Geology and mineralization, Ohio and Mt. Baldy Districts, Marysvale, Piute County, Utah

The Ohio and Mt. Baldy Mining Districts near Marysvale, Utah occupy a cauldron complex in the Bullion Canyon Volcanics. This complex contains three rock groups of three volcanic episodes. The oldest is a volcanic cone framework series of lahars. The middle group is represented by lava flows, ash flows, and breccias which represent intra-caldera fill. The upper group consists of a local vent complex and the Delano Peak Tuff Member both of which may be related to ring fracture activity. The stages of veining in the area include in order of gradational deposition: (1) early quartz veins, (2) pre-productive main stage quartz veins, (3) productive precious metal bearing main stage quartz veins, (4) productive base metal bearing main stage quartz veins, and (5) alunite veins. The initial fissures and veining probably accompanied resurgent doming of the Delano Peak Tuff Member and older rocks. A period of quiescence of about 7 m.y. occurred between Delano Peak Tuff Member deposition and base metal mineralization (Steven and others, 1977). Fissure deepening and vein mineralization was contemporaneous with magmatic doming. Trace amounts of Mo deposition increased with fissure deepening. The earliest stage of hydrothermal alteration is that of alteration activity that formed K-silicate minerals. This preceded veining activity. Pervasive sericitization and argillization accompanied vein stage (1). Advanced argillic, sericitic, argillic, and propylitic alteration zones accompanied vein stages (2) through (5) and envelope those veins in a zonal fashion in the sequence listed. The dome margins were intensely silicified sometime during vein stages (2) through (3). This fringe area developed stockwork fractures and open fissures after silicification. Vein solutions during vein stage (5) oxidized to sulphuric acid near the water table. K and Al, probably leached from the hot volcanic wall rock, reacted with the acid vein solutions to deposit alanite in the stockworks and fissures soon after base metal deposition --Abstract, page ii

Learning-assisted Theorem Proving with Millions of Lemmas

Large formal mathematical libraries consist of millions of atomic inference steps that give rise to a corresponding number of proved statements (lemmas). Analogously to the informal mathematical practice, only a tiny fraction of such statements is named and re-used in later proofs by formal mathematicians. In this work, we suggest and implement criteria defining the estimated usefulness of the HOL Light lemmas for proving further theorems. We use these criteria to mine the large inference graph of the lemmas in the HOL Light and Flyspeck libraries, adding up to millions of the best lemmas to the pool of statements that can be re-used in later proofs. We show that in combination with learning-based relevance filtering, such methods significantly strengthen automated theorem proving of new conjectures over large formal mathematical libraries such as Flyspeck.Comment: journal version of arXiv:1310.2797 (which was submitted to LPAR conference

Combining hydrogeochemistry, statistics and explorative mapping to estimate regional threshold values of trace elements in groundwater (Sardinia, Italy)

Assessing geochemical baseline and threshold values of potentially toxic elements at adequate scales is fundamental for distinguishing geogenic contamination from anthropogenic pollution in groundwater. This study was aimed to estimate the regional threshold values of Li, Be, B, Al, V, Cr, Mn, Fe, Co, Ni, Cu, Zn, As, Se, Rb, Sr, Mo, Ag, Cd, Sb, Te, Ba, Hg, Tl, Pb, Bi, and U (elements listed according to atomic numbers) in groundwater, compare results to guidelines established for drinking water and the protection of groundwater from contamination, investigate the geographical distribution of trace elements, and assess the potential influence of water-rock interaction. A pre-selection aimed at excluding groundwater samples affected by known anthropogenic activities was carefully carried out based on hydrogeochemical characteristics of waters and considering the potential sources of contamination. The resulting dataset was comprised of 1227 groundwater sampling sites located in Sardinia (Italy). Undetected values were treated using the Regression on Order Statistics method. For elements containing >75 % of undetected values and/or a limited number of samples in the dataset (Li, Rb, Sr, Mo, Ag, Te, Tl, Sb, Hg and Bi), the threshold values were estimated using either the 95th or 97.7th percentiles. For the other elements the mean + 2SD (Standard Deviation), the median + 2MAD (Median Absolute Deviation), and the TIF (Tukey Inner Fence) estimators were also calculated. Geochemical maps allowed to recognize the threshold value of each element at different scales. Regional threshold values of the regulated elements B, Al, V, Cr, Cu and Cd in groundwater were below the Italian and World Health Organization drinking water guidelines, whereas Mn and As were above them. Regional threshold values estimated with TIF exceeded the drinking water guidelines for Ni, Se, Pb and U. Results of this study showed that high concentrations of trace elements in groundwater were primarily dependent on the corresponding amount in parent materials with which the groundwater came into contact. Physical-chemical parameters and geochemical characteristics may contribute to enhancing concentrations of some trace elements in groundwater, e.g. As via reductive dissolution of Fe(III)-Mn(IV) hydroxides/oxides, Pb via formation of stable aqueous complexes, and other elements via adsorption onto fine particles with size below 0.4 μm (i.e. the pore size of filters used). Maps drawn on the centered log-ratio (clr) transformation of hydrogeochemical data, following the CoDA (Compositional Data Analysis) approach, allowed to pinpoint critical areas to be investigated in more detail. For each geological complex, groundwater samples likely representing nearly pristine conditions were identified. The monitoring of these representative groundwater samples may help to pinpoint eventual changes in environmental conditions

