Search results for: Apostolos Kostas
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 26

Search results for: Apostolos Kostas

26 E-Learning in Life-Long Learning: Best Practices from the University of the Aegean

Authors: Chryssi Vitsilaki, Apostolos Kostas, Ilias Efthymiou

Abstract:

This paper presents selected best practices on online learning and teaching derived from a novel and innovating Lifelong Learning program through e-Learning, which has during the last five years been set up at the University of the Aegean in Greece. The university, capitalizing on an award-winning, decade-long experience in e-learning and blended learning in undergraduate and postgraduate studies, recently expanded into continuous education and vocational training programs in various cutting-edge fields. So, in this article we present: (a) the academic structure/infrastructure which has been developed for the administrative, organizational and educational support of the e-Learning process, including training the trainers, (b) the mode of design and implementation based on a sound pedagogical framework of open and distance education, and (c) the key results of the assessment of the e-learning process by the participants, as they are used to feedback on continuous organizational and teaching improvement and quality control.

Keywords: distance education, e-learning, life-long programs, synchronous/asynchronous learning

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25 An Expert System Designed to Be Used with MOEAs for Efficient Portfolio Selection

Authors: Kostas Metaxiotis, Kostas Liagkouras

Abstract:

This study presents an Expert System specially designed to be used with Multiobjective Evolutionary Algorithms (MOEAs) for the solution of the portfolio selection problem. The validation of the proposed hybrid System is done by using data sets from Hang Seng 31 in Hong Kong, DAX 100 in Germany and FTSE 100 in UK. The performance of the proposed system is assessed in comparison with the Non-dominated Sorting Genetic Algorithm II (NSGAII). The evaluation of the performance is based on different performance metrics that evaluate both the proximity of the solutions to the Pareto front and their dispersion on it. The results show that the proposed hybrid system is efficient for the solution of this kind of problems.

Keywords: expert systems, multi-objective optimization, evolutionary algorithms, portfolio selection

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24 Forecasting Thermal Energy Demand in District Heating and Cooling Systems Using Long Short-Term Memory Neural Networks

Authors: Kostas Kouvaris, Anastasia Eleftheriou, Georgios A. Sarantitis, Apostolos Chondronasios

Abstract:

To achieve the objective of almost zero carbon energy solutions by 2050, the EU needs to accelerate the development of integrated, highly efficient and environmentally friendly solutions. In this direction, district heating and cooling (DHC) emerges as a viable and more efficient alternative to conventional, decentralized heating and cooling systems, enabling a combination of more efficient renewable and competitive energy supplies. In this paper, we develop a forecasting tool for near real-time local weather and thermal energy demand predictions for an entire DHC network. In this fashion, we are able to extend the functionality and to improve the energy efficiency of the DHC network by predicting and adjusting the heat load that is distributed from the heat generation plant to the connected buildings by the heat pipe network. Two case-studies are considered; one for Vransko, Slovenia and one for Montpellier, France. The data consists of i) local weather data, such as humidity, temperature, and precipitation, ii) weather forecast data, such as the outdoor temperature and iii) DHC operational parameters, such as the mass flow rate, supply and return temperature. The external temperature is found to be the most important energy-related variable for space conditioning, and thus it is used as an external parameter for the energy demand models. For the development of the forecasting tool, we use state-of-the-art deep neural networks and more specifically, recurrent networks with long-short-term memory cells, which are able to capture complex non-linear relations among temporal variables. Firstly, we develop models to forecast outdoor temperatures for the next 24 hours using local weather data for each case-study. Subsequently, we develop models to forecast thermal demand for the same period, taking under consideration past energy demand values as well as the predicted temperature values from the weather forecasting models. The contributions to the scientific and industrial community are three-fold, and the empirical results are highly encouraging. First, we are able to predict future thermal demand levels for the two locations under consideration with minimal errors. Second, we examine the impact of the outdoor temperature on the predictive ability of the models and how the accuracy of the energy demand forecasts decreases with the forecast horizon. Third, we extend the relevant literature with a new dataset of thermal demand and examine the performance and applicability of machine learning techniques to solve real-world problems. Overall, the solution proposed in this paper is in accordance with EU targets, providing an automated smart energy management system, decreasing human errors and reducing excessive energy production.

Keywords: machine learning, LSTMs, district heating and cooling system, thermal demand

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23 A Mean–Variance–Skewness Portfolio Optimization Model

Authors: Kostas Metaxiotis

Abstract:

Portfolio optimization is one of the most important topics in finance. This paper proposes a mean–variance–skewness (MVS) portfolio optimization model. Traditionally, the portfolio optimization problem is solved by using the mean–variance (MV) framework. In this study, we formulate the proposed model as a three-objective optimization problem, where the portfolio's expected return and skewness are maximized whereas the portfolio risk is minimized. For solving the proposed three-objective portfolio optimization model we apply an adapted version of the non-dominated sorting genetic algorithm (NSGAII). Finally, we use a real dataset from FTSE-100 for validating the proposed model.

Keywords: evolutionary algorithms, portfolio optimization, skewness, stock selection

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22 Atmospheric Circulation Drivers Of Nationally-Aggregated Wind Energy Production Over Greece

Authors: Kostas Philippopoulos, Chris G. Tzanis, Despina Deligiorgi

Abstract:

Climate change adaptation requires the exploitation of renewable energy sources such as wind. However, climate variability can affect the regional wind energy potential and consequently the available wind power production. The goal of the research project is to examine the impact of atmospheric circulation on wind energy production over Greece. In the context of synoptic climatology, the proposed novel methodology employs Self-Organizing Maps for grouping and classifying the atmospheric circulation and nationally-aggregated capacity factor time series for a 30-year period. The results indicate the critical effect of atmospheric circulation on the national aggregated wind energy production values and therefore address the issue of optimum distribution of wind farms for a specific region.

