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opencc-by-4.0Jan 2023View details →

Condition Monitoring for Packaging Industry dataset (CoMoPI)

Condition Monitoring for Packaging Industry dataset (CoMoPI) CoMoPI dataset contains data from eight industrial packaging machines: <table> <thead> <tr> <th> serial </th> <th> Starting Date </th> <th> Ending Date </th> </tr> </thead> <tbody> <tr> <td> A001 </td> <td> 2022-08-10 03:45:00+00:00 </td> <td> 2023-01-09 07:00:00+00:00 </td> </tr> <tr> <td> A005 </td> <td> 2022-09-19 13:15:00+00:00 </td> <td> 2023-01-09 15:45:00+00:00 </td> </tr> <tr> <td> B002 </td> <td> 2022-07-14 14:00:00+00:00 </td> <td> 2023-01-09 15:50:00+00:00 </td> </tr> <tr> <td> B005 </td> <td> 2022-10-04 12:55:00+00:00 </td> <td> 2023-01-05 01:55:00+00:00 </td> </tr> <tr> <td> C003 </td> <td> 2022-12-15 06:50:00+00:00 </td> <td> 2023-01-03 16:35:00+00:00 </td> </tr> <tr> <td> C004 </td> <td> 2022-07-18 07:55:00+00:00 </td> <td> 2022-12-28 08:10:00+00:00 </td> </tr> <tr> <td> E002 </td> <td> 2022-07-14 14:20:00+00:00 </td> <td> 2022-12-03 14:00:00+00:00 </td> </tr> <tr> <td> E004 </td> <td> 2022-11-23 15:25:00+00:00 </td> <td> 2023-01-09 10:00:00+00:00 </td> </tr> </tbody> </table> The dataset provides sensor measurements related to a specific module involved in the watertight closure of packages. It also provides all alarms and warnings generated by the packaging equipment. Dataset description For the sake of simplicity, the dataset is divided into three files, one for sensor measurements, one for alarms and one for warnings. Sensor measurements This data is included in the file called industrial_dataset_sensors_10m_agg.csv. Each row corresponds to average sensor value in a 10-minute window. Beyond the machine identifier ('_serial') and timestamp ('_time'), the following measurements are available: 'AE', 'BE', 'AF', 'BF', 'APP', 'BPP', 'AP', 'BP', 'ALE', 'BLE', 'ALP', 'BLP', 'ADS', 'BDS', 'AES', 'BES'. Suffixes A_ and B_ relate to the two elements that can perform a specific operation required by the watertight closure of packages. For confidentiality reasons, it is not possible to provide further details. Alarm measurements This data is included in the file called industrial_dataset_alarm_10m_agg.csv, according to the following schema: <ul> <li>'_serial' : 'machine unique identifier'</li> <li>'_time' : 'timestamp',</li> <li>'AL_1' : 'Counter of AL_1 alarms' ,</li> <li>...</li> <li>'AL_123' : 'Counter of AL_123 alarms'</li> </ul> Warning measurements This data is included in the file called industrial_dataset_warnings_10m_agg.csv_, according to the following schema: <ul> <li>'_serial' : 'machine unique identifier'</li> <li>'_time' : 'timestamp',</li> <li>'WR_1' : 'Counter of AL_1 alarms' ,</li> <li>...</li> <li>'WR_358' : 'Counter of WR_358 alarms'</li> </ul> Condition monitoring Alarms 'AL_53' are 'AL_54' are related to faulty conditions of the components and can be used as prediction target. The following alarms are generated by the target module: 'AL_17', 'AL_18', 'AL_40', 'AL_41', 'AL_42', 'AL_43', 'AL_45', 'AL_46', 'AL_47', 'AL_48', 'AL_49', 'AL_50', 'AL_51', 'AL_52', 'AL_53', 'AL_54'. Anonymization procedure The anonymization procedure is the following: <ul> <li>To make it impossible to identify the specific piece of equipment, its serial number was replaced with a mock equipment_ID. Moreover, no additional information is provided about the machine, its location and the processed products.</li> <li>Sensor measurements were renamed and rescaled to remove all information related to actual working setup.</li> <li>Alarms and warnings underwent an anonymization process: no description is provided, and the original alarm codes were mapped to mock codes.</li> </ul>

opencc-by-4.0Feb 2023View details →

Model results and configuration files for "Large modeling uncertainty in projecting decadal surface ozone changes over urban and industrial regions of China"

