cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5517/ccdc.csd.cc2fl74f
title: CCDC 2251844: Experimental Crystal Structure Determination

description: Related Article: Peter G. Jones, Elmira Ghabraie, Philipp Klahn|2023|CSD Communication|||
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.cc2fl8ht
title: CCDC 2251886: Experimental Crystal Structure Determination

description: Related Article: Peter G. Jones, Philipp Klahn|2023|CSD Communication|||
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.cc23mryg
title: CCDC 1955416: Experimental Crystal Structure Determination

description: Related Article: Arnold L. Rheingold|2019|CSD Communication|||
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.cc2flr71
title: CCDC 2252343: Experimental Crystal Structure Determination

description: Related Article: Frank R. Fronczek|2023|CSD Communication|||
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: 10.5519/qd.e23mkymm
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (1 records)
DOI: 10.5519/qd.qc595kmn
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (1 records)
DOI: 10.34740/kaggle/dsv/5573073
title: YouTube Daily
DOI: 10.4121/19786900
title: MECAnalysisTool: A method to analyze consumer data

description: This Excel based tool was developed to analyze means-end chain data. The tool consists of a user manual, a calculator file for analyzing your data, and instructional videos.The purpose of this tool is to aggregate laddering data into hierarchical value maps showing means-end chains. The summarized results consist of (1) a summary overview,(2) a matrix, and (3) output for copy/pasting into NodeXL to generate hierarchal value maps (HVMs). To use this tool, you must have collected data via laddering interviews. Ladders are codes linked together consisting of attributes, consequences and values (ACVs).
DOI: 10.4121/ef3d2f15-ebf8-48c3-aeb4-629e176f9d05.v1
title: Raw data to "Quantifying reverse bias degradation of perovskite solar cells"

description: This dataset contains the raw data that is used in the communication "Quantifying reverse bias degradation of perovskite solar cells" .It includes the results of the two characterization steps 1 and 2 (before/after reverse bias degradation), consisting of IV curves, solar cells parameters from IV measurements, dark IV curves (DIV), extended dark IV curves (DIVext), maximum-power-point-tracking (MPPT), and reverse bias currents (RevBiasCurrents). The samples were perovskite solar cells of four different batches (A, B, C, and D) that had a cell area of 0.16 cm2. Four cells were on one glass superstrate which had an area of 3x3 cm2. Further details about the cells and the differences between the batches can be found in the communication and its accompanying electronic supporting information.
DOI: 10.5281/zenodo.7883146
title: Swiss paediatric dentists' preferences and experience on the use of articaine and other local/topical anaesthetics

description: Dataset for all analyses.
DOI: 10.5281/zenodo.7883145
title: Swiss paediatric dentists' preferences and experience on the use of articaine and other local/topical anaesthetics

description: Dataset for all analyses.
DOI: 10.34740/kaggle/dsv/5548691
title: Indian Companies financial Dataset (Scaled MINMAX)
DOI: 10.6084/m9.figshare.21857736.v1
title: Exposing Software Engineering Students to Stressful Projects: Does Diversity Matter?

description: Software development teams have to face stress caused by deadlines, staff turnover, or individual differences in commitment, expertise, and time zones. While students are typically taught the theory of software project management, their exposure to such stress factors is usually limited. However, preparing students for the stress they will have to endure once they work in project teams is important for their own sake, as well as for the sake of team performance in the face of stress. Team performance has been linked to the diversity of software development teams, but little is known about how diversity influences the stress experienced in teams. In order to shed light on this aspect, we provided students with the opportunity to self- experience the basics of project management in self-organizing teams, and studied the impact of six diversity dimensions on team performance, coping with stressors, and positive perceived learning effects. Three controlled experiments at two universities with a total of 65 participants suggest that the social background impacts the perceived stressors the most, while age and work experience have the highest impact on perceived learnings. Most diversity dimensions have a medium correlation with the quality of work, yet no significant relation to the team performance. This lays the foundation to improve students’ training for SE teamwork based on their diversity-related needs and to create diversity-sensitive awareness among educators, employers and researchers.
DOI: 10.6084/m9.figshare.21857736
title: Exposing Software Engineering Students to Stressful Projects: Does Diversity Matter?

