Results 81 to 90 of about 39,536 (308)
Predicting the Sieving Effort for the Number Field Sieve [PDF]
, 2008 We present a new method for predicting the sieving effortfor the number field sieve (NFS) in practice. This method takes relationsfrom a short sieving test as input and simulates relations according tothis test. After removing singletons, we decide how many relations weneed for the factorization according to the simulation and this gives agood estimate
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A characterization of Moessner's sieve
Theoretical Computer Science, 2014 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Christian Clausen +2 more
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Molecular Oncology, EarlyView.This study identifies somatostatin receptor 4 (Sstr4) as a critical tumor suppressor against skin and head/neck cancers (HNSCC, cSCC, and BCC). The loss of Sstr4 removes a check on cell growth, causing hyperactivation of the MAPK‐ERK signaling pathway (↑).
Ali Taqvi +6 more
wiley +1 more source
CrystalsCoal gangue and aluminum ash emerge as quintessential constituents within the ambit of coal-derived solid waste and industrial residue, respectively. Leveraging coal gangue as a primary substrate and aluminum ash as an adjunct aluminum source, molecular ...
Qingping Wang +4 more
doaj +1 more source
TheoretiCSWe introduce determinantal sieving, a new, remarkably powerful tool in the toolbox of algebraic FPT algorithms. Given a polynomial $P(X)$ on a set of variables $X=\{x_1,\ldots,x_n\}$ and a linear matroid $M=(X,\mathcal{I})$ of rank $k$, both over a field $\mathbb{F}$ of characteristic 2, in $2^k$ evaluations we can sieve for those terms in the monomial
Eiben, Eduard +2 more
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, 2018 Most algorithms for hard lattice problems are based on the principle of rank reduction: to solve a problem in a d-dimensional lattice, one first solves one or more problem instances in a sublattice of rank d–1, and then uses this information to find a solution to the original problem.
Thijs Laarhoven, Artur Mariano
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FEBS Open Bio, EarlyView.RoboMic is an automated confocal microscopy pipeline for high‐throughput functional imaging in living cells. Demonstrated with fluorescence recovery after photobleaching (FRAP), it integrates AI‐driven nuclear segmentation, ROI selection, bleaching, and analysis.
Selçuk Yavuz +6 more
wiley +1 more source
Optimizing photoactivation of PA‐mCherry for optical pooled CRISPR screens
FEBS Open Bio, EarlyView.Photoactivatable PA‐mCherry finds widespread use to optically tag individual cells. However, confocal 405 nm UV laser‐scanning (normal scan) is much less efficient than widefield UV illumination, limiting the use of PA‐mCherry on confocal instruments. We remedy this limitation by reporting that rapid and repeated confocal scanning with a low‐intensity,
Sravasti Mukherjee +3 more
wiley +1 more source
Directed evolution of enzymes at the crossroads of tradition and innovation
FEBS Open Bio, EarlyView.An iterative cycle of data‐driven enzyme optimization comprising four stages: genetic diversification of a template enzyme, expression of protein variants, high‐throughput evaluation, and machine‐learning‐guided redesign of the next variant library.
Maria Tomkova +2 more
wiley +1 more source
Scaling Lattice Sieves across Multiple Machines [PDF]
Lattice sieves are algorithms for finding short vectors in lattices. We present an implementation of two such sieves – known as “BGJ1” and “BDGL” in the literature – that scales across multiple servers (with varying success).
Martin R. Albrecht, Joe Rowell
core +4 more sources