EDUCATORS’ KNOWLEDGE AND STANDPOINTS ON BONE MARROW DONATION

Objectives: The objectives of the study are what is the degree of registration of educators, what is the attitude of educators about organ donation, and what are the factors related to the decision to donate. Methods: It is a quantitative cross-sectional study using a structured questionnaire. A sample consisted of 208 teachers with the greater predominance of women. Logarithmic regression was applied to determine the effect of demographics, knowledge evaluation, and evaluation of views toward the possibility of registration in the body donor register. Results: Out of the participants, 7.5% are registered in the organ donor and 20.5% are active body donors. One in two wants to become an organ donor. The views evaluation on a scale with a minimum of 23 and a maximum of 115 was 87.58 (9.62). The knowledge evaluation on a scale with a minimum of 0 and a maximum of 6 was 2.17 (1.46). The underlying impression of participants on their knowledge of organ donation on a scale of 1–6 was 3.18 (1.47). The 45–50 age group is 19.9 times more likely to be registered and the evaluation of views increases. Conclusion: The degree of registration in donor registers (7.5%) is considered low. The assessment of attitudes 87.58 and knowledge 2.17 (1.46) is considered also insufficient. The main source of knowledge is the media. It is necessary to increase the contribution of more reliable sources (academic studies, ministry, and information actions)

Probabilistic Slow Features for Behavior Analysis

A recently introduced latent feature learning technique for time-varying dynamic phenomena analysis is the so-called slow feature analysis (SFA). SFA is a deterministic component analysis technique for multidimensional sequences that, by minimizing the variance of the first-order time derivative approximation of the latent variables, finds uncorrelated projections that extract slowly varying features ordered by their temporal consistency and constancy. In this paper, we propose a number of extensions in both the deterministic and the probabilistic SFA optimization frameworks. In particular, we derive a novel deterministic SFA algorithm that is able to identify linear projections that extract the common slowest varying features of two or more sequences. In addition, we propose an expectation maximization (EM) algorithm to perform inference in a probabilistic formulation of SFA and similarly extend it in order to handle two and more time-varying data sequences. Moreover, we demonstrate that the probabilistic SFA (EM-SFA) algorithm that discovers the common slowest varying latent space of multiple sequences can be combined with dynamic time warping techniques for robust sequence time-alignment. The proposed SFA algorithms were applied for facial behavior analysis, demonstrating their usefulness and appropriateness for this task

Platinum Complexes with a Phosphino-Oxime/Oximate Ligand

The platinum(II) complex [PtCl2(COD)] (2; COD = 1,5- cyclooctadiene) reacted with 1 and 2 equiv. of 2-(diphenylphosphanyl) benzaldehyde oxime (1) to generate [PtCl2{¿2-(P,N)-2- Ph2PC6H4CH=NOH}] (3) and [Pt{¿2-(P,N)-2-Ph2PC6H4CH=NOH}2]- [Cl]2 (4), respectively. Deprotonation of the oxime hydroxyl group of 3 with Na2CO3 led to the selective formation of the dinuclear species (¿-O)-[PtCl{¿2-(P,N)-2-Ph2PC6H4CH=NO}]2 (5), while the related methylated derivative (¿-O)-[PtMe{¿2-(P,N)-2- Ph2PC6H4CH=NO}]2 (7) could be obtained from the direct reaction of [PtMe2(COD)] (6) with the phosphino-oxime ligand 1. In the case of 4, its treatment with Na2CO3 yielded complex [Pt({¿2-(P,N)-2-Ph2PC6H4CH=NO}2H)][Cl] (8), as a result of the deprotonation of only one of the OH groups of 4. On the other hand, contrary to what was observed with 6, no deprotonation of the oxime occurred in the reaction of [PtMe3I]4 (9) with 1, from which the mononuclear PtIV derivative fac-[PtIMe3{¿2-(P,N)- 2-Ph2PC6H4CH=NOH}] (10) was isolated. The solid-state structures of compounds 3, 4, 7 and 10 were determined by X-ray crystallography. In addition, the potential of all the synthesized complexes as catalysts for the dehydrogenative coupling of hydrosilanes with alcohols is also briefly discussed.Peer Reviewe

CONSUMPTION, KNOWLEDGE AND OPINIONS OF EXERCISERS AND ATHLETES ABOUT ENERGY DRINKS. A PUBLIC HEALTH PERSPECTIVE

The energy drinks are beverages that contain caffeine and are consumed by students, children, adolescents and young adults to enhance their athletic and cognitive performance. Significant adverse effects have been reported. They vary from mild symptoms to death. The present study attempts to assess the risk of using energy drinks by exercisers and athletes. In order to achieve this, we evaluate the consumption and knowledge level of the consumers. The lack of awareness can lead to dangerous practices. Views on appropriate public health protection measures are also being investigated. The grade of consumption (35.5%) is within the bounds of the literature. The main source of knowledge is the advertisement (69.2%), which does not guarantee objective information. Therefore, although exercisers and athletes believe that they have adequate knowledge on the subject (91.2%), in fact this is not the case (the knowledge score is 10.12/18). Thus, half of them consume concurrently energy drinks with alcohol (a perilous practice). The study emphasizes the need of taking measures for public health protection

Application of gamma-ray tomographic techniques in granular flows in hoppers.

