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Correlations Among Microstructure, Morphology, Chemistry, and Isotopic Systematics of Hibonite in CM Chondrites

Introduction: Hibonite is a primary refractory phase occurring in many CAIs, typically with spinel and perovskite. Our microstructural studies of CAIs from carbonaceous chondrites reveal a range of stacking defect densities and correlated non-stoichiometry in hibonite. We also conducted a series of annealing experiments, demonstrating that the Mg-Al substitution stabilized the formation of defect-structured hibonite. Here, we continue a detailed TEM analysis of hibonite-bearing inclusions from CM chondrites that have been well-characterized isotopically. We examine possible correlations of microstructure, morphology, mineralogy, and chemical and isotopic systematics of CM hibonites in order to better understand the formation history of hibonite in the early solar nebula. Methods: Fifteen hibonite-bearing inclusions from the Paris CM chondrite were analyzed using a JEOL 7600F SEM and a JEOL 8530F electron microprobe. In addition to three hibonite-bearing inclusions from the Murchison CM chondrite previously reported, we selected three inclusions from Paris, Pmt1-6, 1-9, and 1-10, representing a range of 26Al/27Al ratios and minor element concentrations for a detailed TEM study. We extracted TEM sections from hibonite grains using a FEI Quanta 3D field emission gun SEM/FIB. The sections were then examined using a JEOL 2500SE field-emission scanning TEM equipped with a Thermo-Noran thin window EDX spectrometer. Results and Discussion: A total of six hibonite-bearing inclusions, including two platy hibonite crystals (PLACs) and four spinel-hibonite inclusions (SHIBs), were studied. There are notable differences in chemical and isotopic compositions between the inclusions (Table 1), indicative of their different formation environment or timing. Our TEM observations show perfectly-ordered, stoichiometric hibonite crystals without stacking defects in two PLACs, 2-7-1 and 2-8-2, and in three SHIBs, Pmt1-6, 1-9, and 1-10. In contrast, SHIB 1-9-5 hibonite grains contain a low density of stacking defects linked to an increase in MgO contents, indicating complex, disordered intergrowths of stoichiometric and MgO-enriched hibonites. From the data collected to date, we find no clear correlation between the microstructures of hibonite and its morphological and mineralogical types that reflect distinct chemical and isotopic systematics [6-8,10]. Interestingly, the presence of no or few stacking defects in hibonite from the PLACs and SHIBs are in contrast to our experimental studies that produced very high densities of stacking defects in hibonite [3-5]. Unlike our experi-ments, electron microprobe data from the PLACs and SHIBs hibonite grains show a strong correlation between (Ti4++Si4+) and Mg2+ cations, suggesting that coupled substitutions of (Ti4++Mg2+) and (Si4++Mg2+) for 2Al3+ inhibit the formation of defect-structured hibonite. However, our experimental studies suggest that kinetics (e.g., cooling rate) or other thermal effects also exert a strong control on the microstructures and chemical compositions of hibonite. In Pmt1-6, elongated perovskite grains present at the hibonite grain boundaries display (121) twinning, indicative of a fast cooling (>50degC/min) after high-temperature events. Therefore, the nebular microstructural characteristics of hibonite, at least in this inclusion, would not have destroyed by subsequent high-temperature annealing. Conclusions: Our TEM observations thus far show no clear correlation in microstructures, morphological and mineralogical characteristics, and chemical and isotopic systematics of hibonites from CM chondrites. The observed variation in stacking defect densities in the hibonites may be controlled by thermal processes in the early solar nebula. A detailed TEM analysis of additional CM hibonite samples is underway to evaluate this hypothesis.

