Knowledge-Driven Adaptive Direct Sampling for Reconstructing Geochemical Fields Under Sampling Bias

Purpose: This study investigates the moderating role of Monitoring Operations of Institutional Policy Implementation in Uganda's Mineral Resources Management.
 Methodology: A cross-sectional design has been used in this study to collect data. In order to find the patterns across variables, this strategy entails data gathering at a specific point in time. The study population consists of 39 institutions and 2 ministries; that is Ministry of Energy and Mineral Development and National Environmental Management Authority-(NEMA) and 37 district local governments with mining operations. Districts were chosen in this study based on stratified random selection technique. Ministry of Energy and Mineral Resources and NEMA were picked for this study based on the strata. To guarantee that each group of the institutions have an equitable opportunity to engage in the study, a stratified random sampling technique has been adapted by the study.
 Findings: The results in this study rejects the null hypothesis and accepts alternative hypothesis that Monitoring Operation is a significant moderating effect on Institutional Policy Implementation in Mineral Resource Management. This result implies that at different levels of Monitoring Operations, the effect of Institutional Policy Implementation varies significantly. Particularly, when managers do proper Monitoring Operations, it enhances the effect of Institutional Policy Implementation on Mineral Resource Management.
 Recommendations: The policy implication in this study is that policymakers should enhance Monitoring and Accountability Mechanisms through regular audits and inspections, ensuring compliance with regulations and ethical mining practices. Thus; investing in educational initiatives and awareness programs will raise public awareness of the benefits of sustainable mining practices, empowering local communities to actively engage in decision-making to protect the natural resources.

PageRank is typically computed from the power of transition matrix in a Markov Chain model. It is therefore computationally expensive, and efficient approximation methods to accelerate the computation are necessary, especially when it comes to large graphs. In this paper, we propose two sampling algorithms for PageRank efficient approximation: Direct sampling and Adaptive sampling. Both methods sample the transition matrix and use the sample in PageRank computation. Direct sampling method samples the transition matrix once and uses the sample directly in PageRank computation, whereas adaptive sampling method samples the transition matrix multiple times with an adaptive sample rate which is adjusted iteratively as the computing procedure proceeds. This adaptive sample rate is designed for a good trade-off between accuracy and efficiency for PageRank approximation. We provide detailed theoretical analysis on the error bounds of both methods. We also compare them with several state-of-the-art PageRank approximation methods, including power extrapolation and inner---outer power iteration algorithm. Experimental results on several real-world datasets show that our methods can achieve significantly higher efficiency while attaining comparable accuracy than state-of-the-art methods.

This chapter gives an overview of mineral resources and legislation associated with it in China. The basic legal principles of mineral resources law of China include: state ownership of mineral resources; rational exploitation and sustainable development; and attaching equal importance to mineral resources development and environment protection. The legal institutions such as the property system, mineral resources planning systems, the management system of mineral resources exploration, management system of mineral resources exploitation and the environment protection system in the process of mineral resources exploration all play an important role in the exploration, utilization, protection, and management of mineral resources. Violators will usually have administrative and criminal liability in the mineral resources affairs.

Purpose. The paper is devoted to the theoretical and methodological solution of the scientific problem of substantiating the relationship between the sustainability of mining and the implementation of the circular economy model in the context of the economic security of the state, with an emphasis on the importance of mineral resources. In addition, scientific and practical recommendations have been developed for regulating the circular economy in Ukraine in the context of ensuring economic security. Methods. The paper focuses on various experts and scientists` positions regarding environmental challenges, circular economy, mineral resource management, and economic security. Using the proposed approach of contour analysis of the relationship between the circular economy and the system-forming components of the economic security of the state, the place and role of the circular economy in the system of economic security have been determined. Findings. The research presents the results of a circular economy with the emphasis on mineral resources in the context of the economic security of the state. It has been determined that the circular economy concept combines the peculiarities of various system-forming economic security components (environmental, industrial, energy, mineral resource, social, food). It has been revealed that a circular economy is associated with various scientific trends of the ecological and economic system formation. Originality. The duality of the connection between the implementation of the circular economy model and the components of economic security has been proved, which opens up opportunities for strengthening economic security both through positive effects and certain short-term negative effects. Practical implications. A comprehensive analysis of using mineral resources in the circular economy in the context of the economic security of the state allows forming a number of scientific and practical recommendations for the sustainable ma-nagement of economic security in Ukraine. This makes it possible to create a multi-level system for managing the circular economy in Ukraine, taking into consideration mineral resources.

