Jesuit action in England

JESUIT ACTION IN ENGLAND brings before us one of the most Interesting periods in the history of England, be it political or ecclesiastical. For it combines both classes of history into one interwoven pattern. It is not merely a recitation of cold facts, of days and times and events. But it is full of romance, intrigue, cunning, tragedy, courage, and suspense. This is the story of the birth of the Church of England, of its struggles in its infancy to establish itself in a world hostile to its innovations and determined to destroy it

Verbena canescens var. roemeriana L.M.Perry

https://thekeep.eiu.edu/herbarium_specimens_byname/19397/thumbnail.jp

Verbena canescens var. roemeriana L.M.Perry

https://thekeep.eiu.edu/herbarium_specimens_byname/19397/thumbnail.jp

Capturing Data Provenance from Statistical Software

We have created tools that automate one of the most burdensome aspects of documenting the provenance of research data: describing data transformations performed by statistical software.  Researchers in many fields use statistical software (SPSS, Stata, SAS, R, Python) for data transformation and data management as well as analysis.  The C2Metadata ("Continuous Capture of Metadata for Statistical Data") Project creates a metadata workflow paralleling the data management process by deriving provenance information from scripts used to manage and transform data.  C2Metadata differs from most previous data provenance initiatives by documenting transformations at the variable level rather than describing a sequence of opaque programs.  Command scripts for statistical software are translated into an independent Structured Data Transformation Language (SDTL), which serves as an intermediate language for describing data transformations.   SDTL can be used to add variable-level provenance to data catalogues and codebooks and to create "variable lineages" for auditing software operations.   Better data documentation makes research more transparent and expands the discovery and re-use of research data

Left-handers look before they leap:handedness influences reactivity to novel Tower of Hanoi tasks

A sample of 203 task naïve left- and right-handed participants were asked to complete a combination of the 3- and 4-disk Towers of Hanoi (ToH), manipulating novelty and complexity. Self-reported state anxiety and latency to respond (initiation time) were recorded before each ToH. Novelty had a major effect on initiation time, particularly for left-handers. Left-handers had a longer latency to start and this was significantly longer on the first trial. Irrespective of hand-preference, initiation time reduced on the second trial, however, this was greatest for left-handers. Condition of task did not systematically influence initiation time for right handers, but did for left-handers. State anxiety was influenced by task novelty and complexity in a more complicated way. During the first trial, there was a significant handedness × number of disks interaction with left-handers having significantly higher state anxiety levels before the 3-disk ToH. This suggests that the initial reaction to this task for left-handers was not simply due to perceived difficulty. On their second trial, participants completing a novel ToH had higher state anxiety scores than those completing a repeated version. Overall, left-handers had a larger reduction in their state anxiety across trials. Relating to this, the expected strong positive correlation between state and trait anxiety was absent for left-handed females in their first tower presentation, but appeared on their second. This was driven by low trait anxiety individuals showing a higher state anxiety response in the first (novel) trial, supporting the idea that left-handed females respond to novelty in a way that is not directly a consequence of their trait anxiety. A possible explanation may be stereotype threat influencing the behavior of left-handed females

Arctic microbial ecosystems and impacts of extreme warming during the International Polar Year

As a contribution to the International Polar Year program MERGE (Microbiological and Ecological Responses to Global Environmental change in polar regions), studies were conducted on the terrestrial and aquatic microbial ecosystems of northern Canada (details at: http://www.cen.ulaval.ca/merge/). The habitats included permafrost soils, saline coldwater springs, supraglacial lakes on ice shelves, epishelf lakes in fjords, deep meromictic lakes, and shallow lakes, ponds and streams. Microbiological samples from each habitat were analysed by HPLC pigment assays, light and fluorescence microscopy, and DNA sequencing. The results show a remarkably diverse microflora of viruses, Archaea (including ammonium oxidisers and methanotrophs), Bacteria (including filamentous sulfur-oxidisers in a saline spring and benthic mats of Cyanobacteria in many waterbodies), and protists (including microbial eukaryotes in snowbanks and ciliates in ice-dammed lakes). In summer 2008, we recorded extreme warming at Ward Hunt Island and vicinity, the northern limit of the Canadian high Arctic, with air temperatures up to 20.5 \ub0C. This was accompanied by pronounced changes in microbial habitats: deepening of the permafrost active layer; loss of perennial lake ice and sea ice; loss of ice-dammed freshwater lakes; and 23% loss of total ice shelf area, including complete break-up and loss of the Markham Ice Shelf cryo-ecosystem. These observations underscore the vulnerability of Arctic microbial ecosystems to ongoing climate change.Peer reviewed: YesNRC publication: Ye

