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The internal velocity structure within dense gaseous cores plays a crucial role in providing the initial conditions for star formation in molecular clouds. However, the kinematic properties of dense gas at core scales (~0.01 - 0.1 pc) has not been extensively characterized because of instrument limitations until the unique capabilities of GBT-Argus became available. The ongoing GBT-Argus Large Program, Dynamics in Star-forming Cores (DiSCo) thus aims to investigate the origin and distribution of angular momenta of star-forming cores. DiSCo will survey all starless cores and Class 0 protostellar cores in the Perseus molecular complex down to ~0.01 pc scales with < 0.05 km/s velocity resolution using the dense gas tracer N$_2$H$^+$. Here, we present the first datasets from DiSCo toward the B1 and NGC 1333 regions in Perseus. Our results suggest that a dense core's internal velocity structure has little correlation with other core-scale properties, indicating these gas motions may be originated externally from cloud-scale turbulence. These first datasets also reaffirm the ability of GBT-Argus for studying dense core velocity structure and provided an empirical basis for future studies that address the angular momentum problem with a statistically broad sample., Comment: 17 pages, 12 figures, accepted by MNRAS

Psychiatry research seeks to understand the manifestations of psychopathology in behavior, as measured in questionnaire data, by identifying a small number of latent factors that explain them. While factor analysis is the traditional tool for this purpose, the resulting factors may not be interpretable, and may also be subject to confounding variables. Moreover, missing data are common, and explicit imputation is often required. To overcome these limitations, we introduce interpretability constrained questionnaire factorization (ICQF), a non-negative matrix factorization method with regularization tailored for questionnaire data. Our method aims to promote factor interpretability and solution stability. We provide an optimization procedure with theoretical convergence guarantees, and an automated procedure to detect latent dimensionality accurately. We validate these procedures using realistic synthetic data. We demonstrate the effectiveness of our method in a widely used general-purpose questionnaire, in two independent datasets (the Healthy Brain Network and Adolescent Brain Cognitive Development studies). Specifically, we show that ICQF improves interpretability, as defined by domain experts, while preserving diagnostic information across a range of disorders, and outperforms competing methods for smaller dataset sizes. This suggests that the regularization in our method matches domain characteristics. The python implementation for ICQF is available at \url{https://github.com/jefferykclam/ICQF}.

Stars form from the gravitational collapse of turbulent, magnetized molecular cloud cores. Our non-ideal MHD simulations reveal that the intrinsically anisotropic magnetic resistance to gravity during the core collapse naturally generates dense gravo-magneto-sheetlets within inner protostellar envelopes -- disrupted versions of classical sheet-like pseudodisks. They are embedded in a magnetically dominant background, where less dense materials flow along the local magnetic field lines and accumulate in the dense sheetlets. The sheetlets, which feed the disk predominantly through its upper and lower surfaces, are the primary channels for mass and angular momentum transfer from the envelope to the disk. The protostellar disk inherits a small fraction (up to 10\%) of the magnetic flux from the envelope, resulting in a disk-averaged net vertical field strength of 1-10 mG and a somewhat stronger toroidal field, potentially detectable through ALMA Zeeman observations. The inherited magnetic field from the envelope plays a dominant role in disk angular momentum evolution, enabling the formation of gravitationally stable disks in cases where the disk field is relatively well-coupled to the gas. Its influence remains significant even in marginally gravitationally unstable disks formed in the more magnetically diffusive cases, removing angular momentum at a rate comparable to or greater than that caused by spiral arms. The magnetically driven disk evolution is consistent with the apparent scarcity of prominent spirals capable of driving rapid accretion in deeply embedded protostellar disks. The dense gravo-magneto-sheetlets observed in our simulations may correspond to the ``accretion streamers" increasingly detected around protostars., Comment: 20 pages, 14 figures

We present an overview of the Large Program, ``Early Planet Formation in Embedded Disks (eDisk)'', conducted with the Atacama Large Millimeter/submillimeter Array (ALMA). The ubiquitous detections of substructures, particularly rings and gaps, in protoplanetary disks around T Tauri stars raise the possibility that at least some planet formation may have already started during the embedded stages of star formation. In order to address exactly how and when planet formation is initiated, the program focuses on searching for substructures in disks around 12 Class 0 and 7 Class I protostars in nearby ($< $200 pc) star-forming regions through 1.3 mm continuum observations at a resolution of $\sim7$ au (0.04"). The initial results show that the continuum emission, mostly arising from dust disks around the sample protostars, has relatively few distinctive substructures, such as rings and spirals, in marked contrast to Class II disks. The dramatic difference may suggest that substructures quickly develop in disks when the systems evolve from protostars to Class II sources or alternatively that high optical depth of the continuum emission could obscure internal structures. Kinematic information obtained through CO isotopologue lines and other lines reveals the presence of Keplerian disks around protostars, providing us with crucial physical parameters, in particular, the dynamical mass of the central protostars. We describe the background of the eDisk program, the sample selection and their ALMA observations, the data reduction, and also highlight representative first-look results., Comment: This is a publication of a series of eDisk ALMA large program first-look papers

Recent observations indicate that mm/cm-sized grains may exist in the embedded protostellar disks. How such large grains grow from the micron size (or less) in the earliest phase of star formation remains relatively unexplored. In this study we take a first step to model the grain growth in the protostellar environment, using two-dimensional (2D axisymmetric) radiation hydrodynamic and grain growth simulations. We show that the grain growth calculations can be greatly simplified by the "terminal velocity approximation", where the dust drift velocity relative to the gas is proportional to its stopping time, which is proportional to the grain size. We find that the grain-grain collision from size-dependent terminal velocity alone is too slow to convert a significant fraction of the initially micron-sized grains into mm/cm sizes during the deeply embedded Class 0 phase. Substantial grain growth is achieved when the grain-grain collision speed is enhanced by a factor of 4. The dust growth above and below the disk midplane enables the grains to settle faster towards the midplane, which increases the local dust-to-gas ratio, which, in turn, speeds up further growth there. How this needed enhancement can be achieved is unclear, although turbulence is a strong possibility that deserves further exploration., Comment: Accepted by Monthly Notices of the Royal Astronomical Society

Chemical models and experiments indicate that interstellar dust grains and their ice mantles play an important role in the production of complex organic molecules (COMs). To date, the most complex solid-phase molecule detected with certainty in the ISM is methanol, but the James Webb Space Telescope (JWST) may be able to identify still larger organic species. In this study, we use a coupled chemo-dynamical model to predict new candidate species for JWST detection toward the young star-forming core Cha-MMS1, combining the gas-grain chemical kinetic code MAGICKAL with a 1-D radiative hydrodynamics simulation using Athena++. With this model, the relative abundances of the main ice constituents with respect to water toward the core center match well with typical observational values, providing a firm basis to explore the ice chemistry. Six oxygen-bearing COMs (ethanol, dimethyl ether, acetaldehyde, methyl formate, methoxy methanol, and acetic acid), as well as formic acid, show abundances as high as, or exceeding, 0.01% with respect to water ice. Based on the modeled ice composition, the infrared spectrum is synthesized to diagnose the detectability of the new ice species. The contribution of COMs to IR absorption bands is minor compared to the main ice constituents, and the identification of COM ice toward the core center of Cha-MMS1 with the JWST NIRCAM/Wide Field Slitless Spectroscopy (2.4-5.0 micron) may be unlikely. However, MIRI observations (5-28 micron) toward COM-rich environments where solid-phase COM abundances exceed 1% with respect to the water ice column density might reveal the distinctive ice features of COMs., Comment: Accepted to ApJ (28 Pages, 11 figures)

