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Sentiment computation of UK-originated COVID-19 vaccine tweets: a chronological analysis and news effect
No full textThis study aimed to analyse public sentiments of UK-originated tweets related to COVID-19 vaccines, and it applied six chronological time periods, between January and December 2021. The dates were related to six BBC news reports about the most significant developments in the three main vaccines that were being administered in the UK at the time: Pfizer-BioNTech, Moderna, and Oxford-AstraZeneca. Each time period spanned seven days, starting from the day of the news report. The study employed the bidirectional encoder representations from transformers (BERT) model to analyse the sentiments in 4172 extracted tweets. The BERT model adopts the transformer architecture and uses masked language and next sentence prediction models. The results showed that the overall sentiments for all three vaccines were negative across all six periods, with Moderna having the least negative tweets and the highest percentage of positive tweets overall while AstraZeneca attracted the most negative tweets. However, for all the considered time periods, Period 3 (23–29 May 2021) received the least negative and the most positive tweets, following the related BBC report—’COVID: Pfizer and AstraZeneca jabs work against Indian variant’—despite reports of blood clots associated with AstraZeneca during the same time period. Time periods 5 and 6 had no breaking news related to COVID vaccines, and they reflected no significant changes. We, therefore, concluded that the BBC news reports on COVID vaccines significantly impacted public sentiments regarding the COVID-19 vaccines
The impact of atmospheric plasma/UV laser treatment on the chemical and physical properties of cotton and polyester fabrics
No full textAtmospheric plasma treatment can modify fabric surfaces without affecting their bulk properties. One recently developed, novel variant combines both plasma and UV laser energy sources as a means of energising fibre surfaces. Using this system, the two most commonly used fibres, cotton and polyester, have been studied to assess how respective fabric surfaces were influenced by plasma power dosage, atmosphere composition and the effects of the presence or absence of UV laser (308 nm XeCl) energy. Plasma/UV exposures caused physical and chemical changes on both fabric surfaces, which were characterised using a number of techniques including scanning electron microscopy (SEM), radical scavenging (using 2,2-diphenyl-1-picrylhydrazyl (DPPH)), thermal analysis (TGA/DTG, DSC and DMA), electron paramagnetic resonance (EPR) and X-ray photoelectron spectroscopy (XPS). Other properties studied included wettability and dye uptake. Intermediate radical formation, influenced by plasma power and presence or absence of UV, was key in determining surface changes, especially in the presence of low concentrations of oxygen or carbon dioxide (20%) mixed with either nitrogen or argon. Increased dyeability with methylene blue indicated the formation of carboxyl groups in both exposed cotton and polyester fabrics. In the case of polyester, thermal analysis suggested increased cross-linking had occurred under all conditions
Thinking with My Hands: Embodied Cognition in Practice
No full textThe act of reflection is often considered to be one of the conscious mind – a cognitive act reflecting on one’s lived experience. By adopting principles of reflection defined by Donald Schön in 1983 as reflection-in and reflection-on action, this positioning paper attempts to develop a new methodology for examining and reinterpreting the embodied nature of material reflective thinking. The practice discussed responds to and reinterprets walking acts through methods of stitching-in and stitching-on action. The stitched mark acts as a line that considers concepts of wandering minds, wandering bodies and embodied cognition (Candy Citation2020). Correlations of mind and body wandering through physical and metaphorical space will be drawn on and considered in the context of material thinking and tacit and haptic knowledge. Schön (Citation1983:73) asks the question, ‘In practice of various kinds, what form does reflection-in-action take?’, through this paper I intend to explore what critical-reflective-creative-thinking looks like in a textile practice and examine how the moment of making (stitching/walking) offers opportunities for critical-reflective-creative-thinking with practice
The transition of industry practitioners new to higher education: examining personal and institutional factors in the professional development and practice of new academics
No full textUK universities have responded to government, employer and student demand for teaching and degree programmes which will improve academic and employability outcomes for learners. One of the tactics used in the UK higher education sector has been the recruitment of industry practitioners into universities. Whilst such appointments can provide the desired expertise and credibility for teaching programmes and departments, research suggests that such career changes can provide challenges for both the new academic and the employing institution.The thesis aims to (1) investigate the development of the identity of early-career academics who embark on their new career in academia from well-established business professional environments. It also aims to explore (2) how professional practitioners from industry negotiate their expectations about their new roles and how they respond to perceived tensions and contradictions in formal institutional policies, structures, and procedures and in less formal collegial support environments. The research questions focused on identifying (1) what motivated the professional practitioners to join the academia; (2) how they perceived the transition to their newly developing/acquired identity and (3) how formal institutional procedures, policies, and structures, including (4) (less formal) communities of practice shaped, strengthened and/or hindered the process of this transition to a new professional identity formation of the early-career academics.The research adopted a singular case study approach. It was conducted at a management school in a post’92 UK university with participants who were early-career lecturers with different levels of industry experience. To generate data, a multi-method research strategy was chosen, consisting of questionnaires (N = 8) and semi-structured interviews (N = 10). The research design is predominantly qualitative, based on an interpretivist research paradigm.Activity Theory was used as a tool for understanding and interpreting the contextual and situational complexities, which new academics encounter in their new work context. Activity System was used as a critical site for observing the construction of cultural