description: Software development teams have to face stress caused by deadlines, staff turnover, or individual differences in commitment, expertise, and time zones. While students are typically taught the theory of software project management, their exposure to such stress factors is usually limited. However, preparing students for the stress they will have to endure once they work in project teams is important for their own sake, as well as for the sake of team performance in the face of stress. Team performance has been linked to the diversity of software development teams, but little is known about how diversity influences the stress experienced in teams. In order to shed light on this aspect, we provided students with the opportunity to self- experience the basics of project management in self-organizing teams, and studied the impact of six diversity dimensions on team performance, coping with stressors, and positive perceived learning effects. Three controlled experiments at two universities with a total of 65 participants suggest that the social background impacts the perceived stressors the most, while age and work experience have the highest impact on perceived learnings. Most diversity dimensions have a medium correlation with the quality of work, yet no significant relation to the team performance. This lays the foundation to improve students’ training for SE teamwork based on their diversity-related needs and to create diversity-sensitive awareness among educators, employers and researchers.
DOI: 10.5519/qd.082kw4iv
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (822238 records)
DOI: 10.6084/m9.figshare.22725806
title: Caffeine and mortality dataset

description: Data used in the study of caffeine consumption and mortality from NHANES
DOI: 10.6084/m9.figshare.22679050
title: Data file of RNA-Seq recipe Book 2 Chapter7-2

description: Data file of RNA-Seq recipe Book 2 Chapter7-2
DOI: 10.5517/ccdc.csd.cc2dymqq
title: CCDC 2233014: Experimental Crystal Structure Determination

description: Related Article: Rampal Pandey, Vaishali Singh, Avijit Paul|2022|CSD Communication|||
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.cc2dyp8b
title: CCDC 2233062: Experimental Crystal Structure Determination

description: Related Article: Christopher Zall, William Fernandez, Nilakshi Devi|2022|CSD Communication|||
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.cc2dyptw
title: CCDC 2233079: Experimental Crystal Structure Determination

description: Related Article: Christopher Zall, Nilakshi Devi|2022|CSD Communication|||
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.cc2dypxz
title: CCDC 2233082: Experimental Crystal Structure Determination

description: Related Article: Christopher Zall, Dorothea Hudson, Nilakshi Devi|2022|CSD Communication|||
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.cc2dyrw0
title: CCDC 2233143: Experimental Crystal Structure Determination

description: Related Article: Fengya He|2022|CSD Communication|||
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.cc2dz1q5
title: CCDC 2233417: Experimental Crystal Structure Determination

description: Related Article: Malibongwe Shandu|2022|CSD Communication|||
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.cc2dz8wk
title: CCDC 2233639: Experimental Crystal Structure Determination

description: Related Article: Christopher Zall, Dorothea Hudson|2022|CSD Communication|||
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.cc2dz9xm
title: CCDC 2233671: Experimental Crystal Structure Determination

description: Related Article: Brendan F. Abrahams, Christopher J. Commons, Timothy A. Hudson|2022|CSD Communication|||
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: 10.6084/m9.figshare.19375349
title: <i>In-silico</i> studies on wild orange (<i>Citrus macroptera</i> Mont.) compounds against COVID-19 pro-inflammation targets

