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This paper illustrates a study for the reuse of selected historic buildings in the Medieval City of Rhodes in Greece. This study contributes to the understanding and interpretation of the chronological sequence of major intervention programs for the preservation of the Medieval City. The main idea of the project is the spatial distribution of compatible and various uses to reveal the unique character of the Medieval City. Spatial planning is proposed within the preserved urban zones in order to optimize and harmonize the selected uses according to the needs of sustainable urban development. Criteria to assess the compatible uses that ensure the features and architectural characteristics of the preselected historic buildings, located within the city fabric, were established and validated. The developed methodology that is presented herein and is an indispensable part of a pilot project may be applicable to other cases concerning historic cities. Finally, this paper aims to present a pilot program which promotes the reuse of historic buildings as a part of an integrated preservation plan. Inter-disciplinarity has set the basis for effective policies to guide and control the proposed pilot program, with ultimate objective to ensure sustainable preservation of the Medieval City of Rhodes. [ABSTRACT FROM AUTHOR]

Businesses affected by the pandemic have realized the importance of incorporating digital transformation into their operations. However, as a result of the market lockdown, they realized that they needed to digitalize their firms immediately and make greater attempts to enhance their economic situation by integrating a greater number of technological components. While there have been numerous studies conducted on the adoption of digital transformation in small–medium enterprises, there has been no research carried out on the implementation of digital transformation in the specific industry of driving schools. This paper investigates the significance of digital transformation, as well as the potential for its application in this industry's business setting and the ways in which it can be utilized to improve innovation capabilities and performance. The data for this study came from 300 driving instructors in Greece and Cyprus. Multivariate regression analysis was used to analyze the data. The outcomes suggest that driving schools have a generally positive reaction to and acknowledgement of the increasing speed of digital transformation. The results also give driving school owners useful information that helps them show how important digital transformation is to their businesses. Using the findings of this study, driving schools will be able to improve their operational capabilities and accelerate their development in the post-COVID era. [ABSTRACT FROM AUTHOR]

Recent changes in the fossil-fuel energy sector require coal mining industries to plan for the future, including developing procedures for decommissioning and closure associated with mines. In surface coal mining, the geotechnical issues of decommissioning include the long-term stability of the pit slopes, particularly as the pit is gradually filled with water. This paper investigates such slope stability issues, with emphasis on the conditions prevailing in the Amyntaion surface lignite mine, in Western Macedonia, Greece. Analytical and numerical methods have been developed and used to estimate the temporal evolution of the overall safety factor, as the water level in the pit rises, creating a lake. It is shown that until the water level in the lake reaches a critical depth of approximately 15–35% of the final equilibrium condition, the safety factor against the overall slope instability decreases slightly (by about 3% in the case study, and up to 5–10% in other conditions) compared to its value at the end of exploitation. At higher lake levels, the safety factor increases significantly, as the beneficial effect of the lake water pressure acting on the slope overcomes the adverse effect of pore water pressure rise inside the slope. In typical mines, the critical water depth is achieved within a few years, since the surface area of the pit is smaller at deeper levels; thus, more favorable slope stability conditions are usually reinstated a few years after mine closure, while the small reduction in safety during the initial stages after closure is inconsequential. The paper investigates the parameters influencing the magnitude of the small reduction in the short-term safety factor and produces normalized graphs of the evolution of the safety factor as the lake water level rises. The results of the analyses can be used in preliminary closure studies of surface coal mines. [ABSTRACT FROM AUTHOR]

The focus of experiential tourism is for the consumer or visitor to experience the tourist destination and to actively interact with local people, cultures, and the place itself. In fact, it can be seen as a form of tourism that builds upon place identities, both tangible and intangible, by energetically introducing the visitor to the culture, history, nature, traditions, cuisine, and social life of a place. In doing so, the emotional, physical, or spiritual experience of the consumer becomes a dynamic source of place branding. The paper investigates the main features of experiential tourism in the Greek regions of Central Macedonia, and Eastern Macedonia and Thrace, and discusses their interactions with place identity. Our methodology consists of a qualitative survey based on semi-structured interviews with stakeholders and a thematic analysis to trace the main features of the experiential product and enterprises that develop such products. The paper concludes that experiential tourism in Greece bears many of the features highlighted in the literature. Furthermore, our findings underline some new aspects, especially the links between the experiential product, small and well-qualified enterprises, and a place's tangible and intangible identities, which make experiential tourism an opportunity for locales and their branding. [ABSTRACT FROM AUTHOR]

This paper aims at tackling how the bilateral contracts affect wholesale electricity markets. It examines different levels of bilateral contracts among producers and demand aggregators, aiming to quantify their effect. In addition, it focuses on markets where bilateral contracts could be used as a tool by market participants with a dominant position. Further, the paper examined a case with asymmetrical portfolios, namely where a market participant has a dominant position as in case of Greece, aiming to investigate if bilateral contracts can be used as a tool to manipulate the market. The simulations have been done by an optimization model that provides the economic dispatch and clearing of the day-ahead electricity market. The model incorporated bilateral contracts with committed generating capacity from producers, as well as dynamic bidding strategy per market participant. Results provide useful insights on the design of electricity markets, especially in case of designing voluntary energy exchanges where a market participant has a dominant position. [ABSTRACT FROM AUTHOR]

This paper seeks to underline the driving factors of farmers' engagement in Participatory Research Projects (PRPs). This is a critical issue for formulating efficient and effective technology transfer channels, essential for improving the operational status of agricultural holdings. A survey was conducted on a sample of 326 Greek arable crops farmers. An explanatory framework consisting of three major factor categories and 11 variables was developed. A logistic regression analysis empirically tests the effect of the variables on the participation of farmers in PRP. Furthermore, the relative importance of variables and factors is extracted with the Shapley–Owen decomposition analysis. The results show that Farmers' Willingness and Social Influences are the factors that mostly affect their decision to engage in a PRP. The farmers' ability consisting of socioeconomic and demographic variables has a small effect on their decision-making process. The estimated effects can help decision-makers to shape and prioritize more targeted policies for farmers' engagement in research. Additionally, this paper sets the basis for shifting research from simple estimations of the effect of variables on farmers' decision-making, to a more comprehensive estimation that also accounts for the strength of these relationships. The paper fills a gap in the literature of studies on farmers' decisions for participating in PRPs, by developing and testing an explanatory framework which also accounts for the relative importance of each factor/variable. [ABSTRACT FROM AUTHOR]

This paper will attempt to visualize adult refugees and migrants, as well as a specific multilingual and multicultural educational setting in Greece. This study aspires to depict/present the plurilingual profiles, language needs, and challenges of L2 Greek students through a variety of tools/methods, e.g., questionnaires, portraits, narratives, needs analysis, and assessment tools. In a complementary way, this research focuses on highlighting the value of language portraits, identity texts, and translanguaging in L2 Greek classrooms. Conditions regarding the educational process in the specific educational setting will also be discussed. This was a case study conducted in an open school for migrants in Greece. Eight volunteer teachers at the school and twenty students participated in this research through a multimethod research design. Multilingual profiles and learners' needs and goals became visible, and the teachers managed to "hear" the multilingual voices of their students and understand their multilingual profiles. Overall, it is clear that these findings pave the way for large-scale research to investigate in depth everything presented in this research. Using language portraits and identity texts as group activities helps to conduct a productive discussion in the classroom, through which students gain access to the use of concepts such as "multilingualism", "multiculturalism", and "diversity". [ABSTRACT FROM AUTHOR]

