Προσομοίωση της συμπεριφοράς θερμοηλιακών σταθμών και των θερμοκλινών αποθήκευσης

194 σ.Οι ηλιοθερμικοί σταθμοί παραγωγής ισχύος εκμεταλλεύονται την άμεση ηλιακή ακτινοβολία και παράγουν ατμό τον οποίο χρησιμοποιούν για την παραγωγή ηλεκτρικής ενέργειας κινώντας έναν ατμοστρόβιλο . Η παρούσα εργασία ασχολείται με τις διάφορες τεχνολογίες που χρησιμοποιούν αυτοί οι σταθμοί καθώς και με τα συστήματα αποθήκευσης θερμότητας που εγκαθίστανται σε αυτούς. Πιο συγκεκριμένα προσομοιώνεται η θερμική συμπεριφορά ενός συστήματος αποθήκευσης θερμότητας θερμοκλίνης .The solar thermal power plants operate direct sunlight and generate steam which used to produce electricity by moving a steam turbine. This paper deals with the various technologies that used by these plants as well as heat storage systems installed in them. More precisely the thermal behavior of a thermocline heat storage system is simulated.Ευστράτιος Γ. Παπουτσή

Wildfire danger prediction and understanding with deep learning

The authors thank Fabian Gans who provided the instructions to deploy the data cube in a cloud‐optimized format. Publisher Copyright: © 2022 The Authors.Climate change exacerbates the occurence of extreme droughts and heatwaves, increasing the frequency and intensity of large wildfires across the globe. Forecasting wildfire danger and uncovering the drivers behind fire events become central for understanding relevant climate-land surface feedback and aiding wildfire management. In this work, we leverage Deep Learning (DL) to predict the next day's wildfire danger in a fire-prone part of the Eastern Mediterranean and explainable Artificial Intelligence (xAI) to diagnose model attributions. We implement DL models that capture the temporal and spatio-temporal context, generalize well for extreme wildfires, and demonstrate improved performance over the traditional Fire Weather Index. Leveraging xAI, we identify the substantial contribution of wetness-related variables and unveil the temporal focus of the models. The variability of the contribution of the input variables across wildfire events hints into different wildfire mechanisms. The presented methodology paves the way to more robust, accurate, and trustworthy data-driven anticipation of wildfires.publishersversionpublishe

Wildfire monitoring using satellite images, ontologies and linked geospatial data

Advances in remote sensing technologies have allowed us to send an ever-increasing number of satellites in orbit around Earth. As a result, Earth Observation data archives have been constantly increasing in size in the last few years, and have become a valuable source of data for many scientific and application domains. When Earth Observation data is coupled with other data sources many pioneering applications can be developed. In this paper we show how Earth Observation data, ontologies, and linked geospatial data can be combined for the development of a wildfire monitoring service that goes beyond applications currently deployed in various Earth Observation data centers. The service has been developed in the context of European project TELEIOS that faces the challenges of extracting knowledge from Earth Observation data head-on, capturing this knowledge by semantic annotation encoded using Earth Observation ontologies, and combining these annotations with linked geospatial data to allow the development of interesting applications

The effects of pre-exercise corinthian currants supplementation on antioxidant responses

Τhe use of nutritional supplements before and during a sporting event, especially of a prolonged nature, is very common among competitors and routinely advised by exercise professionals. Corinthian currants have a high carbohydrate content making them a potentially ideal carbohydrate source for prolonged exercise. However, their effectiveness as an ergogenic aid has never been studied.Published versio

Recovery of ergosterol and vitamin D2 from mushroom waste - potential valorization by food and pharmaceutical industries

