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Higher autism trait severity in children associates with diminished integration of angry prosody in semantic processing.
No full text“You Will Do Well”: But How, Exactly? A Curious Ending to the Apostolic Letter of Acts 15
Get PDFIn this paper, I focus on the puzzling ending of the apostolic letter in Acts 15 in which the ad-dressees are told that if they hold to four “essential” prohibitions, they will “do well” (εὖ πράξετε, v. 29). The question as to how, exactly, can destabilise some understandings of the decree, with alternative translations creating different problems, and particularly so where theological com-mitments are at play. Following Danker’s call for greater attention to this phrase, I undertake a fresh, stratified survey of Greek usage across corpora ranging from the arguably less to the more proximate and bring this into dialogue with the senses given in various literary and social ap-proaches to the decree involving epistolary rhetoric, reciprocity theory, and intertextuality. This reveals how purely linguistic data can stand in tension with compositional arguments in different ways and require a more complex arbitration between possibility, likelihood and coherence when both lexical and discourse-level constraints are applied. Whilst not solving the problem of the decree outright, observing the impacts of different readings of εὖ πράξετε on the delicate balances involved presses some oblique but productive questions into the interpretive task
Cognitive reserve predicts episodic memory enhancement induced by transcranial direct current stimulation in healthy older adults
No full textEpisodic memory shows the largest degree of age-related decline. Anodal transcranial Direct CurrentStimulation (tDCS) can enhance episodic memory in aging but there is also evidence of response variability even when using identical stimulation parameters. To explore which inter-individual factors (i.e. age, education, encoding performance, cognitive reserve, tDCS group and timing of tDCSapplication) may directly and/or indirectly modulate verbal memory recall, we used data from our previous tDCS studies that showed enhanced episodic memory recall in 80 healthy older adults. In these studies we used the same paradigm and stimulation parameters but tDCS was applied during different memory stages. Memory recall was tested 48 hours and 30 days after encoding. Univariate regression models showed that tDCS group (Anodal vs. Sham) predicted memory recall, indicating higher scores in the Anodal group than in the Sham group. Encoding performance predicted memory recall in both tDCS groups. Multiple regression models revealed that cognitive reserve, measured with a life experience questionnaire, predicted memory recall only for the Anodal group. Higher cognitive reserve was linked to better memory recall. Accounting for individual differences in cognitive reserve at baseline helps to explain tDCS responsiveness. This knowledge may contribute to optimize its use in older adults
Aging, Nostalgia and Older Punk Women’s Fandom.
No full textDespite their continued engagement as audience throughout their lives, there is some suggestion that ageing, or older, fans have been at large omitted from fan studies (Middlemost, 2022). This does seem to be shifting, however, and there is a growing body of fandom scholarship concerning ageing fans. Indeed, in the context of punk, there has been a growing recognition of the continued significance of punk to older participants and fans (e.g. Andes, 2002, Bennett, 2006, Davis, 2006), contrasting earlier work which theorized punk as a youth subculture (see, for example, Hebdige, 1998). This reflects the increasing academic interest in the ageing popular music audience more broadly (Bennett and Hodkinson 2012). Despite such positive shifts, ageing women continue to be marginalised in such discussions concerning punk and older fans, meaning that much theoretical and conceptual understandings of ageing punks have failed to fully consider the interaction between ageing, gender and fandom
A Systematic Review of Model-Driven Game Development Studies
Get PDF© 2024, [IEEE]. This is an author produced version of a paper published in IEEE Transactions on Games uploaded in accordance with the publisher’s self- archiving policy. The final published version (version of record) is available online at the link. Some minor differences between this version and the final published version may remain. We suggest you refer to the final published version should you wish to cite from it. Model-driven game development (MDGD) leverages the concept of model-driven engineering and game development. The focus of MDGD is to automate the game development process by emphasizing a higher level of abstraction, which will make game development faster and easier. In recent years, researchers in the MDGD community have developed several approaches in this domain. The goal of this paper is to survey and classify existing works in MDGD, identify the challenges in this domain, and provide promising future research directions. To achieve this, we conducted a systematic review by selecting 43 articles from a set of 849. The results show that MDE techniques are used to develop games in various genres. 42% of the investigated studies proposed a graphical concrete syntax for game specification and 56% of them used different target environment tools such as Unity Engine. Moreover, our suggestions include taking advantage of tooling environments and focusing on game components rather than a complete game
