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Relational communication characteristics are an important facet of building effective practitioner-patient care relationships
Get PDFImplications for practice and research
- The quality of healthcare practitioner versus patient relational communication may have a negative or positive impact on patient-centred diabetes care.
- More research is required on approaches to preventing negative patient-practitionerinterpersonal communication experience
Criminal justice and corruption: state power, privatization and legitimacy
Get PDFThis book highlights and examines the level, reach and consequences of corruption in international criminal justice systems. The book argues that corruption in and of criminal justice is an international problem regardless of the jurisdiction and type of political system – democratic, dictatorship or absolute monarchy. It argues that state power combined with the privatization of criminal justice and its policing, custodial institutions and community rehabilitation services is a vast industry within, and across, international jurisdictions that are worth substantial state fund. Criminal Justice and Corruption explains how different theoretical approaches highlight the problem of preventing corruption, discusses the problem of measuring criminal justice corruption, and focuses on individual criminal justice institutions. For each institution Brooks covers key literature and discusses the issues that they face, with a conclusion that reflects on the level and reach of corruption in criminal justice and whether it can maintain its legitimacy, particularly in democratic states
Co-creativity, well-being and agency: A case study analysis of a co-creative arts group for people with dementia
Get PDFAt the heart of this paper is an exploration of artistic co-creativity involving people with dementia and their partners. Co-creativity promotes a relational approach to creativity which nurtures inclusion and participation. This paper investigates how co-creativity can affect well-being from the perspectives of people with dementia and their carers; and explores how well-being and agency might be usefully reconsidered. The article draws on findings from a small-scale study ‘With All’ that focused on music and dance as non-verbal and therefore inclusive artforms. A range of disciplinary perspectives, from psychology, philosophy and social sciences, inform the study. The research used an intrinsic case-study methodology and within this a mixed-methods approach was adopted. This included dialogic interviews, video data analysis and the Canterbury Well-being Scale (CWS). Thematic analysis of the interviews and video data revealed three key themes: autonomy, connections, and art as an enabler. These themes captured the experiences of the participants and facilitated a more nuanced understanding of wellbeing and agency in the context of living with dementia. The analysis of the CWS indicated some improvements in well-being. Following this analysis using multiple data sources, the paper argues that wellbeing and agency are best understood as relational, and ongoing, rather than completed states. Further both wellbeing and agency contain their opposites (ill-being and passivity). This innovative exploration highlighted the importance of co-creative collaboration as a method that was considered valuable by participants, and that therefore should be further considered in future research with people living with dementi
Advocacy journalism, the politics of humanitarian intervention and the Syrian war
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This book focuses on the reporting of human rights in broadly defined times of conflict. It brings together scholarly and professional perspectives on the role of the media in constructing human rights and peacebuilding options in conflict and post-conflict environments, drawing on case studies from Europe, Latin America, the Middle East, Africa, and South Asia. It also provides critical reflections on the challenges faced by journalists and explores the implications of constructing human rights and peacebuilding options in their day-to-day professional activities. The chapters embrace a variety of theoretical, empirical and methodological approaches and will benefit students, scholars and media professionals alike
Closed-loop implantable therapeutic neuromodulation systems based on neurochemical monitoring
Get PDFClosed-loop or intelligent neuromodulation allows adjustable, personalized neuromodulation which usually incorporates the recording of a biomarker, followed by implementation of an algorithm which decides the timing (when?) and strength (how much?) of stimulation. Closed-loop neuromodulation has been shown to have greater benefits compared to open-loop neuromodulation, particularly for therapeutic applications such as pharmacoresistant epilepsy, movement disorders and potentially for psychological disorders such as depression or drug addiction. However, an important aspect of the technique is selection of an appropriate, preferably neural biomarker. Neurochemical sensing can provide high resolution biomarker monitoring for various neurological disorders as well as offer deeper insight into neurological mechanisms. The chemicals of interest being measured, could be ions such as potassium (K+), sodium (Na+ ), calcium (Ca2+ ), chloride (Cl− ), hydrogen (H+ ) or neurotransmitters such as dopamine, serotonin and glutamate. This review focusses on the different building blocks necessary for a neurochemical, closed-loop neuromodulation system including biomarkers, sensors and data processing algorithms. Furthermore, it also highlights the merits and drawbacks of using this biomarker modality
M/EEG-based bio-markers to predict the MCI and Alzheimer's disease: a review from the ML perspective
