Results 61 to 70 of about 19,142 (268)
Reciprocal Monogenic Septinomials of Degree 2n3
We prove a new irreducibility criterion for certain septinomials in ℤ[x], and we use this result to construct infinite families of reciprocal septinomials of degree 2n3 that are monogenic for all n ≥ 1.
Jones Lenny
doaj +1 more source
Automation and Active Learning for the Multi‐Objective Optimization of Antibody Formulations
Successful antibody formulation necessitates balancing factors such as thermal stability, colloidal stability, and viscosity across a vast excipient design space. This work integrates robotic liquid handling, high‐throughput biophysical characterization, and multi‐objective Bayesian optimization in an iterative closed‐loop Design‐Build‐Test‐Learn cycle.
D. Christopher Radford +3 more
wiley +1 more source
Strong monotonicity for analytic ordinary differential equations
We present a necessary and sufficient criterion for the flow of an analytic ordinary differential equation to be strongly monotone; equivalently, strongly order-preserving.
Sebastian Walcher, Christian Zanders
doaj
Our work bridges the gap between skyrmion discovery and material design by demonstrating how atomic‐scale control of exchange interactions enables tunable skyrmion phase transitions in centrosymmetric magnetic metals. ABSTRACT Magnetic skyrmions are topologically protected spin states that hold promise for shaping the future of electronics.
Dasuni N. Rathnaweera +9 more
wiley +1 more source
Products of Irreducible Characters Having Complex-Valued Constituents [PDF]
First, we prove that when a finite solvable group $G$ has a faithful irreducible character $\chi$ such that $\chi\overline{\chi}$ has two irreducible constituents, both must be real-valued.
Lisa R. Hendrixson, Mark L. Lewis
doaj +1 more source
Deep Learning‐Assisted Coherent Raman Scattering Microscopy
The analytical capabilities of coherent Raman scattering microscopy are augmented through deep learning integration. This synergistic paradigm improves fundamental performance via denoising, deconvolution, and hyperspectral unmixing. Concurrently, it enhances downstream image analysis including subcellular localization, virtual staining, and clinical ...
Jianlin Liu +4 more
wiley +1 more source
The microflow equipment monitored with micro X-ray computerized tomography (CT) is employed to investigate the microoccurrence of the irreducible water in a low-permeability sandstone core.
Xiaoyu Gu +8 more
doaj +1 more source
This study introduces FIRE‐GNN, a force‐informed, relaxed equivariant graph neural network for predicting surface work functions and cleavage energies from slab structures. By incorporating surface‐normal symmetry breaking and machine learning interatomic potential‐derived force information, the approach achieves state‐of‐the‐art accuracy and enables ...
Circe Hsu +5 more
wiley +1 more source
Irreducible Triangulations of Surfaces
The authors show that, for any surface \(S\) and any \(k\), there are at most finitely many triangulations of \(S\) such that each edge is in a noncontractible cycle of length \(k\), but is in no shorter noncontractible cycle; such a triangulation is said to be \(k\)-irreducible. If \(S\) is the sphere with \(h\) handles (respectively the sphere with \(
Zhicheng Gao +2 more
openaire +2 more sources
Predicting Performance of Hall Effect Ion Source Using Machine Learning
This study introduces HallNN, a machine learning tool for predicting Hall effect ion source performance using a neural network ensemble trained on data generated from numerical simulations. HallNN provides faster and more accurate predictions than numerical methods and traditional scaling laws, making it valuable for designing and optimizing Hall ...
Jaehong Park +8 more
wiley +1 more source