environments, which can facilitate norms, values and knowledge, which in turn influence the development and practice of those participating within the Activity System (Trowler and Knight, 2000).Additionally, the study used Perry’s (2012) Auditioning Academic concept as a reference point for critical comparison with the new findings and for their refinement in relation to the professional transition of new academics entering higher education from industry.The research identified key motivating factors that attract professionals to enter academia: the expectation of having a better and more satisfactory work-life balance; an opportunity to be stimulated and challenged intellectually in the subject they enjoyed; and finally, the expectation of exercising professional autonomy. The initial engagement and socialisation of the new academics within a clear departmental culture and stable working environment primarily served to shape the professional identity as that of a “teacher”, however; the professional identity of the new academics was perceived as a fluid one with the potential for change in the future. The research findings also point to the strong role of formal and informal institutional structures and communities of practice as playing a pivotal role in the development of new academics’ professional confidence and identity. Ultimately, the study offers new conceptual interpretations of existing theoretical work in the area of professional transition for new academics coming from industry
Remote monitoring system using slow-fast deep convolution neural network model for identifying anti-social activities in surveillance applications
No full textRemote monitoring is the process that monitors and observes information from a distance utilizing sensors or electronic types of equipment. Remote monitoring is used in real-time applications like traffic, forest, military, shops, and hospitals to determine abnormal activities. Earlier research has done video processing methods based on computer vision techniques, but the computational complexity regarding time and memory is high. This paper designs and implements a novel Slow-Fast Convolution Neural Network (SF–CNN) to identify, detect, and classify abnormal behaviours from a surveillance video. The proposed CNN architecture learns the video frames automatically, obtains the most appropriate properties about various objects' behaviour from a large set of videos. The learning process of SF-CNN is carried out in two ways, such as slow learning and fast learning. The slow learning process is enabled when the frame rate is less, and the rapid learning process is enabled when the frame rate is high. Both the learning processes learn spatial and temporal information from the input video. Different objects, such as humans, vehicles, and animals, are detected and recognized according to their actions. All the videos have normal and abnormal activities that vary in various contexts. The proposed SF-CNN architecture provides an end-to-end solution to dealing with multiple constraints abnormal movements. The experiment is carried out on several benchmark datasets, and the performance of the SF-CNN architecture is evaluated. The proposed approach obtained 99.6% of accuracy, which is higher than the other existing techniques
Collaborative Writing as Bio-Digital Quilting: A Relational, Feminist Practice Towards "Academia Otherwise"
No full textIn this article, we explore how quilted poetry as methodology, through the practice of collaborative writing, can help us to attune to and think with what is un/seen, un/heard, and un/spoken in our bio-digital ways of working, as a way of resisting normative, exploitative practices in the neoliberal academia. We are a group of academics with different journeys and localities, connected by a common interest in the effects of boundaries, the dynamics of power, and the desire to do things differently. Drawing on our daily mundane encounters with/in both virtual and physical spaces of academia, including Teams meetings, Outlook emails, Google documents, and Miro board collaborations, we write quilted poetry with fragments of precarious matter: silences, messages, rhythms, feelings, and materialities. We attend to the entanglement of our bodies and their enmeshment in technology and share how bringing relational, feminist theories and the bio-digital together has helped us to both materialise new patterns of relations and enact a more ethical approach to working in academia
TILPDeep a lightweight deep learning technique for handwritten transformed invariant Pashto text recognition
No full textPashto is the native language of Afghanistan and one of Pakistan's most essential and regional languages. The Pashto language has a vast number of native speakers who live in various parts of the world. The handwritten Pashto textual trajectories are hard to recognize and detect due to the cursive style and handwriting variation. The transformation behaviour, i.e., scaling, rotation, and shifting of handwritten text, are the prominent but challenging factors. A lightweight deep learning-based model construction for low and medium-resource devices in a less-constrained environment is challenging. This paper provides a practical, light deep learning-based model for predicting handwritten Pashto words. A massive Pashto-transformed invariant inverted handwritten text dataset is prepared with the help of the Pashtun community. A lightweight MobileNetV2 has been highly tuned for Pashto handwritten text classification, extracting images' features (MoI). We inverted the dataset to make the model more accurate and restrict it to fifteen epochs. Extensive experiments have been conducted to validate the suggested model's performance. The proposed transformed invariant lightweight Pashto deep learning (TILPDeep) technique achieves a training accuracy of 0.9839 and a validation accuracy of 0.9405 for transformed invariant Pashto handwritten inverted text using recognition matrices
Voices and bodies as navigators and educators
No full textStarting with the axiom that embodied knowledge is the only mode of knowledge we possess, this essay argues that courage is a key virtue for artistic and philosophical research. It is rare for our cultural institutions to recognize or reward this virtue. The exploration of our somatic relations to ideas has largely been side-lined as a ‘merely subjective’ pursuit. The most obviously embodied arts such as dance and song are generally presumed to have (at best) a trivial relationship to knowledge. I argue that these arts provide a vast network of under-explored roads to knowledge due to their proximity to the pre-conditions for being alive at all. Breathing, vocalizing and moving are essential to thought and knowledge. The emergent field of performance philosophy explores how rigorous and repeatable experiments in somatic thinking are possible and desirable