7,487 research outputs found

    LEONARDO: A Pan-European Pre-Exascale Supercomputer for HPC and AI applications

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    A new pre-exascale computer cluster has been designed to foster scientific progress and competitive innovation across European research systems, it is called LEONARDO. This paper describes thegeneral architecture of the system and focuses on the technologies adopted for its GPU-accelerated partition. High density processing elements, fast data movement capabilities and mature software stack collections allow the machine to run intensive workloads in a flexible and scalable way. Scientific applications from traditional High Performance Computing (HPC) as well as emerging Artificial Intelligence (AI) domains can benefit from this large apparatus in terms of time and energy to solution

    UMSL Bulletin 2023-2024

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    The 2023-2024 Bulletin and Course Catalog for the University of Missouri St. Louis.https://irl.umsl.edu/bulletin/1088/thumbnail.jp

    Effects of municipal smoke-free ordinances on secondhand smoke exposure in the Republic of Korea

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    ObjectiveTo reduce premature deaths due to secondhand smoke (SHS) exposure among non-smokers, the Republic of Korea (ROK) adopted changes to the National Health Promotion Act, which allowed local governments to enact municipal ordinances to strengthen their authority to designate smoke-free areas and levy penalty fines. In this study, we examined national trends in SHS exposure after the introduction of these municipal ordinances at the city level in 2010.MethodsWe used interrupted time series analysis to assess whether the trends of SHS exposure in the workplace and at home, and the primary cigarette smoking rate changed following the policy adjustment in the national legislation in ROK. Population-standardized data for selected variables were retrieved from a nationally representative survey dataset and used to study the policy action’s effectiveness.ResultsFollowing the change in the legislation, SHS exposure in the workplace reversed course from an increasing (18% per year) trend prior to the introduction of these smoke-free ordinances to a decreasing (−10% per year) trend after adoption and enforcement of these laws (β2 = 0.18, p-value = 0.07; β3 = −0.10, p-value = 0.02). SHS exposure at home (β2 = 0.10, p-value = 0.09; β3 = −0.03, p-value = 0.14) and the primary cigarette smoking rate (β2 = 0.03, p-value = 0.10; β3 = 0.008, p-value = 0.15) showed no significant changes in the sampled period. Although analyses stratified by sex showed that the allowance of municipal ordinances resulted in reduced SHS exposure in the workplace for both males and females, they did not affect the primary cigarette smoking rate as much, especially among females.ConclusionStrengthening the role of local governments by giving them the authority to enact and enforce penalties on SHS exposure violation helped ROK to reduce SHS exposure in the workplace. However, smoking behaviors and related activities seemed to shift to less restrictive areas such as on the streets and in apartment hallways, negating some of the effects due to these ordinances. Future studies should investigate how smoke-free policies beyond public places can further reduce the SHS exposure in ROK

    Digital Innovations for a Circular Plastic Economy in Africa

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    Plastic pollution is one of the biggest challenges of the twenty-first century that requires innovative and varied solutions. Focusing on sub-Saharan Africa, this book brings together interdisciplinary, multi-sectoral and multi-stakeholder perspectives exploring challenges and opportunities for utilising digital innovations to manage and accelerate the transition to a circular plastic economy (CPE). This book is organised into three sections bringing together discussion of environmental conditions, operational dimensions and country case studies of digital transformation towards the circular plastic economy. It explores the environment for digitisation in the circular economy, bringing together perspectives from practitioners in academia, innovation, policy, civil society and government agencies. The book also highlights specific country case studies in relation to the development and implementation of different innovative ideas to drive the circular plastic economy across the three sub-Saharan African regions. Finally, the book interrogates the policy dimensions and practitioner perspectives towards a digitally enabled circular plastic economy. Written for a wide range of readers across academia, policy and practice, including researchers, students, small and medium enterprises (SMEs), digital entrepreneurs, non-governmental organisations (NGOs) and multilateral agencies, policymakers and public officials, this book offers unique insights into complex, multilayered issues relating to the production and management of plastic waste and highlights how digital innovations can drive the transition to the circular plastic economy in Africa. The Open Access version of this book, available at https://www.taylorfrancis.com, has been made available under a Creative Commons Attribution-Non Commercial-No Derivatives (CC-BY-NC-ND) 4.0 license

