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opencc-by-nc-sa-4.0Mar 2024View details →

DCASE 2024 Challenge Task 2 Development Dataset

<p><strong><Data files will be made accessible on April 1st, 2024.></strong></p> <p><strong>Description</strong></p> <p>This dataset is the "development dataset" for the DCASE 2024 Challenge Task 2.</p> <p>The data consists of the normal/anomalous operating sounds of seven types of real/toy machines. Each recording is a single-channel 10-second audio that includes both a machine's operating sound and environmental noise. The following seven types of real/toy machines are used in this task:</p> <ul> <li>ToyCar</li> <li>ToyTrain</li> <li>Fan</li> <li>Gearbox</li> <li>Bearing</li> <li>Slide rail</li> <li>Valve</li> </ul> <p><strong>Overview of the task</strong></p> <p><strong>Anomalous sound detection (ASD) is the task of identifying whether the sound emitted from a target machine is normal or anomalous. </strong>Automatic detection of mechanical failure is an essential technology in the fourth industrial revolution, which involves artificial-intelligence-based factory automation. Prompt detection of machine anomalies by observing sounds is useful for monitoring the condition of machines. </p> <p>This task is the follow-up from DCASE 2020 Task 2 to DCASE 2023 Task 2. The task this year is to develop an ASD system that meets the following five requirements.</p> <p>1. **Train a model using only normal sound** (unsupervised learning scenario)  <br>Because anomalies rarely occur and are highly diverse in real-world factories, it can be difficult to collect exhaustive patterns of anomalous sounds. Therefore, the system must detect unknown types of anomalous sounds that are not provided in the training data. This is the same requirement as in the previous tasks.</p> <p>2. **Detect anomalies regardless of domain shifts** (domain generalization task)  <br>In real-world cases, the operational states of a machine or the environmental noise can change to cause domain shifts. Domain-generalization techniques can be useful for handling domain shifts that occur frequently or are hard-to-notice. In this task, the system is required to use domain-generalization techniques for handling these domain shifts. This requirement is the same as in DCASE 2022 Task 2 and DCASE 2023 Task 2.</p> <p>3. **Train a model for a completely new machine type**  <br>For a completely new machine type, hyperparameters of the trained model cannot be tuned. Therefore, the system should have the ability to train models without additional hyperparameter tuning. This requirement is the same as in DCASE 2023 Task 2.</p> <p>4. **Train a model using a limited number of machines from its machine type**  <br>While sounds from multiple machines of the same machine type can be used to enhance the detection performance, it is often the case that only a  limited number of machines are available for a machine type. In such a case, the system should be able to train models using a few machines from a machine type. This requirement is the same as in DCASE 2023 Task 2.</p> <p>5 . **Train a model both with or without attribute information**<br>While additional attribute information can help enhance the detection performance, we cannot always obtain such information. Therefore, the system must work well both when attribute information is available and when it is not.</p> <p>The last requirement is newly introduced in DCASE 2024 Task2.</p> <p> </p> <p><strong>Definition</strong></p> <p>We first define key terms in this task: "machine type," "section," "source domain," "target domain," and "attributes.".</p> <ul> <li>"Machine type" indicates the type of machine, which in the development dataset is one of seven: fan, gearbox, bearing, slide rail, valve, ToyCar, and ToyTrain.</li> <li>A section is defined as a subset of the dataset for calculating performance metrics.</li> <li>The source domain is the domain under which most of the training data and some of the test data were recorded, and the target domain is a different set of domains under which some of the training data and some of the test data were recorded. There are differences between the source and target domains in terms of operating speed, machine load, viscosity, heating temperature, type of environmental noise, signal-to-noise ratio, etc.</li> <li>Attributes are parameters that define states of machines or types of noise. For several machine types, the attributes are hidden.</li> </ul> <p> </p> <p><strong>Dataset</strong></p> <p>This dataset consists of seven machine types. For each machine type, one section is provided, and the section is a complete set of training and test data. For each section, this dataset provides (i) 990 clips of normal sounds in the source domain for training, (ii) ten clips of normal sounds in the target domain for training, and (iii) 100 clips each of normal and anomalous sounds for the test. The source/target domain of each sample is provided. Additionally, the attributes of each sample in the training and test data are provided in the file names and attribute csv files.</p> <p> </p> <p><strong>File names and attribute csv files</strong></p> <p>File names and attribute csv files provide reference labels for each clip. The given reference labels for each training/test clip include machine type, section index, normal/anomaly information, and attributes regarding the condition other than normal/anomaly. The machine type is given by the directory name. The section index is given by their respective file names. For the datasets other than the evaluation dataset, the normal/anomaly information and the attributes are given by their respective file names. Note that for machine types that has its attribute information hidden, the attribute information in each file names are only labeled as "noAttributes". Attribute csv files are for easy access to attributes that cause domain shifts. In these files, the file names, name of parameters that cause domain shifts (domain shift parameter, dp), and the value or type of these parameters (domain shift value, dv) are listed. Each row takes the following format:</p> <p>    [filename (string)], [d1p (string)], [d1v (int | float | string)], [d2p], [d2v]...</p> <p>For machine types that have their attribute information hidden, all columns except the filename column are left blank for each row.</p> <p><strong>Recording procedure</strong></p> <p>Normal/anomalous operating sounds of machines and its related equipment are recorded. Anomalous sounds were collected by deliberately damaging target machines. For simplifying the task, we use only the first channel of multi-channel recordings; all recordings are regarded as single-channel recordings of a fixed microphone. We mixed a target machine sound with environmental noise, and only noisy recordings are provided as training/test data. The environmental noise samples were recorded in several real factory environments. We will publish papers on the dataset to explain the details of the recording procedure by the submission deadline.</p> <p> </p> <p><strong>Directory structure</strong></p> <p>- /dev_data  </p> <p>    - /raw<br>        - /fan<br>            - /train (only normal clips)  <br>                - /section_00_source_train_normal_0001_<attribute>.wav  <br>                - ...  <br>                - /section_00_source_train_normal_0990_<attribute>.wav  <br>                - /section_00_target_train_normal_0001_<attribute>.wav  <br>                - ...  <br>                - /section_00_target_train_normal_0010_<attribute>.wav  <br>            - /test <br>                - /section_00_source_test_normal_0001_<attribute>.wav    <br>                - ...  <br>                - /section_00_source_test_normal_0050_<attribute>.wav    <br>                - /section_00_source_test_anomaly_0001_<attribute>.wav  <br>                - ...  <br>                - /section_00_source_test_anomaly_0050_<attribute>.wav  <br>                - /section_00_target_test_normal_0001_<attribute>.wav<br>                - ...  <br>                - /section_00_target_test_normal_0050_<attribute>.wav <br>                - /section_00_target_test_anomaly_0001_<attribute>.wav  <br>                - ...  <br>                - /section_00_target_test_anomaly_0050_<attribute>.wav <br>            - attributes_00.csv (attribute csv for section 00)<br>    - /gearbox (The other machine types have the same directory structure as fan.)  <br>    - /bearing<br>    - /slider (`slider` means "slide rail")<br>    - /ToyCar  <br>    - /ToyTrain  <br>    - /valve  </p> <p> </p> <p><strong>Baseline system</strong></p> <p>The baseline system is available on the Github repository <<a href="https://github.com/nttcslab/dcase2023_task2_baseline_ae">https://github.com/nttcslab/dcase2023_task2_baseline_ae</a>>.The baseline systems provide a simple entry-level approach that gives a reasonable performance in the dataset of Task 2. They are good starting points, especially for entry-level researchers who want to get familiar with the anomalous-sound-detection task.</p> <p> </p> <p><strong>Condition of use</strong></p> <p>This dataset was created jointly by <strong>Hitachi, Ltd. </strong>and <strong>NTT Corporation</strong> and is available under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) license.</p> <p> </p> <p><strong>Citation</strong></p> <p><TBD></p> <p> </p> <p><strong>Contact</strong></p> <p>If there is any problem, please contact us:</p> <ul> <li>Tomoya Nishida, <a href="mailto:kota.dohi.gr@hitachi.com">tomoya.nishida.ax@hitachi.com</a></li> <li>Keisuke Imoto, <a href="mailto:keisuke.imoto@ieee.org">keisuke.imoto@ieee.org</a></li> <li>Noboru Harada, <a href="mailto:noboru@ieee.org">noboru@ieee.org</a></li> <li>Daisuke Niizumi, <a href="mailto:daisuke.niizumi.dt@hco.ntt.co.jp">daisuke.niizumi.dt@hco.ntt.co.jp</a></li> <li>Yohei Kawaguchi, <a href="mailto:yohei.kawaguchi.xk@hitachi.com">yohei.kawaguchi.xk@hitachi.com</a></li> </ul>

