| 1. |
- Tobias, Deirdre K, et al.
(author)
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Second international consensus report on gaps and opportunities for the clinical translation of precision diabetes medicine
- 2023
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In: Nature Medicine. - 1546-170X. ; 29:10, s. 2438-2457
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Research review (peer-reviewed)abstract
- Precision medicine is part of the logical evolution of contemporary evidence-based medicine that seeks to reduce errors and optimize outcomes when making medical decisions and health recommendations. Diabetes affects hundreds of millions of people worldwide, many of whom will develop life-threatening complications and die prematurely. Precision medicine can potentially address this enormous problem by accounting for heterogeneity in the etiology, clinical presentation and pathogenesis of common forms of diabetes and risks of complications. This second international consensus report on precision diabetes medicine summarizes the findings from a systematic evidence review across the key pillars of precision medicine (prevention, diagnosis, treatment, prognosis) in four recognized forms of diabetes (monogenic, gestational, type 1, type 2). These reviews address key questions about the translation of precision medicine research into practice. Although not complete, owing to the vast literature on this topic, they revealed opportunities for the immediate or near-term clinical implementation of precision diabetes medicine; furthermore, we expose important gaps in knowledge, focusing on the need to obtain new clinically relevant evidence. Gaps include the need for common standards for clinical readiness, including consideration of cost-effectiveness, health equity, predictive accuracy, liability and accessibility. Key milestones are outlined for the broad clinical implementation of precision diabetes medicine.
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| 2. |
- Wilroth, Johanna, 1994-
(author)
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Exploring Auditory Attention Using EEG
- 2024
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Licentiate thesis (other academic/artistic)abstract
- Listeners with normal-hearing often overlook their ability to comprehend speech in noisy environments effortlessly. Our brain’s adeptness at identifying and amplifying attended voices while suppressing unwanted background noise, known as the cocktail party problem, has been extensively researched for decades. Yet, many aspects of this complex puzzle remain unsolved and listeners with hearing-impairment still struggle to focus on a specific speaker in noisy environments. While recent intelligent hearing aids have improved noise suppression, the problem of deciding which speaker to enhance remains unsolved, leading to discomfort for many hearing aid users in noisy environments.In this thesis, we explore the complexities of the human brain in challenging auditory environments. Two datasets are investigated where participants were tasked to selectively attend to one of two competing voices, replicating a cocktail-party scenario. The auditory stimuli trigger neurons to generate electrical signals that propagate in all directions. When a substantial number of neurons fire simultaneously, their collective electrical signal becomes detectable by small electrodes placed on the head. This method of measuring brain activity, known as electroencephalography (EEG), holds potential to provide feedback to the hearing aids, enabling adjustments to enhance attended voice(s).EEG data is often noisy, incorporating neural responses with artifacts such as muscle movements, eye blinks and heartbeats. In the first contribution of this thesis, we focus on comparing different manual and automatic artifact-rejection techniques and assessing their impact on auditory attention decoding (AAD).While EEG measurements offer high temporal accuracy, spatial resolution is inferior compared to alternative tools like magnetoencephalography (MEG). This difference poses a considerable challenge for source localization with EEG data. In the second contribution of this thesis, we demonstrate anticipated activity in the auditory cortex using EEG data from a single listener, employing Neuro-Current Response Functions (NCRFs). This method, previously evaluated only with MEG data, holds significant promise in hearing aid development.EEG data may involve both linear and nonlinear components due to the propagation of the electrical signals through brain tissue, skull, and scalp with varying conductivities. In the third contribution, we aim to enhance source localization by introducing a binning-based nonlinear detection and compensation method. The results suggest that compensating for some nonlinear components produces more precise and synchronized source localization compared to original EEG data.In the fourth contribution, we present a novel domain adaptation framework that improves AAD performances for listeners with initially low classification accuracy. This framework focuses on classifying the direction (left or right) of attended speech and shows a significant accuracy improvement when transporting poor data from one listener to the domain of good data from different listeners.Taken together, the contributions of this thesis hold promise for improving the lives of hearing-impaired individuals by closing the loop between the brain and hearing aids.
