On the well-posedness of the Maxwell system for linear bianisotropic media

The time dependent Maxwell system is supplemented with the constitutive relations of linear bianisotropc media and is treated as a neutral integro-differential equation in a Hilbert space. By using the theory of abstract Volterra equations and strongly continuous semigroups we obtain general well-posedness results for the corresponding mathematical problem

Global and local curvature in density functional theory

Piecewise linearity of the energy with respect to fractional electron removal or addition is a requirement of an electronic structure method that necessitates the presence of a derivative discontinuity at integer electron occupation. Semi-local exchange-correlation (xc) approximations within density functional theory (DFT) fail to reproduce this behavior, giving rise to deviations from linearity with a convex global curvature that is evidence of many-electron, self-interaction error and electron delocalization. Popular functional tuning strategies focus on reproducing piecewise linearity, especially to improve predictions of optical properties. In a divergent approach, Hubbard U-augmented DFT (i.e., DFT+U) treats self-interaction errors by reducing the local curvature of the energy with respect to electron removal or addition from one localized subshell to the surrounding system. Although it has been suggested that DFT+U should simultaneously alleviate global and local curvature in the atomic limit, no detailed study on real systems has been carried out to probe the validity of this statement. In this work, we show when DFT+U should minimize deviations from linearity and demonstrate that a “+U” correction will never worsen the deviation from linearity of the underlying xc approximation. However, we explain varying degrees of efficiency of the approach over 27 octahedral transition metal complexes with respect to transition metal (Sc–Cu) and ligand strength (CO, NH3, and H2O) and investigate select pathological cases where the delocalization error is invisible to DFT+U within an atomic projection framework. Finally, we demonstrate that the global and local curvatures represent different quantities that show opposing behavior with increasing ligand field strength, and we identify where these two may still coincide.National Science Foundation (U.S.) (Grant ECCS-1449291)MIT Energy Initiative (Seed Grant)Massachusetts Institute of Technolog

Russo-Ukrainian War: Prediction and explanation of Twitter suspension

On 24 February 2022, Russia invaded Ukraine, starting what is now known as the Russo-Ukrainian War, initiating an online discourse on social media. Twitter as one of the most popular SNs, with an open and democratic character, enables a transparent discussion among its large user base. Unfortunately, this often leads to Twitter's policy violations, propaganda, abusive actions, civil integrity violation, and consequently to user accounts' suspension and deletion. This study focuses on the Twitter suspension mechanism and the analysis of shared content and features of the user accounts that may lead to this. Toward this goal, we have obtained a dataset containing 107.7M tweets, originating from 9.8 million users, using Twitter API. We extract the categories of shared content of the suspended accounts and explain their characteristics, through the extraction of text embeddings in junction with cosine similarity clustering. Our results reveal scam campaigns taking advantage of trending topics regarding the Russia-Ukrainian conflict for Bitcoin and Ethereum fraud, spam, and advertisement campaigns. Additionally, we apply a machine learning methodology including a SHapley Additive explainability model to understand and explain how user accounts get suspended

