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The proposed system aims to use various machine learning algorithms to enhance financial prediction and generate highly accurate analyses. It introduces an AI-driven platform which offers inflation-analysis, stock market prediction, and…
The prediction of nuclear observables beyond the finite model spaces that are accessible through modern ab initio methods, such as the no-core shell model, pose a challenging task in nuclear structure theory. It requires reliable tools for…
We use early-time photometry and spectroscopy of 12 Type II plateau supernovae (SNe IIP) to derive their distances using the expanding photosphere method (EPM). We perform this study using two sets of Type II supernova (SN II) atmosphere…
This study uses plasma-profile data from the EUROfusion pedestal database, focusing on the electron-temperature and electron-density profiles in the edge region of H-mode ELMy JET ITER-Like-Wall (ILW) pulses. We make systematic predictions…
BICEP1 is a millimeter-wavelength telescope designed specifically to measure the inflationary B-mode polarization of the Cosmic Microwave Background (CMB) at degree angular scales. We present results from an analysis of the data acquired…
Extreme learning machine (ELM) as a simple and rapid neural network has been shown its good performance in various areas. Different from the general single hidden layer feedforward neural network (SLFN), the input weights and biases in…
Observations of gravitational-wave signals emitted by compact binary inspirals provide unique insights into their properties, but their analysis requires accurate and efficient waveform models. Intermediate- and extreme-mass-ratio inspirals…
AI and deep learning techniques are beginning to play an increasing role in astronomy as a necessary tool to deal with the data avalanche. Here we describe an application for finding resolved Planetary Nebulae (PNe) in crowded, wide-field,…
This paper introduces a method for spatial interpolation of extreme values, and in particular targets the case in which conventional data, resulting from a measurement for example, are available at only a few locations. To overcome this the…
Deep learning-based trajectory prediction models for autonomous driving often struggle with generalization to out-of-distribution (OOD) scenarios, sometimes performing worse than simple rule-based models. To address this limitation, we…
We have conducted a high signal-to-noise spectroscopic survey of 670 nearby early-type stars, to map Diffuse Interstellar Band (DIB) absorption in and around the Local Bubble. The project started with a Southern hemisphere survey conducted…
In recent years (2000-2021), human-space activities have been increasing faster than ever. More than 36000 Earth' orbiting objects, all larger than 10 cm, in orbit around the Earth, are currently tracked by the European Space Agency (ESA).…
Aerosols influence weather and climate by interacting with radiation through absorption and scattering. These effects heavily rely on the optical properties of aerosols, which are mainly governed by attributes such as morphology, size…
Solar irradiance forecasts can be dynamic and unreliable due to changing weather conditions. Near the Arctic circle, this also translates into a distinct set of further challenges. This work is forecasting solar irradiance with Norwegian…
We present measurements of elemental abundances in solar flares with the EUV Variability Experiment (EVE) on the Solar Dynamics Observatory (SDO). EVE observes both high temperature Fe emission lines (Fe XV-Fe XXIV) and continuum emission…
We present a study of the X-ray emission from numerical simulations of hot bubbles in planetary nebulae (PNe). High-resolution, two-dimensional, radiation-hydrodynamical simulations of the formation and evolution of hot bubbles in PNe, with…
An in-depth analysis is performed on the problem that one parameter of the Cube model can affects the final simulation results of space debris long-term evolution model, which weakens the representativeness of the space debris evolution…
Interfacial deformation under electric fields is a common phenomenon in many industrial processes. Particularly, we are interested in the dynamics of sessile soap bubbles in a parallel-plate electric field which exhibits a stable…
Atmospheric aerosols influence the Earth's climate, primarily by affecting cloud formation and scattering visible radiation. However, aerosol-related physical processes in climate simulations are highly uncertain. Constraining these…
We investigate the response of outer radiation belt electron fluxes to different solar wind and geomagnetic indices using an interpretable machine learning method. We reconstruct the electron flux variation during 19 enhancement and 7…