A crop productivity research protocol for long wall mining

Springsure Creek Coal (SCC) intends to develop a coal mine using the long wall mining process under grain farming land near Emerald in Central Queensland (CQ). While this technology will result in some subsidence of the land surface, SCC wishes to maintain productivity of the grain cropping land in the precinct after coal mining. However, the impact of the surface subsidence resulting from that mining process on productivity of cropping land in any Australian landscape is currently unclear. A research protocol to investigate the impacts of subsidence on grain productivity for when the SCC project becomes operational is proposed. The protocol has wider application for other similar mining projects throughout the country. A copy of the full report is accessible on www.aginstitute.com.au.

Quantification of the inevitable: the influence of soil macrofauna on soil water movement in rehabilitated open-cut mined lands

Recolonisation of soil by macrofauna (especially ants, termites and earthworms) in rehabilitated open-cut mine sites is inevitable and, in terms of habitat restoration and function, typically of great value. In these highly disturbed landscapes, soil invertebrates play a major role in soil development (macropore configuration, nutrient cycling, bioturbation, etc.) and can influence hydrological processes such as infiltration, seepage, runoff generation and soil erosion. Understanding and quantifying these ecosystem processes is important in rehabilitation design, establishment and subsequent management to ensure progress to the desired end goal, especially in waste cover systems designed to prevent water reaching and transporting underlying hazardous waste materials. However, the soil macrofauna is typically overlooked during hydrological modelling, possibly due to uncertainties on the extent of their influence, which can lead to failure of waste cover systems or rehabilitation activities. We propose that scientific experiments under controlled conditions and field trials on post-mining lands are required to quantify (i) macrofauna–soil structure interactions, (ii) functional dynamics of macrofauna taxa,and (iii) their effects on macrofauna and soil development over time. Such knowledge would provide crucial information for soil water models, which would increase confidence in mine waste cover design recommendations and eventually lead to higher likelihood of rehabilitation success of open-cut mining land.

Open-pit block sequencing optimization: A mathematical model and solution technique

This study presents a comprehensive mathematical formulation model for a short-term open-pit mine block sequencing problem, which considers nearly all relevant technical aspects in open-pit mining. The proposed model aims to obtain the optimum extraction sequences of the original-size (smallest) blocks over short time intervals and in the presence of real-life constraints, including precedence relationship, machine capacity, grade requirements, processing demands and stockpile management. A hybrid branch-and-bound and simulated annealing algorithm is developed to solve the problem. Computational experiments show that the proposed methodology is a promising way to provide quantitative recommendations for mine planning and scheduling engineers.

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.

Phytophthora in Finnish nurseries

Human-mediated movement of plants and plant products is now generally accepted to be the primary mode of introduction of plant pathogens. Species of the genus Phytophthora are commonly spread in this way and have caused severe epidemics in silviculture, horticulture as well as natural systems all over the world. The aims of the study were to gather information on the occurrence of Phytophthora spp. in Finnish nurseries, to produce information for risk assessments for these Phytophthora spp. by determining their host ranges and tolerance of cold temperatures, and to establish molecular means for their detection. Phytophthora cactorum was found to persist in natural waterbodies and results suggest that irrigation water might be a source of inoculum in nurseries. In addition to P. cactorum, isolates from ornamental nursery Rhododendron yielded three species new to Finland: P. ramorum, P. plurivora and P. pini. The only species with quarantine status, P. ramorum, was most adapted to growth in cold temperatures and able to persist in the nursery in spite of an annual sanitation protocol. Phytophthora plurivora and the closely related P. pini had more hosts among Nordic tree and plant species than P. ramorum and P. cactorum, and also had higher infectivity rates. All four species survived two weeks in -5 °C , and thus soil survival of these Phytophthoras in Finland is likely under current climatic conditions. The most common tree species in Finnish nurseries, Picea abies, was highly susceptible to P. plurivora and P. pini in pathogenicity trials. In a histological examination of P. plurivora in P. abies shoot tissues, fast necrotrophic growth was observed in nearly all tissues. The production of propagules in P. abies shoot tissue was only weakly indicated. In this study, a PCR DGGE technique was developed for simultaneous detection and identification of Phytophthora spp. It reliably detected Phytophthora in plant tissues and could discriminate most test species as well as indicate instances of multiple-species infections. It proved to be a useful detection and identification tool either applied alone or in concert with traditional isolation culture techniques. All of the introduced species of Phytophthora had properties that promote a high risk of establishment and spread in Finland. It is probable that more pathogens of this genus will be introduced and become established in Finland and other Nordic countries unless efficient phytosanitary control becomes standard practice in the international plant trade.