With the advent of ALMA, it is now possible to observationally constrain how disks form around deeply embedded protostars. In particular, the recent ALMA C3H2 line observations of the nearby protostar L1527 have been interpreted as evidence for the so-called "centrifugal barrier," where the protostellar envelope infall is gradually decelerated to a stop by the centrifugal force in a region of super-Keplerian rotation. To test the concept of centrifugal barrier, which was originally based on angular momentum conserving-collapse of a rotating test particle around a fixed point mass, we carry out simple axisymmetric hydrodynamic simulations of protostellar disk formation including a minimum set of ingredients: self-gravity, rotation, and a prescribed viscosity that enables the disk to accrete. We find that a super-Keplerian region can indeed exist when the viscosity is relatively large but, unlike the classic picture of centrifugal barrier, the infalling envelope material is not decelerated solely by the centrifugal force. The region has more specific angular momentum than its surrounding envelope material, which points to an origin in outward angular momentum transport in the disk (subject to the constraint of disk expansion by the infalling envelope), rather than the spin-up of the envelope material envisioned in the classic picture as it falls closer to the center in order to conserve angular momentum. For smaller viscosities, the super-Keplerian rotation is weaker or non-existing. We conclude that, despite the existence of super-Keplerian rotation in some parameter regime, the classic picture of centrifugal barrier is not supported by our simulations.

Misalignment between rotation and magnetic field has been suggested to be one type of physical mechanisms which can easen the effects of magnetic braking during collapse of cloud cores leading to formation of protostellar disks. However, its essential factors are poorly understood. Therefore, we perform a more detailed analysis of the physics involved. We analyze existing simulation data to measure the system torques, mass accretion rates and Toomre Q parameters. We also examine the presence of shocks in the system. While advective torques are generally the strongest, we find that magnetic and gravitational torques can play substantial roles in how angular momentum is transferred during the disk formation process. Magnetic torques can shape the accretion flows, creating two-armed magnetized inflow spirals aligned with the magnetic field. We find evidence of an accretion shock that is aligned according to the spiral structure of the system. Inclusion of ambipolar diffusion as explored in this work has shown a slight influence in the small scale structures but not in the main morphology. We discuss potential candidate systems where some of these phenomena could be present., Comment: 26 pages, 26 figures, 2 tables, Accepted for publication in the Astrophysical Journal

There have been significant efforts devoted to solving the longevity risk given that a continuous growth in population ageing has become a severe issue for many developed countries over the past few decades. The Cairns-Blake-Dowd (CBD) model, which incorporates cohort effects parameters in its parsimonious design, is one of the most well-known approaches for mortality modelling at higher ages and longevity risk. This article proposes a novel mixed-effects time-series approach for mortality modelling and forecasting with considerations of age groups dependence and random cohort effects parameters. The proposed model can disclose more mortality data information and provide a natural quantification of the model parameters uncertainties with no pre-specified constraint required for estimating the cohort effects parameters. The abilities of the proposed approach are demonstrated through two applications with empirical male and female mortality data. The proposed approach shows remarkable improvements in terms of forecast accuracy compared to the CBD model in the short-, mid-and long-term forecasting using mortality data of several developed countries in the numerical examples.

Understanding how material accretes onto the rotationally supported disk from the surrounding envelope of gas and dust in the youngest protostellar systems is important for describing how disks are formed. Magnetohydrodynamic simulations of magnetized, turbulent disk formation usually show spiral-like streams of material (accretion flows) connecting the envelope to the disk. However, accretion flows in these early stages of protostellar formation still remain poorly characterized due to their low intensity and possibly some extended structures are disregarded as being part of the outflow cavity. We use ALMA archival data of a young Class 0 protostar, Lupus 3-MMS, to uncover four extended accretion flow-like structures in C$^{18}$O that follow the edges of the outflows. We make various types of position-velocity cuts to compare with the outflows and find the extended structures are not consistent with the outflow emission, but rather more consistent with a simple infall model. We then use a dendrogram algorithm to isolate five sub-structures in position-position-velocity space. Four out of the five sub-structures fit well ($>$95%) with our simple infall model, with specific angular momenta between $2.7-6.9\times10^{-4}\,$km$\,$s$^{-1}\,$pc and mass-infall rates of $0.5-1.1\times10^{-6}\,M_{\odot}\,$yr$^{-1}$. Better characterization of the physical structure in the supposed "outflow-cavities" is important to disentangle the true outflow cavities and accretion flows., Comment: 23 pages, 12 figures, accepted for publication in The Astrophysical Journal

