998 resultados para Solution mining.


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The technique of in situ leach (ISL) uranium mining is well established in the USA, as well as being used extensively in Eastern Europe and the former Soviet Union. The method is being proposed and tested on uranium deposits in Australia, with sulfuric acid chemistry and no restoration of groundwater following mining. Test sites in the USA were required to restore groundwater to ascertain the extent of impacts and compare costs to alkaline ISL mines. The problems encountered include expensive and difficult restoration, gypsum precipitation, higher salinity and some heavy metals and radionuclides after restoration. One of the most critical issues is whether natural attenuation is capable of restoring groundwater quality and geochemical conditions in an acid leached aquifer zone. The history of acid ISL sites in the USA and Australia are presented in this study, with a particular focus on the demonstration of restoration of groundwater impacts.

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The technique of in situ leach (ISL) uranium mining is well established in the USA, as well as being used extensively in Eastern Europe and the former Soviet Union. The method is being proposed and tested on uranium deposits in Australia, with sulphuric acid chemistry and no restoration of groundwater following mining. ISL mines in the former Soviet Union generally used acid reagents and were operated without due consideration given to environmental protection. At many former mine sites, the extent of groundwater contamination is significant because of high salinity, heavy metal and radionuclide concentrations compared with pre-mining and changes in the hydrogeological regime caused by mining. After the political collapse of the Soviet Union by the early 1990s, most uranium mines were shut down or ordered to be phased out by government policy. Programmes of restoration are now being undertaken but are proving technically difficult and hampered by a lack of adequate financial resources. The history and problems of acid ISL sites in countries of the former Soviet Union and Asia are presented in this study.

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"U.S. AEC Contract AT(49-1)-545."

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"U.S. AEC Contract AT(49-1)-545."

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R.TeMiS (R Text MIning Solution) (Bouchet-Valat & Bastin, 2013) es un paquete de R (RcmdrPlugin.temis) (Bouchet-Valat, 2016), concebido como plugin de R Commander, que permite analizar, manipular y crear corpus de textos (Garnier, 2014). La arquitectura estadística de RTemis corre a cargo del paquete tm desarrollado por Ingo Feinerer (Feinerer, 2008 ; 2011 ; Feinerer, Hornik y Meyer, 2008). R.TeMiS se ha completado con otros paquetes clásicos de R, como el paquete para la representación de los análisis factoriales de correspondencias de Nenadic y Greenacre (2007). También se han desarrollado paquetes específicos para facilitar el uso de R.TeMiS en los estudios de prensa, por ejemplo para la gestión de los corpus de artículos de prensa de la base de datos Factiva. R.TeMiS se presenta como un plugin de R Commander, desarrollado por Fox (2005), lo cual facilita su utilización para los no usuarios de R.

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This work presents and discusses the influence of the surface tension (gamma(LV)) of methanol/water mixtures on the flotation response of apatite versus gangue minerals conditioned with flotation reagents (75 g/t cornstarch and 100 g/t Berol 867) at pH 10.6. Berol 867 is a collector composed of sodium alkyl sarcosinate plus nonionic surfactant. The highest Schulz efficiency of separation (recovery of apatite minus recovery of gangue) was achieved at approximate to 51.0 mN/m. The critical surface tension of wettability (gamma(C)) of apatite was found to occur at 34.7 mN/m when determined by means of gamma flotation experiments, , and it was 33.9 mN/m when determined by Zisman`s approach.

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A frequently desired outcome when rehabilitating Zn toxic sites in Australia is to establish a self-sustaining native ecosystem. Hence, it is important to understand the tolerance of Australian native plants to high concentrations of Zn. Very little is known about the responses of Australian native plants, and trees in particular, to toxic concentrations of Zn. Acacia holosericea, Eucalyptus camaldulensis and Melaleuca leucadendra plants were grown in dilute solution culture for 10 weeks. The seedlings (42 days old) were exposed to six Zn treatments viz., 0.5, 5, 10, 25, 50 and 100 muM. The order of tolerance to toxic concentrations of Zn was E. camaldulensis > A. holosericea > M. leucadendra, the critical external concentrations being approximately 20, 12 and 1.5 muM, respectively. Tissue Zn concentrations increased as solution Zn increased for all species. Root tissue concentrations were higher than shoot tissue concentrations at all solution Zn concentrations. The critical tissue Zn concentrations were approximately 85 and 110 mug g(-1) DM for M. leucadendra, 115 and 155 mug g(-1) DM for A. holosericea and 415 and 370 mug g(-1) DM for E. camaldulensis for the youngest fully expanded leaf and total shoots, respectively. The results from this paper provide the first comprehensive combination of growth responses, critical external concentrations, critical tissue concentrations and plant toxicity symptoms for three important Australian genera, viz., Eucalyptus, Acacia and Melaleuca, for use in the rehabilitation of potentially Zn toxic sites.

