Results 241 to 250 of about 6,527,322 (289)

Pasta, a Versatile Transcriptomic Clock, Maps the Chemical and Genetic Determinants of Aging and Rejuvenation

Advanced Science, EarlyView.
Pasta is a transcriptomic aging clock built on an age‐shift learning framework and trained on 17 000 samples across 21 datasets. It accurately predicts relative biological age across tissues, platforms, and species, captures stemness‐to‐senescence transitions, and identifies age‐modulatory perturbations.
Jérôme Salignon, Maria Tsiokou, Patricia Marqués, Enriqueta Rodríguez‐Diaz, Hazel Ang, Federico Pietrocola, Christian G. Riedel   +6 more
wiley   +1 more source

Visual Prompting Based Incremental Learning for Semantic Segmentation of Multiplex Immuno-Flourescence Microscopy Imagery. [PDF]

Neuroinformatics
Faulkenberry R, Prasad S, Maric D, Roysam B.   +3 more
europepmc   +1 more source

Agent‐Based Simulations of Lung Tumor Evolution Suggest That Ongoing Cell Competition Drives Realistic Clonal Expansions

Advanced Science, EarlyView.
Computational simulations of tumor evolution are increasingly used to infer the rules underlying cancer growth, with the goal of one day recommending tailored treatments. Here we show that the properties of lung cancer sequencing data are best replicated by a model which assumes that cells compete both to proliferate and survive. ABSTRACT Computational
Helena Coggan, James R. M. Black, Carlos Martínez‐Ruiz, Kristiana Grigoriadis, Jasmin Fisher, Nicholas McGranahan   +5 more
wiley   +1 more source

Human Foetal Neuroblasts Exhibit BK Channel‐Dependent Membrane Voltage Oscillations upon Depolarization

Advanced Science, EarlyView.
Primary cultures of neuroblasts isolated from the nucleus basalis of Meynert of 12‐weeks‐old human foetuses were prepared. Whole‐cell patch‐clamp recordings were performed by injecting a depolarizing stimulus current (+500 pA; 500 ms), and the membrane voltage recorded; this stimulus current evoked periodic‐like oscillations in membrane voltage ...
Elisabetta Coppi, Federica Cherchi, Martina Venturini, Federico Tommasi, Sandro Gonzi, Chiara Capacci, Giulia Guarnieri, Pasquale Gallina, Annamaria Morelli, Anna Maria Pugliese   +9 more
wiley   +1 more source

Artificial Intelligence‐Driven Inverse Design of Singlet Fission Candidates in the Acene family

Advanced Science, EarlyView.
In this work, we describe an AI‐driven inverse design platform predicting S1 and T1 energies across acenes with high accuracy. Using Hammett σ constants as descriptors and RNN models coupled with optimization algorithms, it efficiently explores ≈1014 structures, uncovering novel SF candidates from benzene to pentacene. Freely accessible at https://alba.
Rafael G. Uceda, Boris Pérez‐Cañedo, Sandra Míguez‐Lago, Carlos M. Cruz, Joaquín J. Torres, Omar Núñez, Luis Álvarez de Cienfuegos, Antonio J. Mota, Delia Miguel, Juan M. Cuerva   +9 more
wiley   +1 more source

Flexoelectric Suppression of Interfacial Carrier Loss in BaTiO3 Thin‐Film Bulk Photovoltaic Systems

Advanced Science, EarlyView.
In single‐crystalline BaTiO3 thin films, flexoelectric strain gradients strongly enhance photocurrent by suppressing interfacial carrier loss. Loading experiments reveal a ∼35‐fold photocurrent increase with applied force. Self‐consistent electrostatic modeling shows that strain gradients reshape the interfacial potential landscape, strengthen local ...
Minwoo Jang, Hyunkyu Lim, Sanghoon Yeom, Jaewhan Oh, Yongsoo Yang, Hyungwoo Lee   +5 more
wiley   +1 more source

EndoTac: An Endoscopic Camera‐Based Tactile Sensor with High Sensitivity for Minimally Invasive Surgery

Advanced Science, EarlyView.
EndoTac presents a trocar‐compatible endoscopic vision‐based tactile sensor that uses a convex mirror to enlarge side‐facing tactile coverage during minimally invasive vessel palpation. Distorted tactile images are unwarped and processed by a learning model to estimate vascular deformation, enabling sensitive, spatially distributed tactile perception ...
Yupeng Wang, Nicolas Raison, Xuyang Zhang, Aijia Yang, Lukas Lindenroth, Shan Luo   +5 more
wiley   +1 more source

Some of the next articles are maybe not open access.

Related searches:

On the Strength of Incremental Learning

1999
This paper provides a systematic study of incremental learning from noise-free and from noisy data, thereby distinguishing between learning from only positive data and from both positive and negative data. Our study relies on the notion of noisy data introduced in [22]. The basic scenario, named iterative learning, is as follows.
Steffen Lange, Gunter Grieser
openaire   +1 more source

Incremental Learning By Decomposition

2006 5th International Conference on Machine Learning and Applications (ICMLA'06), 2006
Adaptivity in neural networks aims at equipping learning algorithms with the ability to self-update as new training data becomes available. In many application, data arrives over long periods of time, hence the traditional one-shot training phase cannot be applied. The most appropriate training methodology in such circumstances is incremental learning (
openaire   +1 more source

On Appropriate Refractoriness and Weight Increment in Incremental Learning

2013
Neural networks are able to learn more patterns with the incremental learning than with the correlative learning. The incremental learning is a method to compose an associate memory using a chaotic neural network. The capacity of the network is found to increase along with its size which is the number of the neurons in the network and to be larger than
Toshinori Deguchi, Junya Fukuta, Naohiro Ishii   +2 more
openaire   +2 more sources