New non-mammaliaform cynodont from the upper triassic Los Colorados formation, Ischigualasto-Villa Union basin (La Rioja, Argentina)

We report a new species of a small probainognathian cynodont found in the uppermost third of the Los Colorados Formation at the Parque Nacional Talampaya (La Rioja, Argentina). It is represented by a partial cranium with articulated lower jaw. The specimen, PULR-V121, housed at the Universidad Nacional de La Rioja, was analyzed through X-ray micro-tomography in yPF Tecnología S.A. (y-TEC, Ensenada, Buenos Aires, Argentina) using the Bruker SkyScan 1173 instrument. Although the results were acceptable, the resolution was not ideal due to the presence of ferruginous material in the sample. To overcome this issue, we performed a neutron tomography with the highest possible spatial resolution at the ANTARES instrument in the Forschungs-Neutronenquelle Heinz Maier-Leibnitz zentrum (FRM II, Garching, Germany). The new species is a tritheledontid with a unique character state combination. PULR-V121 has a large upper canine in conjunction with a reduced lower one, which is only shared with Riograndia among probainognathian cynodonts and with the mammaliaform Morganucodon. It bears a semicircular, very well-developed, ventrally projected angular process dissimilar from that in other non-mammaliaform cynodonts. It shares with other tritheledontids the presence of upper postcanines with a symmetrical main cusp with convex mesial and distal margins flanked by smaller, lingually placed accessory cusps; lower postcanines with a large, asymmetrical, mesial main cusp followed by smaller distal accessory cusps; and a ventrally bowed secondary osseous palate that reaches posteriorly up to the level of the tips of the upper postcanines and forms deep, narrow, lateral grooves for the lower postcanines. It is unique among prozostrodontians in the presence of a short osseous secondary palate that ends well-anteriorly to the anterior margin of the orbit, not reaching the end of the upper tooth row. Unlike Pachygenelinae, the upper postcanines lack cingula and their major axis is parallel to the tooth row. PULR-V121 is reconstructed as bearing 12 or 13 upper postcanines, a similar number to that observed in Elliotherium (13) and Chaliminia (13), a diagnostic feature of Chalimininae. A reduced number of lower postcanines (seven), regarding the number of upper ones, is a distinctive feature of PULR-V121, in which the last six upper postcanines lack a lower counter-element. PULR- V121 further differs from Chaliminia in having a notably shorter lower tooth row with the ascending process of the dentary well-posterior to the last lower postcanine and the masseteric fossa not reaching the level of the last lower postcanine. PULR-V121 lacks the strong osseous platform in the dentary, lateral to the last lower postcanines, which produces a strong lateral ridge present in the holotype of Chaliminia. The small non-procumbent posterior and the also small anterior (interpreted as i1) lower incisors preserved in PULR-V121 contrast with the relatively large, procumbent lower incisors observed in Chaliminia. PULR-V121 represents a new species that constitutes the second cynodont taxon recognized and the sixth reported cynodont specimen from the Upper Triassic Los Colorados Formation, adding to the diversity and knowledge of Norian South American probainognathians.Fil: Gaetano, Leandro Carlos. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Estudios Andinos "Don Pablo Groeber". Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Estudios Andinos "Don Pablo Groeber"; ArgentinaFil: Abdala, Fernando. Fundación Miguel Lillo. Dirección de Geología. Instituto de Palentologia; ArgentinaFil: Tartaglione, Aureliano. Technische Universität Lichtenbergstr; AlemaniaFil: Schultz, Michael. Technische Universität Lichtenbergstr; AlemaniaFil: Martinelli, Agustín Guillermo. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Museo Argentino de Ciencias Naturales "Bernardino Rivadavia"; ArgentinaFil: Otero, Alejandro. Universidad Nacional de La Plata. Facultad de Ciencias Naturales y Museo. División Paleontología Vertebrados; ArgentinaFil: Leardi, Juan Martín. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Estudios Andinos "Don Pablo Groeber". Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Estudios Andinos "Don Pablo Groeber"; ArgentinaFil: Apaldetti, Cecilia. Universidad Nacional de San Juan. Facultad de Ciencias Exactas, Físicas y Naturales; ArgentinaFil: Krapovickas, Verónica. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Estudios Andinos "Don Pablo Groeber". Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Estudios Andinos "Don Pablo Groeber"; ArgentinaXII Congreso de la Asociación Paleontológica ArgentinaBuenos AiresArgentinaAsociación Paleontológica Argentin

Solution of Ambrosio-Tortorelli model for image segmentation by generalized relaxation method

Image segmentation addresses the problem to partition a given image into its constituent objects and then to identify the boundaries of the objects. This problem can be formulated in terms of a variational model aimed to find optimal approximations of a bounded function by piecewise-smooth functions, minimizing a given functional. The corresponding Euler-Lagrange equations are a set of two coupled elliptic partial differential equations with varying coefficients. Numerical solution of the above system often relies on alternating minimization techniques involving descent methods coupled with explicit or semi-implicit finite-difference discretization schemes, which are slowly convergent and poorly scalable with respect to image size. In this work we focus on generalized relaxation methods also coupled with multigrid linear solvers, when a finite-difference discretization is applied to the Euler-Lagrange equations of Ambrosio-Tortorelli model. We show that non-linear Gauss-Seidel, accelerated by inner linear iterations, is an effective method for large-scale image analysis as those arising from high-throughput screening platforms for stem cells targeted differentiation, where one of the main goal is segmentation of thousand of images to analyze cell colonies morphology

