cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17639/nott.7160
title: Effect of amylose/amylopectin ratio and extent of processing on the physical properties of expanded maize starches - data

description: Data collected for and presented in the research paper titled "Effect of amylose/amylopectin ratio and extent of processing on the physical properties of expanded maize starches".
DOI: 10.17639/nott.7040
title: Step-flow growth of graphene-boron nitride lateral heterostructures by molecular beam epitaxy

description: Integration of graphene and hexagonal boron nitride (hBN) into lateral heterostructures has drawn focus due to the ability to broadly engineer the material properties. Hybrid monolayers with tuneable bandgaps have been reported, while the interface itself possesses unique electronic and magnetic qualities. Herein, we demonstrate lateral heteroepitaxial growth of graphene and hBN by sequential growth using high-temperature molecular beam epitaxy (MBE) on highly ordered pyrolytic graphite (HOPG). We find, using scanning probe microscopy, that graphene growth nucleates at hBN step edges and grows across the surface to form nanoribbons with a controlled width that is highly uniform across the surface. The graphene nanoribbons grow conformally from the armchair edges of hexagonal hBN islands forming multiply connected regions with the growth front alternating from armchair to zigzag in regions nucleated close to the vertices of hexagonal hBN islands. Images with lattice resolution confirm a lateral epitaxial alignment between the hBN and graphene nanoribbons, while the presence of a moiré pattern within the ribbons indicates that some strain relief occurs at the lateral heterojunction. These results demonstrate that high temperature MBE is a viable route towards integrating graphene and hBN in lateral heterostructures.
DOI: 10.17639/nott.7219
title: Dataset for Training Generative Adversarial Networks for Optical Property Mapping using Synthetic Image Data

description: Data and code used to generate deep learning model to generate results in the above paper
DOI: 10.17639/nott.7084
title: Data for: Residual polymer stabiliser causes anisotropic conductivity in metal nanoparticle 2D and 3D printed electronics

description: Experimental data for manuscript "Residual polymer stabiliser causes anisotropic conductivity in metal nanoparticle 2D and 3D printed electronics". Contents: - Raw and exported ToF-SIMS and orbiSIMS data (.itmx and .txt) - Raw and exported XPS data (.vms and .txt) - All used electron micrographs (.tiff + .txt formats) - Electrical resistivity measurements - DSC data
DOI: 10.17639/nott.6475
title: An in vivo systematic genetic analysis of tumour progression in Drosophila - RNAi line: 45052

description: This data set forms part of the larger 'Fly Cancer Screen' data set, which consists of over 700 image sets
description: Metastasis is the leading cause of death for cancer patients. Consequently it is imperative that we improve our understanding of the molecular mechanisms that underlie progression of tumour growth towards malignancy. Advances in genome characterisation technologies have been very successful in identifying commonly mutated or misregulated genes in a variety of human cancers. A major challenge however is the translation of these findings to new biological insight due to the difficulty in evaluating whether these candidate genes drive tumour progression. Using the genetic amenability of Drosophila melanogaster we generated tumours with specific genotypes in the living animal and carried out a detailed systematic loss-of-function analysis to identify numerous conserved genes that enhance or suppress epithelial tumour progression. This enabled the discovery of functional cooperative regulators of invasion and the establishment of a network of conserved ‘invasion suppressors’. RNAi line: 45052 (III) Source: VDRC Name: CG9279 Full name: Also known as: Annotation symbol: CG9279 FlyBase ID: FBgn0036882 File naming convention: File names typically contain representations of date (DDMMYY), RNAi Line, Animal Number and, in some cases, window (to accommodate larger samples that require multiple image stacks)
DOI: 10.17639/nott.6436
title: An in vivo systematic genetic analysis of tumour progression in Drosophila - RNAi line: 4587R2