    Development of a SQUID magnetometry system for cryogenic neutron electric dipole moment experiment

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    A measurement of the neutron electric dipole moment (nEDM) could hold the key to understanding why the visible universe is the way it is: why matter should predominate over antimatter. As a charge-parity violating (CPV) quantity, an nEDM could provide an insight into new mechanisms that address this baryon asymmetry. The motivation for an improved sensitivity to an nEDM is to find it to be non-zero at a level consistent with certain beyond the Standard Model theories that predict new sources of CPV, or to establish a new limit that constrains them. CryoEDM is an experiment that sought to better the current limit of dn<2.9×1026e|d_n| < 2.9 \times 10^{-26}\,e\,cm by an order of magnitude. It is designed to measure the nEDM via the Ramsey Method of Separated Oscillatory Fields, in which it is critical that the magnetic field remains stable throughout. A way of accurately tracking the magnetic fields, moreover at a temperature 0.5\sim 0.5\,K, is crucial for CryoEDM, and for future cryogenic projects. This thesis presents work focussing on the development of a 12-SQUID magnetometry system for CryoEDM, that enables the magnetic field to be monitored to a precision of 0.10.1\,pT. A major component of its infrastructure is the superconducting capillary shields, which screen the input lines of the SQUIDs from the pick up of spurious magnetic fields that will perturb a SQUID's measurement. These are shown to have a transverse shielding factor of >1×107> 1 \times 10^{7}, which is a few orders of magnitude greater than the calculated requirement. Efforts to characterise the shielding of the SQUID chips themselves are also discussed. The use of Cryoperm for shields reveals a tension between improved SQUID noise and worse neutron statistics. Investigations show that without it, SQUIDs have an elevated noise when cooled in a substantial magnetic field; with it, magnetostatic simulations suggest that it is detrimental to the polarisation of neutrons in transport. The findings suggest that with proper consideration, it is possible to reach a compromise between the two behaviours. Computational work to develop a simulation of SQUID data is detailed, which is based on the Laplace equation for the magnetic scalar potential. These data are ultimately used in the development of a linear regression technique to determine the volume-averaged magnetic field in the neutron cells. This proves highly effective in determining the fields within the 0.10.1\,pT requirement under certain conditions

    Speculative futures on ChatGPT and generative artificial intelligence (AI): a collective reflection from the educational landscape

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    While ChatGPT has recently become very popular, AI has a long history and philosophy. This paper intends to explore the promises and pitfalls of the Generative Pre-trained Transformer (GPT) AI and potentially future technologies by adopting a speculative methodology. Speculative future narratives with a specific focus on educational contexts are provided in an attempt to identify emerging themes and discuss their implications for education in the 21st century. Affordances of (using) AI in Education (AIEd)and possible adverse effects are identified and discussed which emerge from the narratives. It is argued that now is the best of times to define human vs AI contribution to education because AI can accomplish more and more educational activities that used to be the prerogative of human educators. Therefore, it is imperative to rethink the respective roles of technology and human educators in education with a future-oriented mindse

    The Development of Microdosimetric Instrumentation for Quality Assurance in Heavy Ion Therapy, Boron Neutron Capture Therapy and Fast Neutron Therapy

