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We explore the kinematics of ionized gas via the [O III] $\lambda$5007 emission lines in active galactic nuclei (AGN) selected on the basis of their mid-infrared (IR) emission, and split into obscured and unobscured populations based on…
Anomaly detection in medical images refers to the identification of abnormal images with only normal images in the training set. Most existing methods solve this problem with a self-reconstruction framework, which tends to learn an identity…
We present an adapted version of the code HII-CHI-Mistry-UV (P\'erez-Montero & Amor\'in 2017) to derive chemical abundances from emission lines in the ultraviolet, for use in narrow line regions (NLR) of Active Galactic Nuclei (AGN). We…
We demonstrate high-resolution non-iterative holographic coherent diffraction imaging with hard X-rays using a novel phase-shifting reference, fabricated by atomic layer deposition to produce nanosharp 3D structure. The method surpasses the…
The Baldwin, Phillips, and Terlevich emission-line ratio diagnostic ([OIII]/H{\beta} versus [NII]/H{\alpha}, hereafter BPT diagram) efficiently separates galaxies whose signal is dominated by star formation <BPT-SF> from those dominated by…
With the high-resolution spectroscopy now available in the optical and satellite UV, it is possible to determine the neutral/ionized column density ratios for several different elements in a single cloud. Assuming ionization equilibrium for…
Understanding the complex ionization structure and chemical composition of \hii\ regions poses a significant challenge in astrophysics. The abundance discrepancy problem, characterized by inconsistencies between abundances derived from…
Positron emission tomography (PET) is the most sensitive molecular imaging modality routinely applied in our modern healthcare. High radioactivity caused by the injected tracer dose is a major concern in PET imaging and limits its clinical…
Long-term spectroscopic monitoring campaigns on active galactic nuclei (AGNs) provide a wealth of information about its interior structure and kinematics. However, a number of the observations suffer from the contamination of second-order…
One well-known way to constrain the hydrogen neutral fraction, x_H, of the high-redshift intergalactic medium (IGM) is through the shape of the red damping wing of the Lya absorption line. We examine this method's effectiveness in light of…
"Changing look" Active Galactic Nuclei (AGN) are a subset of Seyfert galaxies characterized by rapid transitions between Compton-thin and Compton-thick regimes. In their Compton-thin state, the central engine is less obscured, hence…
Emission-line studies in the active galactic nuclei (AGNs), particularly those utilizing high spatial resolution, provide the most accurate method to determine critical quantities of the central engine and of the gas a few tens of parsecs…
We explore the prospects of predicting emission line features present in galaxy spectra given broad-band photometry alone. There is a general consent that colours, and spectral features, most notably the 4000 A break, can predict many…
Contrastive learning has shown great promise over annotation scarcity problems in the context of medical image segmentation. Existing approaches typically assume a balanced class distribution for both labeled and unlabeled medical images.…
Here we report new ${\it ab initio}$ calculations of the effective recombination coefficients for the \ion{N}{ii} recombination spectrum. We have taken into account the density dependence of the coefficients arising from the relative…
Automatic delineation of organ-at-risk (OAR) and gross-tumor-volume (GTV) is of great significance for radiotherapy planning. However, it is a challenging task to learn powerful representations for accurate delineation under limited pixel…
Relativistically broadened and redshifted 6.4 -- 6.9 keV iron K lines are observed from many accretion powered objects, including X-ray binaries and active galactic nuclei (AGN). Existence of gas close to the central engine implies large…
Predicting the ground-state 3D molecular conformations from 2D molecular graphs is critical in computational chemistry due to its profound impact on molecular properties. Deep learning (DL) approaches have recently emerged as promising…
Small, imbalanced datasets and poor input image quality can lead to high false predictions rates with deep learning models. This paper introduces Class-Based Image Composition, an approach that allows us to reformulate training inputs…
Since the discovery of active galactic nuclei (AGN) and their subclasses, a unification scheme of AGN has been long sought. Orientation-based unified models predict that some of the diversity within AGN subclasses can be explained by the…