description: This data set forms part of the larger 'Fly Cancer Screen' data set, which consists of over 700 image sets
description: Metastasis is the leading cause of death for cancer patients. Consequently it is imperative that we improve our understanding of the molecular mechanisms that underlie progression of tumour growth towards malignancy. Advances in genome characterisation technologies have been very successful in identifying commonly mutated or misregulated genes in a variety of human cancers. A major challenge however is the translation of these findings to new biological insight due to the difficulty in evaluating whether these candidate genes drive tumour progression. Using the genetic amenability of Drosophila melanogaster we generated tumours with specific genotypes in the living animal and carried out a detailed systematic loss-of-function analysis to identify numerous conserved genes that enhance or suppress epithelial tumour progression. This enabled the discovery of functional cooperative regulators of invasion and the establishment of a network of conserved ‘invasion suppressors’. RNAi line: 4587R2 (III) Source: NIG Name: CG4587 (1) Full name: Also known as: BG:DS07108 .2 Annotation symbol: CG4587 FlyBase ID: FBgn0028863 File naming convention: File names typically contain representations of date (DDMMYY), RNAi Line, Animal Number and, in some cases, window (to accommodate larger samples that require multiple image stacks)
DOI: 10.17639/nott.6478
title: An in vivo systematic genetic analysis of tumour progression in Drosophila - RNAi line: 44804

description: This data set forms part of the larger 'Fly Cancer Screen' data set, which consists of over 700 image sets
description: Metastasis is the leading cause of death for cancer patients. Consequently it is imperative that we improve our understanding of the molecular mechanisms that underlie progression of tumour growth towards malignancy. Advances in genome characterisation technologies have been very successful in identifying commonly mutated or misregulated genes in a variety of human cancers. A major challenge however is the translation of these findings to new biological insight due to the difficulty in evaluating whether these candidate genes drive tumour progression. Using the genetic amenability of Drosophila melanogaster we generated tumours with specific genotypes in the living animal and carried out a detailed systematic loss-of-function analysis to identify numerous conserved genes that enhance or suppress epithelial tumour progression. This enabled the discovery of functional cooperative regulators of invasion and the establishment of a network of conserved ‘invasion suppressors’. RNAi line: 44804 (III) Source: VDRC Name: CG9572 (2) Full name: Also known as: Annotation symbol: CG9572 FlyBase ID: FBgn0031089 File naming convention: File names typically contain representations of date (DDMMYY), RNAi Line, Animal Number and, in some cases, window (to accommodate larger samples that require multiple image stacks)
DOI: 10.17639/nott.6441
title: An in vivo systematic genetic analysis of tumour progression in Drosophila - RNAi line: 48197

description: This data set forms part of the larger 'Fly Cancer Screen' data set, which consists of over 700 image sets
description: Metastasis is the leading cause of death for cancer patients. Consequently it is imperative that we improve our understanding of the molecular mechanisms that underlie progression of tumour growth towards malignancy. Advances in genome characterisation technologies have been very successful in identifying commonly mutated or misregulated genes in a variety of human cancers. A major challenge however is the translation of these findings to new biological insight due to the difficulty in evaluating whether these candidate genes drive tumour progression. Using the genetic amenability of Drosophila melanogaster we generated tumours with specific genotypes in the living animal and carried out a detailed systematic loss-of-function analysis to identify numerous conserved genes that enhance or suppress epithelial tumour progression. This enabled the discovery of functional cooperative regulators of invasion and the establishment of a network of conserved ‘invasion suppressors’. RNAi line: 48197 (III) Source: VDRC Name: CG4896 (2) Full name: Also known as: Annotation symbol: CG4896 FlyBase ID: FBgn0031319 File naming convention: File names typically contain representations of date (DDMMYY), RNAi Line, Animal Number and, in some cases, window (to accommodate larger samples that require multiple image stacks)
DOI: 10.17639/nott.6443
title: An in vivo systematic genetic analysis of tumour progression in Drosophila - RNAi line: 31169

