Cryopyrin-associated periodic fever syndrome manifesting as Tolosa-Hunt syndrome

Background Tolosa-Hunt syndrome (THS) is characterized by unilateral orbital pain, ipsilateral oculomotor paresis and a prompt response to treatment with corticosteroids. Several reports have demonstrated that the clinical features of THS are not specific to one causal aetiology and can lead to misdiagnosis. Case report We report the case of a patient diagnosed with THS after an episode of unilateral orbital pain and diplopia with demonstration of granulomatous inflammation of both cavernous sinus on cerebral magnetic resonance imaging and an immediate response to treatment with corticosteroids. Progression of the disease over the following years, accompanied by increasing signs of inflammation on cerebral magnetic resonance imaging and cerebrospinal fluid pleocytosis, led to further diagnostic tests. Genetic analyses revealed a heterozygote low-penetrance mutation (Q703K) of the cryopyrin/NLRP3 gene compatible with a cryopyrin-associated periodic fever syndrome. Discussion This case report demonstrates that THS can be a central nervous system manifestation of cryopyrin-associated periodic fever syndrome, which therefore represents a differential diagnosis of THS, even in elderly patients

Analysis of the Copenhagen Accord pledges and its global climatic impacts‚ a snapshot of dissonant ambitions

This analysis of the Copenhagen Accord evaluates emission reduction pledges by individual countries against the Accord's climate-related objectives. Probabilistic estimates of the climatic consequences for a set of resulting multi-gas scenarios over the 21st century are calculated with a reduced complexity climate model, yielding global temperature increase and atmospheric CO2 and CO2-equivalent concentrations. Provisions for banked surplus emission allowances and credits from land use, land-use change and forestry are assessed and are shown to have the potential to lead to significant deterioration of the ambition levels implied by the pledges in 2020. This analysis demonstrates that the Copenhagen Accord and the pledges made under it represent a set of dissonant ambitions. The ambition level of the current pledges for 2020 and the lack of commonly agreed goals for 2050 place in peril the Accord's own ambition: to limit global warming to below 2 °C, and even more so for 1.5 °C, which is referenced in the Accord in association with potentially strengthening the long-term temperature goal in 2015. Due to the limited level of ambition by 2020, the ability to limit emissions afterwards to pathways consistent with either the 2 or 1.5 °C goal is likely to become less feasibl

NoiseGrad: enhancing explanations by introducing stochasticity to model weights

Many efforts have been made for revealing the decision-making process of black-box learning machines such as deep neural networks, resulting in useful local and global explanation methods. For local explanation, stochasticity is known to help: a simple method, called SmoothGrad, has improved the visual quality of gradient-based attribution by adding noise in the input space and taking the average over the noise. In this paper, we extend this idea and propose NoiseGrad that enhances both local and global explanation methods. Specifically, NoiseGrad introduces stochasticity in the weight parameter space, such that the decision boundary is perturbed. NoiseGrad is expected to enhance the local explanation, similarly to SmoothGrad, due to the dual relationship between the input perturbation and the decision boundary perturbation. Furthermore, NoiseGrad can be used to enhance global explanations. We evaluate NoiseGrad and its fusion with SmoothGrad -- FusionGrad -- qualitatively and quantitatively with several evaluation criteria, and show that our novel approach significantly outperforms the baseline methods. Both NoiseGrad and FusionGrad are method-agnostic and as handy as SmoothGrad using simple heuristics for the choice of hyperparameter setting without the need of fine-tuning.Comment: 19 pages, 16 figure

Visualizing the Diversity of Representations Learned by Bayesian Neural Networks

Explainable Artificial Intelligence (XAI) aims to make learning machines less opaque, and offers researchers and practitioners various tools to reveal the decision-making strategies of neural networks. In this work, we investigate how XAI methods can be used for exploring and visualizing the diversity of feature representations learned by Bayesian Neural Networks (BNNs). Our goal is to provide a global understanding of BNNs by making their decision-making strategies a) visible and tangible through feature visualizations and b) quantitatively measurable with a distance measure learned by contrastive learning. Our work provides new insights into the \emph{posterior} distribution in terms of human-understandable feature information with regard to the underlying decision making strategies. The main findings of our work are the following: 1) global XAI methods can be applied to explain the diversity of decision-making strategies of BNN instances, 2) Monte Carlo dropout with commonly used Dropout rates exhibit increased diversity in feature representations compared to the multimodal posterior approximation of MultiSWAG, 3) the diversity of learned feature representations highly correlates with the uncertainty estimate for the output and 4) the inter-mode diversity of the multimodal posterior decreases as the network width increases, while the intra mode diversity increases. These findings are consistent with the recent Deep Neural Networks theory, providing additional intuitions about what the theory implies in terms of humanly understandable concepts.Comment: 16 pages, 18 figure

Flying Adversarial Patches: Manipulating the Behavior of Deep Learning-based Autonomous Multirotors

Autonomous flying robots, e.g. multirotors, often rely on a neural network that makes predictions based on a camera image. These deep learning (DL) models can compute surprising results if applied to input images outside the training domain. Adversarial attacks exploit this fault, for example, by computing small images, so-called adversarial patches, that can be placed in the environment to manipulate the neural network's prediction. We introduce flying adversarial patches, where an image is mounted on another flying robot and therefore can be placed anywhere in the field of view of a victim multirotor. For an effective attack, we compare three methods that simultaneously optimize the adversarial patch and its position in the input image. We perform an empirical validation on a publicly available DL model and dataset for autonomous multirotors. Ultimately, our attacking multirotor would be able to gain full control over the motions of the victim multirotor.Comment: 6 pages, 5 figures, Workshop on Multi-Robot Learning, International Conference on Robotics and Automation (ICRA

Transgender Transitioning and Change of Self-Reported Sexual Orientation

Objective: Sexual orientation is usually considered to be determined in early life and stable in the course of adulthood. In contrast, some transgender individuals report a change in sexual orientation. A common reason for this phenomenon is not known. Methods: We included 115 transsexual persons (70 male-to-female "MtF" and 45 female-to-male "FtM") patients from our endocrine outpatient clinic, who completed a questionnaire, retrospectively evaluating the history of their gender transition phase. The questionnaire focused on sexual orientation and recalled time points of changes in sexual orientation in the context of transition. Participants were further asked to provide a personal concept for a potential change in sexual orientation. Results: In total, 32.9% (n = 23) MtF reported a change in sexual orientation in contrast to 22.2% (n = 10) FtM transsexual persons (p = 0.132). Out of these patients, 39.1% (MtF) and 60% (FtM) reported a change in sexual orientation before having undergone any sex reassignment surgery. FtM that had initially been sexually oriented towards males (= androphilic), were significantly more likely to report on a change in sexual orientation than gynephilic, analloerotic or bisexual FtM (p = 0.012). Similarly, gynephilic MtF reported a change in sexual orientation more frequently than androphilic, analloerotic or bisexual MtF transsexual persons (p = 0.05). Conclusion: In line with earlier reports, we reveal that a change in self-reported sexual orientation is frequent and does not solely occur in the context of particular transition events. Transsexual persons that are attracted by individuals of the opposite biological sex are more likely to change sexual orientation. Qualitative reports suggest that the individual's biography, autogynephilic and autoandrophilic sexual arousal, confusion before and after transitioning, social and self-acceptance, as well as concept of sexual orientation itself may explain this phenomenon