The aim of this dissertation is to demonstrate the potential of novel measurement techniques based on the scanning of gamma-ray transmission in the investigation of axially-symmetric flow properties of granular materials in 3D hoppers. Furthermore, the results of the experimental investigations are compared on a strictly quantitative basis with Newtonian Dynamics (i.e. Discrete Element simulations) and Molecular Dynamics (i.e. kinetic gas theory calculations). Measurements were performed using two specially constructed scanner systems of different geometric configuration of gamma-ray sources and detectors(namely parallel and fan beam arrangements respectively). The fan beam scanner has been developed entirely in the Department of Chemical & Process Engineering by the author of this thesis and therefore a significant part of the thesis deals with major points concerning both hardware and software development as well as associated calibration procedures. Gas-phase continuous mono-disperse systems have been studied using (i) the full tomographic imaging technique which is able to produce 3D planar maps of voidage at selected heights of a storage vessel and (ii) the single profile absorptiometric technique capable of producing voidage profiles in both Cartesian and polar coordinates at much faster acquisition rates. Results were compared with earlier Distinct Element numerical simulations showing encouraging agreement in terms of both the absolute values of voidage and their spatial fluctuations as well as the geometric structure of the static and dynamic particle assemblies. Size segregation in air borne binary mixtures have been quantified using the novel dual energy photon technique which is capable of producing solids fraction profiles for each of the individual components of a binary mixture in addition to the voidage profiles. Spatial and temporal data on solids fractions in a binary mixture were analysed using methodology based on statistical mechanics principles which led to the definition of "micro-turbulence" during flow in terms of the self-diffusion velocities of individual solid components. This then allows the calculation of both the self- and mutual-diffusion coefficients used to quantify size segregation. These calculations were also compared with theoretical predictions based on the kinetic gas theory which was found to grossly over-predict the calculated diffusion coefficients in slow-shearing granular flows

A joint discriminative generative model for deformable model construction and classification

Discriminative classification models have been successfully applied for various computer vision tasks such as object and face detection and recognition. However, deformations can change objects coordinate space and perturb robust similarity measurement, which is the essence of all classification algorithms. The common approach to deal with deformations is either to seek for deformation invariant features or to develop models that describe objects deformations. However, the former approach requires a huge amount of data and a good amount of engineering to be properly trained, while the latter require considerable human effort in the form of carefully annotated data. In this paper, we propose a method that jointly learns with minimal human intervention a generative deformable model using only a simple shape model of the object and images automatically downloaded from the Internet, and also extracts features appropriate for classification. The proposed algorithm is applied on various classification problems such as “in-the-wild” face recognition, gender classification and eye glasses detection on data retrieved by querying into a web image search engine. We demonstrate that not only it outperforms other automatic methods by large margins, but also performs comparably with supervised methods trained on thousands of manually annotated data

Application of gamma-ray tomographic techniques in granular flows in hoppers.

The aim of this dissertation is to demonstrate the potential of novel measurement techniques based on the scanning of gamma-ray transmission in the investigation of axially-symmetric flow properties of granular materials in 3D hoppers. Furthermore, the results of the experimental investigations are compared on a strictly quantitative basis with Newtonian Dynamics (i.e. Discrete Element simulations) and Molecular Dynamics (i.e. kinetic gas theory calculations). Measurements were performed using two specially constructed scanner systems of different geometric configuration of gamma-ray sources and detectors(namely parallel and fan beam arrangements respectively). The fan beam scanner has been developed entirely in the Department of Chemical & Process Engineering by the author of this thesis and therefore a significant part of the thesis deals with major points concerning both hardware and software development as well as associated calibration procedures. Gas-phase continuous mono-disperse systems have been studied using (i) the full tomographic imaging technique which is able to produce 3D planar maps of voidage at selected heights of a storage vessel and (ii) the single profile absorptiometric technique capable of producing voidage profiles in both Cartesian and polar coordinates at much faster acquisition rates. Results were compared with earlier Distinct Element numerical simulations showing encouraging agreement in terms of both the absolute values of voidage and their spatial fluctuations as well as the geometric structure of the static and dynamic particle assemblies. Size segregation in air borne binary mixtures have been quantified using the novel dual energy photon technique which is capable of producing solids fraction profiles for each of the individual components of a binary mixture in addition to the voidage profiles. Spatial and temporal data on solids fractions in a binary mixture were analysed using methodology based on statistical mechanics principles which led to the definition of "micro-turbulence" during flow in terms of the self-diffusion velocities of individual solid components. This then allows the calculation of both the self- and mutual-diffusion coefficients used to quantify size segregation. These calculations were also compared with theoretical predictions based on the kinetic gas theory which was found to grossly over-predict the calculated diffusion coefficients in slow-shearing granular flows

