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Turbulence structure and momentum exchange in compound channel flows with shore ice covered on the floodplains
No full textYesIce cover formed on a river surface is a common natural phenomenon during winter season in cold high latitude northern regions. For the ice-covered river with compound cross-section, the interaction of the turbulence caused by the ice cover and the channel bed bottom affects the transverse mass and momentum exchange between the main channel and floodplains. In this study, laboratory experiments are performed to investigate the turbulent flow of a compound channel with shore ice covered on the floodplains. Results show that the shore ice resistance restricts the development of the water flow and creates a relatively strong shear layer near the edge of the ice-covered floodplain. The mean streamwise velocity in the main channel and on the ice-covered floodplains shows an opposite variation pattern along with the longitudinal distance and finally reaches the longitudinal uniformity. The mixing layer bounded by the velocity inflection point consists of two layers that evolve downstream to their respective fully developed states. The velocity inflection point and strong transverse shear near the interface in the fully developed profile generate the Kelvin-Helmholtz instability and horizontal coherent vortices. These coherent vortices induce quasi-periodic velocity oscillations, while the dominant frequency of the vortical energy is determined through the power spectral analysis. Subsequently, quadrant analysis is used in ascertaining the mechanism for the lateral momentum exchange, which exhibits the governing contributions of sweeps and ejections within the vortex center. Finally, an eddy viscosity model is presented to investigate the transverse momentum exchange. The presented model is well validated through comparison with measurements, whereas the constants α and β appeared in the model need to be further investigated.National Natural Science Foundation of China (NSFC). Grant Numbers: 52020105006, 11872285: State Key Laboratory of Water Resources and Hydropower Engineering Science (WRHES), Wuhan University. Grant Number: 2018HLG0
A complex intervention to reduce avoidable hospital admissions in nursing homes: a research programme including the BHiRCH-NH pilot cluster RCT
No full textYesAn unplanned hospital admission of a nursing home resident distresses the person, their family and nursing home staff, and is costly to the NHS. Improving health care in care homes, including early detection of residents’ health changes, may reduce hospital admissions. Previously, we identified four conditions associated with avoidable hospital admissions. We noted promising ‘within-home’ complex interventions including care pathways, knowledge and skills enhancement, and implementation support. Objectives: Develop a complex intervention with implementation support [the Better Health in Residents in Care Homes with Nursing (BHiRCH-NH)] to improve early detection, assessment and treatment for the four conditions. Determine its impact on hospital admissions, test study procedures and acceptability of the intervention and implementation support, and indicate if a definitive trial was warranted.
Design: A Carer Reference Panel advised on the intervention, implementation support and study documentation, and engaged in data analysis and interpretation. In workstream 1, we developed a complex intervention to reduce rates of hospitalisation from nursing homes using mixed methods, including a rapid research review, semistructured interviews and consensus workshops. The complex intervention comprised care pathways, approaches to enhance staff knowledge and skills, implementation support and clarity regarding the role of family carers. In workstream 2, we tested the complex intervention and implementation support via two work packages. In work package 1, we conducted a feasibility study of the intervention, implementation support and study procedures in two nursing homes and refined the complex intervention to comprise the Stop and Watch Early Warning Tool (S&W), condition-specific care pathways and a structured framework for nurses to communicate with primary care. The final implementation support included identifying two Practice Development Champions (PDCs) in each intervention home, and supporting them with a training workshop, practice development support group, monthly coaching calls, handbooks and web-based resources. In work package 2, we undertook a cluster randomised controlled trial to pilot test the complex intervention for acceptability and a preliminary estimate of effect.
Setting: Fourteen nursing homes allocated to intervention and implementation support (n = 7) or treatment as usual (n = 7).
Participants: We recruited sufficient numbers of nursing homes (n = 14), staff (n = 148), family carers (n = 95) and residents (n = 245). Two nursing homes withdrew prior to the intervention starting.
Intervention: This ran from February to July 2018. Data sources: Individual-level data on nursing home residents, their family carers and staff; system-level data using nursing home records; and process-level data comprising how the intervention was implemented. Data were collected on recruitment rates, consent and the numbers of family carers who wished to be involved in the residents’ care. Completeness of outcome measures and data collection and the return rate of questionnaires were assessed.
