13027 research outputs found
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The Cambridge Handbook of the Law, Policy, and Regulation for Human-Robot Interaction
No full textThe Cambridge Handbook of the Law, Policy, and Regulation for Human-Robot Interaction, edited by Woodrow Barfield, Yueh-Hsuan Weng, and Ugo Pagallo, offers a multidisciplinary and cross-cultural exploration of the legal, policy, and regulatory challenges posed by the anthropomorphism of robots and their growing integration into society. This book was published by Cambridge University Press in 2024 and spans 888 pages. The book provides an analysis of the legal and ethical challenges that jurisdictions across the globe are facing in relation to human-robot interactions.The Handbook arrives at a crucial moment, as advances in robotics and artificial intelligence challenge traditional legal frameworks and demand innovative regulatory approaches. Its multidisciplinary scope makes it a valuable resource for technologists, policymakers, and legislators navigating the complexities of robotic design, law, and regulation. This review evaluates the book’s contribution by situating it within the broader discourse of technology governance, particularly in the European context.</p
Exploring the in vitro and in vivo effects of Tip60 inhibition following TH1834 treatment
No full textThe acetyltransferase Tip60 plays critical roles in multiple critical cellular pathways through its functions as an epigenetic and transcriptional regulator, and as a master regulator of the DNA double-strand break response. In cancer, Tip60 is frequently downregulated and mislocalised, contributing to tumour progression at least partly through altered gene expression patterns. Recent evidence also suggests Tip60 has a role in neurological disorders, particularly in processes related to features such as the neurodegeneration seen in Alzheimer’s disease. While some roles for Tip60 have been defined, many roles have been difficult to explore due to its essential role in cell survival, with current approaches including knockouts/siRNA, inducing apoptosis and significantly complicating any analysis of Tip60-regulated activity and signalling.Here we evaluated the efficacy of TH1834, a novel dual-action Tip60 inhibitor targeting both epigenetic regulation and the DNA damage response pathway. TH1834 drug assays against multiple breast cancer subtypes, and in combination with other inhibitors demonstrated significant anti-tumour specificity of TH1834 and its potential synergies with current chemotherapeutics, particularly against aggressive breast cancer subtypes. This approach highlights the potential of targeting epigenetic mechanisms for cancer therapy, which is significant as epigenetic modifications are reversible.Next generation sequencing analysis revealed TH1834-induced transcriptomic changes in clinically relevant breast cancer subtypes, providing insights into unique subtype-specific roles of Tip60. These findings contribute to the growing understanding of precision medicine approaches in breast cancer treatment, emphasizing the importance of molecular profiling for informing chemotherapeutic decisions.Furthermore, our investigation of Tip60's role extends beyond cancer, to its important new role in neurological disorders. We are the first to explore the effects of Tip60 inhibition in neurological tissue in vivo, investigating in vivo effects of TH1834 treatment on the brain, supporting investigations into Tip60’s role in neurodegenerative disorders, and its potential role as a biomarker and therapeutic target.This comprehensive analysis of Tip60's diverse functions both in vivo and in vitro provides valuable insights for both cancer treatment (using TH1834 therapeutically), and foundationally defining TH1834 effects in vivo in neurological tissue.</p
Real-time digital twin and machine learning solutions for hole quality and tool condition monitoring in robotic drilling of composite materials
No full textRobotic drilling is increasingly used in manufacturing, especially in the aerospace industry, due to its flexibility, reach, and efficiency. Unlike traditional CNC machines, robotic systems can handle complex geometries and large-scale drilling tasks needed for aircraft components such as wings. The use of carbon fibre-reinforced polymer (CFRP) in aviation has grown due to its high strength-to-weight ratio, but drilling CFRP is challenging because of its anisotropic and heterogeneous nature, leading to defects such as delamination and fibre pull-out.To address these challenges, precise monitoring and control of the drilling process are essential, making digital twin technology an ideal solution. A digital twin is a digital representation of a physical system that interacts in real-time through data exchange, enabling continuous monitoring, predictive maintenance, and process optimisation. This technology can enhance the efficiency and quality of robotic drilling by detecting and preventing defects before they occur.This thesis introduces a digital twin framework for robotic drilling. Initially, a generic reference model outlines the critical components of robotic drilling operations. A detailed digital twin architecture is then established according to ISO 23247 standards. To demonstrate the framework’s capabilities, a real-time visualisation system for monitoring drilling parameters is implemented, serving