Han, J.↗

Proceedings for the Workshop on Applied Nuclear Data Activities 2025

The 2025 Workshop for Applied Nuclear Data Activities (WANDA) covered four topic areas in nuclear data: Nuclear Data and Deterrence, Nuclear Data Prioritization for Fusion, High-Assay Low-Enriched Uranium and Novel Moderators for Advanced Reactors, and Data Preservation and Data Workflows. The intention of this workshop is to connect different communities that are invested in nuclear data and have their own unique sets of needs for the purposes of sharing information, fostering collaboration in areas of shared interest, and leveraging synergistic capabilities. The attendance of federal program managers at these workshops is essential in creating awareness of the needs of their respective communities and in providing information to better guide funding investments. In each of these topical sessions, a general description of the nuclear data needs and/or capabilities was presented, along with discussions of existing capabilities that could be leveraged, potential synergistic needs or resources, and challenges that must be overcome for the application space to progress. There are many synergistic nuclear data needs among these application spaces. The discussion largely focused on increasing the accuracy of the nuclear data and better quantifying the data uncertainties that have the greatest impact on applications. The full-day session on data processing and data workflows was by nature intended to be synergistic and applicable to all technical sessions at WANDA. A notable common theme that was highlighted across all sessions was the need for accelerated delivery of nuclear data products across complex and time-consuming workflows.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

metagRoot: a comprehensive database of protein families associated with plant root microbiomes

The plant root microbiome is vital in plant health, nutrient uptake, and environmental resilience. To explore and harness this diversity, we present metagRoot, a specialized and enriched database focused on the protein families of the plant root microbiome. MetagRoot integrates metagenomic, metatranscriptomic, and reference genome-derived protein data to characterize 71 091 enriched protein families, each containing at least 100 sequences. These families are annotated with multiple sequence alignments, CRISPR elements, hidden Markov models, taxonomic and functional classifications, ecosystem and geolocation metadata, and predicted 3D structures using AlphaFold2. MetagRoot is a powerful tool for decoding the molecular landscape of root-associated microbial communities and advancing microbiome-informed agricultural practices by enriching protein family information with ecological and structural context. The database is available at https://pavlopoulos-lab.org/metagroot/ or https://www.metagroot.org.

Chasapi, Maria N↗

MONTI: A Multi-Omics Non-negative Tensor Decomposition Framework for Gene-Level Integrative Analysis

Multi-omics data is frequently measured to enrich the comprehension of biological mechanisms underlying certain phenotypes. However, due to the complex relations and high dimension of multi-omics data, it is difficult to associate omics features to certain biological traits of interest. For example, the clinically valuable breast cancer subtypes are well-defined at the molecular level, but are poorly classified using gene expression data. Here, we propose a multi-omics analysis method called MONTI (Multi-Omics Non-negative Tensor decomposition for Integrative analysis), which goal is to select multi-omics features that are able to represent trait specific characteristics. Here, we demonstrate the strength of multi-omics integrated analysis in terms of cancer subtyping. The multi-omics data are first integrated in a biologically meaningful manner to form a three dimensional tensor, which is then decomposed using a non-negative tensor decomposition method. From the result, MONTI selects highly informative subtype specific multi-omics features. MONTI was applied to three case studies of 597 breast cancer, 314 colon cancer, and 305 stomach cancer cohorts. For all the case studies, we found that the subtype classification accuracy significantly improved when utilizing all available multi-omics data. MONTI was able to detect subtype specific gene sets that showed to be strongly regulated by certain omics, from which correlation between omics types could be inferred. Furthermore, various clinical attributes of nine cancer types were analyzed using MONTI, which showed that some clinical attributes could be well explained using multi-omics data. We demonstrated that integrating multi-omics data in a gene centric manner improves detecting cancer subtype specific features and other clinical features, which may be used to further understand the molecular characteristics of interest. The software and data used in this study are available at: https://github.com/inukj/MONTI.

59 BASIC BIOLOGICAL SCIENCES↗

Robust collection and processing for label-free single voxel proteomics

With advanced mass spectrometry (MS)-based proteomics, genome-scale proteome coverage can be achieved from bulk tissues. However, such bulk measurement lacks spatial resolution and obscures tissue heterogeneity, precluding proteome mapping of tissue microenvironment. Here we report an integrated $\underline{w}et$ $\underline{c}ollection$ of single microscale tissue voxels and $\underline{S}urfactant$$-assisted$ $\underline{O}ne$-$\underline{P}ot$ voxel processing method termed wcSOP for robust label-free single voxel proteomics. wcSOP capitalizes on buffer droplet-assisted wet collection of a single voxel dissected by LCM into the PCR tube cap and MS-compatible surfactant-assisted one-pot voxel processing in the collection cap. This convenient method allows reproducible label-free quantification of ~900 and ~4,600 proteins for single voxels at 20 µm × 20 µm × 10 µm (close to single cells) and 200 µm × 200 µm × 10 µm (~100 cells) from fresh frozen human spleen tissue, respectively. 100s-1000s of protein signatures were spatially resolved between spleen red and white pulp regions depending on the voxel size. Region-specific signaling pathways were enriched from single voxel proteomics data. To evaluate its broad applicability, we applied wcSOP-MS to two commonly accessible, OCT-embedded and FFPE, human archived tissues. It enabled to identify spatially resolved proteome changes and enriched pathways between diseased (breast cancer tumor or AD amyloid plaque) and adjacent normal regions. Antibody-based CODEX and IHC imaging validated label-free MS quantitation for single voxel analysis. The wcSOP-MS method paves the way for routine robust single voxel proteomics and spatial proteomics.

59 BASIC BIOLOGICAL SCIENCES↗

On the Origin of Fluorine-Poor Apatite in Chondrite Parent Bodies

We conducted a petrologic study of apatite within one LL chondrite, six R chondrites, and six CK chondrites. These data were combined with previously published apatite data from a broader range of chondrite meteorites to determine that chondrites host either chlorapatite or hydroxylapatite with ≤33 mol% F in the apatite X-site (unless affected by partial melting by impacts, which can cause F-enrichment of residual apatite). These data indicate that either fluorapatite was not a primary condensate from the solar nebula or that it did not survive lower temperature nebular processes and/or parent body processes. Bulk-rock Cl and F data from chondrites were used to determine that the solar system has a Cl/F ratio of 10.5 ± 1.0 (3σ). The Cl/F ratios of apatite from chondrites are broadly reflective of the solar system Cl/F value, indicating that apatite in chondrites is fluorine poor because the solar system has about an order of magnitude more Cl than F. The Cl/F ratio of the solar system was combined with known apatite-melt partitioning relationships for F and Cl to predict the range of apatite compositions that would form from a melt with a chondritic Cl/F ratio. This range of apatite compositions allowed for the development of a crude model to use apatite X-site compositions from achondrites (and chondrite melt rocks) to determine whether they derive from a volatile-depleted and/or differentiated source, albeit with important caveats that are detailed in the manuscript. This study further highlights the utility of apatite as a mineralogical tool to understand the origin of volatiles (including H 2 O) and the diversity of their associated geological processes throughout the history of our solar system, including at its nascent stage.

Francis M. McCubbin↗

Selective Whole-Genome Amplification as a Tool to Enrich Specimens with Low Treponema pallidum Genomic DNA Copies for Whole-Genome Sequencing

Downstream next-generation sequencing (NGS) of the syphilis spirochete Treponema pallidum subspecies pallidum (T. pallidum) is hindered by low bacterial loads and the overwhelming presence of background metagenomic DNA in clinical specimens. In this study, we investigated selective whole-genome amplification (SWGA) utilizing multiple displacement amplification (MDA) in conjunction with custom oligonucleotides with an increased specificity for the T. pallidum genome and the capture and removal of 5'-C-phosphate-G-3' (CpG) methylated host DNA using the NEBNext Microbiome DNA enrichment kit followed by MDA with the REPLI-g single cell kit as enrichment methods to improve the yields of T. pallidum DNA in isolates and lesion specimens from syphilis patients. Sequencing was performed using the Illumina MiSeq v2 500 cycle or NovaSeq 6000 SP platform. These two enrichment methods led to 93 to 98% genome coverage at 5 reads/site in 5 clinical specimens from the United States and rabbit-propagated isolates, containing >14 T. pallidum genomic copies/μL of sample for SWGA and >129 genomic copies/μL for CpG methylation capture with MDA. Variant analysis using sequencing data derived from SWGA-enriched specimens showed that all 5 clinical strains had the A2058G mutation associated with azithromycin resistance. SWGA is a robust method that allows direct whole-genome sequencing (WGS) of specimens containing very low numbers of T. pallidum, which has been challenging until now.

