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ESSD–ESGAR best practice position statements on the technical performance of videofluoroscopic swallowing studies in adult patients with swallowing disorders

Objectives: Videofluoroscopic swallowing studies (VFSS) remain the gold standard for the instrumental assessment of oropharyngeal swallowing disorders alongside flexible endoscopic evaluation of swallowing (FEES), requiring a high standard of quality and correct implementation. The current best practice position statements aim to guide the clinical practice of VFSS in individuals experiencing swal

Virtual imaging trials in medicine : A brief takeaway of the lessons from the first international summit

Background: The rapid advancement of medical technologies presents significant challenges for researchers and practitioners. While traditional clinical trials remain the gold standard, they are often limited by high costs, lengthy durations, and ethical constraints. In contrast, in-silico trials and digital twins have emerged not only as efficient and ethical alternatives but also as a complementa

International Society on Thrombosis and Haemostasis Clinical Practice Guideline for Treatment of Congenital Haemophilia—A Critical Appraisal

Introduction: Evidence-based clinical practice guidelines drive optimal patient care and facilitate access to high-quality treatment. Creating guidelines for rare diseases such as haemophilia, where evidence does not often come from randomized controlled trials but from non-randomized and well-designed observational studies and real-world data, is challenging. The methodology used for assessing av

Convergence of the Dirichlet–Neumann method for semilinear elliptic equations

The Dirichlet–Neumann method is a common domain decomposition method for nonoverlapping domain decomposition and the method has been studied extensively for linear elliptic equations. However, for nonlinear elliptic equations, there are only convergence results for some specific cases in one spatial dimension. The aim of this manuscript is therefore to prove that the Dirichlet–Neumann method conve

Geostatistical Interpolation Approach for Improving Flood Simulation Within a Data-Scarce Region in the Tibetan Plateau

The complex orography of the Tibetan plateau (TP) and the scarcity and uneven spatial distribution of meteorological stations present significant challenges in accurately estimating meteorological variables for hydrological simulations. This study aims to enhance the accuracy of daily precipitation and temperature interpolation for hydrological simulations in the Lhasa River Basin (LRB), particula

Living Dangerously : Archaeological Insights Into Jomon Engagement With Volcanic Geohazards In Prehistoric Japan

Mount Fuji, the iconic mountain of Japan, remains a young and frequently active volcano. However, despite these dangers, people have continuously lived in the landscapes surrounding Mount Fuji since the peopling of the Japanese Archipelago, approximately 38ka. In this paper we explore the geological history of Mount Fuji and use a landscape archaeology approach to reconstruct how Jomon communities

Transferring spectroscopic stellar labels to 217 million Gaia DR3 XP stars with SHBoost

With Gaia Data Release 3 (DR3), new and improved astrometric, photometric, and spectroscopic measurements for 1.8 billion stars have become available. Alongside this wealth of new data, however, there are challenges in finding efficient and accurate computational methods for their analysis. In this paper, we explore the feasibility of using machine learning regression as a method of extracting bas

Towards drop-in sustainable aviation fuels in aero engine combustors : Fuel effects on combustion performance

The application of sustainable aviation fuels (SAFs) in aviation industry has emerged as a key strategy for reducing the net carbon oxide (CO2) emissions while minimizing modifications to the current aircraft and engine systems. SAFs, which are derived from sustainable feedstocks through biological, thermal and chemical (or their combinations) conversion pathways, can be used in current aero engin

Improving adversarial robustness of traffic sign image recognition networks

The robustness of deep neural networks is an increasingly essential issue as they become more and more prevalent in several real-world applications like autonomous vehicles. If traffic signs turn to adversarial examples, an autonomous vehicle will probably be misled and cause fatal accidents. To improve adversarial robustness, a new cost function for training convolutional neural recognition netwo

All-Cause and Cause-Specific Mortality in Tourette Syndrome and Chronic Tic Disorder

Background: Tourette syndrome (TS) and chronic tic disorder (CTD) may be associated with an increased risk of mortality, but specific causes of death are poorly understood. Objectives: In this matched cohort and sibling cohort study, we estimated the risk of all-cause and cause-specific mortality in individuals with TS/CTD, compared with unaffected matched individuals and unaffected full siblings.

Improving transferability of generated universal adversarial perturbations for image classification and segmentation

Although deep neural networks (DNNs) are high-performance methods for various complex tasks, e.g., environment perception in automated vehicles (AVs), they are vulnerable to adversarial perturbations. Recent works have proven the existence of universal adversarial perturbations (UAPs), which, when added to most images, destroy the output of the respective perception function. Existing attack metho

Contrasting Approaches in the Implementation of GRADE Methodology in Guidelines for Haemophilia and Von Willebrand Disease

Introduction: The 2024 ISTH clinical practice guideline (CPG) for treatment of congenital haemophilia, the NBDF-McMaster Guideline on Care Models for Haemophilia Management, and ASH ISTH NBDF WFH guidelines on the diagnosis and management of VWD all utilised GRADE methodology. Aim: Discuss missed opportunities and the methodological approach of the ISTH Guideline in contrast to how GRADE was previ