To develop in vitro models of cells, tissues and organs we have designed and realized a series of cell culture chambers. Each chamber is purpose designed to simulate a particular feature of the in vivo environment. The bioreactor system is user friendly, and the chambers are easy to produce, sterilize and assemble. In addition they can be connected together to simulate inter-organ or tissue cross-talk. Here we discuss the design philosophy of the bioreactor system and then describe its construction. Preliminary results of validation tests obtained with hepatocytes and endothelial cells are also reported. The results show that endothelial cells are extremely sensitive to small levels of shear stress and that the presence of heterotypic signals from endothelial cells enhances the endogenous metabolic function of hepatocytes.
Hepatocyte function on 3-D microfabricated polymer scaffolds realised with the pressure-activated microsyringe was tested under static and dynamic conditions. The dynamic cell culture was obtained using the multicompartment modular bioreactor system. Hepatocyte cell density, glucose consumption, and albumin secretion rate were measured daily over a week. Cells seeded on scaffolds showed an increase in cell density compared with monolayer controls. Moreover, in dynamic culture, cell metabolic function increased three times in comparison with static monolayer cultures. These results suggest that cell density and cell-cell interactions are mediated by the architecture of the substrate, while the endogenous biochemical functions are regulated by a sustainable supply of nutrients and interstitial-like flow. Thus, a combination of 3-D scaffolds and dynamic flow conditions are both important for the development of a hepatic tissue model for applications in drug testing and regenerative medicine.
A generic "system on a plate" modular multicompartmental bioreactor array which enables microwell protocols to be transferred directly to the bioreactor modules, without redesign of cell culture experiments or protocols is described. The modular bioreactors are simple to assemble and use and can be easily compared with standard controls since cell numbers and medium volumes are quite similar. Starting from fluid dynamic and mass transport considerations, a modular bioreactor chamber was first modeled and then fabricated using "milli-molding," a technique adapted from soft lithography. After confirming that the shear stress was extremely low in the system in the range of useful flow rates, the bioreactor chambers were tested using hepatocytes. The results show that the bioreactor chambers can increase or maintain cell viability and function when the flow rates are below 500 microL/min, corresponding to wall shear stresses of 10(-5) Pa or less at the cell culture surface.
The Fitts’ law describes a correlation between the time needed to complete basic tasks such as pointing movements and the level of knowledge of the specific target to be reached. While it has been largely proved in normal gravity, very few experiments have been carried out in altered gravitational conditions. In our experiment, four subjects were positioned in front of a panel where round targets were placed along a circumference. They carried out pointing movements towards the targets when these were switched on. The task time was acquired and processed off-line. In all the cases, the performance of each subject have been significantly modified in the altered gravitational environment and, in particular, hypergravity seems to affect motor performance more considerably than microgravity. Even if experiments involving several subjects and more complex tasks have to be carried out in order to confirm our findings, these results show that ergonomics could be strongly affected by the modification of gravity, especially during the first phase of exposure to gravity alteration.
A model of osmolarity is proposed in this paper. This model represents a typical example of embedded physiological feedback control in physiology. Extensive simulation tests with a compartmental approach (using the specific software SAAM II) have been performed, showing that the model agrees with the findings published in the literature of endocrine physiology and with medical practice. As a relevant example of application of the models, the diabetes insipidus pathology was considered. In the case of central insipidus diabetes, it is possible to predict effects of a therapy, giving out synthetic ADH (where ADH is the antidiuretic hormone, the vasopressine) for restoring homeostatic conditions. Two kinds of therapy were considered: supply by inhalation or by microinfusion. In the first case, we evaluated the effect of inhalation using a two compartmental model to describe the effect of commercial drug (minirin, that means desmopressine acetate), and compared results with data existing in the literature. In the second case, the aim was to have a helping tool in the study and development of micro-infusors with sensors and controllers embedded so as to be able to release a controlled drug quantity, accorded to the patient and optimized for avoiding hyper- or ipo-concentrations of plasma ADH hormone. In this case, we used a mono-compartmental model, considering that the drug is infused directly in the plasma; results are again compared with data existing in the literature and with experimental data.
Low-cost sensing gloves for reconstruction posture provide measurements which are limited under several regards. They are generated through an imperfectly known model, are subject to noise, and may be less than the number of Degrees of Freedom (DoFs) of the hand. Under these conditions, direct reconstruction of the hand posture is an ill-posed problem, and performance can be very poor. This paper examines the problem of estimating the posture of a human hand using(low-cost) sensing gloves, and how to improve their performance by exploiting the knowledge on how humans most frequently use their hands. To increase the accuracy of pose reconstruction without modifying the glove hardware - hence basically at no extra cost - we propose to collect, organize, and exploit information on the probabilistic distribution of human hand poses in common tasks. We discuss how a database of such an a priori information can be built, represented in a hierarchy of correlation patterns or postural synergies, and fused with glove data in a consistent way, so as to provide a good hand pose reconstruction in spite of insufficient and inaccurate sensing data. Simulations and experiments on a low-cost glove are reported which demonstrate the effectiveness of the proposed techniques.