Polarized dust continuum emission has been observed with ALMA in an increasing number of deeply embedded protostellar systems. It generally shows a sharp transition going from the protostellar envelope to the disk scale, with the polarization fraction typically dropping from ${\sim} 5\%$ to ${\sim} 1\%$ and the inferred magnetic field orientations becoming more aligned with the major axis of the system. We quantitatively investigate these observational trends using a sample of protostars in the Perseus molecular cloud and compare these features with a non-ideal MHD disk formation simulation. We find that the gas density increases faster than the magnetic field strength in the transition from the envelope to the disk scale, which makes it more difficult to magnetically align the grains on the disk scale. Specifically, to produce the observed ${\sim} 1\%$ polarization at ${\sim} 100\,\mathrm{au}$ scale via grains aligned with the B-field, even relatively small grains of $1\,\mathrm{\mu m}$ in size need to have their magnetic susceptibilities significantly enhanced (by a factor of ${\sim} 20$) over the standard value, potentially through superparamagnetic inclusions. This requirement is more stringent for larger grains, with the enhancement factor increasing linearly with the grain size, reaching ${\sim} 2\times 10^4$ for millimeter-sized grains. Even if the required enhancement can be achieved, the resulting inferred magnetic field orientation in the simulation does not show a preference for the major axis, which is inconsistent with the observed pattern. We thus conclude that the observed trends are best described by the model where the polarization on the envelope scale is dominated by magnetically aligned grains and that on the disk scale by scattering., Comment: 13 pages, 6 figures. To be published in MNRAS

A rapid decline in mortality and fertility has become major issues in many developed countries over the past few decades. A precise model for forecasting demographic movements is important for decision making in social welfare policies and resource budgeting among the government and many industry sectors. This article introduces a novel non-parametric approach using Gaussian process regression with a natural cubic spline mean function and a spectral mixture covariance function for mortality and fertility modelling and forecasting. Unlike most of the existing approaches in demographic modelling literature, which rely on time parameters to decide the movements of the whole mortality or fertility curve shifting from one year to another over time, we consider the mortality and fertility curves from their components of all age-specific mortality and fertility rates and assume each of them following a Gaussian process over time to fit the whole curves in a discrete but intensive style. The proposed Gaussian process regression approach shows significant improvements in terms of preciseness and robustness compared to other mainstream demographic modelling approaches in the short-, mid- and long-term forecasting using the mortality and fertility data of several developed countries in our numerical experiments.

Human mortality patterns and trajectories in closely related populations are likely linked together and share similarities. It is always desirable to model them simultaneously while taking their heterogeneity into account. This paper introduces two new models for joint mortality modelling and forecasting multiple subpopulations in adaptations of the multivariate functional principal component analysis techniques. The first model extends the independent functional data model to a multi-population modelling setting. In the second one, we propose a novel multivariate functional principal component method for coherent modelling. Its design primarily fulfils the idea that when several subpopulation groups have similar socio-economic conditions or common biological characteristics, such close connections are expected to evolve in a non-diverging fashion. We demonstrate the proposed methods by using sex-specific mortality data. Their forecast performances are further compared with several existing models, including the independent functional data model and the Product-Ratio model, through comparisons with mortality data of ten developed countries. Our experiment results show that the first proposed model maintains a comparable forecast ability with the existing methods. In contrast, the second proposed model outperforms the first model as well as the current models in terms of forecast accuracy, in addition to several desirable properties.

Image registration has been widely studied over the past several decades, with numerous applications in science, engineering and medicine. Most of the conventional mathematical models for large deformation image registration rely on prescribed landmarks, which usually require tedious manual labeling and are prone to error. In recent years, there has been a surge of interest in the use of machine learning for image registration. In this paper, we develop a novel method for large deformation image registration by a fusion of quasiconformal theory and convolutional neural network (CNN). More specifically, we propose a quasiconformal energy model with a novel fidelity term that incorporates the features extracted using a pre-trained CNN, thereby allowing us to obtain meaningful registration results without any guidance of prescribed landmarks. Moreover, unlike many prior image registration methods, the bijectivity of our method is guaranteed by quasiconformal theory. Experimental results are presented to demonstrate the effectiveness of the proposed method. More broadly, our work sheds light on how rigorous mathematical theories and practical machine learning approaches can be integrated for developing computational methods with improved performance.

