cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5517/ccdc.csd.cc2c86vq
title: CCDC 2182643: Experimental Crystal Structure Determination

description: Related Article: N. Jeyaraman Selvaraj, U. Sathya, S. Gomathi, S. Jegan Jennifer, L. Mathivathanan, I. Abdul Razak|2022|Acta Crystallogr.,Sect.C:Cryst.Struct.Chem.|78|437|doi:10.1107/S2053229622006684
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2c86wr
title: CCDC 2182644: Experimental Crystal Structure Determination

description: Related Article: N. Jeyaraman Selvaraj, U. Sathya, S. Gomathi, S. Jegan Jennifer, L. Mathivathanan, I. Abdul Razak|2022|Acta Crystallogr.,Sect.C:Cryst.Struct.Chem.|78|437|doi:10.1107/S2053229622006684
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2c8jt0
title: CCDC 2182952: Experimental Crystal Structure Determination

description: Related Article: X. Liu, L. Wang, Y. Feng, D. Cui, Z. Liu|2022|Acta Crystallogr.,Sect.E:Cryst.Commun.|78|770|doi:10.1107/S2056989022006740
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2c9m6j
title: CCDC 2183987: Experimental Crystal Structure Determination

description: Related Article: V. Subha, T. Seethalakshmi, T. Balakrishnan, M.J. Percino, P. Venkatesan|2022|Acta Crystallogr.,Sect.E:Cryst.Commun.|78|774|doi:10.1107/S2056989022006831
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2c9wn7
title: CCDC 2184249: Experimental Crystal Structure Determination

description: Related Article: F. Fuhrmann, E. Meier, W. Seichter, M. Mazik|2022|Acta Crystallogr.,Sect.E:Cryst.Commun.|78|785|doi:10.1107/S2056989022006867
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2cb361
title: CCDC 2184452: Experimental Crystal Structure Determination

description: Related Article: I. Mahmudov, Z. Atioğlu, M. Akkurt, Y. Abdullayev, A. Sujayev, A. Bhattarai|2022|Acta Crystallogr.,Sect.E:Cryst.Commun.|78|779|doi:10.1107/S2056989022006910
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2ch647
title: CCDC 2189348: Experimental Crystal Structure Determination

description: Related Article: Z. Atioğlu, M. Akkurt, N.Q. Shikhaliyev, N.A. Mammadova, G.V. Babayeva, V.N. Khrustalev, A. Bhattarai|2022|Acta Crystallogr.,Sect.E:Cryst.Commun.|78|804|doi:10.1107/S2056989022007113
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5281/zenodo.6939889
title: GENEA Challenge 2022 subjective evaluation data

description: This zip archive contains user-study response data and associated analyses and analysis results from the GENEA Challenge 2022 (https://youngwoo-yoon.github.io/GENEAchallenge2022/). The code was written by Gustav Eje Henter and is released under a Creative Commons Attribution 4.0 International license.
DOI: 10.5281/zenodo.6782890
title: An End-to-End Framework for Detecting and Repairing Potential Vulnerabilities

description: Nowadays, program development is getting easier and easier as the various IDE tools provide advice on what to write in the program. But it is not enough to implement a solution to a problem; it is also important that the non-functional properties, like the quality or security of the code, are appropriate in all aspects. One of the most widely used techniques to ensure quality is testing. If the tests fail, one can fix the code immediately. However, security issues are unexpected cases when implementing the program, which is why we do not write tests for them in advance. In many cases, security-relevant bugs can not only cause financial loss but also put human lives at risk, so detecting and fixing them is an important step for the reliability and quality of the program. The tool presented in this paper aims to generate automatic code repairs to potential vulnerabilities in the program. By integrating the recommended fixes, one can easily harden the security of their program early in the development process. A case study on six open-source Java subject systems showed that we were able to generate viable repair patches for 57 out of the 81 detected security issues (70%). For certain types (e.g., revealing private references of mutable objects), our tool reached close to perfect performance.
DOI: 10.5281/zenodo.6778637
title: An End-to-End Framework for Detecting and Repairing Potential Vulnerabilities

