Comparative evaluation of OntoSLAM with other ontologies, it is concluded that this approach outperforms its predecessors in all OQuaRE Excellent Metrics evaluated, with out losing crucial details of Robotics. In distinct, OntoSLAM overcomes in far more than 22 its predecessors in the sub-characteristic of Information Reuse; it is actually superior to its predecessors on Compatibility, Operability, and Transferability categories using a score of 97 ; and it shows the ideal functionality outcomes within the Maintainability category. In the empirical evaluation working with ROS, it is actually GNE-371 Autophagy demonstrated that OntoSLAM is adaptable and compatible with any SLAM algorithm, which permits that this ontology could be released as a ROS package in the future to become made use of with any robot and SLAM algorithm. The outcomes of this operate show that the semantic web is a Streptonigrin Epigenetics solution to standardize and formalize information in Robotics, assisting to enhance the interconnection and interoperability amongst unique robotic systems. It’s achievable to match this semantic layer in the navigation stack of any robot that performs SLAM. The following actions of this perform include things like the test of OntoSLAM collectively with other processes, for example perception and navigation, and the application of OntoSLAM into a wider selection of SLAM algorithms and robots.Author Contributions: Conceptualization, M.A.C.-L., Y.C., R.T.-H. and D.B.-A.; Formal analysis, M.A.C.-L. and Y.C.; Funding acquisition, Y.C. and R.T.-H.; Investigation, M.A.C.-L., Y.C. and D.B.A.; Methodology, M.A.C.-L. and Y.C.; Project administration, Y.C.; Application, M.A.C.-L., M.A. and J.D.-A.; Supervision, Y.C., R.T.-H. and D.B.-A.; Validation, M.A.C.-L., Y.C., D.B.-A., M.A. and J.D.-A.; Visualization, M.A. and J.D.-A.; Writing–original draft, M.A.C.-L. and Y.C.; Writing–review and editing, M.A.C.-L., Y.C. and R.T.-H. All authors have study and agreed towards the published version of the manuscript.Robotics 2021, ten,17 ofFunding: This analysis was funded by FONDO NACIONAL DE DESARROLLO CIENT ICO, TECNOL ICO Y DE INNOVACI TECNOL ICA-FONDECYT as executing entity of CONCYTEC beneath grant agreement no. 01-2019-FONDECYT-BM-INC.INV inside the project RUTAS: Robots for Urban Tourism Centers, Autonomous and Semantic-based. Conflicts of Interest: The authors declare no conflict of interest.
agronomyArticleBreeding for Resilience to Water Deficit and Its Predicted Impact on Forage Mass in Tall FescueBlair L. Waldron 1, , Kevin B. Jensen 1 , Michael D. Peel 1 and Valentin D. PicassoUSDA Agricultural Investigation Service, Forage and Range Study, UMC 6300, Logan, UT 84322, USA; [email protected] (K.B.J.); [email protected] (M.D.P.) Division of Agronomy, University of Wisconsin-Madison, 1575 Linden Dr, Madison, WI 53706, USA; [email protected] Correspondence: [email protected]: Waldron, B.L.; Jensen, K.B.; Peel, M.D.; Picasso, V.D. Breeding for Resilience to Water Deficit and Its Predicted Impact on Forage Mass in Tall Fescue. Agronomy 2021, 11, 2094. https://doi.org/10.3390/ agronomy11112094 Academic Editor: Qi Deng Received: 28 September 2021 Accepted: 16 October 2021 Published: 20 OctoberAbstract: Resilience is increasingly part of the discussion on climate adjust, yet there’s a lack of breeding for resilience per se. This experiment examined the genetic parameters of a novel, direct measure of resilience to water deficit in tall fescue (Lolium arundinaceum (Schreb.) Darbysh.). Heritability, genetic correlations, and predicted acquire from choice were estimated for av.