University of Huddersfield

Modeling planetary gearboxes is an important field of research, since it helps in condition based monitoring of the system. Multiple models with different approaches were developed last decades. They showed interesting results, but they did not reflect all involved phenomena. Indeed, specifically in a complex rotating systems such as staged planetary gearboxes, those models only approximated the dynamic behavior of the investigated system. Hence, in this paper, an algorithm of modeling staged planetary gearbox vibration signature is proposed based on exclusively measured vibration signals. First, in section 2, the dynamic mode decomposition (DMD) will be introduced. Second, in section 3, the DMD algorithm will be implemented on simulated mathematical functions to prove its robustness on future state prediction. Then, in section 4, the experimental staged planetary gearbox test rig is presented. Finally, in section 5, the DMD algorithm is applied to multiple measured vibration signals with different operating conditions as given in section 4. Interesting results are conducted and limits of the approach are presented.

Our paper examines the strategies for achieving economic recovery from the adverse effects of COVID-19 and outlines a pathway for sustainable economic development in Brazil, one of the emerging economies that suffered economic setbacks due to the pandemic. In the post-COVID-19 era, countries worldwide are actively formulating strategies to recover economically and, in most cases, are aiming for targeted sustainable development. Against this backdrop, we adopt Brazil’s time series data of 2001Q1–2019Q4 to investigate and unveil the best global practice for the quick recovery of the country’s economic development and equally advise on the best policies to engender sustainable economic development of the country. Our analysis focused on policy-rooted instruments (energy efficiency, financial development, and technological innovation). To achieve the objectives of this study, we utilized a novel nonlinear autoregressive distributed lag (NARDL), asymmetric econometric techniques to analyze the data. The findings from our analyses confirm the highlighted objectives of the study and support the application of the selected instruments in economic recovery and the pursuit of sustainable development in Brazil. Specifically, the positive shocks to the energy efficiency of Brazil (LNENFFIC) have a positive impact on its economic development in both the short and long run. Similarly, the positive and negative shocks to Brazil’s financial development (FD) displayed positive and negative impacts on Brazil’s economic progress in both short run and long-term periods. The positive and negative shocks to Brazil’s technological innovation influence its economy in both the long run and short run. These findings emphasize that the instruments selected—energy efficiency, financial development, and technology—are effective in reinvigorating Brazil’s economy. The implications suggest that well-designed policies based on these instruments have the potential to make a significant contribution to Brazil’s economic recovery and long-term sustainable development.

Objectives Clinical breast examination (CBE) open the pathway to early detection and diagnosis of breast cancer. This study examined barriers to CBE uptake in seven sub-Saharan African (SSA) countries. Methods Data from the most current Demographic and Health Surveys of Burkina Faso, Cote d’Ivoire, Ghana, and Kenya Mozambique, Senegal and Tanzania was used. A weighted sample size of 65,486 women aged 25–49 years was used to estimate the pooled prevalence of CBE. We employed a multilevel logistic regression modelling technique, with results presented in adjusted odds ratios (aOR) along with a 95% confidence interval (CI). Results The pooled prevalence of CBE uptake in the studied SSA countries is low at 19.2% [95%CI: 18.5–19.8]. Screening uptake was significantly low among women reporting difficulty in getting permission (aOR = 0.88, 95% CI: 0.82–0.95), and distance (aOR = 0.95, 95% CI: 0.89–0.99), as well as those who reported financial constraints (aOR = 0.92, 95% CI: 0.88–0.97), as barriers to access healthcare facilities. However, surprisingly, women who faced travel-alone barriers were 1.19 times (95%CI: 1.10–1.28) more likely to utilise CBE than those who did not face this barrier. Conclusions We conclude that barriers such as difficulties in obtaining permission, long distances to healthcare facilities, and financial constraints significantly reduce the likelihood of women undergoing CBE. The study underscores a need to improve access to healthcare facilities. Practically, this can be achieved by expanding mobile health services and integrating CBE into primary healthcare will help overcome distance-related challenges. Additionally, targeted outreach and transportation initiatives are necessary to support women facing travel barriers.

