1,994 research outputs found

    ‘A little bit patronising if I’m being honest’: working-class mothering and expert discourses.

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    Recent early years policy interventions have focussed on the Home Learning Environment. The ‘Home Learning Environment’ relates to the parenting children receive at home, rather than the physical environment in which they live, enabling a focus on individual behaviour. Family and parenting relations have been a target of state intervention for the last century, positioning working-class mothers as deficient and requiring correction. Little is known about how these discourses impact and shape working-class mothering. I explore how intensive parenting and attendant policy and dominant discourses impact on the day-to-day lives of working-class mothers. To do this, I draw on a critical discourse analysis of the BBC’s Tiny Happy People website to discern current ‘good’ mothering discourses being promoted and narrative analysis of twenty biographical interviews with working-class mothers. The interviews revealed a huge gulf between Tiny Happy People’s ‘good’ mother and the women’s lived realities. Absent and ignored were the significant material constraints faced by many of the women and the time burden created by the intensive mothering model being promoted. Working-class mothering values based on relationships and protecting their children from the effects of growing up working-class mean that Tiny Happy People’s good mothering ideals were mainly rejected as unnecessary or unrealistic by the women interviewed. Policy and other initiatives aimed at working-class people must acknowledge the reality of their lives and target improvements to inadequate housing provision and a labour market which creates low-paid, precarious employment; these initiatives would dramatically transform family life. This research provides the first academic analysis of the BBC’s Tiny Happy People. It highlights the gulf between those in positions of power (whether within government or the media) and the working-class women interviewed

    Computational Modelling of the Plasma in the Charge Exchange Thruster

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    The Charge Exchange Thruster (CXT) is a novel plasma thruster that produces thrust via energetic neutrals leaving the device. This is done by accelerating ions with an electrostatic potential inside of a so-called hollow cathode device: some of these ions then undergo charge exchange and leave the thruster as energetic neutrals whilst others contribute to the formation of an electrical discharge inside the thruster. In this thesis a new 2D-3V particle-in-cell-Monte Carlo (PIC-MCC) simulation code is developed and tested with the purpose of modelling the plasma inside the CXT. This code includes multiple chemical processes involving hydrogen ions, atoms, and molecular species, an external circuit simulation, probabilistic reflections from boundaries, and the generation of secondary electrons, all of which are found to be vital in the plasma initiation and development. The new PIC-MCC code is benchmarked successfully against the theoretical plasma sheath width as well as experimental Paschen curves for a parallel plate discharge, being found to reproduce these results well. Similarly, by modelling hollow cathode discharge systems it is found that the code can reproduce two effects specific to hollow cathode devices, a higher plasma density inside the cathode than outside, as well as beams of energetic neutrals. The code was able to reproduce the experimental results of the original CXT paper reasonably well but suffered from numerical instabilities that prevented the simulation from modelling the discharge in a steady state. It was found that simulating the thruster in a lower pressure discharge mode did not produce as much thrust but was able to reach a steady state and was numerically stable over timescales of tens of microseconds. Future work on investigating the cause of the numerical instabilities at high pressures, as well as a more complex model for the background gas dynamics in the thruster are recommended

