Reaffirming the Teacher Role within the Context of Culturally Responsive Pedagogy: A Case Study and Relevant Issues

The issue of quality teaching has been the subject of educational research, but there is not much empirical support noted in research findings on the connection of quality teaching and the teachers' abilities. Quality teaching is also discussed in terms of culturally responsive pedagogy indicating that this teaching approach underscores the learner-centered approach. The main argument of this article is that emphasis is placed on the role of the teacher as a facilitator in the learning process, suggesting that the Greek teacher role is reaffirmed within the context of culturally responsive pedagogy. In addition, the article describes and explains how cultural variables are determining factors in designing appropriate syllabi for Greek university students and in choosing appropriate teaching methodology techniques for effective teaching in university settings. Specifically, the reason why the dimension of instructional clarity is important in relation to teaching any Greek national cohort is illustrated. Some examples of lesson plans are also presented explaining in detail the materials used, the learning environment and classroom management in relation to a course on English for General Academic Purposes ( EGAP) taught in the first term. A number of activities done in class during this course are described offering some key pedagogical implications

Evaluation of a prior-incorporated statistical model and established classifiers for externally visible characteristics prediction

Human identification through DNA has played an important role in forensic science and in the criminal justice system for decades. It is referring to the association of genetic data with a particular human being and has facilitated police investigations in cases such as the identification of suspected perpetrators from biological traces found at crime scenes, missing persons, or victims of mass disasters [1]. Currently there are two main methods developed: the genotyping through short tandem repeats (STR profiling) and the forensic DNA phenotyping (FDP). Despite the fact that these two methods are aiming in identifying a person through its genetic material, their approach and consequences that come up are completely different. STR profiling compares allele repeats at specific loci in DNA and aims at a match with already known to the police authorities DNA profiles, while FDP, which is the focus on the current study, aims in the prediction of appearance traits of an individual [2, 3]. In contrast with STR profiling, information that arise out of FDP cannot be used as sole evidence in the court [4]. The ability of predicting EVCs from DNA can be used as ‘biological witnesses’ that can only provide leads for the investigative authorities and subsequently narrow down a possible large set of potential suspects. The use of FDP begins a new era of ‘DNA intelligence’ and holds great promise especially in cases where individuals cannot be identified with the conventional method of STR profiling and also in cases where there is no additional knowledge on the sample donor. So far in FDP, traits such as eye, hair and skin color can be predicted reliably with high prediction accuracy and predictive models have already been forensically validated [5-7]. Regarding other appearance traits, the current lack of knowledge on the genetic markers responsible for their phenotypic variation and the lower predictability, especially of intermediate categories, has prevented FDP from being routinely implemented in the field of forensic science. The majority of the predictive models developed for appearance trait prediction were based on multinomial logistic regression (MLR) while only few used other methods such as decision trees and neural networks. Machine learning (ML) approaches have become a widely used tool for classification problems in several fields and they are known for their potential to boost model performance and their ability to handle different and complex types of data [8]. However, within the context of predicting EVCs, a systematic and comparative analysis among different ML approaches that could possibly indicate methods that outperform the standard MLR, has not been conducted so far. In addition, incorporation of priors in the EVC prediction models that may have potential to improve the already existing approaches, has not been investigated in the context of forensics yet. These priors indicate the trait category prevalence values among biogeographic ancestry groups, and their use would allow us to leverage Bayesian statistics in order to build more powerful prediction models. In our case, incorporation of such priors in the model could reflect the additional information from all yet unknown causal genetic factors and act as proxies in the prediction model. Therefore, those two approaches were conducted throughout my PhD project in order to improve the already existing approaches of FDP which was the main aim of my study. In the first study, I aimed to collect a comprehensive data set from previously published sources on the spatial distribution of different appearance traits. I conducted a literature review in order to assemble this information, which later on could be incorporated as priors in the EVCs prediction models. Due to the lack of available and reliable sources, our resulting data set contained only eye and hair color for mostly European countries. More specifically, I collected data on eye color from 16 European and Central Asian countries, while for hair color I collected data from seven European countries. For countries outside of Europe, where the variation is low, it was not possible to assemble trustworthy and population-representative data. Afterwards, I calculated the association of those two traits and obtained a moderate association between them. Interpolation techniques were applied in order to infer trait prevalence values in at least neighboring countries. Resulting prevalences and interpolated values were presented in spatial maps. The subject of the second study was