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| 3. |
- Axholt, Magnus, et al.
(author)
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Optical See-Through Head Mounted Display : Direct Linear Transformation Calibration Robustness in the Presence of User Alignment Noise
- 2010
-
In: Proceedings of the 54th Annual Meeting of the Human Factors and Ergonomics Society. - Linköping : Linköping University Electronic Press. - 9780945289371
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Conference paper (peer-reviewed)abstract
- The correct spatial registration between virtual and real objects in optical see-through augmented reality implies accurate estimates of the user’s eyepoint relative to the location and orientation of the display surface. A common approach is to estimate the display parameters through a calibration procedure involving a subjective alignment exercise. Human postural sway and targeting precision contribute to imprecise alignments, which in turn adversely affect the display parameter estimation resulting in registration errors between virtual and real objects. The technique commonly used has its origin incomputer vision, and calibrates stationary cameras using hundreds of correspondence points collected instantaneously in one video frame where precision is limited only by pixel quantization and image blur. Subsequently the input noise level is several order of magnitudes greater when a human operator manually collects correspondence points one by one. This paper investigates the effect of human alignment noise on view parameter estimation in an optical see-through head mounted display to determine how well astandard camera calibration method performs at greater noise levels than documented in computer vision literature. Through Monte-Carlo simulations we show that it is particularly difficult to estimate the user’s eyepoint in depth, but that a greater distribution of correspondence points in depth help mitigate the effects of human alignment noise.
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| 4. |
- Dahl, Victor Naestholt, et al.
(author)
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Global trends of pulmonary infections with nontuberculous mycobacteria: a systematic review
- 2022
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In: International Journal of Infectious Diseases. - : Elsevier. - 1201-9712 .- 1878-3511. ; 125, s. 120-131
-
Research review (peer-reviewed)abstract
- Objectives: To describe the global trends of pulmonary nontuberculous mycobacteria (NTM) infection and disease.Methods: A systematic review of studies including culture-based NTM data over time. Studies reporting on pulmonary NTM infection and/or disease were included. Information on the use of guideline-based criteria for disease were collected, in which, infection is defined as the absence of symptoms and radiological findings compatible with NTM pulmonary disease. The trends of change for incidence/prevalence were evaluated using linear regressions, and the corresponding pooled estimates were calculated.Results: Most studies reported increasing pulmonary NTM infection (82.1%) and disease (66.7%) trends. The overall annual rate of change for NTM infection and disease per 100,000 persons/year was 4.0% (95% confidence interval [CI]: 3.2-4.8) and 4.1% (95% CI: 3.2-5.0), respectively. For absolute numbers of NTM infection and disease, the overall annual change was 2.0 (95% CI: 1.6-2.3) and 0.5 (95% CI: 0.3-0.7), respectively. An increasing trend was also seen for Mycobacterium avium complex infection (n = 15/19, 78.9%) and disease (n = 10/12, 83.9%) and for Mycobacterium abscessus complex (n = 15/23, 65.2%) infection (n = 11/17, 64.7%) but less so for disease (n = 2/8, 25.0%).Conclusion: Our data indicate an overall increase in NTM worldwide for both infection and disease. The explanation to this phenomenon warrants further investigation.
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| 5. |
- Enflo, Kerstin, et al.
(author)
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Regional convergence and divergence in Sweden, 1860–2010 : Evidence from Swedish historical regional GDP data
- 2018. - 1
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In: The Economic Development of Europe's Regions : A Quantitative History since 1900 - A Quantitative History since 1900. - London : Routledge. - 9780415723381 - 9780429449789 ; , s. 291-309
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Book chapter (other academic/artistic)abstract
- Since industrialization, Sweden has experienced an amazing growth trajectory. In 1850, Sweden was a quite poor and peripheral country, with GDP levels close to the world’s average. One and a half centuries later, Sweden ranks among the richest countries in the world with GDP levels more than three times the world’s average (Schön 2013). Yet apart from a few case studies and some industry studies, little is known about the geographical evolution of Sweden’s growth process. This chapter will fill in the gap by presenting estimates of Swedish regional GDPs for 24 counties corresponding to NUTS 3 regions from 1860 to 2010. Using this data set, we will present descriptive evidence on processes of regional convergence and divergence and discuss some tentative explanations for these patterns.
