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Periodic limb movements in sleep in patients using antidepressants
No full textDepression and periodic limb movement disease are both common disorders which frequently co-exist. Furthermore, antidepressants are known to cause and worsen periodic limb movements in sleep, which can worsen the quality of sleep and subsequently daytime symptoms. However, the effect of antidepressants on periodic limb movements is not uniform and depends on their mechanism of action. In this review we summarise the knowledge on the mechanism of periodic limb movements in sleep, and how changes in the concentration of neurotransmitters can contribute to them. We comprehensively evaluate the literature on antidepressants induced periodic limb movement in sleep. Based on this, we suggest clinical implications and further focus on research.</p
Outcomes following anti-TNF originator to biosimilar switching in children and young people with Juvenile Idiopathic Arthritis (JIA)
No full textObjectives: For cost-saving, children and young people with JIA are being switched (non-medical) from biologic originators to biosimilars. This analysis investigates what happens to those who switch from an anti-TNF originator to biosimilar, regarding drug survival and disease activity, compared with a matched-cohort who remain on originator.Methods: Includes all patients in the UK JIA Biologics Register (cohort study) switching directly from an anti-TNF originator to biosimilar of the same product. All patients were matched (age, gender, disease duration, calendar-year, line of therapy, ILAR) to patients receiving originator. For those matched successfully, Cox-proportional hazard models assessed whether drug persistence differed between those who switched versus those remaining on originator. Change in JADAS-71, and proportion worsening (by ≥1.7units), after six-months was compared between cohorts. This analysis was designed to address a priority research area set by our patient-partners.Results: 224 patients switched from originator to biosimilar; 143(63%) adalimumab, 56(25%) etanercept, 25(11%) infliximab. Of these, 164 patients were matched successfully to those remaining on originator. There was no evidence that patients switching were more likely to stop treatment compared with those remaining on originator: hazard ratio 1.44 (95%CI:0.91-2.26). Of the 50 biosimilar patients who stopped treatment, 18 switched-back to the originator (14 in year one), 27 started a different biologic, and five remained off treatment at last follow-up. Of the 87 matched-patients with available disease activity, there was no evidence that JADAS-71 worsened more after six-months: odds ratio 0.71 (95%CI:0.34-1.52).Conclusions: In this large matched comparative effectiveness analysis, many children and young people with JIA have switched from originators to biosimilars. Disease activity remained similar between patients switching versus those remaining on originator. Three-in-four were still receiving their biosimilar after one year, with switching back to originator uncommon, 9% after one year, suggesting good tolerability of non-medical switching in this patient population.<br/
Abstract Kleisli Structures on 2-categories*
No full textFührmann introduced Abstract Kleisli structures to model call-by-value programming languages with side effects, and showed that they correspond to monads satisfying a certain equalising condition on the unit. We first extend this theory to non-strict morphisms of monads, and to incorporate 2-cells of monads. We then further extend this to a theory of abstract Kleisli structures on 2-categories,characterising when the original pseudomonad can be recovered by the abstract Kleisli structure on its 2-category of free-pseudoalgebras
Sectoral coupling pathway towards a 100 % renewable energy system for Northern Ireland
No full textNorthern Ireland, in alignment with the United Kingdom's net zero targets for 2050, is focusing on a transition to a 100 % renewable energy system. Wind energy is the backbone of this future system due to its abundant resource potential, low environmental impact, and cost-effectiveness. However, achieving a fully variable renewable energy system requires flexibility on the demand side to reliably facilitate the displacement of traditional dispatchable power plants with variable renewable resources such as wind and solar. To address this challenge, this study aims to develop optimal pathways for transitioning Northern Ireland's current energy system to 100 % renewable energy. The proposed model outlines eight pathway steps that reflect technical and operational changes needed on both the supply and demand sides. These steps include: 1) building a reference model, 2) implementing a district heating system, 3) deploying electric heat pumps, 4) reducing reliance on dispatchable power plants, 5) integrating electric vehicles, 6) incorporating demand-side management, 7) producing methanol for buses and trucks, and 8) replacing remaining fossil fuels with synthetic gas. Each step is evaluated using EnergyPLAN, which considers both technical and economic viability alongside the increased penetration of wind and solar power. The findings illustrate that Northern Ireland can transition to a 100 % renewable energy system at a cost comparable to its current system, providing a practical and cost-effective pathway to meet its 2050 target. By analysing the impact of each step individually, this study provides valuable insights for policymakers on effectively decarbonising Northern Ireland's entire energy system
Spousal characteristics and unmet care needs: A longitudinal national study of adults aged 50 and over in England
No full textThis paper investigates unmet needs among dyads of people aged 50 and over in England. Understanding the extent and patterns of unmet needs for long-term care across different social groups is critical for understanding care-related experiences and inequalities and planning the long-term care system. Although spouses are a main source of care support, little is known about how spouses' characteristics relate to one's experience of unmet care needs. This study adopts a dyadic perspective, investigating the association between unmet care needs and spouses' characteristics, including socioeconomic status, health status and the quality of spousal relationships. Drawing on data from the English Longitudinal Study of Ageing (ELSA) (N = 3439), we matched the information of individuals who have care needs to the characteristics of their spouses and used random effects modelling to account for the longitudinal nature of the data. The results show that having a spouse with poorer functional abilities was associated with a higher risk of experiencing objective and subjective unmet needs. Men were more likely to experience objective unmet care needs if their spouses engaged in paid work, but this is not the case for women. Women faced a lower risk of subjective and objective unmet needs when having a closer relationship with their spouse, whereas this pattern was not observed among men. The findings highlight the importance of considering the interpersonal care relationships and gendered dynamics of caregiving, providing insights into designing gender-sensitive intervention programmes to better support people in care needs and their families.</p
