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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

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.

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

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

This study delves into the pressing issue of promoting sustainable tourist behavior in vulnerable heritage villages that are under threat from mass tourism. By employing the Theory of Planned Behavior, we conducted a survey of 406 domestic tourists in Abyaneh, Iran, to evaluate the influence of attitudes, perceived behavioral control, and subjective norms on environmentally responsible intentions.

In recent years, eco-certification has become an important market feature for aquaculture products, with several labels available for producers who want to signal sustainable or responsible production practices. In this study, the literature on the economic effects of eco-certification of aquaculture is reviewed to summarize the current state of knowledge and identify research gaps. The literature

Background: Emerging data suggest a complex pathophysiology of chronic subdural hematoma (CSDH) to which an inflammatory response might contribute. The complement system is activated in acute traumatic setting, although its role in CSDH is unknown. To investigate the complement system in CSDH pathophysiology, we analyzed blood and hematoma fluid biomarkers, as well as immunohistochemistry of the C

The FIRE21 Final Report examines problem-solving networks within Nordic Fire and Rescue Services (FRS) in Sweden, Norway, and Denmark, addressing challenges posed by climate change, technological advancements, and evolving risk landscapes. Through case studies, risk assessments, and theoretical analyses, the project identifies key organizational and individual qualities required for effective emer

In sub-Saharan Africa, more than a quarter of the urban population lives in small towns, with rapid lower level urbanisation being driven largely by lacking rural opportunities. A growing interest in translocality considers relationships that position livelihoods within multiple spatial contexts. Terms of inclusion in translocal relationships vary, and the socio-economic differentiation emerging o

Drawing on modelling of age at death in skeletal remains, this article unveils hitherto unrecognized demographic patterns in the Nordic Corded Ware complex. This population formed part of the European Corded Ware complex that has been linked to disruption observed in the archaeological and genetic record. The newly developed methods of transition analysis 3 (TA3) and death rate ratio (DRR) were usDrawing on modelling of age at death in skeletal remains, this article unveils hitherto unrecognized demographic patterns in the Nordic Corded Ware complex. This population formed part of the European Corded Ware complex that has been linked to disruption observed in the archaeological and genetic record. The newly developed methods of transition analysis 3 (TA3) and death rate ratio (DRR) were us

Deep neural networks tend to be vulnerable to adversarial perturbations, which by adding to a natural image can fool a respective model with high confidence. Recently, the existence of image-agnostic perturbations, also known as universal adversarial perturbations (UAPs), were discovered. However, existing UAPs still lack a sufficiently high fooling rate, when being applied to an unknown target mo

Recent advances in artificial intelligence have increased the importance of security issues. Nowadays, deep neural networks (DNNs) are used in many critical applications such as pilot drones and self-driving cars. So, the DNN's malfunction, due to an attack, may cause irreparable damages. The attack may happen either in training phase (poisoning attacks) or testing phase (evasion attacks) by prese

Susceptibility to adversarial examples is one of the major concerns in convolutional neural networks (CNNs) applications. Training the model with adversarial examples, known as adversarial training, is a common countermeasure to tackle such attacks. In reality, however, defenders are uninformed about how adversarial examples are generated by the attacker. Therefore, it is pivotal to utilize more g

Sensory interplay typically refers to cases where the content of one sensory modality affects the content of another sensory modality. Although there is much evidence today of such interplay, it is unknown how to interpret them. Is it a one-way causal function between two separate states (e.g., a visual process that influences an auditory process), a bidirectional relation between two separate sta

Understanding the aspects of progression for atherosclerotic cardiovascular disease and treatment is key to building reliable clinical decision-support systems. To promote system trust, one step is to make the machine learning models (used by the decision support systems) explainable for clinicians, developers, and researchers. Recently, working with longitudinal clinical trajectories using Graph