MinePath: Mining for Phenotype Differential Sub-paths in Molecular Pathways

PubMed Central

Koumakis, Lefteris; Kartsaki, Evgenia; Chatzimina, Maria; Zervakis, Michalis; Vassou, Despoina; Marias, Kostas; Moustakis, Vassilis; Potamias, George

2016-01-01

Pathway analysis methodologies couple traditional gene expression analysis with knowledge encoded in established molecular pathway networks, offering a promising approach towards the biological interpretation of phenotype differentiating genes. Early pathway analysis methodologies, named as gene set analysis (GSA), view pathways just as plain lists of genes without taking into account either the underlying pathway network topology or the involved gene regulatory relations. These approaches, even if they achieve computational efficiency and simplicity, consider pathways that involve the same genes as equivalent in terms of their gene enrichment characteristics. Most recent pathway analysis approaches take into account the underlying gene regulatory relations by examining their consistency with gene expression profiles and computing a score for each profile. Even with this approach, assessing and scoring single-relations limits the ability to reveal key gene regulation mechanisms hidden in longer pathway sub-paths. We introduce MinePath, a pathway analysis methodology that addresses and overcomes the aforementioned problems. MinePath facilitates the decomposition of pathways into their constituent sub-paths. Decomposition leads to the transformation of single-relations to complex regulation sub-paths. Regulation sub-paths are then matched with gene expression sample profiles in order to evaluate their functional status and to assess phenotype differential power. Assessment of differential power supports the identification of the most discriminant profiles. In addition, MinePath assess the significance of the pathways as a whole, ranking them by their p-values. Comparison results with state-of-the-art pathway analysis systems are indicative for the soundness and reliability of the MinePath approach. In contrast with many pathway analysis tools, MinePath is a web-based system (www.minepath.org) offering dynamic and rich pathway visualization functionality, with the unique characteristic to color regulatory relations between genes and reveal their phenotype inclination. This unique characteristic makes MinePath a valuable tool for in silico molecular biology experimentation as it serves the biomedical researchers’ exploratory needs to reveal and interpret the regulatory mechanisms that underlie and putatively govern the expression of target phenotypes. PMID:27832067

MinePath: Mining for Phenotype Differential Sub-paths in Molecular Pathways.

PubMed

Koumakis, Lefteris; Kanterakis, Alexandros; Kartsaki, Evgenia; Chatzimina, Maria; Zervakis, Michalis; Tsiknakis, Manolis; Vassou, Despoina; Kafetzopoulos, Dimitris; Marias, Kostas; Moustakis, Vassilis; Potamias, George

2016-11-01

Pathway analysis methodologies couple traditional gene expression analysis with knowledge encoded in established molecular pathway networks, offering a promising approach towards the biological interpretation of phenotype differentiating genes. Early pathway analysis methodologies, named as gene set analysis (GSA), view pathways just as plain lists of genes without taking into account either the underlying pathway network topology or the involved gene regulatory relations. These approaches, even if they achieve computational efficiency and simplicity, consider pathways that involve the same genes as equivalent in terms of their gene enrichment characteristics. Most recent pathway analysis approaches take into account the underlying gene regulatory relations by examining their consistency with gene expression profiles and computing a score for each profile. Even with this approach, assessing and scoring single-relations limits the ability to reveal key gene regulation mechanisms hidden in longer pathway sub-paths. We introduce MinePath, a pathway analysis methodology that addresses and overcomes the aforementioned problems. MinePath facilitates the decomposition of pathways into their constituent sub-paths. Decomposition leads to the transformation of single-relations to complex regulation sub-paths. Regulation sub-paths are then matched with gene expression sample profiles in order to evaluate their functional status and to assess phenotype differential power. Assessment of differential power supports the identification of the most discriminant profiles. In addition, MinePath assess the significance of the pathways as a whole, ranking them by their p-values. Comparison results with state-of-the-art pathway analysis systems are indicative for the soundness and reliability of the MinePath approach. In contrast with many pathway analysis tools, MinePath is a web-based system (www.minepath.org) offering dynamic and rich pathway visualization functionality, with the unique characteristic to color regulatory relations between genes and reveal their phenotype inclination. This unique characteristic makes MinePath a valuable tool for in silico molecular biology experimentation as it serves the biomedical researchers' exploratory needs to reveal and interpret the regulatory mechanisms that underlie and putatively govern the expression of target phenotypes.

Depth data research of GIS based on clustering analysis algorithm

NASA Astrophysics Data System (ADS)

Xiong, Yan; Xu, Wenli

2018-03-01

The data of GIS have spatial distribution. Geographic data has both spatial characteristics and attribute characteristics, and also changes with time. Therefore, the amount of data is very large. Nowadays, many industries and departments in the society are using GIS. However, without proper data analysis and mining scheme, GIS will not exert its maximum effectiveness and will waste a lot of data. In this paper, we use the geographic information demand of a national security department as the experimental object, combining the characteristics of GIS data, taking into account the characteristics of time, space, attributes and so on, and using cluster analysis algorithm. We further study the mining scheme for depth data, and get the algorithm model. This algorithm can automatically classify sample data, and then carry out exploratory analysis. The research shows that the algorithm model and the information mining scheme can quickly find hidden depth information from the surface data of GIS, thus improving the efficiency of the security department. This algorithm can also be extended to other fields.

Strategic Integration of Multiple Bioinformatics Resources for System Level Analysis of Biological Networks.

PubMed

D'Souza, Mark; Sulakhe, Dinanath; Wang, Sheng; Xie, Bing; Hashemifar, Somaye; Taylor, Andrew; Dubchak, Inna; Conrad Gilliam, T; Maltsev, Natalia

2017-01-01

Recent technological advances in genomics allow the production of biological data at unprecedented tera- and petabyte scales. Efficient mining of these vast and complex datasets for the needs of biomedical research critically depends on a seamless integration of the clinical, genomic, and experimental information with prior knowledge about genotype-phenotype relationships. Such experimental data accumulated in publicly available databases should be accessible to a variety of algorithms and analytical pipelines that drive computational analysis and data mining.We present an integrated computational platform Lynx (Sulakhe et al., Nucleic Acids Res 44:D882-D887, 2016) ( http://lynx.cri.uchicago.edu ), a web-based database and knowledge extraction engine. It provides advanced search capabilities and a variety of algorithms for enrichment analysis and network-based gene prioritization. It gives public access to the Lynx integrated knowledge base (LynxKB) and its analytical tools via user-friendly web services and interfaces. The Lynx service-oriented architecture supports annotation and analysis of high-throughput experimental data. Lynx tools assist the user in extracting meaningful knowledge from LynxKB and experimental data, and in the generation of weighted hypotheses regarding the genes and molecular mechanisms contributing to human phenotypes or conditions of interest. The goal of this integrated platform is to support the end-to-end analytical needs of various translational projects.

toxoMine: an integrated omics data warehouse for Toxoplasma gondii systems biology research

PubMed Central

Rhee, David B.; Croken, Matthew McKnight; Shieh, Kevin R.; Sullivan, Julie; Micklem, Gos; Kim, Kami; Golden, Aaron

2015-01-01

Toxoplasma gondii (T. gondii) is an obligate intracellular parasite that must monitor for changes in the host environment and respond accordingly; however, it is still not fully known which genetic or epigenetic factors are involved in regulating virulence traits of T. gondii. There are on-going efforts to elucidate the mechanisms regulating the stage transition process via the application of high-throughput epigenomics, genomics and proteomics techniques. Given the range of experimental conditions and the typical yield from such high-throughput techniques, a new challenge arises: how to effectively collect, organize and disseminate the generated data for subsequent data analysis. Here, we describe toxoMine, which provides a powerful interface to support sophisticated integrative exploration of high-throughput experimental data and metadata, providing researchers with a more tractable means toward understanding how genetic and/or epigenetic factors play a coordinated role in determining pathogenicity of T. gondii. As a data warehouse, toxoMine allows integration of high-throughput data sets with public T. gondii data. toxoMine is also able to execute complex queries involving multiple data sets with straightforward user interaction. Furthermore, toxoMine allows users to define their own parameters during the search process that gives users near-limitless search and query capabilities. The interoperability feature also allows users to query and examine data available in other InterMine systems, which would effectively augment the search scope beyond what is available to toxoMine. toxoMine complements the major community database ToxoDB by providing a data warehouse that enables more extensive integrative studies for T. gondii. Given all these factors, we believe it will become an indispensable resource to the greater infectious disease research community. Database URL: http://toxomine.org PMID:26130662

LLNL electro-optical mine detection program

DOE Office of Scientific and Technical Information (OSTI.GOV)

Anderson, C.; Aimonetti, W.; Barth, M.

1994-09-30

Under funding from the Advanced Research Projects Agency (ARPA) and the US Marine Corps (USMC), Lawrence Livermore National Laboratory (LLNL) has directed a program aimed at improving detection capabilities against buried mines and munitions. The program has provided a national test facility for buried mines in arid environments, compiled and distributed an extensive data base of infrared (IR), ground penetrating radar (GPR), and other measurements made at that site, served as a host for other organizations wishing to make measurements, made considerable progress in the use of ground penetrating radar for mine detection, and worked on the difficult problem ofmore » sensor fusion as applied to buried mine detection. While the majority of our effort has been concentrated on the buried mine problem, LLNL has worked with the U.S.M.C. on surface mine problems as well, providing data and analysis to support the COBRA (Coastal Battlefield Reconnaissance and Analysis) program. The original aim of the experimental aspect of the program was the utilization of multiband infrared approaches for the detection of buried mines. Later the work was extended to a multisensor investigation, including sensors other than infrared imagers. After an early series of measurements, it was determined that further progress would require a larger test facility in a natural environment, so the Buried Object Test Facility (BOTF) was constructed at the Nevada Test Site. After extensive testing, with sensors spanning the electromagnetic spectrum from the near ultraviolet to radio frequencies, possible paths for improvement were: improved spatial resolution providing better ground texture discrimination; analysis which involves more complicated spatial queueing and filtering; additional IR bands using imaging spectroscopy; the use of additional sensors other than IR and the use of data fusion techniques with multi-sensor data; and utilizing time dependent observables like temperature.« less

Literature mining, gene-set enrichment and pathway analysis for target identification in Behçet's disease.

PubMed

Wilson, Paul; Larminie, Christopher; Smith, Rona

2016-01-01

To use literature mining to catalogue Behçet's associated genes, and advanced computational methods to improve the understanding of the pathways and signalling mechanisms that lead to the typical clinical characteristics of Behçet's patients. To extend this technique to identify potential treatment targets for further experimental validation. Text mining methods combined with gene enrichment tools, pathway analysis and causal analysis algorithms. This approach identified 247 human genes associated with Behçet's disease and the resulting disease map, comprising 644 nodes and 19220 edges, captured important details of the relationships between these genes and their associated pathways, as described in diverse data repositories. Pathway analysis has identified how Behçet's associated genes are likely to participate in innate and adaptive immune responses. Causal analysis algorithms have identified a number of potential therapeutic strategies for further investigation. Computational methods have captured pertinent features of the prominent disease characteristics presented in Behçet's disease and have highlighted NOD2, ICOS and IL18 signalling as potential therapeutic strategies.

30 CFR 18.82 - Permit to use experimental electric face equipment in a gassy mine or tunnel.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 30 Mineral Resources 1 2011-07-01 2011-07-01 false Permit to use experimental electric face... Modifications of Approved Machines, and Permits To Use Experimental Equipment § 18.82 Permit to use experimental... to use experimental electric face equipment in a gassy mine or tunnel will be considered only when...

30 CFR 18.82 - Permit to use experimental electric face equipment in a gassy mine or tunnel.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 30 Mineral Resources 1 2010-07-01 2010-07-01 false Permit to use experimental electric face... Modifications of Approved Machines, and Permits To Use Experimental Equipment § 18.82 Permit to use experimental... to use experimental electric face equipment in a gassy mine or tunnel will be considered only when...

30 CFR 18.82 - Permit to use experimental electric face equipment in a gassy mine or tunnel.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 30 Mineral Resources 1 2013-07-01 2013-07-01 false Permit to use experimental electric face... Modifications of Approved Machines, and Permits To Use Experimental Equipment § 18.82 Permit to use experimental... to use experimental electric face equipment in a gassy mine or tunnel will be considered only when...

30 CFR 18.82 - Permit to use experimental electric face equipment in a gassy mine or tunnel.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 30 Mineral Resources 1 2012-07-01 2012-07-01 false Permit to use experimental electric face... Modifications of Approved Machines, and Permits To Use Experimental Equipment § 18.82 Permit to use experimental... to use experimental electric face equipment in a gassy mine or tunnel will be considered only when...

30 CFR 18.82 - Permit to use experimental electric face equipment in a gassy mine or tunnel.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 30 Mineral Resources 1 2014-07-01 2014-07-01 false Permit to use experimental electric face... Modifications of Approved Machines, and Permits To Use Experimental Equipment § 18.82 Permit to use experimental... to use experimental electric face equipment in a gassy mine or tunnel will be considered only when...

Identification and elucidation of anthropogenic source contribution in PM10 pollutant: Insight gain from dispersion and receptor models.

PubMed

Roy, Debananda; Singh, Gurdeep; Yadav, Pankaj

2016-10-01

Source apportionment study of PM 10 (Particulate Matter) in a critically polluted area of Jharia coalfield, India has been carried out using Dispersion model, Principle Component Analysis (PCA) and Chemical Mass Balance (CMB) techniques. Dispersion model Atmospheric Dispersion Model (AERMOD) was introduced to simplify the complexity of sources in Jharia coalfield. PCA and CMB analysis indicates that monitoring stations near the mining area were mainly affected by the emission from open coal mining and its associated activities such as coal transportation, loading and unloading of coal. Mine fire emission also contributed a considerable amount of particulate matters in monitoring stations. Locations in the city area were mostly affected by vehicular, Liquid Petroleum Gas (LPG) & Diesel Generator (DG) set emissions, residential, and commercial activities. The experimental data sampling and their analysis could aid understanding how dispersion based model technique along with receptor model based concept can be strategically used for quantitative analysis of Natural and Anthropogenic sources of PM 10 . Copyright © 2016. Published by Elsevier B.V.

A novel forward and backward scattering wave measurement system for optimizing GPR standoff mine/IED detector

NASA Astrophysics Data System (ADS)

Fuse, Yukinori

2012-06-01

Standoff detection of mines and improvised explosive devices by ground penetrating radar has advantages in terms of safety and efficiency. However, the reflected signals from buried targets are often disturbed by those from the ground surface, which vary with the antennas angle, making it more difficult to detect at a safe distance. An understanding of the forward and backward scattering wave is thus essential for improving standoff detection capability. We present some experimental results from using our measurement system for such an analysis.

Combination of beehive matrices analysis and ant biodiversity to study heavy metal pollution impact in a post-mining area (Sardinia, Italy).

PubMed

Satta, Alberto; Verdinelli, Marcello; Ruiu, Luca; Buffa, Franco; Salis, Severyn; Sassu, Antonio; Floris, Ignazio

2012-11-01

Mining activities represent a major source of environment contamination. The aim of this study was to evaluate the use of bees and ants as bioindicators to detect the heavy metal impact in post-mining areas. A biomonitoring programme involving a combination of honeybee hive matrices analysis and ant biodiversity survey was conducted over a 3-year period. The experimental design involved three monitoring stations where repeated sampling activities focused on chemical detection of cadmium (Cd), chrome (Cr) and lead (Pb) from different matrices, both from hosted beehives (foraging bees, honey and pollen) and from the surrounding environment (stream water and soil). At the same time, ant biodiversity (number and abundance of species) was determined through a monitoring programme based on the use of pitfall traps placed in different habitats inside each mining site. The heavy metal content detected in stream water from the control station was always below the analytical limit of quantification. In the case of soil, the content of Cd and Pb from the control was lower than that of mining sites. The mean heavy metal concentrations in beehive matrices from mining sites were mainly higher than the control, and as a result of regression and discriminant analysis, forager bee sampling was an efficient environmental pollution bioindicator. Ant collection and identification highlighted a wide species variety with differences among habitats mostly associated with vegetation features. A lower variability was observed in the polluted landfill characterised by lack of vegetation. Combined biomonitoring with forager bees and ants represents a reliable tool for heavy metal environmental impact studies.

Data Mining of Macromolecular Structures.

PubMed

van Beusekom, Bart; Perrakis, Anastassis; Joosten, Robbie P

2016-01-01

The use of macromolecular structures is widespread for a variety of applications, from teaching protein structure principles all the way to ligand optimization in drug development. Applying data mining techniques on these experimentally determined structures requires a highly uniform, standardized structural data source. The Protein Data Bank (PDB) has evolved over the years toward becoming the standard resource for macromolecular structures. However, the process selecting the data most suitable for specific applications is still very much based on personal preferences and understanding of the experimental techniques used to obtain these models. In this chapter, we will first explain the challenges with data standardization, annotation, and uniformity in the PDB entries determined by X-ray crystallography. We then discuss the specific effect that crystallographic data quality and model optimization methods have on structural models and how validation tools can be used to make informed choices. We also discuss specific advantages of using the PDB_REDO databank as a resource for structural data. Finally, we will provide guidelines on how to select the most suitable protein structure models for detailed analysis and how to select a set of structure models suitable for data mining.

The Functional Genomics Network in the evolution of biological text mining over the past decade.

PubMed

Blaschke, Christian; Valencia, Alfonso

2013-03-25

Different programs of The European Science Foundation (ESF) have contributed significantly to connect researchers in Europe and beyond through several initiatives. This support was particularly relevant for the development of the areas related with extracting information from papers (text-mining) because it supported the field in its early phases long before it was recognized by the community. We review the historical development of text mining research and how it was introduced in bioinformatics. Specific applications in (functional) genomics are described like it's integration in genome annotation pipelines and the support to the analysis of high-throughput genomics experimental data, and we highlight the activities of evaluation of methods and benchmarking for which the ESF programme support was instrumental. Copyright © 2013 Elsevier B.V. All rights reserved.

Modeling of experimental data on trace elements and organic compounds content in industrial waste dumps.

PubMed

Smoliński, Adam; Drobek, Leszek; Dombek, Václav; Bąk, Andrzej

2016-11-01

The main objective of the study presented was to investigate the differences between 20 mine waste dumps located in the Silesian Region of Poland and Czech Republic, in terms of trace elements and polycyclic aromatic hydrocarbons contents. The Principal Component Analysis and Hierarchical Clustering Analysis were applied in exploration of the studied data. Since the data set was affected by outlying objects, the employment of a relevant analysis strategy was necessary. The final PCA model was constructed with the use of the Expectation-Maximization iterative approach preceded by a correct identification of outliers. The analysis of the experimental data indicated that three mine waste dumps located in Poland were characterized by the highest concentrations of dibenzo(g,h,i)anthracene and benzo(g,h,i)perylene, and six objects located in Czech Republic and three objects in Poland were distinguished by high concentrations of chrysene and indeno (1.2.3-cd) pyrene. Three of studied mine waste dumps, one located in Czech Republic and two in Poland, were characterized by low concentrations of Cr, Ni, V, naphthalene, acenaphthene, fluorene, phenanthrene, anthracene, fluoranthen, benzo(a)anthracene, chrysene, benzo (b) fluoranthene, benzo (k) fluoranthene, benzo(a)pyrene, dibenzo(g,h,i)anthracene, benzo(g,h,i)perylene and indeno (1.2.3-cd) pyrene in comparison with the remaining ones. The analysis contributes to the assessment and prognosis of ecological and health risks related to the emission of trace elements and organic compounds (PAHs) from the waste dumps examined. No previous research of similar scope and aims has been reported for the area concerned. Copyright © 2016 Elsevier Ltd. All rights reserved.

Methane Content Estimation in DuongHuy Coal Mine

NASA Astrophysics Data System (ADS)

Nguyen, Van Thinh; Mijał, Waldemar; Dang, Vu Chi; Nguyen, Thi Tuyet Mai

2018-03-01

Methane hazard has always been considered for underground coal mining as it can lead to methane explosion. In Quang Ninh province, several coal mines such as Mạo Khe coal mine, Khe Cham coal mine, especially Duong Huy mine that have high methane content. Experimental data to examine contents of methane bearing coal seams at different depths are not similar in Duong coal mine. In order to ensure safety, this report has been undertaken to determine a pattern of changing methane contents of coal seams at different exploitation depths in Duong Huy underground coal mine.

Development of a Universal Safety Behavior Management System for Coal Mine Workers

PubMed Central

LI, Jizu; LI, Yuejiao; LIU, Xiaoguang

2015-01-01

Background: In China, over 80% of all work-related deaths in the mining industry occur in coal mines and human factors constitute 85% of the direct causes of coal mine accidents, which indicates that significant shortcomings currently exist in the safety behavior management of Chinese coal mine workers. We aimed to verify the impact of human psychological behavior in coal mine accidents systematically through experimental study, theoretical analysis and management application. Methods: Four test instruments (Sensory and cognitive capacity test, Sixteen-Personal Factor Questionnaire, Symptom Checklist 90 Questionnaire and the supervisors’ evaluation) were employed from November 2013 to June 2014 to identify unsafe behavior factors, the self-established Questionnaire of Safety Behavior Norms (QSBN) was also used to propose the safety behavior countermeasures of coal mine employees. Results: The mental health of most coal mine workers’ is relatively poor. The sensory and cognitive capacity of those in different work posts varies greatly, as does the sense of responsibility. Workers are susceptible to external influences, and score low in site management. When the 16-PF and SCL-90 sensory and cognitive assessments were combined, the psychological index predictive power was greatest for estimating sense of efficiency and degree of satisfaction in internal evaluations, while at the same time lowest for estimating control of introversion-extroversion and stress character. Conclusion: The psychological indicators can predict part of employee safety behavior, and assist a coal mine enterprise to recruit staff, develop occupational safety norms and improve the working environment. PMID:26258088

Active Storage with Analytics Capabilities and I/O Runtime System for Petascale Systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Choudhary, Alok

Computational scientists must understand results from experimental, observational and computational simulation generated data to gain insights and perform knowledge discovery. As systems approach the petascale range, problems that were unimaginable a few years ago are within reach. With the increasing volume and complexity of data produced by ultra-scale simulations and high-throughput experiments, understanding the science is largely hampered by the lack of comprehensive I/O, storage, acceleration of data manipulation, analysis, and mining tools. Scientists require techniques, tools and infrastructure to facilitate better understanding of their data, in particular the ability to effectively perform complex data analysis, statistical analysis and knowledgemore » discovery. The goal of this work is to enable more effective analysis of scientific datasets through the integration of enhancements in the I/O stack, from active storage support at the file system layer to MPI-IO and high-level I/O library layers. We propose to provide software components to accelerate data analytics, mining, I/O, and knowledge discovery for large-scale scientific applications, thereby increasing productivity of both scientists and the systems. Our approaches include 1) design the interfaces in high-level I/O libraries, such as parallel netCDF, for applications to activate data mining operations at the lower I/O layers; 2) Enhance MPI-IO runtime systems to incorporate the functionality developed as a part of the runtime system design; 3) Develop parallel data mining programs as part of runtime library for server-side file system in PVFS file system; and 4) Prototype an active storage cluster, which will utilize multicore CPUs, GPUs, and FPGAs to carry out the data mining workload.« less

Extraction of Pharmacokinetic Evidence of Drug–Drug Interactions from the Literature

PubMed Central

Kolchinsky, Artemy; Lourenço, Anália; Wu, Heng-Yi; Li, Lang; Rocha, Luis M.

2015-01-01

Drug-drug interaction (DDI) is a major cause of morbidity and mortality and a subject of intense scientific interest. Biomedical literature mining can aid DDI research by extracting evidence for large numbers of potential interactions from published literature and clinical databases. Though DDI is investigated in domains ranging in scale from intracellular biochemistry to human populations, literature mining has not been used to extract specific types of experimental evidence, which are reported differently for distinct experimental goals. We focus on pharmacokinetic evidence for DDI, essential for identifying causal mechanisms of putative interactions and as input for further pharmacological and pharmacoepidemiology investigations. We used manually curated corpora of PubMed abstracts and annotated sentences to evaluate the efficacy of literature mining on two tasks: first, identifying PubMed abstracts containing pharmacokinetic evidence of DDIs; second, extracting sentences containing such evidence from abstracts. We implemented a text mining pipeline and evaluated it using several linear classifiers and a variety of feature transforms. The most important textual features in the abstract and sentence classification tasks were analyzed. We also investigated the performance benefits of using features derived from PubMed metadata fields, various publicly available named entity recognizers, and pharmacokinetic dictionaries. Several classifiers performed very well in distinguishing relevant and irrelevant abstracts (reaching F1≈0.93, MCC≈0.74, iAUC≈0.99) and sentences (F1≈0.76, MCC≈0.65, iAUC≈0.83). We found that word bigram features were important for achieving optimal classifier performance and that features derived from Medical Subject Headings (MeSH) terms significantly improved abstract classification. We also found that some drug-related named entity recognition tools and dictionaries led to slight but significant improvements, especially in classification of evidence sentences. Based on our thorough analysis of classifiers and feature transforms and the high classification performance achieved, we demonstrate that literature mining can aid DDI discovery by supporting automatic extraction of specific types of experimental evidence. PMID:25961290

Mining biomedical images towards valuable information retrieval in biomedical and life sciences

PubMed Central

Ahmed, Zeeshan; Zeeshan, Saman; Dandekar, Thomas

2016-01-01

Biomedical images are helpful sources for the scientists and practitioners in drawing significant hypotheses, exemplifying approaches and describing experimental results in published biomedical literature. In last decades, there has been an enormous increase in the amount of heterogeneous biomedical image production and publication, which results in a need for bioimaging platforms for feature extraction and analysis of text and content in biomedical images to take advantage in implementing effective information retrieval systems. In this review, we summarize technologies related to data mining of figures. We describe and compare the potential of different approaches in terms of their developmental aspects, used methodologies, produced results, achieved accuracies and limitations. Our comparative conclusions include current challenges for bioimaging software with selective image mining, embedded text extraction and processing of complex natural language queries. PMID:27538578

Extracting semantically enriched events from biomedical literature

PubMed Central

2012-01-01

Background Research into event-based text mining from the biomedical literature has been growing in popularity to facilitate the development of advanced biomedical text mining systems. Such technology permits advanced search, which goes beyond document or sentence-based retrieval. However, existing event-based systems typically ignore additional information within the textual context of events that can determine, amongst other things, whether an event represents a fact, hypothesis, experimental result or analysis of results, whether it describes new or previously reported knowledge, and whether it is speculated or negated. We refer to such contextual information as meta-knowledge. The automatic recognition of such information can permit the training of systems allowing finer-grained searching of events according to the meta-knowledge that is associated with them. Results Based on a corpus of 1,000 MEDLINE abstracts, fully manually annotated with both events and associated meta-knowledge, we have constructed a machine learning-based system that automatically assigns meta-knowledge information to events. This system has been integrated into EventMine, a state-of-the-art event extraction system, in order to create a more advanced system (EventMine-MK) that not only extracts events from text automatically, but also assigns five different types of meta-knowledge to these events. The meta-knowledge assignment module of EventMine-MK performs with macro-averaged F-scores in the range of 57-87% on the BioNLP’09 Shared Task corpus. EventMine-MK has been evaluated on the BioNLP’09 Shared Task subtask of detecting negated and speculated events. Our results show that EventMine-MK can outperform other state-of-the-art systems that participated in this task. Conclusions We have constructed the first practical system that extracts both events and associated, detailed meta-knowledge information from biomedical literature. The automatically assigned meta-knowledge information can be used to refine search systems, in order to provide an extra search layer beyond entities and assertions, dealing with phenomena such as rhetorical intent, speculations, contradictions and negations. This finer grained search functionality can assist in several important tasks, e.g., database curation (by locating new experimental knowledge) and pathway enrichment (by providing information for inference). To allow easy integration into text mining systems, EventMine-MK is provided as a UIMA component that can be used in the interoperable text mining infrastructure, U-Compare. PMID:22621266

Extracting semantically enriched events from biomedical literature.

PubMed

Miwa, Makoto; Thompson, Paul; McNaught, John; Kell, Douglas B; Ananiadou, Sophia

2012-05-23

Research into event-based text mining from the biomedical literature has been growing in popularity to facilitate the development of advanced biomedical text mining systems. Such technology permits advanced search, which goes beyond document or sentence-based retrieval. However, existing event-based systems typically ignore additional information within the textual context of events that can determine, amongst other things, whether an event represents a fact, hypothesis, experimental result or analysis of results, whether it describes new or previously reported knowledge, and whether it is speculated or negated. We refer to such contextual information as meta-knowledge. The automatic recognition of such information can permit the training of systems allowing finer-grained searching of events according to the meta-knowledge that is associated with them. Based on a corpus of 1,000 MEDLINE abstracts, fully manually annotated with both events and associated meta-knowledge, we have constructed a machine learning-based system that automatically assigns meta-knowledge information to events. This system has been integrated into EventMine, a state-of-the-art event extraction system, in order to create a more advanced system (EventMine-MK) that not only extracts events from text automatically, but also assigns five different types of meta-knowledge to these events. The meta-knowledge assignment module of EventMine-MK performs with macro-averaged F-scores in the range of 57-87% on the BioNLP'09 Shared Task corpus. EventMine-MK has been evaluated on the BioNLP'09 Shared Task subtask of detecting negated and speculated events. Our results show that EventMine-MK can outperform other state-of-the-art systems that participated in this task. We have constructed the first practical system that extracts both events and associated, detailed meta-knowledge information from biomedical literature. The automatically assigned meta-knowledge information can be used to refine search systems, in order to provide an extra search layer beyond entities and assertions, dealing with phenomena such as rhetorical intent, speculations, contradictions and negations. This finer grained search functionality can assist in several important tasks, e.g., database curation (by locating new experimental knowledge) and pathway enrichment (by providing information for inference). To allow easy integration into text mining systems, EventMine-MK is provided as a UIMA component that can be used in the interoperable text mining infrastructure, U-Compare.

Breath air measurement using wide-band frequency tuning IR laser photo-acoustic spectroscopy

NASA Astrophysics Data System (ADS)

Kistenev, Yury V.; Borisov, Alexey V.; Kuzmin, Dmitry A.; Bulanova, Anna A.; Boyko, Andrey A.; Kostyukova, Nadezhda Y.; Karapuzikov, Alexey A.

2016-03-01

The results of measuring of biomarkers in breath air of patients with broncho-pulmonary diseases using wide-band frequency tuning IR laser photo-acoustic spectroscopy and the methods of data mining are presented. We will discuss experimental equipment and various methods of intellectual analysis of the experimental spectra in context of above task. The work was carried out with partial financial support of the FCPIR contract No 14.578.21.0082 (ID RFMEFI57814X0082).

Text mining for the biocuration workflow

PubMed Central

Hirschman, Lynette; Burns, Gully A. P. C; Krallinger, Martin; Arighi, Cecilia; Cohen, K. Bretonnel; Valencia, Alfonso; Wu, Cathy H.; Chatr-Aryamontri, Andrew; Dowell, Karen G.; Huala, Eva; Lourenço, Anália; Nash, Robert; Veuthey, Anne-Lise; Wiegers, Thomas; Winter, Andrew G.

2012-01-01

Molecular biology has become heavily dependent on biological knowledge encoded in expert curated biological databases. As the volume of biological literature increases, biocurators need help in keeping up with the literature; (semi-) automated aids for biocuration would seem to be an ideal application for natural language processing and text mining. However, to date, there have been few documented successes for improving biocuration throughput using text mining. Our initial investigations took place for the workshop on ‘Text Mining for the BioCuration Workflow’ at the third International Biocuration Conference (Berlin, 2009). We interviewed biocurators to obtain workflows from eight biological databases. This initial study revealed high-level commonalities, including (i) selection of documents for curation; (ii) indexing of documents with biologically relevant entities (e.g. genes); and (iii) detailed curation of specific relations (e.g. interactions); however, the detailed workflows also showed many variabilities. Following the workshop, we conducted a survey of biocurators. The survey identified biocurator priorities, including the handling of full text indexed with biological entities and support for the identification and prioritization of documents for curation. It also indicated that two-thirds of the biocuration teams had experimented with text mining and almost half were using text mining at that time. Analysis of our interviews and survey provide a set of requirements for the integration of text mining into the biocuration workflow. These can guide the identification of common needs across curated databases and encourage joint experimentation involving biocurators, text mining developers and the larger biomedical research community. PMID:22513129

Text mining for the biocuration workflow.

PubMed

Hirschman, Lynette; Burns, Gully A P C; Krallinger, Martin; Arighi, Cecilia; Cohen, K Bretonnel; Valencia, Alfonso; Wu, Cathy H; Chatr-Aryamontri, Andrew; Dowell, Karen G; Huala, Eva; Lourenço, Anália; Nash, Robert; Veuthey, Anne-Lise; Wiegers, Thomas; Winter, Andrew G

2012-01-01

Molecular biology has become heavily dependent on biological knowledge encoded in expert curated biological databases. As the volume of biological literature increases, biocurators need help in keeping up with the literature; (semi-) automated aids for biocuration would seem to be an ideal application for natural language processing and text mining. However, to date, there have been few documented successes for improving biocuration throughput using text mining. Our initial investigations took place for the workshop on 'Text Mining for the BioCuration Workflow' at the third International Biocuration Conference (Berlin, 2009). We interviewed biocurators to obtain workflows from eight biological databases. This initial study revealed high-level commonalities, including (i) selection of documents for curation; (ii) indexing of documents with biologically relevant entities (e.g. genes); and (iii) detailed curation of specific relations (e.g. interactions); however, the detailed workflows also showed many variabilities. Following the workshop, we conducted a survey of biocurators. The survey identified biocurator priorities, including the handling of full text indexed with biological entities and support for the identification and prioritization of documents for curation. It also indicated that two-thirds of the biocuration teams had experimented with text mining and almost half were using text mining at that time. Analysis of our interviews and survey provide a set of requirements for the integration of text mining into the biocuration workflow. These can guide the identification of common needs across curated databases and encourage joint experimentation involving biocurators, text mining developers and the larger biomedical research community.

[Experimental study on acid mine drainage treatment using mine tailings of Xiangsi Valley, Tongling, China].

PubMed

Zhang, Nan; Chen, Tian-Hu; Zhou, Yue-Fei; Li, Shao-Jie; Jin, Jie; Wang, Yan-Ming

2012-04-01

Mine tailings in Xiangsi Valley, Tongling, China, is a typical skarn-type tailing with high contents of carbonates. This study designed dynamic leaching experiments to investigate the efficiency of this tailing under the acid mine drainage treatment. During 80 d trial period, the physical and chemical properties of influents were fixed and the effluents were monitored. After the trial, the speciation of Fe, Cu and Zn in solid was analyzed. The results showed that during the trial period, pH value maintained above 7.5. Moreover, the concentrations of Cu, Zn, Fe ions in effluents kept below 0.1, 0.4 and 1 mg x L(-1), respectively. In addition, the permeability coefficient of experimental column kept decreasing during the experimental period (from 0.23 cm x s(-1) to 0.10 cm x s(-1)). Five-step sequential extraction method was employed to study the distribution of elements at different depths. The results showed that Cu2+, Zn2+ were removed mainly through sorption and precipitation. This study indicates that Tongling skarn mine tailings have strong acid neutralization as well as heavy metal binding capacities. Therefore, the authors suggest that this mine tailing, which used to be waste, has a potential in AMD control and treatment.

Theoretical and experimental analysis of an equivalent circuit model for the investigation of shallow landmines with acoustic methods

NASA Astrophysics Data System (ADS)

Borgioli, G.; Bulletti, A.; Calzolai, M.; Capineri, L.; Falorni, P.; Masotti, L.; Valentini, S.; Windsor, C.

2007-10-01

Acoustic methods have been recently investigated for the detection of shallow landmines. Some plastic landmines have a flexible case which can made to vibrate by an airborne excitation like a loudspeaker. The soil-mine system shows a resonant behavior which is used as a signature to discriminate from other rigid objects. The mechanical resonance can be detected at the soil surface by a remote sensing systems like a laser interferometer. An equivalent physical model of the mine-soil system has been investigated having the known physical characteristics of mine simulants. The authors designed and built a test-object with known mechanical characteristics (mass, elasticity, damping factor). The model has been characterized in laboratory and the results compared with the classic mass-spring loss oscillator described by Voigt. The vibrations at the soil surface have been measured in various positions with a micro machined accelerometer. The results of the simulations for the acceleration of the soil-mine system agree well with the experiment. The calibrated mine model is useful to investigate the variation of the resonance frequency for various buried depths and to compare the results for different soils in different environmental conditions.

Modeling N Cycling during Succession after Forest Disturbance: an Analysis of N Mining and Retention Hypothesis

NASA Astrophysics Data System (ADS)

Zhou, Z.; Ollinger, S. V.; Ouimette, A.; Lovett, G. M.; Fuss, C. B.; Goodale, C. L.

2017-12-01

Dissolved inorganic nitrogen losses at the Hubbard Brook Experimental Forest (HBEF), New Hampshire, USA, have declined in recent decades, a pattern that counters expectations based on prevailing theory. An unbalanced ecosystem nitrogen (N) budget implies there is a missing component for N sink. Hypotheses to explain this discrepancy include increasing rates of denitrification and accumulation of N in mineral soil pools following N mining by plants. Here, we conducted a modeling analysis fused with field measurements of N cycling, specifically examining the hypothesis relevant to N mining and retention in mineral soils. We included simplified representations of both mechanisms, N mining and retention, in a revised ecosystem process model, PnET-SOM, to evaluate the dynamics of N cycling during succession after forest disturbance at the HBEF. The predicted N mining during the early succession was regulated by a metric representing a potential demand of extra soil N for large wood growth. The accumulation of nitrate in mineral soil pools was a function of the net aboveground biomass accumulation and soil N availability and parameterized based on field 15N tracer incubation data. The predicted patterns of forest N dynamics were consistent with observations. The addition of the new algorithms also improved the predicted DIN export in stream water with an R squared of 0.35 (P<0.01) aganist observations. Predicted mining processes had an average rate of 7.4 kgNha-1yr-1 and Predicted rates of N retention processes were 5.2 kgNha-1yr-1, both of which were in line with estimates only based on field data. The predicted trend of low DIN export could continue for another 70 years to pay back the mined N in mineral soils. Predicted ecosystem N balance showed that N gas loss could account for 14-46% of the total N deposition, the soil mining about 103% during the early succession, and soil retention about 35% at the current forest stage at the HBEF.

Experimental investigation on the infrared refraction and extinction properties of rock dust in tunneling face of coal mine.

PubMed

Wang, Wenzheng; Wang, Yanming; Shi, Guoqing

2015-12-10

Comprehensive experimental research on the fundamental optical properties of dust pollution in a coal mine is presented. Rock dust generated in a tunneling roadway was sampled and the spectral complex refractive index within an infrared range of 2.5-25 μm was obtained by Fourier transform infrared spectroscopy measurement and Kramers-Kronig relation. Experimental results were validated to be consistent with equivalent optical constants simulated by effective medium theory based on component analysis of x-ray fluorescence, which illustrates that the top three mineral components are SiO2 (62.06%), Al2O3 (21.26%), and Fe2O3 (4.27%). The complex refractive index and the spatial distribution tested by a filter dust and particle size analyzer were involved in the simulation of extinction properties of rock dust along the tunneling roadway solved by the discrete ordinates method and Mie scattering model. The compared results illustrate that transmission is obviously enhanced with the increase of height from the floor but weakened with increasing horizontal distance from the air duct.

Integrated pathway-based transcription regulation network mining and visualization based on gene expression profiles.

PubMed

Kibinge, Nelson; Ono, Naoaki; Horie, Masafumi; Sato, Tetsuo; Sugiura, Tadao; Altaf-Ul-Amin, Md; Saito, Akira; Kanaya, Shigehiko

2016-06-01

Conventionally, workflows examining transcription regulation networks from gene expression data involve distinct analytical steps. There is a need for pipelines that unify data mining and inference deduction into a singular framework to enhance interpretation and hypotheses generation. We propose a workflow that merges network construction with gene expression data mining focusing on regulation processes in the context of transcription factor driven gene regulation. The pipeline implements pathway-based modularization of expression profiles into functional units to improve biological interpretation. The integrated workflow was implemented as a web application software (TransReguloNet) with functions that enable pathway visualization and comparison of transcription factor activity between sample conditions defined in the experimental design. The pipeline merges differential expression, network construction, pathway-based abstraction, clustering and visualization. The framework was applied in analysis of actual expression datasets related to lung, breast and prostrate cancer. Copyright © 2016 Elsevier Inc. All rights reserved.

Mining biomedical images towards valuable information retrieval in biomedical and life sciences.

PubMed

Ahmed, Zeeshan; Zeeshan, Saman; Dandekar, Thomas

2016-01-01

Biomedical images are helpful sources for the scientists and practitioners in drawing significant hypotheses, exemplifying approaches and describing experimental results in published biomedical literature. In last decades, there has been an enormous increase in the amount of heterogeneous biomedical image production and publication, which results in a need for bioimaging platforms for feature extraction and analysis of text and content in biomedical images to take advantage in implementing effective information retrieval systems. In this review, we summarize technologies related to data mining of figures. We describe and compare the potential of different approaches in terms of their developmental aspects, used methodologies, produced results, achieved accuracies and limitations. Our comparative conclusions include current challenges for bioimaging software with selective image mining, embedded text extraction and processing of complex natural language queries. © The Author(s) 2016. Published by Oxford University Press.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mattes, R.H.; Bacho, A.; Wade, L.V.

The Lake Lynn Laboratory is a multipurpose mining research laboratory operated by the Bureau of Mines and located in Fairchance, Pa. It consists of both surface and underground facilities. The initial focus of the facility, scheduled for full operation in fall 1982, will be on the problems of fires and explosions in mines. The initial experimental explosion was fired on March 3, 1982. The intent of this document is to provide the reader with detailed information on the physical capabilities of the Lake Lynn Laboratory. Subsequent publications will focus on the capabilities of Lake Lynn as compared with those ofmore » other similar facilities worldwide, and a comparison of initial explosion test results realized at Lake Lynn and comparable results from the Bruceton Experimental Mines.« less

Impact of epidermal leaf mining by the aspen leaf miner (Phyllocnistis populiella) on the growth, physiology, and leaf longevity of quaking aspen

Treesearch

Diane Wagner; Linda DeFoliart; Patricia Doak; Jenny Schneiderheinze

2008-01-01

We studied the effect of epidermal mining on aspen growth and physiology during an outbreak of Phyllocnistis populiella in the boreal forest of interior Alaska. Experimental reduction of leaf miner density across two sites and 3 years significantly increased annual apsen growth rates relative to naturally mined controls. Leaf mining damage was...

