cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.20740912.v1
title: Data constraints over event logs

description: This dataset contains the data constraints that are extracted by visual inspection and analysis of the following event logs: 1- BPIC13cp( https://doi.org/10.4121/uuid:c2c3b154-ab26-4b31-a0e8-8f2350ddac11) 2- BPIC13inc( https://doi.org/10.4121/uuid:500573e6-accc-4b0c-9576-aa5468b10cee) 3- BPIC2015f1 (https://doi.org/10.4121/uuid:a0addfda-2044-4541-a450-fdcc9fe16d17) 4- BPIC2017 (https://doi.org/10.4121/12705737.v2). <br> These constraints can be used for event correlation using EC-SA-Data (https://github.com/DinaBayomie/EC-SA-Data/releases/tag/EC-SA-Data)
DOI: 10.6084/m9.figshare.20696242.v1
title: RAW DATA.xlsx

description: A comparative analysis of the serum biochemical parameters, immune response, antioxidant capacity, and glucose and lipid metabolism of grazing Mongolian sheep in cold and warm seasons was conducted. <br>
DOI: 10.6084/m9.figshare.20741395.v1
title: DADOS.csv

description: Current density responses. Test data
DOI: 10.6084/m9.figshare.20741395
title: DADOS.csv

description: Current density responses. Test data
DOI: 10.5439/1515170
title: ARM X-SAPR Mapped Moments to a Cartesian Grid (MMCG)

description: Mapped Moments to a Cartesian Grid (MMCG), is taking geographic or polar coordinates and mapping the radar data to a Cartesian grid. Such a method, is useful to data users who are not familiar with radar coordinates. It is also useful to map radar data from radar coordinates to Cartesian coordinates, because some schemes for data assimilation require a level of objective analysis.
DOI: 10.5439/1637942
title: Planetary Boundary Layer Height derived from MPL data using Sawyer-Li method

description: Sawyer and Li (2013) developed a technique to derive the PBL height from micropulse lidar (MPL) backscatter measurements using combined wavelet covariance transform and iterative curve-fitting methods. The wavelet covariance transform method applies a Haar wavelet function to MPL backscatter signals (Brooks et al., 2003).
DOI: 10.6084/m9.figshare.20696242
title: Comparisons of Physiological Parameters in Grazing Sheep Between the Cold and Warm Season

description: A comparative analysis of the serum biochemical parameters, immune response, antioxidant capacity, and glucose and lipid metabolism of grazing Mongolian sheep in cold and warm seasons was conducted. <br>
DOI: 10.6084/m9.figshare.20696242.v3
title: Comparisons of Physiological Parameters in Grazing Sheep Between the Cold and Warm Season

description: A comparative analysis of the serum biochemical parameters, immune response, antioxidant capacity, and glucose and lipid metabolism of grazing Mongolian sheep in cold and warm seasons was conducted. <br>
DOI: 10.6084/m9.figshare.20696242.v2
title: Physiological, Immune Response, Antioxidant Capacity and Lipid Metabolism Changes in Grazing Sheep during the Cold Season

description: A comparative analysis of the serum biochemical parameters, immune response, antioxidant capacity, and glucose and lipid metabolism of grazing Mongolian sheep in cold and warm seasons was conducted. <br>
DOI: 10.5281/zenodo.7034138
title: Observation data of a PV site and a Gobi site

description: This is a supplementary file for the submitted paper "The characteristics and parameterizations of the surface albedo of utility-scale photovoltaic plant in the Gobi Desert".
DOI: 10.5281/zenodo.7034139
title: Observation data of a PV site and a Gobi site

description: This is a supplementary file for the submitted paper "The characteristics and parameterizations of the surface albedo of utility-scale photovoltaic plant in the Gobi Desert".
DOI: 10.5281/zenodo.7036447
title: Observation data of a PV site and a Gobi site

