504 research outputs found
Dynamic model of spherical perturbations in the Friedman universe. III. Automodel solutions
A class of exact spherically symmetric perturbations of retarding automodel
solutions linearized around Friedman background of Einstein equations for an
ideal fluid with an arbitrary barotrope value is obtained and investigated.Comment: 12 pages, 4 figures, 8 reference
An EWMA control chart for the multivariate coefficient of variation
This is the peer reviewed version of the following article: Giner-Bosch, V, Tran, KP, Castagliola, P, Khoo, MBC. An EWMA control chart for the multivariate coefficient of variation. Qual Reliab Engng Int. 2019; 35: 1515-1541, which has been published in final form at https://doi.org/10.1002/qre.2459. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving.[EN] Monitoring the multivariate coefficient of variation over time is a natural choice when the focus is on stabilising the relative variability of a multivariate process, as is the case in a significant number of real situations in engineering, health sciences, and finance, to name but a few areas. However, not many tools are available to practitioners with this aim. This paper introduces a new control chart to monitor the multivariate coefficient of variation through an exponentially weighted moving average (EWMA) scheme. Concrete methodologies to calculate the limits and evaluate the performance of the chart proposed and determine the optimal values of the chart's parameters are derived based on a theoretical study of the statistic being monitored. Computational experiments reveal that our proposal clearly outperforms existing alternatives, in terms of the average run length to detect an out-of-control state. A numerical example is included to show the efficiency of our chart when operating in practice.Generalitat Valenciana, Grant/Award Number: BEST/2017/033 and GV/2016/004; Ministerio de Economia y Competitividad, Grant/Award Number: MTM2013-45381-PGiner-Bosch, V.; Tran, KP.; Castagliola, P.; Khoo, MBC. (2019). An EWMA control chart for the multivariate coefficient of variation. Quality and Reliability Engineering International. 35(6):1515-1541. https://doi.org/10.1002/qre.2459S15151541356Kang, C. W., Lee, M. S., Seong, Y. J., & Hawkins, D. M. (2007). A Control Chart for the Coefficient of Variation. Journal of Quality Technology, 39(2), 151-158. doi:10.1080/00224065.2007.11917682Amdouni, A., Castagliola, P., Taleb, H., & Celano, G. (2015). Monitoring the coefficient of variation using a variable sample size control chart in short production runs. The International Journal of Advanced Manufacturing Technology, 81(1-4), 1-14. doi:10.1007/s00170-015-7084-4Amdouni, A., Castagliola, P., Taleb, H., & Celano, G. (2017). A variable sampling interval Shewhart control chart for monitoring the coefficient of variation in short production runs. International Journal of Production Research, 55(19), 5521-5536. doi:10.1080/00207543.2017.1285076Yeong, W. C., Khoo, M. B. C., Tham, L. K., Teoh, W. L., & Rahim, M. A. (2017). Monitoring the Coefficient of Variation Using a Variable Sampling Interval EWMA Chart. Journal of Quality Technology, 49(4), 380-401. doi:10.1080/00224065.2017.11918004Teoh, W. L., Khoo, M. B. C., Castagliola, P., Yeong, W. C., & Teh, S. Y. (2017). Run-sum control charts for monitoring the coefficient of variation. European Journal of Operational Research, 257(1), 144-158. doi:10.1016/j.ejor.2016.08.067Sharpe, W. F. (1994). The Sharpe Ratio. The Journal of Portfolio Management, 21(1), 49-58. doi:10.3905/jpm.1994.409501Van Valen, L. (1974). Multivariate structural statistics in natural history. Journal of Theoretical Biology, 45(1), 235-247. doi:10.1016/0022-5193(74)90053-8Albert, A., & Zhang, L. (2010). A novel definition of the multivariate coefficient of variation. Biometrical Journal, 52(5), 667-675. doi:10.1002/bimj.201000030Aerts, S., Haesbroeck, G., & Ruwet, C. (2015). Multivariate coefficients of variation: Comparison and influence functions. Journal of Multivariate Analysis, 142, 183-198. doi:10.1016/j.jmva.2015.08.006Bennett, B. M. (1977). On multivariate coefficients of variation. Statistische Hefte, 18(2), 123-128. doi:10.1007/bf02932744Underhill, L. G. (1990). The coefficient of variation biplot. Journal of Classification, 7(2), 241-256. doi:10.1007/bf01908718Boik, R. J., & Shirvani, A. (2009). Principal components on coefficient of variation matrices. Statistical Methodology, 6(1), 21-46. doi:10.1016/j.stamet.2008.02.006MacGregor, J. F., & Kourti, T. (1995). Statistical process control of multivariate processes. Control Engineering Practice, 3(3), 403-414. doi:10.1016/0967-0661(95)00014-lBersimis, S., Psarakis, S., & Panaretos, J. (2007). Multivariate statistical process control charts: an overview. Quality and Reliability Engineering International, 23(5), 517-543. doi:10.1002/qre.829Yeong, W. C., Khoo, M. B. C., Teoh, W. L., & Castagliola, P. (2015). A Control Chart for