opencc-by-4.0Dec 2023View details →

A Refined Supply-demand Framework to Quantify Variability in Ecosystem Services Related to Surface Water in Support of Sustainable Development Goals

<p>This database relies on the article entitled "A Refined Supply-demand Framework to Quantify Variability in Ecosystem Services Related to Surface Water in Support of Sustainable Development Goals " to be published in Earth's Future. The file named 'Results' stores the data produced in this study. The file named 'Scripts' stores the python codes used in this study. The file named 'Software' stores the software installation package (Windows 64-bit system). The file named '3basin' stores the shapefile data of Level 3 basin in Xinjiang. The file named "Supplementary Data" contains the necessary Water Bulletin and Statistical Yearbook data.</p>

Continuous Initial Breakdown Development of In-cloud Lightning Flashes

<p>The data contained in the MATLAB .fig files support the manuscript submitted to JGR-Atmospheres titled "Continuous Initial Breakdown Development of In-cloud Lightning Flashes".</p>

opencc-by-4.0Jan 2024View details →

Representative data accompanying the manuscript: Four-dimensional quantitative analysis of cell plate development in Arabidopsis using lattice light sheet microscopy identifies robust transition points between growth phases

<p>Representative data accompanying the manuscript: Sinclair R, Wang M, Jawaid MZ, Longkumer T, Aaron J, Rossetti B, Wait E, McDonald K, Cox D, Heddleston J, Wilkop T, Drakakaki G. (2024). <em>Four-dimensional quantitative analysis of cell plate development in Arabidopsis using lattice light sheet microscopy identifies robust transition points between growth phases.</em> J Exp Bot. 2024 Mar 4: erae091. doi: 10.1093/jxb/erae091.</p> <p>The data show YFP–RABA2a dynamics in dividing cells of Arabidopsis root tips using lattice light sheet microscopy. Treatments with or without Endosidin 7, a cytokinesis-specific callose deposition inhibitor, are shown.</p> <p>Data: </p> <p>22.3 YFP-RABA2A. </p> <p>23.9 YFP-RABA2A ES7 </p>

opencc-by-4.0Nov 2023View details →

Data and Software for Developing a General Comprehensive Evaluation Method for Cross-Scale Precipitation Forecasts