to incorporate the trait prevalence values as priors in the prediction model. However, due to the lack of reliable data that was observed in the first study, the incorporation of the actual priors that would give us the actual insight of their impact in the EVC prediction was not feasible with the current existing knowledge and the available data. Therefore, I assessed the impact of priors across a grid that contained all possible values that priors can take, for a set of appearance traits including eye, hair, skin color, hair structure, and freckles. In this way, I aimed to assess potential pitfalls caused by misspecification of priors. Results were compared and evaluated with the corresponding prior-free' previously established prediction models. The effect of priors was demonstrated in the standard performance measurements, including area under curve (AUC) and overall accuracy. I found out that from all possible prior values, there is a proportion that shows potential in improving the prediction accuracy. However, possible misspecification of priors can significantly diminish the overall accuracy. Based on that, I emphasize the importance of accurate prior values in the prediction modelling in order to identify the actual impact. As a consequence of the above, the use of prior informed models in forensics is currently infeasible and more studies on the topic are necessary in order to extend the current knowledge on spatial trait prevalence. Finally, the focus of the third study was exploring and comparing the performances of methodologies beyond MLR. MLR is considered the standard method for predicting EVCs, since the majority of the predictive models developed are based on that method. Due to the fact that there is still potential for improvement of MLR models, especially for traits such as skin color or hair structure, I aimed at applying different ML methods in order to identify whether there is a potential classifier that outperforms the conventional method of MLR. Therefore I conducted a systematic comparison between MLR and three alternative ML classifiers, namely support vector machines (SVM), random forests (RF) and artificial neural networks (ANN). The traits that I focused on here were eye, hair, and skin color. All models were based on the genetic markers that were previously established in IrisPlex, HIrisPlex and HIrisPlex-S [5-7]. Overall, I observed that all four classifiers performed almost equally well, especially for eye color. Only non-substantial differences were obtained across the different traits and across trait categories. Given this outcome, none of the ML methods applied here performed better than MLR, at least for the three traits of eye, hair, and skin color. Ultimately, due to the easier interpretability of the MLR, it is suggested at least for now and for the currently known marker sets, that the use of MLR is the most appropriate method for predicting appearance traits from DNA. Throughout my PhD project, it became apparent that the available knowledge on spatial trait prevalence values was quite restricted not only in certain appearance traits but also in continental groups. More specifically, most available and reliable data were focused on European populations and the traits that were available were mostly for eye and hair color. For other traits, such as skin color, hair structure, and freckles, the data were either extremely few or nonexistent. This was a significant obstacle throughout the project, since it prevented me from applying and testing the actual impact of the accurate trait prevalence values as priors in EVC prediction. However, the lack of data presented an opportunity to perform in-depth theoretical research, in particular testing the impact of priors within a spatial grid that included its possible values. I found out that there is a proportion of priors that showed potential to improve EVC prediction. However, caution is advised regarding misspecification of priors that can significantly deteriorate the models' performance. Furthermore, the application of different ML approaches did not show any significant improvement on the prediction performance against the standard MLR. This could be due to the nature of the traits, since some of them are multifactorial and affected by various external independent factors or due to possible limitations of the currently known predictive markers. With the available knowledge so far, it is emphasized throughout this study that for the time being, priors are refrained from being incorporated in the EVC prediction models while from the different classifiers applied, MLR is considered as the most appropriate method for EVC prediction due to its easier interpretability. In addition, the presented study highlights the importance of reference data on externally visible traits and the identification of more genetic markers that contribute to certain traits and I hope that the present work will motivate the emergence of these certain types of data collections that potentially may improve the current EVC prediction models

The Use of the Ombudsman's Services for Alleviating International Students' Difficulties

This article offers some suggestions regarding the development of a support strategy by ombudsmen in order to alleviate international students' difficulties when studying in host universities. It is also shown how the Organisational Justice Theory can be used as a framework for understanding the role of ombudsman in higher education settings and how this theory underlines the importance of informational power as a remedy to alleviate the students' difficulties. The main implication drawn from the discussion is that cultural variables may suggest specific care on designing appropriate support strategies where the role of Information Communication Technology (ICT) could be explored. Finally, the article offers some suggestions and a service plan showing how power perceptions of the service provider can impact the students' reaction to the quality of the service

Fabrication of Metasurfaces on Building Construction Materials for Potential Electromagnetic Applications in the Microwave Band

