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Laboratory Comparison of Low-Cost Particulate Matter Sensors to Measure Transient Events of Pollution - Part B - Particle Number Concentrations - Dataset
<p>This repository contains the data used for the analysis of the paper "Laboratory Comparison of Low-Cost Particulate Matter Sensors to Measure Transient Events of Pollution - Part B - Particle Number Concentrations (PNC)" which is under submission.</p> <p> </p> <p>The experimental conditions and the instruments used are detailed in Bulot, F.M.J.; Russell, H.S.; Rezaei, M.; Johnson, M.S.; Ossont, S.J.J.; Morris, A.K.R.; Basford, P.J.; Easton, N.H.C.; Foster, G.L.; Loxham, M.; Cox, S.J. Laboratory Comparison of Low-Cost Particulate Matter Sensors to Measure Transient Events of Pollution. <em>Sensors</em> <strong>2020</strong>, <em>20</em>, 2219. https://doi.org/10.3390/s20082219</p> <p>The files are available in .csv and in .rds (for R) formats. For details about the measurement equipment used<br> during this study, please refer to the methods section of the paper.</p> <p> </p> <p>sensors_raw.csv contains the following headers:</p> <ul> <li>Bin0 to Bin15: Alphasense OPC-R1 particle number concentrations for different size bins</li> <li>Bin[1-3-5-7]MToF: mean time of flight of particles within the corresponding size bins of the Alphasense OPC-R1</li> <li>Checksum: checksum of the Alphasense OPC-R1</li> <li>SFR: sample flow rate of the Alphasense OPC-R1</li> <li>Humidity: relative humidity measured by the Alphasense OPC-R1</li> <li>Temperature: temperature measured by the Alphasense OPC-R1</li> <li>SamplingPeriod: sampling period of the Alphasense OPC-R1</li> <li>gr03um, gr05um, gr10um, gr25um, gr50um, gr100um: PNC measured by the Plantower PMS5003</li> <li>n05, n1, n25, n4, n10: PNC measured by the Sensirion SPS30</li> <li>humidity: relative humidity measured by a Sensirion SHT-3x</li> <li>temperature: temperature measured by a Sensirion SHT-3x</li> <li>sensor: id of the sensors</li> <li>site: name of the air quality monitor hosting the sensors</li> <li>exp: name of the experiment conducted</li> <li>source: source used to generate PM (incense or candle)</li> <li>variation: whether the sensors were exposed to stable or peak concentrations of PM pollution</li> <li>date: date in format yyyy-mm-dd HH:MM:SS</li> </ul> <p>For more explanations about the fields of individual sensors, please refer to their manual (Alphasense OPC-R1: https://kolegite.com/EE_library/datasheets_and_manuals/sensors/OPC/072-0500_OPC-R1_manual_issue_1_250219.pdf ; Plantower PMS5003: https://www.aqmd.gov/docs/default-source/aq-spec/resources-page/plantower-pms5003-manual_v2-3.pdf ; Sensirion SPS30: https://sensirion.com/products/catalog/SPS30/)</p> <p> </p> <p>ops.csv and ops.rds contains the readings from the OPS with the following cut sizes for the bins:</p> <ul> <li>Bin 1 Cut Point (um),0.300</li> <li>Bin 2 Cut Point (um),0.374</li> <li>Bin 3 Cut Point (um),0.465</li> <li>Bin 4 Cut Point (um),0.579</li> <li>Bin 5 Cut Point (um),0.721</li> <li>Bin 6 Cut Point (um),0.897</li> <li>Bin 7 Cut Point (um),1.117</li> <li>Bin 8 Cut Point (um),1.391</li> <li>Bin 9 Cut Point (um),1.732</li> <li>Bin 10 Cut Point (um),2.156</li> <li>Bin 11 Cut Point (um),2.685</li> <li>Bin 12 Cut Point (um),3.343</li> <li>Bin 13 Cut Point (um),4.162</li> <li>Bin 14 Cut Point (um),5.182</li> <li>Bin 15 Cut Point (um),6.451</li> <li>Bin 16 Cut Point (um),8.031</li> <li>Bin 17 Cut Point (um),10.000</li> </ul> <p>nanotracer.csv and nanotracer.rds contain the measurements from the Nanotracer:</p> <ul> <li>N.1.: particles/cm3</li> <li>dp_avg.1.: mean diameter of the particles (nm)</li> <li>P.1.:</li> <li>S_al.1.: Lung Deposited Surface Area in um2/cm3</li> </ul> <p> </p> <p>experimental_conditions.csv and experimental_conditions.rds contain the end dates and start dates of each of the experiment conducted.</p> <p> </p> <p> </p> <p>"pm100_cf1","pm10_cf1","pm25_cf1"</p> <p> </p> <p> </p>
FIG. 7 in Analysis of lichen secondary chemistry doubled the number of Cetrelia W.L. Culb. & C.F. Culb. species (Parmeliaceae, lichenised Ascomycota) in Hungary
FIG. 7. — Distribution of Cetrelia cetrarioides (Delise) W.L. Culb.& C.F.Culb. in Hungary after revision.
