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Exploring the experiences of ethnic minority postgraduate researchers in the UK
Get PDFRacism and inequity remain widespread in Higher Education Institutions (HEIs), hindering ethnic minority (EM) postgraduate researchers’ (PGRs) prospects. A deeper understanding of the experience of EM PGRs and the obstacles they face is needed. This study endeavoured to explore the plurality of EM PGRs’ experiences and generate PGR-led recommendations. As a largely White research team, we also saw the study as a transformative opportunity for ourselves and other academics across the sector. Fifteen EM PGRs enrolled on UK doctoral programmes took part in semi-structured interviews. A reflexive inductive thematic analysis was conducted. Critical Race Theory and Intersectionality were used as backdrops to contextualise the study and its findings. The analysis generated four themes: disempowerment, systemic deficits, weathering and from surviving to thriving. The findings indicate that EM PGRs faced multiple challenges during their doctoral journey, which were often triggered and amplified by circumstances specific to their ethnicity. The results suggest that HE environments are still dominated by White norms as well as oppressive systems and attitudes that disempower EM PGRs and stifle their sense of belonging and ability to thrive. Female and international EM PGRs were particularly marginalised. Participants made recommendations for change, including proactive outreach support for EM PGRs and creating culturally sensitive environments to foster positive doctoral experiences for all. Cultural change within HEIs needs to go beyond superficial policies, and to achieve this, academics and HE leaders need to lead by example in generating profound and durable change
Pseudopolar Format Matrix Description of Near-Range Radar Imaging and Fractional Fourier Transform
Get PDFNear-range radar imaging (NRRI) has evolved into a vital technology with diverse applications spanning fields such as remote sensing, surveillance, medical imaging and non-destructive testing. The Pseudopolar Format Matrix (PFM) has emerged as a promising technique for representing radar data in a compact and efficient manner. In this paper, we present a comprehensive PFM description of near-range radar imaging. Furthermore, this paper also explores the integration of the Fractional Fourier Transform (FrFT) with PFM for enhanced radar signal analysis. The FrFT—a powerful mathematical tool for signal processing—offers unique capabilities in analysing signals with time-frequency localization properties. By combining FrFT with PFM, we have achieved significant advancements in radar imaging, particularly in dealing with complex clutter environments and improving target detection accuracy. Meanwhile, this paper highlights the imaging matrix form of FrFT under the PFM, emphasizing the potential for addressing challenges encountered in near-range radar imaging. Finally, numerical simulation and real-world scenario measurement imaging results verify optimized accuracy and computational efficiency with the fusion of PFM and FrFT techniques, paving the way for further innovations in near-range radar imaging applications
Public Health Challenges and Responses to the Growing Ageing Populations
Get PDFBackground
Human populations are rapidly ageing worldwide due to declining birth rates and rising life expectancies. This profound demographic shift presents complex public health challenges. Synthesizing evidence on key public health issues impacting ageing populations and policy strategies is required to address these needs.
Methods
The study employs narrative literature review based on the PubMed database. Data have been extracted on public health challenges to ageing populations and its recommended policy solutions.
Results
The key public health challenges identified include rising chronic disease burden, risks for preventable multi-morbidities and co-morbidities, disability and dependencies, mental health issues, caregiving gaps, long-term care system deficiencies, health inequities, healthcare access barriers, end-of-life care needs, financial instability, ageism/elder abuse, adverse built environments, climate/disaster threats, and social isolation. Evidence-based policy responses span interventions in healthcare, social services, urban planning, emergency preparedness, economics, technology, anti-ageism advocacy and so on.