Results: The pilot trial showed no effects on hospitalisations or secondary outcomes. No home implemented the intervention tools as expected. Most staff endorsed the importance of early detection, assessment and treatment. Many reported that they ‘were already doing it’, using an early-warning tool; a detailed nursing assessment; or the situation, , assessment, recommendation communication protocol. Three homes never used the S&W and four never used care pathways. Only 16 S&W forms and eight care pathways were completed. Care records revealed little use of the intervention principles. PDCs from five of six intervention homes attended the training workshop, following which they had variable engagement with implementation support. Progression criteria regarding recruitment and data collection were met: 70% of homes were retained, the proportion of missing data was < 20% and 80% of individual level data were collected. Necessary rates of data collection, documentation completion and return over the 6-month study period were achieved. However, intervention tools were not fully adopted, suggesting they would not be sustainable outside the trial. Few hospitalisations for the four conditions suggest it an unsuitable primary outcome measure. Key cost components were estimated.
Limitations: The study homes may already have had effective approaches to early detection, assessment and treatment for acute health changes; consistent with government policy emphasising the need for enhanced health care in homes. Alternatively, the implementation support may not have been sufficiently potent.
Conclusion: A definitive trial is feasible, but the intervention is unlikely to be effective. Participant recruitment, retention, data collection and engagement with family carers can guide subsequent studies, including service evaluation and quality improvement methodologies.
Future work: Intervention research should be conducted in homes which need to enhance early detection, assessment and treatment. Interventions to reduce avoidable hospital admissions may be beneficial in residential care homes, as they are not required to employ nurses.National Institute for Health Research (NIHR) Programme Grants for Applied Research programm
Automated Prediction of Solar Flares Using SDO Data. The Development of An Automated Computer System for Predicting Solar Flares Based on SDO Satellite Data Using HMI Images Analysis, Visualisation, and Deep Learning Technologies
No full textNowadays, space weather has become an international issue to the world's countries
because of its catastrophic effect on space-borne and ground-based systems, and
industries, impacting our lives. One of the main solar activities that is considered as a
major driver of space weather is solar flares. Solar flares can be defined as an enormous
eruption in the sun's atmosphere. This phenomenon happens when magnetic energy stored
in twisted magnetic fields, usually near sunspots, is suddenly released. Yet, their
occurrence is not fully understood. These flares can affect the Earth by the release of
massive quantities of charged particles and electromagnetic radiation. Investigating the
associations between solar flares and sunspot groups is helpful in comprehending the
possible cause and effect relationships among solar flares and sunspot features. 01 This
thesis proposes a new approach developed by integrating advances in image processing,
machine learning, and deep learning with advances in solar physics to extract valuable
knowledge from historical solar data related to sunspot regions and flares.
This dissertation aims to achieve the following:
1) We developed a new prediction algorithm based on the Automated Solar Activity
Prediction system (ASAP) system. The proposed algorithm updates the ASAP system
by extending the training process and optimizing the learning rules to the optimize
performance better. Two neural networks are used in the proposed approach. The first
neural network is used to predict whether a specific sunspot class at a particular time
is likely to produce a significant flare or not. The second neural network is used to
predict the type of this flare, X or M-class.
2) We proposed a new system called the ASAP_Deep system built on top of the ASAP
system introduced in [6] but improves the system with an updated deep learning-based
prediction capability. In addition, we successfully apply Convolutional Neural
Network (CNN) to the sunspot group image without any pr-eprocessing or feature
extraction. Moreover, our system results are considerably better, especially for the
false alarm ratio (FAR); this reduces the losses resulting from the protection measures
applied by companies. In addition, the proposed system achieves a relatively high
score of True Skill Statistic (TSS) and Heidke Skill Score (HSS).
3) We presented a novel system that used the Deep Belief Networks (DBNs) to predict
the solar flares occurrence. The input data are SDO/HMI Intensitygram and
Magnetogram images. The model outputs are "Flare or No-Flare" of significant flare
occurrence (M and X-class flares). In addition, we created a dataset from the sunspots
groups extracted from SDO HMI Intensitygram images. We compared the results
obtained from the complete suggested system with those of three previous flare forecast models using several statistical metrics.
In our view, these developed methods and results represent an excellent initial
step toward enhancing the accuracy of flare forecasting, enhance our understanding of flare occurrence, and develop efficient flare prediction systems. The systems, implementation, results, and future work are explained in this dissertation
Health-risk assessment for roof-harvested rainwater via QMRA in Ikorodu area, Lagos, Nigeria
No full textYesThis paper presents a study to assess the roof-harvested rainwater (RHRW) in the Ikorodu area of Lagos state, Nigeria, and recommends guidance to minimise the health risk for its households. The types, design and use of rainwater harvesting systems have been evaluated in the study area to inspect the human risk of exposure to Escherichia coli (E. coli). To achieve these objectives, a detailed survey involving 125 households has been conducted which showed that 25% of them drink RHRW. Quantitative microbial risk assessment (QMRA) analysis has been used to quantify the risk of exposure to harmful E. coli from RHRW utilised as potable water, based on the ingestion of 2 L of rainwater per day per capita. Results have revealed that the maximum E. coli exposure risk from the consumption of RHRW, without application of any household water treatment technique (HHTTs) and with application of alum only, were 100 and 96 respectively, for the estimated number of infection risk per 10,000 exposed households per year. This estimation has been done based on 7% of E. coli as viable and harmful. Conclusively, it is necessary that a form of disinfectant be applied to the RHRW before use
Hamiltonian modeling and structure modified control of diesel engine
No full textYesA diesel engine is a typical dynamic system. In this paper, a dynamics method is proposed to establish the Hamiltonian model of the diesel engine, which solves the main difficulty of con-structing a Hamiltonian function under the multi-field coupling condition. Furthermore, the control method of Hamiltonian model structure modification is introduced to study the control of a diesel engine. By means of the principle of energy-shaping and Hamiltonian model structure modification theories, the modified energy function is constructed, which is proved to be a quasi-Lyapunov function of the closed-loop system. Finally, the control laws are derived, and the simulations are carried out. The study reveals the dynamic mechanism of diesel engine operation and control and provides a new way to research the modeling and control of a diesel engine system.National Natural Science Foundation of China, grant number 51869007
The Impact of Risk Management on Project Success. A case study of the Land Administration Project, Ghana
No full textWhile previous research suggests that risk management influences project success, less is known about the practical application of the risk management concept on projects and its’ influence on development project success. Thus, this thesis investigates the impact of risk management on project success from a development project perspective. Adopting a qualitative case study approach with semi-structured interviews as the main source of data collection and assessing success from a stakeholder perspective as well as the achievements of the project’s intended outcomes and analysing the various risk management strategies adopted in the pursuance of those outcomes, the findings indicate that risk management practice positively influence development project success. To achieve this, the empirical data shows that risk identification need to be approached strategically to provide a clear focus for project delivery leading to the design of strategic actions to respond to identified risks as well as an effective monitoring and evaluation of the risk management process as a whole. Additionally, the different stakeholder objectives and expectations need to be strategically incorporated into the risk management strategy without deviating from the project’s purpose.
The study recommends the need for development project managers not to over-rely on academic expertise in their identification of risks but make use of the wider pool of knowledge available to them, technical or not and to also pursue the positive impacts of risk. Furthermore, they should widen their risk management strategies to include donor support missions, without deviating from the project’s purpose, to ensure transparency and efficiency
Cytochrome P450 isoforms 1A1, 1B1 AND 2W1 as targets for therapeutic intervention in head and neck cancer
No full textYesEpidemiological studies have shown that head and neck cancer (HNC) is a complex multistage process that in part involves exposure to a combination of carcinogens and the capacity of certain drug-metabolising enzymes including cytochrome P450 (CYP) to detoxify or activate such carcinogens. In this study, CYP1A1, CYP1B1 and CYP2W1 expression in HNC was correlated with potential as target for duocarmycin prodrug activation and selective therapy. In the HNC cell lines, elevated expression was shown at the gene level for CYP1A1 and CYP1B1 whereas CYP2W1 was hardly detected. However, CYP2W1 was expressed in FaDu and Detroit-562 xenografts and in a cohort of human HNC samples. Functional activity was measured in Fadu and Detroit-562 cells using P450-Glo™ assay. Antiproliferative results of duocarmycin prodrugs ICT2700 and ICT2706 revealed FaDu and Detroit-562 as the most sensitive HNC cell lines. Administration of ICT2700 in vivo using a single dose of ICT2700 (150 mg/kg) showed preferential inhibition of small tumour growth (mean size of 60 mm3) in mice bearing FaDu xenografts. Significantly, our findings suggest a potential targeted therapeutic approach to manage HNCs by exploiting intratumoural CYP expression for metabolic activation of duocarmycin-based prodrugs such as ICT2700.The authors would like to thank Bradford Institute for Health Research for funding a PhD studentship to DP through a competitive scheme and Yorkshire Cancer Research programme Grant (B381PA) for supporting our cytochrome P450-focused drug discovery research
