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Online social connections and internet use among people with intellectual disabilities in the United Kingdom during the COVID-19 pandemic
Get PDFHaving a disability, in particular, an intellectual disability, is associated with Internet non-use. This article explores how people with intellectual disabilities used the Internet across the United Kingdom during the COVID-19 pandemic. In April to May 2021, 571 adults with intellectual disabilities were interviewed. Participants most commonly used the Internet for being with family and friends, social media or doing online activities with other people. People who lived with family were the most likely to use social media; people who lived with other people with intellectual disabilities were the least likely. People who self-reported as not lonely were more likely to use the Internet for online activities with others and play video games with others. Social connections were identified as the best thing about the Internet. Many participants chose not to identify a worst thing about Internet use, while others reported issues with technology, online harm and threats to well-being
Exploring the role of HE teachers as change agents in the reconstruction of post-conflict Syria
Get PDFThis article explores Syrian higher education (HE) teachers’ perceptions of their role as change agents in the reconstruction of post-conflict Syria. It utilises the notions of ‘change agent’ and ‘strategic competence’ (previously developed in relation to academics by Idahosa and Vincent) for exploring HE teachers’ capacity to contribute to the post-conflict reconstruction of Syria. This article is based on a small-scale, qualitative study using in-depth interviews to explore the experiences and perspectives of HE teachers who have been working at a conflict-affected university for the duration of the conflict. The study concludes that HE teachers may be considered change agents in post-conflict societies, but that the challenges these teachers face must be taken into account, as must considerations of how the institution and the HE system can facilitate teachers in their change-making remit
Challenging behaviour and its correlates in preschool-aged children with an intellectual disability in Saudi Arabia
Get PDFBackground: Young children with an intellectual disability have a higher risk of developing challenging behaviour (CB). Early identification of risk factors for CB allows for earlier intervention. The aim of the current study was to assess the prevalence and correlates of CB in preschool-aged children with an intellectual disability in Riyadh (Saudi Arabia).
Methods: One hundred twenty parents of preschool-aged (3-6 years old) children who had been diagnosed (DSM-5 criteria) with an intellectual disability completed an online cross-sectional survey that included demographic, CB, and child adaptive skills measures. The relationship between CB and 15 potential correlates (e.g. gender and degree of disability) was examined using independent samples t-tests and chi-squared tests.
Results: Most preschool-aged (3-6 years old) children with an intellectual disability exhibited CB (78.8%, 95% CI [70.3, 85.8]), with a 63.2% prevalence rate for self-injurious behaviours (95% C [53.8, 72.0]), a 57.6% rate for aggressive destructive behaviours (95% CI [48.2, 66.7]) and a 25% rate for stereotypy (95% CI [17.7, 34.0]). The likelihood of a child engaging in self-injurious and stereotyped behaviours was higher in those with autism and intellectual disability. Children with Down syndrome displayed fewer stereotyped behaviours. Low adaptive skill levels were associated with increased overall CB, self-injurious, and stereotyped behaviours.
Conclusions: The identified correlates of CB in this population and cultural context align with the international evidence base. Findings have implications for the importance of early systematic screening of CB in preschool-aged children in Saudi Arabia and other similar contexts. Preventative measures are suggested for preschool-aged children with an intellectual disability who are more likely to demonstrate CB, such as those with autism and poor adaptive behaviours
VocabStudy : a remote collection of naturalistic topic-structured parental speech and toddlers' vocabularies using a mobile phone application
No full textThe current work presents VocabStudy, a collection of natural language samples and children's vocabularies collected remotely by parents via a mobile phone application. The corpus contains 567,003 word tokens and represents 144 hours of speech over a period of six months from the language environment of 63 British toddlers aged 13 to 28 months. The corpus incorporates labeled speech samples of five typical routines: mealtime, bedtime, playtime, bathtime, and nappytime (i.e., diaper). To explore consistency and variability across these five linguistic contexts, topic modeling was employed. The topic most successfully detected as having a unique structure was mealtime, which was identified as such nearly 100% of the time; bathtime, nappytime, and bedtime were found to cluster together most of the time, suggesting that they have a similar language structure; playtime was correctly identified as such about 14% of the time. To validate the accuracy of parents marking the words that their child produced, the child's utterances found in the audio recordings were examined. About 18% of the vocabulary reported by parents appeared in the transcripts, and the reported vocabulary sizes were highly correlated with the number of unique words uttered by the children (ρ = .72, p < 001). The results suggest that most parents marked the words soon after their children start producing them (p < .001, d = 0.9). I discuss the advantages and disadvantages of using a mobile phone application as a method to collect children's data remotely, what worked to keep participants entering data, and what could have been done to avoid some issues encountered
Find the river : discovering the Tsangpo-Brahmaputra in the age of empire
