“PLAY ME”

Created during the COVID-19 pandemic, “PLAY ME” is a video work that discusses the difference between physical-perceptual experience and our limited understanding of the outer world. The artwork uses a first-person walking practice in combination with narration and sound as a mapping tool, and public pianos as a guide for exploring our cities and the aesthetics of digital culture. The purpose of this short manuscript is to analyse the role of the narrator in the self-referential storytelling of my video work “PLAY ME.” I will discuss self-referentialism as a creative tool, and the role of the narrator as a portal for connecting materials with ideas. To do this, it will be helpful to divide and analyse the plot of this work into parts, so the following analysis in artist’s voice will be clearer

I Am Narrating Lost Memories Through Pinecone Structures

In the island of Corfu in Greece, there are four sculptures of pinecones hanging in the streets around Saint Spyridon’s church in the old town; these pinecones can also be found around the icons of the Saint inside the church. Pinecones are an ancient symbol, but in the case of Corfu, they reflect the unity in the society. In this case, pinecones work as a mosaic, pine nuts as tesserae (mosaic tiles), which can include different materials, organisations and forms of energy that co-exist in the city, while the city is the space where the dialogue between diverse types of tesserae takes place. Through my PhD research, being inspired by the above symbol, I propose Pinecone Structures as a new concept of creation for art organisations, where the symbiotic relationship between different media and kinds of materials, enables their equal utilisation to the artist’s practice. This transdisciplinary phenomenon makes all materials, beings and events interact with each other by being a part of the same play. This idea in practice leads to the creation of a mosaic with materials rather than a composition with objects, sounds and notes. The output of my research is the creation of situations in which actions can involve all kinds of materials. This means that I do not use all possible materials throughout my work, but it is important to have them in my palette. This hybrid method of art creation brings together action and metaphors with transdisciplinary practices, by extending and connecting all the materials an artist can use. Pinecone Structures is a concept, which can be perceived and understood at the same time as methodology, epistemology and metaphor. Four main elements shape my practice through the creation of an interactive community. Pinecone Structures, Narration, Space and Society create an “ecosystem”, where disconnected materials or- bit as a single unity. I argue that Pinecone Structures is the concept that connects different types of matter; Narration is the umbrella that covers and gives a purpose to this network; Space is the volume, where the dialogue between the artwork, artwork’s materials and the Society takes place. This approach seeks to blur the borders between the disciplines

Ανασκόπηση ανοιχτής και ενδαγγειακής αποκατάστασης των ανευρυσμάτων της ανωνύμου αρτηρίας

