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Tropical cyclone (TC) inner-core surface wind vectors underpin intensity forecasting and storm-surge prediction, yet direct observations remain scarce: routine aircraft reconnaissance is confined to the North Atlantic and Eastern Pacific…
We use detailed numerical simulations of the coupled chemical, thermal and dynamical evolution of the gas in a turbulent molecular cloud to study the usefulness of the [CI] 609 micron and 370 micron fine structure emission lines as tracers…
Cloud Optical Thickness (COT) is a critical cloud property influencing Earth's climate, weather, and radiation budget. Satellite radiance measurements enable global COT retrieval, but challenges like 3D cloud effects, viewing angles, and…
A dimensionless collisionality scan has been performed in H-mode plasmas on DIII-D tokamak, with detailed measurements of intermediate-to-high wavenumber turbulence using Doppler backscattering systems. It is found that the shorter…
A decade ago, two-dimensional microscopic flow visualization proved the theoretically predicted existence of electroconvection roles as well as their decisive role in destabilizing the concentration polarization layer at ion-selective…
Radiation flow through an inhomogeneous medium is critical in a wide range of physics and astronomy applications from transport across cloud layers on the earth to the propagation of supernova blast-waves producing UV and X-ray emission in…
The impact of large atmospheric disturbances on deep benthic communities is not well known quantitatively. Observations are scarce but may reveal specific processes leading to turbulent disturbances. Here, we present high-resolution…
Edge plasma density fluctuations are shown to have a significant effect on the electron cyclotron resonance heating (ECRH) beam in the DIII-D tokamak. Experimental measurements of the ECRH deposition profile have been taken in three…
Short-term forecasting is an important tool in understanding environmental processes. In this paper, we incorporate machine learning algorithms into a conditional distribution estimator for the purposes of forecasting tropical cyclone…
We study the influence of low-level water and high-level ice clouds on low-resolution reflection spectra and planetary albedos of Earth-like planets orbiting different types of stars in both the visible and near infrared wavelength range.…
Tropical cyclones (TC) generally carry large amounts of water vapor and can cause large-scale extreme rainfall. Passive microwave rainfall (PMR) estimation of TC with high spatial and temporal resolution is crucial for disaster warning of…
Exploring heavy vector mesons of the $ J / \psi$ and $ \Upsilon ( 1 S )$ is crucial for understanding the quark gluon plasma (QGP) formed in heavy ion collisions. The influences of rotational effect on the properties of the $ J / \psi$ and…
Semantic segmentation of raw 3D point clouds is an essential component in 3D scene analysis, but it poses several challenges, primarily due to the non-Euclidean nature of 3D point clouds. Although, several deep learning based approaches…
In-order to understand the results of recent observations of exoplanets, models have become increasingly complex. Unfortunately this increases both the computational cost and output size of said models. We intend to explore if…
Tropical cyclone (TC) intensity forecasting is crucial for early disaster warning and emergency decision-making. Numerous researchers have explored deep-learning methods to address computational and post-processing issues in operational…
Turbulent radiative mixing layers (TRMLs) play an important role in many astrophysical contexts where cool ($\lesssim 10^4$ K) clouds interact with hot flows (e.g., galactic winds, high velocity clouds, infalling satellites in halos and…
Cyclic voltammetry (CV) is a powerful technique for characterizing electrochemical properties of electrochemical devices. During charging-discharging cycles, thermal effect has profound impact on its performance, but existing theoretical…
Emergency response applications for nuclear or radiological events can be significantly improved via deep feature learning due to the hidden complexity of the data and models involved. In this paper we present a novel methodology for rapid…
High-energy collisions at the Large Hadron Collider (LHC) provide valuable insights into open questions in particle physics. However, detector effects must be corrected before measurements can be compared to certain theoretical predictions…
Context. Multitransition CO observations of galaxy centers have revealed that significant fractions of the dense circumnuclear gas have high kinetic temperatures, which are hard to explain by pure photon excitation, but may be caused by…