Accurate estimation of the mining process is vital for the optimal allocation of mineral resources. The development of any country is precisely connected with the management of mineral resources. Therefore, the forecasting of mineral resources contributed much to management, planning, and a maximum allocation of mineral resources. However, it is challenging because of its multiscale variability, nonlinearity, nonstationarity, and high irregularity. In this paper, we proposed two revised hybrid methods to address these issues to predict mineral resources. Our methods are based on denoising, decomposition, prediction, and ensemble principles that are applied to the production of mineral resource time-series data. The performance of the proposed methods is compared with the existing traditional one-stage model (without denoised and decomposition strategies) and two-stage hybrid models (based on denoised strategy), and three-stage hybrid models (with denoised and decomposition strategies). The performance of these methods is evaluated using mean relative error (MRE), mean absolute error (MAE), and mean square error (MSE) as evaluation measures for the production of four principle mineral resources of Pakistan. It is concluded that the proposed framework for the prediction of mineral resources indicated better performance as compared to other existing one-stage, two-stage, and three-stage models. Furthermore, the prediction accuracy of the revised hybrid model is improved by reducing the complexity of the production of mineral resource time-series data.

With the increasing demand for mineral resources in China, how to manage mineral resources scientifically, efficiently and intelligently has become a practical problem faced by relevant governments, enterprises and academia. As the most advanced technology of GIS in recent years, Web GIS can collect, store, process, analyze and visualize heterogeneous, multi-source and massive spatial geographic data. Therefore, introducing Web GIS technology into mine information management and building an information system for massive, multi-source and heterogeneous mine information management is of great significance for the government and enterprises to improve the management efficiency of mineral resources and realize the accurate and scientific planning and management of mineral resources.

Economic growth rate of any country largely depends on the development of mineral sector. Then, the level of technology employed for meeting the extraction conditions must meet environmental norms. Exploration of mineral resources in India and mining is a ready application for technologies for ensuring productivity and efficiency. Use of Geographical Information System (GIS) in mineral resources management is of great help, where each stakeholder can access, use and exchange spatial and nonspatial data for social, economic and environmental activities. With development of communication and information technology, integration of heterogeneous repository of data from the different data sources can be achieved by using Spatial Data Infrastructure (SDI). At the present scenario, the dynamic updating of data, data analysis, data visualisation and data uploading are lacking in most of the information system in GIS environment. For real time integrated mineral resources information monitoring, it is essential to integrate information system with geospatial database. Visualisation of integrated mineral resources information is possible on the desktop environment with the help of GIS. But it is not sufficient for updating the data in dynamic environment. It may be possible to perform dynamic tasks like update, analysis and visualisation of mineral resources information through the mobile devices with the modern high end mobile communication infrastructure. It makes it possible and very useful to take the decision at anytime from anywhere in the world. The data repositories can also be timely updated with the help of common mobile devices from any location, of course with security measure in place. In the present work, a three tier secure framework has been proposed for the mobile based SDI Model for the better management of mineral resources information infrastructure with the use of mobile devices by the integration of geospatial database. The interaction between the various services in the proposed Model has been modeled by using Unified Modeling Language (UML) use case and activity diagrams.

In this work a proposal for the mineral resources having into consideration the economic value of the thermal coal deposits of Colombia is being presented. Also, a methodological proposal is been carried out to determine an approximate economic value of these types of deposits in the country. This methodological proposal arises from the simulation of three possible scenes (optimistic, normal, and pessimist) for the extraction of national coal deposits, given under different types of environmental conditions, technical and financial, proper of this type of research.