<div> </div> <div>Readme for GCEM Data and Code</div> <div> </div> <div>1 The data and code of two typical cases in Section 4.1</div> <div>1.1 Data</div> <div>1.1.1 Observed Precipitation Data</div> <div>1.1.1.1  /1_Two_Typical_Processes_data/1_1Observed_precipitation_data/2019071612</div> <div>(in the 1_Two_Typical_Processes_data.rar file)</div> <div>Hourly precipitation from 00:00 to 12:00 UTC on July 16, 2019 for Case 1</div> <div>surfr01h.nc</div> <div>  surfr02h.nc</div> <div>  surfr03h.nc</div> <div>  surfr04h.nc</div> <div>  surfr05h.nc</div> <div>  surfr06h.nc</div> <div>  surfr07h.nc</div> <div>  surfr08h.nc</div> <div>  surfr09h.nc</div> <div>  surfr10h.nc</div> <div>  surfr11h.nc</div> <div>surfr12h.nc</div> <div>1.1.1.2 /1_Two_Typical_Processes_data/1_1Observed_precipitation_data/2020061312</div> <div>(in the 1_Two_Typical_Processes_data.rar file)</div> <div>Hourly precipitation from 00:00 to 12:00 UTC on June 13,2020 for Case 2</div> <div>surfr01h.nc</div> <div>  surfr02h.nc</div> <div>  surfr03h.nc</div> <div>  surfr04h.nc</div> <div>  surfr05h.nc</div> <div>  surfr06h.nc</div> <div>  surfr07h.nc</div> <div>  surfr08h.nc</div> <div>  surfr09h.nc</div> <div>  surfr10h.nc</div> <div>  surfr11h.nc</div> <div>surfr12h.nc</div> <div>1.1.2 Forecasted Precipitation Data</div> <div>1.1.2.1  /1_Two_Typical_Processes_data/1_2Forecasted_precipitation_data/2019071612</div> <div>(in the 1_Two_Typical_Processes_data.rar file)</div> <div> Data for Case 1 during 00:00-12:00 UTC on July 16, 2019</div> <div>WRF3.2019071600000.nc (initial field at 12:00 UTC on July 16, 2019)</div> <div>WRF3.2019071600012.nc (12-hour accumulated precipitation during 00:00–12:00 UTC on July 16, 2019)</div> <div>1.1.2.2  /1_Two_Typical_Processes_data/1_2Forecasted_precipitation_data/2020061312</div> <div>(in the 1_Two_Typical_Processes_data.rar file)</div> <div> Data for Case 2 during 00:00-12:00 UTC on June 13,2020</div> <div>WRF3.2020061300000.nc (initial field at 12:00 UTC on June 13,2020)</div> <div>WRF3.2020061300012.nc (12-hour accumulated precipitation during 00:00–12:00 UTC on June 13,2020)</div> <div> </div> <div>1.2 Code and Configuration Files</div> <div>1.2.1 GCEM of Software and Configuration</div> <div> (/Code/1_Two_Typical_Processes/1Software_Configuration_of_GCEM in the Code.rar file)</div> <div>pastonc6hd2.f90   Main program, reads observed and forecasted precipitation data, performs GCEM verification, and outputs result files.</div> <div>  module_skinput.f90   Subprogram, module for reading one or more observed precipitation grid file</div> <div>  module_ybinput.f90   Subprogram, module for reading the start (or end) forecasted precipitation grid file</div> <div>  mod_uxpasid2.f90   Subprogram, module for used to perform GCEM verification on forecasted data</div> <div>  module_outnc.f90   Subprogram, module for outputting the verification results in netCDF file format</div> <div>  compilePAS10mmd2.sh   Used to compile source files to generate executable file under Linux</div> <div> r12hfile.txt  Configuration file, used to specify the latitude and longitude range for data source and verification</div> <div> pastonc6hd2.exe   Executable file</div> <div>1.2.2 TS of Software and Configuration</div> <div> (/Code/1_Two_Typical_Processes/2Software_Configuration_of_TS-Score in the Code.rar file)</div> <div>tsmain01.f90   Main program, reads observed and forecasted precipitation data, performs TS verification, and outputs result files.</div> <div>  module_skinput.f90   Subprogram, module for reading one or more observed precipitation grid file  module_ybinput.f90   Subprogram, module for reading the start (or end) forecasted precipitation grid file</div> <div>  module_uxtsiTure.f90   Subprogram, module for used to perform TS verification on forecasted data</div> <div>  compileTS.sh   Used to compile source files to generate executable file under Linux</div> <div> r12hfile.txt   Configuration file, used to specify the latitude and longitude range for data source and verification</div> <div>  tsmain01.exe   Executable file</div> <div> </div> <div>1.3 Output files</div> <div>1.3.1 GCEM verification results</div> <div> (/1_Two_Typical_Processes_data/1_3Results/1_3_1Results_GCEM in the 1_Two_Typical_Processes_data.rar file)</div> <div>   rainverd2019071612012.nc   Result file in netCDF format</div> <div>   rainverd2019071612012.nc.txt   Result explanation file in netCDF format</div> <div>   outnc12hd22019071612.txt   GCEM result file in text format</div> <div>   rainverd2020061312012.nc   Result file in netCDF format </div> <div>   rainverd2020061312012.nc.txt   Result explanation file in netCDF format</div> <div>   outnc12hd22020061312.txt   GCEM result file in text format</div> <div> </div> <div>1.3.2 TS verification results</div> <div> (/1_Two_Typical_Processes_data/1_3Results/1_3_2Results_TS in the 1_Two_Typical_Processes_data.rar file)</div> <div>   ts12h2019071612.txt   TS result file in text format</div> <div>   ts12h2020061312.txt   TS result file in text format</div> <div> </div> <div>1.4 Compiling Environment</div> <div>   The verification program runs in a UNIX environment and requires the intel compiler (v2017) and the netCDF (v4.6.1) support library</div> <div>   UNIX Environment Settings</div> <div># .bashrc</div> <div>module load intel/intel-compiler-2017.5.239</div> <div>module load intelmpi/2019.6.154</div> <div>export F90=ifort</div> <div>export NETCDF=/public/software/mathlib/netcdf/4.6.1_intel-2017_mpi-2017_hdf5-1.8.20-intel2017</div> <div>export NETCDF_LIB=$NETCDF/lib</div> <div>export NETCDF_INC=$NETCDF/include</div> <div>export PATH=$NETCDF/bin:$PATH</div> <div>export LD_LIBRARY_PATH=$NETCDF/lib:$LD_LIBRARY_PATH</div> <div> </div> <div>1.5 Compiling and Running Steps</div> <div>1.5.1 The steps for case 1 during 00:00–12:00 UTC on July 16, 2019</div> <div>   1. Creating an installation and running sub-directory</div> <div>    mkdir p2019</div> <div>   2. Copying data sources, code files and configuration files to this directory</div> <div>   3. Running in this directory</div> <div>    ./compilePAS10mmd2.sh Compile to generate executable file (pastonc6hd2.exe)</div> <div>./compileTS.sh   Compile to generate executable file (tsmain01.exe)</div> <div>   4. Modifying the configuration file (r12hfile.txt)</div> <div>   5. Run the executable files </div> <div>    ./pastonc6hd2.exe > outnc12hd22019071612.txt</div> <div>Creating the GCEM result file (rainverd2019071612012.nc), procedure file (outnc12hd22019071612.txt)</div> <div>./tsmain01.exe >ts12h2019071612.txt</div> <div>Creating the TS result and procedure file (ts12h2019071612.txt)</div> <div> </div> <div>1.5.2 The steps for case 2 during 00:00–12:00 UTC on June 13,2020</div> <div>   1. Creating an installation and running sub-directory</div> <div>    mkdir p2020</div> <div>   2. Copying data sources, code files and configuration files to this directory</div> <div>   3. Running in this directory</div> <div>    ./compilePAS10mmd2.sh Compile to generate executable file (pastonc6hd2.exe)</div> <div>./compileTS.sh   Compile to generate executable file (tsmain01.exe)</div> <div>   4. Modifying the configuration file (r12hfile.txt)</div> <div>   5. Run the executable files</div> <div>    ./pastonc6hd2.exe > outnc12hd22020061312.txt</div> <div>Creating