Data-driven fuzzy analysis in quantitative mineral resource assessment

The integration of geo-information from multiple sources and of diverse nature in developing mineral favourability indexes (MFIs) is a well-known problem in mineral exploration and mineral resource assessment. Fuzzy set theory provides a convenient framework to combine and analyse qualitative and quantitative data independently of their source or characteristics. A novel, data-driven formulation for calculating MFIs based on fuzzy analysis is developed in this paper. Different geo-variables are considered fuzzy sets and their appropriate membership functions are defined and modelled. A new weighted average-type aggregation operator is then introduced to generate a new fuzzy set representing mineral favourability. The membership grades of the new fuzzy set are considered as the MFI. The weights for the aggregation operation combine the individual membership functions of the geo-variables, and are derived using information from training areas and L, regression. The technique is demonstrated in a case study of skarn tin deposits and is used to integrate geological, geochemical and magnetic data. The study area covers a total of 22.5 km(2) and is divided into 349 cells, which include nine control cells. Nine geo-variables are considered in this study. Depending on the nature of the various geo-variables, four different types of membership functions are used to model the fuzzy membership of the geo-variables involved. (C) 2002 Elsevier Science Ltd. All rights reserved.

Application of remote sensing and GIS in mineral resource mapping - An overview

Remote sensing, as a direct adjunct to field, lithologic and structural mapping, and more recently, GIS have played an important role in the study of mineralized areas. A review on the application of remote sensing in mineral resource mapping is attempted here. It involves understanding the application of remote sensing in lithologic, structural and alteration mapping. Remote sensing becomes an important tool for locating mineral deposits, in its own right, when the primary and secondary processes of mineralization result in the formation of spectral anomalies. Reconnaissance lithologic mapping is usually the first step of mineral resource mapping. This is complimented with structural mapping, as mineral deposits usually occur along or adjacent to geologic structures, and alteration mapping, as mineral deposits are commonly associated with hydrothermal alteration of the surrounding rocks. In addition to these, understanding the use of hyperspectral remote sensing is crucial as hyperspectral data can help identify and thematically map regions of exploration interest by using the distinct absorption features of most minerals. Finally coming to the exploration stage, GIS forms the perfect tool in integrating and analyzing various georeferenced geoscience data in selecting the best sites of mineral deposits or rather good candidates for further exploration.

Water, Communities and Mineral Resource Development: Understanding the Risks and Opportunities

Issues around water – its quality, use, availability and environmental value – can be a major point of tension between mineral projects and local communities. Failure to manage these issues appropriately can jeopardise the obtaining of regulatory approvals for new projects and place at risk the ‘social licence to operate’ of existing operations. Conversely, there may also be significant opportunities for companies to engage constructively with communities over water issues and to make a positive contribution to the sustainable development of these communities. Using case studies, this paper will explore the various types of social risks and opportunities associated with water and mineral resource development and identify key learnings relating to the management of these issues.

Typing mineral deposits using their grades and tonnages in an artificial neural network

