Results 31 to 40 of about 14,804 (145)
Machine Learning for Predictive Modeling in Nanomedicine‐Based Cancer Drug Delivery
The integration of AI/ML into nanomedicine offers a transformative approach to therapeutic design and optimization. Unlike conventional empirical methods, AI/ML models (such as classification, regression, and neural networks) enable the analysis of complex clinical and formulation datasets to predict optimal nanoparticle characteristics and therapeutic
Rohan Chand Sahu +3 more
wiley +1 more source
A highly accurate numerical method is given for the solution of boundary value problem of generalized Bagley‐Torvik (BgT) equation with Caputo derivative of order 0<β<2$$ 0<\beta <2 $$ by using the collocation‐shooting method (C‐SM). The collocation solution is constructed in the space Sm+1(1)$$ {S}_{m+1}^{(1)} $$ as piecewise polynomials of degree at ...
Suzan Cival Buranay +2 more
wiley +1 more source
Feynman integral in $\mathbb R^1\oplus\mathbb R^m$ and complex expansion of $_2F_1$
Closed form expressions are proposed for the Feynman integral $$ I_{D, m}(p,q) = \int\frac{d^my}{(2\pi)^m}\int\frac{d^Dx}{(2\pi)^D} \frac1{(x-p/2)^2+(y-q/2)^4} \frac1{(x+p/2)^2+(y+q/2)^4} $$ over $d=D+m$ dimensional space with $(x,y),\,(p,q)\in
Pogány, Tibor K., Shpot, Mykola A.
core +1 more source
Financial Time Series Uncertainty: A Review of Probabilistic AI Applications
ABSTRACT Probabilistic machine learning models offer a distinct advantage over traditional deterministic approaches by quantifying both epistemic uncertainty (stemming from limited data or model knowledge) and aleatoric uncertainty (due to inherent randomness in the data), along with full distributional forecasts.
Sivert Eggen +4 more
wiley +1 more source
Nonparametric Detection of a Time‐Varying Mean
ABSTRACT We propose a nonparametric portmanteau test for detecting changes in the unconditional mean of a univariate time series which may display either long or short memory. Our approach is designed to have power against, among other things, cases where the mean component of the series displays abrupt level shifts, deterministic trending behaviour ...
Fabrizio Iacone, A. M. Robert Taylor
wiley +1 more source
SU(2) nonstandard bases: the case of mutually unbiased bases [PDF]
This paper deals with bases in a finite-dimensional Hilbert space. Such a space can be realized as a subspace of the representation space of SU(2) corresponding to an irreducible representation of SU(2). The representation theory of SU(2) is reconsidered
Albouy, O., Kibler, M. R.
core +3 more sources
Isoperimetric inequalities on slabs with applications to cubes and Gaussian slabs
Abstract We study isoperimetric inequalities on “slabs”, namely weighted Riemannian manifolds obtained as the product of the uniform measure on a finite length interval with a codimension‐one base. As our two main applications, we consider the case when the base is the flat torus R2/2Z2$\mathbb {R}^2 / 2 \mathbb {Z}^2$ and the standard Gaussian measure
Emanuel Milman
wiley +1 more source
Bases for qudits from a nonstandard approach to SU(2)
Bases of finite-dimensional Hilbert spaces (in dimension d) of relevance for quantum information and quantum computation are constructed from angular momentum theory and su(2) Lie algebraic methods.
A. I. Kostrikin +35 more
core +2 more sources
ABSTRACT Purpose This work proposes a method for the simultaneous estimation of the exchange‐dependent relaxation rate Rex$$ {R}_{ex} $$ and the longitudinal relaxation time T1$$ {T}_1 $$ from a single acquisition. Methods A novel acquisition scheme was developed that combines CEST saturation with an inversion pulse and a Look‐Locker readout to capture
Markus Huemer +6 more
wiley +1 more source
Factorization of numbers with Gauss sums: I. Mathematical background
We use the periodicity properties of generalized Gauss sums to factor numbers. Moreover, we derive rules for finding the factors and illustrate this factorization scheme for various examples.
Averbukh, I. Sh. +4 more
core +3 more sources

