Active disturbance rejection control: a guide for design and application

[EN] This tutorial addresses the design of controllers by active disturbance rejection control (ADRC). First, the main blocks in the ADRC loop are described. Next, the formulation of the control problem under the disturbance rejection framework is discussed, as well as the tuning of the gains set which are part of the main loop and a guide on designing of the active disturbance rejection controller is presented. This tutorial aims to offer an introduction to readers about the ADRC and a review of the most significant publications that have contributed to development and advance in the research related to the area. To illustrate the design procedure, two examples are included: thermal control and the multivariable control of a chemical process.[ES] Este tutorial aborda el diseño de controladores lineales por rechazo activo de perturbaciones (ADRC). Se inicia con la descripción de los bloques que componen el lazo ADRC. Seguidamente, se discute la formulación del problema de control en el marco del rechazo de perturbaciones, la sintonización del conjunto de ganancias que hacen parte del lazo y se presenta una guía general para el diseño del controlador lineal por rechazo activo de perturbaciones. Con este tutorial se pretende ofrecer una introducción a los lectores sobre el ADRC y una reseña de los trabajos que indican las tendencias de investigación en el área. Para ilustrar el procedimiento de diseño, se incluyen dos ejemplos: el control de un proceso térmico y el control multivariable de un proceso químico.Martínez, B.; Sanchis, J.; García-Nieto, S.; Martínez, M. (2021). Control por rechazo activo de perturbaciones: guía de diseño y aplicación. Revista Iberoamericana de Automática e Informática industrial. 18(3):201-217. https://doi.org/10.4995/riai.2020.14058OJS201217183Ahi, B., Haeri, M., 2018. Linear active disturbance rejection control from the practical aspects. IEEE/ASME Transactions on Mechatronics 23 (6), 2909-2919. https://doi.org/10.1109/tmech.2018.2871880Ahmad, S., Ali, A., 2019. Active disturbance rejection control of DC-DC boost converter: a review with modifications for improved performance. IET Power Electronics 12 (8), 2095-2107. https://doi.org/10.1049/iet-pel.2018.5767Albertos, P., Garcia, P., Gao, Z., Liu, T., 2014. Disturbance rejection in process control. In: Proceeding of the 11th World Congress on Intelligent Control and Automation. IEEE. https://doi.org/10.1109/wcica.2014.7053408Baquero-Suarez, M., Cortes-Romero, J., Arcos-Legarda, J., Coral-Enriquez, H., 2018. Estabilización automática de una bicicleta sin conductor mediante el enfoque de control por rechazo activo de perturbaciones. Revista Iberoamericana de Automática e Informática industrial 15 (1), 86-100. https://doi.org/10.4995/riai.2017.8832Castillo, A., García, P., Sanz, R., Albertos, P., 2018. Enhanced extended state observer-based control for systems with mismatched uncertainties and disturbances. ISA Transactions 73, 1-10. https://doi.org/10.1016/j.isatra.2017.12.005Chen, W.-H., Yang, J., Guo, L., Li, S., 2016. Disturbance-observer-based control and related methods-an overview. IEEE Transactions on Industrial Electronics 63 (2), 1083-1095. https://doi.org/10.1109/tie.2015.2478397Cheng, Y., Chen, Z., Sun, M., Sun, Q., Aug. 2019. Active disturbance rejection generalized predictive control for a high purity distillation column process with time delay. The Canadian Journal of Chemical Engineering 97 (11), 2941-2951. https://doi.org/10.1002/cjce.23513Chu, Z.,Wu, C., Sepehri, N., 2019. Active disturbance rejection control applied to high-order systems with parametric uncertainties. International Journal of Control, Automation and Systems 17 (6), 1483-1493. https://doi.org/10.1007/s12555-018-0509-8Feng, H., Guo, B.-Z., 2017. Active disturbance rejection control: Old and new results. Annual Reviews in Control 44, 238-248. https://doi.org/10.1016/j.arcontrol.2017.05.003Fu, C., Tan, W., 2016. Tuning of linear ADRC with known plant information. ISA Transactions 65, 384-393. https://doi.org/10.1016/j.isatra.2016.06.016Gao, Z., 2003. Scaling and bandwidth-parameterization based controller tuning. In: Proceedings of the 2003 American Control Conference, 2003. IEEE. https://doi.org/10.1109/acc.2003.1242516Gao, Z., 2014. On the centrality of disturbance rejection in automatic control. ISA Transactions 53 (4), 850-857. https://doi.org/10.1016/j.isatra.2013.09.012Guerrero-Ramírez, E. O., Martínez-Barbosa, A., Ramírez, E.