Improving the Policy Specification for Practical Access Control Systems

Access control systems play a crucial role in protecting the security of information systems by ensuring that only authorized users are granted access to sensitive resources, and the protection is only as good as the access control policies. For enabling a security administrator to express her desired policy conveniently, it is paramount that a policy specification is expressive, comprehensible, and free of inconsistencies. In this dissertation, we study the policy specifications for three practical access control systems (i.e., obligation systems, firewalls, and Security-Enhanced Linux in Android) and improve their expressiveness, comprehensibility, and consistency. First, we improve the expressiveness of obligation policies for handling different types of obligations. We propose a language for specifying obligations as well as an architecture for handling access control policies with these obligations, by extending XACML (i.e., the de facto standard for specifying access control policies). We also implement our design into a prototype system named ExtXACML to handle various obligations. Second, we improve the comprehensibility of firewall policies enabling administrators to better understand and manage the policies. We introduce the tri-modularized design of firewall policies for elevating them from monolithic to modular. To support legacy firewall policies, we also define a five-step process and present algorithms for converting them into their modularized form. Finally, we improve the consistency of Security-Enhanced Linux in Android (SEAndroid) policies for reducing the attack surface in Android systems. We propose a systematic approach as well as a semiautomatic tool for uncovering three classes of policy misconfigurations. We also analyze SEAndroid policies from four Android versions and seven Android phone vendors, and in all of them we observe examples of potential policy misconfigurations

The Decline of Lake Superior\u27s Woodland Caribou: A Historical GIS Analysis

Lake Superior’s woodland caribou have been declining since the early 1800s. This thesis asks: why? We hypothesize that as settlers expanded into the region, industrial development in woodland caribou habitat reduced woodland caribou persistence. Using an Historical Geospatial Information System (HGIS) analysis, we find that historical mining and railroad infrastructure are associated with woodland caribou extirpation, while wetlands and protected areas are associated with caribou persistence. We also conducted a stakeholder synthesis of the region to help understand diverse perspectives within and between advocacy coalitions that take different positions on the most effective caribou restoration policies. Beliefs on recovery options vary broadly. However, there are overlaps among individual beliefs that can lead to compromises on recovery policy. Policymakers should take away that while there may appear to be no easy solution to this wicked problem, there do appear to be areas of common ground on woodland caribou recovery can be found. Listening to and including diverse stakeholders is key to future recovery efforts

