cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/cmr4bcrj6j.1
title: Development of the fully Geant4 compatible package for the simulation of Dark Matter in fixed target experiments

description: The search for new comparably light (well below the electroweak scale) feebly interacting particles is an exciting possibility to explain some mysterious phenomena in physics, among them the origin of Dark Matter. The sensitivity study through detailed simulation of projected experiments is a key point in estimating their potential for discovery.

Several years ago we created the DMG4 package for the simulation of DM (Dark Matter) particles in fixed target experiments. The natural approach is to integrate this simulation into the same program that performs the full simulation of particles in the experiment setup. The Geant4 toolkit framework was chosen as the most popular and versatile solution nowadays.

The simulation of DM particles production by this package accommodates several possible scenarios, employing electron, muon or photon beams and involving various mediators, such as vector, axial vector, scalar, pseudoscalar, or spin 2 particles. The bremsstrahlung, annihilation or Primakoff processes can be simulated.

The package DMG4 contains a subpackage DarkMatter with cross section methods weakly connected to Geant4. It can be used in different frameworks.

In this paper, we present the latest developments of the package, such as extending the list of possible mediator particle types, refining formulas for the simulation and extending the mediator mass range. The user interface is also made more flexible and convenient.

In this work, we also demonstrate the usage of the package, the improvements in the simulation accuracy and some cross check validations.
DOI: 10.17632/k5xy4wstck.1
title: Gender Identity Stigma, Teachers’ Acceptance, and Parental Support as Predictors of Mental Health Among Self-Identified LGBT Senior High School Students

description: The study hypothesized that Gender Identity Stigma, Teachers' Acceptance, and Parental Support are predictors of Mental Health among self-identified LGBT senior high school students. The data shows that the predictive variables significantly predict the outcome variables. Interpretation of the data is based on the questionnaires manual which can be found online. Also, to better understand the data, the authors made an interpretation based on different research data. The data was gathered using Google form which was sent to the participants to which participants answered and submitted their responses.
DOI: 10.17632/kfp5fhgkvf.1
title: Compilation, Revision and Updating of the Global VAR (GVAR) Database, 1979Q2-2023Q3

description: This is the latest version of the Global VAR (GVAR) dataset - a global modelling framework for analyzing the international macroeconomic transmission of shocks while accounting for drivers of economic activity, interlinkages and spillovers between different countries, and the effects of unobserved or observed common factors. This dataset includes quarterly macroeconomic variables for 33 economies (log real GDP, y, the rate of inflation, dp, short-term interest rate, r, long-term interest rate, lr, the log deflated exchange rate, ep, and log real equity prices, eq, as well as quarterly data on commodity prices (oil prices, poil, agricultural raw material, pmat, and metals prices, pmetal), from 1979Q2 to 2023Q3. These 33 countries cover more than 90% of world GDP. 

It would be appreciated if use of the updated dataset could be acknowledged as: “Mohaddes, K. and M. Raissi (2024). Compilation, Revision and Updating of the Global VAR (GVAR) Database, 1979Q2-2023Q3. University of Cambridge: Judge Business School (mimeo)”.

For more details on Global VAR (GVAR) modelling, see also www.mohaddes.org/gvar
DOI: 10.17632/46htwnp833.4
title: Mango DMC and NIR spectra

description: These datasets contain Near-infrared (NIR) absorbance spectra of the wavelength range 309-149 nm of mango mesocarp with corresponding Dry Matter Content (DMC) values. 

The file "MangoDMC_NIR_Data_v3.csv" contains data as used in the publication "Achieving robustness across season, location and cultivar for a NIRS model for intact mango fruit dry matter content" (Postharvest Biology and Technology, 2020, 168:111202; https://www.sciencedirect.com/science/article/pii/S0925521420301629), with addition of data from an additional harvest season, as used in the publication "Evaluation of 1D Convolutional Neural Network in Estimation of Mango Dry Matter Content" (Spectrochimica Acta Part A 2024 311: 124003; https://www.sciencedirect.com/science/article/pii/S1386142524001690). This file is as presented in version 3 of this data repository.

