Non-Newtonian effects in the peristaltic flow of a Maxwell fluid

We analyzed the effect of viscoelasticity on the dynamics of fluids in porous media by studying the flow of a Maxwell fluid in a circular tube, in which the flow is induced by a wave traveling on the tube wall. The present study investigates novelties brought about into the classic peristaltic mechanism by inclusion of non-Newtonian effects that are important, for example, for hydrocarbons. This problem has numerous applications in various branches of science, including stimulation of fluid flow in porous media under the effect of elastic waves. We have found that in the extreme non-Newtonian regime there is a possibility of a fluid flow in the direction {\it opposite} to the propagation of the wave traveling on the tube wall.Comment: to Appear in Phys. Rev. E., 01 September 2001 issu

Search for the Rare Decay KL --> pi0 ee

The KTeV/E799 experiment at Fermilab has searched for the rare kaon decay KL--> pi0ee. This mode is expected to have a significant CP violating component. The measurement of its branching ratio could support the Standard Model or could indicate the existence of new physics. This letter reports new results from the 1999-2000 data set. One event is observed with an expected background at 0.99 +/- 0.35 events. We set a limit on the branching ratio of 3.5 x 10^(-10) at the 90% confidence level. Combining the results with the dataset taken in 1997 yields the final KTeV result: BR(KL --> pi0 ee) < 2.8 x 10^(-10) at 90% CL.Comment: 4 pages, three figure

Relationship Between the Thermodynamic Parameters, Structure, and Anticorrosion Properties of Al-Zr-Ni-Fe-Y Alloys

The influence of the chemical composition on the crystallization process, amorphous phase formation, and the anticorrosion properties of Al-Zr-Ni-Fe-Y alloys are presented. To reduce the number of experiments, a thermodynamic approach was applied in which the entropy and Gibbs free energy of representative alloys were optimized. The low glass-forming ability of Al-Zr-Ni-Fe-Y alloy systems was related to the crystallization of the Al3Zr phase from the melt. The structural analysis showed that phases containing Ni and Fe, such as Al19Ni5Y3, Al10Fe2Y, and Al23Ni6Y4, played a key role in the formation of amorphous alloys. According to this, the simultaneous addition of Ni/Fe and Y is important to prevent the crystallization of Al-based alloys in the melt. The formation of an amorphous phase in Al80Zr5Ni5Fe5Y5 alloys and the complete amorphization of Al85Ni5Fe5Y5 alloys were responsible for the high corrosion resistance compared with fully crystalline alloys. Moreover, the addition of Y had a significant impact on the anticorrosion properties. The XPS results showed that the alloys tended to form a passive Al2O3 and Y2O3 layer on the surface

Measurements Of The Decay Kl → E+e-μ+μ-

Several 132 KL → e+e- μ+ μ- events were observed from the 1997 and 1999 runs of the KTeV experiments, with an estimated background of 0.8 events. In the first measurement of the parameter α using this decay mode, it was found that α=-1.59±0.37. No evidence was found for CP-violating contributions to the KLγ*γ* interaction.9014141801/1141801/5Wolfenstein, L., (1983) Phys. Rev. Lett., 51, p. 1945Belanger, G., Geng, C.Q., (1991) Phys. Rev. D, 43, p. 140Buras, A.J., Fleischer, R., (1998) Advanced Ser. Direct. High Energy Phys., 15, p. 65Uy, Z.E.S., (1991) Phys. Rev. D, 43, p. 802D'Ambrosio, G., Isidori, G., Portolès, J., (1998) Phys. Lett. B, 423, p. 385Alavi-Harati, A., (2001) Phys. Rev. Lett., 87, p. 71801. , KTeV CollaborationAlavi-Harati, A., (2001) Phys. Rev. Lett., 86, p. 5425. , KTeV CollaborationUy, Z.E.S., (2002) Eur. Phys. J. C, 23, p. 113Alavi-Harati, A., (2001) Phys. Rev. Lett., 87, p. 111802. , KTeV CollaborationHamm, J.C., (2002), Ph.D. thesis, The University of Arizona(Fermilab Report No. fERMILAB-THESIS-2002-09)Alavi-Harati, A., (1999) Phys. Rev. Lett., 83, p. 922. , KTeV CollaborationAlavi-Harati, A., (2000) Phys. Rev. D, 61, p. 072006. , KTeV CollaborationBrown, C., (1996) Nucl. Instrum. Methods Phys. Res., Sect. A, 369, p. 248Quinn, G.B., (2000), Ph.D. thesis, The University of ChicagoBarker, A.R., Huang, H., Toale, P.A., Engle, J., hep-ph/0210174Bergström, L., Massó, E., Singer, P., (1983) Phys. Lett., 131 B, p. 229Fanti, V., (1999) Phys. Lett. B, 458, p. 553. , NA48 Collaboratio

