Results 111 to 120 of about 407,221 (296)
A Review of Traditional and Data-Driven Approaches for Disruption Prediction in Different Tokamaks [PDF]
Tokamak is a nuclear fusion reactor; inside, the two lighter nuclei known as deuterium and tritium are first ionized together to form plasma, which is heated up to 150 million degrees Celsius, and then they are confined by the torus-shaped magnetic field.
Priyanka M., Sangeetha J., Jayakumar C.
doaj +1 more source
Dormant cancer cells can hide in distant organs for years, evading treatment and the immune system. This review highlights how signals from the surrounding tissue and immune environment keep these cells inactive or trigger their reawakening. Understanding these mechanisms may help develop therapies to eliminate or control dormant cells and prevent ...
Kanishka Tiwary +1 more
wiley +1 more source
Introduction: This work explores the use of eXplainable artificial intelligence (XAI) to analyze a convolutional neural network (CNN) trained for disruption prediction in tokamak devices and fed with inputs composed of different physical quantities ...
L. Bonalumi +11 more
doaj +1 more source
Radiotherapy (RT) response depends on the DNA repair capacity of tumor and host cells. We show that circulating tumor cell (CTC) counts and apoptosis rates before and after RT predict treatment response and outcome, which can be accessed via easily accessible liquid biopsy approaches. Created in BioRender. Wikman, H.
Yvonne Goy +10 more
wiley +1 more source
An investigation of factors influencing disrupted sleep in university students
Introduction: Sleep disruption is one of the psychosocial issues among college students which might adversely affect their lives. This study examines the role of individual and psychosocial factors and intensive scholastic schedule in disrupted sleep ...
Ishagh Rahimian Boogar +1 more
doaj
Machine learning based disruption prediction using long short-term memory in KSTAR
This study presents a machine learning model for predicting plasma disruptions using the KSTAR database. The model employs a long short-term memory (LSTM) network to capture temporal patterns in zero-dimensional plasma signals.
Jeongwon Lee +7 more
doaj +1 more source
Adaptive learning for disruption prediction in non-stationary conditions
For many years, machine learning tools have proved to be very powerful disruption predictors in tokamaks. On the other hand, the vast majority of the techniques deployed assume that the input data is independent and is sampled from exactly the same probability distribution for the training set, the test set and the final real time deployment.
Murari, A. +230 more
openaire +8 more sources
Loss of IGF‐1R impairs DNA‐PKcs recruitment to chromatin leading to defective end‐joining
IGF‐1R promotes radioresistance by facilitating DNA‐PKcs recruitment to chromatin, enabling non‐homologous end‐joining (NHEJ) repair of double‐strand breaks. Inhibition or loss of IGF‐1R disrupts this recruitment to damage sites, driving compensatory reliance on microhomology‐mediated end‐joining (MMEJ) repair.
Matthew O. Ellis +3 more
wiley +1 more source
Supermassive black hole (SMBH) growth plausibly occurs via runaway astrophysical black hole mergers in nuclear star clusters that form intermediate mass black hole seeds at high redshifts.
Konstantinos Kritos, Joseph Silk
doaj +1 more source
CRISPRI‐mediated gene silencing and phenotypic exploration in nontuberculous mycobacteria. In this Research Protocol, we describe approaches to control, monitor, and quantitatively assess CRISPRI‐mediated gene silencing in M. smegmatis and M. abscessus model organisms.
Vanessa Point +7 more
wiley +1 more source