FIG. 11 in Analysis of lichen secondary chemistry doubled the number of Cetrelia W.L. Culb. & C.F. Culb. species (Parmeliaceae, lichenised Ascomycota) in Hungary
FIG. 11. — Distribution of Cetrelia olivetorum (Nyl.) W.L. Culb. & C.F.Culb.in Hungary after revision.
FIG. 4 in Analysis of lichen secondary chemistry doubled the number of Cetrelia W.L. Culb. & C.F. Culb. species (Parmeliaceae, lichenised Ascomycota) in Hungary
FIG. 4. — Microcrystal tests of A, imbricaric; B, perlatolic; C, olivetoric acids and D, atranorin in GE solvent (glycerine – acetic acid, 3:1 v/v). Scale bars: 50 µm.
FIG. 6 in Analysis of lichen secondary chemistry doubled the number of Cetrelia W.L. Culb. & C.F. Culb. species (Parmeliaceae, lichenised Ascomycota) in Hungary
FIG. 6. — Distribution of Cetrelia cetrarioides (Delise) W.L. Culb. & C.F. Culb.in Hungary before revision.
FIG. 10 in Analysis of lichen secondary chemistry doubled the number of Cetrelia W.L. Culb. & C.F. Culb. species (Parmeliaceae, lichenised Ascomycota) in Hungary
FIG. 10. — Distribution Cetrelia olivetorum (Nyl.) W.L. Culb.& C.F. Culb.in Hungary before revision.
FIG. 2. — A in Analysis of lichen secondary chemistry doubled the number of Cetrelia W.L. Culb. & C.F. Culb. species (Parmeliaceae, lichenised Ascomycota) in Hungary
FIG. 2. — A detail of the chromatographic plate HPTLC nr 74/2014 developed in solvent system C presenting all species under UV 254 nm (A), and sprayed with water (B). Specimens in positions A10-A17 are A10: C. olivetorum (Nyl.) W.L. Culb. & C.F. Culb. (BP 21529), A11: C. monachorum (Zahlbr.) W.L. Culb. & C.F. Culb. (BP 85318), A12: C. olivetorum (BP 84893), A13: C. cetrarioides (Delise) W.L. Culb. & C.F. Culb. (BP 21538), A14: C. olivetorum (BP 22787), A15: C. monachorum (BP 45013), A16: C. olivetorum (BP 21508), A17: C. chicitae (W.L. Culb.) W.L. Culb. & C.F. Culb. (BP 93416). Abbreviations of LSMs are according to Table 2.
FIG. 5 in Analysis of lichen secondary chemistry doubled the number of Cetrelia W.L. Culb. & C.F. Culb. species (Parmeliaceae, lichenised Ascomycota) in Hungary
FIG. 5. — Thalline lobes with marginal soralia of A, Cetrelia cetrarioides (Delise) W.L. Culb. & C.F. Culb.; B, C. chicitae (W.L. Culb.) W.L. Culb. & C.F. Culb.; C, C. monachorum (Zahlbr.) W.L. Culb. & C.F. Culb.; and D, C. olivetorum (Nyl.) W.L. Culb. & C.F. Culb. Scale bars: 1 mm.
FIG. 1 in Analysis of lichen secondary chemistry doubled the number of Cetrelia W.L. Culb. & C.F. Culb. species (Parmeliaceae, lichenised Ascomycota) in Hungary
FIG. 1. — Differential morphological and chemical features in Cetrelia W.L. Culb. & C.F. Culb. species: A, large, not raised pseudocyphellae on upper cortex of C. chicitae (W.L. Culb.) W.L. Culb. & C.F. Culb.; B, small, raised pseudocyphellae on upper cortex of C. monachorum (Zahlbr.) W.L. Culb. & C.F. Culb.; C, brown lower cortex of C. cetrarioides (Delise) W.L. Culb. & C.F. Culb. without rhizines; D, C+ reaction by NaOCl on marginal soralia of Cetrelia olivetorum (Nyl.) W.L. Culb. & C.F. Culb. Scale bars: 500 µm.