description: This is a supplementary file for the submitted paper "The characteristics and parameterizations of the surface albedo of utility-scale photovoltaic plant in the Gobi Desert".
DOI: 10.25917/bgfs-nr77
title: Data and Matlab scripts for article "Distributed Water Storage Measured by Fiber Optic Distributed Acoustic Sensing" submitted to Geophysical Research Letters by Becker, Harris, Pevzner
DOI: 10.6084/m9.figshare.20741419
title: Event-time constraints

description: This dataset contains the event-time constraints that are extracted by computing the quartiles (Q1 and Q3) of the activities execution time for the following event logs: 1- BPIC13cp( https://doi.org/10.4121/uuid:c2c3b154-ab26-4b31-a0e8-8f2350ddac11) 2- BPIC13inc( https://doi.org/10.4121/uuid:500573e6-accc-4b0c-9576-aa5468b10cee) 3- BPIC2015f1 (https://doi.org/10.4121/uuid:a0addfda-2044-4541-a450-fdcc9fe16d17) 4- BPIC2017 (https://doi.org/10.4121/12705737.v2). These constraints can be used for event correlation using EC-SA-Data (https://github.com/DinaBayomie/EC-SA-Data/releases/tag/EC-SA-Data)
DOI: 10.6084/m9.figshare.20741419.v1
title: Event-time constraints

description: This dataset contains the event-time constraints that are extracted by computing the quartiles (Q1 and Q3) of the activities execution time for the following event logs: 1- BPIC13cp( https://doi.org/10.4121/uuid:c2c3b154-ab26-4b31-a0e8-8f2350ddac11) 2- BPIC13inc( https://doi.org/10.4121/uuid:500573e6-accc-4b0c-9576-aa5468b10cee) 3- BPIC2015f1 (https://doi.org/10.4121/uuid:a0addfda-2044-4541-a450-fdcc9fe16d17) 4- BPIC2017 (https://doi.org/10.4121/12705737.v2). These constraints can be used for event correlation using EC-SA-Data (https://github.com/DinaBayomie/EC-SA-Data/releases/tag/EC-SA-Data)
DOI: 10.5281/zenodo.7034773
title: Revisiting Machine Learning based Test Case Prioritization for Continuous Integration

description: Aborted version
DOI: 10.5281/zenodo.7034635
title: Revisiting Machine Learning based Test Case Prioritization for Continuous Integration

description: Aborted version
DOI: 10.6084/m9.figshare.20736760
title: The files contain codes for the presence of fragments from 18 chicken breeds obtained by RFLP genotyping

description: The files contain codes for the presence of fragments from 18 chicken breeds obtained by RFLP genotyping. File 1: 0-Ts, 1-LGG, 2-LMF, 3-NH File 2: 0-YC, 1-OMF, 2-UG, 3-MG File 3:0-RW,1-FS,2-BL,3-CBl, File 4:0-NH,1-RIR,2-YC,3-ZS, File 5:0-SL,1-Pm,2-ZS,3-RIR, File 6:0-LMF,1-LGG,2-Pu,3-ABS, Rhode Island Red (RIR), Russian White (RW), Cochin Blue (CBl), Faverolles Salmon (FS), Moscow Game (MG), New Hampshire (NH), Sussex Light (SL), Uzbek Game (UG), Orloff Mille Fleur (OMF), Yurlov Crower (YC), Pushkin (Pu), Tsarskoye Selo (Ts), Leningrad Golden-and -gray (LGG), Leningrad Mille Fleur (LMF), Zagorsk Salmon (ZS), Pervomai (Pm), Australorp Black Speckled (ABS), and Brahma Light (BL).
DOI: 10.6084/m9.figshare.20736760.v1
title: The files contain codes for the presence of fragments from 18 chicken breeds obtained by RFLP genotyping