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.

Greater Bangalore: Emerging Urban Heat Island

Bangalore is experiencing unprecedented urbanisation and sprawl in recent times due to concentrated developmental activities with impetus on industrialisation for the economic development of the region. This concentrated growth has resulted in the increase in population and consequent pressure on infrastructure, natural resources and ultimately giving rise to a plethora of serious challenges such as climate change, enhanced green-house gases emissions, lack of appropriate infrastructure, traffic congestion, and lack of basic amenities (electricity, water, and sanitation) in many localities, etc. This study shows that there has been a growth of 632% in urban areas of Greater Bangalore across 37 years (1973 to 2009). Urban heat island phenomenon is evident from large number of localities with higher local temperatures. The study unravels the pattern of growth in Greater Bangalore and its implication on local climate (an increase of ~2 to 2.5 ºC during the last decade) and also on the natural resources (76% decline in vegetation cover and 79% decline in water bodies), necessitating appropriate strategies for the sustainable management.

Geoinformatics for Urbanisation and Urban Sprawl Pattern Analysis

Urbanisation is the increase in the population of cities in proportion to the region's rural population. Urbanisation in India is very rapid with urban population growing at around 2.3 percent per annum. Urban sprawl refers to the dispersed development along highways or surrounding the city and in rural countryside with implications such as loss of agricultural land, open space and ecologically sensitive habitats. Sprawl is thus a pattern and pace of land use in which the rate of land consumed for urban purposes exceeds the rate of population growth resulting in an inefficient and consumptive use of land and its associated resources. This unprecedented urbanisation trend due to burgeoning population has posed serious challenges to the decision makers in the city planning and management process involving plethora of issues like infrastructure development, traffic congestion, and basic amenities (electricity, water, and sanitation), etc. In this context, to aid the decision makers in following the holistic approaches in the city and urban planning, the pattern, analysis, visualization of urban growth and its impact on natural resources has gained importance. This communication, analyses the urbanisation pattern and trends using temporal remote sensing data based on supervised learning using maximum likelihood estimation of multivariate normal density parameters and Bayesian classification approach. The technique is implemented for Greater Bangalore – one of the fastest growing city in the World, with Landsat data of 1973, 1992 and 2000, IRS LISS-3 data of 1999, 2006 and MODIS data of 2002 and 2007. The study shows that there has been a growth of 466% in urban areas of Greater Bangalore across 35 years (1973 to 2007). The study unravels the pattern of growth in Greater Bangalore and its implication on local climate and also on the natural resources, necessitating appropriate strategies for the sustainable management.

Spatial Data Mining and Modeling for visualisation of Rapid Urbanisation

Rapid urbanisation in India has posed serious challenges to the decision makers in regional planning involving plethora of issues including provision of basic amenities (like electricity, water, sanitation, transport, etc.). Urban planning entails an understanding of landscape and urban dynamics with causal factors. Identifying, delineating and mapping landscapes on temporal scale provide an opportunity to monitor the changes, which is important for natural resource management and sustainable planning activities. Multi-source, multi-sensor, multi-temporal, multi-frequency or multi-polarization remote sensing data with efficient classification algorithms and pattern recognition techniques aid in capturing these dynamics. This paper analyses the landscape dynamics of Greater Bangalore by: (i) characterisation of direct impervious surface, (ii) computation of forest fragmentation indices and (iii) modeling to quantify and categorise urban changes. Linear unmixing is used for solving the mixed pixel problem of coarse resolution super spectral MODIS data for impervious surface characterisation. Fragmentation indices were used to classify forests – interior, perforated, edge, transitional, patch and undetermined. Based on this, urban growth model was developed to determine the type of urban growth – Infill, Expansion and Outlying growth. This helped in visualising urban growth poles and consequence of earlier policy decisions that can help in evolving strategies for effective land use policies.