Computer vision techniques for facial image characterization

The main field of interest of this thesis is the characterization of facial images, such as facial expression recognition, face recognition and facial pose recognition. One of the most crucial issues that every facial image analysis algorithm in computer vision encounters is the high dimensionality of the provided image data. A popular category of methods that obtain a more manageable problem is the subspace image representation algorithms, which aim to discover the latent image features by projecting the high dimensional input data to a low dimensional subspace. In this thesis two subspace learning methods are presented, that aim to enhance classes discrimination in the projection subspace. The first method modifies the cost function of the original Nonnegative Matrix Factorization algorithm by incorporating appropriate discriminant factors inspired by Clustering Discriminant Analysis, while the second operates on the random features instead of the actual high dimensional input data and derives an optimal projection matrix, such that the separating margin between the projected samples of different classes is maximized. Experimental results for face recognition and facial expression recognition on various popular datasets shown that the developed algorithms exploiting the discriminant low dimensional facial image representations achieved superior recognition performance compared against various competing algorithms. Subsequently, an algorithm for the incremental training of multiclass support vector machines is presented, which exploits a set of novel multiplicative update rules and a warm start optimization framework, in order to achieve computational efficiency, when the training data collection is sequentially enriched and dynamic adaptation of the classifier is required. Experimental results on various data collections and for facial pose recognition, verified that the developed method is faster than retraining the classifier from scratch, while the achieved classification accuracy rate is maintained at the same level.Το αντικείμενο το οποίο πραγματεύεται η διδακτορική αυτή διατριβή είναι ο χαρακτηρισμός εικόνων προσώπου, όπως είναι η αναγνώριση εκφράσεων, η αναγνώριση προσώπου, αλλά και η αναγνώριση της πόζας του. Στη μηχανική όραση ένα από τα πιο σημαντικά προβλήματα που καλείται να αντιμετωπίσει κάθε αλγόριθμος ανάλυσης εικόνων προσώπου, είναι η πολύ υψηλή διάσταση των δεδομένων εισόδου. Μια δημοφιλής κατηγορία μεθόδων για την αποδοτικότερη επεξεργασία αυτών, είναι οι μέθοδοι εκμάθησης υποχώρων οι οποίες στοχεύουν να ανακαλύψουν τα κρυμμένα χαρακτηριστικά των εικόνων, προκειμένου να εξάγουν κατάλληλες διακριτικές αναπαραστάσεις, των δεδομένων, μικρότερης διάστασης. Στη συνέχεια της διατριβής προτείνονται δύο διακριτικές μέθοδοι εκμάθησης υποχώρων, όπου η πρώτη τροποποιεί την συνάρτηση αποσύνθεσης της μεθόδου μη αρνητικής παραγοντοποίησης πινάκων εισάγοντας κατάλληλους διακριτικούς περιορισμούς εμπνευσμένους από τη διακριτική ανάλυση υποκλάσεων, ενώ η δεύτερη χρησιμοποιεί τυχαία χαρακτηριστικά, αντί για τα αρχικά διανύσματα χαρακτηριστικών υψηλής διάστασης, προκειμένου να προσδιορίσει έναν κατάλληλο υποχώρο προβολής χαμηλής διάστασης στον οποίο το περιθώριο μεταξύ των προβεβλημένων δειγμάτων διαφορετικών κλάσεων μεγιστοποιείται. Πειραματικά αποτελέσματα για τα προβλήματα της αναγνώρισης προσώπου, αλλά και της έκφρασής του, σε διάφορα δημοφιλή σύνολα δεδομένων, έδειξαν ότι οι προτεινόμενοι αλγόριθμοι μπορούν να επιτύχουν εξαιρετική μείωση της διάστασης των δεδομένων, αλλά και υψηλότερη απόδοση αναγνώρισης σε σχέση με πολλές ανταγωνιστικές μεθόδους μείωσης διάστασης που έχουν προταθεί στη βιβλιογραφία. Επίσης, στη συνέχεια της διατριβής, μελετάται η επαυξητική εκπαίδευση των μηχανών εδραίων διανυσμάτων πολλών κλάσεων και παρουσιάζεται ένας αλγόριθμος εκπαίδευσής τους, ο οποίος αξιοποιώντας τη βέλτιστη λύση που υπολογίστηκε προγενέστερα αλλά και πρωτότυπους πολλαπλασιαστικούς κανόνες ανανέωσης, προσφέρει μειωμένο υπολογιστικό κόστος για την προσαρμογή του κατηγοριοποιητή στα νέα δεδομένα εκπαίδευσης σε σχέση με τη συμβατική προσέγγιση μαζικής εκπαίδευσης από την αρχή. Ο προτεινόμενος αλγόριθμος εφαρμόστηκε σε διάφορα σύνολα δεδομένων αλλά και στο πρόβλημα της αναγνώρισης της πόζας προσώπου