Background A large amount of mushroom waste is generated during mushroom production (accounting for up to 20% of total production) and is mainly composed of mushrooms that do not meet the specifications set by retailers because of misshapen caps and/or stalks. Mushrooms are notable for their ergosterol (a precursor of vitamin D2) content which is converted to vitamin D2 after exposure to natural or artificial ultraviolet (UV) irradiation. Therefore, mushroom waste could be used as a source for the recovery of both ergosterol and vitamin D2 which could be valorized by both pharmaceutical and food industries. Scope and approach The current review presents a comprehensive summary of research performed regarding the extraction, purification and determination of ergosterol and vitamin D2 (ergocalciferol) from mushroom matrices. Additionally, studies related to the impact of sample preparation and especially of drying methods on the retention of ergosterol and vitamin D2 are presented. Finally, the potential valorization of mushroom waste sterols by food and pharmaceutical industries is discussed. Key findings and conclusions Ergosterol and vitamin D2 contents vary among different mushroom species. Sample drying is a crucial step that precedes sterol extraction and has a significant impact on the retention of ergosterol and vitamin D2. The extraction of sterols from mushrooms can be conducted by either conventional (e.g., Soxhlet extraction) or non-conventional methods (e.g., ultrasound-assisted extraction (UAE), microwave-assisted extraction (MAE), deep eutectic solvents (DES) extraction, supercritical fluid extraction (SFE), and pressurized liquid extraction (PLE)) or their combination. The application of non-conventional methods such as UAE and MAE facilitate in shorter extraction times than the conventional methods. The valorization of mushroom extracts enriched in ergosterol and vitamin D2 by both pharmaceutical and food industries requires further work

Managing big, linked, and open earth-observation data: Using the TELEIOS/LEO software stack

Big Earth-observation (EO) data that are made freely available by space agencies come from various archives. Therefore, users trying to develop an application need to search within these archives, discover the needed data, and integrate them into their application. In this article, we argue that if EO data are published using the linked data paradigm, then the data discovery, data integration, and development of applications becomes easier. We present the life cycle of big, linked, and open EO data and show how to support their various stages using the software stack developed by the European Union (EU) research projects TELEIOS and the Linked Open EO Data for Precision Farming (LEO). We also show how this stack of tools can be used to implement an operational wildfire-monitoring service

Wildfire monitoring via the integration of remote sensing with innovative information technologies

In the Institute for Space Applications and Remote Sensing of the National Observatory of Athens (ISARS/NOA) volumes of Earth Observation images of different spectral and spatial resolutions are being processed on a systematic basis to derive thematic products that cover a wide spectrum of applications during and after wildfire crisis, from fire detection and fire-front propagation monitoring, to damage assessment in the inflicted areas. The processed satellite imagery is combined with auxiliary geo-information layers, including land use/land cover, administrative boundaries, road and rail network, points of interest, and meteorological data to generate and validate added-value fire-related products. The service portfolio has become available to institutional End Users with a mandate to act on natural disasters and that have activated Emergency Support Services at a European level in the framework of the operational GMES projects SAFER and LinkER. Towards the goal of delivering integrated services for fire monitoring and management, ISARS/NOA employs observational capacities which include the operation of MSG/SEVIRI and NOAA/AVHRR receiving stations, NOA's in-situ monitoring networks for capturing meteorological parameters to generate weather forecasts, and datasets originating from the European Space Agency and third party satellite operators. The qualified operational activity of ISARS/NOA in the domain of wildfires management is highly enhanced by the integration of state-of-the-art Information Technologies that have become available in the framework of the TELEIOS (EC/ICT) project. TELEIOS aims at the development of fully automatic processing chains reliant on a) the effective storing and management of the large amount of EO and GIS data, b) the post-processing refinement of the fire products using semantics, and c) the creation of thematic maps and added-value services. The first objective is achieved with the use of advanced Array Database technologies, such as MonetDB, to enable efficiency in accessing large archives of image data and metadata in a fully transparent way, without worrying for their format, size, and location, as well as efficiency in processing such data using state-of-the-art implementations of image processing algorithms expressed in a high-level Scientific Query Language (SciQL). The product refinement is realized through the application of update operations that incorporate human evidence and human logic, with semantic content extracted from thematic information coming from auxiliary geo-information layers and sources, for reducing considerably the number of false alarms in fire detection, and improving the credibility of the burnt area assessment. The third objective is approached via the combination of the derived fire-products with Linked Geospatial Data, structured accordingly and freely available in the web, using Semantic Web technologies. These technologies are built on top of a robust and modular computational environment, to facilitate several wildfire applications to run efficiently, such as real-time fire detection, fire-front propagation monitoring, rapid burnt area mapping, after crisis detailed burnt scar mapping, and time series analysis of burnt areas. The approach adopted allows ISARS/NOA to routinely serve requests from the end-user community, irrespective of the area of interest and its extent, the observation time period, or the data volume involved, granting the opportunity to combine innovative IT solutions with remote sensing techniques and