-G., Linares-Flores, J., Sira-Ramírez, H., 2018. Control del convertidor CD/CD reductor-paralelo implementado en FPGA. Revista Iberoamericana de Automática e Informática industrial 15 (3), 309-316. https://doi.org/10.4995/riai.2018.8925Guo, B.-Z., Zhao, Z.-L., 2016. Active Disturbance Rejection Control for Nonlinear Systems. John Wiley & Sons Singapore Pte. Ltd. https://doi.org/10.1002/9781119239932Han, J., 2009. From PID to active disturbance rejection control. IEEE Transactions on Industrial Electronics 56 (3), 900-906. https://doi.org/10.1109/tie.2008.2011621He, T., Wu, Z., Li, D., Wang, J., 2020. A tuning method of active disturbance rejection control for a class of high-order processes. IEEE Transactions on Industrial Electronics 67 (4), 3191-3201. https://doi.org/10.1109/tie.2019.2908592Herbst, G., 2013. A simulative study on active disturbance rejection control (ADRC) as a control tool for practitioners. Electronics 2 (4), 246-279. https://doi.org/10.3390/electronics2030246Herbst, G., 2016. Practical active disturbance rejection control: Bumpless transfer, rate limitation, and incremental algorithm. IEEE Transactions on Industrial Electronics 63 (3), 1754-1762. https://doi.org/10.1109/tie.2015.2499168Huang, C., Du, B., 2016. Dierentially flatness active disturbance rejection control approach via algebraic parameter identification to double tank problem. In: 2016 35th Chinese Control Conference (CCC). IEEE. https://doi.org/10.1109/chicc.2016.7553678Huang, Y., Xue, W., 2014. Active disturbance rejection control: Methodology and theoretical analysis. ISA Transactions 53 (4), 963-976. https://doi.org/10.1016/j.isatra.2014.03.003Huilcapi, V., Herrero, J. M., Blasco, X., Martínez-Iranzo, M., 2017. Non-linear identification of a peltier cell model using evolutionary multi-objective optimization. IFAC-PapersOnLine 50 (1), 4448-4453. https://doi.org/10.1016/j.ifacol.2017.08.372Inoue, S., Ishida, Y., 2016. Design of a model-following controller using a decoupling active disturbance rejection control method. Journal of Electrical & Electronic Systems 05 (01). https://doi.org/10.4172/2332-0796.1000174Li, D., Chen, X., Zhang, J., Jin, Q., 2020. On parameter stability region of LADRC for time-delay analysis with a coupled tank application. Processes 8 (2), 223. https://doi.org/10.3390/pr8020223Li, J., Qi, X. H., Wan, H., Xia, Y. Q., 2017a. Active disturbance rejection control: theoretical results summary and future researches. Kongzhi Lilun Yu Yingyong/Control Theory and Applications 34, 281-295. https://doi.org/10.7641/CTA.2017.60363Li, J., Xia, Y., Qi, X., Gao, Z., 2017b. On the necessity, scheme, and basis of the linear-nonlinear switching in active disturbance rejection control. IEEE Transactions on Industrial Electronics 64 (2), 1425-1435. https://doi.org/10.1109/tie.2016.2611573Li, S., Yang, J., Chen,W.-H., Chen, X., 2012. Generalized extended state observer based control for systems with mismatched uncertainties. IEEE Transactions on Industrial Electronics 59 (12), 4792-4802. https://doi.org/10.1109/tie.2011.2182011Liang, Q., Wang, C. B., Pan, J. W., Wei, Y. H., Wang, Y., 2015. Parameter identification of b0 and parameter tuning law in linear active disturbance rejection control. Kongzhi yu Juece/Control and Decision 30, 1691-1695. https://doi.org/10.13195/j.kzyjc.2014.0943Luyben, W. L., 1990. Process Modeling, Simulation, and Control for Chemical Engineers. McGraw-Hill.Madonski, R., Gao, Z., Lakomy, K., 2015. Towards a turnkey solution of industrial control under the active disturbance rejection paradigm. In: 2015 54th Annual Conference of the Society of Instrument and Control Engineers of Japan (SICE). IEEE. https://doi.org/10.1109/sice.2015.7285478Madonski, R., Piosik, A., Herman, P., 2013. High-gain disturbance observer tuning seen as a multicriteria optimization problem. In: 21st Mediterranean Conference on Control and Automation. IEEE. https://doi.org/10.1109/med.2013.6608905Madonski, R., Shao, S., Zhang, H., Gao, Z., Yang, J., Li, S., 2019. General error-based active disturbance rejection control for swift industrial implementations. Control Engineering Practice 84, 218-229. https://doi.org/10.1016/j.conengprac.2018.11.021Marlin, T., 2000. Process Control: Designing Processes and Control Systems for Dynamic Performance. McGraw-Hill.Martínez, B. V., Jul 2020. Active Disturbance Rejection Control-implementation examples. Version 1.0.0. url: https://www.mathworks.com/matlabcentral/fileexchange/78459.Maxim, A., Copot, D., Copot, C., Ionescu, C. M., 