Testing, Validation and Dissemination of an Innovative Biotechnology for Air and Water Treatment.

The present study is aimed to follow the start-up in the Italian and European framework of an American biotechnology for environmental decontamination and it focused on field testing stage for air treatment application, in parallel with a bench/pilot scale application on industrial wastewater treatment. The biotechnology applied is based on immobilized cell bioreactors, where air is ventilated and water is recirculated to provide the optimal conditions for the development of a mixed bacteria consortium, growing on contaminants captured from contaminated media (i.e. air or wastewater). The technology proposed has been studied from different perspectives, i.e. emission risk, overall sustainability and remediation performance. Several pilot installations have been accomplished for air treatment application, in different areas of interest. In particular, in the healthcare sector (hemodialysis unit, operatory room, intensive care unit and anatomo-pathological laboratory), where the protection against microbial and chemical agents is perceived as a necessity, both for operators and patients, the biotechnology displayed remarkable results, particularly on VOCs and bacterial count. In order to try and address one of the most challenging issue for air treatment, i.e. odor containment, two major pilot applications have been performed, on waste and wastewater treatment plant, with promising, but still unsteady results. A new opportunity for application was envisaged in radioactivity contaminated indoor environments and a preliminary impact assessment has been outlined, based on results obtained in different fields. For wastewater treatment, a single pilot scale plant was implemented and silk manufacturing effluent was object of the experimental remediation attempted. In a cost-effective perspective, the implementation of this system appears to be suitable for several solutions, i.e. within the framework of a multi-stage treatment process or as independent and easily implementable wastewater technology for cottage-scale manufacturing or small communities

Aeronautical engineering: A continuing bibliography with indexes (supplement 189)

This bibliography lists 579 reports, articles and other documents introduced into the NASA scientific and technical information system in June 1985

George C. Marshall Space Flight Center Research and Technology Report 2014

Many of NASA's missions would not be possible if it were not for the investments made in research advancements and technology development efforts. The technologies developed at Marshall Space Flight Center contribute to NASA's strategic array of missions through technology development and accomplishments. The scientists, researchers, and technologists of Marshall Space Flight Center who are working these enabling technology efforts are facilitating NASA's ability to fulfill the ambitious goals of innovation, exploration, and discovery

Particle Swarm Optimization

Particle swarm optimization (PSO) is a population based stochastic optimization technique influenced by the social behavior of bird flocking or fish schooling.PSO shares many similarities with evolutionary computation techniques such as Genetic Algorithms (GA). The system is initialized with a population of random solutions and searches for optima by updating generations. However, unlike GA, PSO has no evolution operators such as crossover and mutation. In PSO, the potential solutions, called particles, fly through the problem space by following the current optimum particles. This book represents the contributions of the top researchers in this field and will serve as a valuable tool for professionals in this interdisciplinary field

Aeronautical Engineering. A continuing bibliography with indexes, supplement 135, May 1981

This bibliography lists 536 reports, articles, and other documents introduced into the NASA scientific and technical information system in April 1981

Factories of the Future

Engineering; Industrial engineering; Production engineerin

Aeronautical Engineering: A continuing bibliography with indexes (supplement 205)

This bibliography lists 517 reports, articles and other documents introduced into the NASA scientific and technical information system in September 1986

Numerical Simulation in Biomechanics and Biomedical Engineering

In the first contribution, Morbiducci and co-workers discuss the theoretical and methodological bases supporting the Lagrangian- and Euler-based methods, highlighting their application to cardiovascular flows. The second contribution, by the Ansón and van Lenthe groups, proposes an automated virtual bench test for evaluating the stability of custom shoulder implants without the necessity of mechanical testing. Urdeitx and Doweidar, in the third paper, also adopt the finite element method for developing a computational model aim to study cardiac cell behavior under mechano-electric stimulation. In the fourth contribution, Ayensa-Jiménez et al. develop a methodology to approximate the multidimensional probability density function of the parametric analysis obtained developing a mathematical model of the cancer evolution. The fifth paper is oriented to the topological data analysis; the group of Cueto and Chinesta designs a predictive model capable of estimating the state of drivers using the data collected from motion sensors. In the sixth contribution, the Ohayon and Finet group uses wall shear stress-derived descriptors to study the role of recirculation in the arterial restenosis due to different malapposed and overlapping stent conditions. In the seventh contribution, the research group of Antón demonstrates that the simulation time can be reduced for cardiovascular numerical analysis considering an adequate geometry-reduction strategy applicable to truncated patient specific artery. In the eighth paper, Grasa and Calvo present a numerical model based on the finite element method for simulating extraocular muscle dynamics. The ninth paper, authored by Kahla et al., presents a mathematical mechano-pharmaco-biological model for bone remodeling. Martínez, Peña, and co-workers propose in the tenth paper a methodology to calibrate the dissection properties of aorta layer, with the aim of providing useful information for reliable numerical tools. In the eleventh contribution, Martínez-Bocanegra et al. present the structural behavior of a foot model using a detailed finite element model. The twelfth contribution is centered on the methodology to perform a finite, element-based, numerical model of a hydroxyapatite 3D printed bone scaffold. In the thirteenth paper, Talygin and Gorodkov present analytical expressions describing swirling jets for cardiovascular applications. In the fourteenth contribution, Schenkel and Halliday propose a novel non-Newtonian particle transport model for red blood cells. Finally, Zurita et al. propose a parametric numerical tool for analyzing a silicone customized 3D printable trachea-bronchial prosthesis