description: Nowadays, program development is getting easier and easier as the various IDE tools provide advice on what to write in the program. But it is not enough to implement a solution to a problem; it is also important that the non-functional properties, like the quality or security of the code, are appropriate in all aspects. One of the most widely used techniques to ensure quality is testing. If the tests fail, one can fix the code immediately. However, security issues are unexpected cases when implementing the program, which is why we do not write tests for them in advance. In many cases, security-relevant bugs can not only cause financial loss but also put human lives at risk, so detecting and fixing them is an important step for the reliability and quality of the program. The tool presented in this paper aims to generate automatic code repairs to potential vulnerabilities in the program. By integrating the recommended fixes, one can easily harden the security of their program early in the development process. A case study on six open-source Java subject systems showed that we were able to generate viable repair patches for 57 out of the 81 detected security issues (70%). For certain types (e.g., revealing private references of mutable objects), our tool reached close to perfect performance.
DOI: 10.5281/zenodo.6596516
title: eeg-workshops/mkpy_data_examples/data

description: EEG data files for eeg-workshops/mkpy_data_examples. For more information see the docs and github source. Updated docs and data files for mkpy v0.2.7, Python 3.9. mkh5 format HDF5 EEG recordings with and without included epoch tables.
DOI: 10.5281/zenodo.3960356
title: eeg-workshops/mkpy_data_examples/data

description: EEG data files for eeg-workshops/mkpy_data_examples. For more information see the docs and github source. Updated docs and data files for mkpy v0.2.7, Python 3.9. mkh5 format HDF5 EEG recordings with and without included epoch tables.
DOI: 10.6084/m9.figshare.19930220
title: Dataset for Acanthochromis microplastic lab study 2019

description: The current study experimentally explored the influence of periodic consumption of polystyrene (PS) microplastic fragments on the body condition and fitness of a tropical marine fish. Adult damselfish, <em>Acanthochromis polyacanthus</em>, were pulse fed microplastic fragments bound with one of two different common plasticizers (DEHP or DEHT) together with virgin-plastic and no-plastic controls. Ingestion of plastic over a 150d period had no detectable effect on growth, indices of body condition, or gonadosomatic indices. Histology of the liver showed no detrimental effects of ingesting any of the plastic treatments on hepatocyte density or vacuolation. Plastic consumption also had no effects on the number of clutches produced over the breeding period, the number of eggs or the survival of the embryos.
DOI: 10.6084/m9.figshare.19930220.v1
title: Dataset for Acanthochromis microplastic lab study 2019

description: The current study experimentally explored the influence of periodic consumption of polystyrene (PS) microplastic fragments on the body condition and fitness of a tropical marine fish. Adult damselfish, <em>Acanthochromis polyacanthus</em>, were pulse fed microplastic fragments bound with one of two different common plasticizers (DEHP or DEHT) together with virgin-plastic and no-plastic controls. Ingestion of plastic over a 150d period had no detectable effect on growth, indices of body condition, or gonadosomatic indices. Histology of the liver showed no detrimental effects of ingesting any of the plastic treatments on hepatocyte density or vacuolation. Plastic consumption also had no effects on the number of clutches produced over the breeding period, the number of eggs or the survival of the embryos.
DOI: 10.21227/4f98-sb04
title: Automation Transparency

description: The automation transparency dataset includes information from 3483 articles. The 3445 articles are retrieved from four electronic databases, search 31 articles from reference lists of the 3445 articles, and 8 articles from personal communications and IEEE standard searches. The electronic databases are IEEE Xplore, Compendex (including Inspec), Scopus, and Web of Science. We searched each database with a string of twenty terms. The dataset includes information on the article, including its database, title, authors, source, abstract, year, author keywords, index keywords, publisher, citation, and DOI. In addition, the dataset includes our coding information, including our rationale for identifying an article as relevant, whether we identified an article as relevant or irrelevant, whether transparency was used explicitly or implicitly, an instance wherein transparency is used in the article, the way transparency is operationalized, whether transparency was used with the see-into or see-through connotation, the automation/application for which transparency was used based on author keywords.
DOI: 10.57770/2vttke
title: Escaping from Zero Gradient: Revisiting Action-Constrained Reinforcement Learning via Frank-Wolfe Optimization