Keywords: wind energy, atmospheric circulation, capacity factor, self-organizing maps

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21 User Requirements Analysis for the Development of Assistive Navigation Mobile Apps for Blind and Visually Impaired People

Authors: Paraskevi Theodorou, Apostolos Meliones

Abstract:

In the context of the development process of two assistive navigation mobile apps for blind and visually impaired people (BVI) an extensive qualitative analysis of the requirements of potential users has been conducted. The analysis was based on interviews with BVIs and aimed to elicit not only their needs with respect to autonomous navigation but also their preferences on specific features of the apps under development. The elicited requirements were structured into four main categories, namely, requirements concerning the capabilities, functionality and usability of the apps, as well as compatibility requirements with respect to other apps and services. The main categories were then further divided into nine sub-categories. This classification, along with its content, aims to become a useful tool for the researcher or the developer who is involved in the development of digital services for BVI.

Keywords: accessibility, assistive mobile apps, blind and visually impaired people, user requirements analysis

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20 Impact of Ship Traffic to PM 2.5 and Particle Number Concentrations in Three Port-Cities of the Adriatic/Ionian Area

Authors: Daniele Contini, Antonio Donateo, Andrea Gambaro, Athanasios Argiriou, Dimitrios Melas, Daniela Cesari, Anastasia Poupkou, Athanasios Karagiannidis, Apostolos Tsakis, Eva Merico, Rita Cesari, Adelaide Dinoi

Abstract:

Emissions of atmospheric pollutants from ships and harbour activities are a growing concern at International level given their potential impacts on air quality and climate. These close-to-land emissions have potential impact on local communities in terms of air quality and health. Recent studies show that the impact of maritime traffic to atmospheric particulate matter concentrations in several coastal urban areas is comparable with the impact of road traffic of a medium size town. However, several different approaches have been used for these estimates making difficult a direct comparison of results. In this work an integrated approach based on emission inventories and dedicated measurement campaigns has been applied to give a comparable estimate of the impact of maritime traffic to PM2.5 and particle number concentrations in three major harbours of the Adriatic/Ionian Seas. The influences of local meteorology and of the logistic layout of the harbours are discussed.

Keywords: ship emissions, PM2.5, particle number concentrations, impact of shipping to atmospheric aerosol

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19 Designing a Patient Monitoring System Using Cloud and Semantic Web Technologies

Authors: Chryssa Thermolia, Ekaterini S. Bei, Stelios Sotiriadis, Kostas Stravoskoufos, Euripides G. M. Petrakis

Abstract:

Moving into a new era of healthcare, new tools and devices are developed to extend and improve health services, such as remote patient monitoring and risk prevention. In this concept, Internet of Things (IoT) and Cloud Computing present great advantages by providing remote and efficient services, as well as cooperation between patients, clinicians, researchers and other health professionals. This paper focuses on patients suffering from bipolar disorder, a brain disorder that belongs to a group of conditions called effective disorders, which is characterized by great mood swings.We exploit the advantages of Semantic Web and Cloud Technologies to develop a patient monitoring system to support clinicians. Based on intelligently filtering of evidence-knowledge and individual-specific information we aim to provide treatment notifications and recommended function tests at appropriate times or concluding into alerts for serious mood changes and patient’s non-response to treatment. We propose an architecture, as the back-end part of a cloud platform for IoT, intertwining intelligence devices with patients’ daily routine and clinicians’ support.

Keywords: bipolar disorder, intelligent systems patient monitoring, semantic web technologies, healthcare

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18 Qualitative and Quantitative Traits of Processed Farmed Fish in N. W. Greece

Authors: Cosmas Nathanailides, Fotini Kakali, Kostas Karipoglou

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The filleting yield and the chemical composition of farmed sea bass (Dicentrarchus labrax); rainbow trout (Oncorynchus mykiss) and meagre (Argyrosomus regius) was investigated in farmed fish in NW Greece. The results provide an estimate of the quantity of fish required to produce one kilogram of fillet weight, an estimation which is required for the operational management of fish processing companies. Furthermore in this work, the ratio of feed input required to produce one kilogram of fish fillet (FFCR) is presented for the first time as a useful indicator of the ecological footprint of consuming farmed fish. The lowest lipid content appeared in meagre (1,7%) and the highest in trout (4,91%). The lowest fillet yield and fillet yield feed conversion ratio (FYFCR) was in meagre (FY=42,17%, FFCR=2,48), the best fillet yield (FY=53,8%) and FYFCR (2,10) was exhibited in farmed rainbow trout. This research has been co-financed by the European Union (European Social Fund – ESF) and Greek national funds through the Operational Program "Education and Lifelong Learning" of the National Strategic Reference Framework (NSRF) - Research Funding Program: ARCHIMEDES III. Investing in knowledge society through the European Social Fund.

Keywords: farmed fish, flesh quality, filleting yield, lipid

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17 Bayesian Inference for High Dimensional Dynamic Spatio-Temporal Models

Authors: Sofia M. Karadimitriou, Kostas Triantafyllopoulos, Timothy Heaton

Abstract:

Reduced dimension Dynamic Spatio-Temporal Models (DSTMs) jointly describe the spatial and temporal evolution of a function observed subject to noise. A basic state space model is adopted for the discrete temporal variation, while a continuous autoregressive structure describes the continuous spatial evolution. Application of such a DSTM relies upon the pre-selection of a suitable reduced set of basic functions and this can present a challenge in practice. In this talk, we propose an online estimation method for high dimensional spatio-temporal data based upon DSTM and we attempt to resolve this issue by allowing the basis to adapt to the observed data. Specifically, we present a wavelet decomposition in order to obtain a parsimonious approximation of the spatial continuous process. This parsimony can be achieved by placing a Laplace prior distribution on the wavelet coefficients. The aim of using the Laplace prior, is to filter wavelet coefficients with low contribution, and thus achieve the dimension reduction with significant computation savings. We then propose a Hierarchical Bayesian State Space model, for the estimation of which we offer an appropriate particle filter algorithm. The proposed methodology is illustrated using real environmental data.