This paper develops a multi-sector computable general equilibrium (CGE) model with specific features for Greece and the non-EU Rest of the World (RoW). The novelty of this work stems from the lack of energy-focused CGE models for Greece in the current literature. The study's objective is to determine how the Greek economy would react if a 30% import tariff and a quota of 67% on energy imports and 35% on remaining imports were implemented. Furthermore, if quotas and tariffs are in force, the Greek economy will initiate countermeasures by increasing investment in renewable energies through substitution and a 35% subsidy. To quantify this, the 2015 Input-Output (I-O) table for Greece and the non-EU RoW was used. To offer a better understanding, the 36 production sectors have been divided into Agriculture, Energy, Manufacturing, and Services. The quota scenario resulted in a reduction in all sectors in domestic production in terms of output and domestic uses, with some sectors experiencing around a 30% reduction. Renewable energy investments, on the other hand, have proven to be effective for domestic production, increasing output and domestic uses by (6.561%) and (7.886%), respectively. In terms of import tariffs, prices have increased, resulting in a significant decrease in household consumption that exceeds 30% in several sectors. Finally, policy recommendations for addressing these trade barriers and Greece's renewable energy opportunities are proposed. [ABSTRACT FROM AUTHOR]

This paper presents a holistic guiding methodology for the development of a geospatial tool to be used for the documentation, planning, smart management and dissemination of a country's network of historic hiking trails. To deal with the challenges and to ensure the sustainability of a historic site, geospatial documentation merging authoritative and crowdsourced data and a WebGIS-based spatial analysis is necessary. Geospatial data collection should include professional field surveys, professional and crowdsourced photographic documentation and video recording of the existing historic walking/hiking trails. A geodatabase, structured using relational model technology, including vector spatial entities (feature classes), mosaics (raster) and tabulated data (geodatabase tables), should be developed on a commercial or open platform; in this case, the ArcGIS Pro is used. Entities with embedded descriptive information and metadata for the technical, legal, historical, and administrative context may then be created. An object-oriented data model is needed to connect spatial and descriptive information. Spatial and descriptive queries or correlations between attribute fields of spatial entities must be enabled for specialized information retrieval by either experts or users. Next, a web GIS application to present the developed geodatabase in a visually appealing and informative way is created. It should integrate 2D maps with built-in tools and should support advanced functionalities, such as: (i) pop-ups that display brief information and images about specific spots along the trails; (ii) dynamic visualization of the vertical profile of each trail; (iii) multimedia information about landmarks, natural features and scenic viewpoints. Finally, the tool includes a feedback service and continuous efficiency monitoring and assessment, and enables adjustments, if and where needed. The tool is tested and used for 10 historical walking/hiking trails of the archaeological and Holy Site of Meteora, Central Greece. This is a UNESCO World Heritage site. The network, with a total length of 35 km, leads to six monasteries, still active since the 12th century, passing by gigantic rocks and beautiful natural landscapes. The site is famous globally and the greater area is continuously overcrowded with visitors. The tool is anticipated to be used for the documentation and management of the whole walking/hiking historic trail network of Greece in the future. [ABSTRACT FROM AUTHOR]

In recent times, the power sector has become a focal point of extensive scientific interest, driven by a convergence of factors, such as mounting global concerns surrounding climate change, the persistent increase in electricity prices within the wholesale energy market, and the surge in investments catalyzed by technological advancements across diverse sectors. These evolving challenges have necessitated the emergence of new imperatives aimed at effectively managing energy resources, ensuring grid stability, bolstering reliability, and making informed decisions. One area that has garnered particular attention is the accurate prediction of end-user electricity load, which has emerged as a critical facet in the pursuit of efficient energy management. To tackle this challenge, machine and deep learning models have emerged as popular and promising approaches, owing to their having remarkable effectiveness in handling complex time series data. In this paper, the development of an algorithmic model that leverages an automated process to provide highly accurate predictions of electricity load, specifically tailored for the island of Thira in Greece, is introduced. Through the implementation of an automated application, an array of deep learning forecasting models were meticulously crafted, encompassing the Multilayer Perceptron, Long Short-Term Memory (LSTM), One Dimensional Convolutional Neural Network (CNN-1D), hybrid CNN–LSTM, Temporal Convolutional Network (TCN), and an innovative hybrid model called the Convolutional LSTM Encoder–Decoder. Through evaluation of prediction accuracy, satisfactory performance across all the models considered was observed, with the proposed hybrid model showcasing the highest level of accuracy. These findings underscore the profound significance of employing deep learning techniques for precise forecasting of electricity demand, thereby offering valuable insights with which to tackle the multifaceted challenges encountered within the power sector. By adopting advanced forecasting methodologies, the electricity sector moves towards greater efficiency, resilience and sustainability. [ABSTRACT FROM AUTHOR]

This paper deals with the creation, in realistic terms, of an offshore wind farm between the Greek islands of Karpathos and Kassos in the Dodecanese complex. In this context, the terms and conditions for the possible existence of an offshore wind park in Greece are analyzed; the technical components of such a project are described; the offshore wind farm, which was designed by the authors, is presented in detail; and the location selected for its installation is assessed. Moreover, the benefits for the islands of Karpathos and Kassos and for the Greek State, as well as financial data adapted to this specific offshore wind farm and SWOT analysis for the two phases of the project, are presented. The authors conclude that an investment in this project would be viable in economic terms and feasible, despite it being a small-scale project. [ABSTRACT FROM AUTHOR]

Kos is the third largest island of the Dodecanese, located in the southeastern Aegean Sea, Greece. The island's remarkable location both in a prominent geodynamic space and at a crossroads of East, West and South has endowed it with a unique wealth of geological, biological, cultural, and traditional heritage. Steep mountain ranges consisting of Alpine Mesozoic rocks alternate with low-altitude plateaus featuring marine and lacustrine sediments that contain fossils of past life. In addition, the transition of barren land to lush forests where numerous species of flora and fauna thrive is unique to Greek ecosystems. This environment hosted civilizations and activities that gradually led to the present-day cultural and religious state of the island, where people and nature coexist respectfully on one of the country's most favourite destinations. In an effort to further enhance the public's awareness of the geo-cultural heritage of Kos, an online ESRI Hub was created, featuring several individual ESRI StoryMaps web apps regarding each specific aspect of the island's heritage. The goal of this paper is to discuss the importance of using such means for disseminating geoscientific information to the public, to describe the methods used and to give a brief presentation of its content. [ABSTRACT FROM AUTHOR]

