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A new tool, PyHoLo software, was developed to help automate the process of determining magnetic field B from a series of holograms, registered at different environmental conditions (e.g. for upside and downside orientations of a sample in a specimen holder). This procedure involves translating single holograms into phase shift of electron wave, but also alignment of holograms (i.e. shift, rotation, magnification) and finally calculation of magnetic field in an area selected for investigation. PyHoLo gives functionality for performing all those steps without having to refer to different programs and tools. The workflow and results of this procedure are discussed using as an example sample of FeCuSiB. Program summary Program title: PyHoLo CPC Library link to program files: http://dx.doi.org/10.17632/n4rgzbnbpw.1 Licensing provisions: GNU General Public License 3 Programming language: Python Nature of problem: (1) Determination of electric and magnetic fields in a sample on the basis of electron holograms, registered on transmission electron microscope during off-axis holography experiment. (2) Alignment of electron holograms acquired for different sample orientations and at different external conditions. Solution method: PyHoLo adapts procedures for all steps required to translate experimental holograms into electric and magnetic signals, i.e. restoration of total phase shift, alignment of electron holograms (shift, rotation, magnification, warping), phase separation. There is no need to refer to different tools and programs. Additional comments: PyHoLo requires Python 3.6 or newer and a number of external libraries to work (see README or manual for details). PyHoLo is a constant work in progress, developed by only one person, so it might be a little rough around the edges. References: For instructions on installation and execution of PyHoLo see README.txt (provided with the source files).

We present b i m E X , a Mathematica package for exact computations in 3 + 1 bimetric relativity. It is based on the x A c t bundle, which can handle computations involving both abstract tensors and their components. In this communication, we refer to the latter case as concrete computations. The package consists of two main parts. The first part involves the abstract tensors, and focuses on how to deal with multiple metrics in x A c t . The second part takes an ansatz for the primary variables in a chart as the input, and returns the covariant BSSN bimetric equations in components in that chart. Several functions are implemented to make this process as fast and user-friendly as possible. The package has been used and tested extensively in spherical symmetry and was the workhorse in obtaining the bimetric covariant BSSN equations and reproducing the bimetric 3 + 1 equations in the spherical polar chart. Program summary Program Title: b i m E X Program Files doi: http://dx.doi.org/10.17632/2s5d7csc9w.1 Licensing provisions: GNU General Public License 3.0 Programming language: M a t h e m a t i c a Supplementary material: • [1.] README file, containing instructions about how to use the working example. • [2.] Working example, constituted by the notebooks: • [(a)] bimEX_Working_Example.nb • [(b)] bimEX_Decomposition_Lists_Loader.nb • [(c)] bimEX_Decomposition_xAct_Loader.nb Nature of problem: Writing the bimetric covariant BSSN equations in any desired ansatz and chart. Solution method: Definition of functions within the M a t h e m a t i c a package x A c t , which computes all the components of the defined abstract tensors and reduce the abstract tensors to their representation in components. Additional comments: GitHub repository at https://github.com/nubirel/bimEX

BACKGROUND: Circadian rhythms are fundamental to health and are particularly important for mental wellbeing. Disrupted rhythms of rest and activity are recognised as risk factors for major depressive disorder and bipolar disorder.METHODS: We conducted a genome-wide association study (GWAS) of low relative amplitude (RA), an objective measure of rest-activity cycles derived from the accelerometer data of 71,500 UK Biobank participants. Polygenic risk scores (PRS) for low RA were used to investigate potential associations with psychiatric phenotypes.OUTCOMES: Two independent genetic loci were associated with low RA, within genomic regions for Neurofascin (NFASC) and Solute Carrier Family 25 Member 17 (SLC25A17). A secondary GWAS of RA as a continuous measure identified a locus within Meis Homeobox 1 (MEIS1). There were no significant genetic correlations between low RA and any of the psychiatric phenotypes assessed. However, PRS for low RA was significantly associated with mood instability across multiple PRS thresholds (at PRS threshold 0·05: OR = 1·02, 95% CI = 1·01-1·02, p = 9·6 × 10-5), and with major depressive disorder (at PRS threshold 0·1: OR = 1·03, 95% CI = 1·01-1·05, p = 0·025) and neuroticism (at PRS threshold 0·5: Beta = 0·02, 95% CI = 0·007-0·04, p = 0·021).INTERPRETATION: Overall, our findings contribute new knowledge on the complex genetic architecture of circadian rhythmicity and suggest a putative biological link between disrupted circadian function and mood disorder phenotypes, particularly mood instability, but also major depressive disorder and neuroticism.FUNDING: Medical Research Council (MR/K501335/1).

Information Retrieval (IR) plays a key role in diverse Software Engineering (SE) tasks. Similarity metric is the core component of any IR techniques whose performance differs for various document types. Different SE tasks operate on different types of documents like bug reports, software descriptions, source code, etc., that often contain non-standard domain-specific vocabulary. Thus, it is important to understand which similarity metrics are suitable for different SE documents. We analyze the performance of different similarity metrics on various SE documents including a diverse combination of textual (e.g., description, readme), code (e.g., source code, API, import package), and a mixture of text and code (e.g., bug reports) artifacts. We observe that, in general, the context-aware IR models achieve better performance on textual artifacts. In contrast, simple keyword-based bag-of-words models perform better in code artifacts.

Writing quality is an important component in defining students’ capabilities. However, providing comprehensive feedback to students about their writing is a cumbersome and time-consuming task that can dramatically impact the learning outcomes and learners’ performance. The aim of this paper is to introduce a fully automated method of generating essay feedback in order to help improve learners’ writing proficiency. Using the TASA (Touchstone Applied Science Associates, Inc.) corpus and the textual complexity indices reported by the ReaderBench framework, more than 740 indices were reduced to five components using a Principal Component Analysis (PCA). These components may represent some of the basic linguistic constructs of writing. Feedback on student writing for these five components is generated using an extensible rule engine system, easily modifiable through a configuration file, which analyzes the input text and detects potential feedback at various levels of granularity: sentence, paragraph or document levels. Our prototype consists of a user-friendly web interface to easily visualize feedback based on a combination of text color highlighting and suggestions of improvement.

README files play an essential role in shaping a developer's first impression of a software repository and in documenting the software project that the repository hosts. Yet, we lack a systematic understanding of the content of a typical README file as well as tools that can process these files automatically. To close this gap, we conduct a qualitative study involving the manual annotation of 4,226 README file sections from 393 randomly sampled GitHub repositories and we design and evaluate a classifier and a set of features that can categorize these sections automatically. We find that information discussing the `What' and `How' of a repository is very common, while many README files lack information regarding the purpose and status of a repository. Our multi-label classifier which can predict eight different categories achieves an F1 score of 0.746. To evaluate the usefulness of the classification, we used the automatically determined classes to label sections in GitHub README files using badges and showed files with and without these badges to twenty software professionals. The majority of participants perceived the automated labeling of sections based on our classifier to ease information discovery. This work enables the owners of software repositories to improve the quality of their documentation and it has the potential to make it easier for the software development community to discover relevant information in GitHub README files.

