Results 71 to 80 of about 59,151 (296)

A few-shot fine-grained image recognition method [PDF]

Bulletin of the Polish Academy of Sciences: Technical Sciences, 2023
Jianwei Wang, Deyun Chen
doaj   +1 more source

pH‐mediated activation of the lysosomal arginine sensor SLC38A9

FEBS Letters, EarlyView.
Cells monitor nutrient levels via the lysosomal transporter SLC38A9 to activate the mechanistic target of rapamycin complex 1 (mTORC1). This study reveals that SLC38A9 function is regulated by pH. We identified histidine 544 as a critical pH sensor that undergoes conformational changes to control amino acid efflux from lysosomes; therefore, it ...
Xuelang Mu, Ampon Sae Her, Tamir Gonen
wiley   +1 more source

An unexpected alternative viologen electron mediator site in tungsten‐containing formate dehydrogenase

FEBS Letters, EarlyView.
An unexpected alternative interaction site for ethyl viologen was identified in formate dehydrogenase 1 from Methylorubrum extorquens. Combined mutagenesis, kinetic analysis, and docking revealed that aromatic residues near an iron–sulfur cluster enable flavin mononucleotide‐independent electron transfer, offering a framework for engineering improved ...
Eleni G. Poloniataki, Yong Hwan Kim
wiley   +1 more source

Reasoning-Enhanced Few-Shot Human Activity Recognition via Visual Reinforcement Learning

IEEE Access
Most existing human activity recognition (HAR) models rely on large-scale labeled datasets for training, which makes it difficult for HAR models to recognize activity classes unseen during training when only a few samples are available.
Wenqi Zheng, Yutaka Arakawa
doaj   +1 more source

Task-Adaptive Negative Envision for Few-Shot Open-Set Recognition

, 2022
We study the problem of few-shot open-set recognition (FSOR), which learns a recognition system capable of both fast adaptation to new classes with limited labeled examples and rejection of unknown negative samples.
Huang, Shiyuan, Chang, Shih-Fu, Han, Guangxing, Ma, Jiawei   +3 more
core  

Electron transfer between complexes III and IV in S. cerevisiae mitochondrial membranes

FEBS Letters, EarlyView.
Mitochondrial oxidative phosphorylation in S. cerevisiae mitoplasts is limited by complex IV catalytic capacity, rather than two‐dimensional cytochrome c diffusion. At physiological cytochrome c : supercomplex ratios at salinity equivalent to that of 20 mm monovalent salt, activity is maximized, indicating that this low ionic strength accurately mimics
Ana Paula Lobez, Mikael Oliveberg, Peter Brzezinski   +2 more
wiley   +1 more source

Few-Shot Visual Recognition

, 2022
A lot of training data is needed for deep learning models to have a good performance • Few-shot learning aims to tackle this issue • Few-shot learning models are given limited novel data per class for ...
Kian, Ming Lim, Wei, Han Liu, Chin, Poo Lee, Thian, Song Ong   +3 more
core  

Three phosphatase families form a community: The phosphohydrolases that act upon inositol pyrophosphates

FEBS Letters, EarlyView.
Inositol pyrophosphates are energy‐rich signaling molecules that perform critical functions in cells. Three different families of phosphatases hydrolyze the β phosphate of the inositol pyrophosphate molecules: two have narrow specificities and one is promiscuous.
Ronda J. Rolfes
wiley   +1 more source

TRAIL‐PEG‐Apt‐PLGA nanosystem as an aptamer‐targeted drug delivery system potential for triple‐negative breast cancer therapy using in vivo mouse model

Molecular Oncology, EarlyView.
Aptamers are used both therapeutically and as targeting agents in cancer treatment. We developed an aptamer‐targeted PLGA–TRAIL nanosystem that exhibited superior therapeutic efficacy in NOD/SCID breast cancer models. This nanosystem represents a novel biotechnological drug candidate for suppressing resistance development in breast cancer.
Gulen Melike Demirbolat, Aslihan Kucuk, Omer Erdogan, Samed Ozer, Bensu Kozan, Tugba Cuceli, Erkan Gumus, Evrim Cevik, Ozge Cevik   +8 more
wiley   +1 more source

Semi-supervised few-shot learning approach for plant diseases recognition

Plant Methods, 2021
Background Learning from a few samples to automatically recognize the plant leaf diseases is an attractive and promising study to protect the agricultural yield and quality.
Yang Li, Xuewei Chao
doaj   +1 more source