New contributions to the understanding of Kiruna-type iron oxide-apatite deposits revealed by magnetite ore and gangue mineral geochemistry at the El Romeral deposit, Chile

Iron oxide-apatite (IOA) or Kiruna-type deposits are an important source of iron and other elements including REE, U, Ag, and Co. The genesis of these deposits remains controversial, with models that range from a purely magmatic origin to others that involve variable degrees of hydrothermal fluid involvement. To elucidate the formation processes of this deposit type, we focused on the Chilean Iron Belt of Cretaceous age and performed geochemical analyses on samples from El Romeral, one of the largest IOA deposits in northern Chile. We present a comprehensive field emission electron microprobe analysis (FE-EMPA) dataset of magnetite, apatite, actinolite, pyroxene, biotite, pyrite, and chalcopyrite, obtained from representative drill core samples. Two different types of magnetite grains constitute the massive magnetite bodies: an early inclusion-rich magnetite (Type I); and a pristine, inclusion-poor magnetite (Type II) that usually appears as an overgrowth around Type I magnetite. High V (∼2500-2800 ppm) and Ti concentrations (∼80-3000 ppm), and the presence of high-temperature silicate mineral inclusions (e.g., pargasite, ∼800-1020°C) determined by micro-Raman analysis indicate a magmatic origin for Type I magnetite. On the other hand, high V (2300-2700 ppm) and lower Ti (50-400 ppm) concentrations of pristine, inclusion-poor Type-II magnetite indicate a shift from magmatic to hydrothermal conditions for this mineralization event. Furthermore, the composition of primary actinolite (Ca- and Mg-rich cores) within Type-II magnetite, the presence of F-rich apatite and high Co:Ni ratios (>1-10) of late stage pyrite mineralization are consistent with a high temperature (up to 840°C) genesis for the deposit. At shallow depths of the deposit, the presence of pyrite with low Co:Ni ratios (<0.5) and OH-rich apatite which contains higher Cl concentrations relative to F record a dominance of lower temperature hydrothermal conditions (<600°C) and a lesser magmatic contribution. This vertical zonation, which correlates with the sub-vertical shape of the massive iron ore bodies, is concordant with a transition from magmatic to hydrothermal domains described in several IOA deposits along the Chilean Iron Belt, and supports a magmatic-hydrothermal model for the formation of the El Romeral. The close spatial and temporal association of the deposit with the Romeral Fault System suggests that a pressure drop related to changes in the tectonic stress had a significant impact on Fe solubility, triggering ore precipitation

Quantum effects on the BKT phase transition of two-dimensional Josephson arrays

The phase diagram of two dimensional Josephson arrays is studied by means of the mapping to the quantum XY model. The quantum effects onto the thermodynamics of the system can be evaluated with quantitative accuracy by a semiclassical method, the {\em pure-quantum self-consistent harmonic approximation}, and those of dissipation can be included in the same framework by the Caldeira-Leggett model. Within this scheme, the critical temperature of the superconductor-to-insulator transition, which is a Berezinskii-Kosterlitz-Thouless one, can be calculated in an extremely easy way as a function of the quantum coupling and of the dissipation mechanism. Previous quantum Monte Carlo results for the same model appear to be rather inaccurate, while the comparison with experimental data leads to conclude that the commonly assumed model is not suitable to describe in detail the real system.Comment: 4 pages, 2 figures, to be published in Phys. Rev.

G-CORE a core for future graph query languages

We report on a community effort between industry and academia to shape the future of graph query languages. We argue that existing graph database management systems should consider supporting a query language with two key characteristics. First, it should be composable, meaning, that graphs are the input and the output of queries. Second, the graph query language should treat paths as first-class citizens. Our result is G-CORE, a powerful graph query language design that fulfills these goals, and strikes a careful balance between path query expressivity and evaluation complexity

G-CORE a core for future graph query languages

We report on a community effort between industry and academia to shape the future of graph query languages. We argue that existing graph database management systems should consider supporting a query language with two key characteristics. First, it should be composable, meaning, that graphs are the input and the output of queries. Second, the graph query language should treat paths as first-class citizens. Our result is G-CORE, a powerful graph query language design that fulfills these goals, and strikes a careful balance between path query expressivity and evaluation complexity

