111 research outputs found
Probabilistic Joint Face-Skull Modelling for Facial Reconstruction
We present a novel method for co-registration of two independent statistical shape models. We solve the problem of aligning a face model to a skull model with stochastic optimization based on Markov Chain Monte Carlo (MCMC). We create a probabilistic joint face-skull model and show how to obtain a distribution of plausible face shapes given a skull shape. Due to environmental and genetic factors, there exists a distribution of possible face shapes arising from the same skull. We pose facial reconstruction as a conditional distribution of plausible face shapes given a skull shape. Because it is very difficult to obtain the distribution directly from MRI or CT data, we create a dataset of artificial face-skull pairs. To do this, we propose to combine three data sources of independent origin to model the joint face-skull distribution: a face shape model, a skull shape model and tissue depth marker information. For a given skull, we compute the posterior distribution of faces matching the tissue depth distribution with Metropolis-Hastings. We estimate the joint faceskull distribution from samples of the posterior. To find faces matching to an unknown skull, we estimate the probability of the face under the joint faceskull model. To our knowledge, we are the first to provide a whole distribution of plausible faces arising from a skull instead of only a single reconstruction. We show how the face-skull model can be used to rank a face dataset and on average successfully identify the correct match in top 30%. The face ranking even works when obtaining the face shapes from 2D images. We furthermore show how the face-skull model can be useful to estimate the skull position in an MR-image
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Shift work and cognitive impairment in later life - results of a cross-sectional pilot study testing the feasibility of a large-scale epidemiologic investigation
Background: The effect of shift work on impairment of cognition in later life has not yet been sufficiently investigated. Therefore, we aimed at testing the feasibility of a large-scale epidemiologic study examining this putative association in a pilot study. Methods: Between January and April 2017, a cross-sectional study invited a random sample of 425 former and current employees of a German university hospital aged 55 years and older to undergo a cognitive test battery (including the Repeatable Battery for the Assessment of Neuropsychological Status, Trail Making Test, Letter-Number Span, and Vocabulary Test) and to complete a self-administered questionnaire on socio-demographic characteristics, chronotype, sleep, occupational history including shift work, and medical history. Fifty percent of the invitees were registered in the hospital's occupational records as currently working or having worked in a shift system. The feasibility of a large-scale study was evaluated by the response of the study sample and the completeness of data. In addition, we calculated the prevalence of shift work and cognitive impairment in the study population. Results: Seventy five subjects (18%) completed the questionnaire, of whom 47 (11% of the total sample) participated in cognitive testing. In all but four items assessed in the questionnaire, the proportion of missing data was below 10 %, suggesting that the quality of collected data can be considered as high. Eighty percent of the participants reported that they ever worked in a shift system, indicating selective participation by exposure to shift work. With respect to chronotype, the majority of the study subjects rated themselves as rather evening type, while a quarter considered themselves as definite morning type. All cognitive tests could be carried out completely. We observed slight difficulties in at least one of the cognitive tests in 17 participants (36%) while two participants (4%) showed more pronounced signs of cognitive impairment. Conclusion: The present pilot study only partially supported the feasibility of the planned large-scale study. As response rates were low and depended on exposure to shift work, a better way of sampling and recruitment needs to be identified. The questionnaire and the test battery appear to be viable instruments
Postwachstumsprojekte im Spannungsfeld von kollektiven und einzelnen Sinnzusammenhängen
Postwachstumsprojekte reagieren auf aktuelle Krisen der kapitalistischen Gesellschaft. Sie stellen jedoch keine konfliktfreien sozialen Gebilde dar, sondern bergen Spannungen vor allem zwischen einem kollektiven Sinn und einer Vielfalt an individuellen Eigensinnen. Wie diese differenten Sinnformen gefasst werden können, wie sie sich in einzelnen Postwachstumsprojekten manifestieren und wie sie gelöst werden, stellen die Ausgangsfragen dieser Podiumsdiskussion dar. Nebst der Suche nach Antworten auf die gestellten Fragen geht es darum, reflexive Kritiken zu formulieren, die als solidarische Einlassung zu einer produktiven Reflexion anregen. Postwachstum wird damit nicht auf die ökonomische Dimension beengt, sondern es werden vielfältige soziale Formen identifiziert, in die Irritationen eingebunden sein können. Auf der Basis eigener Forschungsergebnisse, aber auch auf der Basis gemachter Praxiserfahrungen in Postwachstumsprojekten wird schließlich die Rolle soziologischer Forscher:innen in der Annäherung an Postwachstumsprojekte diskutiert