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| 6. |
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| 7. |
- Enflo, Kerstin, et al.
(author)
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Swedish regional GDP 1855-2000 Estimations and general trends in the Swedish regional system
- 2014
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In: Research in Economic History. - 0363-3268. ; 30, s. 47-89
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Book chapter (peer-reviewed)abstract
- This paper uses a method devised by Geary and Stark to estimate regional GDPs for 24 Swedish provinces 1855-2007. In empirical tests, we find that the Swedish estimations yield results of good precision, comparable to those reported in the international literature. From the literature, we generate six expectations concerning the development of regional GDPs in Sweden. Using the GDP estimations, we test these expectations empirically. We find that the historical regional GDPs show a high correlation over time, but that the early industrialization process co-evolved with a dramatic redistribution of productive capacity. We show that the regional inequalities in GDP per capita were at their lowest point in modern history in the early 1980s. However, while efficiency in the regional system has never been as equal, absolute regional differences in scale of production has increased dramatically over our investigated period. This process has especially benefited the metropolitan provinces. We present detailed sources of our estimations and also sketch a research agenda from our results.
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| 8. |
- Günther, Sebastian, et al.
(author)
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Smooth as steel wool : Effects of visual stimuli on the haptic perception of roughness in virtual reality
- 2022
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In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems. - New York, NY, USA : Association for Computing Machinery (ACM). ; , s. 1-17
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Conference paper (peer-reviewed)abstract
- Haptic Feedback is essential for lifelike Virtual Reality (VR) experiences. To provide a wide range of matching sensations of being touched or stroked, current approaches typically need large numbers of different physical textures. However, even advanced devices can only accommodate a limited number of textures to remain wearable. Therefore, a better understanding is necessary of how expectations elicited by different visualizations affect haptic perception, to achieve a balance between physical constraints and great variety of matching physical textures.In this work, we conducted an experiment (N=31) assessing how the perception of roughness is affected within VR. We designed a prototype for arm stroking and compared the effects of different visualizations on the perception of physical textures with distinct roughnesses. Additionally, we used the visualizations’ real-world materials, no-haptics and vibrotactile feedback as baselines. As one result, we found that two levels of roughness can be sufficient to convey a realistic illusion.
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| 9. |
- Gustafsson, Fredrik K., et al.
(author)
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Accurate 3D Object Detection using Energy-Based Models
- 2021
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In: 2021 IEEE/CVF Conference on Computer Vision and Pattern Recogition Workshops (CVPRW 2021). - : Institute of Electrical and Electronics Engineers (IEEE). - 9781665448994 ; , s. 2849-2858
-
Conference paper (peer-reviewed)abstract
- Accurate 3D object detection (3DOD) is crucial for safe navigation of complex environments by autonomous robots. Regressing accurate 3D bounding boxes in cluttered environments based on sparse LiDAR data is however a highly challenging problem. We address this task by exploring recent advances in conditional energy-based models (EBMs) for probabilistic regression. While methods employing EBMs for regression have demonstrated impressive performance on 2D object detection in images, these techniques are not directly applicable to 3D bounding boxes. In this work, we therefore design a differentiable pooling operator for 3D bounding boxes, serving as the core module of our EBM network. We further integrate this general approach into the state-of-the-art 3D object detector SA-SSD. On the KITTI dataset, our proposed approach consistently outperforms the SA-SSD baseline across all 3DOD metrics, demonstrating the potential of EBM-based regression for highly accurate 3DOD. Code is available at https://github.com/fregu856/ebms_3dod.
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| 10. |
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| 11. |
- Gustafsson, Fredrik K., et al.
