Characterization of human mesenchymal stem cells from Ewing sarcoma patients. Pathogenetic implications

Ewing Sarcoma (EWS) is a mesenchymal-derived tumor that generally arises in bone and soft tissue. Intensive research regarding the pathogenesis of EWS has been insufficient to pinpoint the early events of Ewing sarcomagenesis. However, the Mesenchymal Stem Cell (MSC) is currently accepted as the most probable cell of origin

Controller-observer design and dynamic parameter identification for model-based control of an electromechanical lower-limb rehabilitation system

[EN] Rehabilitation is a hazardous task for a mechanical system, since the device has to interact with the human extremities without the hands-on experience the physiotherapist acquires over time. A gap needs to be filled in terms of designing effective controllers for this type of devices. In this respect, the paper describes the design of a model-based control for an electromechanical lower-limb rehabilitation system based on a parallel kinematic mechanism. A controller-observer was designed for estimating joint velocities, which are then used in a hybrid position/force control scheme. The model parameters are identified by customising an approach based on identifying only the relevant system dynamics parameters. Findings obtained through simulations show evidence of improvement in tracking performance compared with those where the velocity was estimated by numerical differentiation. The controller is also implemented in an actual electromechanical system for lower-limb rehabilitation tasks. Findings based on rehabilitation tasks confirm the findings from simulations.This work was partially financed by the Plan Nacional de I+D, Comision Interministerial de Ciencia y Tecnologia (FEDERCICYT) under the project DPI2013-44227-R and by the Instituto U. de Automatica e Informatica Industrial (ai2) of the Universitat Politecnica de Valencia.Valera Fernández, Á.; Díaz-Rodríguez, M.; Vallés Miquel, M.; Oliver, E.; Mata Amela, V.; Page Del Pozo, AF. (2017). Controller-observer design and dynamic parameter identification for model-based control of an electromechanical lower-limb rehabilitation system. International Journal of Control. 90(4):702-714. https://doi.org/10.1080/00207179.2016.1215529S702714904Åström, K. J., & Murray, R. M. (2010). Feedback Systems. doi:10.2307/j.ctvcm4gdkAtkeson, C. G., An, C. H., & Hollerbach, J. M. (1986). 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Robotics and Computer-Integrated Manufacturing, 30(5), 468-477. doi:10.1016/j.rcim.2014.02.003De Jalon, J.G. & Bayo, E. (1994). Kinematic and dynamic simulation of multibody systems: the real-time challenge. New York: Springer Verlag.Díaz, I., Gil, J. J., & Sánchez, E. (2011). Lower-Limb Robotic Rehabilitation: Literature Review and Challenges. Journal of Robotics, 2011, 1-11. doi:10.1155/2011/759764Díaz-Rodríguez, M., Iriarte, X., Mata, V., & Ros, J. (2009). On the Experiment Design for Direct Dynamic Parameter Identification of Parallel Robots. Advanced Robotics, 23(3), 329-348. doi:10.1163/156855308x397550Díaz-Rodríguez, M., Mata, V., Valera, Á., & Page, Á. (2010). A methodology for dynamic parameters identification of 3-DOF parallel robots in terms of relevant parameters. Mechanism and Machine Theory, 45(9), 1337-1356. doi:10.1016/j.mechmachtheory.2010.04.007Gautier, M. (1991). Numerical calculation of the base inertial parameters of robots. Journal of Robotic Systems, 8(4), 485-506. doi:10.1002/rob.4620080405Gautier, M., & Khalil, W. (s. f.). On the identification of the inertial parameters of robots. Proceedings of the 27th IEEE Conference on Decision and Control. doi:10.1109/cdc.1988.194738Jamwal, P. K., Hussain, S., & Xie, S. Q. (2013). Review on design and control aspects of ankle rehabilitation robots. Disability and Rehabilitation: Assistive Technology, 10(2), 93-101. doi:10.3109/17483107.2013.866986Janabi-Sharifi, F., Hayward, V., & Chen, C.