Differentially Private Frequent Subgraph Mining

PubMed Central

Xu, Shengzhi; Xiong, Li; Cheng, Xiang; Xiao, Ke

2016-01-01

Mining frequent subgraphs from a collection of input graphs is an important topic in data mining research. However, if the input graphs contain sensitive information, releasing frequent subgraphs may pose considerable threats to individual's privacy. In this paper, we study the problem of frequent subgraph mining (FGM) under the rigorous differential privacy model. We introduce a novel differentially private FGM algorithm, which is referred to as DFG. In this algorithm, we first privately identify frequent subgraphs from input graphs, and then compute the noisy support of each identified frequent subgraph. In particular, to privately identify frequent subgraphs, we present a frequent subgraph identification approach which can improve the utility of frequent subgraph identifications through candidates pruning. Moreover, to compute the noisy support of each identified frequent subgraph, we devise a lattice-based noisy support derivation approach, where a series of methods has been proposed to improve the accuracy of the noisy supports. Through formal privacy analysis, we prove that our DFG algorithm satisfies ε-differential privacy. Extensive experimental results on real datasets show that the DFG algorithm can privately find frequent subgraphs with high data utility. PMID:27616876

Long Term Analysis of Deformations in Salt Mines: Kłodawa Salt Mine Case Study, Central Poland

NASA Astrophysics Data System (ADS)

Cała, Marek; Tajduś, Antoni; Andrusikiewicz, Wacław; Kowalski, Michał; Kolano, Malwina; Stopkowicz, Agnieszka; Cyran, Katarzyna; Jakóbczyk, Joanna

2017-09-01

Located in central Poland, the Kłodawa salt dome is 26 km long and about 2 km wide. Exploitation of the dome started in 1956, currently rock salt extraction is carried out in 7 mining fields and the 12 mining levels at the depth from 322 to 625 meters below sea level (m.b.s.l.). It is planned to maintain the mining activity till 2052 and extend rock salt extraction to deeper levels. The dome is characterised by complex geological structure resulted from halokinetic and tectonic processes. Projection of the 3D numerical analysis took into account the following factors: mine working distribution within the Kłodawa mine (about 1000 rooms, 350 km of galleries), complex geological structure of the salt dome, complicated structure and geometry of mine workings and distinction in rocks mechanical properties e.g. rock salt and anhydrite. Analysis of past mine workings deformation and prediction of future rock mass behaviour was divided into four stages: building of the 3D model (state of mine workings in year 2014), model extension of the future mine workings planned for extraction in years 2015-2052, the 3D model calibration and stability analysis of all mine workings. The 3D numerical model of Kłodawa salt mine included extracted and planned mine workings in 7 mining fields and 14 mining levels (about 2000 mine workings). The dimensions of the model were 4200 m × 4700 m × 1200 m what was simulated by 33 million elements. The 3D model was calibrated on the grounds of convergence measurements and laboratory tests. Stability assessment of mine workings was based on analysis of the strength/stress ratio and vertical stress. The strength/stress ratio analysis enabled to indicate endangered area in mine workings and can be defined as the factor of safety. Mine workings in state close to collapse are indicated by the strength/stress ratio equals 1. Analysis of the vertical stress in mine workings produced the estimation of current state of stress in comparison to initial (pre-mining) conditions. The long-term deformation analysis of the Kłodawa salt mine for year 2014 revealed that stability conditions were fulfilled. Local disturbances indicated in the numerical analysis were connected with high chambers included in the mining field no 1 and complex geological structure in the vicinity of mine workings located in the mining fields no 2 and 3. Moreover, numerical simulations that projected the future extraction progress (till year 2052) showed positive performance. Local weakness zones in the mining field no 7 are associated with occurrence of carnallite layers and intensive mining which are planned in the mining field no 6 at the end of rock salt extraction.

Managing biological networks by using text mining and computer-aided curation

NASA Astrophysics Data System (ADS)

Yu, Seok Jong; Cho, Yongseong; Lee, Min-Ho; Lim, Jongtae; Yoo, Jaesoo

2015-11-01

In order to understand a biological mechanism in a cell, a researcher should collect a huge number of protein interactions with experimental data from experiments and the literature. Text mining systems that extract biological interactions from papers have been used to construct biological networks for a few decades. Even though the text mining of literature is necessary to construct a biological network, few systems with a text mining tool are available for biologists who want to construct their own biological networks. We have developed a biological network construction system called BioKnowledge Viewer that can generate a biological interaction network by using a text mining tool and biological taggers. It also Boolean simulation software to provide a biological modeling system to simulate the model that is made with the text mining tool. A user can download PubMed articles and construct a biological network by using the Multi-level Knowledge Emergence Model (KMEM), MetaMap, and A Biomedical Named Entity Recognizer (ABNER) as a text mining tool. To evaluate the system, we constructed an aging-related biological network that consist 9,415 nodes (genes) by using manual curation. With network analysis, we found that several genes, including JNK, AP-1, and BCL-2, were highly related in aging biological network. We provide a semi-automatic curation environment so that users can obtain a graph database for managing text mining results that are generated in the server system and can navigate the network with BioKnowledge Viewer, which is freely available at http://bioknowledgeviewer.kisti.re.kr.

Contribution of soil fauna to soil functioning in degraded environments: a multidisciplinary approach

NASA Astrophysics Data System (ADS)

Gargiulo, Laura; Mele, Giacomo; Moradi, Jabbar; Kukla, Jaroslav; Jandová, Kateřina; Frouz, Jan

2016-04-01

The restoration of the soil functions is essential for the recovery of highly degraded sites and, consequently, the study of the soil fauna role in the soil development in such environments has great potential from a practical point of view. The soils of the post-mining sites represent unique models for the study of the natural ecological succession because mining creates similar environments characterized by the same substrate, but by different ages according to the year of closure of mines. The aim of this work was to assess the contribution of different species of macrofauna on the evolution of soil structure and on the composition and activity of the microbial community in soil samples subjected to ecological restoration or characterized by spontaneous ecological succession. For this purpose, an experimental test was carried out in two sites characterized by different post-mining conditions: 1) natural succession, 2) reclamation with planting trees. These sites are located in the post-mining area of Sokolov (Czech Republic). For the experimental test repacked soil cores were prepared in laboratory with sieved soil sampled from the two sites. The soil cores were prepared maintaining the sequence of soil horizons present in the field. These samples were inoculated separately with two genera of earthworms (Lumbricus and Aporrectodea) and two of centipedes (Julida and Polydesmus). In particular, based on their body size, were inoculated for each cylinder 2 individuals of millipedes, 1 individual of Lumbricus and 4 individuals of Aporrectodea. For each treatment and for control samples 5 replicates were prepared and all samples were incubated in field for 1 month in the two original sampling sites. After the incubation the samples were removed from the field and transported in laboratory in order to perform the analysis of microbial respiration, of PLFA (phospholipid-derived fatty acids) and ergosterol contents and finally for the characterization of soil structure. All replicates were subjected to soil respiration measurement by means of chemical titration method. Then some replicates were destructively analyzed for PLFA and ergosterol and others were used for the 3D soil image analysis of the soil pore system. The soil cores were imaged using X-ray microtomography and three-dimensional image processing was performed in order to obtain 3D reconstructions and preliminary analysis of the identified biopores. The experimental approach used in this multidisciplinary study showed a promising potential to provide new useful information about the widely differentiated contribution of many types of macrofauna to the formation of the soil pore system and to the development of the soil microbial functions in different types of environments.

Intermittent gravity-driven flow of grains through narrow pipes

NASA Astrophysics Data System (ADS)

Alvarez, Carlos A.; de Moraes Franklin, Erick

2017-01-01

Grain flows through pipes are frequently found in various settings, such as in pharmaceutical, chemical, petroleum, mining and food industries. In the case of size-constrained gravitational flows, density waves consisting of alternating high- and low-compactness regions may appear. This study investigates experimentally the dynamics of density waves that appear in gravitational flows of fine grains through vertical and slightly inclined pipes. The experimental device consisted of a transparent glass pipe through which different populations of glass spheres flowed driven by gravity. Our experiments were performed under controlled ambient temperature and relative humidity, and the granular flow was filmed with a high-speed camera. Experimental results concerning the length scales and celerities of density waves are presented, together with a one-dimensional model and a linear stability analysis. The analysis exhibits the presence of a long-wavelength instability, with the most unstable mode and a cut-off wavenumber whose values are in agreement with the experimental results.

Text Mining for Neuroscience

NASA Astrophysics Data System (ADS)

Tirupattur, Naveen; Lapish, Christopher C.; Mukhopadhyay, Snehasis

2011-06-01

Text mining, sometimes alternately referred to as text analytics, refers to the process of extracting high-quality knowledge from the analysis of textual data. Text mining has wide variety of applications in areas such as biomedical science, news analysis, and homeland security. In this paper, we describe an approach and some relatively small-scale experiments which apply text mining to neuroscience research literature to find novel associations among a diverse set of entities. Neuroscience is a discipline which encompasses an exceptionally wide range of experimental approaches and rapidly growing interest. This combination results in an overwhelmingly large and often diffuse literature which makes a comprehensive synthesis difficult. Understanding the relations or associations among the entities appearing in the literature not only improves the researchers current understanding of recent advances in their field, but also provides an important computational tool to formulate novel hypotheses and thereby assist in scientific discoveries. We describe a methodology to automatically mine the literature and form novel associations through direct analysis of published texts. The method first retrieves a set of documents from databases such as PubMed using a set of relevant domain terms. In the current study these terms yielded a set of documents ranging from 160,909 to 367,214 documents. Each document is then represented in a numerical vector form from which an Association Graph is computed which represents relationships between all pairs of domain terms, based on co-occurrence. Association graphs can then be subjected to various graph theoretic algorithms such as transitive closure and cycle (circuit) detection to derive additional information, and can also be visually presented to a human researcher for understanding. In this paper, we present three relatively small-scale problem-specific case studies to demonstrate that such an approach is very successful in replicating a neuroscience expert's mental model of object-object associations entirely by means of text mining. These preliminary results provide the confidence that this type of text mining based research approach provides an extremely powerful tool to better understand the literature and drive novel discovery for the neuroscience community.

Reverse engineering biomolecular systems using -omic data: challenges, progress and opportunities.

PubMed

Quo, Chang F; Kaddi, Chanchala; Phan, John H; Zollanvari, Amin; Xu, Mingqing; Wang, May D; Alterovitz, Gil

2012-07-01

Recent advances in high-throughput biotechnologies have led to the rapid growing research interest in reverse engineering of biomolecular systems (REBMS). 'Data-driven' approaches, i.e. data mining, can be used to extract patterns from large volumes of biochemical data at molecular-level resolution while 'design-driven' approaches, i.e. systems modeling, can be used to simulate emergent system properties. Consequently, both data- and design-driven approaches applied to -omic data may lead to novel insights in reverse engineering biological systems that could not be expected before using low-throughput platforms. However, there exist several challenges in this fast growing field of reverse engineering biomolecular systems: (i) to integrate heterogeneous biochemical data for data mining, (ii) to combine top-down and bottom-up approaches for systems modeling and (iii) to validate system models experimentally. In addition to reviewing progress made by the community and opportunities encountered in addressing these challenges, we explore the emerging field of synthetic biology, which is an exciting approach to validate and analyze theoretical system models directly through experimental synthesis, i.e. analysis-by-synthesis. The ultimate goal is to address the present and future challenges in reverse engineering biomolecular systems (REBMS) using integrated workflow of data mining, systems modeling and synthetic biology.

Systematic review of community health impacts of mountaintop removal mining.

PubMed

Boyles, Abee L; Blain, Robyn B; Rochester, Johanna R; Avanasi, Raghavendhran; Goldhaber, Susan B; McComb, Sofie; Holmgren, Stephanie D; Masten, Scott A; Thayer, Kristina A

2017-10-01

The objective of this evaluation is to understand the human health impacts of mountaintop removal (MTR) mining, the major method of coal mining in and around Central Appalachia. MTR mining impacts the air, water, and soil and raises concerns about potential adverse health effects in neighboring communities; exposures associated with MTR mining include particulate matter (PM), polycyclic aromatic hydrocarbons (PAHs), metals, hydrogen sulfide, and other recognized harmful substances. A systematic review was conducted of published studies of MTR mining and community health, occupational studies of MTR mining, and any available animal and in vitro experimental studies investigating the effects of exposures to MTR-mining-related chemical mixtures. Six databases (Embase, PsycINFO, PubMed, Scopus, Toxline, and Web of Science) were searched with customized terms, and no restrictions on publication year or language, through October 27, 2016. The eligibility criteria included all human population studies and animal models of human health, direct and indirect measures of MTR-mining exposure, any health-related effect or change in physiological response, and any study design type. Risk of bias was assessed for observational and experimental studies using an approach developed by the National Toxicology Program (NTP) Office of Health Assessment and Translation (OHAT). To provide context for these health effects, a summary of the exposure literature is included that focuses on describing findings for outdoor air, indoor air, and drinking water. From a literature search capturing 3088 studies, 33 human studies (29 community, four occupational), four experimental studies (two in rat, one in vitro and in mice, one in C. elegans), and 58 MTR mining exposure studies were identified. A number of health findings were reported in observational human studies, including cardiopulmonary effects, mortality, and birth defects. However, concerns for risk of bias were identified, especially with respect to exposure characterization, accounting for confounding variables (such as socioeconomic status), and methods used to assess health outcomes. Typically, exposure was assessed by proximity of residence or hospital to coal mining or production level at the county level. In addition, assessing the consistency of findings was challenging because separate publications likely included overlapping case and comparison groups. For example, 11 studies of mortality were conducted with most reporting higher rates associated with coal mining, but many of these relied on the same national datasets and were unable to consider individual-level contributors to mortality such as poor socioeconomic status or smoking. Two studies of adult rats reported impaired microvascular and cardiac mitochondrial function after intratracheal exposure to PM from MTR-mining sites. Exposures associated with MTR mining included reports of PM levels that sometimes exceeded Environmental Protection Agency (EPA) standards; higher levels of dust, trace metals, hydrogen sulfide gas; and a report of increased public drinking water violations. This systematic review could not reach conclusions on community health effects of MTR mining because of the strong potential for bias in the current body of human literature. Improved characterization of exposures by future community health studies and further study of the effects of MTR mining chemical mixtures in experimental models will be critical to determining health risks of MTR mining to communities. Without such work, uncertainty will remain regarding the impact of these practices on the health of the people who breathe the air and drink the water affected by MTR mining. Published by Elsevier Ltd.

30 CFR 785.13 - Experimental practices mining.

Code of Federal Regulations, 2012 CFR

2012-07-01

... practice shall contain descriptions, maps, plans, and data which show— (1) The nature of the experimental....S. Department of Agriculture, Soil Conservation Service. (f) Each person undertaking an experimental...

30 CFR 785.13 - Experimental practices mining.

Code of Federal Regulations, 2014 CFR

2014-07-01

... practice shall contain descriptions, maps, plans, and data which show— (1) The nature of the experimental....S. Department of Agriculture, Soil Conservation Service. (f) Each person undertaking an experimental...

30 CFR 785.13 - Experimental practices mining.

Code of Federal Regulations, 2013 CFR

2013-07-01

... practice shall contain descriptions, maps, plans, and data which show— (1) The nature of the experimental....S. Department of Agriculture, Soil Conservation Service. (f) Each person undertaking an experimental...

An Empirical Model for Mine-Blast Loading

DTIC Science & Technology

2014-10-17

fledged experimental program. The numerical approach however suffers from several drawbacks in the mine blast simulations. First, it is a very...Suffield consisted in a pendulum type device to measure global impulse of buried mine [15]. One of the main purposes of the ONAGER pendulum was to study...TP-1 Terminal effects, KTA 1-34 report, 2004. [15] Bues, R., Hlady, S.L. and Bergeron, D.M., Pendulum Measurement of Land Mine Blast Output, Volume

Strip mine reclamation: criteria and methods for measurement of revegetation success. Progress report, April 1, 1980-March 31, 1981

DOE Office of Scientific and Technical Information (OSTI.GOV)

Carrel, J.E.; Kucera, C.L.; Johannsen, C.J.

1980-12-01

During this contract period research was continued at finding suitable methods and criteria for determining the success of revegetation in Midwestern prime ag lands strip mined for coal. Particularly important to the experimental design was the concept of reference areas, which were nearby fields from which the performance standards for reclaimed areas were derived. Direct and remote sensing techniques for measuring plant ground cover, production, and species composition were tested. 15 mine sites were worked in which were permitted under interim permanent surface mine regulations and in 4 adjoining reference sites. Studies at 9 prelaw sites were continued. All sitesmore » were either in Missouri or Illinois. Data gathered in the 1980 growing season showed that 13 unmanaged or young mineland pastures generally had lower average ground cover and production than 2 reference pastures. In contrast, yields at approximately 40% of 11 recently reclaimed mine sites planted with winter wheat, soybeans, or milo were statistically similar to 3 reference values. Digital computer image analysis of color infrared aerial photographs, when compared to ground level measurements, was a fast, accurate, and inexpensive way to determine plant ground cover and areas. But the remote sensing approach was inferior to standard surface methods for detailing plant species abundance and composition.« less

Development of Test Rig for Robotization of Mining Technological Processes - Oversized Rock Breaking Process Case

NASA Astrophysics Data System (ADS)

Pawel, Stefaniak; Jacek, Wodecki; Jakubiak, Janusz; Zimroz, Radoslaw

2017-12-01

Production chain (PCh) in underground copper ore mine consists of several subprocesses. From our perspective implementation of so called ZEPA approach (Zero Entry Production Area) might be very interesting [16]. In practice, it leads to automation/robotization of subprocesses in production area. In this paper was investigated a specific part of PCh i.e. a place when cyclic transport by LHDs is replaced with continuous transport by conveying system. Such place is called dumping point. The objective of dumping points with screen is primary classification of the material (into coarse and fine material) and breaking oversized rocks with hydraulic hammer. Current challenges for the underground mining include e.g. safety improvement as well as production optimization related to bottlenecks, stoppages and operational efficiency of the machines. As a first step, remote control of the hydraulic hammer has been introduced, which not only transferred the operator to safe workplace, but also allowed for more comfortable work environment and control over multiple technical objects by a single person. Today literature analysis shows that current mining industry around the world is oriented to automation and robotization of mining processes and reveals technological readiness for 4th industrial revolution. The paper is focused on preliminary analysis of possibilities for the use of the robotic system to rock-breaking process. Prototype test rig has been proposed and experimental works have been carried out. Automatic algorithms for detection of oversized rocks, crushing them as well as sweeping and loosening of material have been formulated. Obviously many simplifications have been assumed. Some near future works have been proposed.

78 FR 2893 - Endangered and Threatened Species: Designation of a Nonessential Experimental Population for...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-01-15

..., agricultural diversions, road construction and maintenance, mining, and urban and rural development. Factors..., agriculture, mining, and urbanization have eliminated, degraded, simplified, and fragmented habitat...

Second-year results of hybrid poplar test plantings on bituminous strip-mine spoils in Pennsylvania

Treesearch

Grant Davis

1964-01-01

During the period 1946-49, The Pennsylvania State University established 22 experimental plantings of trees and shrubs on strip-mine spoil banks in the Bituminous Region of Pennsylvania to determine which species were best suited for revegetating such sites. When 10-year growth on the experimental plots was evaluated, a clone of hybrid poplar was found to have outgrown...

Working with Data: Discovering Knowledge through Mining and Analysis; Systematic Knowledge Management and Knowledge Discovery; Text Mining; Methodological Approach in Discovering User Search Patterns through Web Log Analysis; Knowledge Discovery in Databases Using Formal Concept Analysis; Knowledge Discovery with a Little Perspective.

ERIC Educational Resources Information Center

Qin, Jian; Jurisica, Igor; Liddy, Elizabeth D.; Jansen, Bernard J; Spink, Amanda; Priss, Uta; Norton, Melanie J.

2000-01-01

These six articles discuss knowledge discovery in databases (KDD). Topics include data mining; knowledge management systems; applications of knowledge discovery; text and Web mining; text mining and information retrieval; user search patterns through Web log analysis; concept analysis; data collection; and data structure inconsistency. (LRW)

Finding Relevant Parameters for the Thin-film Photovoltaic Cells Production Process with the Application of Data Mining Methods.

PubMed

Ulaczyk, Jan; Morawiec, Krzysztof; Zabierowski, Paweł; Drobiazg, Tomasz; Barreau, Nicolas

2017-09-01

A data mining approach is proposed as a useful tool for the control parameters analysis of the 3-stage CIGSe photovoltaic cell production process, in order to find variables that are the most relevant for cell electric parameters and efficiency. The analysed data set consists of stage duration times, heater power values as well as temperatures for the element sources and the substrate - there are 14 variables per sample in total. The most relevant variables of the process have been found based on the so-called random forest analysis with the application of the Boruta algorithm. 118 CIGSe samples, prepared at Institut des Matériaux Jean Rouxel, were analysed. The results are close to experimental knowledge on the CIGSe cells production process. They bring new evidence to production parameters of new cells and further research. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

CFD analysis on gas distribution for different scrubber redirection configurations in sump cut.

PubMed

Zheng, Y; Organiscak, J A; Zhou, L; Beck, T W; Rider, J P

2015-01-01

The National Institute for Occupational Safety and Health's Office of Mine Safety and Health Research recently developed a series of models using computational fluid dynamics (CFD) to study the gas distribution around a continuous mining machine with various fan-powered flooded bed scrubber discharge configurations. CFD models using Species Transport Model without reactions in FLUENT were constructed to evaluate the redirection of scrubber discharge toward the mining face rather than behind the return curtain. The following scenarios are considered in this study: 100 percent of the discharge redirected back toward the face on the off-curtain side of the continuous miner; 100 percent of the discharge redirected back toward the face, but divided equally to both sides of the machine; and 15 percent of the discharge redirected toward the face on the off-curtain side of the machine, with 85 percent directed into the return. These models were compared against a model with a conventional scrubber discharge, where air is directed away from the face into the return. The CFD models were calibrated and validated based on experimental data and accurately predicted sulfur hexafluoride (SF 6 ) gas levels at four gas monitoring locations. One additional prediction model was simulated to consider a different scrubber discharge angle for the 100 percent redirected, equally divided case. These models identified relatively high gassy areas around the continuous miner, which may not warrant their use in coal mines with medium to high methane liberation rates. This paper describes the methodology used to develop the CFD models, and the validation of the models based on experimental data.

Experimental evaluation of the drag coefficient for smooth spheres by free fall experiments in old mines

NASA Astrophysics Data System (ADS)

Maroto, J. A.; Dueñas-Molina, J.; de Dios, J.

2005-05-01

Mines of Linares, Jaén, Spain, have been exploited from the age of the Phoenicians, Carthaginians and Romans. These silver and lead mines reached their maximum splendour at the end of the 19th century and at the beginning of the 20th century. Nevertheless, all the mining works finished in the 1970s and the diverse machinery was sold. Only the shafts remain since then which has now permitted carrying out interesting free fall experiments using smooth spheres of both cork and cast iron. The experiments were facilitated by the fact that the tubular shape of the shafts provides excellent transmission of sound, which made feasible the recording of the impact sound of the spheres with water at the bottom of the shafts at distances of up to 200 m. By using these experimental data, we have carried out an evaluation of the drag coefficient for the movement of smooth spheres through the air in the laminar regime with Reynolds number in the interval 103 to 2 × 105. This evaluation was in excellent agreement with the literature data. From the theoretical point of view, the analysis of the free fall movement includes a variety of concepts such as Newton's second law, the drag force, Archimedes principle and the velocity of sound, which makes these experiments very attractive for both physics teachers and physics students at university level. Finally, an easy experiment is proposed in this paper which has permitted an approximate evaluation of the drag coefficient for smooth spheres to be carried out in a laboratory environment.

Comparative Characterization of Crofelemer Samples Using Data Mining and Machine Learning Approaches With Analytical Stability Data Sets.

PubMed

Nariya, Maulik K; Kim, Jae Hyun; Xiong, Jian; Kleindl, Peter A; Hewarathna, Asha; Fisher, Adam C; Joshi, Sangeeta B; Schöneich, Christian; Forrest, M Laird; Middaugh, C Russell; Volkin, David B; Deeds, Eric J

2017-11-01

There is growing interest in generating physicochemical and biological analytical data sets to compare complex mixture drugs, for example, products from different manufacturers. In this work, we compare various crofelemer samples prepared from a single lot by filtration with varying molecular weight cutoffs combined with incubation for different times at different temperatures. The 2 preceding articles describe experimental data sets generated from analytical characterization of fractionated and degraded crofelemer samples. In this work, we use data mining techniques such as principal component analysis and mutual information scores to help visualize the data and determine discriminatory regions within these large data sets. The mutual information score identifies chemical signatures that differentiate crofelemer samples. These signatures, in many cases, would likely be missed by traditional data analysis tools. We also found that supervised learning classifiers robustly discriminate samples with around 99% classification accuracy, indicating that mathematical models of these physicochemical data sets are capable of identifying even subtle differences in crofelemer samples. Data mining and machine learning techniques can thus identify fingerprint-type attributes of complex mixture drugs that may be used for comparative characterization of products. Copyright © 2017 American Pharmacists Association®. All rights reserved.

Biodiversity of freshwater diatom communities during 1000 years of metal mining, land use, and climate change in central Sweden.

PubMed

De Laender, F; Verschuren, D; Bindler, R; Thas, O; Janssen, C R

2012-08-21

We subjected a unique set of high-quality paleoecological data to statistical modeling to examine if the biological richness and evenness of freshwater diatom communities in the Falun area, a historical copper (Cu) mining region in central Sweden, was negatively influenced by 1000 years of metal exposure. Contrary to ecotoxicological predictions, we found no negative relation between biodiversity and the sedimentary concentrations of eight metals. Strikingly, our analysis listed metals (Co, Fe, Cu, Zn, Cd, Pb) or the fractional land cover of cultivated crops, meadow, and herbs indicating land disturbance as potentially promoting biodiversity. However, correlation between metal- and land-cover trends prevented concluding which of these two covariate types positively affected biodiversity. Because historical aqueous metal concentrations--inferred from solid-water partitioning--approached experimental toxicity thresholds for freshwater algae, positive effects of metal mining on biodiversity are unlikely. Instead, the positive relationship between biodiversity and historical land-cover change can be explained by the increasing proportion of opportunistic species when anthropogenic disturbance intensifies. Our analysis illustrates that focusing on the direct toxic effects of metals alone may yield inaccurate environmental assessments on time scales relevant for biodiversity conservation.

Gene prioritization and clustering by multi-view text mining

PubMed Central

2010-01-01

Background Text mining has become a useful tool for biologists trying to understand the genetics of diseases. In particular, it can help identify the most interesting candidate genes for a disease for further experimental analysis. Many text mining approaches have been introduced, but the effect of disease-gene identification varies in different text mining models. Thus, the idea of incorporating more text mining models may be beneficial to obtain more refined and accurate knowledge. However, how to effectively combine these models still remains a challenging question in machine learning. In particular, it is a non-trivial issue to guarantee that the integrated model performs better than the best individual model. Results We present a multi-view approach to retrieve biomedical knowledge using different controlled vocabularies. These controlled vocabularies are selected on the basis of nine well-known bio-ontologies and are applied to index the vast amounts of gene-based free-text information available in the MEDLINE repository. The text mining result specified by a vocabulary is considered as a view and the obtained multiple views are integrated by multi-source learning algorithms. We investigate the effect of integration in two fundamental computational disease gene identification tasks: gene prioritization and gene clustering. The performance of the proposed approach is systematically evaluated and compared on real benchmark data sets. In both tasks, the multi-view approach demonstrates significantly better performance than other comparing methods. Conclusions In practical research, the relevance of specific vocabulary pertaining to the task is usually unknown. In such case, multi-view text mining is a superior and promising strategy for text-based disease gene identification. PMID:20074336

Data Mining and Machine Learning Tools for Combinatorial Material Science of All-Oxide Photovoltaic Cells.

PubMed

Yosipof, Abraham; Nahum, Oren E; Anderson, Assaf Y; Barad, Hannah-Noa; Zaban, Arie; Senderowitz, Hanoch

2015-06-01

Growth in energy demands, coupled with the need for clean energy, are likely to make solar cells an important part of future energy resources. In particular, cells entirely made of metal oxides (MOs) have the potential to provide clean and affordable energy if their power conversion efficiencies are improved. Such improvements require the development of new MOs which could benefit from combining combinatorial material sciences for producing solar cells libraries with data mining tools to direct synthesis efforts. In this work we developed a data mining workflow and applied it to the analysis of two recently reported solar cell libraries based on Titanium and Copper oxides. Our results demonstrate that QSAR models with good prediction statistics for multiple solar cells properties could be developed and that these models highlight important factors affecting these properties in accord with experimental findings. The resulting models are therefore suitable for designing better solar cells. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Prediction of customer behaviour analysis using classification algorithms

NASA Astrophysics Data System (ADS)

Raju, Siva Subramanian; Dhandayudam, Prabha

2018-04-01

Customer Relationship management plays a crucial role in analyzing of customer behavior patterns and their values with an enterprise. Analyzing of customer data can be efficient performed using various data mining techniques, with the goal of developing business strategies and to enhance the business. In this paper, three classification models (NB, J48, and MLPNN) are studied and evaluated for our experimental purpose. The performance measures of the three classifications are compared using three different parameters (accuracy, sensitivity, specificity) and experimental results expose J48 algorithm has better accuracy with compare to NB and MLPNN algorithm.

Experimental Study on Comprehensive Performance of Full Tailings Paste Filling in Jiaojia Gold Mine.

NASA Astrophysics Data System (ADS)

Zhang, Z. H.; Zou, Q. B.; Wang, P. Z.

2017-11-01

Filling mining method is the main method of modern underground mining. High concentration cementation is carried out using coarse tailing of +37 μm, and the mine has maturely used classified tailings paste filling technology. The gold mine studied on the performance of full tailings paste filling in order to maximize the use of tailings, reduce -37 μm fine tailings discharged into the tailing pond, reduce mining cost and eliminate security risks. The results show that: comprehensive index of full tailings paste filling is higher than that of classified tailings high concentration cementation filling, and the full tailings paste filling of 76% mass concentration has the best comprehensive index of slump, expansibility, yield stress and viscosity to meet the mining method requirements, which can effectively reduce the mining loss rate and dilution rate.

Preference Mining Using Neighborhood Rough Set Model on Two Universes.

PubMed

Zeng, Kai

2016-01-01

Preference mining plays an important role in e-commerce and video websites for enhancing user satisfaction and loyalty. Some classical methods are not available for the cold-start problem when the user or the item is new. In this paper, we propose a new model, called parametric neighborhood rough set on two universes (NRSTU), to describe the user and item data structures. Furthermore, the neighborhood lower approximation operator is used for defining the preference rules. Then, we provide the means for recommending items to users by using these rules. Finally, we give an experimental example to show the details of NRSTU-based preference mining for cold-start problem. The parameters of the model are also discussed. The experimental results show that the proposed method presents an effective solution for preference mining. In particular, NRSTU improves the recommendation accuracy by about 19% compared to the traditional method.

Genomics Portals: integrative web-platform for mining genomics data.

PubMed

Shinde, Kaustubh; Phatak, Mukta; Johannes, Freudenberg M; Chen, Jing; Li, Qian; Vineet, Joshi K; Hu, Zhen; Ghosh, Krishnendu; Meller, Jaroslaw; Medvedovic, Mario

2010-01-13

A large amount of experimental data generated by modern high-throughput technologies is available through various public repositories. Our knowledge about molecular interaction networks, functional biological pathways and transcriptional regulatory modules is rapidly expanding, and is being organized in lists of functionally related genes. Jointly, these two sources of information hold a tremendous potential for gaining new insights into functioning of living systems. Genomics Portals platform integrates access to an extensive knowledge base and a large database of human, mouse, and rat genomics data with basic analytical visualization tools. It provides the context for analyzing and interpreting new experimental data and the tool for effective mining of a large number of publicly available genomics datasets stored in the back-end databases. The uniqueness of this platform lies in the volume and the diversity of genomics data that can be accessed and analyzed (gene expression, ChIP-chip, ChIP-seq, epigenomics, computationally predicted binding sites, etc), and the integration with an extensive knowledge base that can be used in such analysis. The integrated access to primary genomics data, functional knowledge and analytical tools makes Genomics Portals platform a unique tool for interpreting results of new genomics experiments and for mining the vast amount of data stored in the Genomics Portals backend databases. Genomics Portals can be accessed and used freely at http://GenomicsPortals.org.

Genomics Portals: integrative web-platform for mining genomics data

PubMed Central

2010-01-01

Background A large amount of experimental data generated by modern high-throughput technologies is available through various public repositories. Our knowledge about molecular interaction networks, functional biological pathways and transcriptional regulatory modules is rapidly expanding, and is being organized in lists of functionally related genes. Jointly, these two sources of information hold a tremendous potential for gaining new insights into functioning of living systems. Results Genomics Portals platform integrates access to an extensive knowledge base and a large database of human, mouse, and rat genomics data with basic analytical visualization tools. It provides the context for analyzing and interpreting new experimental data and the tool for effective mining of a large number of publicly available genomics datasets stored in the back-end databases. The uniqueness of this platform lies in the volume and the diversity of genomics data that can be accessed and analyzed (gene expression, ChIP-chip, ChIP-seq, epigenomics, computationally predicted binding sites, etc), and the integration with an extensive knowledge base that can be used in such analysis. Conclusion The integrated access to primary genomics data, functional knowledge and analytical tools makes Genomics Portals platform a unique tool for interpreting results of new genomics experiments and for mining the vast amount of data stored in the Genomics Portals backend databases. Genomics Portals can be accessed and used freely at http://GenomicsPortals.org. PMID:20070909

Unravelling associations between unassigned mass spectrometry peaks with frequent itemset mining techniques.

PubMed

Vu, Trung Nghia; Mrzic, Aida; Valkenborg, Dirk; Maes, Evelyne; Lemière, Filip; Goethals, Bart; Laukens, Kris

2014-01-01

Mass spectrometry-based proteomics experiments generate spectra that are rich in information. Often only a fraction of this information is used for peptide/protein identification, whereas a significant proportion of the peaks in a spectrum remain unexplained. In this paper we explore how a specific class of data mining techniques termed "frequent itemset mining" can be employed to discover patterns in the unassigned data, and how such patterns can help us interpret the origin of the unexpected/unexplained peaks. First a model is proposed that describes the origin of the observed peaks in a mass spectrum. For this purpose we use the classical correlative database search algorithm. Peaks that support a positive identification of the spectrum are termed explained peaks. Next, frequent itemset mining techniques are introduced to infer which unexplained peaks are associated in a spectrum. The method is validated on two types of experimental proteomic data. First, peptide mass fingerprint data is analyzed to explain the unassigned peaks in a full scan mass spectrum. Interestingly, a large numbers of experimental spectra reveals several highly frequent unexplained masses, and pattern mining on these frequent masses demonstrates that subsets of these peaks frequently co-occur. Further evaluation shows that several of these co-occurring peaks indeed have a known common origin, and other patterns are promising hypothesis generators for further analysis. Second, the proposed methodology is validated on tandem mass spectrometral data using a public spectral library, where associations within the mass differences of unassigned peaks and peptide modifications are explored. The investigation of the found patterns illustrates that meaningful patterns can be discovered that can be explained by features of the employed technology and found modifications. This simple approach offers opportunities to monitor accumulating unexplained mass spectrometry data for emerging new patterns, with possible applications for the development of mass exclusion lists, for the refinement of quality control strategies and for a further interpretation of unexplained spectral peaks in mass spectrometry and tandem mass spectrometry.

Surface mining and the flood of April 1977

Treesearch

Willie R. Curtis

1977-01-01

Data from experimental sites in Breathitt County, Kentucky, and Raleigh County, West Virginia, showed that during a major rainstorm on 4 April 1977 streamflow from surface-mined watersheds peaked lower than that from adjacent or nearby unmined watersheds.

GEOGLE: context mining tool for the correlation between gene expression and the phenotypic distinction.

PubMed

Yu, Yao; Tu, Kang; Zheng, Siyuan; Li, Yun; Ding, Guohui; Ping, Jie; Hao, Pei; Li, Yixue

2009-08-25

In the post-genomic era, the development of high-throughput gene expression detection technology provides huge amounts of experimental data, which challenges the traditional pipelines for data processing and analyzing in scientific researches. In our work, we integrated gene expression information from Gene Expression Omnibus (GEO), biomedical ontology from Medical Subject Headings (MeSH) and signaling pathway knowledge from sigPathway entries to develop a context mining tool for gene expression analysis - GEOGLE. GEOGLE offers a rapid and convenient way for searching relevant experimental datasets, pathways and biological terms according to multiple types of queries: including biomedical vocabularies, GDS IDs, gene IDs, pathway names and signature list. Moreover, GEOGLE summarizes the signature genes from a subset of GDSes and estimates the correlation between gene expression and the phenotypic distinction with an integrated p value. This approach performing global searching of expression data may expand the traditional way of collecting heterogeneous gene expression experiment data. GEOGLE is a novel tool that provides researchers a quantitative way to understand the correlation between gene expression and phenotypic distinction through meta-analysis of gene expression datasets from different experiments, as well as the biological meaning behind. The web site and user guide of GEOGLE are available at: http://omics.biosino.org:14000/kweb/workflow.jsp?id=00020.

Quarry identification of historical building materials by means of laser induced breakdown spectroscopy, X-ray fluorescence and chemometric analysis

NASA Astrophysics Data System (ADS)

Colao, F.; Fantoni, R.; Ortiz, P.; Vazquez, M. A.; Martin, J. M.; Ortiz, R.; Idris, N.

2010-08-01

To characterize historical building materials according to the geographic origin of the quarries from which they have been mined, the relative content of major and trace elements were determined by means of Laser Induced Breakdown Spectroscopy (LIBS) and X-ray Fluorescence (XRF) techniques. 48 different specimens were studied and the entire samples' set was divided in two different groups: the first, used as reference set, was composed by samples mined from eight different quarries located in Seville province; the second group was composed by specimens of unknown provenance collected in several historical buildings and churches in the city of Seville. Data reduction and analysis on laser induced breakdown spectroscopy and X-ray fluorescence measurements was performed using multivariate statistical approach, namely the Linear Discriminant Analysis (LDA), Principal Component Analysis (PCA) and Soft Independent Modeling of Class Analogy (SIMCA). A clear separation among reference sample materials mined from different quarries was observed in Principal Components (PC) score plots, then a supervised soft independent modeling of class analogy classification was trained and run, aiming to assess the provenance of unknown samples according to their elemental content. The obtained results were compared with the provenance assignments made on the basis of petrographical description. This work gives experimental evidence that laser induced breakdown spectroscopy measurements on a relatively small set of elements is a fast and effective method for the purpose of origin identification.

Observational studies as human experimentation: the uranium mining experience in the Navajo Nation (1947-66).

PubMed

Moure-Eraso, R

1999-01-01

This article evaluates how an observational epidemiologic study of federal agencies in uranium miners became an experiment of opportunity for radiation effects. Navajo miners and communities suffered environmental exposures caused by the practices of uranium mining and milling in the Navajo reservation during the 1947 to 1966 period. A historical review of the state-of-the-art knowledge of the health effects of uranium mining and milling during the years prior to 1947 was conducted. Contemporary prevention and remediation practices also were assessed. An appraisal of the summary of findings of a comprehensive evaluation of radiation human experimentation conducted by the U.S. federal government in 1995-96 (ACHRE) demonstrates that uranium miners, including Navajo miners, were the single group that was put more seriously at risk of harm from radiation exposures, with inadequate disclosure and often with fatal consequences. Uranium miners were unwilling and unaware victims of human experimentation to evaluate the health effects of radiation. The failure of the State and U.S. Governments to issue regulations or demand installation of known mine-dust exposure control measures caused widespread environmental damage in the Navajo Nation.

Environmental Impact Assessment of Rosia Jiu Opencast Area Using AN Integrated SAR Analysis

NASA Astrophysics Data System (ADS)

Poenaru, V. D.; Negula, I. F. Dana; Badea, A.; Cuculici, R.

2016-06-01

The satellite data provide a new perspective to analyse and interpret environmental impact assessment as function of topography and vegetation. The main goal of this paper is to investigate the new Staring Spotlight TerraSAR-X mode capabilities to monitor land degradation in Rosia Jiu opencast area taking into account the mining engineering standards and specifications. The second goal is to relate mining activities with spatio-temporal dynamics of land degradation by using differential Synthetic Aperture Radar interferometry (DInSAR). The experimental analysis was carried out on data acquired in the LAN_2277 scientific proposal framework during 2014-2015 period. A set of 25 very height resolution SAR data gathered in the VV polarisation mode with a resolution of 0.45 m x 0.16m and an incidence angle of 37° have been used in this study. Preliminary results showed that altered terrain topography with steep slopes and deep pits has led to the layover of radar signal. Initially, ambiguous results have been obtained due to the highly dynamic character of subsidence induced by activities which imply mass mining methods. By increasing the SAR data number, the land degradation assessment has been improved. Most of the interferometric pairs have low coherence therefore the product coherence threshold was set to 0.3. A coherent and non-coherent analysis is performed to delineate land cover changes and complement the deformation model. Thus, the environmental impact of mining activities is better studied. Moreover, the monitoring of changes in pit depths, heights of stock-piles and waste dumps and levels of tailing dumps provide additional information about production data.

Drug target identification using network analysis: Taking active components in Sini decoction as an example

NASA Astrophysics Data System (ADS)

Chen, Si; Jiang, Hailong; Cao, Yan; Wang, Yun; Hu, Ziheng; Zhu, Zhenyu; Chai, Yifeng

2016-04-01

Identifying the molecular targets for the beneficial effects of active small-molecule compounds simultaneously is an important and currently unmet challenge. In this study, we firstly proposed network analysis by integrating data from network pharmacology and metabolomics to identify targets of active components in sini decoction (SND) simultaneously against heart failure. To begin with, 48 potential active components in SND against heart failure were predicted by serum pharmacochemistry, text mining and similarity match. Then, we employed network pharmacology including text mining and molecular docking to identify the potential targets of these components. The key enriched processes, pathways and related diseases of these target proteins were analyzed by STRING database. At last, network analysis was conducted to identify most possible targets of components in SND. Among the 25 targets predicted by network analysis, tumor necrosis factor α (TNF-α) was firstly experimentally validated in molecular and cellular level. Results indicated that hypaconitine, mesaconitine, higenamine and quercetin in SND can directly bind to TNF-α, reduce the TNF-α-mediated cytotoxicity on L929 cells and exert anti-myocardial cell apoptosis effects. We envisage that network analysis will also be useful in target identification of a bioactive compound.

Drug target identification using network analysis: Taking active components in Sini decoction as an example

PubMed Central

Chen, Si; Jiang, Hailong; Cao, Yan; Wang, Yun; Hu, Ziheng; Zhu, Zhenyu; Chai, Yifeng

2016-01-01

Identifying the molecular targets for the beneficial effects of active small-molecule compounds simultaneously is an important and currently unmet challenge. In this study, we firstly proposed network analysis by integrating data from network pharmacology and metabolomics to identify targets of active components in sini decoction (SND) simultaneously against heart failure. To begin with, 48 potential active components in SND against heart failure were predicted by serum pharmacochemistry, text mining and similarity match. Then, we employed network pharmacology including text mining and molecular docking to identify the potential targets of these components. The key enriched processes, pathways and related diseases of these target proteins were analyzed by STRING database. At last, network analysis was conducted to identify most possible targets of components in SND. Among the 25 targets predicted by network analysis, tumor necrosis factor α (TNF-α) was firstly experimentally validated in molecular and cellular level. Results indicated that hypaconitine, mesaconitine, higenamine and quercetin in SND can directly bind to TNF-α, reduce the TNF-α-mediated cytotoxicity on L929 cells and exert anti-myocardial cell apoptosis effects. We envisage that network analysis will also be useful in target identification of a bioactive compound. PMID:27095146

Levels of polycyclic aromatic hydrocarbons and dibenzothiophenes in wetland sediments and aquatic insects in the oil sands area of northeastern Alberta, Canada.

PubMed

Wayland, Mark; Headley, John V; Peru, Kerry M; Crosley, Robert; Brownlee, Brian G

2008-01-01

An immense volume of tailings and tailings water is accumulating in tailings ponds located on mine leases in the oil sands area of Alberta, Canada. Oil sands mining companies have proposed to use tailings- and tailings water-amended lakes and wetlands as part of their mine remediation plans. Polycyclic aromatic hydrocarbons (PAHs) are substances of concern in oil sands tailings and tailings water. In this study, we determined concentrations of PAHs in sediments, insect larvae and adult insects collected in or adjacent to three groups of wetlands: experimental wetlands to which tailings or tailings water had been purposely added, oil sands wetlands that were located on the mine leases but which had not been experimentally manipulated and reference wetlands located near the mine leases. Alkylated PAHs dominated the PAH profile in all types of samples in the three categories of wetlands. Median and maximum PAH concentrations, especially alkylated PAH concentrations, tended to be higher in sediments and insect larvae in experimental wetlands than in the other types of wetlands. Such was not the case for adult insects, which contained higher than expected levels of PAHs in the three types of ponds. Overlap in PAH concentrations in larvae among pond types suggests that any increase in PAH levels resulting from the addition of tailings and tailings water to wetlands would be modest. Biota-sediment accumulation factors were higher for alkylated PAHs than for their parent counterparts and were lower in experimental wetlands than in oil sands and reference wetlands. Research is needed to examine factors that affect the bioavailability of PAHs in oil sands tailings- or tailings water-amended wetlands.