Get PDFThis paper reviews the state-of-the-art neuromarkers development for the prognosis of Alzheimer's disease (AD) and mild cognitive impairment (MCI). The first part of this paper is devoted to reviewing the recently emerged machine learning (ML) algorithms based on electroencephalography (EEG) and magnetoencephalography (MEG) modalities. In particular, the methods are categorized by different types of neuromarkers. The second part of the review is dedicated to a series of investigations that further highlight the differences between these two modalities. First, several source reconstruction methods are reviewed and their source-level performances explored, followed by an objective comparison between EEG and MEG from multiple perspectives. Finally, a number of the most recent reports on classification of MCI/AD during resting state using EEG/MEG are documented to show the up-to-date performance for this well-recognized data collecting scenario. It is noticed that the MEG modality may be particularly effective in distinguishing between subjects with MCI and healthy controls, a high classification accuracy of more than 98% was reported recently; whereas the EEG seems to be performing well in classifying AD and healthy subjects, which also reached around 98% of the accuracy. A number of influential factors have also been raised and suggested for careful considerations while evaluating the ML-based diagnosis systems in the real-world scenarios
A heterogeneous IoV architecture for data forwarding in vehicle to infrastructure communication
Get PDFThe Internet of vehicles (IoV) is a newly emerged wave that converges Internet of things (IoT) into vehicular networks to benefit from ubiquitous Internet connectivity. Despite various research efforts, vehicular networks are still striving to achieve higher data rate, seamless connectivity, scalability, security, and improved quality of service, which are the key enablers for IoV. It becomes even more critical to investigate novel design architectures to accomplish efficient and reliable data forwarding when it comes to handling the emergency communication infrastructure in the presence of natural epidemics. The article proposes a heterogeneous network architecture incorporating multiple wireless interfaces (e.g., wireless access in vehicular environment (WAVE), long-range wireless fidelity (WiFi), and fourth generation/long-term evolution (4G/LTE)) installed on the on-board units, exploiting the radio over fiber approach to establish a context-aware network connectivity. This heterogeneous network architecture attempts to meet the requirements of pervasive connectivity for vehicular ad hoc networks (VANETs) to make them scalable and adaptable for IoV supporting a range of emergency services. The architecture employs the Best Interface Selection (BIS) algorithm to always ensure reliable communication through the best available wireless interface to support seamless connectivity required for efficient data forwarding in vehicle to infrastructure (V2I) communication successfully avoiding the single point of failure. Moreover, the simulation results clearly argue about the suitability of the proposed architecture in IoV environment coping with different types of applications against individual wireless technologies
Computer vision and deep learning-enabled UAVs: proposed use cases for visually impaired people in a smart city
Get PDFTechnological research and innovation have advanced at a rapid pace in recent years, and one group hoping to benefit from this, is visually impaired people (VIP). Technology may enable them to find new ways of travelling around smart cities, thus improving their quality of life (QoL). Currently, there are approximately 110 million VIP worldwide, and continuous research is crucial to find innovative solutions to their mobility problems. Recent advances such as the increase in Unmanned Aerial Vehicles (UAVs), smartphones and wearable devices, together with an ever-growing uptake of deep learning, computer vision, the Internet of Things (IoT), and virtual and augmented reality (VR)/(AR), have provided VIP with the hope of having an improved QoL. In particular, indoor and outdoor spaces could be improved with the use of such technologies to make them suitable for VIP. This paper examines use cases both indoors and outdoors and provides recommendations of how deep learning and computer vision-enabled UAVs could be employed in smart cities to improve the QoL for VIP in the coming years
Impact of low-e window films on energy consumption and CO2 emissions of an existing UK hotel building
Get PDFIn order to fulfil the UK government’s ambitious goal of 80% reductions in greenhouse gas emissions by 2050 compared to the levels of 1990s, unprecedented measures for improving the energy efficiency of buildings are needed. This study investigates the impact of a specific type of Low-emissivity (Low-E) window film—Thinsulate Climate Control 75—on the holistic energy consumption of an existing United Kingdom (UK) hotel building. Building modelling and energy simulation software EDSL TAS is used to conduct the study. The result of the simulations demonstrates that by applying Thinsulate films, savings in heating, cooling, and total energy consumptions are achieved by 3%, 20%, and 2.7%, respectively. Also 4.1% and 5.1% savings are achieved in annual CO2 emissions and total energy costs, respectively, while the initial costs may be an issue. This study found that application of Low-E window films results in slightly better energy performance of the hotel regarding its heating-dominant climate. The study also recommends using average annual actual energy consumption data for a time range, instead of picking a single year’s data for validating purposes
