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Background: Migrants globally, including refugees and asylum seekers, have experienced adverse clinical and socioeconomic impacts of the COVID-19 pandemic. For approximately 56,000 refugees and asylum seekers in Reception and Identification Centers (RICs) and Reception Sites (RS) in Greece, living in severely substandard living conditions, prevention measures have been impossible with limited provision in terms of routine testing, surveillance, and access to healthcare. These migrant populations have experienced prolonged lockdowns and restricted movement since the pandemic began. We aimed to assess the impact of COVID-19 on refugees and asylum seekers in reception facilities in Greece and explore implications for policy and practice. Methods: A retrospective analysis of policy documents and national surveillance data was conducted to identify COVID-19 outbreaks and estimate incidence among asylum seekers and refugees residing in these camps during the first 9 months of the epidemic in Greece (26th February - 15th November 2020). Incidence proportion (IP) of COVID-19 confirmed cases was calculated for three population groups (refugees and asylum seekers in RICs, refugees and asylum seekers in RSs, and the general population in Greece) during three time periods (first wave, second wave, and overall across the 9-month period). Findings: Twenty-five COVID-19 outbreaks were identified in refugee and asylum seeker reception facilities, with 6 (85.7%) of 7 RICs and 18 (56.3%) of 32 RSs reporting at least one outbreak during the study period. The overall 9-month COVID-19 IP among refugee and asylum seeker populations residing in RSs on the Greek mainland was 1758 cases per 100,000 population; in RICs the incidence was 2052 cases per 100,000 population. Compared to the general population the risk of COVID-19 infection among refugees and asylum seekers in reception facilities was 2.5 to 3 times higher (p-value

Background: Although socioeconomic disparities adversely affect health, studies referring to the “healthy immigrant effect” imply more favorable health outcomes in immigrants than natives. We aimed to investigate the impact of immigration on several perinatal parameters. Methods: Birth records (01/01/2010 − 31/12/2014) from a public maternity hospital in Athens, Greece were reviewed for maternal (ethnicity, age, delivery mode) and neonatal (gender, birthweight, gestational age) variables. Immigrants were classified by country of origin, according to Human Development Index. Comparison of results between Greeks and immigrants were made. Stratification by maternal age (< and ≥35 years) was conducted to test for confounding and interaction. Results: Almost one-third of 7506 deliveries applied to immigrants; 36.3% of Greeks and 19.2% of immigrants [risk ratio (RR) = 0.53, 95% confidence interval (CI) = 0.52–0.54] delivered at ≥35 years; 10.5% of Greek and 7.0% of immigrant neonates weighted

Since 2008, Greece suffers a severe economic crisis. Adverse health outcomes have been reported, but studies on perinatal health are sparse. We aimed to examine the impact of economic crisis on perinatal parameters during early and established crisis periods. Birth records of 14 923 neonates, born in a public maternity hospital from 2005–2014, were reviewed for maternal (age, delivery mode) and neonatal (gender, birthweight, gestational age) variables. Univariable analysis tested the association of study variables with time-periods 2005–2007, 2009–2011 and 2012–2014. Multivariable logistic regression analysis identified factors independently associated with low birthweight (LBW) (

Background: Research on Roma health is fragmentary as major methodological obstacles often exist. Reliable estimates on vaccination coverage of Roma children at a national level and identification of risk factors for low coverage could play an instrumental role in developing evidence-based policies to promote vaccination in this marginalized population group. Methods: We carried out a national vaccination coverage survey of Roma children. Thirty Roma settlements, stratified by geographical region and settlement type, were included; 7-10 children aged 24-77 months were selected from each settlement using systematic sampling. Information on children's vaccination coverage was collected from multiple sources. In the analysis we applied weights for each stratum, identified through a consensus process. Results: A total of 251 Roma children participated in the study. A vaccination document was presented for the large majority (86%). We found very low vaccination coverage for all vaccines. In 35-39% of children 'minimum vaccination' (DTP3 and IPV2 and MMR1) was administered, while 34-38% had received HepB3 and 31-35% Hib3; no child was vaccinated against tuberculosis in the first year of life. Better living conditions and primary care services close to Roma settlements were associated with higher vaccination indices. Conclusions: Our study showed inadequate vaccination coverage of Roma children in Greece, much lower than that of the non-minority child population. This serious public health challenge should be systematically addressed, or, amid continuing economic recession, the gap may widen. Valid national estimates on important characteristics of the Roma population can contribute to planning inclusion policies. © 2016 The Author.