Introduction Globally, the prevalence of undernutrition is highest in the sub-Saharan African region with over a third of the world’s stunted children residing in this region. Many studies have explored child nutrition in sub-Saharan Africa, but they often overlook the intricate nuances of maternal knowledge. We examined the association between maternal nutritional knowledge and childhood nutritional outcomes. Methods This was a secondary analysis utilizing data from the Demographic and Health Survey of eight sub-Saharan African countries that were conducted between 2019 and 2022, focusing on children aged 6 to 23 months. The study used latent class analysis to identify discrete patterns of nutrition and health-related knowledge and mixed-effects logistic regression to assess their association with childhood nutritional outcomes namely, stunting and wasting. Statistical significance was determined at p < 0.05. Results Most participants knew the importance of colostrum (76.8%) and continued breastfeeding (76.7%), as well as immunization (60.0%) and diarrhoea prevention and treatment strategies (65.1%). However, only 24.49% knew about family planning. Children of high knowledge group/class had a 17% lower risk of childhood stunting (crude model; COR = 0.83; 95%CI: 0.77, 0.90, adjusted model; AOR = 0.89; 95%CI: 0.82, 0.97) and a 22% lower risk of wasting (COR = 0.78; 95%CI: 0.69, 0.89, adjusted model; AOR = 0.84; 95%CI: 0.73, 0.96) compared to those from the low knowledge group/class. Conclusion These results highlight the pivotal role of maternal knowledge in shaping children’s health outcomes and emphasize the urgent need for targeted interventions and comprehensive maternal education programs to address the identified knowledge gaps and improve child health outcomes.

Background Interactive electronic devices (IEDs) are ubiquitous in young children's lives. However, research on their impact on learning and development is still limited. The aim of this study was to understand the perspectives of early years practitioners (EYPs) and public health consultants (PHCs) on the use of IEDs in children aged 3–5. Methods Using purposive sampling techniques, we recruited four EYPs and two PHCs from children's nurseries and a government organisation in the northwest of England. Semi‐structured interviews were used to collect data, which were audio‐recorded, transcribed verbatim and anonymised. Data were analysed using reflective thematic analysis. Results EYPs and PHCs noted that although IEDs could negatively impact child development and behaviour, they could also aid in learning. EYPs expressed concerns about the impact of parents' own IED habits on children's communication and social skills. On the other hand, PHCs stressed that substituting outdoor play with the use of these devices could affect children's social and physical skills and reduce physical activity levels, which are crucial for development. Finally, both EYPs and PHCs agreed that there was a need to improve parents' and EYP's knowledge and to develop interactive interventions to promote an understanding of how IEDs should be used with young children. Conclusion EYPs and PHCs acknowledge the potential advantages of using IEDs as a teaching tool for children. However, they have concerns about the long‐term effects on communication, social and physical skills and how children are impacted by their parents' use of these devices. To support policy statements, future research should offer further evidence of the benefits and harms of IED use.

Background Advancements in medical science have focused largely on patient care, often overlooking the well-being of health care professionals (HCPs). This oversight has consequences; not only are HCPs prone to mental and physical health challenges, but the quality of patient care may also endure as a result. Such concerns are also exacerbated by unprecedented crises like the COVID-19 pandemic. Compared to other sectors, HCPs report high incidence of stress, depression, and suicide, among other challenging factors that have a significant negative impact on their well-being. Objective Given these substantial concerns, the development of a tool specifically designed to be used in clinical settings to measure the well-being of HCPs is essential. Methods A United Kingdom–based cross-sectional pilot study was carried out to measure self-reported well-being in a cohort of 148 physicians, using the newly developed well-being thermometer. The aim of the tool is to allow respondents to develop an individual sense of “well-being intelligence” thus supporting HCPs to have better insight and control over their well-being and allow insights into how to manage it. The tool consists of 5 well-being domains—health, thoughts, emotions, spiritual, and social. Each domain can be measured individually or combined to produce an overall well-being score. Results The tool demonstrated good internal consistency; the Cronbach α in this study was 0.84 for the total scale. Conclusions Results from this cohort demonstrated that the well-being thermometer can be used to gather intelligence of staff well-being. This is a promising new tool that will assist HCPs to recognize their own well-being needs and allow health care organizations to facilitate change in policies and practices to reflect a better understanding of staff well-being.

