19684 research outputs found
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Data for: Thermoelectric performance of oriented SrTiO3 nanofilms containing Σ3{111} grain boundary interfaces
No full textCharacterization of Electromechanical Transmissions in the FDM 3D Printing Process Enables for Condition Monitoring via Multi-information Fusion
No full textFused Deposition Modeling (FDM) 3D printing has emerged as a highly utilized technology worldwide due to its user-friendly operation, ability to work with several materials, and environmentally conscious approach. Nevertheless, the limitations of technological development result in the persistence of weaknesses in FDM 3D printing, such as extended printing duration, irregularities in the electromechanical transmission system, and inconsistent printing quality. The study aims to investigate online condition monitoring methods in the FDM 3D printing process, concentrating especially on the fusion of many information sources. Prior to this, the optimal placement of the fixed sensors has been deliberated. Subsequently, an examination was conducted on the attributes of the printing route and the optimal conditions of the synchronous transmission belt using multi-information. Furthermore, an analysis was performed on the distinctive qualities of each signal in order to establish a correlation between the signals and the 3D printing procedure. Lastly, the efficacy of each signal will be examined to suggest the need for additional investigation. Current evidence suggests that mounting the sensor on the nozzle module yields higher efficiency compared to alternative mounting sites. Additionally, the vibration frequency and current signals provide clear insights into the printing process and the condition of the synchronous transmission belt.</p
Digital health interventions for occupational burnout in healthcare professionals:a multi-site randomised non-inferiority trial
No full textBackground: Occupational burnout affects between 11 % and 30 % of healthcare professionals and is associated with staff sickness, job turnover, increased costs and poorer quality of care. This study aimed to compare the effects of two theoretically distinctive interventions for burnout in healthcare professionals. Methods: This multi-site randomised non-inferiority trial recruited 465 healthcare professionals working across 20 National Health Service (NHS) providers in England. Recruitment took place between October 1, 2020 and June 30, 2021. Participants were randomly assigned to digital health interventions based on cognitive behavioural therapy (CBT; n = 227) or job crafting (JC; n = 238), each of which lasted 6-weeks and involved participation in weekly webinars (1hr) supplemented by online coping skills modules. The primary outcome (Oldenburg Burnout Inventory) was measured at baseline, after 6 weeks, and after 6 months. Between-group differences were compared using analysis of covariance adjusting for baseline measures, testing a non-inferiority hypothesis. Results: At 6 weeks, the adjusted mean difference of 0.47 (95 % CI: –0.25 to 1.20; p = .197) in the OLBI favoured CBT. Although this difference was not statistically significant, the non-inferiority hypothesis was not supported based on a pre-specified minimum clinically important difference. At 6 months, the adjusted mean difference favoured CBT indicating superiority; 0.80 (95 % CI: 0.05 to 1.54; p = .036). Conclusions: Brief digital health interventions can help to improve occupational burnout and well-being in healthcare professionals. CBT was more effective than JC.</p
Vehicle Wheel Monitoring and Diagnosis Based on the Vibration Signals of an On-Rotor Sensor
No full textWheel bearings and tyres are vital components of various vehicles. Their conditions are one of critical factors influencing fuel efficiency, vehicle handling, ride comfort and safe operations, which are more significantly concerned by modern autonomous vehicles. This study introduces a novel On-Rotor Sensing (ORS) method to collect acceleration responses on wheel hub to obtain more accurate and comprehensive information for on-line monitoring wheel conditions. The method is exemplified by a field experiment when a on road car is equipped with an ORS triaxial MEMS accelerometer and ran with different tyre pressures at different speeds. The high signal to noise data from the ORS allows instantaneous wheel rotation speed to be easily calculated for online wheel lockage monitoring and wheel order tracking analysis. Based on tyre resonance responses in the frequency bands from 70 to 200 Hz, the radial and lateral vibrations give a comprehensive detection of changes in tyre pressures using either changes in spectral amplitudes or spectral centroids. However, the lateral amplitudes along can produce sufficiently good detection in the speed ranges tested. Wheel order tracking analysis can be implemented with the instantaneous speed information, making it possible to observe bearing ball pass frequency outer race (BPFO) to assess bearing health conditions. In addition, the amplitudes of wheel harmonics are more accurate, allowing better monitoring and assessing wheel eccentricity and imbalances.</p
Effects of operation and maintenance costs on the financial sustainability of micro hydropower schemes
No full textImplementation of hydropower, a renewable energy source with lifespan, requires effective operation and maintenance (O&M) strategies. However, existing guidelines lack consensus on estimating O&M costs, particularly for small-scale projects, which may be more sensitive to O&M fluctuations. This study analyses the economic performance of four hydropower schemes, focusing on the impact of O&M costs on several key financial metrics: the Internal Rate of Return (IRR), Net Present Value (NPV) and Levelised Cost of Electricity (LCOE). We show that higher O&M costs reduce financial viability in a scheme-specific manner: scheme 1 becomes unprofitable when O&M costs exceed 3%, dropping its IRR to 1.8%; scheme 2 remains viable up to 4% but fails to meet the minimum 3.5% IRR required for economic feasibility; schemes 3 and 4 are more resilient, maintaining profitability up to 5% O&M costs, with scheme 4 achieving IRR of 10%. We emphasise that hydropower performance is sensitive to capital costs, generation, and O&M costs. Scheme 4 achieved the best balance among these factors. The novelty of this research lies in comparing different O&M cost estimations of hydropower schemes and their effects on NPV, IRR and LCOE, offering insights into O&M cost thresholds and recommending scheme-specific O&M planning.</p
