Nataliakulikite, Ca4Ti2(Fe3+,fe2+)(Si,fe3+,al)o11, a new perovskite-supergroup mineral from hatrurim basin, negev desert, Israel

Nataliakulikite, Ca4Ti2(Fe3+,Fe2+)(Si,Fe3+,Al)O11, is a mineral intermediate between perovskite CaTiO3 and brownmillerite Ca2(Fe,Al)2O5. It was discovered as a minor mineral in a high-temperature pyrometamorphic larnite-gehlenite rock at the Nahal Morag Canyon of the Hatrurim Basin, Israel. Nataliakulikite is associated with larnite, flamite, gehlenite, magnesioferrite, Fe3+-rich perovskite, fluorapatite, barite, Hashemite, and retrograde phases (afwillite, hillebrandite, portlandite, calcite, ettringite, hydrogarnet, and other hydrated Ca-silicates). The mineral forms brown subhedral or prismatic grains (up to 20 µm) and their intergrowths (up to 50 µm). Its empirical formula (n = 47) is (Ca3.992Sr0.014U0.004)(Ti1.933Zr0.030Nb0.002) (Fe3+0.610Fe2+0.405Cr0.005Mn0.005)(Si0.447Fe3+0.337Al0.216)O11 and shows Si predominance in tetrahedral site. The unit-cell parameters (HRTEM data) and space group are: a = 5.254, b = 30.302, c = 5.488 Å, V = 873.7 Å3, Pnma, Z = 4. These dimensions and Electron backscatter diffraction (EBSD) data strongly support the structural identity between nataliakulikite and synthetic Ca4Ti2Fe3+2O11 (2CaTiO3·Ca2Fe3+2O5), an intermediate compound in the system CaTiO3-Ca2Fe3+2O5. In general, this mineral is a Si-Fe2+-rich natural analog of synthetic Ca4Ti2Fe3+2O11. The X-ray powder diffraction data (CuKα-radiation), calculated from unit-cell dimensions, show the strongest lines {d [Å], (Icalc)} at: 2.681(100), 1.898(30), 2.627(26), 2.744(23), 1.894(22), 15.151(19), 1.572(14), 3.795(8). The calculated density is 4.006 g/cm3. The crystal structure of nataliakulikite has not been refined because of small sizes of grains. The Raman spectrum shows strong bands at 128, 223, 274, 562, and 790 cm−1. Nataliakulikite from the Hatrurim Basin crystallized under the conditions of combustion metamorphism at high temperatures (1160–1200◦C) and low pressures (HT-region of the spurrite-merwinite facies). © 2019 by the authors. Licensee MDPI, Basel, Switzerland.Russian Science Foundation, RSF: 0330-2016-0004, 17-17-01056, IGM SD 0330-2016-0005Ben-Gurion University of the Negev, BGUThis research was funded by the Russian Science Foundation, grant number 17-17-01056. The field work and sample collection was partly supported the State assignment projects (IGM SD 0330-2016-0005, 0330-2016-0004). Acknowledgments: The authors would like to thank M.V. Khlestov (IGM SD RAS) for technical assistance at SEM studies. Yevgeny Vapnik (Ben-Gurion University, Beer-Sheva, Israel) is thanked for providing of fruitful field trips in the Hatrurim Basin in 2004 and 2019. The last version of the manuscript was improved through comments and suggestions by T. Perepelova (IGM, Novosibirsk). We are highly appreciative of the valuable comments and suggestions of two anonymous reviewers

Ellinaite, CaCr2O4, a New Natural Post-Spinel Oxide from Hatrurim Basin, Israel, and Juína Kimberlite Field, Brazil