Machine learning modeling of superconducting critical temperature

Superconductivity has been the focus of enormous research effort since its discovery more than a century ago. Yet, some features of this unique phenomenon remain poorly understood; prime among these is the connection between superconductivity and chemical/structural properties of materials. To bridge the gap, several machine learning schemes are developed herein to model the critical temperatures ($T_{\mathrm{c}}$) of the 12,000+ known superconductors available via the SuperCon database. Materials are first divided into two classes based on their $T_{\mathrm{c}}$ values, above and below 10 K, and a classification model predicting this label is trained. The model uses coarse-grained features based only on the chemical compositions. It shows strong predictive power, with out-of-sample accuracy of about 92%. Separate regression models are developed to predict the values of $T_{\mathrm{c}}$ for cuprate, iron-based, and "low-$T_{\mathrm{c}}$" compounds. These models also demonstrate good performance, with learned predictors offering potential insights into the mechanisms behind superconductivity in different families of materials. To improve the accuracy and interpretability of these models, new features are incorporated using materials data from the AFLOW Online Repositories. Finally, the classification and regression models are combined into a single integrated pipeline and employed to search the entire Inorganic Crystallographic Structure Database (ICSD) for potential new superconductors. We identify more than 30 non-cuprate and non-iron-based oxides as candidate materials.Comment: 17 pages, 7 figure

Connecting the dots between PubMed abstracts

Background: There are now a multitude of articles published in a diversity of journals providing information about genes, proteins, pathways, and diseases. Each article investigates subsets of a biological process, but to gain insight into the functioning of a system as a whole, we must integrate information from multiple publications. Particularly, unraveling relationships between extra-cellular inputs and downstream molecular response mechanisms requires integrating conclusions from diverse publications. Methodology: We present an automated approach to biological knowledge discovery from PubMed abstracts, suitable for "connecting the dots" across the literature. We describe a storytelling algorithm that, given a start and end publication, typically with little or no overlap in content, identifies a chain of intermediate publications from one to the other, such that neighboring publications have significant content similarity. The quality of discovered stories is measured using local criteria such as the size of supporting neighborhoods for each link and the strength of individual links connecting publications, as well as global metrics of dispersion. To ensure that the story stays coherent as it meanders from one publication to another, we demonstrate the design of novel coherence and overlap filters for use as post-processing steps. Conclusions: We demonstrate the application of our storytelling algorithm to three case studies: i) a many-one study exploring relationships between multiple cellular inputs and a molecule responsible for cell-fate decisions, ii) a many-many study exploring the relationships between multiple cytokines and multiple downstream transcription factors, and iii) a one-to-one study to showcase the ability to recover a cancer related association, viz. the Warburg effect, from past literature. The storytelling pipeline helps narrow down a scientist's focus from several hundreds of thousands of relevant documents to only around a hundred stories. We argue that our approach can serve as a valuable discovery aid for hypothesis generation and connection exploration in large unstructured biological knowledge bases.Institute for Critical Technology and Applied Science, Virginia Tech, and the US National Science Foundation through grant CCF-0937133.Scopu

Reduced sediment supply in a fast eroding landscape? A multi-proxy sediment budget of the upper Rhone basin, Central Alps

Alpine water and sediment supply influence the sediment budget of many important European fluvial systems such as the Rhine, Rhône and Po rivers. In the light of human induced climate change and landscape modification, it becomes increasingly important to understand the mechanisms of sediment production and supply in Alpine sediment systems. This study aims to investigate the modern sediment budget of the upper Rhône basin, one of the largest Alpine intramontane watersheds, located in the Central Alps of southwestern Switzerland. Major areas of sediment generation are fingerprinted by framework petrography, heavy mineral concentrations and bulk geochemistry. The relative contributions of the three major sources to the sediment of the trunk Rhône river are identified by compositional mixing modelling. Concentrations of the terrestrial cosmogenic nuclide 10Be measured in quartz separated from fluvial sediments provide spatially averaged denudation rates for selected tributary basins. Results from sediment fingerprinting and mixing modelling suggest that tributaries located in the North and the East of the catchment are generating most of the sediment transported by the Rhône river to its primary sedimentary sink in Lake Geneva. Despite having some of the highest denudation rates within the basin, tributaries located in the southern area of the Rhône basin are relatively underrepresented in the sediment budget of the Rhône river. These tributaries are severely affected by human activities, for example through sediment mining as well as water and sediment abstraction in large hydropower reservoirs. Together, these processes reduce the basin-wide sediment discharge by about 50%, thereby explaining most of the observed compositional pattern. In addition, there is evidence suggesting that large amounts of glaciogenic sediments are currently supplied by retreating glaciers. Glaciogenic material with its low 10Be concentrations can lead to a significant overestimation of denudation rates and thus limit the applicability of cosmogenic nuclide analysis in such glaciated settings