as a foundational step toward a fully functional digital twin system.To evaluate the quality of drilled holes in-situ, a hybrid classification model was developed as part of a unified product digital twin. The classifier, trained and tested with a random selection of drilled holes, achieved approximately 90% overall prediction accuracy on unseen holes. This machine learning approach, using a convolutional neural network and support vector machine classifier, can improve inspection reliability while reducing production time for drilled composite components.Subsequently, a process digital twin combining a machine learning model and real-time sensor data of a robotic drill was developed to estimate hole quality and tool condition. An ensemble neural network model, combining an artificial neural network with a genetic algorithm, was used to assess drilled hole quality. The model was tested on the machined holes to relate process input parameters and drilling torques to hole quality. Model predictions were validated with six unseen datasets, with five predicted accurately. A full factorial study using analysis of variance (ANOVA) showed that tool condition is the largest contributor to drilling torque. This real-time monitoring method can improve manufacturing productivity and ensure high-quality drilled components.This thesis on developing both product and process digital twins represents a crucial step towards a fully unified digital twin system. The developed methods, integrating both the product and manufacturing processes, have shown potential in enhancing the precision, efficiency, and quality of robotic drilling operations. By combining real-time data with advanced machine learning models, the approach not only improves in-situ inspection and predictive maintenance but also streamlines manufacturing workflows. As the research progresses, this digital twin framework paves the way for more sophisticated, interconnected systems that can revolutionise production practices in aerospace and other industries.</p
Mathematical modelling of the cold-rolling process
No full textIn this thesis two types of mathematical modelling techniques are used to model metal sheet rolling: the finite element (FE) method and asymptotics-based approaches. The modelling conducted here forms part of a large-scale research project aimed at improving the efficiency and control capabilities of the rolling process. Since large amounts of CO2 are produced globally each year during rolling, it is of utmost importance to continue to improve the fundamental understanding of such metal forming processes in order to reduce waste. In the absence of accurate experimental descriptions of through-thickness stress and strain distributions, the FE model in this thesis provides a necessary benchmark for asymptotics-based models. Given their quick-to-compute nature, asymptotics-based models provide a potential route to online control of the rolling process, if sufficient accuracy with respect to the FE method can be achieved.In the FE analysis of the rolling process in this thesis, the model is carefully developed to give accurate through-thickness predictions of stress and strain distributions during the steady-state cold-rolling process. These through-thickness predictions unveil an oscillatory pattern, which is largely absent in the existing literature, that is shown to have important consequences for residual stress in the rolled sheet. Care is taken by considering the number of elements through thickness, convergence to a steady state, and the avoidance of other numerical artefacts such as shear locking and hourglassing. We find that the meshes used in previous FE models of cold rolling are usually woefully under-resolved, which reduces FE model accuracy in a number of ways. Convergence of roll force and roll torque, used in previous studies to validate models, are shown here to be poor indicators of through-thickness stress and strain convergence. We also show that the through-thickness oscillatory pattern may have important consequences for residual stress predictions and for predicting the curvature of the sheet during asymmetric rolling.In terms of the asymptotic analysis, we begin by considering simple one-dimensional models of the full rolling problem, which includes a rigid-perfectly-plastic analysis inside the roll gap and a linear elastic analysis outside the roll gap. This asymptotics-based model compares reasonably well against FE results for long-and-thin roll gaps since through-thickness variations are less important for these parameter regimes. However, the one-dimensional model performs poorly otherwise, as it fails to capture the oscillatory pattern observed in the FE results. We conduct two-dimensional boundary-layer analysis around the roll-gap entrance to describe the rapid change in stress and strain quantities in this region of the deforming sheet. We also predict the boundary between the sub-yield and at-yield zones in the roll-gap entrance.Although FE models are quite accurate, their slow computation time does not allow for real-time control. Accurate asymptotics-based models such as the rigid-perfectly-plastic analysis conducted by Erfanian et al. (2024) (which captures the oscillatory pattern observed in the FE results) are desirable due to their quick-to-compute nature. These asymptotic models could prove to be crucial for online control to correct for manufacturing errors as they happen.</p
