University of the Aegean

About: University of the Aegean is a education organization based out in Mytilene, Greece. It is known for research contribution in the topics: Population & Tourism. The organization has 2818 authors who have published 8100 publications receiving 179275 citations. The organization is also known as: UAEG.

Search for squarks and gluinos with the ATLAS detector in final states with jets and missing transverse momentum using √s = 8 TeV proton-proton collision data

Abstract: A search for squarks and gluinos in final states containing high-p T jets, missing transverse momentum and no electrons or muons is presented. The data were recorded in 2012 by the ATLAS experiment in s√=8 TeV proton-proton collisions at the Large Hadron Collider, with a total integrated luminosity of 20.3 fb−1. Results are interpreted in a variety of simplified and specific supersymmetry-breaking models assuming that R-parity is conserved and that the lightest neutralino is the lightest supersymmetric particle. An exclusion limit at the 95% confidence level on the mass of the gluino is set at 1330 GeV for a simplified model incorporating only a gluino and the lightest neutralino. For a simplified model involving the strong production of first- and second-generation squarks, squark masses below 850 GeV (440 GeV) are excluded for a massless lightest neutralino, assuming mass degenerate (single light-flavour) squarks. In mSUGRA/CMSSM models with tan β = 30, A 0 = −2m 0 and μ > 0, squarks and gluinos of equal mass are excluded for masses below 1700 GeV. Additional limits are set for non-universal Higgs mass models with gaugino mediation and for simplified models involving the pair production of gluinos, each decaying to a top squark and a top quark, with the top squark decaying to a charm quark and a neutralino. These limits extend the region of supersymmetric parameter space excluded by previous searches with the ATLAS detector.

Olive groves: ``The life and identity of the Mediterranean''

Abstract: Olive tree cultivation in theMediterranean goes back to ancient times. Evensince the Roman Age, olive cultivation spreadto the entire Mediterranean basin. Thislongevous tree integrates and identifieseconomically, socially, and culturally theinhabitants of this basin and determines itsrural landscape. For the residents of theMediterranean, olive oil constituted the mainsource of nutritional fats, their most valuableexport product, and was identified with theirculture. Even now, olive cultivation has amultiple importance for the Mediterranean. Theolive groves, which grow mostly on inclined,shallow, and low fertility soils, and onhand-made stone terraces, have limited wateringrequirements and sustain the fragile naturalresources of the Mediterranean. Today,olive cultivation in the Mediterranean is anadditional income source and supports thepopulation in rural areas during the winterperiod, which profit from summer and seatourism activity. Although anagro-ecosystem, the olive grove resembles thenatural Mediterranean ecosystem and abandonmenttransforms them into natural Mediterranean typeforests. Their change of use from olivecultivation to pasture degrades the ecosystemand decreases the natural resources, because ofover-grazing. At this time, two major factorsthreaten the traditional olive cultivation (i)the competition of the intensive olive grovesin plain and irrigated areas and (ii) thecheaper seed-oils, which intensify theabandonment of traditional olive groves andchange them into pasture, resulting in thedeterioration of the ecosystem. Olivecultivation has left its mark on life in theMediterranean and has contributed to thesustainability of natural resources.Nevertheless, it succumbs under the pressure ofcurrent socioeconomic situations. Today, theconservation of olives in productionconstitutes a necessity for the fragileMediterranean ecosystems and a challenge foreverybody involved.

Overview of Advanced Computer Vision Systems for Skin Lesions Characterization

Abstract: During the last years, computer-vision-based diagnosis systems have been used in several hospitals and dermatology clinics, aiming mostly at the early detection of skin cancer, and more specifically, the recognition of malignant melanoma tumour. In this paper, we review the state of the art in such systems by first presenting the installation, the visual features used for skin lesion classification, and the methods for defining them. Then, we describe how to extract these features through digital image processing methods, i.e., segmentation, border detection, and color and texture processing, and we present the most prominent techniques for skin lesion classification. The paper reports the statistics and the results of the most important implementations that exist in the literature, while it compares the performance of several classifiers on the specific skin lesion diagnostic problem and discusses the corresponding findings.