Invest to Save: Report and Recommendations of the NSF-DELOS Working Group on Digital Archiving and Preservation

Digital archiving and preservation are important areas for research and development, but there is no agreed upon set of priorities or coherent plan for research in this area. Research projects in this area tend to be small and driven by particular institutional problems or concerns. As a consequence, proposed solutions from experimental projects and prototypes tend not to scale to millions of digital objects, nor do the results from disparate projects readily build on each other. It is also unclear whether it is worthwhile to seek general solutions or whether different strategies are needed for different types of digital objects and collections. The lack of coordination in both research and development means that there are some areas where researchers are reinventing the wheel while other areas are neglected. Digital archiving and preservation is an area that will benefit from an exercise in analysis, priority setting, and planning for future research. The WG aims to survey current research activities, identify gaps, and develop a white paper proposing future research directions in the area of digital preservation. Some of the potential areas for research include repository architectures and inter-operability among digital archives; automated tools for capture, ingest, and normalization of digital objects; and harmonization of preservation formats and metadata. There can also be opportunities for development of commercial products in the areas of mass storage systems, repositories and repository management systems, and data management software and tools.

Asteroseismic detection of latitudinal differential rotation in 13 Sun-like stars

The differentially rotating outer layers of stars are thought to play a role in driving their magnetic activity, but the underlying mechanisms that generate and sustain differential rotation are poorly understood. We report the measurement of latitudinal differential rotation in the convection zones of 40 Sun-like stars using asteroseismology. For the most significant detections, the stars' equators rotate approximately twice as fast as their mid-latitudes. The latitudinal shear inferred from asteroseismology is much larger than predictions from numerical simulations.Comment: 45 pages, 11 figures, 4 tables, published in Scienc

Butterfly diagram of a Sun-like star observed using asteroseismology

Stellar magnetic fields are poorly understood but are known to be important for stellar evolution and exoplanet habitability. They drive stellar activity, which is the main observational constraint on theoretical models for magnetic field generation and evolution. Starspots are the main manifestation of the magnetic fields at the stellar surface. In this study we measure the variation of their latitude with time, called a butterfly diagram in the solar case, for the solar analogue HD 173701 (KIC 8006161). To that effect, we use Kepler data, to combine starspot rotation rates at different epochs and the asteroseismically determined latitudinal variation of the stellar rotation rates. We observe a clear variation of the latitude of the starspots. It is the first time such a diagram is constructed using asteroseismic data.Comment: 8 pages, 4 figures, accepted in A&A Letter

Development of a single retention time prediction model integrating multiple liquid chromatography systems: Application to new psychoactive substances.

Database-driven suspect screening has proven to be a useful tool to detect new psychoactive substances (NPS) outside the scope of targeted screening; however, the lack of retention times specific to a liquid chromatography (LC) system can result in a large number of false positives. A singular stream-lined, quantitative structure-retention relationship (QSRR)-based retention time prediction model integrating multiple LC systems with different elution conditions is presented using retention time data (n = 1281) from the online crowd-sourced database, HighResNPS. Modelling was performed using an artificial neural network (ANN), specifically a multi-layer perceptron (MLP), using four molecular descriptors and one-hot encoding of categorical labels. Evaluation of test set predictions (n = 193) yielded coefficient of determination (R2) and mean absolute error (MAE) values of 0.942 and 0.583 min, respectively. The model successfully differentiated between LC systems, predicting 54%, 81% and 97% of the test set within ±0.5, ±1 and ±2 min, respectively. Additionally, retention times for an analyte not previously observed by the model were predicted within ±1 min for each LC system. The developed model can be used to predict retention times for all analytes on HighResNPS for each participating laboratory's LC system to further support suspect screening

Combining pressing and alkaline extraction to increase protein yield from Ulva fenestrata biomass

Many seaweed species have a high production potential and attract interest as future protein sources. A high fiber and ash content, however, demand extraction of the protein to improve its digestibility and protein utilization in food or feed. This study explores three different approaches for protein extraction from Ulva fenestrata in order to maximize the protein extraction yield. Soluble protein was recovered either by mechanical pressing or by homogenization and osmotic shock of the biomass followed by alkaline extraction. The soluble protein was then concentrated by isoelectric precipitation. A combined procedure was carried out by pressing the biomass and following subjecting the residual pulp fraction to homogenization, osmotic shock and alkaline extraction. The three methods were ranked as follows with respect to protein extraction yield (as % of biomass protein); the combined method (23.9 \ub1 0.3%)> the alkaline extraction (6.8 \ub1 0.2%)> mechanical pressing (5.0 \ub1 0.2%). The significant increase when combining the methods was ascribed to a high precipitation yield after alkaline extraction of the pulp, hypothesized to be due to a reduced conductivity of the alkali-soluble protein fraction when derived from pulp rather than whole biomass