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We present a path-based design model and system for designing and creating visualisations. Our model represents a systematic approach to constructing visual representations of data or concepts following a predefined sequence of steps. The initial step involves outlining the overall appearance of the visualisation by creating a skeleton structure, referred to as a flowpath. Subsequently, we specify objects, visual marks, properties, and appearance, storing them in a gene. Lastly, we map data onto the flowpath, ensuring suitable morphisms. Alternative designs are created by exchanging values in the gene. For example, designs that share similar traits, are created by making small incremental changes to the gene. Our design methodology fosters the generation of diverse creative concepts, space-filling visualisations, and traditional formats like bar charts, circular plots and pie charts. Through our implementation we showcase the model in action. As an example application, we integrate the output visualisations onto a smartwatch and visualisation dashboards. In this article we (1) introduce, define and explain the path model and discuss possibilities for its use, (2) present our implementation, results, and evaluation, and (3) demonstrate and evaluate an application of its use on a mobile watch., Comment: 11 pages, 14 figures, accepted for publication in IEEE Transactions on Visualization and Computer Graphics

Administrative databases, such as the English School Census (ESC), are rich sources of information that are potentially useful for researchers. For such data sources to be made available, however, strict guarantees of privacy would be required. To achieve this, synthetic data methods can be used. Such methods, when protecting the confidentiality of tabular data (contingency tables), often utilise the Poisson or Poisson-mixture distributions, such as the negative binomial (NBI). These distributions, however, are either equidispersed (in the case of the Poisson) or overdispersed (e.g. in the case of the NBI), which results in excessive noise being applied to large low-risk counts. This paper proposes the use of the (discretized) gamma family (GAF) distribution, which allows noise to be applied in a more bespoke fashion. Specifically, it allows less noise to be applied as cell counts become larger, providing an optimal balance in relation to the risk-utility trade-off. We illustrate the suitability of the GAF distribution on an administrative-type data set that is reminiscent of the ESC.

An approach to amputation, the process of introducing missing values to a complete dataset, is presented. It allows to construct missingness indicators in a flexible and principled way via copulas and Bernoulli margins and to incorporate dependence in missingness patterns. Besides more classical missingness models such as missing completely at random, missing at random, and missing not at random, the approach is able to model structured missingness such as block missingness and, via mixtures, monotone missingness, which are patterns of missing data frequently found in real-life datasets. Properties such as joint missingness probabilities or missingness correlation are derived mathematically. The approach is demonstrated with mathematical examples and empirical illustrations in terms of a well-known dataset.

We show that differential privacy type guarantees can be obtained when using a Poisson synthesis mechanism to protect counts in contingency tables. Specifically, we show how to obtain $(\epsilon, \delta)$-probabilistic differential privacy guarantees via the Poisson distribution's cumulative distribution function. We demonstrate this empirically with the synthesis of an administrative-type confidential database.

We present 870 um polarimetric observations toward 61 protostars in the Orion molecular clouds, with ~400 au (1") resolution using the Atacama Large Millimeter/submillimeter Array. We successfully detect dust polarization and outflow emission in 56 protostars, in 16 of them the polarization is likely produced by self-scattering. Self-scattering signatures are seen in several Class 0 sources, suggesting that grain growth appears to be significant in disks at earlier protostellar phases. For the rest of the protostars, the dust polarization traces the magnetic field, whose morphology can be approximately classified into three categories: standard-hourglass, rotated-hourglass (with its axis perpendicular to outflow), and spiral-like morphology. 40.0% (+-3.0%) of the protostars exhibit a mean magnetic field direction approximately perpendicular to the outflow on several 100--1000 au scales. However, in the remaining sample, this relative orientation appears to be random, probably due to the complex set of morphologies observed. Furthermore, we classify the protostars into three types based on the C17O (3--2) velocity envelope's gradient: perpendicular to outflow, non-perpendicular to outflow, and unresolved gradient (<1.0~km/s/arcsec). In protostars with a velocity gradient perpendicular to outflow, the magnetic field lines are preferentially perpendicular to outflow, most of them exhibit a rotated hourglass morphology, suggesting that the magnetic field has been overwhelmed by gravity and angular momentum. Spiral-like magnetic fields are associated with envelopes having large velocity gradients, indicating that the rotation motions are strong enough to twist the field lines. All of the protostars with a standard-hourglass field morphology show no significant velocity gradient due to the strong magnetic braking., Comment: 12 pages, 5 figures (16 pages and 7 figures for the supplementary materials) Accepted for publication on ApJ Letters

