Wind Farm Deployment in Uninhabited Islets: A Case Study the Region of the South Aegean (Greece)

The transition of nations to renewable energy sources is a fact, and the deployment of renewable energy (RE) projects has increased in the last decades. The deployment of energy projects in uninhabited islets (islands) provides a promising opportunity for low-carbon energy transition. Considering the importance of the spatial dimension of RE projects, in this research, we identified and ranked uninhabited islets (UIs) for wind farm deployment in the South Aegean Sea, Greece. The proposed methodology combines geographic information systems (GIS) and two multicriteria analysis methods (AHP and TOPSIS) using some restrictions found in Greek law as well as assessment criteria considering environmental, economic, and technical aspects. The appropriate UIs were then ranked under four different policy scenarios (baseline, equal criteria weights, a policy scenario oriented to technical/economic criteria, and a policy scenario focusing on environmental criteria). The results indicated the existence of three UIs for siting wind farms in the region of the South Aegean, with the same ranking of these UIs under different scenarios. The proposed methodology provides useful guidelines for selecting UIs as wind farm sites in Greece and could be applied in other countries worldwide

Data and Spatial Analysis for Economy and Education of 28 E.U. Member-States for 2014

The objective of the paper is the study of geographic, economic and educational variables and their contribution to determine the position of each member-state among the EU-28 countries based on the values of seven variables as given by Eurostat. The Data Analysis methods of Multiple Factorial Correspondence Analysis (MFCA) Principal Component Analysis and Factor Analysis have been used. The cross tabulation tables of data consist of the values of seven variables for the 28 countries for 2014. The data are manipulated using the CHIC Analysis V 1.1 software package. The results of this program using MFCA and Ascending Hierarchical Classification are given in arithmetic and graphical form. For comparison reasons with the same data the Factor procedure of Statistical package IBM SPSS 20 has been used. The numerical and graphical results presented with tables and graphs, demonstrate the agreement between the two methods. The most important result is the study of the relation between the 28 countries and the position of each country in groups or clouds, which are formed according to the values of the corresponding variables

Wind Farm Deployment in Uninhabited Islets: A Case Study the Region of the South Aegean (Greece)

The transition of nations to renewable energy sources is a fact, and the deployment of renewable energy (RE) projects has increased in the last decades. The deployment of energy projects in uninhabited islets (islands) provides a promising opportunity for low-carbon energy transition. Considering the importance of the spatial dimension of RE projects, in this research, we identified and ranked uninhabited islets (UIs) for wind farm deployment in the South Aegean Sea, Greece. The proposed methodology combines geographic information systems (GIS) and two multicriteria analysis methods (AHP and TOPSIS) using some restrictions found in Greek law as well as assessment criteria considering environmental, economic, and technical aspects. The appropriate UIs were then ranked under four different policy scenarios (baseline, equal criteria weights, a policy scenario oriented to technical/economic criteria, and a policy scenario focusing on environmental criteria). The results indicated the existence of three UIs for siting wind farms in the region of the South Aegean, with the same ranking of these UIs under different scenarios. The proposed methodology provides useful guidelines for selecting UIs as wind farm sites in Greece and could be applied in other countries worldwide

Απόψεις Γονέων και Εκαπιδευτικών για το Νηπιαγωγείο

Αντικείμενο της παρούσας ερευνητικής εργασίας αποτελεί η διερεύνηση των παραδοχών των γονέων και των εκπαιδευτικών για το ρόλο του νηπιαγωγείου. Ειδικότερα, θα διερευνηθεί η σχέση ανάμεσα στις αντιλήψεις των εκπαιδευτικών για την προσχολική εκπαίδευση και τις αντίστοιχες αντιλήψεις των γονέων. Επιπλέον, θα διερευνηθεί η συνεργασία σχολείου και οικογένειας καθώς και παράγοντες που διευκολύνουν ή δυσχεραίνουν αυτή τη σχέση και τα οφέλη που προκύπτουν από μια καλή συνεργασία. Γενικά, έχουν πραγματοποιηθεί πολλές έρευνες με επίκεντρο τους εκπαιδευτικούς και τους γονείς στο εξωτερικό αλλά και στην Ελλάδα και καλύπτουν αρκετές πτυχές. Η παρούσα εργασία εστιάζει ταυτόχρονα σε γονείς και εκπαιδευτικούς στο ελληνικό νηπιαγωγείο μελετώντας τις παραδοχές τους.The purpose of this research paper is to investigate the assumptions of parents and teachers about how they perceive the role of kindergarten. In particular, the relationship between teachers' perceptions of early childhood education and parents' respectively will be explored. In addition, school and family cooperation will be explored as well as factors that facilitate or hinder this relationship and the benefits of good cooperation. In general, many surveys have been carried out focusing on teachers and parents abroad and in Greece, covering several aspects. This paper focuses simultaneously on parents and teachers in the Greek preschool studying their assumptions

DIANA-mAP: Analyzing miRNA from Raw NGS Data to Quantification

microRNAs (miRNAs) are small non-coding RNAs (~22 nts) that are considered central post-transcriptional regulators of gene expression and key components in many pathological conditions. Next-Generation Sequencing (NGS) technologies have led to inexpensive, massive data production, revolutionizing every research aspect in the fields of biology and medicine. Particularly, small RNA-Seq (sRNA-Seq) enables small non-coding RNA quantification on a high-throughput scale, providing a closer look into the expression profiles of these crucial regulators within the cell. Here, we present DIANA-microRNA-Analysis-Pipeline (DIANA-mAP), a fully automated computational pipeline that allows the user to perform miRNA NGS data analysis from raw sRNA-Seq libraries to quantification and Differential Expression Analysis in an easy, scalable, efficient, and intuitive way. Emphasis has been given to data pre-processing, an early, critical step in the analysis for the robustness of the final results and conclusions. Through modularity, parallelizability and customization, DIANA-mAP produces high quality expression results, reports and graphs for downstream data mining and statistical analysis. In an extended evaluation, the tool outperforms similar tools providing pre-processing without any adapter knowledge. Closing, DIANA-mAP is a freely available tool. It is available dockerized with no dependency installations or standalone, accompanied by an installation manual through Github