Age models, sediment fluxes and palaeoclimatic reconstructions for the Chinese loess and palaeosol sequences     

R. Thompson  B. A. Maher 《Geophysical Journal International》1995,123(2):611-622

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Book review     

Louis J. Maher Jr. 《Mathematical Geosciences》1987,19(6):575-577

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Lead removal from wastewater using faujasite tuff     

K. M. Ibrahim  T. Akashah 《Environmental Geology》2004,46(6-7):865-870

The Jordanian chabazite-phillipsite tuff and faujasite-phillipsite tuff have suitable mineralogical and technical properties that enable them to be used for ion-exchange processes. These include suitable grain size and total cation exchange capacity, acceptable zeolite content, good attrition resistance and high packed-bed density. The chabazite-phillipsite tuff (ZE1 and ZE2) has an excellent efficiency to remove Pb and an acceptable efficiency to remove Fe, Cu, Zn and Ni from effluent wastewater of a battery factory and other industries. The faujasite-phillipsite tuff (ZE3) is 6.97 times more efficient than the ZE1 and ZE2. A bed of ZE3 (1,000 kg) loaded in a 1.17-m³ column is capable of cleaning about 2,456 m³ of the effluent from the factory at a cost of US $200/ton. The wastewater is contaminated with 20 ppm Pb in the presence of competing ions including Ca (210 ppm), Na (1,950 ppm) and Fe (169 ppm). This quantity of wastewater is equivalent to 120 working days of effluent discharge from the factory at a flow rate of 20 m³/day.  相似文献   

Propagation of Coronal Mass Ejections Observed During the Rising Phase of Solar Cycle 24     

M. Syed Ibrahim  P. K. Manoharan  A. Shanmugaraju 《Solar physics》2017,292(9):133

In this study, we investigate the interplanetary consequences and travel time details of 58 coronal mass ejections (CMEs) in the Sun–Earth distance. The CMEs considered are halo and partial halo events of width \({>}\,120\)°. These CMEs occurred during 2009?–?2013, in the ascending phase of the Solar Cycle 24. Moreover, they are Earth-directed events that originated close to the centre of the solar disk (within about \(\pm30\)° from the Sun’s centre) and propagated approximately along the Sun–Earth line. For each CME, the onset time and the initial speed have been estimated from the white-light images observed by the LASCO coronagraphs onboard the SOHO space mission. These CMEs cover an initial speed range of \({\sim}\,260\,\mbox{--}\,2700~\mbox{km}\,\mbox{s}^{-1}\). For these CMEs, the associated interplanetary shocks (IP shocks) and interplanetary CMEs (ICMEs) at the near-Earth environment have been identified from in-situ solar wind measurements available at the OMNI data base. Most of these events have been associated with moderate to intense IP shocks. However, these events have caused only weak to moderate geomagnetic storms in the Earth’s magnetosphere. The relationship of the travel time with the initial speed of the CME has been compared with the observations made in the previous Cycle 23, during 1996?–?2004. In the present study, for a given initial speed of the CME, the travel time and the speed at 1 AU suggest that the CME was most likely not much affected by the drag caused by the slow-speed dominated heliosphere. Additionally, the weak geomagnetic storms and moderate IP shocks associated with the current set of Earth-directed CMEs indicate magnetically weak CME events of Cycle 24. The magnetic energy that is available to propagate CME and cause geomagnetic storm could be significantly low.  相似文献   

Modeling the stochastic dependence of air pollution index data   总被引：1，自引：1，他引：0  

Yousif?AlyousifiEmail author  Nurulkamal?Masseran  Kamarulzaman?Ibrahim 《Stochastic Environmental Research and Risk Assessment (SERRA)》2018,32(6):1603-1611

The air pollution index (API) is a common tool, which is often used for determining the quality of air in the environment. In this study, a discrete-time Markov chain model is applied for describing the stochastic behaviour of API data. The study reported in this paper is conducted based on the data collected from Klang city in Malaysia for a period of 3 years (2012–2014). Based on the API data, we considered a five-state Markov chain for depicting the five different states of the air pollution. We identified the Markov chain is an ergodic Markov chain and determined the limiting distribution for each state of the air pollution. In addition, we have identified the mean first passage time from one state to another. Based on the limiting distribution and the mean return time, we found that the risk of occurrences for unhealthy events is small. However, the risk remains notably troubling. Therefore, the standard of air quality in Klang falls within a margin that is considered healthy for human beings.  相似文献   

Dynamic behavior of a smart device on a surface subjected to earthquake motion          下载免费PDF全文

Yunsu Na  Sherif El-Tawil  Ahmed Ibrahim  Ahmed Eltawil 《地震工程与结构动力学》2018,47(9):1905-1920

