1,484 research outputs found
Optimization-based iterative learning for precise quadrocopter trajectory tracking
Current control systems regulate the behavior of dynamic systems by reacting to noise and unexpected disturbances as they occur. To improve the performance of such control systems, experience from iterative executions can be used to anticipate recurring disturbances and proactively compensate for them. This paper presents an algorithm that exploits data from previous repetitions in order to learn to precisely follow a predefined trajectory. We adapt the feed-forward input signal to the system with the goal of achieving high tracking performance—even under the presence of model errors and other recurring disturbances. The approach is based on a dynamics model that captures the essential features of the system and that explicitly takes system input and state constraints into account. We combine traditional optimal filtering methods with state-of-the-art optimization techniques in order to obtain an effective and computationally efficient learning strategy that updates the feed-forward input signal according to a customizable learning objective. It is possible to define a termination condition that stops an execution early if the deviation from the nominal trajectory exceeds a given bound. This allows for a safe learning that gradually extends the time horizon of the trajectory. We developed a framework for generating arbitrary flight trajectories and for applying the algorithm to highly maneuverable autonomous quadrotor vehicles in the ETH Flying Machine Arena testbed. Experimental results are discussed for selected trajectories and different learning algorithm parameter
The introduction of a bi-adaptive smoothed particle hydrodynamics formulation beneficial for machining process simulations
Machining is one of the most important industrial production processes and, therefore, it is of great interest to have a tool suitable to describe the behavior of a real machined workpiece in a simulation. Due to its meshless nature, the Smoothed Particle Hydrodynamics (SPH) method is a quite promising, but frequently not well known alternative to mesh-based techniques, with the Finite Element Method leading the way, when simulating cutting processes. In order to demonstrate this, we present a broad variety of simulation results generated by our enhanced, bi-adaptive SPH cutting algorithm and evaluate them with respect to experimental data. But not only the final results, also the way how to extend the basic SPH code for solids to two adaptive components in order to meet the special requirements demanded by the cutting scenario, the ASPH extension and a newly developed refinement algorithm, is presented
ARE YOU WILLING TO WAIT LONGER FOR INTERNET PRIVACY?
It becomes increasingly common for governments, service providers and specialized data aggregators to systematically collect traces of personal communication on the Internet without the user’s knowledge or approval. An analysis of these personal traces by data mining algorithms can reveal sensitive personal information, such as location data, behavioral patterns, or personal profiles including preferences and dislikes. Recent studies show that this information can be used for various purposes, for example by insurance companies or banks to identify potentially risky customers, by governments to observe their citizens, and also by repressive regimes to monitor political opponents. Online anonymity software, such as Tor, can help users to protect their privacy, but often comes at the prize of low usability, e.g., by causing increased latency during surfing. In this exploratory study, we determine factors that influence the usage of Internet anonymity software. In particular, we show that Internet literacy, Internet privacy awareness and Internet privacy concerns are important antecedents for determining an Internet user’s intention to use anonymity software, and that Internet patience has a positive moderating effect on the intention to use anonymity software, as well as on its perceived usefulness
INFLUENCE OF LIGNIN EXTRACT ON THE ACTIVITY OF ENZYMES, RELATED TO CARBOHYDRATE AND PEPTIDE DIGESTION
In cooperation with the Latvian Institute of Wood Chemistry, the following research work shows quantitative experiments in investigation of affect of different concentrations of Lignin on the activity of enzymes Pepsin and ? - Amylase. All experiments are made “in vitro” and corresponding environments were simulated. The long – term aim of this research project is, to give evidence about the different effects of lignin on human enzymes to establish a cost – efficiently, natural drug. This research work is related to the European COST program, action CM0804: Chemical Biology with Natural Products: "The main objective of the Action is to advance the use of natural products as tools for chemical biology. Applying modern techniques and advancing them, natural products will prove to be instrumental in discovering target proteins and biological pathways that are of relevance to diseases. This in turn, should facilitate and speed up subsequent drug discovery efforts in the pharmaceutical industry."
