182 research outputs found

    First application of hemi-body electron beam irradiation for Kaposi sarcoma at the lower extremities

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    Kaposi’s sarcoma (KS) is a systemic neoplastic disease that can present cutaneous symptoms and is usually treated with a systematic approach due to its extent. Due to its radiosensitivity, radiotherapy is considered one of its main treatments, for palliation and local control of the skin and mucosal lesions. The aim of this paper was to report the first case of KS treated by hemi-body electron irradiation protocol in Greece. A fractionated 40 Gy hemi-body electron irradiation was prescribed to a 60-year-old male patient with KS at his legs. Dose uniformity was verified on a daily basis by thermo luminescence dosimetry (TLD). The treatment resulted to complete clinical response. Limited irradiation-derived side effects appeared. This is the first case ever to be treated with hemi-body electron irradiation protocol in Greece. To the best of our knowledge, this is also the first time that a single field hemi-body electron beam irradiation at a total skin electron beam (TSEB)-like configuration is reported to be used for KS

    Metal assemblages in Late Bronze Age Greek mainland funerary contexts: an investigation for their identification as functional metal hoards

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    Bronze Age metal hoards in Europe have been extensively studied with a focus on their intended purpose and the reason/s behind their survival in the archaeological record, but definite answers cannot be given. A similar issue is also encountered in the Late Bronze Age Aegean more specifically and debate exists whether the increase in metal hoarding in the final centuries of the Late Bronze Age in the Aegean is the result of a copper/bronze shortage or abundance. Both in the Aegean and wider Europe, most scholars studying metal hoards are focusing on those from non-funerary contexts, dismissing the idea that metal assemblages in tombs interpreted as grave goods may also be hoards and which may have even been intended to be retrieved in the face of poverty and/or a metal shortage. This possibility has only been briefly looked at by Greek scholars and archaeologists and so the purpose of this thesis is to study further this possibility using the case studies of the Late Bronze Age tholos tombs at Kokla and Nichoria and the chamber tombs 2, 7 and 10 at Dendra in the Peloponnese. The research questions that are answered in this project are: can the content and context of selected non-funerary metal hoards provide any clues for their identification? Are there content similarities between funerary metal assemblages and non-funerary metal hoards? Could the funerary metal assemblages be retrieved from the tomb and put back into circulation? Can a metal shortage be responsible for the increase in metal hoarding on the late LBA Greek mainland? Through the study of metal assemblages from these tombs that are not clearly associated with any burials and their comparison to selected non-funerary hoards, also from the Late Bronze Age Greek mainland, this thesis shows that there are significant similarities between the two in the content and to some extent even the context. It concludes that these funerary metal assemblages can reasonably be considered as retrievable hoards to be used in times of need. The availability of scrap metal, the good-quality bronzework and the Linear B tablets from Pylos are argued to indicate that there was not a copper/bronze shortage on the mainland in the final centuries of the Late Bronze Age. Therefore, this research also concludes that the rise in metal hoarding during that time probably does not relate to an actual copper/bronze shortage

    Proper Orthogonal Decomposition Analysis of a Turbulent Swirling Self-Excited Premixed Flame

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    Thermoacoustic oscillations constitute a serious threat to the integrity of combustion systems. The goal of the present work is to determine the effect of the equivalence ratio (φ), inlet flow velocity (U), and burner geometry on the characteristics of the self-excited oscillations and to reveal the dominant mechanisms. It also focuses on the data post-processing aiming at extracting information about the dynamics that are not captured through classical ensemble-averaging, and hence the Proper Orthogonal Decomposition technique is used. Experiments were conducted with a fully-premixed air/methane flame stabilized on a conical bluff body. Self-excited acoustic instabilities were induced by extending the length of the combustion chamber downstream of the bluff body. The flame was visualised using OH* chemiluminescence and OH PLIF at 5 kHz. Proper Orthogonal Decomposition (POD) and Fast Fourier Transform analysis were conducted on the imaging data. A strong effect of the chamber length was found, which primarily drove the generation of acoustic oscillation and flame-vortex interaction. Significant differences in the flame roll-up were found when either the burner geometry or the equivalence ratio was altered. Changes were detected in the frequency of oscillations, which showed a general trend to increase with φ and U and decrease with the length of the duct. Analysis of the POD modes allowed an estimate of the convection speed of the flame structures associated with the dominant frequency and it was found that this convection speed was about 1.5 U for most conditions studied