In this paper, we present a systematic GIS-based approach for producing updated, upscaled, unified and reevaluated maps for the Ionian Islands of Greece, which is an area of great geological interest. In particular, Cephalonia and Lefkada are two islands with an increased and intense seismicity. Therefore, a common GIS geodatabase was produced for handling the geoinformation of the area. New upscaled (scale 1:50,000) geotechnical and seismotectonic maps of these islands were produced based on older ones. On the other hand, the corresponding maps of the islands, based on the categories of the Greek antiseismic code and Eurocode 8, were produced in an effort to correlate them. Beyond that, all the available isoseismal maps of the earthquakes that hit the Ionian Islands were gathered in an effort to evaluate them and to find possible correlations with the other types of maps. Based on the correlation results, the consideration of the Vs30 parameter in the Greek antiseismic code is proposed for a better categorization of the geological formations. [ABSTRACT FROM AUTHOR]

A new assessment method named GEOAM (geoeducational assessment method), that will be a useful tool for highlighting the geoeducational and geoethical value of a geosite, is proposed. This method takes into account, initially, 11 criteria, which are grouped into 8 categories. Each criterion addresses a different aspect of the geosite's potential for promoting sustainable development, environmental management, and education. A simplified scoring system using a scale of 1–5 is used, where each criterion is scored based on the degree to which it is presented or implemented. The method was piloted in eight geotopes of the Kalymnos Island and five geotopes of the Nisyros Island, in the SE Aegean Sea, Greece. The implementation of this assessment method highlighted the geoeducational value of these geosites. Based on the criteria and subcriteria incorporated in GEOAM, this paper discusses GEOAM's potential to promote sustainable development and rational environmental management by directing educators and stakeholders toward actions that conserve and protect geoheritage for future generations, while also contributing to the economic, social, and cultural development of the surrounding communities. By quantifying the geoeducational potential of geosites and integrating essential concepts such as geoconservation and geoethics, the implementation of this new assessment method can benefit the educational community, tourism industry, and environmental conservation efforts. [ABSTRACT FROM AUTHOR]

This paper presents the development of a fuel model that can describe fuel situations in areas dominated by Cistus spp. (rockrose) in Greece. In order to obtain the necessary fuel data, thirty (30) 1 m2 plots were destructively sampled in phryganic areas dominated by Cistus creticus, Cistus parviflorus, and Cistus salvifolius in western Greece. To develop the fuel model for Cistus spp., field measurements were supplemented with published parameter values for Cistus salvifolius. The resulting fuel model (with a height of 9.44 cm) is suitable for describing Cistus spp.-dominated phryganic areas of relatively low vegetation height in southeastern Europe. Once developed, the fuel model was inputted into the BehavePlus system to produce surface fire rate of spread predictions (ROSpred, m·min−1), which were then compared to 21 surface fire ROS field observations (ROSobs) obtained from wildfires or prescribed burns in areas covered by Cistus spp. It was found that the ROS for the Cistus spp. fuel model significantly underpredicted the actual ROS. A statistically significant linear regression equation was developed to mathematically describe the relationship between the predicted and observed ROS. This equation can be used to adjust BehavePlus predictions to more accurately reflect the real-world fire behavior for this fuel type. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to highlight the application of TQM in primary education (PE) by exploring teachers' views and, more specifically, by examining the impact of their demographic data on their attitude towards TQM. A study was conducted among teachers in Greek public primary schools with the aim being to investigate their views on seven TQM parameters. The study used a structured questionnaire that was positively evaluated for validity and reliability. In total, 2088 completed questionnaires were collected, and non-parametric tests were employed. The results reveal statistically significant differences among groups of respondents based on gender, job–position, educational level, age, and years of experience in PE, as well as geographical location of the school. The study provides real-time empirical evidence of TQM in PE, enriching the existing literature, which lacks empirical and validated data from the PE level. The data revealed by the study indicate differences in perception of the TQM concept and its application among the participants, and their response should be further analysed to explore the reasons that generate them and, thus, facilitate the initiation of TQM practices within a PE school environment. [ABSTRACT FROM AUTHOR]

Arbutus andrachne, the Greek strawberry tree, is an evergreen shrub or small tree in the family Ericaceae native to the Mediterranean basin, and is a valuable phytogenetic resource. In the context of sustainable exploitation of A. andrachne, four Greek natural populations of species were selected and a detailed germination protocol, molecular analysis, and cultivation practices were reported herein for the first time. The 1 month period of cold stratification or the treatment with gibberellic acid resulted in similar patterns of seed germination over a wide temperature range for all four populations. Differences among the four populations were observed in five of six morphological traits measured in 1-year-old seedlings. The 2-year-old plants grown in plastic bags (2.26 L in volume) showed superior growth rates. Foliage, but not roots, of 2-year-old seedlings supplemented with mineral fertilizers had higher fresh masses than untreated seedlings. The four A. andrachne accessions exhibited more genetic variability within than among populations. [ABSTRACT FROM AUTHOR]

The EU energy and climate policy has set quantitative goals for decarbonization based on the energy efficiency and the evolution of energy systems. The utilization of demand side flexibility can help towards this direction and achieve the target of higher levels of penetration in regard to intermittent renewable energy production and carbon emission reduction. This paper presents a simulation-based assessment of thermal flexibility in a typical office building in Greece, which is a representative Mediterranean country. The use of variable speed heat pumps coupled with hydronic terminal units was evaluated. The research focused mainly on the evaluation of energy flexibility offered by energy stored in the form of thermal energy by utilizing the building's thermal mass. The demand response potential under hourly CO2eq intensity and energy prices was investigated. The flexibility potential was evaluated under different demand response strategies, and the effect of demand response on energy consumption, operational costs, CO2eq emissions and thermal comfort was analyzed and discussed. The results showed that both control strategies based on both the CO2eqintensity signal and spot price signal have, in some cases, the potential for cost and emission savings, and in other cases, the potential to depreciate in terms of emissions and cost the increase of energy consumption due to load shifting. [ABSTRACT FROM AUTHOR]

Simple Summary: This study refers to the mapping the dairy sheep and goat industry in Greece, in which information was obtained from 325 sheep and 119 goat farms. The findings can be used as baseline measurements; individual farms and cohorts of farms can be compared against the current results to draw conclusions against the countrywide situation. The results can also be used as reference points for the future, in order to assess changes that might have occurred in the meantime. Finally, the findings can be useful in the health management of small ruminants, in providing evidence-based support, within the scope of health management. The small ruminant industry is the most important branch of Greek agriculture. Nevertheless, despite the importance of small ruminant farming for Greece, no detailed mapping of the respective farms has been undertaken and published. The present work refers to mapping the dairy sheep and goat industry in Greece through an extensive, countrywide cross-sectional study, in which information was obtained from 325 sheep and 119 goat farms. The objectives were the collection, the classification and the presentation of data obtained from all these farms through interviews, using a questionnaire and through examination of samples collected during the visits. All the farms enrolled in the study were visited by the investigators. Initially, information was obtained by means of a detailed, structured questionnaire with 442 questions. Moreover, samples of milk were collected from the bulk-tank of each farm and faecal samples were collected from female animals in each farm. The milk samples were processed for cytological and microbiological examination. Staphylococcus spp. and Listeria spp. isolates were recovered and identified at a species level; furthermore, a full antibiotic sensitivity pattern assessment was conducted. Faecal samples were processed by standard parasitological tests for the identification of protozoan, trematode, cestode and gastrointestinal and respiratory nematode parasites. The paper presents the cumulative findings of the study, i.e., the answers to the questions during the interviews and the results of the laboratory examinations performed in the samples; the findings are presented separately for sheep and goat farms. The findings can be used as baseline measurements; individual farms and cohorts of farms can be compared against the current results to draw conclusions against the countrywide situation. Moreover, the current results can be used as reference points for the future, in order to assess changes that might have occurred in the meantime. The study also described the differences between farms with sheep or goats; in total, differences in 137 parameters were identified. Some of these can be attributed to the different management systems practiced; sheep flocks are managed mostly under the intensive or semi-intensive system, whilst goat herds are managed mostly under the semi-extensive or extensive system. These findings can be useful in the health management of small ruminants, in providing evidence-based support and within the scope of precise livestock medicine and health management. [ABSTRACT FROM AUTHOR]