description: This repo contains code accompanying the paper, Escaping from Zero Gradient: Revisiting Action-Constrained ReinforcementLearning via Frank-Wolfe Optimization (UAI 2021). It includes code for running the NFWPO algorithm presented in the paper, and other baseline methods such as DDPG+OptLayer, DDPG+Projection, DDPG+Reward Shaping, SAC+Projection, PPO+Projection, TRPO+Projection, FOCOPS.
DOI: 10.6084/m9.figshare.19930226
title: TF-C Pretrain FD-B

description: - Paper: Self-Supervised Contrastive Pre-Training For Time Series via Time-Frequency Consistency - Paper link: - Github repo: https://github.com/mims-harvard/TFC-pretraining - Project website: <br> <strong>FD-A</strong> and <strong>FD-B</strong> are subsets taken from the <strong>FD</strong> dataset, which is gathered from an electromechanical drive system that monitors the condition of rolling bearings and detect damages in them. There are four subsets of data collected under various conditions, whose parameters include rotational speed, load torque, and radial force. Each rolling bearing can be undamaged, inner damaged, and outer damaged, which leads to three classes in total. We denote the subsets corresponding to condition A and condition B as Faulty Detection Condition A (<strong>FD-A</strong>) and Faulty Detection Condition B (<strong>FD-B</strong>) , respectively. Each original recording has a single channel with sampling frequency of 64k Hz and lasts 4 seconds. To deal with the long duration, we followe the procedure described by Eldele et al., that is, we use sliding window length of 5,120 observations and a shifting length of either 1,024 or 4,096 to make the final number of samples relatively balanced between classes.
DOI: 10.34740/kaggle/dsv/3722453
title: BBC News
DOI: 10.6084/m9.figshare.19930244
title: TF-C Pretrain HAR

description: - Paper: Self-Supervised Contrastive Pre-Training For Time Series via Time-Frequency Consistency - Paper link: - Github repo: https://github.com/mims-harvard/TFC-pretraining - Project website: <br> <strong>HAR</strong> contains recordings of 30 health volunteers performing six daily activities such as walking, walking upstaris, walking downstairs, sitting, standing, and laying. The prediction labels are the six activities. The wearable sensors on a smartphone measure triaxial linear acceleration and triaxial angular velocity at 50 Hz. After preprocessing and isolating out gravitational acceleration from body acceleration, there are nine channels in total. To line up the semantic domain with the channels in the dataset use during fine-tuning <strong>Gesture</strong> we only use the three channels of body linear accelerations. <br> <br>
DOI: 10.6084/m9.figshare.19930247
title: TF-C Pretrain Gesture

description: - Paper: Self-Supervised Contrastive Pre-Training For Time Series via Time-Frequency Consistency - Paper link: - Github repo: https://github.com/mims-harvard/TFC-pretraining - Project website: <br> <strong>Gesture</strong> contains accelerometer measurements of eight simple gestures that differed based on the paths of hand movement. The eight gestures are: hand swiping left, right, up, down, hand waving in a counterclockwise circle, or in clockwise circle, hand waving in a square, and waving a right arrow. The classification labels are those eight different types of gestures. The original paper reports inclusion of 4,480 gesture measurements, but through UCR Database we were only able to recover 440 measurements. The dataset is balanced with 55 samples each class and is of a suitable size for our purpose of fine-tuning experiments. Sampling frequency is not explicitly reported in the original paper but is presumably 100 Hz. The dataset uses three channels corresponding to three coordinate directions of linear acceleration.
DOI: 10.6084/m9.figshare.19930232
title: space-time distribution characteristics data.xlsx

