Constantinos Tsanaktsidis

The use of conventional fuels for heat, energy, or motion production is largely determined by the concentration of water in the fuel. Therefore, the knowledge of the moisture content is of particular importance for combustion efficiency. Specifically, the presence of water in fuels can cause corrosion, and during preheating the water vapor can cause extinguishing of the flame, while at low temperatures it can cause blockage of the network by ice that can be formed. In general, the presence of water can contribute to the development of organic and inorganic substrates that may contribute to fuel turbidity, a fact that is addressed by the addition of chemical additives. In the present work, the possibility of removing moisture from heating diesel fuel through the properties of ionic and non-ionic organic polymers, namely polyvinyl alcohol (PVA) and polyethylene oxide (PEO), was studied. The experimental data obtained by the addition of the polymers to the diesel showed that the fuel’s physicochemical properties were within the suitability limits, while the moisture content was decreased from 62 mg/kg to 50 mg/kg and 53 mg/kg, respectively, for PVA and PEO polymers. A mathematical expression of adsorption was used to simulate the experimental findings. In addition, the sulfur content was decreased from 941 mg/kg to 937 mg/kg when PVA was used. The methodology proposed for improving the physicochemical properties of heating diesel through organic polymers can optimize its combustion behavior to be more environmentally friendly.

This paper addresses the critical challenge of energy management for autonomous robots in the context of large-scale photovoltaic parks. The dynamic and vast nature of these environments, characterized by dense, structured rows of solar panels, introduces unique complexities, including uneven terrain, varied operational demands, and the need for equitable resource allocation among diverse robot fleets. The presented framework adapts and significantly extends the Affinity Propagation algorithm for strategic charging station placement within photovoltaic parks. The key contributions include: (1) a multi-attribute grid-based environment model that quantifies terrain difficulty and panel-specific obstacles; (2) an extended multi-factor scoring function that incorporates penalties for terrain inaccessibility and proximity to sensitive photovoltaic infrastructure; (3) a sophisticated, energy-aware consumption model that accounts for terrain friction, slope, and rolling resistance; and (4) a novel multi-agent fairness constraint that ensures equitable access to charging resources across heterogeneous robot sub-fleets. Through extensive simulations on synthesized photovoltaic park environments, it is demonstrated that the enhanced algorithm not only significantly reduces travel distance and energy consumption but also promotes a fairer, more efficient operational ecosystem, paving the way for scalable and sustainable robotic maintenance and inspection.

The precise regulation of water content plays a pivotal role in determining several the critical properties of marine fuels, including combustion stability, corrosion resistance, and the mitigation of pollutant emissions. The present study introduces an innovative, additive-free technique for moisture extraction from Marine Gasoil (MGO) utilizing the hydrophilic polymer polyacrylamide, which leverages its polar amino groups to attract water molecules. This process facilitates the physical extraction of moisture without modifying the fuel’s composition, in contrast to traditional drying techniques or chemical additions. Experimental findings indicate a 34.6% decrease in water content in MGO (from 29.3 mg/kg to 19.15 mg/kg) and a 36.5% reduction in MGO–biodiesel blends (from 32.04 mg/kg to 20.34 mg/kg), accomplished within one hour of treatment. The scientific significance of this work lies in its discovery of polyacrylamide’s ability to retain moisture within a nonpolar fuel matrix—a phenomenon not previously investigated in maritime fuel applications. The findings highlight the potential for further research into polymer–fuel interactions and non-chemical strategies for fuel enhancement. Economically, the proposed technology reduces dependence on costly chemical additives and energy-intensive drying processes, while environmentally, it improves combustion efficiency and lowers emissions of hydrocarbons (HC), carbon monoxide (CO), and smoke. Overall, the results introduce a novel, sustainable, and practical process for improving maritime fuel quality, while supporting compliance with increasingly stringent regional and global environmental regulations.

Nowadays, there is wide advocacy for a transition to circular economic models. Fly Ash (FA) in particular is a major by-product of coal combustion and its annual waste has reached one million tonnes. Cenospheres (CSs) are considered as possibly the most valuable element within FA. Thus, in this research, polymeric foam replication was employed to fabricate ceramic foams based on a CS matrix, for potential biomedical applications. For the fabrication of foams, four types of natural marine sponges were used as templates along with a binder agent. The specimens were sintered at 1200 °C for 1 h. The results were encouraging as the specimens obtained retained the given shape and geometry. Further research will enhance the potential of such materials for future use in biomedical engineering.