Keywords: multidimensional Laplace prior, particle filtering, spatio-temporal modelling, wavelets

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16 Coastalization and Urban Sprawl in the Mediterranean: Using High-Resolution Multi-Temporal Data to Identify Typologies of Spatial Development

Authors: Apostolos Lagarias, Anastasia Stratigea

Abstract:

Coastal urbanization is heavily affecting the Mediterranean, taking the form of linear urban sprawl along the coastal zone. This process is posing extreme pressure on ecosystems, leading to an unsustainable model of growth. The aim of this research is to analyze coastal urbanization patterns in the Mediterranean using High-resolution multi-temporal data provided by the Global Human Settlement Layer (GHSL) database. Methodology involves the estimation of a set of spatial metrics characterizing the density, aggregation/clustering and dispersion of built-up areas. As case study areas, the Spanish Coast and the Adriatic Italian Coast are examined. Coastalization profiles are examined and selected sub-areas massively affected by tourism development and suburbanization trends (Costa Blanca/Murcia, Costa del Sol, Puglia, Emilia-Romagna Coast) are analyzed and compared. Results show that there are considerable differences between the Spanish and the Italian typologies of spatial development, related to the land use structure and planning policies applied in each case. Monitoring and analyzing spatial patterns could inform integrated Mediterranean strategies for coastal areas and redirect spatial/environmental policies towards a more sustainable model of growth

Keywords: coastalization, Mediterranean, multi-temporal, urban sprawl, spatial metrics

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15 Evaluating the Performance of 28 EU Member Countries on Health2020: A Data Envelopment Analysis Evaluation of the Successful Implementation of Policies

Authors: Elias K. Maragos, Petros E. Maravelakis, Apostolos I. Linardis

Abstract:

Health2020 is a promising framework of policies provided by the World Health Organization (WHO) and aiming to diminish the health and well-being inequalities among the citizens of the European Union (EU) countries. The major demographic, social and environmental changes, in addition to the resent economic crisis prevent the unobstructed and successful implementation of this framework. The unemployment rates and the percentage of people at risk of poverty have increased among the citizens of EU countries. At the same time, the adopted fiscal, economic policies do not help governments to serve their social role and mitigate social and health inequalities. In those circumstances, there is a strong pressure to organize all health system resources efficiently and wisely. In order to provide a unified and value-based framework of valuation, we propose a valuation framework using data envelopment analysis (DEA) and dynamic DEA. We believe that the adopted methodology could provide a robust tool which can capture the degree of success with which policies have been implemented and is capable to determine which of the countries developed the requested policies efficiently and which of the countries have been lagged. Using the proposed methodology, we evaluated the performance of 28 EU member-countries in relation to the Health2020 peripheral targets. We adopted several versions of evaluation, measuring the effectiveness and the efficiency of EU countries from 2011 to 2016. Our results showed stability in technological changes and revealed a group of countries which were benchmarks in most of the years for the inefficient countries.

Keywords: DEA, Health2020, health inequalities, malmquist index, policies evaluation, well-being

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14 Marketing Parameters on Consumer's Perceptions of Farmed Sea Bass in Greece

Authors: Sophia Anastasiou, Cosmas Nathanailides, Fotini Kakali, Kostas Karipoglou

Abstract:

Wild fish are considered as testier and in fish restaurants are offered at twice the price of farmed fish. Several chemical and structural differences can affect the consumer's attitudes for farmed fish. The structure and chemical composition of fish muscle is also important for the performance of farmed fish during handling, storage and processing. In the present work we present the chemical and sensory parameters which are used as indicators of fish flesh quality and we investigated the perceptions of consumers for farmed sea bass and the organoleptic differences between samples of wild and farmed sea bass. A questionnaire was distributed to a group of various ages that were regular consumers of sea bass. The questionnaire included a survey on the perceptions on taste and appearance differences between wild and farmed sea bass. A significant percentage (>40%) of the participants stated their perception of superior taste of wild sea bass versus the farmed fish. The participants took part in an organoleptic assessment of wild and farmed sea bass prepared and cooked by a local fish restaurant. Portions were evaluated for intensity of sensorial attributes from 1 (low intensity) to 5 (high intensity). The results indicate that contrary to the assessor's perception, farmed sea bass scored better in al organoleptic parameters assessed with marked superiority in texture and taste over the wild sea bass. This research has been co-financed by the European Union (European Social Fund – ESF) and Greek national funds through the Operational Program "Education and Lifelong Learning" of the National Strategic Reference Framework (NSRF) - Research Funding Program: ARCHIMEDES III. Investing in knowledge society through the European Social Fund.

Keywords: fish marketing, farmed fish, seafood quality, wild fish

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13 A Semidefinite Model to Quantify Dynamic Forces in the Powertrain of Torque Regulated Bascule Bridge Machineries

Authors: Kodo Sektani, Apostolos Tsouvalas, Andrei Metrikine

Abstract:

The reassessment of existing movable bridges in The Netherlands has created the need for acceptance/rejection criteria to assess whether the machineries are meet certain design demands. However, the existing design code defines a different limit state design, meant for new machineries which is based on a simple linear spring-mass model. Observations show that existing bridges do not confirm the model predictions. In fact, movable bridges are nonlinear systems consisting of mechanical components, such as, gears, electric motors and brakes. Next to that, each movable bridge is characterized by a unique set of parameters. However, in the existing code various variables that describe the physical characteristics of the bridge are neglected or replaced by partial factors. For instance, the damping ratio ζ, which is different for drawbridges compared to bascule bridges, is taken as a constant for all bridge types. In this paper, a model is developed that overcomes some of the limitations of existing modelling approaches to capture the dynamics of the powertrain of a class of bridge machineries First, a semidefinite dynamic model is proposed, which accounts for stiffness, damping, and some additional variables of the physical system, which are neglected by the code, such as nonlinear braking torques. The model gives an upper bound of the peak forces/torques occurring in the powertrain during emergency braking. Second, a discrete nonlinear dynamic model is discussed, with realistic motor torque characteristics during normal operation. This model succeeds to accurately predict the full time history of the occurred stress state of the opening and closing cycle for fatigue purposes.