description: The files contain codes for the presence of fragments from 18 chicken breeds obtained by RFLP genotyping. File 1: 0-Ts, 1-LGG, 2-LMF, 3-NH File 2: 0-YC, 1-OMF, 2-UG, 3-MG File 3:0-RW,1-FS,2-BL,3-CBl, File 4:0-NH,1-RIR,2-YC,3-ZS, File 5:0-SL,1-Pm,2-ZS,3-RIR, File 6:0-LMF,1-LGG,2-Pu,3-ABS, Rhode Island Red (RIR), Russian White (RW), Cochin Blue (CBl), Faverolles Salmon (FS), Moscow Game (MG), New Hampshire (NH), Sussex Light (SL), Uzbek Game (UG), Orloff Mille Fleur (OMF), Yurlov Crower (YC), Pushkin (Pu), Tsarskoye Selo (Ts), Leningrad Golden-and -gray (LGG), Leningrad Mille Fleur (LMF), Zagorsk Salmon (ZS), Pervomai (Pm), Australorp Black Speckled (ABS), and Brahma Light (BL).
DOI: 10.25574/51750
title: Chandra X-ray Observatory ObsId 51750
DOI: 10.25574/51755
title: Chandra X-ray Observatory ObsId 51755
DOI: 10.25574/51762
title: Chandra X-ray Observatory ObsId 51762
DOI: 10.25574/51773
title: Chandra X-ray Observatory ObsId 51773
DOI: 10.25574/51781
title: Chandra X-ray Observatory ObsId 51781
DOI: 10.25574/51798
title: Chandra X-ray Observatory ObsId 51798
DOI: 10.25574/51804
title: Chandra X-ray Observatory ObsId 51804
DOI: 10.25574/51810
title: Chandra X-ray Observatory ObsId 51810
DOI: 10.25574/51815
title: Chandra X-ray Observatory ObsId 51815
DOI: 10.25574/51820
title: Chandra X-ray Observatory ObsId 51820
DOI: 10.25574/51825
title: Chandra X-ray Observatory ObsId 51825
DOI: 10.25574/51829
title: Chandra X-ray Observatory ObsId 51829
DOI: 10.25574/51833
title: Chandra X-ray Observatory ObsId 51833
DOI: 10.25574/51837
title: Chandra X-ray Observatory ObsId 51837
DOI: 10.25574/51842
title: Chandra X-ray Observatory ObsId 51842
DOI: 10.25574/51847
title: Chandra X-ray Observatory ObsId 51847
DOI: 10.25574/51852
title: Chandra X-ray Observatory ObsId 51852
DOI: 10.25574/51859
title: Chandra X-ray Observatory ObsId 51859
DOI: 10.25574/51864
title: Chandra X-ray Observatory ObsId 51864
DOI: 10.25574/51868
title: Chandra X-ray Observatory ObsId 51868
DOI: 10.25574/51873
title: Chandra X-ray Observatory ObsId 51873
DOI: 10.25574/51877
title: Chandra X-ray Observatory ObsId 51877
DOI: 10.25574/51888
title: Chandra X-ray Observatory ObsId 51888
DOI: 10.25574/51900
title: Chandra X-ray Observatory ObsId 51900
DOI: 10.25574/51906
title: Chandra X-ray Observatory ObsId 51906
DOI: 10.25574/51912
title: Chandra X-ray Observatory ObsId 51912
DOI: 10.25574/51918
title: Chandra X-ray Observatory ObsId 51918
DOI: 10.25574/51921
title: Chandra X-ray Observatory ObsId 51921
DOI: 10.25574/51927
title: Chandra X-ray Observatory ObsId 51927
DOI: 10.25574/51934
title: Chandra X-ray Observatory ObsId 51934
DOI: 10.25574/51940
title: Chandra X-ray Observatory ObsId 51940
DOI: 10.25574/51946
title: Chandra X-ray Observatory ObsId 51946
DOI: 10.25574/51950
title: Chandra X-ray Observatory ObsId 51950
DOI: 10.25574/51954
title: Chandra X-ray Observatory ObsId 51954
DOI: 10.25574/51958
title: Chandra X-ray Observatory ObsId 51958
DOI: 10.25574/51962
title: Chandra X-ray Observatory ObsId 51962
DOI: 10.25574/51966
title: Chandra X-ray Observatory ObsId 51966
DOI: 10.25574/51971
title: Chandra X-ray Observatory ObsId 51971
DOI: 10.25574/51987
title: Chandra X-ray Observatory ObsId 51987
DOI: 10.25574/51997
title: Chandra X-ray Observatory ObsId 51997
DOI: 10.5281/zenodo.7036469
title: Revisiting Machine Learning based Test Case Prioritization for Continuous Integration