The tidal wave of Western feminism has swept across the globe, leaving an indelible mark upon the diverse cultures of Africa. Within this context, the feminist movement has been amplified by the pressing need to decolonise the discourses surrounding identity, rights, space, epistemology, and race, among other fundamental constructs. Regrettably, the core of this radical feminist wave has often been misread, misinterpreted, and grossly misrepresented the experiences of African women. The prevalent portrayal has been one that casts African women as second-class citizens, whose rights are disrespected and violated by their male counterparts. Grounded in the Shona culture of Zimbabwe, and as part of a broader critical examination of cultural and global studies, this paper endeavours to uncover and correct the egregious misrepresentations and misreadings of the rights and roles of the Shona woman, at least from a cultural vantage point. This paper advances the argument that Western feminism is a colonial construct, one that has been imposed upon the women of Zimbabwe by imperialist forces, with the intention of sowing anarchy within African culture and the cherished institution of the family. It concludes that the very discourse of identity necessitates a process of decolonisation and reconstruction.

Based on large eddy simulations, intermittent airflow within an urban street canyon was simulated. The practice of time‐varying inflow conditions (TVIC) required a time series of inflow wind velocity, which could be collected on a varying curve of the moving averaged measured data. The influences of the time interval of the wind series and the varying trend (or molded line) between adjacent data on airflow within the street canyon were analyzed. The results showed that TVIC would result in larger average wind velocity and turbulence intensity than that simulated under steady inflow conditions (SIC). The simulated total vertical air exchanges under TVIC would be one order of magnitude higher than that simulated under SIC. Airflow characteristics within street canyons were influenced by the varying trends and the time intervals of the time‐series inflow wind. Average vertical wind velocity and turbulent kinetic energy (TKE) simulated under the stepped varying trend was higher than that under the jagged varying trend. The shorter the time interval, the larger the TKE within the street canyon. Vertical air exchanges induced by turbulence (ACH′) at the roof level simulated under the stepped molded lines were twice that of the jagged molded line. Under the time interval of 30 s, the ACH′ was significantly increased, which was 2.558 times that simulated with a time interval of 1 min. Thus, the suggested practical approach for time‐varying inflow simulations is to obtain time‐series wind data with a time interval of 1 min or less, and the linearly molded line would be critical; for larger time intervals, reasonable molded lines would be required.

This paper makes use of a time-varying parameter VAR (TVP-VAR) with stochastic volatility using OECD data to explore the impact of the uncertainty associated with COVID-19 stabilization shocks on inflation. The findings document that the response of inflation is primarily positive, implying that such uncertainty shocks propagate like aggregate supply shocks with the results remaining robust under alternative uncertainty shocks and inflation metrics.

