1,556 research outputs found

    The Epidemiology and Management of Kawasaki Disease in Australia

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    Kawasaki disease (KD) is a syndrome of systemic inflammation with the potential to cause life-threatening aneurysms of the coronary arteries. I sought to contribute to our understanding of this important condition, particularly with regard to Australian children. By determining the hospitalisation rate and IVIG-treatment rate I estimated the incidence of KD to be about 14 per 100,000 children under the age of 5 between 2007 and 2015. I also showed that the hospitalisation rate nationally had increased on average 3.5% annually between 1993 and 2018, with significant changes in the age distribution over that period. In collaboration with the Paediatric Active Enhanced Disease Surveillance (PAEDS) network, I undertook a large multicentre prospective surveillance study of KD in Australia. My analysis of that cohort confirmed several of the findings from the survey, such as the preference of Australian clinicians for low-dose aspirin from the time of diagnosis, and the considerable variability around how IVIG resistance is diagnosed and managed. Importantly, I observed that a significant subset of children diagnosed with, and treated for, KD do not meet the diagnostic criteria outlined in the 2017 statement by the American Heart Association. This work has contributed significantly to the understanding of KD’s epidemiology, management, and outcomes in Australia. I have shown that the incidence of the condition is increasing, and the clinical picture is changing. I identified important areas of practice variation and highlighted the need for international collaboration around agreed definitions (such as for IVIG resistance). Finally, I have played a central role in establishing an important resource for future resource: prospective surveillance of KD in Australia continues, with well over 700 cases recruited so far. It is hoped that this work will be of benefit to the researchers, clinicians, patients, and families affected by KD now, and into the future

    Comparison of different methods for shaping amorphous solid dispersions

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    On Linear Equivalence, Canonical Forms, and Digital Signatures

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    The LESS signature scheme, introduced in 2020, represents a fresh research direction to obtain practical code-based signatures. LESS is based on the linear equivalence problem for codes, and the scheme is entirely described using matrices, which define both the codes, and the maps between them. It makes sense then, that the performance of the scheme depends on how efficiently such objects can be represented. In this work, we investigate canonical forms for matrices, and how these can be used to obtain very compact signatures. We present a new notion of equivalence for codes, and prove that it reduces to linear equivalence; this means there is no security loss when applying canonical forms to LESS. Additionally, we flesh out a potential application of canonical forms to cryptanalysis, and conclude that this does not improve on existing attacks, for the regime of interest. Finally, we analyze the impact of our technique, showing that it yields a drastic reduction in signature size when compared to the LESS submission, resulting in the smallest sizes for code-based signature schemes based on zero-knowledge

    Three-dimensional printing as a cutting-edge, versatile and personalizable vascular stent manufacturing procedure:Toward tailor-made medical devices

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    Vascular stents (VS) have revolutionized the treatment of cardiovascular diseases, as evidenced by the fact that the implantation of VS in coronary artery disease (CAD) patients has become a routine, easily approachable surgical intervention for the treatment of stenosed blood vessels. Despite the evolution of VS throughout the years, more efficient approaches are still required to address the medical and scientific challenges, especially when it comes to peripheral artery disease (PAD). In this regard, three-dimensional (3D) printing is envisaged as a promising alternative to upgrade VS by optimizing the shape, dimensions and stent backbone (crucial for optimal mechanical properties), making them customizable for each patient and each stenosed lesion. Moreover, the combination of 3D printing with other methods could also upgrade the final device. This review focuses on the most recent studies using 3D printing techniques to produce VS, both by itself and in combination with other techniques. The final aim is to provide an overview of the possibilities and limitations of 3D printing in the manufacturing of VS. Furthermore, the current situation of CAD and PAD pathologies is also addressed, thus highlighting the main weaknesses of the already existing VS and identifying research gaps, possible market niches and future directions.This work was funded by the Basque Country Government/Eusko Jaurlaritza (Department of Education, University and Research, Consolidated Groups IT448- 22) . Sandra Ruiz-Alonso and Fouad Al -Hakim thank the Basque Country Government for the granted fellowships PRE_2021_2_0153 and PRE_2021_2_0181, respectively. Denis Scaini gratefully acknowledges support from IKERBASQUE, the Basque Foundation of Science

    Ditransitives in germanic languages. Synchronic and diachronic aspects

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    This volume brings together twelve empirical studies on ditransitive constructions in Germanic languages and their varieties, past and present. Specifically, the volume includes contributions on a wide variety of Germanic languages, including English, Dutch, and German, but also Danish, Swedish, and Norwegian, as well as lesser-studied ones such as Faroese. While the first part of the volume focuses on diachronic aspects, the second part showcases a variety of synchronic aspects relating to ditransitive patterns. Methodologically, the volume covers both experimental and corpus-based studies. Questions addressed by the papers in the volume are, among others, issues like the cross-linguistic pervasiveness and cognitive reality of factors involved in the choice between different ditransitive constructions, or differences and similarities in the diachronic development of ditransitives. The volume’s broad scope and comparative perspective offers comprehensive insights into well-known phenomena and furthers our understanding of variation across languages of the same family

    Exploring annotations for deductive verification

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    Efficient Algorithms for Minimizing Compositions of Convex Functions and Random Functions and Its Applications in Network Revenue Management

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    In this paper, we study a class of nonconvex stochastic optimization in the form of minxXF(x):=Eξ[f(ϕ(x,ξ))]\min_{x\in\mathcal{X}} F(x):=\mathbb{E}_\xi [f(\phi(x,\xi))], where the objective function FF is a composition of a convex function ff and a random function ϕ\phi. Leveraging an (implicit) convex reformulation via a variable transformation u=E[ϕ(x,ξ)]u=\mathbb{E}[\phi(x,\xi)], we develop stochastic gradient-based algorithms and establish their sample and gradient complexities for achieving an ϵ\epsilon-global optimal solution. Interestingly, our proposed Mirror Stochastic Gradient (MSG) method operates only in the original xx-space using gradient estimators of the original nonconvex objective FF and achieves O~(ϵ2)\tilde{\mathcal{O}}(\epsilon^{-2}) sample and gradient complexities, which matches the lower bounds for solving stochastic convex optimization problems. Under booking limits control, we formulate the air-cargo network revenue management (NRM) problem with random two-dimensional capacity, random consumption, and routing flexibility as a special case of the stochastic nonconvex optimization, where the random function ϕ(x,ξ)=xξ\phi(x,\xi)=x\wedge\xi, i.e., the random demand ξ\xi truncates the booking limit decision xx. Extensive numerical experiments demonstrate the superior performance of our proposed MSG algorithm for booking limit control with higher revenue and lower computation cost than state-of-the-art bid-price-based control policies, especially when the variance of random capacity is large. KEYWORDS: stochastic nonconvex optimization, hidden convexity, air-cargo network revenue management, gradient-based algorithm
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