Results 51 to 60 of about 7,585 (289)
Time‐resolved X‐ray solution scattering captures how proteins change shape in real time under near‐native conditions. This article presents a practical workflow for light‐triggered TR‐XSS experiments, from data collection to structural refinement. Using a calcium‐transporting membrane protein as an example, the approach can be broadly applied to study ...
Fatemeh Sabzian‐Molaei +3 more
wiley +1 more source
In this study, we developed a deep learning method for mitotic figure counting in H&E‐stained whole‐slide images and evaluated its prognostic impact in 13 external validation cohorts from seven different cancer types. Patients with more mitotic figures per mm2 had significantly worse patient outcome in all the studied cancer types except colorectal ...
Joakim Kalsnes +32 more
wiley +1 more source
Increasing Robustness of True Random Number Generators against Attacks
Random number generation is a critical issue in numerous cryptographic applications: it is used for generation of initialization vectors, challenges, nonces and confidential keys.
Haddad, Patrick +3 more
core +1 more source
Locking phenomenon on ring oscillators used in True Random Number Generators
International audienceTo ensure the security of electronic devices, true random numbers are required by cryptographic systems. Several True Random Number Generators (TNRG) designs have been proposed, each with different characteritics and implementation ...
Fischer, Viktor +4 more
core +5 more sources
Low Cost and Precise Jitter Measurement Method for TRNG Entropy Assessment
Random number generators and specifically true random number generators (TRNGs) are essential in cryptography. TRNGs implemented in logic devices usually exploit the time instability of clock signals generated in freely running oscillators as source of ...
Florent Bernard +4 more
doaj +1 more source
True Random Number Generators on IQM Spark
Random number generation is fundamental for many modern applications including cryptography, simulations and machine learning. Traditional pseudo-random numbers may offer statistical unpredictability, but are ultimately deterministic. On the other hand, True Random Number Generation (TRNG) offers true randomness.
Andrzej Gnatowski +3 more
openaire +2 more sources
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
True random number generators (TRNGs) allow the generation of true random bit sequences, guaranteeing the unpredictability and perfect balancing of the generated values.
Andrea Stanco +5 more
doaj +1 more source
Evolutionarily divergent DUF4465 domains have a common vitamin B12‐binding function
We show that DUF4465 family proteins, widespread across bacteria from gut microbiomes, hydrothermal vents, and soil, share a common vitamin B12‐binding function. These augmented β‐jellyroll proteins bind vitamin B12 via extended loops. Our findings establish sequence‐diverse DUF4465 proteins as a widespread class of B12‐binding proteins, highlighting ...
Charlea Clarke +4 more
wiley +1 more source
Design and Analysis of Digital True Random Number Generator
Random number generator is a key component for strengthening and securing the confidentiality of electronic communications. Random number generators can be divided as either pseudo random number generators or true random number generators.
Yadav, Avantika
core +1 more source