This repository includes files as described below: 1. namelist_CBMZ09_example.input, namelist_MOZART202_example.input: Two WRF-chem namelist files for CBMZ and MOZART simulation. They are modified according to the namelist from <a href="https://github.com/wrfchem-leeds/WRFotron">https://github.com/wrfchem-leeds/WRFotron</a>. 2. wps_namelist_example.wps: namelist for WRF Preprocessing System (WPS) 3. temporal_hourly_scale_factor_emission.csv: Hourly scale factors for emissions. Hourly allocation is applied to all emission data (i.e., emissions for 2017, 2030 and perturbated emissions of NOx, VOCs). 4. vertical_emission_ratio.csv Vertical shares (ratios) of emissions. Emissions from sectors of power and industry are vertically allocated based on this file. Vertical allocation is conducted for all emission data. These shares are suggested by MICS-ASIA III intercomparison framework. 5. 01_2030_2017_simulations.zip: Simulated MDA8 ozone under future (2030) and 2017 emission scenarios by the two chemical mechanisms (i.e., CBMZ, MOZART). 6. 02_perturbations_of_NOxVOCs.zip: Simulated MDA8 ozone given perturbations of NOx and VOCs emissions by the two chemical mechanisms. 7. 03_hourly_diff_O3_NOx_OH_HNO3.zip: Differences of hourly simulated concentrations of O3, NOx, OH and HNO3 during July in the Base-2017 scenario between CBMZ and MOZART (CBMZ - MOZART).

opencc-by-4.0Apr 2022View details →

Supplementary datasets for "ARBRE: Computational resource to predict pathways towards industrially important aromatic compounds"

Supplementary datasets accompanying the manuscript "ARBRE: Computational resource to predict pathways towards industrially important aromatic compounds" published in the Metabolic Engineering Journal (<a href="https://doi.org/10.1016/j.ymben.2022.03.013">https://doi.org/10.1016/j.ymben.2022.03.013). </a>In line with the standards of open science, the ARBRE toolbox is freely available to the scientific community on gitHub (<a href="https://github.com/EPFL-LCSB/ARBRE">https://github.com/EPFL-LCSB/ARBRE</a>) and we also provide the web-version at <a href="http://lcsb-databases.epfl.ch/arbre/">http://lcsb-databases.epfl.ch/arbre/</a> ARBRE: Aromatic compounds RetroBiosynthesis Repository and Explorer is a new computational resource consisting of a comprehensive biochemical reaction network centered around aromatic amino acid biosynthesis and a computational toolbox for navigating this network. ARBRE encompasses over 33′000 known and 390′000 novel reactions predicted with generalized enzymatic reactions rules and over 74′000 compounds, of which 19′000 are known to biochemical databases and 55′000 only to PubChem. Over 1′000 molecules that were solely part of the PubChem database before and were previously impossible to integrate into a biochemical network are included in the ARBRE reaction network by assigning enzymatic reactions. ARBRE can be applied for pathway search, enzyme annotation, pathway ranking, visualization, and network expansion around known biochemical pathways and products of lignin degradation to predict valuable compound derivations. Supplementary files are organized as follows: - 1-s2.0-S1096717622000490-mmc4.docx contains Supplementary Figures 1-4 and Tables 1, 2,  and 4. - 1-s2.0-S1096717622000490-mmc2.xlsx contains Supplementary Table 3. - 1-s2.0-S1096717622000490-mmc1.xlsx contains Supplementary Table 5 - 1-s2.0-S1096717622000490-mmc3.xlsx contains Supplementary Table 6

opencc-by-4.0Jul 2023View details →

Chironomid taxa relative abundance information and lake identifiers for: Changes in midge assemblages reflect climate and trophic gradients across north temperate and boreal lakes since the pre-industrial period

