Fishes and other aquatic species in the Byzantine literature. Classification, terminology and scientific names.

Fishes and other aquatic species were substantial food in the every day life of Byzantine people. The predomination of Christianity contributed to the increased consumption of fishes and other seafood compared to the meat of land animals and chicken. More than a hundred ten names of fishes and about thirty names of other aquatic organisms are found in the sources of the Byzantine literature. Most frequent references are found in the medical texts of the Byzantine doctors, where, fishes are classified in categories depending on their physiology and origin, because, according to the writers, these are determining factors for the evaluation of the nutritional value of each species.The purpose of this study is to present the terminology of the fishes and the various aquatic species that are found in the Byzantine sources and to identify, in parallel, each species with its current scientific name.  Fishes and other aquatic species were substantial food in the every day life of Byzantine people. The predomination of Christianity contributed to the increased consumption of fishes and other seafood compared to the meat of land animals and chicken. More than a hundred ten names of fishes and about thirty names of other aquatic organisms are found in the sources of the Byzantine literature. Most frequent references are found in the medical texts of the Byzantine doctors, where, fishes are classified in categories depending on their physiology and origin, because, according to the writers, these are determining factors for the evaluation of the nutritional value of each species.The purpose of this study is to present the terminology of the fishes and the various aquatic species that are found in the Byzantine sources and to identify, in parallel, each species with its current scientific name. 

Asymmetrische Fragmentsynthesen des Bryostatins (C1-C16 und C19-C27), Pederins (C10-C17), Leucascandrolids (C1-C9), Hennoxazols (C2-C8) und Macrolactins (C11-C17) : neuartige Entschützungsmethoden von SEM-Ethern und Dithianen

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Εύρεση Υπό-Γεγονότων Χρησιμοποιώντας Μέσα Κοινωνικής Δικτύωσης

Η παρούσα πτυχιακή εργασία είναι βασισμένη στη δημοσίευση (paper) “Automatic SubEvent Detection in Emergency Management using Social Media” και σκοπός της είναι να μελετήσει πειραματικά τα διάφορα στάδια υλοποίησης ενός μηχανισμού αυτόματης εύρεσης υπό-γεγονότων μέσα σε ένα αρχικό γεγονός, χρησιμοποιώντας μέσα κοινωνικά δικτύωσης όπως περιγράφονται στη δημοσίευση, κάνοντας ωστόσο ορισμένες διαφοροποιήσεις. Ο μηχανισμός αυτός αποτελείται από τα εξής στάδια: εύρεση δεδομένων, προ-επεξεργασία (pre-processing) δεδομένων, συσταδοποίηση (clustering) και ανάλυση των τελικών συστάδων (clusters)-αποτελεσμάτων. Τα δεδομένα που θα χρησιμοποιήσουμε, θα τα λάβουμε από τη μεγαλύτερη πλατφόρμα κοινωνικής δικτύωσης, το Twitter , τα οποία δεν θα είναι άλλα από τα λεγόμενα tweets που έχουν κάνει διάφοροι χρήστες σε ένα καθορισμένο χρονικό διάστημα. Στη συνέχεια, θα εισάγουμε τα δεδομένα αυτά στο εργαλείο (tool) WEKA και θα κάνουμε μια προ-επεξεργασία, εφαρμόζοντας μια σειρά ενεργειών, για να τα φέρουμε στη μορφή που θέλουμε. Έπειτα, θα προχωρήσουμε σε συσταδοποίηση των δεδομένων, χρησιμοποιώντας τον αλγόριθμο k-means και τέλος σε εξαγωγή των αποτελεσμάτων για ανάλυση. Θα υπάρχουν κάποιες μικρές διαφορές σε σχέση με τη δημοσίευση που αναφέρεται παραπάνω, οι οποίες αφορούν κυρίως την πηγή των δεδομένων και τον αλγόριθμο συσταδοποίησης. Συγκεκριμένα, στη δημοσίευση χρησιμοποιούνται δεδομένα από τις πλατφόρμες YouTube και Flickr σε αντίθεση με το Twitter που επιλέξαμε εμείς, ενώ ο αλγόριθμος συσταδοποίησης που χρησιμοποιούμε είναι ο k-means σε αντίθεση με τον SOM (Self Organizing Map). Παρά τις διαφοροποιήσεις αυτές, θα παρατηρήσουμε έπ(ειτα από πειραματική μελέτη, ότι τα αποτελέσματα που παράγονται, πλησιάζουν σε μεγάλο βαθμό εκείνα της δημοσίευσης, που σημαίνει ότι μέσα από κάποιο επείγον γεγονός, μπορούμε να χρησιμοποιήσουμε δεδομένα από μεγάλες πλατφόρμες προκειμένου να εντοπίσουμε μικρότερα σημαντικά γεγονότα και να αντιδράσουμε σε αυτά.This bachelor thesis is based on the “Automatic Sub-Event Detection in Emergency Management using Social Media” paper and its purpose is to conduct experimental studies on the various stages of a mechanism implementation that automatically detects sub-events when a large event occurs, using social media the way it is described on the paper, but with few alterations. This mechanism consists of the following stages: data collection, data preprocessing, clustering and analysis of the final clusters-results. The data that we will use, are collected by the biggest social media platform, Twitter, and consist of various tweets, generated by the users of the platform within a specific period of time. Next, we are going to import our data into the WEKA tool and preprocess it until we reach the appropriate data-form that we need. After the data preprocessing is completed, we will execute the K-means clustering algorithm and then export the clusters-results so we can later analyze them. There will be a few differences with the paper, mostly the way we collect the data and execute the clustering algorithm. Specifically, in the paper, data is collected from social media platforms like Flickr and YouTube and not from Twitter, while the clustering algorithm that is being used is the Self Organizing Map algorithm and not K-Means. Despite those differences, we will notice after experimental studies that our results are similar to the results that are presented in the paper, which means that when a big event occurs, we can use data from social media platforms to detect sub-events and react to them