2019. The 5w's for control as part of industry 4.0: Why, what, where, who, and when-a PID and MPC control perspective. Inventions 4 (1), 10. https://doi.org/10.3390/inventions4010010Nowicki, M., Madonski, R., Kozlowski, K., 2015. First look at conditions on applicability of ADRC. In: 2015 10th International Workshop on Robot Motion and Control (RoMoCo). IEEE. https://doi.org/10.1109/romoco.2015.7219750Parvathy, R., Daniel, A. E., 2013. A survey on active disturbance rejection control. In: 2013 International Mutli-Conference on Automation, Computing, Communication, Control and Compressed Sensing (iMac4s). IEEE. https://doi.org/10.1109/imac4s.2013.6526432Pérez-Polo, M., Albertos, P., 2007. Nonisothermal stirred-tank reactor with irreversible exothermic reaction a ! b: 2. nonlinear phenomena. In: Selected Topics in Dynamics and Control of Chemical and Biological Processes. Springer Berlin Heidelberg, pp. 243-279. https://doi.org/10.1007/978-3-540-73187_8Reynoso, G., Blasco, X., Sanchis, J., Herrero, J. M., 2017. Controller Tuning with Evolutionary Multiobjective Optimization. Springer International Publishing. https://doi.org/10.1007/978-3-319-41301-3Sanz, R., Garcia, P., Albertos, P., 2015. Active disturbance rejection by state feedback: Experimental validation in a 3-dof quadrotor platform. In: 2015 54th Annual Conference of the Society of Instrument and Control Engineers of Japan (SICE). pp. 794-799. https://doi.org/10.1109/SICE.2015.7285349Sira-Ramírez, H., 2018. From flatness, GPI observers, GPI control and flat filters to observer-based ADRC. Control Theory and Technology 16 (4), 249-260. https://doi.org/10.1007/s11768-018-8134-xSun, L., Li, D., Gao, Z., Yang, Z., Zhao, S., 2016. Combined feedforward and model-assisted active disturbance rejection control for non-minimum phase system. ISA Transactions 64, 24-33. https://doi.org/10.1016/j.isatra.2016.04.020Sun, L., Zhang, Y., Li, D., Lee, K. Y., 2019. Tuning of active disturbance rejection control with application to power plant furnace regulation. Control Engineering Practice 92, 104122. https://doi.org/10.1016/j.conengprac.2019.104122Tan,W., Fu, C., 2016. Linear active disturbance-rejection control: Analysis and tuning via imc. IEEE Transactions on Industrial Electronics 63 (4), 2350-2359.Teppa-Garran, P., Garcia, G., 2014. ADRC tuning employing the LQR approach for decoupling uncertain MIMO systems. Information Technology And Control 43 (2). https://doi.org/10.5755/j01.itc.43.2.4059Wu, X., Chen, Z., Zhao, Y., Sun, L., Sun, M., 2018. A comprehensive decoupling control strategy for a gas flow facility based on active disturbance rejection generalized predictive control. The Canadian Journal of Chemical Engineering 97 (3), 762-776. https://doi.org/10.1002/cjce.23215Xue,W., Huang, Y., 2015. Performance analysis of active disturbance rejection tracking control for a class of uncertain LTI systems. ISA Transactions 58, 133-154. https://doi.org/10.1016/j.isatra.2015.05.001Xue, W., Huang, Y., Gao, Z., 2016. On ADRC for non-minimum phase systems: canonical form selection and stability conditions. Control Theory and Technology 14 (3), 199-208. https://doi.org/10.1007/s11768-016-6041-6Zhang, B., Tan, W., Li, J., 2019. Tuning of linear active disturbance rejection controller with robustness specification. ISA Transactions 85, 237-246. https://doi.org/10.1016/j.isatra.2018.10.018Zhao, C., Li, D., 2014. Control design for the SISO system with the unknown order and the unknown relative degree. ISA Transactions 53 (4), 858-872. https://doi.org/10.1016/j.isatra.2013.10.001Zhao, C., Li, D., Cui, J., Tian, L., 2018. Decentralized low-order ADRC design for MIMO system with unknown order and relative degree. Personal and Ubiquitous Computing 22 (5-6), 987-1004. https://doi.org/10.1007/s00779-018-1158-xZhao, S., Gao, Z., 2010. Active disturbance rejection control for non-minimum phase systems. In: Proceedings of the 29th Chinese Control Conference. pp. 6066-6070.Zhao, S., Gao, Z., 2014. Modified active disturbance rejection control for time delay systems. ISA Transactions 53 (4), 882-888. https://doi.org/10.1016/j.isatra.2013.09.013Zhao, S., Xue, W., Gao, Z., 2013. Achieving minimum settling time subject to undershoot constraint in systems with one or two real right half plane zeros. 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Three-dimensional geometric morphometrics of thorax-pelvis covariation and its potential for predicting the thorax morphology: A case study on Kebara 2 Neandertal

