ABSTRACT
Higher education providers across the globe are confronting overwhelming disruptive patterns due to the COVID-19 epidemic. which has dramatically reshaped the face of global higher education. Transnational higher education (TNHE) is gaining traction as a method of bringing globally renowned learning to students' doorsteps. With competition heating up again following the disruption to foreign student flows caused by the COVID-19 epidemic, demand for global study opportunities closer to home is expected to surge, opening new opportunities for transnational education projects around the world. To deliver the same student experience as before the COVID19 pandemic's temporary switch from the typical teaching practices setting to remote online learning, however, has been challenging for all parties. However, TNHE can assist in the rebuilding of the post-COVID-19 international education system. The difficulties that TNHE programs are currently encountering are examined in this essay along with prospective consequences on teaching, learning, and student assistance as the post-COVID-19 educational landscape evolves. This research is supported by both a detailed analysis of the literature and unofficial data from many parties. It also examines the best way to build a strong transnational education environment over the next ten years in order to improve the standard and sustainability of international higher education.
ABSTRACT
One of the most pressing challenges facing restaurants since the COVID-19 outbreak began is personnel. A staffing scarcity across the business has resulted in a slew of issues, including significantly longer wait times and irritated clients. A robot waiter may make a huge impact in a restaurant in this situation. This research led to the formation of a low-cost Arduino-based Android application control Robot that can work as a restaurant waiter. The proposed model can follow a path, avoid obstacles, serve meals to a specific consumer, and return to the kitchen on its own. To precisely follow the line, the PID algorithm is utilized. To detect potential obstructions, a sonar sensor is used. On an LCD, messages and warnings are displayed. An Android app that allows the chief to select a particular table for serving meals. For convenience, the robot's current state is displayed in the application. Our testing results show that the robot performs satisfactorily over 90% of the time. It should be emphasized that the offered model is adaptable to any restaurant. © 2022 IEEE.
ABSTRACT
Brexit, COVID-19 and climate change pose challenges of national and global importance. They continue to have impacts across the economy, society, health, and the environment, all of which are determinants of health and well-being. Between 2018 and 2021, Public Health Wales undertook three Health Impact Assessments (HIA) in relation to the impact of the challenges in Wales. Based on these, work has been carried out to map the synergies across the 'Triple Challenge'. This paper highlights the commonalities in the impact of the three challenges for Wales, discusses the process carried out, learns from it and proposes actions that can be taken to mitigate harm. Results indicate the three components of the Triple Challenge must not be viewed as separate silos as they have cumulative multi-faceted impacts. This affects some population groups more negatively than others and present a 'Triple Challenge' to nation states in the UK and Europe. A HIA approach can enable a range of stakeholders to critically view similar challenges not just as single issues but as a holistic whole to mobilise action.
ABSTRACT
Early identification and adequate treatment can help prevent lung disorders from becoming chronic, severe, and life-threatening. X-ray images are commonly used and an automated and effective method involving deep learning techniques can potentially contribute to quick and accurate diagnosis of lung disorders. However, in the study of medical imaging using deep learning, two obstacles limit interpretability. One is an insufficient and imbalanced number of training samples in most medical datasets. The other is excessive training time. Although training time can be reduced by decreasing the number of pixels in the images, training with low resolution images tends to result in poor performance. This study represents a solution to overcome these impediments by balancing the number of images and reducing overall processing time while preserving accuracy. The dataset used in this research contains an unequal number of images in the different classes. The quantity of data in the classes is balanced by creating synthetic images based on the patterns and characteristics of the original images, using a Deep Convolutional Generative Adversarial Network (DCGAN). Unwanted regions are removed from the X-ray images, the brightness and contrast of the images are enhanced, and the abnormalities are highlighted by using different artifact removal, noise reduction, and enhancement techniques. We propose a Modified Compact Convolutional Transformer (MCCT) model using 32 × 32 sized images for the categorization of lung disorders into four classes. An ablation study of eleven cases is employed to adjust several hyper parameters and layer topologies. This reduces training time while preserving accuracy. Six transfer learning models, VGG19, VGG16, ResNet152, ResNet50, ResNet50V2, and MobileNet are applied with the same image size the performance is compared with the proposed MCCT model. Our MCCT model records the greatest test accuracy of 95.37%, requiring a short training time, 10-12 s/epoch, whereas the other models only reach near-moderate performance with accuracies ranging from 43% to 79% and training times of 80-90 s/epoch. The robustness of the model with regards to the number of training samples is validated by training the model multiple times reducing the number of training images gradually from 49621 images to 6204 images. Results suggest that even with a smaller dataset, the performance is sustained. Our proposed approach may contribute to an effective CAD based diagnostic system by addressing the issues of insufficient and imbalanced numbers of medical images, excessive training times and low-resolution images. © 2022
ABSTRACT
Since the spread of the coronavirus disease 2019 (COVID-19) was designated as a pandemic by the World Health Organization, health care systems have been forced to adapt rapidly to defer less urgent care during the crisis.The United States (U.S.) has adopted a four-phase approach to decreasing and then resuming non-essential work. Through strong restrictive measures, Phase I slowed the spread of disease, allowing states to safely diagnose, isolate, and treat patients with COVID-19. In support of social distancing measures, non-urgent studies were postponed, and this created a backlog. Now, as states transition to Phase II, restrictions on non-essential activities will ease, and radiology departments must re-establish care while continuing to mitigate the risk ofCOVID-19 transmission all while accommodating this backlog. In this article, we propose a roadmap that incorporates the current practice guidelines and subject matter consensus statements for the phased reopening of non-urgent and elective radiology services. This roadmap will focus on operationalizing these recommendations for patient care and workforce management. Tiered systems are proposed for the prioritization of elective procedures, with physician-to-physician communication encouraged. Infection control methods, provision of personal protective equipment (PPE), and physical distancingmeasures are highlighted. Finally, changes in hours of operation, hiring strategies, and remote reading servicesare discussed for their potential to ease the transition to normal operations.
