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Understanding financial institutions – The role of reading economic news in Germany and the UK
Get PDFThis chapter argues that the news media play an important factor in educating the public about financial institutions. It presents some novel survey results, exploring the role of economic news use for the perceived understanding of financial institutions in Germany and the UK. Two web-based surveys were conducted: one in the UK in winter 2018 and one in Germany in summer 2019. Findings show that economic news use is positively related with a better perceived understanding of financial institutions in both countries, even after controlling for demographics and financial socialization. We find that the level of perceived understanding of financial institutions is positively related with education and income and negatively related with being female. The need for information significantly impacted the relationship between economic news use and understanding of financial institutions in the UK but not in Germany. Practical implications for economic and financial news journalists are discussed
From architecture to community [Workshop]
No full textThe workshop 'From Architecture to Community', hosted by Camden Kilburn Library and produced for the London Festival of Architecture, gives voice to anyone interested in creating and shaping the future of community spaces. How do we imagine the future of the disused Kingsgate Community centre? Facilitated by students and tutors from Middlesex University|Interiors, the workshop is open to everyone. The workshop outcomes will contribute to the ongoing work within the research project Kilburn Lab
Demand for external finance by environmentally-motivated SMEs: An exploration of geographical disparities and potential in relation to Net Zero
No full textUsing UK Longitudinal Small Business Survey (LSBS) 2017-2021 annual data waves and geographical and digital accessibility indices, the paper investigates how regional disparities and peripheral location impact on the use and demand for external funding by green UK SMEs and social enterprises (SEs). Green SMEs are defined by the LSBS as those that declare having environmental goals as their sole or primary business objective, and those that have green objectives but prioritise profit-making. Social enterprises have social or ethical goals, generate income from trading activities, and use resultant profits to further those goals. Although the paper focuses on geographical disparities, it also examines whether the rise of digital finance and FinTech has changed how SMEs obtain external finance. The relationship between green external financing and SME skills and capabilities, future business intentions, industrial sectors and other business environment characteristics, such as urban versus rural location, local deprivation index, is also analysed
Malignant Mesothelioma subtyping via sampling driven multiple instance prediction on tissue image and cell morphology data
Get PDFMalignant Mesothelioma is a difficult to diagnose and highly lethal cancer usually associated with asbestos exposure. It can be broadly classified into three subtypes: Epithelioid, Sarcomatoid, and a hybrid Biphasic subtype in which significant components of both of the previous subtypes are present. Early diagnosis and identification of the subtype informs treatment and can help improve patient outcome. However, the subtyping of malignant mesothelioma, and specifically the recognition of transitional features from routine histology slides has a high level of inter-observer variability. In this work, we propose an end-to-end multiple instance learning (MIL) approach for malignant mesothelioma subtyping. This uses an adaptive instance-based sampling scheme for training deep convolutional neural networks on bags of image patches that allows learning on a wider range of relevant instances compared to max or top-N based MIL approaches. We also investigate augmenting the instance representation to include aggregate cellular morphology features from cell segmentation. The proposed MIL approach enables identification of malignant mesothelial subtypes of specific tissue regions. From this a continuous characterisation of a sample according to predominance of sarcomatoid vs epithelioid regions is possible, thus avoiding the arbitrary and highly subjective categorisation by currently used subtypes. Instance scoring also enables studying tumor heterogeneity and identifying patterns associated with different subtypes. We have evaluated the proposed method on a dataset of 234 tissue micro-array cores with an AUROC of 0.89±0.05 for this task. The dataset and developed methodology is available for the community at: https://github.com/measty/PINS
Concurrent carbon capture and biocementation through the carbonic anhydrase (CA) activity of microorganisms ‑ a review and outlook
