54 research outputs found

    Approaches to the application of unmanned aerial systems in the field of maritime industry and education

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    The modern possibilities for using "drone" technology and its increasing availability have been studied. Possible practical aspects of the application of unmanned aerial systems (UASs) in the maritime industry and education are revealed. The article clarifies the capacity of the UASs as modern technology and pedagogical lever. The author's practical approach to increasing the educational process's efficiency in maritime training through the innovative use of UAVs is shared. The author presents the economically accessible aviation "drone" capabilities as a means of observation, inspection, and pedagogical interaction with students in a natural environment

    Photodynamic therapy using Luciferase nanoconjugate as a treatment for colon cancer

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    Photodynamic Therapy (PDT) has proven itself in previous studies to be a successful therapeutic treatment for surface tumors, but its effectiveness is limited to only shallow depths that allow for the penetration of light. This study demonstrates that we have improved upon the conventional method of PDT and have overcome the previous depth limitation by creating the light at the location of the tumor in situ. We conjugated a bioluminescent protein, Luciferase, to a semiconductor nanoparticle, TiO2, and with a cell specific antibody, anti-EGFR monoclonal antibody C225. The nanoconjugate, TiDoL-C225, was then activated by ATP and Luciferin in a reaction that creates reactive oxygen species (ROS) and induces apoptosis in the tumor cells. We created the optimal nanoconjugate synthesis protocol to make TiDoL and TiDoL-C225 for use in the PDT treatment. The TiDoL-C225 nanoconjugate is able to bind specifically to colon caner cells as the C225 antibody recognizes EGFR expressed at the surface of the cells, and further, when activated it will react only with the tumor cells. The optimal cell staining protocols were developed to visualize the treatment process and later analyze with the laser confocal microscope. The TiDoL nanoconjugate was found to only be operational and effective at killing tumor cells after being activated by Luciferin and ATP, which then enhances the control we have over the therapy. The TiDoL-C225 nanoconjugate increases the efficacy of binding to tumor cells and the speed of the reaction in the cells to begin apoptosis, even in lower concentrations when compared to the free TiDoL nanoconjugate. Finally, our PDT technique allowed us to monitor the tumor cells as they begin to undergo apoptosis in less than five minutes after the Luciferin was added to activate the reaction. The advantage of our method of PDT with the TiDoL-C225 nanoconjugate is that it can be used for early detection as well as developed into an effective treatment for cancers in all depths of tissue

    Identifying Most Probable Negotiation Scenario in Bilateral Contracts with Reinforcement Learning

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    This paper proposes an adaptation of the Q-Learning reinforcement learning algorithm, for the identification of the most probable scenario that a player may face, under different contexts, when negotiating bilateral contracts. For that purpose, the proposed methodology is integrated in a Decision Support System that is capable to generate several different scenarios for each negotiation context. With this complement, the tool can also identify the most probable scenario for the identified negotiation context. A realistic case study is conducted, based on real contracts data, which confirms the learning capabilities of the proposed methodology. It is possible to identify the most probable scenario for each context over the learned period. Nonetheless, the identified scenario might not always be the real negotiation scenario, given the variable nature of such negotiations. However, this work greatly reduces the frequency of such unexpected scenarios, contributing to a greater success of the supported player over time.This work has received funding from National Funds through FCT (Fundaçao da Ciencia e Tecnologia) under the project SPET – 29165, call SAICT 2017.info:eu-repo/semantics/publishedVersio

    Nord Pool Ontology to Enhance Electricity Markets Simulation in MASCEM

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    This paper proposes the use of ontologies to enable information and knowledge exchange, to test different electricity market models and to allow players from different systems to interact in common market environments. Multi-agent based software is particularly well fitted to analyse dynamic and adaptive systems with complex interactions among its constituents, such as the complex and dynamic electricity markets. The main drivers are the markets’ restructuring and evolution into regional and continental scales, along with the constant changes brought by the increasing necessity for an adequate integration of renewable energy sources. An ontology to represent the concepts related to the Nord Pool Elspot market is proposed. It is validated through a case study considering the simulation of Elspot market. Results show that heterogeneous agents are able to effectively participate in the simulation by using the proposed ontologies to support their communications with the Nord Pool market operator.This work has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No. 641794 (project DREAM-GO) and from FEDER Funds through COMPETE program and from National Funds through FCT under the project UID/EEA/00760/2013.info:eu-repo/semantics/publishedVersio
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