This paper leverages concepts from an existing model to simulate the planar response of a smart device subjected to friction forces induced by an underlying moving plane. An interpolation technique is used to enhance detection of transition points (between sticking and sliding states), which must be accurately identified because of the frequency of their occurrence during seismic motion. The behavior of a smart device on an unconstrained table or desk, which is itself on a moving floor, is introduced and discussed. After validation of the results using experimental data, the revised model is used to study the sliding potential of smart devices on a surface during strong seismic events. Sliding spectra associated with selected ground motions are presented and extended to incorporate the effect of vertical accelerations with the purpose of assessing their influence. It is shown that vertical accelerations have a minimal effect on the sliding behavior of smart devices and that a “probability of exceeding the slip limit” curve can be developed to relate the probability of sticking to a demand parameter that represents the ground motion.  相似文献   

Efficient ensemble forecasting of marine ecology with clustered 1D models and statistical lateral exchange: application to the Red Sea     

Denis Dreano  Kostas Tsiaras  George Triantafyllou  Ibrahim Hoteit 《Ocean Dynamics》2017,67(7):935-947

Forecasting the state of large marine ecosystems is important for many economic and public health applications. However, advanced three-dimensional (3D) ecosystem models, such as the European Regional Seas Ecosystem Model (ERSEM), are computationally expensive, especially when implemented within an ensemble data assimilation system requiring several parallel integrations. As an alternative to 3D ecological forecasting systems, we propose to implement a set of regional one-dimensional (1D) water-column ecological models that run at a fraction of the computational cost. The 1D model domains are determined using a Gaussian mixture model (GMM)-based clustering method and satellite chlorophyll-a (Chl-a) data. Regionally averaged Chl-a data is assimilated into the 1D models using the singular evolutive interpolated Kalman (SEIK) filter. To laterally exchange information between subregions and improve the forecasting skills, we introduce a new correction step to the assimilation scheme, in which we assimilate a statistical forecast of future Chl-a observations based on information from neighbouring regions. We apply this approach to the Red Sea and show that the assimilative 1D ecological models can forecast surface Chl-a concentration with high accuracy. The statistical assimilation step further improves the forecasting skill by as much as 50%. This general approach of clustering large marine areas and running several interacting 1D ecological models is very flexible. It allows many combinations of clustering, filtering and regression technics to be used and can be applied to build efficient forecasting systems in other large marine ecosystems.  相似文献   

Near-surface foundation level assessment from seismic measurements: a case study of north Jeddah City,Saudi Arabia     

Mogren  Saad  Aldahri  Maher  Abdelrahman  Kamal  Zahran  Hani 《Arabian Journal of Geosciences》2020,13(5):1-22

In this study, a comprehensive assessment on the generation mechanism, distribution characteristics, and extension rules of structure cracks was conducted by in situ monitoring and field investigation in the Chengchao Iron Mine. Structure cracks are affected by many factors, e.g., surface deformation, structure strength, occurrence position, and machine vibration. They initially occur in a structure when the strength of the structure is not enough to resist the inner strain as surface deformation increases. In contrast, increases in width and length of structure crack exert stress release in the structure and thus decrease structure deformation surrounding the crack. A great ground crack may adversely aggravate structure cracking and release the stress of surrounding rock masses. In addition, micro cracks in rock masses provide favorable conditions for the generation and extension of cracks, resulting that cracks occur in shaft walls more easily and extend towards the deeper. The initial distribution of cracks is generally consistent with such micro cracks. Subsequently, cracks in deep rock masses will extend along the strike of the mined-out area as surface deformation increases. Sensibilities to cracking of structures are changed by their different strain resistances and become stronger from bolt-shotcrete shaft, bolt-shotcrete tunnel, and brick-concrete building to brick wall. Based on distribution characteristics of cracks and wave velocity in rock masses, the overlaying strata affected by underground mining can be divided into four zones: broken zone, broken transition zone, crack generation zone, and micro deformation zone.  相似文献   

Prediction of Chemical Oxygen Demand (COD) Based on Wavelet Decomposition and Neural Networks     

Davut Hanbay  Ibrahim Turkoglu  Yakup Demir 《洁净——土壤、空气、水》2007,35(3):250-254

The chemical oxygen demand (COD) parameter of a wastewater treatment plant is predicted based on wavelet decomposition, entropy, and neural networks (NN) for rapid COD analysis. This paper also describes the usage of wavelet and NNs for parameter prediction. Data from a wastewater treatment plant in Malatya, Turkey, were used. This dataset consists of daily values of influents and effluents for a year. To reduce the dimension of input parameters and to decrease the NN training time, wavelet decomposition and entropy were used. Test results were presented graphically. The test results of the trained model were found to be closer to the measured COD values.  相似文献   

Reply to Comment on “The Keisarhjelmen detachment records Silurian–Devonian extensional collapse in Northern Svalbard”          下载免费PDF全文

Alvar Braathen  Per Terje Osmundsen  Harmon Maher  Morgan Ganerød 《地学学报》2018,30(4):322-324

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