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Custodian of wealth: an assessment of insurers' risk management practices
No full textUnlike the banking industry, the insurers' risk management framework (RMF) is not governed internationally. For this reason, their risk management (RM) practices are not comparable. We surveyed insurance personnel regarding understanding risk and risk management (URRM), risk identification (RI), risk assessment and analysis (RAA), risk monitoring (RMON), and risk management practices (RMP). These insurance personnel were working at various hierarchical levels in life and non-life insurance. These insurers were operating in developed and emerging insurance market. We took USA and UK insurers as a proxy for developed insurance market. Meanwhile, Chinese, and Pakistani insurers were substituted for emerging insurance market. We analyzed the data through descriptive statistics and an ordered logit model. Our results showed that insurers' RM is stronger, but large differences exist at the hierarchical, insurer type and country levels. Apart from policy implications, our findings suggest that to achieve sustained competitive advantage insurers should minimize these differences
NEURAL NETWORK PREDICTIVE MODELS TO DETERMINE THE EFFECT OF BLOOD COMPOSITION ON THE PATIENT-SPECIFIC ANEURYSM
No full textUsing the data obtained from the computational fluid dynamics simulations, a back-propagation neural network model was developed to predict the velocity magnitudes and the instantaneous wall shear stresses in two patient-specific aneurysms. The models were also used to determine the effect of the blood composition on the rapture risk of the aneurysms. Based on the possible combination, five back propagation models were developed. The architecture of five models is determined based on number of neurons in the hidden layer. All the models in each algorithm were trained and tested. The accuracy of the developed models was evaluated through statistical analysis of the network output in terms of mean absolute error, root mean squared error, mean squared error, and error deviation. According to the results obtained, all BPA effectively predicted velocity magnitude and instantaneous wall shear stress. Model 1 was, however, less accurate when compared to the other five models, as it had one neuron in its hidden layer. The analysis confirms that the neuron number in the hidden layer play a definitive role in predicting the respective outputs. The performance assessment all of the back-propagation models revealed that the error incurred was acceptable. The algorithms' training and testing in this study were satisfactory, since the network output was in reasonably good conformity with the target computational fluid dynamics result
Addiction recovery stories: Bethany Holmes in conversation with Lisa Ogilvie
No full textPurpose: The purpose of this paper is to examine recovery through lived experience. It is part of a series that explores candid accounts of addiction and recovery to identify important components in the recovery process. Design/methodology/approach: The G-CHIME model comprises six elements important to addiction recovery (growth, connectedness, hope, identity, meaning in life and empowerment). It provides a standard to against which to consider addiction recovery, having been used in this series, as well as in the design of interventions that improve well-being and strengthen recovery. In this paper, a first-hand account is presented, followed by a semi-structured e-interview with the author of the account. Narrative analysis is used to explore the account and interview through the G-CHIME model. Findings: This paper shows that addiction recovery is a remarkable process that can be effectively explained using the G-CHIME model. The significance of each component in the model is apparent from the account and e-interview presented. Originality/value: Each account of recovery in this series is unique, and as yet, untold
Engaging young people with sexual health services in general practice surgeries - A qualitative study of health care professionals