Conclusions
Proactively addressing the array of public health challenges faced by rapidly growing ageing populations globally requires implementing collaborative, multisectoral policy solutions focused on promoting healthy, equitable, and socially engaged ageing. Healthcare systems, communities, and policies must be optimized to meet the needs of elderly people and tap into their strengths
Modelling and Optimising the Performance of Graphene Oxide-Cu2SnS3-Polyaniline nanocomposite as an Adsorbent for Mercury Ion Removal
Get PDFFinding a cost-effective, efficient and environmentally friendly technique for removal of mercury ion (Hg2+) in water and wastewater can be a challenge task. This paper presents a novel and efficient adsorbent known as the Graphene oxide-Cu2SnS3-Polyaniline (GO-CTS-PANI) nanocomposite, which was synthesised and utilised to eliminate mercury ions (Hg2+) from water samples. The soft–soft interaction between Hg2+ and sulfur atoms besides chelating interaction between -N and Hg2+ and also electrostatic interaction are the main mechanisms for Hg2+ adsorption onto the GO-CTS-PANI adsorbent. Various characterisation techniques, including Fourier transform infrared spectrophotometry (FT-IR), Field Emission Scanning Electron Microscopy (FESEM), Energy-dispersive X-ray spectroscopy (EDX), Elemental Mapping analysis, and X-ray diffraction analysis (XRD), were employed to analyse the adsorbent. The Box-Behnken method, utilising Design Expert Version 7.0.0, was employed to optimise the crucial factors influencing the adsorption process, such as pH, adsorbent quantity, and contact time. The results indicated that the most efficient adsorption occurred at pH 6.5, with 12 mg of GO-CTS-PANI adsorbent, and a 30-minute contact time, achieving a maximum removal rate of 95% for 50 mg/L Hg2+ ions. The study also explored the isotherm and kinetics of the adsorption process, revealing that adsorption took place in sequential layers (Freundlich isotherm) and was followed by a physical interaction between the adsorbent and the adsorbate. The pseudo second-order kinetic equation proved to be a suitable model for interpreting the kinetic data. Furthermore, Response Surface Methodology (RSM) analysis indicated that pH was the most influential parameter in enhancing adsorption efficiency. In addition to traditional models, this study employed artificial intelligence methods, such as the Random Forest algorithm, to enhance the prediction of adsorption process efficiency. The findings demonstrated that the Random Forest algorithm exhibited high accuracy, achieving a correlation coefficient of 0.98. Overall, this research underscores the potential of the GO-CTS-PANI composite for effectively removing Hg2+ ions from water resources
Physics-Informed AI-based Modelling for Flood Early Warning Systems
No full textToday, the vast majority of early warning systems (EWS) are introduced in which advanced deep learning, recurrent neural network or ensemble-based data mining techniques are applied to provide more accurate and reliable flood forecasting [1]. This trend have been gained more trends mainly due to recent advances in computational capabilities, technological enhancement, and data science-based modelling have empowered these data-driven models [2]. A novel addition in this community is the physics-informed neural network models (PINN), integrating physical principles and constraints into architecture of data driven models. This hybrid approach is particularly beneficial in scenarios where prior knowledge of underlying physics such as nature of rainfall occurrence or catchments hydraulic characteristics are limited [3].
In the present study, PINN-based ensemble multi-class data mining model, inspired by [4] is introduced for forecasting water level classes ranging from no risk to high risk in the context of urban drainage systems (UDS). To keep simplicity, this model is developed with only two datasets: rainfall and UDS water levels. In addition to conventional inputs such as rainfall intensity, duration, session, and soil moisture, two physics-informed rainfall inputs - namely, the potential future return period (RP) of current rainfall and the current return period class - are incorporated. Additionally, two physics-informed catchment water level inputs - specifically, the water level class at the current timestep and the duration of the current class - are integrated into the model framework. The introduction of these new parameters aims to offer valuable insights into system dynamics, enhancing the model's ability to comprehend both short-term and long-term memory patterns.
The results, assessed using the method outlined in [2], indicate a substantial improvement in hit rates - from 67% to 88% - compared to a benchmark model. Notably, time lags in the correct detection of water level classes, are halved on average, reducing from 2-timstep intervals. More specifically, the rate of event underestimation decreases from 7% to 2%, showcasing that the new method has the potential to reduce false alarms in EWS. It is essential to note that the application of PINN is currently limited to using only physics-informed input data. However, a promising avenue for future exploration involves extending this approach to adjusting hyperparameters of data-driven models with physics equations. This adaptation is recommended for future directions in research and application
Telehealth education for South Asian immigrants in America with type 2 diabetes and hypertension
Get PDFMultimorbidity is one of the pressing global medical issues facing health systems in the developed world today2. The co-existence significantly worsens the prognosis of both diseases and language differences may make it difficult for immigrants to learn about the disease condition1-2. Whilst there are several management techniques for this condition, it is important to provide culturally and linguistically adapted interventions for this group of individuals1. In the last decade, experts in diabetes education from numerous nations have identified the benefits of individualised education encompassing linguistic and cultural considerations. The Diabetes Research, Education, and Action for Minorities (DREAM) study examines the feasibility and benefits of an evidence-based community health worker (CHW) led culturally tailored telehealth education in improving diabetes care1
