The elemental composition of the Sun II. The iron group elements Sc to Ni

We redetermine the abundances of all iron group nuclei in the Sun, based on neutral and singly-ionised lines of Sc, Ti, V, Mn, Fe, Co and Ni in the solar spectrum. We employ a realistic 3D hydrodynamic model solar atmosphere, corrections for departures from local thermodynamic equilibrium (NLTE), stringent line selection procedures and high quality observational data. We have scoured the literature for the best quality oscillator strengths, hyperfine constants and isotopic separations available for our chosen lines. We find $\log \epsilon_\mathrm{Sc}=3.16\pm0.04$, $\log \epsilon_\mathrm{Ti}=4.93\pm0.04$, $\log \epsilon_\mathrm{V}=3.89\pm0.08$, $\log \epsilon_\mathrm{Cr}=5.62\pm0.04$, $\log \epsilon_\mathrm{Mn}=5.42\pm0.04$, $\log \epsilon_\mathrm{Fe}=7.47\pm0.04$, $\log \epsilon_\mathrm{Co}=4.93\pm0.05$ and $\log \epsilon_\mathrm{Ni}=6.20\pm0.04$. Our uncertainties factor in both statistical and systematic errors (the latter estimated for possible errors in the model atmospheres and NLTE line formation). The new abundances are generally in good agreement with the CI meteoritic abundances but with some notable exceptions. This analysis constitutes both a full exposition and a slight update of the preliminary results we presented in Asplund, Grevesse, Sauval & Scott (arXiv:0909.0948), including full line lists and details of all input data we employed.Comment: 10 figures, 24 pages + 10 online-only pages of tables. v2. Matches version accepted by A&

The elemental composition of the Sun III. The heavy elements Cu to Th

We re-evaluate the abundances of the elements in the Sun from copper ($Z=29$) to thorium ($Z=90$). Our results are mostly based on neutral and singly-ionised lines in the solar spectrum. We use the latest 3D hydrodynamic solar model atmosphere, and in a few cases also correct for departures from local thermodynamic equilibrium (LTE) using non-LTE (NLTE) calculations performed in 1D. In order to minimise statistical and systematic uncertainties, we make stringent line selections, employ the highest-quality observational data and carefully assess oscillator strengths, hyperfine constants and isotopic separations available in the literature, for every line included in our analysis. Our results are typically in good agreement with the abundances in the most pristine meteorites, but there are some interesting exceptions. This analysis constitutes both a full exposition and a slight update of the relevant parts of the preliminary results we presented in Asplund, Grevesse, Sauval & Scott (arXiv:0909.0948), including full line lists and details of all input data that we have employed.Comment: 5 figures, 18 pages + 6 online-only pages of tables. v2. Matches version accepted by A&

War and Economics: Spanish Civil War Finances Revisited

This paper reviews how the Spanish civil war was financed. We present new evidence to show that the two combatant parties, the Republican government and the Franco administration followed similar financial strategies. In both cases money creation, rather than new taxes or the issue of debt, was the main mechanism used to cover the expenses of the war. We argue, contrary to the established knowledge, that both sides consumed a similar amount of domestic and foreign resources. We also argue that the Spanish Republic did not lose the war because of a lack of means. International factors, such as the Non-Intervention agreement promoted by France and Great Britain, and the military setbacks of the Republican army during the first year of the war, were decisive for Franco’s victory in 1939.Spain, civil war, financial resources

Pulsating stars in the VMC survey

The VISTA survey of the Magellanic Clouds system (VMC) began observations in 2009 and since then, it has collected multi-epoch data at Ks and in addition multi-band data in Y and J for a wide range of stellar populations across the Magellanic system. Among them are pulsating variable stars: Cepheids, RR Lyrae, and asymptotic giant branch stars that represent useful tracers of the host system geometry.Comment: 8 pages, 7 figures, proceeding contribution of invited presentation at "Wide-field variability surveys: a 21st-century perspective", San Pedro de Atacama (Chile

The economic value of guaranteed water supply for irrigation under scarcity conditions

Resource /Energy Economics and Policy,

British Bryological Society expedition to Mulanje Mountain, Malawi : 13., new and other unpublished records

