1401 research outputs found
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Raw Data - Development of a Body-Worn Textile-Based Strain Sensor: Application to Diabetic Foot Assessment
No full textThis dataset contain the raw data associated with the development of a silver adheisive based strain sensor. The data contains the output of parametric testing covering the number of turns, sensor length and cure temperature of the strain gauge design, collected through quasi-static testing. The second set out data assess a series of robustness improvement made to the sensor, collected through quasi-static testing and some cyclic loading. The final set of data was used to assess sensor performance. The data takes the form of text files collected from the proposed sensor and csv files from the instron used to conduct testing
A Geometric Model of Impingement During Dislocation Prone Activities in Dual Mobility, Lipped Liner and Standard Acetabular Cups
No full textThis dataset relates to the geometric modelling of impingement during dislocation-prone activities of daily living (ADLs) and walking in standard (STD), dual mobility (DM) and lipped liner (LL) acetabular cup systems
Mean concentration (mg/L) of water chemistry variables found in water samples
No full textData released as supplementary material for the paper 'Walker, J.R., Hassall, C. The effects of water chemistry and lock-mediated connectivity on macroinvertebrate diversity and community structure in a canal in northern England. Urban Ecosyst 24, 491–500 (2021). https://doi.org/10.1007/s11252-020-01053-8'.
Data is mean concentration (mg/L) of water chemistry variables found in water samples from the Leeds-Liverpool Canal in Leeds
University of Leeds Campus iTree Dataset
No full textThis dataset contains information about 1450 trees present on the University of Leeds campus in 2017 and 2018. The dataset accompanies the report Gugan et al., 2019, ‘University of Leeds: Enhancing the Benefits of Trees on Campus’, by United Bank of Carbon & Leeds Ecosystem, Atmosphere and Forest Centre,
University of Leeds; available here: https://leaf.leeds.ac.uk/news/i-tree-leeds-putting-a-value-on-the-citys-trees
Data associated with 'Protein-induced membrane asymmetry modulates OMP folding kinetics and stability'
No full textRaw data associated with the paper "Protein-induced membrane asymmetry modulates OMP folding kinetics and stability" containing fluorescence folding traces, gel images, DLS and electrostatic potential files, as well as underlying figure data
Data associated with 'Unveiling astringency mechanism of plant proteins'
No full textRaw data for all figures in the associated paper 'Unveiling astringency mechanism of plant proteins
Valence Framing in Multi-attribute Decision-making
No full textThis dataset contains responses from an online discrete choice experiment (DCE) designed to examine the effects of valence framing in a multi-attribute decision-making context. Three types of framing were manipulated across different attributes: risky-choice framing (gain vs. loss) was applied to the seat availability attribute, where options were described in terms of either seats free or seats taken; attribute framing (positive vs. negative) was applied to the service quality attribute, with descriptions highlighting either customer satisfaction or dissatisfaction levels; and goal framing (gain vs. loss) was applied to the CO₂ emissions attribute, emphasising either relative emissions saved or missed out on being saved. In each choice task, respondents selected their preferred alternative from two trains defined by these attributes and travel time and cost. The dataset also includes task completion timestamps, demographic information including age, gender, income, and the order in which each respondent completed the choice tasks, as well as self-reported risk preference
Data associated with "Employing Deep Mutational Scanning in the E. coli Periplasm to Decode the Thermodynamic Landscape For Amyloid Formation"
Get PDFDeep 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
Data for Dissolution of Different Animal Hair Yarn in 1-Ethyl-3-methylimidazolium Acetate
No full textThe partial dissolution of cashmere and merino wool yarns in the ionic liquid 1-ethyl-3-methylimidazolium acetate was studied, both with and without pretreatment of the yarns using sodium bisulfite. The cross-sections of both yarn fibers were analyzed using optical microscopy for different dissolution times and temperatures. It was found that the dissolution of cashmere yarn (CY) and merino wool yarn (WY) has two competing processes, one rate limited by disulfide bonds and the other rate limited by hydrogen bonds. The yarn dissolution obeyed time-temperature superposition. From this, two activation energies for each yarn were obtained, one with respect to low temperature (LT) and one for high temperature (HT), ECY LT = 110 ± 12 kJ/mol, ECY HT = 61 ± 6 kJ/mol, EWY LT = 124 ± 14 kJ/mol and EWY HT = 35 ± 1 kJ/mol. The crossover temperature between the low and high temperature regimes was found to be 70°C. The reducing agent (sodium bisulfite) was used to cleave the disulfide bonds in CY and WY. FTIR spectroscopy provided evidence that the disulfide bonds were in fact cleaved during this pretreatment. A single linear regime (instead of two) was found on the Arrhenius graphs of the pretreated cashmere (PCY) and the pretreated merino wool yarn (PWY), strongly confirming our hypothesis that at low temperatures the disulfide bonds determined the rate of dissolution. The subsequent dissolution activation energies were found to be reduced from the low temperature activation energies for the CY and WY, with their values being EPCY = 62 ± 4 kJ/mol and EPWY = 66 ± 3 kJ/mol respectively. With further analysis, the self-diffusion coefficient of [C2mim][OAc] for the CY, PWY and PCY dissolution systems were quantified, and compared to the self-diffusion coefficient of pure [C2mim][OAc] measured using NMR
Data for Hybrid Biocomposites: From Molecular Behaviour to Material Properties in Silk Fibroin/Cellulose Films
No full textData Set for the associated article, "Hybrid Biocomposites: From Molecular Behaviour to Material Properties in Silk Fibroin/Cellulose Films". Hybrid biomaterials of silk fibroin and cellulose offer improvements over single-component alternatives in the pursuit of optimised and sustainable materials: showing superior strength, biocompatibility, and flexibility. We investigate the behaviours of fully dissolved and coagulated hybrid films at various compositions and characterise the system with X-ray diffraction, dynamic mechanical thermal,
thermogravimetric, and mechanical analyses. We confirm a system optimum in modulus, maximum strength, and maximum strain at failure (2.2 GPa, 28 MPa, and 3.3 % respectively) at 85-95 % cellulose and 5-15 % silk fibroin hybrid composition. Thermogravimetric analysis indicates this is due to increasing interaction density in hybrid compositions correlated with the formation of a hybrid mixed phase up to 4 wt %. We recreate conflicting trends in literature showing sample flexibility improving and reducing with addition of silk fibroin and indicate this is due to variations in sample creep and strain rate. We report a slow stress relaxation and time-dependent viscoelasticity causing this, using comparative mechanical tests at different rates of deformation. We propose a slipping mechanism for stress relaxation similar to those seen in other biopolymer-based biological systems, for example actin filaments in cytoskeletons