Programming Education for Blind and Low Vision Users:Beyond Reading the Screen

Learning to program is often considered a difficult task, but this difficulty is multiplied for blind and low vision users, especially among young learners who may be learning about their assistive technologies (such as screen readers) alongside learning to program. In this position paper we argue that the entire paradigm of screenreading is a flawed way to construct an auditory interface for users with limited or no functional vision. We contend that block-like paradigms – despite historically being inaccessible – actually point towards a superior design where the abstract syntax tree is used to produce an auditory interface directly, rather than relying on reading out a plain-text rendering of the syntax tree. We believe that this can have benefits for learners and professionals alik

The Lived Experiences of Individuals with Type 2 Diabetes Mellitus with Poor Glycaemic Control in Nigeria:A Qualitative Study

Background:Many individuals living with type 2 diabetes mellitus (T2DM) struggle to maintain optimal glycaemic control. Reports from Nigeria show particularly high rates of poor glycaemic control, increasing the risk of microvascular and macrovascular complications. Little research has explored the lived experiences of individuals living with T2DM with poor glycaemic control in Nigeria, particularly in secondary healthcare settings, to guide improvements in care.Objective:This study explored the experiences of individuals living with T2DM with poor glycaemic control.Method:A qualitative research design was used. Semi-structured, individual interviews were conducted with 14 participants, aged 35 to 74 years, recruited from 3 secondary healthcare institutions in Lagos, Nigeria.Results:Four key themes were generated: (1) Beyond the T2DM diagnosis, which captures the perceptions of T2DM, the financial burden of the condition, and the onset of physical health issues associated with T2DM; (2) Psychological impact of T2DM, which highlights mental health difficulties and experiences of stigma; (3) Managing and living with T2DM, which describes the use of traditional medicine, the influence of religious beliefs and the importance of community and social networks and (4) Diabetes care at secondary healthcare institutions, which highlights patient-provider interactions and the gaps in information and education.Conclusion:The findings provide valuable insight into the lived experiences of individuals with T2DM with poor glycaemic control and underscore the importance of addressing knowledge gaps and providing psychological support as integral components of comprehensive diabetes care

Generalized hydrodynamics: A perspective

Conventional hydrodynamics describes systems with few long-lived excitations. In one dimension, however, many experimentally relevant systems feature a large number of long-lived excitations and conserved quantities even at high temperature, because they are proximate to integrable limits. Such models cannot be treated using conventional hydrodynamics. The framework of generalized hydrodynamics (GHD) was recently developed to treat the dynamics of one-dimensional models: It combines ideas from integrability, hydrodynamics, and kinetic theory to come up with a quantitative theory of transport. GHD has successfully settled several long-standing questions about one-dimensional transport; it has also been leveraged to study dynamical questions beyond the transport of conserved quantities and to systems that are not integrable. In this article, we introduce the main ideas and predictions of GHD, survey some of the most recent theoretical extensions and experimental tests of the GHD framework, and discuss some open questions in transport that the GHD perspective might elucidate.</p

The value of mental science:we publish what matters

Summary Recent changes to US research funding are having far-reaching consequences that imperil the integrity of science and the provision of care to vulnerable populations. Resisting these changes, the BJPsych Portfolio reaffirms its commitment to publishing mental science and advancing psychiatric knowledge that improves the mental health of one and all.</p

bpfCP:Efficient and extensible process checkpointing via eBPF

Live migration, snapshotting, and accelerated startup of applications or containers have long been implemented using checkpoint and restore primitives. To save or 'checkpoint', it is necessary to dump not only its userspace state, but also a large amount of state in the kernel. The current widely used implementation on Linux relies heavily on the /proc file system and special system call interfaces, but these suffer from poor performance and lack extensibility. In this paper, we propose bpfCP, a process checkpointing scheme that dumps in-kernel state via eBPF programs, which improves performance and extensibility. Our preliminary evaluation shows that bpfCP can achieve significant performance improvements in dumping multiple types of in-kernel state of processes

The Moral Gaze:A Pluralistic Analysis of the Impact of Social Judgement on Parents, Parenting and Access to Support, to Benefit Children and Families

This paper explores parents’ narratives about encountering moralized expectations of parenting. We contribute original and significant findings which identify moralized judgement as a determinant between concealing potential child maltreatment, and help-seeking to support child protection and welfare. We adopted a rigorous plural qualitative approach of interpretative phenomenological analysis and narrative analysis of N=24 parents in England, who had experienced parenting support from Children’s services. Participants revealed that moral judgements from their birth families and child’s school were particularly relevant. While fear of moral judgement deterred parents from open dialogue, feeling accepted and valued enabled greater self-efficacy and acceptance of support needs

