Results 51 to 60 of about 2,485 (226)
Götterdämmerung over total least squares
The traditional way of solving non-linear least squares (LS) problems in Geodesy includes a linearization of the functional model and iterative solution of a nonlinear equation system.
Malissiovas G., Neitzel F., Petrovic S.
doaj +1 more source
TSTScope is an interpretable AI framework that integrates single‐cell transcriptomes with TCR information through curated gene‐program constraints. By linking receptor context to functional T cell states, it reveals response‐associated tumor‐specific T cell programs in lung cancer immunotherapy cohorts and defines an MPR score associated with ...
Shiwei Cao +8 more
wiley +1 more source
TH17–Associated Polyamine Metabolism‐Guided Nanozyme Promotes Alveolar Bone Repair in Periodontitis
A pronounced TH17‐skewed immune response is identified in experimental periodontitis, and enrichment of the polyamine pathway is observed during TH17 differentiation, suggesting its potential as an immunometabolic target. Inspired by these findings, DFMO@Ui‐Mn is developed as a therapeutic platform combining cascade ROS scavenging with immunometabolic ...
Cheng Zhu +12 more
wiley +1 more source
A‐site substitution in Nb2AlC with Fe yields Nb2FeC, a near room‐temperature ferromagnetic MAX phase. Synchrotron‐based spectroscopy and scanning transmission X‐ray microscopy (STXM) with X‐ray magnetic circular dichroism reveal intrinsic bulk ferromagnetism confined to Fe layers, with weak interlayer coupling across Nb2C layer.
Sambhu Charan Das +17 more
wiley +1 more source
On The Errors-In-Variables Model With Singular Dispersion Matrices
While the Errors-In-Variables (EIV) Model has been treated as a special case of the nonlinear Gauss- Helmert Model (GHM) for more than a century, it was only in 1980 that Golub and Van Loan showed how the Total Least-Squares (TLS) solution can be ...
Schaffrin B., Snow K., Neitzel F.
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A machine learning method, opt‐GPRNN, is presented that combines the advantages of neural networks and kernel regressions. It is based on additive GPR in optimized redundant coordinates and allows building a representation of the target with a small number of terms while avoiding overfitting when the number of terms is larger than optimal.
Sergei Manzhos, Manabu Ihara
wiley +1 more source
Predictive models successfully screen nanoparticles for toxicity and cellular uptake. Yet, complex biological dynamics and sparse, nonstandardized data limit their accuracy. The field urgently needs integrated artificial intelligence/machine learning, systems biology, and open‐access data protocols to bridge the gap between materials science and safe ...
Mariya L. Ivanova +4 more
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Deformation analysis by an improved similarity transformation
In this contribution, deformation analysis is rigorously performed by a non-linear 3-D similarity transformation. In contrast to traditional methods based on linear least-squares (LLS), here we solve a non-linear problem without any linearization.
Vahid Mahboub
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Sparse Bayesian learning (SBL) is applied to the coprime array for underdetermined wideband direction of arrival (DOA) estimation. Using the augmented covariance matrix, the coprime array can achieve a higher number of degrees of freedom (DOFs) to ...
Yanhua Qin +3 more
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Redescription of the Triassic cynodont Cistecynodon parvus and reassessment of its phylogeny
Abstract Cynodontia is an important subclade of Therapsida that first occurred in the late Permian. It includes extinct subclades which are the non‐mammaliaform cynodonts and Mammaliaformes, with the latter ultimately giving rise to crown mammals. The systematics of non‐mammaliaform cynodonts has been extensively studied and is relatively well‐resolved,
Erin S. Lund +4 more
wiley +1 more source