FIG. 13 in Analysis of lichen secondary chemistry doubled the number of Cetrelia W.L. Culb. & C.F. Culb. species (Parmeliaceae, lichenised Ascomycota) in Hungary
FIG. 13. — The number of Cetrelia W.L. Culb. & C.F. Culb. species after revision in various parts of Hungary.
FIG. 3. — A in Analysis of lichen secondary chemistry doubled the number of Cetrelia W.L. Culb. & C.F. Culb. species (Parmeliaceae, lichenised Ascomycota) in Hungary
FIG. 3. — A detail of the chromatographic plate TLC nr 1903 developed in solvent system C presenting C. chicitae (W.L. Culb.) W.L. Culb. & C.F. Culb. specimens under UV 254 nm (A), UV 366 nm (B) and sprayed with anisaldehyde/sulphuric acid (C). Specimens in positions 3-9 are: 3, from Page County, Virginia, United States (BP 75822); 4, from the Bükk Mts, Hungary (BP 71276); 5, from the Zemplén Mts, Hungary (BP 49905); 6, from Pocahontas County, West Virginia, United States (BP 91365); 7, from Ukraine (BP 44999); 8, from Romania (BP 85320); 9, from Poland (BP 21508). Abbreviations of LSMs are according to Table 2.
Dataset for: Ace and ace-like genes of invasive redlegged earth mite: Copy number variation, target-site mutations, and their associations with organophosphate insensitivity
<p class="MsoNormal">This repository contains the scripts and data required to replicate the analyses in Thia et al.'s, "Evolution of an acetylcholinesterase<em> </em>gene complex and its contribution toward organophosphate insensitivity in an invasive mite pest", submitted to <em>Pest Management Science</em>.</p> <p class="MsoNormal">In this work, Thia et al. use a combination of experimental selection and pool-seq genomic analyses to understand the genetic mechanisms underpinning organophosphate insensitivity in the redlegged earth mite, <em>Halotydeus destructor</em>. There is a special emphasis on disentangling the roles of copy number variation and target-site mutations in the acetylcholinesterase genes, <em>ace,</em> and radiated <em>ace</em>-like genes<span>.</span></p> <p class="MsoNormal">There are three major analyses: (1) an F<sub>ST</sub> genome scan to identify outlier loci between alive (insensitive) and dead (sensitive) mites; (2) an analysis of <em>ace </em>copy number variation between alive and dead mites; and (3) an analysis of candidate target-site mutations in the <em>ace</em> gene.</p>
To disperse or compete? Coevolution of traits leads to a limited number of reproductive strategies
<p><span><span>Reproductive strategies are defined by a combination of behavioural, morphological, and life-history traits. Reproductive investment and offspring propagule size are two key traits defining reproductive strategies. While a substantial amount of work has been devoted to understanding the independent fitness effects of each of these traits, it remains unclear how coevolution between them ultimately affects the evolution of reproductive strategies, and how this might influence the relationship between dispersal and environmental factors. In this study, we explore how the evolution of reproductive strategies defined by these two coevolving traits is influenced by resource availability and spatial structuring of the environment using a simulation model. We find three possible equilibrium strategies across all scenarios: a competitor strategy with high reproductive investment (producing large propagules which disperse short distances), and two coloniser strategies differing in reproductive investment (both producing small propagules which disperse long distances). The possible equilibrium strategies for each scenario depended on starting conditions, spatial structure and resource availability. Evolutionary transitions between these equilibrium strategies were more likely in heterogeneous than homogeneous landscapes and at higher resource levels. Transition from coloniser strategy to competitor strategy was usually a two-step process, with changes in propagule size following initial evolution in investment. This highlights how the interaction between the two trait axes affects the evolution of reproductive strategies, particularly where fitness valleys preclude the simultaneous evolution of traits. Our results highlight the need to incorporate trait coevolution into evolutionary models to help develop a more integrative understanding of the structure of natural populations and how the interaction between traits constrains or hinders evolutionary processes.</span></span></p>
CNETML: maximum likelihood inference of phylogeny from copy number profiles of multiple samples