Arctic microbial ecosystems and impacts of extreme warming during the International Polar Year

As a contribution to the International Polar Year program MERGE (Microbiological and Ecological Responses to Global Environmental change in polar regions), studies were conducted on the terrestrial and aquatic microbial ecosystems of northern Canada (details at: http://www.cen.ulaval.ca/merge/). The habitats included permafrost soils, saline coldwater springs, supraglacial lakes on ice shelves, epishelf lakes in fjords, deep meromictic lakes, and shallow lakes, ponds and streams. Microbiological samples from each habitat were analysed by HPLC pigment assays, light and fluorescence microscopy, and DNA sequencing. The results show a remarkably diverse microflora of viruses, Archaea (including ammonium oxidisers and methanotrophs), Bacteria (including filamentous sulfur-oxidisers in a saline spring and benthic mats of Cyanobacteria in many waterbodies), and protists (including microbial eukaryotes in snowbanks and ciliates in ice-dammed lakes). In summer 2008, we recorded extreme warming at Ward Hunt Island and vicinity, the northern limit of the Canadian high Arctic, with air temperatures up to 20.5 \ub0C. This was accompanied by pronounced changes in microbial habitats: deepening of the permafrost active layer; loss of perennial lake ice and sea ice; loss of ice-dammed freshwater lakes; and 23% loss of total ice shelf area, including complete break-up and loss of the Markham Ice Shelf cryo-ecosystem. These observations underscore the vulnerability of Arctic microbial ecosystems to ongoing climate change.Peer reviewed: YesNRC publication: Ye

The effect of oxygenate molecular structure on soot production in direct-injection diesel engines.

A combined experimental and kinetic modeling study of soot formation in diesel engine combustion has been used to study the addition of oxygenated species to diesel fuel to reduce soot emissions. This work indicates that the primary role of oxygen atoms in the fuel mixture is to reduce the levels of carbon atoms available for soot formation by fixing them in the form of CO or COz. When the structure of the oxygenate leads to prompt and direct formation of CO2, the oxygenate is less effective in reducing soot production than in cases when all fuel-bound 0 atoms produce only CO. The kinetic and molecular structure principles leading to this conclusion are described

Automating the Capture of Data Transformation Metadata from Statistical Analysis Software

The C2Metadata (“Continuous Capture of Metadata for Statistical Data”) Project automates one of the most burdensome aspects of documenting the provenance of research data: describing data transformations performed by statistical software. Researchers in many fields use statistical software (SPSS, Stata, SAS, R, Python) for data transformation and data management as well as analysis. The C2Metadata Project creates a metadata workflow paralleling the data management process by deriving provenance information from scripts used to manage and transform data. C2Metadata differs from most previous data provenance initiatives by documenting transformations at the variable level rather than describing a sequence of opaque programs. Scripts used with statistical software are translated into an independent Structured Data Transformation Language (SDTL), which serves as an intermediate language for describing data transformations. SDTL can be used to add variable-level provenance to data catalogs and codebooks and to create “variable lineages” for auditing software operations. Better data documentation makes research more transparent and expands the discovery and re-use of research data.National Science Foundation grant ACI-1640575https://deepblue.lib.umich.edu/bitstream/2027.42/156014/3/Automating_metadata_capture_v15.pd

Provenance Metadata for Statistical Data: An Introduction to Structured Data Transformation Language (SDTL)

Structured Data Transformation Language (SDTL) provides structured, machine actionable representations of data transformation commands found in statistical analysis software. The Continuous Capture of Metadata for Statistical Data Project (C2Metadata) created SDTL as part of an automated system that captures provenance metadata from data transformation scripts and adds variable derivations to standard metadata files. SDTL also has potential for auditing scripts and for translating scripts between languages. SDTL is expressed in a set of JSON schemas, which are machine actionable and easily serialized to other formats. Statistical software languages have a number of special features that have been carried into SDTL. We explain how SDTL handles differences among statistical languages and complex operations, such as merging files and reshaping data tables from “wide” to “long”.National Science Foundation grant ACI-1640575https://deepblue.lib.umich.edu/bitstream/2027.42/156015/1/SDTL_Intro_v14.pdfDescription of SDTL_Intro_v14.pdf : Main articl