Beneficial effects of dark chocolate for episodic memory in healthy young adults: a parallel-groups acute intervention with a white chocolate control

There is good evidence that cocoa flavonoids can acutely improve cognitive function in humans, possibly via mechanisms such as increased cerebral blood flow. To date, much of the evidence is based on measures of executive function with extracts and cocoa-based interventions with a high flavonoid content. The aim of the present study was to explore whether benefits to episodic verbal memory and mood are observed two hours post consumption of a commercially available dark chocolate (DC) bar relative to a 35 g white chocolate bar (WC). Ninety-eight healthy young adults (n = 57 females) aged 18−24 years consumed either a 35 g DC bar or a calorie-matched low flavonoid WC bar. Verbal episodic memory and mood were assessed pre consumption and 2 h post consumption. An ANOVA analysis showed that the DC was associated with better verbal memory performance for several outcome measures of the Rey Auditory Verbal Learning Test relative to the WC, however, there were no effects on mood. These findings lend support to the notion that everyday available portions of dark chocolate can confer benefits to the brain in healthy consumers

The life?course formation of teachers? profession. How emotions affect VET teachers? social identity.

One of the less developed issues in the sociology of education concerns how the social formation of emotions affects teachers? collective identities. In this article we outline the ingredients of a conceptual scheme explaining the emotional dynamics which form teachers? social identities through a life-course perspective. In particular, we show how educational and job experiences related to teachers? social trajectories create emotional dynamics in their identities which undermine the sense of belongingness to their profession. Our methodology was based on biographical ? narrative interviews treated through a Critical Realism prism in order to bring to the fore the causal process through which a specific outcome is formed. By researching the extreme case of VET teachers in Greece who were put into redundancy for two years in the memorandum years, we explore why the threat of job loss, instead of mobilizing collective action, feeds feelings of self-blame and of shame which annul teachers? social ties.

Macrofaunal assemblages associated with the sponge Sarcotragus foetidus Schmidt, 1862 (Porifera: Demospongiae) at the coasts of Cyprus and Greece

Background: This paper describes a dataset of macrofaunal organisms associated with the sponge Sarcotragus foetidus Schmidt, 1862, collected by scuba diving from two sampling sites: one in Greece (North Aegean Sea) and one in Cyprus (Levantine Sea). New information: This dataset includes macrofaunal taxa inhabiting the demosponge Sarcotragus foetidus and contributes to the ongoing efforts of the Ocean Biogeographic Information System (OBIS) which aims at filling the gaps in our current knowledge of the world's oceans. This is the first paper, to our knowledge, where the macrofauna associated with S. foetidus from the Levantine Basin is being recorded. In total, 90 taxa were recorded, from which 83 were identified to the species level. Eight of these species are new records for the Levantine Basin. The dataset contains 213 occurrence records, fully annotated with all required metadata. It is accessible at http://lifewww-00.her.hcmr.gr:8080/medobis/resource.do?r=organismic_assemblages_sarcotragus_foetidus_cyprus_greec