Get PDFBiocementation, i.e., the production of biomimetic cement through the metabolic activity of microorganisms, offers exciting new prospects for various civil and environmental engineering applications. This paper presents a systematic literature review on a biocementation pathway, which uses the carbonic anhydrase (CA) activity of microorganisms that sequester CO2 to produce biocement. The aim is the future development of this technique for civil and (geo-)environmental engineering applications towards CO2-neutral or negative processes. After screening 248 potentially relevant peer-reviewed journal papers published between 2002 and 2023, 38 publications studying CA-biocementation were considered in the review. Some of these studies used pure CA enzyme rather than bacteria-produced CA. Of these studies, 7 used biocementation for self-healing concrete, 6 for CO2 sequestration, 10 for geotechnical applications, and 15 for (geo-)environmental applications. A total of 34 bacterial strains were studied, and optimal conditions for their growth and enzymatic activity were identified. The review concluded that the topic is little researched; more studies are required both in the laboratory and field (particularly long-term field experiments, which are totally lacking). No studies on the numerical modelling of CA-biocementation and the required kinetic parameters were found. The paper thus consulted the more widely researched field of CO2 sequestration using the CA-pathway, to identify other microorganisms recommended for further research and reaction kinetic parameters for numerical modelling. Finally, challenges to be addressed and future research needs were discussed
A comparative analysis of the skilled use of automated feedback tools through the lens of teacher feedback literacy
Get PDFEffective learning depends on effective feedback, which in turn requires a set of skills, dispositions and practices on the part of both students and teachers which have been termed feedback literacy. A previously published teacher feedback literacy competency framework has identified what is needed by teachers to implement feedback well. While this framework refers in broad terms to the potential uses of educational technologies, it does not examine in detail the new possibilities of automated feedback (AF) tools, especially those that are open by offering varying degrees of transparency and control to teachers. Using analytics and artificial intelligence, open AF tools permit automated processing and feedback with a speed, precision and scale that exceeds that of humans. This raises important questions about how human and machine feedback can be combined optimally and what is now required of teachers to use such tools skillfully. The paper addresses two research questions: Which teacher feedback competencies are necessary for the skilled use of open AF tools? and What does the skilled use of open AF tools add to our conceptions of teacher feedback competencies? We conduct an analysis of published evidence concerning teachers’ use of open AF tools through the lens of teacher feedback literacy, which produces summary matrices revealing relative strengths and weaknesses in the literature, and the relevance of the feedback literacy framework. We conclude firstly, that when used effectively, open AF tools exercise a range of teacher feedback competencies. The paper thus offers a detailed account of the nature of teachers’ feedback literacy practices within this context. Secondly, this analysis reveals gaps in the literature, signalling opportunities for future work. Thirdly, we propose several examples of automated feedback literacy, that is, distinctive teacher competencies linked to the skilled use of open AF tools
Evaluating student evaluations: evidence of gender bias against women in higher education based on perceived learning and instructor personality
Get PDFGiven student evaluations are an integral part of academic employment and progression in higher education, it is crucial to explore various biases amongst students that may influence their ratings. Several studies report a clear gender bias in student evaluation where male instructors receive significantly higher ratings as compared to female instructors. However, there is very limited research about gender biases in underrepresented samples such as South Asia and the Middle East. We examined whether perception of male and female instructors differed in terms of how they facilitate learning and level of engagement, using an experimental design. Six hundred and seventy-one university students were asked to watch a video of an online lecture on psychology, delivered by either a male or female lecturer, after which they were asked to evaluate their experience and instructor personality characteristics. To ensure consistency across content, tone, delivery, environment, and overall appearance, photorealistic 3D avatars were used to deliver the lectures. Only gender as a factor was manipulated. Given the racial representation in the region, a total of four videos were developed representing males (n = 317) and females (n = 354) of White and South Asian race. Overall, male instructors scored significantly higher in variables representing personality characteristics such as enthusiasm and expressiveness compared to female instructors. Participants did not however view male and female instructors to be different in terms of presentation and subject knowledge. Findings