File 1: Relative abundances for chironomid taxa used in the manuscript: Changes in midge assemblages reflect climate and trophic gradients across north temperate and boreal lakes since the pre-industrial period. Lake_ID corresponds to the lake IDs attributed to each lake sampled as part of the LakePulse Network File 2: Lake_ID, lake name, latitude, longitude, sampling date, province, and ecozone for the 69 lakes examined in the manuscript: Changes in midge assemblages reflect climate and trophic gradients across north temperate and boreal lakes since the pre-industrial period.

opencc-by-4.0Aug 2023View details →

Dataset: Music Industry Professionals' Perspectives on Music Streaming Services and Recommendation

Questionnaire response data set Here, we include the data retrieved from participants at Eurosonic Noorderslag 2023, as described in the paper cited above. When using, analyzing, or publishing this data in any way, please make sure to attribute it to the authors and cite it accordingly. We include the data in .xlsx, .csv format (semicolon-separated, and .tsv format (tab-separated). We suggest using the Excel file, as its layout makes it more easily readable. The complete question list as used in the questionnaire is published separately on <a href="https://doi.org/10.5281/zenodo.8121151">https://doi.org/10.5281/zenodo.8121151</a>. Paper title Looking at the FAccTs: Exploring Music Industry Professionals’ Perspectives on Music Streaming Services and Recommendations Paper abstract Music recommender systems, commonly integrated into streaming services, help listeners find music. Previous research on such systems has focused on providing the best possible recommendations for these services' consumers, as well as on fairness for artists who release their music on streaming services. While those insights are imperative, another group of stakeholders has been omitted so far: the many other professionals working in the music industry. They, too, are (in)directly affected by music streaming services. Therefore, this work explores the perspective of music industry professionals. We present a study that addresses the role of streaming services and recommender systems in their jobs. Results indicate this role is significant. Furthermore, participants feel that music recommender systems lack transparency and are insufficiently controllable, for both customers and artists. Finally, participants desire that music streaming services take charge of increasing recommendation diversity, and variety in consumers' listening behavior and taste. Citation Karlijn Dinnissen, Isabella Saccardi, Marloes Vredenborg, and Christine Bauer. 2023. Looking at the FAccTs: Exploring Music Industry Professionals’ Perspectives on Music Streaming Services and Recommendations. In 2nd International Conference of the ACM Greek SIGCHI Chapter (CHIGREECE 2023), September 27–28, 2023, Athens, Greece. ACM, New York, NY, USA, 5 pages. https://doi.org/10.1145/3609987.3610011

opencc-by-4.0Aug 2023View details →

Data Artifact: Rebasing Microarchitectural Research with Industry Traces

Data Artifact of the paper "Rebasing Microarchitectural Research with Industry Traces", published at the 2023 IEEE International Symposium on Workload Characterization. It includes the original CVP-1 traces used in the paper.Note: the improved converted traces used in the paper are available at https://doi.org/10.5281/zenodo.10199624.Abstract: Microarchitecture research relies on performance models with various degrees of accuracy and speed. In the past few years, one such model, ChampSim, has started to gain significant traction by coupling ease of use with a reasonable level of detail and simulation speed. At the same time, datacenter class workloads, which are not trivial to set up and benchmark, have become easier to study via the release of hundreds of industry traces following the first Championship Value Prediction (CVP-1) in 2018. A tool was quickly created to port the CVP-1 traces to the ChampSim format, which, as a result, have been used in many recent works. We revisit this conversion tool and find that several key aspects of the CVP-1 traces are not preserved by the conversion. We therefore propose an improved converter that addresses most conversion issues as well as patches known limitations of the CVP-1 traces themselves. We evaluate the impact of our changes on two commits of ChampSim, with one used for the first Instruction Championship Prefetching (IPC-1) in 2020. We find that the performance variation stemming from higher accuracy conversion is significant.

opencc-by-4.0Mar 2023View details →

Numerical simulations and experimental measurements of the ULB semi-industrial furnace for the development of a Digital Twin