Geochemical Data for Upper Mineral Creek, Colorado, Under Existing Ambient Conditions and During an Experimental pH Modification, August 2005

USGS Publications Warehouse

Runkel, Robert L.; Kimball, Briant A.; Steiger, Judy I.; Walton-Day, Katherine

2009-01-01

Mineral Creek, an acid mine drainage stream in south-western Colorado, was the subject of a water-quality study that employed a paired synoptic approach. Under the paired synoptic approach, two synoptic sampling campaigns were conducted on the same study reach. The initial synoptic campaign, conducted August 22, 2005, documented stream-water quality under existing ambient conditions. A second synoptic campaign, conducted August 24, 2005, documented stream-water quality during a pH-modification experiment that elevated the pH of Mineral Creek. The experimental pH modification was designed to determine the potential reductions in dissolved constituent concentrations that would result from the implementation of an active treatment system for acid mine drainage. During both synoptic sampling campaigns, a solution containing lithium bromide was injected continuously to allow for the calculation of streamflow using the tracer-dilution method. Synoptic water-quality samples were collected from 30 stream sites and 11 inflow locations along the 2-kilometer study reach. Data from the study provide spatial profiles of pH, concentration, and streamflow under both existing and experimentally-altered conditions. This report presents the data obtained August 21-24, 2005, as well as the methods used for sample collection and data analysis.

ChimerDB 3.0: an enhanced database for fusion genes from cancer transcriptome and literature data mining.

PubMed

Lee, Myunggyo; Lee, Kyubum; Yu, Namhee; Jang, Insu; Choi, Ikjung; Kim, Pora; Jang, Ye Eun; Kim, Byounggun; Kim, Sunkyu; Lee, Byungwook; Kang, Jaewoo; Lee, Sanghyuk

2017-01-04

Fusion gene is an important class of therapeutic targets and prognostic markers in cancer. ChimerDB is a comprehensive database of fusion genes encompassing analysis of deep sequencing data and manual curations. In this update, the database coverage was enhanced considerably by adding two new modules of The Cancer Genome Atlas (TCGA) RNA-Seq analysis and PubMed abstract mining. ChimerDB 3.0 is composed of three modules of ChimerKB, ChimerPub and ChimerSeq. ChimerKB represents a knowledgebase including 1066 fusion genes with manual curation that were compiled from public resources of fusion genes with experimental evidences. ChimerPub includes 2767 fusion genes obtained from text mining of PubMed abstracts. ChimerSeq module is designed to archive the fusion candidates from deep sequencing data. Importantly, we have analyzed RNA-Seq data of the TCGA project covering 4569 patients in 23 cancer types using two reliable programs of FusionScan and TopHat-Fusion. The new user interface supports diverse search options and graphic representation of fusion gene structure. ChimerDB 3.0 is available at http://ercsb.ewha.ac.kr/fusiongene/. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

Efficient Data Mining for Local Binary Pattern in Texture Image Analysis

PubMed Central

Kwak, Jin Tae; Xu, Sheng; Wood, Bradford J.

2015-01-01

Local binary pattern (LBP) is a simple gray scale descriptor to characterize the local distribution of the grey levels in an image. Multi-resolution LBP and/or combinations of the LBPs have shown to be effective in texture image analysis. However, it is unclear what resolutions or combinations to choose for texture analysis. Examining all the possible cases is impractical and intractable due to the exponential growth in a feature space. This limits the accuracy and time- and space-efficiency of LBP. Here, we propose a data mining approach for LBP, which efficiently explores a high-dimensional feature space and finds a relatively smaller number of discriminative features. The features can be any combinations of LBPs. These may not be achievable with conventional approaches. Hence, our approach not only fully utilizes the capability of LBP but also maintains the low computational complexity. We incorporated three different descriptors (LBP, local contrast measure, and local directional derivative measure) with three spatial resolutions and evaluated our approach using two comprehensive texture databases. The results demonstrated the effectiveness and robustness of our approach to different experimental designs and texture images. PMID:25767332

Mining high-throughput experimental data to link gene and function

PubMed Central

Blaby-Haas, Crysten E.; de Crécy-Lagard, Valérie

2011-01-01

Nearly 2200 genomes encoding some 6 million proteins have now been sequenced. Around 40% of these proteins are of unknown function even when function is loosely and minimally defined as “belonging to a superfamily”. In addition to in silico methods, the swelling stream of high-throughput experimental data can give valuable clues for linking these “unknowns” with precise biological roles. The goal is to develop integrative data-mining platforms that allow the scientific community at large to access and utilize this rich source of experimental knowledge. To this end, we review recent advances in generating whole-genome experimental datasets, where this data can be accessed, and how it can be used to drive prediction of gene function. PMID:21310501

Personalized Privacy-Preserving Frequent Itemset Mining Using Randomized Response

PubMed Central

Sun, Chongjing; Fu, Yan; Zhou, Junlin; Gao, Hui

2014-01-01

Frequent itemset mining is the important first step of association rule mining, which discovers interesting patterns from the massive data. There are increasing concerns about the privacy problem in the frequent itemset mining. Some works have been proposed to handle this kind of problem. In this paper, we introduce a personalized privacy problem, in which different attributes may need different privacy levels protection. To solve this problem, we give a personalized privacy-preserving method by using the randomized response technique. By providing different privacy levels for different attributes, this method can get a higher accuracy on frequent itemset mining than the traditional method providing the same privacy level. Finally, our experimental results show that our method can have better results on the frequent itemset mining while preserving personalized privacy. PMID:25143989

Personalized privacy-preserving frequent itemset mining using randomized response.

PubMed

Sun, Chongjing; Fu, Yan; Zhou, Junlin; Gao, Hui

2014-01-01

Frequent itemset mining is the important first step of association rule mining, which discovers interesting patterns from the massive data. There are increasing concerns about the privacy problem in the frequent itemset mining. Some works have been proposed to handle this kind of problem. In this paper, we introduce a personalized privacy problem, in which different attributes may need different privacy levels protection. To solve this problem, we give a personalized privacy-preserving method by using the randomized response technique. By providing different privacy levels for different attributes, this method can get a higher accuracy on frequent itemset mining than the traditional method providing the same privacy level. Finally, our experimental results show that our method can have better results on the frequent itemset mining while preserving personalized privacy.

Mining Deployment Optimization

NASA Astrophysics Data System (ADS)

Čech, Jozef

2016-09-01

The deployment problem, researched primarily in the military sector, is emerging in some other industries, mining included. The principal decision is how to deploy some activities in space and time to achieve desired outcome while complying with certain requirements or limits. Requirements and limits are on the side constraints, while minimizing costs or maximizing some benefits are on the side of objectives. A model with application to mining of polymetallic deposit is presented. To obtain quick and immediate decision solutions for a mining engineer with experimental possibilities is the main intention of a computer-based tool. The task is to determine strategic deployment of mining activities on a deposit, meeting planned output from the mine and at the same time complying with limited reserves and haulage capacities. Priorities and benefits can be formulated by the planner.

miRTex: A Text Mining System for miRNA-Gene Relation Extraction

PubMed Central

Li, Gang; Ross, Karen E.; Arighi, Cecilia N.; Peng, Yifan; Wu, Cathy H.; Vijay-Shanker, K.

2015-01-01

MicroRNAs (miRNAs) regulate a wide range of cellular and developmental processes through gene expression suppression or mRNA degradation. Experimentally validated miRNA gene targets are often reported in the literature. In this paper, we describe miRTex, a text mining system that extracts miRNA-target relations, as well as miRNA-gene and gene-miRNA regulation relations. The system achieves good precision and recall when evaluated on a literature corpus of 150 abstracts with F-scores close to 0.90 on the three different types of relations. We conducted full-scale text mining using miRTex to process all the Medline abstracts and all the full-length articles in the PubMed Central Open Access Subset. The results for all the Medline abstracts are stored in a database for interactive query and file download via the website at http://proteininformationresource.org/mirtex. Using miRTex, we identified genes potentially regulated by miRNAs in Triple Negative Breast Cancer, as well as miRNA-gene relations that, in conjunction with kinase-substrate relations, regulate the response to abiotic stress in Arabidopsis thaliana. These two use cases demonstrate the usefulness of miRTex text mining in the analysis of miRNA-regulated biological processes. PMID:26407127

An improved Pearson's correlation proximity-based hierarchical clustering for mining biological association between genes.

PubMed

Booma, P M; Prabhakaran, S; Dhanalakshmi, R

2014-01-01

Microarray gene expression datasets has concerned great awareness among molecular biologist, statisticians, and computer scientists. Data mining that extracts the hidden and usual information from datasets fails to identify the most significant biological associations between genes. A search made with heuristic for standard biological process measures only the gene expression level, threshold, and response time. Heuristic search identifies and mines the best biological solution, but the association process was not efficiently addressed. To monitor higher rate of expression levels between genes, a hierarchical clustering model was proposed, where the biological association between genes is measured simultaneously using proximity measure of improved Pearson's correlation (PCPHC). Additionally, the Seed Augment algorithm adopts average linkage methods on rows and columns in order to expand a seed PCPHC model into a maximal global PCPHC (GL-PCPHC) model and to identify association between the clusters. Moreover, a GL-PCPHC applies pattern growing method to mine the PCPHC patterns. Compared to existing gene expression analysis, the PCPHC model achieves better performance. Experimental evaluations are conducted for GL-PCPHC model with standard benchmark gene expression datasets extracted from UCI repository and GenBank database in terms of execution time, size of pattern, significance level, biological association efficiency, and pattern quality.

An Improved Pearson's Correlation Proximity-Based Hierarchical Clustering for Mining Biological Association between Genes

PubMed Central

Booma, P. M.; Prabhakaran, S.; Dhanalakshmi, R.

2014-01-01

Microarray gene expression datasets has concerned great awareness among molecular biologist, statisticians, and computer scientists. Data mining that extracts the hidden and usual information from datasets fails to identify the most significant biological associations between genes. A search made with heuristic for standard biological process measures only the gene expression level, threshold, and response time. Heuristic search identifies and mines the best biological solution, but the association process was not efficiently addressed. To monitor higher rate of expression levels between genes, a hierarchical clustering model was proposed, where the biological association between genes is measured simultaneously using proximity measure of improved Pearson's correlation (PCPHC). Additionally, the Seed Augment algorithm adopts average linkage methods on rows and columns in order to expand a seed PCPHC model into a maximal global PCPHC (GL-PCPHC) model and to identify association between the clusters. Moreover, a GL-PCPHC applies pattern growing method to mine the PCPHC patterns. Compared to existing gene expression analysis, the PCPHC model achieves better performance. Experimental evaluations are conducted for GL-PCPHC model with standard benchmark gene expression datasets extracted from UCI repository and GenBank database in terms of execution time, size of pattern, significance level, biological association efficiency, and pattern quality. PMID:25136661

Identifying Understudied Nuclear Reactions by Text-mining the EXFOR Experimental Nuclear Reaction Library

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hirdt, J.A.; Brown, D.A., E-mail: dbrown@bnl.gov

The EXFOR library contains the largest collection of experimental nuclear reaction data available as well as the data's bibliographic information and experimental details. We text-mined the REACTION and MONITOR fields of the ENTRYs in the EXFOR library in order to identify understudied reactions and quantities. Using the results of the text-mining, we created an undirected graph from the EXFOR datasets with each graph node representing a single reaction and quantity and graph links representing the various types of connections between these reactions and quantities. This graph is an abstract representation of the connections in EXFOR, similar to graphs of socialmore » networks, authorship networks, etc. We use various graph theoretical tools to identify important yet understudied reactions and quantities in EXFOR. Although we identified a few cross sections relevant for shielding applications and isotope production, mostly we identified charged particle fluence monitor cross sections. As a side effect of this work, we learn that our abstract graph is typical of other real-world graphs.« less

Identifying Understudied Nuclear Reactions by Text-mining the EXFOR Experimental Nuclear Reaction Library

NASA Astrophysics Data System (ADS)

Hirdt, J. A.; Brown, D. A.

2016-01-01

The EXFOR library contains the largest collection of experimental nuclear reaction data available as well as the data's bibliographic information and experimental details. We text-mined the REACTION and MONITOR fields of the ENTRYs in the EXFOR library in order to identify understudied reactions and quantities. Using the results of the text-mining, we created an undirected graph from the EXFOR datasets with each graph node representing a single reaction and quantity and graph links representing the various types of connections between these reactions and quantities. This graph is an abstract representation of the connections in EXFOR, similar to graphs of social networks, authorship networks, etc. We use various graph theoretical tools to identify important yet understudied reactions and quantities in EXFOR. Although we identified a few cross sections relevant for shielding applications and isotope production, mostly we identified charged particle fluence monitor cross sections. As a side effect of this work, we learn that our abstract graph is typical of other real-world graphs.

An examination of the effects of mountaintop removal coal mining on respiratory symptoms and COPD using propensity scores.

PubMed

Hendryx, Michael; Luo, Juhua

2015-01-01

Previous research on public health consequences of mountaintop removal (MTR) coal mining has been limited by the observational nature of the data. The current study used propensity scores, a method designed to overcome this limitation, to draw more confident causal inferences about mining effects on respiratory health using non-experimental data. These data come from a health survey of 682 adults residing in two rural areas of Virginia, USA characterized by the presence or absence of MTR mining. Persons with a history of occupational exposure as coal miners were excluded. Nine covariates including age, sex, current and former smoking, overweight, obesity, high school education, college education, and exposure to coal as a home-heating source were selected to estimate propensity scores. Propensity scores were tested for balance and then used as weights to create quasi-experimental exposed and unexposed groups. Results indicated that persons in the mountaintop mining group had significantly (p < 0.0001) elevated prevalence of respiratory symptoms and chronic obstructive pulmonary disease. The results suggest that impaired respiratory health results from exposure to MTR environments and not from other risks.

Big data mining: In-database Oracle data mining over hadoop

NASA Astrophysics Data System (ADS)

Kovacheva, Zlatinka; Naydenova, Ina; Kaloyanova, Kalinka; Markov, Krasimir

2017-07-01

Big data challenges different aspects of storing, processing and managing data, as well as analyzing and using data for business purposes. Applying Data Mining methods over Big Data is another challenge because of huge data volumes, variety of information, and the dynamic of the sources. Different applications are made in this area, but their successful usage depends on understanding many specific parameters. In this paper we present several opportunities for using Data Mining techniques provided by the analytical engine of RDBMS Oracle over data stored in Hadoop Distributed File System (HDFS). Some experimental results are given and they are discussed.

Back analysis of fault-slip in burst prone environment

NASA Astrophysics Data System (ADS)

Sainoki, Atsushi; Mitri, Hani S.

2016-11-01

In deep underground mines, stress re-distribution induced by mining activities could cause fault-slip. Seismic waves arising from fault-slip occasionally induce rock ejection when hitting the boundary of mine openings, and as a result, severe damage could be inflicted. In general, it is difficult to estimate fault-slip-induced ground motion in the vicinity of mine openings because of the complexity of the dynamic response of faults and the presence of geological structures. In this paper, a case study is conducted for a Canadian underground mine, herein called "Mine-A", which is known for its seismic activities. Using a microseismic database collected from the mine, a back analysis of fault-slip is carried out with mine-wide 3-dimensional numerical modeling. A back analysis is conducted to estimate the physical and mechanical properties of the causative fracture or shear zones. One large seismic event has been selected for the back analysis to detect a fault-slip related seismic event. In the back analysis, the shear zone properties are estimated with respect to moment magnitude of the seismic event and peak particle velocity (PPV) recorded by a strong ground motion sensor. The estimated properties are then validated through comparison with peak ground acceleration recorded by accelerometers. Lastly, ground motion in active mining areas is estimated by conducting dynamic analysis with the estimated values. The present study implies that it would be possible to estimate the magnitude of seismic events that might occur in the near future by applying the estimated properties to the numerical model. Although the case study is conducted for a specific mine, the developed methodology can be equally applied to other mines suffering from fault-slip related seismic events.

CFD gas distribution analysis for different continuous-miner scrubber redirection configurations

PubMed Central

Zheng, Y.; Organiscak, J.A.; Zhou, L.; Beck, T.W.; Rider, J.P.

2018-01-01

The U.S. National Institute for Occupational Safety and Health (NIOSH)’s Pittsburgh Mining Research Division (PMRD) recently developed a series of models using computational fluid dynamics (CFD) to study gas distribution around a continuous mining machine with various fan-powered flooded bed scrubber discharge configurations in an exhaust curtain working face. CFD models utilizing species transport model without reactions in FLUENT were constructed to evaluate the redirection of scrubber discharge toward the mining face rather than behind the return curtain. The study illustrates the gas distribution in the slab (second) cut. The following scenarios are considered in this study: 100 percent of the discharge redirected back toward the face on the off-curtain side; 100 percent of the discharge redirected back toward the face, but divided equally to both sides; and 15 percent of the discharge redirected toward the face on the off-curtain side, with 85 percent directed toward the return curtain. These models are compared against a model with a conventional scrubber discharge where air is directed away from the face into the return. The models were validated against experimental data, proving to accurately predict sulfur hexafluoride (SF6) gas levels at four gas monitoring locations. This study includes a predictive simulation examining a 45° scrubber angle compared with the 23° angle for the 100 percent redirected, equally divided case. This paper describes the validation of the CFD models based on experimental data of the gas distribution results. PMID:29375242

CFD gas distribution analysis for different continuous-miner scrubber redirection configurations.

PubMed

Zheng, Y; Organiscak, J A; Zhou, L; Beck, T W; Rider, J P

2017-01-01

The U.S. National Institute for Occupational Safety and Health (NIOSH)'s Pittsburgh Mining Research Division (PMRD) recently developed a series of models using computational fluid dynamics (CFD) to study gas distribution around a continuous mining machine with various fan-powered flooded bed scrubber discharge configurations in an exhaust curtain working face. CFD models utilizing species transport model without reactions in FLUENT were constructed to evaluate the redirection of scrubber discharge toward the mining face rather than behind the return curtain. The study illustrates the gas distribution in the slab (second) cut. The following scenarios are considered in this study: 100 percent of the discharge redirected back toward the face on the off-curtain side; 100 percent of the discharge redirected back toward the face, but divided equally to both sides; and 15 percent of the discharge redirected toward the face on the off-curtain side, with 85 percent directed toward the return curtain. These models are compared against a model with a conventional scrubber discharge where air is directed away from the face into the return. The models were validated against experimental data, proving to accurately predict sulfur hexafluoride (SF 6 ) gas levels at four gas monitoring locations. This study includes a predictive simulation examining a 45° scrubber angle compared with the 23° angle for the 100 percent redirected, equally divided case. This paper describes the validation of the CFD models based on experimental data of the gas distribution results.

Hazards and occupational risk in hard coal mines - a critical analysis of legal requirements

NASA Astrophysics Data System (ADS)

Krause, Marcin

2017-11-01

This publication concerns the problems of occupational safety and health in hard coal mines, the basic elements of which are the mining hazards and the occupational risk. The work includes a comparative analysis of selected provisions of general and industry-specific law regarding the analysis of hazards and occupational risk assessment. Based on a critical analysis of legal requirements, basic assumptions regarding the practical guidelines for occupational risk assessment in underground coal mines have been proposed.

Teaching the Scientific Method: It's All in the Perspective

ERIC Educational Resources Information Center

Ayers, James M.; Ayers, Kathleen M.

2007-01-01

A three unit module of inquiry, including morphological comparison, cladogram construction, and data mining has been developed to teach students the nature of experimental science. Students generate angiosperm morphological data, form cladistic hypotheses, then mine taxonomic, bioinformatic and historical data from many sources to replicate and…

Novel Microbial Assemblages Dominate Weathered Sulfide-Bearing Rock from Copper-Nickel Deposits in the Duluth Complex, Minnesota, USA

PubMed Central

Lapakko, Kim A.; Wenz, Zachary J.; Olson, Michael C.; Roepke, Elizabeth W.; Novak, Paige J.; Bailey, Jake V.

2017-01-01

ABSTRACT The Duluth Complex in northeastern Minnesota hosts economically significant deposits of copper, nickel, and platinum group elements (PGEs). The primary sulfide mineralogy of these deposits includes the minerals pyrrhotite, chalcopyrite, pentlandite, and cubanite, and weathering experiments show that most sulfide-bearing rock from the Duluth Complex generates moderately acidic leachate (pH 4 to 6). Microorganisms are important catalysts for metal sulfide oxidation and could influence the quality of water from mines in the Duluth Complex. Nevertheless, compared with that of extremely acidic environments, much less is known about the microbial ecology of moderately acidic sulfide-bearing mine waste, and so existing information may have little relevance to those microorganisms catalyzing oxidation reactions in the Duluth Complex. Here, we characterized the microbial communities in decade-long weathering experiments (kinetic tests) conducted on crushed rock and tailings from the Duluth Complex. Analyses of 16S rRNA genes and transcripts showed that differences among microbial communities correspond to pH, rock type, and experimental treatment. Moreover, microbial communities from the weathered Duluth Complex rock were dominated by taxa that are not typically associated with acidic mine waste. The most abundant operational taxonomic units (OTUs) were from the genera Meiothermus and Sulfuriferula, as well as from diverse clades of uncultivated Chloroflexi, Acidobacteria, and Betaproteobacteria. Specific taxa, including putative sulfur-oxidizing Sulfuriferula spp., appeared to be primarily associated with Duluth Complex rock, but not pyrite-bearing rocks subjected to the same experimental treatment. We discuss the implications of these results for the microbial ecology of moderately acidic mine waste with low sulfide content, as well as for kinetic testing of mine waste. IMPORTANCE Economic sulfide mineral deposits in the Duluth Complex may represent the largest undeveloped source of copper and nickel on Earth. Microorganisms are important catalysts for sulfide mineral oxidation, and research on extreme acidophiles has improved our ability to manage and remediate mine wastes. We found that the microbial assemblages associated with weathered rock from the Duluth Complex are dominated by organisms not widely associated with mine waste or mining-impacted environments, and we describe geochemical and experimental influences on community composition. This report will be a useful foundation for understanding the microbial biogeochemistry of moderately acidic mine waste from these and similar deposits. PMID:28600313

Novel Microbial Assemblages Dominate Weathered Sulfide-Bearing Rock from Copper-Nickel Deposits in the Duluth Complex, Minnesota, USA.

PubMed

Jones, Daniel S; Lapakko, Kim A; Wenz, Zachary J; Olson, Michael C; Roepke, Elizabeth W; Sadowsky, Michael J; Novak, Paige J; Bailey, Jake V

2017-08-15

The Duluth Complex in northeastern Minnesota hosts economically significant deposits of copper, nickel, and platinum group elements (PGEs). The primary sulfide mineralogy of these deposits includes the minerals pyrrhotite, chalcopyrite, pentlandite, and cubanite, and weathering experiments show that most sulfide-bearing rock from the Duluth Complex generates moderately acidic leachate (pH 4 to 6). Microorganisms are important catalysts for metal sulfide oxidation and could influence the quality of water from mines in the Duluth Complex. Nevertheless, compared with that of extremely acidic environments, much less is known about the microbial ecology of moderately acidic sulfide-bearing mine waste, and so existing information may have little relevance to those microorganisms catalyzing oxidation reactions in the Duluth Complex. Here, we characterized the microbial communities in decade-long weathering experiments (kinetic tests) conducted on crushed rock and tailings from the Duluth Complex. Analyses of 16S rRNA genes and transcripts showed that differences among microbial communities correspond to pH, rock type, and experimental treatment. Moreover, microbial communities from the weathered Duluth Complex rock were dominated by taxa that are not typically associated with acidic mine waste. The most abundant operational taxonomic units (OTUs) were from the genera Meiothermus and Sulfuriferula , as well as from diverse clades of uncultivated Chloroflexi , Acidobacteria , and Betaproteobacteria Specific taxa, including putative sulfur-oxidizing Sulfuriferula spp., appeared to be primarily associated with Duluth Complex rock, but not pyrite-bearing rocks subjected to the same experimental treatment. We discuss the implications of these results for the microbial ecology of moderately acidic mine waste with low sulfide content, as well as for kinetic testing of mine waste. IMPORTANCE Economic sulfide mineral deposits in the Duluth Complex may represent the largest undeveloped source of copper and nickel on Earth. Microorganisms are important catalysts for sulfide mineral oxidation, and research on extreme acidophiles has improved our ability to manage and remediate mine wastes. We found that the microbial assemblages associated with weathered rock from the Duluth Complex are dominated by organisms not widely associated with mine waste or mining-impacted environments, and we describe geochemical and experimental influences on community composition. This report will be a useful foundation for understanding the microbial biogeochemistry of moderately acidic mine waste from these and similar deposits. Copyright © 2017 American Society for Microbiology.

A communication efficient and scalable distributed data mining for the astronomical data

NASA Astrophysics Data System (ADS)

Govada, A.; Sahay, S. K.

2016-07-01

In 2020, ∼60PB of archived data will be accessible to the astronomers. But to analyze such a paramount data will be a challenging task. This is basically due to the computational model used to download the data from complex geographically distributed archives to a central site and then analyzing it in the local systems. Because the data has to be downloaded to the central site, the network BW limitation will be a hindrance for the scientific discoveries. Also analyzing this PB-scale on local machines in a centralized manner is challenging. In this, virtual observatory is a step towards this problem, however, it does not provide the data mining model (Zhang et al., 2004). Adding the distributed data mining layer to the VO can be the solution in which the knowledge can be downloaded by the astronomers instead the raw data and thereafter astronomers can either reconstruct the data back from the downloaded knowledge or use the knowledge directly for further analysis. Therefore, in this paper, we present Distributed Load Balancing Principal Component Analysis for optimally distributing the computation among the available nodes to minimize the transmission cost and downloading cost for the end user. The experimental analysis is done with Fundamental Plane (FP) data, Gadotti data and complex Mfeat data. In terms of transmission cost, our approach performs better than Qi et al. and Yue et al. The analysis shows that with the complex Mfeat data ∼90% downloading cost can be reduced for the end user with the negligible loss in accuracy.

Applications of ERTS-1 data to landscape change in eastern Tennessee

NASA Technical Reports Server (NTRS)

Rehder, J. B. (Principal Investigator)

1973-01-01

The author has identified the following significant results. The analysis of landscape change in eastern Tennessee from ERTS-1 data is being derived from three avenues of experimentation and analysis: (1) a multi-stage sampling procedure utilizing ground and aircraft imagery for ground truth and control; (2) a densitometric and computer analytical experiment for the analysis of gray tone signatures and comparisons for landscape change detection and monitoring; and (3) an ERTS image enhancement procedure for the detection and analysis of photomorphic regions. Significant results include: maps of strip mining changes and forest inventory, watershed identification and delimitation, and agricultural regions derived from spring plowing patterns appearing on the ERTS-1 imagery.

Mining high-throughput experimental data to link gene and function.

PubMed

Blaby-Haas, Crysten E; de Crécy-Lagard, Valérie

2011-04-01

Nearly 2200 genomes that encode around 6 million proteins have now been sequenced. Around 40% of these proteins are of unknown function, even when function is loosely and minimally defined as 'belonging to a superfamily'. In addition to in silico methods, the swelling stream of high-throughput experimental data can give valuable clues for linking these unknowns with precise biological roles. The goal is to develop integrative data-mining platforms that allow the scientific community at large to access and utilize this rich source of experimental knowledge. To this end, we review recent advances in generating whole-genome experimental datasets, where this data can be accessed, and how it can be used to drive prediction of gene function. Copyright © 2011 Elsevier Ltd. All rights reserved.

A harmonic linear dynamical system for prominent ECG feature extraction.

PubMed

Thi, Ngoc Anh Nguyen; Yang, Hyung-Jeong; Kim, SunHee; Do, Luu Ngoc

2014-01-01

Unsupervised mining of electrocardiography (ECG) time series is a crucial task in biomedical applications. To have efficiency of the clustering results, the prominent features extracted from preprocessing analysis on multiple ECG time series need to be investigated. In this paper, a Harmonic Linear Dynamical System is applied to discover vital prominent features via mining the evolving hidden dynamics and correlations in ECG time series. The discovery of the comprehensible and interpretable features of the proposed feature extraction methodology effectively represents the accuracy and the reliability of clustering results. Particularly, the empirical evaluation results of the proposed method demonstrate the improved performance of clustering compared to the previous main stream feature extraction approaches for ECG time series clustering tasks. Furthermore, the experimental results on real-world datasets show scalability with linear computation time to the duration of the time series.

Final Technical Report for ARRA Funding

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rusack, Roger; Mans, Jeremiah; Poling, Ronald

Final technical report of the University of Minnesota experimental high energy physics group for ARRA support. The Cryogenic Dark Matter Experiment (CDMS) used the funds received to construct a new passive shield to protect a high-purity germanium detector located in the Soudan mine in Northern Minnesota from cosmic rays. The BESIII and the CMS groups purchased computing hardware to assemble computer farms for data analysis and to generate large volumes of simulated data for comparison with the data collected.

One-Dimensional Model for Mud Flows.

DTIC Science & Technology

1985-10-01

law relation between the Chezy coefficient and the flow Reynolds number. Jeyapalan et al. [2], in their analysis of mine tailing dam failures...8217.. .: -:.. ; .r;./. : ... . :\\ :. . ... . RESULTS The model is compared with several dambreak experiments performed by Jeyapalan et al. [3]. In these...0.34 seconds per computational node. 5i Test 6 Test 2 Test 7 44 E 3 A2 Experimental Results0 Jeyapalan at al. (3) - C6- Numerical Results 4 8 12 i6 Time

Data-Mining Technologies for Diabetes: A Systematic Review

PubMed Central

Marinov, Miroslav; Mosa, Abu Saleh Mohammad; Yoo, Illhoi; Boren, Suzanne Austin

2011-01-01

Background The objective of this study is to conduct a systematic review of applications of data-mining techniques in the field of diabetes research. Method We searched the MEDLINE database through PubMed. We initially identified 31 articles by the search, and selected 17 articles representing various data-mining methods used for diabetes research. Our main interest was to identify research goals, diabetes types, data sets, data-mining methods, data-mining software and technologies, and outcomes. Results The applications of data-mining techniques in the selected articles were useful for extracting valuable knowledge and generating new hypothesis for further scientific research/experimentation and improving health care for diabetes patients. The results could be used for both scientific research and real-life practice to improve the quality of health care diabetes patients. Conclusions Data mining has played an important role in diabetes research. Data mining would be a valuable asset for diabetes researchers because it can unearth hidden knowledge from a huge amount of diabetes-related data. We believe that data mining can significantly help diabetes research and ultimately improve the quality of health care for diabetes patients. PMID:22226277

An Application of Multiplier Analysis in Analyzing the Role of Mining Sectors on Indonesian National Economy

NASA Astrophysics Data System (ADS)

Subanti, S.; Hakim, A. R.; Hakim, I. M.

2018-03-01

This purpose of the current study aims is to analyze the multiplier analysis on mining sector in Indonesia. The mining sectors defined by coal and metal; crude oil, natural gas, and geothermal; and other mining and quarrying. The multiplier analysis based from input output analysis, this divided by income multiplier and output multiplier. This results show that (1) Indonesian mining sectors ranked 6th with contribute amount of 6.81% on national total output; (2) Based on total gross value added, this sector contribute amount of 12.13% or ranked 4th; (3) The value from income multiplier is 0.7062 and the value from output multiplier is 1.2426.

Reliability and safety, and the risk of construction damage in mining areas

NASA Astrophysics Data System (ADS)

Skrzypczak, Izabela; Kogut, Janusz P.; Kokoszka, Wanda; Oleniacz, Grzegorz

2018-04-01

This article concerns the reliability and safety of building structures in mining areas, with a particular emphasis on the quantitative risk analysis of buildings. The issues of threat assessment and risk estimation, in the design of facilities in mining exploitation areas, are presented here, indicating the difficulties and ambiguities associated with their quantification and quantitative analysis. This article presents the concept of quantitative risk assessment of the impact of mining exploitation, in accordance with ISO 13824 [1]. The risk analysis is illustrated through an example of a construction located within an area affected by mining exploitation.

Restoring Forests and Associated Ecosystem Services on Appalachian Coal Surface Mines

NASA Astrophysics Data System (ADS)

Zipper, Carl E.; Burger, James A.; Skousen, Jeffrey G.; Angel, Patrick N.; Barton, Christopher D.; Davis, Victor; Franklin, Jennifer A.

2011-05-01

Surface coal mining in Appalachia has caused extensive replacement of forest with non-forested land cover, much of which is unmanaged and unproductive. Although forested ecosystems are valued by society for both marketable products and ecosystem services, forests have not been restored on most Appalachian mined lands because traditional reclamation practices, encouraged by regulatory policies, created conditions poorly suited for reforestation. Reclamation scientists have studied productive forests growing on older mine sites, established forest vegetation experimentally on recent mines, and identified mine reclamation practices that encourage forest vegetation re-establishment. Based on these findings, they developed a Forestry Reclamation Approach (FRA) that can be employed by coal mining firms to restore forest vegetation. Scientists and mine regulators, working collaboratively, have communicated the FRA to the coal industry and to regulatory enforcement personnel. Today, the FRA is used routinely by many coal mining firms, and thousands of mined hectares have been reclaimed to restore productive mine soils and planted with native forest trees. Reclamation of coal mines using the FRA is expected to restore these lands' capabilities to provide forest-based ecosystem services, such as wood production, atmospheric carbon sequestration, wildlife habitat, watershed protection, and water quality protection to a greater extent than conventional reclamation practices.

Text Mining of Journal Articles for Sleep Disorder Terminologies.

PubMed

Lam, Calvin; Lai, Fu-Chih; Wang, Chia-Hui; Lai, Mei-Hsin; Hsu, Nanly; Chung, Min-Huey

2016-01-01

Research on publication trends in journal articles on sleep disorders (SDs) and the associated methodologies by using text mining has been limited. The present study involved text mining for terms to determine the publication trends in sleep-related journal articles published during 2000-2013 and to identify associations between SD and methodology terms as well as conducting statistical analyses of the text mining findings. SD and methodology terms were extracted from 3,720 sleep-related journal articles in the PubMed database by using MetaMap. The extracted data set was analyzed using hierarchical cluster analyses and adjusted logistic regression models to investigate publication trends and associations between SD and methodology terms. MetaMap had a text mining precision, recall, and false positive rate of 0.70, 0.77, and 11.51%, respectively. The most common SD term was breathing-related sleep disorder, whereas narcolepsy was the least common. Cluster analyses showed similar methodology clusters for each SD term, except narcolepsy. The logistic regression models showed an increasing prevalence of insomnia, parasomnia, and other sleep disorders but a decreasing prevalence of breathing-related sleep disorder during 2000-2013. Different SD terms were positively associated with different methodology terms regarding research design terms, measure terms, and analysis terms. Insomnia-, parasomnia-, and other sleep disorder-related articles showed an increasing publication trend, whereas those related to breathing-related sleep disorder showed a decreasing trend. Furthermore, experimental studies more commonly focused on hypersomnia and other SDs and less commonly on insomnia, breathing-related sleep disorder, narcolepsy, and parasomnia. Thus, text mining may facilitate the exploration of the publication trends in SDs and the associated methodologies.

Mine safety assessment using gray relational analysis and bow tie model

PubMed Central

2018-01-01

Mine safety assessment is a precondition for ensuring orderly and safety in production. The main purpose of this study was to prevent mine accidents more effectively by proposing a composite risk analysis model. First, the weights of the assessment indicators were determined by the revised integrated weight method, in which the objective weights were determined by a variation coefficient method and the subjective weights determined by the Delphi method. A new formula was then adopted to calculate the integrated weights based on the subjective and objective weights. Second, after the assessment indicator weights were determined, gray relational analysis was used to evaluate the safety of mine enterprises. Mine enterprise safety was ranked according to the gray relational degree, and weak links of mine safety practices identified based on gray relational analysis. Third, to validate the revised integrated weight method adopted in the process of gray relational analysis, the fuzzy evaluation method was used to the safety assessment of mine enterprises. Fourth, for first time, bow tie model was adopted to identify the causes and consequences of weak links and allow corresponding safety measures to be taken to guarantee the mine’s safe production. A case study of mine safety assessment was presented to demonstrate the effectiveness and rationality of the proposed composite risk analysis model, which can be applied to other related industries for safety evaluation. PMID:29561875

Data mining for multiagent rules, strategies, and fuzzy decision tree structure

NASA Astrophysics Data System (ADS)

Smith, James F., III; Rhyne, Robert D., II; Fisher, Kristin

2002-03-01

A fuzzy logic based resource manager (RM) has been developed that automatically allocates electronic attack resources in real-time over many dissimilar platforms. Two different data mining algorithms have been developed to determine rules, strategies, and fuzzy decision tree structure. The first data mining algorithm uses a genetic algorithm as a data mining function and is called from an electronic game. The game allows a human expert to play against the resource manager in a simulated battlespace with each of the defending platforms being exclusively directed by the fuzzy resource manager and the attacking platforms being controlled by the human expert or operating autonomously under their own logic. This approach automates the data mining problem. The game automatically creates a database reflecting the domain expert's knowledge. It calls a data mining function, a genetic algorithm, for data mining of the database as required and allows easy evaluation of the information mined in the second step. The criterion for re- optimization is discussed as well as experimental results. Then a second data mining algorithm that uses a genetic program as a data mining function is introduced to automatically discover fuzzy decision tree structures. Finally, a fuzzy decision tree generated through this process is discussed.

Potassium Permanganate as an Alternative for Gold Mining Wastewater Treatment

NASA Astrophysics Data System (ADS)

Ordiales, M.; Fernández, D.; Verdeja, L. F.; Sancho, J.

2015-09-01

The feasibility of using potassium permanganate as a reagent for cyanide oxidation in wastewater was experimentally studied. Both artificial and production wastewater from two different gold mines were tested. The experiments had three goals: determine the optimum reagent concentration and reaction time required to achieve total cyanide removal, obtain knowledge of the reaction kinetics, and improve the management of the amount of reagent. The results indicate that potassium permanganate is an effective and reliable oxidizing agent for the removal of cyanide from gold mining wastewater.

Polymerization and oscillation stuttering in a filamentous model of the subcellular Min oscillation

NASA Astrophysics Data System (ADS)

Rutenberg, Andrew; Sengupta, Supratim; Sain, Anirban; Derr, Julien

2011-03-01

We present a computational model of the E. coli Min oscillation that involves polymerization of MinD filaments followed by depolymerization stimulated by filament-end zones of MinE. Our stochastic model is fully three-dimensional, and tracks the diffusion and interactions of every MinD and MinE molecule. We recover self-organized Min oscillations. We investigate the experimental phenomenon of oscillation stuttering, which we relate to the disruption of MinE tip-binding at the filament scale.

Handling Dynamic Weights in Weighted Frequent Pattern Mining

NASA Astrophysics Data System (ADS)

Ahmed, Chowdhury Farhan; Tanbeer, Syed Khairuzzaman; Jeong, Byeong-Soo; Lee, Young-Koo

Even though weighted frequent pattern (WFP) mining is more effective than traditional frequent pattern mining because it can consider different semantic significances (weights) of items, existing WFP algorithms assume that each item has a fixed weight. But in real world scenarios, the weight (price or significance) of an item can vary with time. Reflecting these changes in item weight is necessary in several mining applications, such as retail market data analysis and web click stream analysis. In this paper, we introduce the concept of a dynamic weight for each item, and propose an algorithm, DWFPM (dynamic weighted frequent pattern mining), that makes use of this concept. Our algorithm can address situations where the weight (price or significance) of an item varies dynamically. It exploits a pattern growth mining technique to avoid the level-wise candidate set generation-and-test methodology. Furthermore, it requires only one database scan, so it is eligible for use in stream data mining. An extensive performance analysis shows that our algorithm is efficient and scalable for WFP mining using dynamic weights.

Evaluation of the environmental contamination at an abandoned mining site using multivariate statistical techniques--the Rodalquilar (Southern Spain) mining district.

PubMed

Bagur, M G; Morales, S; López-Chicano, M

2009-11-15

Unsupervised and supervised pattern recognition techniques such as hierarchical cluster analysis, principal component analysis, factor analysis and linear discriminant analysis have been applied to water samples recollected in Rodalquilar mining district (Southern Spain) in order to identify different sources of environmental pollution caused by the abandoned mining industry. The effect of the mining activity on waters was monitored determining the concentration of eleven elements (Mn, Ba, Co, Cu, Zn, As, Cd, Sb, Hg, Au and Pb) by inductively coupled plasma mass spectrometry (ICP-MS). The Box-Cox transformation has been used to transform the data set in normal form in order to minimize the non-normal distribution of the geochemical data. The environmental impact is affected mainly by the mining activity developed in the zone, the acid drainage and finally by the chemical treatment used for the benefit of gold.

The accident analysis of mobile mine machinery in Indian opencast coal mines.

PubMed

Kumar, R; Ghosh, A K

2014-01-01

This paper presents the analysis of large mining machinery related accidents in Indian opencast coal mines. The trends of coal production, share of mining methods in production, machinery deployment in open cast mines, size and population of machinery, accidents due to machinery, types and causes of accidents have been analysed from the year 1995 to 2008. The scrutiny of accidents during this period reveals that most of the responsible factors are machine reversal, haul road design, human fault, operator's fault, machine fault, visibility and dump design. Considering the types of machines, namely, dumpers, excavators, dozers and loaders together the maximum number of fatal accidents has been caused by operator's faults and human faults jointly during the period from 1995 to 2008. The novel finding of this analysis is that large machines with state-of-the-art safety system did not reduce the fatal accidents in Indian opencast coal mines.

Spatial Data Mining for Estimating Cover Management Factor of Universal Soil Loss Equation

NASA Astrophysics Data System (ADS)

Tsai, F.; Lin, T. C.; Chiang, S. H.; Chen, W. W.

2016-12-01

Universal Soil Loss Equation (USLE) is a widely used mathematical model that describes long-term soil erosion processes. Among the six different soil erosion risk factors of USLE, the cover-management factor (C-factor) is related to land-cover/land-use. The value of C-factor ranges from 0.001 to 1, so it alone might cause a thousandfold difference in a soil erosion analysis using USLE. The traditional methods for the estimation of USLE C-factor include in situ experiments, soil physical parameter models, USLE look-up tables with land use maps, and regression models between vegetation indices and C-factors. However, these methods are either difficult or too expensive to implement in large areas. In addition, the values of C-factor obtained using these methods can not be updated frequently, either. To address this issue, this research developed a spatial data mining approach to estimate the values of C-factor with assorted spatial datasets for a multi-temporal (2004 to 2008) annual soil loss analysis of a reservoir watershed in northern Taiwan. The idea is to establish the relationship between the USLE C-factor and spatial data consisting of vegetation indices and texture features extracted from satellite images, soil and geology attributes, digital elevation model, road and river distribution etc. A decision tree classifier was used to rank influential conditional attributes in the preliminary data mining. Then, factor simplification and separation were considered to optimize the model and the random forest classifier was used to analyze 9 simplified factor groups. Experimental results indicate that the overall accuracy of the data mining model is about 79% with a kappa value of 0.76. The estimated soil erosion amounts in 2004-2008 according to the data mining results are about 50.39 - 74.57 ton/ha-year after applying the sediment delivery ratio and correction coefficient. Comparing with estimations calculated with C-factors from look-up tables, the soil erosion values estimated with C-factors generated from spatial data mining results are more in agreement with the values published by the watershed administration authority.

