From the horse’s mouth : oral assessment in Journalism education

Viva voces and practical oral assessments have been a recognised method of student assessment, in widely diverse academic fields for decades and perhaps even longer (Huxham et al., 2012). However, such assessment methods have not, hitherto, been utilised in London Metropolitan University’s Journalism education programme. This is, perhaps, somewhat surprising given that journalism is, by its very nature, a professional discipline that employs a variety of sensory modalities - extended through technological media - to achieve its effects and impact. This article will examine why this variety seems not to be reflected in the assessment regimes of associated journalism education programmes and will also raise the following questions: is this simply a preference that may need to be challenged, and, more provocatively, does it therefore suggest a lack of desire amongst Journalism educators to innovate? For the purpose of this paper, I will be examining the Journalism School in London Metropolitan University and, more specifically, the undergraduate programme of that school

Are You There, Robert Downey Jr.? It’s Me, Your Biographer: Mainstreaming entertainment journalism across literary genres

This project is a commentary accompanying three of my published books – two unauthorised celebrity biographies about movie star Robert Downey Jr. and TV scientist Professor Brian Cox and a textbook about entertainment journalism. Using these three texts, this piece of work explores how my background as a showbusiness journalist informs both their execution and my wider writing practice. It examines how entertainment journalism is currently perceived by the public and why it should be given sufficient weight in terms of its adherence to Galtung and Ruge’s (1965) and Harcup and O’Neill’s (2001) taxonomies of news values and its impact on society. Looking at theorists across celebrity culture, journalism and linguistics, alongside various practitioners, it will explore how the construction of unauthorised celebrity biography responds to myth-making and narrative theory and how that feeds into my academic writing. Then, utilising different methodologies including persona, narrative, showbusiness journalism tropes and the teaching of so-called soft skills required by modern employers, as well as considering the goal of media textbooks, it will demonstrate how I have used my style of writing to create ‘tribridity’ within the textbook form by introducing celebrity journalism into the format, alongside memoir and how that is reflected in my teaching practice

ADAPTIVE FLIGHT AND ECHOLOCATION BEHAVIOR IN BATS

Bats use sonar to identify and localize objects as they fly and navigate in the dark. They actively adjust the timing, intensity, and frequency content of their sonar signals in response to task demands. They also control the directional characteristics of their sonar vocalizations with respect to objects in the environment. Bats demonstrate highly maneuverable and agile flight, producing high turn rates and abrupt changes in speed, as they travel through the air to capture insects and avoid obstacles. Bats face the challenge of coordinating flight kinematics with sonar behavior, as they adapt to meet the varied demands of their environment. This thesis includes three studies, one on the comparison of flight and echolocation behavior between an open space and a complex environment, one on the coordination of flight and echolocation behavior during climbing and turning, and one on the flight kinematic changes that occur under wind gust conditions. In the first study, we found that bats adapt the structure of the sonar signals, temporal patterning, and flight speed in response to a change in their environment. We also found that flight stereotypy developed over time in the more complex environment, but not to the extent expected from previous studies of non-foraging bats. We found that the sonar beam aim of the bats predicted flight turn rate, and that the relationship changed as the bats reacted to the obstacles. In the second study, we characterized the coordination of flight and sonar behavior as bats made a steep climb and sharp turns while they navigated a net obstacle. We found the coordinated production of sonar pulses with the wingbeat phase became altered during navigation of tight turns. In the third study, we found that bats adapt wing kinematics to perform under wind gust conditions. By characterizing flight and sonar behaviors in an insectivorous bat species, we find evidence for tight coordination of sensory and motor systems for obstacle navigation and insect capture. Through these studies, we learn about the mechanisms by which mammals and other organisms process sensory information to adapt their behaviors

Evaluation of the Clinical, Technical, and Financial Aspects of Cost-Effectiveness Analysis of Artificial Intelligence in Medicine: Scoping Review and Framework of Analysis