This dataset contains the numerical and experimental data used to build the Digital Twin in Aversano et al. (https://doi.org/10.1016/j.proci.2020.06.045) and the adaptive Digital Twin in Procacci et al. (https://doi.org/10.1016/j.proci.2022.07.029). The directory "Numerical_data" includes 45 text files containing the data coming from the CFD simulations of the ULB furnace.  In each file, for each computational cell the features reported are:   - the cell's position in x, y, z coordinates and in meters.  - the cell's temperature in K.   - the cell's species mass fraction of NO (mf-pollut-pollutant-0), CO, OH, H2, H2O, CO2, O2, CH4. The details of the setup of the numerical simulations are reported in Aversano et al. The numerical simulations have been computed for different values of the equivalence ratio (phi), blend of H2-CH4 (H2) and  inlet diameter (D). The simulations for different inlet diameter where computed using different meshes, with slightly different numbers of cells. In the file 'cases_parameters.csv', the value of the parameters is reported for of each simulation. There is a  discrepancy between the naming of the simulations in Aversano et al. and the one used in naming the files, so both are reported. The experimental measurements used to validate the numerical simulations can be found in the directory "Experimental_data". Each file contains the value of the measured temperature along with the position in x and z in meters (y being 0). The temperature is in K. The experimental uncertainty is estimated at 10 K. The file 'grid.vtu' contains the computational grid used to solve the CFD simulations. It can be opened using VTK-based software  such as Paraview or Pyvista. Changelog: - In version V1, some simulations were corrupted during data export. - Added the grid file in V3

opencc-by-4.0Dec 2019View details →

HGIS data of Greater London's Industry 1893-95

Based on the First Revised Series of the Ordnance Survey London Town Plans. You can find a different version of the Georeferenced maps on the National Library of Scotland website:   <a href="https://maps.nls.uk/geo/explore/#zoom=11&lat=51.4907&lon=-0.1331&layers=163&b=1">https://maps.nls.uk/geo/explore/#zoom=11&lat=51.4907&lon=-0.1331&layers=163&b=1</a> Each factory is coded to indicate whether it is on both or just one of the two 19th century series of Ordnance Survey London Town Plans. I have also tried to catagorize the factories. There are some other incomplete fields or fields used in earlier versions of this database. Data used in Jim Clifford, West Ham and the River Lea A Social and Environmental History of London’s Industrialized Marshland, 1839–1914, UBC Press, 2017, https://www.ubcpress.ca/west-ham-and-the-river-lea

Fig. 13 in The bony fishes (Teleostei) caught by industrial trawlers off the Brazilian North coast, with insights into its conservation

Fig. 13. Species of the order Perciformes, family Mullidae, (A) Upeneus parvus AZUSC 5445, 167 mm TL, family Kyphosidae, (B) Kyphosus vaigiensis MPEG 35156, 524 mm TL, family Gobiidae, (C) Priolepis dawsoni not cataloged, AZUSC 5667, 80 mm TL, family Acanthuridae, (D) Acanthurus chirurgus MPEG 35178, 85 mm TL, family Sphyraenidae, (E) Sphyraena guachancho MPEG 35063, 297 mm TL.

Fig. 12 in The bony fishes (Teleostei) caught by industrial trawlers off the Brazilian North coast, with insights into its conservation

Fig. 12. Species of the order Perciformes, family Sciaenidae, (A) Ctenosciaena gracilicirrhus MPEG 35609, 145 mm TL, (B) Cynoscion acoupa not cataloged, 310 mm TL, (C) Cynoscion jamaicensis MPEG 35588 173 mm TL, (D) Cynoscion leiarchus MPEG 35229 183 mm TL, (E) Cynoscion microlepidotus not cataloged, 320 mm TL, (F) Cynoscion similis MPEG 35042 254 mm TL, (G) Cynoscion steindachneri not cataloged, 250 mm TL, (H) Cynoscion virescens not cataloged, 340 mm TL, (I) Isopisthus parvipinnis MPEG 35051, 175 mm TL, (J) Larimus breviceps MPEG s/n, 150 mm TL, (K) Macrodon ancylodon MPEG 35059, 230 mm TL, (L) Ophioscion punctatissimus AZUSC 5178, 160 mm TL.