(author)
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Evaluating Scalable Bayesian Deep Learning Methods for Robust Computer Vision
- 2020
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In: 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW 2020). - : IEEE Computer Society. - 9781728193601 ; , s. 1289-1298
-
Conference paper (peer-reviewed)abstract
- While deep neural networks have become the go-to approach in computer vision, the vast majority of these models fail to properly capture the uncertainty inherent in their predictions. Estimating this predictive uncertainty can be crucial, for example in automotive applications. In Bayesian deep learning, predictive uncertainty is commonly decomposed into the distinct types of aleatoric and epistemic uncertainty. The former can be estimated by letting a neural network output the parameters of a certain probability distribution. Epistemic uncertainty estimation is a more challenging problem, and while different scalable methods recently have emerged, no extensive comparison has been performed in a real-world setting. We therefore accept this task and propose a comprehensive evaluation framework for scalable epistemic uncertainty estimation methods in deep learning. Our proposed framework is specifically designed to test the robustness required in real-world computer vision applications. We also apply this framework to provide the first properly extensive and conclusive comparison of the two current state-of-the-art scalable methods: ensembling and MC-dropout. Our comparison demonstrates that ensembling consistently provides more reliable and practically useful uncertainty estimates. Code is available at https://github.com/fregu856/evaluating_bdl.
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| 12. |
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| 13. |
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| 14. |
- Gustafsson, Fredrik K., et al.
(author)
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Learning Proposals for Practical Energy-Based Regression
- 2022
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In: International conference on artificial intelligence and statistics, vol 151. - : JMLR-JOURNAL MACHINE LEARNING RESEARCH. ; , s. 4685-4704
-
Conference paper (peer-reviewed)abstract
- Energy-based models (EBMs) have experienced a resurgence within machine learning in recent years, including as a promising alternative for probabilistic regression. However, energy-based regression requires a proposal distribution to be manually designed for training, and an initial estimate has to be provided at test-time. We address both of these issues by introducing a conceptually simple method to automatically learn an effective proposal distribution, which is parameterized by a separate network head. To this end, we derive a surprising result, leading to a unified training objective that jointly minimizes the KL divergence from the proposal to the EBM, and the negative log-likelihood of the EBM. At test-time, we can then employ importance sampling with the trained proposal to efficiently evaluate the learned EBM and produce standalone predictions. Furthermore, we utilize our derived training objective to learn mixture density networks (MDNs) with a jointly trained energy-based teacher, consistently outperforming conventional MDN training on four real-world regression tasks within computer vision. Code is available at https://github.com/fregu856/ebms_proposals.
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| 15. |
- Gustafsson, Fredrik K., 1993-
(author)
-
Towards Accurate and Reliable Deep Regression Models
- 2023
-
Doctoral thesis (other academic/artistic)abstract
- Regression is a fundamental machine learning task with many important applications within computer vision and other domains. In general, it entails predicting continuous targets from given inputs. Deep learning has become the dominant paradigm within machine learning in recent years, and a wide variety of different techniques have been employed to solve regression problems using deep models. There is however no broad consensus on how deep regression models should be constructed for best possible accuracy, or how the uncertainty in their predictions should be represented and estimated. These open questions are studied in this thesis, aiming to help take steps towards an ultimate goal of developing deep regression models which are both accurate and reliable enough for real-world deployment within medical applications and other safety-critical domains.The first main contribution of the thesis is the formulation and development of energy-based probabilistic regression. This is a general and conceptually simple regression framework with a clear probabilistic interpretation, using energy-based models to represent the true conditional target distribution. The framework is applied to a number of regression problems and demonstrates particularly strong performance for 2D bounding box regression, improving the state-of-the-art when applied to the task of visual tracking.The second main contribution is a critical evaluation of various uncertainty estimation methods. A general introduction to the problem of estimating the predictive uncertainty of deep models is first provided, together with an extensive comparison of the two popular methods ensembling and MC-dropout. A number of regression uncertainty estimation methods are then further evaluated, specifically examining their reliability under real-world distribution shifts. This evaluation uncovers important limitations of current methods and serves as a challenge to the research community. It demonstrates that more work is required in order to develop truly reliable uncertainty estimation methods for regression.