Dynamic Intelligence Assessment:Benchmarking LLMs on the Road to AGI with a Focus on Model Confidence
Get PDFAs machine intelligence evolves, the need to test and compare the problem-solving abilities of different AI models grows. However, current benchmarks are often simplistic, allowing models to perform uniformly well and making it difficult to distinguish their capabilities. Additionally, benchmarks typically rely on static question-answer pairs that the models might memorize or guess. To address these limitations, we introduce Dynamic Intelligence Assessment (DIA), a novel methodology for testing AI models using dynamic question templates and improved metrics across multiple disciplines such as mathematics, cryptography, cybersecurity, and computer science. The accompanying dataset, DIA-Bench, contains a diverse collection of challenge templates with mutable parameters presented in various formats, including text, PDFs, compiled binaries, visual puzzles, and CTF-style cybersecurity challenges. Our framework introduces four new metrics to assess a model's reliability and confidence across multiple attempts. These metrics revealed that even simple questions are frequently answered incorrectly when posed in varying forms, highlighting significant gaps in models' reliability. Notably, API models like GPT-4o often overestimated their mathematical capabilities, while ChatGPT-4o demonstrated better performance due to effective tool usage. In self-assessment, OpenAI's o1-mini proved to have the best judgement on what tasks it should attempt to solve. We evaluated 25 state-of-the-art LLMs using DIA-Bench, showing that current models struggle with complex tasks and often display unexpectedly low confidence, even with simpler questions. The DIA framework sets a new standard for assessing not only problem-solving but also a model's adaptive intelligence and ability to assess its limitations. The dataset is publicly available on the project's page: https://github.com/DIA-Bench
Acid washing-assisted synthesis of porous Co3O4 nanosheet catalyst featuring efficient benzene oxidation performance
No full textCo-based catalysts exhibit considerable catalytic activity in oxidative reactions, yet challenges remain in synthesizing Co 3O 4 materials featuring both large surface area and high activity. Here, ultrathin La 0.029CoO x nanosheets were post-treated with various concentrations of dilute nitric acid to obtain the two-dimensionally geometric Co 3O 4-H nanosheets catalysts. Among them, the resultant Co 3O 4-0.1H catalyst disclosed significantly enhanced catalytic activity, enabling to achieve 100 % conversion of benzene at 230 °C under an ultrahigh weight hourly space velocity (WHSV) of 60,000 mL·g −1·h −1. Additionally, the catalyst also displayed excellent catalytic durability and well catalytic stability over 5 cyclic tests and 45 h of long-period operation. A thorough characterization results revealed that the superior catalytic performance of Co 3O 4-0.1H was attributed to its distinct nanosheet morphology, high specific surface area and abundant surface defect sites. This work highlights the effectiveness and simplicity of acid washing treatment strategy in improving the catalytic oxidation activity of transition metal oxide catalysts.</p
Advancing Paleontology: A Survey on Deep Learning Methodologies in Fossil Image Analysis
No full textUnderstanding ancient organisms and their paleo-environments through the study of body fossils represents a central tenet of paleontology. Advances in digital image capture over the past several decades now allow for efficient and accurate documentation, curation and interrogation of fossil anatomy over disparate length scales. Despite these developments, key body fossil image processing and analysis tasks, such as segmentation and classification still require significant user intervention, which can be labor-intensive and subject to human bias. Recent advancements in deep learning offer the potential to automate fossil image analysis while improving throughput and limiting operator bias. Despite the recent emergence of deep learning within paleontology, challenges such as the scarcity of diverse, high quality image datasets and the complexity of fossil morphology necessitate further advancements and the adoption of concepts from other scientific domains. Here, we comprehensively review state-of-the-art deep learning-based methodologies applied towards body fossil analysis while grouping the studies based on the fossil type and nature of the task. Furthermore, we analyze existing literature to tabulate dataset information, neural network architecture type, key results, and comprehensive textual summaries. Finally, based on the collective limitations of the existing studies, we discuss novel techniques for fossil data augmentation and fossil image enhancements, which can be combined with advanced neural network architectures, such as diffusion models, generative hybrid networks, transformers, and graph neural networks, to improve body fossil image analysis.<br/
Fathers' experiences of perinatal death following miscarriage, stillbirth, and neonatal death:A meta-ethnography
No full textFollowing a perinatal death, parents can experience mental health difficulties and social stigma around the loss that can lead to increased feelings of isolation. This meta-synthesis aimed to explore partners' experiences of perinatal death following miscarriage, stillbirth and neonatal death. A search of six electronic databases resulted in the inclusion of 18 studies involving over 300 fathers. Using meta-ethnography five themes: were developed 1) The pain with loss, 2) state of shock, 3) suffering in silence, 4) disconnection from the self and others' and 5) coping. A lack of support available from services or familial support networks led to isolation. Coping strategies fostering open communication often allowed fathers to process the death of their baby, and many spoke positively of their ongoing connection with their baby that died. However, consequences of unhealthy coping mechanisms, including avoidance or blame, resulted in the father's disconnection from the self, others or the world.</p