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Our group is developing a cyber-physical walking system (CPWS) for people paralyzed by spinal cord injuries (SCI). The current CPWS consists of a functional neuromuscular stimulation (FNS) system and a powered lower-limb exoskeleton for walking with leg movements in the sagittal plane. We are developing neural control systems that learn to assist the user of this CPWS to walk with stability. In a previous publication (Liu et al., Biomimetics, 2019, 4, 28), we showed a neural controller that stabilized a simulated biped in the sagittal plane. We are considering adding degrees of freedom to the CPWS to allow more natural walking movements and improved stability. Thus, in this paper, we present a new neural network enhanced control system that stabilizes a three-dimensional simulated biped model of a human wearing an exoskeleton. Results show that it stabilizes human/exoskeleton models and is robust to impact disturbances. The simulated biped walks at a steady pace in a range of typical human ambulatory speeds from 0.7 to 1.3 m/s, follows waypoints at a precision of 0.3 m, remains stable, and continues walking forward despite impact disturbances and adapts its speed to compensate for persistent external disturbances. Furthermore, the neural network controller stabilizes human models of different statures from 1.4 to 2.2 m tall without any changes to the control parameters. Please see videos at the following link: 3D biped walking control . 

Estimating center of mass (COM) through sensor measurements is done to maintain walking and standing stability with exoskeletons. The authors present a method for estimating COM kinematics through an artificial neural network, which was trained by minimizing the mean squared error between COM displacements measured by a gold-standard motion capture system and recorded acceleration signals from body-mounted accelerometers. A total of 5 able-bodied participants were destabilized during standing through: (1) unexpected perturbations caused by 4 linear actuators pulling on the waist and (2) volitionally moving weighted jars on a shelf. Each movement type was averaged across all participants. The algorithm’s performance was quantified by the root mean square error and coefficient of determination ( R 2 ) calculated from both the entire trial and during each perturbation type. Throughout the trials and movement types, the average coefficient of determination was 0.83, with 89% of the movements with R 2  > .70, while the average root mean square error ranged between 7.3% and 22.0%, corresponding to 0.5- and 0.94-cm error in both the coronal and sagittal planes. COM can be estimated in real time for balance control of exoskeletons for individuals with a spinal cord injury, and the procedure can be generalized for other gait studies. 

A control system for simulated two-dimensional bipedal walking was developed. The biped model was built based on anthropometric data. At the core of the control is a Deep Deterministic Policy Gradients (DDPG) neural network that is trained in GAZEBO, a physics simulator, to predict the ideal foot location to maintain stable walking under external impulse load. Additional controllers for hip joint movement during stance phase, and ankle joint torque during toeoff, help to stabilize the robot during walking. The simulated robot can walk at a steady pace of approximately 1m/s, and during locomotion it can maintain stability with a 30N-s impulse applied at the torso. This work implement DDPG algorithm to solve biped walking control problem. The complexity of DDPG network is decreased through carefully selected state variables and distributed control system. 

The production of strange hadrons ($$ {\textrm{K}}_{\textrm{S}}^0 $$$K_S^0$, Λ, Ξ^±, and Ω^±), baryon-to-meson ratios (Λ/$$ {\textrm{K}}_{\textrm{S}}^0 $$$K_S^0$, Ξ/$$ {\textrm{K}}_{\textrm{S}}^0 $$$K_S^0$, and Ω/$$ {\textrm{K}}_{\textrm{S}}^0 $$$K_S^0$), and baryon-to-baryon ratios (Ξ/Λ, Ω/Λ, and Ω/Ξ) associated with jets and the underlying event were measured as a function of transverse momentum (p_T) in pp collisions at$$ \sqrt{s} $$$\sqrt{s}$= 13 TeV and p Pb collisions at$$ \sqrt{s_{\textrm{NN}}} $$$\sqrt{s_{\mathrm{NN}}}$= 5.02 TeV with the ALICE detector at the LHC. The inclusive production of the same particle species and the corresponding ratios are also reported. The production of multi-strange hadrons, Ξ^±and Ω^±, and their associated particle ratios in jets and in the underlying event are measured for the first time. In both pp and p–Pb collisions, the baryon-to-meson and baryon-to-baryon yield ratios measured in jets differ from the inclusive particle production for low and intermediate hadronp_T(0.6–6 GeV/c). Ratios measured in the underlying event are in turn similar to those measured for inclusive particle production. In pp collisions, the particle production in jets is compared with Pythia8 predictions with three colour-reconnection implementation modes. None of them fully reproduces the data in the measured hadronp_Tregion. The maximum deviation is observed for Ξ^±and Ω^±which reaches a factor of about six. The event multiplicity dependence is further investigated in p−Pb collisions. In contrast to what is observed in the underlying event, there is no significant event-multiplicity dependence for particle production in jets. The presented measurements provide novel constraints on hadronisation and its Monte Carlo description. In particular, they demonstrate that the fragmentation of jets alone is insufficient to describe the strange and multi-strange particle production in hadronic collisions at LHC energies.