    Context-Dependent Acquisition of Antimicrobial Resistance Mechanisms

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    Natural transformation is a process whereby bacteria actively take up free DNA from the environment while in a physiological state termed competence. Uptaken DNA is then recombined into the recipient’s genome or reconverted into extra-chromosomal genetic elements. The inducing stimuli for competence vary widely between transformable species and competence induction is affected by a host of abiotic factors found in bacterial environments. Natural transformation is recognised to be responsible for the dissemination of antimicrobial resistance genes both within and between species, contributing to the global antimicrobial resistance crisis threatening modern medicine. Despite being the first mechanism of horizontal gene transfer discovered, the evolutionary benefits of natural transformation are still under debate. This thesis is comprised of four standalone research chapters which aimed 1) to determine if chemotherapeutic compounds affect the transformation frequencies of transformable bacteria. This provides important information which can have implications on the contraction of a life-threatening infection in cancer patients. 2) to determine if other environmentally relevant bacteria affect the transformation frequencies of transformable bacteria. Understanding the contexts under which bacteria transform in their natural environments can help us to predict the spread of antimicrobial resistance mechanisms via natural transformation. 3) to produce a resource of genomic information for the scientific community, allowing researchers to improve our understanding of the Acinetobacter genus. And 4) to determine if environmentally relevant bacteria affect the transformation frequencies of transformable bacteria to find evidence for the sex hypothesis for natural transformation. This was performed by using biotic interactions as a selection pressure and DNA from a range of related species as a substrate for transformation. Together, these chapters provide information about the contexts under which transformation is both regulated and selected for in realistic environmental contexts. Enhancing our understanding of how and when bacteria naturally transform, in both natural and clinical environments, can help us to monitor and establish preventative measures to limit the spread of antimicrobial resistance genes between bacteria

    Multidisciplinary perspectives on Artificial Intelligence and the law

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    This open access book presents an interdisciplinary, multi-authored, edited collection of chapters on Artificial Intelligence (‘AI’) and the Law. AI technology has come to play a central role in the modern data economy. Through a combination of increased computing power, the growing availability of data and the advancement of algorithms, AI has now become an umbrella term for some of the most transformational technological breakthroughs of this age. The importance of AI stems from both the opportunities that it offers and the challenges that it entails. While AI applications hold the promise of economic growth and efficiency gains, they also create significant risks and uncertainty. The potential and perils of AI have thus come to dominate modern discussions of technology and ethics – and although AI was initially allowed to largely develop without guidelines or rules, few would deny that the law is set to play a fundamental role in shaping the future of AI. As the debate over AI is far from over, the need for rigorous analysis has never been greater. This book thus brings together contributors from different fields and backgrounds to explore how the law might provide answers to some of the most pressing questions raised by AI. An outcome of the Católica Research Centre for the Future of Law and its interdisciplinary working group on Law and Artificial Intelligence, it includes contributions by leading scholars in the fields of technology, ethics and the law.info:eu-repo/semantics/publishedVersio

    Climate Change and Critical Agrarian Studies

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    Climate change is perhaps the greatest threat to humanity today and plays out as a cruel engine of myriad forms of injustice, violence and destruction. The effects of climate change from human-made emissions of greenhouse gases are devastating and accelerating; yet are uncertain and uneven both in terms of geography and socio-economic impacts. Emerging from the dynamics of capitalism since the industrial revolution — as well as industrialisation under state-led socialism — the consequences of climate change are especially profound for the countryside and its inhabitants. The book interrogates the narratives and strategies that frame climate change and examines the institutionalised responses in agrarian settings, highlighting what exclusions and inclusions result. It explores how different people — in relation to class and other co-constituted axes of social difference such as gender, race, ethnicity, age and occupation — are affected by climate change, as well as the climate adaptation and mitigation responses being implemented in rural areas. The book in turn explores how climate change – and the responses to it - affect processes of social differentiation, trajectories of accumulation and in turn agrarian politics. Finally, the book examines what strategies are required to confront climate change, and the underlying political-economic dynamics that cause it, reflecting on what this means for agrarian struggles across the world. The 26 chapters in this volume explore how the relationship between capitalism and climate change plays out in the rural world and, in particular, the way agrarian struggles connect with the huge challenge of climate change. Through a huge variety of case studies alongside more conceptual chapters, the book makes the often-missing connection between climate change and critical agrarian studies. The book argues that making the connection between climate and agrarian justice is crucial

    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

    20th SC@RUG 2023 proceedings 2022-2023

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    Adversarial Deep Learning and Security with a Hardware Perspective