the GCEM result file (rainverd2020061312012.nc), procedure file (outnc12hd22020061312.txt)</div> <div>./tsmain01.exe >ts12h2020061312.txt</div> <div>Creating the TS result and procedure file (ts12h2019071612.txt)</div> <div> </div> <div>1.6 Module code main interface description</div> <div>1.6.1 skinput()</div> <div>subroutine skinput(skfile,skfilenum,rain,gridskx,gridsky,longitude,latitude)</div> <div>  integer,intent(in) :: skfilenum</div> <div>  character(len=200),dimension(skfilenum),intent(in) :: skfile</div> <div>  real,dimension(:,:),allocatable,intent(out) :: rain</div> <div>  integer,intent(out) :: gridskx,gridsky</div> <div> </div> <div>usage: Read a set of observed precipitation data files and output grid accumulated precipitation</div> <div>skfile, A set of filenames that are arrays of strings (input)</div> <div>skfilenum, Number of files (input)</div> <div>rain, Accumulated precipitation, rain(nx,ny) (output)</div> <div>gridskx, grid points, nx (output)</div> <div>gridsky, grid points, ny (output)</div> <div>gridlon, Longitude array, gridlon(nx) (output)</div> <div>gridlat, Latitude array, gridlat(ny) (output)</div> <div> </div> <div>1.6.2 ybinput()</div> <div>subroutine ybinput(ybfile,apcp,gridybx,gridyby,gridyblon,gridyblat)</div> <div>  character(len=200),intent(in) :: ybfile</div> <div>  real,dimension(:,:),allocatable,intent(out) :: apcp,gridyblat,gridyblon</div> <div>  integer,intent(out) :: gridybx,gridyby</div> <div> </div> <div>usage: Read a set of forecasted precipitation data files and output forecast grid precipitation</div> <div>ybfile, Forecast file (input)</div> <div>apcp, forecasted precipitation array, apcp(nx, ny) (output)</div> <div>gridybx, Number of grid points for forecast data, nx (output)</div> <div>gridyby, Number of grid points for forecast data, ny (output)</div> <div>gridyblon, Longitude of forecast data, gridyblon(nx, ny) (output)</div> <div>gridyblat, Latitude of forecast data, gridyblat(nx, ny) (output)</div> <div> </div> <div>1.6.3 uxpasid2()</div> <div>subroutine uxpasid2(ui,xi,level,pas,iTure,iclass,ieps)</div> <div>  real,intent(in)  ::  ui,xi,level</div> <div>  real,intent(out) :: pas,ieps</div> <div>  integer,intent(out) :: iTure,iclass</div> <div> </div> <div>usage: Read in the observed and forecasted precipitation, and output the PAS score result</div> <div>rainsk, Observed precipitation (input)</div> <div>rainyb, Forecasted precipitation (input)</div> <div>level, Specifing magnitude (input)</div> <div>ipas, Pas score value (0-1) or correct value of no precipitation forecast (1)</div> <div>iTure, 0 indicates that the rating is correct for a no precipitation forecast;</div> <div>1 indicates a PAS score of ≥ the specified magnitude;</div> <div>9 indicates that it is not in the no precipitation test, nor is it the verification the specified magnitude;</div> <div>-999 indicates default.</div> <div>iclass, 0 indicates the category (no precipitation forecast is correct)</div> <div>1 indicates the category of insufficient precipitation forecast (observation u<10mm)</div> <div>2 indicates the category of excessive(or equal) precipitation forecast(observation u<10mm)</div> <div>3 indicates the category of insufficient precipitation forecast (observation u≥10mm)</div> <div>4 indicates the category of excessive(or equal) precipitation forecast(observation u≥10mm)</div> <div>-999 indicates default.</div> <div>ieps, 0 indicates the forecasted and observed precipitation are equal</div> <div><0 indicates insufficient precipitation forecast</div> <div>>0 indicates excessive precipitation forecast</div> <div>-999 indicates default.</div> <div> </div> <div>1.6.4 outpasnc()</div> <div>subroutine outpasnc(title,vtime,vhour,gridncx,gridncy,gridnclon,gridnclat,rainncsk,rainncyb,&</div> <div>                 pasc,pas01,pas10,pas25,pas50, pas2p5,pas5,pas15, pascnc,pasnc01,pasnc10,&</div> <div>                 pasnc25,pasnc50,pasnc2p5,pasnc5,pasnc15,ipsnc,epsnc,iepsnc,ips,eps,ieps)</div> <div>  character(len=10),intent(in) :: vtime,title</div> <div>  integer,intent(in) :: vhour,gridncx,gridncy</div> <div>  character(len=10) :: chour</div> <div>  real,dimension(gridncx),intent(in) :: gridnclon</div> <div>  real,dimension(gridncy),intent(in) :: gridnclat</div> <div>  real,dimension(gridncx,gridncy),intent(in) :: rainncsk,rainncyb,pascnc,pasnc01</div> <div>  real,dimension(gridncx,gridncy),intent(in) :: pasnc10,pasnc25,pasnc50,ipsnc,epsnc,iepsnc</div> <div>  real,dimension(gridncx,gridncy),intent(in) ::pasnc2p5,pasnc5,pasnc15</div> <div>  real,intent(in) :: pasc,pas01,pas10,pas25,pas50,ips,eps,ieps,pas2p5,pas5,pas15</div> <div> </div> <div>usage: Output data to a netCDF format file</div> <div>title, File name tag (d)</div> <div>vtime, time string (yyyymmdddhh, eg. 2019071612)</div> <div>vhour, Accumulated precipitation duration (12)</div> <div>gridncx, x grid points (240)</div> <div>gridncy, y grid points (200)</div> <div>gridnclon, x grid points longitude array </div> <div>gridnclat, y grid points latitude array</div> <div>rainncsk, Observed precipitation</div> <div>rainncyb, Forecasted precipitation</div> <div>pasc, PASC</div> <div>pas01, ≥0.1mm PAS</div> <div>pas10, ≥10mm PAS</div> <div>pas25, ≥25mm PAS</div> <div>pas50, ≥50mm PAS</div> <div>pas2p5, ≥2.5mm PAS</div> <div>pas5, ≥5mm PAS</div> <div>pas15, ≥15mm PAS</div> <div>pascnc, PASC array</div> <div>pasnc01, ≥0.1mm PAS array</div> <div>pasnc10, ≥10mm PAS array</div> <div>pasnc25, ≥25mm PAS array</div> <div>pasnc50, ≥50mm PAS array</div> <div>pasnc2p5, ≥2.5mm PAS array</div> <div>pasnc5, ≥5mm PAS array</div> <div>pasnc15, ≥15mm PAS array</div> <div>ipsnc, IPS array</div> <div>epsnc, EPS array</div> <div>iepsnc, IEPS array</div> <div>ips, IPS</div> <div>eps, EPS</div> <div>ieps IEPS</div> <div> </div> <div>2 The data and code of extreme rainfall event in Section 4.2</div> <div>2.1 Data</div> <div>2.1.1 Observed Precipitation Data</div> <div> (/2_1Observed_precipitation_data in the 2_1Observed_precipitation_data.rar file)</div> <div>CMPAday-2021072100UTC.nc</div> <div>CMPAday-2021072200UTC.nc</div> <div>2.1.2 Forecasted Precipitation Data</div> <div>2.1.2.1 PWAFS data</div> <div> (in the wrfout_2021071812012.rar, wrfout_2021071812036.rar, wrfout_2021071912012.rar, wrfout_2021071912036.rar, wrfout_2021072012012.rar and wrfout_2021072012036.rar files)</div> <div>wrfout_2021071812012.nc (initial field at 12:00 UTC on 18 July 2021, with forecast time of 12 hours)</div> <div>wrfout_2021071812036.nc (initial field at 12:00 UTC on 18 July 2021, with forecast time of 36 hours)</div> <div>wrfout_2021071912012.nc (initial field at 12:00 UTC on 19 July 2021, with forecast time of 12 hours)</div> <div>wrfout_2021071912036.nc (initial field at 12:00 UTC on 19 July 2021, with forecast time of 36 hours)</div> <div>wrfout_2021072012012.nc (initial field at 12:00 UTC on 20 July 2021, with forecast time of 12 hours)</div> <div>wrfout_2021072012036.nc (initial field at 12:00 UTC on 20 July 2021, with forecast time of 36 hours)</div> <div>2.1.2.2 GRAPES data</div> <div>  (/2_2_2Forecasted_02_data in the 2_2_2Forecasted_02_data.rar file)</div> <div>GRAPES2021071812012.nc (initial field at 12:00 UTC on 18 July 2021, with forecast time of 12 hours)</div> <div>GRAPES2021071812036.nc (initial field at 12:00 UTC on 18 July 2021, with forecast time of 36 hours)</div> <div>GRAPES2021071912012.nc (initial field at 12:00 UTC on 19 July 2021, with forecast time of 12 hours)</div> <div>GRAPES2021071912036.nc (initial field at 12:00 UTC on 19 July 2021, with forecast time of 36 hours)</div> <div>GRAPES2021072012012.nc (initial field at 12:00 UTC on 20 July 2021, with forecast time of 12 hours)</div> <div>GRAPES2021072012036.nc (initial field at 12:00 UTC on 20 July 2021, with forecast time of 36 hours)</div> <div> </div> <div>2.2 Code and Configuration Files</div> <div>2.2.1 PAS of Software and Configuration</div> <div>  (/Code/2_extreme_rainfall_event/1Software_Configuration_of_PAS in the Code.rar file)</div> <div>pasmain250mm.f90 Main program, reads observed and forecasted precipitation data, performs GCEM verification, and outputs result files.