AIMC Topic: Temperature

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Facilitating ab initio configurational sampling of multicomponent solids using an on-lattice neural network model and active learning.

The Journal of chemical physics
We propose a scheme for ab initio configurational sampling in multicomponent crystalline solids using Behler-Parinello type neural network potentials (NNPs) in an unconventional way: the NNPs are trained to predict the energies of relaxed structures ...

Light responsive plasmonic silicone elastomer/hydrogel soft actuator.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Soft robots offer unique advantages in their ability to interact with fragile organisms. Light responsive soft actuators are promising for the development of the untethered soft robots. However, this requires a mechanism for converting the externally...

A neural network-assisted open boundary molecular dynamics simulation method.

The Journal of chemical physics
A neural network-assisted molecular dynamics method is developed to reduce the computational cost of open boundary simulations. Particle influxes and neural network-derived forces are applied at the boundaries of an open domain consisting of explicit...

The relationship between rising temperatures and malaria incidence in Hainan, China, from 1984 to 2010: a longitudinal cohort study.

The Lancet. Planetary health
BACKGROUND: The influence of rising global temperatures on malaria dynamics and distribution remains controversial, especially in central highland regions. We aimed to address this subject by studying the spatiotemporal heterogeneity of malaria and t...

A genetic algorithm and backpropagation neural network based temperature compensation method of spin-exchange relaxation-free co-magnetometer.

The Review of scientific instruments
This paper presents a temperature compensation method based on the genetic algorithm (GA) and backpropagation (BP) neural network to reduce the temperature induced error of the spin-exchange relaxation-free (SERF) co-magnetometer. The fluctuation of ...

Drivers of harmful algal blooms in coastal areas of Eastern Mediterranean: a machine learning methodological approach.

Mathematical biosciences and engineering : MBE
Harmful algal species are present in the Mediterranean Sea and are often associated with toxic events affecting the nearby coastal zones. The presence of 18 marine microalgae, at genus level, associated with potentially harmful characteristics was pr...

Somatosensory actuator based on stretchable conductive photothermally responsive hydrogel.

Science robotics
Mimicking biological neuromuscular systems' sensory motion requires the unification of sensing and actuation in a singular artificial muscle material, which must not only actuate but also sense their own motions. These functionalities would be of gre...

Collective dynamics in entangled worm and robot blobs.

Proceedings of the National Academy of Sciences of the United States of America
Living systems at all scales aggregate in large numbers for a variety of functions including mating, predation, and survival. The majority of such systems consist of unconnected individuals that collectively flock, school, or swarm. However, some agg...

Mapping the global potential transmission hotspots for severe fever with thrombocytopenia syndrome by machine learning methods.

Emerging microbes & infections
Severe fever with thrombocytopenia syndrome (SFTS) is an emerging infectious disease with increasing spread. Currently SFTS transmission has expanded beyond Asian countries, however, with definitive global extents and risk patterns remained obscure. ...

Machine learning prediction on number of patients due to conjunctivitis based on air pollutants: a preliminary study.

European review for medical and pharmacological sciences
OBJECTIVE: A prediction of the number of patients with conjunctivitis plays an important role in providing adequate treatment at the hospital, but such accurate predictive model currently does not exist. The current study sought to use machine learni...