Σκοπός: Καθώς τα ανευρύσματα της ανωνύμου αρτηρίας αποτελούν σπάνια νοσολογική οντότητα σκοπός της παρούσης εργασίας είναι να συλλεχθούν τα υπάρχοντα δεδομένα και να εξαχθούν χρήσιμα συμπεράσματα τόσο για τα χαρακτηριστικά της νόσου όσο και για τις μεθόδους αντιμετώπισης. Απώτερος στόχος είναι η ανάλυση και σύγκριση των αποτελεσμάτων της ανοιχτής και της κλειστής / υβριδικής μεθόδου αντιμετώπισης ώστε να παραχθούν και να καταγραφούν συμπεράσματα για χρήση στην καθημερινή κλινική πράξη. Υλικό και μέθοδος: Πραγματοποιήθηκε συστηματική διαδικτυακή έρευνα στις βάσεις δεδομένων Medline, Google Scholar και Scopus με ευρείς όρους αναζήτησης χωρίς χρονικούς περιορισμούς. Συμπεριελήφθησαν τόσο τα αληθή όσο και τα ψευδή ανευρύσματα. Η συντριπτική πλειονότητα των μελετών ήταν αναφορές μεμονωμένων περιστατικών ή μικρές αναδρομικές σειρές με λιγότερους από 5 ασθενείς. Τα δεδομένα καταγράφηκαν σε φύλλα διαχείρισης (Excel) και αναλύθηκαν με βάση ενδεδειγμένες στατιστικές μεθόδους. Αποτελέσματα: Ανευρέθηκαν 341 ανευρύσματα ανωνύμου αρτηρίας από το 1828 έως και το τέλος του 2019 που αναλύθηκαν ως προς τα δημογραφικά και κλινικά χαρακτηριστικά τους και τη μεταβολή αυτών στο πέρασμα του χρόνου. Στη σύγκριση των μεθόδων αντιμετώπισης συμμετείχαν 162 περιπτώσεις που αντιμετωπίσθηκαν ανοιχτά, 43 κλειστά και 18 υβριδικά από το 1962 και μετά. Το συχνότερο αίτιο ανευρυσμάτων είναι τα ψευδοανευρύσματα απότοκα κλειστής τραυματικής κάκωσης του θώρακα. Τα πρώιμα αποτελέσματα ήταν ικανοποιητικά και για τις δύο μεθόδους αντιμετώπισης αν και το είδος των επιπλοκών διέφερε σημαντικά. Ο μικρός χρόνος μετεγχειρητικής παρακολούθησης (10,5 μήνες) για την ενδαγγειακή μέθοδο δεν επιτρέπει την εξαγωγή ασφαλών μακροχρόνιων συμπερασμάτων. Συμπεράσματα: Η ενδαγγειακή αντιμετώπιση αποτελεί ελκυστική εναλλακτική μέθοδο της ανοιχτής επέμβασης και, τα τελευταία χρόνια, παρέχει υποσχόμενα αποτελέσματα. Οι κλασικές επιπλοκές της ανοιχτής μεθόδου (από το αναπνευστικό και κεντρικό νευρικό σύστημα), αλλά και αυτές των ενδαγγειακών προθέσεων (ενδοδιαφυγή, μετακίνηση) παραμένουν στο επίκεντρο του προβληματισμού. Η προσεκτική επιλογή των ασθενών είναι απαραίτητη καθώς παραμένει αναπάντητο το ερώτημα της μακροβιότητας των ενδοπροθέσεων.Objectives: Innominate artery aneurysms are a rare entity. The purpose of this work is to collect existing data and reach conclusions about both the characteristics of the disease and the methods of treatment. The ultimate goal is to analyze and compare the results of the open and closed/hybrid methods of treatment in order to produce conclusions for use in daily clinical practice. Material and Methods: A systematic online research was performed on Medline, Google Scholar, and Scopus databases with extensive search terms and no time constraints. Both true and false aneurysms were included. The overwhelming majority of studies were case reports or small retrospective series with less than 5 patients. Data were recorded in Excel sheets and analyzed using appropriate statistical methods. Results: 341 innominate artery aneurysms were found from 1828 to the end of 2019 that were analyzed for their demographic and clinical characteristics and their change over time. Comparison of treatment methods involved 162 open, 43 closed and 18 hybrid cases from 1962 onwards. The most common cause of innominate artery aneurysms is pseudoaneurysms due to closed thoracic injury. Early results were satisfactory for both methods although the type of complications varied significantly. The short post-operative follow-up time (10.5 months) for the endovascular treatment does not allow safe long-term conclusions to be drawn. Conclusions: Endovascular therapy offers an attractive alternative to open surgery and, in recent years, has yielded promising results. The classic open complications (from respiratory and central nervous system) and those of endovascular treatment (endoleaks and migration) remain at the center of concern. Careful selection of patients is essential as there is still insufficient data in the literature on the long-term outcome of stents

Agnostic Learning for Packing Machine Stoppage Prediction in Smart Factories

The cyber-physical convergence is opening up new business opportunities for industrial operators. The need for deep integration of the cyber and the physical worlds establishes a rich business agenda towards consolidating new system and network engineering approaches. This revolution would not be possible without the rich and heterogeneous sources of data, as well as the ability of their intelligent exploitation, mainly due to the fact that data will serve as a fundamental resource to promote Industry 4.0. One of the most fruitful research and practice areas emerging from this data-rich, cyber-physical, smart factory environment is the data-driven process monitoring field, which applies machine learning methodologies to enable predictive maintenance applications. In this paper, we examine popular time series forecasting techniques as well as supervised machine learning algorithms in the applied context of Industry 4.0, by transforming and preprocessing the historical industrial dataset of a packing machine's operational state recordings (real data coming from the production line of a manufacturing plant from the food and beverage domain). In our methodology, we use only a single signal concerning the machine's operational status to make our predictions, without considering other operational variables or fault and warning signals, hence its characterization as ``agnostic''. In this respect, the results demonstrate that the adopted methods achieve a quite promising performance on three targeted use cases

