Results 51 to 60 of about 4,793 (299)

An Algorithmic Approach to Information and Meaning [PDF]

open access: yes, 2011
While it is legitimate to study ideas and concepts related to information in their broadest sense, that formal approaches properly belong in specific contexts is a fact that is too often ignored. That their use outside these contexts amounts to misuse or
Zenil, Hector
core  

Structural insights and therapeutic targets in Acinetobacter baumannii capsule biosynthesis

open access: yesFEBS Letters, EarlyView.
Hypervirulent KL49 A. baumannii's capsular polysaccharide contains the nonulosonic acid 8‐epi‐Leg5,7Ac2, synthesized by epimerization via ElaA, ElaB, and ElaC. Crystal structures of ElaA, ElaB, and ElaC reveal their role in CMP‐Leg5,7Ac2 synthesis and regioselective C8 epimerization.
Woo Cheol Lee   +7 more
wiley   +1 more source

An overview of higher randomness [PDF]

open access: yes, 2017
We will give an overview of the main results and last progresses in higher randomness. We will first talk about how, many results of algorithmic randomness can be transferred in the higher setting (we cover for this part results from the paper ...
Monin, Benoit
core  

The role of miR‐335‐5p in the redifferentiation of BRAF p.V600E thyroid cancers

open access: yesMolecular Oncology, EarlyView.
The BRAF p.V600E mutation promotes thyroid cancer dedifferentiation and radioiodine resistance. Using a network approach, we identified miR‐335‐5p as a key regulator of BRAF‐mutated thyroid tumors. Restoring miR‐335‐5p increased thyroid‐specific gene expression and iodine uptake in cells and organoids.
Valeria Pecce   +11 more
wiley   +1 more source

Bitslice Masking and Improved Shuffling:

open access: yesTransactions on Cryptographic Hardware and Embedded Systems, 2022
We revisit the popular adage that side-channel countermeasures must be combined to be efficient, and study its application to bitslice masking and shuffling. Our main contributions are twofold. First, we improve this combination: by shuffling the shares
Melissa Azouaoui   +3 more
doaj   +1 more source

Algorithmic randomness and computability [PDF]

open access: yes, 2006
We examine some recent work which has made significant progress in out understanding of algorithmic randomness, relative algorithmic randomness and their relationship with algorithmic computability and relative algorithmic ...
Downey, Rod
core  

Interrogating the immune landscape of microsatellite stable RAS‐mutated colon cancer

open access: yesMolecular Oncology, EarlyView.
COLOSSUS project RAS‐mutated MSS colon cancer study explored transcriptomics and immune cell density by immunohistochemistry (IHC), Immunoscore (IS), ISIC/TuLIS scores, mutation counts, and detected different prevalences but similar microenvironment composition across immune markers with clinical relevance for future immunotherapy combination ...
Rodrigo Dienstmann   +61 more
wiley   +1 more source

Algorithmic independence of initial condition and dynamical law in thermodynamics and causal inference

open access: yesNew Journal of Physics, 2016
We postulate a principle stating that the initial condition of a physical system is typically algorithmically independent of the dynamical law. We discuss the implications of this principle and argue that they link thermodynamics and causal inference. On
Dominik Janzing   +2 more
doaj   +1 more source

An introduction to randomized algorithms

open access: yesDiscrete Applied Mathematics, 1991
The concept of randomization is known to be an extremely important tool for the design of algorithms. Its use often yields better time or space complexity compared with the best deterministic algorithms we know of for the same problem; moreover resulting randomized algorithms are often very simple to understand and implement.
openaire   +1 more source

A randomized maximum-flow algorithm [PDF]

open access: yes30th Annual Symposium on Foundations of Computer Science, 1989
Summary: A randomized algorithm for computing a maximum flow is presented. For an \(n\)-vertex \(m\)-edge network, the running time is \(O(nm + n^2 (\log n)^2)\) with probability at least \(1 - 2^{- \sqrt {nm}}\). The algorithm is always correct, and in the worst case runs in \(O(nm \log n)\) time.
Cheriyan, J., Hagerup, T.
openaire   +2 more sources

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