Energy self sufficiency, as well as optimal management of power in buildings is gaining importance, while obtaining power from traditional fossil energy sources is becoming more and more expensive. In this context, millimeter scale metasurfaces can be employed to harvest energy from microwave sources. They can also be used as sensors in the microwave regime for efficient power management solutions. In the current study, a simple spray printing method is proposed to develop metasurfaces in construction materials, i.e., plasterboard and wood. Such materials are used in the interior design of buildings; therefore, the implementation of metasurfaces in large areas, such as walls, doors and floors, is realized. The fabricated metasurfaces were characterized regarding their electromagnetic performance. It is hereby shown that the investigated metasurfaces exhibit an efficient electromagnetic response in the frequency range 4 to 7 GHz, depending on the MS. Thus, spray printed metasurfaces integrated on construction materials can potentially be used for electromagnetic applications, for buildings power self efficiency and management.Comment: 14pages, 8 figure

Multiple sclerosis: Immunopathology and treatment update

The treatment of multiple sclerosis (MS) has changed over the last 20 years. All immunotherapeutic drugs target relapsing remitting MS (RRMS) and it still remains a medical challenge in MS to develop a treatment for progressive forms. The most common injectable disease-modifying therapies in RRMS include β-interferons 1a or 1b and glatiramer acetate. However, one of the major challenges of injectable disease-modifying therapies has been poor treatment adherence with approximately 50% of patients discontinuing the therapy within the first year. Herein, we go back to the basics to understand the immunopathophysiology of MS to gain insights in the development of new improved drug treatments. We present current disease-modifying therapies (interferons, glatiramer acetate, dimethyl fumarate, teriflunomide, fingolimod, mitoxantrone), humanized monoclonal antibodies (natalizumab, ofatumumab, ocrelizumab, alemtuzumab, daclizumab) and emerging immune modulating approaches (stem cells, DNA vaccines, nanoparticles, altered peptide ligands) for the treatment of MS

Μελέτη παρασιτικών επιστρεφόντων κυμάτων (backward waves) σε κοιλότητες γυροτρονίων υψηλής ισχύος