</div> <div>pasgmain250mm.f90 Main program, reads observed and forecasted precipitation data, performs GCEM verification, and outputs result files.</div> <div>  module_skinput.f90   Subprogram, module for reading one or more observed precipitation grid file</div> <div>  module_ybinput.f90   Subprogram, module for reading the start (or end) forecasted precipitation grid file</div> <div>  module_ybinputGrapes.f90 Subprogram, module for reading the start (or end) forecasted precipitation grid file</div> <div>  mod_uxpasid2.f90   Subprogram, module for used to perform GCEM verification on forecasted data</div> <div>  module_outnc.f90   Subprogram, module for outputting the verification results in netCDF file format</div> <div>  compilePAS250mm.sh Used to compile source files to generate executable file under Linux</div> <div>  compileGrapesPAS250mm.sh Used to compile source files to generate executable file under Linux</div> <div>r12hfilePWAFS2021071812036-12.txt Configuration file, used to specify the latitude and longitude range for data source and verification</div> <div>r12hfilePWAFS2021071912036-12.txt Configuration file, used to specify the latitude and longitude range for data source and verification</div> <div>r12hfilePWAFS2021072012036-12.txt Configuration file, used to specify the latitude and longitude range for data source and verification</div> <div>r12hfileGRAPES2021071812036-12.txt Configuration file, used to specify the latitude and longitude range for data source and verification</div> <div>r12hfileGRAPES2021071912036-12.txt Configuration file, used to specify the latitude and longitude range for data source and verification</div> <div>r12hfileGRAPES2021072012036-12.txt Configuration file, used to specify the latitude and longitude range for data source and verification</div> <div>pasmain250mm.exe Executable file</div> <div>pasgmain250mm.exe Executable file</div> <div>2.2.2 TS of Software and Configuration</div> <div> (/Code/2_extreme_rainfall_event/2Software_Configuration_of_TS in the Code.rar file)</div> <div>tsmain250mm.f90 Main program, reads observed and forecasted precipitation data, performs TS verification, and outputs result files.</div> <div>tsgmain250mm.f90 Main program, reads observed and forecasted precipitation data, performs TS verification, and outputs result files.</div> <div>module_skinput.f90 Subprogram, module for reading one or more observed precipitation grid file</div> <div>module_ybinput.f90 Subprogram, module for reading the start (or end) forecasted precipitation grid file</div> <div>module_ybinputGrapes.f90 Subprogram, module for reading the start (or end) forecasted precipitation grid file</div> <div>module_uxtsiTure.f90 Subprogram, module for used to perform TS verification on forecasted data</div> <div>compileTS250mm.sh Used to compile source files to generate executable file under Linux</div> <div>compileGrapesTS250mm.sh Used to compile source files to generate executable file under Linux</div> <div>r12hfilePWAFS2021071812036-12.txt Configuration file, used to specify the latitude and longitude range for data source and verification</div> <div>r12hfilePWAFS2021071912036-12.txt Configuration file, used to specify the latitude and longitude range for data source and verification</div> <div>r12hfilePWAFS2021072012036-12.txt Configuration file, used to specify the latitude and longitude range for data source and verification</div> <div>r12hfileGRAPES2021071812036-12.txt Configuration file, used to specify the latitude and longitude range for data source and verification</div> <div>r12hfileGRAPES2021071912036-12.txt Configuration file, used to specify the latitude and longitude range for data source and verification</div> <div>r12hfileGRAPES2021072012036-12.txt Configuration file, used to specify the latitude and longitude range for data source and verification</div> <div>tsmain250mm.exe Executable file</div> <div>tsgmain250mm.exe Executable file</div> <div>2.2.3 FSS of Software and Configuration</div> <div>  (/Code/2_extreme_rainfall_event/3Software_Configuration_of_FSS in the Code.rar file)</div> <div>fssmain250mm.f90 Main program, reads observed and forecasted precipitation data, performs TS verification, and outputs result files.</div> <div>fssgmain250mm.f90 Main program, reads observed and forecasted precipitation data, performs TS verification, and outputs result files.</div> <div>module_skinput.f90 Subprogram, module for reading one or more observed precipitation grid file</div> <div>module_ybinput.f90 Subprogram, module for reading the start (or end) forecasted precipitation grid file</div> <div>module_ybinputGrapes.f90 Subprogram, module for reading the start (or end) forecasted precipitation grid file</div> <div>module_FSSom.f90 Subprogram, module for used to perform FSS verification on forecasted data</div> <div>compilefss250mm.sh Used to compile source files to generate executable file under Linux</div> <div>compileGrapesfss250mm.sh Used to compile source files to generate executable file under Linux</div> <div>r12hfilePWAFS2021071812036-12.txt Configuration file, used to specify the latitude and longitude range for data source and verification</div> <div>r12hfilePWAFS2021071912036-12.txt Configuration file, used to specify the latitude and longitude range for data source and verification</div> <div>r12hfilePWAFS2021072012036-12.txt Configuration file, used to specify the latitude and longitude range for data source and verification</div> <div>r12hfileGRAPES2021071812036-12.txt Configuration file, used to specify the latitude and longitude range for data source and verification</div> <div>r12hfileGRAPES2021071912036-12.txt Configuration file, used to specify the latitude and longitude range for data source and verification</div> <div>r12hfileGRAPES2021072012036-12.txt Configuration file, used to specify the latitude and longitude range for data source and verification</div> <div>fssmain250mm.exe Executable file</div> <div>fssgmain250mm.exe Executable file</div> <div> </div> <div>2.3 Output files</div> <div>2.3.1 GCEM verification results</div> <div> (/2_3Results/2_3_1Results_PAS in the 2_3Results.rar file)</div> <div>   rainverd2021072000001.nc    Result file in netCDF format</div> <div>   rainverd2021072000001.nc.txt   Result explanation file in netCDF format</div> <div>   rainverd2021072100001.nc    Result file in netCDF format</div> <div>   rainverd2021072100001.nc.txt   Result explanation file in netCDF