Anchor-Free Localization Method for Mobile Targets in Coal Mine Wireless Sensor Networks

PubMed Central

Pei, Zhongmin; Deng, Zhidong; Xu, Shuo; Xu, Xiao

2009-01-01

Severe natural conditions and complex terrain make it difficult to apply precise localization in underground mines. In this paper, an anchor-free localization method for mobile targets is proposed based on non-metric multi-dimensional scaling (Multi-dimensional Scaling: MDS) and rank sequence. Firstly, a coal mine wireless sensor network is constructed in underground mines based on the ZigBee technology. Then a non-metric MDS algorithm is imported to estimate the reference nodes’ location. Finally, an improved sequence-based localization algorithm is presented to complete precise localization for mobile targets. The proposed method is tested through simulations with 100 nodes, outdoor experiments with 15 ZigBee physical nodes, and the experiments in the mine gas explosion laboratory with 12 ZigBee nodes. Experimental results show that our method has better localization accuracy and is more robust in underground mines. PMID:22574048

Anchor-free localization method for mobile targets in coal mine wireless sensor networks.

PubMed

Pei, Zhongmin; Deng, Zhidong; Xu, Shuo; Xu, Xiao

2009-01-01

Severe natural conditions and complex terrain make it difficult to apply precise localization in underground mines. In this paper, an anchor-free localization method for mobile targets is proposed based on non-metric multi-dimensional scaling (Multi-dimensional Scaling: MDS) and rank sequence. Firstly, a coal mine wireless sensor network is constructed in underground mines based on the ZigBee technology. Then a non-metric MDS algorithm is imported to estimate the reference nodes' location. Finally, an improved sequence-based localization algorithm is presented to complete precise localization for mobile targets. The proposed method is tested through simulations with 100 nodes, outdoor experiments with 15 ZigBee physical nodes, and the experiments in the mine gas explosion laboratory with 12 ZigBee nodes. Experimental results show that our method has better localization accuracy and is more robust in underground mines.

Mining moving object trajectories in location-based services for spatio-temporal database update

NASA Astrophysics Data System (ADS)

Guo, Danhuai; Cui, Weihong

2008-10-01

Advances in wireless transmission and mobile technology applied to LBS (Location-based Services) flood us with amounts of moving objects data. Vast amounts of gathered data from position sensors of mobile phones, PDAs, or vehicles hide interesting and valuable knowledge and describe the behavior of moving objects. The correlation between temporal moving patterns of moving objects and geo-feature spatio-temporal attribute was ignored, and the value of spatio-temporal trajectory data was not fully exploited too. Urban expanding or frequent town plan change bring about a large amount of outdated or imprecise data in spatial database of LBS, and they cannot be updated timely and efficiently by manual processing. In this paper we introduce a data mining approach to movement pattern extraction of moving objects, build a model to describe the relationship between movement patterns of LBS mobile objects and their environment, and put up with a spatio-temporal database update strategy in LBS database based on trajectories spatiotemporal mining. Experimental evaluation reveals excellent performance of the proposed model and strategy. Our original contribution include formulation of model of interaction between trajectory and its environment, design of spatio-temporal database update strategy based on moving objects data mining, and the experimental application of spatio-temporal database update by mining moving objects trajectories.

Union Underground: Political Issues. Comparing Political Experiences, Experimental Edition.

ERIC Educational Resources Information Center

Gillespie, Judith A.; Lazarus, Stuart

This is the third unit to the second-semester "Comparing Political Experiences" course which focuses on a specific, controversial, political issue. The unit analyzes the concept of political maintenance by studying the United Mine Workers of America (UMWA) between 1918 and 1975 and its fight to secure mine safety standards. A documentary…

Validating a Finite Element Model of a Structure Subjected to Mine Blast with Experimental Modal Analysis

DTIC Science & Technology

2017-11-01

The Under-body Blast Methodology (UBM) for the Test and Evaluation (T&E) program was established to provide a capability for the US Army Test and... Evaluation Command to assess the vulnerability of vehicles to under-body blast. Finite element (FE) models are part of the current UBM for T&E methodology...Methodology (UBM) for the Test and Evaluation (T&E) program was established to provide a capability for the US Army Test and Evaluation Command

Effect of adaptation and pulp density on bioleaching of mine waste using indigenous acidophilic bacteria

NASA Astrophysics Data System (ADS)

Cho, K.; Kim, B.; Lee, D.; Choi, N.; Park, C.

2011-12-01

Adaptation to environment is a natural phenomena that takes place in many animals, plants and microorganisms. These adapted organisms achieve stronger applicability than unadapted organisms after habitation in a specific environment for a long time. In the biohydrometallurgical industry, adaptation to special environment conditions by selective culturing is the most popular method for improving bioleaching activity of strains-although that is time consuming. This study investigated the influence of the bioleaching efficiency of mine waste under batch experimental conditions (adaptation and pulp density) using the indigenous acidophilic bacteria collected from acid mine drainage in Go-seong and Yeon-hwa, Korea. We conducted the batch experiments at the influences of parameters, such as the adaptation of bacteria and pulp density of the mine waste. In the adaptation case, the value of pH in 1'st adaptation bacteria sample exhibited lower than in 2'nd adaptation bacteria sample. And the content of both Cu and Zn at 1'st adaptation bacteria sample appeared lower than at 2'nd adaptation bacteria sample. In the SEM analysis, the rod-shaped bacteria with 1μm in length were observed on the filter paper (pore size - 0.45μm). The results of pulp density experiments revealed that the content of both Cu and Zn increased with increasing pulp density, since the increment of pulp density resulted in the enhancement of bioleaching capacity.

Control order and visuomotor strategy development for joystick-steered underground shuttle cars.

PubMed

Cloete, Steven; Zupanc, Christine; Burgess-Limerick, Robin; Wallis, Guy

2014-09-01

In this simulator-based study, we aimed to quantify performance differences between joystick steering systems using first-order and second-order control, which are used in underground coal mining shuttle cars. In addition, we conducted an exploratory analysis of how users of the more difficult, second-order system changed their behavior over time. Evidence from the visuomotor control literature suggests that higher-order control devices are not intuitive, which could pose a significant risk to underground mine personnel, equipment, and infrastructure. Thirty-six naive participants were randomly assigned to first- and second-order conditions and completed three experimental trials comprising sequences of 90 degrees turns in a virtual underground mine environment, with velocity held constant at 9 km/h(-1). Performance measures were lateral deviation, steering angle variability, high-frequency steering content, joystick activity, and cumulative time in collision with the virtual mine wall. The second-order control group exhibited significantly poorer performance for all outcome measures. In addition, a series of correlation analyses revealed that changes in strategy were evident in the second-order group but not the first-order group. Results were consistent with previous literature indicating poorer performance with higher-order control devices and caution against the adoption of the second-order joystick system for underground shuttle cars. Low-cost, portable simulation platforms may provide an effective basis for operator training and recruitment.

Effects of diesel exhaust aftertreatment devices on concentrations and size distribution of aerosols in underground mine air.

PubMed

Bugarski, Aleksandar D; Schnakenberg, George H; Hummer, Ion A; Cauda, Emanuele; Janisko, Samuel I; Patts, Larry D

2009-09-01

Three types of uncatalyzed diesel particulate filter (DPF) systems, three types of high-temperature disposable filter elements (DFEs), and one diesel oxidation catalytic converter (DOC) were evaluated in underground mine conditions for their effects on the concentrations and size distributions of diesel aerosols. Those effects were compared with the effects of a standard muffler. The experimental work was conducted directly in an underground environment using a unique diesel laboratory developed in an underground experimental mine. The DPF systems reduced total mass of aerosols in the mine air approximately 10-fold for light-load and 20-fold or more for high-load test conditions. The DFEs offered similar reductions in aerosol mass concentrations. The efficiency of the new DFEs significantly increased with accumulation of operating time and buildup of diesel particulate matter in the porous structure of the filter elements. A single laundering process did not exhibit substantial effects on performance of the filter element The effectiveness of DPFs and DFEs in removing aerosols by number was strongly influenced by engine operating mode. The concentrations of nucleation mode aerosols in the mine air were found to be substantially higher for both DPFs and DFEs when the engine was operated at high-load modes than at low-load modes. The effects of the DOC on mass and number concentrations of aerosols in mine air were relatively minor when compared to those of the DPF and DFE systems.

Numerical modeling anti-personnel blast mines coupled to a deformable leg structure

NASA Astrophysics Data System (ADS)

Cronin, Duane; Worswick, Mike; Williams, Kevin; Bourget, Daniel; Pageau, Gilles

2001-06-01

The development of improved landmine protective footwear requires an understanding of the physics and damage mechanisms associated with a close proximity blast event. Numerical models have been developed to model surrogate mines buried in soil using the Arbitrary Lagrangian Eulerian (ALE) technique to model the explosive and surrounding air, while the soil is modeled as a deformable Lagrangian solid. The advantage of the ALE model is the ability to model large deformations, such as the expanding gases of a high explosive. This model has been validated using the available experimental data [1]. The effect of varying depth of burial and soil conditions has been investigated with these numerical models and compares favorably to data in the literature. The surrogate landmine model has been coupled to a numerical model of a Simplified Lower Leg (SLL), which is designed to mimic the response and failure mechanisms of a human leg. The SLL consists of a bone and tissue simulant arranged as concentric cylinders. A new strain-rate dependant hyperelastic material model for the tissue simulant, ballistic gelatin, has been developed to model the tissue simulant response. The polymeric bone simulant material has been characterized and implemented as a strain-rate dependent material in the numerical model. The numerical model results agree with the measured response of the SLL during experimental blast tests [2]. The numerical model results are used to explain the experimental data. These models predict that, for a surface or sub-surface buried anti-personnel mine, the coupling between the mine and SLL is an important effect. In addition, the soil properties have a significant effect on the load transmitted to the leg. [1] Bergeron, D., Walker, R. and Coffey, C., 1998, “Detonation of 100-Gram Anti-Personnel Mine Surrogate Charges in Sand”, Report number SR 668, Defence Research Establishment Suffield, Canada. [2] Bourget, D., Williams, K., Pageau, G., and Cronin, D., “AP Mine Blast Effects on Surrogate Lower Leg”, Military Aspects of Ballistics and Shock, MABS 16, 2000.

Biblio-MetReS for user-friendly mining of genes and biological processes in scientific documents.

PubMed

Usie, Anabel; Karathia, Hiren; Teixidó, Ivan; Alves, Rui; Solsona, Francesc

2014-01-01

One way to initiate the reconstruction of molecular circuits is by using automated text-mining techniques. Developing more efficient methods for such reconstruction is a topic of active research, and those methods are typically included by bioinformaticians in pipelines used to mine and curate large literature datasets. Nevertheless, experimental biologists have a limited number of available user-friendly tools that use text-mining for network reconstruction and require no programming skills to use. One of these tools is Biblio-MetReS. Originally, this tool permitted an on-the-fly analysis of documents contained in a number of web-based literature databases to identify co-occurrence of proteins/genes. This approach ensured results that were always up-to-date with the latest live version of the databases. However, this 'up-to-dateness' came at the cost of large execution times. Here we report an evolution of the application Biblio-MetReS that permits constructing co-occurrence networks for genes, GO processes, Pathways, or any combination of the three types of entities and graphically represent those entities. We show that the performance of Biblio-MetReS in identifying gene co-occurrence is as least as good as that of other comparable applications (STRING and iHOP). In addition, we also show that the identification of GO processes is on par to that reported in the latest BioCreAtIvE challenge. Finally, we also report the implementation of a new strategy that combines on-the-fly analysis of new documents with preprocessed information from documents that were encountered in previous analyses. This combination simultaneously decreases program run time and maintains 'up-to-dateness' of the results. http://metres.udl.cat/index.php/downloads, metres.cmb@gmail.com.

Finding novel relationships with integrated gene-gene association network analysis of Synechocystis sp. PCC 6803 using species-independent text-mining.

PubMed

Kreula, Sanna M; Kaewphan, Suwisa; Ginter, Filip; Jones, Patrik R

2018-01-01

The increasing move towards open access full-text scientific literature enhances our ability to utilize advanced text-mining methods to construct information-rich networks that no human will be able to grasp simply from 'reading the literature'. The utility of text-mining for well-studied species is obvious though the utility for less studied species, or those with no prior track-record at all, is not clear. Here we present a concept for how advanced text-mining can be used to create information-rich networks even for less well studied species and apply it to generate an open-access gene-gene association network resource for Synechocystis sp. PCC 6803, a representative model organism for cyanobacteria and first case-study for the methodology. By merging the text-mining network with networks generated from species-specific experimental data, network integration was used to enhance the accuracy of predicting novel interactions that are biologically relevant. A rule-based algorithm (filter) was constructed in order to automate the search for novel candidate genes with a high degree of likely association to known target genes by (1) ignoring established relationships from the existing literature, as they are already 'known', and (2) demanding multiple independent evidences for every novel and potentially relevant relationship. Using selected case studies, we demonstrate the utility of the network resource and filter to ( i ) discover novel candidate associations between different genes or proteins in the network, and ( ii ) rapidly evaluate the potential role of any one particular gene or protein. The full network is provided as an open-source resource.

Host-Guest Complexes with Protein-Ligand-Like Affinities: Computational Analysis and Design

PubMed Central

Moghaddam, Sarvin; Inoue, Yoshihisa

2009-01-01

It has recently been discovered that guests combining a nonpolar core with cationic substituents bind cucurbit[7]uril (CB[7]) in water with ultra-high affinities. The present study uses the Mining Minima algorithm to study the physics of these extraordinary associations and to computationally test a new series of CB[7] ligands designed to bind with similarly high affinity. The calculations reproduce key experimental observations regarding the affinities of ferrocene-based guests with CB[7] and β-cyclodextrin and provide a coherent view of the roles of electrostatics and configurational entropy as determinants of affinity in these systems. The newly designed series of compounds is based on a bicyclo[2.2.2]octane core, which is similar in size and polarity to the ferrocene core of the existing series. Mining Minima predicts that these new compounds will, like the ferrocenes, bind CB[7] with extremely high affinities. PMID:19133781

Improving the Repair Planning System for Mining Equipment on the Basis of Non-destructive Evaluation Data

NASA Astrophysics Data System (ADS)

Drygin, Michael; Kuryshkin, Nicholas

2017-11-01

The article tells about forming a new concept of scheduled preventive repair system of the equipment at coal mining enterprises, based on the use of modem non-destructive evaluation methods. The approach to the solution for this task is based on the system-oriented analysis of the regulatory documentation, non-destructive evaluation methods and means, experimental studies with compilation of statistics and subsequent grapho-analytical analysis. The main result of the work is a feasible explanation of using non-destructive evaluation methods within the current scheduled preventive repair system, their high efficiency and the potential of gradual transition to condition-based maintenance. In practice wide use of nondestructive evaluation means w;ill allow to reduce significantly the number of equipment failures and to repair only the nodes in pre-accident condition. Considering the import phase-out policy, the solution for this task will allow to adapt the SPR system to Russian market economy conditions and give the opportunity of commercial move by reducing the expenses for maintenance of Russian-made and imported equipment.

Feature Mining and Health Assessment for Gearboxes Using Run-Up/Coast-Down Signals

PubMed Central

Zhao, Ming; Lin, Jing; Miao, Yonghao; Xu, Xiaoqiang

2016-01-01

Vibration signals measured in the run-up/coast-down (R/C) processes usually carry rich information about the health status of machinery. However, a major challenge in R/C signals analysis lies in how to exploit more diagnostic information, and how this information could be properly integrated to achieve a more reliable maintenance decision. Aiming at this problem, a framework of R/C signals analysis is presented for the health assessment of gearbox. In the proposed methodology, we first investigate the data preprocessing and feature selection issues for R/C signals. Based on that, a sparsity-guided feature enhancement scheme is then proposed to extract the weak phase jitter associated with gear defect. In order for an effective feature mining and integration under R/C, a generalized phase demodulation technique is further established to reveal the evolution of modulation feature with operating speed and rotation angle. The experimental results indicate that the proposed methodology could not only detect the presence of gear damage, but also offer a novel insight into the dynamic behavior of gearbox. PMID:27827831

Feature Mining and Health Assessment for Gearboxes Using Run-Up/Coast-Down Signals.

PubMed

Zhao, Ming; Lin, Jing; Miao, Yonghao; Xu, Xiaoqiang

2016-11-02

Vibration signals measured in the run-up/coast-down (R/C) processes usually carry rich information about the health status of machinery. However, a major challenge in R/C signals analysis lies in how to exploit more diagnostic information, and how this information could be properly integrated to achieve a more reliable maintenance decision. Aiming at this problem, a framework of R/C signals analysis is presented for the health assessment of gearbox. In the proposed methodology, we first investigate the data preprocessing and feature selection issues for R/C signals. Based on that, a sparsity-guided feature enhancement scheme is then proposed to extract the weak phase jitter associated with gear defect. In order for an effective feature mining and integration under R/C, a generalized phase demodulation technique is further established to reveal the evolution of modulation feature with operating speed and rotation angle. The experimental results indicate that the proposed methodology could not only detect the presence of gear damage, but also offer a novel insight into the dynamic behavior of gearbox.

EVALUATION OF THE EFFECTS OF WEATHERING ON A 50-YEAR OLD RETORTED OIL-SHALE WASTE PILE, RULISON EXPERIMENTAL RETORT, COLORADO.

USGS Publications Warehouse

Tuttle, Michele L.W.; Dean, Walter E.; Ackerman, Daniel J.; ,

1985-01-01

An oil-shale mine and experimental retort were operated near Rulison, Colorado by the U. S. Bureau of Mines from 1926 to 1929. Samples from seven drill cores from a retorted oil-shale waste pile were analyzed to determine 1) the chemical and mineral composition of the retorted oil shale and 2) variations in the composition that could be attributed to weathering. Unweathered, freshly-mined samples of oil shale from the Mahogany zone of the Green River Formation and slope wash collected away from the waste pile were also analyzed for comparison. The waste pile is composed of oil shale retorted under either low-temperature (400-500 degree C) or high-temperature (750 degree C) conditions. The results of the analyses show that the spent shale within the waste pile contains higher concentrations of most elements relative to unretorted oil shale.

Tidal analysis and Arrival Process Mining Using Automatic Identification System (AIS) Data

DTIC Science & Technology

2017-01-01

files, organized by location. The data were processed using the Python programming language (van Rossum and Drake 2001), the Pandas data analysis...ER D C/ CH L TR -1 7- 2 Coastal Inlets Research Program Tidal Analysis and Arrival Process Mining Using Automatic Identification System...17-2 January 2017 Tidal Analysis and Arrival Process Mining Using Automatic Identification System (AIS) Data Brandan M. Scully Coastal and

MSL: Facilitating automatic and physical analysis of published scientific literature in PDF format.

PubMed

Ahmed, Zeeshan; Dandekar, Thomas

2015-01-01

Published scientific literature contains millions of figures, including information about the results obtained from different scientific experiments e.g. PCR-ELISA data, microarray analysis, gel electrophoresis, mass spectrometry data, DNA/RNA sequencing, diagnostic imaging (CT/MRI and ultrasound scans), and medicinal imaging like electroencephalography (EEG), magnetoencephalography (MEG), echocardiography  (ECG), positron-emission tomography (PET) images. The importance of biomedical figures has been widely recognized in scientific and medicine communities, as they play a vital role in providing major original data, experimental and computational results in concise form. One major challenge for implementing a system for scientific literature analysis is extracting and analyzing text and figures from published PDF files by physical and logical document analysis. Here we present a product line architecture based bioinformatics tool 'Mining Scientific Literature (MSL)', which supports the extraction of text and images by interpreting all kinds of published PDF files using advanced data mining and image processing techniques. It provides modules for the marginalization of extracted text based on different coordinates and keywords, visualization of extracted figures and extraction of embedded text from all kinds of biological and biomedical figures using applied Optimal Character Recognition (OCR). Moreover, for further analysis and usage, it generates the system's output in different formats including text, PDF, XML and images files. Hence, MSL is an easy to install and use analysis tool to interpret published scientific literature in PDF format.

What's Mine Is Mine: Twelve-Month-Olds Use Possessive Pronouns to Identify Referents

ERIC Educational Resources Information Center

Saylor, Megan M.; Ganea, Patricia A.; Vazquez, Maria D.

2011-01-01

This research investigated 12-month-olds' ability to use person-specific language to determine to which of several absent things a person is referring. Infants were introduced to two experimenters who played separately with a different ball. One researcher asked infants to retrieve her object when both balls were hidden. Infants selected the…

30 CFR 785.13 - Experimental practices mining.

Code of Federal Regulations, 2010 CFR

2010-07-01

... purposes, or to allow an alternative postmining land use, and may be undertaken if they are approved by the... accordance with the requirements of subchapter G of this chapter. (b) An application for an experimental... duration of the experimental practice, and any special monitoring which will be conducted; (2) How use of...

Mariano Lake Mine: Legal Documents and Settlements

EPA Pesticide Factsheets

Mariano Lake Mine Administrative Order on Consent (AOC) with Statement of Work (SOW) and Mariano Lake Mine Site Settlement Agreement for Engineering Evaluation/Cost Analysis and Statement of Work (SOW) for the Mariano Lake Mine Site.

A cost-benefit analysis of landfill mining and material recycling in China

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhou, Chuanbin, E-mail: cbzhou@rcees.ac.cn; Gong, Zhe; Hu, Junsong

Highlights: • Assessing the economic feasibility of landfill mining. • We applied a cost-benefit analysis model for landfill mining. • Four material cycling and energy recovery scenarios were designed. • We used net present value to evaluate the cost-benefit efficiency. - Abstract: Landfill mining is an environmentally-friendly technology that combines the concepts of material recycling and sustainable waste management, and it has received a great deal of worldwide attention because of its significant environmental and economic potential in material recycling, energy recovery, land reclamation and pollution prevention. This work applied a cost-benefit analysis model for assessing the economic feasibility, whichmore » is important for promoting landfill mining. The model includes eight indicators of costs and nine indicators of benefits. Four landfill mining scenarios were designed and analyzed based on field data. The economic feasibility of landfill mining was then evaluated by the indicator of net present value (NPV). According to our case study of a typical old landfill mining project in China (Yingchun landfill), rental of excavation and hauling equipment, waste processing and material transportation were the top three costs of landfill mining, accounting for 88.2% of the total cost, and the average cost per unit of stored waste was 12.7 USD ton{sup −1}. The top three benefits of landfill mining were electricity generation by incineration, land reclamation and recycling soil-like materials. The NPV analysis of the four different scenarios indicated that the Yingchun landfill mining project could obtain a net positive benefit varying from 1.92 million USD to 16.63 million USD. However, the NPV was sensitive to the mode of land reuse, the availability of energy recovery facilities and the possibility of obtaining financial support by avoiding post-closure care.« less

Study of application of ERTS-A imagery to fracture-related mine safety hazards in the coal mining industry

NASA Technical Reports Server (NTRS)

Wier, C. E.; Wobber, F. J.; Russell, O. R.; Martin, K. R. (Principal Investigator)

1973-01-01

The author has identified the following significant results. Mined land reclamation analysis procedures developed within the Indiana portion of the Illinois Coal Basin were independently tested in Ohio utilizing 1:80,000 scale enlargements of ERTS-1 image 1029-15361-7 (dated August 21, 1972). An area in Belmont County was selected for analysis due to the extensive surface mining and the different degrees of reclamation occurring in this area. Contour mining in this area provided the opportunity to extend techniques developed for analysis of relatively flat mining areas in Indiana to areas of rolling topography in Ohio. The analysts had no previous experience in the area. Field investigations largely confirmed office analysis results although in a few areas estimates of vegetation percentages were found to be too high. In one area this error approximated 25%. These results suggest that systematic ERTS-1 analysis in combination with selective field sampling can provide reliable vegetation percentage estimates in excess of 25% accuracy with minimum equipment investment and training. The utility of ERTS-1 for practical and reasonably reliable update of mined lands information for groups with budget limitations is suggested. Many states can benefit from low cost updates using ERTS-1 imagery from public sources.

Radon dynamics and reduction in an underground mine in Brazil. Implications for workers' exposure.

PubMed

Evangelista, H; Pereira, E B; Fernandes, H M; Sampaio, M

2002-01-01

This work was aimed at studying the behaviour of 222Rn in an experimental underground copper mine in Brazil with a single entrance. The 222Rn concentrations, meaured by using a dynamic radon measuring technique. varied between 30.5 Bq.m(-3), during ventilated conditions applied to the mine galleries, and 19.4 x 10(3) Bq.(-3) for non-ventilated conditions and when operational mining activities were conducted inside. High radon concentration surges were observed after blasting and drilling activities. In the cases of inadequate ventilation, it was estimated that workers could be subjected to exposures as high as 10 microSv.h(-1), only due to 222Rn and its short-lived progeny. The results show the importance of real-time measurements to evaluate radon dynamics during mining operations.

Air pollutant intrusion into the Wieliczka Salt Mine

USGS Publications Warehouse

Salmon, L.G.; Cass, G.R.; Kozlowski, R.; Hejda, A.; Spiker, E. C.; Bates, A.L.

1996-01-01

The Wieliczka Salt Mine World Cultural Heritage Site contains many rock salt sculptures that are threatened by water vapor condensation from the mine ventilation air. Gaseous and particulate air pollutant concentrations have been measured both outdoors and within the Wieliczka Salt Mine, along with pollutant deposition fluxes to surfaces within the mine. One purpose of these measurements was to determine whether or not low deliquescence point ionic materials (e.g., NH4NO3) are accumulating on surfaces to an extent that would exacerbate the water vapor condensation problems in the mine. It was found that pollutant gases including SO2 and HNO3 present in outdoor air are removed rapidly and almost completely from the air within the mine by deposition to surfaces. Sulfur isotope analyses confirm the accumulation of air pollutant-derived sulfur in liquid dripping from surfaces within the mine. Particle deposition onto interior surfaces in the mine is apparent, with resulting soiling of some of those sculptures that have been carved from translucent rock salt. Water accumulation by salt sculpture surfaces was studied both experimentally and by approximate thermodynamic calculations. Both approaches suggest that the pollutant deposits on the sculpture surfaces lower the relative humidity (RH) at which a substantial amount of liquid water will accumulate by 1% to several percent. The extraordinarily low SO2 concentrations within the mine may explain the apparent success of a respiratory sanatorium located deep within the mine.

Analysis of Mining Terrain Deformation Characteristics with Deformation Information System

NASA Astrophysics Data System (ADS)

Blachowski, Jan; Milczarek, Wojciech; Grzempowski, Piotr

2014-05-01

Mapping and prediction of mining related deformations of the earth surface is an important measure for minimising threat to surface infrastructure, human population, the environment and safety of the mining operation itself arising from underground extraction of useful minerals. The number of methods and techniques used for monitoring and analysis of mining terrain deformations is wide and increasing with the development of geographical information technologies. These include for example: terrestrial geodetic measurements, global positioning systems, remote sensing, spatial interpolation, finite element method modelling, GIS based modelling, geological modelling, empirical modelling using the Knothe theory, artificial neural networks, fuzzy logic calculations and other. The aim of this paper is to introduce the concept of an integrated Deformation Information System (DIS) developed in geographic information systems environment for analysis and modelling of various spatial data related to mining activity and demonstrate its applications for mapping and visualising, as well as identifying possible mining terrain deformation areas with various spatial modelling methods. The DIS concept is based on connected modules that include: the spatial database - the core of the system, the spatial data collection module formed by: terrestrial, satellite and remote sensing measurements of the ground changes, the spatial data mining module for data discovery and extraction, the geological modelling module, the spatial data modeling module with data processing algorithms for spatio-temporal analysis and mapping of mining deformations and their characteristics (e.g. deformation parameters: tilt, curvature and horizontal strain), the multivariate spatial data classification module and the visualization module allowing two-dimensional interactive and static mapping and three-dimensional visualizations of mining ground characteristics. The Systems's functionality has been presented on the case study of a coal mining region in SW Poland where it has been applied to study characteristics and map mining induced ground deformations in a city in the last two decades of underground coal extraction and in the first decade after the end of mining. The mining subsidence area and its deformation parameters (tilt and curvature) have been calculated and the latter classified and mapped according to the Polish regulations. In addition possible areas of ground deformation have been indicated based on multivariate spatial data analysis of geological and mining operation characteristics with the geographically weighted regression method.

An Evaluation of Practical Applicability of Multi-Assortment Production Break-Even Analysis based on Mining Companies

NASA Astrophysics Data System (ADS)

Fuksa, Dariusz; Trzaskuś-Żak, Beata; Gałaś, Zdzisław; Utrata, Arkadiusz

2017-03-01

In the practice of mining companies, the vast majority of them produce more than one product. The analysis of the break-even, which is referred to as CVP (Cost-Volume-Profit) analysis (Wilkinson, 2005; Czopek, 2003) in their case is significantly constricted, given the necessity to include multi-assortment structure in the analysis, which may have more than 20 types of assortments (depending on the grain size) in their offer, as in the case of open-pit mines. The article presents methods of evaluation of break-even (volume and value) for both a single-assortment production and a multi-assortment production. The complexity of problem of break-even evaluation for multi-assortment production has resulted in formation of many methods, and, simultaneously, various approaches to its analysis, especially differences in accounting fixed costs, which may be either totally accounted for among particular assortments, relating to the whole company or partially accounted for among particular assortments and partially relating to the company, as a whole. The evaluation of the chosen methods of break-even analysis, given the availability of data, was based on two examples of mining companies: an open-pit mine of rock materials and an underground hard coal mine. The selection of methods was set by the available data provided by the companies. The data for the analysis comes from internal documentation of the mines - financial statements, breakdowns and cost calculations.

Soil acidification as a confounding factor on metal phytotoxicity in soils spiked with copper-rich mine wastes.

PubMed

Ginocchio, Rosanna; De la Fuente, Luz María; Sánchez, Pablo; Bustamante, Elena; Silva, Yasna; Urrestarazu, Paola; Rodríguez, Patricio H

2009-10-01

Pollution of soil with mine wastes results in both Cu enrichment and soil acidification. This confounding effect may be very important in terms of phytotoxicity, because pH is a key parameter influencing Cu solubility in soil solution. Laboratory toxicity tests were used to assess the effect of acidification by acidic mine wastes on Cu solubility and on root elongation of barley (Hordeum vulgare L.). Three contrasting substrates (two soils and a commercial sand) and two acidic, Cu-rich mine wastes (oxidized tailings [OxT] and smelter dust [SmD]) were selected as experimental materials. Substrates were spiked with a fixed amount of either SmD or OxT, and the pH of experimental mixtures was then modified in the range of 4.0 to 6.0 and 7.0 using PIPES (piperazine-1,4-bis(2-ethanesulfonic acid)), MES (2-(N-morpholino)ethanesulfonic acid), and MOPS (3-(N-Morpholino)-propanesulfonic acid) buffers. Chemical (pore-water Cu and pH) and toxicological (root length of barley plants) parameters were determined for experimental mixtures. Addition of SmD and OxT to substrates resulted in acidification (0.11-1.16 pH units) and high levels of soluble Cu and Zn. Neutralization of experimental mixtures with MES (pH 6.0) and MOPS (pH 7.0) buffers resulted in a marked decrease in soluble Cu and Zn, but the intensity of the effect was substrate-dependent. Adjustment of soil pH above the range normally considered to be toxic to plants (pH in water extract, > 5.5) significantly reduced metal toxicity in barley, but phytotoxicity was not completely eliminated. The present results stress the importance of considering confounding effects on derivation of toxicity thresholds to plants when using laboratory phytotoxicity tests.

Simulation of patient flow in multiple healthcare units using process and data mining techniques for model identification.

PubMed

Kovalchuk, Sergey V; Funkner, Anastasia A; Metsker, Oleg G; Yakovlev, Aleksey N

2018-06-01

An approach to building a hybrid simulation of patient flow is introduced with a combination of data-driven methods for automation of model identification. The approach is described with a conceptual framework and basic methods for combination of different techniques. The implementation of the proposed approach for simulation of the acute coronary syndrome (ACS) was developed and used in an experimental study. A combination of data, text, process mining techniques, and machine learning approaches for the analysis of electronic health records (EHRs) with discrete-event simulation (DES) and queueing theory for the simulation of patient flow was proposed. The performed analysis of EHRs for ACS patients enabled identification of several classes of clinical pathways (CPs) which were used to implement a more realistic simulation of the patient flow. The developed solution was implemented using Python libraries (SimPy, SciPy, and others). The proposed approach enables more a realistic and detailed simulation of the patient flow within a group of related departments. An experimental study shows an improved simulation of patient length of stay for ACS patient flow obtained from EHRs in Almazov National Medical Research Centre in Saint Petersburg, Russia. The proposed approach, methods, and solutions provide a conceptual, methodological, and programming framework for the implementation of a simulation of complex and diverse scenarios within a flow of patients for different purposes: decision making, training, management optimization, and others. Copyright © 2018 Elsevier Inc. All rights reserved.

Prioritizing abandoned coal mine reclamation projects within the contiguous United States using geographic information system extrapolation.

PubMed

Gorokhovich, Yuri; Reid, Matthew; Mignone, Erica; Voros, Andrew

2003-10-01

Coal mine reclamation projects are very expensive and require coordination of local and federal agencies to identify resources for the most economic way of reclaiming mined land. Location of resources for mine reclamation is a spatial problem. This article presents a methodology that allows the combination of spatial data on resources for the coal mine reclamation and uses GIS analysis to develop a priority list of potential mine reclamation sites within contiguous United States using the method of extrapolation. The extrapolation method in this study was based on the Bark Camp reclamation project. The mine reclamation project at Bark Camp, Pennsylvania, USA, provided an example of the beneficial use of fly ash and dredged material to reclaim 402,600 sq mi of a mine abandoned in the 1980s. Railroads provided transportation of dredged material and fly ash to the site. Therefore, four spatial elements contributed to the reclamation project at Bark Camp: dredged material, abandoned mines, fly ash sources, and railroads. Using spatial distribution of these data in the contiguous United States, it was possible to utilize GIS analysis to prioritize areas where reclamation projects similar to Bark Camp are feasible. GIS analysis identified unique occurrences of all four spatial elements used in the Bark Camp case for each 1 km of the United States territory within 20, 40, 60, 80, and 100 km radii from abandoned mines. The results showed the number of abandoned mines for each state and identified their locations. The federal or state governments can use these results in mine reclamation planning.

WIPP conceptual design report. Addendum A. Design calculations for Waste Isolation Pilot Plant (WIPP)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Not Available

1977-04-01

The design calculations for the Waste Isolation Pilot Plant (WIPP) are presented. The following categories are discussed: general nuclear calculations; radwaste calculations; structural calculations; mechanical calculations; civil calculations; electrical calculations; TRU waste surface facility time and motion analysis; shaft sinking procedures; hoist time and motion studies; mining system analysis; mine ventilation calculations; mine structural analysis; and miscellaneous underground calculations.

Location and stability analysis of the Michigamme Underground Mine for the US-41 re-alignment in Marquette County, Michigan.

DOT National Transportation Integrated Search

2008-08-01

A proposed realignment of US-41 near Michigamme, Michigan will be located over an abandoned underground iron ore : mine. The mine, known as the Michigamme Mine, was started in 1872 and closed in 1901. Initial mining operations : were started in seven...

Detection of antipersonnel (AP) mines using mechatronics approach

NASA Astrophysics Data System (ADS)

Shahri, Ali M.; Naghdy, Fazel

1998-09-01

At present there are approximately 110 million land-mines scattered around the world in 64 countries. The clearance of these mines takes place manually. Unfortunately, on average for every 5000 mines cleared one mine clearer is killed. A Mine Detector Arm (MDA) using mechatronics approach is under development in this work. The robot arm imitates manual hand- prodding technique for mine detection. It inserts a bayonet into the soil and models the dynamics of the manipulator and environment parameters, such as stiffness variation in the soil to control the impact caused by contacting a stiff object. An explicit impact control scheme is applied as the main control scheme, while two different intelligent control methods are designed to deal with uncertainties and varying environmental parameters. Firstly, a neuro-fuzzy adaptive gain controller (NFAGC) is designed to adapt the force gain control according to the estimated environment stiffness. Then, an adaptive neuro-fuzzy plus PID controller is employed to switch from a conventional PID controller to neuro-fuzzy impact control (NFIC), when an impact is detected. The developed control schemes are validated through computer simulation and experimental work.

Co-evolutionary data mining for fuzzy rules: automatic fitness function creation phase space, and experiments

NASA Astrophysics Data System (ADS)

Smith, James F., III; Blank, Joseph A.

2003-03-01

An approach is being explored that involves embedding a fuzzy logic based resource manager in an electronic game environment. Game agents can function under their own autonomous logic or human control. This approach automates the data mining problem. The game automatically creates a cleansed database reflecting the domain expert's knowledge, it calls a data mining function, a genetic algorithm, for data mining of the data base as required and allows easy evaluation of the information extracted. The co-evolutionary fitness functions, chromosomes and stopping criteria for ending the game are discussed. Genetic algorithm and genetic program based data mining procedures are discussed that automatically discover new fuzzy rules and strategies. The strategy tree concept and its relationship to co-evolutionary data mining are examined as well as the associated phase space representation of fuzzy concepts. The overlap of fuzzy concepts in phase space reduces the effective strategies available to adversaries. Co-evolutionary data mining alters the geometric properties of the overlap region known as the admissible region of phase space significantly enhancing the performance of the resource manager. Procedures for validation of the information data mined are discussed and significant experimental results provided.

Research of land resources comprehensive utilization of coal mining in plain area based on GIS: case of Panyi Coal Mine of Huainan Mining Group Corp.

NASA Astrophysics Data System (ADS)

Dai, Chunxiao; Wang, Songhui; Sun, Dian; Chen, Dong

2007-06-01

The result of land use in coalfield is important to sustainable development in resourceful city. For surface morphology being changed by subsidence, the mining subsidence becomes the main problem to land use with the negative influence of ecological environment, production and steadily develop in coal mining areas. Taking Panyi Coal Mine of Huainan Mining Group Corp as an example, this paper predicted and simulated the mining subsidence in Matlab environment on the basis of the probability integral method. The change of land use types of early term, medium term and long term was analyzed in accordance with the results of mining subsidence prediction with GIS as a spatial data management and spatial analysis tool. The result of analysis showed that 80% area in Panyi Coal Mine be affected by mining subsidence and 52km2 perennial waterlogged area was gradually formed. The farmland ecosystem was gradually turned into wetland ecosystem in most study area. According to the economic and social development and natural conditions of mining area, calculating the ecological environment, production and people's livelihood, this paper supplied the plan for comprehensive utilization of land resource. In this plan, intervention measures be taken during the coal mining and the mining subsidence formation and development, and this method can solve the problems of Land use at the relative low cost.

Solar Data Mining at Georgia State University

NASA Astrophysics Data System (ADS)

Angryk, R.; Martens, P. C.; Schuh, M.; Aydin, B.; Kempton, D.; Banda, J.; Ma, R.; Naduvil-Vadukootu, S.; Akkineni, V.; Küçük, A.; Filali Boubrahimi, S.; Hamdi, S. M.

2016-12-01

In this talk we give an overview of research projects related to solar data analysis that are conducted at Georgia State University. We will provide update on multiple advances made by our research team on the analysis of image parameters, spatio-temporal patterns mining, temporal data analysis and our experiences with big, heterogeneous solar data visualization, analysis, processing and storage. We will talk about up-to-date data mining methodologies, and their importance for big data-driven solar physics research.

Experimental Measurement of In Situ Stress

NASA Astrophysics Data System (ADS)

Tibbo, Maria; Milkereit, Bernd; Nasseri, Farzine; Schmitt, Douglas; Young, Paul

2016-04-01

The World Stress Map data is determined by stress indicators including earthquake focal mechanisms, in situ measurement in mining, oil and gas boreholes as well as the borehole cores, and geologic data. Unfortunately, these measurements are not only infrequent but sometimes infeasible, and do not provide nearly enough data points with high accuracy to correctly infer stress fields in deep mines around the world. Improvements in stress measurements of Earth's crust is fundamental to several industries such as oil and gas, mining, nuclear waste management, and enhanced geothermal systems. Quantifying the state of stress and the geophysical properties of different rock types is a major complication in geophysical monitoring of deep mines. Most stress measurement techniques involve either the boreholes or their cores, however these measurements usually only give stress along one axis, not the complete stress tensor. The goal of this project is to investigate a new method of acquiring a complete stress tensor of the in situ stress in the Earth's crust. This project is part of a comprehensive, exploration geophysical study in a deep, highly stressed mine located in Sudbury, Ontario, Canada, and focuses on two boreholes located in this mine. These boreholes are approximately 400 m long with NQ diameters and are located at depths of about 1300 - 1600 m and 1700 - 2000 m. Two borehole logging surveys were performed on both boreholes, October 2013 and July 2015, in order to perform a time-lapse analysis of the geophysical changes in the mine. These multi-parameter surveys include caliper, full waveform sonic, televiewer, chargeability (IP), and resistivity. Laboratory experiments have been performed on borehole core samples of varying geologies from each borehole. These experiments have measured the geophysical properties including elastic modulus, bulk modulus, P- and S-wave velocities, and density. The apparatus' used for this project are geophysical imaging cells capable of hydrostatic stress (σ1 = σ2 = σ3), differential stress (σ1 > σ2 = σ3), and the unique true triaxial stress (σ1 > σ2 > σ3). Velocity surveys can be acquired along all three axes, and therefore the effects of σ1,σ2,σ3 on the velocity-stress curve can be obtained. These geophysical cells are being used to reproduce the borehole P- and S-wave velocities by altering the differential stress, allowing for the unique position of determining the stress tensor. Currently, results have been obtained for differential stress (σ1 > σ2 = σ3), and true triaxial experiments will determine if σ3 is the missing factor to reproducing the borehole velocities. This project is the first to combine time - lapse borehole logging data and experimental laboratory data to infer a complete stress tensor.

Tailings dam-break flow - Analysis of sediment transport

NASA Astrophysics Data System (ADS)

Aleixo, Rui; Altinakar, Mustafa

2015-04-01

A common solution to store mining debris is to build tailings dams near the mining site. These dams are usually built with local materials such as mining debris and are more vulnerable than concrete dams (Rico et al. 2008). of The tailings and the pond water generally contain heavy metals and various toxic chemicals used in ore extraction. Thus, the release of tailings due to a dam-break can have severe ecological consequences in the environment. A tailings dam-break has many similarities with a common dam-break flow. It is highly transient and can be severely descructive. However, a significant difference is that the released sediment-water mixture will behave as a non-Newtonian flow. Existing numerical models used to simulate dam-break flows do not represent correctly the non-Newtonian behavior of tailings under a dam-break flow and may lead to unrealistic and incorrect results. The need for experiments to extract both qualitative and quantitative information regarding these flows is therefore real and actual. The present paper explores an existing experimental data base presented in Aleixo et al. (2014a,b) to further characterize the sediment transport under conditions of a severe transient flow and to extract quantitative information regarding sediment flow rate, sediment velocity, sediment-sediment interactions a among others. Different features of the flow are also described and analyzed in detail. The analysis is made by means of imaging techniques such as Particle Image Velocimetry and Particle Tracking Velocimetry that allow extracting not only the velocity field but the Lagrangian description of the sediments as well. An analysis of the results is presented and the limitations of the presented experimental approach are discussed. References Rico, M., Benito, G., Salgueiro, AR, Diez-Herrero, A. and Pereira, H.G. (2008) Reported tailings dam failures: A review of the European incidents in the worldwide context , Journal of Hazardous Materials, 152, 846-852 . Aleixo, R., Ozeren, Y., Altinakar, M. and Wren, D. (2014a) Velocity Measurements using Particle Tracking in Tailings dam Failure experiments, Proceedings of the 3rd IAHR-Europe conference, Porto, Portugal. Aleixo, R., Ozeren, Y., Altinakar, M. (2014b) Tailing dam-break analysis by means of a combined PIV-PTV tool, Proceedings of the River Flow Conference, Lausanne, Switzerland.