description: Aborted version
DOI: 10.6084/m9.figshare.20741848
title: Data

description: The mechanical response of battery-pack systems (BPSs) under crush and vibration conditions is an important research topic in automotive engineering. A multi-objective optimization design involving multiple operating conditions is developed to imitate real complex road conditions. In this study, a dual-objective optimization method based on a multi-objective genetic algorithm is proposed to evaluate the crushing stress of BPS modules and the vibration fatigue life of a BPS.
DOI: 10.6084/m9.figshare.20741848.v2
title: Data

description: The mechanical response of battery-pack systems (BPSs) under crush and vibration conditions is an important research topic in automotive engineering. A multi-objective optimization design involving multiple operating conditions is developed to imitate real complex road conditions. In this study, a dual-objective optimization method based on a multi-objective genetic algorithm is proposed to evaluate the crushing stress of BPS modules and the vibration fatigue life of a BPS.
DOI: 10.34740/kaggle/dsv/4141609
title: Russian Invasion of Ukraine
DOI: 10.6084/m9.figshare.20742248
title: Additional file 2 of Modeling exercise using optogenetically contractible Drosophila larvae

description: Additional file 2: Supplementary Table 1. Identification of Differentially Expressed Genes (DEGs) in acute exercise compared to controls. List of differentially expressed genes in exercised body wall muscle compared to controls.
DOI: 10.6084/m9.figshare.20742248.v1
title: Additional file 2 of Modeling exercise using optogenetically contractible Drosophila larvae

description: Additional file 2: Supplementary Table 1. Identification of Differentially Expressed Genes (DEGs) in acute exercise compared to controls. List of differentially expressed genes in exercised body wall muscle compared to controls.
DOI: 10.6084/m9.figshare.20742251
title: Additional file 3 of Modeling exercise using optogenetically contractible Drosophila larvae

description: Additional file 3: Supplementary Table 2. Identification of upregulated genes within the multiple GO terms related to morphogenesis. List of all upregulated genes of at least 1.5 fold change within the multiple GO terms that are related to morphogenesis.
DOI: 10.6084/m9.figshare.20742251.v1
title: Additional file 3 of Modeling exercise using optogenetically contractible Drosophila larvae

description: Additional file 3: Supplementary Table 2. Identification of upregulated genes within the multiple GO terms related to morphogenesis. List of all upregulated genes of at least 1.5 fold change within the multiple GO terms that are related to morphogenesis.
DOI: 10.6084/m9.figshare.20742262
title: Additional file 1 of Measles incidence in South Africa: a six-year review, 2015—2020

description: Additional file 1: Supplementary Table 1. Datasets analysed during the study.
DOI: 10.6084/m9.figshare.20742262.v1
title: Additional file 1 of Measles incidence in South Africa: a six-year review, 2015—2020

description: Additional file 1: Supplementary Table 1. Datasets analysed during the study.
DOI: 10.5281/zenodo.7036479
title: Supplementary materials of the paper entitled: "Generating Natural Language Requirements via Adversarial Examples in Deep Learning"

