Dataset associated with 'Reactive fluid-like ferroelectrics: a gateway to the next generation of ferroelectric liquid crystalline polymer networks'

This dataset contains the data associated with the article titled 'Reactive fluid-like ferroelectrics: a gateway to the next generation of ferroelectric liquid crystalline polymer networks', published in Small. The data is provided either as raw data files or the files used to plot figures in the relevant article. Data is focused primarily on structural characterisation and material properties of the monomers synthesised in the article, whilst also extending to the data obtained in the polymer stabilisation studies conducted in the relevant article

Predictive modelling of the COMATOSE transporter reveals a conserved ligand binding pocket for acyl-CoAs and validates previous functional studies

Models of plant peroxisomal transporter COMATOSE (CTS) generated with AlphaFold2/3. Three distinct states were produced of the apo, ATP-bound and ADP-bound conformations. Docking of C22:0-CoA and CoA alone to models of plant peroxisomal transporter COMATOSE (CTS). These models include the apo, ATP-bound and ADP-boudn conformations generated with AlphaFold2/3

Soil physical, chemical and hydrological data from agroforestry plots at Spen Farm, Yorks, UK, 2022-23

Soil and forest floor litter data sampled between 2022 and 2023 at the Spen Farm High Value Timber Agroforestry plots. Trees at the site were planted in 1988, and sampled areas include continuous woodland blocks of three species - sycamore, wild cherry and hazel, along with adjacent arable control blocks. Each block is replicated four times. Soil properties are measured between 0 and 50cm at 10cm intervals, and mineral soil measurements are supplemented by measurements of the forest floor L and combined F and H horizons. The dataset also includes measurements of saturated hydraulic conductivity taken at the soil surface

Room Temperature Catalytic Degradation of Phenolic Compounds Using Inkjet-Printed Gold Nanotape-PVA Hydrogels

Dataset includes all data needed for reader to create all plots found in the paper ' Room Temperature Catalytic Degradation of Phenolic Compounds Using Inkjet-Printed Gold Nanotape-PVA Hydrogels

Teacher’s current practices of identifying and supporting children with speech, language and communication needs in early childhood education settings in Ghana - Interview transcript

This dataset presents a rich collection of qualitative insights gathered from 20 Kindergarten (KG) teachers within the Gomoa-Central District of Ghana. The data is generated from semi-structured interviews conducted between December 2021 and February 2022, exploring the teachers' day-to-day practices in identifying and supporting children with Speech, Language, and Communication Needs (SLCN) within the framework of Ghana's recently introduced KG curriculum. The interviews delved into how teachers currently recognize children with SLCN, any changes in their approaches following the new curriculum, their understanding of the curriculum's guidelines related to SLCN, and their experiences with associated training initiatives. The dataset comprises verbatim transcripts of these in-depth conversations, offering detailed narratives of teachers' experiences. Complementing these qualitative accounts is background information collected from each participating teacher, including details such as their gender, age, educational qualifications, years of teaching service, and their specific circuit. The findings highlight a shift in teachers' practices towards more play-based and thematic teaching approaches encouraged by the new curriculum. This dataset offers a valuable understanding of the realities of SLCN identification and support in Ghanaian early childhood education from the perspective of the practitioners themselves, making it a significant resource for researchers, policymakers, and educators interested in this critical area

Dataset associated with 'The Effect of Templating on the Mechanical Properties of Smectic Liquid Crystal Elastomers'.

This dataset contains the data associated with the article titled 'The Effect of Templating on the Mechanical Properties of Smectic Liquid Crystal Elastomers', published in Journal of Materials Chemistry C.. This data is provided in the form of either the raw data collected, or the files used to plot the figures in the published article. The data is mainly focused on the material properties of smectic liquid crystal elastomers (LCEs) detailed in the associated article, including: mechanical testing of the LCEs, thermal analysis and X-ray scattering studies. The LCEs in question all display smectic ordering, which persists up to their thermal degradation, however the samples differ in that some were polymerised in the nematic phase, and others the smectic phase. This gives rise to different degrees of smectic order, which in turn vastly impact their mechanical properties

Combined clinoptilolite and Fe(O)OH for efficient removal of Cu(II) and Pb(II) with enhanced solid-liquid separation - Data set

Raw data for all figures in the associated paper: Combined clinoptilolite and Fe(O)OH for efficient removal of Cu(II) and Pb(II) with enhanced solid-liquid separatio

Data associated with "Employing Deep Mutational Scanning in the E. coli Periplasm to Decode the Thermodynamic Landscape For Amyloid Formation"

Deep mutational scanning (DMS) assays provide a powerful method to generate large-scale datasets essential for advancing AI-driven predictions in biology. The tripartite β-lactamase assay (TPBLA), in which a protein of interest is inserted between two domains of β-lactamase, has previously been reported as capable of detecting and quantitating protein aggregation of proteins and biologics in the oxidising periplasm of E. coli and used as a platform for identifying small molecule inhibitors of aggregation . Here, we repurpose TPBLA into a high-throughput DMS platform. We validate this format using a saturation library of the intrinsically disordered peptide Aβ42, linked to Alzheimer’s disease, demonstrating strong agreement between observed variant fitness scores and variants’ behaviour using our previously reported low-throughput TPBLA assay. The results of the DMS revealed variant fitness scores that correlate with known amyloid-promoting regions. An in silico approach using FoldX-derived per-residue thermodynamic stability confirmed that the TPBLA reports on amyloid fibril stability. In vitro experiments support this finding, showing a strong correlation between variant fitness scores and the critical concentration of amyloid formation. Machine learning using the DMS data identified β‐sheet propensity and polarity as primary drivers of variant fitness scores. The derived model is also able to predict thermodynamically stabilising regions in other amyloid systems, underscoring its generalisability. Collectively, our results demonstrate the TPBLA as a versatile platform for generating robust datasets to advance predictive modelling and to inform the design of aggregation‐resistant proteins

Ceramic 3D printed parts

This dataset contains 5197 images, and the corresponding annotations, of ceramic 3D printed parts. The dataset was used to train a Yolov8 model for defect detection purposes, and is split into training, validation and test datasets

Data for 'Inkjet Printing of Cadmium-Free Quantum Dots-Based Electroluminescent Devices'

The datasets are original data associated with the published paper ‘Inkjet Printing of Cadmium-Free Quantum Dots-Based Electroluminescent Devices’ and corresponding supporting information