Results 251 to 260 of about 3,942,699 (304)

Investigation of Complement Activation and Cytokine Signatures in AQP4+ NMOSD, MOGAD, and MS

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Aquaporin‐4‐IgG seropositive neuromyelitis optica spectrum disorder (AQP4+ NMOSD), myelin oligodendrocyte glycoprotein antibody‐associated disease (MOGAD), and multiple sclerosis (MS) are pathophysiologically distinct neuroinflammatory disorders. Complement activation is a major mechanism of injury in AQP4+ NMOSD, whereas its role in
Angeliki G. Filippatou, Susana Dominguez‐Penuela, David Acero‐Garces, Georgios Gakis, Matthew D. Smith, Yasmin Resto, Maria Reyes‐Mantilla, Haiwen Chen, Isabella Hernandez, Yana Said, Andrea Salazar‐Camelo, Christina Huynh, Alessia Tassoni, Ted Yednock, Rick Artis, Yaisa Andrews‐Zwilling, Scott D. Newsome, Shiv Saidha, Pavan Bhargava, Ellen M. Mowry, Kathryn C. Fitzgerald, Peter A. Calabresi, Carlos A. Pardo, Elias S. Sotirchos   +23 more
wiley   +1 more source

Stage‐Specific Patterns of Imaging and Non‐Motor Biomarkers in Spinocerebellar Ataxia Type 3

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Advancements in disease‐modifying therapies for spinocerebellar ataxia Type 3 (SCA3) underscore the need for robust biomarkers to monitor disease progression and evaluate treatment efficacy. Although motor phenotypes have been well characterized, less is known about non‐motor and imaging‐based features across different disease stages.
Chun Li, Zhi‐Xian Ye, Xuan‐Yu Chen, Liang‐Liang Qiu, Zhi‐li Chen, Yu‐Sen Qiu, Wei Lin, Ru‐Ying Yuan, Xin‐Tong Yu, Chun‐Yu Huang, Xin‐Yuan Chen, Min‐Ting Lin, Jian‐Ping Hu, Wan‐Jin Chen, Ning Wang, Shao‐Bo Yao, Shi‐Rui Gan, Ying Fu   +17 more
wiley   +1 more source

Discounted Dynamic Programming

The Annals of Mathematical Statistics, 1965
openaire   +2 more sources

Robust Dynamic Programming [PDF]

Mathematics of Operations Research, 2005
In this paper we propose a robust formulation for discrete time dynamic programming (DP). The objective of the robust formulation is to systematically mitigate the sensitivity of the DP optimal policy to ambiguity in the underlying transition probabilities.
Garud N. Iyengar
exaly   +3 more sources

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Aggregation in Dynamic Programming

Operations Research, 1987
Reducing the size of a dynamic program through state aggregation can significantly reduce both the data and the computation time required to solve a problem. We develop a new algorithm that combines state aggregation and disaggregation steps within a single-pass procedure. The solution obtained is automatically feasible for the original problem.
James C. Bean, John R. Birge, Robert L. Smith 0002   +2 more
openaire   +2 more sources

Explainable dynamic programming

Journal of Functional Programming, 2021
Abstract In this paper, we present a method for explaining the results produced by dynamic programming (DP) algorithms. Our approach is based on retaining a granular representation of values that are aggregated during program execution. The explanations that are created from the granular representations can answer questions of why one
Martin Erwig, Prashant Kumar
openaire   +2 more sources

Dynamic programming as multiagent programming

1992
We show that the search technique of dynamic programming models a form of multiagent computation characterized by the interaction of cooperating/competing agents. For this reason, dynamic programming algorithms can be easily implemented in an object-oriented concurrent language environment.
Jean-Marc Andreoli, Remo Pareschi, Marc Bourgois   +2 more
openaire   +2 more sources

Pathwise Dynamic Programming

Mathematics of Operations Research, 2018
We present a novel method for deriving tight Monte Carlo confidence intervals for solutions of stochastic dynamic programming equations. Taking some approximate solution to the equation as an input, we construct pathwise recursions with a known bias. Suitably coupling the recursions for lower and upper bounds ensures that the method is applicable even
Christian Bender, Christian Gärtner, Nikolaus Schweizer   +2 more
openaire   +3 more sources

Dynamic program parallelization

ACM SIGPLAN Lisp Pointers, 1992
Static program analysis limits the performance improvements possible from compile-time parallelization. Dynamic program parallelization shifts a portion of the analysis from complie-time to run-time, thereby enabling optimizations whose static detection is overly expensive or impossible. Lambda tagging
Huelsbergen, Lorenz, Larus, James R.
openaire   +2 more sources