1. Integration of Data for Resource Evaluation.- Application of recent developments of regression analysis in regional mineral resource evaluation.- Poisson regression analysis and its application.- Measurement, sampling and interpretation.- Levels of information and probability mapping.- Review of geomathematical applications for mineral resources evaluation in China.- 2. Statistical Analysis of Geochemical Data.- New approaches to the recognition of anomalies in exploration geochemistry.- Univariate patterns in the design of multivariate analysis techniques for geochemical data evaluation.- Application of robust statistics in the analysis of geochemical data.- 3. Statistical Mehtods for Oil and Gas Resource Evaluation.- U.S. Geological Survey assessment methodology for estimation of undiscovered petroleum resources in play analysis of the Artic National Wildlife Refuge.- Statistical evaluation of petroleum deposits before discovery.- On assessing dry probabilities in offshore oil and gas exploration: an application of Bayes's theorem.- Statistical analysis of oil and gas discovery data.- 4. Image Processing in Earth Sciences.- Automated integration of mineral resource data by image processing and artificial intelligence.- Principles of mathematical morphology.- The use of geological image analysis in remote sensing and seismic attribute integration for resource assessment.- Statistical image processing.- 5. Statistical Analysis of Spatial Data.- Spatial analysis of patterns of land-based and ocean-floor ore deposits.- Point processes for the earth sciences.- 6. Geostatistics.- An unconventional approach to geostatistical estimation.- Case studies on modelling complex sulphide orebodies for ore reserve estimation using geostatistical methods.- A Bayesian approach to surface estimation.- Conditional simulation of indicator data. Case study of a multi-seam coal deposit.- Factorial kriging as a method to include spatial structure into classification. A case study on a sulphide orebody.- Geostatistical techniques for interpreting multivariate spatial information.- 7. Other Statisitcal Methodologies for Geoscience Data.- The shape of Lloydminster oil and gas deposit attribute data.- Confidence bands for the distribution and quantile functions for truncated and randomly censored data.- Geostatistical crustal abundance resource models.- 8. Artificial Intelligence in Earth Sciences.- The usage of Artificial intelligence in remote sensing: a review of applications and current research.- GEOVALUATOR, an expert system for resource appraisal: a demonstration prototype for kaolin in Georgia, U.S.A.- GEMS: a microcomputer-based expert system for digital image data.- On the understanding of geological cross-sections by expert systems.- 9. Other Contributed Papers.- Examples of spatial analysis and management in the geographical and conformal projection domains.- A classification procedure for exploitable reserves.- Drainage and divide networks derived from high-fidelity digital terrain models.- An algebraic model for data structure and manipulation as a design basis for integrated geoscience processing systems.- Case study on application of qualitative data analysis techniques to an uranium mineralization.- A shell for microcomputer exploration software used in developing countries.- Optimal exploration strategies: the synthesis of resource assessments and operations research.- Advantages and limitations of discovery process modeling: the case of the Northern West Siberian gas plays.- Some aspects of multivariate analysis.- Workshop Reports.- Current problems and future developments in multivariate analysis.- Current problems and future developments in oil and gas resource modeling and forecasting.- Current problems and future developments in spatial statistics and image processing.- Current problems and future developments in mineral and energy resource expert system development.- Current problems and future developments in the use of microcomputers.

The use of principal component analysis (PCA) for soil heavy metals characterization provides useful information for decision making and policies regarding the potential sources of soil contamination. However, the concentration of heavy metal pollutants is spatially heterogeneous. Accounting for such spatial heterogeneity in soil heavy metal pollutants will improve our understanding with respect to the distribution of the most influential soil heavy metal pollutants. In this study, geographically weighted principal component analysis (GWPCA) was used to describe the spatial heterogeneity and connectivity of soil heavy metals in Kumasi, Ghana. The results from the conventional PCA revealed that three principal components cumulatively accounted for 86% of the total variation in the soil heavy metals in the study area. These components were largely dominated by Fe and Zn. The results from the GWPCA showed that the soil heavy metals are spatially heterogeneous and that the use of PCA disregards this considerable variation. This spatial heterogeneity was confirmed by the spatial maps constructed from the geographically weighted correlations among the variables. After accounting for the spatial heterogeneity, the proportion of variance explained by the three geographically weighted principal components ranged between 85% and 89%. The first three identified GWPC were largely dominated by Fe, Zn and As, respectively. The location of the study area where these variables are dominated provides information for remediation.

A relatively new Multiple Point Statistics algorithm, Direct Sampling (DS), has been tested using a turbidite lobe succession as an example. A seismically derived probability cube was used as auxiliary data. The results show that the combination of low resolution auxiliary data (reservoir is seismically tuned) and a high resolution training image produces geologically realistic reservoir facies geometries. It is shown that it is convenient to use the reservoir grid as a training image, which is an efficient way in order to achieve a reliable correlation between facies in the training image and auxiliary data. Since the training image is highly non-stationary, only the realisations obtained when applying a high weight (>0.4) of the auxiliary variable can be appropriately used. Simulations produced by the IMPALA algorithm are less convincing, which leads to the conclusion that it is recommendable to use DS in similar cases.