the Multivariate Coefficient of Variation. Quality and Reliability Engineering International, 32(3), 1213-1225. doi:10.1002/qre.1828Lim, A. J. X., Khoo, M. B. C., Teoh, W. L., & Haq, A. (2017). Run sum chart for monitoring multivariate coefficient of variation. Computers & Industrial Engineering, 109, 84-95. doi:10.1016/j.cie.2017.04.023Roberts, S. W. (1966). A Comparison of Some Control Chart Procedures. Technometrics, 8(3), 411-430. doi:10.1080/00401706.1966.10490374Roberts, S. W. (1959). Control Chart Tests Based on Geometric Moving Averages. Technometrics, 1(3), 239-250. doi:10.1080/00401706.1959.10489860Lucas, J. M., & Saccucci, M. S. (1990). Exponentially Weighted Moving Average Control Schemes: Properties and Enhancements. Technometrics, 32(1), 1-12. doi:10.1080/00401706.1990.10484583Wijsman, R. A. (1957). Random Orthogonal Transformations and their use in Some Classical Distribution Problems in Multivariate Analysis. The Annals of Mathematical Statistics, 28(2), 415-423. doi:10.1214/aoms/1177706969The general sampling distribution of the multiple correlation coefficient. (1928). Proceedings of the Royal Society of London. Series A, Containing Papers of a Mathematical and Physical Character, 121(788), 654-673. doi:10.1098/rspa.1928.0224Paolella, M. S. (2007). Intermediate Probability. doi:10.1002/9780470035061WalckC.Handbook on statistical distributions for experimentalists. Tech. Rep. SUFPFY/96‐01 Stockholm Particle Physics Group Fysikum University of Stockholm;2007. http://inspirehep.net/record/1389910BROOK, D., & EVANS, D. A. (1972). An approach to the probability distribution of cusum run length. Biometrika, 59(3), 539-549. doi:10.1093/biomet/59.3.539Castagliola, P., Celano, G., & Psarakis, S. (2011). Monitoring the Coefficient of Variation Using EWMA Charts. Journal of Quality Technology, 43(3), 249-265. doi:10.1080/00224065.2011.11917861Vining, G. (2009). Technical Advice: Phase I and Phase II Control Charts. Quality Engineering, 21(4), 478-479. doi:10.1080/08982110903185736Scilab Enterprises: Scilab: Free and open source software for numerical computation Version 6.0.0.http://www.scilab.org;2017.Nelder, J. A., & Mead, R. (1965). A Simplex Method for Function Minimization. The Computer Journal, 7(4), 308-313. doi:10.1093/comjnl/7.4.308PAGE, E. S. (1954). CONTINUOUS INSPECTION SCHEMES. Biometrika, 41(1-2), 100-115. doi:10.1093/biomet/41.1-2.100Über die hypergeometrische Reihe . (1836). Journal für die reine und angewandte Mathematik (Crelles Journal), 1836(15), 39-83. doi:10.1515/crll.1836.15.3
Chimeric 14-3-3 proteins for unraveling interactions with intrinsically disordered partners
In eukaryotes, several "hub" proteins integrate signals from different interacting partners that bind through intrinsically disordered regions. The 14-3-3 protein hub, which plays wide-ranging roles in cellular processes, has been linked to numerous human disorders and is a promising target for therapeutic intervention. Partner proteins usually bind via insertion of a phosphopeptide into an amphipathic groove of 14-3-3. Structural plasticity in the groove generates promiscuity allowing accommodation of hundreds of different partners. So far, accurate structural information has been derived for only a few 14-3-3 complexes with phosphopeptide-containing proteins and a variety of complexes with short synthetic peptides. To further advance structural studies, here we propose a novel approach based on fusing 14-3-3 proteins with the target partner peptide sequences. Such chimeric proteins are easy to design, express, purify and crystallize. Peptide attachment to the C terminus of 14-3-3 via an optimal linker allows its phosphorylation by protein kinase A during bacterial co-expression and subsequent binding at the amphipathic groove. Crystal structures of 14-3-3 chimeras with three different peptides provide detailed structural information on peptide-14-3-3 interactions. This simple but powerful approach, employing chimeric proteins, can reinvigorate studies of 14-3-3/phosphoprotein assemblies, including those with challenging low-affinity partners, and may facilitate the design of novel biosensors
Scaling in Complex Systems: Analytical Theory of Charged Pores
In this paper we find an analytical solution of the equilibrium ion
distribution for a toroidal model of a ionic channel, using the Perfect
Screening Theorem (PST). The ions are charged hard spheres, and are treated
using a variational Mean Spherical Approximation (VMSA) .
Understanding ion channels is still a very open problem, because of the many
exquisite tuning details of real life channels. It is clear that the electric
field plays a major role in the channel behaviour, and for that reason there
has been a lot of work on simple models that are able to provide workable
theories. Recently a number of interesting papers have appeared that discuss
models in which the effect of the geometry, excluded volume and non-linear
behaviour is considered.
