Both the global research community and federal governments are embracing a move toward more open sharing of the products of research. Historically, the primary product of research has been the peer-reviewed journal article for fundamental research and government technical report for applied research and engineering for government sponsored research. However, advances in information technology, new “open access” business models, and government policies are working to make publications and supporting materials much more accessible to the general public. These same drivers are obscuring the distinction between the data generated through the course of research and the associated publications. These developments have the potential to significantly enhance the value of both publications and the supporting digital research data, turning them into valuable assets that can be shared and reused by other researchers. The confluence of these shifts in the research landscape leads one to the conclusion that technical publications and their supporting research data must become bound together in a rational fashion. However, bringing these two research products together will require establishment of new policies and a supporting data infrastructure that have essentially no precedent in the materials community, and indeed are stressing many other fields of research. This document raises the key issues that must be addressed in developing these policies and infrastructure, and suggests a path forward in creating the solutions.

I present the progress that has been made towards implementing a Square Root Information Filter (SRIF) into the asteroid-modelling software SHAPE. I compare SRIF’s performance with the current fitting algorithm, with the conclusion that SRIF has the potential to perform substantially better than its predecessor. I show the results of SRIF operating on previously collected delay-doppler data for the asteroid 2000 ET70. I also discuss potential future changes to improve shape’s fitting speed and accuracy.

Knowledge transfer is computationally challenging, due in part to the curse of dimensionality, compounded by source and target domains expressed using different features (e.g., documents written in different languages). Recent work on manifold learning has shown that data collected in real-world settings often have high-dimensional representations, but lie on low-dimensional manifolds. Furthermore, data sets collected from similar generating processes often present different high-dimensional views, even though their underlying manifolds are similar. The ability to align these data sets and extract this common structure is critical for many transfer learning tasks. In this paper, we present a novel framework for aligning two sequentially-ordered data sets, taking advantage of a shared low-dimensional manifold representation. Our approach combines traditional manifold alignment and dynamic time warping algorithms using alternating projections. We also show that the previously-proposed canonical time warping algorithm is a special case of our approach. We provide a theoretical formulation as well as experimental results on synthetic and real-world data, comparing manifold warping to other alignment methods.

Gaia is a European Space Agency (ESA) astrometry space mission, and a successor to the ESA Hipparcos mission. The main goal of the Gaia mission is to collect high-precision astrometric data (i.e. positions, parallaxes, and proper motions) for the brightest one billion objects in the sky. This data, complemented with G band, multi-epoch photometric and low resolution (lowers) spectroscopic data collected from the same observing platform, will allow astronomers to reconstruct the formation history, structure, and evolution of the Galaxy. In addition, the Gaia satellite is an excellent transient discovery instrument, covering the whole sky (including the Galactic plane) for the next 5 years, at high spatial resolution (50 to 100 mas, similar to the Hubble space telescope (HST)) with precise photometry (1% at G=19) and milliarcsecond astrometry (down to ∼20mag). Thus, Gaia provides a unique opportunity for the discovery of large numbers of transient and anomalous events, e.g. supernovae, black hole binaries and tidal disruption events. We discuss the validation of the alerts stream for the first six months of the Gaia observations, in particular noting how a significant ground based campaign involving photometric and spectroscopic followup of early Gaia alerts is now in place. We discuss the validation approach, and highlight in more detail the specific case of Type Ia supernova (SNe Ia) to be discovered by Gaia. The intense initial ground based validation campaign will ensure that the Gaia alerts stream for the remainder of the Gaia mission, are well classified.

Dihydrobiopterin (H₂Bip) and biopterin (Bip) accumulate in the skin of patients suffering from vitiligo, whose lack of melanin causes a deficient protection against UV radiation. H₂Bip and Bip undergo photooxidation upon UV irradiation and the former acts as a photosensitizer of biomolecules. The aim of this work is to study the photochemical reactions of these compounds triggered by sunlight under outdoor conditions. H₂Bip and Bip in aqueous solutions were exposed to sunlight in La Plata city (34.90∘S, 57.92∘W) from Spring equinox to near Summer solstice and the spectral solar irradiance was recorded with a high-resolution spectrometer. The photochemical reactions were followed by HPLC and UV-Vis spectrophotometry. Upon sun exposure, excitation of H₂Bip leads to the formation of dimers and to its oxidation to Bip, which, in turn, is photooxidized into 6-formylpterin (Fop). Further excitation induces the oxidation of Fop to 6-carboxypterin, which is much more photostable than Bip and Fop and then it is accumulated in the solution. Rates of reactant consumption were determined under different weather conditions and the corresponding quantum yields were also calculated. We have demonstrated that solar radiation causes significant oxidation of the pterin derivatives investigated within a few minutes, even in cloudy days. Finally, the biological implications of our results are discussed.

