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Revision of crystal structure of the rare U-oxide mineral richetite provided crystallographic evidence for the presence of pentavalent U. The structure of richetite, space group P1, a = 12.0919(2), b = 16.3364(4), c = 20.2881(4) A, α = 68.800(2), β = 78.679(2), g = 76.118(2)°, with V = 3600.65(14) A3 and Z = 1, was solved by charge-flipping algorithm and refined to an agreement index (R) of 5.6% for 9955 unique reflections collected using microfocus X-ray source. The refined structure, in line with the previous structure determination, contains U-O-OH sheets of the α-U3O8 type (protasite topology) and an interstitial complex comprising Pb2+, Fe2+, Mg2+ cations and molecular H2O. However, the polyhedral geometry, the bond-valence sum incident at one U site within the sheet (U17) together with charge-balance requirements, indicate that U17 site is occupied by U5+. The U17Φ7 (Φ: O, OH) polyhedra is distorted, with two shorter U-O bond-lengths (∼2.01 A), four longer U-O bond-lengths (∼2.2 A) and one, very long U-O bond (2.9 A). The color of richetite also supports the presence of U5+ in the structure The current results show that α-U3O8 type of sheet can incorporate U5+ Richetite is the third mineral containing pentavalent uranium that occurs in nature.

An investigation of sample 41647 from the Platinum Placer of Ugol'nyi Ruchei, Norilsk Cu-Ni deposit, Russia, stored in the systematic collection of the Fersman Mineralogical Museum, revealed that it contained a mineral that can be identified as the original stannopalladinite described in 1947. As the literature information on the latter is controversial, the mineral was re-investigated using modern analytical techniques. Stannopalladinite occurs as spherical and ovoid-shaped grains up to 0.08 mm, closely intergrown with tetraferroplatinum as part of flattened, prismatic crystals up to 6 mm long. The micro-indentation hardness of stannopalladinite (VHN, 30 g load) is 244 kg/mm2 (range 233-266, n = 4), corresponding to a Mohs hardness of 4. The calculated density is 9.781 g/cm3. In reflected light, stannopalladinite is pale pink. The bireflectance is noticeable only in oil immersion. In crossed nicols the mineral exhibits strong anisotropy with colour effects changing from reddish purple to greyish blue and polysynthetic twinning of grains. The reflectance curves show distinct anomalous dispersion. The chemical composition (wt.%, electron microprobe data, mean of 11 analyses) is: Cu 8.48, Pd 61.21, Pt 0.89, Sn 25.87, Pb 3.70, total 100.15. The empirical formula calculated on the basis of 4 atoms per formula unit is (Pd2.42Cu0.56Pt0.02)Σ3.00(Sn0.92Pb0.08)Σ1.00. The ideal chemical formula of stannopalladinite is therefore proposed as (Pd,Cu)3Sn instead of Pd3Sn2 used in the official IMA List of Minerals. The strongest powder X-ray diffraction lines are [dobs, Å (I, %) (hkl)]: 2.292 (42) (231), 2.166 (100) (331), 2.034 (10) (710), 1.916 (15) (141) and 1.851 (15) (630). The powder X-ray data are indexed in the orthorhombic unit cell with a = 14.634(2), b = 8.5253(6), c = 4.5946(3) Å and V = 573.24(7) Å3 (Z = 8). Stannopalladinite can be reliably identified among all other minerals belonging to the binary Pd-Sn and ternary Pd-Cu-Sn systems by a combination of chemical, optical and X-ray data.

