Related papers: Measuring Thermal Profiles in High Explosives usin…
In this article, we study the production of Hydrogen and Helium isotopes in heavy-ion collisions in the incident energy range between 80 and 150 MeV/nucleon. We compare their inclusive multiplicities emitted in the transverse plane of the…
Understanding the thermal behavior of additive manufacturing (AM) processes is crucial for enhancing the quality control and enabling customized process design. Most purely physics-based computational models suffer from intensive…
The computational workload involved in Convolutional Neural Networks (CNNs) is typically out of reach for low-power embedded devices. There are a large number of approximation techniques to address this problem. These methods have…
Calculations of transition intensities for small molecules like H$_2$O, CO, CO$_2$ based on s high-quality potential energy surface (PES) and dipole moment surface (DMS) can nowadays reach sub-percent accuracy. An extension of this…
Atmospheric retrievals (AR) of exoplanets typically rely on a combination of a Bayesian inference technique and a forward simulator to estimate atmospheric properties from an observed spectrum. A key component in simulating spectra is the…
Every time a chemical reaction occurs, an energy exchange between reactants and environment exists, which is defined as the enthalpy of the reaction. In the last decades, research has resulted in an increasing number of devices at the…
Motivated by the fact that characteristics of different sound classes are highly diverse in different temporal scales and hierarchical levels, a novel deep convolutional neural network (CNN) architecture is proposed for the environmental…
Simulations based on experimental data obtained from multifragmenting quasi-fused nuclei produced in central $^{129}$Xe + $^{nat}$Sn collisions have been used to deduce event by event freeze-out properties in the thermal excitation energy…
The kinetic energy variation of emitted light clusters has been employed as a clock to explore the time evolution of the temperature for thermalizing composite systems produced in the reactions of 26A, 35A and 47A MeV $^{64}$Zn with…
We have introduced a new method of estimating the electron temperature and density of H II regions by using single dish observations. In this method, multiple hydrogen radio recombination lines of different bands are computed under the…
A novel, to the best of our knowledge, ultralow-temperature luminescence thermometry strategy is proposed, based on a measurement of relative intensities of hyperfine components in the spectra of Ho$^{3+}$ ions doped into a crystal. A…
We introduce a nanocalorimetric technique based on microsecond-pulsed heating (\mu s-PHnC) that enables high-sensitivity, quasi-isothermal heat capacity measurements on nanoscale samples. Such resolution is critical for exploring…
A model in which a projectile like fragment can be simply regarded as a remnant after removal of some part of the projectile leads to an excited fragment. This excitation energy can be calculated with a Hamiltonian that gives correct…
In deep geological repositories for high level nuclear waste with close canister spacings, bentonite buffers can experience temperatures higher than 100 {\deg}C. In this range of extreme temperatures, phenomenological constitutive laws face…
Wearable electrocardiogram (ECG) measurement using dry electrodes has a problem with high-intensity noise distortion. Hence, a robust noise reduction method is required. However, overlapping frequency bands of ECG and noise make noise…
In this work, we study the information content learned by a convolutional neural network (CNN) when trained to carry out the inverse mapping between a database of synthetic Ca II intensity spectra and the vertical stratification of the…
Besides the lot of advantages offered by the 3D stacking of devices in an integrated circuit there is a chance of device damage due to rise in peak temperature value. Hence, in order to make use of all the potential benefits of the vertical…
A number of works infer radial temperature profiles of envelopes surrounding young stellar objects using several rotational transitions in a pixel-by-pixel or azimuthally-averaged basis. However, in many cases the assumption that the…
The material properties selection for designing acoustic filters with optimal performance over a range of frequencies requires considerable effort to fabricate and test laboratory samples. To simplify this procedure, one may test a single…
A wide range of deep learning-based machine learning techniques are extensively applied to the design of high-entropy alloys (HEAs), yielding numerous valuable insights. Kolmogorov-Arnold Networks (KAN) is a recently developed architecture…