1,331 research outputs found
An examination of the verbal behaviour of intergroup discrimination
This thesis examined relationships between psychological flexibility, psychological inflexibility, prejudicial attitudes, and dehumanization across three cross-sectional studies with an additional proposed experimental study. Psychological flexibility refers to mindful attention to the present moment, willing acceptance of private experiences, and engaging in behaviours congruent with one’s freely chosen values. Inflexibility, on the other hand, indicates a tendency to suppress unwanted thoughts and emotions, entanglement with one’s thoughts, and rigid behavioural patterns. Study 1 found limited correlations between inflexibility and sexism, racism, homonegativity, and dehumanization. Study 2 demonstrated more consistent positive associations between inflexibility and prejudice. And Study 3 controlled for right-wing authoritarianism and social dominance orientation, finding inflexibility predicted hostile sexism and racism beyond these factors. While showing some relationships, particularly with sexism and racism, psychological inflexibility did not consistently correlate with varied prejudices across studies.
The proposed randomized controlled trial aims to evaluate an Acceptance and Commitment Therapy intervention to reduce sexism through enhanced psychological flexibility. Overall, findings provide mixed support for the utility of flexibility-based skills in addressing complex societal prejudices. Research should continue examining flexibility integrated with socio-cultural approaches to promote equity
Multidisciplinary perspectives on Artificial Intelligence and the law
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
Cultures of Citizenship in the Twenty-First Century: Literary and Cultural Perspectives on a Legal Concept
In the early twenty-first century, the concept of citizenship is more contested than ever. As refugees set out to cross the Mediterranean, European nation-states refer to "cultural integrity" and "immigrant inassimilability," revealing citizenship to be much more than a legal concept. The contributors to this volume take an interdisciplinary approach to considering how cultures of citizenship are being envisioned and interrogated in literary and cultural (con)texts. Through this framework, they attend to the tension between the citizen and its spectral others - a tension determined by how a country defines difference at a given moment
AI: Limits and Prospects of Artificial Intelligence
The emergence of artificial intelligence has triggered enthusiasm and promise of boundless opportunities as much as uncertainty about its limits. The contributions to this volume explore the limits of AI, describe the necessary conditions for its functionality, reveal its attendant technical and social problems, and present some existing and potential solutions. At the same time, the contributors highlight the societal and attending economic hopes and fears, utopias and dystopias that are associated with the current and future development of artificial intelligence
On the Utility of Representation Learning Algorithms for Myoelectric Interfacing
Electrical activity produced by muscles during voluntary movement is a reflection of the firing patterns of relevant motor neurons and, by extension, the latent motor intent driving the movement. Once transduced via electromyography (EMG) and converted into digital form, this activity can be processed to provide an estimate of the original motor intent and is as such a feasible basis for non-invasive efferent neural interfacing. EMG-based motor intent decoding has so far received the most attention in the field of upper-limb prosthetics, where alternative means of interfacing are scarce and the utility of better control apparent. Whereas myoelectric prostheses have been available since the 1960s, available EMG control interfaces still lag behind the mechanical capabilities of the artificial limbs they are intended to steer—a gap at least partially due to limitations in current methods for translating EMG into appropriate motion commands. As the relationship between EMG signals and concurrent effector kinematics is highly non-linear and apparently stochastic, finding ways to accurately extract and combine relevant information from across electrode sites is still an active area of inquiry.This dissertation comprises an introduction and eight papers that explore issues afflicting the status quo of myoelectric decoding and possible solutions, all related through their use of learning algorithms and deep Artificial Neural Network (ANN) models. Paper I presents a Convolutional Neural Network (CNN) for multi-label movement decoding of high-density surface EMG (HD-sEMG) signals. Inspired by the successful use of CNNs in Paper I and the work of others, Paper II presents a method for automatic design of CNN architectures for use in myocontrol. Paper III introduces an ANN architecture with an appertaining training framework from which simultaneous and proportional control emerges. Paper Iv introduce a dataset of HD-sEMG signals for use with learning algorithms. Paper v applies a Recurrent Neural Network (RNN) model to decode finger forces from intramuscular EMG. Paper vI introduces a Transformer model for myoelectric interfacing that do not need additional training data to function with previously unseen users. Paper vII compares the performance of a Long Short-Term Memory (LSTM) network to that of classical pattern recognition algorithms. Lastly, paper vIII describes a framework for synthesizing EMG from multi-articulate gestures intended to reduce training burden