Offensive Language Detection in Tweets Using Machine Learning Methods

Αναμφίβολα, η προσβλητική γλώσσα έχει γίνει διαδεδομένη στα μέσα κοινωνικής δικτύωσης τα τελευταία χρόνια λόγω της αυξανόμενης δημοτικότητάς τους. Ο αυξανόμενος αριθμός χρηστών που τείνουν να δημοσιεύουν προσβλητικό περιεχόμενο στοχεύοντας σε άτομα ή ομάδες επιφέρει σοβαρές επιπτώσεις όχι μόνο στην ευημερία των ατόμων, αλλά και στην ίδια την κοινωνία. Το γεγονός αυτό έχει προκαλέσει ανησυχία στις κυβερνήσεις, στις εταιρείες μέσων κοινωνικής δικτύωσης, αλλά και στις ακαδημαϊκές και κοινωνικές κοινότητες, οι οποίες έχουν καταβάλει συντονισμένες προσπάθειες για τον περιορισμό διάδοσης της προσβλητικής γλώσσας στο διαδίκτυο και τη δημιουργία ενός ασφαλέστερου διαδικτυακού χώρου. Ωστόσο, παρά τις προσπάθειές τους, η ανάγκη ταχείας επεξεργασίας ογκώδους πληροφορίας για τον εντοπισμό και την αναφορά προσβλητικής γλώσσας έχει καταστήσει την ανάπτυξη συστημάτων μηχανικής μάθησης κάτι παραπάνω από επιτακτική. Συνεπώς, στην παρούσα διπλωματική εργασία, εισάγονται τρία διαφορετικά μοντέλα μηχανικής μάθησης, τα οποία εκτελούν δυαδική ταξινόμηση κειμένου, για τον εντοπισμό προσβλητικής γλώσσας σε αγγλικά δημοσιεύματα κειμένων από το Twitter. Τα προτεινόμενα μοντέλα, τα οποία αποτελούνται από δύο απλούς ταξινομητές και ένα Bidirectional Stacked LSTM, αξιοποιούν τα contextual embeddings που προέρχονται από το BERTLARGE-Uncased με fine-tuning του σε τέσσερα σύνολα δεδομένων εκπαίδευσης συγκεντρωμένα σε ένα. Η διαδικασία προετοιμασίας των δεδομένων περιλαμβάνει καθαρισμό και προ-επεξεργασία των δεδομένων, καθώς και υποδειγματοληψίας των δεδομένων για την αντιμετώπιση της ανισορροπίας των κλάσεων. Η αποτελεσματικότητα των προτεινόμενων μεθόδων αξιολογείται σε δύο διαθέσιμα σύνολα δεδομένων αξιολόγησης, τα OLID 2019 και OLID 2020, με βάση έξι μετρικές, καθώς και τις καμπύλες μάθησης της απώλειας και της ακρίβειας. Η συγκριτική ανάλυση μεταξύ αυτών των μεθόδων αποδεικνύει ότι η συνένωση των τεσσάρων τελευταίων κρυφών επιπέδων του BERT που περνούν σε έναν ταξινομητή υπερτερεί των άλλων μοντέλων επιτυγχάνοντας 77,8% και 86,8% Macro-F1 σκορ στα δύο σύνολα δεδομένων αξιολόγησης αντίστοιχα. Η σύγκριση με προηγούμενες συναφείς μεθόδους αποκαλύπτει ότι, μολονότι τα αποτελέσματα είναι ικανοποιητικά, υπάρχουν περιθώρια για περισσότερο πειραματισμό και βελτίωση στο μέλλον.Undoubtedly, offensive language has become ubiquitous in social media over the last years due to the increasing popularity of social media platforms. The growing number of users that tend to post offensive content targeting individuals or groups has led to significant repercussions not only for the well-being of the targets, but also for society itself. This has raised concern in governments, social media companies as well as academic and social communities, who have made concerted efforts to curb the dissemination of offensive language online and create a safer digital space. Nevertheless, despite their endeavors, the need to rapidly process huge amounts of content in order to detect and report offensive language has made the development of machine learning systems more than imperative. Consequently, in the present thesis, three different machine learning models, which perform binary text classification, are introduced to detect offensive language in English texts from Twitter. The proposed models, which constitute two simple classifiers and a Bidirectional Stacked LSTM, utilize contextual embeddings pooled from BERTLARGE-Uncased by fine-tuning its various layers on four training datasets combined in one. The data preparation process involved data cleaning and preprocessing as well as data down-sampling to handle class imbalance. The effectiveness of the proposed methods is evaluated on two available test sets, OLID 2019 and OLID 2020, based on six metrics, the learning curves of loss and accuracy as well. Comparative analysis between those methods demonstrates that the concatenation of the last four hidden layers of BERT fed in a classifier outperforms the other models by achieving 77.8% and 86.8% Macro-F1 scores on the two test sets respectively. Comparison with previous related methods indicates that, although the results are satisfactory, there is room for further experimentation and improvement in the future

Acute hepatitis and myositis associated with Erythema infectiosum by Parvovirus B19 in an adolescent

Background: Erythema infectiosum is the most common clinical manifestation of Parvovirus B19 infection although it has also been associated with rheumatologic diseases and various types of systemic vasculitides. Acute hepatitis and benign myositis however are rarely reported in association with Parvovirus B19 infection. Case presentation: Here we report a 14-year old male, who developed acute hepatitis and benign myositis associated with erythema infectiosum following Parvovirus B19 infection. Conclusion: Parvovirus B19 infection has rarely been associated with acute hepatitis and exceptionally rarely with benign myositis. Parvovirus B19 should be considered in the differential diagnosis of acute non-A to E hepatitis and in the case of acute benign myositis presenting with a rash especially in children