description: One-fifth of COVID-19 patients suffer a severe course of COVID-19 (SARS-CoV-2) infection; however, the specific causes remain unclear. Despite numerous papers that have been flooded in different scientific journals clear clinical picture of COVID-19 aftermath persists to remain fuzzy. The survivors of severe COVID-19infection having defeated the virus are just the starting of an uncharted recovery path. Currently, there is no drug available that is safe to consume to combat this pandemic. However, researchers still struggling to find specific therapeutic solutions. The present study employed an <i>in silico</i> approach to assessing the inhibitory potential of the phytochemicals obtained from GC-MS analysis of <i>Citrus macroptera</i> against inflammatory proteins like COX-2, NMDAR and VCAM-1 which remains in a hyperactive state even after a patient is fully cured of this deadly mRNA virus. An extensive molecular docking investigation of the phyto-compounds at the active binding pockets of the inflammatory proteins revealed the promising inhibitory potential of the phytochemicals. Reasonable physicochemical attributes of the compounds following Lipinski’s rule of five, VEBER and PAINS analysis further established them as potential therapeutic candidates against aforesaid inflammatory proteins. MM-GBSA binding free energy estimation revealed that Limonene was the most promising candidate displaying the highest binding efficacy with the concerned VCAM-1 protein included in the present analysis. An interesting finding is the phytochemicals exhibited better binding energy scores with the concerned COX-2, VCAM-1 and NMDA receptor proteins than the conventional drugs that are specifically targeted against them. Our <i>in silico</i> results suggest that all the natural phyto-compounds derived from <i>C. macroptera</i> could be employed in Post covid inflammation complexities after appropriate pre-clinical and clinical trials for further scientific validation. Communicated by Ramaswamy H. Sarma
DOI: 10.6084/m9.figshare.19375349.v1
title: <i>In-silico</i> studies on wild orange (<i>Citrus macroptera</i> Mont.) compounds against COVID-19 pro-inflammation targets

description: One-fifth of COVID-19 patients suffer a severe course of COVID-19 (SARS-CoV-2) infection; however, the specific causes remain unclear. Despite numerous papers that have been flooded in different scientific journals clear clinical picture of COVID-19 aftermath persists to remain fuzzy. The survivors of severe COVID-19infection having defeated the virus are just the starting of an uncharted recovery path. Currently, there is no drug available that is safe to consume to combat this pandemic. However, researchers still struggling to find specific therapeutic solutions. The present study employed an <i>in silico</i> approach to assessing the inhibitory potential of the phytochemicals obtained from GC-MS analysis of <i>Citrus macroptera</i> against inflammatory proteins like COX-2, NMDAR and VCAM-1 which remains in a hyperactive state even after a patient is fully cured of this deadly mRNA virus. An extensive molecular docking investigation of the phyto-compounds at the active binding pockets of the inflammatory proteins revealed the promising inhibitory potential of the phytochemicals. Reasonable physicochemical attributes of the compounds following Lipinski’s rule of five, VEBER and PAINS analysis further established them as potential therapeutic candidates against aforesaid inflammatory proteins. MM-GBSA binding free energy estimation revealed that Limonene was the most promising candidate displaying the highest binding efficacy with the concerned VCAM-1 protein included in the present analysis. An interesting finding is the phytochemicals exhibited better binding energy scores with the concerned COX-2, VCAM-1 and NMDA receptor proteins than the conventional drugs that are specifically targeted against them. Our <i>in silico</i> results suggest that all the natural phyto-compounds derived from <i>C. macroptera</i> could be employed in Post covid inflammation complexities after appropriate pre-clinical and clinical trials for further scientific validation. Communicated by Ramaswamy H. Sarma
DOI: 10.6084/m9.figshare.19420246
title: Computational studies suggest compounds restoring function of p53 cancer mutants can bind SARS-CoV-2 spike protein

description: It is reasonable to think that cancer patients undergoing chemotherapy or immunotherapy may have a more aggressive course if they are positive for the novel coronavirus disease. Their compulsive condition requires investigation into effective drugs. We applied computational techniques to a series of compounds known for restoring the function of p53 cancer mutant p53<sup>R175H</sup> and p53<sup>G245S</sup>. Two potent inhibitors, 1-(3-chlorophenyl)-3-(1, 3 -thiazol-2-yl) urea (CTU, PubChem NSC321792) with the highest binding affinity −6.92 kcal/mol followed by a thiosemicarbazone compound N’-(1-(Pyridin-2-yl)ethylidene) azetidine − 1 -carbothiohydrazide (NPC, PubChem NSC319726) with −6.75 kcal/mol were subjected to Molecular Dynamics simulation with receptor binding domain (RBD) and compared with control ligand dexamethasone. In particular, CTU adheres to pocket 1 with an average free energy of binding −21.65 ± 2.89 kcal/mol at the RBD - angiotensin-converting enzyme 2 binding region with the highest frequency of amino acid residues after reaching a local equilibrium in 100 ns MD simulation trajectory. A significant enthalpy contribution from the independent simulations unfolds the possibility of dual binding sites for NPC as shifted pocket 1 (−15.59 ± 5.98 kcal/mol) and pocket 2 (−18.90 ± 5.02 kcal/mol). The obtained results for these two compounds are in good agreement with dexamethasone (−18.45 ± 2.42 kcal/mol). Taken together our findings could facilitate the discovery of small molecules that restore the function of p53 cancer mutants newly against COVID-19 in cancer patients. Communicated by Ramaswamy H. Sarma
DOI: 10.6084/m9.figshare.19420246.v2
title: Computational studies suggest compounds restoring function of p53 cancer mutants can bind SARS-CoV-2 spike protein