New Artificial Urinary Sphincter Devices in the Treatment of Male Iatrogenic Incontinence

Severe persistent stress incontinence following radical prostatectomy for prostate cancer treatment, although not very common, remains the most annoying complication affecting patient’s quality of life, despite good surgical oncological results. When severe incontinence persists after the first postoperative year and conservative treatment has been failed, surgical treatment has to be considered. In these cases it is generally accepted that artificial urinary sphincter is the gold standard treatment. AUS 800 by American Medical Systems has been successfully used for more than 35 years. Recently three more sphincter devices, the Flow-Secure, the Periurethral Constrictor, and the ZSI 375, have been developed and presented in the market. A novel type of artificial urinary sphincter, the Tape Mechanical Occlusive Device, has been inserted in live canines as well as in human cadavers. These new sphincter devices are discussed in this paper focusing on safety and clinical results

Advanced glycation end products as a biomarker for incisional hernia

Background: Incisional hernia is one of the most frequent complications after abdominal surgery, with incidences up to 30%. A reliable biomarker for the prediction of this complication is lacking. Advanced glycosylation end products (AGEs), also known as non-enzymatic collagen crosslinks, are correlated with aging, smoking, hyperglycemia, hyperlipidemia and oxidative stress. In this study the accumulation of AGEs and the relation between AGEs and incisional hernia were investigated. Materials and methods: In an explorato

Satisfacción a largo plazo reportada por el paciente con diferentes prótesis de pene inflables: comparación entre AMS 700CX y Coloplast Titan

Article in PressErectile dysfunction (ED) is one of the most prevalent male sexual disorders worldwide. When conservative treatment is unsuccessful, contraindicated or causes unacceptable side effects penile prosthesis implantation is a definitive option for the management of ED. Although considered a third-line therapy, it achieves the highest satisfaction rates as compared with non-surgical treatment. Three-piece inflatable penile prothesis (IPP) represents the most sophisticated implantable device, AMS 700CX™ and Coloplast Titan® being the two most commonly used. Although there are several studies evaluating patient satisfaction with either model, there is little published data comparing both models.info:eu-repo/semantics/acceptedVersio