Excel spreadsheet containing raw data, organized by figure.

This archive contains raw data of visual and acoustic mapping of perforations in Utah FORGE well 16A(78)-32 acquired during the August 2024 circulation program. The dataset includes downhole images captured by EV, a downhole visual analytics company, providing visual records of each perforation. Images are organized in two folders: one set with perforation visualization overlays and one without. An included Excel spreadsheet provides the organized raw data.

A large data-set of index and dynamic parameters measured from resonant column (RC) and cyclic torsional shear(CTS) tests on 170 undisturbed isotropically consolidated fine-grained specimens deriving from 90 sites in Central and Northern Italy is made available. Tests were all performed over the past 20 years at the Geotechnical Laboratory of the Civil and Environmental Engineering Department of the Florence University using the same apparatus and following the same standardized procedures.

The experimental data are organized in an excel file (named as “Italian_Clays_Archive.xlsx”). For each tested sample, the main physical, index and dynamic properties measured are archived with the code number of the sample (No) in the sheet named as “Dataset” as well as any information available about the borehole from which the sample has been taken. The list and the meaning of the symbols used can be found in the sheet named as “Legend”. Other sheets containing borehole stratigraphy are named as “XX-ST” (where “XX” stands as the bore-hole code, BH) and they can be recalled directly from the “Dataset” sheet. Note that stratigraphy is given in its original format, when available. However, depth and thickness of each layer can be easily deduced by the figure provided and the soil lithology is well represented by the symbol used that are those generally adopted internationally. Finally, the sheets named as "YY-CTS-STEPZ" (where “YY” and “Z” stand as the sample code, No, and the step number, respectively) contain the shear stress and strain values measured after CTS tests at different steps (i.e. amplitudes of the cyclic dynamic torsional loading applied) during the 1st, 5th, 15th, 20th and 25^th.and/or and/or the corresponding shear modulus and damping ratio calculated from the same cycles.

The selected samples were taken mostly in Holocene and Pleistocene fluvio-lacustrine soil deposits at depths ranging from 1 m to 75 m below ground level and they mainly consist of normally and over-consolidated clayey silts or clays (1 < OCR < 9.4) of medium-to-high plasticity (4 < PI < 84), with very low-to high consistency (-1< Ic < 1.9) and initial void ratio, e₀, ranging between 0.175 and 2.456. The database also includes some samples of organic clays of low consistency, very high water content and void ratio and low unit weight. The initial (small strain) values of shear modulus, G₀, and damping ratio, D₀, range between 21 MPa and 292 MPa and between 0.8% and 5.1%, respectively. The smallest and the largest shear strain values induced by RC and CTS tests are 1.9x10^-5 % and 6.3x10^-1%, respectively.