Background: Cost-effectiveness analysis of artificial intelligence (AI) in medicine demands consideration of clinical, technical, and economic aspects to generate impactful research of a novel and highly versatile technology. Objective: We aimed to systematically scope existing literature on the cost-effectiveness of AI and to extract and summarize clinical, technical, and economic dimensions required for a comprehensive assessment. Methods: A scoping literature review was conducted to map medical, technical, and economic aspects considered in studies on the cost-effectiveness of medical AI. Based on these, a framework for health policy analysis was developed. Results: Among 4820 eligible studies, 13 met the inclusion criteria for our review. Internal medicine and emergency medicine were the clinical disciplines most frequently analyzed. Most of the studies included were from the United States (5/13, 39%), assessed solutions requiring market access (9/13, 69%), and proposed optimization of direct resources as the most frequent value proposition (7/13, 53%). On the other hand, technical aspects were not uniformly disclosed in the studies we analyzed. A minority of articles explicitly stated the payment mechanism assumed (5/13, 38%), while it remained unspecified in the majority (8/13, 62%) of studies. Conclusions: Current studies on the cost-effectiveness of AI do not allow to determine if the investigated AI solutions are clinically, technically, and economically viable. Further research and improved reporting on these dimensions seem relevant to recommend and assess potential use cases for this technology

Impact of Noisy Labels on Dental Deep Learning—Calculus Detection on Bitewing Radiographs

Supervised deep learning requires labelled data. On medical images, data is often labelled inconsistently (e.g., too large) with varying accuracies. We aimed to assess the impact of such label noise on dental calculus detection on bitewing radiographs. On 2584 bitewings calculus was accurately labeled using bounding boxes (BBs) and artificially increased and decreased stepwise, resulting in 30 consistently and 9 inconsistently noisy datasets. An object detection network (YOLOv5) was trained on each dataset and evaluated on noisy and accurate test data. Training on accurately labeled data yielded an mAP50: 0.77 (SD: 0.01). When trained on consistently too small BBs model performance significantly decreased on accurate and noisy test data. Model performance trained on consistently too large BBs decreased immediately on accurate test data (e.g., 200% BBs: mAP50: 0.24; SD: 0.05; p < 0.05), but only after drastically increasing BBs on noisy test data (e.g., 70,000%: mAP50: 0.75; SD: 0.01; p < 0.05). Models trained on inconsistent BB sizes showed a significant decrease of performance when deviating 20% or more from the original when tested on noisy data (mAP50: 0.74; SD: 0.02; p < 0.05), or 30% or more when tested on accurate data (mAP50: 0.76; SD: 0.01; p < 0.05). In conclusion, accurate predictions need accurate labeled data in the training process. Testing on noisy data may disguise the effects of noisy training data. Researchers should be aware of the relevance of accurately annotated data, especially when testing model performances

QCD Sum Rules for Masses of Excited Heavy Mesons

The masses of excited heavy mesons are studied with sum rules in the heavy quark effective theory. A set of interpolating currents creating (annihilating) excited heavy mesons with arbitrary spin and parity are proposed and their properties are discussed. Numerical results at the leading order of the {\cal O}(1/m_Q) expansion are obtained for the lowest doublets (0^+, 1^+) and (1^+, 2^+).Comment: LateX, 12 pages including 2 fig

How Do Rights Become Real?: Formal and Informal Institutions in South Africa's Land Reform

Summary Central components of South Africa's post?apartheid land reform comprise ambitious and wide?ranging ‘rights?based’ laws and programmes. But how do legally defined rights to resources become effective command over those resources? And what are the limits to social change through legal reform? Two central issues which arise are: supplementing the passing of new legislation with the detailed design of programmes to implement these laws, and the interplay of formal and informal institutions in the complex social arenas within which people actually live. Both centrally involve issues of power, authority and contestation, and require us to consider law as only one source of rule?making in society. The environmental entitlements framework helps us to explore these questions

Algorithm Engineering in Robust Optimization

Robust optimization is a young and emerging field of research having received a considerable increase of interest over the last decade. In this paper, we argue that the the algorithm engineering methodology fits very well to the field of robust optimization and yields a rewarding new perspective on both the current state of research and open research directions. To this end we go through the algorithm engineering cycle of design and analysis of concepts, development and implementation of algorithms, and theoretical and experimental evaluation. We show that many ideas of algorithm engineering have already been applied in publications on robust optimization. Most work on robust optimization is devoted to analysis of the concepts and the development of algorithms, some papers deal with the evaluation of a particular concept in case studies, and work on comparison of concepts just starts. What is still a drawback in many papers on robustness is the missing link to include the results of the experiments again in the design