Incorporating the interrelationship between primary and support processes in monitoring and optimising longwall coal mining efficiency

This thesis increased the researchers understanding of the relationship between operations and maintenance in underground longwall coal mines, using data from a Queensland underground coal mine. The thesis explores various relationships between recorded variables. Issues with human recorded data was uncovered, and results emphasised the significance of variables associated with conveyor operation to explain production.

Microbial aspects of acid generation and bioremediation with relevance to indian mining

The role of Acidithiobacillus group of bacteria in acid generation and heavy metal dissolution was studied with relevance to some Indian mines. Microorganisms implicated in acid generation such as Acidithiobacillus Acidithicibacillus thiooxidans and Leptospirillum ferrooxidans were isolated from abandoned mines, waste rocks and tailing dumps. Arsenite oxidizing Thiomonas and Bacillus group of bacteria were isolated and their ability to oxidize As (111) to As (V) established. Mine isolated Sulfate reducing bacteria were used to remove dissolved copper, zinc, iron and arsenic from solutions.

A pilot study of the Social Water Assessment Protocol in a mining region of Ghana

The Social Water Assessment Protocol (SWAP) is a tool consisting of a series of questions on fourteen themes designed to capture the social context of water around a mine site. A pilot study of the SWAP, conducted in Prestea-Huni Valley, Ghana, showed that some communities were concerned about whether the groundwater was potable. The mining company’s concern was that there was a cycle of dependency amongst communities that received treated water from the mining company. The pilot identified potential data sources and stakeholder groups for each theme, gaps in themes and suggested refinements to questions to improve the SWAP.

Water management capacity building to support rapidly developing mining economies

Many developing countries are experiencing rapid expansion in mining with associated water impacts. In most cases mining expansion is outpacing the building of national capacity to ensure that sustainable water management practices are implemented. Since 2011, Australia's International Mining for Development Centre (IM4DC) has funded capacity building in such countries including a program of water projects. Five projects in particular (principally covering experiences from Peru, Colombia, Ghana, Zambia, Indonesia, Philippines and Mongolia) have provided insight into water capacity building priorities and opportunities. This paper reviews the challenges faced by water stakeholders, and proposes the associated capacity needs. The paper uses the evidence derived from the IM4DC projects to develop a set of specific capacity-building recommendations. Recommendations include: the incorporation of mine water management in engineering and environmental undergraduate courses; secondments of staff to suitable partner organisations; training to allow site staff to effectively monitor water including community impacts; leadership training to support a water stewardship culture; training of officials to support implementation of catchment management approaches; and the empowerment of communities to recognise and negotiate solutions to mine-related risks. New initiatives to fund the transfer of multi-disciplinary knowledge from nations with well-developed water management practices are called for.

Genomic alterations in Myeloproliferative Neoplasms and Myelodysplastic Syndromes

Myeloproliferative neoplasms (MPN) and myelodysplastic syndromes (MDS) are a heterogeneous group of clonal hematopoietic disorders whose etiology and molecular pathogenesis are poorly understood. During the past decade, enormous developments in microarray technology and bioinformatics methods have made it possible to mine novel molecular alterations in a large number of malignancies, including MPN and MDS, which has facilitated the detection of new prognostic, predictive and therapeutic biomarkers for disease stratification. By applying novel microarray techniques, we profiled copy number alterations and microRNA (miRNA) expression changes in bone marrow aspirate and blood samples. In addition, we set up and validated an miRNA expression test for bone marrow core biopsies in order to utilize the large archive material available in many laboratories. We also tested JAK2 mutation status and compare it with the in vitro growth pattern of hematologic progenitors cells. In the study focusing on 100 MPN cases, we detected a Janus kinase 2 (JAK2) mutation in 71 cases. We observed spontaneous erythroid colony growth in all mutation-positive cases in addition to nine mutation negative cases. Interestingly, seven JAK2V167F negative ET cases showed spontaneous megakaryocyte colony formation, one case of which also harbored a myeloproliferative leukemia virus oncogene (MPL) mutation. We studied copy number alterations in 35 MPN and 37 MDS cases by using oligonucleotide-based array comparative hybridization (array CGH). Only one essential thrombocythemia (ET) case presented copy number alterations in chromosomes 1q and 13q. In contrast, MDS cases were characterized by numerous novel cryptic chromosomal aberrations with the most common copy number losses at 5q21.3q33.1 and 7q22.1q33, while the most common copy number gain was trisomy 8. As for the study of the bone marrow core biopsy samples, we showed that even though these samples were embedded in paraffin and underwent decalcification, they were reliable sources of miRNA and suitable for array expression analysis. Further, when studying the miRNA expression profiles of the 19 MDS cases, we found that, compared to controls, two miRNAs (one human Epstein-Barr virus (miR-BART13) miRNA and one human (has-miR-671-5p) miRNA) were downregulated, whereas two other miRNAs (hsa-miR-720 and hsa-miR-21) were upregulated. However, we could find no correlation between copy number alterations and microRNA expression when integrating these two data. This thesis brings to light new information about genomic changes implicated in the development of MPN and MDS, and also underlines the power of applying genome-wide array screening techniques in neoplasias. Rapid advances in molecular techniques and the integration of different genomic data will enable the discovery of the biological contexts of many complex disorders, including myeloid neoplasias.

