Contributors:AL-Alawi Mubarak, ahmed B, Mohamed Yasser
The uniqueness and the complexity of industrial construction project data have always been a challenge in research. The confidentiality of the data also contributes to the difficulty of avail data to researchers and the public, especially those projects related to industrial projects such as oil and gas facility projects. Therefore, data generators capable of generating a large number of simulated data have been a pressing demand by the research communities. This data describes a data generator that is capable of producing simulated industrial pipelines data.
The industrial pipelines data are complex in nature and the data generator is capable of generating a set of pipelines that preserves the topological and physical properties of the pipeline formation components. Each generated component has eight components. These are:
1. Line number
2. The type of pipeline branch
3. Component location (seq_in_branch)
4. The id of the previously connected component
5. Component type
6. Component diameter
7. Component length
8. The running direction (x, y, z) of the component
The data is a Python program code. It runs in a simple Python Integrated Development Environment (IDLE) and saves the generated data in a text file within the program code folder directory. The generated data can be used in studies related to the optimization of industrial pipelines fabrication, transportation, and on-site installation processes. The industrial pipelines data generator can allow different optimization algorithms to be tested under a large number of instance of problems. Also, the availability of the generator program code will enable the researchers to extend the development in the industrial pipeline data.
We investigated the association between pain and creatine kinase levels to assess the risk of muscle injury after a professional soccer match. 80 players from a professional soccer club in the first division of the Brazilian football league were evaluated during four full seasons. They were assessed 36 to 48 hours after the match and followed up for muscle injury over the next five days. The assessment consisted of blood sampling for CK analysis and application of The 4-point Verbal Rating Scale (“no pain” on the far left and “pain in a specific area of the muscle” on the far right). The data shows injury occurrence, injury location, CK concentration and pain score. It can be used to draw conclusions about muscle injury predictors.
The dataset consists of mobile laser scanning data of an exposed rock mass located at Mittagong in New South Wales, Australia. The images of the area and field data of structural discontinuity collected from compass, clinometer and measuring tape are also included. The dataset also includes dip and dip direction of discontinuity planes identified through several algorithms.
Data collected from U.S. workers. Survey delivered and sample obtained using Prolific (https://www.prolific.co/), with a sample representative of the U.S. population across age, gender and ethnicity. The high performance cycle questionnaire was developed by Borgogni and Dello Russo (2012). A self-report questionnaire developed by Onwezen, van Veldhoven and Biron (2014) was used to assess job performance. Data was transferred to SPSS AMOS for structural equation modeling analysis.
The shown results in this article are meant to be a demonstration of the
presented method. The data files included in this archive contain all raw data
used for plotting all the figures shown in the article.
The shown figures are based on three different, but representative experiments.
The file numbers represent our internal identification number. Use the following
key to resolve ids to material names and a short description of the material:
ID short name description
546214 EP-10SCF Bisphonel A epoxy (DER 331, DOW) filled with 10 vol.%
short carbon fiber (A385, Tenax), in-house manufactured
548671 PA6-10SCF-8Gr Polyamide 6 filled with 10 vol. % short carbon fibers
(A385, Tenax) and 8 vol.% graphite
(RGC39A, Superior Graphite), in-house manufactured
550187 PPS-40GR Polyphenylene sulfide filled with 40 wt.% graphite,
commercially available as TECACOMP PPS TC black 4084
To each id belong at least of two files, one with file extension 'proc' and one
with 'proc.header.yaml'. The proc file is a tab separated ascii table and
contains data recorded by our tribometer as well as data processed from them.
The yaml files contain all necessary header information of each respective proc
file of which especially the header name and (column) index is important for
Additionally, id 550187 contains files with extension 'xt' and 'xt.header.yaml'.
The xt file is tab separated ascii table and contains the temporally and
laterally resolved data of the luminance used for plotting the xt plot.
The yaml file, similar for the proc file, contain all necessary header
Information for importing the data files:
All header files follow a standardized serialization format called yaml. The
proc and xt files files are strict tab separated ascii tables. Therefore, all
data can be easily read by any programming language of your choice, e.g. python,
ruby or matlab. With additional effort, an import into excel or similar software
is also possible.
This was the data underlying the study, which included as follows:
Table S1 Putative targets in IJT
Table S2 Known therapeutic NSCLC-related targets
Table S3 Known therapeutic targets of IJT acting on NSCLC
Table S4 Topological features of all nodes in the compound-compound target network
Table S5 Protein-protein interactions of therapeutic targets of IJT on NSCLC
Table S6 Topological features of all nodes in the T-T network of putative IJT targets, known therapeutic target and interactional human proteins
Table S7 Topological features of hub nodes in theT-T network for IJT against NSCLC extracted from Fig. 4
Table S8 Significant pathways
Table S9 Molecular docking