format</div> <div>   rainverd2021072200001.nc    Result file in netCDF format</div> <div>   rainverd2021072200001.nc.txt   Result explanation file in netCDF format</div> <div>   outnc22021072000_250mm.txt  GCEM result file in text format</div> <div>   outnc22021072100_250mm.txt  GCEM result file in text format</div> <div>   outnc22021072200_250mm.txt  GCEM result file in text format</div> <div>   rainverg2021072000001.nc    Result file in netCDF format</div> <div>   rainverg2021072000001.nc.txt   Result explanation file in netCDF format</div> <div>   rainverg2021072100001.nc    Result file in netCDF format</div> <div>   rainverg2021072100001.nc.txt   Result explanation file in netCDF format</div> <div>   rainverg2021072200001.nc    Result file in netCDF format</div> <div>   rainverg2021072200001.nc.txt   Result explanation file in netCDF format</div> <div>   outgnc22021072000_250mm.txt  GCEM result file in text format</div> <div>   outgnc22021072100_250mm.txt  GCEM result file in text format</div> <div>   outgnc22021072200_250mm.txt  GCEM result file in text format</div> <div>2.3.2 TS verification results</div> <div> (/2_3Results/2_3_2Results_TS in the 2_3Results.rar file)</div> <div>   ts2021072000_24h250mm.txt   TS result file in text format</div> <div>   ts2021072100_24h250mm.txt   TS result file in text format</div> <div>   ts2021072200_24h250mm.txt   TS result file in text format</div> <div>   tsg2021072000_24h250mm.txt   TS result file in text format</div> <div>   tsg2021072100_24h250mm.txt   TS result file in text format</div> <div>   tsg2021072200_24h250mm.txt   TS result file in text format</div> <div>2.3.3 FSS verification results</div> <div> (/2_3Results/2_3_3Results_FSS in the 2_3Results.rar file)</div> <div>   fss2021072000_24h250mm.txt   TS result file in text format</div> <div>   fss2021072100_24h250mm.txt   TS result file in text format</div> <div>   fss2021072200_24h250mm.txt   TS result file in text format</div> <div>   fssg2021072000_24h250mm.txt   TS result file in text format</div> <div>   fssg2021072100_24h250mm.txt   TS result file in text format</div> <div>   fssg2021072200_24h250mm.txt   TS result file in text format</div> <div> </div> <div>2.4 Compiling Environment</div> <div>   The verification program runs in a UNIX environment and requires the intel compiler (v2017) and the netCDF (v4.6.1) support library</div> <div>   UNIX Environment Settings</div> <div># .bashrc</div> <div>module load intel/intel-compiler-2017.5.239</div> <div>module load intelmpi/2019.6.154</div> <div>export F90=ifort</div> <div>export NETCDF=/public/software/mathlib/netcdf/4.6.1_intel-2017_mpi-2017_hdf5-1.8.20-intel2017</div> <div>export NETCDF_LIB=$NETCDF/lib</div> <div>export NETCDF_INC=$NETCDF/include</div> <div>export PATH=$NETCDF/bin:$PATH</div> <div>export LD_LIBRARY_PATH=$NETCDF/lib:$LD_LIBRARY_PATH</div> <div> </div> <div>2.5 Compiling and Running Steps</div> <div>2.5.1 Creating an installation and running sub-directory</div> <div>    mkdir zzby</div> <div>2.5.2 Copying data sources, code files and configuration files to this directory</div> <div>2.5.3 Running in this directory</div> <div>./compilePAS250mm.sh   Compile to generate executable file (pasmain250mm.exe)</div> <div>./compileGrapesPAS250mm.sh   Compile to generate executable file (pasgmain250mm.exe)</div> <div>./compileTS250mm.sh   Compile to generate executable file (tsmain250mm.exe)</div> <div>./compileGrapesTS250mm.sh   Compile to generate executable file (tsgmain250mm.exe)</div> <div>./compilefss250mm.sh   Compile to generate executable file (fssmain250mm.exe)</div> <div>./compileGrapesfss250mm.sh   Compile to generate executable file (fssgmain250mm.exe)</div> <div>2.5.4 Modifying the configuration file (r12hfile.txt)</div> <div>Link Configuration file to r12hfile.txt</div> <div>Mainly modifying the data sources</div> <div>2.5.5 Run the executable files</div> <div>Link different configuration files, and run executable files, then output different results.</div> <div>Creating the GCEM result and procedure files</div> <div>./pasmain250mm.exe > outnc22021072000_250mm.txt</div> <div>./pasmain250mm.exe > outnc22021072100_250mm.txt</div> <div>./pasmain250mm.exe > outnc22021072200_250mm.txt</div> <div>./pasgmain250mm.exe > outgnc22021072000_250mm.txt</div> <div>./pasgmain250mm.exe > outgnc22021072100_250mm.txt</div> <div>./pasgmain250mm.exe > outgnc22021072200_250mm.txt</div> <div>Creating the TS result and procedure files</div> <div>./tsmain250mm.exe > ts2021072000_24h250mm.txt</div> <div>./tsmain250mm.exe > ts2021072100_24h250mm.txt</div> <div>./tsmain250mm.exe > ts2021072200_24h250mm.txt</div> <div>./tsgmain250mm.exe > tsg2021072000_24h250mm.txt</div> <div>./tsgmain250mm.exe > tsg2021072100_24h250mm.txt</div> <div>./tsgmain250mm.exe > tsg2021072200_24h250mm.txt</div> <div>Creating the FSS result and procedure files</div> <div>./fssmain250mm.exe >fss2021072000_24h250mm.txt</div> <div>./fssmain250mm.exe >fss2021072100_24h250mm.txt</div> <div>./fssmain250mm.exe >fss2021072200_24h250mm.txt</div> <div>./fssgmain250mm.exe >fssg2021072000_24h250mm.txt</div> <div>./fssgmain250mm.exe >fssg2021072100_24h250mm.txt</div> <div>./fssgmain250mm.exe >fssg2021072200_24h250mm.txt</div> <div> </div> <div>3 PAS mini-program</div> <div>3.1 Code for PAS mini-program</div> <div>(/Code/3_Software_of_PAS in the Code.rar file)</div> <div>  pas10ux.f90   Main program, used to perform PAS verification on single point precipitation forecast</div> <div>  mod_uxpasid2.f90   Subprogram, Module for PAS of single point forecast</div> <div>  compilePAS10ux.sh   Used to compile source files to generate executable file under Linux</div> <div>  pas10ux.exe   Executable file</div> <div> </div> <div>3.2 The steps for PAS mini-program</div> <div>   1. Creating an installation and running sub-directory</div> <div>    mkdir pas</div> <div>   2. Copying code files and configuration files to this directory</div> <div>   3. Running in this directory</div> <div>    ./compilePAS10ux.sh Compile to generate executable file (pastonc6hd2.exe)</div> <div>   4. linking the executable file as pas</div> <div>    ln -sf pas10ux.exe pas</div> <div>   5. Running the PAS mini-program</div> <div> </div> <div>for example: ./pas 15 20</div> <div>Parameter 1:  15   represents observed precipitation</div> <div>Parameter 2:  20   represents forecasted precipitation</div> <div>Output: 0.895   1</div> <div> </div> <div>    The following instructions for specific usage:</div> <div>pas rainsk rainyb [level]</div> <div>    Input parameters</div> <div>    Parameter 1 (rainsk): observed precipitation (mm)</div> <div>    Parameter 2 (rainyb): forecasted precipitation (mm)</div> <div>    Parameter 3 (level): Specifing magnitude (Optional, default to ≥0.1 mm)</div> <div>    Onput parameters</div> <div>Parameter 1 (ipas): Pas score value (0-1) or correct value of no precipitation forecast (1);</div> <div>-999.000 represents default.</div> <div>Parameter 2 (iTure):</div> <div>0 indicates that the rating is correct for a no precipitation forecast;</div> <div>1 indicates a PAS score of ≥ the specified magnitude;</div> <div>9 indicates that it is not in the no precipitation test, nor is it the verification the specified magnitude;</div> <div>-999 indicates default.</div> <div> </div> <div> </div>