Further results are provided of the 1991 British Bryological Society Expedition to Mulanje Mt., Malawi including 168 taxa of bryophyte, comprising 72 taxa of liverwort (38 new to Malawi) and 96 taxa of mosses (45 new to Malawi)

Personalization of Learning Objects according to the Skill Set of the Learner using Knowledge Graph

There are numerous eLearning tools have been developed to provide the learning objects for the learners to grow in knowledge in any discipline. There is an increasing need and the demand for educational applications which provides learning object based on the ability of the learners to acquire the learning content according to their ability. Even though there were quite a lot of factors like motivation, geographic location and prerequisite knowledge that influences the learning ability, the knowledge representation for different types of learners is an important factor. Hence a system called Knowledge Graph for Online Learner (KGOL) is proposed to create a knowledge graph for the learning objects and enable the learners to understand the learning concepts better. The system utilizes heterogeneous pedagogical data from the education domain to provide personalized learning content in an eLearning environment. The learner is categorized by their learning ability and the system identifies the relationship between the concepts and pulls out the concepts in the learning objects. Specifically, it adopts the information extraction technique called Named Entity Recognition (NER) which uses spaCy, which is an open-source library for advanced Natural Language Processing in Python. The proposed system also uses student skill set from learning activity to find out the learning ability level to peruse the course content based on the classed such as highly skilled, moderate and slow learners. The proposed system demonstrates the architecture with the knowledge graph constructed for the Programming language to different types of learners. The researchers have demonstrated the proposed work with the python language. For learners’ classification, a machine learning algorithm called random forest has been used; NER and spaCy library have been used to extract the information and to construct KG for learning object on python programming language. There are three predicate levels used to provide the learning object using KG to different learners based on their learning ability like highly skilled, moderate and slow learner

Assessing uncertainty in dynamic functional connectivity

Functional connectivity (FC) - the study of the statistical association between time series from anatomically distinct regions (Friston, 1994, 2011) - has become one of the primary areas of research in the field surrounding resting state functional magnetic resonance imaging (rs-fMRI). Although for many years researchers have implicitly assumed that FC was stationary across time in rs-fMRI, it has recently become increasingly clear that this is not the case and the ability to assess dynamic changes in FC is critical for better understanding of the inner workings of the human brain (Hutchison et al., 2013; Chang and Glover, 2010). Currently, the most common strategy for estimating these dynamic changes is to use the sliding-window technique. However, its greatest shortcoming is the inherent variation present in the estimate, even for null data, which is easily confused with true time-varying changes in connectivity (Lindquist et al., 2014). This can have serious consequences as even spurious fluctuations caused by noise can easily be confused with an important signal. For these reasons, assessment of uncertainty in the sliding-window correlation estimates is of critical importance. Here we propose a new approach that combines the multivariate linear process bootstrap (MLPB) method and a sliding-window technique to assess the uncertainty in a dynamic FC estimate by providing its confidence bands. Both numerical results and an application to rs-fMRI study are presented, showing the efficacy of the proposed method

Gas-Phase Lubrication of ta-C by Glycerol and Hydrogen Peroxide. Experimental and Computer Modeling

Tetrahedrally coordinated hydrogen-free amorphous diamond-like carbon coating (denoted as ta-C) presents ultralow friction under boundary lubrication conditions at 80 °C in presence of OH-containing molecules. To understand the mechanism of ultralow friction, we performed gas-phase lubrication experiments followed by time-of-flight secondary ion mass spectrometry (ToF-SIMS) analyses and this using two simple molecules: deuterated glycerol and hydrogen peroxide. The experiments were complemented by computer simulations using the ReaxFF reactive force field. These simulations suggest a ta-C surface rich in sp^2 carbon with some reactive sp^1 carbon atoms, in agreement with previous energy filtered transmission electron microscopy (EFTEM) results. Sliding simulations show that the carbon surface atoms react with glycerol and hydrogen peroxide to form OH-termination. Moreover, the hydroxylation is then followed by the chemical dissociation of some of the glycerol molecules leading to the formation of water. This is in agreement with the secondary ion mass spectrometry (SIMS) analyses and mass spectrometer results obtained with gas-phase lubrication experiments with the same molecules. Both experimental and computer simulations strongly suggest that the hydroxylation of the carbon surface is at the origin of ultralow friction together with the formation of water-rich film in the sliding interface