Asset pricing in the Middle East’s equity markets
Get PDFYesThis paper undertakes a comparison between five multifactor variants of the capital asset pricing model. These include additional factors based on size, book to market value, momentum, liquidity and a new investor protection metric based on the product of institutional quality in a country and the proportion of free float shares, which captures the impact of controlling block holders. Using monthly returns of 909 blue chip firms from 18 Middle East & North African equity markets for 16 years, we show that a two factor CAPM augmented with a factor mimicking portfolio based on the investor protection metric yields the highest explanatory power. Analysis of Kalman filter time varying investor protection betas reveals investor protection premiums in Egypt, Iraq, Lebanon and Tunisia and corresponding discounts in Israel, Saudi Arabia, Kuwait, Oman, Dubai and Abu Dhabi
Exploring circular economy in the hospitality industry: empirical evidence from Scandinavian hotel operators
Get PDFYesThe circular economy is gaining momentum in corporate circles and European economic policies. However, its relevance and applicability to service dominated industries, such as tourism and hospitality, is poorly researched. This study investigates Scandinavian hotel operators’ understanding of the circular economy, its drivers, enablers, barriers, and value creation potential. This exploratory study gathers feedback from ten Scandinavian hotel chains managers and proposes a circular economy applicability framework to test the concept’s relevance to hotel operators. The research findings highlight respondents’ interest and expose introductory to intermediate level of understanding of the circular economy. Conditional to specific enabling levers, the research confirms the applicability and value creation potential of the circular economy to hotel operators. The research provides hotel operators with recommendations on circular economy value creation opportunities, deployment pathways and suggests future research directions
A systematic review to identify research priority setting in Black and minority ethnic health and evaluate their processes
Get PDFYesBlack, Asian and minority ethnic communities suffer from disproportionately poorer health than the general population. This issue has been recently exemplified by the large numbers of infection rates and deaths caused by covid-19 in BAME populations. Future research has the potential to improve health outcomes for these groups. High quality research priority setting is crucial to effectively consider the needs of the most vulnerable groups of the population.
The purpose of this systematic review is to identify existing research priority studies conducted for BAME health and to determine the extent to which they followed good practice principles for research priority setting.
Method: Included studies were identified by searching Medline, Cinnahl, PsychINFO, Psychology and Behavioral Sciences Collection, as well as searches in grey literature. Search terms included “research priority setting”, “research prioritisation”, “research agenda”, “Black and minority ethnic”, “ethnic group”. Studies were included if they identified or elicited research priorities for BAME health and if they outlined a process of conducting a research prioritisation exercise. A checklist of Nine Common Themes of Good Practice in research priority setting was used as a methodological framework to evaluate the research priority processes of each study.
Results: Out of 1514 citations initially obtained, 17 studies were included in the final synthesis. Topic areas for their research prioritisation exercise included suicide prevention, knee surgery, mental health, preterm birth, and child obesity. Public and patient involvement was included in eleven studies. Methods of research prioritisation included workshops, Delphi techniques, surveys, focus groups and interviews. The quality of empirical evidence was diverse. None of the exercises followed all good practice principles as outlined in the checklist. Areas that were lacking in particular were: the lack of a comprehensive approach to guide the process; limited use of criteria to guide discussion around priorities; unequal or no representation from ethnic minorities, and poor evaluation of their own processes.
Conclusions: Research priority setting practices were found to mostly not follow good practice guidelines which aim to ensure rigour in priority setting activities and support the inclusion of BAME communities in establishing the research agenda. Research is unlikely to deliver useful findings that can support relevant research and positive change for BAME communities unless they fulfil areas of good practice such as inclusivity of key stakeholders’ input, planning for implementation of identified priorities, criteria for deciding on priorities, and evaluation of their processes in research priority setting.This work was supported by the National Institute for Health Research (NIHR) under its Applied Research Collaboration (ARC) Yorkshire and Humber in the form of Ph.D. funding to HI [NIHR200166], the UK Prevention Research Partnership (UKPRP) in the form of funding to JW and RM [MR/S037527/1], the NIHR Clinical Research Network in the form of funding to JW, and the NIHR ARC Yorkshire and Humber in the form of funding to RM