203,313 research outputs found
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M-estimator, and D-optimality model construction using orthogonal forward regression
This correspondence introduces a new orthogonal forward regression (OFR) model identification algorithm using D-optimality for model structure selection and is based on an M-estimators of parameter estimates. M-estimator is a classical robust parameter estimation technique to tackle bad data conditions such as outliers. Computationally, The M-estimator can be derived using an iterative reweighted least squares (IRLS) algorithm. D-optimality is a model structure robustness criterion in experimental design to tackle ill-conditioning in model Structure. The orthogonal forward regression (OFR), often based on the modified Gram-Schmidt procedure, is an efficient method incorporating structure selection and parameter estimation simultaneously. The basic idea of the proposed approach is to incorporate an IRLS inner loop into the modified Gram-Schmidt procedure. In this manner, the OFR algorithm for parsimonious model structure determination is extended to bad data conditions with improved performance via the derivation of parameter M-estimators with inherent robustness to outliers. Numerical examples are included to demonstrate the effectiveness of the proposed algorithm
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Robust neurofuzzy rule base knowledge extraction and estimation using subspace decomposition combined with regularization and D-optimality
A new robust neurofuzzy model construction algorithm has been introduced for the modeling of a priori unknown dynamical systems from observed finite data sets in the form of a set of fuzzy rules. Based on a Takagi-Sugeno (T-S) inference mechanism a one to one mapping between a fuzzy rule base and a model matrix feature subspace is established. This link enables rule based knowledge to be extracted from matrix subspace to enhance model transparency. In order to achieve maximized model robustness and sparsity, a new robust extended Gram-Schmidt (G-S) method has been introduced via two effective and complementary approaches of regularization and D-optimality experimental design. Model rule bases are decomposed into orthogonal subspaces, so as to enhance model transparency with the capability of interpreting the derived rule base energy level. A locally regularized orthogonal least squares algorithm, combined with a D-optimality used for subspace based rule selection, has been extended for fuzzy rule regularization and subspace based information extraction. By using a weighting for the D-optimality cost function, the entire model construction procedure becomes automatic. Numerical examples are included to demonstrate the effectiveness of the proposed new algorithm
1ST MEASUREMENT OF GAMMA(D(S)(+)-]MU+NU)/GAMMA(D(S)(+)-]PHI-PI+)
Complete Author List:
ACOSTA D, ATHANAS M, MASEK G, PAAR H, BEAN A, GRONBERG J, KUTSCHKE R, MENARY S, MORRISON RJ, NAKANISHI S, NELSON HN, NELSON TK, RICHMAN JD, RYD A, TAJIMA H, SCHMIDT D, SPERKA D, WITHERELL MS, PROCARIO M, YANG S, BALEST R, CHO K, DAOUDI M, FORD WT, JOHNSON DR, LINGEL K, LOHNER M, RANKIN P, SMITH JG, ALEXANDER JP, BEBEK C, BERKELMAN K, BESSON D, BROWDER TE, CASSEL DG, CHO HA, COFFMAN DM, DRELL PS, EHRLICH R, GALIK RS, GARCIASCIVERES M, GEISER B, GITTELMAN B, GRAY SW, HARTILL DL, HELTSLEY BK, JONES CD, JONES SL, KANDASWAMY J, KATAYAMA N, KIM PC, KREINICK DL, LUDWIG GS, MASUI J, MEVISSEN J, MISTRY NB, NG CR, NORDBERG E, OGG M, PATTERSON JR, PETERSON D, RILEY D, SALMAN S, SAPPER M, WORDEN H, WURTHWEIN F, AVERY P, FREYBERGER A, RODRIGUEZ J, STEPHENS R, YELTON J, CINABRO D, HENDERSON S, KINOSHITA K, LIU T, SAULNIER M, SHEN F, WILSON R, YAMAMOTO H, ONG B, SELEN M, SADOFF AJ, AMMAR R, BALL S, BARINGER P, COPPAGE D, COPTY N, DAVIS R, HANCOCK N, KELLY M, KWAK N, LAM H, KUBOTA Y, LATTERY M, NELSON JK, PATTON S, PERTICONE D, POLING R, SAVINOV V, SCHRENK S, WANG R, ALAM MS, KIM IJ, NEMATI B, ONEILL JJ, SEVERINI H, SUN CR, ZOELLER MM, CRAWFORD G, DAUBENMIER CM, FULTON R, FUJINO D, GAN KK, HONSCHEID K, KAGAN H, KASS R, LEE J, MALCHOW R, MORROW F, SKOVPEN Y, SUNG M, WHITE