Results 121 to 130 of about 11,050,393 (374)
On the definition of a close-to-convex function
, 1978 The standard definition of a close-to-convex function involves a complex numerical factor eiβ which is on occasion erroneously replaced by 1. While it is known to experts in the field that this replacement cannot be made without essentially changing the ...
A. Goodman, E. Saff
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Proceedings of the American Mathematical Society, 1974 The purpose of this paper is to prove convexity properties for the tensor product, determinant, and permanent of hermitian matrices.
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Advanced Functional Materials, EarlyView.Walnut seeds are enclosed in a remarkably strong shell made of sclerenchyma, separated by a pectin‐rich suture tissue. Different cell shapes and chemical composition of this tissue point to an opening mechanism, which is triggered by cyclic humidity changes.
Sebastian J. Antreich +3 more
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Journal of Inequalities and Applications, 2019 In the article, we establish some new general fractional integral inequalities for exponentially m-convex functions involving an extended Mittag-Leffler function, provide several kinds of fractional integral operator inequalities and give certain special
Saima Rashid +4 more
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Infima of convex functions [PDF]
Transactions of the American Mathematical Society, 1989 Let Γ ( X ) \Gamma (X) be the lower semicontinuous, proper, convex functions on a real normed linear space X X . We produce a simple description of what is, essentially, the weakest topology on Γ ( X ) \Gamma (X) such that the value ...
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Locking Metastable Topological Domains in Nematic Liquid Crystal Pi Cells
Advanced Functional Materials, EarlyView.Selective photopolymerization in the presence of a controlled voltage defines permanent director walls that lock‐in metastable bend and twist configurations within nematic liquid crystal Pi cells. Q‐tensor simulations corroborate the experiments, demonstrating the topological state stabilization.
Adithya Pradeep +7 more
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The Lov\'asz Hinge: A Novel Convex Surrogate for Submodular Losses [PDF]
, 2017 Learning with non-modular losses is an important problem when sets of predictions are made simultaneously. The main tools for constructing convex surrogate loss functions for set prediction are margin rescaling and slack rescaling.
Blaschko, Matthew, Yu, Jiaqian
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Advanced Healthcare Materials, Volume 14, Issue 7, March 14, 2025.This paper presents a microphysiological system containing an array of individually addressable living corneal tissues constructed using primary human cells. The bioengineered eye model can simulate acute exposure of the human cornea to different types of environmental toxicants and provides a novel platform for visualization and quantitative ...
Se‐jeong Kim +12 more
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Filomat, 2019 Let A,B, and X be bounded linear operators on a separable Hilbert space such that A,B are positive, X ? ?I, for some positive real number ?, and ? ? [0,1]. Among other results, it is shown that if f(t) is an increasing function on [0,?) with f(0) = 0 such that f(?t) is convex, then ?|||f(?A + (1-?)B) + f(?|A-B|)|||?|||?f(A)X + (1-?)Xf (B ...
Omar Hirzallah, Ata Abu-As’ad
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Nonconvex Lipschitz function in plane which is locally convex outside a discontinuum [PDF]
, 2013 We construct a Lipschitz function on $\er^{2}$ which is locally convex on the complement of some totally disconnected compact set but not convex. Existence of such function disproves a theorem that appeared in a paper by L.
Pokorny, Dusan
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