Reprint of Solution of Ambrosio-Tortorelli model for image segmentation by generalized relaxation method

Image segmentation addresses the problem to partition a given image into its constituent objects and then to identify the boundaries of the objects. This problem can be formulated in terms of a variational model aimed to find optimal approximations of a bounded function by piecewise-smooth functions, minimizing a given functional. The corresponding Euler-Lagrange equations are a set of two coupled elliptic partial differential equations with varying coefficients. Numerical solution of the above system often relies on alternating minimization techniques involving descent methods coupled with explicit or semi-implicit finite-difference discretization schemes, which are slowly convergent and poorly scalable with respect to image size. In this work we focus on generalized relaxation methods also coupled with multigrid linear solvers, when a finite-difference discretization is applied to the Euler-Lagrange equations of Ambrosio-Tortorelli model. We show that non-linear Gauss-Seidel, accelerated by inner linear iterations, is an effective method for large-scale image analysis as those arising from high-throughput screening platforms for stem cells targeted differentiation, where one of the main goal is segmentation of thousand of images to analyze cell colonies morphology

Obstacle Avoidance via Landmark Clustering in a Path-Planning Algorithm

In this paper we present a new 2D decentralized path-planning algorithm for a swarm of multi-rotor UAVs operating in an unknown environment. The way-points of the reference trajectories are computed as solutions of a sequence of optimization problems. In order to obtain coordination, the optimization problems are defined by considering the goal of the flight mission, the desired formation shape and the detected obstacles. The obstacle avoidance strategy is based on the clustering of the detected landmarks. Then the no-fly zones are obtained by fitting the minimum area rectangle boxes surrounding the clusters. The algorithm is tested through simulations of realistic scenarios

Development of an autonomous multi-rotor UAV for outdoor missions in unknown environments

In this paper we present the development of a multi-rotor system for autonomous outdoor flights in an unknown environment. We propose a modular framework scheme to perform the functions of guidance, navigation and control using the sensor measurements. The localization and mapping tasks are performed simultaneously by the guidance module through an Extended Kalman Filter (EKF). The estimated map allows the guidance module to plan the reference trajectory avoiding the collision by evaluating the solutions of a sequence of constrained optimization problems. The control module computes the autopilot commands to follow the reference trajectory through a robust Model Predictive Control technique. The overall system is tested through simulations of realist scenarios

An Observer-Based Output Feedback Controller for the Finite-Time Stabilization of Markov Jump Linear Systems

In this letter, we investigate the finite-time output feedback control problem for continuous-time Markov jump linear systems. In this context, the first result is a sufficient condition for stochastic finite-time stability, requiring the solution of a feasibility problem constrained by differential linear matrix inequalities. Afterward, we consider the stabilization problem via output feedback dynamical controllers. The usual machinery pursued in the deterministic case would lead to stabilization conditions depending on differential bilinear matrix inequalities, that cannot be solved in practice. Therefore, a different methodology, based on the separation approach provided by Amato et al., is exploited to design an observer-based output feedback controller, which can be computed by solving an optimization problem depending on linear constraints. A non-trivial application example, involving the finite-time stabilization of the longitudinal dynamics of a helicopter, is presented in order to illustrate the effectiveness of the proposed technique

Conditions for annular finite-time stability of Itô stochastic linear time-varing systems with Markov switching

In this study, the authors tackle some control problems related to the class of continuous-time, stochastic linear time-varying systems with Markov switching. First, the annular stochastic finite-time stability problem is considered, and two sufficient conditions are derived by considering the Itô formalism. Both conditions require the solution of a feasibility problem based on differential linear matrix inequalities. The former turns out to be less conservative and, therefore, is exploited in the analysis context; however, it cannot be converted into a computationally tractable condition for feedback purposes. The latter, which is based on a more conservative assumption, allows us to solve the state-feedback design problem. They show that the proposed approach obtains less conservative results with respect to the previous literature. Moreover, the application of the methodology to the finite-time control of a satellite illustrates the effectiveness of the proposed approach when facing engineering problems

Proofs of “A Systematic Constrained Control Framework for Unmanned Aerial Vehicles based on Explicit Reference Governor”

info:eu-repo/semantics/publishe

Nonlinear dynamic inversion with neural networks for the flight control of a low cost tilt rotor UAV

This paper deals with the development of a flight control scheme based on the Nonlinear Dynamic Inversion technique (NDI). Such a scheme has been implemented on the Flight Control System (FCS) of a trirotors prototype model used to simulate tilt rotor air vehicles dynamics during all those phases when aerodynamic surfaces are less effective or not effective at all. An adaptive flight control scheme has been developed based on Radial Basis Function Neural Network (RBFNN) and NDI making both attitude and trajectory tracking control system less sensitive to modelling errors. To demonstrate the effectiveness of the proposed control technique both numerical simulations and experimental tests have been performed. To this end a scaled multi-rotor test bed has been built simulating a tilt rotor unmanned air vehicle (UAV) in hovering and low speed flight conditions. The control system has been implemented on an embedded board based on an ARM Cortex M4 processor and a low cost Inertial Measurement Unit with triaxial MEMS accelerometer, gyroscope and magnetometer sensors. As accuracy of NDI control system can be affected by model uncertainties and sharp transients due to the RBFNN adaptation transients, a model calibration phase is needed. To this end preliminary flight tests have been performed for UAV dynamic model identification and control parameters tuning