 

Abstract A newly developed observable for correlations between symmetry planes, which characterize the direction of the anisotropic emission of produced particles, is measured in Pb–Pb collisions at $$\sqrt{s_\text {NN}}$$ s NN  = 2.76 TeV with ALICE. This so-called Gaussian Estimator allows for the first time the study of these quantities without the influence of correlations between different flow amplitudes. The centrality dependence of various correlations between two, three and four symmetry planes is presented. The ordering of magnitude between these symmetry plane correlations is discussed and the results of the Gaussian Estimator are compared with measurements of previously used estimators. The results utilizing the new estimator lead to significantly smaller correlations than reported by studies using the Scalar Product method. Furthermore, the obtained symmetry plane correlations are compared to state-of-the-art hydrodynamic model calculations for the evolution of heavy-ion collisions. While the model predictions provide a qualitative description of the data, quantitative agreement is not always observed, particularly for correlators with significant non-linear response of the medium to initial state anisotropies of the collision system. As these results provide unique and independent information, their usage in future Bayesian analysis can further constrain our knowledge on the properties of the QCD matter produced in ultrarelativistic heavy-ion collisions. 

A study of multiplicity and pseudorapidity distributions of inclusive photons measured in pp and p–Pb collisions at a center-of-mass energy per nucleon–nucleon collision of$$\sqrt{s_{\textrm{NN}}}~=~5.02$$$\sqrt{s_{\text{NN}}}=5.02$ TeV using the ALICE detector in the forward pseudorapidity region 2.3 $$<~\eta _\textrm{lab} ~<$$$<{\eta }_{\text{lab}}<$ 3.9 is presented. Measurements in p–Pb collisions are reported for two beam configurations in which the directions of the proton and lead ion beam were reversed. The pseudorapidity distributions in p–Pb collisions are obtained for seven centrality classes which are defined based on different event activity estimators, i.e., the charged-particle multiplicity measured at midrapidity as well as the energy deposited in a calorimeter at beam rapidity. The inclusive photon multiplicity distributions for both pp and p–Pb collisions are described by double negative binomial distributions. The pseudorapidity distributions of inclusive photons are compared to those of charged particles at midrapidity in pp collisions and for different centrality classes in p–Pb collisions. The results are compared to predictions from various Monte Carlo event generators. None of the generators considered in this paper reproduces the inclusive photon multiplicity distributions in the reported multiplicity range. The pseudorapidity distributions are, however, better described by the same generators.

 

This article reports measurements of the angle between differently defined jet axes in pp collisions at$$ \sqrt{s} $$$\sqrt{s}$= 5.02 TeV carried out by the ALICE Collaboration. Charged particles at midrapidity are clustered into jets with resolution parametersR= 0.2 and 0.4. The jet axis, before and after Soft Drop grooming, is compared to the jet axis from the Winner-Takes-All (WTA) recombination scheme. The angle between these axes, ∆R_axis, probes a wide phase space of the jet formation and evolution, ranging from the initial high-momentum-transfer scattering to the hadronization process. The ∆R_axisobservable is presented for 20<$$ {p}_{\textrm{T}}^{\textrm{ch}\ \textrm{jet}} $$$p_T^{\mathrm{ch}\mathrm{jet}}$<100 GeV/c, and compared to predictions from the PYTHIA 8 and Herwig 7 event generators. The distributions can also be calculated analytically with a leading hadronization correction related to the non-perturbative component of the Collins-Soper-Sterman (CSS) evolution kernel. Comparisons to analytical predictions at next-to-leading-logarithmic accuracy with leading hadronization correction implemented from experimental extractions of the CSS kernel in Drell-Yan measurements are presented. The analytical predictions describe the measured data within 20% in the perturbative regime, with surprising agreement in the non-perturbative regime as well. These results are compatible with the universality of the CSS kernel in the context of jet substructure.