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    Bacillus subtilis EA-CB0575 genome reveals clues for plant growth promotion and potential for sustainable agriculture
    (Springer, 2020-01-01) Franco-Sierra, N.D.; Posada, L.F.; Santa-María, G.; Romero-Tabarez, M.; Villegas-Escobar, V.; Álvarez, J.C.; Universidad EAFIT. Departamento de Ciencias; Biodiversidad, Evolución y Conservación
    Bacillus subtilis is a remarkably diverse bacterial species that displays many ecological functions. Given its genomic diversity, the strain Bacillus subtilis EA-CB0575, isolated from the rhizosphere of a banana plant, was sequenced and assembled to determine the genomic potential associated with its plant growth promotion potential. The genome was sequenced by Illumina technology and assembled using Velvet 1.2.10, resulting in a whole genome of 4.09 Mb with 4332 genes. Genes involved in the production of indoles, siderophores, lipopeptides, volatile compounds, phytase, bacilibactin, and nitrogenase were predicted by gene annotation or by metabolic pathway prediction by RAST. These potential traits were determined using in vitro biochemical tests, finding that B. subtilis EA-CB0575 produces two families of lipopeptides (surfactin and fengycin), solubilizes phosphate, fixes nitrogen, and produces indole and siderophores compounds. Finally, strain EA-CB0575 increased 34.60% the total dry weight (TDW) of tomato plants with respect to non-inoculated plants at greenhouse level. These results suggest that the identification of strain-specific genes and predicted metabolic pathways might explain the strain potential to promote plant growth by several mechanisms of action, accelerating the development of plant biostimulants for sustainable agricultural. © 2020, Springer-Verlag GmbH Germany, part of Springer Nature.
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    Upper limb posture estimation in robotic and virtual reality-based rehabilitation
    (HINDAWI PUBLISHING CORPORATION, 2014-07-08) Cortés C; Ardanza A; Molina-Rueda F; Cuesta-Gómez A; Unzueta L; Epelde G; Ruiz OE; De Mauro A; Florez J; Universidad EAFIT. Departamento de Ingeniería Mecánica; Laboratorio CAD/CAM/CAE
    New motor rehabilitation therapies include virtual reality (VR) and robotic technologies. In limb rehabilitation, limb posture is required to (1) provide a limb realistic representation in VR games and (2) assess the patient improvement. When exoskeleton devices are used in the therapy, the measurements of their joint angles cannot be directly used to represent the posture of the patient limb, since the human and exoskeleton kinematic models differ. In response to this shortcoming, we propose a method to estimate the posture of the human limb attached to the exoskeleton. We use the exoskeleton joint angles measurements and the constraints of the exoskeleton on the limb to estimate the human limb joints angles. This paper presents (a) the mathematical formulation and solution to the problem, (b) the implementation of the proposed solution on a commercial exoskeleton system for the upper limb rehabilitation, (c) its integration into a rehabilitation VR game platform, and (d) the quantitative assessment of the method during elbow and wrist analytic training. Results show that this method properly estimates the limb posture to (i) animate avatars that represent the patient in VR games and (ii) obtain kinematic data for the patient assessment during elbow and wrist analytic rehabilitation. © 2014 Camilo Cortés et al.