Στην παρούσα εργασία γίνεται εφαρμογή ενός Αλγορίθμου Βελτιστοποίησης Αποικίας Μυρμηγκιών, για την ελαχιστοποίηση του κόστους των αγωγών δύο υπό πίεση ακτινωτών αρδευτικών δικτύων βαρύτητας. Οι ευρετικοί και μεθευρετικοί αλγόριθμοι βελτιστοποίησης έχουν τύχει μεγάλης αναγνώρισης και ανάπτυξης τα τελευταία χρόνια σε πολλούς τομείς έρευνας. Όμως, η εφαρμογή τους σε υπό πίεση δίκτυα άρδευσης είναι πολύ περιορισμένη. Για την ανάπτυξη του αλγορίθμου χρησιμοποιήθηκε η γλώσσα προγραμματισμού Fortran. Στον κώδικα προγραμματισμού ενσωματώθηκαν όλοι οι απαραίτητοι υδραυλικοί υπολογισμοί και ο έλεγχος της υδραυλικής συνέπειας των αποτελεσμάτων. Για την καλύτερη αξιολόγηση της μεθόδου πραγματοποιήθηκε συγκριτική αξιολόγηση των αποτελεσμάτων με τη μέθοδο του Γραμμικού Προγραμματισμού., The present paper deals with the application of an Ant Colony Optimization Algorithm for the cost minimization of pipes of two branched pressurized gravity irrigation networks. Heuristic and meta-heuristic optimization algorithms have received much recognition and growth in recent years in many fields of research. However, their applications in pressurized irrigation networks are very limited. For the development of the algorithm the programming language Fortran was used. In the programming code all the necessary hydraulic calculations and the control of hydraulic consistency of the results are integrated. To better evaluate the method, a comparative analysis of the results with the method of Linear Programming was made.

Αντικείμενο της εργασίας αυτής, είναι η εκτίμηση του υδατικού αποτυπώματος (ΥΑ) (Water Footprint) των καλλιεργειών της πεδιάδας Θεσσαλονίκης. Ο υπολογισμός του ΥΑ, έγινε με δύο διαφορετικές μεθοδολογίες. Η πρώτη προτάθηκε από τους Hoekstra-Chapagain (μέθοδος H-C) και η δεύτερη αναπτύχθηκε αργότερα από τους Ridoutt-Pfister (μέθοδος R-P) ως μία αναθεωρημένη μορφή της αρχικής μεθόδου. Στα ερευνητικά πλαίσια αυτής της εργασίας, εκτιμήθηκε επιπρόσθετα, το ΥΑ των παραπάνω καλλιεργειών με τη μέθοδο H-C, κάτω από ένα σενάριο κλιματικής αλλαγής. Εκτιμήθηκε επίσης ο δείκτης πίεσης νερού (WSI) (Water Stress Index) της μεθόδου R-P με τη βοήθεια δεδομένων κλιματικών και υδατικής διαθεσιμότητας της υπό μελέτη περιοχής. Αξιοποιώντας τις πληροφορίες του ΥΑ των καλλιεργειών μπορεί να δρομολογηθεί η παραγωγή προς λιγότερο υδροβόρες και ρυπογόνες κατευθύνσεις εξασφαλίζοντας την ποσοτική και ποιοτική διαφύλαξη των υδατικών πόρων., Aim of this paper is the water footprint (WF) estimation of crops in the plain of Thessaloniki. Two different methodologies were applied for the estimation of the WF. The first introduced by Hoekstra and Chapagain (H-C method) and the second which is a revised version of the first, by Ridoutt and Pfister (R-P method). In the research part of this study, the WF of the above crops, under one climate change scenario, was estimated by the H-C method. Furthermore, the WSI (Water Stress Index) after R-P method, was calculated based on regional climate and water availability data. Utilizing information of the water footprint of crops we can infer which activities consume large quantities of water and where it is possible replace them, to other less demanding in order to implement the proper management of water resources.