The skeletal torso is a complex structure of outstanding importance in understanding human body shape evolution, but reconstruction usually entails an element of subjectivity as researchers apply their own anatomical expertise to the process. Among different fossil reconstruction methods, 3D geometric morphometric techniques have been increasingly used in the last decades. Two-block partial least squares analysis has shown great potential for predicting missing elements by exploiting the covariation between two structures (blocks) in a reference sample: one block can be predicted from the other one based on the strength of covariation between blocks. The first aim of this study is to test whether this predictive approach can be used for predicting thorax morphologies from pelvis morphologies within adult Homo sapiens reference samples with known covariation between the thorax and the pelvis. The second aim is to apply this method to Kebara 2 Neandertal (Israel, ∼60 ka) to predict its thorax morphology using two different pelvis reconstructions as predictors. We measured 134 true landmarks, 720 curve semilandmarks, and 160 surface semilandmarks on 60 3D virtual torso models segmented from CT scans. We conducted three two-block partial least squares analyses between the thorax (block 1) and the pelvis (block 2) based on the H. sapiens reference samples after performing generalized Procrustes superimposition on each block separately. Comparisons of these predictions in full shape space by means of Procrustes distances show that the male-only predictive model yields the most reliable predictions within modern humans. In addition, Kebara 2 thorax predictions based on this model concur with the thorax morphology proposed for Neandertals. The method presented here does not aim to replace other techniques, but to rather complement them through quantitative prediction of a virtual 'scaffold' to articulate the thoracic fossil elements, thus extending the potential of missing data estimation beyond the methods proposed in previous works

