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Effects of textured insoles on dynamic balance and ankle muscle activity in soccer players with and without chronic ankle instability
Get PDFBACKGROUND: Chronic ankle instability (CAI) poses challenges in sports. Textured insoles (TI) are a promising intervention for enhancing dynamic balance in CAI athletes. This study aimed to investigate the effects of TI on dynamic balance performance and ankle muscle activity in soccer players with and without CAI.
METHODS: Thirty-eight soccer players (19 CAI, 19 non-CAI) participated. Participants performed a modified star excursion balance test (mSEBT) while wearing TI and standard insoles (SI). The %SEBT reach distance and electromyography (EMG) activity of tibialis anterior (TA), medial gastrocnemius (MG), and peroneus longus (PL) were measured during maximum reached in each direction of the mSEBT.
RESULTS: No significant effects or interactions were found between ankle conditions (CAI vs. non-CAI) or insole types (TI vs. SI) on %SEBT reach. However, CAI players showed greater MG activity in posteromedial and posterolateral direction (P=0.04, P=0.01).
CONCLUSIONS: Overall, the application of TI did not have immediate effects on dynamic balance performance or ankle muscle activity in either CAI or non-CAI soccer players. Nonetheless, CAI players seemed to employ a different ankle strategy involving the MG muscle, possibly to control stability during dynamic movement, particularly in the posteromedial and posterolateral directions
Decarbonisation of the steel tube industry: Integration a novel SHIP system with a multiple air impingement jets tube heater for coating processes
No full textThis thesis was submitted for the award of Doctor of Philosophy and was awarded by Brunel University LondonA new Solar Heating for Industrial Processes (SHIP) system was investigated and designed to reduce greenhouse gas (GHG) emissions in the powder-based coating process for manufacturing of steel tubes. The new system includes a solar thermal rotary Fresnel collector (RFC), a phase change material (PCM) thermal energy storage system (TESS) and a novel tube heater, that utilises the heat generated by the thermal collector and stored in the PCM TESS to heat up the tubes to a temperature up to 240 oC before they are coated.
The novelty of this system is rooted in the development of a novel tube heater which employs multiple air impingement jets as the main mechanism of transferring heat to the tubes without interrupting their movement. It was designed using computer-aided design (CAD) tools and modelled numerically using a computational fluid dynamics (CFD) solver. The design was optimised numerically through a parametric analysis to maximise the heat transfer to a static tube by evaluating critical parameters including the length and diameter of the tube heater, diameter of the impingement jets and distance between them. The optimised design was evaluated for its thermal performance on a moving tube using two CFD models: FLUENT Dynamic Mesh model and FLUENT – Transient Thermal model. The numerical results of the parametric analysis and the two dynamic models were experimentally validated using a test rig that evaluates the real-life thermal performance of the tube heater.
The numerical and experimental findings were used in the development of a transient simulation model for the integrated SHIP system. The results of simulations have shown that a SHIP system with RFC, PCM TESS and jet impingement tube heater can lead to 9.1% and 12.2% reduction in fossil fuel use during the powder-based coating process, in low and high irradiance regions in Europe, respectively.
As a result, the assessment of the environmental and economic benefits of the new SHIP system, comparing the fossil fuel energy consumption before and after implementation of the newly developed SHIP system, demonstrated significant reduction of CO2 emissions and savings, reaching 11.6 tonnes CO2 and €6,281 annually with a cumulative of 116.3 tonnes CO2 and €100,674 in 10 years, respectively.