Air pollution is a pressing concern in urban areas, necessitating the critical monitoring of air quality to understand its implications for public health. Internet of Things (IoT) devices are widely utilized in air pollution monitoring due to their sensor capabilities and seamless data transmission over the Internet. Artificial intelligence (AI) and machine learning techniques play a crucial role in classifying patterns derived from sensor data. Environmental stations offer a multitude of parameters that can be obtained to uncover hidden patterns showcasing the impact of pollution on the surrounding environment. This paper focuses on utilizing the CO parameter as an indicator of pollution in two datasets collected from wireless environmental monitoring devices in the greater Port area and the Town Hall of Igoumenitsa City in Greece. The datasets are normalized to facilitate their utilization in classification algorithms. The k-means algorithm is applied, and the elbow method is used to determine the optimal number of clusters. Subsequently, the datasets are introduced to the grammatical evolution algorithm to calculate the percentage fault. This method constructs classification programs in a human-readable format, making it suitable for analysis. Finally, the proposed method is compared against four state-of-the-art models: the Adam optimizer for optimizing artificial neural network parameters, a genetic algorithm for training an artificial neural network, the Bayes model, and the limited-memory BFGS method applied to a neural network. The comparison reveals that the GenClass method outperforms the other approaches in terms of classification error. [ABSTRACT FROM AUTHOR]

Mobility as a Service (MaaS) is an innovative mobility service that aims to redesign the future of urban mobility by integrating multi-modal transportation and app-based technologies to enable seamless urban mobility. While MaaS pilot demonstrations and schemes implementation have taken place in different cities at a global level, and relevant studies focus on the MaaS barriers and users' characteristics, the planning process for implementing MaaS is rarely presented. This paper summarizes the services to be integrated into the MaaS Athens' demo site in Greece and describes the planning process that was followed to showcase the demo. The demo site is located within the urban area of Athens, including a public transport operator, a bike-sharing service, a taxi operator, and a municipality public transport operator. The demonstration runs developments in a real corridor that has the potential to prepare the MaaS eco-system deployment and market uptake. Three travel cases are planned: (1) Multimodal work trip; (2) MaaS for tourists; and (3) Interurban/urban interfaces, for work and shopping/leisure trips. The user journeys are defined in detail and the main information for each user journey is presented. The study concludes with challenges that were faced during the demo planning and recommendations for achieving the MaaS goals. [ABSTRACT FROM AUTHOR]

The aim of this paper is the selection of suitable tree crop cultivation sites in mountainous less favoured areas, as a forest policy measure under the scope of sustainable development. Ten different crop types were proposed as being most suitable in the study area, Pierion Municipal Unit, which is located in the Municipality of Katerini, in the Pieria Prefecture of Greece. In order to determine the most suitable sites for cultivation, data layers that involved the factors of topography, climate, pedology and geology were derived from existing maps and free-of-charge datasets, so that they could be consequently processed with the aid of Geographic Information Systems (GIS). The data processing was performed by following criteria, which were established in accordance with the current literature and were translated into Boolean algebra expressions. The latter helped to identify locations where the values of the factors that were employed were most favourable for the cultivation of walnut trees (Juglans sp.), olive trees (Olea sp.), cherry trees (Prunus sp.), apple (Malus sp.), dogwood trees (Cornus sp.), pomegranate trees (Punica sp.), chestnut trees (Castanea sp.) and other crop types. Moreover, the resulting map indicated that the majority of the suitable sites for cultivation were considered favourable for growing walnut trees (24.9%), followed by cherry trees (19.6%) and olive trees (12.1%). Proposing the most suitable cultivations within the study area contributes to forest policy planning and promotes the sustainable development of mountainous less favoured areas, leading to a more rational management of natural resources, a raised awareness of environmental protection, the maintenance of the local population and income enhancement through the production of high quality crops and sustainable yields. [ABSTRACT FROM AUTHOR]

This paper aims to reconstruct the alluvial activity for the Lilas river, the second-largest catchment of Euboea Island (Central Western Aegean Sea), for approximately the last three and a half millennia. The middle reaches (Gides basin) exhibit several historical alluvial terraces that were first recognised in the 1980s but have remained poorly studied, resulting in uncertain chronological control of palaeofluvial activity. In order to reconstruct the past fluvial dynamics of the Lilas river, a ca. 2.5 m thick stratigraphic profile has been investigated for granulometry and magnetic parameters. Absolute dating of the sediments was possible by applying Optically Stimulated Luminescence (OSL). The results reveal: (i) two coarse-grained aggradational episodes dated from the Mycenaean/Early Iron Age and the Roman periods, respectively, (ii) a phase of rapid fine-grained vertical accretion corresponding to the Late Byzantine to early Venetian periods, (iii) potential evidence for final alluvial deposition from the Little Ice Age/Ottoman period, and (iv) two major incision episodes inferred from Ancient Greek times and most of the Byzantine period. Based on the published core material, the paper also evaluates the direct impacts of the Late Holocene alluviation recorded mid-stream on the fluvial system situated downstream in the deltaic area. Sediment sourcing is attempted based on the magnetic properties of the catchment lithology and of alluvium collected upstream along the main stream bed. Finally, the present paper discusses the possible links between Late Holocene hydroclimatic oscillations and the aggradational/incision phases revealed in the Gides basin. Correlations are attempted with regional palaeoclimate records obtained for the Aegean. In addition to climatic variability, anthropogenic factors are considered: specific land use for agricultural purposes, in particular during the Mycenaean period, the Roman and the Late Byzantine/Early Venetian periods, might have enhanced sediment deposition. Archaeological information and pollen records were also evaluated to reconstruct regional land-use patterns and possible impacts on soil accumulation over the last 3.5 millennia. [ABSTRACT FROM AUTHOR]