Mitrofanovite, Pt3Te4, is a new telluride discovered in low-sulfide disseminated ore in the East Chuarvy deposit, Fedorovo-Pana intrusion, Kola Peninsula, Russia. It forms anhedral grains (up to ∼20 µm ×50 µm) commonly in intergrowths with moncheite in aggregates with lukkulaisvaaraite, kotulskite, vysotskite, braggite, keithconnite, rustenburgite and Pt-Fe alloys hosted by a chalcopyrite-pentlandite-pyrrhotite matrix. Associated silicates are: orthopyroxene, augite, olivine, amphiboles and plagioclase. Mitrofanovite is brittle; it has a metallic lustre and a grey streak. Mitrofanovite has a good cleavage, along {001}. In plane-polarised light, mitrofanovite is bright white with medium to strong bireflectance, slight pleochroism, and strong anisotropy on non-basal sections with greyish brown rotation tints; it exhibits no internal reflections. Reflectance values for the synthetic analogue of mitrofanovite in air (Ro, Re' in %) are: 58.4, 54.6 at 470 nm; 62.7, 58.0 at 546 nm; 63.4, 59.1 at 589 nm; and 63.6, 59.5 at 650 nm. Fifteen electron-microprobe analyses of mitrofanovite gave an average composition: Pt 52.08, Pd 0.19, Te 47.08 and Bi 0.91, total 100.27 wt.%, corresponding to the formula (Pt2.91Pd0.02)Σ2.93(Te4.02Bi0.05)Σ4.07 based on 7 atoms; the average of eleven analyses on synthetic analogue is: Pt 52.57 and Te 47.45, total 100.02 wt.%, corresponding to Pt2.94Te4.06. The density, calculated on the basis of the formula, is 11.18 g/cm3. The mineral is trigonal, space group R3#8 m, with a=3.9874(1), c=35.361(1) Å, V=486.91(2) Å3 and Z=3. The crystal structure was solved and refined from the powder X-ray-diffraction data of synthetic Pt3Te4. Mitrofanovite is structurally and chemically related to moncheite (PtTe2). The strongest lines in the powder X-ray diffraction pattern of synthetic mitrofanovite [d in Å (I)(hkl)] are: 11.790(23)(003), 5.891(100)(006), 2.851(26)(107), 2.137(16)(1013), 2.039(18)(0114), 1.574(24)(0120), 1.3098(21)(0027). The structural identity of natural mitrofanovite with synthetic Pt3Te4 was confirmed by electron backscatter diffraction measurements on the natural sample. The mineral name is chosen to honour Felix P. Mitrofanov, a Russian geologist who was among the first to discover platinum-group element mineralisation in the Fedorova-Pana complex.

The experimental electron density distributions in two coordination compounds – one with a central Cu(I) atom and the other with Cu(II), coordinated by the same biphenyldiimino dithioether ( bite ) type of ligand – have been obtained from high-resolution X-ray reflection data to model the possible electron predisposition for the redox reaction in blue copper proteins. The bite ligand has been adapted to the conformation required by the central atom.

Microbialites provide some of the oldest direct evidence of life on Earth. They reached their peak during the Proterozoic and declined afterward. Their decline has been attributed to grazing and/or burrowing by metazoans, to changes in ocean chemistry, or to competition with other calcifying organisms. The freshwater microbialites at Laguna Bacalar (Mexico) provide an opportunity to better understand microbialite growth in terms of interaction between grazing organisms versus calcium carbonate precipitation. The Laguna Bacalar microbialites are described in terms of their distinct mesostructures. Stromatolites display internal lamination, attributed to the precipitation of calcite and the upward migration of cyanobacteria during periods of low sedimentation. Thrombolitic stromatolites show internal lamination in addition to internal clotting. The clotting is seen as a result of binding and/or trapping of micritic peloids by cyanobacteria and attributed to periods of high sedimentation. The carbonates in both microbialites had similar C- and O-stable–isotopic signatures, both enriched in 13C relative to bivalves, suggesting photosynthetic CO2 uptake was the trigger for carbonate precipitation. This implies that the rate of microbialite growth is largely a function of ambient carbonate saturation state, while the texture is especially dependent on accretion rates and sediment deposition on their surface. Importantly, the coexistence with grazing animals suggests no significant inhibition on microbialite growth, thereby calling into question the decline of microbialite as a result of metazoan evolution. Varying sedimentation rates are likely important in controlling the distribution of thrombolite–stromatolite packages in the geological record, given the importance of this factor at Bacalar.

