Weather Forecast of the Milky Way: Shear and Stellar feedback determine the lives of Galactic-scale filaments

The interstellar medium (ISM) is an inseparable part of the Milky Way ecosystem whose evolutionary history remains a challenging question. We trace the evolution of the molecular ISM using a sample of Young Stellar Objects (YSO) association --molecular cloud complex (YSO-MC complex). We derive their three-dimensional (3D) velocities by combining the Gaia astrometric measurements of the YSO associations and the CO observations of the associated molecular clouds. Based on the 3D velocities, we simulate the motions of the YSO-MC complexes in the Galactic potential and forecast the ISM evolution by tracing the motions of the individual complexes, and reveal the roles of shear and stellar feedback in determining ISM evolution: Galactic shear stretches Galactic-scale molecular cloud complexes, such as the G120 Complex, into Galactic-scale filaments, and it also contributes to the destruction of the filaments; while stellar feedback creates interconnected superbubbles whose expansion injects peculiar velocities into the ISM. The Galactic-scale molecular gas clumps are often precursors of the filaments and the Galactic-scale filaments are transient structures under a constant stretch by shear. This evolutionary sequence sets a foundation to interpret other gas structures. Animations are available at https://gxli.github.io/ISM-6D/movie.html.Comment: Accepted by MNRAS letter

(meso-5,7,7,12,14,14-Hexamethyl-1,4,8,11-tetra­azacyclo­tetra­deca-4,11-diene)nickel(II) bis­[O,O′-bis(4-methyl­phen­yl) dithio­phosphate]

In the title compound, [Ni(C16H32N4)](C14H14O2PS2)2 or [Ni(trans[14]dien)][S2P(OC6H4Me-4)2]2, where trans[14]dien is meso-5,7,7,12,14,14-hexa­methyl-1,4,8,11-tetra­azacyclo­tetra­deca-4,11-diene, the NiII ion lies across a centre of inversion and is four-coordinated in a relatively undistorted square-planar arrangement by the four N atoms of the macrocyclic ligand trans[14]dien. The two O,O′-di(4-methyl­phen­yl)dithio­phos­phates act as counter-ions to balance the charge. Important geometric data include Ni—N = 1.9135 (16) and 1.9364 (15) Å

IMass time: The future, in future!

Joseph John Thomson discovered and proved the existence of electrons through a series of experiments. His work earned him a Nobel Prize in 1906 and initiated the era of mass spectrometry (MS). In the intervening time, other researchers have also been awarded the Nobel Prize for significant advances in MS technology. The development of soft ionization techniques was central to the application of MS to large biological molecules and led to an unprecedented interest in the study of biomolecules such as proteins (proteomics), metabolites (metabolomics), carbohydrates (glycomics), and lipids (lipidomics), allowing a better understanding of the molecular underpinnings of health and disease. The interest in large molecules drove improvements in MS resolution and now the challenge is in data deconvolution, intelligent exploitation of heterogeneous data, and interpretation, all of which can be ameliorated with a proposed IMass technology. We define IMass as a combination of MS and artificial intelligence, with each performing a specific role. IMass will offer advantages such as improving speed, sensitivity, and analyses of large data that are presently not possible with MS alone. In this study, we present an overview of the MS considering historical perspectives and applications, challenges, as well as insightful highlights of IMass

Video Event Extraction via Tracking Visual States of Arguments

Video event extraction aims to detect salient events from a video and identify the arguments for each event as well as their semantic roles. Existing methods focus on capturing the overall visual scene of each frame, ignoring fine-grained argument-level information. Inspired by the definition of events as changes of states, we propose a novel framework to detect video events by tracking the changes in the visual states of all involved arguments, which are expected to provide the most informative evidence for the extraction of video events. In order to capture the visual state changes of arguments, we decompose them into changes in pixels within objects, displacements of objects, and interactions among multiple arguments. We further propose Object State Embedding, Object Motion-aware Embedding and Argument Interaction Embedding to encode and track these changes respectively. Experiments on various video event extraction tasks demonstrate significant improvements compared to state-of-the-art models. In particular, on verb classification, we achieve 3.49% absolute gains (19.53% relative gains) in F1@5 on Video Situation Recognition