Selective voltammetric determination of electroactive neuromodulating species in biological samples using iron(II) phthalocyanine modified multi-wall carbon nanotubes paste electrode

Iron(II) phthalocyanine (FePc) modified multi-wall carbon nanotubes paste electrodes (MWCNTPEs) were used as voltammetric sensors to selectively detect dopamine (DA) in the presence of serotonin (5-HT). The electrochemical behavior of DA at the new modified electrode was investigated using CV. The enhanced current response of DA indicates that FePc modification of the MWCNTPE surface results in a high catalytic activity for the redox reaction of DA. Differential pulse voltammetry was applied in detection of DA and 5-HT at FePc-MWCNTPE. The method parameters were optimized. Detection limit of 2.05 × 10⁻⁷ M was obtained for DA by using the electrocatalytic oxidation signal corresponding to the Fe^II/Fe^III redox process. The separation between the peak potentials of DA and 5-HT is 170 mV which is large enough for the simultaneously, selective determination of the two chemical species in their mixtures. There was no electrochemical response for ascorbic acid (AA) added in the sample. The monoamine neurotransmitter measuring method has been tested in analyzing deproteinized serum samples.     

Indoor robot gardening: design and implementation

This paper describes the architecture and implementation of a distributed autonomous gardening system with applications in urban/indoor precision agriculture. The garden is a mesh network of robots and plants. The gardening robots are mobile manipulators with an eye-in-hand camera. They are capable of locating plants in the garden, watering them, and locating and grasping fruit. The plants are potted cherry tomatoes enhanced with sensors and computation to monitor their well-being (e.g. soil humidity, state of fruits) and with networking to communicate servicing requests to the robots. By embedding sensing, computation, and communication into the pots, task allocation in the system is de-centrally coordinated, which makes the system scalable and robust against the failure of a centralized agent. We describe the architecture of this system and present experimental results for navigation, object recognition, and manipulation as well as challenges that lie ahead toward autonomous precision agriculture with multi-robot teams.     

Rule-based tools for the configuration of ambient intelligence systems: a comparative user study

Multimedia Tools and Applications - This paper describes a 63-participant user study that compares two widely known systems supporting end users in creating trigger-action rules for the Internet of...     

Managing the requirements flow from strategy to release in large-scale agile development: a case study at Ericsson

In a large organization, informal communication and simple backlogs are not sufficient for the management of requirements and development work. Many large organizations are struggling to successfully adopt agile methods, but there is still little scientific knowledge on requirements management in large-scale agile development organizations. We present an in-depth study of an Ericsson telecommunications node development organization which employs a large scale agile method to develop telecommunications system software. We describe how the requirements flow from strategy to release, and related benefits and problems. Data was collected by 43 interviews, which were analyzed qualitatively. The requirements management was done in three different processes, each of which had a different process model, purpose and planning horizon. The release project management process was plan-driven, feature development process was continuous and implementation management process was agile. The perceived benefits included reduced development lead time, increased flexibility, increased planning efficiency, increased developer motivation and improved communication effectiveness. The recognized problems included difficulties in balancing planning effort, overcommitment, insufficient understanding of the development team autonomy, defining the product owner role, balancing team specialization, organizing system-level work and growing technical debt. The study indicates that agile development methods can be successfully employed in organizations where the higher level planning processes are not agile. Combining agile methods with a flexible feature development process can bring many benefits, but large-scale software development seems to require specialist roles and significant coordination effort.     

An efficient deconvolution algorithm for estimating oxygen consumption during muscle activities

The reconstruction of an unknown input function from noisy measurements in a biological system is an ill-posed inverse problem. Any computational algorithm for its solution must use some kind of regularization technique to neutralize the disastrous effects of amplified noise components on the computed solution. In this paper, following a hierarchical Bayesian statistical inversion approach, we seek estimates for the input function and regularization parameter (hyperparameter) that maximize the posterior probability density function. We solve the maximization problem simultaneously for all unknowns, hyperparameter included, by a suitably chosen quasi-Newton method. The optimization approach is compared to the sampling-based Bayesian approach. We demonstrate the efficiency and robustness of the deconvolution algorithm by applying it to reconstructing the time courses of mitochondrial oxygen consumption during muscle state transitions (e.g., from resting state to contraction and recovery), from the simulated noisy output of oxygen concentration dynamics on the muscle surface. The model of oxygen transport and metabolism in skeletal muscle assumes an in vitro cylindrical structure of the muscle in which the oxygen from the surrounding oxygenated solution diffuses into the muscle and is then consumed by the muscle mitochondria. The algorithm can be applied to other deconvolution problems by suitably replacing the forward model of the system.     

Personalization in cultural heritage: the road travelled and the one ahead

Over the last 20?years, cultural heritage has been a favored domain for personalization research. For years, researchers have experimented with the cutting edge technology of the day; now, with the convergence of internet and wireless technology, and the increasing adoption of the Web as a platform for the publication of information, the visitor is able to exploit cultural heritage material before, during and after the visit, having different goals and requirements in each phase. However, cultural heritage sites have a huge amount of information to present, which must be filtered and personalized in order to enable the individual user to easily access it. Personalization of cultural heritage information requires a system that is able to model the user (e.g., interest, knowledge and other personal characteristics), as well as contextual aspects, select the most appropriate content, and deliver it in the most suitable way. It should be noted that achieving this result is extremely challenging in the case of first-time users, such as tourists who visit a cultural heritage site for the first time (and maybe the only time in their life). In addition, as tourism is a social activity, adapting to the individual is not enough because groups and communities have to be modeled and supported as well, taking into account their mutual interests, previous mutual experience, and requirements. How to model and represent the user(s) and the context of the visit and how to reason with regard to the information that is available are the challenges faced by researchers in personalization of cultural heritage. Notwithstanding the effort invested so far, a definite solution is far from being reached, mainly because new technology and new aspects of personalization are constantly being introduced. This article surveys the research in this area. Starting from the earlier systems, which presented cultural heritage information in kiosks, it summarizes the evolution of personalization techniques in museum web sites, virtual collections and mobile guides, until recent extension of cultural heritage toward the semantic and social web. The paper concludes with current challenges and points out areas where future research is needed.