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| 16. |
- Gustafsson, Stefan, et al.
(author)
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Development and validation of deep learning ECG-based prediction of myocardial infarction in emergency department patients
- 2022
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In: Scientific Reports. - : Springer Nature. - 2045-2322. ; 12
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Journal article (peer-reviewed)abstract
- Myocardial infarction diagnosis is a common challenge in the emergency department. In managed settings, deep learning-based models and especially convolutional deep models have shown promise in electrocardiogram (ECG) classification, but there is a lack of high-performing models for the diagnosis of myocardial infarction in real-world scenarios. We aimed to train and validate a deep learning model using ECGs to predict myocardial infarction in real-world emergency department patients. We studied emergency department patients in the Stockholm region between 2007 and 2016 that had an ECG obtained because of their presenting complaint. We developed a deep neural network based on convolutional layers similar to a residual network. Inputs to the model were ECG tracing, age, and sex; and outputs were the probabilities of three mutually exclusive classes: non-ST-elevation myocardial infarction (NSTEMI), ST-elevation myocardial infarction (STEMI), and control status, as registered in the SWEDEHEART and other registries. We used an ensemble of five models. Among 492,226 ECGs in 214,250 patients, 5,416 were recorded with an NSTEMI, 1,818 a STEMI, and 485,207 without a myocardial infarction. In a random test set, our model could discriminate STEMIs/NSTEMIs from controls with a C-statistic of 0.991/0.832 and had a Brier score of 0.001/0.008. The model obtained a similar performance in a temporally separated test set of the study sample, and achieved a C-statistic of 0.985 and a Brier score of 0.002 in discriminating STEMIs from controls in an external test set. We developed and validated a deep learning model with excellent performance in discriminating between control, STEMI, and NSTEMI on the presenting ECG of a real-world sample of the important population of all-comers to the emergency department. Hence, deep learning models for ECG decision support could be valuable in the emergency department.
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| 17. |
- Hermansson, Joel, et al.
(author)
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Autonomous Landing of an Unmanned Aerial Vehicle
- 2010
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Reports (other academic/artistic)abstract
- This paper is concerned with the problem of autonomously landing an unmanned aerial vehicle (UAV) on a stationary platform. Our solution consists of two parts, a sensor fusion framework producing estimates of the UAV state and a control system that computes appropriate actuator commands. There are three sensors used, a camera, a GPS and a compass. Besides the description of the solution, we also present experimental results illustrating the results obtained in using our system to autonomously land an UAV.
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| 18. |
- Inglese, Alessandro, et al.
(author)
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Light-induced degradation in multicrystalline silicon: the role of copper
- 2016
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In: PROCEEDINGS OF THE 6TH INTERNATIONAL CONFERENCE ON CRYSTALLINE SILICON PHOTOVOLTAICS (SILICONPV 2016). - : Elsevier. ; , s. 808-814
-
Conference paper (peer-reviewed)abstract
- In this contribution, we provide an insight into the light-induced degradation of multicrystalline (mc-) silicon caused by copper contamination. Particularly we analyze the degradation kinetics of intentionally contaminated B- and Ga-doped mc-Si through spatially resolved photoluminescence (PL) imaging. Our results show that even small copper concentrations are capable of causing a strong LID effect in both B- and Ga-doped samples. Furthermore, the light intensity, the dopant and the grain quality were found to strongly impact the degradation kinetics, since faster LID was observed with stronger illumination intensity, B-doping and in the grains featuring low initial lifetime. Interestingly after degradation we also observe the formation of bright denuded zones near the edges of the B-doped grains, which might indicate the possible accumulation of copper impurities at the grain boundaries.
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| 19. |
- Kjerrulf, Martin, et al.
(author)
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Interferon-gamma receptor-deficient mice exhibit impaired gut mucosal immune responses but intact oral tolerance.