Ellinaite, a natural analog of the post-spinel phase β-CaCr2O4, was discovered at the Hatrurim Basin, Hatrurim pyrometamorphic formation (the Mottled Zone), Israel, and in an inclusion within the super-deep diamond collected at the placer of the Sorriso River, Juína kimberlite field, Brazil. Ellinaite at the Hatrurim Basin is confined to a reduced rankinite-gehlenite paralava, where it occurs as subhedral grains up to 30μm in association with gehlenite, rankinite and pyrrhotite or forms the rims overgrowing zoned chromite-magnesiochromite. The empirical formula of the Hatrurim sample is (Ca0.960Fe0.0162+Na0.012Mg0.003)0.992(Cr1.731V0.1833+Ti0.0683+Al0.023Ti0.0034+)2.008O4. The mineral crystallizes in the orthorhombic system, space group Pnma, unit-cell parameters refined from X-ray single-crystal data: A 8.868(9), b 2.885(3), c 10.355(11)Å, V 264.9(5)Å3 and ZCombining double low line4. The crystal structure of ellinaite from the Hatrurim Basin has been solved and refined to R1Combining double low line0.0588 based on 388 independent observed reflections. Ellinaite in the Juína diamond occurs within the micron-sized polyphase inclusion in association with ferropericlase, magnesioferrite, orthorhombic MgCr2O4, unidentified iron carbide and graphite. Its empirical formula is Ca1.07(Cr1.71Fe0.063+V0.06Ti0.03Al0.03Mg0.02Mn0.02)ς1.93O4. The unit-cell parameters obtained from HRTEM data are as follows: Space group Pnma, a 9.017, b 2.874Å, c 10.170Å, V 263.55Å3, ZCombining double low line4. Ellinaite belongs to a group of natural tunnel-structured oxides of the general formula AB2O4, the so-called post-spinel minerals: Marokite CaMn2O4, xieite FeCr2O4, harmunite CaFe2O4, wernerkrauseite CaFe23+Mn4+O6, chenmingite FeCr2O4, maohokite MgFe2O4 and tschaunerite Fe(FeTi)O4. The mineral from both occurrences seems to be crystallized under highly reduced conditions at high temperatures (>1000°C), but under different pressure: Near-surface (Hatrurim Basin) and lower mantle (Juína diamond). © 2021 Victor V. Sharygin et al.Raman spectroscopy and EBSD investigations for the Hatrurim ellinaite were done on state assignment of IGM SB RAS (IX.125.2) and the Initiative Project of Ministry of Science and Higher Education of the Russian Federation (Act 211 of the Government of the Russian Federation (grant agreement no. 02.A03.21.0006)). SEM and microprobe studies for the Hatrurim ellinaite were supported by the Russian Science Foundation (grant no. 17-17-01056p). Crystallographic studies of the Hatrurim ellinaite were provided by the Russian Science Foundation (grant no. 18-17-00079)

A systematic review to identify areas of enhancements of pandemic simulation models for operational use at provincial and local levels

<p>Abstract</p> <p>Background</p> <p>In recent years, computer simulation models have supported development of pandemic influenza preparedness policies. However, U.S. policymakers have raised several <it>concerns </it>about the practical use of these models. In this review paper, we examine the extent to which the current literature already addresses these <it>concerns </it>and identify means of enhancing the current models for higher operational use.</p> <p>Methods</p> <p>We surveyed PubMed and other sources for published research literature on simulation models for influenza pandemic preparedness. We identified 23 models published between 1990 and 2010 that consider single-region (e.g., country, province, city) outbreaks and multi-pronged mitigation strategies. We developed a plan for examination of the literature based on the concerns raised by the policymakers.</p> <p>Results</p> <p>While examining the concerns about the adequacy and validity of data, we found that though the epidemiological data supporting the models appears to be adequate, it should be validated through as many updates as possible during an outbreak. Demographical data must improve its interfaces for access, retrieval, and translation into model parameters. Regarding the concern about credibility and validity of modeling assumptions, we found that the models often simplify reality to reduce computational burden. Such simplifications may be permissible if they do not interfere with the performance assessment of the mitigation strategies. We also agreed with the concern that social behavior is inadequately represented in pandemic influenza models. Our review showed that the models consider only a few social-behavioral aspects including contact rates, withdrawal from work or school due to symptoms appearance or to care for sick relatives, and compliance to social distancing, vaccination, and antiviral prophylaxis. The concern about the degree of accessibility of the models is palpable, since we found three models that are currently accessible by the public while other models are seeking public accessibility. Policymakers would prefer models scalable to any population size that can be downloadable and operable in personal computers. But scaling models to larger populations would often require computational needs that cannot be handled with personal computers and laptops. As a limitation, we state that some existing models could not be included in our review due to their limited available documentation discussing the choice of relevant parameter values.</p> <p>Conclusions</p> <p>To adequately address the concerns of the policymakers, we need continuing model enhancements in critical areas including: updating of epidemiological data during a pandemic, smooth handling of large demographical databases, incorporation of a broader spectrum of social-behavioral aspects, updating information for contact patterns, adaptation of recent methodologies for collecting human mobility data, and improvement of computational efficiency and accessibility.</p

Hiv treatment as prevention: Models, data, and questions-towards evidence-based decision-making

textabstractAntiretroviral therapy (ART) for those infected with HIV can prevent onward transmission of infection, but biological efficacy alone is not enough to guide policy decisions about the role of ART in reducing HIV incidence. Epidemiology, economics, demography, statistics, biology, and mathematical modelling will be central in framing key decisions in the optimal use of ART. PLoS Medicine, with the HIV Modelling Consortium, has commissioned a set of articles that examine different aspects of HIV treatment as prevention with a forward-looking research agenda. Interlocking themes across these articles are discussed in this introduction. We hope that this article, and others in the collection, will provide a foundation upon which greater collaborations between disciplines will be formed, and will afford deeper insights into the key factors involved, to help strengthen the support for evidence-based decision-making in HIV prevention