Μια πιθανή πηγή ενέργειας που μπορεί να καλύψει τις ενεργειακές απαιτήσεις του αυξανόμενου πληθυσμού της Γης στο μέλλον βασίζεται στη θερμοπυρηνική σύντηξη μαγνητικά περιορισμένου πλάσματος. Η πυρηνική σύντηξη είναι η συνένωση ελαφριών πυρήνων σε βαρύτερους με ταυτόχρονη απελευθέρωση ενέργειας. Για να επιτευχθεί πυρηνική σύντηξη, πρέπει να ξεπεραστεί ένα ουσιαστικό ενεργειακό φράγμα (φράγμα Coulomb) ηλεκτροστατικών δυνάμεων. Η υπέρβαση του ενεργειακού φράγματος μπορεί να συμβεί με θέρμανση του πλάσματος σε θερμοκρασία πολλών εκατομμυρίων βαθμών Kelvin, που έχει ως αποτέλεσμα τον διαχωρισμό των ηλεκτρονίων από τους πυρήνες τους. Το πλάσμα στους αντιδραστήρες σύντηξης μπορεί να θερμανθεί αποτελεσματικά από μικροκύματα. Η απορρόφηση της ενέργειας των μικροκυμάτων είναι πιο αποτελεσματική όταν η συχνότητα είναι κοντά στην κυκλοτρονική συχνότητα των ηλεκτρονίων στο μαγνητικά περιορισμένο πλάσμα (~100 GHz 200 GHz). Μέχρι σήμερα τα γυροτρόνια είναι η μόνη πηγή υψηλής μικροκυματικής ισχύος που μπορούν να λειτουργήσουν αποτελεσματικά και αξιόπιστα σε αυτές τις συχνότητες με ισχύ της τάξης των MW. Η μικροκυματική ισχύς στα γυροτρόνια παράγεται με τη μετατροπή κινητικής ενέργειας μιας δέσμης ηλεκτρονίων σε ηλεκτρομαγνητική. Τα ηλεκτρόνια, αφού επιταχυνθούν από κάποια αξιόλογη διαφορά δυναμικού, εκτελούν κυκλοτρονική περιστροφή γύρω από τις δυναμικές γραμμές ενός εξωτερικά επιβαλλόμενου ισχυρού μόνιμου μαγνητικού πεδίου και διεγείρουν (μέσα σε κάποιο κατάλληλο ηλεκτροδυναμικό σύστημα) ένα ηλεκτρομαγνητικό κύμα συχνότητας παραπλήσιας με την ηλεκτρονική κυκλοτρονική συχνότητα. Έρευνες σε γυροτρόνια ισχύος της τάξης των MW έδειξε την ύπαρξη παρασιτικών ρυθμών, οι οποίοι μειώνουν την παραγόμενη ισχύ της διάταξης. Οι ρυθμοί αυτοί έχει δειχθεί ότι οδεύουν αντίθετα από την ηλεκτρονική δέσμη και γι’ αυτό χαρακτηρίζονται ως επιστρέφοντες ρυθμοί (backward modes). Οι επιστρέφοντες ρυθμοί αλληλεπιδρούν με τη δέσμη, μειώνοντας έως και 10% την παραγόμενη ισχύ. Η παρούσα διπλωματική εργασία έχει σκοπό την περαιτέρω μελέτη των ρυθμών και την εξάρτησή τους από φυσικές και αριθμητικές παραμέτρους μέσω προσομοιώσεων. Η μελέτη της εξάρτησης από αριθμητικές παραμέτρους αποσκοπεί στο να δείξει πόσο αξιόπιστο είναι το μοντέλο αλληλεπίδρασης σε ό,τι αφορά τη σωστή προσομοίωση παρασιτικών επιστρεφόντων κυμάτων, τα οποία μέχρι τώρα αγνοούνταν, κατά κανόνα, στις πολυρρυθμικές προσομοιώσεις. Η μελέτη της εξάρτησης από φυσικές παραμέτρους βοηθά στην κατανόηση των αιτιών της διέγερσης των παρασιτικών. Ο κώδικας αλληλεπίδρασης που χρησιμοποιείται στην εργασία ονομάζεται EURIDICE και είναι ένας κώδικας προσομοίωσης της αλληλεπίδρασης δέσμης - πεδίου. Στην διπλωματική γίνεται μια εισαγωγή στην αρχή λειτουργίας των γυροτρονίων και στη συνέχεια ακολουθεί μια σειρά προσομοιώσεων που πραγματοποιήθηκαν. Τα αποτελέσματα των προσομοιώσεων καθώς και τα φυσικά συμπεράσματα που έχουν εξαχθεί παρουσιάζονται αναλυτικά.One potential source of energy that may be able to meet the demands of the growing population in the future is thermonuclear fusion of magnetically confined plasma. Nuclear fusion is the fusion of light nuclei into heavier ones with the simultaneous release of energy. To achieve nuclear fusion, a substantial energy barrier (Coulomb barrier) of electrostatic forces must be overcome. Overcoming the energy barrier can occur by heating the plasma to a temperature of about one million degrees Kelvins, which results in the separation of the electrons from their nuclei. The plasma in fusion reactors can be efficiently heated by microwaves. Absorption of microwave energy is most efficient when the frequency is close to the cyclotron frequency of electrons in the magnetically confined plasma (~100 GHz – 200 GHz). To date, gyrotrons are the only source of high, MW-level microwave power that can operate efficiently and reliably at this range of frequencies. Microwave power in gyrotrons is generated by converting the kinetic energy of an electron beam into electromagnetic energy. The electrons, after being accelerated by some appreciable potential difference, perform cyclotron rotation around the field lines of an externally imposed strong magnetostatic field and excite (within some suitable electrodynamic system) an electromagnetic wave of frequency close to the electron cyclotron frequency. Research on MW class gyrotrons has shown the existence of parasitic modes, which reduce the generated power of the device. These modes have been shown to travel opposite to the electron beam and are therefore characterized as backward waves. These backward waves interact with the beam, reducing the output power by up to 10%. This thesis aims to further study the backward waves and their dependence on physical and numerical parameters through simulations. The study of the numerical parameters’ dependence is intended to show how reliable the interaction model is in correctly simulating parasitic backward waves, which until now have typically been ignored in multi mode simulations. The study on the dependence on physical parameters helps to understand the causes of parasitic excitation. The software used in this work is called EURIDICE and is an ‘‘in-house’’ beam field interaction simulation code. In this thesis there is an introduction to the principle of operation of gyrotrons and then follows a series of simulations that were done. The results of the simulations, as well as the physical conclusions, are presented in detail. To strengthen the reliability of the results, further simulations are carried out that more closely approximate the physical problem and evaluate the validity of the code. Finally, the causes of stimulation of backward waves are studied with the ultimate aim of suppressing them