Our capacity to process large complex data sources is ever-increasing, providing us with new, important applied research questions to address, such as how to handle missing values in large-scale databases. Mitra et al. (2023) noted the phenomenon of Structured Missingness (SM), which is where missingness has an underlying structure. Existing taxonomies for defining missingness mechanisms typically assume that variables' missingness indicator vectors $M_1$, $M_2$, ..., $M_p$ are independent after conditioning on the relevant portion of the data matrix $\mathbf{X}$. As this is often unsuitable for characterising SM in multivariate settings, we introduce a taxonomy for SM, where each ${M}_j$ can depend on $\mathbf{M}_{-j}$ (i.e., all missingness indicator vectors except ${M}_j$), in addition to $\mathbf{X}$. We embed this new framework within the well-established decomposition of mechanisms into MCAR, MAR, and MNAR (Rubin, 1976), allowing us to recast mechanisms into a broader setting, where we can consider the combined effect of $\mathbf{X}$ and $\mathbf{M}_{-j}$ on ${M}_j$. We also demonstrate, via simulations, the impact of SM on inference and prediction, and consider contextual instances of SM arising in a de-identified nationwide (US-based) clinico-genomic database (CGDB). We hope to stimulate interest in SM, and encourage timely research into this phenomenon.

The initial conditions found in infrared dark clouds (IRDCs) provide insights on how high-mass stars and stellar clusters form. We have conducted high-angular resolution and high-sensitivity observations toward thirty-nine massive IRDC clumps, which have been mosaicked using the 12m and 7m arrays from the Atacama Large Millimeter/submillimeter Array (ALMA). The targets are 70 $\mu$m dark massive (220-4900 $M_\odot$), dense ($>$10$^4$ cm$^{-3}$), and cold ($\sim$10-20K) clumps located at distances between 2 and 6 kpc. We identify an unprecedented number of 839 cores, with masses between 0.05 and 81 $M_\odot$ using 1.3 mm dust continuum emission. About 55% of the cores are low-mass ($<$1 $M_\odot$), whereas $\lesssim$1% (7/839) are high-mass ($\gtrsim$27 $M_\odot$). We detect no high-mass prestellar cores. The most massive cores (MMC) identified within individual clumps lack sufficient mass to form high-mass stars without additional mass feeding. We find that the mass of the MMCs is correlated with the clump surface density, implying denser clumps produce more massive cores and a larger number of cores. There is no significant mass segregation except for a few tentative detections. In contrast, most clumps show segregation once the clump density is considered instead of mass. Although the dust continuum emission resolves clumps in a network of filaments, some of which consist of hub-filament systems, the majority of the MMCs are not found in the hubs. Our analysis shows that high-mass cores and MMCs have no preferred location with respect to low-mass cores at the earliest stages of high-mass star formation., Comment: Accepted for Publication in ApJ. 54 pages, 40 figures, 5 tables

Until recently, multiple synthetic data sets were always released to analysts, to allow valid inferences to be obtained. However, under certain conditions - including when saturated count models are used to synthesize categorical data - single imputation ($m=1$) is sufficient. Nevertheless, increasing $m$ causes utility to improve, but at the expense of higher risk, an example of the risk-utility trade-off. The question, therefore, is: which value of $m$ is optimal with respect to the risk-utility trade-off? Moreover, the paper considers two ways of analysing categorical data sets: as they have a contingency table representation, multiple categorical data sets can be averaged before being analysed, as opposed to the usual way of averaging post-analysis. This paper also introduces a pair of metrics, $\tau_3(k,d)$ and $\tau_4(k,d)$, that are suited for assessing disclosure risk in multiple categorical synthetic data sets. Finally, the synthesis methods are demonstrated empirically.

