Results 131 to 140 of about 1,884,911 (319)

Stochastic Constraint Programming

, 2008
To model combinatorial decision problems involving uncertainty and probability, we introduce stochastic constraint programming. Stochastic constraint programs contain both decision variables (which we can set) and stochastic variables (which follow a ...
Walsh, Toby
core   +1 more source

Use of Symptomatic Drug Treatment for Fatigue in Multiple Sclerosis and Patterns of Work Loss

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective To describe the use of central stimulants and amantadine for fatigue in MS and evaluate a potential association with reduced work loss in people with MS. Methods We conducted a nationwide, matched, register‐based cohort study in Sweden (2006 to 2023) using national registers with prospective data collection.
Simon Englund, Johan Reutfors, Thomas Frisell, Fredrik Piehl   +3 more
wiley   +1 more source

A 50-spin surface acoustic wave Ising machine

Communications Physics
Time-multiplexed spinwave Ising Machines have unveiled a route towards miniaturized and low-cost combinatorial optimization solvers but are constrained in the number of spins by nonlinear spinwave dispersion.
Artem Litvinenko, Roman Khymyn, Roman Ovcharov, Johan Åkerman   +3 more
doaj   +1 more source

Handy formulas for binomial moments

Modern Stochastics: Theory and Applications
Despite the relevance of the binomial distribution for probability theory and applied statistical inference, its higher-order moments are poorly understood.
Maciej Skorski
doaj   +1 more source

Discovery and Targeted Proteomic Studies Reveal Striatal Markers Validated for Huntington's Disease

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Clinical trials for Huntington's disease (HD) enrolling persons before clinical motor diagnosis (CMD) lack validated biomarkers. This study aimed to conduct an unbiased discovery analysis and a targeted examination of proteomic biomarkers scrutinized by clinical validation. Methods Cerebrospinal fluid was obtained from PREDICT‐HD and
Daniel Chelsky, Cara Joyce, H. Jeremy Bockholt, Paul A. Rudnick, William H. Adams, Fiona McAllister, Justin W. Smock, Michael A. Newton, Jane S. Paulsen   +8 more
wiley   +1 more source

Entropy computing, a paradigm for optimization in open photonic systems

Communications Physics
Finding better solutions to combinatorial optimization problems could have a large positive impact on many real-world application areas, such as logistics. For this reason, significant efforts have been made to design novel optimization paradigms.
Lac Nguyen, Mohammad-Ali Miri, R. Joseph Rupert, Wesley Dyk, Sam Wu, Nick Vrahoretis, Irwin Huang, Milan Begliarbekov, Nicholas Chancellor, Uchenna Chukwu, Pranav Mahamuni, Cesar Martinez-Delgado, David Haycraft, Carrie Spear, Joel Russell Huffman, Yong Meng Sua, Yu-Ping Huang   +16 more
doaj   +1 more source

Predicting Epileptogenic Tubers in Patients With Tuberous Sclerosis Complex Using a Fusion Model Integrating Lesion Network Mapping and Machine Learning

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Accurate localization of epileptogenic tubers (ETs) in patients with tuberous sclerosis complex (TSC) is essential but challenging, as these tubers lack distinct pathological or genetic markers to differentiate them from other cortical tubers.
Tinghong Liu, Qi Wang, Suhui Kuang, Dezhi Cao, Ping Ding, Shaohui Zhang, Haihua Wei, Zhirong Wei, Jinshan Xu, Xinyu Huang, Bing Liu, Shuli Liang   +11 more
wiley   +1 more source

Bayesian Estimation Improves Prediction of Outcomes After Epilepsy Surgery

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT We estimated the statistical power of studies predicting seizure freedom after epilepsy surgery. We extracted data from a Cochrane meta‐analysis. The median power across all studies was 14%. Studies with a median sample size or less (n ≤ 56) and a statistically significant result exaggerated the true effect size by a factor of 5.4, while the ...
Adam S. Dickey, Vineet Reddy, Ammar A. Rashied, Nigel P. Pedersen, Robert T. Krafty   +4 more
wiley   +1 more source

Connection between single-layer quantum approximate optimization algorithm interferometry and thermal distribution sampling

Frontiers in Quantum Science and Technology
The quantum approximate optimization algorithm (QAOA) was originally proposed to find approximate solutions to combinatorial optimization problems on quantum computers. However, the algorithm has also attracted interest for sampling purposes since it was
Pablo Díez-Valle, Diego Porras, Juan José García-Ripoll   +2 more
doaj   +1 more source

On the decoder error probability of linear codes [PDF]

By using coding and combinatorial techniques, an approximate formula for the weight distribution of decodable words of most linear block codes is evaluated.
Cheung, K.-M.
core   +1 more source