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Currently, the quality of the Indonesian national road network is inadequate due to several constraints, including overcapacity and overloaded trucks. The high deterioration rate of the road infrastructure in developing countries along with major budgetary restrictions and high growth in traffic have led to an emerging need for improving the performance of the highway maintenance system. However, the high number of intervening factors and their complex effects require advanced tools to successfully solve this problem. The high learning capabilities of Data Mining (DM) are a powerful solution to this problem. In the past, these tools have been successfully applied to solve complex and multi-dimensional problems in various scientific fields. Therefore, it is expected that DM can be used to analyze the large amount of data regarding the pavement and traffic, identify the relationship between variables, and provide information regarding the prediction of the data. In this paper, we present a new approach to predict the International Roughness Index (IRI) of pavement based on DM techniques. DM was used to analyze the initial IRI data, including age, Equivalent Single Axle Load (ESAL), crack, potholes, rutting, and long cracks. This model was developed and verified using data from an Integrated Indonesia Road Management System (IIRMS) that was measured with the National Association of Australian State Road Authorities (NAASRA) roughness meter. The results of the proposed approach are compared with the IIRMS analytical model adapted to the IRI, and the advantages of the new approach are highlighted. We show that the novel data-driven model is able to learn (with high accuracy) the complex relationships between the IRI and the contributing factors of overloaded trucks

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Cobre Las Cruces is a renowned copper mining company located in Sevilla, with unexpected problems in wireless communications that have a direct affectation in production. Therefore, the main goals are to improve the WiFi infrastructure, to secure it and to detect and prevent from attacks and from the installation of rogue (and non-authorized) APs. All of that integrated with the current ICT infrastructure.This project has been divided into four phases, although only two of them have been included into the TFC; they are the analysis of the current situation and the design of a WLAN solution.Once the analysis part was finished, some weaknesses were detected. Subjects such as lack of connectivity and control, ignorance about installed WiFi devices and their localization and state and, by and large, the use of weak security mechanisms were some of the problems found. Additionally, due to the fact that the working area became larger and new WiFi infrastructures were added, the first phase took more time than expected.As a result of the detailed analysis, some goals were defined to solve and it was designed a centralized approach able to cope with them. A solution based on 802.11i and 802.1x protocols, digital certificates, a probe system running as IDS/IPS and ligthweight APs in conjunction with a Wireless LAN Controller are the main features.

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The paper presents some contemporary approaches to spatial environmental data analysis. The main topics are concentrated on the decision-oriented problems of environmental spatial data mining and modeling: valorization and representativity of data with the help of exploratory data analysis, spatial predictions, probabilistic and risk mapping, development and application of conditional stochastic simulation models. The innovative part of the paper presents integrated/hybrid model-machine learning (ML) residuals sequential simulations-MLRSS. The models are based on multilayer perceptron and support vector regression ML algorithms used for modeling long-range spatial trends and sequential simulations of the residuals. NIL algorithms deliver non-linear solution for the spatial non-stationary problems, which are difficult for geostatistical approach. Geostatistical tools (variography) are used to characterize performance of ML algorithms, by analyzing quality and quantity of the spatially structured information extracted from data with ML algorithms. Sequential simulations provide efficient assessment of uncertainty and spatial variability. Case study from the Chernobyl fallouts illustrates the performance of the proposed model. It is shown that probability mapping, provided by the combination of ML data driven and geostatistical model based approaches, can be efficiently used in decision-making process. (C) 2003 Elsevier Ltd. All rights reserved.

