Results 81 to 90 of about 549,366 (277)
Wasserstein Distance Guided Representation Learning for Domain Adaptation
, 2018 Domain adaptation aims at generalizing a high-performance learner on a target domain via utilizing the knowledge distilled from a source domain which has a different but related data distribution.
Qu, Yanru +3 more
core +1 more source
Cell wall target fragment discovery using a low‐cost, minimal fragment library
FEBS Letters, EarlyView.LoCoFrag100 is a fragment library made up of 100 different compounds. Similarity between the fragments is minimized and 10 different fragments are mixed into a single cocktail, which is soaked to protein crystals. These crystals are analysed by X‐ray crystallography, revealing the binding modes of the bound fragment ligands.
Kaizhou Yan +5 more
wiley +1 more source
FEBS Letters, EarlyView.We reconstituted Synechocystis glycogen synthesis in vitro from purified enzymes and showed that two GlgA isoenzymes produce glycogen with different architectures: GlgA1 yields denser, highly branched glycogen, whereas GlgA2 synthesizes longer, less‐branched chains.
Kenric Lee +3 more
wiley +1 more source
Open DGML: Intrusion Detection Based on Open-Domain Generation Meta-Learning
Applied SciencesNetwork security is crucial for national infrastructure, but the increasing number of network intrusions poses significant challenges. To address this issue, we propose Open DGML, a framework based on open-domain generalization meta-learning for ...
Kaida Jiang +4 more
doaj +1 more source
Soft Prompt Generation for Domain Generalization
Large pre-trained vision language models (VLMs) have shown impressive zero-shot ability on downstream tasks with manually designed prompt. To further adapt VLMs to downstream tasks, soft prompt is proposed to replace manually designed prompt, which undergoes fine-tuning based on specific domain data.
Bai, Shuanghao +4 more
openaire +2 more sources
Domain Generalization for Domain-Linked Classes
, 2023 Domain generalization (DG) focuses on transferring domain-invariant knowledge from multiple source domains (available at train time) to an, a priori, unseen target domain(s). This requires a class to be expressed in multiple domains for the learning algorithm to break the spurious correlations between domain and class.
Kaai, Kimathi +2 more
openaire +2 more sources
Structural biology of ferritin nanocages
FEBS Letters, EarlyView.Ferritin is a conserved iron‐storage protein that sequesters iron as a ferric mineral core within a nanocage, protecting cells from oxidative damage and maintaining iron homeostasis. This review discusses ferritin biology, structure, and function, and highlights recent cryo‐EM studies revealing mechanisms of ferritinophagy, cellular iron uptake, and ...
Eloise Mastrangelo, Flavio Di Pisa
wiley +1 more source
Structural insights into an engineered feruloyl esterase with improved MHET degrading properties
FEBS Letters, EarlyView.A feruloyl esterase was engineered to mimic key features of MHETase, enhancing the degradation of PET oligomers. Structural and computational analysis reveal how a point mutation stabilizes the active site and reshapes the binding cleft, expading substrate scope.
Panagiota Karampa +5 more
wiley +1 more source
DANSK: Domain Generalization of Danish Named Entity Recognition
Northern European Journal of Language TechnologyNamed entity recognition is an important application within Danish NLP, essential within both industry and research. However, Danish NER is inhibited by a lack coverage across domains and entity types.
Kenneth Enevoldsen +2 more
doaj +1 more source
The Peierls-Nabarro model as a limit of a Frenkel-Kontorova model [PDF]
, 2010 We study a generalization of the fully overdamped Frenkel-Kontorova model in dimension $n\geq 1.$ This model describes the evolution of the position of each atom in a crystal, and is mathematically given by an infinite system of coupled first order ODEs.
Fino, Ahmad +2 more
core +5 more sources