<p>This folder includes simulated and real data used in validating CNETML, a new maximum likelihood method designed to reconstruct the evolutionary history of multiple samples of a single patient which may be taken at different locations and/or times, which can take as input (relative) total integer copy numbers called from shallow whole genome sequencing data.</p>
The data presented in Figure 6, the 120 mare domes hosting no RMDSs shown in Fig. 5, and all the RMDSs (more than 6400 in number) identified in Mare Tranquillitatis
<p>The datasets presented here are provided as supporting information for our work, the detail of which is as below:</p> <p>Feng Zhang, James W. Head, Lionel Wilson, Yibo Meng, Christian Wӧhler, Dijun Guo, Shengli Niu, Roberto Bugiolacchi, Le Qiao, Yanan Dang, Yang Liu, Yongliao Zou</p> <p><strong>Insights into Lunar Basaltic Volcanism from Mare Domes Superposed by Ring-Moat Dome Structures (RMDSs) in Mare Tranquillitatis</strong></p> <p>Journal of Geophysical Research: Planets, 129, e2023JE007969. https://doi.org/10.1029/2023JE007969.</p> <p>A detailed description of these datasets is provided below:</p> <p>(1) 527_RMDSs_in_mare_plains_Fig6.csv</p> <p>Measured morphometric properties (e.g., diameter, height, slope, etc.) of the 527 RMDSs (Fig. 6), which are located in the lunar maira surrounding the 200 mare domes in the Tranquillitatis basin on the Moon as shown in the paper Fig. 4 (green solid circles and stars).</p> <p>(2) Supporting_Table_S1_Dome_Without_RMDS_120_Fig5.xlsx</p> <p>Locations and morphometric parameters of the 120 mare domes without being superposed by RMDSs: their locations can be found in the paper Fig. 4 (green stars) and their morphometric parameters (e.g., diameter, height, slope, volume, etc.) can refer to Figure 5 for statistics. The newly identified 38 mare domes hosting no RMDSs are labeled in red color, and they were not reported in previous studies.</p> <p>(3) 1027_RMDSs_on_domes_Fig6.csv</p> <p>Measured morphometric properties (e.g., diameter, height, slope, etc.) of the 1027 RMDSs (Fig. 6), which are located on the 80 mare domes in the Tranquillitatis basin on the Moon as shown in the paper Fig. 4 (green solid circles).</p> <p>(4) RMDSs in Tranquillitatis-Shp-style.zip</p> <p>All the RMDSs of ~6400 in number are located in Mare Tranquillitatis and have been identified up to the submission of the paper.</p>
Data and Code for the paper "GUI Testing of Android Applications: Investigating the Impact of the Number of Testers on Different Exploratory Testing Strategies"
<p>This package contains data and code to replicate the findings presented in our paper titled "<em>GUI Testing of Android Applications: Investigating the Impact of the Number of Testers on Different Exploratory Testing Strategies</em>".</p> <p><strong>Abstract</strong></p> <p>Graphical User Interface (GUI) testing plays a pivotal role in ensuring the quality and functionality of mobile apps. In this context, Exploratory Testing (ET), a distinctive methodology in which individual testers pursue a creative, and experience-based approach to test design, is often used as an alternative or in addition to traditional scripted testing. Managing the exploratory testing process is a challenging task, that can easily result either in wasteful spending or in inadequate software quality, due to the relative unpredictability of exploratory testing activities, which depend on the skills and abilities of individual testers. A number of works have investigated the<br> diversity of testers’ performance when using ET strategies, often in a crowdtesting setting. These works, however, investigated ET effectiveness in detecting bugs, and not in scenarios in which the goal is to generate a re-executable test suite, as well. Moreover, less work has been conducted on evaluating the impact of adopting different exploratory testing strategies. As a first step towards filling this gap in the literature, in this work we conduct an empirical evaluation involving four open-source Android apps and twenty masters students, that we believe can be representative of practitioners partaking in exploratory testing activities. The students were asked to generate test suites for the apps using a Capture and Replay tool and different exploratory testing strategies. We then compare the effectiveness, in terms of aggregate code coverage, that different-sized groups of students using different exploratory testing strategies may achieve. Results provide deeper insights into code coverage dynamics to project managers interested in using exploratory approaches to test simple Android apps, on which they can make more informed decisions.