Get PDFDespite the enormous size and economic and scientific significance of the Tsangpo-Brahmaputra River, questions of where and what it was generated successive waves of dispute from the mid-eighteenth to early twentieth centuries. Geographical discovery in the eastern Himalayan borderlands neither entailed the application of fixed theories and techniques, nor resulted from consistent flows of information along established channels. Europeans instead understood the region’s rivers in many different ways, influenced by sporadic deluges of data, competing forms of expertise, shifting imperatives of colonial political economy, unsettling encounters with various bodies of water, and heterogeneous Asian knowledge structures. Informants, infrastructures, and cosmologies of often-overlooked communities at imperial margins fundamentally reshaped European knowledge. Under these conditions, practitioners of spatial sciences came to thrive on the proliferation of models and objects of discovery rather than seeking definitive closure
Forecasting global climate drivers using Gaussian processes and convolutional autoencoders
Get PDFMachine learning (ML) methods have become an important tool for modelling and forecasting complex high-dimensional spatiotemporal datasets such as those found in environmental and climate modelling applications. ML approaches can offer a fast, low-cost alternative to short-term forecasting than expensive numerical simulation while addressing a significant outstanding limitation of numerical modelling by being able to robustly and dynamically quantify predictive uncertainty. Low-cost and near-instantaneous forecasting of high-level climate variables has clear applications in early warning systems, nowcasting, and parameterising small-scale locally relevant simulations. This paper presents a novel approach for multi-task spatiotemporal regression by combining data-driven autoencoders with Gaussian Processes (GP) to produce a probabilistic tensor-based regression model. The proposed method is demonstrated for forecasting one-step-ahead temperature and pressure on a global scale simultaneously. By conducting probabilistic regression in the learned latent space, samples can be propagated back to the original feature space to produce uncertainty estimates at a vastly reduced computational cost. The composite GP-autoencoder model was able to simultaneously forecast global temperature and pressure values with average errors of 3.82 °C and 638 hPa, respectively. Further, on average the true values were within the proposed posterior distribution 95.6% of the time illustrating that the model produces a well-calibrated predictive posterior distribution
Quantitative rates of convergence to equilibrium for the degenerate linear Boltzmann equation on the Torus
Get PDFWe study the linear relaxation Boltzmann equation on the torus with a spatially varying jump rate which can be zero on large sections of the domain. In \cite{BS13} Bernard and Salvarani showed that this equation converges exponentially fast to equilibrium if and only if the jump rate satisfies the geometric control condition of Bardos, Lebeau and Rauch \cite{BLR91}. In \cite{HL15} Han-Kwan and Léautaud showed a more general result for linear Boltzmann equations under the action of potentials in different geometric contexts, including the case of unbounded velocities. In this paper we obtain quantitative rates of convergence to equilibrium when the geometric control condition is satisfied, using a probabilistic approach based on Doeblin's theorem from Markov chains
Learning a neuron by a shallow ReLU network : dynamics and implicit bias for correlated inputs
Get PDFWe prove that, for the fundamental regression task of learning a single neuron, training a one-hidden layer ReLU network of any width by gradient flow from a small initialisation converges to zero loss and is implicitly biased to minimise the rank of network parameters. By assuming that the training points are correlated with the teacher neuron, we complement previous work that considered orthogonal datasets. Our results are based on a detailed non-asymptotic analysis of the dynamics of each hidden neuron throughout the training. We also show and characterise a surprising distinction in this setting between interpolator networks of minimal rank and those of minimal Euclidean norm. Finally we perform a range of numerical experiments, which corroborate our theoretical findings
Personalized chronomodulated 5-fluorouracil treatment : a physiologically based pharmacokinetic precision dosing approach for optimizing cancer therapy
No full textThe discovery of circadian clock genes greatly amplified the study of diurnal variations impacting cancer therapy, transforming it into a rapidly growing field of research. Especially, use of chronomodulated treatment with 5-fluorouracil (5-FU) has gained significance. Studies indicate high interindividual variability (IIV) in diurnal variations in dihydropyrimidine dehydrogenase (DPD) activity – a key enzyme for 5-FU metabolism. However, the influence of individual DPD chronotypes on chronomodulated therapy remains unclear and warrants further investigation. To optimize precision dosing of chronomodulated 5-FU, this study aims to: (i) build physiologically-based pharmacokinetic (PBPK) models for 5-FU, uracil, and their metabolites, (ii) assess the impact of diurnal variation on DPD activity, (iii) estimate individual DPD chronotypes, and (iv) personalize chronomodulated 5-FU infusion rates based on a patient's DPD chronotype. Whole-body PBPK models were developed with PK-Sim(R) and MoBi(R). Sinusoidal functions were used to incorporate variations in enzyme activity and chronomodulated infusion rates as well as to estimate individual DPD chronotypes from DPYD mRNA expression or DPD enzymatic activity. Four whole-body PBPK models for 5-FU, uracil, and their metabolites were established utilizing data from 41 5-FU and 10 publicly available uracil studies. IIV in DPD chronotypes was assessed and personalized chronomodulated administrations were developed to achieve (i) comparable 5-FU peak plasma concentrations, (ii) comparable 5-FU exposure, and (iii) constant 5-FU plasma levels via “noise cancellation” chronomodulated infusion. The developed PBPK models capture the extent of diurnal variations in DPD activity and can help investigate individualized chronomodulated 5-FU therapy through testing alternative personalized dosing strategies