured at the CERN n_TOF installation with high resolution in the energy range from 1 eV to 440 keV. An R-matrix analysis of the resolved resonance region, between 1 eV and 100 keV, was carried out using the SAMMY code. In the interval between 100 keV and 440 keV we report the average capture cross section. The background in the entire neutron energy range could be reliably determined from the measurement of a 208Pb sample. Other systematic effects in this measurement could be investigated and precisely corrected by means of detailed Monte Carlo simulations. We obtain a Maxwellian average capture cross section for 204Pb at kT=30 keV of 79(3) mb, in agreement with previous experiments. However our cross section at kT=5 keV is about 35% larger than the values reported so far. The implications of the new cross section for the s-process abundance contributions in the Pb/Bi region are discussed.Comment: 8 pages, 3 figures, article submitted to Phys. Rev.

Generative Embedding for Model-Based Classification of fMRI Data

Decoding models, such as those underlying multivariate classification algorithms, have been increasingly used to infer cognitive or clinical brain states from measures of brain activity obtained by functional magnetic resonance imaging (fMRI). The practicality of current classifiers, however, is restricted by two major challenges. First, due to the high data dimensionality and low sample size, algorithms struggle to separate informative from uninformative features, resulting in poor generalization performance. Second, popular discriminative methods such as support vector machines (SVMs) rarely afford mechanistic interpretability. In this paper, we address these issues by proposing a novel generative-embedding approach that incorporates neurobiologically interpretable generative models into discriminative classifiers. Our approach extends previous work on trial-by-trial classification for electrophysiological recordings to subject-by-subject classification for fMRI and offers two key advantages over conventional methods: it may provide more accurate predictions by exploiting discriminative information encoded in ‘hidden’ physiological quantities such as synaptic connection strengths; and it affords mechanistic interpretability of clinical classifications. Here, we introduce generative embedding for fMRI using a combination of dynamic causal models (DCMs) and SVMs. We propose a general procedure of DCM-based generative embedding for subject-wise classification, provide a concrete implementation, and suggest good-practice guidelines for unbiased application of generative embedding in the context of fMRI. We illustrate the utility of our approach by a clinical example in which we classify moderately aphasic patients and healthy controls using a DCM of thalamo-temporal regions during speech processing. Generative embedding achieves a near-perfect balanced classification accuracy of 98% and significantly outperforms conventional activation-based and correlation-based methods. This example demonstrates how disease states can be detected with very high accuracy and, at the same time, be interpreted mechanistically in terms of abnormalities in connectivity. We envisage that future applications of generative embedding may provide crucial advances in dissecting spectrum disorders into physiologically more well-defined subgroups

High-accuracy determination of the U 238 / U 235 fission cross section ratio up to ≈1 GeV at n-TOF at CERN

Published by the American Physical Society under the terms of the Creative Commons Attribution 3.0 License. Further distribution of this work must maintain attribution to the author(s) and the published article’s title, journal citation, and DOIThe U238 to U235 fission cross section ratio has been determined at n-TOF up to ≈1 GeV, with two different detection systems, in different geometrical configurations. A total of four datasets has been collected and compared. They are all consistent to each other within the relative systematic uncertainty of 3-4%. The data collected at n-TOF have been suitably combined to yield a unique fission cross section ratio as a function of neutron energy. The result confirms current evaluations up to 200 MeV. Good agreement is also observed with theoretical calculations based on the INCL++/Gemini++ combination up to the highest measured energy. The n-TOF results may help solve a long-standing discrepancy between the two most important experimental datasets available so far above 20 MeV, while extending the neutron energy range for the first time up to ≈1 GeV.Peer reviewedFinal Published versio