-S. J. (2000). Discrete-time adaptive windowing for velocity estimation. IEEE Transactions on Control Systems Technology, 8(6), 1003-1009. doi:10.1109/87.880606Janot, A., Gautier, M., Jubien, A., & Vandanjon, P. O. (2014). Comparison Between the CLOE Method and the DIDIM Method for Robots Identification. IEEE Transactions on Control Systems Technology, 22(5), 1935-1941. doi:10.1109/tcst.2014.2299544Janot, A., Vandanjon, P.-O., & Gautier, M. (2016). A revised Durbin-Wu-Hausman test for industrial robot identification. Control Engineering Practice, 48, 52-62. doi:10.1016/j.conengprac.2015.12.017Jiménez-Fabián, R., & Verlinden, O. (2012). Review of control algorithms for robotic ankle systems in lower-limb orthoses, prostheses, and exoskeletons. Medical Engineering & Physics, 34(4), 397-408. doi:10.1016/j.medengphy.2011.11.018Khalil, W., Vijayalingam, A., Khomutenko, B., Mukhanov, I., Lemoine, P., & Ecorchard, G. (2014). OpenSYMORO: An open-source software package for symbolic modelling of robots. 2014 IEEE/ASME International Conference on Advanced Intelligent Mechatronics. doi:10.1109/aim.2014.6878246Marchal-Crespo, L., & Reinkensmeyer, D. J. (2009). Review of control strategies for robotic movement training after neurologic injury. Journal of NeuroEngineering and Rehabilitation, 6(1). doi:10.1186/1743-0003-6-20Meng, W., Liu, Q., Zhou, Z., Ai, Q., Sheng, B., & Xie, S. (Shane). (2015). Recent development of mechanisms and control strategies for robot-assisted lower limb rehabilitation. Mechatronics, 31, 132-145. doi:10.1016/j.mechatronics.2015.04.005Page, A., Candelas, P., & Belmar, F. (2006). On the use of local fitting techniques for the analysis of physical dynamic systems. European Journal of Physics, 27(2), 273-279. doi:10.1088/0143-0807/27/2/010Raibert, M. H., & Craig, J. J. (1981). Hybrid Position/Force Control of Manipulators. Journal of Dynamic Systems, Measurement, and Control, 103(2), 126-133. doi:10.1115/1.3139652Ramsay, J. O., & Silverman, B. W. (2005). Functional Data Analysis. Springer Series in Statistics. doi:10.1007/b98888Saglia, J. A., Tsagarakis, N. G., Dai, J. S., & Caldwell, D. G. (2013). Control Strategies for Patient-Assisted Training Using the Ankle Rehabilitation Robot (ARBOT). IEEE/ASME Transactions on Mechatronics, 18(6), 1799-1808. doi:10.1109/tmech.2012.2214228Vallés, M., Cazalilla, J., Valera, Á., Mata, V., Page, Á., & Díaz-Rodríguez, M. (2015). A 3-PRS parallel manipulator for ankle rehabilitation: towards a low-cost robotic rehabilitation. Robotica, 35(10), 1939-1957. doi:10.1017/s0263574715000120Vallés, M., Cazalilla, J. I., Valera, Á., Mata, V., & Page, Á. (2013). Implementación basada en el middleware OROCOS de controladores dinámicos pasivos para un robot paralelo. Revista Iberoamericana de Automática e Informática Industrial RIAI, 10(1), 96-103. doi:10.1016/j.riai.2012.11.009Vallés, M., Díaz-Rodríguez, M., Valera, Á., Mata, V., & Page, Á. (2012). Mechatronic Development and Dynamic Control of a 3-DOF Parallel Manipulator. Mechanics Based Design of Structures and Machines, 40(4), 434-452. doi:10.1080/15397734.2012.687292Wu, F. X., Zhang, W. J., Li, Q., & Ouyang, P. R. (2002). Integrated Design and PD Control of High-Speed Closed-loop Mechanisms. 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First Sagittarius A* Event Horizon Telescope results. I. The shadow of the supermassive black hole in the center of the Milky Way

Galaxie

Immunophenotype and CD99 Expression Patterns of Human Mesenchymal Stem Cells and Their Implication in Ewing Sarcoma Genesis, Biology and Treatment

Transplantation and immunomodulatio

Some complexity aspects of secondary school timetabling problems

We consider timetabling problems of secondary schools, in which the students can choose their own curricula. Besides finding a time slot and classroom assignment, every student must be assigned to a subject group for each subject in his curriculum. This problem is NP-hard for several independent reasons. In this paper we investigate the borderline between "easy" and "hard" subproblems. In particular, we show that the addition of blocks of size two,i.e. two lessons to be taught at consecutive time slots,or the addition of a constraint on the subject group size changes a subproblem from polynomially solvable to NP-hard