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The objective of this research is to observe the state of customer value management in Outotec Oyj, determine the key development areas and develop a phase model with which to guide the development of a customer value based sales tool. The study was conducted with a constructive research approach with the focus of identifying a problem and developing a solution for the problem. As a basis for the study, the current literature involving customer value assessment and solution and customer value selling was studied. The data was collected by conducting 16 interviews in two rounds within the company and it was analyzed by coding openly. First, seven important development areas were identified, out of which the most critical were “Customer value mindset inside the company” and “Coordination of customer value management activities”. Utilizing these seven areas three functionality requirements, “Preparation”, “Outotec’s value creation and communication” and “Documentation” and three development requirements for a customer value sales tool were identified. The study concluded with the formulation of a phase model for building a customer value based sales tool. The model included five steps that were defined as 1) Enable customer value utilization, 2) Connect with the customer, 3) Create customer value, 4) Define tool to facilitate value selling and 5) Develop sales tool. Further practical activities were also recommended as a guide for executing the phase model.

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There is consensus worldwide that the artisanal and small-scale mining (ASM) sector is comprised of individuals who are trapped in a vicious cycle of poverty, lacking the necessary financial and technological means to improve their standards of living. Minimal work, however, has been undertaken to identify the very factors behind miners' plight, which inevitably vary from country to country. This paper uses a case study of Ghana to argue that an increased dependence upon mercury for amalgamation In artisanal gold-mining communities is one such-albeit overlooked-"agent of poverty". There is mounting empirical evidence which suggests that dealings with the monoponistic middlemen who supply mercury, purchases of costly medicines to remedy ailments caused by mercury poisoning, and a lack of appropriate safeguards and alternatives to amalgamation, are preventing gold miners from improving their practices and livelihoods. The solution to the problem lies in breaking this cycle of dependency, which can be achieved by providing miners with robust support services, mercury-free technologies and education. (c) 2006 Elsevier Ltd. All rights reserved.

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Metabolic stable isotope labeling is increasingly employed for accurate protein (and metabolite) quantitation using mass spectrometry (MS). It provides sample-specific isotopologues that can be used to facilitate comparative analysis of two or more samples. Stable Isotope Labeling by Amino acids in Cell culture (SILAC) has been used for almost a decade in proteomic research and analytical software solutions have been established that provide an easy and integrated workflow for elucidating sample abundance ratios for most MS data formats. While SILAC is a discrete labeling method using specific amino acids, global metabolic stable isotope labeling using isotopes such as (15)N labels the entire element content of the sample, i.e. for (15)N the entire peptide backbone in addition to all nitrogen-containing side chains. Although global metabolic labeling can deliver advantages with regard to isotope incorporation and costs, the requirements for data analysis are more demanding because, for instance for polypeptides, the mass difference introduced by the label depends on the amino acid composition. Consequently, there has been less progress on the automation of the data processing and mining steps for this type of protein quantitation. Here, we present a new integrated software solution for the quantitative analysis of protein expression in differential samples and show the benefits of high-resolution MS data in quantitative proteomic analyses.

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Aircraft Maintenance, Repair and Overhaul (MRO) feedback commonly includes an engineer’s complex text-based inspection report. Capturing and normalizing the content of these textual descriptions is vital to cost and quality benchmarking, and provides information to facilitate continuous improvement of MRO process and analytics. As data analysis and mining tools requires highly normalized data, raw textual data is inadequate. This paper offers a textual-mining solution to efficiently analyse bulk textual feedback data. Despite replacement of the same parts and/or sub-parts, the actual service cost for the same repair is often distinctly different from similar previously jobs. Regular expression algorithms were incorporated with an aircraft MRO glossary dictionary in order to help provide additional information concerning the reason for cost variation. Professional terms and conventions were included within the dictionary to avoid ambiguity and improve the outcome of the result. Testing results show that most descriptive inspection reports can be appropriately interpreted, allowing extraction of highly normalized data. This additional normalized data strongly supports data analysis and data mining, whilst also increasing the accuracy of future quotation costing. This solution has been effectively used by a large aircraft MRO agency with positive results.