TG, FT-IR and NMR characterization of n-C16H34 contaminated alumina and silica after mechanochemical treatment

This paper deals with the application of mechanochemistry to model systems composed of alumina or silica artificially contaminated with n-C16H34. The mechanochemical treatment was carried out by means of a ring mill for times ranging from 10 to 40 h. Thermogravimetry and infrared and nuclear magnetic resonance spectroscopies were used for the characterization of the mechanochemical products. The results have indicated that, in the case of alumina, almost all the contaminant n-C16H34 undergoes a complex oxidative reaction path whose end products are strongly held on the surface. These end products are most likely made of crosslinked, partially oxidized hydrocarbon chains bond to the solid surface via COO− groups. In the case of silica, the hydrocarbon undergoes a different, equally complex reaction path, but to a lower extent. In this case the end products are most probably carbonylic compounds and graphitic carbon. Then, for both solid matrices, the mechanochemical treatment promotes significant modification of the chemical nature of the polluting hydrocarbon with end products much more difficult to remove from the surface. As the systems studied are models of sites contaminated by aliphatic hydrocarbon, the results are worthy of consideration in relation to the mobility of the contaminants in the environment

How to exploit abstract user interfaces in MARIA

In model-based approaches, Abstract User Interfaces enable the specification of interactive applications in a modality-independent manner, which is then often used for authoring multi-device interactive applications. In this paper we discuss two solutions for exploiting abstract UIs. We consider the MARIA language for such comparison. The overall aim is to improve the efficiency of the model-based process, thus making it easier to adopt and apply

How to exploit abstract user interfaces in MARIA

In model-based approaches, Abstract User Interfaces enable the specification of interactive applications in a modality-independent manner, which is then often used for authoring multi-device interactive applications. In this paper we discuss two solutions for exploiting abstract UIs. We consider the MARIA language for such comparison. The overall aim is to improve the efficiency of the model-based process, thus making it easier to adopt and apply

An Adaptive Behaviour-Based Strategy for SARs interacting with Older Adults with MCI during a Serious Game Scenario

The monotonous nature of repetitive cognitive training may cause losing interest in it and dropping out by older adults. This study introduces an adaptive technique that enables a Socially Assistive Robot (SAR) to select the most appropriate actions to maintain the engagement level of older adults while they play the serious game in cognitive training. The goal is to develop an adaptation strategy for changing the robot's behaviour that uses reinforcement learning to encourage the user to remain engaged. A reinforcement learning algorithm was implemented to determine the most effective adaptation strategy for the robot's actions, encompassing verbal and nonverbal interactions. The simulation results demonstrate that the learning algorithm achieved convergence and offers promising evidence to validate the strategy's effectiveness

A set of languages for context-aware adaptation

The creation of service front ends able to adapt to the context of use involves a wide spectrum of aspects to be considered by developers and designers. A context-aware adaptation enabled application needs a simultaneous management of very different application functionalities, such as the context sensing, identifying different given situations, determining the appropriate reactions and the execution of the adaptation effects. In this paper we describe an adaptation architecture for tackling this complexity and we present a set of languages that address the definition of the various aspects of an adaptive application