Study - research on education of the primary health care executives

In our times, a period of economic and institutional crisis, every system has to prove its effectiveness. The education and vocational training of personnel working in Primary Health Care (P.H.C) is also included in this frame. It is a well-known fact that the most important element upon which effectiveness in various work related environments is dependent on, is the education and prior vocational training that is provided. Therefore, what PHC has to offer is directly linked to the level of the education and adequate training previously provided. The method used in order to make the evaluation is a mixed one. It is a combination of qualitative and quantitative approaches with the ultimate aim of increasing the validity of the findings. The quantitative part is implemented by means of questionnaire which the directors of Health Centers were kindly invited to answer. It is the directors' responsibility, by law, to monitor and evaluate their subordinates for their work performance but also care for the vocational training and education they get. It is presumed, therefore, that they are sensitized and knowledgeable about the subject in question. The qualitative part is materialized through interviews of distinguished individuals who are prestigious and highly influential, possessing vital posts directly concurrent with the subject at hand. Consequently they have full knowledge on the particular subject. Through the findings and the results it became apparent that the situation in PHC is bleak and according to many even completely absent. There are many problems that can be identified in the field of education and vocational training in terms of politics, resources, institutional framework and quality. Taking these problems into consideration, various proposals are formulated and advisable solutions are suggested. The material mentioned above is in the position to engrave directions of Educational Politics and Health Politics thus contributing to a much more efficient Organization and Management of Educational Units but also of services provided in Primary Health Care or even Health in general.Στην εποχή μας, εποχή της οικονομικής και θεσμικής κρίσης, κάθε σύστημα οφείλει να αποδεικνύει την αποτελεσματικότητα του. Στα πλαίσια αυτά εντάσσεται και η αξιολόγηση της εκπαίδευσης των στελεχών της Π.Φ.Υ. Είναι γνωστό ότι σημαντικό στοιχείο στην απόδοση κάθε χώρου αποτελεί η εκπαίδευση, που παρέχεται γι' αυτόν. Επομένως, η προσφορά της Π.Φ.Υ., συναρτάται άμεσα με το επίπεδο της παρεχόμενης εκπαίδευσης. Προκειμένου να γίνει η αξιολόγηση χρησιμοποιείται μικτή μέθοδος, δηλαδή ένας συνδυασμός ποιοτικής και ποσοτικής μελέτης, με σκοπό την αύξηση της αξιοπιστίας των ευρημάτων. Το ποσοτικό μέρος υλοποιείται με ερωτηματολόγιο, που κλήθηκαν να απαντήσουν οι διευθυντές των κέντρων υγείας. Αυτοί είναι εκ του νόμου υπεύθυνοι να ελέγχουν και να βαθμολογούν τους υφισταμένους τους για την προσφορά και την εκπαίδευση τους. Τεκμαίρεται, λοιπόν, ότι είναι ευαισθητοποιημένοι και γνώστες του εν λόγω θέματος. Το ποιοτικό σκέλος υλοποιείται με συνεντεύξεις ατόμων, που διαθέτουν κύρος, επιρροή και κατέχουν καίριες θέσεις, σχετικές με το αντικείμενο. Επομένως, κατέχουν το συγκεκριμένο αντικείμενο. Από την επεξεργασία των αποτελεσμάτων προέκυψε ότι η κατάσταση στην Π.Φ.Υ. είναι ζοφερή, μάλιστα κατά πολλούς παντελώς απούσα. Στην εκπαίδευση εντοπίζονται πολλά προβλήματα σε επίπεδο πολιτικών, πόρων, θεσμικού πλαισίου και ποιότητας. Βάσει αυτών διατυπώνονται προτάσεις και προβάλλονται οι ενδεδειγμένες λύσεις. Το ανωτέρω υλικό χαράσσει κατευθύνσεις Εκπαιδευτικής Πολιτικής και Πολιτικής Υγείας και συμβάλλει στην αρτιότερη Οργάνωση και Διοίκηση εκπαιδευτικών μονάδων, αλλά και υπηρεσιών πρωτοβάθμιας φροντίδας υγείας και υγείας γενικότερα