description: Supplementary materials of the paper entitled: "Generating Natural Language Requirements via Adversarial Examples in Deep Learning" File A: Datasets (.txt) A1: Webex A2: Zoom A3: Teams A4: Word A5: Power Point A6: Excel File B: Python Code (Both Ours and Baseline) B1: adversarial_samples.ipynb B2: Baseline.ipynb FIle C: Result Tables (.xlsx) C1: Table of Perturbed outputs in WebEx C2: Table of Perturbed outputs in Zoom C3: Table of Perturbed outputs in Teams C4: Table of Perturbed outputs in Word C5: Table of Perturbed outputs in Power Point C6: Table of Perturbed outputs in Excel (Excel) File D: Trend of Adversarial Shifts (Graphs) D1: Adversarial shifts of office suit (LSTM) D2: Adversarial shifts of video conferencing suit (LSTM) D3: Non-Adversarial shifts of office suit (LSTM) D4: Non-Adversarial shifts of video conferencing suit(LSTM) D5: Adversarial shifts of office suit (GRU) D6: Adversarial shifts of video conferencing suit (GRU) D7: Non-Adversarial shifts of office suit (GRU) D8: Non-Adversarial shifts of video conferencing suit(GRU) D9: Adversarial shifts of office suit (Bi-LSTM) D10: Adversarial shifts of video conferencing suit (Bi-LSTM) D11: Non-Adversarial shifts of office suit (Bi-LSTM) D12: Non-Adversarial shifts of video conferencing suit(Bi-LSTM) File E: Adversarial Examples (.pdf) E1: Adversarial vs Original in WebEx E2: Adversarial vs Original in Zoom E3: Adversarial vs Original in Teams E4: Adversarial vs Original in Word E5: Adversarial vs Original in Power Point E6: Adversarial vs Original in Excel File F: Questionnaire <br> <br> <br> <br> <br> <br>
DOI: 10.5281/zenodo.7036478
title: Supplementary materials of the paper entitled: "Generating Natural Language Requirements via Adversarial Examples in Deep Learning"

description: Supplementary materials of the paper entitled: "Generating Natural Language Requirements via Adversarial Examples in Deep Learning" File A: Datasets (.txt) A1: Webex A2: Zoom A3: Teams A4: Word A5: Power Point A6: Excel File B: Python Code (Both Ours and Baseline) B1: adversarial_samples.ipynb B2: Baseline.ipynb FIle C: Result Tables (.xlsx) C1: Table of Perturbed outputs in WebEx C2: Table of Perturbed outputs in Zoom C3: Table of Perturbed outputs in Teams C4: Table of Perturbed outputs in Word C5: Table of Perturbed outputs in Power Point C6: Table of Perturbed outputs in Excel (Excel) File D: Trend of Adversarial Shifts (Graphs) D1: Adversarial shifts of office suit (LSTM) D2: Adversarial shifts of video conferencing suit (LSTM) D3: Non-Adversarial shifts of office suit (LSTM) D4: Non-Adversarial shifts of video conferencing suit(LSTM) D5: Adversarial shifts of office suit (GRU) D6: Adversarial shifts of video conferencing suit (GRU) D7: Non-Adversarial shifts of office suit (GRU) D8: Non-Adversarial shifts of video conferencing suit(GRU) D9: Adversarial shifts of office suit (Bi-LSTM) D10: Adversarial shifts of video conferencing suit (Bi-LSTM) D11: Non-Adversarial shifts of office suit (Bi-LSTM) D12: Non-Adversarial shifts of video conferencing suit(Bi-LSTM) File E: Adversarial Examples (.pdf) E1: Adversarial vs Original in WebEx E2: Adversarial vs Original in Zoom E3: Adversarial vs Original in Teams E4: Adversarial vs Original in Word E5: Adversarial vs Original in Power Point E6: Adversarial vs Original in Excel File F: Questionnaire <br> <br> <br> <br> <br> <br>
DOI: 10.14457/tu.the.2021.496
title: A 1064-nm picosecond laser for the treatment of keratosis pilaris: a randomized, prospective, comparative study