The investigations documented in this thesis highlight the capabilities of the novel SHIP and tube heater system that surpass those of conventional SHIP technologies. Recommendations for future work included investigation of the effect different jet shapes and inlet diameters, as well as more detailed environmental and economic assessments
Chatbot Technology Use and Acceptance Using Educational Personas
Get PDFData Availability Statement:
The data presented in this study are available upon request from the corresponding author.Chatbots are computer programs that mimic human conversation using text or voice or both. Users’ acceptance of chatbots is highly influenced by their persona. Users develop a sense of familiarity with chatbots as they use them, so they become more approachable, and this encourages them to interact with the chatbots more readily by fostering favorable opinions of the technology. In this study, we examine the moderating effects of persona traits on students’ acceptance and use of chatbot technology at higher educational institutions in the UK. We use an Extended Unified Theory of Acceptance and Use of Technology (Extended UTAUT2). Through a self-administrated survey using a questionnaire, data were collected from 431 undergraduate and postgraduate computer science students. This study employed a Likert scale to measure the variables associated with chatbot acceptance. To evaluate the gathered data, Structural Equation Modelling (SEM) coupled with multi-group analysis (MGA) using SmartPLS3 were used. The estimated Cronbach’s alpha highlighted the accuracy and legitimacy of the findings. The results showed that the emerging factors that influence students’ adoption and use of chatbot technology were habit, effort expectancy, and performance expectancy. Additionally, it was discovered that the Extended UTAUT2 model did not require grades or educational level to moderate the correlations. These results are important for improving user experience and they have implications for academics, researchers, and organizations, especially in the context of native chatbots.This research was funded by the University of Technology and Applied Sciences, Salalah, Oman and Ministry of Higher Education, Research and Innovation, Oman
Testosterone undecanoate is associated with improved ageing male symptoms score in men with type 2 diabetes and adult-onset testosterone deficiency: re-analyzed results from a randomised controlled trial
Get PDFAvailability of data and materials:
The datasets that support the findings of this study are available from Professor Sudarshan Ramachandran upon reasonable request.Aim: To evaluate changes in quality of life via the ageing male symptom scale (AMSS) and somatic, psychological, and sexual sub-scales following testosterone undecanoate (TU) or placebo (P) treatment in men with type 2 diabetes mellitus (T2DM) and adult-onset testosterone deficiency (TD) via a re-analysis of the BLAST (Burntwood, Lichfield, Atherstone, Sutton Coldfield, and Tamworth) randomised controlled trial (RCT).
Methods: Analysis of data from the BLAST RCT in men with T2DM and adult-onset TD was performed. Summation baseline and study-end AMSS data were available in 170 men (94: P; 76: TU) with subscale data available in 82 men. Rank-sum and sign-rank tests determined inter/intra-group differences, whilst linear/multiple regression models identified predictors of AMSS change.
Results: AMSS improved significantly in P [–2 (median), p = 0.010] and TU [–6 (median), p 49. In the cohort with subscale AMSS data, TU was associated with improvements in somatic, psychological, and sexual subscales, whilst improvement was limited to the somatic subscale in the men on P. TU (reference: P) and higher baseline AMSS were significantly and independently associated with AMSS improvement. The improvement in summation AMSS associated with TU (reference: P) was only evident in men with mild depression and no anxiety (based on baseline Hospital Anxiety and Depression Scale data).
Conclusions: TU appeared associated with improved AMSS (summation and subscales) in men with T2DM and adult-onset TD demonstrating symptoms (AMSS ≥ 27) with this benefit mediated by levels of depression and anxiety (European Union Clinical Trials Register, EudraCT 2008-000931-16).The practice expenses (BLAST RCT) of the research are supported by a grant from Bayer plc [BSP-SOP-040]
Optimising EV Efficiency with Hybrid Energy Storage and Advanced Control Strategies
Get PDFThis study examines a hybrid energy storage system (HESS) that integrates Lithium-Ion Batteries (LIB) with Supercapacitors (SCs). The HESS is built with a completely active topology that guarantees precise regulation of energy flow. Comparison of Proportional-Integral (PI) and Online Radial Basis Function (RBF) controllers is conducted via simulations are performed utilising representative driving cycles. The Online RBF controller surpasses the PI controller by reducing power losses and ensuring stable State of Charge (SoC) profiles. The results emphasise how HESS can improve Electric Vehicle (EV) performance and emphasise the vital role of control methods in attaining optimal energy management
Detecting Plant Diseases Using Machine Learning Models
Get PDFData Availability Statement:
Data is contained within the following links: https://github.com/nazarkohut/tomato-disease-detection-train; https://www.kaggle.com/datasets/emmarex/plantdisease; https://www.kaggle.com/datasets/cookiefinder/tomato-disease-multiple-sources; https://github.com/mamta-joshi-gehlot/Tomato-Village.Acknowledgments:
The authors would like to thank the Armed Forces of Ukraine for providing the security to perform this work. This work was only possible because of the resilience and courage of the Ukrainian Army.Sustainable agriculture is pivotal to global food security and economic stability, with plant disease detection being a key challenge to ensuring healthy crop production. The early and accurate identification of plant diseases can significantly enhance agricultural practices, minimize crop losses, and reduce the environmental impacts. This paper presents an innovative approach to sustainable development by leveraging machine learning models to detect plant diseases, focusing on tomato crops—a vital and globally significant agricultural product. Advanced object detection models including YOLOv8 (minor and nano variants), Roboflow 3.0 (Fast), EfficientDetV2 (with EfficientNetB0 backbone), and Faster R-CNN (with ResNet50 backbone) were evaluated for their precision, efficiency, and suitability for mobile and field applications. YOLOv8 nano emerged as the optimal choice, offering a mean average precision (MAP) of 98.6% with minimal computational requirements, facilitating its integration into mobile applications for real-time support to farmers. This research underscores the potential of machine learning in advancing sustainable agriculture and highlights future opportunities to integrate these models with drone technology, Internet of Things (IoT)-based irrigation, and disease management systems. Expanding datasets and exploring alternative models could enhance this technology’s efficacy and adaptability to diverse agricultural contexts.This research received no external funding
Assessment of life cycle impacts of sustainable technologies in industrial environments
Get PDFThis thesis was submitted for the award of Doctor of Philosophy and was awarded by Brunel University LondonThis thesis focuses on the analysis and assessment of the life cycle impacts of heat pipe-based heat exchangers (HPHE) in energy-intensive industries (EIIs), namely the steel, aluminium, and ceramics industries. These industries, vital to the European economy, are responsible for substantial greenhouse gas emissions, which renders their decarbonisation a key priority. Waste heat recovery (WHR) innovations, such as the HPHE, offer an attractive solution by capturing and reusing waste heat to improve energy efficiency and reduce emissions. This is the premise of the ETEKINA project, that has served as the starting point for this study.
The research investigates the economic and environmental implications of HPHEs, through a life cycle assessment (LCA). The LCA involves the quantification of the environmental impacts through the calculation of indicators, such as global warming potential and human carcinogenic toxicity. To perform the calculations, the goal, scope, functional unit, boundary conditions and inventories of the LCA are created. The LCA is thus carried out for the three industrial demonstrations of the ETEKINA project, the ceramics, aluminium and steel industries.
Additionally, the thesis explores business modelling to assess the market viability of HPHE technologies, considering economic benefits such as reduced operational costs and enhanced competitiveness in global markets.
Key findings highlight the energy-saving potential of HPHEs, translating it to environmental indicators, identifying hotspots for further design and production improvement, and aligning the development work with the decarbonisation targets outlined in the European Green Deal and the Paris Agreement
Eight years into the horizon of aspirational maternal and newborn health pledges: a nationwide cross-sectional exploration of the Burundian EmONC network capacity and budget deficits
Get PDFData availability statement: Data may be obtained from a third party and are not publicly available. This study used a set of different datasets from EmONC facility survey and routine monitoring data and cost data. These datasets are not publicly available as primarily owned by the Burundian MoH and are bound by a strong data sharing policy which does not permit authors to share them. However, these data can be obtained by sending a reasonable request to the reproductive, maternal, newborn, child and adolescent’s health programme of the Burundian MoH. The corresponding author can share STATA command files upon request.Supplementary materials are available online at: https://bmjopen.bmj.com/content/14/5/e083546#supplementary-materials .Objective: The Burundian emergency obstetric and neonatal care (EmONC) programme, which was initiated in 2017 and supported by a specific policy, does not appear to reverse maternal and newborn mortality trends. Our study examined the capacity challenges facing participating EmONC facilities and developed alternative investment proposals to improve their readiness paying particular attention to EmONC professionals, physical infrastructure, and capital equipment.
Design: Cross-sectional study.
Setting: Burundian EmONC facilities (n=112).
Participants: We examined EmONC policy documents, consulted 12 maternal and newborn health experts and 23 stakeholders and policymakers, surveyed all EmONC facilities (n=112), and collected cost data from the Ministry of Health and local suppliers in Burundi. We developed three context-specific EmONC resource benchmark standards by facility type; the Burundian policy norms and the expert minimum and maximum suggested thresholds; and used these alternatives to estimate EmONC resource gaps. We forecasted three corresponding budget estimates needed to address prevailing deficits taking a government perspective for a 5-year EmONC investment strategy. Additionally, we explored relationships between EmONC professionals and selected measures of service delivery using bivariate analyses and graphically.