Operational Wildfire Monitoring and Disaster Management Support Using State-of-the-art EO and Information Technologies

Fires have been one of the main driving forces in the evolution of plants and ecosystems, determining the current structure and composition of the Landscapes. However, significant alterations in the fire regime have occurred in the recent decades, primarily as a result of socioeconomic changes, increasing dramatically the catastrophic impacts of wildfires as it is reflected in the increase during the 20th century of both, number of fires and the annual area burnt. Therefore, the establishment of a permanent robust fire monitoring system is of paramount importance to implement an effective environmental management policy. Such an integrated system has been developed in the Institute for Space Applications and Remote Sensing of the National Observatory of Athens (ISARS/NOA). Volumes of Earth Observation images of different spectral and spatial resolutions are being processed on a systematic basis to derive thematic products that cover a wide spectrum of applications during and after wildfire crisis, from fire detection and fire-front propagation monitoring, to damage assessment in the inflicted areas. The processed satellite imagery is combined with auxiliary geo-information layers and meteorological data to generate and validate added-value fire-related products. The service portfolio has become available to institutional End Users with a mandate to act on natural disasters in the framework of the operational GMES projects SAFER and LinkER addressing fire emergency response and emergency support needs for the entire European Union. Towards the goal of delivering integrated services for fire monitoring and management, ISARS/NOA employs observational capacities which include the operation of MSG/SEVIRI and NOAA/AVHRR receiving stations, NOA’s in-situ monitoring networks for capturing meteorological parameters to generate weather forecasts, and datasets originating from the European Space Agency and third party satellite operators. The qualified operational activity of ISARS/NOA in the domain of wildfires management is highly enhanced by the integra

On the security of consumer wearable devices in the Internet of Things

Miniaturization of computer hardware and the demand for network capable devices has resulted in the emergence of a new class of technology called wearable computing. Wearable devices have many purposes like lifestyle support, health monitoring, fitness monitoring, entertainment, industrial uses, and gaming. Wearable devices are hurriedly being marketed in an attempt to capture an emerging market. Owing to this, some devices do not adequately address the need for security. To enable virtualization and connectivity wearable devices sense and transmit data, therefore it is essential that the device, its data and the user are protected. In this paper the use of novel Integrated Circuit Metric (ICMetric) technology for the provision of security in wearable devices has been suggested. ICMetric technology uses the features of a device to generate an identification which is then used for the provision of cryptographic services. This paper explores how a device ICMetric can be generated by using the accelerometer and gyroscope sensor. Since wearable devices often operate in a group setting the work also focuses on generating a group identification which is then used to deliver services like authentication, confidentiality, secure admission and symmetric key generation. Experiment and simulation results prove that the scheme offers high levels of security without compromising on resource demands

Real-Time Wildfire Monitoring Using Scientific Database and Linked Data Technologies

We present a real-time wildfire monitoring service that exploits satellite images and linked geospatial data to detect hotspots and monitor the evolution of fire fronts. The service makes heavy use of scientific database technologies (array databases, SciQL, data vaults) and linked data technologies (ontologies, linked geospatial data, stSPARQL) and is implemented on top of MonetDB and Strabon. The service is now operational at the National Observatory of Athens and has been used during the previous summer by emergency managers monitoring wildfires in Greece