Keywords: Dynamics of movable bridges, Bridge machinery, Powertrains, Torque measurements

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12 Platform Integration for High-Throughput Functional Screening Applications

Authors: Karolis Leonavičius, Dalius Kučiauskas, Dangiras Lukošius, Arnoldas Jasiūnas, Kostas Zdanys, Rokas Stanislovas, Emilis Gegevičius, Žana Kapustina, Juozas Nainys

Abstract:

Screening throughput is a common bottleneck in many research areas, including functional genomics, drug discovery, and directed evolution. High-throughput screening techniques can be classified into two main categories: (i) affinity-based screening and (ii) functional screening. The first one relies on binding assays that provide information about the affinity of a test molecule for a target binding site. Binding assays are relatively easy to establish; however, they reveal no functional activity. In contrast, functional assays show an effect triggered by the interaction of a ligand at a target binding site. Functional assays might be based on a broad range of readouts, such as cell proliferation, reporter gene expression, downstream signaling, and other effects that are a consequence of ligand binding. Screening of large cell or gene libraries based on direct activity rather than binding affinity is now a preferred strategy in many areas of research as functional assays more closely resemble the context where entities of interest are anticipated to act. Droplet sorting is the basis of high-throughput functional biological screening, yet its applicability is limited due to the technical complexity of integrating high-performance droplet analysis and manipulation systems. As a solution, the Droplet Genomics Styx platform enables custom droplet sorting workflows, which are necessary for the development of early-stage or complex biological therapeutics or industrially important biocatalysts. The poster will focus on the technical design considerations of Styx in the context of its application spectra.

Keywords: functional screening, droplet microfluidics, droplet sorting, dielectrophoresis

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11 Classifying Affective States in Virtual Reality Environments Using Physiological Signals

Authors: Apostolos Kalatzis, Ashish Teotia, Vishnunarayan Girishan Prabhu, Laura Stanley

Abstract:

Emotions are functional behaviors influenced by thoughts, stimuli, and other factors that induce neurophysiological changes in the human body. Understanding and classifying emotions are challenging as individuals have varying perceptions of their environments. Therefore, it is crucial that there are publicly available databases and virtual reality (VR) based environments that have been scientifically validated for assessing emotional classification. This study utilized two commercially available VR applications (Guided Meditation VR™ and Richie’s Plank Experience™) to induce acute stress and calm state among participants. Subjective and objective measures were collected to create a validated multimodal dataset and classification scheme for affective state classification. Participants’ subjective measures included the use of the Self-Assessment Manikin, emotional cards and 9 point Visual Analogue Scale for perceived stress, collected using a Virtual Reality Assessment Tool developed by our team. Participants’ objective measures included Electrocardiogram and Respiration data that were collected from 25 participants (15 M, 10 F, Mean = 22.28  4.92). The features extracted from these data included heart rate variability components and respiration rate, both of which were used to train two machine learning models. Subjective responses validated the efficacy of the VR applications in eliciting the two desired affective states; for classifying the affective states, a logistic regression (LR) and a support vector machine (SVM) with a linear kernel algorithm were developed. The LR outperformed the SVM and achieved 93.8%, 96.2%, 93.8% leave one subject out cross-validation accuracy, precision and recall, respectively. The VR assessment tool and data collected in this study are publicly available for other researchers.

Keywords: affective computing, biosignals, machine learning, stress database

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10 Detection of Flood Prone Areas Using Multi Criteria Evaluation, Geographical Information Systems and Fuzzy Logic. The Ardas Basin Case

Authors: Vasileiou Apostolos, Theodosiou Chrysa, Tsitroulis Ioannis, Maris Fotios

Abstract:

The severity of extreme phenomena is due to their ability to cause severe damage in a small amount of time. It has been observed that floods affect the greatest number of people and induce the biggest damage when compared to the total of annual natural disasters. The detection of potential flood-prone areas constitutes one of the fundamental components of the European Natural Disaster Management Policy, directly connected to the European Directive 2007/60. The aim of the present paper is to develop a new methodology that combines geographical information, fuzzy logic and multi-criteria evaluation methods so that the most vulnerable areas are defined. Therefore, ten factors related to geophysical, morphological, climatological/meteorological and hydrological characteristics of the basin were selected. Afterwards, two models were created to detect the areas pronest to flooding. The first model defined the gravitas of each factor using Analytical Hierarchy Process (AHP) and the final map of possible flood spots were created using GIS and Boolean Algebra. The second model made use of the fuzzy logic and GIS combination and a respective map was created. The application area of the aforementioned methodologies was in Ardas basin due to the frequent and important floods that have taken place these last years. Then, the results were compared to the already observed floods. The result analysis shows that both models can detect with great precision possible flood spots. As the fuzzy logic model is less time-consuming, it is considered the ideal model to apply to other areas. The said results are capable of contributing to the delineation of high risk areas and to the creation of successful management plans dealing with floods.