- 1997
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In: Immunology. - 0019-2805. ; 92:1, s. 60-8
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Journal article (peer-reviewed)abstract
- Interferon-gamma (IFN-gamma) receptor knock-out (IFN-gamma R -/-) mice were used to analyse the role of IFN-gamma in mucosal immune responses following oral immunization. We found that the IFN-gamma R -/- mice demonstrated 50% reduced spot-forming cell (SFC) responses in the gut lamina propria and spleen after oral immunization with keyhold limpet haemocyanin (KLH) plus cholera toxin (CT) adjuvant. The IFN-gamma R -/- mice exhibited 10-fold reduced total serum KLH-specific antibody levels compared with wild-type mice after oral immunization, while after intravenous immunization, no such difference was seen, suggesting a selective impairment of mucosal immune responses. Moreover, oral immunizations resulted in impaired interleukin-4 (IL-4), IL-10 and IFN-gamma production by spleen T cells from IFN-gamma R -/- mice, indicating that no reciprocal up-regulation of Th2-activities had occurred despite the lack of IFN-gamma R function. No reduction in Th1 or Th2 cytokines was observed following systemic immunizations. Despite potentially strong modulating effects of IFN-gamma on epithelial cell IgA transcytosis and electrolyte barrier functions, CT-immunized IFN-gamma R -/- mice demonstrated unaltered protection against CT in ligated intestinal loops together with normal anti-CT IgA and total IgA levels in gut lavage. Oral feeding with KLH followed by parenteral immunization resulted in strongly suppressed SFC numbers and reduced cell-mediated immunity in both wild-type and IFN-gamma R -/- mice. CT-adjuvant abrogated induction of oral tolerance in both IFN-gamma R -/- and wild-type mice. Collectively, our data argue that the two major response patterns induced by oral administration of protein antigen, i.e. active IgA immunity and oral tolerance, are differently regulated. Thus, IFN-gamma R -/- mice have impaired mucosal immune responses while induction of oral tolerance appears to be unaffected by the lack of IFN-gamma functions.
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| 20. |
- Koehler, Niklas, et al.
(author)
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Pretomanid-resistant tuberculosis
- 2023
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In: Journal of Infection. - : W B SAUNDERS CO LTD. - 0163-4453 .- 1532-2742. ; 86:5, s. 520-524
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Journal article (other academic/artistic)
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| 21. |
- Kristan, M., et al.
(author)
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The Eighth Visual Object Tracking VOT2020 Challenge Results
- 2020
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In: Computer Vision. - Cham : Springer International Publishing. - 9783030682378 ; , s. 547-601
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Conference paper (peer-reviewed)abstract
- The Visual Object Tracking challenge VOT2020 is the eighth annual tracker benchmarking activity organized by the VOT initiative. Results of 58 trackers are presented; many are state-of-the-art trackers published at major computer vision conferences or in journals in the recent years. The VOT2020 challenge was composed of five sub-challenges focusing on different tracking domains: (i) VOT-ST2020 challenge focused on short-term tracking in RGB, (ii) VOT-RT2020 challenge focused on “real-time” short-term tracking in RGB, (iii) VOT-LT2020 focused on long-term tracking namely coping with target disappearance and reappearance, (iv) VOT-RGBT2020 challenge focused on short-term tracking in RGB and thermal imagery and (v) VOT-RGBD2020 challenge focused on long-term tracking in RGB and depth imagery. Only the VOT-ST2020 datasets were refreshed. A significant novelty is introduction of a new VOT short-term tracking evaluation methodology, and introduction of segmentation ground truth in the VOT-ST2020 challenge – bounding boxes will no longer be used in the VOT-ST challenges. A new VOT Python toolkit that implements all these novelites was introduced. Performance of the tested trackers typically by far exceeds standard baselines. The source code for most of the trackers is publicly available from the VOT page. The dataset, the evaluation kit and the results are publicly available at the challenge website (http://votchallenge.net ).
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| 22. |
- Kuehlewein, Laura, et al.
