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The Football Association's Women’s Super League and female soccer fans: fan engagement and the importance of supporter clubs
Get PDFThe global soccer market has seen a growth in the professionalization of women’s teams and as a result, spectatorship and fandom have augmented. Women’s soccer was historically perceived as a taboo; however, stakeholder support has generated visibility and enhanced commercialization opportunities. The Football Association in England instituted the Women’s Super League (hereafter WSL) during 2010, and the first season commenced in 2011 with eight teams. Subsequently, in 2021 there were 12 professional women’s teams in the top-tier of the league and 11 teams in the championship. A qualitative case study approach is utilized, via the use of semi-structured interviews to explore the demographics and motives of women who watch soccer at the elite level and their socialization into fan communities. The study concludes by acquiring an understanding of the consumption of female soccer fans within the WSL and focuses upon the relationship between supporter clubs and fan socialization
Society for Acute Medicine Benchmarking Audit 2021 (SAMBA21): assessing national performance of acute medicine services
No full textIntroduction: The Society for Acute Medicine Benchmarking Audit 2021 (SAMBA21) took place on 17th June 2021, providing the first assessment of performance against the Society for Acute Medicine's Clinical Quality Indicators (CQIs) within acute medical units since the start of the COVID-19 pandemic.
Methods: All acute hospitals in the UK were invited to participate. Data were collected on unit structure, and for patients admitted to acute medicine services over a 24-hour period, with follow-up at 7 days.
Results: 158 units participated in SAMBA21, from 156 hospitals. 8973 patients were included. The number of admissions per unit had increased compared to SAMBA19 (Sign test p<0.005). An early warning score was recorded within 30 minutes of hospital arrival in 77.4% of patients. 87.4% of unplanned admissions were seen by a tier 1 clinician within 4 hours of arrival. Overall, the medical team performed the initial clinician assessment for 36.4% of unplanned medical admissions. More than a third of medical admissions had their initial assessment in Same Day Emergency Care (SDEC) in 25.4% of hospitals. 62.1% of unplanned admissions were seen by two other clinical decision makers prior to consultant review. Of those unplanned admissions requiring consultant review, 67.8% were seen within the target time. More than a third of unplanned admissions were discharged the same day in 41.8% of units.
Conclusion: Performance against the CQIs for acute medicine was maintained in comparison to previous rounds of SAMBA, despite increased admissions. There remains considerable variation in unit structure and performance within acute medical services
Positive psychology pioneers: Mihaly Csiksentmihalyi's power and potential to influence mental health nursing
No full textThis article is the second in a series that celebrates the work of positive psychologists and how their work has the power and potential to influence mental health nursing practice. Focusing on Mihaly Csikszentmihalyi (1934–2021) and his work on flow will help to bring interest and understanding to this exciting and developing area of mental health nursing practice. The practical activities provided in the article will help the reader increase their own awareness of flow to develop its use and transferability within their own life
An investigation of determinants of outsourcing in two Chinese hospitals: the intrinsic impacts and influence of cultural factors towards outsourcing
Get PDFIt is acknowledged in the literature that most understanding and knowledge on healthcare
outsourcing are not derived from the healthcare sector but from other industries. Previous
research on outsourcing in China mainly focus on studying China as an outsourcing
destination. It is in this context that this research has explored the conceptual validity of
the factors affecting outsourcing identified in the Western outsourcing literature in a
public and a private hospital in China. A theoretical framework was developed from the
literature whereby management at both hospitals were interviewed to identify the factors
affecting outsourcing in the two Chinese hospitals. In the absence of guidance from the
existing literature in making cultural adaptions and adjustments in implementing
outsourcing in China, this research provides valuable and empirical insights into how
Guanxi and Mianzi has guided and shaped the social behaviour on the basis of reciprocal
obligations in building a highly trusted and committed outsourcing partnership. This
original finding demonstrates how Guanxi and Mianzi contribute to enhance the loyalty
and commitment of suppliers and employees, in lieu of contracts in Western outsourcing
context, which has provided profound understanding on the impacts of informal controls
in implementing a Western developed model in Hospital A and Hospital B. The
development of two revised conceptual frameworks has clearly contributed to fill the
literature gap and provided insights into the decision-making process in a non-Western
context of implementing outsourcing in the Chinese healthcare sector
Use of regional computing to minimize the social big data effects
Get PDFSmart devices are commonly used these days, especially in smart cities, resulting in massive social media engagement and heavy workload generation. Statistics show that over 4.41 billion people will subscribe to social media by 2025, which covers the majority of the world’s population. Its versatility and enriched features allow users to upload and download large data (e.g. High Definition (HD)) videos and HD live streaming). This heavy workload overburdens the mainstream network and social media cloud, increasing the delay and costs for instant communications. To cope with the aforementioned challenges, this paper aims to minimize the social big data effects on the mainstream network and the social media cloud servers. In connection with these objectives, a survey result shows that 75% of social connections originate from the local region, and their data has no need for instant migration to the remote cloud servers. We extended the Edge/Fog computing concept to create Regional Computing (RC) for Social Media Platforms (SMP). These servers are created at the regional level. Initially, the data is stored and processed at regional computing servers and later on, in off-peak hours, migrated to the cloud servers. The initial result shows that the regional computing servers filter the content regionally and minimize the burden on the mainstream network. It also reduces the cloud server’s workload, resulting in minimal delays and costs
ECDSA based water bodies prediction from satellite images with UNet
Get PDFDetection of water bodies from satellite images plays a vital role in research development.