Methodology based on genetic heuristics for in-vivo characterizing the patient-specific biomechanical behavior of the breast tissues

[EN] This paper presents a novel methodology to in-vivo estimate the elastic constants of a constitutive model proposed to characterize the mechanical behavior of the breast tissues. An iterative search algorithm based on genetic heuristics was constructed to in-vivo estimate these parameters using only medical images, thus avoiding invasive measurements of the mechanical response of the breast tissues. For the first time, a combination of overlap and distance coefficients were used for the evaluation of the similar- ity between a deformed MRI of the breast and a simulation of that deformation. The methodology was validated using breast software phantoms for virtual clinical trials, compressed to mimic MRI-guided biopsies. The biomechanical model chosen to characterize the breast tissues was an anisotropic neo-Hookean hyperelastic model. Results from this analysis showed that the algorithm is able to find the elastic constants of the constitutive equations of the proposed model with a mean relative error of about 10%. Furthermore, the overlap between the reference deformation and the simulated deformation was of around 95% showing the good performance of the proposed methodology. This methodology can be easily extended to characterize the real biomechanical behavior of the breast tissues, which means a great novelty in the field of the simulation of the breast behavior for applications such as surgical planing, surgical guidance or cancer diagnosis. This reveals the impact and relevance of the presented work.This project has been funded by MECD (reference AP2009-2414) and US National Institutes of Health (R01 Grant #CA154444), and the US National Science Foundation (III Grant #0916690). The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH, and NSF. The authors of this manuscript have no conflict of interest with the presented workLago, MA.; Rupérez Moreno, MJ.; Martínez Martínez, F.; Martinez-Sanchis, S.; Bakic, P.; Monserrat, C. (2015). Methodology based on genetic heuristics for in-vivo characterizing the patient-specific biomechanical behavior of the breast tissues. Expert Systems with Applications. 42(21):7942-7950. https://doi.org/10.1016/j.eswa.2015.05.058S79427950422

A framework for modelling the biomechanical behaviour of the human liver during breathing in real time using machine learning

Progress in biomechanical modelling of human soft tissue is the basis for the development of new clinical applications capable of improving the diagnosis and treatment of some diseases (e.g. cancer), as well as the surgical planning and guidance of some interventions. The finite element method (FEM) is one of the most popular techniques used to predict the deformation of the human soft tissue due to its high accuracy. However, FEM has an associated high computational cost, which makes it difficult its integration in real-time computer-aided surgery systems. An alternative for simulating the mechanical behaviour of human organs in real time comes from the use of machine learning (ML) techniques, which are much faster than FEM. This paper assesses the feasibility of ML methods for modelling the biomechanical behaviour of the human liver during the breathing process, which is crucial for guiding surgeons during interventions where it is critical to track this deformation (e.g. some specific kind of biopsies) or for the accurate application of radiotherapy dose to liver tumours. For this purpose, different ML regression models were investigated, including three tree-based methods (decision trees, random forests and extremely randomised trees) and other two simpler regression techniques (dummy model and linear regression). In order to build and validate the ML models, a labelled data set was constructed from modelling the deformation of eight ex-vivo human livers using FEM. The best prediction performance was obtained using extremely randomised trees, with a mean error of 0.07 mm and all the samples with an error under 1 mm. The achieved results lay the foundation for the future development of some real-time software capable of simulating the human liver deformation during the breathing process during clinical interventions.This work has been funded by the Spanish Ministry of Economy and Competitiveness (MINECO) through research projects TIN2014-52033-R and DPI2013-40859-R, both also supported by European FEDER funds. The authors acknowledge the kind collaboration of the personnel from the hospital involved in the research.Lorente, D.; Martínez-Martínez, F.; Rupérez Moreno, MJ.; Lago, MA.; Martínez-Sober, M.; Escandell-Montero, P.; Martínez-Martínez, JM.... (2017). A framework for modelling the biomechanical behaviour of the human liver during breathing in real time using machine learning. Expert Systems with Applications. 71:342-357. doi:10.1016/j.eswa.2016.11.037S3423577

