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Diversity in Computing
No full textThis edition of Sapienta leads with an article by Miles Berry, Professor of Computing Education at the University of Roehampton. Berry discusses the lack of diversity in computing and how it could be addressed, including schemes designed to increase the mix of students studying the subject, teaching approaches such as peer instruction, pair programming and storytelling, a focus on the relevance of computing, and consideration of potential career opportunities.He also notes the challenges of taking part in computing, with some students not being given the opportunity to take the subject, and perhaps, the lack of a broad qualification holding others back. Despite these and other issues, Berry says it is worth exploring role models and examples, and suggests former pupils and diverse individuals working locally in creative or tech related industries may provide inspiration and an understanding of the relevance of computing for all
Impact of Combined Prebiotic Galacto-Oligosaccharides and Bifidobacterium breve-Derived Postbiotic on Gut Microbiota and HbA1c in Prediabetic Adults: A Double-Blind, Randomized, Placebo-Controlled Study
No full textResearch‐informed counselling and psychotherapy: A training and accreditation agenda
No full textAbstractTraining and accreditation standards play a critical role in the development of a research‐informed agenda. This commentary on Barkham et al. (Counselling and Psychotherapy Research, 2024) discusses obstacles to fully integrating research into the training and standard agendas, and the potential role that the British Association for Counselling and Psychotherapy (BACP) can play in helping to overcome such obstacles. Knowledge of research evidence is currently limited in training and accreditation standards for counselling and psychotherapy, and course tutors are often not familiar—or engaged—with research findings. In the development of professional standards (for instance, within SCoPEd), the BACP should work to ensure that research competencies are comprehensive, contemporary and explained in a granular manner. Further helpful developments might include an annual research‐oriented conference for trainers and clinical supervisors, a journal dedicated to disseminating research and good practice in training and clinical supervision and/or a training/clinical supervision research network to coordinate activities in these area. BACP events—across all elements of the profession—should strive to address issues of research awareness and participation, and the use of research to inform practice. Critically, across all of these possibilities, BACP's Research Department, alone, cannot be left to support moves to a research‐informed profession. Rather, an organisation‐wide initiative is needed in which appreciation of the research evidence is at the heart of all aspects of the Association's work
Impossible visibilities of Black and Global Majority staff at an ethnically diverse English university
No full textContingent conversations build more than language: How communicative interactions in toddlerhood relate to preschool executive function skills
No full textWho Can Be the Monkey? The Use of a Novel Story-based Program Incorporating Music and Dance to Enhance Peer Acceptance and Inclusion for Young Autistic Pupils in Mainstream Schools
No full textAnticipating the Nearness of Coronary Heart Infection Utilizing Machine Learning Classifiers
No full textResearchers are putting in a lot of time and energy into developing methods to use machine learning algorithms, a subfield of AI, to diagnose disease in an individual patient. Extensive studies have been conducted on the potential benefits of using machine learning techniques in the treatment of cardiovascular disease. For this preliminary study, the study have zeroed down on heart illness to get as specific as possible about our methodology. In this paper, the authors investigate the differences in accuracy between different machine learning approaches specifically, (SVM), (KNN), and a(ANN) when applied to the categorization of cardiovascular illness. Our research makes use of approximately seventy thousand patient records from the Kaggle dataset, which focuses on cardiovascular disease The Kaggle dataset comprises a limited number of variables per patient record, encompassing serum cholesterol, diastolic and systolic blood pressure, relative blood glucose levels, and the presence or absence of angina. The present study examines the Kaggle dataset and employs the (KNN), (SVM), and (ANN) methodologies. The results indicate that the K-nearest neighbors (KNN) algorithm, specifically with a value of 9 for the number of neighbors, achieved an accuracy of 0.997. The SVM model using default hyperparameters achieved an accuracy of 0.9997. The Support Vector Machine (SVM) model utilizing a Radial Basis Function (RBF) kernel and a C value of 100.0 exhibited an accuracy of 0.9998. Conversely, the SVM model employing a linear kernel and a C value of 1000.0 achieved a perfect accuracy of 1.000. The Feedforward neural network achieved a perfect accuracy of 1.000 using the Adam optimization algorithm after 10 epochs and 50 batches.In future research, the authors intend to employ a deep neural network hypermodel in order to enhance the accuracy of their findings
The Magpies: Reflections on Liminality, Domestication, and Animal Agency
No full textAre domestication and justice compatible? This chapter utilizes reflections from the authors’ relationship with two magpies as a springboard for thinking about the wrongs of domestication. The chapter argues that reflection on liminal animals' agential capacities and powers shines a light on the structural injustice inherent to relationships between humans and domesticated animals. In short, the practices and processes of domestication inevitably expose animals to unnecessary risk of harm and unjustifiably curtail their abilities for self-determination. The chapter ends by considering and rejecting the claim that domesticated animals are better off than liminal animals since we can cater for their every nee