Undifferentiated embryonal sarcoma of the liver mimicking acute appendicitis. Case report and review of the literature

BACKGROUND: Undifferentiated embryonal sarcoma (UES) of liver is a rare malignant neoplasm, which affects mostly the pediatric population accounting for 13% of pediatric hepatic malignancies, a few cases has been reported in adults. CASE PRESENTATION: We report a case of undifferentiated embryonal sarcoma of the liver in a 20-year-old Caucasian male. The patient was referred to us for further investigation after a laparotomy in a district hospital for spontaneous abdominal hemorrhage, which was due to a liver mass. After a through evaluation with computed tomography scan and magnetic resonance imaging of the liver and taking into consideration the previous history of the patient, it was decided to surgically explore the patient. Resection of I–IV and VIII hepatic lobe. Patient developed disseminated intravascular coagulation one day after the surgery and died the next day. CONCLUSION: It is a rare, highly malignant hepatic neoplasm, affecting almost exclusively the pediatric population. The prognosis is poor but recent evidence has shown that long-term survival is possible after complete surgical resection with or without postoperative chemotherapy

A New Approach for Broken Rotor Bar Detection in Induction Motors Using Frequency Extraction in Stray Flux Signals

This paper offers a reliable solution to the detection of broken rotor bars in induction machines with a novel methodology, which is based on the fact that the fault-related harmonics will have oscillating amplitudes due to the speed ripple effect. The method consists of two main steps: Initially, a time-frequency transformation is used and the focus is given on the steady-state regime; thereupon, the fault-related frequencies are handled as periodical signals over time and the classical fast Fourier transform is used for the evaluation of their own spectral content. This leads to the discrimination of subcomponents related to the fault and to the evaluation of their amplitudes. The versatility of the proposed method relies on the fact that it reveals the aforementioned signatures to detect the fault, regardless of the spatial location of the broken rotor bars. Extensive finite element simulations on a 1.1 MW induction motor and experimental testing on a 1.1 kW induction motor lead to the conclusion that the method can be generalized on any type of induction motor independently from the size, power, number of poles, and rotor slot numbers

On the broken rotor bar diagnosis using time-frequency analysis:'Is one spectral representation enough for the characterisation of monitored signals?'

© 2019 Institution of Engineering and Technology. All rights reserved. This work enhances the knowledge of the diagnostic potential of the broken bar fault in induction motors. Since a series of studies have been published over the years regarding condition monitoring and fault diagnostics of these machines, it is essential to reach a common ground on why - sometimes - different techniques render different results. In this context, an investigation is provided with regards to the optimal window that should be adopted for the implementation of a proper time-frequency analysis of the monitored signals. On this agenda, this study attempts to set lower and upper bound limits for proper windowing from the digital signal processing point of view. This is done by proposing a formula for the lower limit, which is derived according to the specific frequencies one desires to put under inspection and which are the fault-related signatures. Finally, a discussion on the upper bound is put onwards; results from finite-element simulations are examined with the discussed approach in both the transient regime and the steady state, while experimental results verify the simulations with satisfying accuracy

FEM approach for diagnosis of induction machines' non-adjacent broken rotor bars by short-time Fourier transform spectrogram

Rotor electrical faults are an issue frequently encountered when applying condition monitoring and fault diagnosis on induction machines. The detection via the analysis of the stator current becomes challenging when the rotor cage suffers from multiple breakages at non-adjacent positions. In that case, electromagnetic asymmetries induced by the broken bars can be masked in such a way, that the diagnostic ability is highly likely to be obscured, thus leading to misinterpretation of the monitored signals’ signatures. A new approach is proposed in this work to overcome this problem while the motor is at steady state. In this paper, an industrial 6.6kV, 1.1MW induction motor is simulated with Finite Element Analysis (FEM) and its electromagnetic variables are analysed and studied under healthy state and several faulty conditions. The analysis of the stator current and stray flux waveforms is executed in both the transient and the steady state and aims to diagnose the challenging cases where the rotor breakages are nonconsecutive with regards to their spatial location. The results show the potential of flux analysis to fault severity regardless of the spatial position of the broken bars