Results 41 to 50 of about 14,407 (260)

SPG4 and Dementia: Expanding the Clinical Spectrum

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Hereditary spastic paraplegia (HSP) is a group of disorders characterized by progressive spasticity and lower limb weakness, with mutations in SPG4/SPAST being the most common cause. Detailed studies and clinical and molecular comparisons across different populations are missing.
Emanuele Panza, Arun Meyyazhagan, Eliseo Picchi, Gustavo Ribas, Ingrid Faber, Ryosuke Miyamoto, Preethi Basavaraju, Paolo Eusebi, Haripriya Kuchi Bhotla, Mario Stasi, Fabrizio Gaudiello, Francesco Patti, Filippo Maria Santorelli, Marcondes Cavalcante França Jr, José Luiz Pedroso, Orlando Graziani Povoas Barsottini, Hélio Afonso Ghizoni Teive, Peter Henry St George‐Hyslop, Toshitaka Kawarai, Antonio Orlacchio   +19 more
wiley   +1 more source

Interpolation based on context modeling for hierarchical compression of multidimensional signals [PDF]

Компьютерная оптика, 2018
Context algorithms for interpolation of multidimensional signals in the compression problem are researched. A hierarchical compression method for arbitrary dimension signals is considered.
Mikhael Gashnikov
doaj   +1 more source

Unleashing the Power of Machine Learning in Nanomedicine Formulation Development

Advanced Functional Materials, EarlyView.
A random forest machine learning model is able to make predictions on nanoparticle attributes of different nanomedicines (i.e. lipid nanoparticles, liposomes, or PLGA nanoparticles) based on microfluidic formulation parameters. Machine learning models are based on a database of nanoparticle formulations, and models are able to generate unique solutions
Thomas L. Moore, Cristiano Pesce, Antonietta Greco, Claudia Pisante, Greta Avancini, Valentina Di Francesco, Yosi Shamay, Paolo Decuzzi   +7 more
wiley   +1 more source

A comparative study between kriging and adaptive sparse tensor-product methods for multi-dimensional approximation problems in aerodynamics design*

ESAIM: Proceedings and Surveys, 2015
The performances of two multivariate interpolation procedures are compared using functions that are either synthetic or coming from a shape optimization problem in aerodynamics. The aim is to evaluate the efficiency of adaptive sparse
Chkifa Abdellah, Cohen Albert, Passaggia Pierre-Yves, Peter Jacques   +3 more
doaj   +1 more source

Multivariate Refinable Interpolating Functions

Applied and Computational Harmonic Analysis, 1999
The author gives an algorithm for the construction of refinable interpolating functions for an arbitrary dilation matrix. This construction of refinable interpolating functions is an intermediate step in the construction of orthonormal wavelet bases and is of interest in its own right.
openaire   +2 more sources

Predicting Atomic Charges in MOFs by Topological Charge Equilibration

Advanced Functional Materials, EarlyView.
An atomic charge prediction method is presented that is able to accurately reproduce ab‐initio‐derived reference charges for a large number of metal–organic frameworks. Based on a topological charge equilibration scheme, static charges that fulfill overall neutrality are quickly generated.
Babak Farhadi Jahromi, Sumukh Shankar Sharadaprasad, Rochus Schmid   +2 more
wiley   +1 more source

Solvability of multivariate interpolation

Journal für die reine und angewandte Mathematik (Crelles Journal), 1989
An ordinary polynomial interpolation scheme is described by the admissible polynomials \(P(x)=\sum_{i\in S}a_ ix^ i\), \(x=(x_ 1,...,x_ s)\), \(i=(i_ 1,...,i_ s)\), \(s\geq 2\), where S is a lower set of lattice points i, and by the knot sets \(A_ q\subset S\), \(q=1,...,m\), which give the orders \(\alpha \in A_ q\) of the derivatives \(\partial P ...
openaire   +2 more sources

PRELIVE: A Framework for Predicting Lipid Nanoparticles In Vivo Efficacy and Reducing Reliance on Animal Testing

Advanced Functional Materials, EarlyView.
PREdicting LNP In Vivo Efficacy (PRELIVE) framework enables the prediction of lipid nanoparticle (LNPs) organ‐specific delivery through dual modeling approaches. Composition‐based models using formulation parameters and protein corona‐based models using biological fingerprints both achieve high predictive accuracy across multiple organs.
Belal I. Hanafy, Chuan‐En Lu, Kai Liu, Audrey Gallud   +3 more
wiley   +1 more source

A Hybrid Missing Data Imputation Method for Batch Process Monitoring Dataset

Sensors, 2023
Batch process monitoring datasets usually contain missing data, which decreases the performance of data-driven modeling for fault identification and optimal control. Many methods have been proposed to impute missing data; however, they do not fulfill the
Qihong Gan, Lang Gong, Dasha Hu, Yuming Jiang, Xuefeng Ding   +4 more
doaj   +1 more source

Multivariate Newton Interpolation

, 2018
For $m,n \in \mathbb{N}$, $m\geq 1$ and a given function $f : \mathbb{R}^m\longrightarrow \mathbb{R}$, the polynomial interpolation problem (PIP) is to determine a unisolvent node set $P_{m,n} \subseteq \mathbb{R}^m$ of $N(m,n):=|P_{m,n}|=\binom{m+n}{n}$ points and the uniquely defined polynomial $Q_{m,n,f}\in _{m,n}$ in $m$ variables of degree ...
Hecht, Michael, Hoffmann, Karl B., Cheeseman, Bevan L., Sbalzarini, Ivo F.   +3 more
openaire   +2 more sources