A test of the ability of a probabilistic neural network to classify deposits into types on the basis of deposit tonnage and average Cu, Mo, Ag, Au, Zn, and Pb grades is conducted. The purpose is to examine whether this type of system might serve as a basis for integrating geoscience information available in large mineral databases to classify sites by deposit type. Benefits of proper classification of many sites in large regions are relatively rapid identification of terranes permissive for deposit types and recognition of specific sites perhaps worthy of exploring further. Total tonnages and average grades of 1,137 well-explored deposits identified in published grade and tonnage models representing 13 deposit types were used to train and test the network. Tonnages were transformed by logarithms and grades by square roots to reduce effects of skewness. All values were scaled by subtracting the variable's mean and dividing by its standard deviation. Half of the deposits were selected randomly to be used in training the probabilistic neural network and the other half were used for independent testing. Tests were performed with a probabilistic neural network employing a Gaussian kernel and separate sigma weights for each class (type) and each variable (grade or tonnage). Deposit types were selected to challenge the neural network. For many types, tonnages or average grades are significantly different from other types, but individual deposits may plot in the grade and tonnage space of more than one type. Porphyry Cu, porphyry Cu-Au, and porphyry Cu-Mo types have similar tonnages and relatively small differences in grades. Redbed Cu deposits typically have tonnages that could be confused with porphyry Cu deposits, also contain Cu and, in some situations, Ag. Cyprus and kuroko massive sulfide types have about the same tonnages. Cu, Zn, Ag, and Au grades. Polymetallic vein, sedimentary exhalative Zn-Pb, and Zn-Pb skarn types contain many of the same metals. Sediment-hosted Au, Comstock Au-Ag, and low-sulfide Au-quartz vein types are principally Au deposits with differing amounts of Ag. Given the intent to test the neural network under the most difficult conditions, an overall 75% agreement between the experts and the neural network is considered excellent. Among the largestclassification errors are skarn Zn-Pb and Cyprus massive sulfide deposits classed by the neuralnetwork as kuroko massive sulfides—24 and 63% error respectively. Other large errors are the classification of 92% of porphyry Cu-Mo as porphyry Cu deposits. Most of the larger classification errors involve 25 or fewer training deposits, suggesting that some errors might be the result of small sample size. About 91% of the gold deposit types were classed properly and 98% of porphyry Cu deposits were classes as some type of porphyry Cu deposit. An experienced economic geologist would not make many of the classification errors that were made by the neural network because the geologic settings of deposits would be used to reduce errors. In a separate test, the probabilistic neural network correctly classed 93% of 336 deposits in eight deposit types when trained with presence or absence of 58 minerals and six generalized rock types. The overall success rate of the probabilistic neural network when trained on tonnage and average grades would probably be more than 90% with additional information on the presence of a few rock types.

The effect of water fluoridation on the bone mineral density of young women [Saskatoon study]

Introduction: Osteogenic effects of therapeutic fluoride have been reported; however, the impact of exposure to low level water fluoridation on bone density is not clear. We investigated the effect of long-term exposure to fluoridated water from growth to young adulthood on bone mineral density (BMD). Methods: BMD was measured in 24 healthy women from Regina (fluoride 0.1 mg/L) and 33 from Saskatoon (fluoride 1.0 mg/L), with no differences between groups for height, weight, lifestyle or dietary factors. Results: Saskatoon women had significantly higher mean BMD at total anterior-posterior lumbar spine (APS) and estimated volumetric L3 (VLS), with no difference at total body (TB) or proximal femur (PF). Conclusion: Exposure to water fluoridation during the growing years may have a power impact on axial spine bone density in young women.

Population pharmacokinetics and pharmacodynamics: An underutilized resource

A meeting was convened in Canberra, Australia, at the request of the Australian Drug Evaluation Committee (ADEC), on December 3-4, 1997 to discuss the role of population pharmacokinetics and pharmacodynamics in drug evaluation and development. The ADEC was particularly concerned about registration of drugs in the pediatric age group. The population approach could be used more often than is currently the case in pharmacokinetic and pharmacodynamic studies to provide valuable information for the safe and effective use of drugs in neonates, infants, and children. The meeting ultimately broadened to include discussion about other subgroups. The main conclusions of the meeting were: 1. The population approach, pharmacokinetic and pharmacodynamic analysis, is a valuable tool both for drug registration purposes and for optimal dosing of drugs in specific groups of patients, 2. Population pharmacokinetic and pharmacodynamic studies are able to fill in the gaps' in registration of drugs, for example, to provide information on optimal pediatric dosing. Such studies provide a basis for enhancing product information to improve rational prescribing, 3. Expertise is required to perform the population studies and expertise, with a clinical perspective, is also required to evaluate such studies if they are to be submitted as part of a drug registration dossier Such expertise is available in the Australasian region and is increasing. Centers of excellence with the appropriate expertise to advise and assist should be encouraged to develop and grow in the region, 4. The use of the population approach by the pharmaceutical industry needs to be encouraged to provide valuable information not obtainable by other techniques. The acceptance of population pharmacokinetic and pharmacodynamic analyses by regulatory agencies also needs to be encouraged, and 5. Development of the population approach to pharmacokinetics and pharmacodynamics is needed from a public health perspective to ensure that all available information is collected and used to improve the way drugs are used. This important endeavor needs funding and support at the local and international levels.