Integration of a polygenic score into guideline-recommended prediction of cardiovascular disease
Background and Aims It is not clear how a polygenic risk score (PRS) can be best combined with guideline-recommended tools for cardiovascular disease (CVD) risk prediction, e.g. SCORE2.Methods A PRS for coronary artery disease (CAD) was calculated in participants of UK Biobank (n = 432 981). Within each tenth of the PRS distribution, the odds ratios (ORs)-referred to as PRS-factor-for CVD (i.e. CAD or stroke) were compared between the entire population and subgroups representing the spectrum of clinical risk. Replication was performed in the combined Framingham/Atherosclerosis Risk in Communities (ARIC) populations (n = 10 757). The clinical suitability of a multiplicative model 'SCORE2 x PRS-factor' was tested by risk reclassification.Results In subgroups with highly different clinical risks, CVD ORs were stable within each PRS tenth. SCORE2 and PRS showed no significant interactive effects on CVD risk, which qualified them as multiplicative factors: SCORE2 x PRS-factor = total risk. In UK Biobank, the multiplicative model moved 9.55% of the intermediate (n = 145 337) to high-risk group increasing the individuals in this category by 56.6%. Incident CVD occurred in 8.08% of individuals reclassified by the PRS-factor from intermediate to high risk, which was about two-fold of those remained at intermediate risk (4.08%). Likewise, the PRS-factor shifted 8.29% of individuals from moderate to high risk in Framingham/ARIC.Conclusions This study demonstrates that absolute CVD risk, determined by a clinical risk score, and relative genetic risk, determined by a PRS, provide independent information. The two components may form a simple multiplicative model improving precision of guideline-recommended tools in predicting incident CVD. Structured Graphical Abstract The left panel shows that relative risk related to polygenic disposition [1-10 tenth of the polygenic risk score (PRS) distribution] is independent of having a low, intermediate, or high clinical risk by SCORE2 in the UK Biobank. Thereby, the odds ratio from the PRS (relative risk) can be used as a genetic factor (PRS-factor) to multiply the absolute clinical risk estimate from SCORE2. If this is being done, similar to 10% of the intermediate-risk group is being upgraded to a higher total risk (right panel). Subgroups that were genetically upgraded had incident event rates that were similar to those in the original high-risk groups and substantially increased the overall numbers of individuals correctly assessed to be at high risk. CVD, cardiovascular disease
In Silico Assessment of Safety and Efficacy of Screw Placement for Pediatric Image-Guided Otologic Surgery.
Introduction: Current high-accuracy image-guided systems for otologic surgery use fiducial screws for patient-to-image registration. Thus far, these systems have only been used in adults, and the safety and efficacy of the fiducial screw placement has not yet been investigated in the pediatric population. Materials and Methods: In a retrospective study, CT image data of the temporal region from 11 subjects meeting inclusion criteria (8-48 months at the time of surgery) were selected, resulting in n = 20 sides. These datasets were investigated with respect to screw stability efficacy in terms of the cortical layer thickness, and safety in terms of the distance of potential fiducial screws to the dura mater or venous sinuses. All of these results are presented as distributions, thickness color maps, and with descriptive statistics. Seven regions within the temporal bone were analyzed individually. In addition, four fiducial screws per case with 4 mm thread-length were placed in an additively manufactured model according to the guidelines for robotic cochlear implantation surgery. For all these screws, the minimal distance to the dura mater or venous sinuses was measured, or if applicable how much they penetrated these structures. Results: The cortical layer has been found to be mostly between 0.7-3.3 mm thick (from the 5th to the 95th percentile), while even thinner areas exist. The distance from the surface of the temporal bone to the dura mater or the venous sinuses varied considerably between the subjects and ranged mostly from 1.1-9.3 mm (from the 5th to the 95th percentile). From all 80 placed fiducial screws of 4 mm thread length in the pediatric subject younger than two years old, 22 touched or penetrated either the dura or the sigmoid sinus. The best regions for fiducial placement would be the mastoid area and along the petrous pyramid in terms of safety. In terms of efficacy, the parietal followed by the petrous pyramid, and retrosigmoid regions are most suited. Conclusion: The current fiducial screws and the screw placement guidelines for adults are insufficiently safe or effective for pediatric patients
API design for machine learning software: experiences from the scikit-learn project
Scikit-learn is an increasingly popular machine learning li- brary. Written
in Python, it is designed to be simple and efficient, accessible to
non-experts, and reusable in various contexts. In this paper, we present and
discuss our design choices for the application programming interface (API) of
the project. In particular, we describe the simple and elegant interface shared
by all learning and processing units in the library and then discuss its
advantages in terms of composition and reusability. The paper also comments on
