Results 81 to 90 of about 17,567 (165)

Analysis strategies for time-resolved X-ray solution scattering at high repetition rate XFEL sources. [PDF]

J Synchrotron Radiat
Haubro ML, Zederkof DB, Khakhulin D, Yousef H, Jiang Y, Macias IJB, Kluyver T, Lima F, Biednov M, Milne C, Uemura Y, Zalden P, Wang H, Dohn AO, Mitterer K, Markmann V, Ohlson O, Wachter-Lehn MT, Lenzen P, Jensen BK, Høholdt A, van Driel TB, Nimmrich A, Selenius E, Levi G, Møller KB, Nielsen MM, Haldrup K.   +27 more
europepmc   +1 more source

Analytical construction and visualization of nonlinear waves in the (2+1) dimensional Kadomtsev-Petviashvili-Sawada-Kotera-Ramani equation with stability analysis. [PDF]

Sci Rep
Ahmed M, Ahmed HM, Badra N, Samir I.
europepmc   +1 more source

Spatiotemporal Maps for Dynamic MRI Reconstruction. [PDF]

IEEE Trans Comput Imaging
Lobos RA, Wang X, Fung RTL, He Y, Frey D, Gupta D, Liu Z, Fessler JA, Noll DC.   +8 more
europepmc   +1 more source

Analytical characterization of optical solitons and bifurcation analysis for the (2+1)-D Wazwaz-Kaur Boussinesq equation. [PDF]

Sci Rep
Samir I, Badra N, Abdalla NSE, Ramadan ME, Ahmed HM.   +4 more
europepmc   +1 more source

Innovative solutions for lossy nonlinear transmission lines model using a modified extended mapping approach with fractional effects. [PDF]

Sci Rep
Hussein HH, Alexan W, Kandil SA.
europepmc   +1 more source

SOLVE: A structured orthogonal latent variable framework for disentangling confounding in matrix data. [PDF]

Biol Methods Protoc
She J, Alterovitz G.
europepmc   +1 more source

Dynamical behavior of analytical solutions and bifurcation analysis for a novel structured (2+1)-dimensional Kadomtsev-Petviashvili equation via analytic approach. [PDF]

Sci Rep
Ghayad MS, Hamada MY, Ahmed HM, Emadifar H, Ahmed KK.   +4 more
europepmc   +1 more source

RFGLNet for adverse weather domain-generalized semantic segmentation with frequency low-rank enhancement. [PDF]

Sci Rep
Ye X, Shi X, Li Y.
europepmc   +1 more source

Coevolution of cooperative lifestyles and reduced cancer prevalence in mammals. [PDF]

Sci Adv
Sierra C, Maxwell J, Flaibani N, de la Vega CS, Ventura AC, Lavagnino NJ, Blaustein M.   +6 more
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Automatic Differentiation is Essential in Training Neural Networks for Solving Differential Equations. [PDF]

J Sci Comput
Chen C, Yang Y, Xiang Y, Hao W.
europepmc   +1 more source