Human-robot cooperation for robust surface treatment using non-conventional sliding mode control

© 2018 ISA This work presents a human-robot closely collaborative solution to cooperatively perform surface treatment tasks such as polishing, grinding, deburring, etc. The method considers two force sensors attached to the manipulator end-effector and tool: one sensor is used to properly accomplish the surface treatment task, while the second one is used by the operator to guide the robot tool. The proposed scheme is based on task priority and adaptive non-conventional sliding mode control. The applicability of the proposed approach is substantiated by experimental results using a redundant 7R manipulator: the Sawyer cobot

A Sliding Mode Control Architecture for Human-Manipulator Cooperative Surface Treatment Tasks

© 2018 IEEE. This paper presents a control architecture readily suitable for surface treatment tasks such as polishing, grinding, finishing or deburring as carried out by a human operator, with the added benefit of accuracy, recurrence and physical strength as administered by a robotic manipulator partner. The shared strategy effectively couples the human operator propioceptive abilities and fine skills through his interactions with the autonomous physical agent. The novel proposed control scheme is based on task prioritization and a non-conventional sliding mode control, which is considered to benefit from its inherent robustness and low computational cost. The system relies on two force sensors, one located between the last link of the robot and the surface treatment tool, and the other located in some place of the robot end-effector: the former is used to suitably accomplish the conditioning task, while the latter is used by the operator to manually guide the robotic tool. When the operator chooses to cease guiding the tool, the robot motion safely switches back to an automatic reference tracking. The paper presents the theories for the novel collaborative controller, whilst its effectiveness for robotic surface treatment is substantiated by experimental results using a redundant 7R manipulator and a mock-up conditioning tool

Protection of Spanish Ibex (Capra pyrenaica) against Bluetongue Virus Serotypes 1 and 8 in a Subclinical Experimental Infection

Many wild ruminants such as Spanish ibex (Capra pyrenaica) are susceptible to Bluetongue virus (BTV) infection, which causes disease mainly in domestic sheep and cattle. Outbreaks involving either BTV serotypes 1 (BTV-1) and 8 (BTV-8) are currently challenging Europe. Inclusion of wildlife vaccination among BTV control measures should be considered in certain species. In the present study, four out of fifteen seronegative Spanish ibexes were immunized with a single dose of inactivated vaccine against BTV-1, four against BTV-8 and seven ibexes were non vaccinated controls. Seven ibexes (four vaccinated and three controls) were inoculated with each BTV serotype. Antibody and IFN-gamma responses were evaluated until 28 days after inoculation (dpi). The vaccinated ibexes showed significant (P<0.05) neutralizing antibody levels after vaccination compared to non vaccinated ibexes. The non vaccinated ibexes remained seronegative until challenge and showed neutralizing antibodies from 7 dpi. BTV RNA was detected in the blood of non vaccinated ibexes from 2 to the end of the study (28 dpi) and in target tissue samples obtained at necropsy (8 and 28 dpi). BTV-1 was successfully isolated on cell culture from blood and target tissues of non vaccinated ibexes. Clinical signs were unapparent and no gross lesions were found at necropsy. Our results show for the first time that Spanish ibex is susceptible and asymptomatic to BTV infection and also that a single dose of vaccine prevents viraemia against BTV-1 and BTV-8 replication

Thyroid hormones and skeletal muscle — new insights and potential implications

Thyroid hormone signalling regulates crucial biological functions, including energy expenditure, thermogenesis, development and growth. The skeletal muscle is a major target of thyroid hormone signalling. The type two (DIO2) and three (DIO3) iodothyronine deiodinases have been identified in skeletal muscle. DIO2 expression is tightly regulated and catalyzes outer ring monodeiodination of the secreted prohormone tetraiodothyronine (T(4)) to generate the active hormone triiodothyronine (T(3)). T(3) may remain in the myocyte to signal through nuclear receptors or exit the cell to mix with the extracellular pool. By contrast, DIO3 inactivates T(3) through removal of an inner ring iodine. Regulation of the expression and activity of deiodinases constitutes a cell-autonomous, pre-receptor mechanism for controlling the intracellular concentration of T(3). This local control of T(3) activity is crucial during the various phases of myogenesis. Here, we review the roles of T3 in skeletal muscle development and homeostasis, with a focus on the emerging local deiodinase-mediated control of T3 signalling. Moreover, we discuss these novel findings in the context of both muscle homeostasis and pathology, and examine how they can be therapeutically harnessed to improve satellite cell-mediated muscle repair in patients with skeletal muscle disorders, muscle atrophy or injury

Increased power by harmonizing structural MRI site differences with the ComBat batch method in ENIGMA

A common limitation of neuroimaging studies is their small sample sizes. To overcome this hurdle, the Enhancing Neuro Imaging Genetics through Meta-Analysis (ENIGMA) Consortium combines neuroimaging data from many institutions worldwide. However, this introduces heterogeneity due to different scanning devices and sequences. ENIGMA projects commonly address this heterogeneity with random-effects meta-analysis or mixed-effects mega -analysis. Here we tested whether the batch adjustment method, ComBat, can further reduce site-related het-erogeneity and thus increase statistical power. We conducted random-effects meta-analyses, mixed-effects mega -analyses and ComBat mega-analyses to compare cortical thickness, surface area and subcortical volumes between 2897 individuals with a diagnosis of schizophrenia and 3141 healthy controls from 33 sites. Specifically, we compared the imaging data between individuals with schizophrenia and healthy controls, covarying for age and sex. The use of ComBat substantially increased the statistical significance of the findings as compared to random - effects meta-analyses. The findings were more similar when comparing ComBat with mixed-effects mega-analysis, although ComBat still slightly increased the statistical significance. ComBat also showed increased statistical power when we repeated the analyses with fewer sites. Results were nearly identical when we applied the ComBat harmonization separately for cortical thickness, cortical surface area and subcortical volumes. Therefore, we recommend applying the ComBat function to attenuate potential effects of site in ENIGMA projects and other multi-site structural imaging work. We provide easy-to-use functions in R that work even if imaging data are partially missing in some brain regions, and they can be trained with one data set and then applied to another (a requirement for some analyses such as machine learning).</p