description: It is reasonable to think that cancer patients undergoing chemotherapy or immunotherapy may have a more aggressive course if they are positive for the novel coronavirus disease. Their compulsive condition requires investigation into effective drugs. We applied computational techniques to a series of compounds known for restoring the function of p53 cancer mutant p53<sup>R175H</sup> and p53<sup>G245S</sup>. Two potent inhibitors, 1-(3-chlorophenyl)-3-(1, 3 -thiazol-2-yl) urea (CTU, PubChem NSC321792) with the highest binding affinity −6.92 kcal/mol followed by a thiosemicarbazone compound N’-(1-(Pyridin-2-yl)ethylidene) azetidine − 1 -carbothiohydrazide (NPC, PubChem NSC319726) with −6.75 kcal/mol were subjected to Molecular Dynamics simulation with receptor binding domain (RBD) and compared with control ligand dexamethasone. In particular, CTU adheres to pocket 1 with an average free energy of binding −21.65 ± 2.89 kcal/mol at the RBD - angiotensin-converting enzyme 2 binding region with the highest frequency of amino acid residues after reaching a local equilibrium in 100 ns MD simulation trajectory. A significant enthalpy contribution from the independent simulations unfolds the possibility of dual binding sites for NPC as shifted pocket 1 (−15.59 ± 5.98 kcal/mol) and pocket 2 (−18.90 ± 5.02 kcal/mol). The obtained results for these two compounds are in good agreement with dexamethasone (−18.45 ± 2.42 kcal/mol). Taken together our findings could facilitate the discovery of small molecules that restore the function of p53 cancer mutants newly against COVID-19 in cancer patients. Communicated by Ramaswamy H. Sarma
DOI: 10.6084/m9.figshare.19420246.v1
title: Computational studies suggest compounds restoring function of p53 cancer mutants can bind SARS-CoV-2 spike protein

description: It is reasonable to think that cancer patients undergoing chemotherapy or immunotherapy may have a more aggressive course if they are positive for the novel coronavirus disease. Their compulsive condition requires investigation into effective drugs. We applied computational techniques to a series of compounds known for restoring the function of p53 cancer mutant p53<sup>R175H</sup> and p53<sup>G245S</sup>. Two potent inhibitors, 1-(3-chlorophenyl)-3-(1, 3 -thiazol-2-yl) urea (CTU, PubChem NSC321792) with the highest binding affinity −6.92 kcal/mol followed by a thiosemicarbazone compound N’-(1-(Pyridin-2-yl)ethylidene) azetidine − 1 -carbothiohydrazide (NPC, PubChem NSC319726) with −6.75 kcal/mol were subjected to Molecular Dynamics simulation with receptor binding domain (RBD) and compared with control ligand dexamethasone. In particular, CTU adheres to pocket 1 with an average free energy of binding −21.65 ± 2.89 kcal/mol at the RBD - angiotensin-converting enzyme 2 binding region with the highest frequency of amino acid residues after reaching a local equilibrium in 100 ns MD simulation trajectory. A significant enthalpy contribution from the independent simulations unfolds the possibility of dual binding sites for NPC as shifted pocket 1 (−15.59 ± 5.98 kcal/mol) and pocket 2 (−18.90 ± 5.02 kcal/mol). The obtained results for these two compounds are in good agreement with dexamethasone (−18.45 ± 2.42 kcal/mol). Taken together our findings could facilitate the discovery of small molecules that restore the function of p53 cancer mutants newly against COVID-19 in cancer patients.