cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/j3z5bmvmnd.6
title: GC-EI-MS datasets of trimethylsilyl (TMS) and tert-butyl dimethylsilyl (TBDMS) derivatives for development of machine learning-based compound identification approaches

description: In the field of environment and health studies, recent trends have focused on the identification of contaminants of emerging concern (CECs). This is a complex, challenging task, as compound databases (DBs) and mass spectral libraries (MSLs) concerning these compounds are very poor. This is particularly true for semi-polar organic contaminants that have to be derivatized prior to gas chromatography-mass spectrometry (GC-MS) analysis with electron impact ionization (EI), for which it is barely possible to find any records. In particular, there is a severe lack of datasets of GC-EI-MS spectra generated and made publicly available for the purpose of development, validation and performance evaluation of cheminformatics-assisted compound structure identification (CSI) approaches, including novel cutting-edge machine learning (ML) approaches.
In order to fill in this gap, we have generated 12 datasets of GC-EI-MS spectra of trimethylsilyl (TMS) and tert-butyldimethylsilyl (TBDMS) derivatives, which can be used to support machine learning-assisted CSI and to aid in cheminformatics-assisted identification of silylated derivatives in GC-MS laboratories working in the field of environment and health. The dataset includes:
- Four test datasets of raw (RAW) and processed (BS) GC-EI-MS spectra of TMS and TBDMS derivatives of CECs, given as .txt, .mgf and .msp files;
- Two sets of corresponding metadata (for TMS and TBDMS derivatives), which contain the IUPAC name, exact mass, molecular formula, InChI, InChIKey, SMILES and PubChemID of each CEC and the corresponding CEC-TMS or CEC-TBDMS derivative, where available;
- Metadata for four datasets of GC-EI-MS spectra of TMS derivatives derived from the NIST 17 Mass Spectral Library, including an initial dataset selected from the library and three datasets generated by applying consecutive filtering approaches. These metadata files contain common name, InChIKey, molecular formula, CAS number, exact mass, molecular weight, NIST number and ID of the GC-EI-MS spectra. TMS derivatives_0.1 refers to the original dataset derived from the NIST 17 Mass Spectral Library, TMS derivatives_1.1 to the dataset resulting after a first filtering step, TMS derivatives_2.1 after second and TMS derivatives_3.1 after third and final filtering step; and
- Metadata for four datasets of GC-EI-MS spectra of TBDMS derivatives derived from the NIST 17 Mass Spectral Library, including an initial dataset selected from the library and three datasets generated by applying three consecutive filtering steps. These metadata files contain the name, InChIKey, molecular formula, CAS number, exact mass, molecular weight, the NIST number and the ID of the GC-EI-MS spectra. TBDMS derivatives_0.1 refers to the original dataset derived from the NIST 17 Mass Spectral Library, TBDMS derivative_1.1 to the dataset resulting after a first filtering step, TBDMS derivative_2.1 after second and TBDMS_3.1 after third and final filtering step.
DOI: 10.17632/mfyj79476m.1
title: STUDY ON SUSTAINABLE DEVELOPMENT OF APPLE PRODUCTION AND TRADE IN NEPAL

description: The report aimed at analyzing the impact of economics on apple fruits based livelihoods in Nepal by reviewing the literature and compiling data analysis obtained from the ministry source. The study based on the apple fruit. Apple is an important fruit grown in Nepal and are available worldwide. The total production of apples in the world during the year 2016 was 89,329.1 thousand metric tonnes from an area of 5,293.34 thousand hectares with a productivity of 18.6 Mt/ha while in Nepal the total production was 41,012 metric tonnes from an area of 5,625 hectares with a productivity of 7.3 Mt/ha. During analysis, the result showed the import of apple was increasing compared to previous years from neighboring countries. It was observed that Nepal import 2.8 million metric ton of apples while export was 477 metric tons on average over the 6 fiscal years. Apple was a high-value cash crop grown in hill and mountain districts in Nepal at the elevations of roughly between 1800 and 2000 meters above sea level. Though the production and yield of apple were limited compared to other major fruits, its contribution to people’s livelihoods was significant as it has a high market value. Most of the apple growers were the small-scale producer in Nepal, therefore through analysis of Cobb-Douglas production function, the production of apple has the characteristics of decreasing returns to scale, the use efficiency of labor and capital has a positive impact. Moreover, the country has the great scope in producing apple but these have not been explored properly. The study reveals that the sustainable development of apple production was possible by supporting small-scale producers and vulnerable groups. This study also attempted to analyze the production, trade, and consumption and it's correlation coefficients from which the export and consumption correlation revealed that there was a significant negative correlation. Similarly, there was a negative correlation between production and import. In addition, the consumption trend of apple shows increasing and can be consumed fresh and processed into a value-added product. The results found in this study were an indicator to improve the domestic production and foreign trade. Finally, it was suggested to produce more apples by adopting systematic production and utilizing available resources to become self-sufficient and sustainable in the apple production. Keywords: Apple Production, Consumption, Trade, Correlation, Cobb-Douglas Model
DOI: 10.17632/w2wywtk5gy.1
title: Working Files of UAV AI Paper

