Chemical analysis of Greek pollen - Antioxidant, antimicrobial and proteasome activation properties

<p>Abstract</p> <p>Background</p> <p>Pollen is a bee-product known for its medical properties from ancient times. In our days is increasingly used as health food supplement and especially as a tonic primarily with appeal to the elderly to ameliorate the effects of ageing. In order to evaluate the chemical composition and the biological activity of Greek pollen which has never been studied before, one sample with identified botanical origin from sixteen different common plant taxa of Greece has been evaluated.</p> <p>Results</p> <p>Three different extracts of the studied sample of Greek pollen, have been tested, in whether could induce proteasome activities in human fibroblasts. The water extract was found to induce a highly proteasome activity, showing interesting antioxidant properties. Due to this activity the aqueous extract was further subjected to chemical analysis and seven flavonoids have been isolated and identified by modern spectral means. From the methanolic extract, sugars, lipid acids, phenolic acids and their esters have been also identified, which mainly participate to the biosynthetic pathway of pollen phenolics. The total phenolics were estimated with the Folin-Ciocalteau reagent and the total antioxidant activity was determined by the DPPH method while the extracts and the isolated compounds were also tested for their antimicrobial activity by the dilution technique.</p> <p>Conclusions</p> <p>The Greek pollen is rich in flavonoids and phenolic acids which indicate the observed free radical scavenging activity, the effects of pollen on human fibroblasts and the interesting antimicrobial profile.</p

Elastic Networks in Reshaping Human Intentions by Proactive Social Robot Moves

This paper focuses on reshaping a previously detected human intention into a desired one, using contextual motions of mobile robots, which are in our applications, autonomous mobile 2-steps stairs and a chair. Our system first estimates the current intention based on human heading and trajectory depicted as orientation and location. Our previous reshaping applications have shown that the current human intention has to be deviated towards the new desired one in phases. In our novel approach, Elastic network generates way points of trajectories each of which acts as transient trajectories directed towards the desired intention's location. Our methodology aims at generating an "intention trajectory" towards the final goal. The initial way points possess destabilizing effects on the obstinance of the person intention making the "robot gain the curiosity and the trust of the person". Each way point generated by the elastic network is executed by moves of an adequate robot (here mobile 2-steps or chair) in adequate directions (towards coffee table, PC, TV, library). After each robot moves, the resulting human intention is estimated and compared to the desired goal in the intention space. Intention trajectories are searched in two modes: the "confident mode" and the "suspicious mode" which are defining human body-mood detected relying on proxemics. This paper analyzes our novel approach of planning trajectories via elastic networks based on these two modes

Genetically tuned fuzzy scheduling for flexible manufacturing systems.

This paper focuses on the development and implementation of a Genetically Tuned Fuzzy Scheduler (GTFS) for heterogeneous FMS under uncertainty. The scheduling system takes input from a table and creates an optimum master schedule. The GTFS uses fuzzy rulebase and inferencing where fuzzy sets are generated by a genetic algorithm to tune the optimization. The fuzzy optimization is based on time criticality in deadline and machine need, taking into account machine availability, uniformity, process time and selectability