C, WHITMORE J, WILSON P, BUTLER F, FU X, KALBFLEISCH G, LAMBRECHT M, ROSS WR, SKUBIC P, SNOW J, WANG PL, WOOD M, BORTOLETTO D, BROWN DN, FAST J, MCILWAIN RL, MIAO T, MILLER DH, MODESITT M, SCHAFFNER SF, SHIBATA EI, SHIPSEY IPJ, WANG PN, BATTLE M, ERNST J, KROHA H, ROBERTS S, SPARKS K, THORNDIKE EH, WANG CH, DOMINICK J, SANGHERA S, SHELKOV V, SKWARNICKI T, STROYNOWSKI R, VOLOBOUEV I, ZADOROZHNY P, ARTUSO M, HE D, GOLDBERG M, HORWITZ N, KENNETT R, MONETI GC, MUHEIM F, MUKHIN Y, PLAYFER S, ROZEN Y, STONE S, THULASIDAS M, VASSEUR G, ZHU G, BARTELT J, CSORNA SE, EGYED Z, JAIN V, SHELDON P, AKERIB DS, BARISH B, CHADHA M, CHAN S, COWEN DF, EIGEN G, MILLER JS, OGRADY C, URHEIM J, WEINSTEIN A
Measurements of the absolute branching fractions for D-s(+) -> eta e(+)nu(e) and D-s(+) -> eta ' e(+)nu(e)
By analyzing 482 pb(-1) of e(+)e(-) collision data collected at root s = 4.009 GeV with the BESIII detector at the BEPCII collider, we measure the absolute branching fractions for the semileptonic decays D-s(+) -> eta e(+)nu(e) and D-s(+) -> eta ' e(+)nu(e) to be B(D-s(+) -> eta e(+)nu(e)) = (2.30 +/- 0.31 +/- 0.08)% and B(D-s(+) -> eta ' e(+)nu(e)) = (0.93 +/- 0.30 +/- 0.05)%, respectively, and their ratio B(D-s(+) -> eta ' e(+)nu(e)) / B(D-s(+) -> eta ' e(+)nu(e)) = 0.40 +/- 0.14 +/- 0.02, where the first uncertainties are statistical and the second ones are systematic. The results are in good agreement with previous measurements within uncertainties; they can be used to determine the eta-eta' mixing angle and improve upon the D-s(+) semileptonic branching ratio precision
Exclusive production of Ds+Ds-,D-s*D-+(s)-, and D-s*D-+(s)*(-) via e(+)e(-) annihilation with initial-state radiation
We perform a study of exclusive production of Ds+Ds-,D-s*(+),D-s(-), and D-s*D-+(s)*- final states in initial-state radiation events from e(+)e(-) annihilations at a center-of-mass energy near 10.58 GeV, to search for charmonium 1(--) states. The data sample corresponds to an integrated luminosity of 525 fb(-1) and was recorded by the BABAR experiment at the PEP-II storage ring. Ds+Ds-,D-s*(+),D-s(-) and ,D-s*(+),D-s*(-) mass spectra show evidence of the known psi resonances. Limits are extracted for the branching ratios of the decays X(4260) -> D-s(()*()+) D-s(()*()-
First observations of B̅[0 over s]→D[superscript +]D[superscript -], D[+ over s]D[superscript -] and D[superscript 0]D̅[superscript 0] decays
First observations and measurements of the branching fractions of the B̅[0 over s]→D[superscript +]D[superscript -], B̅[0 over s]→D[+ over s]D[superscript -] and B̅[0 over s]→D[superscript 0]D̅[superscript 0] decays are presented using 1.0 fb[superscript -1] of data collected by the LHCb experiment. These branching fractions are normalized to those of B̅[superscript 0]→D[superscript +]D[superscript -], B[superscript 0]→D[superscript -]D[+ over s] and B[superscript -]→D[superscript 0]D[- over s], respectively. An excess of events consistent with the decay B̅[superscript 0]→D[superscript 0]D̅[superscript 0] is also seen, and its branching fraction is measured relative to that of B[superscript -]→D[superscript 0]D[- over s]. Improved measurements of the branching fractions B(B̅[0 over s]→D[+ over s]D[- over s]) and B(B[superscript -]→D[superscript 0]D[- over s]) are reported, each relative to B(B[superscript 0]→D[superscript -]D[+ over s]). The ratios of branching fractions are B(B̅[0 over s]→D[superscript +]D[superscript -])/B(B̅[superscript 0]→D[superscript +]D[superscript -])=1.08±0.20±0.10, B(B̅[0 over s]→D[+ over s]D[superscript -])/B(B[superscript 0]→D[superscript -]D[+ over s])=0.050±0.008±0.004, B(B̅[0 over s]→D[superscript 0]D̅[superscript 0])/B(B[superscript -]→D[superscript 0]D[- over s])=0.019±0.003±0.003, B(B̅[superscript 0]→D[superscript 0]D̅[superscript 0])/B(B[superscript -]→D[superscript 0]D[- over s])<0.0024 at 90% CL, B(B̅[0 over s]→D[+ over s]D[- over s])/B(B[superscript 0]→D[superscript -]D[+ over s])=0.56±0.03±0.04, B(B[superscript -]→D[superscript 0]D[- over s])/B(B[superscript 0]→D[superscript -]D[+ over s])=1.22±0.02±0.07, where the uncertainties are statistical and systematic, respectively.National Science Foundation (U.S.
