Search · four archives
Search · four archives
21 papers · ranked by Valyu relevance
Andrei D. Polyanin
The study gives a brief overview of existing modifications of the method of functional separation of variables for nonlinear PDEs. It proposes a more general approach to the construction of exact solutions to nonlinear equations of applied mathematics and mathematical physics, based on a special transformation with an…
Simon Ekhammar, Nikolay Gromov, Paul Ryan
In this paper we show how the Functional Separation of Variables (FSoV) method can be applied to the problem of computing overlaps with integrable boundary states in integrable systems. We demonstrate our general method on the example of a particular boundary state, a singlet of the symmetry group, in an su(3) rational…
Andrei D. Polyanin
This note shows that in looking for exact solutions to nonlinear PDEs, the direct method of functional separation of variables can, in certain cases, be more effective than the method of differential constraints based on the compatibility analysis of PDEs with a single constraint (invariant surface condition). This…
Yizuo Chen, Adnan Darwiche, Nikolai Leonenko, Luis Enrique Sucar + 1 more
'David Danks'] We study the identification of causal effects, motivated by two improvements to identifiability that can be attained if one knows that some variables in a causal graph are functionally determined by their parents (without needing to know the specific functions). First, an unidentifiable causal effect may…
Yizuo Chen, Adnan Darwiche
We study the identification of causal effects, motivated by two improvements to identifiability which can be attained if one knows that some variables in a causal graph are functionally determined by their parents (without needing to know the specific functions). First, an unidentifiable causal effect may become…
Laurie Berrie, Kellyn F Arnold, Georgia D Tomova, Mark S Gilthorpe + 1 more
'Peter W G Tennant'] Title: Abstract Deterministic variables are variables that are functionally determined by one or more parent variables. They commonly arise when a variable has been functionally created from one or more parent variables, as with derived variables, and in compositional data, where the “whole”…
Aneta Sawikowska, Anna Piasecka, Piotr Kachlicki, Paweł Krajewski + 1 more
'Silas G. Villas-Boas'] Peak overlapping is a common problem in chromatography, mainly in the case of complex biological mixtures, i.e., metabolites. Due to the existence of the phenomenon of co-elution of different compounds with similar chromatographic properties, peak separation becomes challenging. In this paper…
Fabrizio Maturo, Rosanna Verde
Scientific progress has contributed to creating many devices to gather vast amounts of biomedical data over time. The goal of these devices is generally to monitor people's health conditions, diagnose, and prevent patients' diseases, for example, to discover cardiovascular disorders or predict epileptic seizures. A…
Fabrizio Maturo, Annamaria Porreca
Unbiased Functional Principal Components Importance through Ad-Hoc Conditional Permutations Authors: ['Fabrizio Maturo' 'Annamaria Porreca'] This paper introduces a novel supervised classification strategy that integrates functional data analysis (FDA) with tree-based methods, addressing the challenges of…
Authors not listed
Rapid and robust simulation of chemical processes is critical to conduct process design, optimization, techno-economic analysis, and sustainability analysis. Yet, efficiently solving simulation models remains a challenge due to the highly coupled and nonlinear nature of the underlying algebraic equations that capture…
Il-Youp Kwak, Candace R. Moore, Edgar P. Spalding, Karl W. Broman
We previously proposed a simple regression-based method to map quantitative trait loci underlying function-valued phenotypes. In order to better handle the case of noisy phenotype measurements and accommodate the correlation structure among time points, we propose an alternative approach that maintains much of the…
Zack Williams, Frederick Manby
In a previous paper we presented a new hybrid functional B-LYP-osUW12-D3(BJ) containing the Unsöld-w12 (UW12) hybrid correlation model. In this paper we present a new 15-parameter range-separated hybrid density functional using a power series expansion together with UW12 correlation. This functional is optimised using…
Manuel Escabias, Ana M. Aguilera, Christian Acal
The functional logit regression model was proposed by Escabias et al. (2004) with the objective of modeling a scalar binary response variable from a functional predictor. The model estimation proposed in that case was performed in a subspace of L 2 (T) of squared integrable functions of finite dimension, generated by a…
Olga Bokareva, Patrick Zobel, Ayla Kruse, Omar Baig + 4 more
Density functional theory is an efficient computational tool to investigate photophysical and photochemical processes in transition metal complexes, giving invaluable assistance in the interpretation of spectroscopic and catalytic experiments. Optimally-tuned range-separated functionals are particularly promising, as…
Farideh Badichi Akher, Yinan Shu, Zoltan Varga, Suman Bhaumik + 1 more
Machine-learned representations of potential energy surfaces generated in the output layer of a feedforward neural network are becoming increasingly popular. One difficulty with neural-network output is that it is often unreliable in regions where training data is missing or sparse. Humandesigned potentials often build…
Michael Asamoah-Boaheng, Emmanuel Kofi Sam
In this study the characterisation and separation/discrimination of three sheep breeds (crosses, West African Dwarfs (WAD) and West African Long Legged (WALL)] based on their physical traits (morphological characterisation) was investigated extensively with the application of discriminant analysis. The study’s main…
Torsti Schulz, Marjo Saastamoinen, Jarno Vanhatalo
Variance partitioning is a common tool for statistical analysis and interpretation in both observational and experimental studies in ecology. Its popularity has led to a proliferation of methods with sometimes confusing or contradicting interpretations. Here, we present variance partitioning as a general tool in a…
Carlos P. Carmona, Nicola Pavanetto, Giacomo Puglielli
Functional trait space analyses are pivotal to define species’ ecological strategies across the tree of life. Yet, there is no single application that streamlines the many sometimes-troublesome steps needed to build and analyze functional trait spaces. To fill this gap, we propose funspace, an R package to easily…
Abdelghani Ghazdali, Abdelilah Hakim, Amine Laghrib, Nezha Mamouni + 1 more
'Said Raghay'] Background The electrocardiogram (ECG) is a diagnostic tool that records the electrical activity of the heart, and depicts it as a series of graph-like tracings, or waves. Being able to interpret these details allows diagnosis of a wide range of heart problems. Fetal electrocardiogram (FECG) extraction…
Tobias Seidel, Lena-Marie Ränger, Thomas Grützner, Michael Bortz
In this work we present a new approach that we use to simulate and optimize multiple dividing wall columns at the same time. Instead of considering all model equations as constraints and all process variables as optimization variables in a large and highly nonlinear optimization problem we only incorporate a subset of…
Nating Wang, Tinyi Chu, Jiangtao Luo, Rongling Wu + 1 more
QTL mapping is a powerful tool to infer the complexity of the genetic architecture underlying phenotypic traits, and has been extended to include longitudinal traits measured at multiple temporal/spatial points. Here, we introduce the R package Funmap2 based on the functional mapping framework, which integrates…