Finite Element Simulation of Dense Wire Packings
A finite element program is presented to simulate the process of packing and
coiling elastic wires in two- and three-dimensional confining cavities. The
wire is represented by third order beam elements and embedded into a
corotational formulation to capture the geometric nonlinearity resulting from
large rotations and deformations. The hyperbolic equations of motion are
integrated in time using two different integration methods from the Newmark
family: an implicit iterative Newton-Raphson line search solver, and an
explicit predictor-corrector scheme, both with adaptive time stepping. These
two approaches reveal fundamentally different suitability for the problem of
strongly self-interacting bodies found in densely packed cavities. Generalizing
the spherical confinement symmetry investigated in recent studies, the packing
of a wire in hard ellipsoidal cavities is simulated in the frictionless elastic
limit. Evidence is given that packings in oblate spheroids and scalene
ellipsoids are energetically preferred to spheres.Comment: 17 pages, 7 figures, 1 tabl
To Explain or Not to Explain?—Artificial Intelligence Explainability in Clinical Decision Support Systems
Explainability for artificial intelligence (AI) in medicine is a hotly debated topic. Our paper presents a review of the key arguments in favor and against explainability for AI-powered Clinical Decision Support System (CDSS) applied to a concrete use case, namely an AI-powered CDSS currently used in the emergency call setting to identify patients with life-threatening cardiac arrest. More specifically, we performed a normative analysis using socio-technical scenarios to provide a nuanced account of the role of explainability for CDSSs for the concrete use case, allowing for abstractions to a more general level. Our analysis focused on three layers: technical considerations, human factors, and the designated system role in decision-making. Our findings suggest that whether explainability can provide added value to CDSS depends on several key questions: technical feasibility, the level of validation in case of explainable algorithms, the characteristics of the context in which the system is implemented, the designated role in the decision-making process, and the key user group(s). Thus, each CDSS will require an individualized assessment of explainability needs and we provide an example of how such an assessment could look like in practice
Understanding chronic nematode infections: evolutionary considerations, current hypotheses and the way forward
Similarities and Differences between Colicin and Filamentous Phage Uptake by Bacterial Cells
International audienceGram-negative bacteria have evolved a complex envelope to adapt and survive in a broad range of ecological niches. This physical barrier is the first line of defense against noxious compounds and viral particles called bacteriophages. Colicins are a family of bactericidal proteins produced by and toxic to Escherichia coli and closely related bacteria. Filamentous phages have a complex structure, composed of at least five capsid proteins assembled in a long thread-shaped particle, that protects the viral DNA. Despite their difference in size and complexity, group A colicins and filamentous phages both parasitize multiprotein complexes of their sensitive host for entry. They first bind to a receptor located at the surface of the target bacteria before specifically recruiting components of the Tol system to cross the outer membrane and find their way through the periplasm. The Tol system is thought to use the proton motive force of the inner membrane to maintain outer membrane integrity during the life cycle of the cell. This review describes the sequential docking mechanisms of group A colicins and filamentous phages during their uptake by their bacterial host, with a specific focus on the translocation step, promoted by interactions with the Tol system
Assessing Trustworthy AI in times of COVID-19. Deep Learning for predicting a multi-regional score conveying the degree of lung compromise in COVID-19 patients
Abstract—The paper's main contributions are twofold: to demonstrate how to apply the general European Union’s High-Level Expert Group’s (EU HLEG) guidelines for trustworthy AI in practice for the domain of healthcare; and to investigate the research question of what does “trustworthy AI” mean at the time of the COVID-19 pandemic. To this end, we present the results of a post-hoc self-assessment to evaluate the trustworthiness of an AI system for predicting a multi-regional score conveying the degree of lung compromise in COVID-19 patients, developed and verified by an interdisciplinary team with members from academia, public hospitals, and industry in time of pandemic. The AI system aims to help radiologists to estimate and communicate the severity of damage in a patient’s lung from Chest X-rays. It has been experimentally deployed in the radiology department of the ASST Spedali Civili clinic in Brescia (Italy) since December 2020 during pandemic time. The methodology we have applied for our post-hoc assessment, called Z-Inspection®, uses socio-technical scenarios to identify ethical, technical and domain-specific issues in the use of the AI system in the context of the pandemic.</p
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