Revista Jurídica Digital UANDES
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The influence of metal substrate on CRUD build-up under simulated PWR conditions
No full textCRUD deposition tests were carried out on several micro-orifice specimens in a Hastelloy C-276 and a SS 316L flow loop. The results showed that irrespective of the material used for the construction of the discs (SS 304L, Titanium, Alloy 690, Zirlo and Magnesia stabilised Zirconia) no significant differences in term of radial CRUD build-up were observed. The effect of the Ni and Fe cations dissolved in the water was also investigated; the results revealed that CRUD build-up rate increased with the ferrous ions concentration and decreased with nickel ions. Finally, SEM and Energy Dispersive X-Ray Spectroscopy were used to characterise the oxide morphology showing higher particulate build-up for the specimens tested in the Hastelloy autoclave
Sample-efficient Deep Reinforcement Learning with Imaginary Rollouts for Human-Robot Interaction
No full textDeep reinforcement learning has proven to be a great success in allowing agents to learn complex tasks. However, its application to actual robots can be prohibitively expensive. Furthermore, the unpredictability of human behaviorin human-robot interaction tasks can hinder convergence to a good policy. In this paper, we present an architecture that allows agents to learn models of stochastic environments and use them to accelerate learning. We descirbe how an environment model can be learned online and used to generate synthetic transitions, as well as how an agent can leverage these synthetic data to accelerate learning. We validate our approach using an experiment in which a robotic arm has to complete a task composed of a series of actions based on human gestures. Results show that our approach leads to significantly fasterlearning, requiring much less interaction with the environment. Furthermore, we demonstrate how learned models can be used by a robot to produce optimal plans in real world applications
Deploying a Deep Learning Agent for HRI with Potential “end-users” at Multiple Sheltered Housing Sites
No full textWith the global population aging at an alarming rate, the need to find alternative ways to deliver quality assistance is becoming a pressing concern for health and care systems. To promptly provide companion-like assistance, robots need to gain social intelligence in an autonomous way, without relying on human operators. The work described in this paper aims to develop a deep learning agent that, by means of convolutional neural network architecture in the decision making loop, could understand when and how, to interact with one, or more people, gathered in a room. This was done by training a robot to assess the level of user engagement at the initiation of the interaction, so that the robot could detect the person most willing to start interacting. The robot’s performance as a deep learning agent was tested through an experiment with potential “end-users”, following an iterative process, over four days. The deep learning agent was able to take the right decision 59% of the times by the end of the experiment, from an initial success rate of 44% on the first day, proving the potential of such technologies in this application field
Response to: Assessing the risk of bias and publication bias should be integral parts of the systematic review
No full textAstrophysics with the Spatially and Spectrally Resolved Sunyaev-Zeldovich Effects A Millimetre/Submillimetre Probe of the Warm and Hot Universe
No full textIn recent years, observations of the Sunyaev-Zeldovich (SZ) effect havehad significant cosmological implications and have begun to serve as a powerful and independent probe of the warm and hot gas that pervades the Universe. As a few pioneering studies have already shown, SZ observations both complement X-ray observations – the traditional tool for studying the intra-cluster medium – and bring unique capabilities for probing astrophysical processes at high redshifts and out to the low-density regions in the outskirts of galaxy clusters. Advances in SZ observations have largely been driven by developments in centimetre-, millimetre-, and submillimetre-wave instrumentation on ground-based facilities, with notable exceptions including results from the Planck satellite. Here we review the utility of the thermal, kinematic, relativistic, non-thermal, and polarised SZ effects for studies of galaxy clusters and other large scale structures, incorporating the many advances over the past two decades that have impacted SZ theory, simulations, and observations. We also discuss observational results, techniques, and challenges, and aim to give an overview and perspective on emerging opportunities, with the goal of highlighting some of the exciting new directions in this field
An agenda for sustainability transitions research:State of the art and future directions
