Elemental Analysis of Colonial Period Ceramics from Moquegua, Peru

Recent scholarship demonstrates growth in archaeological analysis of Spanish colonial reducciones in Andean South America. Critical to understanding the impact of reducciones on indigenous populations is examining production and circulation of craft goods after Spanish conquest. Because it characterizes the elemental composition of archaeological pottery, Laser Ablation Inductively Coupled Plasma Mass Spectrometry (LA-ICP-MS) is an invaluable tool for examining resource procurement and long distance exchange. In this thesis, I report data derived from XRF and LA-ICP-MS analyses of pottery from two sites in the Moquegua Valley, Peru: Torata Alta and Sabaya. Both sites were founded during Inca control of the valley (c. 1450-1535) but were also occupied into the seventeenth century and have strong Spanish colonial components. Comparing the data with an existing ICP-MS database on locally available clays, I examine differential resource procurement as well as access to imported goods among indigenous and Spanish communities in early colonial Moquegua

Use of the University of Minnesota Biocatalysis/Biodegradation Database for study of microbial degradation

Microorganisms are ubiquitous on earth and have diverse metabolic transformative capabilities important for environmental biodegradation of chemicals that helps maintain ecosystem and human health. Microbial biodegradative metabolism is the main focus of the University of Minnesota Biocatalysis/Biodegradation Database (UM-BBD). UM-BBD data has also been used to develop a computational metabolic pathway prediction system that can be applied to chemicals for which biodegradation data is currently lacking. The UM-Pathway Prediction System (UM-PPS) relies on metabolic rules that are based on organic functional groups and predicts plausible biodegradative metabolism. The predictions are useful to environmental chemists that look for metabolic intermediates, for regulators looking for potential toxic products, for microbiologists seeking to understand microbial biodegradation, and others with a wide-range of interests

Going public: UK companies’ use of capital markets

Public capital markets play an important role in financing the activities of non-financial companies in the United Kingdom, providing them with the main alternative to bank loans and private sources of finance. Although a small number of UK companies issue public bonds and equity, those that do account for a relatively large share of domestic investment and employment. Since the start of the financial crisis in 2007, bond and equity issuance has allowed some large companies to dampen the impact of the contraction in bank lending and the worsening economic outlook on investment and hiring. This suggests that there may be macroeconomic benefits to broadening access to public capital markets. The Bank has helped support primary corporate bond issuance at times of impaired secondary market functioning since 2009 through its Corporate Bond Secondary Market Scheme.

The Litlyngton Missal: Its Patron, Iconography, and Messages

The Litlyngton Missal, Westminster Abbey Library MS 37, is a lavishly illuminated English service book commissioned by Abbot Nicholas Litlyngton 1383-4 and donated to his Benedictine monastery at Westminster. This thesis examines the life of this medieval ecclesiastical patron and investigates how his missal is an expression not simply of a desire to be commemorated, but is also a reflection of his priorities as a member of Westminster’s monastic community. While the study’s emphasis is on the missal’s iconography, both text and image are contextually examined in order to better appreciate the patron’s intended messages of personal devotion to the cult of the Blessed Virgin Mary, the abbey’s promotion, and protection of its privileges. This study scrutinizes the abbey’s particular status in relation to the crown and how this is reflected through the missal, most especially through the inclusion of coronation orders and royal exequies. Considering the rubrics and illuminations of these ceremonies through the lens of Westminster Abbey and its abbot elucidates their authorship and clarifies why, atypically, they were included in a service book of this kind. Analysis of documentation and examination of the book’s stages of creation affords a better understanding of the missal’s production than has been obtained to date and shows that there is an overarching aesthetic cohesion to the book. The thesis offers a critical reappraisal of the missal’s illumination and reveals previously unacknowledged innovation and subtlety. The thesis considers what images occur, where, and how they relate to the text. The findings regarding the imagery are contextualised by comparison with illumination schemes of other English missals of fourteenth and fifteenth century missals and service books. The thesis discussion begins with a biographical study of Nicholas Litlyngton in chapter one, providing a clear context to the man who commissioned the missal. Chapter two considers Litlyngton specifically in his role as patron of the missal. The focus of chapter three is the production of the missal, focusing on its scribe, the illuminators, and their style. Discussion of the contested matter of number of artists and attribution of work also occurs in this chapter. Chapter four scrutinises the text and images connected to the royal ceremonies and examines the motivation behind their inclusion in the missal. The final chapter considers the manuscript’s iconographic programme through a comparative study of other English missals, and interprets the extent of convention or innovation in the Litlyngton Missal’s illuminations. Chapter five also examines messages contained in the images and reflects on their significance and purpose

The University of Minnesota pathway prediction system: predicting metabolic logic

The University of Minnesota pathway prediction system (UM-PPS, http://umbbd.msi.umn.edu/predict/) recognizes functional groups in organic compounds that are potential targets of microbial catabolic reactions, and predicts transformations of these groups based on biotransformation rules. Rules are based on the University of Minnesota biocatalysis/biodegradation database (http://umbbd.msi.umn.edu/) and the scientific literature. As rules were added to the UM-PPS, more of them were triggered at each prediction step. The resulting combinatorial explosion is being addressed in four ways. Biodegradation experts give each rule an aerobic likelihood value of Very Likely, Likely, Neutral, Unlikely or Very Unlikely. Users now can choose whether they view all, or only the more aerobically likely, predicted transformations. Relative reasoning, allowing triggering of some rules to inhibit triggering of others, was implemented. Rules were initially assigned to individual chemical reactions. In selected cases, these have been replaced by super rules, which include two or more contiguous reactions that form a small pathway of their own. Rules are continually modified to improve the prediction accuracy; increasing rule stringency can improve predictions and reduce extraneous choices. The UM-PPS is freely available to all without registration. Its value to the scientific community, for academic, industrial and government use, is good and will only increase