ABSTRACT
Novel coronavirus disease 2019 (COVID-19) pandemic has produced profound effects on the global healthcare systems including every specialty. Pregnant women are physiologically immunocompromised and may be affected more by the pandemic than the general population. New and unique challenges were encountered by hospitals and healthcare providers (HCPs) related to medical, surgical and strategic management involved in obstetric care. Data of obstetric patients presenting in labour and delivery unit from April to July 2020 was studied. In all 533 patients presented, 46 (8.6%) were COVID-19 positive. Overall, 41% cesarean sections were performed with one mortality and one COVID-19-positive neonate. The challenges faced by HCPs regarding delivery of care and collective successive measures taken to overcome those challenges as well as challenges faced by patients related to healthcare provision are also addressed. Strategies adopted for timely intervention to overcome those challenges were implemented for smooth and safe care to all patients and staff. We believe that planning and preparing proactively is the key to address any pandemic like COVID-19.
ABSTRACT
The SARS-COV-02 pandemic has globally resulted in a number of policies and interventions to address and reduce the transmission of the disease throughout the population. Mitigation measures have ranged from ‘Staying at Home' or ‘Lockdowns' to social distancing policies and requirements to work from home when you can. Whilst there are a number of papers which discuss the effects of home or remote working on employees and their families the large scale shift, accelerated pace and wider impacts of such a shift has not been well explored in the literature or has been focussed on specific topics, for example, productivity. HIA is promoted as a beneficial tool to identify the wider impacts of a policy, plan or intervention across a population and as such is well placed to examine and articulate who in a population may be affected and how, and the inequalities that may be created by an intervention such as home working. Using the lens of social determinants and equity focussed-HIA, this work examines the wider impact of home working in Wales during the COVID-19 pandemic. It provides a coherent overview of the major impacts on health and the particular populations affected. It articulates the process followed, the key evidence based findings, discusses the gaps in the evidence base that require further exploration and the impact and influence it has had to date. Finally, it shares the transferable learning, which will be of use to researchers, policy and decision makers, organisations and public health agencies.
ABSTRACT
The Covid-19 pandemic has wreaked havoc throughout the world, with 150 million cases to date and over 3 million lives claimed worldwide. Objectives: To explore the impact of the Covid-19 lockdown on psychological health parameters i.e. depression, anxiety and stress as well as on body mass index among medical students studying in a private medical college in Pakistan. Study Design: Experimental study. Methodology: This study with enrolled students (n=233) was carried out after ethical review committee’s (ERC) approval at CMH Kharian Medical College (CKMC), Physiology Department, Kharian-Pakistan. Both male and female medical students were enrolled. In phase 1, the students reported to the Physiology laboratory where age and gender were recorded. The pre-lockdown readings of BMI and DASS-21(Depression, Anxiety, Stress) scale were taken. In phase-2, the post-lockdown readings of BMI and DASS-21 scale were taken once the students returned to campus. Statistical analysis: Data was analyzed by SPSS software, version 21. BMI and DASS-21 score were presented as mean + SD. Statistical significance was taken at p value <0.05. Results: In present study, results showed that there was a decrease in level of depression post-Covid-19-lockdown among enrolled subjects with significant p-values (0.019*) in the pre and post covid-19-lockdown comparison. Conclusion: We concluded that significant difference was seen between Pre & Post Covid-19-lockdown depression with p-value of <0.019. However, insignificant difference was seen between Pre & Post Covid-19-lockdown anxiety and stress with p-value of >0.05. Key Words: Covid-19 lockdown, Medical students, Depression, BMI and Anxiety.