Laser doppler velocimetry measurements in the Limerick bubbly flow rig
No full textThe reliable reproduction of the complex gas-liquid multiphase dynamics of large-scale bubble columns is quite challenging for two-fluid Computational Fluid Dynamics (CFD) simulations due to insufficient accurate experimental data available to improve the hydrodynamic models underpinning these simulations and to validate the simulation results.The primary goal of this thesis was to efficiently employ the Laser Doppler Velocimetry (LDV) technique to study the liquid-phase velocity characteristics in the near-wall region of a large-scale rectangular bubble column (LimBuRig) to create a reliable extensive database for the CFD community for validating various 2-fluid CFD models (used to simulate bubbly flows in bubble columns) and provide suggestions for modifying those. To achieve these objectives, initial LDV measurements were extensively carried out on a small-scale 70x70 mm transparent square flow channel equipped with a single-needle sparger. Conducted mostly during the pandemic times, these experiments were aimed at gaining hands-on experience with the LDV data acquisition process for bubbly flows.After that unique experiments were performed to acquire extensive quantitative data on liquid velocities in a wall layer of the pilot-scale Limerick Bubbly Flow Rig which is 2.5 m in height and has a horizontal cross-sectional area of 400 mm x 200 mm. The liquid velocity data were obtained using 2-D Laser Doppler Velocimetry along several horizontal lines at distances up to 5 mm from the front wall, with and without any co-flow of liquid. Different uniform and non-uniform flow configurations were created by varying the aeration rates and/or liquid co-flow conditions on two square sections on the bottom part of the column, thus allowing the study of the interaction of two different bubbly flows at a certain height above the gas distributors.Data collection was challenging due to the frequent obstruction of the laser beams by the bubbles, noise due to multiple scattering events in the system, and the uneven distribution of seeder particles in the flow, thus giving rise to a very poor data rate at most locations. At a relatively small proportion of the measuring points, the data rate was sufficiently high to allow the reporting of meaningful velocity data including PDFs, spectra, and ACFs.For both with and without liquid co-flow, the velocity pdf histograms of liquid velocities follow a Gaussian-type distribution centered around 0 m/s, suggesting no net liquid circulation at these locations. At most locations, when the data rate is considerably high (~500-1000 Hz) the power spectral densities of liquid velocity fluctuations represent an energy-cascading process (obeying an almost -5/3 power law with deviations at certain frequencies). At other locations, no energy cascade is noticed from the power spectral densities.So we can conclude that near the front walls, a liquid boundary layer has formed and shows locally and intermittently a quasi-turbulence type process where large-scale non-coherent bursts penetrate to take part in the energy transfer process from bigger to smaller scales. </p
A bourdieusian exploration of knowledge sharing practices in the agriculture sector: the case of Uganda
No full textThe agriculture sector constitutes a cornerstone of Uganda's economy, characterized by a diverse array of actors possessing heterogeneous knowledge. However, knowledge sharing among these actors remains limited. The primary aim of this study was to enhance heterogeneous knowledge sharing within the Ugandan agriculture sector.This study applied Pierre Bourdieu’s framework to analyse the sector’s knowledge sharing practices. The sector was conceptualized as a field with various knowledge actors possessing distinct habituses and capitals. Empirically, the study engaged 231 participants belonging to 8 distinct agriculture actor groups, i.e. smallholder farmers, medium scale commercial farmers, high scale commercial farmers, herbalists, technical agriculture specialists, agribusiness players, Government officials and NGO officials. The data revealed three key factors influencing knowledge sharing in the sector: class consciousness, capital and power, and doxa.Class consciousness, shaped by people’s social background and dispositions (habitus) guarantees their membership into social classes, causing agriculture actors to share knowledge only within heir social classes. The varying forms of capital (mostly class-relevant) are a source of different power levels, and lead actors to only share knowledge to enhance or protect their preferred capitals and powers. There is also an established doxa in the sector, which has shaped the unspoken assumptions and established beliefs, including how actors engage in knowledge sharing.Due to these complexities, knowledge sharing across the social classes is limited and is ineffective when forced. The study proposes using medium-scale commercial farmers as boundary spanners to promote knowledge flow across the sector’s social classes. The researcher also calls for inclusive development of agriculture programs and deliberate leadership to disrupt the current field structure, as well as use of mass media to influence a change in actors’ habituses. However, achieving positive results will be a gradual process due to deeply ingrained structural issues within the agricultural sector.</p
