Results 61 to 70 of about 3,942,699 (304)

Evolutionary programming with q-Gaussian mutation for dynamic optimization problems [PDF]

, 2008
This article is posted here with permission from IEEE - Copyright @ 2008 IEEEThe use of evolutionary programming algorithms with self-adaptation of the mutation distribution for dynamic optimization problems is investigated in this paper. In the proposed
Yang, S, Tinos, Renato, Shengxiang Yang, Tinos, R, Renato Tinos, Yang, Shengxiang   +5 more
core   +1 more source

From mice to humans—divergent strategies for intestinal homeostasis and regeneration

FEBS Letters, EarlyView.
Recent advances such as organoid genome editing, xenotransplantation, imaging, and whole‐genome sequencing have enabled direct studies of human intestinal stem cells (ISCs). These studies reveal species‐specific features, including slower ISC proliferation, distinct injury responses, slower somatic mutation accumulation in humans, and an inverse ...
Keiko Ishikawa, Shinya Sugimoto, Toshiro Sato   +2 more
wiley   +1 more source

Design and analysis strategies for robust microbiome ageing research

FEBS Letters, EarlyView.
The gut microbiome changes with age and associates with age‐related morbidity and mortality, establishing it as a potential biomarker and intervention target for ageing. Realising this potential requires methodological rigour, yet distinguishing biological signals from methodological artefacts remains challenging across cohorts. This review provides an
Mark Olenik, İsmail Güderer, Yi Wang, Tayyaba Alvi, Prasoon Pandey, Handan Melike Dönertaş   +5 more
wiley   +1 more source

Algebraic Dynamic Programming [PDF]

, 2002
Dynamic programming is a classic programming technique, applicable in a wide variety of domains, like stochastic systems analysis, operations research, combinatorics of discrete structures, flow problems, parsing with ambiguous grammars, or biosequence analysis. Yet, no methodology is available for designing such algorithms. The matrix recurrences that
Giegerich, Robert, Meyer, Carsten
openaire   +2 more sources

Dynamic programming for multi-view disparity/depth estimation [PDF]

, 2006
novel algorithm for disparity/depth estimation from multi-view images is presented. A dynamic programming approach with window-based correlation and a novel cost function is proposed..
Anantrasirichai, N, Redmill, DW, Canagarajah, CN, Bull, DR   +3 more
core   +1 more source

ABL kinase‐dependent phosphorylation of SH proteins promotes their direct interaction with CRK family SH2 domains

FEBS Letters, EarlyView.
CT10 regulator of kinase (CRK) and CRK‐Like (CRKL) are signaling adaptors driving cell adhesion, motility, differentiation, and proliferation. SH2‐domain containing (SH) proteins are enriched in YXXP motifs which when phosphorylated create preferred binding sites for CRK family SH2 domains.
Phoebe M. Cousens, Brendan W. Chandler, Anna M. Schmoker, Jaye L. Weinert, Charlotte A. Kearns, Warren T. Yacawych, Amila Šemić, Alicia M. Ebert, Bryan A. Ballif   +8 more
wiley   +1 more source

Microbiome‐blood–brain barrier interactions in aging — mechanisms and therapeutic potential

FEBS Letters, EarlyView.
Aging reshapes the gut microbiome (↓SCFA‐producing commensals; ↑pro‐inflammatory outputs), shifting circulating metabolites (↓SCFAs; ↑LPS, ↑TMAO, ↑PAA) that act at the BBB to increase nonspecific transcytosis, alter transport, and promote astrocyte reactivity, heightening brain vulnerability.
Daniel Cuervo‐Zanatta, Hari Baskar Balasubramanian, Amir Pasokh, Marietta Zille   +3 more
wiley   +1 more source

Spatial cluster detection using dynamic programming

BMC Medical Informatics and Decision Making, 2012
Background The task of spatial cluster detection involves finding spatial regions where some property deviates from the norm or the expected value.
Sverchkov Yuriy, Jiang Xia, Cooper Gregory F   +2 more
doaj   +1 more source

Output‐feedback stochastic model predictive control of chance‐constrained nonlinear systems

IET Control Theory & Applications, 2023
This study covers the output‐feedback model predictive control (MPC) of nonlinear systems subjected to stochastic disturbances and state chance constraints. The stochastic optimal control problem is solved in a stochastic dynamic programming fashion, and
Jingyu Zhang, Toshiyuki Ohtsuka
doaj   +1 more source

Regularization by dynamic programming [PDF]

Journal of Inverse and Ill-posed Problems, 2007
We investigate continuous regularization methods for linear inverse problems of static and dynamic type. These methods are based on dynamic programming approaches for linear quadratic optimal control problems. We prove regularization properties and also obtain rates of convergence for our methods.
Stefan Kindermann 0001, A. Leitao
openaire   +2 more sources