Results 111 to 120 of about 217,546 (313)

CORRECTION OF DEPENDENT ERRORS BY THE TURBOcodec based ON ATTACHED evenly convolutional codes

open access: yesDoklady Belorusskogo gosudarstvennogo universiteta informatiki i radioèlektroniki, 2019
The organization methods of dependent (packet) error correction by the turbocodecs based both on a sub systematic convolutional codes with uniform threshold decoding algorithm and recursive systematic convolutional codes are considered. The effectiveness
E. G. Makeichik   +2 more
doaj  

LightRoseTTA: High‐Efficient and Accurate Protein Structure Prediction Using a Light‐Weight Deep Graph Model

open access: yesAdvanced Science, EarlyView.
Accurately predicting protein structure is of great significance in biological research. LightRoseTTA, a light‐weight deep graph network, to achieve prediction for proteins is presented. Notably, three highlights are possessed by LightRoseTTA: i) high‐accurate structure prediction for proteins; ii) high‐efficient training and inference; and iii) low ...
Xudong Wang   +7 more
wiley   +1 more source

Duality between Multidimensional Convolutional Codes and Systems [PDF]

open access: yesarXiv, 1999
Multidimensional convolutional codes generalize (one dimensional) convolutional codes and they correspond under a natural duality to multidimensional systems widely studied in the systems literature.
arxiv  

Structural Diversity of Mitochondria in the Neuromuscular System across Development Revealed by 3D Electron Microscopy

open access: yesAdvanced Science, EarlyView.
Mitochondria across the entire neuromuscular system have been comprehensively reconstructed at different developmental stages using 3D electron microscopy. Fundamental structural principles related to synaptic function are preserved across development, and these morphologies are adapted to ensure effective neural circuit function.
J. Alexander Bae   +9 more
wiley   +1 more source

On Convolutional Coupled Codes [PDF]

open access: yesAEU - International Journal of Electronics and Communications, 2004
This thesis is about convolutional coupled codes - codes constructed via concatenation of several outer systematic convolutional encoders and several inner systematic block encoders linked by divers interleavers. The code is nonsystematic, since only the redundancy produced from the outer and inner encoders is transmitted.
openaire   +2 more sources

Epileptiform Activity and Seizure Risk Follow Long‐Term Non‐Linear Attractor Dynamics

open access: yesAdvanced Science, EarlyView.
This study leverages the HAVOK framework to model long‐term, nonlinear attractor dynamics underlying epileptiform activity and seizure risk in epilepsy patients. By identifying key forcing mechanisms driving chaotic transitions, the findings improve seizure risk forecasting over multi‐day cycles and provide a pathway for personalized, data‐driven ...
Richard E Rosch   +4 more
wiley   +1 more source

Different coding characteristics between flight and freezing in dorsal periaqueductal gray of mice during exposure to innate threats

open access: yesAnimal Models and Experimental Medicine, Volume 5, Issue 6, Page 491-501, December 2022., 2022
Flight and freezing are two vital defensive behaviors in the process of avoiding natural enemies in mice. We investigated the neural activity in dPAG nuclei of mice under two defensive behaviors, and found different coding features between flight and freezing behaviors. Abstract Background Flight and freezing are two vital defensive behaviors that mice
Denghui Liu   +5 more
wiley   +1 more source

On negacyclic MDS-convolutional codes

open access: yesLinear Algebra and its Applications, 2014
New families of classical and quantum optimal negacyclic convolutional codes are constructed in this paper. This optimality is in the sense that they attain the classical (quantum) generalized Singleton bound. The constructions presented in this paper are performed algebraically and not by computational search.
openaire   +3 more sources

scHeteroNet: A Heterophily‐Aware Graph Neural Network for Accurate Cell Type Annotation and Novel Cell Detection

open access: yesAdvanced Science, EarlyView.
scHeteroNet) is a novel graph neural network model that explicitly addresses heterophily in single‐cell sequencing data enabling accurate cell type annotation and novel cell type discovery. By leveraging heterophily‐aware message passing and novelty propagation mechanisms, scHeteroNet achieves superior performance in both cell annotation and detection ...
Jiacheng Liu   +7 more
wiley   +1 more source

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