Bioengineering Glioblastoma Cell Migration Conduits to Mimic Complex and Biorelevant Tumour Microenvironments
No full textGlioblastoma (GMB) treatment remains a substantial unmet need due to its aggressive and highly infiltrative characteristics, facilitated by microstructures within brain tissue such as capillaries and neuronal projections. These key features are seldom represented in pre-clinical models that attempt to evaluate underpinning migratory pathways, leaving drug screening efforts and clinical translation futile. Here, our innovative approach towards modelling biorelevant GBM microenvironments incorporates migratory tracts that are synonymous with migratory pathways observed in GBM patients. This study utilises glioma cell lines U87 and U251 to identify preferential migration strategies in response to physiochemical and mechanical gradients that are fashioned using extracellular matrix-like components. GBM spheroids were printed into collagen conduits of varying density, all encased in a non-cell adhesive hydrogel with stiffness akin to brain matter. Using our newly developed and physiologically advanced bioprinted system and following from our group’s previous work on investigating the role of RhoGTPase-activating proteins (ARHGAPs) as potential contributors to GBM therapeutic resistance (Cheng et al, Cell Reports, 2025) we then introduced stable knockdowns of ARHGAP 12 and 29 to elucidate whether a synergistic effect on migration could be initiated with a panel of antimigratory drugs (CCG-1423, rhosin or combination). Using confocal and light-sheet microscopy, MTT viability assays and physical cytometry, distinct differences were observed in phenotype, adhesion, migration and actin polymerisation between models, with models containing ARHGAP 29 knockdowns and drug cocktail combinations displaying significantly reduced migratory activity, increased adhesion within spheroids, reduced F-actin signalling and reduced cell viability. When compared with classical 2D migration models, striking differences were seen in migratory behaviours, supporting the need for more biorelevant models in predicting in vivo responses. From this, we propose that these sophisticated systems are more capable of tailoring novel, personalised treatments for GBM to subsequently improve patient prognosis
Bioinformatic investigation of Gla-domain containing proteins encoded by non-vertebrate species genomes
No full textMartin Birch - Catalyst:The Pivotal Role of Deep Purple’s Sound Engineer on the Classic Mk2 Albums
No full textThe final chapter of Part Two by Jan-Peter Herbst is an appreciation of the pivotal role of Deep Purple Mk2’s sound engineer, Martin Birch in the recording of In Rock, Fireball, Machine Head and the ‘live’ Made in Japan. It examines how he encouraged and captured the loud and distorted, riff heavy, hard rock sound of the Mk2 Purple band in the studio and on stage. In this respect, Herbst seeks to situate Birch’s emergence, as an innovative sound engineer and later producer, as coinciding with the emergence of the heavy metal genre itself and its defining aesthetic criteria: the group pursuit of absolute musical and instrumental loudness. It was this driving aesthetic of pushing sound capture into the ‘red zone’ by means of instrumental speed, aggression, energy, and intensity, that provided the challenge for the young, up-and-coming studio engineers, like Birch, to find a way to capture the ‘live’ sound of the band in the studio and thereby ‘define’ on vinyl the heavy metal sound. But as Herbst also notes, while the pioneering albums of Black Sabbath and their recording engineer Tom Allom (as well as his work with Judas Priest), have been acknowledged as a formative influence on the development of the heavy metal ‘sound,’ Purple’s sound engineer on all their classic albums, has not been afforded the same level of appreciation. Paying tribute to Birch’s contribution to capturing and defining the classic heavy metal sound in the studio and thereby on vinyl, the chapter aims to decipher Birch’s sonic signature by documenting his role in the recording of three of Deep Purple’s classic and hugely influential albums – In Rock, Machine Head, and Made In Japan. The analysis acknowledges Birch’s innovative engineering of heavy metal in its formative phase, both sonically as an art form, but also in respect of the producer’s role, which has become a blueprint for later producers to this day. Birch also recorded and produced Ritchie Blackmore’s Rainbow (1975-1986), David Coverdale’s Whitesnake (1978-1984), later Black Sabbath (1980-1981), and most notably Iron Maiden (1981-1992)
The motherhood penalty in the United Kingdom:An unconditional quantile regression analysis
No full textUtilizing longitudinal data sourced from Understanding Society, this study employs panel methodologies and unconditional quantile regression (UQR) analysis to explore the prevalence and impact of the motherhood penalty within the context of the United Kingdom. Our panel findings underscore the persistent existence of a motherhood penalty among average UK mothers. However, our UQR findings unveil notable variations in the motherhood penalty across the wage distribution. Specifically, our UQR analysis reveals that the motherhood penalty is most pronounced in the bottom half of the wage distribution, remaining statistically significant across all quantiles up to the median. Thereafter, the magnitude of the motherhood penalty diminishes, eventually transitioning into a motherhood premium among the highest earners
Bluetooth Low Energy Dataset Using In-Phase and Quadrature Samples for Indoor Localization
Get PDFOne significant challenge in research is to collect a large amount of data and learn the underlying relationship between the input and the output variables. This article outlines the process of collecting and validating a dataset designed to determine the angle of arrival (AoA) using Bluetooth low energy (BLE) technology. The data, collected in a laboratory setting, are intended to approximate real-world industrial scenarios. This article discusses the data collection process, the structure of the dataset, and the methodology adopted for automating sample labeling for supervised learning. The collected samples and the process of generating ground-truth (GT) labels were validated using the Texas instruments (TIs) phase difference of arrival (PDoA) implementation on the data, yielding a mean absolute error (MAE) at one of the heights without obstacles of 25.71°. The distance estimation on BLE was implemented using a Gaussian process regression algorithm, yielding an MAE of 0.174 m.</p
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