description: Collated data of 641 UAV trips across cultivated area of 100 Sq Kilometers in Paderu and Araku Valley. Including Soil Moisture and Plant Growth. Static Data at the State Level is updated for the last four crop seasons
DOI: 10.17632/xkwjwvst66.1
title: Calculations of undetected untagged rhino that avoided us

description: To study the role that oxpeckers might play in helping rhino evade humans, we recorded the number of oxpeckers seen on two groups of the rhinos we encountered. Rhinos tagged with radio transmitters- which allowed us to track them using radiotelemetry while evading detection from oxpeckers- carried the bird on their backs more than half the time (56%). The untagged black rhinos we found, carried no oxpeckers most of the time (17%). Our data suggests that other untagged rhinos which carried the birds might have avoided encountering the us altogether. Using the difference we observed between oxpeckers on the tagged versus untagged rhino, we estimated that between forty to fifty percent of all possible black rhino encounters were thwarted by the presence of oxpeckers. Therefore, we used the average oxpecker number on tagged rhino as a baseline estimate for average oxpecker presence on the wider rhino population. We then used the difference in oxpecker number seen on tagged and untagged rhino to estimate the proportion and number of potential untagged rhino encounters that were prevented by resident oxpecker on rhino, given hypothetical numbers of occasions that rhino evaded us (Ru) during our activities in the study area to generate 100 rhino encounters (Rd: such that Ru + Rd = the total number of encounters possible). Data used to develop Figure 1, also see Quantification and Statistical analysis in STAR methods to see Equation 1 and how the number of untagged rhino with oxpecker that avoided us were generated. As expected, the % Ruo asymptotes towards 56% (the proportion of oxpecker present on rhino with horn implant transmitters) where Ru is large, i.e., ≥400, because 20% or fewer of all rhino, i.e., (Ru/ (Rd + Ru)) × 100 = 100/500, are assumed to have been detected.
DOI: 10.17632/k5m7fv49xv.1
title: A Tape-Reading Molecular Ratchet

description: Supplementary Data (1H & 13C NMR, CD and MS files) for "A Tape-Reading Molecular Ratchet"
DOI: 10.17632/6cbnvr4fwk.1
title: Bilirubin links heme metabolism to neuroprotection by scavenging superoxide (Vasavda et al., 2019)

description: Source code associated with "Bilirubin links heme metabolism to neuroprotection by scavenging superoxide" by Vasavda et al. (2019)
DOI: 10.17632/f8fwg4j9tw.1
title: AELAS: Automatic ELAStic property derivations via high-throughput first-principles computation

description: The elastic properties are fundamental and important for crystalline materials as they relate to other mechanical properties, various thermodynamic qualities as well as some critical physical properties. However, a complete set of experimentally determined elastic properties is only available for a small subset of known materials, and an automatic scheme for the derivations of elastic properties that is adapted to high-throughput computation is much demanding. In this paper, we present the AELAS code, an automated program for calculating second-order elastic constants of both two-dimensional and three-dimensional single crystal materials with any symmetry, which is designed mainly for high-throughput first-principles computation. Other derivations of general elastic properties such as Young’s, bulk and shear moduli as well as Poisson’s ratio of polycrystal materials, Pugh ratio, Cauchy pressure, elastic anisotropy and elastic stability criterion, are also implemented in this code. The implementation of the code has been critically validated by a lot of evaluations and tests on a broad class of materials including two-dimensional and three-dimensional materials, providing its efficiency and capability for high-throughput screening of specific materials with targeted mechanical properties.
DOI: 10.17632/m5jhkc3p9d.1
title: Ab initio computational database of the dielectric properties of oxides

description: Ab initio computational database of the dielectric properties of oxides. The database contains optimized structures, ionic and electronic dielectric tensors, and other properties in json format.
DOI: 10.17632/wpdkxnh8cf.2
title: The Primary data for Shidian meteorites

description: The Primary data for Shidian meteorites include mineral composition, bulk chemistry, whole rock oxygen and Cr isotopic compositions, reflectance spectrum, and density and porosity data.
DOI: 10.17632/7cznpvzv6r.1
title: VMM Malware Dataset

description: VMM Malware Dataset contains the system call traces of Malware and Virus program executions inside virtual machines, traced from the Xen Hypervisor. It also includes the system call traces of few Benign samples. It will be beneficial for the researchers who are interested in the development of IDS with Machine learning and deep learning models.
DOI: 10.17632/289m8hcgt2.2
title: Mass Transfer Solver Tool: A software to calculate mass transfer coefficients for Packed-bed Columns 

description: The Mass Transfer Solver Tool is a calculation software for gas-liquid mass transfer coefficients for random and structured packed-bed columns. This software refers to the work of Flagiello et al. (2021) entitled "A tool for mass transfer evaluation in packed-bed columns for chemical engineering students" and published in the scientific journal of Education for Chemical Engineers (https://doi.org/10.1016/j.ece.2021.08.001).

