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The struggle to get a PhD: the collaborative autoethnographic accounts of two 'journeymen'
No full textThe PhD is the ultimate indicator of academic excellence. The journey is familiar to most University academics and is a journey the majority have successfully completed. Yet, just as it is said history is written by the victors, so most accounts written about doing a PhD, are written by those who have succeeded, not by 'journeymen', such as the narrators of this account. There is a need for narrative accounts that both acknowledge the difficulty of the journey and also show how some candidates have battled, to achieve their PhDs. Such stories have the power to inspire those who may be struggling on their own PhD journeys. Academics can share these accounts with their own PhD students and thus hopefully improve completion rates and change practice. The authors of this narrative have adopted a collaborative autoethnographic approach to their PhD journeys. The parallel narratives are in four interdependent sections. The narratives start with both authors' unsuccessful attempts to get a PhD and end with how they, after completing their PhDs, started collaborating on research. From the authors' first attempts, their respective PhD journeys took 20 to 30 years to come to completion. The accounts show that personality features such as resilience, motivation and grit, as well as the appearance of supervisors and partners i.e. allies of help at the right time can make the difference between success and failure. Both, now in their sixties, they are looking forward to many more exciting years of joint research
A qualitative study of the experiences of care home managers during the COVID-19 pandemic in England: implications for future practice
No full textRationale and Aim: The term ‘care home’ refers to residential facilities in the UK that offer permanent residential care for the elderly. Care homes were severely impacted by the COVID-19 pandemic, as the elderly and the frail were at a greater risk than the general population of being unable to recover from infection in a care home setting. The social care crisis in the UK has been widely discussed in recent years. However, the pandemic uncovered both long-standing problems and some new ones associated with social care services. Hence, this study set out to undertake a qualitative investigation examining the lived experiences of care home managers during the COVID-19 pandemic in England and the implications for their development and approaches to future practice in social care. Methodology: This study used a qualitative phenomenological approach informed by an interpretivist research paradigm. Due to the large amount of responsibility and the need for care home managers to remain on site due to the pandemic, the methodology involved semi-structured interviews conducted online to promote participation and handle logistical preparations. The study included 12 care home managers from across England, working in both publicly financed and privately owned facilities of diverse sizes. Findings and Conclusion: The managerial and administrative tasks of care home managers were significantly altered by the pandemic. Uncertainty about how things should work, the inefficiency of current processes and the motivation to act out of concern for workers’ safety all indicate a lack of knowledge. Due to the lack of available care home staff (such as care staff, nurses and catering assistants), the managers had to take on additional responsibilities, such as filling in for other personnel and performing administrative tasks related to policy management. The managers disclosed their personal struggles in this area. The substantial knowledge asymmetry and ambiguity surrounding regulation and rapidly changing guidance was difficult to manage and share and enforce such guidance at care home level. Managers are considered knowledge brokers who spread information and ensure learning for both staff and residents’ families, and they are considered able to motivate employees by addressing their specific requirements. They are also increasingly required to use more digital resources to perform their duties, as digitalisation is a growing trend. This influx of new initiatives and new ways of working coincided with severely decreased financing, scarce resources and a severe staff shortage. The managers identified significant levels of stress, worry and exhaustion, as well as structural obstacles to education, future development and growth. Recommendations: Five recommendations were made in this study: an undertaking to improve human resources support to meet care home managers’ needs, the establishment of Communities of Practice (CoPs), a strengthening of the care home managers’ voice within the sector, enhancing of authentic multiorganisational partnerships and a true identification of healthcare system resilience (genuine preparedness)
Diagnostic and cost-effectiveness of axial skeleton MRI in staging high-risk prostate cancer