59 BASIC BIOLOGICAL SCIENCES↗

The rhesus measurement system: A new instrument for space research

The Rhesus Research Facility (RRF) is a research environment designed to study the effects of microgravity using rhesus primates as human surrogates. This experimental model allows investigators to study numerous aspects of microgravity exposure without compromising crew member activities. Currently, the RRF is slated for two missions to collect its data, the first mission is SLS-3, due to fly in late 1995. The RRF is a joint effort between the United States and France. The science and hardware portions of the project are being shared between the National Aeronautics and Space Administration (NASA) and France's Centre National D'Etudes Spatiales (CNES). The RRF is composed of many different subsystems in order to acquire data, provide life support, environmental enrichment, computer facilities and measurement capabilities for two rhesus primates aboard a nominal sixteen day mission. One of these subsystems is the Rhesus Measurement System (RMS). The RMS is designed to obtain in-flight physiological measurements from sensors interfaced with the subject. The RMS will acquire, preprocess, and transfer the physiologic data to the Flight Data System (FDS) for relay to the ground during flight. The measurements which will be taken by the RMS during the first flight will be respiration, measured at two different sites; electromyogram (EMG) at three different sites; electroencephalogram (EEG); electrocardiogram (ECG); and body temperature. These measurements taken by the RMS will assist the research team in meeting the science objectives of the RRF project.

Schonfeld, Julie E.↗

Analyzing HM-5 data with NAIGEM v.2015.1.315 and NAIGEM v.2.1.4

Two HM-5 units were used to measure uranium items. For each measurement, the enrichment calibration was determined. The built-in software to determine the enrichment calibration was NAIGEM version 2015.1.315. The data were later analyzed by a standalone NAIGEM, version 2.1.4, in order to study the behavior of the NAIGEM software with the HM-5 data and the relationships between various parameters in the NAIGEM code and the HM-5.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Cyote-attack Chain Estimator

Attack Chain Estimator (ACE) Application Overview The Attack Chain Estimator (ACE) Application is a sophisticated tool designed for the ingestion, classification, sequencing, and enrichment of cybersecurity threat reports. This application leverages advanced machine learning models and extensive historical data to provide comprehensive insights into cyber threats, specifically targeting Industrial Control Systems (ICS). Purpose The primary functions of the ACE Application include: Ingestion of Cybersecurity Threat Reporting: Capable of ingesting text-based threat reports in markdown or text file format. Supports ingestion of structured data from other sources in STIX/JSON format. Classification of Report’s Text-Based Events: Utilizes a DeBERTa classifier, specifically trained on cybersecurity data, to map the events to MITRE ATT&CK for ICS Tactics and Techniques. Classification is performed using multiple Jupyter notebooks and machine learning workflows hosted as FastAPI microservices: regex_data deberta_base_35_train_hft_classifier_mlflow.ipynb hft_regex_classifier_mlflow.ipynb param_train_hft_classifier_mlflow.ipynb regex_tactic_tech.ipynb Ordering of Tactics, Techniques, and Observable Events: Sequences the identified tactics, techniques, and events to form a coherent attack chain. Enrichment with Historical Attack Chain Details: Enhances the attack chain with details from historical attacks using a Markov model developed from CyOTE Precursor Analysis Report data. The Markov model is available as a FastAPI endpoint for seamless integration. Enrichment with Adversary Emulation Capabilities Data: Integrates adversary emulation capabilities data using MITRE Caldera for OT adversary abilities UUIDs. Export of Output Files: Provides options to export the enriched attack chain in JSON or CSV formats. Routing of Output to Other Applications: Facilitates routing of output to various platforms and applications, including: Threat Intelligence Platforms COREII Scout for Threat Intelligence Analysis COREII Modeling and Simulation for Adversary Emulation Technical Description The ACE Application is an advanced cybersecurity tool designed to provide detailed threat analysis and sequence generation. It is built on a robust architecture that integrates natural language processing, machine learning, and historical data modeling. Key Components: Data Ingestion Module: Handles the input of threat reports and data from various formats, ensuring flexibility in data sources. Classification Engine: Employs DeBERTa-based classifiers hosted as FastAPI microservices to analyze and classify threat report events in accordance with the MITRE ATT&CK framework for ICS. Sequence Generator: Orders the classified events into a logical attack chain, providing clear insight into the sequence of tactics and techniques used in the threat. Enrichment Engine: Integrates historical data and adversary emulation capabilities to enhance the attack chain with valuable context and additional details. The historical data enrichment is powered by a Markov model, which is available as a FastAPI endpoint. Export and Routing Module: Facilitates the export of the enriched attack chain in multiple formats and routes the output to designated applications for further analysis or emulation.