The current version (4) has an additional file ".csv". This file augments the data of version 3 with data from additional instruments and seasons as used in the submitted thesis of Jeremy Walsh, 2024, Central Queensland University, "Deep Learning in Estimation of Fruit Attributes Using Near Infrared Spectroscopy".
DOI: 10.17632/46jtgzt4cb.2
title: Risk of fungal infection in patients with psoriasis receiving biologics: a retrospective single-center cohort study

description: Supplemental materials for "Risk of fungal infection in patients with psoriasis receiving biologics: a retrospective single-center cohort study"
DOI: 10.17632/kb36mjdmsn.1
title: Dataset for an Interpretable Classification Model for Systemic Lupus Erythematosus 

description: The dataset used in this study is from the Sultan Qaboos University Hospital’s Rheumatology clinic collected by (Al Sawafi S., 2021). It includes 214 Omani patient records from 2006 to 2019 that have met the entry criteria set by EULAR. Entry criteria require a positive Antinuclear Antibodies test (ANA test) after which the rest of the classification additive criteria are applied. Of the 219 patients 138 are diagnosed with SLE, this was also confirmed by a physician on case-by-case bases. The remaining 81 patients have other control diseases. The dataset includes demographic data, clinical data, and laboratory data.
We developed an early detection model for SLE with an interpretation functionality that establishes trust in prediction. SHAP interpretation tool was implemented to explain and justify individual predictions and thereby eliminate any risk of misclassification. Additionally, a minimum set of 13 early predictors achieved the highest scores of 0.95 AUC and 0.89 F-1 metric. With these scores, our model can reasonably predict the presence or absence of SLE. The features comprise demographic and clinical symptoms available at physicians at early stages. It was found that four clinical features had the highest influence on the prediction in addition to the patient’s age. 
Alopecia, renal, ACL, and hemolytic anemia are all indicators of lupus activity at varying rates, combined with the patient’s age and age-onset the model was able to establish a profile of the disease relative to Omanis. It was found that the four critical features are more frequent in other Arab cohorts and the model has the potential to be extended to include those ethnicities.
With such scores, our model can predict with reasonable certainty the presence and absence of SLE. This can alert physicians to investigate further with the help of immunological tests such as antinuclear antibodies test and Anti-dsDNA test. Future work includes training the model to categorize non-SLE patients into “possible-SLE” and “highly unlikely” that can help monitor patients suspected of developing SLE in the future. The symptom frequency also dictates that some features carry more weight in classification than other features, thus Class-Weight classification can be applied against normal classifiers to hopefully obtain better performance.
DOI: 10.17632/m96d4m4stg.1
title: Cotton Futures Price Series : US, China and India

description: The daily closing price of the cotton contracts traded at ICE, ZCE and MCX per 1000 kg of cotton.The price data for the MCX Cotton futures, ICE cotton futures and ZCE cotton futures were taken from the Bloomberg database.
DOI: 10.17632/jww53v3ycd
title: Endothelial mTORC2-Foxo1 axis is an iron-responsive sensor to govern systemic iron homeostasis

description: uncropped Western blot data and original data for all figures
DOI: 10.17632/dd62d5hyzr.2
title: The key material properties of ultra-high-performance concrete (UHPC)

description: The dataset was developed to predict the compressive strength, flexural strength, workability, and porosity of Ultra-high-performance concrete (UHPC) in order to expedite the design process of UHPC. The dataset has 1,228 experimental data covering 24 mix design variables of UHPC. The mix design variables can be grouped into four categories: (1) Category 1: variables of the cementitious systems, (2) Category 2: variables of the reinforcing fibers, (3) Category 3: curing time, and (4) Category 4: dimensions of the test specimens. For more information about the development of the datasets, please refer to the accompanying research article: Soroush Mahjoubi, Weina Meng, Yi Bao, Auto-tune learning framework for prediction of flowability, mechanical properties, and porosity of ultra-high-performance concrete (UHPC), Applied Soft Computing, 2021, 108182. https://doi.org/10.1016/j.asoc.2021.108182.
DOI: 10.17632/z8phkgphm9.1
title: Black Swan events in the financial market: A network approach

description: The data set consists of 483 stocks that were continuously traded on the S&P 500 Index in the period from June 28, 2016 to August 9, 2023, and each stock has 1,791 data points of the daily closing price adjusted for splits and dividends. Sample data are separated into two subsets: the stabilization period before the market crash and the market disruption period during the COVID-19 pandemic and the Russian-Ukrainian war. The cut-off point for the separation of the two sub-periods was set on January 20, 2020. Therefore, the stabilization period is defined between June 29, 2016 and January 17, 2020; the market disruption period is set between January 21, 2020 and August 09, 2023. The split between the two periods is equal, with 895 time series in each period (approximately 3.5 years). Companies are classified into 11 economic sectors according to the classification of Yahoo Finance. These historical data were collected from Yahoo Finance (https://finance.yahoo.com; accessed on 10.09.2023). The data set contains two matrices of cross-correlation networks of stock returns, based on the minimal spanning tree approach for the aforementioned time periods.
DOI: 10.17632/4gzzc9k49n.3
title: FOSD Female Speech Dataset