The uncertainty in time of particle detection within a scintillator detector, characterised by the coincidence time resolution (CTR), is explored with respect to the interaction position within the scintillator crystal itself. Electronic collimation between two scintillator detectors is utilised to determine the CTR with depth of interaction (DOI) for different materials, geometries and wrappings. Significantly, no relationship between the CTR and DOI is observed within experimental error. Confinement of the interaction position is seen to degrade the CTR in long scintillator crystals by 10%.

INTRODUCTORY PARAGRAPH We explored the microbial contributions to decomposition using a sophisticated approach to DNA Stable Isotope Probing (SIP). Our experiment evaluated the dynamics and ecological characteristics of functionally defined microbial groups that metabolize labile and structural C in soils. We added to soil a complex amendment representing plant derived organic matter substituted with either ¹³C-xylose or ¹³C-cellulose to represent labile and structural C pools derived from abundant components of plant biomass. We found evidence for ¹³C-incorporation into DNA from ¹³C-xylose and ¹³C-cellulose in 49 and 63 operational taxonomic units (OTUs), respectively. The types of microorganisms that assimilated ¹³C in the ¹³C-xylose treatment changed over time being predominantly _Firmicutes_ at day 1 followed by _Bacteroidetes_ at day 3 and then _Actinobacteria_ at day 7. These ¹³C-labeling dynamics suggest labile C traveled through different trophic levels. In contrast, microorganisms generally metabolized cellulose-C after 14 days and did not change to the same extent in phylogenetic composition over time. Microorganisms that metabolized cellulose-C belonged to poorly characterized but cosmopolitan soil lineages including _Verrucomicrobia_, _Chloroflexi_ and _Planctomycetes_.

INTRODUCTION In the early 1600s, Galileo Galilei turned a telescope toward Jupiter. In his log book each night, he drew to-scale schematic diagrams of Jupiter and some oddly-moving points of light near it. Galileo labeled each drawing with the date. Eventually he used his observations to conclude that the Earth orbits the Sun, just as the four Galilean moons orbit Jupiter. History shows Galileo to be much more than an astronomical hero, though. His clear and careful record keeping and publication style not only let Galileo understand the Solar System, it continues to let _anyone_ understand _how_ Galileo did it. Galileo’s notes directly integrated his DATA (drawings of Jupiter and its moons), key METADATA (timing of each observation, weather, telescope properties), and TEXT (descriptions of methods, analysis, and conclusions). Critically, when Galileo included the information from those notes in _Siderius Nuncius_ , this integration of text, data and metadata was preserved, as shown in Figure 1. Galileo's work advanced the "Scientific Revolution," and his approach to observation and analysis contributed significantly to the shaping of today's modern "Scientific Method" . Today most research projects are considered complete when a journal article based on the analysis has been written and published. Trouble is, unlike Galileo's report in _Siderius Nuncius_, the amount of real data and data description in modern publications is almost never sufficient to repeat or even statistically verify a study being presented. Worse, researchers wishing to build upon and extend work presented in the literature often have trouble recovering data associated with an article after it has been published. More often than scientists would like to admit, they cannot even recover the data associated with their own published works. Complicating the modern situation, the words "data" and "analysis" have a wider variety of definitions today than at the time of Galileo. Theoretical investigations can create large "data" sets through simulations (e.g. The Millennium Simulation Project). Large scale data collection often takes place as a community-wide effort (e.g. The Human Genome project), which leads to gigantic online "databases" (organized collections of data). Computers are so essential in simulations, and in the processing of experimental and observational data, that it is also often hard to draw a dividing line between "data" and "analysis" (or "code") when discussing the care and feeding of "data." Sometimes, a copy of the code used to create or process data is so essential to the use of those data that the code should almost be thought of as part of the "metadata" description of the data. Other times, the code used in a scientific study is more separable from the data, but even then, many preservation and sharing principles apply to code just as well as they do to data. So how do we go about caring for and feeding data? Extra work, no doubt, is associated with nurturing your data, but care up front will save time and increase insight later. Even though a growing number of researchers, especially in large collaborations, know that conducting research with sharing and reuse in mind is essential, it still requires a paradigm shift. Most people are still motivated by piling up publications and by getting to the next one as soon as possible. But, the more we scientists find ourselves wishing we had access to extant but now unfindable data , the more we will realize why bad data management is bad for science. How can we improve? THIS ARTICLE OFFERS A SHORT GUIDE TO THE STEPS SCIENTISTS CAN TAKE TO ENSURE THAT THEIR DATA AND ASSOCIATED ANALYSES CONTINUE TO BE OF VALUE AND TO BE RECOGNIZED. In just the past few years, hundreds of scholarly papers and reports have been written on questions of data sharing, data provenance, research reproducibility, licensing, attribution, privacy, and more--but our goal here is _not_ to review that literature. Instead, we present a short guide intended for researchers who want to know why it is important to "care for and feed" data, with some practical advice on how to do that. The set of Appendices at the close of this work offer links to the types of services referred to throughout the text. BOLDFACE LETTERING below highlights actions one can take to follow the suggested rules.