Fig. 7 in The bony fishes (Teleostei) caught by industrial trawlers off the Brazilian North coast, with insights into its conservation

Fig. 7. Species of the order Aulopiformes, family Synodontidae, (A) Saurida caribbaea MPEG 35598, 94 mm TL, (B) Synodus bondi MPEG 35202, 262 mm TL, (C) Synodus poeyi not cataloged, 160 mm TL, order Holocentriformes, family Holocentridae, (D) Holocentrus adscensionis AZUSC 5180, 210 mm TL, (E) Myripristis jacobus AZUSC 5181, 128 mm TL, order Ophidiiformes, family Ophidiidae, (F) Brotula barbata AZUSC 5141, 202 mm TL, (G) Lepophidium brevibarbe MPEG 35849, 234 mm TL, order Lophiiformes, family Antennariidae, (H) Antennarius striatus MPEG 35201, 114 mm TL, family Ogcocephalidae, (I) Halieutichthys aculeatus MPEG 35851, 36 mm TL, (J) Ogcocephalus nasutus MPEG 35167, 131 TL, (K) Ogcocephalus notatus AZUSC 5068, 120 mm TL, (L) Ogcocephalus pumilus MPEG 34615, 157 mm TL, order Beloniformes, family Exocoetidae, (M) Parexocoetus hillianus not cataloged, 150 mm TL, order Gasterosteiformes, family Fistulariidae, (N) Fistularia petimba AZUSC 5182, 560 mm TL, (O) Fistularia tabacaria AZUSC 5669, 590 mm TL, (O) Scorpaena brasiliensis MPEG 35141, 119 mm TL, (Q) Scorpaena isthmensis AZUSC 5644, 97 mm TL.

Fig. 11 in The bony fishes (Teleostei) caught by industrial trawlers off the Brazilian North coast, with insights into its conservation

Fig. 11. Species of the order Perciformes, family Pomacanthidae, (A) Holacanthus ciliaris not cataloged, 350 mmm TL, family Polynemidae, (B) Polydactylus virginicus MPEG 35182 306 mm TL, family Scaridae, (C) Sparisoma axillare not cataloged, 170 mm TL, family Sparidae, (D) Sparisoma frondosum AZUSC 5446, 120 mm TL, (E) Calamus penna MPEG 35709, 226 mm TL, (F) Calamus pennatula not cataloged, 230 mm TL.

Fig. 9 in The bony fishes (Teleostei) caught by industrial trawlers off the Brazilian North coast, with insights into its conservation

Fig. 9. Species of the order Perciformes, family Carangidae, (A) Alectis ciliaris MPEG 35701, 221 mm TL, (B) Caranx bartholomaei MPEG 35181, 323 mm TL, (C) Caranx crysos MPEG 35183, 350 mm TL, (D) Decapterus macarellus not cataloged, 220 mm TL, (E) Decapterus punctatus AZUSC 5551, 176 mm TL, (F) Decapterus tabi not cataloged, 240 mm TL, (G) Oligoplites saliens AZUSC 4660, 280 mm TL, (H) Selar crumenophthalmus MPEG 35137, 266 mm TL, (I) Selene setapinnis MPEG 35190, 243 mm TL, (J) Seriola dumerili not cataloged, 200 mm TL, (K) Trachinotus cayennensis MPEG 34410, 265 mm TL.

Fig. 6 in The bony fishes (Teleostei) caught by industrial trawlers off the Brazilian North coast, with insights into its conservation

Fig. 6. Species of the order Clupeiformes, family Clupeidae, (A) Lile piquitinga MPEG 35023, 95 mm TL, family Engraulidae, (B) Anchoa filifera MPEG 35122, 31 mm TL, (C) Anchoa pectoralis not cataloged, 100 mm TL, (D) Anchovia clupeoides not cataloged, 94 mm TL, (E) Anchoviella lepidentostole MPEG 35240, 118 mm TL, family Pristigasteridae, (F) Chirocentrodon bleekerianus MPEG 35674, 108 mm TL, (G) Odontognathus mucronatus MPEG 35048, 142 mm TL, (H) Pellona harroweri MPEG 35700, 136 mm TL, ordem Siluriformes, family Ariidae, (I) Amphiarius phrygiatus MPEG 35077, 345 mm TL, (J) Notarius grandicassis MPEG 35204, 410 mm TL, (K) Sciades couma not cataloged, 423 mm TL.