(author)
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Clinical phenotype and course of PDE6A-associated retinitis pigmentosa disease, characterized in preparation for a gene supplementation trial
- 2020
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In: JAMA Ophthalmology. - : American Medical Association (AMA). - 2168-6165. ; 138:12, s. 1241-1250
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Journal article (peer-reviewed)abstract
- IMPORTANCE Treatment trials require sound knowledge on the natural course of disease. OBJECTIVE To assess clinical features, genetic findings, and genotype-phenotype correlations in patients with retinitis pigmentosa (RP) associated with biallelic sequence variations in the PDE6A gene in preparation for a gene supplementation trial. DESIGN, SETTING, AND PARTICIPANTS This prospective, longitudinal, observational cohort study was conducted from January 2001 to December 2019 in a single center (Centre for Ophthalmology of the University of Tübingen, Germany) with patients recruited multinationally from 12 collaborating European tertiary referral centers. Patients with retinitis pigmentosa, sequence variants in PDE6A, and the ability to provide informed consent were included. EXPOSURES Comprehensive ophthalmological examinations; validation of compound heterozygosity and biallelism by familial segregation analysis, allelic cloning, or assessment of next-generation sequencing-read data, where possible. MAIN OUTCOMES AND MEASURES Genetic findings and clinical features describing the entire cohort and comparing patients harboring the 2 most common disease-causing variants in a homozygous state (c.304C>A;p.(R102S) and c.998 + 1G>A;p.?). RESULTS Fifty-seven patients (32 female patients [56%]; mean [SD], 40 [14] years) from 44 families were included. All patients completed the study. Thirty patients were homozygous for disease-causing alleles. Twenty-seven patients were heterozygous for 2 different PDE6A variants each. The most frequently observed alleles were c.304C>A;p.(R102S), c.998 + 1G>A;p.?, and c.2053G>A;p.(V685M). The mean (SD) best-corrected visual acuity was 0.43 (0.48) logMAR (Snellen equivalent, 20/50). The median visual field area with object III4e was 660 square degrees (5th and 95th percentiles, 76 and 11 019 square degrees; 25th and 75th percentiles, 255 and 3923 square degrees). Dark-adapted and light-adapted full-field electroretinography showed no responses in 88 of 108 eyes (81.5%). Sixty-nine of 108 eyes (62.9%) showed additional findings on optical coherence tomography imaging (eg, cystoid macular edema or macular atrophy). The variant c.998 + 1G>A;p.? led to a more severe phenotype when compared with the variant c.304C>A;p.(R102S). CONCLUSIONS AND RELEVANCE Seventeen of the PDE6A variants found in these patients appeared to be novel. Regarding the clinical findings, disease was highly symmetrical between the right and left eyes and visual impairment was mild or moderate in 90% of patients, providing a window of opportunity for gene therapy.
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| 23. |
- Martin, Tim, et al.
(author)
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Guarantees for data-driven control of nonlinear systems using semidefinite programming : A survey
- 2023
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In: Annual Reviews in Control. - : Elsevier. - 1367-5788 .- 1872-9088. ; 56
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Research review (peer-reviewed)abstract
- This survey presents recent research on determining control-theoretic properties and designing controllers with rigorous guarantees using semidefinite programming and for nonlinear systems for which no mathematical models but measured trajectories are available. Data-driven control techniques have been developed to circumvent a time-consuming modelling by first principles and because of the increasing availability of data. Recently, this research field has gained increased attention by the application of Willems' fundamental lemma, which provides a fertile ground for the development of data-driven control schemes with guarantees for linear time-invariant systems. While the fundamental lemma can be generalized to further system classes, there does not exist a comparable data-based system representation for nonlinear systems. At the same time, nonlinear systems constitute the majority of practical systems. Moreover, they include additional challenges such as data-based surrogate models that prevent system analysis and controller design by convex optimization. Therefore, a variety of data-driven control approaches has been developed with different required prior insights into the system to ensure a guaranteed inference. In this survey, we will discuss developments in the context of data-driven control for nonlinear systems. In particular, we will focus on methods based on system representations providing guarantees from finite data, while the analysis and the controller design boil down to convex optimization problems given as semidefinite programming. Thus, these approaches achieve reasonable advances compared to the state-of-the-art system analysis and controller design by models from system identification. Specifically, the paper covers system representations based on extensions of Willems' fundamental lemma, set membership, kernel techniques, the Koopman operator, and feedback linearization.