Η σιδηροπενία στους αιμοδότες

Η σιδηροπενία, η οποία ορίζεται με βάση τα επίπεδα φερριτίνης ορού ή πλάσματος ως <12μg/L σε παιδιά 0-5 ετών, και ως <15mg/L σε παιδιά μεγαλύτερα των 5 ετών και ενήλικες, αποτελεί την πιο κοινή διατροφική ανεπάρκεια σε παγκόσμιο επίπεδο και μπορεί να είναι απόλυτη, σχετική, και να συνοδεύεται από αναιμία. Η σιδηροπενία πλήττει πλέον περίπου το 35% του παγκόσμιου πληθυσμού. Το φαινόμενο εντείνεται στον πληθυσμό των αιμοδοτών, θέτοντας σε κίνδυνο τόσο την υγεία τους, όσο και την ομαλότητα της διαδικασίας της αιμοδοσίας και το απόθεμα των τραπεζών αίματος. Σκοπός της παρούσας μελέτης είναι να παρουσιάσει μια αμερόληπτη επισκόπηση της υπάρχουσας γνώσης σχετικά με την εμφάνιση της σιδηροπενίας στους αιμοδότες. Η επισκόπηση της βιβλιογραφίας έδειξε πως οι παράγοντες που συμβάλλουν, κατά κανόνα, στην ανάπτυξη υψηλών πιθανοτήτων εμφάνισης σιδηροπενίας ανάμεσα στους αιμοδότες είναι το γυναικείο φύλο, κυρίως προ της εμμηνόπαυσης, η νεαρότερη ηλικία και η εντατικότητα της αιμδοσίας, συμπεριλαμβανομένης της συχνότητας, της χρονικής απόστασης μεταξύ διαδοχικών αιμοδοσιών και του χρονικού διαστήματος από την τελευταία αιμοδοσία. Δευτερεύοντες, όχι τόσο ισχυρά εδραιωμένοι παράγοντες, όπως το μειωμένο βάρος, η απουσία καπνίσματος, η μαύρη φυλή, καθώς και γενετικοί πολυμορφισμοί, κυρίως των γονιδίων HFE και TMPRSS6, αποτελούν επίσης, παράγοντες κινδύνου. Η αντιμετώπιση του προβλήματος, η οποία μπορεί να επιτευχθεί κυρίως μέσω συμπληρωμάτων σιδήρου, μείωσης της συχνότητας των αιμοδοσιών με ταυτόχρονη αύξηση της χρονικής διάρκειας μεταξύ διαδοχικών αιμοδοσιών, αλλά και με συστηματική μέτρηση και αξιολόγηση των επιπέδων σιδήρου και φερριτίνης, είναι καίριας σημασίας προκειμένου να εξασφαλιστεί η υγεία των αιμοδοτών και να προληφθεί η έλλειψη αίματος στα κέντρα αιμοδοσίας.Iron deficiency (ID), defined based on ferritin levels <12μg/L in children 0-5 years old, and <15mg/L for children older than 5 years old and adults comprises the most common dietary deficiency worldwide and can be classified as absolute, relative and potentially lead to iron-deficient anemia. About 35% of the global population is currently suffering from iron deficiency, jeopardizing the donor’s health, as well as the process of blood donation itself and the blood bank stock. The aim of the current study is to present an unbiased review of the current knowledge concerning the prevalence of iron deficiency in whole blood donors. The review of up-to-date bibliography has shown that the main factors that are associated with an elevated risk of presenting with iron deficiency among whole blood donors are female sex, mainly for pre-menopausal women, younger age and blood donation intensity, including donation frequency, inter-donation intervals and time elapsed since the last donation. Along with these factors, other, secondary factors that are less well-established, such as reduced weight, non-smoking lifestyle, black race, as well as genetic polymorphisms, mainly on the genes HFE and TMPRSS6, are also considered to be risk factors. Facing this problem, which could be achieved by supplementary iron intake, reducing the donation intensity via reducing the donation frequency and prolonging the inter-donation interval, as well as by systematic and proper monitoring of iron status and ferritin levels, is of paramount importance in order to ensure the patient’s well-being and prevent blood shortage in blood donation centers

BotArtist: Twitter bot detection Machine Learning model based on Twitter suspension

Twitter as one of the most popular social networks, offers a means for communication and online discourse, which unfortunately has been the target of bots and fake accounts, leading to the manipulation and spreading of false information. Towards this end, we gather a challenging, multilingual dataset of social discourse on Twitter, originating from 9M users regarding the recent Russo-Ukrainian war, in order to detect the bot accounts and the conversation involving them. We collect the ground truth for our dataset through the Twitter API suspended accounts collection, containing approximately 343K of bot accounts and 8M of normal users. Additionally, we use a dataset provided by Botometer-V3 with 1,777 Varol, 483 German accounts, and 1,321 US accounts. Besides the publicly available datasets, we also manage to collect 2 independent datasets around popular discussion topics of the 2022 energy crisis and the 2022 conspiracy discussions. Both of the datasets were labeled according to the Twitter suspension mechanism. We build a novel ML model for bot detection using the state-of-the-art XGBoost model. We combine the model with a high volume of labeled tweets according to the Twitter suspension mechanism ground truth. This requires a limited set of profile features allowing labeling of the dataset in different time periods from the collection, as it is independent of the Twitter API. In comparison with Botometer our methodology achieves an average 11% higher ROC-AUC score over two real-case scenario datasets

Density functional theory for modelling large molecular adsorbate–surface interactions: a mini-review and worked example

First-principles simulation has played an ever-increasing role in the discovery and interpretation of the chemical properties of surface–adsorbate interactions. Nevertheless, key challenges remain for the computational chemist wishing to study surface chemistry: modelling the full extent of experimental conditions, managing computational cost, minimising human effort in simulation set-up and maximising accuracy. This article introduces new tools for streamlining surface chemistry simulation set-up and reviews some of the challenges in first-principles, density functional theory (DFT) simulation of surface phenomena. Furthermore, we provide a worked example of Co tetraphenylporphyrin on Au(1 1 1) in which we analyse electronic and energetic properties with semi-local DFT and compare to predictions made from hybrid functional and the so-called DFT+U correction. Through both review and the worked example, we aim to provide a pedagogical introduction to the challenges and the insight that first-principles simulation can provide in surface chemistry.National Science Foundation (U.S.) (ECCS-1449291

Experimental Classification and Enhanced Suppression of Parasitic Oscillations in Gyrotron Beam Tunnels

High-power gyrotrons may suffer from parasitic oscillations that are excited in the electron-beam compression zone. Different damping structures are proposed in the literature that reduce the possibility of parasitic excitation by increasing the starting currents of the modes. In this work, we focus on a dielectric-loaded (stacked) beam tunnel. Based on our previous theoretical studies, we make targeted modifications to the beam tunnel in order to classify the parasitic signals and localize the areas where they are excited. After two successive modifications, the beam tunnel exhibits improved behavior with higher starting currents of the parasitic modes. The experiments are performed by using a modular 170-GHz, 1-MW short-pulse gyrotron, which due to its flanged construction gives the possibility to modify the beam tunnel without affecting the rest of the tube