description: Keratosis pilaris is a common skin disorder characterized by small keratotic papules on the proximal extremities; yet, very few treatment options are currently available, with mostly unpredictable and unsatisfactory results. Picosecond laser has been proven to be effective for the treatment of pigmented skin lesion and skin rejuvenation but has not been studied for the treatment of KP. This study aimed to evaluate the efficacy and safety of picosecond laser for the treatment of KP. Fifteen patients diagnosed with keratosis pilaris on both upper arms were enrolled, but twelve patients completed the study successfully. All patients were treated with a 1064-nm picosecond laser only one side of the upper arm randomly for three sessions at 4-week interval. Clinical assessment was evaluated by two dermatologists through taken digital photograph. The objective outcomes were assessed using Antera3D. Patient satisfaction score on overall improvement, pain score and adverse effects were also evaluated. The results demonstrated statistically significant of the change in median of overall improvement at week 4, week 8, and week 12 with p-value of 0.003, 0.013, 0.006 respectively on the picosecond laser treated side, while the control side showed no significant improvement (p&gt;0.05). The side effects included mild to moderate erythema, burning sensation, itching, and pinpoint bleeding. One patient (8.33%) had post-inflammatory hyperpigmentation on picosecond laser treated side at week 12. No hypopigmentation, infection or scarring was observed throughout the study. In conclusion, a 1064-nm picosecond laser can be served as a safe modality and efficacious for keratosis pilaris treatment.
DOI: 10.14457/tu.the.2021.497
title: The efficacy and safety of topical hemp seed extract in treatment of acne vulgaris: a split-face, double-blinded, randomized, controlled trial

description: A prevalent chronic inflammatory skin condition affecting teenagers and young adults is acne vulgaris. The disease may have a negative influence on wellbeing in both physical and psychological ways. Treatment of acne vulgaris is depends on disease severity. Currently, first-line medical therapy for acne vulgaris mostly come with side effects varies from irritation to teratogenicity. Cannabidiol (CBD), one of the most well-known phytocannabinoid from Cannabis Sativa L. plant, is shown to have an ability to cure acne vulgaris by its antilipogenic, anti-proliferative and anti-inflammatory effects. Several studies have been proven that hemp seed and its extract contain CBD as a major composition of all phytocannabinoids. Recent studies about potential of CBD and hemp seed extract for treating acne vulgaris is still in vitro, but lack of clinical trial in human. Therefore, this study compares the effectiveness of topical hemp seed extract to a placebo in the treatment of acne vulgaris. For a period of 12 weeks, topical treatments will be given twice daily to either the left or right side of their faces, at random. The result will be interpreted objectively by acne lesion count, erythema index, sebum level and subjectively by physichian’s clinical assessment score and patient’s satisfaction score. The result revealed a statistically decreased of acne lesion count particularly in inflammatory acne lesions. Moreover, sebum level was also found significantly reduction by decreased 44.79% from baseline. However, contrasting from previous research, we established that there was no significant improvement in erythema index. Adverse events found in hemp seed extract cream were mild, including skin dryness and itchiness. There was no serious adverse effects presented in both interventions. In conclusion, hemp seed extract cream is safe and effective alternative treatment option for mild to moderate acne vulgaris.
DOI: 10.14457/tu.the.2021.498
title: Comparison of Malassezia spp. colonization between human skin exposed to high and low ambient air pollution

description: Background: The skin microbiota is essential for human health; altered skin microbiome colonization and homeostasis may be associated with several inflammatory skin conditions and other inflammatory diseases. The effects of particulate matter of diameter less than 2.5 micrometers (PM2.5) on the skin and the skin microbiome are poorly understood. Malassezia spp. are commensal fungi commonly found on the human skin, and they also play a pathogenic role in various skin diseases. It is hypothesized that the exposure of human skin to air pollution with a high concentration of PM2.5 might be associated with Malassezia spp. colonization. The aim of this study was to compare Malassezia spp. colonization on healthy human skin between people living in two major cities in Thailand with different air qualities: one city with highly polluted ambient air and the other with less polluted air. Methods: Skin microbiome samples from 66 participants were collected using swabbing and scraping techniques. The skin fungal composition was analyzed using high-throughput sequencing based on internal transcribed spacer 2 (ITS2) rDNA. Results: A significant difference was found in alpha and beta diversities and the relative abundance of fungal profiles between the groups. The relative abundance of Malassezia spp. was found to be significantly higher in the highly polluted area than in the less polluted area.Conclusion: This study demonstrates that ambient air polluted with high concentrations of PM2.5 may alter Malassezia spp. colonization on healthy human skin, which could lead to dysbiosis of the cutaneous ecosystem and eventually result in some skin disorders.