Data-driven extraction of relative reasoning rules to limit combinatorial explosion in biodegradation pathway prediction

Motivation: The University of Minnesota Pathway Prediction System (UM-PPS) is a rule-based expert system to predict plausible biodegradation pathways for organic compounds. However, iterative application of these rules to generate biodegradation pathways leads to combinatorial explosion. We use data from known biotransformation pathways to rationally determine biotransformation priorities (relative reasoning rules) to limit this explosion. Results: A total of 112 relative reasoning rules were identified and implemented. In one prediction step, i.e. as per one generation predicted, the use of relative reasoning decreases the predicted biotransformations by over 25% for 50 compounds used to generate the rules and by about 15% for an external validation set of 47 xenobiotics, including pesticides, biocides and pharmaceuticals. The percentage of correctly predicted, experimentally known products remains at 75% when relative reasoning is used. The set of relative reasoning rules identified, therefore, effectively reduces the number of predicted transformation products without compromising the quality of the predictions. Availability: The UM-PPS server is freely available on the web to all users at the time of submission of this manuscript and will be available following publication at http://umbbd.msi.umn.edu/predict/. Contact: [email protected] Supplementary information: Supplementary data are available at Bioinformatics onlin

Predicting biodegradation products and pathways: a hybrid knowledge- and machine learning-based approach

Motivation: Current methods for the prediction of biodegradation products and pathways of organic environmental pollutants either do not take into account domain knowledge or do not provide probability estimates. In this article, we propose a hybrid knowledge- and machine learning-based approach to overcome these limitations in the context of the University of Minnesota Pathway Prediction System (UM-PPS). The proposed solution performs relative reasoning in a machine learning framework, and obtains one probability estimate for each biotransformation rule of the system. As the application of a rule then depends on a threshold for the probability estimate, the trade-off between recall (sensitivity) and precision (selectivity) can be addressed and leveraged in practice. Results: Results from leave-one-out cross-validation show that a recall and precision of ∼0.8 can be achieved for a subset of 13 transformation rules. Therefore, it is possible to optimize precision without compromising recall. We are currently integrating the results into an experimental version of the UM-PPS server. Availability: The program is freely available on the web at http://wwwkramer.in.tum.de/research/applications/biodegradation/data. Contact: [email protected]

The University of Minnesota pathway prediction system: predicting metabolic logic

The University of Minnesota pathway prediction system (UM-PPS, http://umbbd.msi.umn.edu/predict/) recognizes functional groups in organic compounds that are potential targets of microbial catabolic reactions, and predicts transformations of these groups based on biotransformation rules. Rules are based on the University of Minnesota biocatalysis/biodegradation database (http://umbbd.msi.umn.edu/) and the scientific literature. As rules were added to the UM-PPS, more of them were triggered at each prediction step. The resulting combinatorial explosion is being addressed in four ways. Biodegradation experts give each rule an aerobic likelihood value of Very Likely, Likely, Neutral, Unlikely or Very Unlikely. Users now can choose whether they view all, or only the more aerobically likely, predicted transformations. Relative reasoning, allowing triggering of some rules to inhibit triggering of others, was implemented. Rules were initially assigned to individual chemical reactions. In selected cases, these have been replaced by super rules, which include two or more contiguous reactions that form a small pathway of their own. Rules are continually modified to improve the prediction accuracy; increasing rule stringency can improve predictions and reduce extraneous choices. The UM-PPS is freely available to all without registration. Its value to the scientific community, for academic, industrial and government use, is good and will only increas

Field-scale remediation of atrazine-contaminated soil using recombinant Escherichia coli expressing atrazine chlorohydrolase

We performed the first field-scale atrazine remediation study in the United States using chemically killed, recombinant organisms. This field study compared biostimulation methods for enhancing atrazine degradation with a novel bioaugmentation protocol using a killed and stabilized whole-cell suspension of recombinant Escherichia coli engineered to overproduce atrazine chlorohyrolase, AtzA. AtzA dechlorinates atrazine, producing non-toxic and non-phytotoxic hydroxyatrazine. Soil contaminated by an accidental spill of atrazine (up to 29 000 p.p.m.) supported significant populations of indigenous microorganisms capable of atrazine catabolism. Laboratory experiments indicated that supplementing soil with carbon inhibited atrazine biodegradation, but inorganic phosphate stimulated atrazine biodegradation. A subsequent field-scale study consisting of nine (0.75m3) treatment plots was designed to test four treatment protocols in triplicate. Control plots contained moistened soil; biostimulation plots received 300 p.p.m. phosphate; bioaugmentation plots received 0.5% (w/w) killed, recombinant E. coli cells encapsulating AtzA; and combination plots received phosphate plus the enzyme-containing cells. After 8 weeks, atrazine levels declined 52% in plots containing killed recombinant E. coli cells, and 77% in combination plots. In contrast, atrazine levels in control and biostimulation plots did not decline significantly. These data indicate that genetically engineered bacteria overexpressing catabolic genes significantly increased degradation in this soil heavily contaminated with atrazine