Paul, Tony [Idaho National Laboratory (INL), Idaho↗

Gamma Spectrometry Code Rodeo for Uranium Enrichment—FY 2022 Report

In the first two quarters of FY22, data acquisition continued at ORNL and LLNL using uranium sources of known enrichments. This was an FY21 task which could not be completed in FY21 because of problems encountered with the ORNL M400 CZT in Q4 of FY21, and the subsequent repairs. The detector was received back from H3D in the first of September 2021 , and the measurements resumed . Measurements using the repaired detector were completed in Q1 of FY22. The spectra were distributed by ORNL to the analyzing labs. Analysis results were received in Q2 of FY2022. The results from the various codes were intercompared and an ANOVA analysis was performed. Random and systematic uncertainties were established for each code. The ANOVA results and discussions were included in a revised version of FY21Annual Report issued in March 2022. A paper was presented at the INMM 2022Annual Conference, with the analysis results from the various isotopic codes, and the ANOVA table with random and systematic uncertainties. The Project Work Plan (PWP) for FY22 included a task to perform field testing of the M400 CZT and the analysis codes using UF 6 cylinder measurements at the Framatome Fuel Fabrication Facility in Richland, WA. PNNL was the lead for the field testing task. PNNL drafted a Field Test Plan, and refined it based on comments received from the team. PNNL coordinated with Framatome facility, the logistics of carrying out the field testing . A collimator and shield made out of TFlex (tungsten impregnated polymer) was designed and professionally manufactured. The collimators were used in the field test measurements. The measurements at Framatome were completed on April 21, 2022. A total of 34 Type 30B cylinders were measured using three M400 detectors (PNNL, LLNL, and ORNL detectors). Measurements using M400 were taken at two locations on the side of each cylinder and from the end-on bottom location. Additionally, HPGe measurements were taken at the end-on location to establish ground truth. Cylinder wall thickness measurements were also made at all three locations. To gain a better understanding of the effect of background from surrounding cylinders, the same five cylinders measured individually in low background locations were measured again in the cylinder storage yards. Due to inclement weather, manufacturer delays, shipping delays, and equipment failure, the measurement campaign spanned twice as long compared to the original timeline. Gamma-ray spectra from M400 and HPGe detectors, along with the cylinder data and photographs were organized and shared with the collaborators for further analysis. Spectra were analyzed by the participating laboratories. FY22 PWP also consists of tasks related to plutonium source measurements, adapting the codes to analyze plutonium spectra, and inter-comparison of the results from various codes. Plutonium spectra are being acquired at LANL, ORNL, and LLNL. LANL, SNL and LLNL are in the process of modifying FRAM, GADRAS, and CZTU, respectively. The plutonium related tasks will be completed in Q2 of FY23.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Prognosis of Wind Turbine Gearbox Bearing Failures Using SCADA and Modeled Data