description: This paper made an investigation in Beijing Xizhimen subway station and surveyed the large passenger flow of A1 entrance, A1 exit, and Line 2 of the station during the morning peak hours from 7:40 a.m. to 8:40 a.m. The survey took 5 minutes as a period and took observation data during one period as 1 group. Each observation location has obtained 12 group data. This paper has surveyed the passenger flow, density, speed, and the related hardware facilities in the following seven locations: security checkpoint, ticket entrance, platform stairs of Line 2, the platform of Line 2, exiting stairs of Line 2, transfer channel from Line 2 to Line 13, and ticket exit.
DOI: 10.6084/m9.figshare.19930232.v1
title: space-time distribution characteristics data.xlsx

description: This paper made an investigation in Beijing Xizhimen subway station and surveyed the large passenger flow of A1 entrance, A1 exit, and Line 2 of the station during the morning peak hours from 7:40 a.m. to 8:40 a.m. The survey took 5 minutes as a period and took observation data during one period as 1 group. Each observation location has obtained 12 group data. This paper has surveyed the passenger flow, density, speed, and the related hardware facilities in the following seven locations: security checkpoint, ticket entrance, platform stairs of Line 2, the platform of Line 2, exiting stairs of Line 2, transfer channel from Line 2 to Line 13, and ticket exit.
DOI: 10.6084/m9.figshare.19930253
title: TF-C Pretrain ECG

description: - Paper: Self-Supervised Contrastive Pre-Training For Time Series via Time-Frequency Consistency - Paper link: - Github repo: https://github.com/mims-harvard/TFC-pretraining - Project website: <br> <strong>ECG</strong> is taken as a subset from the 2017 PhysioNet Challenge that focuses on ECG recording classification. The single lead ECG measures four different underlying conditions of cardiac arrhythmias. More specifically, these classes correspond to the recordings of normal sinus rhythm, atrial fibrillation (AF), alternative rhythm, or others (too noisy to be classified). The recordings are sampled at 300 Hz. Furthermore, the dataset is imbalanced, with much fewer samples from the atrial fibrillation and noisy classes out of all four. To preprocess the dataset, we use the code from the CLOCS paper, which applied fixed-length window of 1,500 observations to divide up the long recordings into short samples of 5 seconds in duration that is still physiologically meaningful.
DOI: 10.5517/ccdc.csd.cc27kf8j
title: CCDC 2072327: Experimental Crystal Structure Determination

description: Related Article: Shuang-Yun Yang, Fei-Ke Zhao, Hong Pang, Liang-Zhu Chen, Ren-Bin Shi, Bing-Hu Fang|2022|J.Mol.Struct.|1265|133335|doi:10.1016/j.molstruc.2022.133335
DOI: 10.5517/ccdc.csd.cc27kf9k
title: CCDC 2072328: Experimental Crystal Structure Determination

description: Related Article: Shuang-Yun Yang, Fei-Ke Zhao, Hong Pang, Liang-Zhu Chen, Ren-Bin Shi, Bing-Hu Fang|2022|J.Mol.Struct.|1265|133335|doi:10.1016/j.molstruc.2022.133335
DOI: 10.5517/ccdc.csd.cc27kfbl
title: CCDC 2072329: Experimental Crystal Structure Determination

description: Related Article: Shuang-Yun Yang, Fei-Ke Zhao, Hong Pang, Liang-Zhu Chen, Ren-Bin Shi, Bing-Hu Fang|2022|J.Mol.Struct.|1265|133335|doi:10.1016/j.molstruc.2022.133335
DOI: 10.5517/ccdc.csd.cc27kfdn
title: CCDC 2072331: Experimental Crystal Structure Determination

description: Related Article: Shuang-Yun Yang, Fei-Ke Zhao, Hong Pang, Liang-Zhu Chen, Ren-Bin Shi, Bing-Hu Fang|2022|J.Mol.Struct.|1265|133335|doi:10.1016/j.molstruc.2022.133335
DOI: 10.6084/m9.figshare.19930250
title: TF-C Pretrain EMG