The focus of this work is on providing an open source software recommendations using the Github API. Specifically, we propose a hybrid method that considers the programming languages, topics and README documents that appear in the users’ repositories. To demonstrate our approach, we implement a proof of concept that provides recommendations.

Writing is a central skill needed for learning that is tightly linked to text comprehension. Good writing skills are gained through practice and are characterized by clear and organized language, accurate grammar usage, strong text cohesion, and sophisticated wording. Providing constructive feedback can help learners improve their writing; however, providing feedback is a time-consuming process. The aim of this paper is to present an updated version of the tool ReadME, which generates automated and personalized feedback designed to help learners improve the quality of their writing. Sampling a corpus of over 15,000 essays, we used the ReaderBench framework to generate more than 1,200 textual complexity indices. These indices were then grouped into six writing components using a Principal Component Analysis. Based on the components generated by the PCA, as well as individual index values, we created an extensible rule-based engine to provide personalized feedback at four granularity levels: document, paragraph, sentence, and word levels. The ReadME tool consists of a multi-layered, interactive visualization interface capable of providing feedback to writers by highlighting sections of texts that may benefit from revision.

GitHub is one of the largest and most popular repository hosting service today, having about 14 million users and more than 54 million repositories as of March 2017. This makes it an excellent platform to find projects that developers are interested in exploring. GitHub showcases its most popular projects by cataloging them manually into categories such as DevOps tools, web application frameworks, and game engines. We propose that such cataloging should not be limited only to popular projects. We explore the possibility of developing such cataloging system by automatically extracting functionality descriptive text segments from readme files of GitHub repositories. These descriptions are then input to LDA-GA, a state-of-the-art topic modeling algorithm, to identify categories. Our preliminary experiments demonstrate that additional meaningful categories which complement existing GitHub categories can be inferred. Moreover, for inferred categories that match GitHub categories, our approach can identify additional projects belonging to them. Our experimental results establish a promising direction in realizing automatic cataloging system for GitHub.

Data variability is a commonly observed phenomenon in Electronic Health Records (EHR) data networks. A common question asked in scientific investigations of EHR data is whether the cross-site and -time variability reflects an underlying data quality error at one or more contributing sites versus actual differences driven by various idiosyncrasies in the healthcare settings. Although research analysts and data scientists have commonly used various statistical methods to detect and account for variability in analytic datasets, self service tools to facilitate exploring cross-organizational variability in EHR data warehouses are lacking and could benefit from meaningful data visualizations. DQe-v, an interactive, database-agnostic tool for visually exploring variability in EHR data provides such a solution. DQe-v is built on an open source platform, R statistical software, with annotated scripts and a readme document that makes it fully reproducible. To illustrate and describe functionality of DQe-v, we describe the DQe-v’s readme document which includes a complete guide to installation, running the program, and interpretation of the outputs. We also provide annotated R scripts and an example dataset as supplemental materials. DQe-v offers a self service tool to visually explore data variability within EHR datasets irrespective of the data model. GitHub and CIELO offer hosting and distribution of the tool and can facilitate collaboration across any interested community of users as we target improving usability, efficiency, and interoperability.

To uncover interesting and actionable information from natural language documents authored by software developers, many researchers rely on "out-of-the-box" NLP libraries. However, software artifacts written in natural language are different from other textual documents due to the technical language used. In this paper, we first analyze the state of the art through a systematic literature review in which we find that only a small minority of papers justify their choice of an NLP library. We then report on a series of experiments in which we applied four state-of-the-art NLP libraries to publicly available software artifacts from three different sources. Our results show low agreement between different libraries (only between 60% and 71% of tokens were assigned the same part-of-speech tag by all four libraries) as well as differences in accuracy depending on source: For example, spaCy achieved the best accuracy on Stack Overflow data with nearly 90% of tokens tagged correctly, while it was clearly outperformed by Google's SyntaxNet when parsing GitHub ReadMe files. Our work implies that researchers should make an informed decision about the particular NLP library they choose and that customizations to libraries might be necessary to achieve good results when analyzing software artifacts written in natural language.

Automatic building of software projects provides a desirable foundation to support a large variety of software engineering research tasks based on open software repositories. In this paper, we propose the first technique to automatically extract software build commands from software readme files and Wiki pages, and combine the extracted commands for software building. Specifically, we leverage the Named Entity Recognition (NER) technique for build-command extraction, and prioritize the extracted build commands to identify which one should be used in software build. Our experiment on top Java projects from GitHub reveals that, the proposed technique can correctly identify more than 90% of build commands, and can successfully build 84% of the projects that can be built successfully through manual inspection of software support documents.

GitHub contains millions of repositories among which many are similar with one another (i.e., having similar source codes or implementing similar functionalities). Finding similar repositories on GitHub can be helpful for software engineers as it can help them reuse source code, build prototypes, identify alternative implementations, explore related projects, find projects to contribute to, and discover code theft and plagiarism. Previous studies have proposed techniques to detect similar applications by analyzing API usage patterns and software tags. However, these prior studies either only make use of a limited source of information or use information not available for projects on GitHub. In this paper, we propose a novel approach that can effectively detect similar repositories on GitHub. Our approach is designed based on three heuristics leveraging two data sources (i.e., GitHub stars and readme files) which are not considered in previous works. The three heuristics are: repositories whose readme files contain similar contents are likely to be similar with one another, repositories starred by users of similar interests are likely to be similar, and repositories starred together within a short period of time by the same user are likely to be similar. Based on these three heuristics, we compute three relevance scores (i.e., readme-based relevance, stargazer-based relevance, and time-based relevance) to assess the similarity between two repositories. By integrating the three relevance scores, we build a recommendation system called RepoPal to detect similar repositories. We compare RepoPal to a prior state-of-the-art approach CLAN using one thousand Java repositories on GitHub. Our empirical evaluation demonstrates that RepoPal achieves a higher success rate, precision and confidence over CLAN.