A search for the decay B+→K+ννˉB^+ \to K^+ \nu \bar{\nu}

We search for the rare flavor-changing neutral-current decay $B^+ \to K^+ \nu \bar{\nu}$ in a data sample of 82 fb$^{-1}$ collected with the {\sl BABAR} detector at the PEP-II B-factory. Signal events are selected by examining the properties of the system recoiling against either a reconstructed hadronic or semileptonic charged-B decay. Using these two independent samples we obtain a combined limit of ${\mathcal B}(B^+ \to K^+ \nu \bar{\nu})<5.2 \times 10^{-5}$ at the 90% confidence level. In addition, by selecting for pions rather than kaons, we obtain a limit of ${\mathcal B}(B^+ \to \pi^+ \nu \bar{\nu})<1.0 \times 10^{-4}$ using only the hadronic B reconstruction method.Comment: 7 pages, 8 postscript figures, submitted to Phys. Rev. Let

High-reflectivity broadband distributed Bragg reflector lattice matched to ZnTe

We report on the realization of a high quality distributed Bragg reflector with both high and low refractive index layers lattice matched to ZnTe. Our structure is grown by molecular beam epitaxy and is based on binary compounds only. The high refractive index layer is made of ZnTe, while the low index material is made of a short period triple superlattice containing MgSe, MgTe, and ZnTe. The high refractive index step of Delta_n=0.5 in the structure results in a broad stopband and the reflectivity coefficient exceeding 99% for only 15 Bragg pairs.Comment: 4 pages, 3 figure

EuFe2_2As2_2 under high pressure: an antiferromagnetic bulk superconductor

We report the ac magnetic susceptibility $\chi_{ac}$ and resistivity $\rho$ measurements of EuFe$_2$As$_2$ under high pressure $P$. By observing nearly 100% superconducting shielding and zero resistivity at $P$ = 28 kbar, we establish that $P$-induced superconductivity occurs at $T_c \sim$~30 K in EuFe$_2$As$_2$. $\rho$ shows an anomalous nearly linear temperature dependence from room temperature down to $T_c$ at the same $P$. $\chi_{ac}$ indicates that an antiferromagnetic order of Eu$^{2+}$ moments with $T_N \sim$~20 K persists in the superconducting phase. The temperature dependence of the upper critical field is also determined.Comment: To appear in J. Phys. Soc. Jpn., Vol. 78 No.

Neuroimaging-based classification of PTSD using data-driven computational approaches: a multisite big data study from the ENIGMA-PGC PTSD consortium

Background: Recent advances in data-driven computational approaches have been helpful in devising tools to objectively diagnose psychiatric disorders. However, current machine learning studies limited to small homogeneous samples, different methodologies, and different imaging collection protocols, limit the ability to directly compare and generalize their results. Here we aimed to classify individuals with PTSD versus controls and assess the generalizability using a large heterogeneous brain datasets from the ENIGMA-PGC PTSD Working group. Methods: We analyzed brain MRI data from 3,477 structural-MRI; 2,495 resting state-fMRI; and 1,952 diffusion-MRI. First, we identified the brain features that best distinguish individuals with PTSD from controls using traditional machine learning methods. Second, we assessed the utility of the denoising variational autoencoder (DVAE) and evaluated its classification performance. Third, we assessed the generalizability and reproducibility of both models using leave-one-site-out cross-validation procedure for each modality. Results: We found lower performance in classifying PTSD vs. controls with data from over 20 sites (60 % test AUC for s-MRI, 59 % for rs-fMRI and 56 % for D-MRI), as compared to other studies run on single-site data. The performance increased when classifying PTSD from HC without trauma history in each modality (75 % AUC). The classification performance remained intact when applying the DVAE framework, which reduced the number of features. Finally, we found that the DVAE framework achieved better generalization to unseen datasets compared with the traditional machine learning frameworks, albeit performance was slightly above chance. Conclusion: These results have the potential to provide a baseline classification performance for PTSD when using large scale neuroimaging datasets. Our findings show that the control group used can heavily affect classification performance. The DVAE framework provided better generalizability for the multi-site data. This may be more significant in clinical practice since the neuroimaging-based diagnostic DVAE classification models are much less site-specific, rendering them more generalizable.Stress-related psychiatric disorders across the life spa