2007 GREAT Day Program
SUNY Geneseo’s First Annual G.R.E.A.T. Day.https://knightscholar.geneseo.edu/program-2007/1001/thumbnail.jp
2017 GREAT Day Program
SUNY Geneseo’s Eleventh Annual GREAT Day.https://knightscholar.geneseo.edu/program-2007/1011/thumbnail.jp
Measuring the impact of COVID-19 on hospital care pathways
Care pathways in hospitals around the world reported significant disruption during the recent COVID-19 pandemic but measuring the actual impact is more problematic. Process mining can be useful for hospital management to measure the conformance of real-life care to what might be considered normal operations. In this study, we aim to demonstrate that process mining can be used to investigate process changes associated with complex disruptive events. We studied perturbations to accident and emergency (A &E) and maternity pathways in a UK public hospital during the COVID-19 pandemic. Co-incidentally the hospital had implemented a Command Centre approach for patient-flow management affording an opportunity to study both the planned improvement and the disruption due to the pandemic. Our study proposes and demonstrates a method for measuring and investigating the impact of such planned and unplanned disruptions affecting hospital care pathways. We found that during the pandemic, both A &E and maternity pathways had measurable reductions in the mean length of stay and a measurable drop in the percentage of pathways conforming to normative models. There were no distinctive patterns of monthly mean values of length of stay nor conformance throughout the phases of the installation of the hospital’s new Command Centre approach. Due to a deficit in the available A &E data, the findings for A &E pathways could not be interpreted
Complexity Science in Human Change
This reprint encompasses fourteen contributions that offer avenues towards a better understanding of complex systems in human behavior. The phenomena studied here are generally pattern formation processes that originate in social interaction and psychotherapy. Several accounts are also given of the coordination in body movements and in physiological, neuronal and linguistic processes. A common denominator of such pattern formation is that complexity and entropy of the respective systems become reduced spontaneously, which is the hallmark of self-organization. The various methodological approaches of how to model such processes are presented in some detail. Results from the various methods are systematically compared and discussed. Among these approaches are algorithms for the quantification of synchrony by cross-correlational statistics, surrogate control procedures, recurrence mapping and network models.This volume offers an informative and sophisticated resource for scholars of human change, and as well for students at advanced levels, from graduate to post-doctoral. The reprint is multidisciplinary in nature, binding together the fields of medicine, psychology, physics, and neuroscience
Application of knowledge management principles to support maintenance strategies in healthcare organisations
Healthcare is a vital service that touches people's lives on a daily basis by providing treatment and
resolving patients' health problems through the staff. Human lives are ultimately dependent on the skilled
hands of the staff and those who manage the infrastructure that supports the daily operations of the
service, making it a compelling reason for a dedicated research study. However, the UK healthcare sector
is undergoing rapid changes, driven by rising costs, technological advancements, changing patient
expectations, and increasing pressure to deliver sustainable healthcare. With the global rise in healthcare
challenges, the need for sustainable healthcare delivery has become imperative. Sustainable healthcare
delivery requires the integration of various practices that enhance the efficiency and effectiveness of
healthcare infrastructural assets. One critical area that requires attention is the management of
healthcare facilities.
Healthcare facilitiesis considered one of the core elements in the delivery of effective healthcare services,
as shortcomings in the provision of facilities management (FM) services in hospitals may have much more
drastic negative effects than in any other general forms of buildings. An essential element in healthcare
FM is linked to the relationship between action and knowledge. With a full sense of understanding of
infrastructural assets, it is possible to improve, manage and make buildings suitable to the needs of users
and to ensure the functionality of the structure and processes.
The premise of FM is that an organisation's effectiveness and efficiency are linked to the physical
environment in which it operates and that improving the environment can result in direct benefits in
operational performance. The goal of healthcare FM is to support the achievement of organisational
mission and goals by designing and managing space and infrastructural assets in the best combination of
suitability, efficiency, and cost. In operational terms, performance refers to how well a building
contributes to fulfilling its intended functions.
Therefore, comprehensive deployment of efficient FM approaches is essential for ensuring quality
healthcare provision while positively impacting overall patient experiences. In this regard, incorporating
knowledge management (KM) principles into hospitals' FM processes contributes significantly to ensuring
sustainable healthcare provision and enhancement of patient experiences. Organisations implementing
KM principles are better positioned to navigate the constantly evolving business ecosystem easily.