Keywords: analytical hierarchy process, flood prone areas, fuzzy logic, geographic information system

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9 Experimental Study of Sand-Silt Mixtures with Torsional and Flexural Resonant Column Tests

Authors: Meghdad Payan, Kostas Senetakis, Arman Khoshghalb, Nasser Khalili

Abstract:

Dynamic properties of soils, especially at the range of very small strains, are of particular interest in geotechnical engineering practice for characterization of the behavior of geo-structures subjected to a variety of stress states. This study reports on the small-strain dynamic properties of sand-silt mixtures with particular emphasis on the effect of non-plastic fines content on the small strain shear modulus (Gmax), Young’s Modulus (Emax), material damping (Ds,min) and Poisson’s Ratio (v). Several clean sands with a wide range of grain size characteristics and particle shape are mixed with variable percentages of a silica non-plastic silt as fines content. Prepared specimens of sand-silt mixtures at different initial void ratios are subjected to sequential torsional and flexural resonant column tests with elastic dynamic properties measured along an isotropic stress path up to 800 kPa. It is shown that while at low percentages of fines content, there is a significant difference between the dynamic properties of the various samples due to the different characteristics of the sand portion of the mixtures, this variance diminishes as the fines content increases and the soil behavior becomes mainly silt-dominant, rendering no significant influence of sand properties on the elastic dynamic parameters. Indeed, beyond a specific portion of fines content, around 20% to 30% typically denoted as threshold fines content, silt is controlling the behavior of the mixture. Using the experimental results, new expressions for the prediction of small-strain dynamic properties of sand-silt mixtures are developed accounting for the percentage of silt and the characteristics of the sand portion. These expressions are general in nature and are capable of evaluating the elastic dynamic properties of sand-silt mixtures with any types of parent sand in the whole range of silt percentage. The inefficiency of skeleton void ratio concept in the estimation of small-strain stiffness of sand-silt mixtures is also illustrated.

Keywords: damping ratio, Poisson’s ratio, resonant column, sand-silt mixture, shear modulus, Young’s modulus

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8 Mediterranean Diet, Duration of Admission and Mortality in Elderly, Hospitalized Patients: A Cross-Sectional Study

Authors: Christos Lampropoulos, Maria Konsta, Ifigenia Apostolou, Vicky Dradaki, Tamta Sirbilatze, Irini Dri, Christina Kordali, Vaggelis Lambas, Kostas Argyros, Georgios Mavras

Abstract:

Objectives: Mediterranean diet has been associated with lower incidence of cardiovascular disease and cancer. The purpose of our study was to examine the hypothesis that Mediterranean diet may protect against mortality and reduce admission duration in elderly, hospitalized patients. Methods: Sample population included 150 patients (78 men, 72 women, mean age 80±8.2). The following data were taken into account in analysis: anthropometric and laboratory data, dietary habits (MedDiet score), patients’ nutritional status [Mini Nutritional Assessment (MNA) score], physical activity (International Physical Activity Questionnaires, IPAQ), smoking status, cause and duration of current admission, medical history (co-morbidities, previous admissions). Primary endpoints were mortality (from admission until 6 months afterwards) and duration of admission, compared to national guidelines for closed consolidated medical expenses. Logistic regression and linear regression analysis were performed in order to identify independent predictors for mortality and admission duration difference respectively. Results: According to MNA, nutrition was normal in 54/150 (36%) of patients, 46/150 (30.7%) of them were at risk of malnutrition and the rest 50/150 (33.3%) were malnourished. After performing multivariate logistic regression analysis we found that the odds of death decreased 30% per each unit increase of MedDiet score (OR=0.7, 95% CI:0.6-0.8, p < 0.0001). Patients with cancer-related admission were 37.7 times more likely to die, compared to those with infection (OR=37.7, 95% CI:4.4-325, p=0.001). According to multivariate linear regression analysis, admission duration was inversely related to Mediterranean diet, since it is decreased 0.18 days on average for each unit increase of MedDiet score (b:-0.18, 95% CI:-0.33 - -0.035, p=0.02). Additionally, the duration of current admission increased on average 0.83 days for each previous hospital admission (b:0.83, 95% CI:0.5-1.16, p<0.0001). The admission duration of patients with cancer was on average 4.5 days higher than the patients who admitted due to infection (b:4.5, 95% CI:0.9-8, p=0.015). Conclusion: Mediterranean diet adequately protects elderly, hospitalized patients against mortality and reduces the duration of hospitalization.

Keywords: Mediterranean diet, malnutrition, nutritional status, prognostic factors for mortality

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7 Hypersonic Propulsion Requirements for Sustained Hypersonic Flight for Air Transportation

Authors: James Rate, Apostolos Pesiridis

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In this paper, the propulsion requirements required to achieve sustained hypersonic flight for commercial air transportation are evaluated. In addition, a design methodology is developed and used to determine the propulsive capabilities of both ramjet and scramjet engines. Twelve configurations are proposed for hypersonic flight using varying combinations of turbojet, turbofan, ramjet and scramjet engines. The optimal configuration was determined based on how well each of the configurations met the projected requirements for hypersonic commercial transport. The configurations were separated into four sub-configurations each comprising of three unique derivations. The first sub-configuration comprised four afterburning turbojets and either one or two ramjets idealised for Mach 5 cruise. The number of ramjets required was dependent on the thrust required to accelerate the vehicle from a speed where the turbojets cut out to Mach 5 cruise. The second comprised four afterburning turbojets and either one or two scramjets, similar to the first configuration. The third used four turbojets, one scramjet and one ramjet to aid acceleration from Mach 3 to Mach 5. The fourth configuration was the same as the third, but instead of turbojets, it implemented turbofan engines for the preliminary acceleration of the vehicle. From calculations which determined the fuel consumption at incremental Mach numbers this paper found that the ideal solution would require four turbojet engines and two Scramjet engines. The ideal mission profile was determined as being an 8000km sortie based on an averaging of popular long haul flights with strong business ties, which included Los Angeles to Tokyo, London to New York and Dubai to Beijing. This paper deemed that these routes would benefit from hypersonic transport links based on the previously mentioned factors. This paper has found that this configuration would be sufficient for the 8000km flight to be completed in approximately two and a half hours and would consume less fuel than Concord in doing so. However, this propulsion configuration still result in a greater fuel cost than a conventional passenger. In this regard, this investigation contributes towards the specification of the engine requirements throughout a mission profile for a hypersonic passenger vehicle. A number of assumptions have had to be made for this theoretical approach but the authors believe that this investigation lays the groundwork for appropriate framing of the propulsion requirements for sustained hypersonic flight for commercial air transportation. Despite this, it does serve as a crucial step in the development of the propulsion systems required for hypersonic commercial air transportation. This paper provides a methodology and a focus for the development of the propulsion systems that would be required for sustained hypersonic flight for commercial air transportation.

