A standardized framework for accurate, high-throughput genotyping of recombinant and non-recombinant viral sequences

Human immunodeficiency virus type-1 (HIV-1), hepatitis B and C and other rapidly evolving viruses are characterized by extremely high levels of genetic diversity. To facilitate diagnosis and the development of prevention and treatment strategies that efficiently target the diversity of these viruses, and other pathogens such as human T-lymphotropic virus type-1 (HTLV-1), human herpes virus type-8 (HHV8) and human papillomavirus (HPV), we developed a rapid high-throughput-genotyping system. The method involves the alignment of a query sequence with a carefully selected set of pre-defined reference strains, followed by phylogenetic analysis of multiple overlapping segments of the alignment using a sliding window. Each segment of the query sequence is assigned the genotype and sub-genotype of the reference strain with the highest bootstrap (>70%) and bootscanning (>90%) scores. Results from all windows are combined and displayed graphically using color-coded genotypes. The new Virus-Genotyping Tools provide accurate classification of recombinant and non-recombinant viruses and are currently being assessed for their diagnostic utility. They have incorporated into several HIV drug resistance algorithms including the Stanford (http://hivdb.stanford.edu) and two European databases (http://www.umcutrecht.nl/subsite/spread-programme/ and http://www.hivrdb.org.uk/) and have been successfully used to genotype a large number of sequences in these and other databases. The tools are a PHP/JAVA web application and are freely accessible on a number of servers including

Experimentele identificatie van robotdynamica

status: publishe

Improving the dynamic accuracy of industrial robots by trajectory pre-compensation

This paper presents a method to improve the path tracking accuracy of an industrial robot without replacing the standard industrial controller. By calculating off-line an appropriate trajectory pre-compensation, the effects of the nonlinear dynamics are compensated. This is realized by filtering the desired trajectory with the inverse dynamic model of the robot and its velocity controller. This compensation is applied as a velocity feed-forward in the standard industrial controller avoiding the need for a torque control interface. The presented method is experimentally validated on a KUKA IR 361 industrial robot. The results show clearly improved path tracking accuracy on circular trajectories.status: publishe

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This paper considers the practical implementation of a new maximum likelihood robot identification method, developed by Olsen and Petersen. In particular, the practical issue concerning the estimation of the joint velocities and accelerations from joint angle measurements, and its consequence on the parameter estimation and accuracy, is considered. Simulation and experimental results on a KUKA IR 361 industrial robot are discussed, and compared with models obtained using a much simpler weighted least squares method. KEY WORDS—excitation trajectories, weighted least squares, maximum likelihood, robot dynamics 1

Setting priorities in Healthcare. Investing in the right innovations at the right time

This white paper explores the current situation in the healthcare sector – and where it could be in the future. It outlines how we can make our health organisations more innovative – and crucially, how we can decide which ideas are worth investing in

Maximum likelihood identification of a dynamic robot model: implementation issues

This paper considers the practical implementation of a new maximum likelihood robot identification method, developed by Olsen and Petersen. In particular, the practical issue concerning the estimation of the joint velocities and accelerations from joint angle measurements, and its consequence on the parameter estimation and accuracy, is considered. Simulation and experimental results on a KUKA IR 361 industrial robot are discussed, and compared with models obtained using a much simpler weighted least squares method.status: publishe

Dynamic model identification for industrial robots - Integrated experiment design and parameter estimation

status: publishe

Iterative optimization of parameterized trajectories for complex mechatronic systems

status: publishe

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In this paper, we discuss a new experimental robot load identification method that is used in industry. The method is based on periodic robot excitation and the maximum likelihood estimation of the parameters, techniques adopted from Swevers et al. (1997 IEEE Transactions on Robotics and Automation 13(5):730–740). This method provides: (1) accurate estimates of the robot load inertial parameters; and (2) accurate actuator torque predictions. These are both essential for the acceptance of the results in an industrial environment. The key element to the success of this method is the comprehensiveness of the applied model, which includes, besides the dynamics resulting from the robot load and motor inertia, the coupling between the actuator torques, the mechanical losses in the motors and the efficiency of the transmissions. Accurate estimates of the robot link and motor inertial parameters, which can be considered identical for all robots o

Thrombotic microangiopathy after traumatic brain injury: A case report and review of the literature

Key Clinical Message This case report supports that trauma can rarely cause thrombotic microangiopathy (TMA). Early recognition is important due to a high mortality of untreated TMA, but diagnosis can be delayed by attributing lab abnormalities as due to blood loss. Abstract Major trauma can provoke coagulopathy, ranging from hypo‐ to hypercoagulation. Thrombotic microangiopathy (TMA), characterized by hemolytic anemia, renal failure, thrombocytopenia, and intravascular hemolysis, results in bleeding tendency but also microvascular thrombosis. We report a rare case of isolated traumatic brain injury leading to TMA treated with plasmapheresis