description: - Paper: Self-Supervised Contrastive Pre-Training For Time Series via Time-Frequency Consistency - Paper link: - Github repo: https://github.com/mims-harvard/TFC-pretraining - Project website: <br> Electromyograms (EMG) measures muscle responses as electrical activity to neural stimulation, and they can be use to diagnose certain muscular dystrophies and neuropathies. <strong>EMG</strong> consists of single-channel EMG recording from the tibialis anterior muscle of three volunteers that are healthy, suffering from neuropathy, and suffering from myopathy, respectively. The recordings are sampled with the frequency of 4K Hz. Each patient, i.e., their disorder, is a separate classification category. Then the recordings are split into time series samples using a fixed-length window of 1,500 observations.
DOI: 10.5519/qd.bsfhfoud
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (17 records)
DOI: 10.5281/zenodo.4280918
title: Dataset related to article "Optimization of a Luciferase-Expressing Non-Invasive Intrapleural Model of Malignant Mesothelioma in Immunocompetent Mice"

description: This record contains data related to article "Optimization of a Luciferase-Expressing Non-Invasive Intrapleural Model of Malignant Mesothelioma in Immunocompetent Mice" Malignant Pleural Mesothelioma (MPM) is an aggressive tumor of the pleural lining that is usually identified at advanced stages and resistant to current therapies. Appropriate pre-clinical mouse tumor models are of pivotal importance to study its biology. Usually, tumor cells have been injected intraperitoneally or subcutaneously. Using three available murine mesothelioma cell lines with different histotypes (sarcomatoid, biphasic, epithelioid), we have set up a simplified model of in vivo growth orthotopically by inoculating tumor cells directly in the thorax with a minimally invasive procedure. Mesothelioma tumors grew along the pleura and spread on the superficial areas of the lungs, but no masses were found outside the thoracic cavity. As observed in human MPM, tumors were highly infiltrated by macrophages and T cells. The luciferase-expressing cells can be visualized in vivo by bioluminescent optical imaging to precisely quantify tumor growth over time. Notably, the bioluminescence signal detected in vivo correctly matched the tumor burden quantified with classical histology. In contrast, the subcutaneous or intraperitoneal growth of these mesothelioma cells was considered either non-representative of the human disease or unreliable to precisely quantify tumor load. Our non-invasive in vivo model of mesothelioma is simple and reproducible, and it reliably recapitulates the human disease.
DOI: 10.5281/zenodo.4280917
title: Dataset related to article "Optimization of a Luciferase-Expressing Non-Invasive Intrapleural Model of Malignant Mesothelioma in Immunocompetent Mice"

description: This record contains data related to article "Optimization of a Luciferase-Expressing Non-Invasive Intrapleural Model of Malignant Mesothelioma in Immunocompetent Mice" Malignant Pleural Mesothelioma (MPM) is an aggressive tumor of the pleural lining that is usually identified at advanced stages and resistant to current therapies. Appropriate pre-clinical mouse tumor models are of pivotal importance to study its biology. Usually, tumor cells have been injected intraperitoneally or subcutaneously. Using three available murine mesothelioma cell lines with different histotypes (sarcomatoid, biphasic, epithelioid), we have set up a simplified model of in vivo growth orthotopically by inoculating tumor cells directly in the thorax with a minimally invasive procedure. Mesothelioma tumors grew along the pleura and spread on the superficial areas of the lungs, but no masses were found outside the thoracic cavity. As observed in human MPM, tumors were highly infiltrated by macrophages and T cells. The luciferase-expressing cells can be visualized in vivo by bioluminescent optical imaging to precisely quantify tumor growth over time. Notably, the bioluminescence signal detected in vivo correctly matched the tumor burden quantified with classical histology. In contrast, the subcutaneous or intraperitoneal growth of these mesothelioma cells was considered either non-representative of the human disease or unreliable to precisely quantify tumor load. Our non-invasive in vivo model of mesothelioma is simple and reproducible, and it reliably recapitulates the human disease.