Keywords: hypersonic, ramjet, propulsion, Scramjet, Turbojet, turbofan

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6 Aorta Adhesion Molecules in Cholesterol-Fed Rats Supplemented with Extra Virgin Olive Oil or Sunflower Oil, in Either Commercial or Modified Forms

Authors: Ageliki I. Katsarou, Andriana C. Kaliora, Antonia Chiou, Apostolos Papalois, Nick Kalogeropoulos, Nikolaos K. Andrikopoulos

Abstract:

Chronic inflammation plays a pivotal role in CVD development, while phytochemicals have been shown to reduce CVD risk. Several studies have correlated olive oil consumption with CVD prevention and CVD risk reduction. However, the effect of individual olive oil macro- or micro-constituents and possible synergisms among them needs to be further elucidated. Herein, extra virgin olive oil (EVOO) lipidic and polar phenolics fractions were evaluated for their effect on inflammatory markers in cholesterol-fed rats. Oils combining different characteristics as to their polar phenolic content and lipid profile were used. Male Wistar rats were fed for 9 weeks on either a high-cholesterol diet (HCD) or a HCD supplemented with oils, either commercially available, i.e. EVOO, sunflower oil (SO), or modified as to their polar phenol content, i.e. phenolics deprived-EVOO (EVOOd), SO enriched with the EVOO phenolics (SOe). Post-intervention, aorta and blood samples were collected. HCD induced dyslipidemia, manifested by serum total cholesterol and low-density lipoprotein cholesterol elevation. Additionally, HCD resulted in higher adhesion molecules’ levels in rat aorta. In the case of E-selectin, this increase was attenuated by HCD supplementation with EVOO and EVOOd, while no alterations were observed in SO and SOe groups. No differences were observed between pairs of commercial and modified oils, indicating that oleates may be the components responsible for aorta E-selectin levels lowering. The same was true for vascular adhesion molecule-1 (VCAM-1); augmentation in cholesterol-fed animals was attenuated by EVOO and EVOOd diets, highlighting oleates effect. In addition, VCAM-1 levels were higher in SO group compared to the respective SOe, indicating that in the presence of phenolic compounds linoleic acid have become less prone to oxidation. Intercellular adhesion molecule-1 (ICAM-1) levels were higher in cholesterol-fed rats, however not affected by any of the oils supplemented during the intervention. Overall, EVOO was found superior in regulating adhesion molecule levels in rat aorta compared to SO. EVOO and EVOOd exhibited analogous effects on all adhesion molecules assessed, indicating that EVOO major constituents (oleates) improve E-selectin and VCAM-1 levels in rat aorta, independently from phenolics presence. Further research is needed to elucidate the effect of phenolics and oleates in other tissues.

Keywords: extra virgin olive oil, cholesterol-fed rats, polar phenolics, adhesion molecules

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5 TNF-Alpha and MDA Levels in Hearts of Cholesterol-Fed Rats Supplemented with Extra Virgin Olive Oil or Sunflower Oil, in Either Commercial or Modified Forms

Authors: Ageliki I. Katsarou, Andriana C. Kaliora, Antonia Chiou, Apostolos Papalois, Nick Kalogeropoulos, Nikolaos K. Andrikopoulos

Abstract:

Oxidative stress is a major mechanism underlying CVDs while inflammation, an intertwined process with oxidative stress, is also linked to CVDs. Extra virgin olive oil (EVOO) is widely known to play a pivotal role in CVD prevention and CVD reduction. However, in most studies, olive oil constituents are evaluated individually and not as part of the native food, hence potential synergistic effects as drivers of EVOO beneficial properties may be underestimated. In this study, EVOO lipidic and polar phenolics fractions were evaluated for their effect on inflammatory (TNF-alpha) and oxidation (malondialdehyde/MDA) markers, in cholesterol-fed rats. Thereat, oils with discernible lipidic profile and polar phenolic content were used. Wistar rats were fed on either a high-cholesterol diet (HCD) or a HCD supplemented with oils, either commercially available, i.e. EVOO, sunflower oil (SO), or modified as to their polar phenol content, i.e. phenolics deprived-EVOO (EVOOd), SO enriched with the EVOO phenolics (SOe). After 9 weeks of dietary intervention, heart and blood samples were collected. HCD induced dylipidemia shown by increase in serum total cholesterol, low-density lipoprotein cholesterol (LDL-c) and triacylglycerols. Heart tissue has been affected by dyslipidemia; oxidation was indicated by increase in MDA in cholesterol-fed rats and inflammation by increase in TNF-alpha. In both cases, this augmentation was attenuated in EVOO and SOe diets. With respect to oxidation, SO enrichment with the EVOO phenolics brought its lipid peroxidation levels as low as in EVOO-fed rats. This suggests that phenolic compounds may act as antioxidant agents in rat heart. A possible mechanism underlying this activity may be the protective effect of phenolics in mitochondrial membrane against oxidative damage. This was further supported by EVOO/EVOOd comparison with the former presenting lower heart MDA content. As for heart inflammation, phenolics naturally present in EVOO as well as phenolics chemically added in SO, exhibited quenching abilities in heart TNF-alpha levels of cholesterol-fed rats. TNF-alpha may have played a causative role in oxidative stress induction while the opposite may have also happened, hence setting up a vicious cycle. Overall, diet supplementation with EVOO or SOe attenuated hypercholesterolemia-induced increase in MDA and TNF-alpha in Wistar rat hearts. This is attributed to phenolic compounds either naturally existing in olive oil or as fortificants in seed oil.