Purpose The recent publication “Supplement to European Guidelines”, version 1.0, 2013, (S1), has reviewed the tests for quality assurance of digital mammographic equipment. The majority of the tests considered as essential or desirable regard the detector and the resulting quality of the images. The analyses are very demanding if no suitable tools for the automatic analysis of the images are available. The authors developed a free prototype of such a tool to be improved with the practise and the feedbacks of the possible users. Methods MaMMoS1 is a homemade software for analyzing mammographic digital images. It was written in MATLAB® but it does not require Matlab installed on the computer. It was developed at our facilities for helping us in our routine quality controls. In the intention of the authors it would be a starting platform that should be improved by feedback and suggestions from the users. Currently it performs the following test-items described in S1: (Essential) 2b.2.2.1.1 Response function/2b.2.2.1.2 Noise evaluation. 2b.2.1.3.5 AEC Breast thickness and composition compensation. 2b.2.2.3.1 Image receptor homogeneity. 2b.2.4.5 Ghost image/erasure thoroughness. (Desirable) 2b.2.1.3.6 Local dense area. It can be downloaded at: https://www.fisicamedica.it/gruppi/gruppo-regionale/toscana . Instructions for the installation and use of the software are given in a readme file. Results The software has been routinely applied proving useful for the calculation of the requested parameters. Each test requires no more than a few seconds. It is possible to process images on site and so it is possible to identify defective performance soon after the measurements, possibly apply corrective procedures and repeat the test. Conclusions The introduction of MaMMoS1 in our quality assurance program has allowed economic and human resources savings as a considerable amount of time during each check can be saved. It can be updated to include additional analysis and tools to make the quality checks faster and easier for the user. The detector performances, homogeneity, response function, ghost, and noise, can be fully explored so the software can be used for digital detector of other modalities with respect to mammography an in the future include additional more specific features. Download : Download high-res image (208KB) Download : Download full-size image

CoastSat is an open-source software toolkit written in Python that enables the user to obtain time-series of shoreline position at any sandy coastline worldwide from 30+ years (and growing) of publicly available satellite imagery. The toolkit exploits the capabilities of Google Earth Engine to efficiently retrieve Landsat and Sentinel-2 images cropped to any user-defined region of interest. The resulting images are pre-processed to remove cloudy pixels and enhance spatial resolution, before applying a robust and generic shoreline detection algorithm. This novel shoreline detection technique combines a supervised image classification and a sub-pixel resolution border segmentation to map the position of the shoreline with an accuracy of ~10 m. The purpose of CoastSat is to provide coastal managers, engineers and scientists a user-friendly and practical toolkit to monitor and explore their coastlines. The software is freely-available on GitHub ( https://github.com/kvos/CoastSat ) and is accompanied by guided examples (Jupyter Notebook) plus step-by-step README documentation.

The TAU code is a 1D line-by-line radiative transfer code, which is generally applicable for modelling transmission spectra of close-in extrasolar planets. The inputs are the assumed pressure-temperature profile of the planetary atmosphere, the continuum absorption coefficients and the absorption cross-sections for the trace molecular absorbers present in the model, as well as the fundamental system parameters taken from the published literature. The program then calculates the optical path through the planetary atmosphere of the radiation from the host star, and quantifies the absorption due to the modelled composition in a transmission spectrum of transit depth as a function of wavelength. The code is written in C++, parallelised using OpenMP, and is available for public download and use from http://www.ucl.ac.uk/exoplanets/., 29 pages, 7 figures

We present a code for solving the single-particle, time-independent Schr\"odinger equation in two dimensions. Our program utilizes the imaginary time propagation (ITP) algorithm, and it includes the most recent developments in the ITP method: the arbitrary order operator factorization and the exact inclusion of a (possibly very strong) magnetic field. Our program is able to solve thousands of eigenstates of a two-dimensional quantum system in reasonable time with commonly available hardware. The main motivation behind our work is to allow the study of highly excited states and energy spectra of two-dimensional quantum dots and billiard systems with a single versatile code, e.g., in quantum chaos research. In our implementation we emphasize a modern and easily extensible design, simple and user-friendly interfaces, and an open-source development philosophy., Comment: Fixed terminology in orthonormalization algorithms

This dataset contains the full text transcripts from 15 semi-structured interviews (approximately 44,100 words) conducted during November and December 2014 with participants involved in various aspects of the process of health-related comics production. These participants are authors and publishers and their work is publicly recognised in the comics community. The dataset has been deposited in the Open Health Data Dataverse repository as a zipped folder containing 15 individual simple text files corresponding to each interview and a ReadMe file containing contextual information and other metadata. An initial domain analysis of the interviews was published as Farthing, A., & Priego, E. (2016). ‘Graphic Medicine’ as a Mental Health Information Resource: Insights from Comics Producers. 'The Comics Grid: Journal of Comics Scholarship', 6(1), 3. DOI: http://doi.org/10.16995/cg.74

Recently, accumulating studies have indicated that microRNAs (miRNAs) play an important role in exploring the pathogenesis of various human diseases at the molecular level and may result in the design of specific tools for diagnosis, treatment evaluation and prevention. Experimental identification of disease-related miRNAs is time-consuming and labour-intensive. Hence, there is a stressing need to propose efficient computational methods to detect more potential miRNA–disease associations. Currently, several computational approaches for identifying disease-related miRNAs on the miRNA–disease network have gained much attention by means of integrating miRNA functional similarities and disease semantic similarities. However, these methods rarely consider the network topological similarity of the miRNA–disease association network. Here, in this paper we develop an improved computational method named NTSMDA that is based on known miRNA–disease network topological similarity to exploit more potential disease-related miRNAs. We achieve an AUC of 89.4% by using the leave-one-out cross-validation experiment, demonstrating the excellent predictive performance of NTSMDA. Furthermore, predicted highly ranked miRNA–disease associations of breast neoplasms, lung neoplasms and prostatic neoplasms are manually confirmed by different related databases and literature, providing evidence for the good performance and potential value of the NTSMDA method in inferring miRNA–disease associations. The R code and readme file of NTSMDA can be downloaded from https://github.com/USTC-HIlab/NTSMDA.

Background Metagenomics is a genomics research discipline devoted to the study of microbial communities in environmental samples and human and animal organs and tissues. Sequenced metagenomic samples usually comprise reads from a large number of different bacterial communities and hence tend to result in large file sizes, typically ranging between 1–10 GB. This leads to challenges in analyzing, transferring and storing metagenomic data. In order to overcome these data processing issues, we introduce MetaCRAM, the first de novo, parallelized software suite specialized for FASTA and FASTQ format metagenomic read processing and lossless compression. Results MetaCRAM integrates algorithms for taxonomy identification and assembly, and introduces parallel execution methods; furthermore, it enables genome reference selection and CRAM based compression. MetaCRAM also uses novel reference-based compression methods designed through extensive studies of integer compression techniques and through fitting of empirical distributions of metagenomic read-reference positions. MetaCRAM is a lossless method compatible with standard CRAM formats, and it allows for fast selection of relevant files in the compressed domain via maintenance of taxonomy information. The performance of MetaCRAM as a stand-alone compression platform was evaluated on various metagenomic samples from the NCBI Sequence Read Archive, suggesting 2- to 4-fold compression ratio improvements compared to gzip. On average, the compressed file sizes were 2-13 percent of the original raw metagenomic file sizes. Conclusions We described the first architecture for reference-based, lossless compression of metagenomic data. The compression scheme proposed offers significantly improved compression ratios as compared to off-the-shelf methods such as zip programs. Furthermore, it enables running different components in parallel and it provides the user with taxonomic and assembly information generated during execution of the compression pipeline. Availability The MetaCRAM software is freely available at http://web.engr.illinois.edu/~mkim158/metacram.html. The website also contains a README file and other relevant instructions for running the code. Note that to run the code one needs a minimum of 16 GB of RAM. In addition, virtual box is set up on a 4GB RAM machine for users to run a simple demonstration. Electronic supplementary material The online version of this article (doi:10.1186/s12859-016-0932-x) contains supplementary material, which is available to authorized users.

