Effect of active components from Garlic on AGEs formation

Advanced glycation end-products are Maillard reaction products that are found in thermal processed food. This compounds are often referred as unhealthy for human diet, namely because of their capacity to form amino-acid dimers. There is a broad range of answers to get about how these products are formed, how they interact with the organism and how these reactions can be inhibited to prevent the referred effects. Some compounds from garlic are thought to be able to inhibit these reactions. This study using spectrophotometric, High Performance Liquid Chromatography-Tandem Mass Spectrometry (HPLC-MS/MS) and Fourier transformed infrared spectroscopy (FTIR) analysis, helps to understand better not only not only the effect of some compounds obtained from garlic, diallyl sulfide (DAS), diallyl disulfide (DADS) and diallyl trisulfide (DATS), on these AGEs production reaction, but also helped to understand better the reaction itself.

Dynamic Analysis and Pattern Visualization of Forest Fires

This paper analyses forest fires in the perspective of dynamical systems. Forest fires exhibit complex correlations in size, space and time, revealing features often present in complex systems, such as the absence of a characteristic length-scale, or the emergence of long range correlations and persistent memory. This study addresses a public domain forest fires catalogue, containing information of events for Portugal, during the period from 1980 up to 2012. The data is analysed in an annual basis, modelling the occurrences as sequences of Dirac impulses with amplitude proportional to the burnt area. First, we consider mutual information to correlate annual patterns. We use visualization trees, generated by hierarchical clustering algorithms, in order to compare and to extract relationships among the data. Second, we adopt the Multidimensional Scaling (MDS) visualization tool. MDS generates maps where each object corresponds to a point. Objects that are perceived to be similar to each other are placed on the map forming clusters. The results are analysed in order to extract relationships among the data and to identify forest fire patterns.

Formation Control Driven by Cooperative Object Tracking

In this paper we introduce a formation control loop that maximizes the performance of the cooperative perception of a tracked target by a team of mobile robots, while maintaining the team in formation, with a dynamically adjustable geometry which is a function of the quality of the target perception by the team. In the formation control loop, the controller module is a distributed non-linear model predictive controller and the estimator module fuses local estimates of the target state, obtained by a particle filter at each robot. The two modules and their integration are described in detail, including a real-time database associated to a wireless communication protocol that facilitates the exchange of state data while reducing collisions among team members. Simulation and real robot results for indoor and outdoor teams of different robots are presented. The results highlight how our method successfully enables a team of homogeneous robots to minimize the total uncertainty of the tracked target cooperative estimate while complying with performance criteria such as keeping a pre-set distance between the teammates and the target, avoiding collisions with teammates and/or surrounding obstacles.