Large rivers are generally heterogeneous and productive systems that receive important inputs of dissolved organic matter (DOM) from terrestrial and in situ sources. Thus, they are likely to play a significant role in the biogeochemical cycling of the DOM flowing to the oceans. The asymmetric spatial gradient driven by directional flow and environmental heterogeneity contributes to the fate of DOM flowing downstream. Yet, the relative effects of spatial connectivity and environmental heterogeneity on DOM dynamics are poorly understood. For example, since environmental variables show spatial heterogeneity, the variation explained by environmental and spatial variables may be redundant. We used the St. Lawrence River (SLR) as a representative large river to resolve the unique influences of environmental heterogeneity and spatial connectivity on DOM dynamics. We used three-dimensional fluorescence matrices combined with parallel factor analysis (PARAFAC) to characterize the DOM pool in the SLR. Seven fluorophores were modeled, of which two were identified to be of terrestrial origin and three from algal exudates. We measured a set of environmental variables that are known to drive the fate of DOM in aquatic systems. Additionally, we used asymmetric eigenvector map (AEM) modeling to take spatial connectivity into account. The combination of spatial and environmental models explained 85% of the DOM variation. We show that spatial connectivity is an important driver of DOM dynamics, as a large fraction of environmental heterogeneity was attributable to the asymmetric spatial gradient. Along the longitudinal axis, we noted a rapid increase in dissolved organic carbon (DOC), mostly controlled by terrestrial input of DOM originating from the tributaries. Variance partitioning demonstrated that freshly produced protein-like DOM was found to be the preferential substrate for heterotrophic bacteria undergoing rapid proliferation, while humic-like DOM was more correlated to the diffuse attenuation coefficient of UVA radiation.

A review of sustainable mining and resource management: Transitioning from the life cycle of the mine to the life cycle of the mineral

SummaryCurrent predictions about climate change and its impact on fire regimes have spurred research on how increasing fire frequencies will affect the population dynamics of fire‐dependent species. There has been less consideration of changes in the spatial characteristics of fire regimes, despite recognition of the importance of spatial heterogeneity and connectivity in population dynamics.Here, we test the hypothesis that spatial heterogeneity in fire regimes may not benefit obligate seeders with canopy seed bank, due to regeneration constraints into non‐burned areas. We develop a size‐structured population model for a population ofTecate cypressCallitropsis forbesii(Jeps.) Little, a rare obligate seeder of conservation concern, across a complex landscape in theSantaAnaMountains (Orange,CA,USA). Combining the population model with field measurements of stand structure and fire history, we test the roles of heterogeneity in fire regime and dispersal among patches with differing fire history on population persistence.The model predicts population persistence at fire return intervals >17 years, the approximate fire return interval at the site over the last century. However, population growth and population persistence increase when subpopulations are connected by dispersal and, within a small window of fire return intervals, when subpopulations have uncorrelated fire dynamics. Contrary to our expectations, spatial heterogeneity in fire regime increased population growth rates at intermediate (15–25 year) fire return intervals.Synthesis and applications. Conservation efforts focused on isolated populations of fire‐dependent species should focus on both the temporal (fire return interval) and spatial (heterogeneity in fire occurrence) aspects of fire regimes. For one threatenedCypress species, we find that the interaction between temporal and spatial characteristics of a fire regime can increase the risks of population extinction, particularly under fire regimes characterized by more frequent, larger and more spatially homogenous fire. Species with fragmented subpopulations not well connected by dispersal also have a greater risk of extinction under these fire regimes.

The legal forms of land tenure by communal society, known as communal, are varies in Indonesia. Communal title has been considered as a juridical and common term, although each of communal societies actually has their own different technical term. Making communal land as an investment place of managing mineral and coal resources might bring some legal issues for communal society. The first issue related to less optimal implementation of the principles of investment law by both government and investors. It would impact on the emerging conflicts between communal society and investors. Second, the position of communal land loaded by given-period mining permit would turn into the state property after the period ended.