In this paper we study the problem of improving human hand pose sensing device performance by exploiting the knowledge on how humans most frequently use their hands in grasping tasks. In a companion paper we studied the problem of maximizing the reconstruction accuracy of the hand pose from partial and noisy data provided by any given pose sensing device (a sensorized "glove") taking into account statistical a priori information. In this paper we consider the dual problem of how to design pose sensing devices, i.e. how and where to place sensors on a glove, to get maximum information about the actual hand posture. We study the continuous case, whereas individual sensing elements in the glove measure a linear combination of joint angles, the discrete case, whereas each measure corresponds to a single joint angle, and the most general hybrid case, whereas both continuous and discrete sensing elements are available. The objective is to provide, for given a priori information and fixed number of measurements, the optimal design minimizing in average the reconstruction error. Solutions relying on the geometrical synergy definition as well as gradient flow-based techniques are provided. Simulations of reconstruction performance show the effectiveness of the proposed optimal design.
We present an industrial case study in automotive control of significant complexity: the new common rail fuel injection system for Diesel engines, currently under production by Magneti Marelli Powertrain.In this system, an inlet metering valve, introduced before the High Pressure (HP) pump, regulates the fuel flow that supplies the common rail according to the engine operating point (e.g. engine speed, desired torque). The standard approach followed in automotive control is to use a mean–value model for the plant and to develop a controller based on this model.I n this particular case, this approach does not provide a satisfactory solution as the discrete–continuous interactions in the fuel injection system, due to the slow time–varying frequency of the HP pump cycles and the fast sampling frequency of sensing and actuation, play a fundamental role.W e present a design approach based on a hybrid model of the Magneti Marelli Powertrain common–rail fuel–injection system for four-cylinder multi–jet engines and a hybrid approach to the design of a rail pressure controller.T he hybrid controller is compared with a classical mean–value based approach to automotive control design whereby the quality of the hybrid solution is demonstrated.
Approaches to robot motion planning and control that involve tools such as automata, languages, temporal logics, and grammars, have been recently termed "symbolic." In this article, we review some existing results, discuss their relevance and applicability, and outline some of the main open questions and challenges in the area.
A model reference adaptive-sliding mode control is presented and applied for a variable stiffness actuated (VSA) system. The VSA is a flexible stiffness machine with two coupled actuators in each link, and its safety during the movement can be guaranteed by varying both stiffness and the angular variables. Realisation of precise control of two coupled actuators poses a considerable challenge, however, because of uncertain time-varying parameters and unknown variation bounds. In this paper a neuro-sliding mode approach based on model reference adaptive control (MRAC) is proposed. The proposed MRAC control structure induces the VSA to follow its nominal dynamics with help of sliding mode control efforts. The sliding gain, implemented by a simple neural network (NN), is adaptively updated based on the Lyapunov criterion. A control law and adaptive laws for the sliding mode control as well as the weights in the NN are established so that the closed-loop system is stable in the sense of Lyapunov. The tracking errors of both the angular variables and stiffness are managed to guarantee the system to be asymptotically stable rather than uniformly ultimately bounded. And, the feasibility of the proposed control approach is demonstrated by means of experimental results as well as computer simulations.
In this paper we propose a novel policy for steering multiple vehicles between assigned independent start and goal configurations and ensuring collision avoidance. The policy rests on the assumption that agents are all cooperating by implementing the same traffic rules. However, the policy is completely decentralized, as each agent decides its own motion by applying those rules only on locally available information, and totally scalable, in the sense that the amount of information processed by each agent and the computational complexity of the algorithms are not increasing with the number of agents in the scenario. The proposed policy applies to systems in which new vehicle may enter the scene and start interacting with existing ones at any time, while others may leave. Under mild conditions on the initial configurations, the policy is shown to be safe, i.e. to guarantee collision avoidance throughout the system evolution. In the paper, conditions are discussed on the desired configurations of agents under which the ultimate convergence of all vehicles to their goals can also be guaranteed. To show that such conditions are actually necessary and sufficient, which turns out to be a challenging liveness verification problem for a complex hybrid automaton, we employ a probabilistic verification method. The paper finally reports on simulations for systems of several tens of vehicles, and with some experimental implementation showing the practicality of the approach.