description: This data set forms part of the larger 'Fly Cancer Screen' data set, which consists of over 700 image sets
description: Metastasis is the leading cause of death for cancer patients. Consequently it is imperative that we improve our understanding of the molecular mechanisms that underlie progression of tumour growth towards malignancy. Advances in genome characterisation technologies have been very successful in identifying commonly mutated or misregulated genes in a variety of human cancers. A major challenge however is the translation of these findings to new biological insight due to the difficulty in evaluating whether these candidate genes drive tumour progression. Using the genetic amenability of Drosophila melanogaster we generated tumours with specific genotypes in the living animal and carried out a detailed systematic loss-of-function analysis to identify numerous conserved genes that enhance or suppress epithelial tumour progression. This enabled the discovery of functional cooperative regulators of invasion and the establishment of a network of conserved ‘invasion suppressors’. RNAi line: 31169 (III) Source: Bloomington Name: CG5037 (2) Full name: Also known as: Annotation symbol: CG5037 FlyBase ID: FBgn0032222 File naming convention: File names typically contain representations of date (DDMMYY), RNAi Line, Animal Number and, in some cases, window (to accommodate larger samples that require multiple image stacks)
DOI: 10.17639/nott.6442
title: An in vivo systematic genetic analysis of tumour progression in Drosophila - RNAi line: 42787

description: This data set forms part of the larger 'Fly Cancer Screen' data set, which consists of over 700 image sets
description: Metastasis is the leading cause of death for cancer patients. Consequently it is imperative that we improve our understanding of the molecular mechanisms that underlie progression of tumour growth towards malignancy. Advances in genome characterisation technologies have been very successful in identifying commonly mutated or misregulated genes in a variety of human cancers. A major challenge however is the translation of these findings to new biological insight due to the difficulty in evaluating whether these candidate genes drive tumour progression. Using the genetic amenability of Drosophila melanogaster we generated tumours with specific genotypes in the living animal and carried out a detailed systematic loss-of-function analysis to identify numerous conserved genes that enhance or suppress epithelial tumour progression. This enabled the discovery of functional cooperative regulators of invasion and the establishment of a network of conserved ‘invasion suppressors’. RNAi line: 42787 (III) Source: VDRC Name: CG5037 (1) Full name: Also known as: Annotation symbol: CG5037 FlyBase ID: FBgn0032222 File naming convention: File names typically contain representations of date (DDMMYY), RNAi Line, Animal Number and, in some cases, window (to accommodate larger samples that require multiple image stacks)
DOI: 10.17639/nott.6483
title: An in vivo systematic genetic analysis of tumour progression in Drosophila - RNAi line: 13636

description: This data set forms part of the larger 'Fly Cancer Screen' data set, which consists of over 700 image sets
description: Metastasis is the leading cause of death for cancer patients. Consequently it is imperative that we improve our understanding of the molecular mechanisms that underlie progression of tumour growth towards malignancy. Advances in genome characterisation technologies have been very successful in identifying commonly mutated or misregulated genes in a variety of human cancers. A major challenge however is the translation of these findings to new biological insight due to the difficulty in evaluating whether these candidate genes drive tumour progression. Using the genetic amenability of Drosophila melanogaster we generated tumours with specific genotypes in the living animal and carried out a detailed systematic loss-of-function analysis to identify numerous conserved genes that enhance or suppress epithelial tumour progression. This enabled the discovery of functional cooperative regulators of invasion and the establishment of a network of conserved ‘invasion suppressors’. RNAi line: 13636 (III) Source: VDRC Name: Chd3 Full name: Chd3 Also known as: Annotation symbol: CG9594 FlyBase ID: FBgn0023395 File naming convention: File names typically contain representations of date (DDMMYY), RNAi Line, Animal Number and, in some cases, window (to accommodate larger samples that require multiple image stacks)
DOI: 10.17639/nott.6477
title: An in vivo systematic genetic analysis of tumour progression in Drosophila - RNAi line: 44802