The Hall effect is recently shown to be efficient in magnetized dense molecular cores, and could lead to a bimodal formation of rotationally supported discs (RSDs) in the first core phase. However, how such Hall dominated systems evolve in the protostellar accretion phase remains unclear. We carry out 2D axisymmetric simulations including Hall effect and Ohmic dissipation, with realistic magnetic diffusivities computed from our equilibrium chemical network. We find that Hall effect only becomes efficient when the large population of very small grains (VSGs: $\lesssim$10 nm) is removed from the standard MRN size distribution. With such an enhanced Hall effect, however, the bimodality of disc formation does not continue into the main accretion phase. The outer part of the initial $\sim$40 AU disc formed in the anti-aligned configuration (${\bf \Omega \cdot B}<0$) flattens into a thin rotationally supported Hall current sheet as Hall effect moves the poloidal magnetic field radially inward relative to matter, leaving only the inner $\lesssim$10--20 AU RSD. In the aligned configuration (${\bf \Omega \cdot B}>0$), disc formation is suppressed initially but a counter-rotating disc forms subsequently due to efficient azimuthal Hall drift. The counter-rotating disc first grows to $\sim$30 AU as Hall effect moves the magnetic field radially outward, but only the inner $\lesssim$10 AU RSD is long-lived like in the anti-aligned case. Besides removing VSGs, cosmic ray ionization rate should be below a few 10$^{-16}$ s$^{-1}$ for Hall effect to be efficient in disc formation. We conclude that Hall effect produces small $\lesssim$10--20 AU discs regardless of the polarity of the magnetic field, and that radially outward diffusion of magnetic fields remains crucial for disc formation and growth., Comment: 22 pages, 18 figures

Non-ideal MHD effects have been shown recently as a robust mechanism of averting the magnetic braking "catastrophe" and promoting protostellar disc formation. However, the magnetic diffusivities that determine the efficiency of non-ideal MHD effects are highly sensitive to microphysics. We carry out non-ideal MHD simulations to explore the role of microphysics on disc formation and the interplay between ambipolar diffusion (AD) and Hall effect during the protostellar collapse. We find that removing the smallest grain population ($\lesssim$10 nm) from the standard MRN size distribution is sufficient for enabling disc formation. Further varying the grain sizes can result in either a Hall-dominated or an AD-dominated collapse; both form discs of tens of AU in size regardless of the magnetic field polarity. The direction of disc rotation is bimodal in the Hall dominated collapse but unimodal in the AD-dominated collapse. We also find that AD and Hall effect can operate either with or against each other in both radial and azimuthal directions, yet the combined effect of AD and Hall is to move the magnetic field radially outward relative to the infalling envelope matter. In addition, microphysics and magnetic field polarity can leave profound imprints both on observables (e.g., outflow morphology, disc to stellar mass ratio) and on the magnetic field characteristics of protoplanetary discs. Including Hall effect relaxes the requirements on microphysics for disc formation, so that prestellar cores with cosmic-ray ionization rate of $\lesssim$2--3$\times10^{-16}$ s$^{-1}$ can still form small discs of $\lesssim$10 AU radius. We conclude that disc formation should be relatively common for typical prestellar core conditions, and that microphysics in the protostellar envelope is essential to not only disc formation, but also protoplanetary disc evolution., Comment: 21 pages, 16 figures, submitted to MNRAS

In order to interact with objects in our environment, humans rely on an understanding of the actions that can be performed on them, as well as their properties. When considering concrete motor actions, this knowledge has been called the object affordance. Can this notion be generalized to any type of interaction that one can have with an object? In this paper we introduce a method to represent objects in a space where each dimension corresponds to a broad mode of interaction, based on verb selectional preferences in text corpora. This object embedding makes it possible to predict human judgments of verb applicability to objects better than a variety of alternative approaches. Furthermore, we show that the dimensions in this space can be used to predict categorical and functional dimensions in a state-of-the-art mental representation of objects, derived solely from human judgements of object similarity. These results suggest that interaction knowledge accounts for a large part of mental representations of objects., Comment: 17 pages, 13 figures, 6 tables