</p> <p> </p> <p><strong>Contents and Instructions</strong></p> <p>This package contains:</p> <ul> <li><strong>apps-under-test.zip</strong> A zip archive containing the source code of the four Android applications we considered in our study, namely MunchLife, TippyTipper, Trolly, and SimplyDo.</li> <li><strong>apps-under-test-instrumented.zip</strong> A zip archive containing the instrumented source code of the four Android applications we used to compute branch coverage.</li> <li><strong>students-test-suites.zip</strong> A zip archive containing the test suites developed by the students using Uninformed Exploratory Testing (referred to as "Black Box" in the subdirectories) and Informed Exploratory Testing (referred to as "White Box" in the subdirectories). This also includes coverage reports.</li> <li><strong>compute-coverage-unions.zip </strong>A zip archive containing Python scripts we developed to compute the aggregate LOC coverage of all possible subsets of students. The scripts have been tested on MS Windows. To compute the LOC coverage achieved by any possible subsets of testers using IET and UET strategies, run the <em>analysisAndReport.py</em> script. To compute the LOC coverage achieved by mixed crowds in which some testers use a U+IET approach and others use a UET approach, run the <em>analysisAndReport_UET_IET_combinations_emma.py</em> script.</li> <li><strong>branch-coverage-computation.zip </strong>A zip archive containing Python scripts we developed to compute the aggregate branch coverage of all considered subsets of students. The scripts have been tested on MS Windows. To compute the branch coverage achieved by any possible subsets of testers using UET and I+UET strategies, run the <em>branch_coverage_analysis.py</em> script. To compute the code coverage achieved by mixed crowds in which some testers use a U+IET approach and others use a UET approach, run the <em>mixed_branch_coverage_analysis.py</em> script.</li> <li><strong>data-analysis-scripts.zip</strong> A zip archive containing R scripts to merge and manipulate coverage data, to carry out statistical analysis and draw plots. All data concerning RQ1 and RQ2 is available as a ready-to-use R data frame in the <em>./data/all_coverage_data.rds</em> file. All data concerning RQ3 is available in the <em>./data/all_mixed_coverage_data.rds </em>file.</li> </ul>
Data for "Beyond Magic Numbers: Atomic Scale Equilibrium Nanoparticle Shapes for Any Size"
<p>This record contains <a href="https://wiki.fysik.dtu.dk/ase/ase/db/db.html">ASE databases</a> in sqlite format that contain the minimum energy structures of nanoparticles of Ag, Au, Cu, and Pd as determined in the paper "<em>Beyond Magic Numbers: Atomic Scale Equilibrium Nanoparticle Shapes for Any Size</em>", Rahm and Erhart, Nano Letters <strong>17</strong>, 5775 (2017); <a href="http://doi.org/10.1021/acs.nanolett.7b02761">doi: 10.1021/acs.nanolett.7b02761</a></p> <p>The <code>access-database.py</code> script included in this record demonstrates how to access the databases. It requires the <a href="https://wiki.fysik.dtu.dk/ase/">ASE package</a> to be installed.</p>
The upper bounds for the number of bins and the total number of variables before and after reducing for the two dimensional vector bin packing problem
<p>The upper bounds for the number of bins and the total number of variables before and after reducing for the two dimensional vector bin packing problem, This dataset is a result of the research: Đorđe Stakić, Tatjana Davidović, Ana Anokić, Dragan Urošević "VNS-based matheuristics for the two dimensional vector bin packing problem", SYM-OP-IS, 2023.</p>
Number of publications in French for the winners of the Nobel Prize for Literature (extraction of the BnF catalog)
<p>Python script and dataset.</p> <p>The dataset contains the number of publications in French one can find in the catalog of the Bibliothèque nationale de France (BnF) for every winner of the Nobel Prize of Literature.</p> <p>Idea from LIBER : <a href="https://twitter.com/kiru/status/1677413039132352512">https://twitter.com/kiru/status/1677413039132352512</a></p>
Figure 1 in The first description of male of Raphignathus arcus Akyol (Acari: Raphignathidae) and a variation in the number of genital setae of its a female
Figure 1. Raphignathus arcus Akyol (male): A. Dorsal view of idiosoma, B. Ventral view of idiosoma, C. Leg I, D. Leg II, E. Leg III, F. Leg IV, G. Palp, H. Abnormal genital setae of female of R. arcus.
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