Results 201 to 210 of about 574,210 (309)

Research on traffic representation in network anomaly detection

Tongxin xuebao
Aiming to address the problem of information loss in traffic representation for network anomaly detection, the impact of feature information dimension of different traffic representation on anomaly detection performance was analyzed from the perspective ...
SUN Jianwen, ZHANG Bin, CHANG Heyu
doaj  

Self-organizing network representation of human heart. [PDF]

Chaos
Liu R, Yang H.
europepmc   +1 more source

A light‐triggered Time‐Resolved X‐ray Solution Scattering (TR‐XSS) workflow with application to protein conformational dynamics

FEBS Open Bio, EarlyView.
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, Fredrik Orädd, Konstantinos Magkakis, Magnus Andersson   +3 more
wiley   +1 more source

Natural sounds can be reconstructed from human neuroimaging data using deep neural network representation. [PDF]

PLoS Biol
Park JY, Tsukamoto M, Tanaka M, Kamitani Y.   +3 more
europepmc   +1 more source

Heterogeneous Network Representation Learning: A Unified Framework with Survey and Benchmark. [PDF]

IEEE Trans Knowl Data Eng, 2022
Yang C, Xiao Y, Zhang Y, Sun Y, Han J.
europepmc   +1 more source

Applicability of mitotic figure counting by deep learning: a development and pan‐cancer validation study

FEBS Open Bio, EarlyView.
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, Maria X. Isaksen, Frida Julbø, Manohar Pradhan, Andreas Kleppe, Sepp De Raedt, Ole‐Johan Skrede, Turid Torheim, John Arne Nesheim, Hans Martin Mohn, Hanne A. Askautrud, Karolina Cyll, Wanja Kildal, Emma Rewcastle, Melinda Lillesand, Vebjørn Kvikstad, Emiel Janssen, Robert Jones, Odd Terje Brustugun, Bjørn Brennhovd, Erik Skaaheim Haug, Lill‐Tove Rasmussen Busund, Elin Richardsen, Sigve Andersen, Tom Dønnem, Kristina Lindemann, Gunnar Kristensen, Neil A. Shepherd, Marco Novelli, Knut Liestøl, David Kerr, Håvard E. Danielsen, Tarjei S. Hveem   +32 more
wiley   +1 more source

DeeWaNA: An Unsupervised Network Representation Learning Framework Integrating Deepwalk and Neighborhood Aggregation for Node Classification. [PDF]

Entropy (Basel)
Xu X, Lu X, Wang J.
europepmc   +1 more source

Integrating Multimodal and Longitudinal Neuroimaging Data with Multi-Source Network Representation Learning. [PDF]

Neuroinformatics, 2022
Zhang W, Braden BB, Miranda G, Shu K, Wang S, Liu H, Wang Y.   +6 more
europepmc   +1 more source

Iron homeostasis disruption and lipid peroxidation in skeletal muscle during short‐term immobilization

FEBS Open Bio, EarlyView.
14‐day casting‐induced immobilization reduced gastrocnemius muscle mass and increased non‐heme iron and ferritin heavy chain levels. Despite iron accumulation, transferrin receptor 1 and iron regulatory protein 2 were paradoxically upregulated. Lipid peroxidation was elevated without compensatory antioxidant responses.
Haruka Yokogawa, Kazuhiko Higashida, Naoya Nakai   +2 more
wiley   +1 more source

Relieving the Incompatibility of Network Representation and Classification for Long-Tailed Data Distribution.

Comput Intell Neurosci, 2021
Hu H, Gao M, Wu M.
europepmc   +1 more source