Dendritic Poly(ether imine) Based Gene Delivery Vector

The nonviral vector based gene delivery approach is attractive due to advantages associated with molecular-level modifications suitable for optimization of vector properties. In a new class of nonviral gene delivery systems, we herein report the potential of poly(ether Mine) (PETIM) dendrimers to mediate an effective gene delivery function. PETIM dendrimer, constituted with tertiary amine branch points, n-propyl ether linkers and primary amines at their peripheries, exhibits significantly reduced toxicities, over a broad concentration range. The dendrimer complexes pDNA effectively, protects DNA from endosomal damages, and delivers to the cell nucleus. Gene transfection studies, utilizing a reporter plasmid pEGFP-C1 and upon complexation with dendrimer, showed a robust expression of the encoded protein. The study shows that PETIM dendrimers are hitherto unknown novel gene delivery vectors, combining features of poly(ethylene imine)-based polymers and dendrimers, yet are relatively nontoxic and structurally precise.

Enhanced lithium-ion transport in PEG-based composite polymer electrolyte with Mn0.03Zn0.97Al2O4 nanoparticles

The ion conduction and thermal properties of composite solid polymer electrolyte (SPE) comprising Poly(ethylene) Glycol (PEG, mol wt. 2000), lithium perchlorate (LiClO4) and insulating Mn0.03Zn0.97Al2O4 nanoparticle fillers were studied by complex impedance analysis and DSC techniques. The average size of the nanoparticles was determined by powder X-ray diffraction (XRD) using Scherrer's equation and was found to be similar to 8 nm. The same was also determined by TEM imaging and found to be similar to 12 nm. The glass transition temperature T, as measured by differential scanning calorimeter (DSC), showed a minimum at 5 mol% of narroparticles. Fractional crystallinity was determined using DSC. NMR was used to deter-mine crystallinity of a pure PEG sample, which was then used as the standard. Fractional crystallinity X. was the lowest for 5 mol% and beyond. The ionic conductivity of the composite polymer electrolyte containing 5 mol% Mn0.03Zn0.97Al2O4 nanoparticles was found to be 1.82 x 10(-5) S/cm, while for the pristine one, it was 7.27 x 10(-7) S/cm at room temperature. As a function of nanoparticle content, conductivity was observed to go through two maxima, one at around 5 mol% and another shallower one at around 12 mol%. The temperature dependence of conductivity could be divided into two regions, one consistent with Arrhenius behaviour and the other with VTF. We conclude that the enhancement of ionic conductivity on the addition of Mn0.03Zn0.97Al2O4 nanoparticles is a result of reduction in both the T, and the crystallinity. (C) 2002 Elsevier Science B.V. All rights reserved.

Stream-Close: Fast mining of Closed Frequent Itemsets in high speed data streams

With the emergence of large-volume and high-speed streaming data, the recent techniques for stream mining of CFIpsilas (closed frequent itemsets) will become inefficient. When concept drift occurs at a slow rate in high speed data streams, the rate of change of information across different sliding windows will be negligible. So, the user wonpsilat be devoid of change in information if we slide window by multiple transactions at a time. Therefore, we propose a novel approach for mining CFIpsilas cumulatively by making sliding width(ges1) over high speed data streams. However, it is nontrivial to mine CFIpsilas cumulatively over stream, because such growth may lead to the generation of exponential number of candidates for closure checking. In this study, we develop an efficient algorithm, stream-close, for mining CFIpsilas over stream by exploring some interesting properties. Our performance study reveals that stream-close achieves good scalability and has promising results.

Biosorption of heavy metal ions from aqueous and cyanide solutions using fungal biomass

A waste fungal biomass containing killed cells of Aspergillus niger was efficiently used in the removal of toxic metal ions such as nickel, calcium, iron and chromium from aqueous solutions. The role of different parameters such as initial metal ion concentration, solution pH and biomass concentration on biosorption capacity was established. The maximum metal uptake was found to be dependent on solution pH and increased with biomass loading upto 10g/L. The adsorption densities for various metal ions could be arranged as Ca>Cr (III)>Ni>Fe>Cr (VI). The effect of the presence of various metal ions in binary, ternary and quaternary combinations on biosorption was also assessed. Ni uptake was significantly affected, while that of Cr (VI) the least, in the presence of other metal ions. Uptake of base metals from an industrial cyanide effluent was studied using different species of fungi such as Aspergillus niger, Aspergillus terreus and Penicillium funiculosum and yeast such as Saccharomyces cerevisiae which were isolated from a gold mine. Traces of gold present in the cyanide effluent could be efficiently recovered. Among the four base metal contaminants present in the cyanide effluent, zinc was found to be most efficiently biosorbed, followed by iron, copper and lead. The role of both living and dead biomass on biosorption was distinguished and probable mechanisms illustrated.