Using advanced artificial intelligence (AI) technology in learning environments is one of the latest challenges for educators and education policymakers. Conversational AI brings new possibilities for alternative and innovative Information and Communication Technologies (ICT) tools, such as AI chatbots. This paper reports on field experiments with an AI chatbot and provides insights into its contribution to Content and Language Integrated Learning (CLIL). More specifically, this paper presents an experimental use case of an educational AI chatbot called AsasaraBot, designed to teach high school students cultural content in a foreign language, i.e., English or French. The content is related to the Minoan Civilization, emphasizing the characteristic figurine of the Minoan Snake Goddess. The related chatbot-based educational program has been evaluated at public and private language schools in Greece. The findings from these experiments show that the use of AI chatbot technology for interactive ICT-based learning is suitable for learning foreign languages and cultural content at the same time. The AsasaraBot AI chatbot has been designed and implemented in the context of a postgraduate project using open-source and free software. [ABSTRACT FROM AUTHOR]

This paper tests the suitability of automated point cloud classification tools provided by the popular image-based modeling (IBM) software package Agisoft Metashape for the generation of digital terrain models (DTMs) at moderately-vegetated archaeological sites. DTMs are often required for various forms of archaeological mapping and analysis. The suite of tools provided by Agisoft are relatively user-friendly as compared to many point cloud classification algorithms and do not require the use of additional software. Based on a case study from the Mycenaean site of Kastrouli, Greece, the mostly-automated, geometric classification tool "Classify Ground Points" provides the best results and produces a quality DTM that is sufficient for mapping and analysis. Each of the methods tested in this paper can likely be improved through manual editing of point cloud classification. [ABSTRACT FROM AUTHOR]

Measuring social capital has been a challenging task over the past few decades, and, still, many of its dimensions and manifestations have not been thoroughly or evidently explored. The possible causes may be the ever-changing evolutionary perspectives that take place within the various levels of analysis—micro, meso, and macro—or within the various settings, where some of its core dimensions—bonding, bridging, and linking—are developed, or even among the contexts where its core determinants and features—trust, norms, connections, ties, etc.—are observed. Having in mind the various streams of research and theoretical discourses on social capital formation, this paper aims to surface the identification of the possible evidence on the formation of social capital among social economy organizations, and particularly among social enterprises. In doing so, it aims to explore the relational and cognitive features that drive social enterprises in their interorganizational cooperation with other social enterprises and third-sector organizations. The findings suggest that the central components of social capital, such as the sharing of common values, trust, reciprocity, and trustworthiness, are among those features that were valued most among the participants in the survey during their cooperation and engagement in common activities with other organizations. [ABSTRACT FROM AUTHOR]

Serifos island is characterized by rich geodiversity, industrial and cultural heritage. The present paper focuses on the geological and mining heritage of Serifos, with the aim of integrating the island in the international environment of Geoparks, in the near future. In this geopark, Serifos can highlight the rich geological heritage of the island combined with the rich industrial heritage as expressed by mining activities since prehistoric times and the mining facilities of iron and copper mines. During the present study, six geotrails have been developed to link these cultural and ecological sites with the geological heritage. Along the routes, the geodiversity is explained, including its relationship with the surrounding biodiversity, and the historical and cultural aspects of the region. In the proposed geocultural routes (geotrails), the dialectic relationship between Humans and Nature is determined by historical conditions and by the record of the process that transforms space into a landscape. The geological-mining heritage of Serifos will attract people from all over the world with different kind of interests and will make it known to alternative tourists. The results of this paper are intended to constitute a valuable tool for enhancing and raising awareness of the geological heritage of the island of Serifos. [ABSTRACT FROM AUTHOR]

The paper explores the potentials of shape memory alloys (SMAs) for the design of autoreactive façade systems without using additional external energy. The exploration is conducted and assessed through the design of a façade concept for the city of Athens in Greece, aiming to improve both the indoor and outdoor environment by means of a kinetic autoreactive system featuring a dual-seasonal function, with a focus on the building's direct and indirect impact on the urban heat island (UHI) effect. The paper covers a demonstration of the methodology followed, using a feedback-loop logic informed by environmental and energy performance evaluation studies in Grasshopper to optimize the geometry and movement of the shading component. During the façade design process, a comprehensive and systematic computational toolset is being developed, targeted on the abovementioned performance evaluation studies. Through the development and assessment of the façade concept, the objective is to explore the potentials and limitations for the application of autoreactive envelopes in the façade design. At the same time, the aim is to exploit the possibilities and optimization potentials offered through the developed iterative computational workflows, by showcasing the methodology and interoperability logic of the digital tools used for the data interchange. [ABSTRACT FROM AUTHOR]

Medicinal and aromatic plants are a consistent component of the biodiversity heritage in numerous countries worldwide. Origanum dictamnus L. (Lamiaceae family), also known as Dittany, an endemic plant of the Greek island of Crete, has been widely used as traditional medicine since antiquity, all over Europe. The aim of the present review is to provide a thorough and detailed account of Dittany in antiquity, the plant's physical characteristics and ecology, and its cultivation methods, as well as its chemical components, biological properties, and pharmacological studies. The information is presented and analyzed in a critical manner. A total of 86 research studies were systematically reviewed based on the Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) guidelines. The findings indicate that Dittany is one of the most important medicinal and aromatic plants, with many uses not only in pharmacology but also in gastronomy. While a large body of literature exists regarding the application of essential oils, the number of publications concerning the plant's cultivation is rather small. Therefore, the main focus of this review is on the cultivation methods and the significance of cultivating and employing Dittany in Greece and the wider Mediterranean region in the future. Further research on this plant species is warranted since it has significant medicinal, economic, and environmental value. [ABSTRACT FROM AUTHOR]

In this research, we present the first steps toward developing a data-driven agent-based model (ABM) specifically designed for simulating infectious disease dynamics in Greece. Amidst the ongoing COVID-19 pandemic caused by SARS-CoV-2, this research holds significant importance as it can offer valuable insights into disease transmission patterns and assist in devising effective intervention strategies. To the best of our knowledge, no similar study has been conducted in Greece. We constructed a prototype ABM that utilizes publicly accessible data to accurately represent the complex interactions and dynamics of disease spread in the Greek population. By incorporating demographic information and behavioral patterns, our model captures the specific characteristics of Greece, enabling accurate and context-specific simulations. By using our proposed ABM, we aim to assist policymakers in making informed decisions regarding disease control and prevention. Through the use of simulations, policymakers have the opportunity to explore different scenarios and predict the possible results of various intervention measures. These may include strategies like testing approaches, contact tracing, vaccination campaigns, and social distancing measures. Through these simulations, policymakers can assess the effectiveness and feasibility of these interventions, leading to the development of well-informed strategies aimed at reducing the impact of infectious diseases on the Greek population. This study is an initial exploration toward understanding disease transmission patterns and a first step towards formulating effective intervention strategies for Greece. [ABSTRACT FROM AUTHOR]