SIMPL: A Simplified Model-Based Program for the Analysis and Visualization of Groundwater Rebound in Abandoned Mines to Prevent Contamination of Water and Soils by Acid Mine Drainage

PubMed Central

Kim, Sung-Min

2018-01-01

Cessation of dewatering following underground mine closure typically results in groundwater rebound, because mine voids and surrounding strata undergo flooding up to the levels of the decant points, such as shafts and drifts. SIMPL (Simplified groundwater program In Mine workings using the Pipe equation and Lumped parameter model), a simplified lumped parameter model-based program for predicting groundwater levels in abandoned mines, is presented herein. The program comprises a simulation engine module, 3D visualization module, and graphical user interface, which aids data processing, analysis, and visualization of results. The 3D viewer facilitates effective visualization of the predicted groundwater level rebound phenomenon together with a topographic map, mine drift, goaf, and geological properties from borehole data. SIMPL is applied to data from the Dongwon coal mine and Dalsung copper mine in Korea, with strong similarities in simulated and observed results. By considering mine workings and interpond connections, SIMPL can thus be used to effectively analyze and visualize groundwater rebound. In addition, the predictions by SIMPL can be utilized to prevent the surrounding environment (water and soil) from being polluted by acid mine drainage. PMID:29747480

Stability Analysis of Railway Subgrade in Mining Area Based on Dinsar

NASA Astrophysics Data System (ADS)

Xu, J.; Hu, J.; Ding, J.

2018-04-01

DInSAR technology have been applied to monitor the mining subsidence and the stability of the railway subgrade. A total of 10 Sentinel-1A images acquired from 2015/9/26 to 2016/2/23 were used in DInSAR analysis. The study mining area is about 13.4 km2. Mining have induced serious land subsidence involve a large area that causing different levels of damages to infrastructures on the land. There is an important railway near the mining area, the DInSAR technology is applied to analyse the subsidence near the railway, which can warn early the possible deformation that may occur during underground mining. The DInSAR results was verified by the field measurement. The results show that the mining did not cause subsidence of railway subgrade and did not affect the stability of railway subgrade.

Sustainability Activities In The Mining Sector: Current Status And Challenges Ahead Limestone Mining In Nusakambangan

NASA Astrophysics Data System (ADS)

Ayuningrum, Theresia Vika; Purnaweni, Hartuti

2018-02-01

Potential Karst area in Nusakambangan has an important role in maintaining the balance of nature. But with the existence of mining activities, will automatically change the environmental conditions there. In order for the utilization of resources to meet the rules of optimization between the interests of mining and sustainability of the environment so in every mining sector activities required a variety of environmental studies. The purpose of this study is to find out how the analysis of environmental management due to limestone mining activities in Nusakambangan so that it can be known the management of mining areas are optimal, wise based on ecological principles, and sustainability. In qualitative research methods, data analysis using description percentage, with the type of data collected in the form of primary data and secondary data.

Characteristics of coal mine ventilation air flows.

PubMed

Su, Shi; Chen, Hongwei; Teakle, Philip; Xue, Sheng

2008-01-01

Coal mine methane (CMM) is not only a greenhouse gas but also a wasted energy resource if not utilised. Underground coal mining is by far the most important source of fugitive methane emissions, and approximately 70% of all coal mining related methane is emitted to the atmosphere through mine ventilation air. Therefore, research and development on mine methane mitigation and utilisation now focuses on methane emitted from underground coal mines, in particular ventilation air methane (VAM) capture and utilisation. To date, most work has focused on the oxidation of very low concentration methane. These processes may be classified based on their combustion kinetic mechanisms into thermal oxidation and catalytic oxidation. VAM mitigation/utilisation technologies are generally divided into two basic categories: ancillary uses and principal uses. However, it is possible that the characteristics of ventilation air flows, for example the variations in methane concentration and the presence of certain compounds, which have not been reported so far, could make some potential VAM mitigation and utilisation technologies unfeasible if they cannot cope with the characteristics of mine site ventilation air flows. Therefore, it is important to understand the characteristics of mine ventilation air flows. Moreover, dust, hydrogen sulphide, sulphur dioxide, and other possible compounds emitted through mine ventilation air into the atmosphere are also pollutants. Therefore, this paper presents mine-site experimental results on the characteristics of mine ventilation air flows, including methane concentration and its variations, dust loadings, particle size, mineral matter of the dust, and other compounds in the ventilation air flows. The paper also discusses possible correlations between ventilation air characteristics and underground mining activities.

String Mining in Bioinformatics

NASA Astrophysics Data System (ADS)

Abouelhoda, Mohamed; Ghanem, Moustafa

Sequence analysis is a major area in bioinformatics encompassing the methods and techniques for studying the biological sequences, DNA, RNA, and proteins, on the linear structure level. The focus of this area is generally on the identification of intra- and inter-molecular similarities. Identifying intra-molecular similarities boils down to detecting repeated segments within a given sequence, while identifying inter-molecular similarities amounts to spotting common segments among two or multiple sequences. From a data mining point of view, sequence analysis is nothing but string- or pattern mining specific to biological strings. For a long time, this point of view, however, has not been explicitly embraced neither in the data mining nor in the sequence analysis text books, which may be attributed to the co-evolution of the two apparently independent fields. In other words, although the word "data-mining" is almost missing in the sequence analysis literature, its basic concepts have been implicitly applied. Interestingly, recent research in biological sequence analysis introduced efficient solutions to many problems in data mining, such as querying and analyzing time series [49,53], extracting information from web pages [20], fighting spam mails [50], detecting plagiarism [22], and spotting duplications in software systems [14].

Application of EREP imagery to fracture-related mine safety hazards and environmental problems in mining

NASA Technical Reports Server (NTRS)

Wier, C. E.; Wobber, F. J.; Amato, R. V.; Russell, O. R. (Principal Investigator)

1973-01-01

The author has identified the following significant results. Numerous fracture traces were detected on both the color transparencies and black and white spectral bands. Fracture traces of value to mining hazards analysis were noted on the EREP imagery which could not be detected on either the ERTS-1 or high altitude aircraft color infrared photography. Several areas of mine subsidence occurring in the Busseron Creek area near Sullivan, Indiana were successfully identified using color photography. Skylab photography affords an increase over comparable scale ERTS-1 imagery in level of information obtained in mined lands inventory and reclamation analysis. A review of EREP color photography permitted the identification of a substantial number of non-fuel mines within the Southern Indiana test area. A new mine was detected on the EREP photography without prior data. EREP has definite value for estimating areal changes in active mines and for detecting new non-fuel mines. Gob piles and slurry ponds of several acres could be detected on the S-190B color photography when observed in association with large scale mining operations. Apparent degradation of water quality resulting from acid mine drainage and/or siltation was noted in several ponds or small lakes and appear to be related to intensive mining activity near Sullivan, Indiana.

Spatial variability of sediment erosion processes using GIS analysis within watersheds in a historically mined region, Patagonia Mountains, Arizona

USGS Publications Warehouse

Brady, Laura M.; Gray, Floyd; Wissler, Craig A.; Guertin, D. Phillip

2001-01-01

In this study, a geographic information system (GIS) is used to integrate and accurately map field studies, information from remotely sensed data, watershed models, and the dispersion of potentially toxic mine waste and tailings. The purpose of this study is to identify erosion rates and net sediment delivery of soil and mine waste/tailings to the drainage channel within several watershed regions to determine source areas of sediment delivery as a method of quantifying geo-environmental analysis of transport mechanisms in abandoned mine lands in arid climate conditions. Users of this study are the researchers interested in exploration of approaches to depicting historical activity in an area which has no baseline data records for environmental analysis of heavily mined terrain.

Application of text mining in the biomedical domain.

PubMed

Fleuren, Wilco W M; Alkema, Wynand

2015-03-01

In recent years the amount of experimental data that is produced in biomedical research and the number of papers that are being published in this field have grown rapidly. In order to keep up to date with developments in their field of interest and to interpret the outcome of experiments in light of all available literature, researchers turn more and more to the use of automated literature mining. As a consequence, text mining tools have evolved considerably in number and quality and nowadays can be used to address a variety of research questions ranging from de novo drug target discovery to enhanced biological interpretation of the results from high throughput experiments. In this paper we introduce the most important techniques that are used for a text mining and give an overview of the text mining tools that are currently being used and the type of problems they are typically applied for. Copyright © 2015 Elsevier Inc. All rights reserved.

Applied technology for mine waste water decontamination in the uranium ores extraction from Romania

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bejenaru, C.; Filip, G.; Vacariu, V.T.

1996-12-31

The exploitation of uranium ores in Romania is carried out in underground mines. In all exploited uranium deposits, mine waste waters results and will still result after the closure of uranium ore extraction activity. The mine waters are radioactively contaminated with uranium and its decay products being a hazard both for underground waters as for the environment. This paper present the results of research work carried out by authors for uranium elimination from waste waters as the problems involved during the exploitation process of the existent equipment as its maintenance in good experimental conditions. The main waste water characteristics aremore » discussed: solids as suspension, uranium, radium, mineral salts, pH, etc. The moist suitable way to eliminate uranium from mine waste waters is the ion exchange process based on ion exchangers in fluidized bed. A flowsheet is given with main advantages resulted.« less

Utility of EXAFS in characterization and speciation of mercury-bearing mine wastes

USGS Publications Warehouse

Kim, C.S.; Rytuba, J.J.; Brown, Gordon E.

1999-01-01

Extensive mining of large mercury deposits located in the California Coast Range has resulted in mercury contamination of both the local environment and water supplies. The solubility, dispersal, and ultimate fate of mercury are all affected by its chemical speciation, which can be most readily determined in a direct fashion using EXAFS spectroscopy. EXAFS spectra of mine wastes collected from several mercury mines in the California Coast Range with mercury concentrations ranging from 230 to 1060 mg/kg (ppm) have been analyzed using a spectral database of mercury minerals and sorbed mercury complexes. While some calcines have been found to consist almost exclusively of mercuric sulfide, HgS, others contain additional, more soluble mercury phases, indicating a greater potential for the release of mercury into solution. This experimental approach can provide a quantitative measurement of the mercury compounds present and may serve as an indicator of the bioavailability and toxicity levels of mercury mine wastes.

Quantification of Operational Risk Using A Data Mining

NASA Technical Reports Server (NTRS)

Perera, J. Sebastian

1999-01-01

What is Data Mining? - Data Mining is the process of finding actionable information hidden in raw data. - Data Mining helps find hidden patterns, trends, and important relationships often buried in a sea of data - Typically, automated software tools based on advanced statistical analysis and data modeling technology can be utilized to automate the data mining process

77 FR 34402 - Notice of Availability of the Final Land Use Analysis and Final Environmental Impact Statement...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-06-11

... mining would occur directly beneath the lake itself and no surface mining would take place. East Lynn... Rockspring have approved mining and reclamation plans from the West Virginia Department of Environmental... plan purposes if leases were to be issued and mine plans approved. The Office of Surface Mining...

CoBOP: Electro-Optic Identification Laser Line Sean Sensors

DTIC Science & Technology

1998-01-01

Electro - Optic Identification Sensors Project[1] is to develop and demonstrate high resolution underwater electro - optic (EO) imaging sensors, and associated image processing/analysis methods, for rapid visual identification of mines and mine-like contacts (MLCs). Identification of MLCs is a pressing Fleet need. During MCM operations, sonar contacts are classified as mine-like if they are sufficiently similar to signatures of mines. Each contact classified as mine-like must be identified as a mine or not a mine. During MCM operations in littoral areas,

Diversity and role of plasmids in adaptation of bacteria inhabiting the Lubin copper mine in Poland, an environment rich in heavy metals.

PubMed

Dziewit, Lukasz; Pyzik, Adam; Szuplewska, Magdalena; Matlakowska, Renata; Mielnicki, Sebastian; Wibberg, Daniel; Schlüter, Andreas; Pühler, Alfred; Bartosik, Dariusz

2015-01-01

The Lubin underground mine, is one of three mining divisions in the Lubin-Glogow Copper District in Lower Silesia province (Poland). It is the source of polymetallic ore that is rich in copper, silver and several heavy metals. Black shale is also significantly enriched in fossil organic matter in the form of long-chain hydrocarbons, polycyclic aromatic hydrocarbons, organic acids, esters, thiophenes and metalloporphyrins. Biological analyses have revealed that this environment is inhabited by extremophilic bacteria and fungi. Kupfershiefer black shale and samples of water, bottom and mineral sediments from the underground (below 600 m) Lubin mine were taken and 20 bacterial strains were isolated and characterized. All exhibited multi-resistant and hypertolerant phenotypes to heavy metals. We analyzed the plasmidome of these strains in order to evaluate the diversity and role of mobile DNA in adaptation to the harsh conditions of the mine environment. Experimental and bioinformatic analyses of 11 extrachromosomal replicons were performed. Three plasmids, including a broad-host-range replicon containing a Tn3 family transposon, carried genes conferring resistance to arsenic, cadmium, cobalt, mercury and zinc. Functional analysis revealed that the resistance modules exhibit host specificity, i.e., they may increase or decrease tolerance to toxic ions depending on the host strain. The other identified replicons showed diverse features. Among them we identified a catabolic plasmid encoding enzymes involved in the utilization of histidine and vanillate, a putative plasmid-like prophage carrying genes responsible for NAD biosynthesis, and two repABC-type plasmids containing virulence-associated genes. These findings provide an unique molecular insight into the pool of extrachromosomal replicons and highlight their role in the biology and adaptation of extremophilic bacteria inhabiting terrestrial deep subsurface.

Finding novel relationships with integrated gene-gene association network analysis of Synechocystis sp. PCC 6803 using species-independent text-mining

PubMed Central

Kreula, Sanna M.; Kaewphan, Suwisa; Ginter, Filip

2018-01-01

The increasing move towards open access full-text scientific literature enhances our ability to utilize advanced text-mining methods to construct information-rich networks that no human will be able to grasp simply from ‘reading the literature’. The utility of text-mining for well-studied species is obvious though the utility for less studied species, or those with no prior track-record at all, is not clear. Here we present a concept for how advanced text-mining can be used to create information-rich networks even for less well studied species and apply it to generate an open-access gene-gene association network resource for Synechocystis sp. PCC 6803, a representative model organism for cyanobacteria and first case-study for the methodology. By merging the text-mining network with networks generated from species-specific experimental data, network integration was used to enhance the accuracy of predicting novel interactions that are biologically relevant. A rule-based algorithm (filter) was constructed in order to automate the search for novel candidate genes with a high degree of likely association to known target genes by (1) ignoring established relationships from the existing literature, as they are already ‘known’, and (2) demanding multiple independent evidences for every novel and potentially relevant relationship. Using selected case studies, we demonstrate the utility of the network resource and filter to (i) discover novel candidate associations between different genes or proteins in the network, and (ii) rapidly evaluate the potential role of any one particular gene or protein. The full network is provided as an open-source resource. PMID:29844966

Combinatorial and high-throughput screening of materials libraries: review of state of the art.

PubMed

Potyrailo, Radislav; Rajan, Krishna; Stoewe, Klaus; Takeuchi, Ichiro; Chisholm, Bret; Lam, Hubert

2011-11-14

Rational materials design based on prior knowledge is attractive because it promises to avoid time-consuming synthesis and testing of numerous materials candidates. However with the increase of complexity of materials, the scientific ability for the rational materials design becomes progressively limited. As a result of this complexity, combinatorial and high-throughput (CHT) experimentation in materials science has been recognized as a new scientific approach to generate new knowledge. This review demonstrates the broad applicability of CHT experimentation technologies in discovery and optimization of new materials. We discuss general principles of CHT materials screening, followed by the detailed discussion of high-throughput materials characterization approaches, advances in data analysis/mining, and new materials developments facilitated by CHT experimentation. We critically analyze results of materials development in the areas most impacted by the CHT approaches, such as catalysis, electronic and functional materials, polymer-based industrial coatings, sensing materials, and biomaterials.

A teaching-learning sequence on a socio-scientific issue: analysis and evaluation of its implementation in the classroom*

NASA Astrophysics Data System (ADS)

Vázquez-Alonso, Ángel; Aponte, Abdiel; Manassero-Mas, María-Antonia; Montesano, Marisa

2016-07-01

This study examines the effectiveness of a teaching-learning sequence (TLS) to improve the understanding of the influences and interactions between a technology (mining) and society. The aim of the study is also to show the possibility of both teaching and assessing the most innovative issues and aspects of scientific competence and their impact on the understanding of the nature of science. The methodology used a quasi-experimental, pre-post-test design with a control group, with pre-post-test differences as the empirical indicators of improved understanding. Improvements were modest, as the empirical differences (pre-post and experimental-control group) were not large, but the experimental group scored more highly than the control group. The areas that showed improvement were identified. The paper includes the TLS itself and the standardized assessment tools that are functional and transferable to other researchers and teachers.

The improved Apriori algorithm based on matrix pruning and weight analysis

NASA Astrophysics Data System (ADS)

Lang, Zhenhong

2018-04-01

This paper uses the matrix compression algorithm and weight analysis algorithm for reference and proposes an improved matrix pruning and weight analysis Apriori algorithm. After the transactional database is scanned for only once, the algorithm will construct the boolean transaction matrix. Through the calculation of one figure in the rows and columns of the matrix, the infrequent item set is pruned, and a new candidate item set is formed. Then, the item's weight and the transaction's weight as well as the weight support for items are calculated, thus the frequent item sets are gained. The experimental result shows that the improved Apriori algorithm not only reduces the number of repeated scans of the database, but also improves the efficiency of data correlation mining.

The Necessity of Public Relations for Sustainable Mining Activities

NASA Astrophysics Data System (ADS)

Lee, Hyunbock; Ji, Sangwoo

2015-04-01

This paper reports research about the necessity of image making for sustainable mine developments in the Republic of Korea. One of the big risks in mining activities is mining area residents opposing mine developments and operations. Analysis of the media reports on disputes between mining companies and residents can determine causes of opposing mine developments, dispute process, and influences of disputes on processes of mining projects. To do this, civil complaints from 2009 to 2012 and 24 media reports since 2000 on opposing mining activities are analyzed. And, to analyze difficulties of mining companies, the survey is conducted to target to mining companies. 57 representatives of mining companies are participated in the survey. The result of analysis cited that the major reasons of anti-mining activities are environmental degradation and reduced agricultural productivity. And specifically because of water pollution (50%), crop damages (33%), and mining dust pollution (21%), communities of mining area are against mine developments and operations. However, 25% of residents have experience of the damage caused by mining activities and the remaining 75% of residents opposing mining activities simply have anxiety about mining pollution. In the past, construction-oriented, environment-unfriendly mining projects had lasted. And while mine reclamation had been postponed in abandoned mines, mining area residents had suffered from mining pollution. So, mining area residents are highly influenced by the prejudice that mining activities are harmful to mining area communities. Current mining projects in South Korea, unlike the past mining activity, focus on minimizing environmental damage and contributing to mining area communities financially. But, in many case of disputes between mining companies and mining area residents, the both cannot reach an agreements because of the negative prejudice. Moreover, some communities categorically refuse any mining activity. On the other hand, in the survey to determine what the greatest difficulties of the current mining activities, 54% of mining companies chose environmental regulations, 26% of mining companies chose conflicts between mine area residents and mining companies. Environmental regulations are may defined as the greatest difficulty of current mining activities. But most of environmental regulation's problems are caused by frictions with residents, because all of South Korean mines are very close to villages. So, the biggest difficulty of mining activities can be defined conflicts between residents and mining companies. Moreover, general people in South Korea including some mining engineers recognize the mining industry as a declined and pollution industry. Without clear understanding of mining activities, any mine developments and policies related to mining activities cannot be made by rational discussions. And, if their recognition is not formed in a rational way, it will be turned to extreme fear or blind hatred. Therefore, to understand mining activities correctly, the effective public relations strategy is necessary such as corporate advertisements or public advertisements.

The Analysis of Object-Based Change Detection in Mining Area: a Case Study with Pingshuo Coal Mine

NASA Astrophysics Data System (ADS)

Zhang, M.; Zhou, W.; Li, Y.

2017-09-01

Accurate information on mining land use and land cover change are crucial for monitoring and environmental change studies. In this paper, RapidEye Remote Sensing Image (Map 2012) and SPOT7 Remote Sensing Image (Map 2015) in Pingshuo Mining Area are selected to monitor changes combined with object-based classification and change vector analysis method, we also used R in highresolution remote sensing image for mining land classification, and found the feasibility and the flexibility of open source software. The results show that (1) the classification of reclaimed mining land has higher precision, the overall accuracy and kappa coefficient of the classification of the change region map were 86.67 % and 89.44 %. It's obvious that object-based classification and change vector analysis which has a great significance to improve the monitoring accuracy can be used to monitor mining land, especially reclaiming mining land; (2) the vegetation area changed from 46 % to 40 % accounted for the proportion of the total area from 2012 to 2015, and most of them were transformed into the arable land. The sum of arable land and vegetation area increased from 51 % to 70 %; meanwhile, build-up land has a certain degree of increase, part of the water area was transformed into arable land, but the extent of the two changes is not obvious. The result illustrated the transformation of reclaimed mining area, at the same time, there is still some land convert to mining land, and it shows the mine is still operating, mining land use and land cover are the dynamic procedure.

Numerical simulation of trace element transport on subsurface environment pollution in coal mine spoil.

PubMed

Qiang, Xue; Bing, Liang; Hui-yun, Wang; Lei, Liu

2006-01-01

An understanding of the dynamic behavior of trace elements leaching from coal mine spoil is important in predicting the groundwater quality. The relationship between trace element concentrations and leaching times, pH values of the media is studied. Column leaching tests conducted in the laboratory showed that there was a close correlation between pH value and trace element concentrations. The longer the leaching time, the higher the trace element concentrations. Different trace elements are differently affected by pH values of leaching media. A numerical model for water flow and trace element transport has been developed based on analyzing the characteristics of migration and transformation of trace elements leached from coal mine spoil. Solutions to the coupled model are accomplished by Eulerian-Lagrangian localized adjoint method. Numerical simulation shows that rainfall intensity determined maximum leaching depth. As rainfall intensity is 3.6ml/s, the outflow concentrations indicate a breakthrough of trace elements beyond the column base, with peak concentration at 90cm depth. And the subsurface pollution range has a trend of increase with time. The model simulations are compared to experimental results of trace element concentrations, with reasonable agreement between them. The analysis and modeling of trace elements suggested that the infiltration of rainwater through the mine spoil might lead to potential groundwater pollution. It provides theoretical evidence for quantitative assessment soil-water quality of trace element transport on environment pollution.

Combination of automated high throughput platforms, flow cytometry, and hierarchical clustering to detect cell state.

PubMed

Kitsos, Christine M; Bhamidipati, Phani; Melnikova, Irena; Cash, Ethan P; McNulty, Chris; Furman, Julia; Cima, Michael J; Levinson, Douglas

2007-01-01

This study examined whether hierarchical clustering could be used to detect cell states induced by treatment combinations that were generated through automation and high-throughput (HT) technology. Data-mining techniques were used to analyze the large experimental data sets to determine whether nonlinear, non-obvious responses could be extracted from the data. Unary, binary, and ternary combinations of pharmacological factors (examples of stimuli) were used to induce differentiation of HL-60 cells using a HT automated approach. Cell profiles were analyzed by incorporating hierarchical clustering methods on data collected by flow cytometry. Data-mining techniques were used to explore the combinatorial space for nonlinear, unexpected events. Additional small-scale, follow-up experiments were performed on cellular profiles of interest. Multiple, distinct cellular profiles were detected using hierarchical clustering of expressed cell-surface antigens. Data-mining of this large, complex data set retrieved cases of both factor dominance and cooperativity, as well as atypical cellular profiles. Follow-up experiments found that treatment combinations producing "atypical cell types" made those cells more susceptible to apoptosis. CONCLUSIONS Hierarchical clustering and other data-mining techniques were applied to analyze large data sets from HT flow cytometry. From each sample, the data set was filtered and used to define discrete, usable states that were then related back to their original formulations. Analysis of resultant cell populations induced by a multitude of treatments identified unexpected phenotypes and nonlinear response profiles.

Assessment of the possible reuse of MSW coming from landfill mining of old open dumpsites.

PubMed

Masi, S; Caniani, D; Grieco, E; Lioi, D S; Mancini, I M

2014-03-01

The present study addresses the theme of recycling potential of old open dumpsites by using landfill mining. Attention is focused on the possible reuse of the residual finer fraction (<4 mm), which constitutes more than 60% of the total mined material, sampled in the old open dumpsite of Lavello (Southern Italy). We propose a protocol of analysis of the landfill material that links chemical analyses and environmental bioassays. This protocol is used to evaluate the compatibility of the residual matrix for the disposal in temporary storages and the formation of "bio-soils" to be used in geo-environmental applications, such as the construction of barrier layers of landfills, or in environmental remediation activities. Attention is mainly focused on the presence of heavy metals and on the possible interaction with test organisms. Chemical analyses of the residual matrix and leaching tests showed that the concentration of heavy metals is always below the legislation limits. Biological acute tests (with Lepidum sativum, Vicia faba and Lactuca sativa) do not emphasize adverse effects to the growth of the plant species, except the bioassay with V. faba, which showed a dose-response effect. The new developed chronic bioassay test with Spartium junceum showed a good adaptation to stress conditions induced by the presence of the mined landfill material. In conclusion, the conducted experimental activities demonstrated the suitability of the material to be used for different purposes. Copyright © 2013 Elsevier Ltd. All rights reserved.

Microarray data and gene expression statistics for Saccharomyces cerevisiae exposed to simulated asbestos mine drainage.

PubMed

Driscoll, Heather E; Murray, Janet M; English, Erika L; Hunter, Timothy C; Pivarski, Kara; Dolci, Elizabeth D

2017-08-01

Here we describe microarray expression data (raw and normalized), experimental metadata, and gene-level data with expression statistics from Saccharomyces cerevisiae exposed to simulated asbestos mine drainage from the Vermont Asbestos Group (VAG) Mine on Belvidere Mountain in northern Vermont, USA. For nearly 100 years (between the late 1890s and 1993), chrysotile asbestos fibers were extracted from serpentinized ultramafic rock at the VAG Mine for use in construction and manufacturing industries. Studies have shown that water courses and streambeds nearby have become contaminated with asbestos mine tailings runoff, including elevated levels of magnesium, nickel, chromium, and arsenic, elevated pH, and chrysotile asbestos-laden mine tailings, due to leaching and gradual erosion of massive piles of mine waste covering approximately 9 km 2 . We exposed yeast to simulated VAG Mine tailings leachate to help gain insight on how eukaryotic cells exposed to VAG Mine drainage may respond in the mine environment. Affymetrix GeneChip® Yeast Genome 2.0 Arrays were utilized to assess gene expression after 24-h exposure to simulated VAG Mine tailings runoff. The chemistry of mine-tailings leachate, mine-tailings leachate plus yeast extract peptone dextrose media, and control yeast extract peptone dextrose media is also reported. To our knowledge this is the first dataset to assess global gene expression patterns in a eukaryotic model system simulating asbestos mine tailings runoff exposure. Raw and normalized gene expression data are accessible through the National Center for Biotechnology Information Gene Expression Omnibus (NCBI GEO) Database Series GSE89875 (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE89875).

Simulation of switching overvoltages in the mine electric power supply system

NASA Astrophysics Data System (ADS)

Ivanchenko, D. I.; Novozhilov, N. G.

2017-02-01

Overvoltages occur in mine power supply systems during switching off consumers with high inductive load, such as transformers, reactors and electrical machines. Overvoltages lead to an increase of insulation degradation rate and may cause electric faults, power outage, fire and explosion of methane and coal dust. This paper is dedicated to simulation of vacuum circuit breaker switching overvoltages in a mine power supply system by means of Simulink MATLAB. The model of the vacuum circuit breaker implements simulation of transient recovery voltage, current chopping and an electric arc. Obtained results were compared to available experimental data.

Computational fluid dynamic modeling of a medium-sized surface mine blasthole drill shroud

PubMed Central

Zheng, Y.; Reed, W.R.; Zhou, L.; Rider, J.P.

2016-01-01

The Pittsburgh Mining Research Division of the U.S. National Institute for Occupational Safety and Health (NIOSH) recently developed a series of models using computational fluid dynamics (CFD) to study airflows and respirable dust distribution associated with a medium-sized surface blasthole drill shroud with a dry dust collector system. Previously run experiments conducted in NIOSH’s full-scale drill shroud laboratory were used to validate the models. The setup values in the CFD models were calculated from experimental data obtained from the drill shroud laboratory and measurements of test material particle size. Subsequent simulation results were compared with the experimental data for several test scenarios, including 0.14 m3/s (300 cfm) and 0.24 m3/s (500 cfm) bailing airflow with 2:1, 3:1 and 4:1 dust collector-to-bailing airflow ratios. For the 2:1 and 3:1 ratios, the calculated dust concentrations from the CFD models were within the 95 percent confidence intervals of the experimental data. This paper describes the methodology used to develop the CFD models, to calculate the model input and to validate the models based on the experimental data. Problem regions were identified and revealed by the study. The simulation results could be used for future development of dust control methods for a surface mine blasthole drill shroud. PMID:27932851

Application of multivariate analysis to investigate the trace element contamination in top soil of coal mining district in Jorong, South Kalimantan, Indonesia

NASA Astrophysics Data System (ADS)

Pujiwati, Arie; Nakamura, K.; Watanabe, N.; Komai, T.

2018-02-01

Multivariate analysis is applied to investigate geochemistry of several trace elements in top soils and their relation with the contamination source as the influence of coal mines in Jorong, South Kalimantan. Total concentration of Cd, V, Co, Ni, Cr, Zn, As, Pb, Sb, Cu and Ba was determined in 20 soil samples by the bulk analysis. Pearson correlation is applied to specify the linear correlation among the elements. Principal Component Analysis (PCA) and Cluster Analysis (CA) were applied to observe the classification of trace elements and contamination sources. The results suggest that contamination loading is contributed by Cr, Cu, Ni, Zn, As, and Pb. The elemental loading mostly affects the non-coal mining area, for instances the area near settlement and agricultural land use. Moreover, the contamination source is classified into the areas that are influenced by the coal mining activity, the agricultural types, and the river mixing zone. Multivariate analysis could elucidate the elemental loading and the contamination sources of trace elements in the vicinity of coal mine area.

Coal Mine Roadway Stability in Soft Rock: A Case Study

NASA Astrophysics Data System (ADS)

Shen, Baotang

2014-11-01

Roadway instability has always been a major concern in deep underground coal mines where the surrounding rock strata and coal seams are weak and the in situ stresses are high. Under the high overburden and tectonic stresses, roadways could collapse or experience excessive deformation, which not only endangers mining personnel but could also reduce the functionality of the roadway and halt production. This paper describes a case study on the stability of roadways in an underground coal mine in Shanxi Province, China. The mine was using a longwall method to extract coal at a depth of approximately 350 m. Both the coal seam and surrounding rock strata were extremely weak and vulnerable to weathering. Large roadway deformation and severe roadway instabilities had been experienced in the past, hence, an investigation of the roadway failure mechanism and new support designs were needed. This study started with an in situ stress measurement programme to determine the stress orientation and magnitude in the mine. It was found that the major horizontal stress was more than twice the vertical stress in the East-West direction, perpendicular to the gateroads of the longwall panel. The high horizontal stresses and low strength of coal and surrounding rock strata were the main causes of roadway instabilities. Detailed numerical modeling was conducted to evaluate the roadway stability and deformation under different roof support scenarios. Based on the modeling results, a new roadway support design was proposed, which included an optimal cable/bolt arrangement, full length grouting, and high pre-tensioning of bolts and cables. It was expected the new design could reduce the roadway deformation by 50 %. A field experiment using the new support design was carried out by the mine in a 100 m long roadway section. Detailed extensometry and stress monitorings were conducted in the experimental roadway section as well as sections using the old support design. The experimental section produced a much better roadway profile than the previous roadway sections. The monitoring data indicated that the roadway deformation in the experimental section was at least 40-50 % less than the previous sections. This case study demonstrated that through careful investigation and optimal support design, roadway stability in soft rock conditions can be significantly improved.

An improved clustering algorithm based on reverse learning in intelligent transportation

NASA Astrophysics Data System (ADS)

Qiu, Guoqing; Kou, Qianqian; Niu, Ting

2017-05-01

With the development of artificial intelligence and data mining technology, big data has gradually entered people's field of vision. In the process of dealing with large data, clustering is an important processing method. By introducing the reverse learning method in the clustering process of PAM clustering algorithm, to further improve the limitations of one-time clustering in unsupervised clustering learning, and increase the diversity of clustering clusters, so as to improve the quality of clustering. The algorithm analysis and experimental results show that the algorithm is feasible.

Performance analysis of a multispectral system for mine detection in the littoral zone

NASA Astrophysics Data System (ADS)

Hargrove, John T.; Louchard, Eric

2004-09-01

Science & Technology International (STI) has developed, under contract with the Office of Naval Research, a system of multispectral airborne sensors and processing algorithms capable of detecting mine-like objects in the surf zone. STI has used this system to detect mine-like objects in a littoral environment as part of blind tests at Kaneohe Marine Corps Base Hawaii, and Panama City, Florida. The airborne and ground subsystems are described. The detection algorithm is graphically illustrated. We report on the performance of the system configured to operate without a human in the loop. A subsurface (underwater bottom proud mine in the surf zone and moored mine in shallow water) mine detection capability is demonstrated in the surf zone, and in shallow water with wave spillage and foam. Our analysis demonstrates that this STI-developed multispectral airborne mine detection system provides a technical foundation for a viable mine counter-measures system for use prior to an amphibious assault.

A Principal Component Analysis/Fuzzy Comprehensive Evaluation for Rockburst Potential in Kimberlite

NASA Astrophysics Data System (ADS)

Pu, Yuanyuan; Apel, Derek; Xu, Huawei

2018-02-01

Kimberlite is an igneous rock which sometimes bears diamonds. Most of the diamonds mined in the world today are found in kimberlite ores. Burst potential in kimberlite has not been investigated, because kimberlite is mostly mined using open-pit mining, which poses very little threat of rock bursting. However, as the mining depth keeps increasing, the mines convert to underground mining methods, which can pose a threat of rock bursting in kimberlite. This paper focuses on the burst potential of kimberlite at a diamond mine in northern Canada. A combined model with the methods of principal component analysis (PCA) and fuzzy comprehensive evaluation (FCE) is developed to process data from 12 different locations in kimberlite pipes. Based on calculated 12 fuzzy evaluation vectors, 8 locations show a moderate burst potential, 2 locations show no burst potential, and 2 locations show strong and violent burst potential, respectively. Using statistical principles, a Mahalanobis distance is adopted to build a comprehensive fuzzy evaluation vector for the whole mine and the final evaluation for burst potential is moderate, which is verified by a practical rockbursting situation at mine site.

Borehole hydraulic coal mining system analysis

NASA Technical Reports Server (NTRS)

Floyd, E. L.

1977-01-01

The borehole hydraulic coal mining system accesses the coal seam through a hole drilled in the overburden. The mining device is lowered through the hole into the coal seam where it fragments the coal with high pressure water jets which pump it to the surface as a slurry by a jet pump located in the center of the mining device. The coal slurry is then injected into a pipeline for transport to the preparation plant. The system was analyzed for performance in the thick, shallow coal seams of Wyoming, and the steeply pitching seams of western Colorado. Considered were all the aspects of the mining operation for a 20-year mine life, producing 2,640,000 tons/yr. Effects on the environment and the cost of restoration, as well as concern for health and safety, were studied. Assumptions for design of the mine, the analytical method, and results of the analysis are detailed.

Text Mining for Protein Docking

PubMed Central

Badal, Varsha D.; Kundrotas, Petras J.; Vakser, Ilya A.

2015-01-01

The rapidly growing amount of publicly available information from biomedical research is readily accessible on the Internet, providing a powerful resource for predictive biomolecular modeling. The accumulated data on experimentally determined structures transformed structure prediction of proteins and protein complexes. Instead of exploring the enormous search space, predictive tools can simply proceed to the solution based on similarity to the existing, previously determined structures. A similar major paradigm shift is emerging due to the rapidly expanding amount of information, other than experimentally determined structures, which still can be used as constraints in biomolecular structure prediction. Automated text mining has been widely used in recreating protein interaction networks, as well as in detecting small ligand binding sites on protein structures. Combining and expanding these two well-developed areas of research, we applied the text mining to structural modeling of protein-protein complexes (protein docking). Protein docking can be significantly improved when constraints on the docking mode are available. We developed a procedure that retrieves published abstracts on a specific protein-protein interaction and extracts information relevant to docking. The procedure was assessed on protein complexes from Dockground (http://dockground.compbio.ku.edu). The results show that correct information on binding residues can be extracted for about half of the complexes. The amount of irrelevant information was reduced by conceptual analysis of a subset of the retrieved abstracts, based on the bag-of-words (features) approach. Support Vector Machine models were trained and validated on the subset. The remaining abstracts were filtered by the best-performing models, which decreased the irrelevant information for ~ 25% complexes in the dataset. The extracted constraints were incorporated in the docking protocol and tested on the Dockground unbound benchmark set, significantly increasing the docking success rate. PMID:26650466

Comparison of fall and spring planting on strip-mine spoils in the bituminous region of Pennsylvania

Treesearch

Grant Davis

1973-01-01

To evaluate fall versus spring planting of 10 coniferous tree species and 5 hardwood shrub species, experimental plantings were established over a 2-year period on 7 graded strip-mine spoils. In general, initial tree survival was better with spring planting than with fall planting, especially on the more acid sites. Shrubs survived well with both spring and fall...

ERTS-1 data applied to strip mining

NASA Technical Reports Server (NTRS)

Anderson, A. T.; Schubert, J.

1976-01-01

Two coal basins within the western region of the Potomac River Basin contain the largest strip-mining operations in western Maryland and West Virginia. The disturbed strip-mine areas were delineated along with the surrounding geological and vegetation features by using ERTS-1 data in both analog and digital form. The two digital systems employed were (1) the ERTS analysis system, a point-by-point digital analysis of spectral signatures based on known spectral values and (2) the LARS automatic data processing system. These two systems aided in efforts to determine the extent and state of strip mining in this region. Aircraft data, ground-verification information, and geological field studies also aided in the application of ERTS-1 imagery to perform an integrated analysis that assessed the adverse effects of strip mining. The results indicated that ERTS can both monitor and map the extent of strip mining to determine immediately the acreage affected and to indicate where future reclamation and revegetation may be necessary.

Mines Systems Safety Improvement Using an Integrated Event Tree and Fault Tree Analysis

NASA Astrophysics Data System (ADS)

Kumar, Ranjan; Ghosh, Achyuta Krishna

2017-04-01

Mines systems such as ventilation system, strata support system, flame proof safety equipment, are exposed to dynamic operational conditions such as stress, humidity, dust, temperature, etc., and safety improvement of such systems can be done preferably during planning and design stage. However, the existing safety analysis methods do not handle the accident initiation and progression of mine systems explicitly. To bridge this gap, this paper presents an integrated Event Tree (ET) and Fault Tree (FT) approach for safety analysis and improvement of mine systems design. This approach includes ET and FT modeling coupled with redundancy allocation technique. In this method, a concept of top hazard probability is introduced for identifying system failure probability and redundancy is allocated to the system either at component or system level. A case study on mine methane explosion safety with two initiating events is performed. The results demonstrate that the presented method can reveal the accident scenarios and improve the safety of complex mine systems simultaneously.

Using Statistics and Data Mining Approaches to Analyze Male Sexual Behaviors and Use of Erectile Dysfunction Drugs Based on Large Questionnaire Data.

PubMed

Qiao, Zhi; Li, Xiang; Liu, Haifeng; Zhang, Lei; Cao, Junyang; Xie, Guotong; Qin, Nan; Jiang, Hui; Lin, Haocheng

2017-01-01

The prevalence of erectile dysfunction (ED) has been extensively studied worldwide. Erectile dysfunction drugs has shown great efficacy in preventing male erectile dysfunction. In order to help doctors know drug taken preference of patients and better prescribe, it is crucial to analyze who actually take erectile dysfunction drugs and the relation between sexual behaviors and drug use. Existing clinical studies usually used descriptive statistics and regression analysis based on small volume of data. In this paper, based on big volume of data (48,630 questionnaires), we use data mining approaches besides statistics and regression analysis to comprehensively analyze the relation between male sexual behaviors and use of erectile dysfunction drugs for unravelling the characteristic of patients who take erectile dysfunction drugs. We firstly analyze the impact of multiple sexual behavior factors on whether to use the erectile dysfunction drugs. Then, we explore to mine the Decision Rules for Stratification to discover patients who are more likely to take drugs. Based on the decision rules, the patients can be partitioned into four potential groups for use of erectile dysfunction: high potential group, intermediate potential-1 group, intermediate potential-2 group and low potential group. Experimental results show 1) the sexual behavior factors, erectile hardness and time length to prepare (how long to prepares for sexual behaviors ahead of time), have bigger impacts both in correlation analysis and potential drug taking patients discovering; 2) odds ratio between patients identified as low potential and high potential was 6.098 (95% confidence interval, 5.159-7.209) with statistically significant differences in taking drug potential detected between all potential groups.

Data mining with iPlant: a meeting report from the 2013 GARNet workshop, Data mining with iPlant.

PubMed

Martin, Lisa; Cook, Charis; Matasci, Naim; Williams, Jason; Bastow, Ruth

2015-01-01

High-throughput sequencing technologies have rapidly moved from large international sequencing centres to individual laboratory benchtops. These changes have driven the 'data deluge' of modern biology. Submissions of nucleotide sequences to GenBank, for example, have doubled in size every year since 1982, and individual data sets now frequently reach terabytes in size. While 'big data' present exciting opportunities for scientific discovery, data analysis skills are not part of the typical wet bench biologist's experience. Knowing what to do with data, how to visualize and analyse them, make predictions, and test hypotheses are important barriers to success. Many researchers also lack adequate capacity to store and share these data, creating further bottlenecks to effective collaboration between groups and institutes. The US National Science Foundation-funded iPlant Collaborative was established in 2008 to form part of the data collection and analysis pipeline and help alleviate the bottlenecks associated with the big data challenge in plant science. Leveraging the power of high-performance computing facilities, iPlant provides free-to-use cyberinfrastructure to enable terabytes of data storage, improve analysis, and facilitate collaborations. To help train UK plant science researchers to use the iPlant platform and understand how it can be exploited to further research, GARNet organized a four-day Data mining with iPlant workshop at Warwick University in September 2013. This report provides an overview of the workshop, and highlights the power of the iPlant environment for lowering barriers to using complex bioinformatics resources, furthering discoveries in plant science research and providing a platform for education and outreach programmes. © The Author 2014. Published by Oxford University Press on behalf of the Society for Experimental Biology. All rights reserved. For permissions, please email: journals.permissions@oup.com.

Geomechanical characterization of the Upper Carboniferous under thermal stress for the evaluation of a High Temperature - Mine Thermal Energy Storage (HT-MTES)

NASA Astrophysics Data System (ADS)

Hahn, Florian; Brüggemann, Nina; Bracke, Rolf; Alber, Michael

2017-04-01

The goal of this R&D project is to create a technically and economically feasible conceptual model for a High Temperature - Mine Thermal Energy Storage (HT-MTES) for the energetic reuse of a mine on the example of the Prosper-Haniel coal mine in Bottrop, Germany. This project is funded by the "Initiative Energy Storage" program of the German Federal Ministries BMWi, BMU and BMBF. At the end of 2018, the last operative coal mine in North Rhine-Westphalia, Germany (Prosper-Haniel), is going to be closed down, plugged and abandoned. Large amounts of subsurface infrastructures, resembled mainly by open parts of former galleries and mining faces are going to be flooded, after the mine is closed down and therefore have the potential to become an enormous geothermal reservoir for a seasonal heat storage. During the summer non-used (waste) heat from solar thermal power plants, garbage incineration, combined heat and power plants (CHP) or industrial production processes can be stored within dedicated drifts of the mine. During the winter season, this surplus heat can be extracted and directly utilized in commercial and/or residential areas. For the evaluation of such a HT-MTES within a former coal mine, the corresponding geomechanical parameters of the Upper Carboniferous under thermal stress needs to be evaluated. Therefore the main rock types of the Upper Carboniferous (claystone, siltstone and sandstone) are subject to a geomechanical characterization before and after thermal cyclic loadings of temperatures up to 200 °C. The samples have been collected directly from the coal mine Prosper-Haniel within a depth range of 1000 - 1200 m. Unconfined compressive and tensile strengths, as well as triaxial tests were performed at room temperature. Furthermore, a range of petrophysical properties like density, thin-section analysis and P-wave velocities were determined. First results show an indication that the overall strength properties of the samples are not effected by thermal cyclic loadings with temperatures of up to 200 °C. However, a reduction in the Young's modulus was observed in all samples, after thermal cyclic loads were induced. This effect is mainly correlated to a relaxation of the grain bonds and a pore space expansion. Currently, the experimental focus was set on the evaluation of the collected siltstone samples. Therefore further experiments are needed to undermine these results also for the claystone and sandstone samples.

