Effects of energy drinks on mental health and academic performance of university students: A systematic review and meta-analysis protocol

Objectives: Energy drink (ED) consumption is frequently observed among higher education students and is often associated with increased concentration and academic performance. However, the purported benefits are not fully supported by scientific evidence. This protocol details methods for a systematic review and meta-analysis to evaluate the effects of ED on university students’ mental health and academic performance. Methods: The PECO framework will guide the search strategy, and the protocol will follow the PRISMA-P 2015, PRESS 2015, and PRISMA-S guidelines. The searches will be conducted in the following databases: Web of Science, Scopus, Ovid, PubMed, Embase, FSTA, CINAHL, and SPORTDiscus. The GRADE recommendations and the Downs and Black scale will assess study quality and bias. All statistical analyses will be conducted using Comprehensive Meta-analysis software. We will use Cochran’s Q with p < 0.05 to indicate significant heterogeneity and I² to quantify heterogeneity between studies. The Trim and Fill technique and Egger’s regression test will be applied to evaluate the funnel plot that will be generated. Results: Carrying out the systematic review proposed by this protocol will provide evidence on the short-, medium-, and long-term effects of ED use on academic performance and mental health among higher education students. Conclusion: A deeper understanding of ED consumption among higher education students can inform the development of evidence-based educational and public health policies to promote student well-being and mitigate associated health risks

Flush: A Biography. The Cambridge Edition of the Works of Virginia Woolf

The Cambridge Edition of Virginia Woolf's 1931 fictional biography of Elizabeth Barrett Browning's cocker spaniel. Includes extensive introduction, explanatory notes, textual notes and textual apparatus, unpublished drafts and Atlantic Monthly magazine version of the text

Elucidating the mode of action of Occidiofungin - a current first in class antifungal

Fungal infections are responsible for an approximate 1.5 million deaths annually, with there being no licensed vaccines or vaccines currently in clinical study for fungal disease. This combined with the increasing resistance to the current antifungals in clinical use, highlights an ever increasing need for new antifungal research. My research aims to elucidate the mode of action of a current first in class antifungal known as Occidiofungin. This antifungal is currently undergoing clinical trials and has shown potent broad spectrum activity in the treatment of pathogenic yeast. My aim was to determine the mechanism that this drug uses in order to kill fungal cells. Previous research suggested that Occidiofungin may target the Actin cytoskeleton and as Actin is essential to cell function this may represent a plausible mode of action. I employed a range of techniques to investigate whether Occidiofungin inhibits the function of Actin and whether recognised Actin-related modes of cell death were activated. My findings suggest that Actin is not targeted but rather Occidiofungin induces necrosis in cells in a gradual manner. This finding was strengthened by observations that a fluorescent tagged Occidiofungin (Alkyne Occidiofungin) was not internalised but accumulated at the outer surface of the yeast cell. The fungal specificity of Occidiofungin was also investigated through the use of haemolysis assays and the Galleria mellonella infection model. This pre-clinical data suggested that Occidiofungin is indeed fungal specific and so is a promising candidate for use as a future therapeutic. Future research will determine the fungal specific target of Occidiofungin that is responsible for the induction of necrosis which may in turn lead to the expansion of this class of antifungal. If targeting the fungal cell wall, upon recognition of the target component, this would have broad applications both in the knowledge of the drug and proof that is has fungal specificity, it could also indicate a novel site that could be used in drug design and development

Understanding the role of metabolic syndrome in prostate cancer risk: A UK Biobank prospective cohort study

Predictive value of metabolic syndrome for prostate cancer risk is not clear. We aimed to assess the association between metabolic syndrome and its components with prostate cancer incidence. The primary outcome was prostate cancer incidence, i.e., incidence rate ratios and adjusted cumulative incidence curves derived from flexible parametric survival models. Adjusted cumulative incidence curves were derived using a flexible survival parametrical modeling framework. We analysed UK Biobank data including 242,349 adult males, recruited during 2006–2010 and followed up until 2021, during which 6,467 (2.7%) participants were diagnosed with prostate cancer. Our findings indicate that metabolic syndrome, as a whole, was not associated with prostate cancer risk (incidence rate ratios, 1.07; 95% confidence interval, 0.94–1.22). However, specific components such as hypertension and obesity increased the risk (incidence rate ratios, 1.22; 95% confidence interval, 1.03–1.44 and incidence rate ratios, 1.24; 95% confidence interval, 1.05–1.46, respectively). Other components, such as prediabetes/diabetes and low cholesterol, were associated with a reduced risk (incidence rate ratios, 0.80; 95% confidence interval, 0.67–0.94 and incidence rate ratios, 0.82; 95% confidence interval, 0.69–0.97, respectively), while hyperlipidaemia showed no significant effect (incidence rate ratios, 1.07; 95% confidence interval, 0.93–1.24). Further research is needed to understand the underlying mechanisms behind these relationships. Prostate cancer prevention strategies might benefit from targeting modifiable risk factors, particularly hypertension and obesity

A mixed method evaluation of a novel targeted health messaging intervention to promote COVID-19 protective behaviours and vaccination among black and South Asian communities living in the UK (The COBHAM study)

Aim: To evaluate an intervention (a film and electronic leaflet) disseminated via text message by general practices to promote COVID-19 preventative behaviours in Black and South Asian communities. Methods: We carried out a before-and-after questionnaire study of attitudes to and implementation of COVID-19 preventative behaviours and qualitative interviews about the intervention with people registered with 26 general practices in England who identified as Black or South Asian. Results: In the 108 people who completed both questionnaires, we found no significant change in attitudes to and implementation of COVID-19 preventative behaviours, although power was too low to detect significant effects. A key qualitative finding was that participants felt they did not ‘belong’ to the group targeted by the intervention. Conclusion: Interventions targeting ethnic minorities in the UK need to acknowledge the heterogeneity of experience and circumstances of the target group so that people feel that the intervention is relevant to them

