Results 51 to 60 of about 9,064 (165)

Cell segmentation by multi-resolution analysis and maximum likelihood estimation (MAMLE) [PDF]

BMC Bioinformatics, 2013
AbstractBackgroundCell imaging is becoming an indispensable tool for cell and molecular biology research. However, most processes studied are stochastic in nature, and require the observation of many cells and events. Ideally, extraction of information from these images ought to rely on automatic methods.
Ribeiro Andre S., Kandhavelu Meenakshisundaram, Yli-Harja Olli, Chowdhury Sharif   +3 more
openaire   +2 more sources

The Regulation and Function of Hippo/YAP Pathway in Cancer

The FASEB Journal, Volume 40, Issue 7, 15 April 2026.
Hippo/YAP pathway signaling plays critical roles in the progression of multiple cancer types. This review summarizes current knowledge of Hippo/YAP pathway regulation and function in cancer. We discuss the core components of the Hippo/YAP pathway; its crosstalk with other signaling pathways; regulation by non‐coding RNAs; roles of YAP signaling in ...
Chinmoy Ghosh, Ruchi Kakar, Seline Torkamboor, Yue Sun   +3 more
wiley   +1 more source

A Dynamic Role of Mastermind-Like 1: A Journey Through the Main (Path)ways Between Development and Cancer

Frontiers in Cell and Developmental Biology, 2020
Major signaling pathways, such as Notch, Hedgehog (Hh), Wnt/β-catenin and Hippo, are targeted by a plethora of physiological and pathological stimuli, ultimately resulting in the modulation of genes that act coordinately to establish specific biological ...
Sabrina Zema, Maria Pelullo, Francesca Nardozza, Maria Pia Felli, Isabella Screpanti, Diana Bellavia   +5 more
doaj   +1 more source

Deep deterministic policy gradient - model-agnostic meta-learning framework: Efficient adaptation in continuous control tasks

Results in Engineering
Deep reinforcement learning (DRL) demonstrates superior performance in continuous control tasks. However, extensive training across a variety of environments is frequently necessitates extensive training.
Ebrahim Hamid Sumiea, Said Jadid Abdulkadir, Hitham Seddig Alhussian, Safwan Mahmood Al-Selwi, Alawi Alqushaibi, Mohammed Gamal Ragab, Abdul Muiz Fayyaz   +6 more
doaj   +1 more source

Smart Waste, Smarter World: Exploring Waste Types, Trends, and Tech‐Driven Valorization Through Artificial Intelligence, Internet of Things, and Blockchain

Sustainable Development, Volume 34, Issue S2, Page 132-153, March 2026.
ABSTRACT Global municipal solid waste generation is projected to exceed 3.8 billion tonnes annually by 2050. This makes the need for smart, inclusive, and scalable waste valorization systems more urgent than ever. This review critically explores the shift from conventional waste management to intelligent, technology‐driven solutions aligned with ...
Segun E. Ibitoye, Amit K. Ball, Raul V. Rodriguez, Olalekan A. Olayemi, Peplluis Esteva, Peter O. Omoniyi, Isaac K. Adegun, Rasheedat M. Mahamood, Esther T. Akinlabi   +8 more
wiley   +1 more source

Small Sample-Oriented Prediction Method of Mechanical Properties for Hot Rolled Strip Steel Based on Model Independent Element Learning

IEEE Access
In this paper, a new method based on Model-Agnostic Meta-Learning (MAML) is proposed to address the small sample problem in predicting the mechanical properties of hot rolled strip steel.
Hongyi Wu, Borui Zhang, Zhiwei Li
doaj   +1 more source

Hypernetwork Approach to Bayesian MAML (Student Abstract)

Proceedings of the AAAI Conference on Artificial Intelligence
The main goal of Few-Shot learning algorithms is to enable learning from small amounts of data. One of the most popular and elegant Few-Shot learning approaches is Model-Agnostic Meta-Learning (MAML). In this paper, we propose a novel framework for Bayesian MAML called BH-MAML, which employs Hypernetworks for weight updates.
Borycki, Piotr, Kubacki, Piotr, Przewięźlikowski, Marcin, Kuśmierczyk, Tomasz, Tabor, Jacek, Spurek, Przemysław   +5 more
openaire   +2 more sources

Meta Reinforcement Learning for Automated Cyber Defence

Applied AI Letters, Volume 7, Issue 1, February 2026.
ABSTRACT Reinforcement learning (RL) solutions have shown considerable promise for automating the defense of networks to cyber attacks. However, a limitation to their real world deployment is the sample efficiency and generalizability of RL agents. This means that even small changes to attack types require a new agent to be trained from scratch.
Andrew Thomas, Nick Tillyer
wiley   +1 more source

Nitrate Enhances Gastric Mucosa Defense and Repair Process in Ethanol‐Induced Gastric Ulcer Rats via the Notch–Tff2 Pathway

MedComm, Volume 7, Issue 2, February 2026.
Nitrate protects the three major barriers of the gastric mucosa, alleviating bleeding and inflammation of ethanol‐induced gastric ulcer in rats, and promotes migration of gastric epithelial cells, accelerating the restoration of the ulcerated epithelium, which is strongly related to TFF2, a gastric mucosal protective factor negatively regulated by the ...
Ying Liu, Xin Wen, Yuxuan Lin, Chunmei Zhang, Jinsong Wang, Guangyong Sun, Dong Zhang, Renhong Yan, Mo Chen, Songlin Wang, Shaorong Li   +10 more
wiley   +1 more source

High-Resolution PM₁₀ Estimation Using Satellite Data and Model-Agnostic Meta-Learning

Remote Sensing
Characterizing the spatial distribution of particles smaller than 10 μm (PM10) is of great importance for air quality management yet is very challenging because of the sparseness of air quality monitoring stations.
Yue Yang, Jan Cermak, Xu Chen, Yunping Chen, Xi Hou   +4 more
doaj   +1 more source