Background Alzheimer’s Disease research lacks a suitable model to match the sporadic version of Alzheimer’s Disease (SAD). We a propose a model that will use 7PA2 cells which is a CHO modified to express the V717F mutation for APP (Indiana mutation). The 7PA2 cells will then be placed inside alginate microbeads to produce a factory that constantly produces amyloid species. Then the injected into the brains of rats. Generating pathological changes which can be compared against previous models and human data to test whether this model is more appropriate than current models. Method Alginate beads where produced of various different concentrations of alginate (Alg) and the gelling agent (calcium chloride ‐ CaCl2). 0.4 ‐ 8%Alg and 0.1M CaCl2 ‐ 1M CaCl2. Stability measured as change in diameter using a Keynes microscope and comparing diameter for beads containing bv2 cells and no cells. Stability also compared in aCSF. Young Modulus was measured using a texture analyser and rheometer. Inflammatory effects of alginate on BV‐2 cells characterised through TNF‐alpha. Result We found no changes in stability with changes in Alg or CaCl2 or if beads were in aCSF or distilled water for 4 weeks. (n = 50). No significant effects of alginate on TNF‐alpha expression levels. Young Modulus of Alg beads of 1.5% Alg and 0.3%M closely matches brain environment. Conclusion Alginate beads are stable over time in a brain‐like environment. Furthermore alginate beads of 1.5% Alg and 0.3%M closely match the brain environment. Alginate also causes no significant inflammatory response. Therefore alginate is a suitable carrier for 7PA2 further work must now be done in characterising 7PA2 cells and their amyloid species and the eventual effects in the brain.

Although the dynamic van der Waals model has great potential in numerically simulating pool boiling, it is still limited to low liquid–vapor density ratios (about 10:1) due to the inherent thermodynamic inconsistency. This study proposes a thermodynamic consistency simplified dynamic van der Waals model to simulate pool boiling with large liquid–vapor density ratios. This model is based on the thermodynamic relationship associating the gradients of temperature and generalized chemical potential with the divergence of the reversible viscous stress tensor. A novel semi-discrete numerical algorithm that satisfies the thermodynamic consistency for this mathematical model is also proposed. The numerical results exhibit excellent agreement with that of analytical, validating the effectiveness and applicability of the proposed model for vapor–liquid coexistence. Compared to the original dynamic van der Waals model, the proposed model and algorithm can effectively reduce the spurious velocity at the vapor–liquid interface, breaking the limitations of low-density ratio and leading to stable simulation at higher-density ratios under low saturation temperatures. The approach is used to model pool boiling at low saturation temperatures with different wettability and liquid–vapor density ratios, and the saturation temperature significantly lower than reported in comparable literature (as low as 0.45Tc and the liquid–vapor density ratio is about 225:1). Compared to low liquid–vapor density ratios, larger liquid–vapor density ratios inhibit bubble coalescence, thereby suppressing the formation of large bubbles. In addition, larger density ratios more effectively maintain the shape of bubbles.

Assessment is central in education and the teaching-learning process. This study attempts to explore the perspectives and views about quality assessment among teachers of English as a Foreign Language (EFL), and to find ways of promoting quality assessment. Quantitative methodology was used to collect data. To answer the study questions, a questionnaire was distributed to 37 EFL teachers at a public college in Oman. The findings show that the majority of teachers are not satisfied with the current assessment practices and they believe that much effort is needed to promote quality assessment. Furthermore, the vast majority of teachers assume that using alternative assessment tools such as moderation, building an item bank, having tight exam policies and procedures, providing clear exam instructions, training teachers on quality assessment, and aligning assessment with teaching would help in fostering quality assessment. Based on teachers' views and findings from the literature, the study proposes a multidimensional model for quality assessment which may help in achieving and promoting quality assessment.

During recent decades, changes in lifestyle have led to widespread nutritional obesity and its related complications. Remodelling adipose tissue as a therapeutic goal for obesity and its complications has attracted much attention and continues to be actively explored. The endothelium lines all blood vessels and is close to all cells, including adipocytes. The endothelium has been suggested to act as a paracrine organ. We explore the role of endothelial insulin-like growth factor-1 receptor (IGF-1R), as a paracrine modulator of white adipose phenotype. We show that a reduction in endothelial IGF-1R expression in the presence of high-fat feeding in male mice leads to depot-specific beneficial white adipose tissue remodelling, increases whole-body energy expenditure and enhances insulin sensitivity via a non-cell-autonomous paracrine mechanism. We demonstrate that increased endothelial malonate may be contributory and that malonate prodrugs have potentially therapeutically relevant properties in the treatment of obesity-related metabolic disease.