Synthetic biology has had profound effects on human life. It has provided more effective anti-malarial medicine, cheaper insulin, new useful bio-materials, and greener biofuels. However, much remains to be learned in order to synthesize proteins more efficiently. To explore the potential of the DIY biology movement to engage in meaningful synthetic biology bioinformatics research, we developed a bioinformatics workshop to study determinants of protein expression levels in plants. We extracted possible ribosome binding and translation initiation sequences and looked for correlations with experimentally determined protein levels, using publicly available data sets for the widely studied plants _Oryza sativa_ and _Arabidopsis thaliana_. The working group was open to the public and met every other week for 3 hours, typically starting with a short, relevant presentation followed by hands-on data work. We aim to develop, experimentally validate, and publish our consensus sequences, anticipating that our work will be useful for plant synthetic biology research. We hope our experience will serve as a model for future community projects that serve the dual purpose of educating curious members of the public while also generating useful scientific results.

INTRODUCTION The Higgs boson with mass around 125 GeV recently discovered by the ATLAS and CMS experiments  at the LHC is found to have properties compatible with the Standard Model predictions , as shown for example in Fig. [fig:ellis] . Coupled with the absence of any other indication so far for new physics at the LHC, be it either through precision measurements or via direct searches, this fundamental observation seems to push the energy scale of any physics beyond the Standard Model above several hundred GeV. The higher-energy LHC run, which is expected to start in 2015 at $ \sim 13$-14 TeV, will extend the sensitivity to new physics to 1 TeV or more. Fundamental discoveries may therefore be made in this energy range by 2017-2018. Independently of the outcome of this higher-energy run, however, there must be new phenomena, albeit at unknown energy scales, as shown by the evidence for non-baryonic dark matter, the cosmological baryon-antibaryon asymmetry and non-zero neutrino masses, which are all evidence for physics beyond the Standard Model. In addition to the high-luminosity upgrade of the LHC, new particle accelerators will be instrumental to understand the physics underlying these observations.

We combine _Kepler_ photometry with ground-based spectra to present a comprehensive dynamical model of the double red giant eclipsing binary KIC 9246715. While the two stars are very similar in mass ($M_1 = 2.171 \ M_{\odot}$, $M_2 = 2.149 \ M_{\odot}$) and radius ($R_1 = 8.37 \ R_{\odot}$, $R_2 = 8.30 \ R_{\odot}$), an asteroseismic analysis finds one main set of solar-like oscillations with unusually low-amplitude, wide modes. A second set of oscillations from the other star may exist, but this marginal detection is extremely faint. Because the two stars are nearly twins, KIC 9246715 is a difficult target for a precise test of the asteroseismic scaling relations, which yield M = 2.17 ± 0.14 M⊙ and R = 8.26 ± 0.18 R⊙. Both stars are consistent with the inferred asteroseismic properties, but we suspect the main oscillator is Star 2 because it is less active than Star 1. We find evidence for stellar activity and modest tidal forces acting over the 171-day eccentric orbit, which are likely responsible for the essential lack of solar-like oscillations in one star and weak oscillations in the other. Mixed modes indicate the main oscillating star is on the secondary red clump (a core-He-burning star), and stellar evolution modeling supports this with a coeval history for a pair of red clump stars. This system is a useful case study and paves the way for a detailed analysis of more red giants in eclipsing binaries, an important benchmark for asteroseismology.

This paper describes the deployment of a novel ubiquitous behaviour change system for social interaction and reflection amongst school children. For four weeks, a class of schoolchildren (Year 5) was monitored with Fitbit activity monitors and their daily physical activity was visualised on a custom ambient display. In addition, video segments describing mission-based activities were shown on tablet devices to the children at the start of each week. The ambient display would indicate if they performed better than the previous day. We describe how the system was designed and developed, present findings from the in-the-wild study, and provide design guidelines for future studies.