description: This is FOSD-based Female Speech Dataset which is useful for creating text-to-speech model. It comprises of 7637 audio files totalling more than 9.5 recording hours. All files are in *.wav format (16 kHz sampling rate, 32-bit float, mono). This dataset is useful for various TTS-related applications. THE DATA OR SOFTWARE IS PROVIDED “AS IS”, WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE DATA OR SOFTWARE OR THE USE OR OTHER DEALINGS IN THE DATA OR SOFTWARE. Patent and trademark rights are not licensed under this FPT Public License.
DOI: 10.17632/mfpvmk8cnm.1
title: Ethiopian Crop Type 2020 (EthCT2020) dataset

description: A detailed description of the EthCT2020 dataset is provided in the journal (Data in Brief) article "Ethiopian Crop Type 2020 (EthCT2020) dataset: Crop type data for environmental and agricultural remote sensing applications in complex Ethiopian smallholder wheat-based farming systems (Meher season 2020/21)".

For the 2020/21 main cropping season, the Ethiopian Crop Type 2020 (EthCT2020) dataset compiled from multiple sources provides 2,793 harmonized, quality-controlled, and georeferenced in-situ samples on annual crop types (7 crop groups; 22 crop classes) at smallholder field level across the complex and highly fragmented agricultural landscape of Ethiopia. The focus was on rainfed, wheat-based farming systems.

Sources:
a) Nationwide ground data collection campaign using ODK and GPS (GDCC),
b) Wheat Rust Toolbox, a database for field disease surveillance and monitoring using ODK (WRTB), and
c) CIMMYT farm household survey database (FHSD).
DOI: 10.17632/n6xg5fzsbv.1
title: UNIBO Powertools Dataset

description: The UNIBO Powertools Dataset has been collected in a laboratory test by an Italian Equipment producer. The cycling experiments are designed to analyze different cells intended for use in various cleaning equipment such as vacuum and automated floor cleaners. The vast dataset is composed of 27 batteries. The main features of the dataset are: (1) the use of batteries from different manufacturers, (2) cells with several nominal capacities, (3) cycling is performed until the cell's end-of-life and thus data regarding the cell at different life stages are produced. Three types of tests have been conducted. (I) The standard test, where the battery was discharged at 5A current in main cycles. (II), the high current test, where the battery was discharged at 8A current in main cycles. (III), the preconditioned test, where the battery cells are stored at 45°C environments for 90 days before conducting the test. During discharge, the sampling period is 10 seconds. The experiments were conducted using the following procedure: (1) Charge cycle: Constant Current-Constant Voltage (CC-CV) at 1.8A and 4.2V (100mA cut-off ) (2) Discharge cycle: Constant Current until cut-off voltage (2.5V) (3) Repeat steps 1 and 2 (main cycle) 100 times (4) Capacity measurement: charge CC-CV 1A 4.2V (100mA cut-off ) and discharge CC 0.1A 2.5V (5) Repeat the above steps until the end of life of the battery cell Data are described in data-description.md test_result.csv contains all the records but the last one of each charge/discharge run. test_result.csv contains the last record of each run. A python file for loading data is available at https://github.com/KeiLongW/battery-state-estimation If you use this dataset, please cite our paper: Kei Long Wong, Michael Bosello, Rita Tse, Carlo Falcomer, Claudio Rossi, Giovanni Pau. 2021. Li-Ion Batteries State-of-Charge Estimation Using Deep LSTM at Various Battery Specifications and Discharge Cycles. In Conference on Information Technology for Social Good (GoodIT ’21), September 9–11, 2021, Roma, Italy. ACM, New York, NY, USA, 7 pages. https://doi.org/10.1145/3462203.3475878
DOI: 10.17632/t6j2h22jpx.1
title: PlantaeK: A leaf database of native plants of Jammu and Kashmir