Keywords: extra virgin olive oil, hypercholesterolemic rats, MDA, polar phenolics, TNF-alpha

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4 Influence of Microparticles in the Contact Region of Quartz Sand Grains: A Micro-Mechanical Experimental Study

Authors: Sathwik Sarvadevabhatla Kasyap, Kostas Senetakis

Abstract:

The mechanical behavior of geological materials is very complex, and this complexity is related to the discrete nature of soils and rocks. Characteristics of a material at the grain scale such as particle size and shape, surface roughness and morphology, and particle contact interface are critical to evaluate and better understand the behavior of discrete materials. This study investigates experimentally the micro-mechanical behavior of quartz sand grains with emphasis on the influence of the presence of microparticles in their contact region. The outputs of the study provide some fundamental insights on the contact mechanics behavior of artificially coated grains and can provide useful input parameters in the discrete element modeling (DEM) of soils. In nature, the contact interfaces between real soil grains are commonly observed with microparticles. This is usually the case of sand-silt and sand-clay mixtures, where the finer particles may create a coating on the surface of the coarser grains, altering in this way the micro-, and thus the macro-scale response of geological materials. In this study, the micro-mechanical behavior of Leighton Buzzard Sand (LBS) quartz grains, with interference of different microparticles at their contact interfaces is studied in the laboratory using an advanced custom-built inter-particle loading apparatus. Special techniques were adopted to develop the coating on the surfaces of the quartz sand grains so that to establish repeatability of the coating technique. The characterization of the microstructure of coated particles on their surfaces was based on element composition analyses, microscopic images, surface roughness measurements, and single particle crushing strength tests. The mechanical responses such as normal and tangential load – displacement behavior, tangential stiffness behavior, and normal contact behavior under cyclic loading were studied. The behavior of coated LBS particles is compared among different classes of them and with pure LBS (i.e. surface cleaned to remove any microparticles). The damage on the surface of the particles was analyzed using microscopic images. Extended displacements in both normal and tangential directions were observed for coated LBS particles due to the plastic nature of the coating material and this varied with the variation of the amount of coating. The tangential displacement required to reach steady state was delayed due to the presence of microparticles in the contact region of grains under shearing. Increased tangential loads and coefficient of friction were observed for the coated grains in comparison to the uncoated quartz grains.

Keywords: contact interface, microparticles, micro-mechanical behavior, quartz sand

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3 Prognostic Factors for Mortality and Duration of Admission in Malnourished Hospitalized, Elderly Patients: A Cross-Sectional Study

Authors: Christos E. Lampropoulos, Maria Konsta, Vicky Dradaki, Irini Dri, Tamta Sirbilatze, Ifigenia Apostolou, Christina Kordali, Konstantina Panouria, Kostas Argyros, Georgios Mavras

Abstract:

Malnutrition in hospitalized patients is related to increased morbidity and mortality. Purpose of our study was to assess nutritional status of hospitalized, elderly patients with various nutritional scores and to detect unfavorable prognostic factors, related to increased mortality and extended duration of admission. Methods: 150 patients (78 men, 72 women, mean age 80±8.2) were included in this cross-sectional study. Nutritional status was assessed by Mini Nutritional Assessment (MNA full, short-form), Malnutrition Universal Screening Tool (MUST) and short Nutritional Appetite Questionnaire (sNAQ). The following data were incorporated in analysis: Anthropometric and laboratory data, physical activity (International Physical Activity Questionnaires, IPAQ), smoking status, dietary habits and mediterranean diet (assessed by MedDiet score), cause and duration of current admission, medical history (co-morbidities, previous admissions). Primary endpoints were the mortality (from admission until 6 months afterwards) and duration of admission, compared to national guidelines for closed consolidated medical expenses. Mann-Whitney two-sample statistics or t-test was used for group comparisons and Spearman or Pearson coefficients for testing correlation between variables. Results: Normal nutrition was assessed in 54/150 (36%), 92/150 (61.3%) and in 106/150 (70.7%) of patients, according to full MNA, MUST and sNAQ questionnaires respectively. Mortality rate was 20.7% (31/150 patients). The patients who died until 6 months after admission had lower BMI (24±4.4 vs 26±4.8, p=0.04) and albumin levels (2.9±0.7 vs 3.4±0.7, p=0.002), significantly lower full MNA (14.5±7.3 vs 20.7±6, p<0.0001) and short-form MNA scores (7.3±4.2 vs 10.5±3.4, p=0.0002) compared to non-dead one. In contrast, the aforementioned patients had higher MUST (2.5±1.8 vs 0.5±1.02, p=<0.0001) and sNAQ scores (2.9±2.4 vs 1.1±1.3, p<0.0001). Additionally, they showed significantly lower MedDiet (23.5±4.3 vs 31.1±5.6, p<0.0001) and IPAQ scores (37.2±156.2 vs 516.5±1241.7, p<0.0001) compared to remaining one. These patients had extended hospitalization [5 (0-13) days vs 0 (-1-3) days, p=0.001]. Patients who admitted due to cancer depicted higher mortality rate (10/13, 77%), compared to those who admitted due to infections (12/73, 18%), stroke (4/15, 27%) or other causes (4/49, 8%) (p<0.0001). Extension of hospitalization was negatively correlated to both full (Spearman r=-0.35, p<0.0001) and short-form MNA (Spearman r=-0.33, p<0.0001) and positively correlated to MUST (Spearman r=0.34, p<0.0001) and sNAQ (Spearman r=0.3, p=0.0002). Additionally, the extension was inversely related to MedDiet score (Spearman r=-0.35, p<0.0001), IPAQ score (Spearman r=-0.34, p<0.0001), albumin levels (Pearson r=-0.36, p<0.0001), Ht (Pearson r=-0.2, p=0.02) and Hb (Pearson r=-0.18, p=0.02). Conclusion: A great proportion of elderly, hospitalized patients are malnourished or at risk of malnutrition. All nutritional scores, physical activity and albumin are significantly related to mortality and increased hospitalization.

