DELVE-ing into the Jet: A Thin Stellar Stream on a Retrograde Orbit at 30 kpc

We perform a detailed photometric and astrometric analysis of stars in the Jet stream using data from the first data release of the DECam Local Volume Exploration Survey DR1 and Gaia EDR3. We discover that the stream extends over ∼ 29° on the sky (increasing the known length by 18°), which is comparable to the kinematically cold Phoenix, ATLAS, and GD-1 streams. Using blue horizontal branch stars, we resolve a distance gradient along the Jet stream of 0.2 kpc deg−1, with distances ranging from D ⊙ ∼ 27–34 kpc. We use natural splines to simultaneously fit the stream track, width, and intensity to quantitatively characterize density variations in the Jet stream, including a large gap, and identify substructure off the main track of the stream. Furthermore, we report the first measurement of the proper motion of the Jet stream and find that it is well aligned with the stream track, suggesting the stream has likely not been significantly perturbed perpendicular to the line of sight. Finally, we fit the stream with a dynamical model and find that it is on a retrograde orbit, and is well fit by a gravitational potential including the Milky Way and Large Magellanic Cloud. These results indicate the Jet stream is an excellent candidate for future studies with deeper photometry, astrometry, and spectroscopy to study the potential of the Milky Way and probe perturbations from baryonic and dark matter substructure.

Three-dimensional segmentation of computed tomography data using Drishti Paint : new tools and developments

Computed tomography (CT) has become very widely used in scientific and medical research and industry for its non-destructive and high-resolution means of detecting internal structure. Three-dimensional segmentation of computed tomography data sheds light on internal features of target objects. Three-dimensional segmentation of CT data is supported by various well-established software programs, but the powerful functionalities and capabilities of open-source software have not been fully revealed. Here, we present a new release of the open-source volume exploration, rendering and three-dimensional segmentation software, Drishti v. 2.7. We introduce a new tool for thresholding volume data (i.e. gradient thresholding) and a protocol for performing three-dimensional segmentation using the 3D Freeform Painter tool. These new tools and workflow enable more accurate and precise digital reconstruction, three-dimensional modelling and three-dimensional printing results. We use scan data of a fossil fish as a case study, but our procedure is widely applicable in biological, medical and industrial research.

A new tool for 3D segmentation of computed tomography data: Drishti Paint and its applications

Computational tomography is more and more widely used in many fields for its non-destructive and high-resolution in detecting internal structures of the samples. 3D segmentation of computed tomography data, which sheds light into internal features of target objects, is increasingly gaining in importance. However, how to efficiently and precisely reconstruct computed tomography data and better represent the data remains a hassle. Here, using a set of scan data of a fossil fish as a case study, we present a new release of open-source volume exploration, rendering, and 3D segmentation software, Drishti v2.6.6, and its protocol for performing 3D segmentation and other advanced applications. We provide new toolsets and workflow to segment computed tomography data thus benefit the scientific community with more accurate and precise digital reconstruction, 3D modelling and 3D printing results. Our procedure is widely applicable not only in palaeontology, but also in biological, medical, and industrial researches, and can be used as a framework to segment computed tomography and other forms of volumetric data from any research field.

The Economy of Canopy Space Occupation and Shade Production in Early- to Late-Successional Temperate Tree Species and Their Relation to Productivity

Light capture is linked to occupation of canopy space by tree crowns, which requires investment of carbon and nutrients. We hypothesize that (i) late-successional trees invest more in casting shade than in occupying space than early-successional trees, and (ii) shade production and crown volume expansion are generally greater in more productive species. For six Central European early-successional (Betula pendula, Pinus sylvestris), mid/late-successional (Quercus petraea, Carpinus betulus), and late-successional tree species (Tilia cordata, Fagus sylvatica), we measured through full-tree harvests (1) crown volume, (2) the costs of canopy space exploration (carbon (C) and nutrients invested to fill crown volume), of space occupation (annual foliage production per volume), and of shade production (foliage needed to reduce light transmittance), and (3) related the costs to aboveground productivity (ANPP). The C and nutrient costs of canopy volume exploration and occupation were independent of the species’ seral stage, but increased with ANPP. In contrast, the cost of shade production decreased from early-to late-successional species, suggesting that the economy of shade production is more decisive for the competitive superiority of late-successional species than the economy of canopy space exploration and occupation.