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    Adversarial deep learning is the field of study which analyzes deep learning in the presence of adversarial entities. This entails understanding the capabilities, objectives, and attack scenarios available to the adversary to develop defensive mechanisms and avenues of robustness available to the benign parties. Understanding this facet of deep learning helps us improve the safety of the deep learning systems against external threats from adversaries. However, of equal importance, this perspective also helps the industry understand and respond to critical failures in the technology. The expectation of future success has driven significant interest in developing this technology broadly. Adversarial deep learning stands as a balancing force to ensure these developments remain grounded in the real-world and proceed along a responsible trajectory. Recently, the growth of deep learning has begun intersecting with the computer hardware domain to improve performance and efficiency for resource constrained application domains. The works investigated in this dissertation constitute our pioneering efforts in migrating adversarial deep learning into the hardware domain alongside its parent field of research

    Adaptive Microarchitectural Optimizations to Improve Performance and Security of Multi-Core Architectures

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    With the current technological barriers, microarchitectural optimizations are increasingly important to ensure performance scalability of computing systems. The shift to multi-core architectures increases the demands on the memory system, and amplifies the role of microarchitectural optimizations in performance improvement. In a multi-core system, microarchitectural resources are usually shared, such as the cache, to maximize utilization but sharing can also lead to contention and lower performance. This can be mitigated through partitioning of shared caches.However, microarchitectural optimizations which were assumed to be fundamentally secure for a long time, can be used in side-channel attacks to exploit secrets, as cryptographic keys. Timing-based side-channels exploit predictable timing variations due to the interaction with microarchitectural optimizations during program execution. Going forward, there is a strong need to be able to leverage microarchitectural optimizations for performance without compromising security. This thesis contributes with three adaptive microarchitectural resource management optimizations to improve security and/or\ua0performance\ua0of multi-core architectures\ua0and a systematization-of-knowledge of timing-based side-channel attacks.\ua0We observe that to achieve high-performance cache partitioning in a multi-core system\ua0three requirements need to be met: i) fine-granularity of partitions, ii) locality-aware placement and iii) frequent changes. These requirements lead to\ua0high overheads for current centralized partitioning solutions, especially as the number of cores in the\ua0system increases. To address this problem, we present an adaptive and scalable cache partitioning solution (DELTA) using a distributed and asynchronous allocation algorithm. The\ua0allocations occur through core-to-core challenges, where applications with larger performance benefit will gain cache capacity. The\ua0solution is implementable in hardware, due to low computational complexity, and can scale to large core counts.According to our analysis, better performance can be achieved by coordination of multiple optimizations for different resources, e.g., off-chip bandwidth and cache, but is challenging due to the increased number of possible allocations which need to be evaluated.\ua0Based on these observations, we present a solution (CBP) for coordinated management of the optimizations: cache partitioning, bandwidth partitioning and prefetching.\ua0Efficient allocations, considering the inter-resource interactions and trade-offs, are achieved using local resource managers to limit the solution space.The continuously growing number of\ua0side-channel attacks leveraging\ua0microarchitectural optimizations prompts us to review attacks and defenses to understand the vulnerabilities of different microarchitectural optimizations. We identify the four root causes of timing-based side-channel attacks: determinism, sharing, access violation\ua0and information flow.\ua0Our key insight is that eliminating any of the exploited root causes, in any of the attack steps, is enough to provide protection.\ua0Based on our framework, we present a systematization of the attacks and defenses on a wide range of microarchitectural optimizations, which highlights their key similarities.\ua0Shared caches are an attractive attack surface for side-channel attacks, while defenses need to be efficient since the cache is crucial for performance.\ua0To address this issue, we present an adaptive and scalable cache partitioning solution (SCALE) for protection against cache side-channel attacks. The solution leverages randomness,\ua0and provides quantifiable and information theoretic security guarantees using differential privacy. The solution closes the performance gap to a state-of-the-art non-secure allocation policy for a mix of secure and non-secure applications
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