description: This data set forms part of the larger 'Fly Cancer Screen' data set, which consists of over 700 image sets
description: Metastasis is the leading cause of death for cancer patients. Consequently it is imperative that we improve our understanding of the molecular mechanisms that underlie progression of tumour growth towards malignancy. Advances in genome characterisation technologies have been very successful in identifying commonly mutated or misregulated genes in a variety of human cancers. A major challenge however is the translation of these findings to new biological insight due to the difficulty in evaluating whether these candidate genes drive tumour progression. Using the genetic amenability of Drosophila melanogaster we generated tumours with specific genotypes in the living animal and carried out a detailed systematic loss-of-function analysis to identify numerous conserved genes that enhance or suppress epithelial tumour progression. This enabled the discovery of functional cooperative regulators of invasion and the establishment of a network of conserved ‘invasion suppressors’. RNAi line: 44802 (III) Source: VDRC Name: CG9572 (1) Full name: Also known as: Annotation symbol: CG9572 FlyBase ID: FBgn0031089 File naming convention: File names typically contain representations of date (DDMMYY), RNAi Line, Animal Number and, in some cases, window (to accommodate larger samples that require multiple image stacks)
DOI: 10.17639/nott.7077
title: Molecular quantum ring formed from a pi-conjugated macrocycle

description: The electronic structure of a molecular quantum ring (stacks of 40-unit cyclic porphyrin polymers) is characterised via scanning tunnelling microscopy and scanning tunnelling spectroscopy. Our measurements access the energetic and spatial distribution of the electronic states and, utilising a combination of density functional theory and tight binding calculations, we interpret the experimentally obtained electronic structure in terms of coherent quantum states confined around the circumference of the π-conjugated macrocycle. These findings demonstrate that large (53 nm circumference) cyclic porphyrin polymers have the potential to act as molecular quantum rings.
DOI: 10.17639/nott.7081
title: Developing immune-regulatory materials using immobilized monosaccharides with immune-instructive properties

description: Dataset contains raw and processed data used for the creation of figures in publication "Developing immune-regulatory materials using immobilized monosaccharides with immune-instructive properties"
DOI: 10.17639/nott.7082
title: Methodology for the synthesis of methacrylate monomers using designed single mode microwave applicators

description: Dataset contains raw and processed data used for the creation of figures in publication entitled 'Methodology for the synthesis of methacrylate monomers using designed single mode microwave applicators'
DOI: 10.17639/nott.7043
title: Performances Received by Plays set in the Ancient World, 1732-1831

description: This spreadsheet details the performances that different plays set in the ancient world received during the period from 1732 to 1831.
DOI: 10.17639/nott.7073
title: Securely located dedications in Delphi: 600-400 BCE
title: Delphic monuments: 600-400 BCE

description: This spreadsheet details the monumental dedications from Delphi that can be securely located in the sanctuary space, from c. 600-400 BCE.
DOI: 10.17639/nott.7058
title: Spatially resolved molecular compositions of insoluble multi-layer deposits responsible for increased pollution from internal combustion engines

description: Data required to recreate all figures including uncropped images for the article published in ACS Applied Materials and Interfaces: - 3D OrbiSIMS data: itmx. files of full depth profiles for all samples itmx. files of chemical imaging data sets for the gasoline and diesel injector samples at upper and lower depth. - XPS spectra from all deposit samples - exported as excel files. - SEM images - exported as a pdf. file. -Optical profilometry images of the gasoline and diesel injector
DOI: 10.17639/nott.7076
title: Structural characterisation of molecular conformation and the incorporation of adatoms in an on-surface Ullmann-type reaction

description: The on-surface synthesis of covalently bonded materials differs from solution-phase synthesis in several respects. The transition from a three-dimensional reaction volume to quasi two-dimensional confinement, as is the case for on-surface synthesis, has the potential to facilitate alternative reaction pathways to those available in solution. Ullmann-type reactions, where the surface plays a role in the coupling of aryl-halide functionalised species, has been shown to facilitate extended one- and two-dimensional structures. Here we employ a combination of scanning tunnelling microscopy (STM), X-ray photoelectron spectroscopy (XPS) and X-ray standing wave (XSW) analysis to perform a chemical and structural characterisation of the Ullmann-type coupling of two iodine functionalised species on a Ag(111) surface held under ultra-high vacuum (UHV) conditions. Our results allow characterisation of molecular conformations and adsorption geometries within an on-surface reaction and provide insight into the incorporation of metal adatoms within the intermediate structures of the reaction.
DOI: 10.17639/nott.7042
title: A participatory system dynamics model to investigate sustainable urban water management in Ebbsfleet Garden City

