Results 81 to 90 of about 1,144,226 (279)

Domain Adaptation with Sentiment Domain Adapter

The field of domain adaptation, particularly in cross-domain sentiment classification, leverages labeled data from a source domain alongside unlabeled or sparsely labeled data from a target domain. The objective is to enhance performance in the target domain by mitigating the discrepancies in data distributions.
Aiden Carter, Wyne Nasir, Ethan Parker
openaire   +1 more source

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

Agile Domain Adaptation

2019 International Joint Conference on Neural Networks (IJCNN), 2019
Domain adaptation investigates the problem of leveraging knowledge from a well-labeled source domain to an unlabeled target domain, where the two domains are drawn from different data distributions. Because of the distribution shifts, different target samples have distinct degrees of difficulty in adaptation.
Li, Jingjing, Jing, Mengmeng, Xie, Yue, Lu, Ke, Huang, Zi   +4 more
openaire   +2 more sources

Transferrin receptor 1‐mediated iron uptake supports thermogenic activation in human cervical‐derived adipocytes

FEBS Letters, EarlyView.
In this study, we found that human cervical‐derived adipocytes maintain intracellular iron level by regulating the expression of iron transport‐related proteins during adrenergic stimulation. Melanotransferrin is predicted to interact with transferrin receptor 1 based on in silico analysis.
Rahaf Alrifai, Mizuki Seo, Gyath Karadsheh, Fachrur Rizal Mahendra, Máté Á Demény, Ferenc Győry, János András Mótyán, László Fésüs, Endre Kristóf, Rini Arianti   +9 more
wiley   +1 more source

Category-Level Adversaries for Semantic Domain Adaptation

IEEE Access, 2019
Recent advances in deep learning, especially deep convolutional neural networks, have led to great performance improvement over semantic segmentation systems. Unfortunately, training deep neural networks (DNNs) requires a humongous amount of labeled data,
Congcong Ruan, Wei Wang, Haifeng Hu, Dihu Chen   +3 more
doaj   +1 more source

Heuristic Domain Adaptation

, 2020
In visual domain adaptation (DA), separating the domain-specific characteristics from the domain-invariant representations is an ill-posed problem. Existing methods apply different kinds of priors or directly minimize the domain discrepancy to address this problem, which lack flexibility in handling real-world situations.
Cui, Shuhao, Jin, Xuan, Wang, Shuhui, He, Yuan, Huang, Qingming   +4 more
openaire   +2 more sources

Pareto Domain Adaptation

, 2021
Domain adaptation (DA) attempts to transfer the knowledge from a labeled source domain to an unlabeled target domain that follows different distribution from the source. To achieve this, DA methods include a source classification objective to extract the source knowledge and a domain alignment objective to diminish the domain shift, ensuring knowledge ...
Lv, Fangrui, Liang, Jian, Gong, Kaixiong, Li, Shuang, Liu, Chi Harold, Li, Han, Liu, Di, Wang, Guoren   +7 more
openaire   +2 more sources

The planar cell polarity protein Vangl2 interacts with the PDZ‐domains of Scribble but not with a unique PDZ‐like domain in Inturned

FEBS Letters, EarlyView.
Structural and biochemical characterisations show that the planar cell polarity (PCP) protein Inturned harbours a unique PDZ‐like domain that does not bind canonical PDZ‐binding motifs (PBMs) like that of another PCP protein Vangl2. In contrast, the apical‐basal polarity protein Scribble contains four PDZ domains that bind Vangl2, but one PDZ domain ...
Stephan Wilmes, Jan Brysch, Carmen Gelze, Lilli Meier, Daniel Kümmel   +4 more
wiley   +1 more source

Spatial–Temporal Temperature Forecasting Using Deep-Neural-Network-Based Domain Adaptation

Atmosphere
Accurate temperature forecasting is critical for various sectors, yet traditional methods struggle with complex atmospheric dynamics. Deep neural networks (DNNs), especially transformer-based DNNs, offer potential advantages, but face challenges with ...
Vu Tran, François Septier, Daisuke Murakami, Tomoko Matsui   +3 more
doaj   +1 more source

Calpain small subunit homodimerization is robust and calcium‐independent

FEBS Letters, EarlyView.
Calpains dimerize via penta‐EF‐hand (PEF) domains. Using single‐molecule force spectroscopy, we measured the strength and kinetics of PEF–PEF homodimer binding. The interaction is robust, shows a transient conformational step before dissociation, and remains largely insensitive to Ca2+.
Nesha May O. Andoy, Trina Dykstra‐MacPherson, Mathias A. Bell, Peter L. Davies, Ruby May A. Sullan   +4 more
wiley   +1 more source