Theoretical analysis of the focusing of acoustic waves by two-dimensional sonic crystals

Motivated by a recent experiment on acoustic lenses, we perform numerical calculations based on a multiple scattering technique to investigate the focusing of acoustic waves with sonic crystals formed by rigid cylinders in air. The focusing effects for crystals of various shapes are examined. The dependance of the focusing length on the filling factor is also studied. It is observed that both the shape and filling factor play a crucial role in controlling the focusing. Furthermore, the robustness of the focusing against disorders is studied. The results show that the sensitivity of the focusing behavior depends on the strength of positional disorders. The theoretical results compare favorably with the experimental observations, reported by Cervera, et al. (Phys. Rev. Lett. 88, 023902 (2002)).Comment: 8 figure

Interactive translation prediction versus conventional post-editing in practice: a study with the CasMaCat workbench

[EN] We conducted a field trial in computer-assisted professional translation to compare interactive translation prediction (ITP) against conventional post-editing (PE) of machine translation (MT) output. In contrast to the conventional PE set-up, where an MT system first produces a static translation hypothesis that is then edited by a professional (hence "post-editing"), ITP constantly updates the translation hypothesis in real time in response to user edits. Our study involved nine professional translators and four reviewers working with the web-based CasMaCat workbench. Various new interactive features aiming to assist the post-editor/translator were also tested in this trial. Our results show that even with little training, ITP can be as productive as conventional PE in terms of the total time required to produce the final translation. Moreover, translation editors working with ITP require fewer key strokes to arrive at the final version of their translation.This work was supported by the European Union’s 7th Framework Programme (FP7/2007–2013) under grant agreement No 287576 (CasMaCat ).Sanchis Trilles, G.; Alabau, V.; Buck, C.; Carl, M.; Casacuberta Nolla, F.; Garcia Martinez, MM.; Germann, U.... (2014). Interactive translation prediction versus conventional post-editing in practice: a study with the CasMaCat workbench. Machine Translation. 28(3-4):217-235. https://doi.org/10.1007/s10590-014-9157-9S217235283-4Alabau V, Leiva LA, Ortiz-Martínez D, Casacuberta F (2012) User evaluation of interactive machine translation systems. In: Proceedings of the 16th Annual Conference of the European Association for Machine Translation, pp 20–23Alabau V, Buck C, Carl M, Casacuberta F, García-Martínez M, Germann U, González-Rubio J, Hill R, Koehn P, Leiva L, Mesa-Lao B, Ortiz-Martínez D, Saint-Amand H, Sanchis-Trilles G, Tsoukala C (2014) Casmacat: A computer-assisted translation workbench. In: Proceedings of the 14th Conference of the European Chapter of the Association for Computational Linguistics, pp 25–28Alves F, Vale D (2009) Probing the unit of translation in time: aspects of the design and development of a web application for storing, annotating, and querying translation process data. Across Lang Cultures 10(2):251–273Bach N, Huang F, Al-Onaizan Y (2011) Goodness: A method for measuring machine translation confidence. In: Proceedings of the Annual Meeting of the Association for Computational Linguistics, pp 211–219Barrachina S, Bender O, Casacuberta F, Civera J, Cubel E, Khadivi S, Lagarda AL, Ney H, Tomás J, Vidal E, Vilar JM (2009) Statistical approaches to computer-assisted translation. Comput Linguist 35(1):3–28Brown PF, Della Pietra SA, Della Pietra VJ (1993) The mathematics of statistical machine translation: parameter estimation. Comput Linguist 19(2):263–311Callison-Burch C, Koehn P, Monz C, Post M, Soricut R, Specia L (2012) Findings of the 2012 workshop on statistical machine translation. In: Proceedings of the Seventh Workshop on Statistical Machine Translation, pp 10–51Carl M (2012a) The CRITT TPR-DB 1.0: A database for empirical human translation process research. In: Proceedings of the AMTA 2012 Workshop on Post-Editing Technology and Practice, pp 1–10Carl M (2012b) Translog-II: a program for recording user activity data for