No full textBackground:Evidence to date suggests that young people are becoming more sexually active and are forming relationships during the early stages of their lives, sometimes engaging in sexual risk-taking, which contributes to high rates of conception and sexually transmitted infections (STIs). Young people at risk of adverse sexual health outcomes are the least likely to engage with reproductive and sexual health promotion programmes and services (RSHPPs), especially in mainstream clinics such as general practice (GP) surgeries. The study aimed to explore the views and experiences of service providers.Materials and Methods:A qualitative approach to explore the views and experiences of designing and implementing RSHPPs for young people in GP surgeries was used. A total of seven participants were interviewed, including four general practitioners (GPs), two of whom were managers at the practice; one nurse; one healthcare and support worker; and one practice manager.Results:The context of RSHPPs such as local health priorities and partnerships to address STIs and unplanned pregnancies among young people contribute to the implementation and engagement of young people with RSHPPs. Training of GPs, nurses, and support workers helps develop confidence and overcome personal factors by promoting effective engagement of young people with RSHPPs.Conclusion:Addressing local health priorities such as reducing teenage pregnancies and STIs requires organisations to provide RSHPPs in both non-clinical and clinical settings to ensure that RSHPPs are accessible to young people. There is room for improvement in access to RSH for young people in GP surgeries by addressing organisational and structural barriers to access
A vision transformer approach for traffic congestion prediction in urban areas
No full textTraffic problems continue to deteriorate because of the increasing population in urban areas that rely on many modes of transportation, the transportation infrastructure has achieved considerable strides in the last several decades. This has led to an increase in congestion control difficulties, which directly affect citizens through air pollution, fuel consumption, traffic law breaches, noise pollution, accidents, and loss of time. Traffic prediction is an essential aspect of an intelligent transportation system in smart cities because it helps reduce traffic congestion. This article aims to design and enforce a traffic prediction scheme that is efficient and accurate in forecasting traffic flow. Available traffic flow prediction methods are still unsuitable for real-world applications. This fact motivated us to work on a traffic flow forecasting issue using Vision Transformers (VTs). In this work, VTs were used in conjunction with Convolutional neural networks (CNNs) to predict traffic congestion in urban spaces on a city-wide scale. In our proposed architecture, a traffic image is fed to the CNN, which generates feature maps. These feature maps are then fed to the VT, which employs the dual techniques of tokenization and projection. Tokenization is used to convert features into tokens containing Vision information, which are then sent to projection, where they are transformed into feature maps and ultimately delivered to LSTM. The experimental results demonstrate that the vision transformer prediction method based on Spatio-temporal characteristics is an excellent way of predicting traffic flow, particularly during anomalous traffic situations. The proposed technology surpasses traditional methods in terms of precision, accuracy and recall and aids in energy conservation. Through rerouting, the proposed work will benefit travellers and reduce fuel use
Is supported living a pathway to recovery? A preliminary investigation of a new model.
No full textEvidence suggests supported living can improve functioning and reduce need. However, its lack of a clear definition has presented significant challenges to establishing a definitive evaluation of its efficacy. The present study evaluated the efficacy of a defined model of supported living using in terms of reductions made to aspects of clinical and social recovery.A naturalistic, non-controlled assessment was conducted using the Camberwell Assessment of Need Clinical Scale (CAN-C) with a sample of adults with severe and enduring mental illness residing with a UK-based mental health company at one of twelve UK locations.Analysis regarding preliminary outcomes relating to health and social need is presented with comparison between admission and 6-months post-admission (N=90). Additional analysis relating to outcomes at twelve-months is also provided (N=39). Significant outcomes are noted at both timepoints in terms of reducing unmet need and levels of formal and informal help given/required during tenancy.Our findings support that, even in the absence of clinical recovery, opportunities exist to make meaningful and valuable improvements to unmet need and functional independence, with implications for clinical practice in the context of supported living.The findings provide encouraging early indications of the benefits of the model in making meaningful reductions to functional and psychological needs in individuals with severe and enduring mental illness
The Maker Project: Thinking Through Practice – analysing the importance of creativity and skill within education and society.