related to facilitating learning suggest that male instructors were perceived to have made instructions more interesting, kept participants' attention for longer, and were more interesting compared to female instructors. In terms of engagement, male instructors were perceived to be more expressive, enthusiastic, and entertaining, compared to female instructors. Given the experimental design, these findings can clearly be attributed to gender bias, which is also in line with previous research. With an underrepresented sample, an online platform delivery, and inclusion of multiple races, these findings significantly add value to the current literature regarding gender stereotypes in higher education. The results are even more concerning as they provide strong evidence of gender bias which may contribute to subconscious discrimination against women academics in the region
MesoGraph: automatic profiling of mesothelioma subtypes from histological images
Get PDFMesothelioma is classified into three histological subtypes, epithelioid, sarcomatoid, and biphasic, according to the relative proportions of epithelioid and sarcomatoid tumor cells present. Current guidelines recommend that the sarcomatoid component of each mesothelioma is quantified, as a higher percentage of sarcomatoid pattern in biphasic mesothelioma shows poorer prognosis. In this work, we develop a dual-task graph neural network (GNN) architecture with ranking loss to learn a model capable of scoring regions of tissue down to cellular resolution. This allows quantitative profiling of a tumor sample according to the aggregate sarcomatoid association score. Tissue is represented by a cell graph with both cell-level morphological and regional features. We use an external multicentric test set from Mesobank, on which we demonstrate the predictive performance of our model. We additionally validate our model predictions through an analysis of the typical morphological features of cells according to their predicted score
Strength and conditioning practices of Brazilian Olympic sprint and jump coaches
Get PDFOlympic coaches are likely to have adequate knowledge and implement effective training programs. This study aimed to describe and critically examine the strength and conditioning practices adopted by Brazilian Olympic sprint and jump coaches. Nineteen Olympic coaches (age: 50.2 ± 10.8 years; professional experience: 25.9 ± 13.1 years) completed a survey consisting of eight sections: 1) background information; 2) strength-power development; 3) speed training; 4) plyometrics; 5) flexibility training; 6) physical testing; 7) technology use; and 8) programming. It was noticed that coaches prioritized the development of explosiveness, power, and sprinting speed in their training programs, given the specific requirements of sprint and jump events. Nevertheless, unexpectedly, we observed: (1) large variations in the number of repetitions performed per set during resistance training in the off-season period, (2) a higher volume of resistance training prescribed during the competitive period (compared to other sports), and (3) infrequent use of traditional periodization models. These findings are probably related to the complex characteristics of modern competitive sports (e.g., congested competitive schedule) and the individual needs of sprinters and jumpers. Identification of training practices commonly used by leading track and field coaches may help practitioners and sport scientists create more effective research projects and training programs
Machine-learning-based software to group heterogeneous students for online peer assessment activities
Get PDFSince the academic year 2017/2018, a peer assessment activity was included in the online Genomics laboratory for the master’s degree course in Biological Sciences of the University of Camerino, with the aim of improving learning outcomes and soft skills in students, such as team building and critical thinking. Creating groups in university courses is not easy because of the large number of students, that leads teachers to realize groups totally randomly, a procedure that is not always effective. One of the factors that influences the success of collaborative learning is the creation of heterogeneous groups based on the students’ behaviors. Despite little improvements, the online genomics laboratory highlighted some gaps. Random groups didn’t ensure that each group was composed of heterogeneous students, and it leads some students to have a bad perception of the peer review activity, negatively affecting their engagement and motivation. This work proposes a new Machine Learning Approach and the realization of a specific software, able to create effective heterogeneous groups to be involved in the online peer assessment process, in order to improve learning outcomes and satisfaction in the students. The aim is to check the improvement of the peer assessment effectiveness using heterogeneous groups compared to random groups of students. Two editions of the online laboratory of Genomics were analysed, examining the students’ results and perceptions to verify the impact of the Machine Learning approach designed in this work