Mobile Application Coverage: The 30% Curse and Ways Forward## Purpose In this artifact, we provide the information about our benchmarks used for manual and tool exploration. We include coverage results achieved by tools and human analysts as well as plots of the coverage progression over time for analysts. We further provide manual analysis results for our case study, more specifically extracted reasons for unreachability for the case study apps and extracted code-level properties, which constitute a ground truth for future work in coverage explainability. Finally, we identify a list of beyond-GUI exploration tools and categorize them for future work to take inspiration from. We are claiming available and reusable badges; the artifact is fully aligned with the results described in our paper and comprehensively documented.## ProvenanceThe paper preprint is available here: https://people.ece.ubc.ca/mjulia/publications/Mobile_Application_Coverage_ICSE2025.pdf## Data The artifact submission is organized into five parts:- 'BenchInfo' excel sheet describing our experiment dataset- 'Coverage' folder containing coverage results for tools and analysts (RQ1) - 'Reasons' excel sheet describing our manually extracted reasons for unreachability (RQ2)- 'ActivationProperties' excel sheet describing our manually extracted code properties of unreached activities (RQ3)- 'ActivationProperties-Graph' pdf which presents combinations of the extracted code properties in a graph format.- 'BeyondGUI' folder containing information about identified techniques which go beyond GUI exploration.The artifact requires about 15MB of storage.### Dataset: 'BenchInfo.xlsx'This file list the full application dataset used for experiments into three tabs: 'BenchNotGP' (apps from AndroTest dataset which are not on Google Play), 'BenchGP' (apps from AndroTest which are also on Google Play) and 'TopGP' (top ranked free apps from Google Play). Each tab contains the following information:- Application Name- Package Name- Version Used (Latest)- Original Version- # Activities- Minimum SDK- Target SDK- # Permissions (in Manifest)- List of Permissions (in Manifest)- # Features (in Manifest)- List of Features (in Manifest)The 'TopGP' sheet also includes Google-Play-specific information, namely:- Category (one of 32 app categories)- Downloads- Popularity RankThe 'BenchGP' and 'BenchNotGP' sheets also include the original version (included in the AndroTest benchmark) and the source (one of F-Droid, Github or Google Code Archives).### RQ1: 'Coverage'The 'Coverage' folder includes coverage results for tools and analysts, and is structured as follows:- 'CoverageResults.xlsx": An excel sheet containing the coverage results achieved by each human analysts and tool. - The first tab described the results over all apps for analysts combined, tools combined, and analysts + tools, which map to Table II in the paper. - Each of the following 42 tab, one per app in TopGP, marks the activities reached by Analyst 1, Analyst 2, Tool 1 (ape) and Tool 2 (fastbot), with an 'x' in the corresponding column to indicate that the activity was reached by the given agent.- 'Plots': A folder containing plots of the progressive coverage over time of analysts, split into one folder for 'Analyst1' and one for 'Analyst2'. - Each of the analysts' folder includes a subfolder per benchmark ('BenchNotGP', 'BenchGP' and 'TopGP'), containing as many png files as applications in the benchmark (respectively 47, 14 and 42 image files) named 'ANALYST_[X]_[APP_PACKAGE_NAME]'.png.### RQ2: 'Reasons.xslx'This file contains the extracted reasons for unreachability for the 11 apps manually analyzed. - The 'Summary' tab provides an overview of unreached activities per reasons over all apps and per app, which corresponds to Table III in the paper. - The following 11 tabs, each corresponding to and named after a single application, describe the reasons associated with each activity of that application. Each column corresponds to a single reason and 'x' indicates that the activity is unreached due to the reason in that column. The top row sums up the total number of activities unreached due to a given reason in each column.- The activities at the bottom which are greyed out correspond to activities that were reached during exploration, and are thus excluded from the reason extraction.### RQ3: 'ActivationProperties.xslx'This file contains the full list of activation properties extracted for each of the 185 activities analyzed for RQ2.The first half of the columns (columns C-M) correspond to the reasons (excluding Transitive, Inconclusive and No Caller) and the second half (columns N-AD) correspond to properties described in Figure 5 in the paper, namely:- Exported- Activation Location: - Code: GUI/lifecycle, Other Android or App-specific - Manifest- Activation Guards: - Enforcement: In Code or In Resources - Restriction: Mandatory or Discretionary- Data: - Type: Parameters, Execution Dependencies - Format: Primitive, Strings, ObjectsThe rows are grouped by applications, and each row correspond to an activity of that application. 'x' in a given column indicates the presence of the property in that column within the analyzed path to the activity. The third and fourth rows sums up the numbers and percentages for each property, as reported in Figure 5.### RQ3: 'ActivationProperties-Graph.pdf'This file shows combinations of the individual properties listed in 'ActivationProperties.xlsx' in a graph format, extending the combinations described in Table IV with data (types and format) and reasons for unreachability.### BeyondGUIThis folder includes:- 'ToolInfo.xlsx': an excel sheet listing the identified 22 beyond-GUI papers, the date of publication, availability, invasiveness (Source code, Bytecode, framework, OS) and their targeting strategy (None, Manual or Automated).- ToolClassification.pdf': a pdf file describing our paper selection methodology as well as a classication of the techniques in terms of Invocation Strategy, Navigation Strategy, Value Generation Strategy, and Value Generation Types. We fully introduced these categories in the pdf file.## Requirements & technology skills assumed by the reviewer evaluating the artifactThe artifact entirely consists of Excel sheets which can be opened with common Excel visualization software, i.e., Microsoft Excel, coverage plots as PNG files and PDF files. It requires about 15MB of storage in total.No other specific technology skills are required of the reviewer evaluating the artifact.

Data is organized using an excel spreadsheet. We included a METADATA sheet in the data file to document what is in each sheet. Data collected include phosphorus loads from bioretention cells, heavy metals, hydraulicdata collected include phosphorus load/concentration and heavy metals. This dataset is associated with the following publication: Ament, M.R., E.D. Roy, Y. Yuan, and S.E. Hurley. Phosphorus Removal, Metals Dynamics, and Hydraulics in Stormwater Bioretention Systems Amended with Drinking Water Treatment Residuals. Journal of Sustainable Water in the Built Environment. American Society of Civil Engineers (ASCE), New York, NY, USA, 8(3): 04022003, (2022).