Crystal chemical algorithms were used to estimate the chemical composition of selected mineral phases observed with the CheMin X-ray diffractometer onboard the NASA Curiosity rover in Gale crater, Mars. The sampled materials include two wind-blown soils, Rocknest and Gobabeb, six mudstones in the Yellowknife Bay formation (John Klein and Cumberland) and the Murray formation (Confidence Hills, Mojave2, and Telegraph Peak), as well as five sandstones, Windjana and the samples of the unaltered Stimson formation (Big Sky and Okoruso) and the altered Stimson formation (Greenhorn and Lubango). The major mineral phases observed with the CheMin instrument in the Gale crater include plagioclase, sanidine, P21/c and C2/c clinopyroxene, orthopyroxene, olivine, spinel, and alunite-jarosite group minerals. The plagioclase analyzed with CheMin has an overall estimated average of An40(11) with a range of An30(8) to An63(6). The soil samples, Rocknest and Gobabeb, have an average of An56(8) while the Murray, Yellowknife Bay, unaltered Stimson, and altered Stimson formations have averages of An38(2), An37(5), An45(7), and An35(6), respectively. Alkali feldspar, specifically sanidine, average composition is Or74(17) with fully disordered Al/Si. Sanidine is most abundant in the Wind-jana sample (∼26 wt% of the crystalline material) and is fully disordered with a composition of Or87(5). The P21/c clinopyroxene pigeonite observed in Gale crater has a broad compositional range {[Mg0.95(12)-1.54(17)Fe0.18(17)-1.03(9)Ca0.00-0.28(6)]Σ2Si2O6} with an overall average of Mg1.18(19)Fe0.72(7)Ca0.10(9)Si2O6. The soils have the lowest Mg and highest Fe compositions [Mg0.95(5)Fe1.02(7)Ca0.03(4)Si2O6] of all of the Gale samples. Of the remaining samples, those of the Stimson formation exhibit the highest Mg and lowest Fe [average = Mg1.45(7)Fe0.35(13)Ca0.19(6)Si2O6]. Augite, C2/c clinopyroxene, is detected in just three samples, the soil samples [average = Mg0.92(5)Ca0.72(2)Fe0.36(5)Si2O6] and Windjana (Mg1.03(7)Ca0.75(4)Fe0.21(9)Si2O6). Orthopyroxene was not detected in the soil samples and has an overall average composition of Mg0.79(6)Fe1.20(6)Ca0.01(2)Si2O6 and a range of [Mg0.69(7)-0.86(20)Fe1.14(20)-1.31(7)Ca0.00-0.04(4)]Σ2Si2O6, with Big Sky exhibiting the lowest Mg content [Mg0.69(7)Fe1.31(7)Si2O6] and Okoruso exhibiting the highest [Mg0.86(20)Fe1.14(20)Si2O6]. Appreciable olivine was observed in only three of the Gale crater samples, the soils and Windjana. Assuming no Mn or Ca, the olivine has an average composition of Mg1.19(12)Fe0.81(12)SiO4 with a range of 1.08(3) to 1.45(7) Mg apfu. The soil samples [average = Mg1.11(4)Fe0.89SiO4] are significantly less magnesian than Windjana [Mg1.35(7)Fe0.65(7)SiO4]. We assume magnetite (Fe3O4) is cation-deficient (Fe3-x∎xO4) in Gale crater samples [average = Fe2.83(5)∎0.14O4; range 2.75(5) to 2.90(5) Fe apfu], but we also report other plausible cation substitutions such as Al, Mg, and Cr that would yield equivalent unit-cell parameters. Assuming cation-deficient magnetite, the Murray formation [average = Fe2.77(2)∎0.23O4] is noticeably more cation-deficient than the other Gale samples analyzed by CheMin. Note that despite the presence of Ti-rich magnetite in martian meteorites, the unit-cell parameters of Gale magnetite do not permit significant Ti substitution. Abundant jarosite is found in only one sample, Mojave2; its estimated composition is (K0.51(12)Na0.49)(Fe2.68(7)Al0.32)(SO4)2(OH)6. In addition to providing composition and abundances of the crystalline phases, we calculate the lower limit of the abundance of X-ray amorphous material and the composition thereof for each of the samples analyzed with CheMin. Each of the CheMin samples had a significant proportion of amorphous SiO2, except Windjana that has 3.6 wt% SiO2. Excluding Windjana, the amorphous materials have an SiO2 range of 24.1 to 75.9 wt% and an average of 47.6 wt%. Windjana has the highest FeOT (total Fe content calculated as FeO) at 43.1 wt%, but most of the CheMin samples also contain appreciable Fe, with an average of 16.8 wt%. With the exception of the altered Stimson formation samples, Greenhorn and Lubango, the majority of the observed SO3 is concentrated in the amorphous component (average = 11.6 wt%). Furthermore, we provide average amorphous-component compositions for the soils and the Mount Sharp group formations, as well as the limiting element for each CheMin sample.