It has a wide range of applications like the prediction of natural disasters, detecting drought and
flood conditions. There were few existing applications that focused on detecting water bodies that
are becoming extinct in nature. The dataset to train this deep learning model is taken from Kaggle.
It has two classes namely water bodies and masks. There is a total of 2841 sentinel-2 satellite images
with corresponding 2841 masks. Additionally, the present work focuses on using UNet, Tensorflow
to detect the water bodies. It uses a Nadam optimizer to reduce the losses. It also finds best-optimized parameters for the activation function, a number of nodes in each layer. This proposed model
achieves integrity by embedding a security feature Elliptic Curve Digital Signature Algorithm (ECDSA). It generates a digital signature for the predicted area of water bodies which helps to secure
the key and the detected water bodies while transmitting in a channel. Thus the proposed model
ensures the performance accuracy of 94% which can also work the same for edge detection, detection in blurred and low-resolution images. The model is highly robust
Hospitals management transformative initiatives; towards energy efficiency and environmental sustainability in healthcare facilities
Get PDFEnergy-saving is a growing challenge worldwide due to population growth, economic activity, and high consumption rates that are unsustainable in the long term. Healthcare facilities and hospitals face the challenge of increases in operational costs. This research aims to appraise challenges to adopting energy-saving policies, and proposes a roadmap for sustainability and energy efficiency management in hospitals and healthcare facilities.
Eight hospitals were examined as case studies through qualitative interviews with hospital senior management, executives, and healthcare facilities managers in addition to collecting relevant data from the literature; there is critical appraisal, and content analysis of this data.
The research established factors influencing implementation and challenges to energy-saving strategies. The research proposed guidelines for efficient energy management in hospitals and healthcare facilities. The research concluded that best performance is secured by integrating the proposed guidelines with the adoption of ISO 50001 energy management systems to achieve the United Nations’ (UN) sustainable development goal (SDGs) – SDG7 ‘affordable and clean energy.’
The study is limited to the initiatives/experiences of the hospitals studied in the MENA region.
The research findings, conclusions, recommendations, and proposed guidelines enrich the body of knowledge. This will allow industry key stakeholders, hospitals and healthcare facilities managers to overcome challenges of implementing energy management. In addition, adopting the proposed guidelines will improve energy efficiency and help hospitals in green initiatives as they seek to demonstrate their support for UN SDGs
David Vann’s "Legend of a suicide": Dismantling the trauma paradigm
Get PDFThis article argues that David Vann’s Legend of a Suicide (2008) offers us a culturally significant exploration of hegemonic theories around how we understand, or are said to understand, the temporality of trauma, its effect upon identity via its effect upon memory, and its representation in narrative. Moreover, the specific structure of Vann’s text as a short story cycle enables it to present, query and disrupt ways of thinking about chronology, narrative, and identity, such that it offers a productive modeling of the complications inherent in adhering to exclusionary and prescriptive ideas about how trauma might be narrated
Evolution and evaluation: sarcasm analysis for Twitter data using sentiment analysis
Get PDFThis paper addresses the evolution and evaluation of sarcasm in textual form. The growing popularity of
social networking sites is well known, and every individual generates a whole new set of opinions in form of blogs, micro-posts, etc. Sentiment analysis is one of the fastest evolving aspects of artificial intelligence categorizing opinions under
positive, negative, or neutral sentiments. One such part of sentiment analysis is sarcasm. Sarcasm is becoming a common
phenomenon in networking sites where expressing murky feelings wrapped by positive words for conveying contempt is
highly used, making it difficult to understand the actual meaning of a statement. When reading customer reviews or
complaints, it might be helpful to understand the consumers' genuine intentions in order to enhance the efficiency of
customer support or after-sales services. In this paper, different classifiers- Decision Tree, Naïve Bayes, K-Nearest, and
Support Vector machine are used to predict a statement under the category sarcastic or non-sarcastic using tweeter data,
the following proposed methodology is used for the experimental evaluation concluding that the given classifiers SVM
gains the highest accuracy of 93%, whereas Naïve Bayes and Decision Tree are performing well with an accuracy of 83%
and 86% respectively along with the lowest of 51% attained by KNN
A tale of two Peters: an analysis of the life of Peter Green using collaborative/community autoethnography and digital team ethnography
Get PDFThe purpose of this analysis was to mirror the late guitarist Peter Green’s life experiences through insights from Andrew Voyce, who recovered from mental illness, and expertise from Peter Bryngelsson, a Swedish professional musician and author.
The authors used a mixed method of collaborative autoethnography, psychobiography and digital team ethnography.
Despite having not previously attracted academic interest, Peter Green’s experiences of mental health problems and his return to recording and performance provide a rich data source when mirrored and compared to the lives and experiences of Andrew Voyce and Peter Bryngelsson.
The main limitation of this piece of work is that Peter Green died in 2020. During the process of writing the authors have had to follow different, mostly unacademic, sources which have described various parts of Peter Green’s life. The authors have given examples and drawn conclusions from their own lives as well as from academic sources, which they have found appropriate.
Both Andrew Voyce’s and Peter Bryngelsson’s stories would be helpful when it comes to a deeper understanding as to why Peter Green ‘took a left turn’ i.e., turned his back on an accepted life style.
Acid casualty is a problem connected to both mental distress and to the music industry. Peter Bryngelsson’s story tells us that one can remain sane and drug free and still be an influential and creative musician.
The analysis has brought together two stories of mental distress in combination with insights