On the Interplay between Mechanical and Computational Intelligence in Robot Hands

Researchers have made tremendous advances in robotic grasping in the past decades. On the hardware side, a lot of robot hand designs were proposed, covering a large spectrum of dexterity (from simple parallel grippers to anthropomorphic hands), actuation (from underactuated to fully actuated), and sensing capabilities (from only open/close states to tactile sensing). On the software side, grasping techniques also evolved significantly, from open-loop control, classical feedback control, to learning-based policies. However, most of the studies and applications follow the one-way paradigm that mechanical engineers/researchers design the hardware first and control/learning experts write the code to use the hand. In contrast, we aim to study the interplay between the mechanical and computational aspects in robotic grasping. We believe both sides are important but cannot solve grasping problems on their own, and both sides are highly connected by the laws of physics and should not be developed separately. We use the term "Mechanical Intelligence" to refer to the ability realized by mechanisms to appropriately respond to the external inputs, and we show that incorporating Mechanical Intelligence with Computational Intelligence is beneficial for grasping. The first part of this thesis is to derive hand underactuation mechanisms from grasp data. The mechanical coordination in robot hands, which is one type of Mechanical Intelligence, corresponds to the concept of dimensionality reduction in Machine Learning. However, the resulted low-dimensional manifolds need to be realizable using underactuated mechanisms. In this project, we first collect simulated grasp data without accounting for underactuation, apply a dimensionality reduction technique (we term it "Mechanically Realizable Manifolds") considering both pre-contact postural synergies and post-contact joint torque coordination, and finally build robot hands based on the resulted low-dimensional models. We also demonstrate a real-world application on a free-flying robot for the International Space Station. The second part is about proprioceptive grasping for unknown objects by taking advantage of hand compliance. Mechanical compliance is intrinsically connected to force/torque sensing and control. In this work, we proposed a series-elastic hand providing embodied compliance and proprioception, and an associated grasping policy using a network of proportional-integral controllers. We show that, without any prior model of the object and with only proprioceptive sensing, a robot hand can make stable grasps in a reactive fashion. The last part is about developing the Mechanical and Computational Intelligence jointly --- to co-optimize the mechanisms and control policies using deep Reinforcement Learning (RL). Traditional RL treats robot hardware as immutable and models it as part of the environment. In contrast, we move the robot hardware out of the environment, express its mechanics as auto-differentiable physics and connect it with the computational policy to create a unified policy (we term this method "Hardware as Policy"), which allows RL algorithms to back-propagate gradients w.r.t both hardware and computational parameters and optimize them in the same fashion. We present a mass-spring toy problem to illustrate this idea, and also a real-world design case of an underactuated hand. The three projects we present in this thesis are meaningful examples to demonstrate the interplay between the mechanical and computational aspects of robotic grasping. In the Conclusion part, we summarize some high-level philosophies and suggestions to integrate Mechanical and Computational Intelligence, as well as the high-level challenges that still exist when pushing this area forward

Autonomous Navigation of Automated Guided Vehicle Using Monocular Camera

This paper presents a hybrid control algorithm for Automated Guided Vehicle (AGV) consisting of two independent control loops: Position Based Control (PBC) for global navigation within manufacturing environment and Image Based Visual Servoing (IBVS) for fine motions needed for accurate steering towards loading/unloading point. The proposed hybrid control separates the initial transportation task into global navigation towards the goal point, and fine motion from the goal point to the loading/unloading point. In this manner, the need for artificial landmarks or accurate map of the environment is bypassed. Initial experimental results show the usefulness of the proposed approach.COBISS.SR-ID 27383808