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    This thesis presents research for the development of new microdosimetric instrumentation for use with solid-state microdosimeters in order to improve their portability for radioprotection purposes and for QA in various hadron therapy modalities. Monte Carlo simulation applications are developed and benchmarked, pertaining to the context of the relevant therapies considered. The simulation and experimental findings provide optimisation recommendations relating to microdosimeter performance and possible radioprotection risks by activated materials. The first part of this thesis is continuing research into the development of novel Silicon-on-Insulator (SOI) microdosimeters in the application of hadron therapy QA. This relates specifically to the optimisation of current microdosimeters, development of Monte Carlo applications for experimental validation, assessment of radioprotection risks during experiments and advanced Monte Carlo modelling of various accelerator beamlines. Geant4 and MCNP6 Monte Carlo codes are used extensively in this thesis, with rigorous benchmarking completed in the context of experimental verification, and evaluation of the similarities and differences when simulating relevant hadron therapy facilities. The second part of this thesis focuses on the development of a novel wireless microdosimetry system - the Radiodosimeter, to improve the operation efficiency and minimise any radioprotection risks. The successful implementation of the wireless Radiodosimeter is considered as an important milestone in the development of a microdosimetry system that can be operated by an end-user with no prior knowledge

    SiPM detector timing response study for the electron-ion collider

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    The Electron-Ion Collider (EIC) will be a new high luminosity large-scale and high polarization collider designed to investigate the QCD dynamics in the nucleons with unprecedented precision. It is planned to be built at the Brookhaven National Lab in the US. Through a dRICH prototype, the performance of Silicon PhotoMultipliers (SiPM), the baseline photo-sensor candidate for the dRICH was tested. The employed SiPM readout electronics chip, ALCOR, provides the time-of-hit measurement through the rollover, coarse and fine time contributions. In this dissertation, a study on the refinement of the Time Resolution of the Reference Timing system (owing to the fine time correction) is presented. The corrections applied in order to improve the value of the system Time Resolution is based on parameters obtained from the measured fine time component of the registered time coincidence signals. The performance of the calibration procedure described, several checks were performed on dedicated channels. The results show that it represents an accurate approximation for the correction of 90% of the analysed data. The performance of the studied SiPMs displayed satisfying results in both applications - the Imaging SiPMs were successful in registering the Cherenkov light signal and the Timing SiPMs provided a Reference Time value which allowed to correctly track the signal time-of-hits. The Reference Timing system was calibrated to provide a measured Time Resolution of 135 ± 2 ps. A preliminary study of the Imaging sensor Time Resolution, which for was calculated to be for a single photoelectron within approximately 500 ps, indicates that the value of the Timing system Time Resolution is adequate for the framework. Note that although these preliminary Time Resolution illustrate satisfactory results, they do not include corrections for effects such as time walk, time over threshold or low sensor bias voltage working conditions, which would presumably further improve the results

    Beam scanning by liquid-crystal biasing in a modified SIW structure

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    A fixed-frequency beam-scanning 1D antenna based on Liquid Crystals (LCs) is designed for application in 2D scanning with lateral alignment. The 2D array environment imposes full decoupling of adjacent 1D antennas, which often conflicts with the LC requirement of DC biasing: the proposed design accommodates both. The LC medium is placed inside a Substrate Integrated Waveguide (SIW) modified to work as a Groove Gap Waveguide, with radiating slots etched on the upper broad wall, that radiates as a Leaky-Wave Antenna (LWA). This allows effective application of the DC bias voltage needed for tuning the LCs. At the same time, the RF field remains laterally confined, enabling the possibility to lay several antennas in parallel and achieve 2D beam scanning. The design is validated by simulation employing the actual properties of a commercial LC medium

    Machine learning approach towards predicting turbulent fluid flow using convolutional neural networks

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    Using convolutional neural networks, we present a novel method for predicting turbulent fluid flow through an array of obstacles in this thesis. In recent years, machine learning has exploded in popularity due to its ability to create accurate data driven models and the abundance of available data. In an attempt to understand the characteristics of turbulent fluid flow, we utilise a novel convolutional autoencoder neural network to predict the first ten POD modes of turbulent fluid flow. We find that the model is able to predict the first two POD modes well although and with less accuracy for the remaining eight POD modes. In addition, we find that the ML-predicted POD modes are accurate enough to be used to reconstruct turbulent flow that adequately captures the large-scale details of the original simulation
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