Predictive maintenance and condition monitoring systems for wind turbines have seen increased adoption to minimize downtime, reducing operation and maintenance costs. On today’s wind power plants, the integrated supervisory control and data acquisition (SCADA) system provides low- frequency operational data that can be leveraged to quantify a wind turbine’s health. The aim of this study is to utilize machine-learning techniques to predict axial cracking failures in wind turbine gearbox bearings up to 1 month ahead of time. The failures are assumed to have occurred when the investigated bearing was replaced. While current SCADA systems show the overall condition of a wind turbine, often they do not allow for the investigation of specific gearbox bearings’ health. To enrich bearing fault signatures, additional data are computed through physics-based models using gearbox design information. Based on SCADA data, modeled data, and bearing failure log data from an actual wind plant, the performances of different machine-learning models on unseen data are then evaluated using industry-standard metrics such as precision, recall, and F1 score. Results show the overall system performance enhancement in predicting bearing failure when modeled data are included with SCADA data. The reduction in terms of false alarms is about 50%, and improvement in terms of precision and F1 score is about 33% and 12% respectively, based on the best modeling case in this study.

49 EE - Wind and Water Power Program - Wind (EE-4W↗

Deimos: HALEU TRISO Heated Critical Experiment Data

Deimos was the first critical experiment using high-assay low-enriched uranium (HALEU) TRistructural ISOtropic (TRISO) fuel in over 40 years. HALEU TRISO is the desired fuel form for many of the advanced reactor designs in development; however, very little experimental data are available for this fuel type. Deimos was designed to utilize existing HALEU TRISO fuel in a large graphite moderator to obtain nuclear and reactor physics data to fill the gaps surrounding this fuel type and enrichment. In addition to cold critical data, three separate heated experiments were conducted to measure the temperature reactivity coefficient for this type of system. These measured coefficients were then compared to simulated coefficients to a first level order of fidelity. This comparison showed very good agreement for the experiment where only the inner core was heated and good agreement for the other two configurations, which included heating portions of the outer core. Less agreement when the outer core was heated is attributed to potential heating in the beryllium reflector, which has a positive temperature reactivity coefficient and was unaccounted for in the first-order models. Future heated experiments with Deimos will include temperature monitoring of the beryllium reflector to account for beryllium heating in the simulations.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Getting allometry right at the Oak Ridge free‐air CO 2 enrichment experiment: Old problems and new opportunities for global change experiments

Societal Impact Statement Free‐air CO 2 enrichment (FACE) experiments provide essential data on forest responses to increasing atmospheric CO 2 for evaluations of climate change impacts on humanity. Understanding and reducing the uncertainty in the experimental results is critical to ensure scientific and public confidence in the models and policy initiatives that derive therefrom. One source of uncertainty is the estimation of tree biomass using mathematical relationships between biomass and easily obtained and non‐destructive measurements (allometry). We evaluated the robustness of the allometric relationships established at the beginning of a FACE experiment and discuss the challenges and opportunities for the new generation of FACE experiments. Summary Long‐term field experiments to elucidate forest responses to rising atmospheric CO 2 concentration require allometric equations to estimate tree biomass from non‐destructive measurements of tree size. We analyzed whether the allometric equations established at the beginning of a free‐air CO 2 enrichment (FACE) experiment in a Liquidambar styraciflua plantation were still valid at the end of the 12 year experiment. Aboveground woody biomass was initially predicted by an equation that included bole diameter, taper, and height, assuming that including taper and height as predictors would accommodate changes in tree structure that might occur over time and in response to elevated CO 2 . At the conclusion of the FACE experiment, we harvested 23 trees, measured dimensions and dry mass of boles and branches, and extracted and measured the woody root mass of 10 trees. Although 10 of the harvested trees were larger than the trees used to establish the allometric relationship, measured aboveground woody biomass was well predicted by the original allometry. The initial linear equation between bole basal area and woody root biomass underestimated final root biomass by 28%, but root biomass was just 21% of total wood mass, and errors in aboveground and belowground estimates were offsetting. The allometry established at the beginning of the experiment provided valid predictions of tree biomass throughout the experiment. New allometric approaches using terrestrial laser scanning should reduce an important source of uncertainty in decade‐long forest experiments and in assessments of centuries‐long forest biomass accretion used in evaluating carbon offsets and climate mitigation.