empirical reading and writing research. In: Proceedings of the Eighth International Conference on Language Resources and Evaluation, pp 4108–4112Carl M (2014) Produkt- und Prozesseinheiten in der CRITT Translation Process Research Database. In: Ahrens B (ed) Translationswissenschaftliches Kolloquium III: Beiträge zur Übersetzungs- und Dolmetschwissenschaft (Köln/Germersheim). Peter Lang, Frankfurt am Main, pp 247–266Carl M, Kay M (2011) Gazing and typing activities during translation : a comparative study of translation units of professional and student translators. Meta 56(4):952–975Doherty S, O’Brien S, Carl M (2010) Eye tracking as an MT evaluation technique. Mach Transl 24(1):1–13Elming J, Carl M, Balling LW (2014) Investigating user behaviour in post-editing and translation using the Casmacat workbench. In: O’Brien S, Winther Balling L, Carl M, Simard M, Specia L (eds) Post-editing of machine translation: processes and applications. Cambridge Scholar Publishing, Newcastle upon Tyne, pp 147–169Federico M, Cattelan A, Trombetti M (2012) Measuring user productivity in machine translation enhanced computer assisted translation. In: Proceedings of the Tenth Biennial Conference of the Association for Machine Translation in the AmericasFlournoy R, Duran C (2009) Machine translation and document localization at adobe: From pilot to production. In: Proceedings of MT Summit XIIGreen S, Heer J, Manning CD (2013) The efficacy of human post-editing for language translation. In: Proceedings of SIGCHI Conference on Human Factors in Computing Systems, pp 439–448Guerberof A (2009) Productivity and quality in mt post-editing. In: Proceedings of MT Summit XII-Workshop: Beyond Translation Memories: New Tools for Translators MTGuerberof A (2012) Productivity and quality in the post-editing of outputs from translation memories and machine translation. Ph.D. ThesisJust MA, Carpenter PA (1980) A theory of reading: from eye fixations to comprehension. Psychol Rev 87(4):329Koehn P (2009a) A process study of computer-aided translation. Mach Transl 23(4):241–263Koehn P (2009b) A web-based interactive computer aided translation tool. In: Proceedings of ACL-IJCNLP 2009 Software Demonstrations, pp 17–20Krings HP (2001) Repairing texts: empirical investigations of machine translation post-editing processes, vol 5. Kent State University Press, KentLacruz I, Shreve GM, Angelone E (2012) Average pause ratio as an indicator of cognitive effort in post-editing: a case study. In: Proceedings of the AMTA 2012 Workshop on Post-Editing Technology and Practice, pp 21–30Langlais P, Foster G, Lapalme G (2000) Transtype: A computer-aided translation typing system. In: Proceedings of the 2000 NAACL-ANLP Workshop on Embedded Machine Translation Systems, pp 46–51Leiva LA, Alabau V, Vidal E (2013) Error-proof, high-performance, and context-aware gestures for interactive text edition. In: Proceedings of the 2013 annual conference extended abstracts on Human factors in computing systems, pp 1227–1232Montgomery D (2004) Introduction to statistical quality control. Wiley, HobokenO’Brien S (2009) Eye tracking in translation process research: methodological challenges and solutions, Copenhagen Studies in Language, vol 38. Samfundslitteratur, Copenhagen, pp 251–266Ortiz-Martínez D, Casacuberta F (2014) The new Thot toolkit for fully automatic and interactive statistical machine translation. In: Proceedings of the 14th Annual Meeting of the European Association for Computational Linguistics: System Demonstrations, pp 45–48Plitt M, Masselot F (2010) A productivity test of statistical machine translation post-editing in a typical localisation context. Prague Bulletin Math Linguist 93(1):7–16Sanchis-Trilles G, Ortiz-Martínez D, Civera J, Casacuberta F, Vidal E, Hoang H (2008) Improving interactive machine translation via mouse actions. In: Proceedings of the Conference on Empirical Methods in Natural Language Processing, pp 485–494Simard M, Foster G (2013) Pepr: Post-edit propagation using phrase-based statistical machine translation. In: Proceedings of MT Summit XIV, pp 191–198Skadiņš R, Puriņš M, Skadiņa I, Vasiļjevs A (2011) Evaluation of SMT in localization to under-resourced inflected language. In: Proceedings of the 15th International Conference of the European Association for Machine Translation, pp 35–4