Star formation primarily occurs in filaments where magnetic fields are expected to be dynamically important. The largest and densest filaments trace spiral structure within galaxies. Over a dozen of these dense ($\sim$10$^4$\,cm$^{-3}$) and long ($>$10\,pc) filaments have been found within the Milky Way, and they are often referred to as "bones." Until now, none of these bones have had their magnetic field resolved and mapped in their entirety. We introduce the SOFIA legacy project FIELDMAPS which has begun mapping $\sim$10 of these Milky Way bones using the HAWC+ instrument at 214\,$\mu$m and 18$\farcs$2 resolution. Here we present a first result from this survey on the $\sim$60\,pc long bone G47. Contrary to some studies of dense filaments in the Galactic plane, we find that the magnetic field is often not perpendicular to the spine (i.e., the center-line of the bone). Fields tend to be perpendicular in the densest areas of active star formation and more parallel or random in other areas. The average field is neither parallel or perpendicular to the Galactic plane nor the bone. The magnetic field strengths along the spine typically vary from $\sim$20 to $\sim$100\,$\mu$G. Magnetic fields tend to be strong enough to suppress collapse along much of the bone, but for areas that are most active in star formation, the fields are notably less able to resist gravitational collapse., Comment: Accepted to ApJL; typo in author list metadata corrected

With a mass of $\sim$1000 $M_\odot$ and a surface density of $\sim$0.5 g cm$^{-2}$, G023.477+0.114 also known as IRDC 18310-4 is an infrared dark cloud (IRDC) that has the potential to form high-mass stars and has been recognized as a promising prestellar clump candidate. To characterize the early stages of high-mass star formation, we have observed G023.477+0.114 as part of the ALMA Survey of 70 $\mu$m Dark High-mass Clumps in Early Stages (ASHES). We have conducted $\sim$1."2 resolution observations with the Atacama Large Millimeter/submillimeter Array (ALMA) at 1.3 mm in dust continuum and molecular line emission. We identified 11 cores, whose masses range from 1.1 $M_\odot$ to 19.0 $M_\odot$. Ignoring magnetic fields, the virial parameters of the cores are below unity, implying that the cores are gravitationally bound. However, when magnetic fields are included, the prestellar cores are close to virial equilibrium, while the protostellar cores remain sub-virialized. Star formation activity has already started in this clump. Four collimated outflows are detected in CO and SiO. H$_2$CO and CH$_3$OH emission coincide with the high-velocity components seen in the CO and SiO emission. The outflows are randomly oriented for the natal filament and the magnetic field. The position-velocity diagrams suggest that episodic mass ejection has already begun even in this very early phase of protostellar formation. The masses of the identified cores are comparable to the expected maximum stellar mass that this IRDC could form (8-19 $M_\odot$). We explore two possibilities on how IRDC G023.477+0.114 could eventually form high-mass stars in the context of theoretical scenarios., Comment: Accepted for publication in ApJ (September 1, 2021). 33 pages, 20 figures, and 5 tables

Over the past three decades, synthetic data methods for statistical disclosure control have continually evolved, but mainly within the domain of survey data sets. There are certain characteristics of administrative databases, such as their size, which present challenges from a synthesis perspective and require special attention. This paper, through the fitting of saturated count models, presents a synthesis method that is suitable for administrative databases that is tuned by two parameters. The method allows large categorical data sets to be synthesized quickly and allows risk and utility metrics to be satisfied a priori, that is, prior to synthetic data generation. The paper explores how the flexibility afforded by two-parameter count models (the negative binomial and Poisson-inverse Gaussian) can be utilised to protect respondents' - especially uniques' - privacy in synthetic data. Finally, an empirical example is carried out through the synthesis of a database which can be viewed as a good substitute to the English School Census., Comment: 37 pages, 6 figures

A full understanding of high-mass star formation requires the study of one of the most elusive components of the energy balance in the interstellar medium: magnetic fields. We report ALMA 1.2 mm, high-resolution (700 au) dust polarization and molecular line observations of the rotating hot molecular core embedded in the high-mass star-forming region IRAS 18089-1732. The dust continuum emission and magnetic field morphology present spiral-like features resembling a whirlpool. The velocity field traced by the H13CO+ (J=3-2) transition line reveals a complex structure with spiral filaments that are likely infalling and rotating, dragging the field with them. We have modeled the magnetic field and find that the best model corresponds to a weakly magnetized core with a mass-to-magnetic-flux ratio (lambda) of 8.38. The modeled magnetic field is dominated by a poloidal component, but with an important contribution from the toroidal component that has a magnitude of 30% of the poloidal component. Using the Davis-Chandrasekhar-Fermi method, we estimate a magnetic field strength of 3.5 mG. At the spatial scales accessible to ALMA, an analysis of the energy balance of the system indicates that gravity overwhelms turbulence, rotation, and the magnetic field. We show that high-mass star formation can occur in weakly magnetized environments, with gravity taking the dominant role., Comment: Accepted for publications in ApJL (12 pages, 5 figures, Appendix)