Predicting Resilience of Interdependent Urban Infrastructure Systems
Climate change is increasing the frequency and the intensity of weather events, leading to large-scale disruptions to critical infrastructure systems. The high level of interdependence among these systems further aggravates the extent of disruptions.
Beatrice Cassottana +5 more
doaj +1 more source
Disruption of hierarchical predictive coding during sleep [PDF]
Significance Sleeping disrupts the conscious awareness of external sounds. We investigated the stage of processing at which this disruption occurs. In the awake brain, when a regular sequence of sounds is presented, a hierarchy of brain areas uses the available regularities to predict forthcoming sounds and to respond with a series of ...
Strauss, Melanie +8 more
openaire +2 more sources
Initial analytical theory of plasma disruption and experimental evidence
It is a great physical challenge to achieve controlled nuclear fusion in magnetic confinement tokamak and solve energy shortage problem for decades. In tokamak plasma, large-scale plasma instability called disruption will halt power production of reactor
Huibin Qiu +13 more
doaj +1 more source
Prediction errors disrupt hippocampal representations and update episodic memories [PDF]
Significance Our brains draw on memories to predict the future; when our predictions are incorrect, we must update our memories to improve future predictions. Past studies have demonstrated that the hippocampus signals prediction error (i.e., surprise) but have not linked this neural signal to memory updating.
Alyssa H. Sinclair +4 more
openaire +2 more sources
Spectroscopic Constraints on the Form of the Stellar Cluster Mass Function [PDF]
This contribution addresses the question of whether the initial cluster mass function (ICMF) has a fundamental limit (or truncation) at high masses. The shape of the ICMF at high masses can be studied using the most massive young (
Adamo +47 more
core +2 more sources
Investigation of Machine Learning Techniques for Disruption Prediction Using JET Data
Disruption prediction and mitigation is of key importance in the development of sustainable tokamak reactors. Machine learning has become a key tool in this endeavour. In this paper, multiple machine learning models are tested and compared.
Joost Croonen +2 more
doaj +1 more source
Adenovirus type 5 E4 Orf3 protein targets promyelocytic leukaemia (PML) protein nuclear domains for disruption via a sequence in PML isoform II that is predicted as a protein interaction site by bioinformatic analysis [PDF]
Human adenovirus type 5 infection causes the disruption of structures in the cell nucleus termed promyelocytic leukaemia (PML) protein nuclear domains or ND10, which contain the PML protein as a critical component. This disruption is achieved through the
Araujo +37 more
core +1 more source
Assessing Financial Vulnerability in the Nonprofit Sector [PDF]
Effective nonprofit governance relies upon understanding an organization's financial condition and vulnerabilities. However, financial vulnerability of nonprofit organizations is a relatively new area of study.
Elizabeth K. Keating +3 more
core +1 more source
Disruption prediction for future tokamaks using parameter-based transfer learning
Tokamaks are the most promising way for nuclear fusion reactors. Disruption in tokamaks is a violent event that terminates a confined plasma and causes unacceptable damage to the device.
Wei Zheng +14 more
doaj +1 more source
Prediction of the endocrine disruption profile of pesticides [PDF]
Numerous manmade chemicals released into the environment can interfere with normal, hormonally regulated biological processes to adversely affect the development and reproductive functions of living species. Various in vivo and in vitro tests have been designed for detecting endocrine disruptors, but the number of chemicals to test is so high that to ...
J, Devillers, E, Bro, F, Millot
openaire +2 more sources