Quantitative X-ray element maps of cassiterite crystals from four localities show that Ti, Fe, Nb, Ta, and W define oscillatory zonation patterns and that the cathodoluminescent response is due to a complex interplay between Ti activated emission paired with quenching effects from Fe, Nb, Ta, and W. Sector zonation is commonly highlighted by domains of high Fe, incorporated via a substitution mechanism independent of Nb and Ta. A second form of sector zonation is highlighted by distributions of W separate to the Fe-dominant sector zone. Both sector zones show quenched cathodoluminescence and are indistinguishable under routine SEM CL imaging. For cassiterite already high in Fe (and Nb or Ta), such as in pegmatitic or granitic samples, the internal structure of the grain may remain obscured when imaged by cathodoluminescence techniques, regardless of the presence of sector zonation. Careful petrogenetic assessments using a combination of panchromatic and hyperspectral CL, aided by quantitative elemental X-ray mapping, is a prerequisite step to elucidate cassiterite petrogenetic history and properly characterize these grains for in situ microanalysis. The absence of a clear petrogenetic framework may lead to unknowingly poor spot selection during in situ analyses for geochronology and trace element geochemistry, and/or erroneous interpretations of U-Pb and O isotopic data.

In this paper, a computer-aided training method for hyperparameter selection of limited data X-ray computed tomography (XCT) reconstruction was proposed. The proposed method employed the ant colony optimisation (ACO) approach to assist in hyperparameter selection for the adaptive-weighted projection-controlled steepest descent (AwPCSD) algorithm, which is a total-variation (TV) based regularisation algorithm. During the implementation, there was a colony of artificial ants that swarm through the AwPCSD algorithm. Each ant chose a set of hyperparameters required for its iterative CT reconstruction and the correlation coefficient (CC) score was given for reconstructed images compared to the reference image. A colony of ants in one generation left a pheromone through its chosen path representing a choice of hyperparameters. Higher score means stronger pheromones/probabilities to attract more ants in the next generations. At the end of the implementation, the hyperparameter configuration with the highest score was chosen as an optimal set of hyperparameters. In the experimental results section, the reconstruction using hyperparameters from the proposed method was compared with results from three other cases: the conjugate gradient least square (CGLS), the AwPCSD algorithm using the set of arbitrary hyperparameters and the cross-validation method.The experiments showed that the results from the proposed method were superior to those of the CGLS algorithm and the AwPCSD algorithm using the set of arbitrary hyperparameters. Although the results of the ACO algorithm were slightly inferior to those of the cross-validation method as measured by the quantitative metrics, the ACO algorithm was over 10 times faster than cross—Validation. The optimal set of hyperparameters from the proposed method was also robust against an increase of noise in the data and can be applicable to different imaging samples with similar context. The ACO approach in the proposed method was able to identify optimal values of hyperparameters for a dataset and, as a result, produced a good quality reconstructed image from limited number of projection data. The proposed method in this work successfully solves a problem of hyperparameters selection, which is a major challenge in an implementation of TV based reconstruction algorithms.