No full textCurrent literature suggests that axial skeleton magnetic resonance imaging (AS-MRI) is more sensitive than Tc 99m bone scintigraphy (BS) for detecting bone metastases (BM) in high-risk prostate cancer (PCa). However, BS is still widely performed. Its diagnostic accuracy has been studied; however, its feasibility and cost implications are yet to be examined. Methods: We reviewed all patients with high risk PCa undergoing AS-MRI over a 5-year period. AS-MRI was performed on patients with histologically confirmed PCa and either PSA > 20 ng/ml, Gleason ≥8, or TNM Stage ≥T3 or N1 disease. All AS-MRI studies were obtained using a 1.5-T AchievaPhilips™MRI scanner. We compared the AS-MRI positivity and equivocal rate with that of BS. Data were analysed according to Gleason score, T-stage and PSA. Multivariate logistic regression analyses were used to quantify the strength of association between positive scans and clinical variables. Feasibility and burden of expenditure was also evaluated. Results: Five hundred three patients with a median age of 72 and a mean PSA of 34.8 ng/ml were analysed. Eighty-eight patients (17.5%) were positive for BM on AS-MRI (mean PSA 99 [95% CI 69.1–129.9]). Comparatively 409 patients (81.3%) were negative for BM on AS-MRI (mean PSA 24.7 (95% CI [21.7–27.7]) (p = 0.007); 1.2% (n = 6) of patients had equivocal results (mean PSA 33.4 [95% CI 10.5–56.3]). There was no significant difference in age (p = 0.122) between this group and patients with a positive scan, but there was a significant difference in PSA (p = 0.028), T stage (p = 0.006) and Gleason score (p = 0.023). In comparison with BS, AS-MRI detection rate was equivalent or higher compared with the literature. Based on NHS tariff calculations, there would be a minimum cost saving of £8406.89. All patients underwent AS-MRI within 14 days. Conclusion: The use of AS-MRI to stage BM in high-risk PCa is both feasible and results in a reduced burden of expenditure
Machine learning based microfluidic sensing device for viscosity measurements
No full textA microfluidic sensing device utilizing fluid–structure interactions and machine learning algorithms is demonstrated. The deflection of microsensors due to fluid flow within a microchannel is analysed using machine learning algorithms to calculate the viscosity of Newtonian and non-Newtonian fluids. Newtonian fluids (glycerol/water solutions) within a viscosity range of 5–100 cP were tested at flow rates of 15–105 mL h−1 (γ = 60.5–398.4 s−1 ) using a sample volume of 80–400 μL. The microsensor deflection data were used to train machine learning algorithms. Two different machine learning (ML) algorithms, support vector machine (SVM) and k-nearest neighbour (k-NN), were employed to determine the viscosity of unknown Newtonian fluids and whole blood samples. An average accuracy of 89.7% and 98.9% is achieved for viscosity measurement of unknown solutions using SVM and k-NN algorithms, respectively. The intelligent microfluidic viscometer presented here has the potential for automated, real-time viscosity measurements for rheological studies
New Technologies and Interventions to Improve the Mental Health of People with Diabetes
No full textThe present paper represents an initial research protocol for the development and evaluation of the Positive Psychology and Artificial Intelligence based Chatbot; Artificial Intelligence Diabetes Assistant—Mental Health (AIDA-MH) and an integrated mobile app designed to enhance mental health outcomes of people with diabetes. The rationale for the proposed research, planned methodology and analysis are discussed in this paper briefly. This proposed project will have quantitative and qualitative data and will be using pre and post intervention with randomized controlled trials, follow-ups and semi-structured interviews at the later stage. This paper is a proposed protocol for future evaluation, therefore, no data is reported and analysed at this stage. The findings and conclusions from this project will be a foundation ground for policy implementation in diabetes services, to integrate digital technology to improve mental health outcomes alongside diabetes outcomes
Twitter sentiment analysis and emotion detection using NLTK and TextBlob
No full textOn a worldwide level, every second around 6000 tweets are sent, which counts to around 200 billion tweets in a year. People share their ideas and views publicly on Twitter, thus it serves as a good platform for analyzing public trends and behaviour towards any person, product or news. Customers frequently utilize social media platforms to share their thoughts and experiences regarding goods and services. Businesses can find areas for improvement and better understand the attitudes of their customers towards their goods and services by using sentiment analysis. In order to perform sentiment analysis on twitter, text classification using Natural Language Processing(NLP) has been proved to be very helpful. Using NLP word tokenizer, we can divide the sentences into different sets of words, thereafter we remove the stop words. Manually tokenizing long tweets and categorizing them into separate groups is challenging. The primary goal of this model is to analyze the tweets related to a given keyword entered by the user, classify the tweets as positive, negative or neutral using (VADER sentiment analysis or alternately). TextBlob library, which will help consumers as well as manufacturers to understand people's overall opinion regarding the product. This study makes an attempt to suggest a text sentiment analysis on twitter data using the NLTK and TextBlob libraries