Equity and timeliness as factors in the effectiveness of an ethical prenatal sequencing service: reflections from parents and professionals
No full textPrenatal sequencing tests are being introduced into clinical practice in many developed countries. In part due to its greater ability to detect genetic variation, offering prenatal sequencing can present ethical challenges. Here we review ethical issues arising following the implementation of prenatal sequencing in the English National Health Service (NHS). We analysed semi structured interviews conducted with 48 parents offered prenatal sequencing and 63 health professionals involved in delivering the service to
identify the ethical issues raised. Two main themes were identified: (1) Equity of access (including issues around eligibility criteria, laboratory analytical processes, awareness and education of clinicians, fear of litigation, geography, parental travel costs, and access to private healthcare), and (2) Timeliness and its impact on parental decision-making in pregnancy (in the context of the law around termination of pregnancy, decision-making in the absence of prenatal sequencing results, and the “importance” of prenatal sequencing results). Recognising both the practical and systemic ethical issues that arise out of delivering a national prenatal sequencing service is crucial. Although specific to the English context, many of the issues we identified are applicable to prenatal
sequencing services more broadly. Education of health professionals and parents will help to mitigate some of these ethical issues
The role of gut microbiota in chronic restraint stress-induced cognitive deficits in mice
Get PDFBackground: Chronic stress induces cognitive deficits. There is a well-established connection between the enteric and central nervous systems through the microbiota-gut-brain (MGB) axis. However, the effects of the gut microbiota on cognitive deficits remain unclear. The present study aimed to elucidate the microbiota composition in cognitive deficits and explore its potential in predicting chronic stress-induced cognitive deficits. Methods: Mice were randomly divided into control and chronic restraint stress (CRS) groups. The mice subjected to CRS were further divided into cognitive deficit (CRS-CD) and non-cognitive deficit (CRS-NCD) groups using hierarchical cluster analysis of novel object recognition test results. The composition and diversity of the gut microbiota were analyzed. Results: After being subjected to chronic restraint distress, the CRS-CD mice travelled shorter movement distances (p = 0.034 vs. CRS-NCD; p < 0.001 vs. control) and had a lower recognition index than the CRS-NCD (p < 0.0001 vs. CRS-NCD; p < 0.0001 vs. control) and control mice. The results revealed that 5 gut bacteria at genus levels were significantly different in the fecal samples of mice in the three groups. Further analyses demonstrated that Muricomes were not only significantly enriched in the CRS-CD group but also correlated with a decreased cognitive index. The area under the receiver operating curve of Muricomes for CRS-induced cognitive deficits was 0.96. Conclusions: Our study indicates that the composition of the gut microbiota is involved in the development of cognitive deficits induced by chronic restraint stress. Further analysis revealed that Muricomes have the potential to predict the development of chronic stress-induced cognitive deficits in mice.
Keywords: Gut microbiota, Chronic restraint stress, Cognitive deficits, Muricomes Mic
‘California on the Vistula River?’ Cannabis users’ engagement with licit and illicit cannabis markets in Poland
Get PDFBackground: Poland, like many other countries, has experienced a shift in its drug policy, as reflected in its government's decision to legalise medical cannabis in 2017. Some media argue that even recreational users are finding ways of using the medical system – in some ways resembling the Californian legalisation of medical cannabis (1996-2016).
Method: Data comes from the Ministry of Health, and an extensive survey of 571 cannabis users asked about their engagement with the licit and illicit cannabis markets in Poland.
Results: Most respondents reported that, at the time of the study, they did not engage with the illicit cannabis market. The majority described themselves as medical users, but a significant proportion identified as recreational users who managed to procure doctors’ prescriptions. This shows that medical users now enjoy better access to cannabis and reflects potential changes to the practices of physicians involved in the market – notably the emergence of cannabis clinics. Some, however, continue to use the illegal cannabis market due to reasons associated with access, price, and quality of cannabis.
Conclusion: This research shows that increasingly more users are likely to opt out of the regulated medical market than the traditional illegal cannabis market. Many of them are recreational users. This could mean that the current policy in Poland is starting to resemble the Californian legalisation of medical cannabis (1996-2016)
A practitioner reflection and response to students’ perceptions of assessment at Higher EducatioN
Get PDFAssessments are an integral component of university programmes. They have the formative function of being instrumental in gauging the level of student engagement, whilst also providing opportunity for feedback to enhance students’ learning. Moreover, assessments have the summative function of providing grades on which degree classifications are based. Therefore, it is crucial that assessments are presented in a format that engage students. Listening to the student voice is an essential step in designing appropriate assessments. The aim of this reflection piece is to review and critique how the student voice is captured. While students have various informal and formal opportunities to voice their views, here we chose to focus on processes that result in recorded data, namely, Student Evaluation of Teaching (SET) surveys, Module Evaluation Surveys (MES), and research on students’ experience of assessments. We conclude by outlining an example of our adjustments to assessments, based on the student voice