Listening to Landscape:Hauntology and the Echoes of Albion

The first book-length exploration of how English landscapes are represented in contemporary electronic and experimental music, Listening to Landscape ploughs its own furrow, combining ideas from psychogeography, hauntology and landscape studies to offer a distinctive take on the way contemporary music deals with the ghosts of an England that is fast disappearing.Away from the Top 40, and often circulating in the form of obscure cassette releases and limited vinyl runs, acts including Belbury Poly, Craven Faults, epic45, Gilroy Mere, Spaceship, Vic Mars, Warrington-Runcorn New Town Development Plan - and many others besides - work in experimental genres including folktronica, ambient, modular synth, drone, post-rock and noise. But all have an apparent preoccupation with summoning the essence of place, often working with ideas of memory, loss and thwarted futurity associated with disappearing or threatened English landscapes.Moving deftly between cultural theory, musicology and geography, Listening to Landscape serves as a primer on the ‘hauntological’ music scene that appears fixated on questions of landscape and Englishness. It argues this music is no mere exercise in nostalgia, but a provocation asking us to re-imagine England’s place in the world at a time of economic and environmental crisis. Listening to Landscape speaks to urgent questions of national identity in the post-Brexit era, offering a distinctive take on the way contemporary culture deals with the ghosts and memories of Albion

Multi-Horizon Glucose Prediction Across Populations With Deep Domain Generalization

Real-time continuous glucose monitoring (CGM), augmented with accurate glucose prediction, offers an effective strategy for maintaining blood glucose levels within a therapeutically appropriate range. This is particularly crucial for individuals with type 1 diabetes (T1D) who require long-term self-management. However, with extensive glycemic variability, developing a prediction algorithm applicable across diverse populations remains a significant challenge. Leveraging meta-learning for domain generalization, we propose GPFormer, a Transformer-based zero-shot learning method designed for multi-horizon glucose prediction. We developed GPFormer on the REPLACE-BG dataset, comprising 226 participants with T1D, and proceeded to evaluate its performance using three external clinical datasets with CGM data. These included the OhioT1DM dataset, a publicly available dataset including 12 T1D participants, as well as two proprietary datasets. The first proprietary dataset included 22 participants, while the second contained 45 participants, encompassing a diverse group with T1D, type 2 diabetes, and those without diabetes, including patients admitted to hospitals. These four datasets include both outpatient and inpatient settings, various intervention strategies, and demographic variability, which effectively reflect real-world scenarios of CGM usage. When compared with a group of machine learning baseline methods, GPFormer consistently demonstrated superior performance and achieved the lowest root mean square error for all the evaluated datasets up to a prediction horizon of two hours. These experimental results highlight the effectiveness and generalizability of the proposed model across a variety of populations, demonstrating its substantial potential to enhance glucose management in a wide range of practical clinical settings.</p

Genome-wide association neural networks identify genes linked to family history of Alzheimer's disease

Augmenting traditional genome-wide association studies (GWAS) with advanced machine learning algorithms can allow the detection of novel signals in available cohorts. We introduce “genome-wide association neural networks (GWANN)” a novel approach that uses neural networks (NNs) to perform a gene-level association study with family history of Alzheimer’s disease (AD). In UK Biobank, we defined cases (n= 42 110) as those with AD or family history of AD and sampled an equal number of controls. The data was split into an 80:20 ratio of training and testing samples, and GWANN was trained on the former followed by identifying associated genes using its performance on the latter. Our method identified 18 genes to be associated with family history of AD. APOE, BIN1, SORL1, ADAM10, APH1B, and SPI1 have been identified by previous AD GWAS. Among the 12 new genes, PCDH9, NRG3, ROR1, LINGO2, SMYD3, and LRRC7 have been associated with neurofibrillary tangles or phosphorylated tau in previous studies. Furthermore, there is evidence for differential transcriptomic or proteomic expression between AD and healthy brains for 10 of the 12 new genes. A series of post hoc analyses resulted in a significantly enriched protein–protein interaction network (P-value &lt;1 × 10 −16), and enrichment of relevant disease and biological pathways such as focal adhesion (P-value = 1 × 10 −4), extracellular matrix organization (P-value = 1 × 10 −4), Hippo signaling (P-value = 7 × 10 −4), Alzheimer’s disease (P-value = 3 × 10 −4), and impaired cognition (P-value = 4 × 10 −3). Applying NNs for GWAS illustrates their potential to complement existing algorithms and methods and enable the discovery of new associations without the need to expand existing cohorts.</p