A novel c.5308_5311delGAGA mutation in Senataxin in a Cypriot family with an autosomal recessive cerebellar ataxia

<p>Abstract</p> <p>Background</p> <p>Senataxin (chromosome 9q34) was recently identified as the causative gene for an autosomal recessive form of Ataxia (ARCA), termed as Ataxia with Oculomotor Apraxia, type 2 (AOA2) and characterized by generalized incoordination, cerebellar atrophy, peripheral neuropathy, "oculomotor apraxia" and increased alpha-fetoprotein (AFP). Here, we report a novel Senataxin mutation in a Cypriot ARCA family.</p> <p>Methods</p> <p>We studied several Cypriot autosomal recessive cerebellar ataxia (ARCA) families for linkage to known ARCA gene loci. We linked one family (909) to the SETX locus on chromosome 9q34 and screened the proband for mutations by direct sequencing.</p> <p>Results</p> <p>Sequence analysis revealed a novel c.5308_5311delGAGA mutation in exon 11 of the SETX gene. The mutation has not been detected in 204 control chromosomes from the Cypriot population, the remaining Cypriot ARCA families and 37 Cypriot sporadic cerebellar ataxia patients.</p> <p>Conclusion</p> <p>We identified a novel SETX homozygous c.5308_5311delGAGA mutation that co-segregates with ARCA with cerebellar atrophy and raised AFP.</p

Hospital Anxiety and Depression Scale (HADS): validation in a Greek general hospital sample

<p>Abstract</p> <p>Background</p> <p>The Hospital Anxiety and Depression Scale (HADS) has been used in several languages to assess anxiety and depression in general hospital patients with good results.</p> <p>Methods</p> <p>The HADS was administered to 521 participants (275 controls and 246 inpatients and outpatients of the Internal Medicine and Surgical Departments in 'Attikon' General Hospital in Athens). The Beck Depression Inventory (BDI) and the State-Trait Anxiety Inventory (STAI) were used as 'gold standards' for depression and anxiety respectively.</p> <p>Results</p> <p>The HADS presented high internal consistency; Cronbach's α cofficient was 0.884 (0.829 for anxiety and 0.840 for depression) and stability (test-retest intraclass correlation coefficient 0.944). Factor analysis showed a two-factor structure. The HADS showed high concurrent validity; the correlations of the scale and its subscales with the BDI and the STAI were high (0.722 – 0.749).</p> <p>Conclusion</p> <p>The Greek version of HADS showed good psychometric properties and could serve as a useful tool for clinicians to assess anxiety and depression in general hospital patients.</p

Brain Bases of Reading Fluency in Typical Reading and Impaired Fluency in Dyslexia

Although the neural systems supporting single word reading are well studied, there are limited direct comparisons between typical and dyslexic readers of the neural correlates of reading fluency. Reading fluency deficits are a persistent behavioral marker of dyslexia into adulthood. The current study identified the neural correlates of fluent reading in typical and dyslexic adult readers, using sentences presented in a word-by-word format in which single words were presented sequentially at fixed rates. Sentences were presented at slow, medium, and fast rates, and participants were asked to decide whether each sentence did or did not make sense semantically. As presentation rates increased, participants became less accurate and slower at making judgments, with comprehension accuracy decreasing disproportionately for dyslexic readers. In-scanner performance on the sentence task correlated significantly with standardized clinical measures of both reading fluency and phonological awareness. Both typical readers and readers with dyslexia exhibited widespread, bilateral increases in activation that corresponded to increases in presentation rate. Typical readers exhibited significantly larger gains in activation as a function of faster presentation rates than readers with dyslexia in several areas, including left prefrontal and left superior temporal regions associated with semantic retrieval and semantic and phonological representations. Group differences were more extensive when behavioral differences between conditions were equated across groups. These findings suggest a brain basis for impaired reading fluency in dyslexia, specifically a failure of brain regions involved in semantic retrieval and semantic and phonological representations to become fully engaged for comprehension at rapid reading rates