International audience; The paper deals with the generation of ReadME files from an ontology-based description of NLP tool. ReadME files are structured and organised according to properties defined in the ontology. One of the problem is being able to deal with multilingual generation of texts. To do so, we propose to map the ontol-ogy elements to multilingual knowledge defined in a SKOS ontology.

Over the years, programmers have developed all sorts of conventions to wrangle the infinitely malleable nature of software. There are rules for how new versions should be numbered; how variables and functions should be named; the use of README files; and so on. Such measures provide consistency, especially for people grappling with software written by others, which can otherwise be a maddeningly obfuscated black box.

The U.S. Geological Survey (USGS) conducts baseline and storm response photography missions to document and understand the changes in vulnerability of the Nation's coasts to extreme storms. On September 1, 2014, the USGS conducted an oblique aerial photographic survey from Navarre Beach, Florida, to Breton Island, Louisiana, aboard a Maule MT57 aircraft at an altitude of 500 feet (ft) and approximately 1,200 ft offshore (Figure 2, http://pubs.usgs.gov/ds/0952/html/ds952_fig2.html). This survey was flown to collect data for assessing incremental changes since the last survey, flown July 2013, and can be used for assessing future coastal change. The photographs provided here are Joint Photographic Experts Group (JPEG) images. The photograph locations are an estimate of the position of the and aircraft do not indicate the location of the feature in the images (see the Navigation Data page for additional details, http://pubs.usgs.gov/ds/0952/html/ds952_nav.html). These photographs document the configuration of the barrier islands and other coastal features at the time of the survey. CSV: Comma separate values files representing table information collected during the flight. JPEG: Images can be opened directly with any JPEG-compatible image viewer. The survey's full-size photographs are divided into ?two ?areas. KML: ds952_2014-?326-FA.kml has? 1,111 photographs. TXT: Text files representing the navigation files, FACS log, metadata and readme files collected during and after the survey. KML: The KMLs provided may be viewed with Google Earth (http://www.google.com/earth/download/ge/agree.html). ExifTool (http://www.sno.phy.queensu.ca/~phil/exiftool/) is a free software program for reading, writing, and manipulating image, audio, and video metadata. ExifTool was used to add the following to the header of each photo: time of collection, Global Positioning System (GPS) latitude, GPS longitude, keywords, credit, artist (photographer), caption, copyright, and contact information. Photographs can be opened directly with any JPEG-compatible image viewer by clicking on a thumbnail on the contact sheet. All image times are recorded in Coordinated Universal Time (UTC). Table 1 (http://pubs.usgs.gov/ds/0952/html/ds952_table.html) provides detailed information about the assigned location, name, date, and time the photograph was taken along with links to the photograph. In addition to the photographs, a Google Earth Keyhole Markup Language (KML) file is provided and can be used to view the images by clicking on the marker and then clicking on either the thumbnail or the link above the thumbnail. The KML files were created using the photographic navigation files. Note: A KML number was assigned to each photograph to aid navigation of the Google Earth file. These numbers correspond to the site labels in Google Earth.

UNLABELLED: Statistical analysis of amino acid and nucleotide sequences, especially sequence alignment, is one of the most commonly performed tasks in modern molecular biology. However, for many tasks in bioinformatics, the requirement for the features in an alignment to be consecutive is restrictive and "n-grams" (aka k-tuples) have been used as features instead. N-grams are usually short nucleotide or amino acid sequences of length n, but the unit for a gram may be chosen arbitrarily. The n-gram concept is borrowed from language technologies where n-grams of words form the fundamental units in statistical language models. Despite the demonstrated utility of n-gram statistics for the biology domain, there is currently no publicly accessible generic tool for the efficient calculation of such statistics. Most sequence analysis tools will disregard matches because of the lack of statistical significance in finding short sequences. This article presents the integrated Biological Language Modeling Toolkit (BLMT) that allows efficient calculation of n-gram statistics for arbitrary sequence datasets. AVAILABILITY: BLMT can be downloaded from http://www.cs.cmu.edu/~blmt/source and installed for standalone use on any Unix platform or Unix shell emulation such as Cygwin on the Windows platform. Specific tools and usage details are described in a "readme" file. The n-gram computations carried out by the BLMT are part of a broader set of tools borrowed from language technologies and modified for statistical analysis of biological sequences; these are available at http://flan.blm.cs.cmu.edu/.

This report presents a set of validation and verification (V&V) MCNP 6.1.1 beta results calculated in parallel, with MPI, obtained using its event generators at intermediate and high-energies compared against various experimental data. It also contains several examples of results using the models at energies below 150 MeV, down to 10 MeV, where data libraries are normally used. This report can be considered as the forth part of a set of MCNP6 Testing Primers, after its first, LA-UR-11-05129, and second, LA-UR-11-05627, and third, LA-UR-26944, publications, but is devoted to V&V with the latest, 1.1 beta version of MCNP6. The MCNP6 test-problems discussed here are presented in the /VALIDATION_CEM/and/VALIDATION_LAQGSM/subdirectories in the MCNP6/Testing/directory. README files that contain short descriptions of every input file, the experiment, the quantity of interest that the experiment measures and its description in the MCNP6 output files, and the publication reference of that experiment are presented for every test problem. Templates for plotting the corresponding results with xmgrace as well as pdf files with figures representing the final results of our V&V efforts are presented. Several technical “bugs” in MCNP 6.1.1 beta were discovered during our current V&V of MCNP6 while running it in parallel with MPI usingmore » its event generators. These “bugs” are to be fixed in the following version of MCNP6. Our results show that MCNP 6.1.1 beta using its CEM03.03, LAQGSM03.03, Bertini, and INCL+ABLA, event generators describes, as a rule, reasonably well different intermediate- and high-energy measured data. This primer isn’t meant to be read from cover to cover. Readers may skip some sections and go directly to any test problem in which they are interested.« less

This abstract describes README-EVAL, a novel measure for semantic parsing evaluation of interpreters for instructions in computer program README files. That is enabled by leveraging the tens of thousands of Open Source Software programs that have been annotated by package maintainers of GNU/Linux operating systems. We plan to make available a public shared implementation of this evaluation.