No full textResearch on sustainability transitions has expanded rapidly in the last ten years, diversified in terms of topics and geographical applications, and deepened with respect to theories and methods. This article provides an extensive review and an updated research agenda for the field, classified into nine main themes: understanding transitions; power, agency and politics; governing transitions; civil society, culture and social movements; businesses and industries; transitions in practice and everyday life; geography of transitions; ethical aspects; and methodologies. The review shows that the scope of sustainability transitions research has broadened and connections to established disciplines have grown stronger. At the same time, we see that the grand challenges related to sustainability remain unsolved, calling for continued efforts and an acceleration of ongoing transitions. Transition studies can play a key role in this regard by creating new perspectives, approaches and understanding and helping to move society in the direction of sustainability.</p
Increased Frequency and Voltage Interactions Affecting Frequency and Transient Stability in Networks with Large Penetration of Renewable Generation
No full textThe paper investigates the frequency and voltage dynamics and stability in power systems with increased penetration of inverter-based renewable energy sources (RES). The case studies presented within the paper show that the frequency dynamics (frequency nadir and rate of change of frequency) is not only affected by the decrease in system inertia but also by increasing frequency/voltage interactions when the proportion of RES exceeds that of synchronous generation. Furthermore, the critical fault clearing Time (CCT) analysis for transient stability indicates that RES fault ride through (FRT) and their settings can have a significant impact on the nearby generators. The studies also demonstrate that voltage and frequency interactions can be reduced and transient stability of synchronous generators improved by applying dynamic voltage support in weak areas of the system
A Methodology for Using GitLab for Software Engineering Learning Analytics
No full textTo bridge the digital skills gap, we need to train more people in Software Engineering techniques. This paper reports on a project exploring the way students solve tasks using collaborative development platforms and version control systems, such as GitLab, to find patterns and evaluation metrics that can be used to improve the course content and reflect on the most common issues the students are facing. In this paper, we explore Learning Analytics approaches that can be used with GitLab and similar tools, and discuss the challenges raised when applying those approaches in Software Engineering Education, with the objective of building a pipeline that supports the full Learning Analytics cycle, from data extraction to data analysis. We focus in particular on the data anonymisation step of the proposed pipeline to explore the available alternatives to satisfy the data protection requirements when handling personal information in academic environments for research purposes
Voices of Kosovo in Manchester
No full textThis article presents a study of eleven oral histories which were undertaken as part of the community oral history project ‘Voices of Kosovo in Manchester’ between 2014 and 2016. The interviewees, who are mainly young adults, recount their experiences during the conflict in Kosovo in the late 1990s, and their move to Manchester, England as refugees in 1999. The study examines the material through the lens of ‘voice’ (Bakhtin): the role of a variety of individual voices, and the role of public voices incorporated in the interviewees’ discourse. It is suggested that the childhood memory of ethno-political conflict lends itself to the expression of a multiplicity of voices
Reflections on the ethics of co-research alongside people living with dementia: a co-operative inquiry.
No full textThis case study is based on a co-operative inquiry project titled ‘The Changing Face of our Neighborhoods’, which is a suite of three cultural heritage films co-produced alongside the Open Doors Research Group in Salford, Greater Manchester, UK (see: https://salfordneighbourhoods.wordpress.com/films/). The Open Doors Research Group operated as a sub-group of the Open Doors Dementia Service which is a peer support group for people living with dementia and their care partners and has been supported by Greater Manchester Mental Health NHS Foundation Trust over the last decade. Co-operative inquiry is part of the participatory research paradigm and is an under-reported and novel approach in the field of dementia research. We worked alongside people living with dementia (with and without capacity) as co-researchers in a collaborative and shared decision-making enterprise. Implementing co-operative inquiry alongside people living with dementia presented a number of challenges for co-researchers and academic researchers alike, and in this case we will share our reflections on some of the main ethical dimensions and shared decision-making processes that were faced over the continuum of the study