    Χρονικές συστάσεις με βραχυπρόθεσμες και μακροπρόθεσμες προτιμήσεις

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    Ο χρόνος είναι ένας σημαντικός παράγοντας όταν γίνονται προτάσεις / συστάσεις και η αποτύπωση με ακρίβεια των προτιμήσεων των χρηστών στην πάροδο του χρόνου είναι μια μεγάλη πρακτική πρόκληση για τα συστήματα συστάσεων (recommender systems). Οι αλγόριθμοι συνεργατικού φιλτραρίσματος (Collaborative Filtering algorithms), που χρησιμοποιούνται σε συστήματα προτάσεων στο διαδίκτυο, συχνά αξιολογούνται όσον αφορά την ακρίβεια των προβλέψεων για την βαθμολογία του χρήστη σε δεδομένη στιγμή και πολλές από τις σημερινές τεχνικές αξιολόγησης αγνοούν το γεγονός ότι οι χρήστες συνεχίζουν να αξιολογούν τα αντικείμενα με την πάροδο του χρόνου, και να αλλάζουν τις προτιμήσεις τους λόγω διαφορετικών εξωτερικών γεγονότων. Η συμπεριφορά των χρηστών μπορεί συχνά να προσδιοριστεί από τις μακροπρόθεσμες και βραχυπρόθεσμες προτιμήσεις. Για την αντιμετώπιση αυτών των προκλήσεων, η πρώτη μέθοδος που ακολουθήσαμε ήταν χρονικός γράφος με βάση χρονικές περιόδους (Session-based Temporal Graph - STG), που μοντελοποιεί ταυτόχρονα τις μακροπρόθεσμες και βραχυπρόθεσμες προτιμήσεις των χρηστών με την πάροδο του χρόνου. Με βάση αυτόν τον γράφο, χρησιμοποιήσαμε τον αλγόριθμο για προτάσεις / συστάσεις Injected Preference Fusion (IPF). Για το δεύτερο μέρος, ακολουθήσαμε μια διαφορετική προσέγγιση με το collaborative Filtering, χρησιμοποιώντας Ανάλυση Κύριων Συνιστωσών (Principal Component Analysis - PCA) και ιεραρχική ομαδοποίηση (hierarchical clustering), για ομαδοποίηση παρόμοιων χρηστών και την δημιουργία συστάσεων με βάση τον χρήστη. Τέλος, αξιολογούμε την αποτελεσματικότητα των μεθόδων χρησιμοποιώντας την βάση δεδομένων του Yelp. Βάση των κριτικών (reviews) φτιάχνονται συστάσεις (recommendations) και αποδεικνύεται ότι η μέθοδος STG εμφανίζει πιο ακριβή αποτελέσματα από την PCA.Time is an important factor when making recommendations and accurately capturing user preferences over time is a great practical challenge in recommender systems. Collaborative Filtering (CF) algorithms, used to build web-based recommender systems, are often evaluated in terms of how accurately they predict user ratings and many current evaluation techniques disregard the fact that users continue to rate items over time and change their preferences due to different external events. User behavior can often be determined by individual’s long-term and short-term preferences. To address these challenges, the first method we used was the session-based Temporal Graph (STG) which simultaneously models users’ long-term and short-term preferences over time. Based on the STG model framework, we used the recommendation algorithm Injected Preference Fusion (IPF). For the second part we tried a different approach with the collaborative filtering, by using Principal Component Analysis (PCA) and hierarchical clustering, to group similar users and making user-based recommendations. Finally, we evaluate the effectiveness of the methods using Yelp dataset. Based on business reviews and making recommendations, we prove that the STG method presents more accurate results than the PCA method
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