ABSTRACT. ρ Ophiuchii is a group of five B-stars, embedded in a nearby molecular cloud: Ophiuchus, at a distance of ∼ 119 pc. A “bubble”-like structure is found in dust thermal emission around ρ Oph. The circular structure on the Hα map further indicates that this bubble is physically connected to the source at the center. The goal of this paper is to estimate the impact of feedback from these embedded B-stars on the molecular cloud, by comparing the energy associated with the material entrained in the bubble to the total turbulent energy of the cloud. In this paper, we combine data from the COMPLETE Survey, which includes ¹²CO (1-0) and ¹³CO (1-0) molecular line emission from FCRAO, an extinction map derived from 2MASS near-infrared data using the NICER algorithm, and far-infrared data from IRIS (60/100 μm) with data from the Herschel Science Archive (PACS 100/160 μm and SPIRE 250/350/500 μm). With the wealth of data tracing different components of the cloud, we try to determine the best strategy to derive physical properties and to estimate the energy budget in the shell and in the cloud. We also experiment with the hierarchical Bayesian-fitting technique introduced by in an effort to eliminate the bias in the derived column densities and/or temperatures induced by noise in the far-IR data. We find that the energy entrained in the bubble is ∼ 12 % of the total turbulent energy of the Ophiuchus molecular cloud. This fraction is similar to the number give for the Perseus molecular cloud, and it suggests the non-negligible role of B-stars in driving the turbulence in clouds. We expect that a complete survey of “bubbles” in the Ophiuchus cloud will reveal the importance of B-star winds in molecular clouds.

Asteroseismology of 1.0 − 2.0M⊙ red giants by the _Kepler_ satellite has enabled the first definitive measurements of interior rotation in both first ascent red giant branch (RGB) stars and those on the Helium burning clump. The inferred rotation rates are 10 − 30 days for the ≈0.2M⊙ He degenerate cores on the RGB and 30 − 100 days for the He burning core in a clump star. Using the MESA code we calculate state-of-the-art stellar evolution models of low mass rotating stars from the zero-age main sequence to the cooling white dwarf (WD) stage. We include transport of angular momentum due to rotationally induced instabilities and circulations, as well as magnetic fields in radiative zones (generated by the Tayler-Spruit dynamo). We find that all models fail to predict core rotation as slow as observed on the RGB and during core He burning, implying that an unmodeled angular momentum transport process must be operating on the early RGB of low mass stars. Later evolution of the star from the He burning clump to the cooling WD phase appears to be at nearly constant core angular momentum. We also incorporate the adiabatic pulsation code, ADIPLS, to explicitly highlight this shortfall when applied to a specific _Kepler_ asteroseismic target, KIC8366239.

ABSTRACT The very long, thin infrared dark cloud Nessie is even longer than had been previously claimed, and an analysis of its Galactic location suggests that it lies directly in the Milky Way’s mid-plane, tracing out a highly elongated bone-like feature within the prominent Scutum-Centaurus spiral arm. Re-analysis of mid-infrared imagery from the Spitzer Space Telescope shows that this IRDC is at least 2, and possibly as many as 8 times longer than had originally been claimed by Nessie’s discoverers, ; its aspect ratio is therefore at least 150:1, and possibly as large as 800:1. A careful accounting for both the Sun’s offset from the Galactic plane (∼25 pc) and the Galactic center’s offset from the (lII, bII)=(0, 0) position defined by the IAU in 1959 shows that the latitude of the true Galactic mid-plane at the 3.1 kpc distance to the Scutum-Centaurus Arm is not b = 0, but instead closer to b = −0.5, which is the latitude of Nessie to within a few pc. Apparently, Nessie lies _in_ the Galactic mid-plane. An analysis of the radial velocities of low-density (CO) and high-density (${\rm NH}_3$) gas associated with the Nessie dust feature suggests that Nessie runs along the Scutum-Centaurus Arm in position-position-velocity space, which means it likely forms a dense ‘spine’ of the arm in real space as well. No galaxy-scale simulation to date has the spatial resolution to predict a Nessie-like feature, but extant simulations do suggest that highly elongated over-dense filaments should be associated with a galaxy’s spiral arms. Nessie is situated in the closest major spiral arm to the Sun toward the inner Galaxy, and appears almost perpendicular to our line of sight, making it the easiest feature of its kind to detect from our location (a shadow of an Arm’s bone, illuminated by the Galaxy beyond). Although the Sun’s (∼25 pc) offset from the Galactic plane is not large in comparison with the half-thickness of the plane as traced by Population I objects such as GMCs and HII regions (∼200 pc; ), it may be significant compared with an extremely thin layer that might be traced out by Nessie-like “bones” of the Milky Way. Future high-resolution extinction and molecular line data may therefore allow us to exploit the Sun’s position above the plane to gain a (very foreshortened) view “from above" of dense gas in Milky Way’s disk and its structure.