cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.14242475
title: Kitekraft flight data acquired on 28 June 2024

description: This dataset captures a flight test of the 2.4m wingspan Kitekraft kite, flown with ground station south of Oberbiberg, Germany. The entire system was operated automatically, only with operators giving high level commands such a launch/land. The kite was reeled out, performed trans-in, flight of 53 figure-8s, trans-out, hover-landing. A main goal of this flight was to perform this entire sequence, test new control software updates, and record anomalies that may occur e.g. due to wind. The kite and ground station were equipped with numerous sensors. The dataset includes a photograph and a README file with a detailed description of the data.
DOI: 10.17639/nott.7074
title: Covid-19: The effects of isolation and social distancing on people with vision impairment
title: Life in lockdown: Living with vision impairment during Covid-19

description: This report presents findings from research on the effects of Covid-19 on people with vision impairment, based on a survey of 937 respondents. The survey contained closed questions and open free text questions, both of which are analysed in this report. The survey specifically addressed constraints to everyday life activities (work, education, leisure, recreation, etc.), the extent to which these were negotiated and how this impacted wellbeing during Covid-19. Additionally, it considered levels of support from essential services and engagement with social distancing measures. The research was undertaken in collaboration with Guide Dogs. Survey respondents include Guide Dogs service users and affiliates of Guide Dogs and Visionary who have vision impairment or care for someone who does.
DOI: 10.17639/nott.39
title: Recognising barriers to implementation of Blue-Green Infrastructure: a Newcastle case study

description: This is a qualitative data collection. These data were collected as part of an interdisciplinary project undertaken by the Blue-Green Cities (BGC) Research Consortium (www.bluegreencities.ac.uk). The project examined the sources of uncertainty and barriers responsible for current concerns and challenges to widespread adoption of Blue-Green Infrastructure in urban flood risk management. The study consisted of nineteen semi-structured interviews with institutional stakeholders in the Newcastle, UK. There is a recognised need for a fundamental change in how the UK manages urban water and flood risk in response to increasingly frequent rainfall events coupled with planned urban expansion. Approaches centred on ‘living with and making space for water’ are increasingly adopted internationally. Nonetheless, widespread implementation of Blue-Green infrastructure (BGI) is currently hampered by barriers that impede uptake and innovation. We investigate the barriers to implementation of BGI in Newcastle, UK, through a series of semi-structured interviews with professional stakeholders. We identify and categorise 17 types of barrier and identify targeted strategies to overcome the dominant barriers. We recommend promotion of BGI’s capacity to meet the objectives of multiple organisations and Local Authority departments, in addition to managing urban water. We conclude that strong business cases, supported by monetised evidence of benefits, and collaborative, inter-agency working could advance implementation of BGI within the current flood risk management legislation.
DOI: 10.17639/nott.7383
title: Drought and heatwave stress on the African eggplant

description: This data was collected as part of the research on the drought and heat stress on the African eggplant to describe the effects of the stress combination on this crop. The data was collected at East Malling, UK, and comprises harvest data, physiological measurements, and nutritional quality data.
DOI: 10.17639/nott.7382
title: Ethics in the Governance of Data and Digital Technology: An analysis of European Data Regulations and Policies

description: Addressing ethical concerns is among the fundamental motivations for the development of policies and regulations for data and digital technologies. In the last few years, the European Commission has issued a number of policies, regulations and legislative proposals for socially desirable and legally compliant data governance for technologies which have ethical implications. What is not obvious, however, is whether and in what way ethics are included explicitly in the way these policies and regulations are created and implemented to address data governance challenges. Given the increasing amount of available digital data, its use for AI and other purposes and the growing amount of regulatory activity around data, this paper explores the role ethics plays in these documents. We examined eight of these documents to map the ethical concerns and justifications underlining their provisions, the ethical principles they promote and the implementation approaches recommended. Our analysis shows that the current EU data governance policy landscape can be read from an ethical perspective as being grounded in ethical thinking, typically expressed in terms of human rights, aware of likely concerns, based on well-established principles and in the process of being codified in regulation, legislation and institutions. However, the practical implementation of these principles, for instance how conflicts among these principles can be resolved, remain unclear. This is the datasets from the research; including the coding tree and analysis of the documents and policies for the research
DOI: 10.17639/nott.7381
title: Enabling High-fidelity Personalized Pharmaceutical Tablets through Multimaterial Inkjet 3D Printing with a Water-soluble Excipient