The role of music and singing as research methods to improve migrants’ involvement in health research and policy-making
No full textThis commentary explores the potential of arts-based research methods, particularly music and singing, to address issues of participatory inequity and the structural bias this creates in health research systems and policies. Focusing on migration as a pressing public health issue in resettlement countries in the Global North, this commentary’s objective is to investigate the use of such creative methods as a means of improving migrants’ participation in health research, knowledge translation and the development of health policy. In doing so, it challenges the overreliance on cognitively and verbally oriented methods in the Global North, which fail to harness the participatory potential of the whole-body sensorium. Drawing on Palmer et al.’s explanatory theoretical model of change and centralizing the concept of participatory space, it advances this discussion within a participatory health research paradigm. The exploration is further informed by a recent scoping review on the use of music as an arts-based method in migrant health research, as well as two case studies using the Irish World Music Café method. It concludes with the proposal that further exploration of music and singing as mechanisms of change in health research is essential if we are to fully understand whether/how music and singing for participatory space-making may reset the health research agenda, putting meaningful, whole-person engagement at the heart of research to inform systems and policies.</p
A multiscale model for espresso brewing: Asymptotic analysis and numerical simulation
No full textWe present a novel multiscale mathematical model of espresso brewing. The model captures liquid infiltration and flow through a packed bed of ground coffee, as well as coffee solubles transport (both in the grains and in the liquid) and solubles dissolution. During infiltration, a sharp interface separates the dry and wet regions of the bed. A matched asymptotic analysis (based on fast dissolution rates) reveals that the bed can be described by four asymptotic regions: a dry region yet to be infiltrated by the liquid, a region in which the liquid is saturated with solubles and very little dissolution occurs, a slender region in which solubles are rapidly extracted from the smallest grains, and region in which slower extraction occurs from larger grains. The position and extent of each of these regions move with time (one being an intrinsic moving internal boundary layer) making the asymptotic analysis intriguing in its own right. The analysis yields a reduced model that elucidates the rate-limiting physical processes. Numerical solutions of the reduced model are compared to those to the full model, demonstrating that the reduced model is both accurate and significantly cheaper to solve.</p
Ligand-assisted colloidal synthesis of alkali metal-based ternary chalcogenide: nanostructuring and phase control in Na−Cu−S system
No full textThe development of sustainable and tunable materials is crucial for advancing modern technologies. We present a controlled synthesis of colloidal Na–Cu–S nanostructures. To overcome the reactivity difference between Na and Cu precursors toward chalcogens in a colloidal synthesis and to achieve metastable phase formation, we designed a single-source precursor for Cu and S. The decomposition of this precursor creates a Cu–S template into which Na ions diffuse to form metastable Na–Cu–S. By leveraging the reactivity of sulfur precursors, we synthesized Na3Cu4S4 (orthorhombic) and Na2Cu4S3 (monoclinic) nanocrystals with distinct properties. A mechanistic investigation reveals a predictive pathway previously unobserved in alkali-metal-based ternary chalcogenide systems. Further, computational DFT calculations demonstrate that Na3Cu4S4 exhibits metallic characteristics while Na2Cu4S3 is semiconducting, with an optimal band gap for photovoltaic applications. This research advances our understanding of ternary chalcogenide systems and establishes a framework for the rational design of complex nanomaterials.</p
RCT Database for <b>A randomised controlled trial of the effect of a nature–based intervention on climate capability in teenagers</b>
No full textWe are experiencing a climate and biodiversity crisis unprecedented in the history of mankind. This novel randomized controlled trial tested an intervention to change climate capability in teenagers. At baseline, prior to allocation, climate capability was measured using the climate capability scale in all participants. The intervention consisted of weekly online climate education and motivation messages and a supervised field trip. The primary outcome was change in climate capability score between baseline and follow-up. A total of 116 students were invited to participate and 86 (73%) agreed to do so with all completing baseline data and 83 (97%) providing outcome data. There was evidence of a significant intervention effect (p<0.01); with an increase in mean climate capability score of 8.2 (4.9 – 11.5) favoring the intervention. A nature-based intervention increased climate capability in teenagers with an associated rise in eco-anxiety. The trial was registered with ISRCTN on 26/10/24 (No: 46298/ www.isrctn.com/ISRCTN18655072)</p