Land Ecological Security Evaluation of Underground Iron Mine Based on PSR Model

NASA Astrophysics Data System (ADS)

Xiao, Xiao; Chen, Yong; Ruan, Jinghua; Hong, Qiang; Gan, Yong

2018-01-01

Iron ore mine provides an important strategic resource to the national economy while it also causes many serious ecological problems to the environment. The study summed up the characteristics of ecological environment problems of underground iron mine. Considering the mining process of underground iron mine, we analysis connections between mining production, resource, environment and economical background. The paper proposed a land ecological security evaluation system and method of underground iron mine based on Pressure-State-Response model. Our application in Chengchao iron mine proves its efficiency and promising guide on land ecological security evaluation.

Measuring MERCI: exploring data mining techniques for examining the neurologic outcomes of stroke patients undergoing endo-vascular therapy at Erlanger Southeast Stroke Center.

PubMed

McNabb, Matthew; Cao, Yu; Devlin, Thomas; Baxter, Blaise; Thornton, Albert

2012-01-01

Mechanical Embolus Removal in Cerebral Ischemia (MERCI) has been supported by medical trials as an improved method of treating ischemic stroke past the safe window of time for administering clot-busting drugs, and was released for medical use in 2004. The importance of analyzing real-world data collected from MERCI clinical trials is key to providing insights on the effectiveness of MERCI. Most of the existing data analysis on MERCI results has thus far employed conventional statistical analysis techniques. To the best of our knowledge, advanced data analytics and data mining techniques have not yet been systematically applied. To address the issue in this thesis, we conduct a comprehensive study on employing state of the art machine learning algorithms to generate prediction criteria for the outcome of MERCI patients. Specifically, we investigate the issue of how to choose the most significant attributes of a data set with limited instance examples. We propose a few search algorithms to identify the significant attributes, followed by a thorough performance analysis for each algorithm. Finally, we apply our proposed approach to the real-world, de-identified patient data provided by Erlanger Southeast Regional Stroke Center, Chattanooga, TN. Our experimental results have demonstrated that our proposed approach performs well.

Radon as a Source of External Background at Homestake Mine

NASA Astrophysics Data System (ADS)

Thomas, Keenan; Mei, Dongming; Zhang, Chao; Gray, Fred; Gaitskell, Richard; Fiorucci, Simon

2009-05-01

External sources of radioactivity are important concerns for experiments planned for DUSEL at the Homestake Mine in Lead, South Dakota. Radon emanation and deposition is a major threat to the targeted sensitivity of low background experimentation such as double beta decay detection and dark matter searches. Methods to reduce and mitigate these measured levels will need to be developed to prevent experimental signals from contamination through airborne radon decays as well as the deposition of radon daughters. Radon levels were measured at various depths at the Homestake Mine in December of 2008, January and March of 2009. These measurements will be useful in the development of an underground ventilation system to dilute radon concentrations in the air and subsequent systems to provide radon-free air to clean rooms, as well as preparing researchers for the hazards they pose to their experiments. In addition, the measured radon level will be used to understand the radon emanation from different types of rock.

MSL: Facilitating automatic and physical analysis of published scientific literature in PDF format

PubMed Central

Ahmed, Zeeshan; Dandekar, Thomas

2018-01-01

Published scientific literature contains millions of figures, including information about the results obtained from different scientific experiments e.g. PCR-ELISA data, microarray analysis, gel electrophoresis, mass spectrometry data, DNA/RNA sequencing, diagnostic imaging (CT/MRI and ultrasound scans), and medicinal imaging like electroencephalography (EEG), magnetoencephalography (MEG), echocardiography  (ECG), positron-emission tomography (PET) images. The importance of biomedical figures has been widely recognized in scientific and medicine communities, as they play a vital role in providing major original data, experimental and computational results in concise form. One major challenge for implementing a system for scientific literature analysis is extracting and analyzing text and figures from published PDF files by physical and logical document analysis. Here we present a product line architecture based bioinformatics tool ‘Mining Scientific Literature (MSL)’, which supports the extraction of text and images by interpreting all kinds of published PDF files using advanced data mining and image processing techniques. It provides modules for the marginalization of extracted text based on different coordinates and keywords, visualization of extracted figures and extraction of embedded text from all kinds of biological and biomedical figures using applied Optimal Character Recognition (OCR). Moreover, for further analysis and usage, it generates the system’s output in different formats including text, PDF, XML and images files. Hence, MSL is an easy to install and use analysis tool to interpret published scientific literature in PDF format. PMID:29721305

Building a glaucoma interaction network using a text mining approach.

PubMed

Soliman, Maha; Nasraoui, Olfa; Cooper, Nigel G F

2016-01-01

The volume of biomedical literature and its underlying knowledge base is rapidly expanding, making it beyond the ability of a single human being to read through all the literature. Several automated methods have been developed to help make sense of this dilemma. The present study reports on the results of a text mining approach to extract gene interactions from the data warehouse of published experimental results which are then used to benchmark an interaction network associated with glaucoma. To the best of our knowledge, there is, as yet, no glaucoma interaction network derived solely from text mining approaches. The presence of such a network could provide a useful summative knowledge base to complement other forms of clinical information related to this disease. A glaucoma corpus was constructed from PubMed Central and a text mining approach was applied to extract genes and their relations from this corpus. The extracted relations between genes were checked using reference interaction databases and classified generally as known or new relations. The extracted genes and relations were then used to construct a glaucoma interaction network. Analysis of the resulting network indicated that it bears the characteristics of a small world interaction network. Our analysis showed the presence of seven glaucoma linked genes that defined the network modularity. A web-based system for browsing and visualizing the extracted glaucoma related interaction networks is made available at http://neurogene.spd.louisville.edu/GlaucomaINViewer/Form1.aspx. This study has reported the first version of a glaucoma interaction network using a text mining approach. The power of such an approach is in its ability to cover a wide range of glaucoma related studies published over many years. Hence, a bigger picture of the disease can be established. To the best of our knowledge, this is the first glaucoma interaction network to summarize the known literature. The major findings were a set of relations that could not be found in existing interaction databases and that were found to be new, in addition to a smaller subnetwork consisting of interconnected clusters of seven glaucoma genes. Future improvements can be applied towards obtaining a better version of this network.

Renewed mining and reclamation: Imapacts on bats and potential mitigation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Brown, P.E.; Berry, R.D.

Historic mining created new roosting habitat for many bat species. Now the same industry has the potential to adversely impact bats. Contemporary mining operations usually occur in historic districts; consequently the old workings are destroyed by open pit operations. Occasionally, underground techniques are employed, resulting in the enlargement or destruction of the original workings. Even during exploratory operations, historic mine openings can be covered as drill roads are bulldozed, or drills can penetrate and collapse underground workings. Nearby blasting associated with mine construction and operation can disrupt roosting bats. Bats can also be disturbed by the entry of mine personnelmore » to collect ore samples or by recreational mine explorers, since the creation of roads often results in easier access. In addition to roost disturbance, other aspects of renewed mining can have adverse impacts on bat populations, and affect even those bats that do not live in mines. Open cyanide ponds, or other water in which toxic chemicals accumulate, can poison bats and other wildlife. The creation of the pits, roads and processing areas often destroys critical foraging habitat, or change drainage patterns. Finally, at the completion of mining, any historic mines still open may be sealed as part of closure and reclamation activities. The net result can be a loss of bats and bat habitat. Conversely, in some contemporary underground operations, future roosting habitat for bats can be fabricated. An experimental approach to the creation of new roosting habitat is to bury culverts or old tires beneath waste rock. Mining companies can mitigate for impacts to bats by surveying to identify bat-roosting habitat, removing bats prior to renewed mining or closure, protecting non-impacted roost sites with gates and fences, researching to identify habitat requirements and creating new artificial roosts.« less

Application and research of block caving in Pulang copper mine

NASA Astrophysics Data System (ADS)

Ge, Qifa; Fan, Wenlu; Zhu, Weigen; Chen, Xiaowei

2018-01-01

The application of block caving in mines shows significant advantages in large scale, low cost and high efficiency, thus block caving is worth promoting in the mines that meets the requirement of natural caving. Due to large scale of production and low ore grade in Pulang copper mine in China, comprehensive analysis and research were conducted on rock mechanics, mining sequence, undercutting and stability of bottom structure in terms of raising mine benefit and maximizing the recovery mineral resources. Finally this study summarizes that block caving is completely suitable for Pulang copper mine.

Attributed community mining using joint general non-negative matrix factorization with graph Laplacian

NASA Astrophysics Data System (ADS)

Chen, Zigang; Li, Lixiang; Peng, Haipeng; Liu, Yuhong; Yang, Yixian

2018-04-01

Community mining for complex social networks with link and attribute information plays an important role according to different application needs. In this paper, based on our proposed general non-negative matrix factorization (GNMF) algorithm without dimension matching constraints in our previous work, we propose the joint GNMF with graph Laplacian (LJGNMF) to implement community mining of complex social networks with link and attribute information according to different application needs. Theoretical derivation result shows that the proposed LJGNMF is fully compatible with previous methods of integrating traditional NMF and symmetric NMF. In addition, experimental results show that the proposed LJGNMF can meet the needs of different community minings by adjusting its parameters, and the effect is better than traditional NMF in the community vertices attributes entropy.

Propagation of fires along mine workings: criteria and limits

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pervushin, Yu.V.

1978-01-01

Underground fires account for over 50% of the accidents occuring in Soviet mines. Their prevention therefore occupies a central place in mine rescue practice and accident prevention. The general features of the physical processes occurring during propagation of a flame have been studied in some detail. Attempts have been made to describe underground fires on the basis of experimental data. However, it is not yet possible to make accurate preductions of the behavior of fires in mine workings: very many factors influence their development. The dynamics of spread of a flame along a working involves such diverse phenomena as heatmore » transfer by thermal conduction, radiation, and convection, transfer of oxygen and combustible gaseous components by draughts and diffusion, various chemical reactions on the surface of combustible materials and within the flames, and finally complex surface effects accompanying heat and mass transfer at interfaces between media. In addition, we must take account of the specific conditions prevailing in a mine - the complex geometrical configuration of the workings, the nonuniformity of the combustible materials, and the role of ventilation and its instability during fires. There can be many approaches to the study of such a many-sided process. The most promising lines seem to be those in which experimental models of the complex of possible phenomena are combined with mathematical models of the process, based on the equations of chemical hydrodynamics, in which the alternative variants are realized on a computer.« less

Characterization of gut microbiota profiles in coronary artery disease patients using data mining analysis of terminal restriction fragment length polymorphism: gut microbiota could be a diagnostic marker of coronary artery disease.

PubMed

Emoto, Takuo; Yamashita, Tomoya; Kobayashi, Toshio; Sasaki, Naoto; Hirota, Yushi; Hayashi, Tomohiro; So, Anna; Kasahara, Kazuyuki; Yodoi, Keiko; Matsumoto, Takuya; Mizoguchi, Taiji; Ogawa, Wataru; Hirata, Ken-Ichi

2017-01-01

The association between atherosclerosis and gut microbiota has been attracting increased attention. We previously demonstrated a possible link between gut microbiota and coronary artery disease. Our aim of this study was to clarify the gut microbiota profiles in coronary artery disease patients using data mining analysis of terminal restriction fragment length polymorphism (T-RFLP). This study included 39 coronary artery disease (CAD) patients and 30 age- and sex- matched no-CAD controls (Ctrls) with coronary risk factors. Bacterial DNA was extracted from their fecal samples and analyzed by T-RFLP and data mining analysis using the classification and regression algorithm. Five additional CAD patients were newly recruited to confirm the reliability of this analysis. Data mining analysis could divide the composition of gut microbiota into 2 characteristic nodes. The CAD group was classified into 4 CAD pattern nodes (35/39 = 90 %), while the Ctrl group was classified into 3 Ctrl pattern nodes (28/30 = 93 %). Five additional CAD samples were applied to the same dividing model, which could validate the accuracy to predict the risk of CAD by data mining analysis. We could demonstrate that operational taxonomic unit 853 (OTU853), OTU657, and OTU990 were determined important both by the data mining method and by the usual statistical comparison. We classified the gut microbiota profiles in coronary artery disease patients using data mining analysis of T-RFLP data and demonstrated the possibility that gut microbiota is a diagnostic marker of suffering from CAD.

Data Mining and Knowledge Management in Higher Education -Potential Applications.

ERIC Educational Resources Information Center

Luan, Jing

This paper introduces a new decision support tool, data mining, in the context of knowledge management. The most striking features of data mining techniques are clustering and prediction. The clustering aspect of data mining offers comprehensive characteristics analysis of students, while the predicting function estimates the likelihood for a…

Ensuring the Environmental and Industrial Safety in Solid Mineral Deposit Surface Mining

NASA Astrophysics Data System (ADS)

Trubetskoy, Kliment; Rylnikova, Marina; Esina, Ekaterina

2017-11-01

The growing environmental pressure of mineral deposit surface mining and severization of industrial safety requirements dictate the necessity of refining the regulatory framework governing safe and efficient development of underground resources. The applicable regulatory documentation governing the procedure of ore open-pit wall and bench stability design for the stage of pit reaching its final boundary was issued several decades ago. Over recent decades, mining and geomechanical conditions have changed significantly in surface mining operations, numerous new software packages and computer developments have appeared, opportunities of experimental methods of source data collection and processing, grounding of the permissible parameters of open pit walls have changed dramatically, and, thus, methods of risk assessment have been perfected [10-13]. IPKON RAS, with the support of the Federal Service for Environmental Supervision, assumed the role of the initiator of the project for the development of Federal norms and regulations of industrial safety "Rules for ensuring the stability of walls and benches of open pits, open-cast mines and spoil banks", which contribute to the improvement of economic efficiency and safety of mineral deposit surface mining and enhancement of the competitiveness of Russian mines at the international level that is very important in the current situation.

Data Mining and Knowledge Management: A System Analysis for Establishing a Tiered Knowledge Management Model.

ERIC Educational Resources Information Center

Luan, Jing; Willett, Terrence

This paper discusses data mining--an end-to-end (ETE) data analysis tool that is used by researchers in higher education. It also relates data mining and other software programs to a brand new concept called "Knowledge Management." The paper culminates in the Tier Knowledge Management Model (TKMM), which seeks to provide a stable…

Exploration of geo-mineral compounds in granite mining soils using XRD pattern data analysis

NASA Astrophysics Data System (ADS)

Koteswara Reddy, G.; Yarakkula, Kiran

2017-11-01

The purpose of the study was to investigate the major minerals present in granite mining waste and agricultural soils near and away from mining areas. The mineral exploration of representative sub-soil samples are identified by X-Ray Diffractometer (XRD) pattern data analysis. The morphological features and quantitative elementary analysis was performed by Scanning Electron Microscopy-Energy Dispersed Spectroscopy (SEM-EDS).The XRD pattern data revealed that the major minerals are identified as Quartz, Albite, Anorthite, K-Feldspars, Muscovite, Annite, Lepidolite, Illite, Enstatite and Ferrosilite in granite waste. However, in case of agricultural farm soils the major minerals are identified as Gypsum, Calcite, Magnetite, Hematite, Muscovite, K-Feldspars and Quartz. Moreover, the agricultural soils neighbouring mining areas, the minerals are found that, the enriched Mica group minerals (Lepidolite and Illite) the enriched Orthopyroxene group minerals (Ferrosilite and Enstatite). It is observed that the Mica and Orthopyroxene group minerals are present in agricultural farm soils neighbouring mining areas and absent in agricultural farm soils away from mining areas. The study demonstrated that the chemical migration takes place at agricultural farm lands in the vicinity of the granite mining areas.

The application of satellite data in monitoring strip mines

NASA Technical Reports Server (NTRS)

Sharber, L. A.; Shahrokhi, F.

1977-01-01

Strip mines in the New River Drainage Basin of Tennessee were studied through use of Landsat-1 imagery and aircraft photography. A multilevel analysis, involving conventional photo interpretation techniques, densitometric methods, multispectral analysis and statistical testing was applied to the data. The Landsat imagery proved adequate for monitoring large-scale change resulting from active mining and land-reclamation projects. However, the spatial resolution of the satellite imagery rendered it inadequate for assessment of many smaller strip mines, in the region which may be as small as a few hectares.

Data management in the modern structural biology and biomedical research environment.

PubMed

Zimmerman, Matthew D; Grabowski, Marek; Domagalski, Marcin J; Maclean, Elizabeth M; Chruszcz, Maksymilian; Minor, Wladek

2014-01-01

Modern high-throughput structural biology laboratories produce vast amounts of raw experimental data. The traditional method of data reduction is very simple-results are summarized in peer-reviewed publications, which are hopefully published in high-impact journals. By their nature, publications include only the most important results derived from experiments that may have been performed over the course of many years. The main content of the published paper is a concise compilation of these data, an interpretation of the experimental results, and a comparison of these results with those obtained by other scientists.Due to an avalanche of structural biology manuscripts submitted to scientific journals, in many recent cases descriptions of experimental methodology (and sometimes even experimental results) are pushed to supplementary materials that are only published online and sometimes may not be reviewed as thoroughly as the main body of a manuscript. Trouble may arise when experimental results are contradicting the results obtained by other scientists, which requires (in the best case) the reexamination of the original raw data or independent repetition of the experiment according to the published description of the experiment. There are reports that a significant fraction of experiments obtained in academic laboratories cannot be repeated in an industrial environment (Begley CG & Ellis LM, Nature 483(7391):531-3, 2012). This is not an indication of scientific fraud but rather reflects the inadequate description of experiments performed on different equipment and on biological samples that were produced with disparate methods. For that reason the goal of a modern data management system is not only the simple replacement of the laboratory notebook by an electronic one but also the creation of a sophisticated, internally consistent, scalable data management system that will combine data obtained by a variety of experiments performed by various individuals on diverse equipment. All data should be stored in a core database that can be used by custom applications to prepare internal reports, statistics, and perform other functions that are specific to the research that is pursued in a particular laboratory.This chapter presents a general overview of the methods of data management and analysis used by structural genomics (SG) programs. In addition to a review of the existing literature on the subject, also presented is experience in the development of two SG data management systems, UniTrack and LabDB. The description is targeted to a general audience, as some technical details have been (or will be) published elsewhere. The focus is on "data management," meaning the process of gathering, organizing, and storing data, but also briefly discussed is "data mining," the process of analysis ideally leading to an understanding of the data. In other words, data mining is the conversion of data into information. Clearly, effective data management is a precondition for any useful data mining. If done properly, gathering details on millions of experiments on thousands of proteins and making them publicly available for analysis-even after the projects themselves have ended-may turn out to be one of the most important benefits of SG programs.

Statistically significant relational data mining :

DOE Office of Scientific and Technical Information (OSTI.GOV)

Berry, Jonathan W.; Leung, Vitus Joseph; Phillips, Cynthia Ann

This report summarizes the work performed under the project (3z(BStatitically significant relational data mining.(3y (BThe goal of the project was to add more statistical rigor to the fairly ad hoc area of data mining on graphs. Our goal was to develop better algorithms and better ways to evaluate algorithm quality. We concetrated on algorithms for community detection, approximate pattern matching, and graph similarity measures. Approximate pattern matching involves finding an instance of a relatively small pattern, expressed with tolerance, in a large graph of data observed with uncertainty. This report gathers the abstracts and references for the eight refereed publicationsmore » that have appeared as part of this work. We then archive three pieces of research that have not yet been published. The first is theoretical and experimental evidence that a popular statistical measure for comparison of community assignments favors over-resolved communities over approximations to a ground truth. The second are statistically motivated methods for measuring the quality of an approximate match of a small pattern in a large graph. The third is a new probabilistic random graph model. Statisticians favor these models for graph analysis. The new local structure graph model overcomes some of the issues with popular models such as exponential random graph models and latent variable models.« less

Microbial functional diversity and enzymatic activity of soil degraded by sulphur mining reclaimed with various waste

NASA Astrophysics Data System (ADS)

Joniec, Jolanta; Frąc, Magdalena

2017-10-01

The aim of the study was to evaluate microbial functional diversity based on community level physiological profiling and β-glucosidase activity changes in soil degraded by sulphur mining and subjected to reclamation with various waste. The experiment was set up in the area of the former `Jeziórko' Sulphur Mine (Poland), on a soilless substrate with a particle size distribution of slightly loamy sand. The experimental variants included the application of post-flotation lime, sewage sludge and mineral wool. The analyses of soil samples included the assessment of the following microbiological indices: β-glucosidase activity and functional diversity average well color development and richness). The results indicate that sewage sludge did not exert a significant impact on the functional diversity of microorganisms present in the reclaimed soil. In turn, the application of other types of waste contributed to a significant increase in the parameters of total metabolic activity and functional diversity of the reclaimed soil. However, the temporal analysis of the metabolic profile of soil microorganisms demonstrated that a single application of waste did not yield a durable, stable metabolic profile in the reclaimed soil. Still, there was an increase in β-glucosidase activity, especially in objects treated with sewage sludge.

Big Data Mining and Adverse Event Pattern Analysis in Clinical Drug Trials

PubMed Central

Federer, Callie; Yoo, Minjae

2016-01-01

Abstract Drug adverse events (AEs) are a major health threat to patients seeking medical treatment and a significant barrier in drug discovery and development. AEs are now required to be submitted during clinical trials and can be extracted from ClinicalTrials.gov (https://clinicaltrials.gov/), a database of clinical studies around the world. By extracting drug and AE information from ClinicalTrials.gov and structuring it into a database, drug-AEs could be established for future drug development and repositioning. To our knowledge, current AE databases contain mainly U.S. Food and Drug Administration (FDA)-approved drugs. However, our database contains both FDA-approved and experimental compounds extracted from ClinicalTrials.gov. Our database contains 8,161 clinical trials of 3,102,675 patients and 713,103 reported AEs. We extracted the information from ClinicalTrials.gov using a set of python scripts, and then used regular expressions and a drug dictionary to process and structure relevant information into a relational database. We performed data mining and pattern analysis of drug-AEs in our database. Our database can serve as a tool to assist researchers to discover drug-AE relationships for developing, repositioning, and repurposing drugs. PMID:27631620

Big Data Mining and Adverse Event Pattern Analysis in Clinical Drug Trials.

PubMed

Federer, Callie; Yoo, Minjae; Tan, Aik Choon

2016-12-01

Drug adverse events (AEs) are a major health threat to patients seeking medical treatment and a significant barrier in drug discovery and development. AEs are now required to be submitted during clinical trials and can be extracted from ClinicalTrials.gov ( https://clinicaltrials.gov/ ), a database of clinical studies around the world. By extracting drug and AE information from ClinicalTrials.gov and structuring it into a database, drug-AEs could be established for future drug development and repositioning. To our knowledge, current AE databases contain mainly U.S. Food and Drug Administration (FDA)-approved drugs. However, our database contains both FDA-approved and experimental compounds extracted from ClinicalTrials.gov . Our database contains 8,161 clinical trials of 3,102,675 patients and 713,103 reported AEs. We extracted the information from ClinicalTrials.gov using a set of python scripts, and then used regular expressions and a drug dictionary to process and structure relevant information into a relational database. We performed data mining and pattern analysis of drug-AEs in our database. Our database can serve as a tool to assist researchers to discover drug-AE relationships for developing, repositioning, and repurposing drugs.

A strategy for selecting data mining techniques in metabolomics.

PubMed

Banimustafa, Ahmed Hmaidan; Hardy, Nigel W

2012-01-01

There is a general agreement that the development of metabolomics depends not only on advances in chemical analysis techniques but also on advances in computing and data analysis methods. Metabolomics data usually requires intensive pre-processing, analysis, and mining procedures. Selecting and applying such procedures requires attention to issues including justification, traceability, and reproducibility. We describe a strategy for selecting data mining techniques which takes into consideration the goals of data mining techniques on the one hand, and the goals of metabolomics investigations and the nature of the data on the other. The strategy aims to ensure the validity and soundness of results and promote the achievement of the investigation goals.

Study on characteristics of EMR signals induced from fracture of rock samples and their application in rockburst prediction in copper mine

NASA Astrophysics Data System (ADS)

Liu, Xiaofei; Wang, Enyuan

2018-06-01

A rockburst is a dynamic disaster that occurs during underground excavation or mining which has been a serious threat to safety. Rockburst prediction and control are as important as any other underground engineering in deep mines. For this paper, we tested electromagnetic radiation (EMR) signals generated during the deformation and fracture of rock samples from a copper mine under uniaxial compression, tension, and cycle-loading experiments, analyzed the changes in the EMR intensity, pulse number, and frequency corresponding to the loading, and a high correlation between these EMR parameters and the applied loading was observed. EMR apparently reflects the deformation and fracture status to the loaded rock. Based on this experimental work, we invented the KBD5-type EMR monitor and used it to test EMR signals generated in the rock surrounding the Hongtoushan copper mine. From the test results, it is determined the responding characteristics of EMR signals generated by changes in mine-generated stresses and stress concentrations and it is proposed that this EMR monitoring method can be used to provide early warning for rockbursts.

Data Mining: The Art of Automated Knowledge Extraction

NASA Astrophysics Data System (ADS)

Karimabadi, H.; Sipes, T.

2012-12-01

Data mining algorithms are used routinely in a wide variety of fields and they are gaining adoption in sciences. The realities of real world data analysis are that (a) data has flaws, and (b) the models and assumptions that we bring to the data are inevitably flawed, and/or biased and misspecified in some way. Data mining can improve data analysis by detecting anomalies in the data, check for consistency of the user model assumptions, and decipher complex patterns and relationships that would not be possible otherwise. The common form of data collected from in situ spacecraft measurements is multi-variate time series which represents one of the most challenging problems in data mining. We have successfully developed algorithms to deal with such data and have extended the algorithms to handle streaming data. In this talk, we illustrate the utility of our algorithms through several examples including automated detection of reconnection exhausts in the solar wind and flux ropes in the magnetotail. We also show examples from successful applications of our technique to analysis of 3D kinetic simulations. With an eye to the future, we provide an overview of our upcoming plans that include collaborative data mining, expert outsourcing data mining, computer vision for image analysis, among others. Finally, we discuss the integration of data mining algorithms with web-based services such as VxOs and other Heliophysics data centers and the resulting capabilities that it would enable.

Figure mining for biomedical research.

PubMed

Rodriguez-Esteban, Raul; Iossifov, Ivan

2009-08-15

Figures from biomedical articles contain valuable information difficult to reach without specialized tools. Currently, there is no search engine that can retrieve specific figure types. This study describes a retrieval method that takes advantage of principles in image understanding, text mining and optical character recognition (OCR) to retrieve figure types defined conceptually. A search engine was developed to retrieve tables and figure types to aid computational and experimental research. http://iossifovlab.cshl.edu/figurome/.

Benchmarking of Neutron Flux Parameters at the USGS TRIGA Reactor in Lakewood, Colorado

NASA Astrophysics Data System (ADS)

Alzaabi, Osama E.

The USGS TRIGA Reactor (GSTR) located at the Denver Federal Center in Lakewood Colorado provides opportunities to Colorado School of Mines students to do experimental research in the field of neutron activation analysis. The scope of this thesis is to obtain precise knowledge of neutron flux parameters at the GSTR. The Colorado School of Mines Nuclear Physics group intends to develop several research projects at the GSTR, which requires the precise knowledge of neutron fluxes and energy distributions in several irradiation locations. The fuel burn-up of the new GSTR fuel configuration and the thermal neutron flux of the core were recalculated since the GSTR core configuration had been changed with the addition of two new fuel elements. Therefore, a MCNP software package was used to incorporate the burn up of reactor fuel and to determine the neutron flux at different irradiation locations and at flux monitoring bores. These simulation results were compared with neutron activation analysis results using activated diluted gold wires. A well calibrated and stable germanium detector setup as well as fourteen samplers were designed and built to achieve accuracy in the measurement of the neutron flux. Furthermore, the flux monitoring bores of the GSTR core were used for the first time to measure neutron flux experimentally and to compare to MCNP simulation. In addition, International Atomic Energy Agency (IAEA) standard materials were used along with USGS national standard materials in a previously well calibrated irradiation location to benchmark simulation, germanium detector calibration and sample measurements to international standards.

Using remote sensing imagery to monitoring sea surface pollution cause by abandoned gold-copper mine

NASA Astrophysics Data System (ADS)

Kao, H. M.; Ren, H.; Lee, Y. T.

2010-08-01

The Chinkuashih Benshen mine was the largest gold-copper mine in Taiwan before the owner had abandoned the mine in 1987. However, even the mine had been closed, the mineral still interacts with rain and underground water and flowed into the sea. The polluted sea surface had appeared yellow, green and even white color, and the pollutants had carried by the coast current. In this study, we used the optical satellite images to monitoring the sea surface. Several image processing algorithms are employed especial the subpixel technique and linear mixture model to estimate the concentration of pollutants. The change detection approach is also applied to track them. We also conduct the chemical analysis of the polluted water to provide the ground truth validation. By the correlation analysis between the satellite observation and the ground truth chemical analysis, an effective approach to monitoring water pollution could be established.

Study of the application of ERTS-A imagery to fracture-related mine safety hazards in the coal mining industry

NASA Technical Reports Server (NTRS)

Wier, C. E.; Wobber, F. J. (Principal Investigator); Russell, O. R.; Amato, R. V.

1972-01-01

The author has identified the following significant results. Various data compilation and analysis activities in support of ERTS-1 imagery interpretation are in progress or are completed. These include the compilation of mine accident data, areas of mine roof instability and the analysis of high altitude color infrared photography and low altitude color and color infrared photography which was acquired by NASA in support of the project. The photography reveals that many fracture lineaments are detectable through a varied thickness of glacial till. These data will be compiled on a series of 1:250,000 scale base maps and evaluated for a correlation between fracture zones and mine accidents and rooffalls. Due to high occurrence of cloud cover in the project area and to the delay in imagery shipments, little progress has been made in the analysis of ERTS-1 imagery.

Using fuzzy data mining to diagnose patients' degrees of melancholia

NASA Astrophysics Data System (ADS)

Huang, Yo-Ping; Kuo, Wen-Lin

2011-06-01

The common treatments of melancholia are psychotherapy and taking medicines. The psychotherapy treatment which this study focuses on is limited by time and location. It is easier for psychiatrists to grasp information from clinical manifestation but it is difficult for psychiatrists to collect information from patients' daily conversations or emotion. To design a system which psychiatrists enable to capture patients' daily symptoms will show great help in the treatment. This study proposes to use fuzzy data mining algorithm to find association rules among keywords segmented from patients' daily voice/text messages to assist psychiatrists extract useful information before outpatient service. Patients of melancholia can use devices such as mobile phones or computers to record their own emotion anytime and anywhere and then uploading the recorded files to the back-end server for further analysis. The analytical results can be used for psychiatrists to diagnose patients' degrees of melancholia. Experimental results will be given to verify the effectiveness of the proposed methodology.

A malware detection scheme based on mining format information.

PubMed

Bai, Jinrong; Wang, Junfeng; Zou, Guozhong

2014-01-01

Malware has become one of the most serious threats to computer information system and the current malware detection technology still has very significant limitations. In this paper, we proposed a malware detection approach by mining format information of PE (portable executable) files. Based on in-depth analysis of the static format information of the PE files, we extracted 197 features from format information of PE files and applied feature selection methods to reduce the dimensionality of the features and achieve acceptable high performance. When the selected features were trained using classification algorithms, the results of our experiments indicate that the accuracy of the top classification algorithm is 99.1% and the value of the AUC is 0.998. We designed three experiments to evaluate the performance of our detection scheme and the ability of detecting unknown and new malware. Although the experimental results of identifying new malware are not perfect, our method is still able to identify 97.6% of new malware with 1.3% false positive rates.

A Malware Detection Scheme Based on Mining Format Information

PubMed Central

Bai, Jinrong; Wang, Junfeng; Zou, Guozhong

2014-01-01

Malware has become one of the most serious threats to computer information system and the current malware detection technology still has very significant limitations. In this paper, we proposed a malware detection approach by mining format information of PE (portable executable) files. Based on in-depth analysis of the static format information of the PE files, we extracted 197 features from format information of PE files and applied feature selection methods to reduce the dimensionality of the features and achieve acceptable high performance. When the selected features were trained using classification algorithms, the results of our experiments indicate that the accuracy of the top classification algorithm is 99.1% and the value of the AUC is 0.998. We designed three experiments to evaluate the performance of our detection scheme and the ability of detecting unknown and new malware. Although the experimental results of identifying new malware are not perfect, our method is still able to identify 97.6% of new malware with 1.3% false positive rates. PMID:24991639

Analysis of radon reduction and ventilation systems in uranium mines in China.

PubMed

Hu, Peng-hua; Li, Xian-jie

2012-09-01

Mine ventilation is the most important way of reducing radon in uranium mines. At present, the radon and radon progeny levels in Chinese uranium mines where the cut and fill stoping method is used are 3-5 times higher than those in foreign uranium mines, as there is not much difference in the investments for ventilation protection between Chinese uranium mines and international advanced uranium mines with compaction methodology. In this paper, through the analysis of radon reduction and ventilation systems in Chinese uranium mines and the comparison of advantages and disadvantages between a variety of ventilation systems in terms of radon control, the authors try to illustrate the reasons for the higher radon and radon progeny levels in Chinese uranium mines and put forward some problems in three areas, namely the theory of radon control and ventilation systems, radon reduction ventilation measures and ventilation management. For these problems, this paper puts forward some proposals regarding some aspects, such as strengthening scrutiny, verifying and monitoring the practical situation, making clear ventilation plans, strictly following the mining sequence, promoting training of ventilation staff, enhancing ventilation system management, developing radon reduction ventilation technology, purchasing ventilation equipment as soon as possible in the future, and so on.

Unsupervised iterative detection of land mines in highly cluttered environments.

PubMed

Batman, Sinan; Goutsias, John

2003-01-01

An unsupervised iterative scheme is proposed for land mine detection in heavily cluttered scenes. This scheme is based on iterating hybrid multispectral filters that consist of a decorrelating linear transform coupled with a nonlinear morphological detector. Detections extracted from the first pass are used to improve results in subsequent iterations. The procedure stops after a predetermined number of iterations. The proposed scheme addresses several weaknesses associated with previous adaptations of morphological approaches to land mine detection. Improvement in detection performance, robustness with respect to clutter inhomogeneities, a completely unsupervised operation, and computational efficiency are the main highlights of the method. Experimental results reveal excellent performance.

Multi-Level Sequential Pattern Mining Based on Prime Encoding

NASA Astrophysics Data System (ADS)

Lianglei, Sun; Yun, Li; Jiang, Yin

Encoding is not only to express the hierarchical relationship, but also to facilitate the identification of the relationship between different levels, which will directly affect the efficiency of the algorithm in the area of mining the multi-level sequential pattern. In this paper, we prove that one step of division operation can decide the parent-child relationship between different levels by using prime encoding and present PMSM algorithm and CROSS-PMSM algorithm which are based on prime encoding for mining multi-level sequential pattern and cross-level sequential pattern respectively. Experimental results show that the algorithm can effectively extract multi-level and cross-level sequential pattern from the sequence database.

Exploitation of multi-temporal Earth Observation imagery for monitoring land cover change in mining sites

NASA Astrophysics Data System (ADS)

Petropoulos, G.; Partsinevelos, P.; Mitraka, Z.

2012-04-01

Surface mining has been shown to cause intensive environmental degradation in terms of landscape, vegetation and biological communities. Nowadays, the commercial availability of remote sensing imagery at high spatiotemporal scales, has improved dramatically our ability to monitor surface mining activity and evaluate its impact on the environment and society. In this study we investigate the potential use of Landsat TM imagery combined with diverse classification techniques, namely artificial neural networks and support vector machines for delineating mining exploration and assessing its effect on vegetation in various surface mining sites in the Greek island of Milos. Assessment of the mining impact in the study area is validated through the analysis of available QuickBird imagery acquired nearly concurrently to the TM overpasses. Results indicate the capability of the TM sensor combined with the image analysis applied herein as a potential economically viable solution to provide rapidly and at regular time intervals information on mining activity and its impact to the local environment. KEYWORDS: mining environmental impact, remote sensing, image classification, change detection, land reclamation, support vector machines, neural networks

Text Mining in Organizational Research

PubMed Central

Kobayashi, Vladimer B.; Berkers, Hannah A.; Kismihók, Gábor; Den Hartog, Deanne N.

2017-01-01

Despite the ubiquity of textual data, so far few researchers have applied text mining to answer organizational research questions. Text mining, which essentially entails a quantitative approach to the analysis of (usually) voluminous textual data, helps accelerate knowledge discovery by radically increasing the amount data that can be analyzed. This article aims to acquaint organizational researchers with the fundamental logic underpinning text mining, the analytical stages involved, and contemporary techniques that may be used to achieve different types of objectives. The specific analytical techniques reviewed are (a) dimensionality reduction, (b) distance and similarity computing, (c) clustering, (d) topic modeling, and (e) classification. We describe how text mining may extend contemporary organizational research by allowing the testing of existing or new research questions with data that are likely to be rich, contextualized, and ecologically valid. After an exploration of how evidence for the validity of text mining output may be generated, we conclude the article by illustrating the text mining process in a job analysis setting using a dataset composed of job vacancies. PMID:29881248

Text Mining in Organizational Research.

PubMed

Kobayashi, Vladimer B; Mol, Stefan T; Berkers, Hannah A; Kismihók, Gábor; Den Hartog, Deanne N

2018-07-01

Despite the ubiquity of textual data, so far few researchers have applied text mining to answer organizational research questions. Text mining, which essentially entails a quantitative approach to the analysis of (usually) voluminous textual data, helps accelerate knowledge discovery by radically increasing the amount data that can be analyzed. This article aims to acquaint organizational researchers with the fundamental logic underpinning text mining, the analytical stages involved, and contemporary techniques that may be used to achieve different types of objectives. The specific analytical techniques reviewed are (a) dimensionality reduction, (b) distance and similarity computing, (c) clustering, (d) topic modeling, and (e) classification. We describe how text mining may extend contemporary organizational research by allowing the testing of existing or new research questions with data that are likely to be rich, contextualized, and ecologically valid. After an exploration of how evidence for the validity of text mining output may be generated, we conclude the article by illustrating the text mining process in a job analysis setting using a dataset composed of job vacancies.

Longwall gate road stability in a steeply pitching thick coal seam with a weak roof. Report of investigations/1995

DOE Office of Scientific and Technical Information (OSTI.GOV)

Barron, L.R.; DeMarco, M.J.

1995-12-31

The U.S. Bureau of Mines conducted a ground pressure analysis of a wide abutment-type chain pillar in a two-entry gate road of a Western U.S. coal mine with an extremely weak immediate roof. This report discusses gate road layout and performance and secondary support effectiveness. The results of the pillar pressure study are compared to pillar loading predicted by a widely used pillar design method and to similar studies in other mines. A stability evaluation of the most recent longwall headgate, using the USBM Analysis of Longwall Pillar Stability (ALPS) indicates marginal stability in first-panel mining and instability in second-panelmore » mining. ALPS and the USBM Coal Mine Roof Rating (CMRR) system are used to evaluate tailgate-mining stability of the previous gate roads and to determine pillar and entry width and top coal thickness criteria for tailgate stability in future panels.« less

Application of advanced computing techniques to the analysis and display of space science measurements

NASA Technical Reports Server (NTRS)

Klumpar, D. M.; Lapolla, M. V.; Horblit, B.

1995-01-01

A prototype system has been developed to aid the experimental space scientist in the display and analysis of spaceborne data acquired from direct measurement sensors in orbit. We explored the implementation of a rule-based environment for semi-automatic generation of visualizations that assist the domain scientist in exploring one's data. The goal has been to enable rapid generation of visualizations which enhance the scientist's ability to thoroughly mine his data. Transferring the task of visualization generation from the human programmer to the computer produced a rapid prototyping environment for visualizations. The visualization and analysis environment has been tested against a set of data obtained from the Hot Plasma Composition Experiment on the AMPTE/CCE satellite creating new visualizations which provided new insight into the data.

Application of data mining approaches to drug delivery.

PubMed

Ekins, Sean; Shimada, Jun; Chang, Cheng

2006-11-30

Computational approaches play a key role in all areas of the pharmaceutical industry from data mining, experimental and clinical data capture to pharmacoeconomics and adverse events monitoring. They will likely continue to be indispensable assets along with a growing library of software applications. This is primarily due to the increasingly massive amount of biology, chemistry and clinical data, which is now entering the public domain mainly as a result of NIH and commercially funded projects. We are therefore in need of new methods for mining this mountain of data in order to enable new hypothesis generation. The computational approaches include, but are not limited to, database compilation, quantitative structure activity relationships (QSAR), pharmacophores, network visualization models, decision trees, machine learning algorithms and multidimensional data visualization software that could be used to improve drug delivery after mining public and/or proprietary data. We will discuss some areas of unmet needs in the area of data mining for drug delivery that can be addressed with new software tools or databases of relevance to future pharmaceutical projects.

A Node Linkage Approach for Sequential Pattern Mining

PubMed Central

Navarro, Osvaldo; Cumplido, René; Villaseñor-Pineda, Luis; Feregrino-Uribe, Claudia; Carrasco-Ochoa, Jesús Ariel

2014-01-01

Sequential Pattern Mining is a widely addressed problem in data mining, with applications such as analyzing Web usage, examining purchase behavior, and text mining, among others. Nevertheless, with the dramatic increase in data volume, the current approaches prove inefficient when dealing with large input datasets, a large number of different symbols and low minimum supports. In this paper, we propose a new sequential pattern mining algorithm, which follows a pattern-growth scheme to discover sequential patterns. Unlike most pattern growth algorithms, our approach does not build a data structure to represent the input dataset, but instead accesses the required sequences through pseudo-projection databases, achieving better runtime and reducing memory requirements. Our algorithm traverses the search space in a depth-first fashion and only preserves in memory a pattern node linkage and the pseudo-projections required for the branch being explored at the time. Experimental results show that our new approach, the Node Linkage Depth-First Traversal algorithm (NLDFT), has better performance and scalability in comparison with state of the art algorithms. PMID:24933123

Semantic web for integrated network analysis in biomedicine.

PubMed

Chen, Huajun; Ding, Li; Wu, Zhaohui; Yu, Tong; Dhanapalan, Lavanya; Chen, Jake Y

2009-03-01

The Semantic Web technology enables integration of heterogeneous data on the World Wide Web by making the semantics of data explicit through formal ontologies. In this article, we survey the feasibility and state of the art of utilizing the Semantic Web technology to represent, integrate and analyze the knowledge in various biomedical networks. We introduce a new conceptual framework, semantic graph mining, to enable researchers to integrate graph mining with ontology reasoning in network data analysis. Through four case studies, we demonstrate how semantic graph mining can be applied to the analysis of disease-causal genes, Gene Ontology category cross-talks, drug efficacy analysis and herb-drug interactions analysis.

Towards Cooperative Predictive Data Mining in Competitive Environments

NASA Astrophysics Data System (ADS)

Lisý, Viliam; Jakob, Michal; Benda, Petr; Urban, Štěpán; Pěchouček, Michal

We study the problem of predictive data mining in a competitive multi-agent setting, in which each agent is assumed to have some partial knowledge required for correctly classifying a set of unlabelled examples. The agents are self-interested and therefore need to reason about the trade-offs between increasing their classification accuracy by collaborating with other agents and disclosing their private classification knowledge to other agents through such collaboration. We analyze the problem and propose a set of components which can enable cooperation in this otherwise competitive task. These components include measures for quantifying private knowledge disclosure, data-mining models suitable for multi-agent predictive data mining, and a set of strategies by which agents can improve their classification accuracy through collaboration. The overall framework and its individual components are validated on a synthetic experimental domain.