59 BASIC BIOLOGICAL SCIENCES↗

Apatite geochemistry as a tool for understanding the petrogenesis of layered mafic-ultramafic rocks in the Bushveld Complex, South Africa

The sources of the magmas that formed the Rustenburg Layered Suite of the Bushveld Complex in South Africa remain debated, despite decades of research. Vertical and lateral variation in bulk rock and mineral separate Sr-Nd isotopic compositions, which generally indicate enriched sources, demonstrate that the layered sequence was formed by the emplacement of multiple batches of magma, crucially resulting in episodes of PGE-Cr-V mineralisation. The Lu-Hf isotope compositions of zircon are, however, at odds with the bulk rock Sr-Nd isotopic heterogeneity as they show near homogeneous compositions throughout the layered sequence (εHf (2.06 Ga) =−8). This lack of variation in Hf isotope composition has been attributed to deep, continental lithospheric mantle-related and/or crustal contamination of plume-derived Bushveld magmas. In this study, we analysed the major, trace element and Sr-Nd isotope geochemistry of apatite in the Rustenburg Layered Suite. Apatite occurs as an intercumulus mineral in the lowermost regions and a cumulus mineral in the uppermost regions of the layered sequence and can therefore be used to test existing models for the isotopic disequilibrium between bulk rock Sr-Nd and zircon Hf isotopic compositions. Apatite is largely chlorapatite in the lowermost regions and fluorapatite in the uppermost regions of the layered sequence. The Merensky Reef is unusual in that it comprises both chlorapatite and fluorapatite. Apatite throughout the layered sequence is generally unzoned and shows no evidence of late-stage alteration. Trace element data show that apatite is enriched in L/HREE, with common negative Eu-Sr anomalies. These trace element signatures are consistent with a magmatic origin for the apatite grains, with prior, or concurrent, plagioclase crystallization from the same melt. Variability in in situ Sr and Nd isotope compositions of apatite is recorded throughout the layered sequence with εNd (2.06 Ga) compositions varying between −2.5 and − 10.2 and initial 87 Sr/ 86 Sr compositions varying between 0.7079 and 0.7103 (for the Marikana dikes only). The variability in Sr-Nd isotope compositions of apatite is consistent with the bulk rock (and mineral separate) variation in Sr-Nd isotope compositions, suggesting apatite preserves primary magmatic compositions in the Rustenburg Layered Suite.

Apatite↗

Using NASA Remotely Sensed Data to Help Characterize Environmental Risk Factors for National Public Health Applications

This project has dual goals in decision ]making activities .. Providing information to decision makers about associations between environmental exposures and health conditions in a large national cohort study. Enriching the CDC Wide ]ranging Online Data for Epidemiologic Research (WONDER) system by integrating environmental exposure data. .. Develop daily high ]quality spatial data sets of environmental variables for the conterminous U.S. for the years 2003-2008 utilizing NASA data (Objective 1). Fine Particulates (PM2.5) (NASA MODIS and EPA AQS). Land Surface Temperature (NASA MODIS). Solar Insolation and Heat ]related Products (Reanalysis Data). Link these environmental variables with public health data from a national cohort study and examine environmental health relationships (Objective 2). Cognitive Function. Hypertension. Make the environmental datasets available to public health professionals, researchers and the general public via the CDC WONDER system (Objective 3).

Al-Hamdan, Mohammad↗