Results: The lowest EmONC resource benchmark revealed that 95% of basic EmONC and all comprehensive EmONC facilities lack corresponding sets of human resources and 90% of all facilities need additional physical infrastructure and capital equipment. Assessed against the highest benchmark which proposes the most progressive set of standards for the prevailing workloads, Burundi would require 162 more medical doctors, 1005 midwives and nurses, 132 delivery rooms, 191 delivery tables, 678 and 156 maternity and newborn care beds, and 395 incubators amounting to US32.9 million funding gap for 5 years; averagely approximating to 5.96% total health budget increase annually.The health facility surveys were funded by WHO country office in Burundi and Mike English is funded by a Senior Research Fellowship from the Wellcome Trust (#207522)
Stock market responses to monetary policy shocks: Firm-level evidence
Get PDFJEL classification: I26; J15; Z13.Using a firm-level data set for the U.S., we investigate the stock price responses to unanticipated and unconventional monetary policy shocks. Our results show that indebtedness/leverage is more important than size or age in explaining the cross-firm variation in responses to monetary policy. We also show that the magnitude of the indebtedness is important while the debt structure is not, and the third quartile of firms drives our results. We assess the robustness of our empirical findings across several dimensions
Public service motivation, public sector preference and employment of Kenyan medical doctor interns: a cross-sectional and prospective study
Get PDFAvailability of data and materials: The datasets generated during and/or analysed during the current study are available from the corresponding author on reasonable request.Supplementary Information is available online at: https://human-resources-health.biomedcentral.com/articles/10.1186/s12960-024-00945-6#Sec12 .Background:
Kenya grapples with a paradox; severe public sector workforce shortages co-exist with rising unemployment among healthcare professionals. Medical schools have increased trainee outputs, but only 45% of newly qualified/registered doctors were absorbed by the public sector during 2015–2018. In such a context, we explore what influences doctors’ career choices at labour market entry, specifically understanding the role of public service motivation (PSM).
Methods:
We conducted a cross-sectional and prospective study of interns and recently graduated doctors to examine PSM, their intention to work in the public sector and their final employment sector and status. We surveyed them on their PSM and job intentions and conducted a prospective follow-up survey of the interns, around one year later, to understand their employment status.
Findings:
We recruited 356 baseline participants and followed up 76 out of 129 eligible interns. The overall PSM score was high among all participants (rated 4.50/5.00) irrespective of sector preferences. 48% (171/356) of the participants preferred to work in the public sector immediately after internship, alongside 16% (57/356) preferring direct entry into specialist training—commonly in the public sector. Only 13% (46/356) and 7% (25/365) preferred to work in the private or faith-based sector. Despite the high proportion of interns preferring public sector jobs, only 17% (13/76) were employed in the public sector at follow-up and 13% (10/76) were unemployed, due to lack of job availability.
Conclusion:
High PSM scores irrespective of sector preferences suggest that doctors are generally committed to serving the ‘public good’. Many intended to work in the public sector but were unable to due to lack of job opportunities. Policymakers have an opportunity to tackle workforce gaps in the public sector as young doctors continue to express a preference for such work. To do this they should prioritise creating adequate and sustainable job opportunities.This work is supported by an Africa Oxford travel grant (AfOx-209). YZ is supported by the University of Oxford Clarendon Fund Scholarship, an Oxford Travel Abroad Bursary and a Keble Association grant. DG and ME are supported by the National Institute for Health Research, Learning to Harness Innovation in Global Health for Quality Care (HIGH-Q) using UK aid from the UK Government to support global health research [NIHR130812]. ME is supported by a Wellcome Trust Senior Research Fellowship (#207522). CN receives funding from the Economic and Social Research Council [grant number ES/T008415/1]. National Institute for Health Research Applied Research Collaboration Oxford and Thames Valley at Oxford Health NHS Foundation Trust. Consortium iNEST (Interconnected North-Est Innovation Ecosystem) funded by the European Union NextGenerationEU (Piano Nazionale di Ripresa e Resilienza (PNRR)—Missione 4 Componente 2, Investimento 1.5—D.D. 1058 23/06/2022, ECS_00000043)
Data sources:
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