implementation details specific to the Python ecosystem and analyzes obstacles
faced by users and developers of the library
Toxic effects of brake wear particles on epithelial lung cells in vitro
Background: Fine particulate matter originating from traffic correlates with increased morbidity and mortality. An important source of traffic particles is brake wear of cars which contributes up to 20% of the total traffic emissions. The aim of this study was to evaluate potential toxicological effects of human epithelial lung cells exposed to freshly generated brake wear particles. Results: An exposure box was mounted around a car's braking system. Lung cells cultured at the air-liquid interface were then exposed to particles emitted from two typical braking behaviours ("full stop" and "normal deceleration"). The particle size distribution as well as the brake emission components like metals and carbons was measured on-line, and the particles deposited on grids for transmission electron microscopy were counted. The tight junction arrangement was observed by laser scanning microscopy. Cellular responses were assessed by measurement of lactate dehydrogenase (cytotoxicity), by investigating the production of reactive oxidative species and the release of the pro-inflammatory mediator interleukin-8. The tight junction protein occludin density decreased significantly (p < 0.05) with increasing concentrations of metals on the particles (iron, copper and manganese, which were all strongly correlated with each other). Occludin was also negatively correlated with the intensity of reactive oxidative species. The concentrations of interleukin-8 were significantly correlated with increasing organic carbon concentrations. No correlation was observed between occludin and interleukin-8, nor between reactive oxidative species and interleukin-8. Conclusion: These findings suggest that the metals on brake wear particles damage tight junctions with a mechanism involving oxidative stress. Brake wear particles also increase pro-inflammatory responses. However, this might be due to another mechanism than via oxidative stress. [Authors]]]>
Vehicle Emissions ; Particulate Matter ; Particle Size ; Epithelial Cells ; Toxicity Tests
eng
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A liposomal peptide vaccine inducing CD8+ T cells in HLA-A2.1 transgenic mice, which recognise human cells encoding hepatitis C virus (HCV) proteins
info:doi:10.1016/j.vaccine.2004.05.009
info:eu-repo/semantics/altIdentifier/doi/10.1016/j.vaccine.2004.05.009
info:eu-repo/semantics/altIdentifier/pmid/15519708
Engler, O. B.
Schwendener, R. A.
Dai, W. J.
Wolk, B.
Pichler, W.
Moradpour, D.
Brunner, T.
Cerny, A.
info:eu-repo/semantics/article
article
2004-11
Vaccine, vol. 23, no. 1, pp. 58-68
info:eu-repo/semantics/altIdentifier/pissn/0264-410X
<![CDATA[Virus specific T cell responses play an important role in resolving acute hepatitis C virus (HCV) infections. Using the HLA-A2.1 transgenic mouse model we investigated the potential of a liposomal peptide vaccine to prime a CD8(+) T cell response against 10 different HCV epitopes, relevant for human applications. We were able to demonstrate the induction of strong cytotoxic T cell responses and high numbers of IFN-gamma-secreting cells, which persisted at high levels for at least 3 months. Co-integrating CpG oligonucleotides into liposomes further increased the number of IFN-gamma-secreting cells by 2-10-fold for most epitopes tested. The frequency of specific cells was further analysed with chimeric A2 tetramers bearing the NS31073-1081 epitope and was estimated at 2-23% of the CD8(+) T cell population. Importantly, mouse effector cells, specific for this epitope, were also capable of lysing a human target cell line expressing HCV proteins. This finding and the specific protection observed in challenge experiments with recombinant vaccinia virus expressing HCV sequences emphasise the biological relevance of the vaccine-induced immune response. In conclusion, such liposome formulations represent a safe and promising strategy to stimulate the CD8(+) T cell against HCV
Structural order in plasmonic superlattices
The assembly of plasmonic nanoparticles into ordered 2D- and 3D-superlattices could pave the way towards new tailored materials for plasmonic sensing, photocatalysis and manipulation of light on the nanoscale. The properties of such materials strongly depend on their geometry, and accordingly straightforward protocols to obtain precise plasmonic superlattices are highly desirable. Here, we synthesize large areas of crystalline mono-, bi- and multilayers of gold nanoparticles >20nm with a small number of defects. The superlattices can be described as hexagonal crystals with standard deviations of the lattice parameter below 1%. The periodic arrangement within the superlattices leads to new well-defined collective plasmon-polariton modes. The general level of achieved superlattice quality will be of benefit for a broad range of applications, ranging from fundamental studies of light-matter interaction to optical metamaterials and substrates for surface-enhanced spectroscopies. Superlattices of nanoparticles promise new properties emerging from the periodic order. Here, the authors describe the synthesis of superlattices of plasmonic gold nanoparticles with high crystallinity and demonstrate how new plasmon-polariton modes appear in the structures
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