Background Predicting type-1 Human Immunodeficiency Virus (HIV-1) protease cleavage site in protein molecules and determining its specificity is an important task which has attracted considerable attention in the research community. Achievements in this area are expected to result in effective drug design (especially for HIV-1 protease inhibitors) against this life-threatening virus. However, some drawbacks (like the shortage of the available training data and the high dimensionality of the feature space) turn this task into a difficult classification problem. Thus, various machine learning techniques, and specifically several classification methods have been proposed in order to increase the accuracy of the classification model. In addition, for several classification problems, which are characterized by having few samples and many features, selecting the most relevant features is a major factor for increasing classification accuracy. Results We propose for HIV-1 data a consistency-based feature selection approach in conjunction with recursive feature elimination of support vector machines (SVMs). We used various classifiers for evaluating the results obtained from the feature selection process. We further demonstrated the effectiveness of our proposed method by comparing it with a state-of-the-art feature selection method applied on HIV-1 data, and we evaluated the reported results based on attributes which have been selected from different combinations. Conclusion Applying feature selection on training data before realizing the classification task seems to be a reasonable data-mining process when working with types of data similar to HIV-1. On HIV-1 data, some feature selection or extraction operations in conjunction with different classifiers have been tested and noteworthy outcomes have been reported. These facts motivate for the work presented in this paper. Software availability The software is available at http://ozyer.etu.edu.tr/c-fs-svm.rar. The software can be downloaded at esnag.etu.edu.tr/software/hiv_cleavage_site_prediction.rar; you will find a readme file which explains how to set the software in order to work.

Most of the time, working with plugins is straightforward. The plugin developer has written a readme file with comprehensive description of the plugin’s features, good installation instructions, and a FAQ. The installation goes smoothly and what you see matches the plugin’s screenshots.

A symbolic program performing the Formal Reduction of Density Operators (FRODO), formerly developed in the MuPAD computer algebra system with the purpose of evaluating the matrix elements of the electronic Hamiltonian between internally contracted functions in a complete active space (CAS) scheme, has been rewritten in Mathematica. New version : A program summary Program title: FRODO Catalogue identifier: ADV Y _v2_0 Program summary URL: http://cpc.cs.qub.ac.uk/summaries/ADVY_v2_0.html Program obtainable from: CPC Program Library, Queen’s University, Belfast, N. Ireland Licensing provisions: Standard CPC licence, http://cpc.cs.qub.ac.uk/licence/licence.html No. of lines in distributed program, including test data, etc.: 3878 No. of bytes in distributed program, including test data, etc.: 170729 Distribution format: tar.gz Programming language: Mathematica Computer: Any computer on which the Mathematica computer algebra system can be installed Operating system: Linux Classification: 5 Catalogue identifier of previous version: ADV Y _v1_0 Journal reference of previous version: Comput. Phys. Comm. 171(2005)63 Does the new version supersede the previous version?: No Nature of problem. In order to improve on the CAS-SCF wavefunction one can resort to multireference perturbation theory or configuration interaction based on internally contracted functions (ICFs) which are obtained by application of the excitation operators to the reference CAS-SCF wavefunction. The previous formulation of such matrix elements in the MuPAD computer algebra system, has been rewritten using Mathematica. Solution method: The method adopted consists in successively eliminating all occurrences of inactive orbital indices (core and virtual) from the products of excitation operators which appear in the definition of the ICFs and in the electronic Hamiltonian expressed in the second quantization formalism. Reasons for new version: Some years ago we published in this journal a couple of papers [1, 2] hereafter to be referred to as papers I and II, respectively dedicated to the automated evaluation of the matrix elements of the molecular electronic Hamiltonian between internally contracted functions [3] (ICFs). In paper II the program FRODO (after Formal Reduction Of Density Operators) was presented with the purpose of providing working formulas for each occurrence of the ICFs. The original FRODO program was written in the MuPAD computer algebra system [4] and was actively used in our group for the generation of the matrix elements to be employed in the third-order n -electron valence state perturbation theory (NEVPT) [5–8] as well as in the internally contracted configuration interaction (IC-CI) [9]. We present a new version of the program FRODO written in the Mathematica system [10]. The reason for the rewriting of the program lies in the fact that, on the one hand, MuPAD does not seem to be any longer available as a stand-alone system and, on the other hand, Mathematica, due to its ubiquitousness, appears to be increasingly the computer algebra system most widely used nowadays. Restrictions: The program is limited to no more than doubly excited ICFs. Running time: The examples described in the Readme file take a few seconds to run. References: [1] C. Angeli, R. Cimiraglia, Comp. Phys. Comm. 166 (2005) 53. [2] C. Angeli, R. Cimiraglia, Comp. Phys. Comm. 171 (2005) 63. [3] H.-J. Werner, P. J. Knowles, Adv. Chem. Phys. 89 (1988) 5803. [4] B. Fuchssteiner, W. Oevel: http://www.mupad.de Mupad research group, university of Paderborn. Mupad version 2.5.3 for Linux. [5] C. Angeli, R. Cimiraglia, S. Evangelisti, T. Leininger, J.-P. Malrieu, J. Chem. Phys. 114 (2001) 10252. [6] C. Angeli, R. Cimiraglia, J.-P. Malrieu, J. Chem. Phys. 117 (2002) 9138. [7] C. Angeli, B. Bories, A. Cavallini, R. Cimiraglia, J. Chem. Phys. 124 (2006) 054108. [8] C. Angeli, M. Pastore, R. Cimiraglia, Theor. Chem. Acc. 117 (2007) 743. [9] C. Angeli, R. Cimiraglia, Mol. Phys. in press, DOI:10.1080/00268976.2012.689872 [10] http://www.wolfram.com/Mathematica . Mathematica version 8 for Linux.

Besides source code, the fundamental source of information about Open Source Software lies in documentation, and other non source code files, like README, INSTALL, or HowTo files, commonly available in the software ecosystem. These documents, written in natural language, provide valuable information during the software development stage, but also in future maintenance and evolution tasks. DMOSS is a toolkit designed to systematically assess the quality of non source code text found in software packages. The toolkit handles a package as an attribute tree, and performs several tree traverse algorithms through a set of plugins, specialized in retrieving specific metrics from text, gathering information about the software. These metrics are later used to infer knowledge about the software, and composed together to build reports that assess the quality of specific features of the software. This paper discusses the motivations for this work, continues with a description of the toolkit implementation and design goals. Follows an example of its usage to process a software package, and the produced report. Finally some final remarks and trends for future work are presented., Fundação para a Ciência e a Tecnologia (FCT)