We present here a 3D model of ionic channels which consists of a charged,
deformable torus with a circular or elliptical cross section, which can be flat
or vertical (close to a cylinder). Extensive comparisons to MC simulations were
performed.
The new solution opens new possibilities, such as studying flexible pores,
and water phase transformations inside the pores using an approach similar to
that used on flat crystal surfaces
Production of phi mesons at mid-rapidity in sqrt(s_NN) = 200 GeV Au+Au collisions at RHIC
We present the first results of meson production in the K^+K^- decay channel
from Au+Au collisions at sqrt(s_NN) = 200 GeV as measured at mid-rapidity by
the PHENIX detector at RHIC. Precision resonance centroid and width values are
extracted as a function of collision centrality. No significant variation from
the PDG accepted values is observed. The transverse mass spectra are fitted
with a linear exponential function for which the derived inverse slope
parameter is seen to be constant as a function of centrality. These data are
also fitted by a hydrodynamic model with the result that the freeze-out
temperature and the expansion velocity values are consistent with the values
previously derived from fitting single hadron inclusive data. As a function of
transverse momentum the collisions scaled peripheral.to.central yield ratio RCP
for the is comparable to that of pions rather than that of protons. This result
lends support to theoretical models which distinguish between baryons and
mesons instead of particle mass for explaining the anomalous proton yield.Comment: 326 authors, 24 pages text, 23 figures, 6 tables, RevTeX 4. To be
submitted to Physical Review C as a regular article. Plain text data tables
for the points plotted in figures for this and previous PHENIX publications
are (or will be) publicly available at http://www.phenix.bnl.gov/papers.htm
The one dimensional Kondo lattice model at partial band filling
The Kondo lattice model introduced in 1977 describes a lattice of localized
magnetic moments interacting with a sea of conduction electrons. It is one of
the most important canonical models in the study of a class of rare earth
compounds, called heavy fermion systems, and as such has been studied
intensively by a wide variety of techniques for more than a quarter of a
century. This review focuses on the one dimensional case at partial band
filling, in which the number of conduction electrons is less than the number of
localized moments. The theoretical understanding, based on the bosonized
solution, of the conventional Kondo lattice model is presented in great detail.
This review divides naturally into two parts, the first relating to the
description of the formalism, and the second to its application. After an
all-inclusive description of the bosonization technique, the bosonized form of
the Kondo lattice hamiltonian is constructed in detail. Next the
double-exchange ordering, Kondo singlet formation, the RKKY interaction and
spin polaron formation are described comprehensively. An in-depth analysis of
the phase diagram follows, with special emphasis on the destruction of the
ferromagnetic phase by spin-flip disorder scattering, and of recent numerical
results. The results are shown to hold for both antiferromagnetic and
ferromagnetic Kondo lattice. The general exposition is pedagogic in tone.Comment: Review, 258 pages, 19 figure
J/psi production from proton-proton collisions at sqrt(s) = 200 GeV
J/psi production has been measured in proton-proton collisions at sqrt(s)=
200 GeV over a wide rapidity and transverse momentum range by the PHENIX
experiment at RHIC. Distributions of the rapidity and transverse momentum,
along with measurements of the mean transverse momentum and total production
cross section are presented and compared to available theoretical calculations.
The total J/psi cross section is 3.99 +/- 0.61(stat) +/- 0.58(sys) +/-
0.40(abs) micro barns. The mean transverse momentum is 1.80 +/- 0.23(stat) +/-
0.16(sys) GeV/c.Comment: 326 authors, 6 pages text, 4 figures, 1 table, RevTeX 4. To be
submitted to PRL. Plain text data tables for the points plotted in figures
for this and previous PHENIX publications are (or will be) publicly available
at http://www.phenix.bnl.gov/papers.htm
Measurement of Single Electron Event Anisotropy in Au+Au Collisions at sqrt(s_NN) = 200 GeV
The transverse momentum dependence of the azimuthal anisotropy parameter v_2,
the second harmonic of the azimuthal distribution, for electrons at
mid-rapidity (|eta| < 0.35) has been measured with the PHENIX detector in Au+Au
collisions at sqrt(s_NN) = 200 GeV. The measurement was made with respect to
the reaction plane defined at high rapidities (|eta| = 3.1 -- 3.9). From the
result we have measured the v_2 of electrons from heavy flavor decay after
subtraction of the v_2 of electrons from other sources such as photon
conversions and Dalitz decay from light neutral mesons. We observe a non-zero
single electron v_2 with a 90% confidence level in the intermediate p_T region.Comment: 330 authors, 11 pages text, RevTeX4, 9 figures, 1 tables. Submitted
to Physical Review C. Plain text data tables for the points plotted in
figures for this and previous PHENIX publications are (or will be) publicly
available at http://www.phenix.bnl.gov/papers.htm
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