Fig. 1 in The bony fishes (Teleostei) caught by industrial trawlers off the Brazilian North coast, with insights into its conservation

Fig. 1. (A) Industrial trawling zone off the North coast of Brazil (modified from Aragão et al., 2001 and Brasil, 2011). Outriggers that target pink-shrimp (red outline) and pair trawlers that target a number of fish species (black dots in the main image and green shading in C-E). The Amazon River plume is shaded gray. The Great Amazon Reef System, as defined by Moura et al. (2016), is shaded orange in all images (A-E), while the system defined by Francini-Filho et al. (2018) is shaded green here, and red in all other images (B-E); (B-E) Kernel density plots of (B) estuarine species; (C) estuarine species also associated with coral reefs; (D) species associated with coral reefs or rock bottom; (E) marine species, not associated with coral reefs.

Fig. 4 in The bony fishes (Teleostei) caught by industrial trawlers off the Brazilian North coast, with insights into its conservation

Fig. 4. Species of the order Anguilliformes, family Heterenchelyidae, (A) Pythonichthys sanguineus, MPEG 35269, 493 mm TL, family Moringuidae, (B) Neoconger sp., AZUSC 4931, 254 mm TL, family Muraenidae, (C) Enchelycore nigricans, AZUSC 5432, 298 mm TL, (D) Gymnothorax conspersus AZUSC 5059, 326 mm TL, (E) Gymnothorax ocellatus AZUSC 5069, 464 mm TL, family Ophichthidae, (F) Aplatophis chauliodus not calaloged, 520 mm TL, (G) Echiophis punctifer MPEG 35510, 932 mm TL, (H) Ophichthus cylindroideus MPEG 35152, 645 mm TL, (I) Ophichthus ophis AZUSC 5179, 1052 mm TL.

Fig. 8 in The bony fishes (Teleostei) caught by industrial trawlers off the Brazilian North coast, with insights into its conservation

Fig. 8. Species of the ordem Perciformes, family Centropomidae, (A) Centropomus ensiferus MPEG 35060, 352 mm TL, family Serranidae, (B) Alphestes afer MPEG 35142, 174 mm TL, (C) Cephalopholis fulva not cataloged, 240 mm TL, (D) Diplectrum radiale MPEG 35149, 221 mm TL, (E) Epinephelus morio AZUSC 5428, 368 mm TL, (F) Hyporthodus nigritus not cataloged, 140 mm TL, (G) Hyporthodus niveatus MPEG 35841, 113 mm TL, (H) Mycteroperca bonaci not cataloged, 420 mm TL, (I) Paralabrax dewegeri AZUSC 5183, 70 mm TL, (J) Paranthias furcifer not cataloged, 270 mm TL, (K) Serranus flaviventris AZUSC 5103, 71 mm TL, (L) Serranus phoebe, AZUSC 5526, 116 mm TL, family Opistognathidae, (M) Lonchopisthus higmani, not cataloged, 80 mm TL, family Priacanthidae, (N) Priacanthus arenatus MPEG 35707 323 TL, family Malacanthidae, (O) Caulolatilus guppyi AZUSC 5668, 180 mm TL, (P) Malacanthus plumieri not cataloged, 420 mm TL, family Pomatomidae, (Q) Pomatomus saltatrix not cataloged, 380 mm TL, family Echeneidae, (R) Echeneis naucrates MPEG 35159, 296 mm TL.

opencc-by-4.0Sep 2018View details →

Figure 4 in Phorodon cannabis Passerini (Hemiptera: Aphididae), a newly recognized pest in North America found on industrial hemp

Figure 4. Phorodon humuli (Schrank). a) Apterous vivipara photomicrograph. b) Antennal segments II–VI. c) Siphunculus. d) Head and antennal segment I (left side dorsum; right side venter). e) Cauda dorsum.

opencc-by-4.0Sep 2018View details →

Figure 1. Phorodon cannabis Passerini. a in Phorodon cannabis Passerini (Hemiptera: Aphididae), a newly recognized pest in North America found on industrial hemp

Figure 1. Phorodon cannabis Passerini. a) Apterae with color form exhibited indoors and outdoors through midsummer. Photograph taken on August 4, 2017. b) Hemp leaf heavily infested with P. cannabis. Photograph taken on September 11, 2017. c) Mixed stages, including alate forms. Photograph taken on August 28, 2017. d) Aphids developing on stem of hemp. Photograph taken on September 31, 2017.