Results 81 to 90 of about 235,048 (260)

Stress History Establishes a Transient Tolerant State That Shapes Antibiotic Survival Upon Resuscitation

Advanced Science, EarlyView.
High‐throughput single‐cell analysis of resuscitating bacteria reveals a starvation‐history‐dependent transiently tolerant subpopulation that survives β$\beta$‐lactam exposure by temporarily reducing growth. Distinct from classical persisters, these actively growing yet dynamically modulated cells dominate survival across clinically relevant antibiotic
Kieran Abbott, Georgeos Hardo, Ruizhe Li, Jack Bradley, Ashraf Zarkan, Somenath Bakshi   +5 more
wiley   +1 more source

CBARS: cluster based classification for activity recognition systems [PDF]

, 2012
Activity recognition focuses on inferring current user activities by leveraging sensory data available on today’s sensor rich environment. Supervised learning has been applied pervasively for activity recognition.
Gaber, Mohamed Medhat, Krishnaswamy, S., Shonali Krishnaswamy, Krishnaswamy, Shonali, Abdallah, Z., Srinivasan, B., Mohamed Medhat Gaber, Gaber, M., Srinivasan, B, Abdallah, Zahraa S., Zahraa Said Abdallah, Bala Srinivasan   +11 more
core   +1 more source

INB3P: A Multi‐Modal and Interpretable Co‐Attention Framework Integrating Property‐Aware Explanations and Memory‐Bank Contrastive Fusion for Blood–Brain Barrier Penetrating Peptide Discovery

Advanced Science, EarlyView.
INB3P is a multimodal framework for blood–brain barrier‐penetrating peptide prediction under extreme data scarcity and class imbalance. By combining physicochemical‐guided augmentation, sequence–structure co‐attention, and imbalance‐aware optimization, it improves predictive performance and interpretability.
Jingwei Lv, Qianyang Wu, Jian Liu, Binlu Yang, Yuanhao Li, Junlin Xu, Yajie Meng, Leyi Wei, Zilong Zhang, Quan Zou, Xiulai Li, Feifei Cui   +11 more
wiley   +1 more source

Semi-Supervised Machine Learning & Deep Learning Models in Crisis-Related Informativeness Classification

, 2019
This study examines the impact of several state-of-the-art Machine Learning and Deep Learning techniques in the context of semi-supervised disaster-related Twitter mining.
Alessandro Rennola (8973167)
core   +1 more source

A Computational Strategy for Identifying Self‐Assembling Food‐Derived Molecules for Antiparasitic Nanotherapy

Advanced Science, EarlyView.
An integrated computational screening strategy identified ursolic acid (UA) and 18β‐glycyrrhetinic acid (18βGA) as a self‐assembling food‐derived molecular pair. The resulting carrier‐free nanoparticles (UA‐18βGA) showed synergistic antiparasitic activity, reduced combined toxicity, and host‐protective anti‐inflammatory effects in zebrafish and murine ...
Shenye Qu, Ting Wang, Jietao Liu, Jiacheng Qin, Bin Yang, Yihang Liu, Pengfei Li, Gaoxue Wang, Fei Ling   +8 more
wiley   +1 more source

A Framework for Context-Aware Semi Supervised Learning

, 2014
Supervised learning techniques require large number of labeled examples to build a classifier which is often difficult and expensive to collect. Unsupervised learning techniques, even though do not require labeled examples often form clusters regardless
Vijaya Geeta Dharmavaram, Shashi Mogalla
core  

A topological approach for semi-supervised learning

Journal of Computational Science
Nowadays, Machine Learning and Deep Learning methods have become the state-of-the-art approach to solve data classification tasks. In order to use those methods, it is necessary to acquire and label a considerable amount of data; however, this is not straightforward in some fields, since data annotation is time consuming and might require expert ...
Adrián Inés, César Domínguez 0001, Jónathan Heras, Gadea Mata, Julio Rubio 0001   +4 more
openaire   +2 more sources

Temporal Interference Stimulation Enhances Neural Regeneration

Advanced Science, EarlyView.
Temporal interference (TI) stimulation is proposed as a non‐invasive approach to enhance neural regeneration in the deep brain. Theta‐band TI modulation selectively promotes neural progenitor cell differentiation in vitro and augments hippocampal neurogenesis in amouse model of Alzheimer's disease‐like amyloidosis.
Sofia Peressotti, Maria Garcia Garrido, Patrycja Dzialecka, Rachel Man Hoi Law, Roberto Portillo‐Lara, Bethany Geary, Elena Faillace, Shirine Merlo‐Nikpay Aslie, Marcelina Wojewska, Maria Otero‐Jimenez, Martina Genta, Luqiao Tan, Karen Duff, Javier Alegre‐Abarrategui, Rylie Green, Nir Grossmann   +15 more
wiley   +1 more source

Automatic annotation for weakly supervised learning of detectors

, 2012
PhDObject detection in images and action detection in videos are among the most widely studied computer vision problems, with applications in consumer photography, surveillance, and automatic media tagging. Typically, these standard detectors are fully
Siva, Parthipan
core  

Local semi-supervised regression for single-image super-resolution

, 2011
In this paper, we propose a local semi-supervised learning-based algorithm for single-image super-resolution. Different from most of example-based algorithms, the information of test patches is considered during learning local regression functions which ...
Xiaoli Pan, LiLuoqing, Luoqing Li, Li, Xuelong, Yan, P., Pingkun Yan, YuanYuan, Yuan Yuan, Yi Tang, TangYi, Yuan, Y., YanPingkun, Tang, Y., PanXiaoli, Pan, X., Xuelong Li, LiXuelong, Li, L.   +17 more
core   +1 more source