This article is an electronic publication in Spectrochimica Acta Electronica (SAE), the electronic section of Spectrochimica Acta Part B (SAB). The hard copy text is accompanied by a disk with two electron number density ( n e ) calculation programs written in Turbo Basic (NNE.EXE) and C language (NE.EXE), data mes ( ∗ .DAT), a text file (NE.WP) with the hard copy paper in WordPerfect 5.1 and a text file (README) for the introduction of the data files and programs. The theoretical aspects and applications of NNE.EXE and NE.EXE are described in the main article for three plasmas having a wide range of electron number density (4 × 10 13 to 1 × 10 17 cm −3 ). The descriptions of the procedure, data format, and hardware requirements can be found in the Appendix and the README file. The determination of n e . is accomplished by least-squares fitting of the entire emission profile or the wing portions of the emission profile of the H β line (486.13 nm) to the theoretical Stark broadened profiles, compiled at electron temperature 2500, 5000, 10000 and 20000 K. This approach can reduce errors in the determination of n e owing to the structural dip in the center of the Stark profiles depending on n e value. The curve-fitting routine employs an interval-halving algorithm to produce new interpolated Stark profiles, reduces number of iterations and time required for calculation, and allows the calculation of n e to the limits set by instrument spectral resolution and the availability of theoretical spectral data. Additionally, each program provides graphic displays allowing the reader to observe the interpolated Stark profiles, the fitting process, and magnitude of residuals during the course of calculation, and the effects of plasma temperatures and spectral resolution on the estimation of n e . In addition to H β , theoretical profiles also are included for H α and H γ to illustrate the suitability and drawbacks of these lines for n e estimation. These programs are extended versions of a program reported earlier in Spectrochimica Acta 44B , 175 (1989).

Summary: pViz.js is a visualization library for displaying protein sequence features in a Web browser. By simply providing a sequence and the locations of its features, this lightweight, yet versatile, JavaScript library renders an interactive view of the protein features. Interactive exploration of protein sequence features over the Web is a common need in Bioinformatics. Although many Web sites have developed viewers to display these features, their implementations are usually focused on data from a specific source or use case. Some of these viewers can be adapted to fit other use cases but are not designed to be reusable. pViz makes it easy to display features as boxes aligned to a protein sequence with zooming functionality but also includes predefined renderings for secondary structure and post-translational modifications. The library is designed to further customize this view. We demonstrate such applications of pViz using two examples: a proteomic data visualization tool with an embedded viewer for displaying features on protein structure, and a tool to visualize the results of the variant_effect_predictor tool from Ensembl. Availability and implementation: pViz.js is a JavaScript library, available on github at https://github.com/Genentech/pviz. This site includes examples and functional applications, installation instructions and usage documentation. A Readme file, which explains how to use pViz with examples, is available as Supplementary Material A. Contact: masselot.alexandre@gene.com Supplementary information: Supplementary data are available at Bioinformatics online.

Summary: The development of bioinformatic solutions for microbial ecology in Perl is limited by the lack of modules to represent and manipulate microbial community profiles from amplicon and meta-omics studies. Here we introduce Bio-Community, an open-source, collaborative toolkit that extends BioPerl. Bio-Community interfaces with commonly used programs using various file formats, including BIOM, and provides operations such as rarefaction and taxonomic summaries. Bio-Community will help bioinformaticians to quickly piece together custom analysis pipelines and develop novel software. Availability an implementation: Bio-Community is cross-platform Perl code available from http://search.cpan.org/dist/Bio-Community under the Perl license. A readme file describes software installation and how to contribute. Contact: f.angly@uq.edu.au Supplementary information: Supplementary data are available at Bioinformatics online

Summary: MGD 3 , a GIS-based database of mod-erate- to large-size dark dune fields on Mars, can be a useful tool in Mars aeolian research. Although MGD 3 is GIS-based, non-GIS users can access the database through spreadsheet tables, while those without GIS software can view MGD 3 with easy to use, free online GIS software. The planet-wide scope of the database, combined with the detailed attributes of the dune fields, allows MGD 3 to be used to address global, re-gional, and local research questions. MGD 3 has been released as USGS OFR 2007-1158 and can be found at http://pubs.usgs.gov/of/2007/1158/. A more complete description of MGD 3 can be found in the “Dunes_ReadMe” file and the “ReadMe_GIS” file in the Documentation folder at the OFR website. The Mars Dunes Consortium website, http://www.mars-dunes.org/, is a central location that provides links to the websites in this abstract. Links to MGD 3 and related sites. USGS OFR 2007-1158 http://pubs.usgs.gov/of/2007/1158/ JMARS http://jmars.asu.edu PIGWAD http://webgis.wr.usgs.gov Mars Dunes Consortium http://www.mars-dunes.org/ ArcReader http://www.esri.com/software/arcgis/arcreader/download.html

Hermes is an experimental language for writing disgributed applications and systems. The language is fully described elsewhere[1]. This report summarizes the major features of The language and provides numerous short code fragments to illustrate the various constructs. Missing from this report is any discussion of user-defined constraints, which are in any case not yet supported in the prototype implementation we have developed. Those wishing to obtain the prototype software may do so via anonymous ftp to software.watson.ibm.com (IP address 129.34.139.5); the files/pub/README.FTP and/pub/hermes/README provide further instructions.

Summary: Multiple sequence alignment (MSA) is a central tool in most modern biology studies. However, despite generations of valuable tools, human experts are still able to improve automatically generated MSAs. In an effort to automatically identify the most reliable MSA for a given protein family, we propose a very simple protocol, named AQUA for ‘Automated quality improvement for multiple sequence alignments’. Our current implementation relies on two alignment programs (MUSCLE and MAFFT), one refinement program (RASCAL) and one assessment program (NORMD), but other programs could be incorporated at any of the three steps. Availability: AQUA is implemented in Tcl/Tk and runs in command line on all platforms. The source code is available under the GNU GPL license. Source code, README and Supplementary data are available at http://www.bork.embl.de/Docu/AQUA. Contact: muller@embl.de, bork@embl.de

The program PABS normalizes relative particle emission probabilities to an absolute scale and calculates the relevant uncertainties on this scale. The program is written in Java using the JDK 1.6 library. For additional information about system requirements, the code itself, and compiling from source, see the README file distributed with this program. The mathematical procedures used are given below.

This chapter describes how the Kismet server can be configured. The kismet.conf config file can be edited directly with one's favorite UNIX text editor (such as vi, pico, emacs). The config file is parsed at runtime by the server and expects a UNIX text file. In general, if one is editing the kismet.conf file, a UNIX editor should be used. Comments in the kismet.conf file are lines starting with a “#” symbol. These are often comments or example configurations, and can usually guide to what options are needed to be set. Lines that do not start with a comment are the actual parameter variables acted upon by the server. The servername parameter allows one to name the server for one's organizational purposes. Kismet requires root access to set monitor mode and other options, then it drops privileges on the Kismet processes to the user specified in this parameter. The username of a nonprivileged (nonroot) user should be specified on the system; the logical place for this is the nonprivileged users home directory. The source line tells Kismet what it needs to know to get data into the program so that one can start scanning. Each source has three parameters: a Kismet source name for the specific type of card, the interface name, and a logical name found in the Kismet client. The Kismet README has a list of compatible sources and their proper interface names. The chapter explains several other parameters of Kismet configuration file. The Kismet server, in addition to the config file, can be controlled at the start by command-line switches.