Malaria has been a severe global and public health concern for the last couple of decades. Ghana, like many other countries in sub–Saharan Africa, is most affected by the disease, with children facing dire consequences. The recent introduction of the RTS, S malaria vaccine holds great potential in reducing malaria fatalities in children. However, RTS, S implementation have inherent challenges that raise the stakes of vaccine defaults in piloted areas in Ghana. In this study, we examine the predictors of RTS, S vaccine defaults using a cross-sectional research design that covers a sample of 765 caregivers in Southern Ghana. Classification models (Binary logistic regression and Random Forest) were performed to identify critical socio-demographic, health and RTS, S related predictors. The findings show that more than a third (38.43%) of children defaulted at least one dose of the malaria vaccine. Key predictors of defaults included sub-metro of residence, cost of traveling to health facilities, experience of adverse events, knowledge about the vaccine doses, caregiver’s employment status, and religion. Our findings emphasize the need for targeted interventions to reduce defaults, mainly focusing on caregiver education on vaccines, reducing financial barriers to healthcare access, and addressing concerns about adverse events.

This study provides a comparative assessment of the capabilities of leading artificial intelligence (AI) tools and human participants in a business management education context. Specifically, we (a) assess how well current language models perform in providing answers to standardised essay‐type assessments in a business and management education context, (b) examine the efficacy of emergent tools in detecting AI‐generated texts and (c) evaluate online AI rewriting and paraphrasing tools and their efficacy in evading detection. Using an exploratory qualitative design, this study generated and evaluated 15 standard essays using ChatGPT (n = 5), Bard (n = 5) and human (n = 5). A comparison is provided between the average performance of AI‐derived essays and that of ChatGPT‐generated essays across all five essays. The results suggest that AI‐generated content can achieve reasonably high marks in management and business assessments. According to the findings of the study, AI's performance is highly influenced by the types of prompts used, the user's experience and the degree to which the user can discern between relevant and irrelevant content. According to the findings, Turnitin's AI detection tool is highly effective at detecting content that has been created by AI, but the effectiveness is reduced by rewriters. The Turnitin AI detection tool, however, is significantly more effective at identifying content generated by Bard compared with content generated by ChatGPT. According to the results, ChatGPT produced better results when the user provided a clear context, outlined the topic and expectations, divided the assessment tasks into sections and fed the prompts in a conversational manner to train the model. By utilising AI chatbots effectively, traditional teaching and assessment methods can be supplemented with targeted and engaging learning experiences.

Unanticipated and rapid change in facial expression are micro-expression (ME) that are hard to hide after an emotionally charged event. Facial microexpressions are transient and subtle, making identification challenging. Recognition of MEs are very crucial in the light of personal intention phase identification. Previous studies had challenges recognizing ME due to complicated spatiotemporal linkage in video data. Using the ConvMixer architecture, we Proposed a novel technique for facial microexpression identification based on convolutional attention mechanism. The research uses SAMM, SMIC, and CASME-II are benchmark datasets used to perform experiments. ConvMixer deployed to analyze the SAMM dataset where ConvMixer achieved an amazing 99.73% accuracy, 97.3% precision, 96.5% recall, and 99% F1-Score while 10-fold cross-validation. In addition, we extended our analysis to the CASME-II dataset, where ConvMixer attained an F1-Score of 99.4%, an accuracy of 99.12%, a precision of 98.3%, and a recall of 98.7%. These findings indicate that ConvMixer regularly outperforms other MER architectures, while capturing video specific and dynamic characteristics. ConvMixer architecture are good in capturing both spatial and temporal correlations and extracts spatial information using depthwise convolutions and channel mixing processes. High F1-Score, recall, precision, and accuracy across several datasets demonstrate the robustness and adaptability of the ConvMixer architecture. Finally, our findings show that the Convolutional Attention-Based Mechanism for facial microexpression recognition (CABM-FMER) works effectively for identifying facial MEs.