Ever since European Directive 2012/27/EU, particular attention has been focused on the improvement of the energy efficiency of the public building stock. According to the directive, local public authorities, regions and municipalities, are expected to develop and implement energy efficiency retrofitting plans for their public building stocks. While conducting such plans, important challenges are raised mainly related to data collection and the manipulation of key performance indicators (KPIs) for many buildings. The present paper deals with the aforementioned challenges through (a) the evaluation of freely available tools developed in the framework of Mediterranean territorial cooperation projects, with respect to the main pillars of energy efficiency planning, and (b) the introduction of a stepwise methodology using selected tools toward a reliable energy efficiency plan extending from the classification of the building stock to the prioritization of projects in terms of a gradual renovation plan based on energy and cost criteria. The methodology is applied for a case study in Greece, which refers to 10 public buildings of the Municipality of Aigialeia in Greece. A reliable renovation plan is developed, taking into account the municipal authority's directions in a specialized decision-making scheme. It is concluded that the suggested methodology is very practical for planning purposes, while for the case studied, a 6-year gradual renovation plan is emerged until a deep retrofit of all buildings, associated with an estimated primary energy saving and CO2 emissions avoidance of more than 1850 MWh and 400 tns, respectively, with a total investment of about EUR 3 million. [ABSTRACT FROM AUTHOR]

In this paper, we develop a novel hybrid recommender system for the tourism domain, which combines (a) a Bayesian preferences elicitation component which operates by asking the user to rate generic images (corresponding to generic types of POIs) in order to build a user model and (b) a novel content-based (CB) recommendations component. The second component can in fact itself be considered a hybrid among two different CB algorithms, each exploiting one of two semantic similarity measures: a hierarchy-based and a non-hierarchy based one. The latter is the recently introduced Weighted Extended Jaccard Similarity (WEJS). We note that WEJS is employed for the first time within a recommender algorithm. We incorporate our algorithm within a real, already available at Google Play, tour-planning mobile application for short-term visitors of the popular touristic destination of Agios Nikolaos, Crete, Greece, and evaluate our approach via extensive simulations conducted on a real-world dataset constructed for the needs of the aforementioned mobile application. Our experiments verify that our algorithms result in effective personalized recommendations of touristic points of interest, while our final hybrid algorithm outperforms our exclusively content-based recommender algorithms in terms of recommendations accuracy. Specifically, when comparing the performance of several hybrid recommender system variants, we are able to come up with a "winner": the most preferable variant of our hybrid recommender algorithm is one using a 〈four elicitation slates, six shown images per slate〉 pair as input to its Bayesian elicitation component. This variant combines increased precision performance with a lightweight preferences elicitation process. [ABSTRACT FROM AUTHOR]

With the exponential growth of electric vehicle sales worldwide over the past years and progress in technology and actions to combat climate change by reducing greenhouse gas emissions, the trend is expected to continue with a significant increase in the deployment of electric vehicles and plug-in hybrids. Given these circumstances, it is essential to identify the constraints that this increase in the number of electric vehicle charging stations poses for the electricity system. Therefore, the analysis developed in this paper discusses the effect of integrating electric vehicle charging stations in a real distribution network with different penetration levels. For this purpose, a typical electric system in Greece, managed by the Greek distribution system operator (HEDNO), is modeled and simulated in DIgSILENT PowerFactory software, one of the most widely used simulation tools in the electricity sector. To study the feasibility of connecting electric vehicle charging stations to the network, different case studies are presented, showing changes in the quantity of electric vehicles feeding power into the network through vehicle-to-grid technology. Quasi-dynamic simulations are used to analyze and discuss the voltage profiles of the system nodes, active power flows with the external source and power losses of the distribution network to determine whether the system is capable of supporting the increase in load produced by the electric vehicle charging stations and to promote awareness of the benefits of implementing vehicle-to-grid connections. [ABSTRACT FROM AUTHOR]

The increasing amount of legal information available online is overwhelming for both citizens and legal professionals, making it difficult and time-consuming to find relevant information and keep up with the latest legal developments. Automatic text summarization techniques can be highly beneficial as they save time, reduce costs, and lessen the cognitive load of legal professionals. However, applying these techniques to legal documents poses several challenges due to the complexity of legal documents and the lack of needed resources, especially in linguistically under-resourced languages, such as the Greek language. In this paper, we address automatic summarization of Greek legal documents. A major challenge in this area is the lack of suitable datasets in the Greek language. In response, we developed a new metadata-rich dataset consisting of selected judgments from the Supreme Civil and Criminal Court of Greece, alongside their reference summaries and category tags, tailored for the purpose of automated legal document summarization. We also adopted several state-of-the-art methods for abstractive and extractive summarization and conducted a comprehensive evaluation of the methods using both human and automatic metrics. Our results: (i) revealed that, while extractive methods exhibit average performance, abstractive methods generate moderately fluent and coherent text, but they tend to receive low scores in relevance and consistency metrics; (ii) indicated the need for metrics that capture better a legal document summary's coherence, relevance, and consistency; (iii) demonstrated that fine-tuning BERT models on a specific upstream task can significantly improve the model's performance. [ABSTRACT FROM AUTHOR]

This paper analyzes the relationships among eight ancient scripts from between Greece and India. We used convolutional neural networks combined with support vector machines to give a numerical rating of the similarity between pairs of signs (one sign from each of two different scripts). Two scripts that had a one-to-one matching of their signs were determined to be related. The result of the analysis is the finding of the following three groups, which are listed in chronological order: (1) Sumerian pictograms, the Indus Valley script, and the proto-Elamite script; (2) Cretan hieroglyphs and Linear B; and (3) the Phoenician, Greek, and Brahmi alphabets. Based on their geographic locations and times of appearance, Group (1) may originate from Mesopotamia in the early Bronze Age, Group (2) may originate from Europe in the middle Bronze Age, and Group (3) may originate from the Sinai Peninsula in the late Bronze Age. [ABSTRACT FROM AUTHOR]

Wildfire is the primary cause of deforestation in fire-prone environments, disrupting the forest transition process generated by multiple social-ecological drivers of modernization. Given the positive feedback between climate change and wildfire-driven deforestation, it seems necessary to abstract the primary- or micro-characteristics of wildfire event(s) and focus on the general behavior of the phenomenon across time and space. This paper intends to couple wildfire self-organizing criticality theory (SOC) and modernization statistics to propose a verisimilar explanation of the phenomenon's evolution in the past decades and a prediction of its trends in Greece. We use power law distributions of the fire frequency–magnitude relationship to estimate the basic SOC parameters and the Weibull reliability method to calculate large-size wildfires' conditional probability as a time function. We use automatic linear modeling to search for the most accurate relationship between wildfire metrics and the best subset of modernization predictors. The discussion concentrates on reframing the political debate on fire prevention vs. suppression, its flaws and limitations, and the core challenges for adopting more efficient wildfire management policies in Greece. [ABSTRACT FROM AUTHOR]