Supported codes and data for "Hydrodynamic and biochemical impacts on the development of hypoxia in the Louisiana–Texas shelf Part 1: roles of nutrient limitation and plankton community"

<p>This dataset comprises matlab codes and truncated raw data from the Gulf-COAWST model hindcast over the northern Gulf of Mexico. The codes and data support the research presented in "Hydrodynamic and Biochemical Impacts on the Development of Hypoxia in the Louisiana–Texas Shelf Part 1: Roles of Nutrient Limitation and Plankton Community" and are organized by sections discussed in the paper.</p> <p>Readers can find the following figures and tables presented in the paper in the listed folders (highlighted by italic and bold font):</p> <p>Figure 2 in <strong><em>section2.3</em></strong></p> <p>Figure 3 in <strong><em>section3.2</em></strong></p> <p>Figures 4–5 in <strong><em>section3.3</em></strong></p> <p>Table 1 and Figure C2 in <strong><em>section3.4</em></strong></p> <p>Figure 6 in <strong><em>section3.5</em></strong></p> <p>Figure 7 in <strong><em>section3.6</em></strong></p> <p>Figures 8–9 and Table 2 in <strong><em>section3.7</em></strong></p> <p>Figures 10, 11, and C3 in <strong><em>section4.1</em></strong></p> <p>Figures 12, 13, 14, C4, and C5 in <strong><em>section4.2</em></strong></p> <p>Figures 15–17 in <strong><em>section4.3</em></strong></p> <p>Figure C1 in <strong><em>section_appendix</em></strong></p> <p>The grid file which is in the netCDF format is stored in folder <strong><em>grid</em></strong>. The folder <em><strong>matlab_toolbox</strong></em> is the toolbox needs for the data processing and figure plotting.</p>