description: Growing urban populations, changes in rainfall patterns and ageing infrastructure represent significant challenges for urban water management (UWM). There is a critical need for research into how cities should adapt to become resilient to these impacts under uncertain futures. UWM challenges in the Ebbsfleet Garden City (UK) were investigated via a participatory process and potential sustainable solutions were explored using a System Dynamics Model (SDM). Collaborative development of the SDM by the Ebbsfleet Learning and Action Alliance developed stakeholders’ understanding of future UWM options and enabled a structured exploration of interdependencies within the current UWM system. Discussion by stakeholders resulted in a focus on potable water use and the development of the SDM to investigate how residential potable water consumption in the Ebbsfleet Garden City might be reduced through a range of interventions, e.g., socio-environmental and economic policy incentives. The SDM approach supports decision-making at a strategic, system-wide level, and facilitates exploration of the long-term consequences of alternative strategies, particularly those that are difficult to include in quantitative models. While an SDM can be developed by experts alone, building it collaboratively allows the process to benefit from local knowledge, resulting in a collective learning process and increased potential for adoption.
DOI: 10.17639/nott.7159
title: DFT data used in training MolE8 chemical ML models

description: =============================================================== Data for paper "MolE8: Finding DFT Potential Energy Surface Minima Values from Force-Field Optimised Organic Molecules with New Machine Learning Representations" Sanha Lee, Kristaps Ermanis* and Jonathan M. Goodman* Yusuf Hamied Department of Chemistry, University of Cambridge, Lensfield Road, Cambridge, CB2 1EW and School of Chemistry, University of Nottingham, University Park Nottingham, Nottingham, NG7 2RD =============================================================== This dataset contains Gaussian DFT optimization and frequency calculation output files for all of the molecules used in the training of the MolE8 representations and machine learning methods. The dataset is divided in 7 parts to keep the archive file sizes manageable. Each folder contains data for around 8000 molecules. The data includes the geometry optimization *a.out files, frequency calculation *f.out files and *sdf files of the optimized structures for wider compatibility with visualization software. Part 1 contains structure files up to 009999A1* Part 2 contains structure files up to 019999A1* Part 3 contains structure files up to 021988A1* Part 4 contains structure files up to 39997A1* Part 5 contains structure files up to 49999A1* Part 6 contains structure files up to 59999A1* Part 6 contains structure files up to 69125A1* All structures in these folders have been optimized and frequencies calculated at B3LYP/6-31g(2df,p) level in gas phase. All of the files can be opened in any text editor. Gaussian output structures can be viewed and the frequency modes visualised in GausView, Avogadro, jmol and in most other molecular viewers/editors. *.sdf files can be viewed in essentially all 3D molecular editors and viewers.
DOI: 10.17639/nott.7300
title: Feasibility of a neonatal early warning score in Kenya

description: Access to these files may be requested by reviewers while they are under embargo. Please contact ctu@nottingham.ac.uk The aim of this study was to test the feasibility and acceptability of an EWS in neonatal units in Kenya. In this study, we report the findings of a prospective observational study to determine the feasibility and key barriers and facilitators to implementation of an EWS in neonatal care in Kenya. A qualitative study aimed to assess acceptability of the tool was also conducted.
DOI: 10.17639/nott.7314
title: Raw data for new compounds described in the paper "Silver(I)-Catalyzed Synthesis of Cuneanes from Cubanes and their Investigation as Isosteres"

description: Raw data for new compounds described in the paper "Silver(I)-Catalyzed Synthesis of Cuneanes from Cubanes and their Investigation as Isosteres"
DOI: 10.17639/nott.7303
title: Wireless electrical-molecular quantum signalling for cancer cell induced death

description: Data set associated with the manuscript.
DOI: 10.17639/nott.7295
title: RoboClean elicitation study data of spoken natural language instructions to a robotic vacuum cleaner

description: Dataset comprising spoken instructions of 21 participants tasked to address a robotic vacuum cleaner. The dataset includes transcribed instructions spoken by participants, timestamps, output messages triggered by matching a Wizard-of-Oz protocol (see this paper: https://doi.org/10.1145/3432942), and categorisations of the instructions.