A brain-region-based meta-analysis method utilizing the Apriori algorithm.

PubMed

Niu, Zhendong; Nie, Yaoxin; Zhou, Qian; Zhu, Linlin; Wei, Jieyao

2016-05-18

Brain network connectivity modeling is a crucial method for studying the brain's cognitive functions. Meta-analyses can unearth reliable results from individual studies. Meta-analytic connectivity modeling is a connectivity analysis method based on regions of interest (ROIs) which showed that meta-analyses could be used to discover brain network connectivity. In this paper, we propose a new meta-analysis method that can be used to find network connectivity models based on the Apriori algorithm, which has the potential to derive brain network connectivity models from activation information in the literature, without requiring ROIs. This method first extracts activation information from experimental studies that use cognitive tasks of the same category, and then maps the activation information to corresponding brain areas by using the automatic anatomical label atlas, after which the activation rate of these brain areas is calculated. Finally, using these brain areas, a potential brain network connectivity model is calculated based on the Apriori algorithm. The present study used this method to conduct a mining analysis on the citations in a language review article by Price (Neuroimage 62(2):816-847, 2012). The results showed that the obtained network connectivity model was consistent with that reported by Price. The proposed method is helpful to find brain network connectivity by mining the co-activation relationships among brain regions. Furthermore, results of the co-activation relationship analysis can be used as a priori knowledge for the corresponding dynamic causal modeling analysis, possibly achieving a significant dimension-reducing effect, thus increasing the efficiency of the dynamic causal modeling analysis.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Solc, J.

The reclamation effort typically deals with consequences of mining activity instead of being planned well before the mining. Detailed assessment of principal hydro- and geochemical processes participating in pore and groundwater chemistry evolution was carried out at three surface mine localities in North Dakota-the Fritz mine, the Indian Head mine, and the Velva mine. The geochemical model MINTEQUA2 and advanced statistical analysis coupled with traditional interpretive techniques were used to determine site-specific environmental characteristics and to compare the differences between study sites. Multivariate statistical analysis indicates that sulfate, magnesium, calcium, the gypsum saturation index, and sodium contribute the most tomore » overall differences in groundwater chemistry between study sites. Soil paste extract pH and EC measurements performed on over 3700 samples document extremely acidic soils at the Fritz mine. The number of samples with pH <5.5 reaches 80%-90% of total samples from discrete depth near the top of the soil profile at the Fritz mine. Soil samples from Indian Head and Velva do not indicate the acidity below the pH of 5.5 limit. The percentage of samples with EC > 3 mS cm{sup -1} is between 20% and 40% at the Fritz mine and below 20% for samples from Indian Head and Velva. The results of geochemical modeling indicate an increased tendency for gypsum saturation within the vadose zone, particularly within the lands disturbed by mining activity. This trend is directly associated with increased concentrations of sulfate anions as a result of mineral oxidation. Geochemical modeling, statistical analysis, and soil extract pH and EC measurements proved to be reliable, fast, and relatively cost-effective tools for the assessment of soil acidity, the extent of the oxidation zone, and the potential for negative impact on pore and groundwater chemistry.« less

Identification of DEP domain-containing proteins by a machine learning method and experimental analysis of their expression in human HCC tissues

NASA Astrophysics Data System (ADS)

Liao, Zhijun; Wang, Xinrui; Zeng, Yeting; Zou, Quan

2016-12-01

The Dishevelled/EGL-10/Pleckstrin (DEP) domain-containing (DEPDC) proteins have seven members. However, whether this superfamily can be distinguished from other proteins based only on the amino acid sequences, remains unknown. Here, we describe a computational method to segregate DEPDCs and non-DEPDCs. First, we examined the Pfam numbers of the known DEPDCs and used the longest sequences for each Pfam to construct a phylogenetic tree. Subsequently, we extracted 188-dimensional (188D) and 20D features of DEPDCs and non-DEPDCs and classified them with random forest classifier. We also mined the motifs of human DEPDCs to find the related domains. Finally, we designed experimental verification methods of human DEPDC expression at the mRNA level in hepatocellular carcinoma (HCC) and adjacent normal tissues. The phylogenetic analysis showed that the DEPDCs superfamily can be divided into three clusters. Moreover, the 188D and 20D features can both be used to effectively distinguish the two protein types. Motif analysis revealed that the DEP and RhoGAP domain was common in human DEPDCs, human HCC and the adjacent tissues that widely expressed DEPDCs. However, their regulation was not identical. In conclusion, we successfully constructed a binary classifier for DEPDCs and experimentally verified their expression in human HCC tissues.

Fuzzy linear model for production optimization of mining systems with multiple entities

NASA Astrophysics Data System (ADS)

Vujic, Slobodan; Benovic, Tomo; Miljanovic, Igor; Hudej, Marjan; Milutinovic, Aleksandar; Pavlovic, Petar

2011-12-01

Planning and production optimization within multiple mines or several work sites (entities) mining systems by using fuzzy linear programming (LP) was studied. LP is the most commonly used operations research methods in mining engineering. After the introductory review of properties and limitations of applying LP, short reviews of the general settings of deterministic and fuzzy LP models are presented. With the purpose of comparative analysis, the application of both LP models is presented using the example of the Bauxite Basin Niksic with five mines. After the assessment, LP is an efficient mathematical modeling tool in production planning and solving many other single-criteria optimization problems of mining engineering. After the comparison of advantages and deficiencies of both deterministic and fuzzy LP models, the conclusion presents benefits of the fuzzy LP model but is also stating that seeking the optimal plan of production means to accomplish the overall analysis that will encompass the LP model approaches.

North Branch Potomac River Basin mine drainage study. Phase I. Baseline survey. Final report

DOE Office of Scientific and Technical Information (OSTI.GOV)

Not Available

1977-05-06

This baseline survey of the mine drainage and related water resources of the North Branch Potomac River Basin established the extent, magnitude, and effects of coal mine drainage pollution. Alternative abatement and reclamation solutions were considered. The study included an analysis of socioeconomic and environmental conditions as related to the mine drainage problem.

Compatibility between Text Mining and Qualitative Research in the Perspectives of Grounded Theory, Content Analysis, and Reliability

ERIC Educational Resources Information Center

Yu, Chong Ho; Jannasch-Pennell, Angel; DiGangi, Samuel

2011-01-01

The objective of this article is to illustrate that text mining and qualitative research are epistemologically compatible. First, like many qualitative research approaches, such as grounded theory, text mining encourages open-mindedness and discourages preconceptions. Contrary to the popular belief that text mining is a linear and fully automated…

Research into robotic automation of drilling equipment by the Institute of Mining, UB RAS

NASA Astrophysics Data System (ADS)

Regotunov, AS; Sukhov, RI

2018-03-01

The article discusses the issues connected with the development of instrumentation for the express-determination of strength characteristics of rocks during blasthole drilling in open pit mines. The trial results of the instrumentation are reported in terms of the drilling rate–energy content interrelation determined in the analyses of experimental drilling block data and by the digital model of rock distribution in depth versus drilling complexity index.

Analysis of Bonds as an Instrument for Financing Mining Investments

NASA Astrophysics Data System (ADS)

Ranosz, Robert

2017-06-01

The purpose of this article is to examine the structure of financing for mining enterprises in the years 2007-2013, with particular emphasis on bonds. The document pays special attention to Polish mining enterprises. The financing structure analysis was based on data collected from financial statements (cash flows) of the largest mining companies in Poland, and their comparison with the results of global mining enterprises pursuant to reports prepared by international advisory firms. The article takes into account capital sources such as: corporate bonds, bank loans and issue of shares. As indicated by the performed analysis, mining enterprises both around the world and in Poland are increasingly eager to take advantage of obtaining business financing from issue of corporate bonds. It should also be recognized that in the analyzed period, both global and Polish mining enterprises deviate from forms of financing such as issue of shares. This may be caused by the fact that the bonds market in Poland is becoming increasingly popular, mainly due to interest rate on bonds being lower in comparison with bank loans. Another reason may be that banks and potential buyers of shares are less eager to finance this type of investment due to a relatively substantial risk acceptable to bondholders.

A cost-benefit analysis of landfill mining and material recycling in China.

PubMed

Zhou, Chuanbin; Gong, Zhe; Hu, Junsong; Cao, Aixin; Liang, Hanwen

2015-01-01

Landfill mining is an environmentally-friendly technology that combines the concepts of material recycling and sustainable waste management, and it has received a great deal of worldwide attention because of its significant environmental and economic potential in material recycling, energy recovery, land reclamation and pollution prevention. This work applied a cost-benefit analysis model for assessing the economic feasibility, which is important for promoting landfill mining. The model includes eight indicators of costs and nine indicators of benefits. Four landfill mining scenarios were designed and analyzed based on field data. The economic feasibility of landfill mining was then evaluated by the indicator of net present value (NPV). According to our case study of a typical old landfill mining project in China (Yingchun landfill), rental of excavation and hauling equipment, waste processing and material transportation were the top three costs of landfill mining, accounting for 88.2% of the total cost, and the average cost per unit of stored waste was 12.7USDton(-1). The top three benefits of landfill mining were electricity generation by incineration, land reclamation and recycling soil-like materials. The NPV analysis of the four different scenarios indicated that the Yingchun landfill mining project could obtain a net positive benefit varying from 1.92 million USD to 16.63 million USD. However, the NPV was sensitive to the mode of land reuse, the availability of energy recovery facilities and the possibility of obtaining financial support by avoiding post-closure care. Copyright © 2014 Elsevier Ltd. All rights reserved.

Characterization of a mine fire using atmospheric monitoring system sensor data.

PubMed

Yuan, L; Thomas, R A; Zhou, L

2017-06-01

Atmospheric monitoring systems (AMS) have been widely used in underground coal mines in the United States for the detection of fire in the belt entry and the monitoring of other ventilation-related parameters such as airflow velocity and methane concentration in specific mine locations. In addition to an AMS being able to detect a mine fire, the AMS data have the potential to provide fire characteristic information such as fire growth - in terms of heat release rate - and exact fire location. Such information is critical in making decisions regarding fire-fighting strategies, underground personnel evacuation and optimal escape routes. In this study, a methodology was developed to calculate the fire heat release rate using AMS sensor data for carbon monoxide concentration, carbon dioxide concentration and airflow velocity based on the theory of heat and species transfer in ventilation airflow. Full-scale mine fire experiments were then conducted in the Pittsburgh Mining Research Division's Safety Research Coal Mine using an AMS with different fire sources. Sensor data collected from the experiments were used to calculate the heat release rates of the fires using this methodology. The calculated heat release rate was compared with the value determined from the mass loss rate of the combustible material using a digital load cell. The experimental results show that the heat release rate of a mine fire can be calculated using AMS sensor data with reasonable accuracy.

String Mining in Bioinformatics

NASA Astrophysics Data System (ADS)

Abouelhoda, Mohamed; Ghanem, Moustafa

Sequence analysis is a major area in bioinformatics encompassing the methods and techniques for studying the biological sequences, DNA, RNA, and proteins, on the linear structure level. The focus of this area is generally on the identification of intra- and inter-molecular similarities. Identifying intra-molecular similarities boils down to detecting repeated segments within a given sequence, while identifying inter-molecular similarities amounts to spotting common segments among two or multiple sequences. From a data mining point of view, sequence analysis is nothing but string- or pattern mining specific to biological strings. For a long time, this point of view, however, has not been explicitly embraced neither in the data mining nor in the sequence analysis text books, which may be attributed to the co-evolution of the two apparently independent fields. In other words, although the word “data-mining” is almost missing in the sequence analysis literature, its basic concepts have been implicitly applied. Interestingly, recent research in biological sequence analysis introduced efficient solutions to many problems in data mining, such as querying and analyzing time series [49,53], extracting information from web pages [20], fighting spam mails [50], detecting plagiarism [22], and spotting duplications in software systems [14].

Human factors model concerning the man-machine interface of mining crewstations

NASA Technical Reports Server (NTRS)

Rider, James P.; Unger, Richard L.

1989-01-01

The U.S. Bureau of Mines is developing a computer model to analyze the human factors aspect of mining machine operator compartments. The model will be used as a research tool and as a design aid. It will have the capability to perform the following: simulated anthropometric or reach assessment, visibility analysis, illumination analysis, structural analysis of the protective canopy, operator fatigue analysis, and computation of an ingress-egress rating. The model will make extensive use of graphics to simplify data input and output. Two dimensional orthographic projections of the machine and its operator compartment are digitized and the data rebuilt into a three dimensional representation of the mining machine. Anthropometric data from either an individual or any size population may be used. The model is intended for use by equipment manufacturers and mining companies during initial design work on new machines. In addition to its use in machine design, the model should prove helpful as an accident investigation tool and for determining the effects of machine modifications made in the field on the critical areas of visibility and control reach ability.

HC StratoMineR: A Web-Based Tool for the Rapid Analysis of High-Content Datasets.

PubMed

Omta, Wienand A; van Heesbeen, Roy G; Pagliero, Romina J; van der Velden, Lieke M; Lelieveld, Daphne; Nellen, Mehdi; Kramer, Maik; Yeong, Marley; Saeidi, Amir M; Medema, Rene H; Spruit, Marco; Brinkkemper, Sjaak; Klumperman, Judith; Egan, David A

2016-10-01

High-content screening (HCS) can generate large multidimensional datasets and when aligned with the appropriate data mining tools, it can yield valuable insights into the mechanism of action of bioactive molecules. However, easy-to-use data mining tools are not widely available, with the result that these datasets are frequently underutilized. Here, we present HC StratoMineR, a web-based tool for high-content data analysis. It is a decision-supportive platform that guides even non-expert users through a high-content data analysis workflow. HC StratoMineR is built by using My Structured Query Language for storage and querying, PHP: Hypertext Preprocessor as the main programming language, and jQuery for additional user interface functionality. R is used for statistical calculations, logic and data visualizations. Furthermore, C++ and graphical processor unit power is diffusely embedded in R by using the rcpp and rpud libraries for operations that are computationally highly intensive. We show that we can use HC StratoMineR for the analysis of multivariate data from a high-content siRNA knock-down screen and a small-molecule screen. It can be used to rapidly filter out undesirable data; to select relevant data; and to perform quality control, data reduction, data exploration, morphological hit picking, and data clustering. Our results demonstrate that HC StratoMineR can be used to functionally categorize HCS hits and, thus, provide valuable information for hit prioritization.

Toxic element mobility assessment and modeling for regional geo-scientific survey to support Risk Assessment in a European Union context

NASA Astrophysics Data System (ADS)

Abdaal, Ahmed; Jordan, Gyozo; Bartha, Andras; Fugedi, Ubul

2013-04-01

The Mine Waste Directive 2006/21/EC requires the risk-based inventory of all mine waste sites in Europe. The geochemical documentation concerning inert classification and ranking of the mine wastes requires detailed field study and laboratory testing and analyses of waste material to assess the Acid Mine Drainage potential and toxic element mobility. The procedure applied in this study used a multi-level decision support scheme including: 1) expert judgment, 2) data review, 3) representative field sampling and laboratory analysis of formations listed in the Inert Mining Waste List, and 4) requesting available laboratory analysis data from selected operating mines. Based on expert judgment, the listed formations were classified into three categories. A: inert B: probably inert, but has to be checked, C: probably not inert, has to be examined. This paper discusses the heavy metal contamination risk assessment (RA) in leached quarry-mine waste sites in Hungary. In total 34 mine waste sites (including tailing lagoons and heaps of both abandoned mines and active quarries) have been selected for scientific testing using the EU Pre-selection Protocol. Over 93 field samples have been collected from the mine sites including Ore (Andesite and Ryolite), Coal (Lignite, black and brown coals), Peat, Alginite, Bauxite, Clay and Limestone. Laboratory analyses of the total toxic element content (aqua regia extraction), the mobile toxic element content (deionized water leaching) and the analysis of different forms of sulfur (sulfuric acid potential) ) on the base of Hungarian GKM Decree No. 14/2008. (IV. 3) concerning mining waste management. A detailed geochemical study together with spatial analysis and GIS has been performed to derive a geochemically sound contamination RA of the mine waste sites. Key parameters such as heavy metal and sulphur content, in addition to the distance to the nearest surface and ground water bodies, or to sensitive receptors such as settlements and protected areas are calculated and statistically evaluated using STATGRAPHICS® in order to calibrate the RA methods. Results show that some of the waste rock materials assumed to be inert were found non/inert. Thus, regional RA needs more spatial and petrological examination with special care to rock and mineral deposit genetics.

The potential of text mining in data integration and network biology for plant research: a case study on Arabidopsis.

PubMed

Van Landeghem, Sofie; De Bodt, Stefanie; Drebert, Zuzanna J; Inzé, Dirk; Van de Peer, Yves

2013-03-01

Despite the availability of various data repositories for plant research, a wealth of information currently remains hidden within the biomolecular literature. Text mining provides the necessary means to retrieve these data through automated processing of texts. However, only recently has advanced text mining methodology been implemented with sufficient computational power to process texts at a large scale. In this study, we assess the potential of large-scale text mining for plant biology research in general and for network biology in particular using a state-of-the-art text mining system applied to all PubMed abstracts and PubMed Central full texts. We present extensive evaluation of the textual data for Arabidopsis thaliana, assessing the overall accuracy of this new resource for usage in plant network analyses. Furthermore, we combine text mining information with both protein-protein and regulatory interactions from experimental databases. Clusters of tightly connected genes are delineated from the resulting network, illustrating how such an integrative approach is essential to grasp the current knowledge available for Arabidopsis and to uncover gene information through guilt by association. All large-scale data sets, as well as the manually curated textual data, are made publicly available, hereby stimulating the application of text mining data in future plant biology studies.

EXACT2: the semantics of biomedical protocols

PubMed Central

2014-01-01

Background The reliability and reproducibility of experimental procedures is a cornerstone of scientific practice. There is a pressing technological need for the better representation of biomedical protocols to enable other agents (human or machine) to better reproduce results. A framework that ensures that all information required for the replication of experimental protocols is essential to achieve reproducibility. Methods We have developed the ontology EXACT2 (EXperimental ACTions) that is designed to capture the full semantics of biomedical protocols required for their reproducibility. To construct EXACT2 we manually inspected hundreds of published and commercial biomedical protocols from several areas of biomedicine. After establishing a clear pattern for extracting the required information we utilized text-mining tools to translate the protocols into a machine amenable format. We have verified the utility of EXACT2 through the successful processing of previously 'unseen' (not used for the construction of EXACT2) protocols. Results The paper reports on a fundamentally new version EXACT2 that supports the semantically-defined representation of biomedical protocols. The ability of EXACT2 to capture the semantics of biomedical procedures was verified through a text mining use case. In this EXACT2 is used as a reference model for text mining tools to identify terms pertinent to experimental actions, and their properties, in biomedical protocols expressed in natural language. An EXACT2-based framework for the translation of biomedical protocols to a machine amenable format is proposed. Conclusions The EXACT2 ontology is sufficient to record, in a machine processable form, the essential information about biomedical protocols. EXACT2 defines explicit semantics of experimental actions, and can be used by various computer applications. It can serve as a reference model for for the translation of biomedical protocols in natural language into a semantically-defined format. PMID:25472549

Perspectives for on-line analysis of bauxite by neutron irradiation

NASA Astrophysics Data System (ADS)

Beurton, Gabriel; Ledru, Bertrand; Letourneur, Philippe

1995-03-01

The interest in bauxite as a major source of alumina results in a strong demand for on-line instrumentation suitable for sorting, blending, and processing operations at the bauxite mine and for monitoring instrumentation in the Bayer process. The results of laboratory experiments based on neutron interactions with bauxite are described. The technique was chosen in order to overcome the problem of spatial heterogeneity in bulk mineral analysis. The evaluated elements contributed to approximately 99.5% of the sample weight. In addition, the measurements provide valuable information on physical parameters such as density, hygrometry, and material flow. Using a pulsed generator, the analysis system offers potential for on-line measurements (borehole logging or conveyor belt). An overall description of the experimental set-up is given. The experimental data include measurements of natural radioactivity, delayed radioactivity induced by activation, and prompt gamma rays following neutron reaction. In situ applications of neutron interactions provide continuous analysis and produce results which are more statistically significant. The key factors contributing to advances in industrial applications are the development of high count rate gamma spectroscopy and computational tools to design measurement systems and interpret their results.

Proceedings: Fourth Workshop on Mining Scientific Datasets

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kamath, C

Commercial applications of data mining in areas such as e-commerce, market-basket analysis, text-mining, and web-mining have taken on a central focus in the JCDD community. However, there is a significant amount of innovative data mining work taking place in the context of scientific and engineering applications that is not well represented in the mainstream KDD conferences. For example, scientific data mining techniques are being developed and applied to diverse fields such as remote sensing, physics, chemistry, biology, astronomy, structural mechanics, computational fluid dynamics etc. In these areas, data mining frequently complements and enhances existing analysis methods based on statistics, exploratorymore » data analysis, and domain-specific approaches. On the surface, it may appear that data from one scientific field, say genomics, is very different from another field, such as physics. However, despite their diversity, there is much that is common across the mining of scientific and engineering data. For example, techniques used to identify objects in images are very similar, regardless of whether the images came from a remote sensing application, a physics experiment, an astronomy observation, or a medical study. Further, with data mining being applied to new types of data, such as mesh data from scientific simulations, there is the opportunity to apply and extend data mining to new scientific domains. This one-day workshop brings together data miners analyzing science data and scientists from diverse fields to share their experiences, learn how techniques developed in one field can be applied in another, and better understand some of the newer techniques being developed in the KDD community. This is the fourth workshop on the topic of Mining Scientific Data sets; for information on earlier workshops, see http://www.ahpcrc.org/conferences/. This workshop continues the tradition of addressing challenging problems in a field where the diversity of applications is matched only by the opportunities that await a practitioner.« less

Probabilistic Model and Analysis of Conventional Preinstalled Mine Field Defense.

DTIC Science & Technology

1980-09-01

process to model the one or two positions of mines in the mine field. The duel between the anti-tank weapon and offensive tanks crossing the field is...mine field. The duel between the anti-tank weapon and offensive tanks crossing the field is modeled with a con- tinuous time Markov chain. Some...11 B. DUEL ------------------------------------------- 15 IV. DUEL

Nanominerals and potentially hazardous elements from coal cleaning rejects of abandoned mines: Environmental impact and risk assessment.

PubMed

Fdez-Ortiz de Vallejuelo, Silvia; Gredilla, Ainara; da Boit, Kátia; Teixeira, Elba C; Sampaio, Carlos H; Madariaga, Juan Manuel; Silva, Luis F O

2017-02-01

Soils around coal mining are important reservoir of hazardous elements (HEs), nanominerals, and ultrafine compounds. This research reports and discusses the soil concentrations of HEs (As, Cd, Cr, Cu, Ni, Pb, and Zn) in coal residues of abandoned mines. To assess differences regarding environmental impact and risk assessment between coal abandoned mines from the Santa Catarina state, eighteen coal cleaning rejects with different mineralogical and chemical composition, from eight abandoned mines were collected. Nanominerals and ultra-fine minerals from mining-contaminated areas were analyzed by X-ray diffraction (XRD), field emission scanning electron microscopy (FE-SEM), and high-resolution transmission electron microscope (HR-TEM), providing new information on the mineralogy and nano-mineralogy of these coal residues. The total contents of 57 elements (HEs, alkali metals, and rare earth elements) were analyzed by Inductively Coupled Plasma Mass Spectrometry (ICP-MS). The calculation of NWACs (Normalized Average Weighted Concentration), together with the chemometric analysis by Principal component analysis (PCA) confirmed the variability of the samples regarding their city and their mine of origin. Moreover, the results confirmed the existence of hotspots in mines near urban areas. Copyright © 2016 Elsevier Ltd. All rights reserved.

New approach for reduction of diesel consumption by comparing different mining haulage configurations.

PubMed

Rodovalho, Edmo da Cunha; Lima, Hernani Mota; de Tomi, Giorgio

2016-05-01

The mining operations of loading and haulage have an energy source that is highly dependent on fossil fuels. In mining companies that select trucks for haulage, this input is the main component of mining costs. How can the impact of the operational aspects on the diesel consumption of haulage operations in surface mines be assessed? There are many studies relating the consumption of fuel trucks to several variables, but a methodology that prioritizes higher-impact variables under each specific condition is not available. Generic models may not apply to all operational settings presented in the mining industry. This study aims to create a method of analysis, identification, and prioritization of variables related to fuel consumption of haul trucks in open pit mines. For this purpose, statistical analysis techniques and mathematical modelling tools using multiple linear regressions will be applied. The model is shown to be suitable because the results generate a good description of the fuel consumption behaviour. In the practical application of the method, the reduction of diesel consumption reached 10%. The implementation requires no large-scale investments or very long deadlines and can be applied to mining haulage operations in other settings. Copyright © 2016 Elsevier Ltd. All rights reserved.

Performance analysis of a multispectral framing camera for detecting mines in the littoral zone and beach zone

NASA Astrophysics Data System (ADS)

Louchard, Eric; Farm, Brian; Acker, Andrew

2008-04-01

BAE Systems Sensor Systems Identification & Surveillance (IS) has developed, under contract with the Office of Naval Research, a multispectral airborne sensor system and processing algorithms capable of detecting mine-like objects in the surf zone and land mines in the beach zone. BAE Systems has used this system in a blind test at a test range established by the Naval Surface Warfare Center - Panama City Division (NSWC-PCD) at Eglin Air Force Base. The airborne and ground subsystems used in this test are described, with graphical illustrations of the detection algorithms. We report on the performance of the system configured to operate with a human operator analyzing data on a ground station. A subsurface (underwater bottom proud mine in the surf zone and moored mine in shallow water) mine detection capability is demonstrated in the surf zone. Surface float detection and proud land mine detection capability is also demonstrated. Our analysis shows that this BAE Systems-developed multispectral airborne sensor provides a robust technical foundation for a viable system for mine counter-measures, and would be a valuable asset for use prior to an amphibious assault.

The application of LANDSAT-1 imagery for monitoring strip mines in the new river watershed in northeast Tennessee, part 2

NASA Technical Reports Server (NTRS)

Shahrokhi, F. (Principal Investigator); Sharber, L. A.

1977-01-01

The author has identified the following significant results. LANDSAT imagery and supplementary aircraft photography of the New River drainage basin were subjected to a multilevel analysis using conventional photointerpretation methods, densitometric techniques, multispectral analysis, and statistical tests to determine the accuracy of LANDSAT-1 imagery for measuring strip mines of common size. The LANDSAT areas were compared with low altitude measurements. The average accuracy over all the mined land sample areas mapped from LANDSAT-1 was 90%. The discrimination of strip mine subcategories is somewhat limited on LANDSAT imagery. A mine site, whether active or inactive, can be inferred by lack of vegetation, by shape, or image texture. Mine ponds are difficult or impossible to detect because of their small size and turbidity. Unless bordered and contrasted with vegetation, haulage roads are impossible to delineate. Preparation plants and refuge areas are not detectable. Density slicing of LANDSAT band 7 proved most useful in the detection of reclamation progress within the mined areas. For most state requirements for year-round monitoring of surface mined land, LANDSAT is of limited value. However, for periodic updating of regional surface maps, LANDSAT may provide sufficient accuracies for some users.

Citation-related reliability analysis for a pilot sample of underground coal mines.

PubMed

Kinilakodi, Harisha; Grayson, R Larry

2011-05-01

The scrutiny of underground coal mine safety was heightened because of the disasters that occurred in 2006-2007, and more recently in 2010. In the aftermath of the 2006 incidents, the U.S. Congress passed the Mine Improvement and New Emergency Response Act of 2006 (MINER Act), which strengthened the existing regulations and mandated new laws to address various issues related to emergency preparedness and response, escape from an emergency situation, and protection of miners. The National Mining Association-sponsored Mine Safety Technology and Training Commission study highlighted the role of risk management in identifying and controlling major hazards, which are elements that could come together and cause a mine disaster. In 2007 MSHA revised its approach to the "Pattern of Violations" (POV) process in order to target unsafe mines and then force them to remediate conditions in their mines. The POV approach has certain limitations that make it difficult for it to be enforced. One very understandable way to focus on removing threats from major-hazard conditions is to use citation-related reliability analysis. The citation reliability approach, which focuses on the probability of not getting a citation on a given inspector day, is considered an analogue to the maintenance reliability approach, which many mine operators understand and use. In this study, the citation reliability approach was applied to a stratified random sample of 31 underground coal mines to examine its potential for broader application. The results clearly show the best-performing and worst-performing mines for compliance with mine safety standards, and they highlight differences among different mine sizes. Copyright © 2010 Elsevier Ltd. All rights reserved.

Data Mining Techniques Applied to Hydrogen Lactose Breath Test.

PubMed

Rubio-Escudero, Cristina; Valverde-Fernández, Justo; Nepomuceno-Chamorro, Isabel; Pontes-Balanza, Beatriz; Hernández-Mendoza, Yoedusvany; Rodríguez-Herrera, Alfonso

2017-01-01

Analyze a set of data of hydrogen breath tests by use of data mining tools. Identify new patterns of H2 production. Hydrogen breath tests data sets as well as k-means clustering as the data mining technique to a dataset of 2571 patients. Six different patterns have been extracted upon analysis of the hydrogen breath test data. We have also shown the relevance of each of the samples taken throughout the test. Analysis of the hydrogen breath test data sets using data mining techniques has identified new patterns of hydrogen generation upon lactose absorption. We can see the potential of application of data mining techniques to clinical data sets. These results offer promising data for future research on the relations between gut microbiota produced hydrogen and its link to clinical symptoms.

Analysis on Heavy Metal Distribution in Overlying Deposit and Pollution Characteristics in Rivers around Dahongshan Fe&Cu Mine in Yunnan Province, China

NASA Astrophysics Data System (ADS)

Huang, Qianrui; Cheng, Xianfeng; Qi, Wufu; Xu, Jun; Yang, Shuran

2017-12-01

Dahongshan Fe&Cu mine in Yunnan Province was endowed with the title of “National Green Mine Pilots” by Chinese Ministry of Land and Resources in April 2013. In order to verify the implementation effects of the green mine and better drive the construction of the green mine by other mine enterprises in Yunnan, the project team investigated overlying deposit in rivers around the Dahongshan mine in the wet season (August) of 2016, investigated mine enterprises, and applied the Potential Ecological Risk Index to evaluate potential ecological hazards of heavy metal pollution in overlying deposit. The results showed that all sampling points were less than 105, indicating the lower ecological hazard degree.

Automated Analysis of Renewable Energy Datasets ('EE/RE Data Mining')

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bush, Brian; Elmore, Ryan; Getman, Dan

This poster illustrates methods to substantially improve the understanding of renewable energy data sets and the depth and efficiency of their analysis through the application of statistical learning methods ('data mining') in the intelligent processing of these often large and messy information sources. The six examples apply methods for anomaly detection, data cleansing, and pattern mining to time-series data (measurements from metering points in buildings) and spatiotemporal data (renewable energy resource datasets).

The impact of atmospheric dust deposition and trace elements levels on the villages surrounding the former mining areas in a semi-arid environment (SE Spain)

NASA Astrophysics Data System (ADS)

Sánchez Bisquert, David; Matías Peñas Castejón, José; García Fernández, Gregorio

2017-03-01

It is understood that particulate matter in the atmosphere from metallic mining waste has adverse health effects on populations living nearby. Atmospheric deposition is a process connecting the mining wasteswith nearby ecosystems. Unfortunately, very limited information is available about atmospheric deposition surrounding rural metallic mining areas. This article will focus on the deposition from mining areas, combined with its impact on nearby rural built areas and populations. Particle samples were collected between June 2011 and March 2013. They were collected according to Spanish legislation in ten specialised dust collectors. They were located near populations close to a former Mediterranean mining area, plus a control, to assess the impact of mining waste on these villages. This article and its results have been made through an analysis of atmospheric deposition of these trace elements (Mn, Zn, As, Cd and Pb). It also includes an analysis of total dust flux. Within this analysis it has considered the spatial variations of atmospheric deposition flux in these locations. The average annual level of total bulk deposition registered was 42.0 g m-2 per year. This was higher than most of the areas affected by a Mediterranean climate or in semi-arid conditions around the world. Regarding the overall analysis of trace elements, the annual bulk deposition fluxes of total Zn far exceeded the values of other areas. While Mn, Cd and Pb showed similar or lower values, and in part much lower than those described in other Mediterranean mining areas. This study confirmed some spatial variability of dust and trace elements, contained within the atmospheric deposition. From both an environmental and a public health perspective, environmental managers must take into account the cumulative effect of the deposition of trace elements on the soil and air quality around and within the villages surrounding metallic mining areas.

Percolator: Scalable Pattern Discovery in Dynamic Graphs

DOE Office of Scientific and Technical Information (OSTI.GOV)

Choudhury, Sutanay; Purohit, Sumit; Lin, Peng

We demonstrate Percolator, a distributed system for graph pattern discovery in dynamic graphs. In contrast to conventional mining systems, Percolator advocates efficient pattern mining schemes that (1) support pattern detection with keywords; (2) integrate incremental and parallel pattern mining; and (3) support analytical queries such as trend analysis. The core idea of Percolator is to dynamically decide and verify a small fraction of patterns and their in- stances that must be inspected in response to buffered updates in dynamic graphs, with a total mining cost independent of graph size. We demonstrate a) the feasibility of incremental pattern mining by walkingmore » through each component of Percolator, b) the efficiency and scalability of Percolator over the sheer size of real-world dynamic graphs, and c) how the user-friendly GUI of Percolator inter- acts with users to support keyword-based queries that detect, browse and inspect trending patterns. We also demonstrate two user cases of Percolator, in social media trend analysis and academic collaboration analysis, respectively.« less

Prediction accident triangle in maintenance of underground mine facilities using Poisson distribution analysis

NASA Astrophysics Data System (ADS)

Khuluqi, M. H.; Prapdito, R. R.; Sambodo, F. P.

2018-04-01

In Indonesia, mining is categorized as a hazardous industry. In recent years, a dramatic increase of mining equipment and technological complexities had resulted in higher maintenance expectations that accompanied by the changes in the working conditions, especially on safety. Ensuring safety during the process of conducting maintenance works in underground mine is important as an integral part of accident prevention programs. Accident triangle has provided a support to safety practitioner to draw a road map in preventing accidents. Poisson distribution is appropriate for the analysis of accidents at a specific site in a given time period. Based on the analysis of accident statistics in the underground mine maintenance of PT. Freeport Indonesia from 2011 through 2016, it is found that 12 minor accidents for 1 major accident and 66 equipment damages for 1 major accident as a new value of accident triangle. The result can be used for the future need for improving the accident prevention programs.

Development of Database for Accident Analysis in Indian Mines

NASA Astrophysics Data System (ADS)

Tripathy, Debi Prasad; Guru Raghavendra Reddy, K.

2016-10-01

Mining is a hazardous industry and high accident rates associated with underground mining is a cause of deep concern. Technological developments notwithstanding, rate of fatal accidents and reportable incidents have not shown corresponding levels of decline. This paper argues that adoption of appropriate safety standards by both mine management and the government may result in appreciable reduction in accident frequency. This can be achieved by using the technology in improving the working conditions, sensitising workers and managers about causes and prevention of accidents. Inputs required for a detailed analysis of an accident include information on location, time, type, cost of accident, victim, nature of injury, personal and environmental factors etc. Such information can be generated from data available in the standard coded accident report form. This paper presents a web based application for accident analysis in Indian mines during 2001-2013. An accident database (SafeStat) prototype based on Intranet of the TCP/IP agreement, as developed by the authors, is also discussed.

Rigid Polyurethane Foam (RPF) Technology for Countermines (Sea) Program Phase II

DOE Office of Scientific and Technical Information (OSTI.GOV)

WOODFIN,RONALD L.; FAUCETT,DAVID L.; HANCE,BRADLEY G.

This Phase II report documents the results of one subtask initiated under the joint Department of Energy (DOE)/Department of Defense (DoD) Memorandum of Understanding (MOU) for Countermine Warfare. The development of Rigid Polyurethane Foams for neutralization of mines and barriers in amphibious assault was the objective of the tasking. This phase of the program concentrated on formation of RPF in water, explosive mine simulations, and development of foam and fabric pontoons. Field experimentation was done primarily at the Energetic Materials Research and Testing Center (EMRTC) of the New Mexico Institute of Mining and Technology, Socorro, NM between February 1996 andmore » September 1998.« less

Modeling of gold production in Malaysia

NASA Astrophysics Data System (ADS)

Muda, Nora; Ainuddeen, Nasihah Rasyiqah; Ismail, Hamizun; Umor, Mohd Rozi

2013-04-01

This study was conducted to identify the main factors that contribute to the gold production and hence determine the factors that affect to the development of the mining industry in Malaysia. An econometric approach was used by performing the cointegration analysis among the factors to determine the existence of long term relationship between the gold prices, the number of gold mines, the number of workers in gold mines and the gold production. The study continued with the Granger analysis to determine the relationship between factors and gold production. Results have found that there are long term relationship between price, gold production and number of employees. Granger causality analysis shows that there is only one way relationship between the number of employees with gold production in Malaysia and the number of gold mines in Malaysia.

Monitoring the growth or decline of vegetation on mine dumps

NASA Technical Reports Server (NTRS)

Gilbertson, B. P. (Principal Investigator)

1975-01-01

The author has identified the following signficant results. It was established that particular mine dumps throughout the entire test area can be detected and identified. It was also established that patterns of vegetative growth on the mine dumps can be recognized from a simple visual analysis of photographic images. Because vegetation tends to occur in patches on many mine dumps, it is unsatisfactory to classify complete dumps into categories of percentage vegetative cover. A more desirable approach is to classify the patches of vegetation themselves. The coarse resolution of conventional densitometers restricts the accuracy of this procedure, and consequently a direct analysis of ERTS CCT's is preferred. A set of computer programs was written to perform the data reading and manipulating functions required for basic CCT analysis.

Open pit mining profit maximization considering selling stage and waste rehabilitation cost

NASA Astrophysics Data System (ADS)

Muttaqin, B. I. A.; Rosyidi, C. N.

2017-11-01

In open pit mining activities, determination of the cut-off grade becomes crucial for the company since the cut-off grade affects how much profit will be earned for the mining company. In this study, we developed a cut-off grade determination mode for the open pit mining industry considering the cost of mining, waste removal (rehabilitation) cost, processing cost, fixed cost, and selling stage cost. The main goal of this study is to develop a model of cut-off grade determination to get the maximum total profit. Secondly, this study is also developed to observe the model of sensitivity based on changes in the cost components. The optimization results show that the models can help mining company managers to determine the optimal cut-off grade and also estimate how much profit that can be earned by the mining company. To illustrate the application of the models, a numerical example and a set of sensitivity analysis are presented. From the results of sensitivity analysis, we conclude that the changes in the sales price greatly affects the optimal cut-off value and the total profit.

Using data mining to segment healthcare markets from patients' preference perspectives.

PubMed

Liu, Sandra S; Chen, Jie

2009-01-01

This paper aims to provide an example of how to use data mining techniques to identify patient segments regarding preferences for healthcare attributes and their demographic characteristics. Data were derived from a number of individuals who received in-patient care at a health network in 2006. Data mining and conventional hierarchical clustering with average linkage and Pearson correlation procedures are employed and compared to show how each procedure best determines segmentation variables. Data mining tools identified three differentiable segments by means of cluster analysis. These three clusters have significantly different demographic profiles. The study reveals, when compared with traditional statistical methods, that data mining provides an efficient and effective tool for market segmentation. When there are numerous cluster variables involved, researchers and practitioners need to incorporate factor analysis for reducing variables to clearly and meaningfully understand clusters. Interests and applications in data mining are increasing in many businesses. However, this technology is seldom applied to healthcare customer experience management. The paper shows that efficient and effective application of data mining methods can aid the understanding of patient healthcare preferences.

Geodynamic risk magnitude as an objective indicator of rockburst prevention effectiveness (in terms of apatite mines in Khibiny)

NASA Astrophysics Data System (ADS)

Fedotova Panin, YuV, VI

2018-03-01

The results of the statistical retrospective analysis of the officially recorded geodynamic events in mines of Apatit Company within the Khibiny Massif are presented. The risks and aftereffects of geodynamic events have been calculated. Under discussion are the results of three calculation variants taking into account the scale of human impact on rock mass. The analysis shows that the main damage due to geodynamic events is different-degree destruction of mine workings while the remaining aftereffects account for less than ten percent. That is, the geodynamic risk in apatite mines can be identified as technological.

Assessing the effectiveness of sustainable land management policies for combating desertification: A data mining approach.

PubMed

Salvati, L; Kosmas, C; Kairis, O; Karavitis, C; Acikalin, S; Belgacem, A; Solé-Benet, A; Chaker, M; Fassouli, V; Gokceoglu, C; Gungor, H; Hessel, R; Khatteli, H; Kounalaki, A; Laouina, A; Ocakoglu, F; Ouessar, M; Ritsema, C; Sghaier, M; Sonmez, H; Taamallah, H; Tezcan, L; de Vente, J; Kelly, C; Colantoni, A; Carlucci, M

2016-12-01

This study investigates the relationship between fine resolution, local-scale biophysical and socioeconomic contexts within which land degradation occurs, and the human responses to it. The research draws on experimental data collected under different territorial and socioeconomic conditions at 586 field sites in five Mediterranean countries (Spain, Greece, Turkey, Tunisia and Morocco). We assess the level of desertification risk under various land management practices (terracing, grazing control, prevention of wildland fires, soil erosion control measures, soil water conservation measures, sustainable farming practices, land protection measures and financial subsidies) taken as possible responses to land degradation. A data mining approach, incorporating principal component analysis, non-parametric correlations, multiple regression and canonical analysis, was developed to identify the spatial relationship between land management conditions, the socioeconomic and environmental context (described using 40 biophysical and socioeconomic indicators) and desertification risk. Our analysis identified a number of distinct relationships between the level of desertification experienced and the underlying socioeconomic context, suggesting that the effectiveness of responses to land degradation is strictly dependent on the local biophysical and socioeconomic context. Assessing the latent relationship between land management practices and the biophysical/socioeconomic attributes characterizing areas exposed to different levels of desertification risk proved to be an indirect measure of the effectiveness of field actions contrasting land degradation. Copyright © 2016 Elsevier Ltd. All rights reserved.

A demonstration of ERTS-1 analog and digital techniques applied to strip mining in Maryland and West Virginia

NASA Technical Reports Server (NTRS)

Anderson, A. T.; Schubert, J.

1974-01-01

The largest contour strip mining operations in western Maryland and West Virginia are located within the Georges Creek and the Upper Potomac Basins. These two coal basins lie within the Georges Creek (Wellersburg) syncline. The disturbed strip mine areas were delineated with the surrounding geological and vegetation features using ERTS-1 data in both analog (imagery) and digital form. The two digital systems used were: (1) the ERTS-Analysis system, a point-by-point digital analysis of spectral signatures based on known spectral values, and (2) the LARS Automatic Data Processing System. The digital techniques being developed will later be incorporated into a data base for land use planning. These two systems aided in efforts to determine the extent and state of strip mining in this region. Aircraft data, ground verification information, and geological field studies also aided in the application of ERTS-1 imagery to perform an integrated analysis that assessed the adverse effects of strip mining. The results indicated that ERTS can both monitor and map the extent of strip mining to determine immediately the acreage affected and indicate where future reclamation and revegetation may be necessary.

Genetic and environmental effects on morphology and asexual reproduction in the moss, Bryum bicolor

DOE Office of Scientific and Technical Information (OSTI.GOV)

Shaw, A.J.

A distinctive form of Bryum bicolor, characterized by stoutly excurrent costae and abundant asexual gemmae, occurs on heavy metal-contaminated tailings of the Conrad Hill Mine in the Piedmont of North Carolina. Plants from two mine site populations, plus two other populations from Richmond, Virginia, were grown on three types of soil in order to determine the degree to which morphological traits, including the number of gemmae per plant, can be modified by substrate. All populations grew equally well in the mine soil, and there was no evidence that plants from the mine site populations were physiologically adapted for growth onmore » the contaminated tailings. Leaf dimensions, costa length, and number of gemmae per stem were strongly influenced by substrate, although some differences between populations were maintained under experimental conditions. Populations also differed in the efficacy with which plants regenerated from gametophytic fragments.« less

From protein sequence to dynamics and disorder with DynaMine.