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Sparse multioutput radial basis function network construction using combined locally regularised orthogonal least square and D-optimality experimental design
A construction algorithm for multioutput radial basis function (RBF) network modelling is introduced by combining a locally regularised orthogonal least squares (LROLS) model selection with a D-optimality experimental design. The proposed algorithm aims to achieve maximised model robustness and sparsity via two effective and complementary approaches. The LROLS method alone is capable of producing a very parsimonious RBF network model with excellent generalisation performance. The D-optimality design criterion enhances the model efficiency and robustness. A further advantage of the combined approach is that the user only needs to specify a weighting for the D-optimality cost in the combined RBF model selecting criterion and the entire model construction procedure becomes automatic. The value of this weighting does not influence the model selection procedure critically and it can be chosen with ease from a wide range of values
D. S. Ruegg. Le traité du tathāgatagarbha de Buston Rin chen grub.
Bareau André. D. S. Ruegg. Le traité du tathāgatagarbha de Buston Rin chen grub.. In: Revue de l'histoire des religions, tome 187, n°1, 1975. pp. 101-102
INNOVATIVE PILLAR[6]ARENE-BASED STATIONARY PHASES FOR HIGH-RESOLUTION GAS CHROMATOGRAPHIC ANALYSES
In this work, the synthesis, fabrication, and characterization of new stationary phases based on pillar[6]arene derivative modified by long alkyl chains (P6A-C10) for high-resolution gas chromatographic (GC) analyses are reported. Pillar[n]arenes are a new class of macrocyclic hosts that can accommodate specific guests due to their highly symmetrical and rigid pillar architectures with π-electron rich cavities. Quantum chemistry calculations have been performed, showing a difference in non-covalent interactions with the P6A-C10 pillar framework, which leads to specific selectivity for aromatic compounds. The GC columns prepared with these innovative stationary phases exhibited a medium polarity, and good reproducibility for run-to-run, day-to-day, and column-to-column analyses [1], demonstrating great potential as new stationary phases in separation science. Furthermore, peculiar advantages are achieved if compared with the commercial HP-5, HP-35, DB-17, and PEG-20M columns, showing unmatched resolving capabilities toward chloroaniline, bromoaniline, iodoaniline, toluidine, and xylene isomers [2].
References:
1. Sun, T., Chen, R., Huang, Q., Ba, M., Cai, Z., Hu, S., Liu, X., Nardiello, D., & Quinto, M., ACS Appl. Mater. Interfaces 14 (2022) 56132−56142.
2. Sun, T., Chen, R., Huang, Q., Ba, M., Cai, Z., Chen, H., Qi, Y., Chen, H., Liu, X., Nardiello, D., & Quinto, M., Anal. Chim. Acta 1251 (2023) 340979
Precise measurement of the branching fractions for B-s(0) -> D-s(()*()+) D-s(()*()-) and first measurement of the D-s*(+) D-s*(-) polarization using e(+)e(-) collisions
We have made a precise measurement of the absolute branching fractions of B-s(0) -> D-s(()*()+) D-s(()*()-) decays using 121.4 fb(-1) of data recorded by the Belle experiment running at the Upsilon(5S) resonance. The results are B(B-s(0) -> D-s(+) D-s(-)) = 0.58(-0.09)(+0.11) +/- 0.13)%, B(B-s(0) -> D-s*(+/-) D-s(-/+)) = (1.76(-0.22)(+0.23) +/- 0.40)%, and B(B-s(0) -> D-s*(+) D-s*(-)) = (1.98(-0.31-0.50)(+0.33+0.52))%; the sum is B(B-s(0) -> D-s(()*()+) D-s(()*()-)) = (4.32(-0.39-1.03)(+0.42+1.04))%. Assuming B-s(0) -> D-s(()*()+) D-s(()*()-) saturates decays to CP-even final states, the branching fraction constrains the ratio Delta Gamma(s)/cos phi(12), where Delta Gamma(s) is the difference in widths between the two B-s-(B) over bar (s) mass eigenstates, and phi(12) is the CP-violating phase in B-s-(B) over bar (s) mixing. We also measure for the first time the longitudinal polarization fraction of B-s(0) -> D-s*(+) D-s*(-); the result is 0.06(-0.17)(+0.18) +/- 0.03. DOI: 10.1103/PhysRevD.87.031101LPH
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