No full textThere is widespread agreement that UK crafts education is in seriousdecline (Pooley and Rowell, 2016). This has knock-on effects for other areasof education, such as we see in Kneebone’s claim detailing how medicalstudents lack basic fine motor skills related to craft skills.This research suggests ways in which creative practice and craft skills canbe re-invigorated and effectively incorporated into pedagogic activities.This process is explored via the design of a practical, skills-based project(The Maker Project) involving a team of crafts-persons who were given theopportunity to develop and document their practice in a totally openended way. The only stipulation was that they work with the same massproduced chair, and they keep records of their creative process.Data was gathered using mixed methods including open dialogue, semi structured interviews, self-reportage and photo-journaling, followed by apublic survey questionnaire. This data was analysed using a modified andenriched version of Kolb’s model of the Experiential Learning Cycle.Results indicate a range of positive outcomes: pedagogic benefits areeasily achievable, health and wellbeing improvements are stronglyindicated, and creative community activity was enhanced. The analysis ofthe Maker Project provides new information on the ways in which craft skillsand creative problem-solving skills circulate. Inspired by models of wholelife learning, the thesis argues that informal but intensive skills-basededucation is a practical and effective means to enrich communities ofpractice
A Hitchhikers Guide to Anxiety Disorders
No full textAD is the commonest mental disorder with a lifetime prevalence rate of 21.1% in Europe, 31.0% in the United States2,3, a point prevalence of 5%, and a greater preponderance amongst women4. Living with ADs can be a long-term challenge. In many cases, it occurs along with other mood disorders5,6. In most cases, AD improves with psychological therapies and medication. Making lifestyle changes, learning coping skills and using relaxation techniques also can help. However, failure to treat AD and its consequences can be economically and socially costly. Therefore, early recognition of the disorder is imperative as that improves the scope for treatment and the prognosis. This guide describes critical aspects of the various subtypes of AD and how to manage them.
Addiction recovery stories: Bradley Maguire in conversation with Lisa Ogilvie
No full textPurpose: The purpose of this paper is to examine recovery through lived experience. It is part of a series that explores candid accounts of addiction and recovery to identify important components in the recovery process. Design/methodology/approach: The G-CHIME model comprises six elements important to addiction recovery (growth, connectedness, hope, identity, meaning in life and empowerment). It provides a standard against which to consider addiction recovery, having been used in this series, as well as in the design of interventions that improve well-being and strengthen recovery. In this paper, a first-hand account is presented, followed by a semi-structured e-interview with the author of the account. Narrative analysis is used to explore the account and interview through the G-CHIME model. Findings: This paper shows that addiction recovery is a remarkable process that can be effectively explained using the G-CHIME model. The significance of each component in the model is apparent from the account and e-interview presented. Originality/value: Each account of recovery in this series is unique and, as yet, untold
Product envelope spectrum optimization-gram: An enhanced envelope analysis for rolling bearing fault diagnosis
No full textThe vibration signal of a faulty rolling bearing exhibits typical non-stationarity - often in the form of cyclostationarity. The spectrum tools often used to characterize cyclostationarity mainly include envelope spectrum, squared envelope spectrum and log-envelope spectrum. In this paper, new detection methods of cyclostationarity are developed for obtaining a larger family of enve-lope analysis and their effectiveness in rolling bearing fault diagnosis is evaluated rigorously. Firstly, based on the simplified Box-Cox transformation, the generalized envelope signals are constructed from the analytic signal for demodulation purposes, and then a spectrum family named generalized envelope spectra (GESs) is proposed to reveal cyclostationarity. Especially, GESs with different transformation parameters exhibit different performance advantages against the random impulse noise and Gaussian background noise which are commonly present in rolling bearing vibration signals. Subsequently, a novel spectrum tool that combines the performance advantages of different GESs, called product envelope spectrum (PES), is developed to strengthen the capability to detect cyclostationarity. Finally, an enhanced envelope analysis named Product Envelope Spectral Optimization-gram (PESOgram) is proposed to improve the accuracy and robustness of PES for rolling bearing fault diagnosis in the presence of different fault-unrelated interference noises. The performance of the PESOgram method is validated on numerically generated signal and experimental signals collected from two railway axle bearing test rigs and compared with several state-of-the-art envelope analysis methods. The results demonstrate the effectiveness of the proposed method for fault diagnosis of rolling bearings and its advantages over other state-of-the-art methods