Vulnerability and fate of a coastal sand dune complex,Rosetta-Idku,northwestern Nile Delta,Egypt

Types, distribution, and origin of recent sand dunes between Rosetta and Idku, in the western sector of the Nile Delta, Egypt were investigated. Sand samples from the dunes, beach, and seafloor were studied for grain size distribution and mineralogical composition. It has been found that most of the dunes in the study area have been subjected to deterioration and removal due to the construction of buildings and the International Coastal Highway. The remnant constitutes a damaged belt of foredunes that extends from El Bouseily village to the west of Idku town. The dune’s origin is interpreted to be the result of coastal drifting and the subsequent transport of sediments of the former Canopic Nile branch eastward by the predominant longshore current and by aeolian processes. The blown sand grains accumulated to form a belt of coastal sand dunes of original longitudinal and crescentic forms. Urbanization of the coast has severely altered the landscape. The study area is considered vulnerable to the impacts of climate change and the expected rise in sea level. The outcome of potential sea level rise is serious; erosion problems are expected to be exacerbated and vast areas from land and property would be lost. Thus, protection and preservation the remaining dunes in the study area are vital requirements for shore protection.     

The chromite deposits associated with ophiolite complexes, Southeastern Desert, Egypt： Petrological and geochemical characteristics and mineralization

1 Introduction The association of massive Fe-Ni-Cu sulfides andchromite is a very unusual feature of podiformchromitites occurring in mantle tectonites of ophioliticcomplexes. It has only been described in theSoutheastern Desert, Egypt, where sulfides a…     

Water availability for the greening of Kuwait

Water resources for agricultural development and landscape enhancement in Kuwait are very scarce; the quality is saline (brackish), and the soil texture is sandy, incapable of holding nutrients and moisture. Most of the rainfall in Kuwait either evaporates due to the high temperatures or percolates through the soil. The rainfall is not sufficient to recharge the underground water supply. A variety of alternative water sources have been studied, including seawater desalination and wastewater treatment. Wastewater treatment proved to be convenient due to the relatively low salinity detected in the treated water. Furthermore, the amount of wastewater is expected to increase as more residential areas are connected to the sewage system as the population increases.

The development of a greenery plan for Kuwait requires intensive water management. This goal can be achieved through manpower training in landscape development, selection of plants tolerant to arid environments, usage of appropriate irrigation and drainage systems, promotion of greenery programs within public and the governmental agencies for their direct participation in urban area beautification, and extension of wastewater treatment techniques.     

浙江花岗岩中斜长石钾交代产生的条纹长石

对研究区内花岗岩类的60个薄片进行了岩相学研究.研究的目的是确定区内岩石中普遍存在的矿物组成及结构类型.     

Structure de socle,sismostratigraphie et héritage structural au cours du rifting au niveau de la marge d'Ifni/Tan-Tan (Maroc sud-occidental)

Seismic reflection profiles from the Ifni/Tan-Tan Atlantic margin of southern Morocco, interpreted in the light of well data and field geology from the Western Anti-Atlas, allowed us to establish the seismostratigraphic framework of the syn-rift series and to reveal (i) a compressional structural style in the pre-Triassic basement similar to that established in the adjacent outcropping onshore basement but with an opposed western vergence, (ii) the importance of inherited anterior structures in the formation of Triassic-Liassic rift structures and (iii) an east–west propagation of these rift structures. To cite this article: N. AbouAli et al., C. R. Geoscience 337 (2005).     

Behavior of Shallow Strip Footing on Twin Voids

This paper numerically examines the bearing capacity and failure mechanism of a shallow strip foundation constructed above twin voids. The voids may refer to caves, caverns, underground aqueduct or tunnels due to water seepage, chemical reaction or deliberately excavated in soil deposit. The ability of numerical model to accurately predict the system behavior is evaluated by performing verification analyses on existing researches. Subsequently, a parametric study carried out to reveal the influence of size of footing/voids and their location (i.e. depth, spacing, eccentricity) on the bearing capacity of footing. To clarify the failure mechanism, the distribution of shear strain in the soil for different scenarios is assessed. The parametric study provided a new framework to determine the bearing capacity and the mode of failure for footings on voids. Based on the results, a criterion can be issued to avoid collapse of footing/voids regarding the shape, location and size of voids. The results can also be used to design construction of a footing on existing voids while the acquired failure mechanisms can be appointed to develop analytical solutions for this problem. Results demonstrated that a critical depth for voids and a critical distance between them exist where the influence on the ultimate bearing capacity of footing disappears.     

Air pollution forecasting from sky images with shallow and deep classifiers

Air pollution is one of the most important problems in the new era. Detecting the level of air pollution from an image taken by a camera can be informative for the people who are not aware of exact air pollution level be declared daily by some organizations like municipalities. In this paper, we propose a method to predict the level of the air pollution of a location by taking an image by a camera of a smart phone then processing it. We collected an image dataset from city of Tehran. Afterward, we proposed two methods for estimation of level of air pollution. In the first method, the images are preprocessed and then Gabor transform is used to extract features from the images. At the end, two shallow classification methods are employed to model and predict the level of air pollution. In the second proposed method, a Convolutional Neural Network(CNN) is designed to receive a sky image as an input and result a level of air pollution. Some experiments have been done to evaluate the proposed method. The results show that the proposed 9 method has an acceptable accuracy in detection of the air pollution level. Our deep classifier achieved accuracy about 59.38% which is 10 about 6% higher than traditional combination of feature extraction and classification methods.