ABSTRACT
Background/AimsDuring the peak of COVID-19 pandemic, there were growingconcerns that rheumatology patients could have an increased risk ofcontracting coronavirus due to the immunosuppressive drugs that theywere taking. British Society for Rheumatology (BSR) recommended inits risk stratification guide in March 2020 that vulnerable patientsshould be either shielded or isolated according to their level of risk.The purpose of this survey is to evaluate the compliance to the riskstratification advice among rheumatology patients in a single centre.MethodsRisk stratification guidance was sent out to 401 patients recommending either to shield or to isolate. Patients were contacted over thetelephone between 14 September and 18 October 2020 to ensure theyhad received a postal letter with risk stratification advice. If received, itwas checked whether they had followed the guidance. Responsesreceived from all participants were analysed.Results93% (373) of patients confirmed that they had received the guidance;however, 8 patients suggested they hadn't received and we wereunable to contact 16 patients, despite trying multiple times. Fourpatients died but they did not have confirmed coronavirus. 267confirmed they were shielding and 83 were isolating, but 21 patientsdecided not to follow the guidance despite the recommendation andtwo patients stopped taking the drugs due to fear of contracting thecoronavirus. Total 258 females and 143 males with the mean age 59.Most common diagnoses were rheumatoid arthritis (227), psoriaticarthritis (97) and axial spondyloarthritis (59). It was noted that out of 7patients who had symptoms suggestive of COVID-19, only threepatients were confirmed to have COVID-19 positive PCR test. Threemost commonly used drugs were Benepali (128) followed by Amjevita(100), then Rituximab (56).ConclusionAlthough uptake of postal communication was high in this study, it wasdifficult to establish how rapidly the guidance was delivered. Werealise the need to employ better ways of communicating with thepatients. Innovative ways such as text messaging and social mediahave an important role in the delivery of a rapid mass communicationduring the pandemic. It was reassuring to note that only a very smallnumber of patients had COVID-19 among the patients who followedthe government advice to either shield or isolate. But, it would beinteresting to see whether the incidence of COVID-19 cases rise sincerheumatology patients are no longer shielding.
ABSTRACT
Aims: Historically the National Diabetes Prevention Programme (NDPP) has low retention rates which are accentuated in the BAME population. We aimed to design and deliver a fun, alternative type 2 diabetes prevention programme that would have an increased retention rate and increase participant's physical activity levels. The Diabetes Prevention Decathlon (DPD) structured education programme featured;weekly health and well-being workshops and physical activity sessions, gamification and the use of a mobile phone application that incentivised continued physical activity between sessions. Method: An innovation grant awarded the opportunity for collaboration between multiple partners within the NHS, public health, community charities, patient groups, and a digital enterprise. This resulted in the creation of the DPD which was piloted in a deprived South West London borough. The inclusion criteria for participants included a HbA1c between 42 and 47 mmol/mol (6.0-6.4%), indicative for non-diabetic hypoglycaemia. Referrals, retention rates, weight loss and physical activity data were recorded over the ten-week programme alongside key demographic markers. Results: With an 87% completion rate (n31), 39 kg group weight loss and 40% increase in activity levels, the programme yielded excellent results compared to the NDPP. Semi-structured interviews highlighted the importance of group interactions and regular opportunities to be physically active. Positive but unplanned outcomes were the high BAME uptake of 77% and subsequent retention 67%, and covid driven agile conversion to virtual delivery. Conclusions: The DPD successfully piloted a new and fun approach to diabetes prevention with further intentions to work with local communities to increase and improve BAME resources.
ABSTRACT
Aims: The covid-19 pandemic has brought many challenges to medical training and education. Clinical guidelines are an important resource especially for redeployed healthcare professionals (HCPs) to manage diabetes emergencies. Our aim is to understand how non-specialist HCPs prefer the diabetic ketoacidosis (DKA) and hyperosmolar hyper-glycaemic state (HHS) guidelines to be presented to improve accessibility and adherence. Methods: An online survey was conducted in January 2021, using a QR code to access the survey via digital platforms including email, posters and MS teams. Results: Among the 101 responders, 42% were core-medical or trust-grade doctors, 22% foundation year 1 doctors, 17% higher specialty trainees and the remainder nurses, healthcare assistants, pharmacists and consultants. Despite online access to national-based trust diabetes guidelines, only 17% of surveyed HCPs were confident in prescribing and administering treatment for DKA or HHS. 92% responders had managed DKA or HHS more than once in the last 6 months. Despite the majority (88%) knowing where to access the current guidelines, only 13% of prescribing responders followed the guideline in prescribing regular basal insulin with fixed-rate intravenous insulin infusion. 88% preferred a pre-printed proforma of the guideline with examples of model prescriptions. Most useful features rated were flowcharts (76%), checklists (72%), criteria for escalation (62%) and model prescriptions (58%). Guidance on fluid management, especially in renal and heart failure, was most frequently requested. Conclusions: An online survey with QR code access has facilitated a good response and has allowed diabetes emergency guidelines to be tailored to the needs of non-specialists during the covid-19 pandemic.