21 papers · ranked by Valyu relevance
Daniel Walsken, Matthias Ehrhardt, Pavel Petrov
The split-step-Padé (SSP) method is widely used to model wave phenomena in various applications, including radio physics, optics and acoustics. In this method, the propagator of the one-way counterpart of the Helmholtz equation is computed through its Padé approximant and a finite-difference discretization of the…
Walsken, Daniel, Petrov, Pavel + 2 more
In this study, a Fourier-based, split-step, Pad´e (SSP) method for solving the parabolic wave equation with applications in guided wave propagation in ocean acoustics is presented. Traditional SSP implementations rely on finite-difference discretizations of the depth-dependent differential operator. This approach…
Kevin Schäfers, Michael Günther
We propose a hierarchical splitting approach to differential equations that provides a design principle for constructing splitting methods for N-split systems by iteratively applying splitting methods for two-split systems. We analyze the convergence order, derive explicit formulas for the leading-order error terms…
Mingkun Yang, Ran Zhu, Qing Wang, Yan Yu
Split Federated Learning is a system-efficient federated learning paradigm that leverages the rich computing resources at a central server to train model partitions. Data heterogeneity across silos, however, presents a major challenge undermining the convergence speed and accuracy of the global model. This paper…
Jiaqi Wu
Phylogenomic analyses are increasingly focused on branch-specific questions within a fixed species tree. However, two pervasive challenges in real datasets—missing taxa and gene-tree/species-tree discordance—complicate the comparability of branches across loci. Here, we introduce SplitAligner, a split-based framework…
Ruoyue Mao, Xiaoyang Shi, Zhiyan Shi, Sotiris Kotsiantis
Classification is an important task in the field of machine learning. Decision tree algorithms are a popular choice for handling classification tasks due to their high accuracy, simple algorithmic process, and good interpretability. Traditional decision tree algorithms, such as ID3, C4.5, and CART, differ primarily in…
Anower Hossen Zihad, Felix Owino, Haibo Yang, Ming Tang + 1 more
—Split learning is a distributed training paradigm where a neural network is partitioned between clients and a server, which allows data to remain at the client while only intermediate activations are shared. Traditional split learning relies on endto-end backpropagation across the client–server split point. This…
R. Altmann, R. Morandin
This paper is devoted to the numerical analysis of a second-order bulk--surface splitting scheme for the semi-linear wave equation with kinetic boundary conditions. The construction is based on the interpretation of the equations as coupled system and the implementation of different difference formulae for the discrete…
Riccardo Russo, Michele Ducceschi, Stefan Bilbao
This work is concerned with the Scalar Auxiliary Variable (SAV) method applied to geometrically nonlinear string models, focusing on the analysis of numerical convergence across various model formulations. An ODE system with a potential akin to that of the geometrically exact string is first analysed, providing both…
Jonathan M. Wood, Saunders Penn, Hyosub E. Kim, Susanne M. Morton
Stable gait in humans relies on both precise estimates of lower limb position and the ability to robustly adapt walking movements across different environments. However, the specific relationship between sensorimotor adaptation and the perception of lower limb position during gait remains unclear. In this study, we…
Kiichi F. Ash, Courtney M. Butowicz, Brad D. Hendershot, Pawel R. Golyski
1.## Background Losses of stability during walking are a significant problem, with >35% of older adults (1,2), > 34% of patients with neurological diseases (3), and >50% of individuals with lower limb loss falling at least once a year (4,5). In addition to injury (6,7), falls can precipitate a fear of falling…
Samantha Jeffcoat, Adrian Aragon, Andrian Kuch, Shawn Farrokhi + 4 more
Studies of locomotor adaptation have shown that adaptation can occur in short bouts and can continue for long bouts or across days. Information about task duration might influence the adaptation of gait features, given that task duration influences the time available to explore and adapt the aspects of gait that reduce…
Daphna Raz, Rachel Marbaker, Sriram Sankaranarayanan, Alaa A. Ahmed
Locomotor learning in novel environments relies on a gradual alteration of motor output to achieve a desired state. Changes in gait outcomes such as step-length asymmetry are typically used to describe this process. Recently, stability-relevant adaptations, quantified by scalar metrics such as the margin of stability…
Ehab M. Almetwally, Mohammad A. Zayed, Sara I. Abo-Hashem, Rahma Sadat + 2 more
This research is devoted to analyze a conformable fractional-order model of nonlinear two-dimensional transmission line metamaterials. The conformable fractional derivative is utilized to broaden classical differentiation while maintaining essential aspects, including the chain rule. Transmission line metamaterials, as…
Authors not listed
Exploring the potential energy surface to sample transition state regions is crucial to understand the atomic processes that govern chemical reactivity. Ideally, the exploration does not require any collective variables that are based on prior chemical domain knowledge. With this in mind, we adapt the stochastic saddle…
Wenjing Ma, Siyu Hou, Lulu Shang, Jiaying Lu + 1 more
Spatiotemporal transcriptomics is an emerging and powerful approach that adds a temporal dimension to spatial transcriptomics, enabling the characterization of dynamic changes in tissue architecture during development or disease progression. Here, we present SpaDOT (Spatial Domain Transition detection), a computational…
Authors not listed
A method has been introduced to derive the solution of the time-independent Schrodinger equation for the simple harmonic oscillator. A trial solution has been chosen as the product of the divergent part of the approximate asymptomatic solution of the Schrodinger equation and an unknown function. By inserting this trial…
Authors not listed
Transition state (TS) geometries of chemical reactions are key to understanding reaction mechanisms and estimating kinetic properties. Inferring these directly from 2D reaction graphs offers chemists a powerful tool for rapid and accessible reaction analysis. Quantum chemical methods for computing TSs are…
Authors not listed
The complete active space self-consistent field (CASSCF) method is essential for describing complex photochemical processes, but its application in ab initio molecular dynamics is often limited by the computational cost associated with four-center two-electron repulsion integrals (ERIs). We present the first…
Authors not listed
Two kinetic schemes of the general modifier mechanism have been analysed in a quasi-steady state approximation, assuming that the reaction product concentration is negligible (a natural assumption for the initial rate method) and without additional simplifying assumptions. The characteristic equations have been…
Dongjian Zhang, Mingshen Zhang, Nuo Li, Chaoxin Zheng + 3 more
Automated domain annotation in spatially resolved transcriptomics (SRT) remains challenging since it depends on gene expression, morphology, and clinical conventions, which vary across cohorts and platforms. While Large Language Model (LLM)-driven agents show promise, current approaches typically condition semantic…