Photovoltaic park (PV) and power generator monitoring is a crucial activity that calls for effective coverage path planning. Artificial intelligence and particularly swarm robotics have brought new methods to tasks such as coverage path planning by having multiple robots work together to cover a specific area. Nonetheless, enhancing energy efficiency in these systems continues to be a crucial obstacle, particularly with the growing focus on sustainability. This research investigates techniques to enhance energy efficiency in swarm robotics, focusing on coverage path planning assignments. The proposed approach merges advanced swarm robotics algorithms with energy-efficient methods to reduce power consumption while still ensuring effective coverage. Thorough simulations in simulated environments of Western Macedonia assess the efficiency of the proposed approach. Even though the proposed approach has a longer convergence time compared to a generic ACO approach, the findings of the simulations indicate that the MOACO approach has substantial enhancements up to 22% in path travel time, in terms of solution quality and energy consumption metrics. The findings of the present work offer valuable insights into the design of sustainable robotic systems and underscore the potential of swarm robotics in achieving efficient coverage path planning. This study adds to the overall objective of creating eco-friendly technologies in robotics, leading to upcoming advancements in the industry.

Humanity has consumed large amounts of energy in recent decades. Energy requirements increase continuously, and fossil fuel overuse pollutes the environment extremely. The researchers turned their attention to alternative solutions, such as renewable sources of fuels, which reduce negative emissions. At the same time, biodiesel is produced from environmentally friendly raw materials and is a competitive fuel with acceptable properties. The scientific community investigates new approaches to further improve the physicochemical properties of biodiesel in more economical ways. Artificial intelligence and nature-inspired techniques are particularly capable of searching for optimal fuels in complex optimization fields. The current study concerns a recent review of biodiesel production approaches based on evolutionary computation methods. These methods lead to innovative biodiesel development, costing less with lower sulfur content. Except for the economic profits, the reduction of environmental emissions in praxis confirms biodiesel appropriateness for more consumption than fossil blends. The algorithms’ accuracy and effectiveness were evaluated in various case studies and detailed results were offered in every publication. The optimal fuels are produced in laboratories and tested in common engines too. In the literature, there exists a gap in relation to the financial and environmental aspects of biodiesel fuel production, which should also be investigated.

In the present study, the processing, characterization, and assessment of novel non-alcoholic and sugar-free drinks based on bioactive extracts from valuable natural sources, such as green tea enriched with Chios mastiha, are considered. Currently, the transition towards the consumption of healthy and sustainable food and beverages promoting human health and well-being is strongly encouraged and biologically active compounds from natural resources have a broad range of ap-plications in this sector. In this context, three beverages (all non-alcoholic, non-carbonated, and sugar-free) were created, including extracts of green tea with Chios mastiha, matcha green tea with Chios mastiha and louisa green tea with Chios mastiha, and an evaluation of their biological potential was performed. Specifically, an analysis of water, extracts, and additives for the beverage production was carried out. Microbiological and nutritional value determination was also conducted in samples of the three products. According to the experimental results, the novel health beverage produced from green tea enriched with Chios Mastiha extracts was found to have improved organoleptic characteristics and was microbiologically stable and safe for a period of 180 days from the production date at 25 °C. It is also considered stable and safe for 3 days after production, even if it remains open at 25 °C. In view of a possible scale-up of this application, safety, and preservation control should continue for at least 540 days from the date of production. In conclusion, the current research findings support the development of a novel non-alcoholic sugar-free health drink based on bioactive extracts from green tea enriched with Chios mastiha, to contribute to maintaining human health and also to strengthen the economy.

Oxidative stress is an imbalance between reactive oxygen species production and antioxidant defense that can lead to reproductive disorders and poor pregnancy outcomes. Environmental pollution under climate change is involved in reactive oxygen species formation and may cause various dysfunctions of the reproductive system. Oxidative stress is a widespread factor that affects the physiology of the male and female reproductive systems, leading to high levels of DNA damage and infertility. Miscarriage, preeclampsia, and premature birth are all linked to oxidative stress. Environmental pollution induces excesses of oxidative stress by expanding ROS generation or overwhelming the physiological responses of the antioxidant defense system. This increases cellular damage, inflammation, and the development of numerous diseases. Here, we present a brief outline of the physiological and developmental roles that oxidative stress plays during pregnancy. We also offer some insights into the underlying mechanisms that have been put forth, which culminate in a summary of the harmful effects of oxidative stress that have an environmental origin in pregnancy-related complications. The current work may motivate the design of more focused wellbeing measures in order to prevent and promote human health and anticipate unfavorable pregnancy outcomes.