Η πρόβλεψη της κλιματικής αλλαγής βασίζεται κυρίως στις εκτιμήσεις των μοντέλων γενικής κυκλοφορίας (General Circulation Models) (GCMs). Οι εκτιμήσεις αυτές αναφέρονται σε μεγάλη χωρική ανάλυση και είναι επιβεβλημένη η εφαρμογή διαδικασιών για τον υποβιβασμό κλίμακας (downscaling) σε κλίμακα είτε τοπική είτε σταθμού. Στην εργασία αυτή ο υποβιβασμός περιγράφει τη σχέση μεταξύ μετεωρολογικών μεταβλητών μεγάλης κλίμακας που προσομοιώνονται από GCMs μοντέλα όπως είναι η βροχόπτωση, η θερμοκρασία, η υγρασία κ.λπ. και της μηνιαίας βροχόπτωσης ενός σταθμού και γίνεται με την εφαρμογή τεχνητών νευρωνικών δικτύων (Artificial Neural Networks) (ANNs) σε συνδυασμό με ανάλυση κυρίων συνιστωσών (PCA). Από την ανάλυση των αποτελεσμάτων συμπεραίνεται η καταλληλότητα των ANNs μοντέλων για τον υποβιβασμό κλίμακας μετεωρολογικών μεταβλητών όπως η βροχόπτωση, η θερμοκρασία, η εξατμισοδιαπνοή κ.λπ., Climate change predictions are generally based on the estimations by general circulation models (GCMs). The GCMs outputs are usually at resolution that is too coarse for many climate change impact studies. Hence, there is a great need to develop tools for downscaling GCM predictions of climate change to regional and local or station scales. This paper examines the potential of the Artificial Neural Network models (ANNs) in combination with Principal Component Analysis (PCA) to describe the relationship between large-scale atmospheric variables such as precipitation, temperature, humidity, pressure, geopotential height etc., and monthly precipitation for a station. It was concluded that ANN-based downscaling models are reliable and can be applied to atmospheric variables downscaling, like precipitation, temperature, evapotranspiration etc.

The last 40 years Monte Carlo (MC) simulations serve as a “gold standard” tool for a wide range of applications in the field of medical physics and tend to be essential in daily clinical practice. Regarding diagnostic imaging applications, such as computed tomography (CT), the assessment of deposited energy is of high interest, so as to better analyze the risks and the benefits of the procedure. The last few years a big effort is done towards personalized dosimetry, especially in pediatric applications. In the present study the GATE toolkit was used and computational pediatric phantoms have been modeled for the assessment of CT examinations dosimetry. The pediatric models used come from the XCAT and IT’IS series. The X-ray spectrum of a Brightspeed CT scanner was simulated and validated with experimental data. Specifically, a DCT-10 ionization chamber was irradiated twice using 120 kVp with 100 mAs and 200 mAs, for 1 sec in 1 central axial slice (thickness = 10mm). The absorbed dose was measured in air resulting in differences lower than 4% between the experimental and simulated data. The simulations were acquired using similar to 10(10) number of primaries in order to achieve low statistical uncertainties. Dose maps were also saved for quantification of the absorbed dose in several children critical organs during CT acquisition.

Web educational resources integrating interactive simulation tools provide students with an in-depth understanding of the medical imaging process. The aim of this work was the development of a purely Web-based, open access, interactive application, as an ancillary learning tool in graduate and postgraduate medical imaging education, including a systematic evaluation of learning effectiveness. The pedagogic content of the educational Web portal was designed to cover the basic concepts of medical imaging reconstruction and processing, through the use of active learning and motivation, including learning simulations that closely resemble actual tomographic imaging systems. The user can implement image reconstruction and processing algorithms under a single user interface and manipulate various factors to understand the impact on image appearance. A questionnaire for pre- and post-training self-assessment was developed and integrated in the online application. The developed Web-based educational application introduces the trainee in the basic concepts of imaging through textual and graphical information and proceeds with a learning-by-doing approach. Trainees are encouraged to participate in a pre- and post-training questionnaire to assess their knowledge gain. An initial feedback from a group of graduate medical students showed that the developed course was considered as effective and well structured. An e-learning application on medical imaging integrating interactive simulation tools was developed and assessed in our institution. © 2014, Society for Imaging Informatics in Medicine.