Keywords: dietary habits, duration of admission, malnutrition, prognostic factors for mortality

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2 Motherhood Factors Influencing the Business Growth of Women-Owned Sewing Businesses in Lagos, Nigeria: A Mixed Method Study

Authors: Oyedele Ogundana, Amon Simba, Kostas Galanakis, Lynn Oxborrow

Abstract:

The debate about factors influencing the business growth of women-owned businesses has been a topical issue in business management. Currently, scholars have identified the issues of access to money, market, and management as canvasing factors influencing the business growth of women-owned businesses. However, the influence of motherhood (household/family context) on business growth is inconclusive in the literature; despite that women are more family-oriented than their male counterparts. Therefore, this research study considers the influence of motherhood factor (household/family context) on the business growth of women-owned sewing businesses (WOSBs) in Lagos, Nigeria. The sewing business sector is chosen as the fashion industry (which includes sewing businesses) currently accounts for the second largest number of jobs in Sub-Saharan Africa, following agriculture. Thus, sewing businesses provide a rich ground for contributing to existing scholarly work. Research questions; (1) In what way does the motherhood factor influence the business growth of WOSBs in Lagos? (2) To what extent does the motherhood factor influence the business growth of WOSBs in Lagos? For the method design, a pragmatic approach, a mixed-methods technique and an abductive form of reasoning are adopted. The method design is chosen because it fits, better than other research perspectives, with the research questions posed in this study. For instance, using a positivist approach will not sufficiently answer research question 1, neither will an interpretive approach sufficiently answer research question 2. Therefore, the research method design is divided into 2 phases, and the results from one phase are used to inform the development of the subsequent phases (only phase 1 has been completed at the moment). The first phase uses qualitative data and analytical method to answer research question 1. While the second phase of the research uses quantitative data and analytical method to answer research question 2. For the qualitative phase, 5 WOSBs were purposefully selected and interviewed. The sampling technique is selected as it was not the intention of the researcher to make any statistical inferences, at this phase, rather the purpose was just exploratory. Therefore, the 5 sampled women comprised of 2 unmarried women, 1 married woman with no child, and 2 married women with children. A 40-60 minutes interview was conducted per participants. The interviews were audio-recorded and transcribed. Thereafter, the data were analysed using thematic analysis in order to unearth patterns and relationships. Findings for the first phase of this research reveals that motherhood (household/family context) directly influences (positively/negatively) the performance of WOSBs in Lagos. Apart from a direct influence on WOSBs, motherhood also moderates (positively/negatively) other factors–e.g., access to money, management/human resources and market/opportunities– influencing WOSBs in Lagos. To further strengthen this conclusion, a word frequency query result shows that ‘family,’ ‘husband’ and ‘children’ are among the 10 words used frequently in all the interview transcripts. This first phase contributes to existing studies by showing the various forms by which motherhood influences WOSBs. The second phase (which data are yet to be collected) would reveal the extent to which motherhood influence the business growth of WOSBs in Lagos.

Keywords: women-owned sewing businesses, business growth, motherhood, Lagos

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1 ARGO: An Open Designed Unmanned Surface Vehicle Mapping Autonomous Platform

Authors: Papakonstantinou Apostolos, Argyrios Moustakas, Panagiotis Zervos, Dimitrios Stefanakis, Manolis Tsapakis, Nektarios Spyridakis, Mary Paspaliari, Christos Kontos, Antonis Legakis, Sarantis Houzouris, Konstantinos Topouzelis

Abstract:

For years unmanned and remotely operated robots have been used as tools in industry research and education. The rapid development and miniaturization of sensors that can be attached to remotely operated vehicles in recent years allowed industry leaders and researchers to utilize them as an affordable means for data acquisition in air, land, and sea. Despite the recent developments in the ground and unmanned airborne vehicles, a small number of Unmanned Surface Vehicle (USV) platforms are targeted for mapping and monitoring environmental parameters for research and industry purposes. The ARGO project is developed an open-design USV equipped with multi-level control hardware architecture and state-of-the-art sensors and payloads for the autonomous monitoring of environmental parameters in large sea areas. The proposed USV is a catamaran-type USV controlled over a wireless radio link (5G) for long-range mapping capabilities and control for a ground-based control station. The ARGO USV has a propulsion control using 2x fully redundant electric trolling motors with active vector thrust for omnidirectional movement, navigation with opensource autopilot system with high accuracy GNSS device, and communication with the 2.4Ghz digital link able to provide 20km of Line of Sight (Los) range distance. The 3-meter dual hull design and composite structure offer well above 80kg of usable payload capacity. Furthermore, sun and friction energy harvesting methods provide clean energy to the propulsion system. The design is highly modular, where each component or payload can be replaced or modified according to the desired task (industrial or research). The system can be equipped with Multiparameter Sonde, measuring up to 20 water parameters simultaneously, such as conductivity, salinity, turbidity, dissolved oxygen, etc. Furthermore, a high-end multibeam echo sounder can be installed in a specific boat datum for shallow water high-resolution seabed mapping. The system is designed to operate in the Aegean Sea. The developed USV is planned to be utilized as a system for autonomous data acquisition, mapping, and monitoring bathymetry and various environmental parameters. ARGO USV can operate in small or large ports with high maneuverability and endurance to map large geographical extends at sea. The system presents state of the art solutions in the following areas i) the on-board/real-time data processing/analysis capabilities, ii) the energy-independent and environmentally friendly platform entirely made using the latest aeronautical and marine materials, iii) the integration of advanced technology sensors, all in one system (photogrammetric and radiometric footprint, as well as its connection with various environmental and inertial sensors) and iv) the information management application. The ARGO web-based application enables the system to depict the results of the data acquisition process in near real-time. All the recorded environmental variables and indices are presented, allowing users to remotely access all the raw and processed information using the implemented web-based GIS application.

Keywords: monitor marine environment, unmanned surface vehicle, mapping bythometry, sea environmental monitoring

Procedia PDF Downloads 93