ADDA is a versatile development platform for AD- and DA-converters. It contains performance analysis algorithms for converters enabling the user to characterise converters and create data-sheets. The converters characterised are either simulated or real products. Currently characterisation and modelling of Nyquist converters are included with delta-sigma converters to follow in a future release. The platform, written in C-language, is free software released with the Gnu General Public License (GPL) and is freely available for all parties interested to contribute with models, analysis methods or measurement setups. New models of converters are easily included in the platform following included templates and the instructions in the README.

et al., We update the all-sky Planck catalogue of 1227 clusters and cluster candidates (PSZ1) published in March 2013, derived from detections of the Sunyaev–Zeldovich (SZ) effect using the first 15.5 months of Planck satellite observations. As an addendum, we deliver an updated version of the PSZ1 catalogue, reporting the further confirmation of 86 Planck-discovered clusters. In total, the PSZ1 now contains 947 confirmed clusters, of which 214 were confirmed as newly discovered clusters through follow-up observations undertaken by the Planck Collaboration. The updated PSZ1 contains redshifts for 913 systems, of which 736 (~ 80.6%) are spectroscopic, and associated mass estimates derived from the Yz mass proxy. We also provide a new SZ quality flag for the remaining 280 candidates. This flag was derived from a novel artificial neural-network classification of the SZ signal. Based on this assessment, the purity of the updated PSZ1 catalogue is estimated to be 94%. In this release, we provide the full updated catalogue and an additional readme file with further information on the Planck SZ detections., The development of Planck has been supported by: ESA; CNES and CNRS/INSU-IN2P3-INP (France); ASI, CNR, and INAF (Italy); NASA and DoE (USA); STFC and UKSA (UK); CSIC, MICINN, JA and RES (Spain); Tekes, AoF and CSC (Finland); DLR and MPG (Germany); CSA (Canada); DTU Space (Denmark); SER/SSO (Switzerland); RCN (Norway); SFI (Ireland); FCT/MCTES (Portugal); and PRACE (EU).

UNLABELLED BioCloneDB is a user-friendly database with a web interface to assist molecular genetics laboratories in managing a local repository of sequence information linked to DNA clones. This tool is designed to assist in high-throughput sequence and gene expression projects, providing a link between both types of information. The unique feature of the application is the automation of batch sequence annotation following BLAST((R)) searches, which is supported by easy-to-use web interfaces. Furthermore, any set of sequences can be annotated against any sequence database. This replaces the need to perform and analyse individual web BLAST((R)) searches or the need to learn how to produce batch searches and perform analysis in a UNIX((R)) operating system. BioCloneDB is open-source software that can be installed on Linux or UNIX((R)) operating systems. To test the application, we used 1400 expressed sequence tags obtained from the filamentous fungus Neurospora crassa. The results were analysed and compared with published results and they show a significant change due to the accumulation of the data in the nr database (ftp://ftp.ncbi.nih.gov/blast/db/). AVAILABILITY BioCloneDB is available for academic use along with documentation, screenshots, database scheme and readme files at http://bioclonedb.agri.huji.ac.il/ CONTACT Oded Yarden (Oded.Yarden@huji.ac.il).

This erratum corrects two errors in the results presented in Cummins, Hassett, and Oliner (2006). First, the dating of one series in the bottom panel of Figure 2 was off by one year. The value we showed for the percent change in the ratio of cash flow to investment (CF/K) for year t actually represented the value for the previous year in our dataset. The corrected version of this panel is shown below. Similarly, the GMM estimates in Table 3 for the sample of unrated firms (columns 3 and 6) reflected data for CF/K that were inadvertently lagged by one year. The corrected version of Table 3 is shown below. We thank Senay Agca for bringing these errors to our attention. In the course of checking the results in the paper, we also discovered that the datasets posted on the AER website for replicating the results in Table 6 do not contain the correct data. Unfortunately, we cannot post the appropriate datasets for Table 6 because we did not save the source data files. We have revised the “readme” file in the posted documentation to alert readers to this problem.

We have made available a number of files, some of which have been mentioned in the text. These can all be found at ftp.liv.ac.uk in the directory ∼ftp/pub/genus2 by anonymous ftp. You should first type: ftp ftp.liv.ac.uk and then login using anonymous as your name, and your e-mail address as your password. Then type: cd ∼ftp/pub/genus2 which will take you to the correct directory. Once you have further changed to the desired subdirectory, then the standard command: get filename will copy the file filename to your local directory. The current directory structure is as follows. In addition to the following files, there is also a file README in each directory, describing the contents of that directory. These should be read to check for any changes recently made to the directory. Please send any questions about these files to: evflynn@liv.ac.uk preferably with the subject header genus 2 ftp files .

When you install a piece of software, you can usually just follow the instructions provided by the README or the INSTALL file. In a way, Apache is no exception. However, Apache is a very complex program, and needs to be compiled and installed with particular care, to make sure that it’s reasonably secure in the short and in the long term.

This data set maps and describes the geology of the Big Bear City 7.5' quadrangle, San Bernardino County, California. Created using Environmental Systems Research Institute's ARC/INFO software, the data base consists of the following items: (1) a rock-unit coverage and attribute tables (polygon and arc) containing geologic contacts, units and rock-unit labels as annotation which are also included in a separate annotation coverage, bbc_anno (2) a point coverage containing structural point data and (3) a coverage containing fold axes. In addition, the data set includes the following graphic and text products: (1) A PostScript graphic plot-file containing the geologic map, topography, cultural data, a Correlation of Map Units (CMU) diagram, a Description of Map Units (DMU), an index map, a regional geologic and structure map, and an explanation for point and line symbols; (2) PDF files of the Readme (including the metadata file as an appendix), and a screen graphic of the plot produced by the PostScript plot file. The geologic map describes a geologically complex area on the north side of the San Bernardino Mountains. Bedrock units in the Big Bear City quadrangle are dominated by (1) large Cretaceous granitic bodies ranging in composition from monzogranite to gabbro, (2) metamorphosed sedimentary rocks ranging in age from late Paleozoic to late Proterozoic, and (3) Middle Proterozoic gneiss. These rocks are complexly deformed by normal, reverse, and thrust faults, and in places are tightly folded. The geologic map database contains original U.S. Geological Survey data generated by detailed field observation and by interpretation of aerial photographs. The map data was compiled on base-stable cronoflex copies of the Big Bear City 7.5' topographic map, transferred to a scribe-guide and subsequently digitized. Lines, points, and polygons were edited at the USGS using standard ARC/INFO commands. Digitizing and editing artifacts significant enough to display at a scale of 1:24,000 were corrected. Within the database, geologic contacts are represented as lines (arcs), geologic units as polygons, and site-specific data as points. Polygon, arc, and point attribute tables (.pat, .aat, and .pat, respectively) uniquely identify each geologic datum.

