Results 91 to 100 of about 537,689 (239)

Generalizing the Gaussian Network Model: Spanning-Tree Thermodynamics Shows Entropy-Driven KRAS Activation. [PDF]

Proteins
ABSTRACT The GTPase KRAS executes a conformational switch between a GTP‐bound active state and a GDP‐bound inactive state, a process central to oncogenic signaling. However, the structural basis of this switching at the level of residue‐contact organization remains incompletely characterized by traditional binary structural models.
Ciftci FS, Erman B.
europepmc   +2 more sources

Privacy‐Preserving Data‐Driven Distributed MPC for Heterogeneous Nonlinear Multi‐Agent Systems

International Journal of Robust and Nonlinear Control, EarlyView.
ABSTRACT Distributed model predictive control (DMPC) is a cornerstone for coordinating multi‐agent systems, yet simultaneously ensuring data privacy, handling unknown nonlinear dynamics, and managing heterogeneous constraints remains an open challenge.
Mahmood Mazare, Hossein Ramezani
wiley   +1 more source

Frequency Shaping for Improving a Trade‐Off Between Control and Privacy Performance: Beyond Differential Privacy

International Journal of Robust and Nonlinear Control, EarlyView.
ABSTRACT In privacy protection of control systems, a trade‐off between control performance and privacy level is often pointed out. Our goal in this paper is to improve this trade‐off by shaping the frequency of noise added for privacy protection when the control objective is to track a reference signal, which is taken as a piece of information whose ...
Rintaro Watanabe, Yu Kawano, Nobutaka Wada, Ming Cao   +3 more
wiley   +1 more source

Fusion or Confusion? Assessing the Impact of Visible‐Thermal Image Fusion for Automated Wildlife Detection

Remote Sensing in Ecology and Conservation, EarlyView.
This study evaluates the performances of synchronous aerial visible (VIS) and thermal infrared (TIR) imagery for detecting great blue heron (Ardea herodias) nests and individuals using a YOLO11n model. VIS and TIR images were automatically aligned using deep learning, and both early and late fusion approaches were tested.
Camille Dionne‐Pierre, Samuel Foucher, Jérôme Théau, Jérôme Lemaître, Patrick Charbonneau, Maxime Brousseau, Mathieu Varin   +6 more
wiley   +1 more source

Closeness Laplacian and closeness signless Laplacian energies of non-commuting graph for dihedral groups

This research investigates the relationship between algebra and graph theory, specifically how algebra facilitates graph theory. Associating matrices with graphs introduces the concept of graph energies.
Abdurahim, Abdurahim, Hakim Maharani, Andika Ellena Saufika, Nawawi, Athirah, Dani, Ifan Hasnan, Romdhini, Mamika Ujianita, Al-Sharqi, Faisal   +5 more
core   +1 more source

Robust Weighted Timed Automata and Games [PDF]

, 2013
Weighted timed automata extend timed automata with cost variables that can be used to model the evolution of various quantities. Although cost-optimal reachability is decidable (in polynomial space) on this model, it becomes undecidable on weighted ...
Markey, Nicolas, Patricia Bouyer, Ocan Sankur, Bouyer, Patricia, Sankur, Ocan, Nicolas Markey   +5 more
core   +1 more source

Rapid and Efficient Affinity Isolation of Engineered Extracellular Vesicles Encapsulating Functional Proteins via Internal Twin‐Strep Tetraspanin Tagging

Small, EarlyView.
Structure‐guided internal twin‐Strep tagging of the tetraspanins CD63 or CD9 enables rapid and efficient antibody‐free affinity isolation of engineered extracellular vesicles (EVs) using Strep technology while allowing luminal protein loading. The approach removes over 96% of contaminants, separates tagged EVs from coexisting viral particles, and ...
Minh‐Tu Pham, Jona Benjamin Krohn, Janis Meyer, Christian Ritter, Martin Schneider, Dominic Helm, Dario Frey, Kleopatra Rapti, Uta Haselmann‐Weiss, Elif Toprak, Viet Loan Dao Thi, Florian Leuschner, Dirk Grimm, Karl Rohr, Ralf Bartenschlager   +14 more
wiley   +1 more source

Image and video analysis using graph neural network for Internet of Medical Things and computer vision applications

CAAI Transactions on Intelligence Technology, EarlyView.
Abstract Graph neural networks (GNNs) have revolutionised the processing of information by facilitating the transmission of messages between graph nodes. Graph neural networks operate on graph‐structured data, which makes them suitable for a wide variety of computer vision problems, such as link prediction, node classification, and graph classification.
Amit Sharma, Ashutosh Sharma, Alexey Tselykh, Alexander Bozhenyuk, Byung‐Gyu Kim   +4 more
wiley   +1 more source

Weighted Total Variation for Hyperspectral Image Denoising Based on Hyper-Laplacian Scale Mixture Distribution

Remote Sensing
Conventional total variation (TV) regularization methods based on Laplacian or fixed-scale Hyper-Laplacian priors impose uniform sparsity penalties on gradients.
Xiaoyu Yu, Jianli Zhao, Sheng Fang, Tianheng Zhang, Liang Li, Xinyue Huang   +5 more
doaj   +1 more source

Enhancing generalized spectral clustering with embedding Laplacian graph regularization

CAAI Transactions on Intelligence Technology, EarlyView.
Abstract An enhanced generalised spectral clustering framework that addresses the limitations of existing methods by incorporating the Laplacian graph and group effect into a regularisation term is presented. By doing so, the framework significantly enhances discrimination power and proves highly effective in handling noisy data.
Hengmin Zhang, Jian Yang, Bob Zhang, Yang Tang, Wenli Du, Bihan Wen   +5 more
wiley   +1 more source