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Saliba N.A.,American University of Beirut | El Jam F.,American University of Beirut | El Tayar G.,American University of Beirut | Obeid W.,American University of Beirut | Roumie M.,National Council for Scientific Research
Atmospheric Research | Year: 2010

Being a semi-enclosed area, the Eastern Mediterranean region experiences high Particulate Matter (PM) levels that could be attributed to sources originating from the region and from long-range transported pollutants. In this study, a long-term evaluation of PM10 and PM2.5 mass concentrations reveals that averages of PM10 and PM2.5 concentrations collected between 2003 and 2007 in several different sites in Beirut exceeded the World Health Organization (WHO) PM10 and PM2.5 annual averages (20 and 10μgm-3, respectively). When compared to other sites in the region, levels fell in general outside the usual range for most other urban sites that are not directly affected by industrial activity. The average PM2.5/PM10 ratios were about 0.42, a value that is typical of urban sites. The overall averages for different seasons were higher in fall and summer as a result of low precipitations, the increase of dust storm activities in fall and the enhancement of sea and land breezes in summer, along with the increase in traffic activities (summer is a high touristic season). Using the HYSPLIT model for about 500 sampled days in Beirut, Lebanon, it was found that 60% of the wind comes from the N, NW and NE, while the remaining 40% comes from the S, SW and SE. Comparing the sources assigned to the pre- (BH) and post- (HH) 2006-war sites, it was found that aged dust increased by 64% in total PM10 and secondary aerosols by 150% in fine PM in HH over BH. Furthermore, much higher average percentages of sulfates and nitrates were determined in fine PMs in HH, indicating increased levels of their precursors NOx, SOx and Ca generated from a higher density of gasoline, diesel vehicles and construction debris. © 2010 Elsevier B.V. Source

Bou Kheir R.,Lebanese University | Bou Kheir R.,University of Aarhus | Greve M.H.,University of Aarhus | Abdallah C.,National Council for Scientific Research | Dalgaard T.,University of Aarhus
Environmental Pollution | Year: 2010

Heavy metal contamination has been and continues to be a worldwide phenomenon that has attracted a great deal of attention from governments and regulatory bodies. In this context, our study proposes a regression-tree model to predict the concentration level of zinc in the soils of northern Lebanon (as a case study of Mediterranean landscapes) under a GIS environment. The developed tree-model explained 88% of variance in zinc concentration using pH (100% in relative importance), surroundings of waste areas (90%), proximity to roads (80%), nearness to cities (50%), distance to drainage line (25%), lithology (24%), land cover/use (14%), slope gradient (10%), conductivity (7%), soil type (7%), organic matter (5%), and soil depth (5%). The overall accuracy of the quantitative zinc map produced (at 1:50.000 scale) was estimated to be 78%. The proposed tree model is relatively simple and may also be applied to other areas. © 2009 Elsevier Ltd. All rights reserved. Source

Flueck W.T.,National Council for Scientific Research | Flueck W.T.,Atlantida Argentina University | Flueck W.T.,University of Basel
Biological Invasions | Year: 2010

A recent review on exotic cervids concluded that deer introduced to Patagonia impacted habitat and native huemul deer Hippocamelus bisulcus. I evaluate these assertions and amend information about this South American case study. Categorizing deer along narrow characteristics may be too restrictive to allow accurate predictions about interactions. More effective is considering the magnitude of plasticity (behavioral, phenotypic, genetic). The dichotomy of native versus exotic deer masks situations where prevailing ecological conditions are far from 'native', such as absence of predators, and such results from artificial settings have limitations. Studies used to contrast effects on vegetation from exotic red deer (Cervus elaphus) versus native huemul did not analyze native deer and provided no data to support conclusions in the review. Huemul were concluded to have high trophic overlap with red deer whose diet, however, was determined in another habitat where the food item of supposed major overlap was absent, and suggesting that red deer might cause exploitation competition was not supported by cited data. There was no mention that huemul are foremost exposed to livestock rather than exotic deer. Concluding that exotic prey including red deer increase predator density resulting in increased predation of huemul (apparent competition), was not supported by cited studies. To the contrary, high-density puma (Puma concolor) could not prevent guanaco (Lama guanicoe) from increasing >13-fold, nor that huemul expanded into these sites. Not only were those studies opposite to conclusions in the review, but none had studied huemul nor predator population trends. Data from little known species like huemul should be used with reservations when aiming at generalizations. © 2009 Springer Science+Business Media B.V. Source

Makkouk K.,National Council for Scientific Research | Pappu H.,Washington State University | Kumari S.G.,International Center for Agricultural Research in the Dry Areas
Advances in Virus Research | Year: 2012

In the Mediterranean region, pea, bean, and faba bean production is affected by around 17 major viruses. These viruses do not have the same ecology and consequently require a variety of different preventive measures to control them. Some of these viruses have a narrow host range, such as Faba bean necrotic yellows virus (FBNYV), and others, such as Alfalfa mosaic virus (AMV) and Cucumber mosaic virus (CMV), a very wide host range. Such features are important when identifying sources of virus inoculum in a region, and the vectors can transmit viruses from natural reservoirs to the crop plants. Some of these viruses are seed borne and, consequently, can be disseminated long distances through infected seeds. Crop losses caused by these viruses are variable, depending on the sensitivity and susceptibility of the crop to infection. Host resistance genes have been identified for some of these viruses, but in others, such as FBNYV, no resistance genes in faba bean have been identified yet. Significant progress was made in developing precise methods for the identification of these viruses, and new virus problems are being identified every year. This chapter is not intended to be a review for pea, bean, and faba bean viruses, but rather focuses on the major viruses which affect these crops in the Mediterranean basin with focus on the progress made over the past two decades. © 2012 Elsevier Inc. Source

Awad M.,National Council for Scientific Research
International Arab Journal of Information Technology | Year: 2010

Image segmentation is an essential step in image processing. The goal of segmentation is to simplify and/or to change the representation of an image into a form easier to analyze. Many image segmentation methods are available but most of these methods are not suitable for satellite images and they require a priori knowledge. In order to overcome these obstacles, a new satellite image segmentation method is developed using an unsupervised artificial neural network method called Kohonen's self-organizing map and a threshold technique. Self-organizing map is used to organize pixels according to grey level values of multiple bands into groups then a threshold technique is used to cluster the image into disjoint regions, this new method is called TSOM. Experiments performed on two different satellite images confirm the stability, homogeneity, and the efficiency (speed wise) of TSOM method with comparison to the iterative self-organizing data analysis method. The stability and homogeneity of both methods are determined using a procedure selected from the functional model. Source

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