This document describes the procedures and methods used to measure total carbon dioxide (TCO{sub 2}) and total alkalinity (TALK) at hydrographic stations taken during the R/V Knorr Indian Ocean cruises (Sections I8SI9S, I9N, I8NI5E, I3, I5WI4, I7N, I1, I10, and I2) in 1994-1996. The measurements were conducted as part of the World Ocean Circulation Experiment (WOCE). The expedition began in Fremantle, Australia, on December 1, 1994, and ended in Mombasa, Kenya, on January 22, 1996. During the nine cruises, 12 WOCE sections were occupied. Total carbon dioxide was extracted from water samples and measured using single-operator multiparameter metabolic analyzers (SOMMAs) coupled to coulometers. The overall precision and accuracy of the analyses was {+-} 1.20 {micro}mol/kg. The second carbonate system parameter, TALK, was determined by potentiometric titration. The precision of the measurements determined from 962 analyses of certified reference material was {+-} 4.2 {micro}mol/kg (REFERENCE). This work was supported by grants from the National Science Foundation, the U. S. Department of Energy, and the National Oceanographic and Atmospheric Administration. The R/V Knorr Indian Ocean data set is available as a numeric data package (NDP) from the Carbon Dioxide Information Analysis Center (CDIAC). The NDP consists of 18 oceanographic data files, twomore » FORTRAN 77 data retrieval routine files, a readme file, and this printed documentation, which describes the contents and format of all files as well as the procedures and methods used to obtain the data. Instructions for accessing the data are provided.« less

Summary: RECSIM takes a general genealogy and simulates the transmission of chromosomes through that genealogy. INDSTATS extracts some basic statistics from the output of RECSIM Availability: The RECSIM and INDSTATS programs together with readme files READMESIM and READMESTATS can be downloaded from http://www.shef.ac.uk/mmge/chris/inbred.html Contact: c.cannings@shef.ac.uk * To whom correspondence should be addressed.

This data set maps the soil-slip susceptibility for several areas in southwestern California. Created using Environmental Systems Research Institute's ARC/INFO software, the data base consists of raster maps containing grid cells coded with soil- slip susceptibility values. In addition, the data set includes the following graphic and text products: (1) postscript graphic plot files containing the soil-slip susceptibility map, topography, cultural data, and a key of the colored map units, and (2) PDF and text files of the Readme (including the metadata file as an appendix) and accompanying text, and a PDF file of the plot files. Intense winter rains commonly generated debris flows in upland areas of southwestern California. These debris flows initiate as small landslides referred to as soil slips. Most of the soil slips mobilize into debris flows that travel down slope at varying speeds and distances. The debris flows can be a serious hazard to people and structures in their paths. The soil-slip susceptibility maps identify those natural slopes most likely to be the sites of soil slips during periods of intense winter rainfall. The maps were largely derived by extrapolation of debris-flow inventory data collected from selected areas of southwestern California. Based on spatial analyses of soil slips, three factors in addition to rainfall, were found to be most important in the origin of soil slips. These factors are geology, slope, and aspect. Geology, by far the most important factor, was derived from existing geologic maps. Slope and aspect data were obtained from 10-meter digital elevation models (DEM). Soil-slip susceptibility maps at a scale of 1:24,000 were derived from combining numerical values for geology, slope, and aspect on a 10-meter cell size for 128 7.5' quadrangles and assembled on 1:100,000-scale topographic maps. The resultant maps of relative soil-slip susceptibility represent the best estimate generated from available debris-flow inventory maps and DEM data.

How do archives provide access to their records and let users search? The answer is archival description. Encoded Archival Description (EAD) in Extensible Markup Language (XML) is the de facto technical standard for "electronic" archival descriptions. It is now used to bridge the gulf between tangible records in archives and digital objects on the World WideWeb. These descriptions are finding aids, which are tools to search and find information about, or references to, archival records. The archival finding aids in EAD are left to searchers (out of sight and contact) to explore in unknown ways: how do searchers interact with these finding aids, and what type of retrieval system is needed to support them. The approach is to apply XML retrieval techniques to the EAD finding aids, develop system evaluation of EAD retrieval, and study information seeking behavior of archival search. The main information retrieval (IR) contributions are the system evaluation of an important "real" and domain-specific search task, a study on the usage of transaction logs for deriving domain-specific test collections, an analysis of search behavior in yet unexplored structured documents, and tailoring IR evaluation to specific searcher stereotypes. The first study involves the design and implementation of the archival search engine README. The README system attempts to incorporate current technologies with the archival structure in finding aids---such as XML retrieval---and simultaneously to uphold the archival principles where this structure is based upon. The system is the proof of concept. Having established this baseline, the next study explores and tests the construction of an IR test collection. A test collection is a key component in IR evaluation. The basis of this test collection are the queries and clicks on archival descriptions that can be found in the search log files of the National Archives of the Netherlands. There is no readily-available test collection for evaluating the accuracy of the retrieval of archival descriptions of records by an archival search engine. Manually creating such a collection is expensive. The study shows that automatically creating a test collection seems viable. Archival principles---such as provenance and original order---are deeply rooted in the arrangement and subsequent description of archival records. These principles have been cast on EAD finding aids as well. The investigation continues by shedding new light on them in a system evaluation. Additionally, the experiments probe XML retrieval-specific issues, such as the retrieval of certain elements. The study concludes by reflecting on the README archival search engine, which is the baseline of the probes in this dissertation. How effective are certain archival principles for archival access in this digital age. Using the archival search log files, the research focus shifts to the arrangement of records in EAD and user search behaviors using this arrangement. The sub-document clicks within the finding aids point to the online interaction of users within "electronic" archival descriptions of records. The analysis of the interactions comprises of quantifying the search behavior. This results in a state diagram that captures different information search behaviors of different people. By analyzing real-world interaction, the discussion on the use of the finding aid in this digital age as access tool becomes more complete. The result is more understanding of online archival search behavior within EAD finding aids, which can be used to improve a search system adapted to existing "electronic" archival description. Finally, the system evaluation deals with tailoring a search engine to the different user stereotypes, namely "expert" and 'novice' groups based on the number of times that a user re-uses the system. The results show that although there are significant differences in terms of search behavior, this does not necessarily mean that for more effective retrieval of archival descriptions, the system needs to be adapted to improve access for these different user groups. The doctoral dissertation is available online at http://dare.uva.nl/record/395154.