Mining allowances, wellbeing and SE development in the mining sector, DRC

<p>This dataset supports the paper "A Congolese mining giant’s social corporate responsibility stuck between false pretense and bricolage: passing through a logic of <em>do no harm</em> to make <em>sustainable development</em> concrete still at issue." currently in the submission phase to a journal. The paper fundamentally questions the relationship between social policies and their application on the field in the mining extraction industry. It relies upon results from a case study implemented by me in DRC between 2018 and 2022, in the frame of a broader multidisciplinary project (Anthropology, Social Economics, Land Management) named “Locals dealing with Developmental Income” (DevInc). </p>

Time-series analysis of rhenium(I) organometallic covalent binding to a model protein for drug development: Raw Diffraction Images (38 week soak). Zenodo

<p>The synchrotron raw diffraction images obtained at 38 weeks and wavelength 0.976 Å, illustrates the covalent coordination of the rhenium(I) tricarbonyl fragment to the His and Asp amino acid residues as well as movement along the solvent channels as described in the publication titled "Time-series analysis of rhenium(I) organometallic covalent binding to a model protein for drug development", written by Jacobs, Helliwell & Brink,<em> IUCrJ</em>, 2024, https://doi.org/10.1107/S2052252524002598.</p> <p>The raw diffraction images for the DLS data sets are made available at the Zenodo research data archive, as specified in the publication.</p>

Dataset for the article: A Family of Experiments to Study how Personality may Affect Software Development Effectiveness in Teams

<p>Raw Data of the article named "A Family of Experiments to Study how Personality may Affect Software Development Effectiveness in Teams"</p>

Suppl. Movie 1: Development when egg naturally detached from the stalk

<p>Samuel Boscq Thesis Chapter 2 Supplementary data</p>

Figure 6 in Development and function of plasmodesmata in zygotes of Fucus distichus

Figure 6: Microinjection of fluorescent tracers into sporophytes of Fucus distichus 10 days after fertilization. (A, C, E) Differential interference contrast microscope images of injected sporophytes. Arrows show the injected cells (B, D, F). Fluorescence microscope images of same sporophytes as in (A), (C), and (E). (A, B) Sporophyte injected with 3 kDa FITC-dextran. (C, D) Sporophyte injected with 10 kDa FITCdextran. (E, F) Sporophyte injected with 40 kDa FITC-dextran. Scale bar=100 µm.

Figure 2 in Development and function of plasmodesmata in zygotes of Fucus distichus

Figure 2: Germling of Fucus distichus 3 days after fertilization. (A) Overview of thallus and part of rhizoid. Arrow indicates the first division plane, and double arrows the border between thallus and rhizoid. (B) First cell division plane. Arrows indicate plasmodesmata. (C) Border between thallus and rhizoid. (D) Septum cell wall in the rhizoid tip. Scale bars=10 µm (A), 200 nm (B–D).

Figure 1 in Development and function of plasmodesmata in zygotes of Fucus distichus

Figure 1: The first cell division of a zygote of Fucus distichus. (A) Whole zygote. Arrow indicates the first division plane. (B) First cell division plane. Scale bars= 10 µm (A), 1 µm (B).

Figure 5 in Development and function of plasmodesmata in zygotes of Fucus distichus

Figure 5: Mature sporophyte of Fucus distichus from the field. (A) Medulla layer. Large vacuoles occupy centers of cells, and other organelles are appressed to the edge. Rectangle indicates area with pit field. (B) Cortex and meristoderm layers. Cells in the cortex contain vacuoles with different contents. (C) Pit field in wall between cortex cells (indicated by rectangle). (D–G) Consecutive serial sections of pit field shown in (C). Ovals in (D) and (F) indicate branched plasmodesmata. (H) Branched plasmodesmata from (D). (I) Branched plasmodesmata from (F). Scale bars=5 µm (A), 10 µm (B), 2 µm (C), 200 nm (D–G), 500 nm (H, I).

Figure 4 in Development and function of plasmodesmata in zygotes of Fucus distichus

Figure 4: Sporophyte of Fucus distichus 10 days after fertilization. (A) Overview of thallus. Beginning of differentiation of cell layers can be seen. (B) Outer and inner cell layers. N, nucleus. Rectangle indicates area of wall with pit field. (C) Enlarged image of pit field in cross wall between cells of outer layer (rectangle in B). (D) Pit fields in cell wall between outer and inner cell layers. (E) Pit field divided in two by an orthogonal cell wall. Scale bars=10 µm (A), 2 µm (B), 200 nm (C), 1 µm (D), 500 nm (E).

Figure 3 in Development and function of plasmodesmata in zygotes of Fucus distichus

Figure 3: Germling of Fucus distichus 5 days after fertilization. (A) Part of thallus. Nuclei (N) are seen in the centers of cells. Arrow indicates first cell division plane. Rectangles indicate areas shown in (B–D). (B) Longitudinal section of plasmodesmata. Arrows show plasmodesmata. (C) Transverse section of plasmodesmata. (D) Magnified image of (C). Scale bars=10 µm (A), 200 nm (B), 2 µm (C), 500 nm (D).

DEVELOPMENT OF THE AGRO-INDUSTRIAL COMPLEX OF RUSSIA AT THE PRESENT STAGE

<p><span>The article shows the development of agriculture in Russia at the present stage. It is agriculture that today is steadily one of the fastest growing sectors of the Russian economy. The production of certain products has been demonstrating historical records for a number of years, which has allowed Russia to become a prominent supplier to world markets. The growth of the agricultural sector has been facilitated by both natural factors (geographical location, large areas of agricultural land, vast water resources), investment inflows and improved management. The introduction of sanctions and government measures aimed at import substitution also contributed to the development of agricultural production in the country. This trend coincided with a significant increase in demand for basic foodstuffs due to population growth, primarily urban population growth, climate change, etc. It should be noted that the growth in demand contributes to the growth of long-term risks of instability in the world markets. </span></p>

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Research Trends in the Development of Generic Skills

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Dataset Used For Research On: Exploring Geographically Weighted Regression In Water Demand Forecasting For A Rapidly Developing City

<div> <p><span><span>Dataset Used For Research On: Exploring Geographically Weighted Regression In Water Demand Forecasting For A Rapidly Developing City</span></span></p> </div> <p> </p>