Dataset Information

Learning to manipulate a whip with simple primitive actions - A simulation study.

ABSTRACT: This simulation study investigated whether a 4-degrees-of-freedom (DOF) arm could strike a target with a 50-DOF whip using a motion profile similar to discrete human movements. The interactive dynamics of the multi-joint arm was modeled as a constant joint-space mechanical impedance, with values derived from experimental measurement. Targets at various locations could be hit with a single maximally smooth motion in joint-space coordinates. The arm movements that hit the targets were identified with fewer than 250 iterations. The optimal actions were essentially planar arm motions in extrinsic task-space coordinates, predominantly oriented along the most compliant direction of both task-space and joint-space mechanical impedances. Of the optimal movement parameters, striking a target was most sensitive to movement duration. This result suggests that the elementary actions observed in human motor behavior may support efficient motor control in interaction with a dynamically complex object.

SUBMITTER: Nah MC

PROVIDER: S-EPMC10405071 | biostudies-literature | 2023 Aug

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Learning to manipulate a whip with simple primitive actions - A simulation study.

Nah Moses C MC Krotov Aleksei A Russo Marta M Sternad Dagmar D Hogan Neville N

iScience 20230714 8

This simulation study investigated whether a 4-degrees-of-freedom (DOF) arm could strike a target with a 50-DOF whip using a motion profile similar to discrete human movements. The interactive dynamics of the multi-joint arm was modeled as a constant joint-space mechanical impedance, with values derived from experimental measurement. Targets at various locations could be hit with a single maximally smooth motion in joint-space coordinates. The arm movements that hit the targets were identified w ...[more]

PMID: 37554449

Similar Datasets

Project description:BackgroundArachnids are a highly successful group of land-dwelling arthropods. They are major contributors to modern terrestrial ecosystems, and have a deep evolutionary history. Whip spiders (Arachnida, Amblypygi), are one of the smaller arachnid orders with ca. 190 living species. Here we restudy one of the oldest fossil representatives of the group, Graeophonus anglicus Pocock, 1911 from the Late Carboniferous (Duckmantian, ca. 315 Ma) British Middle Coal Measures of the West Midlands, UK. Using X-ray microtomography, our principal aim was to resolve details of the limbs and mouthparts which would allow us to test whether this fossil belongs in the extant, relict family Paracharontidae; represented today by a single, blind species Paracharon caecus Hansen, 1921.ResultsTomography reveals several novel and significant character states for G. anglicus; most notably in the chelicerae, pedipalps and walking legs. These allowed it to be scored into a phylogenetic analysis together with the recently described Paracharonopsis cambayensis Engel & Grimaldi, 2014 from the Eocene (ca. 52 Ma) Cambay amber, and Kronocharon prendinii Engel & Grimaldi, 2014 from Cretaceous (ca. 99 Ma) Burmese amber. We recovered relationships of the form ((Graeophonus (Paracharonopsis + Paracharon)) + (Charinus (Stygophrynus (Kronocharon (Charon (Musicodamon + Paraphrynus)))))). This tree largely reflects Peter Weygoldt's 1996 classification with its basic split into Paleoamblypygi and Euamblypygi lineages; we were able to score several of his characters for the first time in fossils. Our analysis draws into question the monophyly of the family Charontidae.ConclusionsOur data suggest that Graeophonus is a crown group amblypygid, and falls within a monophyletic Paleoamblypgi clade, but outside the family Paracharontidae (= Paracharonopsis + Paracharon). Our results also suggest a new placement for the Burmese amber genus Kronocharon, a node further down from its original position. Overall, we offer a broad phylogenetic framework for both the fossil and Recent whip spiders against which future discoveries can be tested.

Project description:Meta-analysis of clinical trials targeting rare events face particular challenges when the data lack adequate number of events and are susceptible to high levels of heterogeneity. The standard meta-analysis methods (DerSimonian Laird (DL) and Mantel-Haenszel (MH)) often lead to serious distortions because of such data sparsity. Applications of the methods suited to specific incidence and heterogeneity characteristics are lacking, thus we compared nine available methods in a simulation study. We generated 360 meta-analysis scenarios where each considered different incidences, sample sizes, between-study variance (heterogeneity) and treatment allocation. We include globally recommended methods such as inverse-variance fixed/random-effect (IV-FE/RE), classical-MH, MH-FE, MH-DL, Peto, Peto-DL and the two extensions for MH bootstrapped-DL (bDL) and Peto-bDL. Performance was assessed on mean bias, mean error, coverage and power. In the absence of heterogeneity, the coverage and power when combined revealed small differences in meta-analysis involving rare and very rare events. The Peto-bDL method performed best, but only in smaller sample sizes involving rare events. For medium-to-larger sample sizes, MH-bDL was preferred. For meta-analysis involving very rare events, Peto-bDL was the best performing method which was sustained across all sample sizes. However, in meta-analysis with 20% or more heterogeneity, the coverage and power were insufficient. Performance based on mean bias and mean error was almost identical across methods. To conclude, in meta-analysis of rare binary outcomes, our results suggest that Peto-bDL is better in both rare and very rare event settings in meta-analysis with limited sample sizes. However, when heterogeneity is large, the coverage and power to detect rare events are insufficient. Whilst this study shows that some of the less studied methods appear to have good properties under sparse data scenarios, further work is needed to assess them against the more complex distributional-based methods to understand their overall performances.

Dataset Information

Learning to manipulate a whip with simple primitive actions - A simulation study.

Publications

Learning to manipulate a whip with simple primitive actions - A simulation study.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets