Final-State Constrained Optimal Control via a Projection Operator Approach

In this paper we develop a numerical method to solve nonlinear optimal control problems with final-state constraints. Specifically, we extend the PRojection Operator based Netwon's method for Trajectory Optimization (PRONTO), which was proposed by Hauser for unconstrained optimal control problems. While in the standard method final-state constraints can be only approximately handled by means of a terminal penalty, in this work we propose a methodology to meet the constraints exactly. Moreover, our method guarantees recursive feasibility of the final-state constraint. This is an appealing property especially in realtime applications in which one would like to be able to stop the computation even if the desired tolerance has not been reached, but still satisfy the constraints. Following the same conceptual idea of PRONTO, the proposed strategy is based on two main steps which (differently from the standard scheme) preserve the feasibility of the final-state constraints: (i) solve a quadratic approximation of the nonlinear problem to find a descent direction, and (ii) get a (feasible) trajectory by means of a feedback law (which turns out to be a nonlinear projection operator). To find the (feasible) descent direction we take advantage of final-state constrained Linear Quadratic optimal control methods, while the second step is performed by suitably designing a constrained version of the trajectory tracking projection operator. The effectiveness of the proposed strategy is tested on the optimal state transfer of an inverted pendulum

Using Knowledge Analytics to Search and Characterize Mass Properties Aerospace Data

There is growing capability in the field of Big Data and Data Analytics which Mass Properties Engineers might like to take advantage of. This paper utilizes an implementation of the IBM Knowledge Analytics and Watson search capabilities to explore a corpus of material developed primarily with the interests of Mass Properties Engineers and vehicle concept developers at its forefront. The full collection of SAWE (Society of Allied Weight Engineers, Inc.) Technical Papers from 1939 through 2015 is a major portion of the knowledge content. Additional aerospace vehicle design information includes metadata from AIAA (American Institute for Aeronautics and Astronautics), and INCOSE (International Council on Systems Engineering) as well as author-provided personal search material. This data is processed with respect to certain expected content, data taxonomies and key words to become the core data in NASA Langley Research Centers Vehicle Analysis Analytics, IBM Watson Content. Processed data becomes the corpus of information which is interrogated to provide examples of finding data for mass regression analysis, technology impacts on MPE (Mass Properties Engineering), mass properties control, standards, and other aspects of interest

The Relativistic Hopfield network: rigorous results

The relativistic Hopfield model constitutes a generalization of the standard Hopfield model that is derived by the formal analogy between the statistical-mechanic framework embedding neural networks and the Lagrangian mechanics describing a fictitious single-particle motion in the space of the tuneable parameters of the network itself. In this analogy the cost-function of the Hopfield model plays as the standard kinetic-energy term and its related Mattis overlap (naturally bounded by one) plays as the velocity. The Hamiltonian of the relativisitc model, once Taylor-expanded, results in a P-spin series with alternate signs: the attractive contributions enhance the information-storage capabilities of the network, while the repulsive contributions allow for an easier unlearning of spurious states, conferring overall more robustness to the system as a whole. Here we do not deepen the information processing skills of this generalized Hopfield network, rather we focus on its statistical mechanical foundation. In particular, relying on Guerra's interpolation techniques, we prove the existence of the infinite volume limit for the model free-energy and we give its explicit expression in terms of the Mattis overlaps. By extremizing the free energy over the latter we get the generalized self-consistent equations for these overlaps, as well as a picture of criticality that is further corroborated by a fluctuation analysis. These findings are in full agreement with the available previous results.Comment: 11 pages, 1 figur

New Variant of the Treatment of Acromion-Clavicular Dislocation With TightRope ® System in a Mini - Open Approach: A Preliminary Clinical Study

Background: Many different surgical techniques have been described to stabilize the acromion-clavicular (AC) dislocations. So far many of these procedures are performed only in arthroscopy. Objectives: In this study, we describe a new technique that utilizes the tightrope with a mini-invasive open approach for the acute stabilization of the acromion-clavicular joint (ACJ) dislocation. Patients and Methods: We set an prospective study aimed to verify the efficacy of this new surgical technique. We treated 28 patients with acute ACJ dislocation with ACJ TightRope ® System with dual mini access. We retrospectively reviewed the data of 34 patients treated with arthroscopic technique. They were considered as the control group. Results: At 6 month’s follow-up, all the 28 patients showed a stable joint during clinical examination and obtained an average Constant score of 98.62/100, with a complete recovery of ROM and strength in abduction. The mean operation time was of 33.7 minutes. The mean recovery duration was 102.8 days. No significant difference was found between the experimental and control groups (P > 0.05). Conclusions: Results of this trial suggest the effectiveness of this new mini-invasive surgical technique in producing clinical and functional recovery in patients with ACJ dislocations

25 years of satellite InSAR monitoring of ground instability and coastal geohazards in the archaeological site of Capo Colonna, Italy

For centuries the promontory of Capo Colonna in Calabria region, southern Italy, experienced land subsidence and coastline retreat to an extent that the archaeological ruins of the ancient Greek sanctuary are currently under threat of cliff failure, toppling and irreversible loss. Gas extraction in nearby wells is a further anthropogenic element to account for at the regional scale. Exploiting an unprecedented satellite Synthetic Aperture Radar (SAR) time series including ERS-1/2, ENVISAT, TerraSAR-X, COSMO-SkyMed and Sentinel-1A data stacks acquired between 1992 and 2016, this paper presents the first and most complete Interferometric SAR (InSAR) baseline assessment of land subsidence and coastal processes affecting Capo Colonna. We analyse the regional displacement trends, the correlation between vertical displacements with gas extraction volumes, the impact on stability of the archaeological heritage, and the coastal geohazard susceptibility. In the last 25 years, the land has subsided uninterruptedly, with highest annual line-of-sight deformation rates ranging between -15 and -20 mm/year in 2011-2014. The installation of 40 pairs of corner reflectors along the northern coastline and within the archaeological park resulted in an improved imaging capability and higher density of measurement points. This proved to be beneficial for the ground stability assessment of recent archaeological excavations, in an area where field surveying in November 2015 highlighted new events of cliff failure. The conceptual model developed suggests that combining InSAR results, geomorphological assessments and inventorying of wave-storms will contribute to unveil the complexity of coastal geohazards in Capo Colonna. © (2016) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only

Distributed Primal Decomposition for Large-Scale MILPs

This paper deals with a distributed Mixed-Integer Linear Programming (MILP) set-up arising in several control applications. Agents of a network aim to minimize the sum of local linear cost functions subject to both individual constraints and a linear coupling constraint involving all the decision variables. A key, challenging feature of the considered set-up is that some components of the decision variables must assume integer values. The addressed MILPs are NP-hard, nonconvex and large-scale. Moreover, several additional challenges arise in a distributed framework due to the coupling constraint, so that feasible solutions with guaranteed suboptimality bounds are of interest. We propose a fully distributed algorithm based on a primal decomposition approach and an appropriate tightening of the coupling constraint. The algorithm is guaranteed to provide feasible solutions in finite time. Moreover, asymptotic and finite-time suboptimality bounds are established for the computed solution. Montecarlo simulations highlight the extremely low suboptimality bounds achieved by the algorithm

The Earthlike Shoreline Morphology of Titan's Ontario Lacus

Ontario Lacus' shoreline features include Earth-like rivers, deltas and flooded topography. Ontario is a dynamic lake, similar in many ways to terrestrial lakes, with active shoreline processes

The Ketogenic Diet Improves Gut–Brain Axis in a Rat Model of Irritable Bowel Syndrome: Impact on 5-HT and BDNF Systems

Altered gut–brain communication can contribute to intestinal dysfunctions in the intestinal bowel syndrome. The neuroprotective high-fat, adequate-protein, low-carbohydrate ketogenic diet (KD) modulates the levels of different neurotransmitters and neurotrophins. The aim was to evaluate the effects of KD on levels of 5-HT, the receptors 5-HT3B and 5-HT4, the 5-HT transporter SERT, the neurotrophin BDNF, and its receptor TrkB in the colon and brain of a rat model of irritable bowel syndrome (IBS). Samples from Wistar rats exposed to maternal deprivation as newborns and then fed with a standard diet (IBS-Std) or KD (IBS-KD) for ten weeks were analyzed. As controls, unexposed rats (Ctrl-Std and Ctrl-KD) were studied. IBS-Std rats had a disordered enteric serotoninergic signaling shown by increased mucosal 5-HT content and reduced SERT, 5-HT3B, and 5-HT4 levels compared to controls. In the brain, these animals showed up-regulation of the BDNF receptor TrkB as a counteracting response to the stress-induced reduction of the neurotrophin. KD showed a dual effect in improving the altered 5-HT and BDNF systems. It down-regulated the increased mucosal 5-HT without affecting transporter and receptor levels. KD improved brain BDNF levels and established negative feedback, leading to a compensatory downregulation of TrkB to maintain a physiological steady state

Distributed Personalized Gradient Tracking with Convex Parametric Models

We present a distributed optimization algorithm for solving online personalized optimization problems over a network of computing and communicating nodes, each of which linked to a specific user. The local objective functions are assumed to have a composite structure and to consist of a known time-varying (engineering) part and an unknown (user-specific) part. Regarding the unknown part, it is assumed to have a known parametric (e.g., quadratic) structure a priori, whose parameters are to be learned along with the evolution of the algorithm. The algorithm is composed of two intertwined components: (i) a dynamic gradient tracking scheme for finding local solution estimates and (ii) a recursive least squares scheme for estimating the unknown parameters via user's noisy feedback on the local solution estimates. The algorithm is shown to exhibit a bounded regret under suitable assumptions. Finally, a numerical example corroborates the theoretical analysis

The effects of a structured education program on preparedness for self-employed careers in Italian undergraduate nursing students

Background and aim of the work: Despite freelance careers in nursing has been becoming a promising component of the current labour market, in the Italian and also international contexts, there is still a paucity of evidence testing whether a structured educational intervention delivered from remote might be useful in increasing the levels of preparedness for self-employed careers among third-year nursing students. This study aimed to test the effects of a structured educational program on the preparedness for self-employed careers in Italian undergraduate nursing students. Methods: The study employed pre-post design with convenience sampling. Data were collected before the structured education program was delivered (T0) and up to one day after the instruction was delivered (T1). Results: In this study, 717 third-year nursing students were enrolled. The most significant difference between T0 and T1 was in the domain of knowledge about pensions and retirement issues, followed by administrative rules knowledge. There were substantial variations between T0 and T1 in the area of logistic characteristics in determining the price of a freelance nursing activity, as well as scores in the domain of care complexity in determining the price of the independent nursing occupation. Conclusions: This study proved the short-term impacts of a structured educational program on enhancing levels of preparation for self-employed professions among Italian undergraduate nursing students. This topic requires more attention from educators and researchers as the demands of prepared healthcare workers to undertake self-employed careers necessitate a greater capacity to properly educate nursing students for self-employed occupations within their undergraduate path. (www.actabiomedica.it)