Deep neural networks (DNNs) are being increasingly used to make predictions from functional magnetic resonance imaging (fMRI) data. However, they are widely seen as uninterpretable "black boxes", as it can be difficult to discover what input information is used by the DNN in the process, something important in both cognitive neuroscience and clinical applications. A saliency map is a common approach for producing interpretable visualizations of the relative importance of input features for a prediction. However, methods for creating maps often fail due to DNNs being sensitive to input noise, or by focusing too much on the input and too little on the model. It is also challenging to evaluate how well saliency maps correspond to the truly relevant input information, as ground truth is not always available. In this paper, we review a variety of methods for producing gradient-based saliency maps, and present a new adversarial training method we developed to make DNNs robust to input noise, with the goal of improving interpretability. We introduce two quantitative evaluation procedures for saliency map methods in fMRI, applicable whenever a DNN or linear model is being trained to decode some information from imaging data. We evaluate the procedures using a synthetic dataset where the complex activation structure is known, and on saliency maps produced for DNN and linear models for task decoding in the Human Connectome Project (HCP) dataset. Our key finding is that saliency maps produced with different methods vary widely in interpretability, in both in synthetic and HCP fMRI data. Strikingly, even when DNN and linear models decode at comparable levels of performance, DNN saliency maps score higher on interpretability than linear model saliency maps (derived via weights or gradient). Finally, saliency maps produced with our adversarial training method outperform those from other methods.

Disks are essential to the formation of both stars and planets, but how they form in magnetized molecular cloud cores remains debated. This work focuses on how the disk formation is affected by turbulence and ambipolar diffusion (AD), both separately and in combination, with an emphasis on the protostellar mass accretion phase of star formation. We find that a relatively strong, sonic turbulence on the core scale strongly warps but does not completely disrupt the well-known magnetically-induced flattened pseudodisk that dominates the inner protostellar accretion flow in the laminar case, in agreement with previous work. The turbulence enables the formation of a relatively large disk at early times with or without ambipolar diffusion, but such a disk remains strongly magnetized and does not persist to the end of our simulation unless a relatively strong ambipolar diffusion is also present. The AD-enabled disks in laminar simulations tend to fragment gravitationally. The disk fragmentation is suppressed by initial turbulence. The ambipolar diffusion facilitates the disk formation and survival by reducing the field strength in the circumstellar region through magnetic flux redistribution and by making the field lines there less pinched azimuthally, especially at late times. We conclude that turbulence and ambipolar diffusion complement each other in promoting disk formation. The disks formed in our simulations inherit a rather strong magnetic field from its parental core, with a typical plasma-$\beta$ of order a few tens or smaller, which is 2-3 orders of magnitude lower than the values commonly adopted in MHD simulations of protoplanetary disks. To resolve this potential tension, longer-term simulations of disk formation and evolution with increasingly more realistic physics are needed., Comment: 24 pages, 16 figures

Distinguishing diagnostic observational signatures produced by MHD models is essential in understanding the physics for the formation of protostellar disks in the ALMA era. Developing suitable tools along with time evolution will facilitate better identification of diagnostic features. With a ray-tracing based radiative transfer code Perspective, we explore time evolution of MHD models carried out in Li, Krasnopolsky & Shang (2013) - most of which have $90^\circ$ misalignment between the rotational axis and the magnetic field. Four visible object types can be characterized, origins of which are dependent on the initial conditions. Our results show complex spiraling density, velocity and polarization structures. The systems are under constant change, but many of those distinctive features are present already early on, and they grow more visible in time, but most could not be identified from the data without examining their change in time. The results suggest that spiraling pseudodisk structures could function as an effective observation signature of the formation process, and we witness accretion in the disk with eccentric orbits which appear as spiral-like perturbation from simple circular Keplerian orbits. Magnetically aligned polarization appears purely azimuthal in the disk and magnetic field can lead to precession of the disk., Comment: 28 pages, 19 Figures and 3 Tables. Accepted for Publication in ApJ