Investigating Mobile Technology for Experiential Outdoor Heritage Practices

This thesis investigates the potential of innovative mobile guides to enhance heritage experiences during walks in historic urban precincts. Focusing on the effects of smartphone-based and mobile projector-based guides, the research explores how different display modalities influence visitors' embodied and social engagement, behaviour, and meaning-making processes in complex, multi-sensory heritage environments. Through a series of empirical studies conducted in Canterbury's historic high street, involving 66 participants, the research employs a multi-method approach including surveys, interviews, observations, and participant-generated materials. The findings reveal that while smartphone guides often create a 'bubble' effect, isolating users from their surroundings, mobile projector guides foster more exploratory, playful, and socially engaged interactions with the heritage site. The thesis proposes a novel approach to designing mobile guides through the lens of 'playful walking', emphasizing the importance of supporting not only cognitive engagement but also multi-sensory, embodied, and social interactions. This approach is synthesized into actionable design considerations and four innovative design directions, illustrated with conceptual examples. Key contributions include technology design, empirical observations on the affordances of different mobile guide types, and a set of design principles for creating devices that support embodied heritage interpretation practices. The research highlights the potential of mobile projector guides to transform static heritage sites into dynamic spaces for interaction, fostering deeper connections between visitors and their surroundings. While primarily focused on historic urban precincts, the findings offer broader implications for designing mobile guides that enhance heritage experiences in contexts such as archaeological sites, living history museums, etc

Explainable artificial intelligence for business and economics: methods, applications and challenges

In recent years, artificial intelligence (AI) has made significant strides in research and shown great potential in various application fields, including business and economics (B&E). However, AI models are often black boxes, making them difficult to understand and explain. This challenge can be addressed using eXplainable Artificial Intelligence (XAI), which helps humans understand the factors driving AI decisions, thereby increasing transparency and confidence in the results. This paper aims to provide a comprehensive understanding of the state-of-the-art research on XAI in B&E by conducting an extensive literature review. It introduces a novel approach to categorising XAI techniques from three different perspectives: samples, features and modelling method. Additionally, the paper identifies key challenges and corresponding opportunities in the field. We hope that this work will promote the adoption of AI in B&E, inspire interdisciplinary collaboration, foster innovation and growth and ensure transparency and explainability

Development of a Microcontroller-Based Recurrent Neural Network Predictive System for Lower Limb Exoskeletons

Practical deployments of exoskeletons can often be limited by cost, limiting access to their usage by those that would benefit from them. Minimising cost whilst not harming effectiveness is therefore desirable for exoskeleton development. For Control Systems governing assistive and rehabilitative exoskeletons that react to the wearer’s movements, there will inevitably be some delay between when their wearer intends to move and when the exoskeleton can assist with this movement. This can lead to situations where a user may be limited by their own assistive exoskeleton, reducing their ability to move freely. A potential solution to this is to provide a proactive method of control, where the most likely path of the wearer’s movement is predicted ahead of the wearer making the motion themselves. This can be used to give the user assistance immediately as they are walking, as well as potentially pre-emptively adjust their gait if they suffer from predictable gait deficiencies. The purpose of this paper is to investigate the Data Collection, Implementation, and Effectiveness of an LSTM Recurrent Neural Network dynamically predicting future movement based off of prior movement. These methods were developed to use off the shelf, Low-Cost Microcontrollers as to minimise their Financial, Weight, and Power Impact on an overall Low-Cost exoskeleton design, as well as to evaluate how effective such an implementation would be when compared to running such a Neural Network on a more powerful processor. The created model was capable of achieving similar accuracies to far more powerful models on High-Powered Laptops

Linear or Cyclic? Theoretical Investigation of Astrophysically Relevant Magnesium-Bearing MgCnH Carbon Chains and Related Isomers

Magnesium-containing molecules, including MgC2H, MgC4H, and MgC6H, have been detected in the interstellar medium, largely facilitated by their high dipole moments. However, despite great efforts, MgC2m + 1H species remain elusive. Given the challenges in obtaining experimental data for these molecules, theoretical studies play a crucial role in guiding their detection. In this work, we present a theoretical analysis of MgCnH isomers (n = 4-7) using density functional theory and coupled-cluster methods to identify low-lying isomers and characterize their structural and electronic properties. Our findings reveal that across the entire series investigated, the global minimum geometry is linear for even values of n, whereas for odd values, a cyclic geometry is favored. Additionally, our calculations highlight the enhanced stability of anionic MgCnH- systems, providing insights that could aid future astronomical detections in the interstellar medium

Harnessing transient CAAC-stabilized mesitylborylenes for chalcogen activation

Newly synthesized adducts of CAAC-bound mesitylborylene with carbon monoxide (CO) and trimethylphosphine (PMe3) are established as efficient precursors for the in situ generation of the dicoordinate borylene [(CAAC)BMes] (CAAC = cyclic(alkyl)(amino)carbene), as demonstrated by their ability to activate elemental chalcogens. Upon thermal or photolytic activation, these precursors readily react with sulfur and selenium, yielding boron chalcogenides characterized by terminal boron–chalcogen double bonds. In contrast, the reaction with tellurium leads to the formation of an unusual diradical ditelluride species with a Te–Te bond. Quantum chemical calculations of its electronic structure indicate an open-shell singlet ground state characterized by significant diradical character. Further investigations into the redox behavior of these boron chalcogenides reveal intriguing transformations, including the redox-induced formation and cleavage of E–E bonds