Mining sentiments from songs using latent dirichlet allocation

Song-selection and mood are interdependent. If we capture a song’s sentiment, we can determine the mood of the listener, which can serve as a basis for recommendation systems. Songs are generally classified according to genres, which don’t entirely reflect sentiments. Thus, we require an unsupervised scheme to mine them. Sentiments are classified into either two (positive/negative) or multiple (happy/angry/sad/...) classes, depending on the application. We are interested in analyzing the feelings invoked by a song, involving multi-class sentiments. To mine the hidden sentimental structure behind a song, in terms of “topics”, we consider its lyrics and use Latent Dirichlet Allocation (LDA). Each song is a mixture of moods. Topics mined by LDA can represent moods. Thus we get a scheme of collecting similar-mood songs. For validation, we use a dataset of songs containing 6 moods annotated by users of a particular website.

Discovering Math APIs by Mining Unit Tests

In today's API-rich world, programmer productivity depends heavily on the programmer's ability to discover the required APIs. In this paper, we present a technique and tool, called MATHFINDER, to discover APIs for mathematical computations by mining unit tests of API methods. Given a math expression, MATHFINDER synthesizes pseudo-code to compute the expression by mapping its subexpressions to API method calls. For each subexpression, MATHFINDER searches for a method such that there is a mapping between method inputs and variables of the subexpression. The subexpression, when evaluated on the test inputs of the method under this mapping, should produce results that match the method output on a large number of tests. We implemented MATHFINDER as an Eclipse plugin for discovery of third-party Java APIs and performed a user study to evaluate its effectiveness. In the study, the use of MATHFINDER resulted in a 2x improvement in programmer productivity. In 96% of the subexpressions queried for in the study, MATHFINDER retrieved the desired API methods as the top-most result. The top-most pseudo-code snippet to implement the entire expression was correct in 93% of the cases. Since the number of methods and unit tests to mine could be large in practice, we also implement MATHFINDER in a MapReduce framework and evaluate its scalability and response time.

Association Rule Sharing Model for Privacy Preservation and Collaborative Data Mining Efficiency

The disclosure of information and its misuse in Privacy Preserving Data Mining (PPDM) systems is a concern to the parties involved. In PPDM systems data is available amongst multiple parties collaborating to achieve cumulative mining accuracy. The vertically partitioned data available with the parties involved cannot provide accurate mining results when compared to the collaborative mining results. To overcome the privacy issue in data disclosure this paper describes a Key Distribution-Less Privacy Preserving Data Mining (KDLPPDM) system in which the publication of local association rules generated by the parties is published. The association rules are securely combined to form the combined rule set using the Commutative RSA algorithm. The combined rule sets established are used to classify or mine the data. The results discussed in this paper compare the accuracy of the rules generated using the C4. 5 based KDLPPDM system and the CS. 0 based KDLPPDM system using receiver operating characteristics curves (ROC).

潘洛铁矿滑坡特征分析及防治

分析了潘洛铁矿露天矿滑坡灾害发生发展的特征,得出该滑坡是一个动态的、多层次的复合型滑坡;找出了影响该边坡稳定的主要因素是大气降雨和采矿切割坡脚;根据这些影响因素和滑坡发展变化规律,提出了科学合理的滑坡治理方案,即动态的综合治理方案.经现场实施后,通过滑坡监测数据表明,该滑坡得到了彻底根治.

A Dynamic Comprehensive Method for Landslide Control

A slope failure is developed due to progressive external loads and deteriorations of slope geomaterials, thus forming a progressive and dynamic development and occurrence of landslides. Site geological properties and other active factors such as hydrodynamic load and human activities are complex and usually unknown, thus this dynamic development and occurrence of landslides can only be understood through the progressive accumulation of knowledge on the landslides. For such a progressive process, this paper proposes a dynamic comprehensive control method for landslide control. This control method takes full advantage of updated monitoring data and site investigations of landslides, and emphasizes the implementation of possible measures for landslide control at reasonable stages and in different groups. These measures are to prevent the occurrence of a landslide disaster. As a case study, a landslide project at the Panluo open-pit iron mine is analyzed to illustrate this dynamic comprehensive control method.

Earthquake Stability Analysis about Fine Grinded Tailings Dams

Based on the broken characteristics about earthquake to tailings dams, the earthquake stability analysis methods for tailings dams are introduced. Taking fine tailings dam in Longdu Tailings Pool as an example, the stability of the dam with various situations while earthquake with seven magnitude takes place there. The results can be used by Longdu Mine for tailings pool safety management.