description: Additive manufacturing offers manufacture of personalised pharmaceutical tablets through design freedoms and material deposition control at an individual voxel level. This control goes beyond geometry and materials choices: inkjet based 3D printing enables the precise deposition (10-80 µm) of multiple materials, which enables integration of precise doses with tailored release rates; in the meanwhile, this technique has demonstrated its capability of high-volume personalised production. In this paper we demonstrate how two dissimilar materials, one water soluble and one insoluble, can be co-printed within a design envelope to dial up a range of release rates including slow (0.98 ± 0.04 mg/min), fast (4.07 ± 0.25 mg/min) and multi-stepped (2.17 ± 0.04 mg/min then 0.70 ± 0.13 mg/min) dissolution curves. To achieve this, we adopted poly-4-acryloylmorpholine (poly-ACMO) as a new photocurable water-soluble carrier and demonstrated its contemporaneous deposition with an insoluble monomer. The water soluble ACMO formulation with aspirin incorporated was successfully printed and cured under UV light and a wide variety of shapes with material distributions that control drug elution was successfully fabricated by inkjet based 3D printing technique, suggesting its viability as a future personalised solid dosage form fabrication routine.
DOI: 10.17639/nott.7486
title: Trace Element concentrations in the River Tone, Somerset, and the River Wensum, Norfolk

description: This dataset contains measured concentrations of trace elements in both waters and sediments, collected during routine sampling as part of the PhD project "Assessing the Impacts of Organic and Inorganic Contaminants on British Rivers: from Sediments to Fish". Samples were collected in 2021 and 2022, and elements were measured using DMA-80 for Hg, and ICP-MS for all other elements, at the University of Nottingham. Site coordinates are included in a separate tab. Full details on sample collection, analytical methodology and data summaries, including interpretations, can be found in the accompanying thesis.
DOI: 10.17639/nott.6507
title: An in vivo systematic genetic analysis of tumour progression in Drosophila - RNAi line: 32329

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: 32329 (III) Source: VDRC Name: cv-c (2) Full name: crossveinless c Also known as: RhoGAP88C, l(3)06951 Annotation symbol: CG34389 FlyBase ID: FBgn0285955 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.7488
title: NHS Covid-19 App Concordances

description: A sample of concordances for the Covid-19 App discourse.
DOI: 10.17639/nott.6860
title: An in vivo systematic genetic analysis of tumour progression in Drosophila - RNAi line: 28588

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: 28588 (III) Source: Bloomington Name: Sema-1b (2) Full name: Semaphorin 1b Also known as: Sema1b, Sema 1b, sema-III Annotation symbol: CG6446 FlyBase ID: FBgn0016059 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.6862
title: An in vivo systematic genetic analysis of tumour progression in Drosophila - RNAi line: 48057

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: 48057 (III) Source: VDRC Name: Sema-2b (1) Full name: Semaphorin 2b Also known as: Sema2b Annotation symbol: CG33960 FlyBase ID: FBgn0264273 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.6867
title: An in vivo systematic genetic analysis of tumour progression in Drosophila - RNAi line: 26413

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: 26413 (III) Source: VDRC Name: Sep2 Full name: Septin 2 Also known as: Annotation symbol: CG4173 FlyBase ID: FBgn0014029 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.6874
title: An in vivo systematic genetic analysis of tumour progression in Drosophila - RNAi line: 5406R3

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: 5406R3 (III) Source: NIG Name: sif (1) Full name: still life Also known as: Dm_3L:26493 , lincRNA.447 Annotation symbol: CG34418 FlyBase ID: FBgn0085447 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.6877
title: An in vivo systematic genetic analysis of tumour progression in Drosophila - RNAi line: 24597

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: 24597 (III) Source: VDRC Name: SK (1) Full name: small conductance calcium-activated potassium channel Also known as: dSK Annotation symbol: CG10706 FlyBase ID: FBgn0029761 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.6861
title: An in vivo systematic genetic analysis of tumour progression in Drosophila - RNAi line: 15810

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: 15810 (III) Source: VDRC Name: Sema-2a Full name: Semaphorin 2a Also known as: Sema-2a, SemaII, sema-II, D-SemaII Annotation symbol: CG4700 FlyBase ID: FBgn0011260 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.6859
title: An in vivo systematic genetic analysis of tumour progression in Drosophila - RNAi line: 6446R3

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: 6446R3 (III) Source: NIG Name: Sema-1b (1) Full name: Semaphorin 1b Also known as: Sema1b, Sema 1b, sema-III Annotation symbol: CG6446 FlyBase ID: FBgn0016059 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.6826
title: An in vivo systematic genetic analysis of tumour progression in Drosophila - RNAi line: 46908

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: 46908 (III) Source: VDRC Name: Rm62 (2) Full name: Rm62 Also known as: Lip, Dmp68, p68 Annotation symbol: CG10279 FlyBase ID: FBgn0003261 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: 10.5281/zenodo.14242561
title: Kitekraft flight data acquired on 27 August 2024

description: This dataset captures a flight test of the 2.4m wingspan Kitekraft kite, flown with ground station south of Oberbiberg, Germany. The entire system was operated automatically, only with operators giving high level commands such a launch/land. The kite was reeled out, performed trans-in, figure-8 flight, trans-out, hover-landing. A main goal of this flight was to perform this entire sequence, test new control software updates, and record anomalies that may occur. The kite and ground station were equipped with numerous sensors. The dataset includes a photograph and a README file with a detailed description of the data.