The MT Solver Tool is based on the use of the most acknowledged models available in the pertinent literature (Onda et al., 1968; Bravo et al., 1985, 1992; Billet and Schultes, 1993; Brunazzi and Paglianti, 1997; Olujić et al. , 2004; Hanley and Chen, 2012) to calculate the gas-side (ky), liquid-side (kx) and interfacial area (ae) coefficients separately.
The software includes a "Library File" where geometric data and model fitting parameters for 144 different packings in size and materials are available. The spreadsheet file "MT Solver" operating in default mode uses the data of the 144 packings available in the "Library File" to calculate the mass transfer coefficients. Futhermore, the software can also be operated in user-defined mode "User-defined MT Solver" in order to customize and expand its use when the considered packing is not included in the Library File.

The MT Solver Tool was also used in teaching activities in the academic year 2020-2021 for the Unit Operation and Sustainable Process Design courses of the Master's degree in Chemical Engineering, at the University of Naples Federico II.

All the instructions for use are given in the work: A tool for mass transfer evaluation in packed-bed columns for chemical engineering students (https://doi.org/10.1016/j.ece.2021.08.001).

Any system bugs, calculation errors deriving from the model equations or the parameters set in the library can be reported to the email address: domenico.flagiello@unina.it (Dr. Domenico Flagiello).
Suggestions for model equations updates or data and packing parameter values ​​included in the library (or new data packing) are also welcome.
DOI: 10.17632/v5jfhsvtmd.5
title: Roman Urdu Word Variations and Normalized Sentiment Review Dataset (RUWV-NSR)

description: We have developed two unique Roman Urdu datasets, translated into English. The first dataset focuses on Roman Urdu words and their spelling variations. This dataset is structured in an Excel file with five columns labeled "Var-1" to "Var-5," each representing up to five variations of Roman Urdu spellings for individual words. The final column, "common," contains the most frequently used spelling for each word. In total, this dataset includes 5,244 unique Roman Urdu words, which, when combined with their variations, amount to 19,527 words.
The second dataset contains Roman Urdu reviews, each labeled with a sentiment. Given the variability in Roman Urdu spellings found on the web, where users often create their own spelling variations, we have normalized the spelling of words across these reviews. This dataset is the first of its kind, containing the largest collection of Roman Urdu reviews, with a total of 28,090 reviews categorized into five sentiment classes.
This dataset is particularly valuable for analyzing Roman Urdu content in contexts such as online product reviews or Roman Urdu articles, which are becoming increasingly common. It offers significant potential for sentiment analysis and language processing applications.
DOI: 10.17632/5nswx78scs.1
title: New Venture Creation Research Dataset (1985-2020)

description: The new venture creation research and publication dataset, which was indexed by Scopus from 1985 to 2020. The dataset contains data authors, authors ID Scopus, title, year, source title, volume, issue, article number in Scopus, DOI, link, affiliation, abstract, index keywords, references, Correspondence Address, editors, publisher, conference name, conference date, conference code, ISSN, language, document type, access type, and EID.
DOI: 10.17632/84n882jk2d.1
title: Who Leads and Who Follows? The Cross-Border Peer Effect in Investment by Chinese and US Firms

description: Data and programs for "Who Leads and Who Follows? The Cross-Border Peer Effect in Investment by Chinese and US Firms" forthcoming in Journal of International Economics. Pre-publication version available at https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3807216
DOI: 10.17632/sywswj7djj.1
title: HighRPD

description: In order to meet the data needs for road pavement distress detection, we have created a standardized dataset road pavement distress named HighRPD, which consists of road pavement distress images captured from a drone perspective. This dataset maintains a uniform image resolution of 640x640 pixels, in alignment with the test dataset specifications for the YOLO v8 model. Meanwhile, informed by the prevalence of road pavement distress, the dataset HighRPD specifically targets road pavement distress classified into three fundamental categories: line, block, and pit. We utilized the Labelbox platform in combination with DarkLabel for constructing our dataset. In summary, a total of 11,696 road pavement images were successfully labeled, including 12,365 line annotations, 8,239 block annotations, and 1,412 pit annotations. 
The HighRPD dataset comprises two subfolders: one named 'images' and the other 'labels'. The 'images' folder contains pictures sized 640x640 pixels in JPG format, while the 'labels' folder contains txt files with labels formatted in the YOLO style. Each object is represented by a single line, formatted as 'class center_x center_y width height'. There are three classes: class 0 for lines, class 1 for blocks, and class 2 for pits. The coordinates (x_center, y_center, width, height) are normalized by dividing x_center and width by the image width, and y_center and height by the image height.
DOI: 10.17632/ddcrrrmxw9.1
title: QERaman: An open-source program for calculating resonance Raman spectra based on Quantum ESPRESSO