Patient-specific dosimetry calculations based on simulation techniques have as a prerequisite the modeling of the modality system and the creation of voxelized phantoms. This procedure requires the knowledge of scanning parameters and patients’ information included in a DICOM file as well as image segmentation. However, the extraction of this information is complicated and time-consuming. The objective of this study was to develop a simple graphical user interface (GUI) to (i) automatically extract metadata from every slice image of a DICOM file in a single query and (ii) interactively specify the regions of interest (ROI) without explicit access to the radiology information system. The user-friendly application developed in Matlab environment. The user can select a series of DICOM files and manage their text and graphical data. The metadata are automatically formatted and presented to the user as a Microsoft Excel file. The volumetric maps are formed by interactively specifying the ROIs and by assigning a specific value in every ROI. The result is stored in DICOM format, for data and trend analysis. The developed GUI is easy, fast and and constitutes a very useful tool for individualized dosimetry. One of the future goals is to incorporate a remote access to a PACS server functionality.

The effects of elevated atmospheric CO2 (560 p.p.m.) and subsequent plant responses on the soil microbial community composition associated with trembling aspen was assessed through the classification of 6996 complete ribosomal DNA sequences amplified from the Rhinelander WI free-air CO2 and O-3 enrichment (FACE) experiments microbial community metagenome. This in-depth comparative analysis provides an unprecedented, detailed and deep branching profile of population changes incurred as a response to this environmental perturbation. Total bacterial and eukaryotic abundance does not change; however, an increase in heterotrophic decomposers and ectomycorrhizal fungi is observed. Nitrate reducers of the domain bacteria and archaea, of the phylum Crenarchaea, potentially implicated in ammonium oxidation, significantly decreased with elevated CO2. These changes in soil biota are evidence for altered interactions between trembling aspen and the microorganisms in its surrounding soil, and support the theory that greater plant detritus production under elevated CO2 significantly alters soil microbial community composition.

Haematologica-the Hematology Journal

Serotypes and antibiotic sensitivities were determined for 338 strains of Streptococcus pneumoniae from children of north-western Greece with invasive pneumococcal disease (IPD), acute otitis media (AOM) and nasopharyngeal carriage. The most common serotypes among the isolates from IPD were 14 and 19F, while 3, 19F, 9V and 14 were the major cause of AOM. In these groups, the heptavalent conjugate vaccine for pneumococci (7vPCV) seems to cover 90.5% of the serotypes isolated from children less than 2 years old. Serotypes 23F and 6B were the most prevalent in carrier strains. Overall, 23.7% of the isolates were penicillin nonsusceptible (PNS), 97% were fully susceptible to cefotaxime, 29% were resistant to erythromycin, 11.2% to co-trimoxazole and 1.2% to clindamycin. FEMS Immunol Med Microbiol

River flow routing provides basic information on a wide range of problems related to the design and operation of river systems. In this paper, three layer cascade correlation Time Delay Artificial Neural Network (TDANN) models have been developed to forecast the one day ahead daily flow at Ilarionas station on the Aliakmon river, in Northern Greece. The networks are time lagged feed-formatted with delayed memory processing elements at the input layer. The network topology is using multiple inputs, which include the time lagged daily flow values further up at Siatista station on the Aliakmon river and at Grevena station on the Venetikos river, which is a tributary to the Aliakmon river and a single output, which are the daily flow values at Ilarionas station. The choice of the input variables introduced to the input layer was based on the cross-correlation. The use of cross-correlation between the ith input series and the output provides a short cut to the problem of the delayed memory determination. Kalman's learning rule was used to modify the artificial neural network weights. The networks are designed by putting weights between neurons, by using the hyperbolic-tangent function for training. The number of nodes in the hidden layer was determined based on the maximum value of the correlation coefficient. The results show a good performance of the TDANN approach for forecasting the daily flow values, at Ilarionas station and demonstrate its adequacy and potential for river flow routing. The TDANN approach introduced in this study is sufficiently general and has great potential to be applicable to many hydrological and environmental applications.

International Journal of Antimicrobial Agents