Junk mail content detection using logistic regression algorithm
No full textIn contemporary times, things have moved away from traditional method to sophisticated way of communication via social media. One of the common ways information is disseminated amongst people is in the use of emails.Emails are very effective, easy and less costly to use by the sender but invariably costly to the recipient. This is due to the effect unwarranted messages which are thrown in tons are being received daily. This paper focus is on developing an effective junk mail content detector to effectively detect the content of messages and properly classify them thereby eliminate spurious emails. Logistic regression and Random Forest algorithms were employed and the result showed thar our model Logistics regression proves a superior performance
Male sexual assault victims: a selective review of the literature and implications for support services
No full textIn recent years much has been done to publicize the plight of female rape victims. However, the sexual assault of adult males has received little attention in the research literature or by the public. This paper provides a selective review of the research into the prevalence and effects of male sexual assault victims. Research shows that the effects of sexual assault on adult males are often severe. This paper also outlines findings from experimental studies that have shown that reactions towards male sexual assault victims depend on both the victim’s sexual orientation and the perpetrator’s gender. Finally, implications for support services are outlined. Victims of both male and female perpetrators are considered, and both gay and heterosexual victims are discussed in relation to the specific needs of these victims. The needs of transgendered victims are also briefly considered, as are the needs of the sexual partners of male sexual assault victims. This paper concludes by offering some suggestions for future research
Electromagnetic wave absorption properties of ternary poly(vinylidene fluoride)/magnetite nanocomposites with carbon nanotubes and graphene
No full textTernary nanocomposite systems of poly(vinylidene fluoride)/magnetite/carbon nanotube (PVDF/Fe3O4/CNT) and poly(vinylidene fluoride)/magnetite/graphene (PVDF/Fe3O4/GN), were prepared using high shear twin screw compounding followed by compression moulding. The electromagnetic (EM) microwave absorption properties of the nanocomposites were investigated in the frequency range of 3–10 GHz. PVDF/Fe3O4/CNT samples with the thickness d = 0.7 mm present a minimum reflection loss (RL) of −28.8 dB at 5.6 GHz, while all the RL values in the measurement frequency range 3–10 GHz are lower than −10 dB. PVDF/Fe3O4/GN with a thickness of 0.9 mm, presents a minimum RL of −22.6 dB at 5.4 GHz, while all the RL values in the measurement frequency range 3–10 GHz are lower than −10 dB as well. The excellent microwave absorption properties of both nanocomposites, in terms of minimum RL value and broad absorption bandwidth, are mainly due to the enhanced magnetic losses. The results indicate that the ternary nanocomposites studied here, can be used as an attractive candidate for EM absorption materials in diverse fields of various technological applications, not only in the frequency range 3–10 GHz, but also at frequencies 10 GHz for PVDF/Fe3O4/GN with a realistic thickness of close to 1 mm
Direct flux control – sensorless control method of PMSM for all speeds – basics and constraints
No full textThe limitations of sensorless control of permanent magnet synchronous machines (PMSMs) are discussed and a viable solution is proposed. The main concept of sensorless control of drives relies on additional information given by the machine during its normal operation. This information provided by the machine is essentially the back-electro motive force and the variance of the stator inductivity, which are dependent on the rotor position. Several approaches and methods have discussed these problems, and in most cases they are not avoidable and that some methods work better on certain speeds of the drives. The direct flux control (DFC) method to combat the above problems at all speeds is presented. The flux linkage signal which contains the necessary information about the rotor position can be measured between the neutral point of a PMSM and an artificial one. The mathematical derivation and the observations from the experiments show that this signal contains a second and a fourth harmonic, which can be used to calculate the rotor position. Furthermore, the limitations of implementing DFC are also addressed