In this paper, we propose an innovative approach for robust prediction of processing tomato yield using open-source AutoML techniques and statistical analysis. Sentinel-2 satellite imagery was deployed to obtain values of five (5) selected vegetation indices (VIs) during the growing season of 2021 (April to September) at 5-day intervals. Actual recorded yields were collected across 108 fields, corresponding to a total area of 410.10 ha of processing tomato in central Greece, to assess the performance of Vis at different temporal scales. In addition, VIs were connected with the crop phenology to establish the annual dynamics of the crop. The highest Pearson coefficient (r) values occurred during a period of 80 to 90 days, indicating the strong relationship between the VIs and the yield. Specifically, RVI presented the highest correlation values of the growing season at 80 (r = 0.72) and 90 days (r = 0.75), while NDVI performed better at 85 days (r = 0.72). This output was confirmed by the AutoML technique, which also indicated the highest performance of the VIs during the same period, with the values of the adjusted R2 ranging from 0.60 to 0.72. The most precise results were obtained with the combination of ARD regression and SVR, which was the most successful combination for building an ensemble (adj. R2 = 0.67 ± 0.02). [ABSTRACT FROM AUTHOR]

This study aims to investigate the effect of mergers and acquisitions (M&A) on shareholders' wealth. Additionally, this study investigates the impact of the economic crisis during 2007–2008 on the shareholders' perceptions of gaining additional value from mergers and acquisitions. In this paper, a sample of 84 M&As from 2006 to 2015 in Greece are studied to investigate the effect on shareholders of bidder companies. We find significantly negative abnormal returns just before the announcement of M&A, which negatively affects the bidder firms' value. It is also observed that after 2009 M&A cases decreased, maybe because of the crisis in Greece that changed the investors' perception of a value-destroying event. Companies that engage in M&A activities during economic downturns tend to experience a decline in shareholder value. This could be due to various factors, such as increased uncertainty and risk associated with such activities during economic uncertainty. By understanding the potential impact of such activities on shareholder value, companies can make more informed decisions about whether and when to pursue M&A opportunities. [ABSTRACT FROM AUTHOR]

Social structure is based on the availability of the Water-Energy-Food Nexus. To cover these needs of society, several solutions of different scales of infrastructures coexist. The construction of infrastructure is capital-intensive; therefore, investment risk is always a consideration. In this paper, we try to evaluate the investment risk by interest rates (IR). We show that IR is a key indicator, which includes multiple parameters of prosperity expressing the political and economic status quo of the society. The selection of a particular scale influences the required capital and is thus one of the most critical decisions. Water supply infrastructure is one of the foundations of society, and the selection of the optimal scale of such infrastructure is often a great challenge in civil engineering. As a case study, we analyse three different scales of water supply infrastructures for the area of West Mani (Greece), i.e., dam, water ponds, and seawater desalination. We evaluate each case by the capital intensity by performing stochastic simulations of interest rates and identify the optimal solution as the one with the smallest median unit cost, in this case, the water ponds. In order to assess the impact of the development level of a country on the resulting unit cost stochastic properties we apply the optimal solution to various countries with different development levels and IR. We show that IR in the least developed countries, being generally higher and more variable, increases the unit cost, including its variability, which ultimately indicates higher investment risk. [ABSTRACT FROM AUTHOR]

Digital transformation in farming via smart farming technologies (SFTs) is highly considered to stimulate sustainability in the food market and agriculture, as well as to promote viability in the agricultural sector and the prosperity of rural areas. In Greece, a great number of SFTs were financed through Action 4.1.1, by the EU's Rural Development Program, supporting agricultural production and promoting sustainable regional development. Within this policy context, this paper aims to examine the transformation level that "smartness" induced in the relationship between agriculture and regional development in Greece. To do so, it builds a multilevel methodological framework thematically describing both "traditional" and smart agriculture in terms of spatial demand, transportation cost, knowledge intensity, and economies of scale, which are theoretically and empirically considered as major pillars related to regional development. The analysis is applied regional data (NUTS 3) in Greece, focusing on the detection of significant spatial and functional changes in the thematic model developed with respect to the proposed methodological framework. Findings provide insights into the effect that the SFTs can have on sustainable regional development, based on the reasoning of relevant background regional economic theories. [ABSTRACT FROM AUTHOR]

The present manuscript describes a case study on the viewpoints of tourism stakeholders on the effect of waste management on a destination′s image. In particular, the study aims to analyze the problems that arose during the summer of 2018 in the touristic image of Corfu because of the waste management on the island. The qualitative method approach through interviews was used to collect the primary data of the survey; online sources were used to collect data to review similar cases. All the stakeholders agree that waste management during the summer of 2018 negatively affected the image of Corfu as a touristic destination. Moreover, based on the interviews′ findings, there is a lack of political will, infrastructure, and information provision from the local authorities on the island of Corfu. Interviews also indicated that an integrated solution to the problem of waste management on the island is the implementation of source separation in households and tourism-related firms with the support of the local authorities. The contribution of this paper is towards identifying the effect that waste management has on the image of a tourist destination. It is the first of its kind conducted in Greece and among the few reported in the literature focusing on the viewpoints of service providers. [ABSTRACT FROM AUTHOR]

One of the main applications of the gravity field and steady-state Ocean Circulation Explorer (GOCE) satellite data is their combination with local gravity anomalies for geoid and gravity field modeling purposes. The aim of the present paper was the determination of an improved geoid model for the wider Hellenic area, using original GOCE SGG data filtered to retain only useful signals inside the measurement bandwidth (MBW) of the satellite. The filtered SGGs, originally at the satellite altitude, were projected to a mean orbit (MO) and then downward continued to the Earth's surface (ES) in order to be combined with local gravity anomalies. For the projection to an MO, grids of disturbing gravity gradients from a global geopotential model (GGM) were used, computed per 1 km from the maximum satellite altitude to that of the MO. The downward continuation process was then undertaken using an iterative Monte Carlo (MC) simulated annealing method with GGM gravity anomalies on the ES used as ground truth data. The final geoid model over the wider Hellenic area was estimated, employing the remove–compute–restore method and both Fast Fourier Transform (FFT) and Least Squares Collocation (LSC). Gravity-only, GOCE-only and combined models using local gravity and GOCE data were determined and evaluation of the results was carried out against available GNSS/levelling data in the study area. From the results achieved, it was concluded that even when FFT is used, so that a combined grid of local gravity and GOCE data is used, improvements to the differences regarding GNSS/levelling data by 14.53% to 27.78% can be achieved. The geoid determination with LSC was focused on three different areas over Greece, with different characteristics in the topography and gravity variability. From these results, improvements from 14.73%, for the well-surveyed local data of Thessaly, to 32.88%, over the mountainous area of Pindos, and 57.10% for the island of Crete for 57.10% were found. [ABSTRACT FROM AUTHOR]

In the present work attention is focused on the friction-yielding damper CAR1 (first prototype of Control-Absorb-Retain damper), which belongs to passive energy dissipation systems. This damper consists of very simple materials; it does not need to be accomplished in heavy industry so enables its use in both developing and undeveloped countries. This paper presents and compares two alternative solutions with the use of the CAR1 to seismic retrofit an existing two-story reinforced-concrete (RC) structure with a moment-resisting frame located in Greece and constructed in 1979 and no longer meets the requirements of current anti-seismic regulations. A nonlinear static pushover analysis is performed to assess the performance of the framed building under different levels of shaking ("Life Safety" and "Collapse"). The pushover analysis is carried out in both the x and y directions. The use of damper CAR1 in seismic retrofitting not only provides a base shear load of up to 149.2% and 135.6% for the first and second redesign solutions but also protects steel diagonal braces from buckling. The appropriate characteristics of the dampers CAR1 has been selected from a wide variety of choices and the strengthening level can be easily adjusted or modified during the years based to the appropriate selection or modification of the number, the dimensions, and the elastoplastic properties of the blades. [ABSTRACT FROM AUTHOR]