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| 24. |
- Müller, Florian, et al.
(author)
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TicTacToes : Assessing Toe Movements as an Input Modality
- 2023
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In: CHI 2023. - : Association for Computing Machinery (ACM).
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Conference paper (peer-reviewed)abstract
- From carrying grocery bags to holding onto handles on the bus, there are a variety of situations where one or both hands are busy, hindering the vision of ubiquitous interaction with technology. Voice commands, as a popular hands-free alternative, struggle with ambient noise and privacy issues. As an alternative approach, research explored movements of various body parts (e.g., head, arms) as input modalities, with foot-based techniques proving particularly suitable for hands-free interaction. Whereas previous research only considered the movement of the foot as a whole, in this work, we argue that our toes offer further degrees of freedom that can be leveraged for interaction. To explore the viability of toe-based interaction, we contribute the results of a controlled experiment with 18 participants assessing the impact of five factors on the accuracy, efficiency and user experience of such interfaces. Based on the findings, we provide design recommendations for future toe-based interfaces.
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| 25. |
- Perez-Recio, Sandra, et al.
(author)
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Identification of Recent Tuberculosis Exposure Using QuantiFERON-TB Gold Plus, a Multicenter Study
- 2021
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In: Microbiology Spectrum. - : American Society for Microbiology. - 2165-0497. ; 9:3
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Journal article (peer-reviewed)abstract
- We investigated whether the difference of antigen tube 2 (TB2) minus antigen tube 1 (TB1) (TB22TB1) of the QuantiFERON-TB gold plus test, which has been postulated as a surrogate for the CD81 T-cell response, could be useful in identifying recent tuberculosis (TB) exposure. We looked at the interferon gamma (IFN-g) responses and differences in TB2 and TB1 tubes for 686 adults with QFT-plus positive test results. These results were compared among groups with high (368 TB contacts), low (229 patients with immune-mediated inflammatory diseases [IMID]), and indeterminate (89 asylum seekers or people from abroad [ASPFA]) risks of recent TB exposure. A TB2-TB1 value.0.6 IU.ml(-1) was deemed to indicate a true difference between tubes. In the whole cohort, 13.6%, 10.9%, and 11.2% of cases had a TB2>TB1 result in the contact, IMID, and ASPFA groups, respectively (P = 0.591). The adjusted odds ratios (aORs) for an association between a TB2-TB1 result of >0.6 IU.ml(-1) and risk of recent exposure versus contacts were 0.71 (95% confidence interval [CI], 0.31 to 1.61) for the IMID group and 0.86 (95% CI, 0.49 to 1.52) for the ASPFA group. In TB contact subgroups, 11.4%, 15.4%, and 17.7% with close, frequent, and sporadic contact had a TB2>TB1 result (P = 0.362). The aORs versus the close subgroup were 1.29 (95% CI, 0.63 to 2.62) for the frequent subgroup and 1.55 (95% CI, 0.67 to 3.60) for the sporadic subgroup. A TB2-TB1 difference of.0.6 IU.ml(-1) was not associated with increased risk of recent TB exposure, which puts into question the clinical potential as a proxy marker for recently acquired TB infection. IMPORTANCE Contact tuberculosis tracing is essential to identify recently infected people, who therefore merit preventive treatment. However, there are no diagnostic tests that can determine whether the infection is a result of a recent exposure or not. It has been suggested that by using the QuantiFERON-TB gold plus, an interferon gamma (IFN-gamma) release assay, a difference in IFN-gamma production between the two antigen tubes (TB2 minus TB1) of.0.6 IU.ml(-1) could serve as a proxy marker for recent infection. In this large multinational study, infected individuals could not be classified according to the risk of recent exposure based on differences in IFN- g in TB1 and TB2 tubes that were higher than 0.6 IU.ml(-1). QuantiFERON-TB gold plus is not able to distinguish between recent and remotely acquired tuberculosis infection, and it should not be used for that purpose in contact tuberculosis tracing.
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