Grip strength predicts cardiac adverse events in patients with cardiac disorders: an individual patient pooled meta-analysis

Objective: Grip strength is a well-characterised measure of weakness and of poor muscle performance, but there is a lack of consensus on its prognostic implications in terms of cardiac adverse events in patients with cardiac disorders. Methods: Articles were searched in PubMed, Cochrane Library, BioMed Central and EMBASE. The main inclusion criteria were patients with cardiac disorders (ischaemic heart disease, heart failure (HF), cardiomyopathies, valvulopathies, arrhythmias); evaluation of grip strength by handheld dynamometer; and relation between grip strength and outcomes. The endpoints of the study were cardiac death, all-cause mortality, hospital admission for HF, cerebrovascular accident (CVA) and myocardial infarction (MI). Data of interest were retrieved from the articles and after contact with authors, and then pooled in an individual patient meta-analysis. Univariate and multivariate logistic regression was performed to define predictors of outcomes. Results: Overall, 23 480 patients were included from 7 studies. The mean age was 62.3±6.9 years and 70% were male. The mean follow-up was 2.82±1.7 years. After multivariate analysis grip strength (difference of 5 kg, 5× kg) emerged as an independent predictor of cardiac death (OR 0.84, 95% CI 0.79 to 0.89, p<0.0001), all-cause death (OR 0.87, 95% CI 0.85 to 0.89, p<0.0001) and hospital admission for HF (OR 0.88, 95% CI 0.84 to 0.92, p<0.0001). On the contrary, we did not find any relationship between grip strength and occurrence of MI or CVA. Conclusion: In patients with cardiac disorders, grip strength predicted cardiac death, all-cause death and hospital admission for HF. Trial registration number: CRD42015025280

Síndromes muy poco frecuentes.

Dismorfología, Citogenética y Clínica: Resultados de estudios sobre los datos del ECEMCAs in previous years, six new syndromes have been selected to be included in this section, aimed to make easier the recognition of syndromes with low-frequency by paediatricians and first health care physicians, particularly those of rural areas. In this Boletín, the following syndromes are included: Megalencephaly-Cutis Marmorata Telangiectatica Congenita syndrome, Van der Woude syndrome, Hay Wells syndrome, Zellweger syndrome, Jeune syndrome and Laurin-Sandrow syndrome. For each syndrome, the most important clinical characteristics, and the present knowledge on their causal factors and mechanisms involved are sumarized.N

Riverhood: political ecologies of socionature commoning and translocal struggles for water justice

Mega-damming, pollution and depletion endanger rivers worldwide. Meanwhile, modernist imaginaries of ordering ‘unruly waters and humans’ have become cornerstones of hydraulic-bureaucratic and capitalist development. They separate hydro/social worlds, sideline river-commons cultures, and deepen socio-environmental injustices. But myriad new water justice movements (NWJMs) proliferate: rooted, disruptive, transdisciplinary, multi-scalar coalitions that deploy alternative river–society ontologies, bridge South–North divides, and translate river-enlivening practices from local to global and vice-versa. This paper's framework conceptualizes ‘riverhood’ to engage with NWJMs and river commoning initiatives. We suggest four interrelated ontologies, situating river socionatures as arenas of material, social and symbolic co-production: ‘river-as-ecosociety’, ‘river-as-territory’, ‘river-as-subject’, and ‘river-as-movement’