In southern Europe, irrigation is the major water user and thus, development of operational tools that support decisions aiming to improve irrigation management, is of great importance. In this study, a web-based participatory decision support system for irrigation management (DSS), based on the principles of UN FAO's paper 56, without requirement for any special monitoring hardware to be installed in each field, is evaluated for the case of a commercial wine grapevine (Vitis vinifera 'Vertzami') located at Epirus (northwest Greece), for two successive years (2021 and 2022). The soil moisture time series that were generated by the DSS's model were compared to those measured by soil moisture sensors. The Mean Absolute Error (MAE) and Root Mean Square Error (RMSE) ranged between 2.98–3.22% and 3.63–4.06%, respectively, under various irrigation practices and goals. Irrigation resulted very high yields and Crop Water Productivity (WPC) was 20–44% improved when following the DSS's recommendations. The results also confirm potential pitfalls of sensor-based soil moisture monitoring and rainfall estimations using mathematical models. Finally, the value of water meters as practical sensors, which could support efficient irrigation management, is underlined. In every case, mindful application of decision support systems that require minimum or no hardware to be installed in each field, could extensively support growers and agronomic consultants to test, document and disseminate good practices and calculate environmental indices. [ABSTRACT FROM AUTHOR]

In the food and beverage industry, many foods, beers, and soft drinks need to be pasteurized in order to minimize the effect of micro-organisms on the physical stability, quality, and flavour of the product. Although modern tunnel pasteurizers provide integrated solutions for precise process monitoring and control, a great number of packaging plants continue to operate with legacy pasteurizers that require irregular manual measurements to be performed by shop floor operators in order to monitor the process. In this context, the present paper presents zPasteurAIzer, an end-to-end system that provides real-time quality monitoring for legacy tunnel pasteurization machines and constitutes a low-cost alternative to replacement or the upgrading of installed equipment by leveraging IoT technologies and AI-enabled virtual sensing techniques. We share details on the design and implementation of the system, which is based on a microservice-oriented architecture and includes functionalities such as configuration of the pasteurizer machine, data acquisition, and preprocessing methodology as well as machine learning-based estimation and live dashboard monitoring of the process parameters. Experimental work has been conducted in a real-world use case at a large brewing manufacturing plant in Greece, and the results indicate the value and potential of the proposed system. [ABSTRACT FROM AUTHOR]

The main objective of the present paper is to achieve the simulation of the long-term (e.g., annual) morphological evolution (bathymetry and shoreline) of a coastal area (Mastichari beach, Greece) due to wind-generated waves in an accurate and cost-effective way. For this purpose, wave climate schematization techniques are adopted in order to reduce the computational effort without losing or distorting the crucial information. Referring to the current practice, the wave chronology is not considered in detail in these acceleration techniques, and therefore, sea bottom and shoreline evolution are not estimated as a function of time. To fill this gap, a novel and easy-to-use chronology-based wave input reduction method is developed to produce representative wave time series of different intensities and durations. The performance of all the applied techniques in the present study is evaluated, and a comparative analysis is conducted. It is shown that the new chronology-based wave input reduction method can achieve a model run-time reduction of about 70%, while at the same time, it provides satisfactorily accurate results. In general, this research could be useful for coastal engineering studies and coastal zone monitoring, and thus, it would be a valuable tool for coastal engineers and marine scientists. [ABSTRACT FROM AUTHOR]

This paper addresses the gap in the scientific literature regarding construction cost estimates for the construction of underground metro stations. It provides preliminary cost estimation models using linear regression for use by the Greek underground metro public transport authority for planning future extensions to the Athens and Thessaloniki networks. At the same time, it contributes to the body of knowledge by proposing material quantity prediction models and presents a two-stage preliminary cost estimation model for the construction of civil engineering works of underground metro stations. Stage one uses the construction cost budgets of six metro stations in Greece to develop a multilinear regression equation for the prediction of the overall cost for construction of civil engineering works; stage two provides estimates of material quantities using linear regression, key quantity ratios, and artificial neural networks. The data analyzed are from the prior measurements of quantities for the construction of the Chaidari to Piraeus extension of the Athens Metro Line 3. After comparing the actual values of costs and quantities with the corresponding predictions, acceptable discrepancies are observed. All models provide estimates within ±25% discrepancies, which are acceptable at the conceptual planning phase in order to initiate project funding quests. [ABSTRACT FROM AUTHOR]

Hydropower plays an essential role in Europe's energy transition and can serve as an important factor in the stability of the electricity system. This is even more crucial in areas that rely strongly on renewable energy production, for instance, solar and wind power, as for example the Peloponnese and the Ionian islands in Greece. To safeguard hydropower's contribution to total energy production, an accurate prediction of the annual precipitation is required. Valuable tools to obtain accurate predictions of future observations are firstly a series of sophisticated data preprocessing techniques and secondly the use of advanced machine learning algorithms. In the present paper, a complete procedure is proposed to obtain accurate predictions of meteorological data, such as precipitation. This procedure is applied to the Greek automated weather stations network, operated by the National Observatory of Athens, in the Peloponnese and the Ionian islands in Greece. The proposed prediction algorithm successfully identified the climatic zones based on their different geographic and climatic characteristics for most meteorological stations, resulting in realistic precipitation predictions. For some stations, the algorithm underestimated the annual total precipitation, a weakness also reported by other research works. [ABSTRACT FROM AUTHOR]

Despite the rising awareness of the mutual benefits of pollination, agricultural production, and biodiversity, Greek planning has scarcely moved toward patterns of pollinator-friendly farm design models. This paper presents data from preliminary research analysis that defined generic landscape design models that can enhance the symbiotic associations between farming production and beekeeping in Greece. The main objective is to determine tailor-made landscape models that can contribute to a portfolio of actions easily apprehensible by non-technical audiences in the farming sector who want to introduce biodiversity enhancements to monoculture farming, fostering a safer, poisonous-free environment for introduced honeybees, simultaneously helping to augment their production yields. A preliminary study was conducted in four agricultural farming estates in Thessaly and the Peloponnese involving apple farming, citrus orchards, and hemp cultivation. It combined the analysis and assessment of land cover classes with regard to the provision of foraging habitat, assessment of foraging suitability, description of connectivity characteristics, and emerging spatial patterns of natural corridors, patches, and edges at an observation perimeter around each farm. Assessment of these data informed design models for planting enrichment and integration of natural patches, such as meadows and shrub corridors. Pilot installations of hives in study areas that combined characteristics of the landscape models presented resulted in the production of 8% to 12% bigger fruits and 30% to 50% increase in the total yield. We conclude that landscape design models for biodiversity enhancement are an important attribute of ecosystem services and require an understanding of specific geographical and landscape parameters to render models operational for bee farming and pollination. [ABSTRACT FROM AUTHOR]