Results 81 to 90 of about 4,793 (299)
FEBS Open Bio, EarlyView.This protocol paper outlines methods to establish the success of a time‐resolved serial crystallographic experiment, by means of statistical analysis of timepoint data in reciprocal space and models in real space. We show how to amplify the signal from excited states to visualise structural changes in successful experiments.
Jake Hill +4 more
wiley +1 more source
Hash Tables as Engines of Randomness at the Limits of Computation: A Unified Review of Algorithms
AlgorithmsHash tables embody a paradox of deterministic structure that emerges from controlled randomness. They have evolved from simple associative arrays into algorithmic engines that operate near the physical and probabilistic limits of computation. This review
Paul A. Gagniuc, Mihai Togan
doaj +1 more source
Non-Algorithmic Theory of Randomness [PDF]
, 2020 This paper proposes an alternative language for expressing results of the algorithmic theory of randomness. The language is more precise in that it does not involve unspecified additive or multiplicative constants, making mathematical results, in principle, applicable in practice.
openaire +2 more sources
Probability, Algorithmic Complexity, and Subjective Randomness [PDF]
, 2007 We present a statistical account of human randomness judgments that uses the idea of algorithmic complexity. We show that an existing measure of the randomness of a sequence corresponds to the assumption that non-random sequences are generated by a ...
Thomas L. Griffiths, Joshua B. Tenenbaum
core
FEBS Open Bio, EarlyView.Activation of the mitochondrial protein OXR1 increases pSyn129 αSynuclein aggregation by lowering ATP levels and altering mitochondrial membrane potential, particularly in response to MSA‐derived fibrils. In contrast, ablation of the ER protein EMC4 enhances autophagic flux and lysosomal clearance, broadly reducing α‐synuclein aggregates.
Sandesh Neupane +11 more
wiley +1 more source
Ultrafast photonic reinforcement learning based on laser chaos
Scientific Reports, 2017 Reinforcement learning involves decision making in dynamic and uncertain environments and constitutes an important element of artificial intelligence (AI).
Makoto Naruse +3 more
doaj +1 more source
Algorithmic Randomness, Quantum Physics, and Incompleteness [PDF]
, 2004 Is randomness in quantum mechanics “algorithmically random”? Is there any relation between Heisenberg’s uncertainty relation and G¨odel’s incompleteness? Can quantum randomness be used to trespass the Turing’s barrier?
Calude, C.S
core
FEBS Open Bio, EarlyView.Evolutionary analysis across 32 placental mammals identified positive selection at residues H148 and W149 in the immune receptor FcγR1. Ancestral reconstruction combined with molecular dynamics simulations reveals how these mutations may influence receptor structure and dynamics, providing insight into the evolution of antibody recognition and immune ...
David A. Young +7 more
wiley +1 more source
FEBS Open Bio, EarlyView.The dFoCC pipeline starts with observed DED and resting‐state coordinates, which are then used to generate a library of triggered states. Correlation analysis of the calculated DED features of each candidate vs observed DED permits quantitative evaluation of candidate structural quality.
Meng Iao Fong +3 more
wiley +1 more source
RoundMi: A quantitative method to analyze mitochondrial morphology in mitotic cells
FEBS Open Bio, EarlyView.RoundMi is a workflow for rapid analysis of mitochondrial morphology in mitotic cells. By combining adaptive preprocessing with automated segmentation and quantification, it enables accurate measurements from single focal plane images, reducing acquisition time and computational demands while remaining compatible with high‐throughput fixed and live ...
Elmira Parvindokht Bararpour +2 more
wiley +1 more source