Heterogenous Big dataset is presented in this proposed work: electrocardiogram (ECG) signal, blood pressure signal, oxygen saturation (SpO2) signal, and the text input. This work is an extension version for our relevant formulating of dataset that presented in [1] and a trustworthy and relevant medical dataset library (PhysioNet [2]) was used to acquire these signals. The dataset includes medical features from heterogenous sources (sensory data and non-sensory). Firstly, ECG sensor’s signals which contains QRS width, ST elevation, peak numbers, and cycle interval. Secondly: SpO2 level from SpO2 sensor’s signals. Third, blood pressure sensors’ signals which contain high (systolic) and low (diastolic) values and finally text input which consider non-sensory data. The text inputs were formulated based on doctors diagnosing procedures for heart chronic diseases. Python software environment was used, and the simulated big data is presented along with analyses.

Excel spreadsheet with individual numerical data organized into separate sheets corresponding to the following figures and figure panels: 2C, 2D, 3C, 3D, 4C, 5D, S1A–S1C, S2A–S2E, S3A–S3F, S6G, S6H, S8A, and S8B.

This Excel based tool was developed to analyze means-end chain data. The tool consists of a user manual, a data input file to correctly organise your MEC data, a calculator file to analyse your data, and instructional videos. The purpose of this tool is to aggregate laddering data into hierarchical value maps showing means-end chains. The summarized results consist of (1) a summary overview, (2) a matrix, and (3) output for copy/pasting into NodeXL to generate hierarchal value maps (HVMs). To use this tool, you must have collected data via laddering interviews. Ladders are codes linked together consisting of attributes, consequences and values (ACVs).

This dataset contains measurements from grain-size, x-ray fluorescence (XRF), and physical properties (including magnetic susceptibility, water content, and shear strength) analyses of five sediment cores collected offshore Thwaites Glacier during cruises NBP19-02 (cores KC04, KC08, and KC23) and NBP20-02 (cores KC33 and KC67). We estimate the cores, which are between 213.5 and 297.5 cm in length, reflect deposition during the last ~10 kyr, consistent with published constraints of deglaciation of this region. Data are organized in Microsoft Excel spreadsheets and core locations are provided in a PDF.

description: Prior to removal of pest species from an area, resource managers must determine if re-immigration from another population is possible. Voles inhabiting Saddle Rock on the southern Oregon coast are suspected to be partially responsible for declines in the Leach s storm petrel colony on the island. The island is very close to the mainland, and it is potentially accessible during below-average low tides. USGS scientists Mark Miller and Susan Haig and colleagues used genetic techniques to assess how much population connectivity the island voles had. Results suggest there is little individual movement between island and mainland vole populations. If local resource managers decide to remove voles from the island to safeguard the important petrel nesting area, it is unlikely that immediate vole recolonization will occur. Data are in an Excel spreadsheet and are organized as follows. Column A contains the sample identifier for each of 34 individuals that were included in analyses. An additional 9 individuals with the suffix R are replicates of samples that were included in analyses as a quality control measure. Samples beginning with SR originated on Saddle Rock, whereas samples beginning with CP originated on Crook Point. Columns B through CN contain data from 91 AFLP loci that were included in analyses. Column headings reflect a shorthand annotation of the form primer combination marker size (i.e., C2-207 indicates a 207bp fragment observed with primer combination C2). In each column, 1 reflects the presence of a marker, whereas 2 indicates its absence.; abstract: Prior to removal of pest species from an area, resource managers must determine if re-immigration from another population is possible. Voles inhabiting Saddle Rock on the southern Oregon coast are suspected to be partially responsible for declines in the Leach s storm petrel colony on the island. The island is very close to the mainland, and it is potentially accessible during below-average low tides. USGS scientists Mark Miller and Susan Haig and colleagues used genetic techniques to assess how much population connectivity the island voles had. Results suggest there is little individual movement between island and mainland vole populations. If local resource managers decide to remove voles from the island to safeguard the important petrel nesting area, it is unlikely that immediate vole recolonization will occur. Data are in an Excel spreadsheet and are organized as follows. Column A contains the sample identifier for each of 34 individuals that were included in analyses. An additional 9 individuals with the suffix R are replicates of samples that were included in analyses as a quality control measure. Samples beginning with SR originated on Saddle Rock, whereas samples beginning with CP originated on Crook Point. Columns B through CN contain data from 91 AFLP loci that were included in analyses. Column headings reflect a shorthand annotation of the form primer combination marker size (i.e., C2-207 indicates a 207bp fragment observed with primer combination C2). In each column, 1 reflects the presence of a marker, whereas 2 indicates its absence.