G-CORE a core for future graph query languages

We report on a community effort between industry and academia to shape the future of graph query languages. We argue that existing graph database management systems should consider supporting a query language with two key characteristics. First, it should be composable, meaning, that graphs are the input and the output of queries. Second, the graph query language should treat paths as first-class citizens. Our result is G-CORE, a powerful graph query language design that fulfills these goals, and strikes a careful balance between path query expressivity and evaluation complexity

Biotic and abiotic predictors of potential N2O emissions from denitrification in Irish grasslands soils: A national-scale field study

Publication history: Accepted - 18 March 2022; Published - 25 March 2022.Large-scale information regarding nitrous oxide (N2O) emissions is needed as an evidence base to underpin land use policy and mitigation approaches. However, the highly variable rates of denitrification make the prediction of N2O emission demanding. Here, we evaluated the role of abiotic and biotic factors on the potential denitrification of Irish soils, in order to identify the key factors regulating potential N2O emissions at a large scale. To do so, we collected 136 soil samples from 32 sites across Ireland, and characterised the soil physico-chemical properties, the prokaryotic and fungal community composition, the abundance of N-cycling genes and evaluated the soil potential nitrification, denitrification and end product N2O/(N2O + N2). We found large differences in soil potential denitrification between sites (up to 41.5 mg N2O–N kg 1 soil day 1) with most of the emissions released in the form of N2O rather than N2. Soils with highest potential nitrification rates also exhibited the highest potential denitrification rates, and similar parameters were linked to both processes. The factors most predictive of soil potential denitrification were soil physico-chemical properties and the prokaryotic community composition. Soil phosphorus content was as important for predicting potential denitrification as was pH and total nitrogen. Soil microbial community structure, rather than denitrifier abundance, was an important predictor of the potential denitrification and the end-product N2O/(N2O + N2). The prokaryotic community composition was more strongly associated with denitrification rates and the resulting end-products than fungal communities. Increased relative abundance of the prokaryotic phyla Actinobacteriota and Crenarchaeota, were positively correlated to complete denitrification. Altogether, these results lay the foundation for a better understanding of the key factors regulating the potential denitrification in soils and identify important properties that enhance prediction of the potential denitrification at larger scales.This research and CD, JR and PRP were financially supported under the National Development Plan, through the Research Stimulus Fund, administered by the Irish Department of Agriculture, Food and the Marine (Grant number 15S655: MINE project)

Density functional theories and self-energy approaches

A purpose-designed microarray platform (Stressgenes, Phase 1) was utilised to investigate the changes in gene expression within the liver of rainbow trout during exposure to a prolonged period of confinement. Tissue and blood samples were collected from trout at intervals up to 648 h after transfer to a standardised confinement stressor, together with matched samples from undisturbed control fish. Plasma ACTH, cortisol, glucose and lactate were analysed to confirm that the neuroendocrine response to confinement was consistent with previous findings and to provide a phenotypic context to assist interpretation of gene expression data. Liver samples for suppression subtractive hybridisation (SSH) library construction were selected from within the experimental groups comprising “early” stress (2–48 h) and “late” stress (96–504 h). In order to reduce redundancy within the four SSH libraries and yield a higher number of unique clones an additional subtraction was carried out. After printing of the arrays a series of 55 hybridisations were executed to cover 6 time points. At 2 h, 6 h, 24 h, 168 h and 504 h 5 individual confined fish and 5 individual control fish were used with control fish only at 0 h. A preliminary list of 314 clones considered differentially regulated over the complete time course was generated by a combination of data analysis approaches and the most significant gene expression changes were found to occur during the 24 h to 168 h time period with a general approach to control levels by 504 h. Few changes in expression were apparent over the first 6 h. The list of genes whose expression was significantly altered comprised predominantly genes belonging to the biological process category (response to stimulus) and one cellular component category (extracellular region) and were dominated by so-called acute phase proteins. Analysis of the gene expression profile in liver tissue during confinement revealed a number of significant clusters. The major patterns comprised genes that were up-regulated at 24 h and beyond, the primary examples being haptoglobin, β-fibrinogen and EST10729. Two representative genes from each of the six k-means clusters were validated by qPCR. Correlations between microarray and qPCR expression patterns were significant for most of the genes tested. qPCR analysis revealed that haptoglobin expression was up-regulated approximately 8-fold at 24 h and over 13-fold by 168 h.This project was part funded by the European Commission (Q5RS-2001-02211), Enterprise Ireland and the Natural Environment Research Council of the United Kingdom