Lung cancer screening with low-dose computed tomography lowers lung cancer mortality but has potential harms. Current guidelines support patients receiving information about the benefits and harms of lung cancer screening during decision-making. To examine the effect of a patient decision aid (PDA) about lung cancer screening compared with a standard educational material (EDU) on decision-making outcomes among smokers. This randomized clinical trial was conducted using 13 state tobacco quitlines. Current and recent tobacco quitline clients who met age and smoking history eligibility for lung cancer screening were enrolled from March 30, 2015, to September 12, 2016, and followed up for 6 months until May 5, 2017. Data analysis was conducted between May 5, 2017, and September 30, 2018. Participants were randomized to the PDA video Lung Cancer Screening: Is It Right for Me? (n = 259) or to EDU (n = 257). The primary outcomes were preparation for decision-making and decisional conflict measured at 1 week. Secondary outcomes included knowledge, intentions, and completion of screening within 6 months of receiving the intervention measured by patient report. Of 516 quit line clients enrolled, 370 (71.7%) were younger than 65 years, 320 (62.0%) were female, 138 (26.7%) identified as black, 47 (9.1%) did not have health insurance, and 226 (43.8%) had a high school or lower educational level. Of participants using the PDA, 153 of 227 (67.4%) were well prepared to make a screening decision compared with 108 of 224 participants (48.2%) using EDU (odds ratio [OR], 2.31; 95% CI, 1.56-3.44; P < .001). Feeling informed about their screening choice was reported by 117 of 234 participants (50.0%) using a PDA compared with 66 of 233 participants (28.3%) using EDU (OR, 2.56; 95% CI, 1.72-3.79; P < .001); 159 of 234 participants (68.0%) using a PDA compared with 110 of 232 (47.4%) participants using EDU reported being clear about their values related to the harms and benefits of screening (OR, 2.37; 95% CI, 1.60-3.51; P < .001). Participants using a PDA were more knowledgeable about lung cancer screening than participants using EDU at each follow-up assessment. Intentions to be screened and screening behaviors did not differ between groups. In this study, a PDA delivered to clients of tobacco quit lines improved informed decision-making about lung cancer screening. Many smokers eligible for lung cancer screening can be reached through tobacco quit lines. ClinicalTrials.gov identifier: NCT02286713.

Vymazalovaite, Pd3Bi2S2 is a new platinum-group mineral discovered in the Komsomolsky mine of the Talnakh deposit, Noril'sk district, Russia. It forms small (from a few µm to 20-35 µm) inclusions or euhedral grains in intergrowths of polarite, sobolevskite, acanthite and unnamed (Pd,Ag)5BiS2 in aggregates (up to ∼200 µm) in galena and rarely in chalcopyrite. It occurs with telargpalite, cooperite, braggite, vysotskite, sopcheite, stibiopalladinite, sobolevskite, moncheite, kotulskite, malyshevite, insizwaite, Au-bearing silver and the newly described mineral kravtsovite (PdAg2S) in association with pyrite, chalcopyrite and galena in vein-disseminated mineralization in skarn rocks. Synthetic vymazalovaite is brittle; it has a metallic lustre and a grey streak. In plane-polarized reflected light, vymazalovaite is creamy grey and appears slightly brownish against galena in the assemblage with chalcopyrite. It exhibits no internal reflections. Average reflectance values in air for natural and synthetic vymazalovaite are (R natural, R synthetic in %) are: 46.35, 45.7 at 470 nm, 47.65, 47.45 at 546 nm, 48.5, 48.2 at 589 nm and 49.5, 49.0 at 650 nm. Seven electron probe micro-analyses of vymazalovaite give an average composition: Pd 40.42, Bi 49.15, Ag 0.55, Pb 1.02, S 7.77 and Se 0.26, total 99.17 wt.%, corresponding to the empirical formula Pd3.05(Bi1.89Ag0.04Pb0.04)Σ1.97(S1.95Se0.03)Σ1.98 based on a total of 7 atoms per formula unit. The simplified formula is Pd3Bi2S2. The mineral is cubic, space group I213, with a = 8.3097(9) Å, V = 573.79(1) Å3 and Z = 4. The density calculated on the basis of the empirical formula and cell dimensions of synthetic vymazalovaite is 9.25 g/cm3. The strongest lines in the powder X-ray diffraction pattern of synthetic vymazalovaite [d in Å (I) (hkl)] are: 4.15(32)(200), 2.93(78)(220), 2.40(100)(220), 2.08(53)(400), 1.695(34)(422), 1.468(35)(440) and 1.252(31)(622). The structural identity of natural vymazalovaite with synthetic Pd3Bi2S2 was confirmed by electron back-scatter diffraction measurements on the natural sample. This new mineral honours Dr Anna Vymazalova of the Czech Geological Survey, Prague.