description: We present an open-source program QERaman that computes first-order resonance Raman spectroscopy of materials using the output data from Quantum ESPRESSO. Complex values of Raman tensors are calculated based on the quantum description of the Raman scattering from calculations of electron-photon and electron-phonon matrix elements, which are obtained by using the modified Quantum ESPRESSO. Our program also calculates the resonant Raman spectra as a function of incident laser energy for linearly- or circularly-polarized light. Hands-on tutorials for graphene and MoS2 are given to show how to run QERaman. All codes, examples, and scripts are available on the GitHub repository.
DOI: 10.17632/xt9hb8dzft.1
title: INET/BFA OHLCV JSE Test Data Samples

description: This test data set provides daily sampled asset allocation test data for Bond, Cash and Equity sector data-studies on the Johannesburg Stock Exchange. It is intended for educational and replication purposes. The data set is a combined test set of ALBI TRI (All Bond Total Return Index test data), JIBAR (Johannesburg Interbank Acceptance Rate Index test data), and JSE ICB (Index Classification Benchmark) total return data for the period 2005-2017. The data is stale and there is no intention to update the data. The data was prepared using INET/BFA data-interfaces under a once-off perpetual research data purchase agreement and post-processed in MATLAB. The data can be made current by updating it using INET/BFA, Datastream, Thomson-Reuters Tick History or Bloomberg Pro data interfaces. The data is not error free and is not fit for any particular commercial purpose given that it is out-of-date and provide "as-is" for research replication, teaching and learning. Use case: The data use case is for teaching and learning purposes, and to provide transparent standard re-usable test cases for machine learning and statistical finance applications relating to asset allocation studies on the JSE.
DOI: 10.17632/p4c49m3pvr.3
title: "GermanFakeNC" - German Fake News Corpus including manually fact-checked false statements

description: "GermanFakeNC" is a German Fake News Corpus including 490 texts which were retrieved from German alternative online media sources. Every fake statement in the text was verified claim-by-claim by authoritative sources (e.g. from local police authorities, scientific studies, the police press office, etc.). The time interval for most of the news is established from December 2015 to March 2018. Description of the .json file: Date: publication date of the article URL: URL of the website A maximum of three false statements are provided: False_Statement_[1-3]_Location: Location of the verified false statement - Title, Teaser or Text False_Statement_[1-3]_Index: The index numbers refer to the token (!) position / number. We tokenized the text with "spaCy" (the free open-source library for Python). Example: Title of Text: "The quick brown fox jumped over the lazy dog. The fox broke both his legs while jumping." False_Statement: The fox broke both his legs while jumping. "False_Statement_1_Location": "Title", "False_Statement_1_Index": "11-19" Ratio_of_Fake_Statements: Percentage of fake found in the article 1 = Text is based on true information. Up to 25% of the information in the text is false 2 = Up to 50% of the information in the text is false. The other statements in the article are factually accurate 3 = Up to 75% of the content non-factual and incorrect 4 = Pure fabrication with up to 100% false information in text 9 = Unclear, unverifiable Overall_Rating of the disinformation in text: range [0.1:1.0]. 0.1 no disinformation in text 0.2 0.3 0.4 0.5 neutral / ambivalent 0.6 0.7 0.8 0.9 1.0 strong disinformative text ====================================================================== The original sources retain the copyright of the data. You are allowed to use this dataset for research purposes only. For more question about the dataset, please contact: Inna Vogel, inna.vogel@sit.fraunhofer.de v1.01/09/2019
DOI: 10.17632/r3yjf35hzr.2
title: Shoplifting Dataset (2022) - CV Laboratory MNNIT Allahabad

description: Synthesized shoplifting dataset is created by ourselves in the CV laboratory of MNNIT Allahabad with the help of 32 Megapixel camera. The recorded videos are of 640x480 resolution and captured at frame rate of 30 frames per second. This dataset has clearly distinguishable person's normal and stealing actions. Our self-created dataset consists of two classes: 
1) Normal
2) Shoplifting
The normal class contains video clips that manifest activities like walking, inspecting shop items, etc. Other side, the shoplifting class has video clips representing object stealing actions by human being like putting store items under clothing or bags etc. 

Note: Dataset required pre-processing step to clean video scenes