description: Computer vision can predominantly be focused to design the strategies for the conservation of the plants. Previous decade’s trends and the current prevailing incidents with respect to global warming, forest fires, and famines act as potential indicators of how much nature is destroyed by human activities. Plants are vitally used in foodstuff, medicine, industry and as well for environmental protection. However, due to lack of resources and knowledge, it is difficult to recognize different plant species, plant diseases, etc. Nowadays modern equipment’s are being designed to address these issues. So considering the challenges, demands, we have constructed a database of different plants. The plants taken for study are the native plants of the Kashmir region of India. The climate of Kashmir remains chilling for a few months and pleasant for the rest of the year. Eight different plants namely Apple, Apricot, Cherry, Cranberry, Grapes, Peach, Pear, and Walnut are selected for the study based on their commercial and medicinal usage. The leaf is the primary object of reference taken for making the database, as they grow much earlier than fruits as well as the other plant parts. For each plant two types of leaves are selected, one healthy and the other diseased. Considering the natural conditions under which the farmers or the agriculturists have to work, the images are captured in broad daylight under the auto mode with the Nikon D-SLR digital camera with an ISO Speed = 100, Aperture = F/5.6, Flash = Not Fired, Shutter Speed = 1/640. All the images are captured by an 18-55 mm lens and are in .JPG format. The leaves are divided into two major classes A and B respectively. The two major classes were then divided into 16 sub classes i.e., eight healthy and eight diseased. The symbol “h” e.g., plant-name_h001 in the images represent healthy images and “d” i.e., plant-name_d001 represents the diseased images. The images are labeled, resized and classified into different classes. The class of healthy images comprises of a total of 1223 images and the diseased images constitute of a total of 934 images. Thus a total of 2157 images were selected from the captured images to sew up this database. Every little step towards a positive perspective marks the beginning of the era of growth with kindness.
DOI: 10.17632/mrh2rbtmbm.1
title: Peran Masyarakat Dalam Penegakan Hukum di Indonesia

description: Penegakan  hukum merupakansarana efektif  untuk  mencapai  tujuan  hukum.  Karena  itusudah  semestinya seluruh  tenaga  dikerahkan  agar  hukum  mampu  bekerja  untuk  mewujudkan  nilai-nilai  moral  dalam  hukum. Dalam  konteks penegakan hukumdi  Indonesia,  maka  peran aktif masyarakat  tentunya  tidak mungkin  dapat dipisahkan. Di Indonesia sendiri masyarakat memiliki peran penting dalamsetiap upaya yang dilakukan oleh negarauntuk  menegakan  hukum.Penelitian  ini  menggunakan  metode  tinjauan  literature (library  research) yaitu penelitian  yangdidasarkan  pada pendapatan-pendapat  ahli. Hasil  penelitian  ini  menunjukan,  bahwa masyarakat  juga  merupakan  bagaian  terpenting  dalam  sebuah  negara,  karena  masyarakat  memiliki  peran untuk  pemeliharaan dan  dukungan  untuk  mencapai  tujuan  dari  suatu negara.   Untuk  mengupayakan adanya penegakan  hukum  yang  berkeadilan  di  Indonesia,  sangat  diperlukan  kepekaan  dan  keaktifan  masyarakat dalam  menghargai  hak  yang  dimiliki  oleh  setiap  orang,  meningkatkan  etika  dan  moral  dengan  kesadaran sendiri, serta menunaikan kewajiban dalam bermasyarakat. Partisipasi masyarakat merupakan unsur penting dalam   perlindugan   dan   penegakan   hukum.   Masyarakat   yang   aktif   dapat   membantu   menghilangkan kemungkinan  terjadinya  pengabaian  terhadap  kasus  hukum.  Peran  masyarakat  dalam  penegakan  hukumdi Indonesia dapat dilakukan  dengan  dua  Jalan,  yaitu  pengawasan  aktif  masyarakat harus dalam  perlindungan dan control terhadap penegakan hukum. Bentuk partisipasi warga negara dalam perlindungan dan penegakan hukum  didalam  lingkungan  sekitarnya  bisa  berupa  masyarakat  aktif  dalam  melaporkan  dugaan  tindakan kriminal yang ada disekitarnya.
DOI: 10.17632/zpmd8krs2b.1
title: Scopus bib file

description: Scopus raw data in bib and excel format
DOI: 10.17632/m8zr9bdxrg.3
title: Data for "The first quantitative study of stereotyped and potential signature whistle production by Indo-Pacific humpback dolphins (Sousa chinensis) in the northern South China Sea""

description: This excel document contains all the data related to the identification and analysis of stereotyped and potential signature whistles for the study entitled "The first quantitative study of stereotyped and potential signature whistle production by Indo-Pacific humpback dolphins (Sousa chinensis) in the northern South China Sea".
DOI: 10.15156/bio/sh0035455.10fu
title: SH0035455.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh0035456.10fu
title: SH0035456.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh0035457.10fu
title: SH0035457.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh0035458.10fu
title: SH0035458.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.