Furthermore, KM is vital in processes and service improvement, strategic decision-making, and
organisational adaptation and renewal.
In this regard, KM principles can be applied to improve hospital FM, thereby ensuring sustainable
healthcare delivery. Knowledge management assumes that organisations that manage their
organisational and individual knowledge more effectively will be able to cope more successfully with the challenges of the new business ecosystem. There is also the argument that KM plays a crucial role in
improving processes and services, strategic decision-making, and adapting and renewing an organisation.
The goal of KM is to aid action – providing "a knowledge pull" rather than the information overload most
people experience in healthcare FM. Other motivations for seeking better KM in healthcare FM include
patient safety, evidence-based care, and cost efficiency as the dominant drivers. The most evidence exists
for the success of such approaches at knowledge bottlenecks, such as infection prevention and control,
working safely, compliances, automated systems and reminders, and recall based on best practices. The
ability to cultivate, nurture and maximise knowledge at multiple levels and in multiple contexts is one of
the most significant challenges for those responsible for KM. However, despite the potential benefits,
applying KM principles in hospital facilities is still limited. There is a lack of understanding of how KM can
be effectively applied in this context, and few studies have explored the potential challenges and
opportunities associated with implementing KM principles in hospitals facilities for sustainable healthcare
delivery.
This study explores applying KM principles to support maintenance strategies in healthcare organisations.
The study also explores the challenges and opportunities, for healthcare organisations and FM
practitioners, in operationalising a framework which draws the interconnectedness between healthcare.
The study begins by defining healthcare FM and its importance in the healthcare industry. It then discusses
the concept of KM and the different types of knowledge that are relevant in the healthcare FM sector.
The study also examines the challenges that healthcare FM face in managing knowledge and how the
application of KM principles can help to overcome these challenges. The study then explores the different
KM strategies that can be applied in healthcare FM. The KM benefits include improved patient outcomes,
reduced costs, increased efficiency, and enhanced collaboration among healthcare professionals.
Additionally, issues like creating a culture of innovation, technology, and benchmarking are considered.
In addition, a framework that integrates the essential concepts of KM in healthcare FM will be presented
and discussed.
The field of KM is introduced as a complex adaptive system with numerous possibilities and challenges.
In this context, and in consideration of healthcare FM, five objectives have been formulated to achieve
the research aim. As part of the research, a number of objectives will be evaluated, including appraising
the concept of KM and how knowledge is created, stored, transferred, and utilised in healthcare FM,
evaluating the impact of organisational structure on job satisfaction as well as exploring how cultural
differences impact knowledge sharing and performance in healthcare FM organisations.
This study uses a combination of qualitative methods, such as meetings, observations, document analysis
(internal and external), and semi-structured interviews, to discover the subjective experiences of
healthcare FM employees and to understand the phenomenon within a real-world context and attitudes of healthcare FM as the data collection method, using open questions to allow probing where appropriate
and facilitating KM development in the delivery and practice of healthcare FM.
The study describes the research methodology using the theoretical concept of the "research onion". The
qualitative research was conducted in the NHS acute and non-acute hospitals in Northwest England.
Findings from the research study revealed that while the concept of KM has grown significantly in recent
years, KM in healthcare FM has received little or no attention. The target population was fifty (five FM
directors, five academics, five industry experts, ten managers, ten supervisors, five team leaders and ten
operatives). These seven groups were purposively selected as the target population because they play a
crucial role in KM enhancement in healthcare FM. Face-to-face interviews were conducted with all
participants based on their pre-determined availability. Out of the 50-target population, only 25 were
successfully interviewed to the point of saturation. Data collected from the interview were coded and
analysed using NVivo to identify themes and patterns related to KM in healthcare FM.
The study is divided into eight major sections. First, it discusses literature findings regarding healthcare
FM and KM, including underlying trends in FM, KM in general, and KM in healthcare FM. Second, the
research establishes the study's methodology, introducing the five research objectives, questions and
hypothesis. The chapter introduces the literature on methodology elements, including philosophical views
and inquiry strategies. The interview and data analysis look at the feedback from the interviews. Lastly, a
conclusion and recommendation summarise the research objectives and suggest further research.
Overall, this study highlights the importance of KM in healthcare FM and provides insights for healthcare
FM directors, managers, supervisors, academia, researchers and operatives on effectively leveraging
knowledge to improve patient care and organisational effectiveness
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