Who gets an annual review for coeliac disease?:Patients with lower health literacy and lower dietary adherence consider them important
No full textThe governance, leadership and management of complementary schools: the case of Greek Cypriot schools in England
No full textThe article explores the governance, leadership and management of complementary schools through the case of Greek Cypriot complementary schools in England with a view to developing a research agenda for this under-researched yet significant sector of education for children and young people. Drawing on stakeholder and bottom-up theories of governance that aim to uncover the intricate networks of groups that surround organisations and the systems in which they exist, we highlight the multiple and sometimes conflicting stakes held. This exploratory research involves interviews with five practitioners in positions of responsibility. The governance, leadership and management of these schools matters because there are concerns about their sustainability requiring a greater appreciation of their contribution, the issues they face and how they make decisions with limited resources. We call for further research to increase the understanding of the sector and to improve the support for practitioners, organisations and communities
“We weren't listened to”: Practitioners views of navigating challenges and opportunities in special education settings through COVID‐19
No full textAbstractWith the increase of special schools in UK and around the world, this study seeked to explore in‐depth the reality of practitioners working with children with SEND in specialist settings throughout the COVID‐19 pandemic. Utilising semi‐structured interviews with 11 special school teachers and leaders, this study found that professionals working in specialist settings experienced parental conflict, challenges related to personal life and working arrangements during this time, and highlighted concerns and opportunities for the future and sustainability of the SEND system. The professionals highlighted some essential components needed to support the development of meaningful careers and the reduction of attrition in the sector such as an increase in pay and greater appreciation of the role. This study has implications for policy and practice in a time of uncertainty pre‐election and during national crises such as high teacher turnover coupled with low teacher recruitment
Optimising air quality prediction in smart cities with hybrid particle swarm optimization‐long‐short term memory‐recurrent neural network model
Get PDFIn smart cities, air pollution is a critical issue that affects individual health and harms the environment. The air pollution prediction can supply important information to all relevant parties to take appropriate initiatives. Air quality prediction is a hot area of research. The existing research encounters several challenges that is, poor accuracy and incorrect real‐time updates. This research presents a hybrid model based on long‐short term memory (LSTM), recurrent neural network (RNN), and Curiosity‐based Motivation method. The proposed model extracts a feature set from the training dataset using an RNN layer and achieves sequencing learning by applying an LSTM layer. Also, to deal with the overfitting issues in LSTM, the proposed model utilises a dropout strategy. In the proposed model, input and recurrent connections can be dropped from activation and weight updates using the dropout regularisation approach, and it utilises a Curiosity‐based Motivation model to construct a novel motivational model, which helps in the reconstruction of long short‐term memory recurrent neural network. To minimise the prediction error, particle swarm optimisation is implemented to optimise the LSTM neural network's weights. The authors utilise an online Air Pollution Monitoring dataset from Salt Lake City, USA with five air quality indicators for comparison, that is, SO2, CO, O3, and NO2, to predict air quality. The proposed model is compared with existing Gradient Boosted Tree Regression, Existing LSTM, and Support Vector Machine based Regression Model. Experimental analysis shows that the proposed method has 0.0184 (Root Mean Square Error (RMSE)), 0.0082 (Mean Absolute Error), 2002*109 (Mean Absolute Percentage Error), and 0.122 (R2‐Score). The experimental findings demonstrate that the proposed LSTM model had RMSE performance in the prescribed dataset and statistically significant superior outcomes compared to existing methods
Precise Mechanical Oscillator Design and Calibration for Characterising Sub-Millimetre Movements in mmWave Radar Systems
No full textFor many industrial and medical applications, measuring sub-millimetre movements has become crucial, for instance, for the precise guidance of surgical robots. The literature shows the feasibility of millimetre-wave (mmWave) radars to deal with such micro-vibrations. However, the availability of reference devices to configure and test these systems is very limited. This work proposes the design of a mechanical oscillator to characterise sub-millimetre vibration detection and measurement using a mmWave radar. The final implementation is fully controllable in both amplitude and frequency. Additionally, it can be wirelessly controlled and synchronised with other systems. Its functioning was experimentally calibrated and tested using the sub-millimetre motion capture system OptiTrack. It was tested to generate low-frequency oscillations from 0.80 Hz to 3.50 Hz with reliable peak amplitudes of 0.05 mm and above, with less than 6% peak amplitude relative error. Finally, the device was used to characterise a 60 GHz mmWave radar with those values