PubMed

Cilia, Elisa; Pancsa, Rita; Tompa, Peter; Lenaerts, Tom; Vranken, Wim F

2013-01-01

Protein function and dynamics are closely related; however, accurate dynamics information is difficult to obtain. Here based on a carefully assembled data set derived from experimental data for proteins in solution, we quantify backbone dynamics properties on the amino-acid level and develop DynaMine--a fast, high-quality predictor of protein backbone dynamics. DynaMine uses only protein sequence information as input and shows great potential in distinguishing regions of different structural organization, such as folded domains, disordered linkers, molten globules and pre-structured binding motifs of different sizes. It also identifies disordered regions within proteins with an accuracy comparable to the most sophisticated existing predictors, without depending on prior disorder knowledge or three-dimensional structural information. DynaMine provides molecular biologists with an important new method that grasps the dynamical characteristics of any protein of interest, as we show here for human p53 and E1A from human adenovirus 5.

Respirable dust measured downwind during rock dust application.

PubMed

Harris, M L; Organiscak, J; Klima, S; Perera, I E

2017-05-01

The Pittsburgh Mining Research Division of the U.S. National Institute for Occupational Safety and Health (NIOSH) conducted underground evaluations in an attempt to quantify respirable rock dust generation when using untreated rock dust and rock dust treated with an anticaking additive. Using personal dust monitors, these evaluations measured respirable rock dust levels arising from a flinger-type application of rock dust on rib and roof surfaces. Rock dust with a majority of the respirable component removed was also applied in NIOSH's Bruceton Experimental Mine using a bantam duster. The respirable dust measurements obtained downwind from both of these tests are presented and discussed. This testing did not measure miners' exposure to respirable coal mine dust under acceptable mining practices, but indicates the need for effective continuous administrative controls to be exercised when rock dusting to minimize the measured amount of rock dust in the sampling device.

A Review of Recent Advancement in Integrating Omics Data with Literature Mining towards Biomedical Discoveries

PubMed Central

Raja, Kalpana; Patrick, Matthew; Gao, Yilin; Madu, Desmond; Yang, Yuyang

2017-01-01

In the past decade, the volume of “omics” data generated by the different high-throughput technologies has expanded exponentially. The managing, storing, and analyzing of this big data have been a great challenge for the researchers, especially when moving towards the goal of generating testable data-driven hypotheses, which has been the promise of the high-throughput experimental techniques. Different bioinformatics approaches have been developed to streamline the downstream analyzes by providing independent information to interpret and provide biological inference. Text mining (also known as literature mining) is one of the commonly used approaches for automated generation of biological knowledge from the huge number of published articles. In this review paper, we discuss the recent advancement in approaches that integrate results from omics data and information generated from text mining approaches to uncover novel biomedical information. PMID:28331849

Archaeal Diversity in Waters from Deep South African Gold Mines

PubMed Central

Takai, Ken; Moser, Duane P.; DeFlaun, Mary; Onstott, Tullis C.; Fredrickson, James K.

2001-01-01

A culture-independent molecular analysis of archaeal communities in waters collected from deep South African gold mines was performed by performing a PCR-mediated terminal restriction fragment length polymorphism (T-RFLP) analysis of rRNA genes (rDNA) in conjunction with a sequencing analysis of archaeal rDNA clone libraries. The water samples used represented various environments, including deep fissure water, mine service water, and water from an overlying dolomite aquifer. T-RFLP analysis revealed that the ribotype distribution of archaea varied with the source of water. The archaeal communities in the deep gold mine environments exhibited great phylogenetic diversity; the majority of the members were most closely related to uncultivated species. Some archaeal rDNA clones obtained from mine service water and dolomite aquifer water samples were most closely related to environmental rDNA clones from surface soil (soil clones) and marine environments (marine group I [MGI]). Other clones exhibited intermediate phylogenetic affiliation between soil clones and MGI in the Crenarchaeota. Fissure water samples, derived from active or dormant geothermal environments, yielded archaeal sequences that exhibited novel phylogeny, including a novel lineage of Euryarchaeota. These results suggest that deep South African gold mines harbor novel archaeal communities distinct from those observed in other environments. Based on the phylogenetic analysis of archaeal strains and rDNA clones, including the newly discovered archaeal rDNA clones, the evolutionary relationship and the phylogenetic organization of the domain Archaea are reevaluated. PMID:11722932

A systems biology approach to the global analysis of transcription factors in colorectal cancer.

PubMed

Pradhan, Meeta P; Prasad, Nagendra K A; Palakal, Mathew J

2012-08-01

Biological entities do not perform in isolation, and often, it is the nature and degree of interactions among numerous biological entities which ultimately determines any final outcome. Hence, experimental data on any single biological entity can be of limited value when considered only in isolation. To address this, we propose that augmenting individual entity data with the literature will not only better define the entity's own significance but also uncover relationships with novel biological entities.To test this notion, we developed a comprehensive text mining and computational methodology that focused on discovering new targets of one class of molecular entities, transcription factors (TF), within one particular disease, colorectal cancer (CRC). We used 39 molecular entities known to be associated with CRC along with six colorectal cancer terms as the bait list, or list of search terms, for mining the biomedical literature to identify CRC-specific genes and proteins. Using the literature-mined data, we constructed a global TF interaction network for CRC. We then developed a multi-level, multi-parametric methodology to identify TFs to CRC. The small bait list, when augmented with literature-mined data, identified a large number of biological entities associated with CRC. The relative importance of these TF and their associated modules was identified using functional and topological features. Additional validation of these highly-ranked TF using the literature strengthened our findings. Some of the novel TF that we identified were: SLUG, RUNX1, IRF1, HIF1A, ATF-2, ABL1, ELK-1 and GATA-1. Some of these TFs are associated with functional modules in known pathways of CRC, including the Beta-catenin/development, immune response, transcription, and DNA damage pathways. Our methodology of using text mining data and a multi-level, multi-parameter scoring technique was able to identify both known and novel TF that have roles in CRC. Starting with just one TF (SMAD3) in the bait list, the literature mining process identified an additional 116 CRC-associated TFs. Our network-based analysis showed that these TFs all belonged to any of 13 major functional groups that are known to play important roles in CRC. Among these identified TFs, we obtained a novel six-node module consisting of ATF2-P53-JNK1-ELK1-EPHB2-HIF1A, from which the novel JNK1-ELK1 association could potentially be a significant marker for CRC.

ThaleMine: A Warehouse for Arabidopsis Data Integration and Discovery.

PubMed

Krishnakumar, Vivek; Contrino, Sergio; Cheng, Chia-Yi; Belyaeva, Irina; Ferlanti, Erik S; Miller, Jason R; Vaughn, Matthew W; Micklem, Gos; Town, Christopher D; Chan, Agnes P

2017-01-01

ThaleMine (https://apps.araport.org/thalemine/) is a comprehensive data warehouse that integrates a wide array of genomic information of the model plant Arabidopsis thaliana. The data collection currently includes the latest structural and functional annotation from the Araport11 update, the Col-0 genome sequence, RNA-seq and array expression, co-expression, protein interactions, homologs, pathways, publications, alleles, germplasm and phenotypes. The data are collected from a wide variety of public resources. Users can browse gene-specific data through Gene Report pages, identify and create gene lists based on experiments or indexed keywords, and run GO enrichment analysis to investigate the biological significance of selected gene sets. Developed by the Arabidopsis Information Portal project (Araport, https://www.araport.org/), ThaleMine uses the InterMine software framework, which builds well-structured data, and provides powerful data query and analysis functionality. The warehoused data can be accessed by users via graphical interfaces, as well as programmatically via web-services. Here we describe recent developments in ThaleMine including new features and extensions, and discuss future improvements. InterMine has been broadly adopted by the model organism research community including nematode, rat, mouse, zebrafish, budding yeast, the modENCODE project, as well as being used for human data. ThaleMine is the first InterMine developed for a plant model. As additional new plant InterMines are developed by the legume and other plant research communities, the potential of cross-organism integrative data analysis will be further enabled. © The Author 2016. Published by Oxford University Press on behalf of Japanese Society of Plant Physiologists. All rights reserved. For permissions, please email: journals.permissions@oup.com.

Factors influencing mine rescue team behaviors.

PubMed

Jansky, Jacqueline H; Kowalski-Trakofler, K M; Brnich, M J; Vaught, C

2016-01-01

A focus group study of the first moments in an underground mine emergency response was conducted by the National Institute for Occupational Safety and Health (NIOSH), Office for Mine Safety and Health Research. Participants in the study included mine rescue team members, team trainers, mine officials, state mining personnel, and individual mine managers. A subset of the data consists of responses from participants with mine rescue backgrounds. These responses were noticeably different from those given by on-site emergency personnel who were at the mine and involved with decisions made during the first moments of an event. As a result, mine rescue team behavior data were separated in the analysis and are reported in this article. By considering the responses from mine rescue team members and trainers, it was possible to sort the data and identify seven key areas of importance to them. On the basis of the responses from the focus group participants with a mine rescue background, the authors concluded that accurate and complete information and a unity of purpose among all command center personnel are two of the key conditions needed for an effective mine rescue operation.

Review and Evaluation of Current Training Programs Found in Various Mining Environments. Final Report. Volume II, Analysis and Recommendations.

ERIC Educational Resources Information Center

Adkins, John; And Others

A project was designed to produce a broad description of current mining training programs and to evaluate their effectiveness with respect to reducing mine injuries. Aggregate training and injury data were used to evaluate the overall training effort at 300 mines as well as specific efforts in 12 categories of training course objectives. From such…

Factor analysis of rock, soil and water geochemical data from Salem magnesite mines and surrounding area, Salem, southern India

NASA Astrophysics Data System (ADS)

Satyanarayanan, M.; Eswaramoorthi, S.; Subramanian, S.; Periakali, P.

2017-09-01

Geochemical analytical data of 15 representative rock samples, 34 soil samples and 55 groundwater samples collected from Salem magnesite mines and surrounding area in Salem, southern India, were subjected to R-mode factor analysis. A maximum of three factors account for 93.8 % variance in rock data, six factors for 84 % variance in soil data, five factors for 71.2 % in groundwater data during summer and six factors for 73.7 % during winter. Total dissolved solids are predominantly contributed by Mg, Na, Cl and SO4 ions in both seasons and are derived from the country rock and mining waste by dissolution of minerals like magnesite, gypsum, halite. The results also show that groundwater is enriched in considerable amount of minor and trace elements (Fe, Mn, Ni, Cr and Co). Nickel, chromium and cobalt in groundwater and soil are derived from leaching of huge mine dumps deposited by selective magnesite mining activity. The factor analysis on trivalent, hexavalent and total Cr in groundwater indicates that most of the Cr in summer is trivalent and in winter hexavalent. The gradational decrease in topographical elevation from northern mine area to the southern residential area, combined regional hydrogeological factors and distribution of ultramafic rocks in the northern part of the study area indicate that these toxic trace elements in water were derived from mine dumps.

Analysis 320 coal mine accidents using structural equation modeling with unsafe conditions of the rules and regulations as exogenous variables.

PubMed

Zhang, Yingyu; Shao, Wei; Zhang, Mengjia; Li, Hejun; Yin, Shijiu; Xu, Yingjun

2016-07-01

Mining has been historically considered as a naturally high-risk industry worldwide. Deaths caused by coal mine accidents are more than the sum of all other accidents in China. Statistics of 320 coal mine accidents in Shandong province show that all accidents contain indicators of "unsafe conditions of the rules and regulations" with a frequency of 1590, accounting for 74.3% of the total frequency of 2140. "Unsafe behaviors of the operator" is another important contributory factor, which mainly includes "operator error" and "venturing into dangerous places." A systems analysis approach was applied by using structural equation modeling (SEM) to examine the interactions between the contributory factors of coal mine accidents. The analysis of results leads to three conclusions. (i) "Unsafe conditions of the rules and regulations," affect the "unsafe behaviors of the operator," "unsafe conditions of the equipment," and "unsafe conditions of the environment." (ii) The three influencing factors of coal mine accidents (with the frequency of effect relation in descending order) are "lack of safety education and training," "rules and regulations of safety production responsibility," and "rules and regulations of supervision and inspection." (iii) The three influenced factors (with the frequency in descending order) of coal mine accidents are "venturing into dangerous places," "poor workplace environment," and "operator error." Copyright © 2016 Elsevier Ltd. All rights reserved.

Deep-sea nematode assemblage has not recovered 26 years after experimental mining of polymetallic nodules (Clarion-Clipperton Fracture Zone, Tropical Eastern Pacific)

NASA Astrophysics Data System (ADS)

Miljutin, Dmitry M.; Miljutina, Maria A.; Arbizu, Pedro Martínez; Galéron, Joëlle

2011-08-01

We investigated nematode assemblages inhabiting the 26-year-old track created by experimental deep-sea mining of polymetallic nodules, and two adjacent, undisturbed sites, one with nodules and one without nodules. The aim was to compare density, assemblage structure, and diversity indices in order to assess the process of recovery of the nematode assemblage inhabiting the disturbed site. This experimental dredging was conducted in 1978 by the Ocean Minerals Company (USA) in the area of a French mining claim in the Clarion-Clipperton Fracture Zone (Tropical Eastern Pacific) at a depth of about 5000 m. The nematode assemblage had not returned its initial state 26 years after the experimental dredging: the total nematode density and biomass within the dredging track were significantly lower than outside the track; the biodiversity indices showed significantly lower nematode diversity within the track; and the structure of the nematode assemblage within the track differed significantly from those in the two undisturbed sites outside the track. However, there were no significant differences in the mean body volumes of adult nematodes and adult-juvenile ratios between the track and reference sites. Parameters such as the rate of sediment restoration (which depends on local hydrological conditions) and the degree and character of the disturbance appeared to be of considerable importance for the recovery rate of the deep-sea nematode assemblages and their ability to recolonize disturbed areas. The rates of recolonization and recovery may vary widely in different deep-sea regions.

Development of Multiscale Biological Image Data Analysis: Review of 2006 International Workshop on Multiscale Biological Imaging, Data Mining and Informatics, Santa Barbara, USA (BII06)

PubMed Central

Auer, Manfred; Peng, Hanchuan; Singh, Ambuj

2007-01-01

The 2006 International Workshop on Multiscale Biological Imaging, Data Mining and Informatics was held at Santa Barbara, on Sept 7–8, 2006. Based on the presentations at the workshop, we selected and compiled this collection of research articles related to novel algorithms and enabling techniques for bio- and biomedical image analysis, mining, visualization, and biology applications. PMID:17634090

Organizational-Legal and Technological Aspects of Ensuring Environmental Safety of Mining Enterprises: Perspective Analysis in the Context of the General Enhancement of Environmental Problem

NASA Astrophysics Data System (ADS)

Vorontsova, Elena; Vorontsov, Andrey; Drozdenko, Yuriy

2017-11-01

The article is devoted to the analysis of problems of maintenance of ecological safety of the mining enterprises. The aim of the work was the formulation of proposals, the implementation of which, in the opinion of the authors, is capable of raising the level of environmental safety of the mining industry and ultimately ensuring the environmentally oriented growth of the Russian economy.

Geotechnical approach for occupational safety risk analysis of critical slope in open pit mining as implication for earthquake hazard

NASA Astrophysics Data System (ADS)

Munirwansyah; Irsyam, Masyhur; Munirwan, Reza P.; Yunita, Halida; Zulfan Usrina, M.

2018-05-01

Occupational safety and health (OSH) is a planned effort to prevent accidents and diseases caused by work. In conducting mining activities often occur work accidents caused by unsafe field conditions. In open mine area, there is often a slump due to unstable slopes, which can disrupt the activities and productivity of mining companies. Based on research on stability of open pit slopes conducted by Febrianti [8], the Meureubo coal mine located in Aceh Barat district, on the slope of mine was indicated unsafe slope conditions, it will be continued research on OSH for landslide which is to understand the stability of the excavation slope and the shape of the slope collapse. Plaxis software was used for this research. After analyzing the slope stability and the effect of landslide on OSH with Job Safety Analysis (JSA) method, to identify the hazard to work safety, risk management analysis will be conducted to classified hazard level and its handling technique. This research aim is to know the level of risk of work accident at the company and its prevention effort. The result of risk analysis research is very high-risk value that is > 350 then the activity must be stopped until the risk can be reduced to reach the risk value limit < 20 which is allowed or accepted.

An analysis of injury claims from low-seam coal mines

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gallagher, S.; Moore, S.; Dempsey, P.G.

2009-07-01

The restricted workspace present in low-seam coal mines forces workers to adopt awkward working postures (kneeling and stooping), which place high physical demands on the knee and lower back. This article provides an analysis of injury claims for eight mining companies operating low-seam coal mines during calendar years 1996-2008. All cost data were normalized using data on the cost of medical care (MPI) as provided by the U.S. Bureau of Labor Statistics. Results of the analysis indicate that the knee was the body part that led in terms of claim cost ($4.2 million), followed by injuries to the lower backmore » ($2.7 million). While the average cost per injury for these body parts was $13,100 and $14,400, respectively (close to the average cost of an injury overall), the high frequency of these injuries resulted in their pre-eminence in terms of cost. Analysis of data from individual mining companies suggest that knee and lower back injuries were a consistent problem across companies, as these injuries were each among the top five most costly part of body for seven out of eight companies studied. Results of this investigation suggest that efforts to reduce the frequency of knee and low back injuries in low-seam mines have the potential to create substantial cost savings.« less

New directions in biomedical text annotation: definitions, guidelines and corpus construction

PubMed Central

Wilbur, W John; Rzhetsky, Andrey; Shatkay, Hagit

2006-01-01

Background While biomedical text mining is emerging as an important research area, practical results have proven difficult to achieve. We believe that an important first step towards more accurate text-mining lies in the ability to identify and characterize text that satisfies various types of information needs. We report here the results of our inquiry into properties of scientific text that have sufficient generality to transcend the confines of a narrow subject area, while supporting practical mining of text for factual information. Our ultimate goal is to annotate a significant corpus of biomedical text and train machine learning methods to automatically categorize such text along certain dimensions that we have defined. Results We have identified five qualitative dimensions that we believe characterize a broad range of scientific sentences, and are therefore useful for supporting a general approach to text-mining: focus, polarity, certainty, evidence, and directionality. We define these dimensions and describe the guidelines we have developed for annotating text with regard to them. To examine the effectiveness of the guidelines, twelve annotators independently annotated the same set of 101 sentences that were randomly selected from current biomedical periodicals. Analysis of these annotations shows 70–80% inter-annotator agreement, suggesting that our guidelines indeed present a well-defined, executable and reproducible task. Conclusion We present our guidelines defining a text annotation task, along with annotation results from multiple independently produced annotations, demonstrating the feasibility of the task. The annotation of a very large corpus of documents along these guidelines is currently ongoing. These annotations form the basis for the categorization of text along multiple dimensions, to support viable text mining for experimental results, methodology statements, and other forms of information. We are currently developing machine learning methods, to be trained and tested on the annotated corpus, that would allow for the automatic categorization of biomedical text along the general dimensions that we have presented. The guidelines in full detail, along with annotated examples, are publicly available. PMID:16867190

Studies on medicinal herbs for cognitive enhancement based on the text mining of Dongeuibogam and preliminary evaluation of its effects.

PubMed

Pak, Malk Eun; Kim, Yu Ri; Kim, Ha Neui; Ahn, Sung Min; Shin, Hwa Kyoung; Baek, Jin Ung; Choi, Byung Tae

2016-02-17

In literature on Korean medicine, Dongeuibogam (Treasured Mirror of Eastern Medicine), published in 1613, represents the overall results of the traditional medicines of North-East Asia based on prior medicinal literature of this region. We utilized this medicinal literature by text mining to establish a list of candidate herbs for cognitive enhancement in the elderly and then performed an evaluation of their effects. Text mining was performed for selection of candidate herbs. Cell viability was determined in HT22 hippocampal cells and immunohistochemistry and behavioral analysis was performed in a kainic acid (KA) mice model in order to observe alterations of hippocampal cells and cognition. Twenty four herbs for cognitive enhancement in the elderly were selected by text mining of Dongeuibogam. In HT22 cells, pretreatment with 3 candidate herbs resulted in significantly reduced glutamate-induced cell death. Panax ginseng was the most neuroprotective herb against glutamate-induced cell death. In the hippocampus of a KA mice model, pretreatment with 11 candidate herbs resulted in suppression of caspase-3 expression. Treatment with 7 candidate herbs resulted in significantly enhanced expression levels of phosphorylated cAMP response element binding protein. Number of proliferated cells indicated by BrdU labeling was increased by treatment with 10 candidate herbs. Schisandra chinensis was the most effective herb against cell death and proliferation of progenitor cells and Rehmannia glutinosa in neuroprotection in the hippocampus of a KA mice model. In a KA mice model, we confirmed improved spatial and short memory by treatment with the 3 most effective candidate herbs and these recovered functions were involved in a higher number of newly formed neurons from progenitor cells in the hippocampus. These established herbs and their combinations identified by text-mining technique and evaluation for effectiveness may have value in further experimental and clinical applications for cognitive enhancement in the elderly. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Stratospheric Sampling and In Situ Atmospheric Chemical Element Analysis During Meteor Showers: A Resource Study

NASA Technical Reports Server (NTRS)

Noever, David A.

2000-01-01

Resources studies for asteroidal mining evaluation have depended historically on remote sensing analysis for chemical elements. During the November 1998 Leonids meteor shower, a stratospheric balloon and various low-density capture media were used to sample fragments from Comet Tempel-Tuttle debris during a peak Earth crossing. The analysis not only demonstrates how potential sampling strategies may improve the projections for metals or rare elements in astromining, but also benchmarks materials during low temperature (-60 F), high dessication environments as seen during atmospheric exposure. The results indicate high aluminum, magnesium and iron content for various sampled particles recovered, but generalization to the sporadic meteors expected from asteroidal sources will require future improvements in larger sampling volumes before a broad-use strategy for chemical analysis can be described. A repeat of the experimental procedure is planned for the November 1999 Leonids' shower, and various improvements for atmospheric sampling will be discussed.

15 CFR 971.202 - Statement of technological experience and capabilities.

Code of Federal Regulations, 2012 CFR

2012-01-01

... GENERAL REGULATIONS OF THE ENVIRONMENTAL DATA SERVICE DEEP SEABED MINING REGULATIONS FOR COMMERCIAL... results to commercial mining. The more test data offered with the application the less analysis will be... step in the mining process, including nodule collection, retrieval, transfer to ship, environmental...

15 CFR 971.202 - Statement of technological experience and capabilities.

Code of Federal Regulations, 2011 CFR

2011-01-01

... GENERAL REGULATIONS OF THE ENVIRONMENTAL DATA SERVICE DEEP SEABED MINING REGULATIONS FOR COMMERCIAL... results to commercial mining. The more test data offered with the application the less analysis will be... step in the mining process, including nodule collection, retrieval, transfer to ship, environmental...

15 CFR 971.202 - Statement of technological experience and capabilities.

Code of Federal Regulations, 2010 CFR

2010-01-01

... GENERAL REGULATIONS OF THE ENVIRONMENTAL DATA SERVICE DEEP SEABED MINING REGULATIONS FOR COMMERCIAL... results to commercial mining. The more test data offered with the application the less analysis will be... step in the mining process, including nodule collection, retrieval, transfer to ship, environmental...

A Framework for Web Usage Mining in Electronic Government

NASA Astrophysics Data System (ADS)

Zhou, Ping; Le, Zhongjian

Web usage mining has been a major component of management strategy to enhance organizational analysis and decision. The literature on Web usage mining that deals with strategies and technologies for effectively employing Web usage mining is quite vast. In recent years, E-government has received much attention from researchers and practitioners. Huge amounts of user access data are produced in Electronic government Web site everyday. The role of these data in the success of government management cannot be overstated because they affect government analysis, prediction, strategies, tactical, operational planning and control. Web usage miming in E-government has an important role to play in setting government objectives, discovering citizen behavior, and determining future courses of actions. Web usage mining in E-government has not received adequate attention from researchers or practitioners. We developed a framework to promote a better understanding of the importance of Web usage mining in E-government. Using the current literature, we developed the framework presented herein, in hopes that it would stimulate more interest in this important area.

Tracking acid mine-drainage in Southeast Arizona using GIS and sediment delivery models

USGS Publications Warehouse

Norman, L.M.; Gray, F.; Guertin, D.P.; Wissler, C.; Bliss, J.D.

2008-01-01

This study investigates the application of models traditionally used to estimate erosion and sediment deposition to assess the potential risk of water quality impairment resulting from metal-bearing materials related to mining and mineralization. An integrated watershed analysis using Geographic Information Systems (GIS) based tools was undertaken to examine erosion and sediment transport characteristics within the watersheds. Estimates of stream deposits of sediment from mine tailings were related to the chemistry of surface water to assess the effectiveness of the methodology to assess the risk of acid mine-drainage being dispersed downstream of abandoned tailings and waste rock piles. A watershed analysis was preformed in the Patagonia Mountains in southeastern Arizona which has seen substantial mining and where recent water quality samples have reported acidic surface waters. This research demonstrates an improvement of the ability to predict streams that are likely to have severely degraded water quality as a result of past mining activities. ?? Springer Science+Business Media B.V. 2007.

A baseline record of trace elements concentration along the beach placer mining areas of Kanyakumari coast, South India.

PubMed

Simon Peter, T; Chandrasekar, N; John Wilson, J S; Selvakumar, S; Krishnakumar, S; Magesh, N S

2017-06-15

Trace element concentration in the beach placer mining areas of Kanyakumari coast, South India was assessed. Sewage and contaminated sediments from mining sites has contaminated the surface sediments. Enrichment factor indicates moderately severe enrichment for Pb, minor enrichment for Mn, Zn, Ni, Fe and no enrichment for Cr and Cu. The Igeo values show higher concentration of Pb ranging in the scale of 3-4, which shows strong contamination due to high anthropogenic activity such as mining and terrestrial influences into the coastal regions. Correlation coefficient shows that most of the elements are associated with each other except Ni and Pb. Factor analysis reveals that Mn, Zn, Fe, Cr, Pb and Cu are having a significant loading and it indicates that these elements are mainly derived from similar origin. The cluster analysis clearly indicated that the mining areas are grouped under cluster 2 and non-mining areas are clustered under group 1. Copyright © 2017 Elsevier Ltd. All rights reserved.

Effects of mining activities on evolution of water chemistry in coal-bearing aquifers in karst region of Midwestern Guizhou, China: evidences from δ13C of dissolved inorganic carbon and δ34S of sulfate.

PubMed

Li, Qingguang; Wu, Pan; Zha, Xuefang; Li, Xuexian; Wu, Linna; Gu, Shangyi

2018-04-24

The generation of acid mine drainage (AMD) may accelerate watershed erosion and promote the migration of heavy metals, then threaten local ecosystems such as aquatic life and even human health. Previous studies have focused primarily on influence of AMD in surface environment. In order to reveal the acidizing processes in karst high-sulfur coalfield in Southwest China, this study, by contrast, focused on the hydrogeochemical evolution process and acidification mechanism of mine water in Zhijin coalfield, western Guizhou Province. The oxidation of pyrite and other sulfides induced strong acidification of mine water according to the water chemical analysis. As a result, a series of geochemical processes such as dissolution of carbonates and silicates, hydrolysis of metal ions, and degassing of CO 2 complicated water chemical evolution. The dissolution of silicates controlled the chemical composition of mine water, but more carbonates might be dissolved during the acidification of mine water. The sources of sulfate are quite different in water samples collected from the two selected mine. According to sulfur isotope analysis, the dissolution of gypsum is the primary source of sulfate in samples from Hongfa mine, whereas sulfide oxidation contributed a large amount of sulfate to the mine water in Fenghuangshan mine. The dissolution of carbonates should be an important source of DIC in mine water and CO 2 originating from organic mineralization might also have a certain contribution. This study elucidated the groundwater chemical evolution processes in high-sulfur coal-bearing strata and provided a foundation for further study of carbonates erosion and carbon emission during acidification of mine water.

Pillar size optimization design of isolated island panel gob-side entry driving in deep inclined coal seam—case study of Pingmei No. 6 coal seam

NASA Astrophysics Data System (ADS)

Zhang, Shuai; Wang, Xufeng; Fan, Gangwei; Zhang, Dongsheng; Jianbin, Cui

2018-06-01

There is a perception that deep roadways are difficult to maintain. To reverse this and to improve the recovery rate of coal resources, gob-side entry driving is widely used in coal mines, especially deep-mining coal mines, in China. Determination of the reasonable pillar size through in situ observation and experimentation plays a vital role for roadway maintenance. Based on the geological conditions of Pingmei No.6 coal seam, a theoretical analysis, numerical simulation, and industrial experiments are carried out to calculate the reasonable width of chain pillars, analyze the lateral support stress distribution law near the gob side, investigate the relationship between the coal pillar stress distribution, roadway surrounding rock stress distribution, roadway surrounding rock deformation and the coal pillar width. The results indicate that 5 m wide coal pillars can ensure that the chain pillars are at a lower stress level and the deformation of roadway surrounding rock is in a more reasonable range. Industrial experiments show that when the chain pillar width is 5 m, the deformation of roadway surrounding rock can meet the requirements of working face safe production. The numerical results agreed well with field measurement and observations, and the industrial experiments results further validated the results of the numerical simulation.

Parametric analysis of the biomechanical response of head subjected to the primary blast loading--a data mining approach.

PubMed

Zhu, Feng; Kalra, Anil; Saif, Tal; Yang, Zaihan; Yang, King H; King, Albert I

2016-01-01

Traumatic brain injury due to primary blast loading has become a signature injury in recent military conflicts and terrorist activities. Extensive experimental and computational investigations have been conducted to study the interrelationships between intracranial pressure response and intrinsic or 'input' parameters such as the head geometry and loading conditions. However, these relationships are very complicated and are usually implicit and 'hidden' in a large amount of simulation/test data. In this study, a data mining method is proposed to explore such underlying information from the numerical simulation results. The heads of different species are described as a highly simplified two-part (skull and brain) finite element model with varying geometric parameters. The parameters considered include peak incident pressure, skull thickness, brain radius and snout length. Their interrelationship and coupling effect are discovered by developing a decision tree based on the large simulation data-set. The results show that the proposed data-driven method is superior to the conventional linear regression method and is comparable to the nonlinear regression method. Considering its capability of exploring implicit information and the relatively simple relationships between response and input variables, the data mining method is considered to be a good tool for an in-depth understanding of the mechanisms of blast-induced brain injury. As a general method, this approach can also be applied to other nonlinear complex biomechanical systems.

Trend Motif: A Graph Mining Approach for Analysis of Dynamic Complex Networks

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jin, R; McCallen, S; Almaas, E

2007-05-28

Complex networks have been used successfully in scientific disciplines ranging from sociology to microbiology to describe systems of interacting units. Until recently, studies of complex networks have mainly focused on their network topology. However, in many real world applications, the edges and vertices have associated attributes that are frequently represented as vertex or edge weights. Furthermore, these weights are often not static, instead changing with time and forming a time series. Hence, to fully understand the dynamics of the complex network, we have to consider both network topology and related time series data. In this work, we propose a motifmore » mining approach to identify trend motifs for such purposes. Simply stated, a trend motif describes a recurring subgraph where each of its vertices or edges displays similar dynamics over a userdefined period. Given this, each trend motif occurrence can help reveal significant events in a complex system; frequent trend motifs may aid in uncovering dynamic rules of change for the system, and the distribution of trend motifs may characterize the global dynamics of the system. Here, we have developed efficient mining algorithms to extract trend motifs. Our experimental validation using three disparate empirical datasets, ranging from the stock market, world trade, to a protein interaction network, has demonstrated the efficiency and effectiveness of our approach.« less

Survey of Analysis of Crime Detection Techniques Using Data Mining and Machine Learning

NASA Astrophysics Data System (ADS)

Prabakaran, S.; Mitra, Shilpa

2018-04-01

Data mining is the field containing procedures for finding designs or patterns in a huge dataset, it includes strategies at the convergence of machine learning and database framework. It can be applied to various fields like future healthcare, market basket analysis, education, manufacturing engineering, crime investigation etc. Among these, crime investigation is an interesting application to process crime characteristics to help the society for a better living. This paper survey various data mining techniques used in this domain. This study may be helpful in designing new strategies for crime prediction and analysis.

A Data Warehouse Architecture for DoD Healthcare Performance Measurements.

DTIC Science & Technology

1999-09-01

design, develop, implement, and apply statistical analysis and data mining tools to a Data Warehouse of healthcare metrics. With the DoD healthcare...framework, this thesis defines a methodology to design, develop, implement, and apply statistical analysis and data mining tools to a Data Warehouse...21 F. INABILITY TO CONDUCT HELATHCARE ANALYSIS

Complementing the Numbers: A Text Mining Analysis of College Course Withdrawals

ERIC Educational Resources Information Center

Michalski, Greg V.

2011-01-01

Excessive college course withdrawals are costly to the student and the institution in terms of time to degree completion, available classroom space, and other resources. Although generally well quantified, detailed analysis of the reasons given by students for course withdrawal is less common. To address this, a text mining analysis was performed…

Multimedia Exploratory Data Analysis for Geospatial Data Mining: The Case for Augmented Seriation.

ERIC Educational Resources Information Center

Gluck, Myke

2001-01-01

Reviews the role of exploratory data analysis (EDA) for spatial data mining and presents a case study addressing environmental risk assessments in New York State to illustrate the feasibility and usability of augmenting seriation for spatial data analysis. Describes augmentation with multimedia tools to understand relationships among spatial,…

Characterization of a mine fire using atmospheric monitoring system sensor data

PubMed Central

Yuan, L.; Thomas, R.A.; Zhou, L.

2017-01-01

Atmospheric monitoring systems (AMS) have been widely used in underground coal mines in the United States for the detection of fire in the belt entry and the monitoring of other ventilation-related parameters such as airflow velocity and methane concentration in specific mine locations. In addition to an AMS being able to detect a mine fire, the AMS data have the potential to provide fire characteristic information such as fire growth — in terms of heat release rate — and exact fire location. Such information is critical in making decisions regarding fire-fighting strategies, underground personnel evacuation and optimal escape routes. In this study, a methodology was developed to calculate the fire heat release rate using AMS sensor data for carbon monoxide concentration, carbon dioxide concentration and airflow velocity based on the theory of heat and species transfer in ventilation airflow. Full-scale mine fire experiments were then conducted in the Pittsburgh Mining Research Division’s Safety Research Coal Mine using an AMS with different fire sources. Sensor data collected from the experiments were used to calculate the heat release rates of the fires using this methodology. The calculated heat release rate was compared with the value determined from the mass loss rate of the combustible material using a digital load cell. The experimental results show that the heat release rate of a mine fire can be calculated using AMS sensor data with reasonable accuracy. PMID:28845058

[The method and application to construct experience recommendation platform of acupuncture ancient books based on data mining technology].

PubMed

Chen, Chuyun; Hong, Jiaming; Zhou, Weilin; Lin, Guohua; Wang, Zhengfei; Zhang, Qufei; Lu, Cuina; Lu, Lihong

2017-07-12

To construct a knowledge platform of acupuncture ancient books based on data mining technology, and to provide retrieval service for users. The Oracle 10 g database was applied and JAVA was selected as development language; based on the standard library and ancient books database established by manual entry, a variety of data mining technologies, including word segmentation, speech tagging, dependency analysis, rule extraction, similarity calculation, ambiguity analysis, supervised classification technology were applied to achieve text automatic extraction of ancient books; in the last, through association mining and decision analysis, the comprehensive and intelligent analysis of disease and symptom, meridians, acupoints, rules of acupuncture and moxibustion in acupuncture ancient books were realized, and retrieval service was provided for users through structure of browser/server (B/S). The platform realized full-text retrieval, word frequency analysis and association analysis; when diseases or acupoints were searched, the frequencies of meridian, acupoints (diseases) and techniques were presented from high to low, meanwhile the support degree and confidence coefficient between disease and acupoints (special acupoint), acupoints and acupoints in prescription, disease or acupoints and technique were presented. The experience platform of acupuncture ancient books based on data mining technology could be used as a reference for selection of disease, meridian and acupoint in clinical treatment and education of acupuncture and moxibustion.

Industrial Internet of Things: (IIoT) applications in underground coal mines.

PubMed

Zhou, C; Damiano, N; Whisner, B; Reyes, M

2017-12-01

The Industrial Internet of Things (IIoT), a concept that combines sensor networks and control systems, has been employed in several industries to improve productivity and safety. U.S. National Institute for Occupational Safety and Health (NIOSH) researchers are investigating IIoT applications to identify the challenges of and potential solutions for transferring IIoT from other industries to the mining industry. Specifically, NIOSH has reviewed existing sensors and communications network systems used in U.S. underground coal mines to determine whether they are capable of supporting IIoT systems. The results show that about 40 percent of the installed post-accident communication systems as of 2014 require minimal or no modification to support IIoT applications. NIOSH researchers also developed an IIoT monitoring and control prototype system using low-cost microcontroller Wi-Fi boards to detect a door opening on a refuge alternative, activate fans located inside the Pittsburgh Experimental Mine and actuate an alarm beacon on the surface. The results of this feasibility study can be used to explore IIoT applications in underground coal mines based on existing communication and tracking infrastructure.

Clustering and Network Analysis of Reverse Phase Protein Array Data.

PubMed

Byron, Adam

2017-01-01

Molecular profiling of proteins and phosphoproteins using a reverse phase protein array (RPPA) platform, with a panel of target-specific antibodies, enables the parallel, quantitative proteomic analysis of many biological samples in a microarray format. Hence, RPPA analysis can generate a high volume of multidimensional data that must be effectively interrogated and interpreted. A range of computational techniques for data mining can be applied to detect and explore data structure and to form functional predictions from large datasets. Here, two approaches for the computational analysis of RPPA data are detailed: the identification of similar patterns of protein expression by hierarchical cluster analysis and the modeling of protein interactions and signaling relationships by network analysis. The protocols use freely available, cross-platform software, are easy to implement, and do not require any programming expertise. Serving as data-driven starting points for further in-depth analysis, validation, and biological experimentation, these and related bioinformatic approaches can accelerate the functional interpretation of RPPA data.

15 CFR 971.204 - Environmental and use conflict analysis.

Code of Federal Regulations, 2013 CFR

2013-01-01

.... If the permit area lies within the area of NOAA's Deep Ocean Mining Environmental Study (DOMES), the... REGULATIONS OF THE ENVIRONMENTAL DATA SERVICE DEEP SEABED MINING REGULATIONS FOR COMMERCIAL RECOVERY PERMITS... Administrator to prepare an environmental impact statement (EIS) on the proposed mining activities, and to...

15 CFR 971.204 - Environmental and use conflict analysis.

Code of Federal Regulations, 2012 CFR

2012-01-01

.... If the permit area lies within the area of NOAA's Deep Ocean Mining Environmental Study (DOMES), the... REGULATIONS OF THE ENVIRONMENTAL DATA SERVICE DEEP SEABED MINING REGULATIONS FOR COMMERCIAL RECOVERY PERMITS... Administrator to prepare an environmental impact statement (EIS) on the proposed mining activities, and to...

15 CFR 971.204 - Environmental and use conflict analysis.

Code of Federal Regulations, 2011 CFR

2011-01-01

.... If the permit area lies within the area of NOAA's Deep Ocean Mining Environmental Study (DOMES), the... REGULATIONS OF THE ENVIRONMENTAL DATA SERVICE DEEP SEABED MINING REGULATIONS FOR COMMERCIAL RECOVERY PERMITS... Administrator to prepare an environmental impact statement (EIS) on the proposed mining activities, and to...

15 CFR 971.204 - Environmental and use conflict analysis.

Code of Federal Regulations, 2014 CFR

2014-01-01

.... If the permit area lies within the area of NOAA's Deep Ocean Mining Environmental Study (DOMES), the... REGULATIONS OF THE ENVIRONMENTAL DATA SERVICE DEEP SEABED MINING REGULATIONS FOR COMMERCIAL RECOVERY PERMITS... Administrator to prepare an environmental impact statement (EIS) on the proposed mining activities, and to...

An AK-LDMeans algorithm based on image clustering

NASA Astrophysics Data System (ADS)

Chen, Huimin; Li, Xingwei; Zhang, Yongbin; Chen, Nan

2018-03-01

Clustering is an effective analytical technique for handling unmarked data for value mining. Its ultimate goal is to mark unclassified data quickly and correctly. We use the roadmap for the current image processing as the experimental background. In this paper, we propose an AK-LDMeans algorithm to automatically lock the K value by designing the Kcost fold line, and then use the long-distance high-density method to select the clustering centers to further replace the traditional initial clustering center selection method, which further improves the efficiency and accuracy of the traditional K-Means Algorithm. And the experimental results are compared with the current clustering algorithm and the results are obtained. The algorithm can provide effective reference value in the fields of image processing, machine vision and data mining.

Application of EREP imagery to fracture-related mine safety hazards and environmental problems in mining. [Indiana

NASA Technical Reports Server (NTRS)

Wier, C. E.; Wobber, F. J.; Amato, R. V.; Russell, O. R. (Principal Investigator)

1974-01-01

The author has identified the following significant results. All Skylab 2 imagery received to date has been analyzed manually and data related to fracture analysis and mined land inventories has been summarized on map-overlays. A comparison of the relative utility of the Skylab image products for fracture detection, soil tone/vegetation contrast mapping, and mined land mapping has been completed. Numerous fracture traces were detected on both color and black and white transparencies. Unique fracture trace data which will contribute to the investigator's mining hazards analysis were noted on the EREP imagery; these data could not be detected on ERTS-1 imagery or high altitude aircraft color infrared photography. Stream segments controlled by fractures or joint systems could be identified in more detail than with ERTS-1 imagery of comparable scale. ERTS-1 mine hazards products will be modified to demonstrate the value of this additional data. Skylab images were used successfully to update a mined land map of Indiana made in 1972. Changes in mined area as small as two acres can be identified. As the Energy Crisis increases the demand for coal, such demonstrations of the application of Skylab data to coal resources will take on new importance.

Characteristics and mechanisms of cardiopulmonary injury caused by mine blasts in shoals: a randomized controlled study in a rabbit model.

PubMed

Han, Gengfen; Wang, Ziming; Wang, Jianmin; Yang, Weixiao; Chen, Jing; Kang, Jianyi; Zhang, Sen; Wang, Aimin; Lai, Xinan

2013-01-01

Because the characteristics of blast waves in water are different from those in air and because kinetic energy is liberated by a pressure wave at the water-air interface, thoracic injuries from mine blasts in shoals may be serious. The aim of the present study was to investigate the characteristics and mechanisms of cardiopulmonary injury caused by mine blasts in shoals. To study the characteristics of cardiopulmonary injury, 56 animals were divided randomly into three experimental groups (12 animals in the sham group, 22 animals in the land group and 22 animals in the shoal group). To examine the biomechanics of injury, 20 animals were divided randomly into the land group and the shoal group. In the experimental model, the water surface was at the level of the rabbit's xiphoid process, and paper electric detonators (600 mg RDX) were used to simulate mines. Electrocardiography and echocardiography were conducted, and arterial blood gases, serum levels of cardiac troponin I and creatine kinase-MB and other physiologic parameters were measured over a 12-hour period after detonation. Pressures in the thorax and abdomen and the acceleration of the thorax were measured. The results indicate that severe cardiopulmonary injury and dysfunction occur following exposure to mine blasts in shoals. Therefore, the mechanisms of cardiopulmonary injury may result from shear waves that produce strain at the water-air interface. Another mechanism of injury includes the propagation of the shock wave from the planta to the thorax, which causes a much higher peak overpressure in the abdomen than in the thorax; as a result, the abdominal organs and diaphragm are thrust into the thorax, damaging the lungs and heart.

Hydrogeochemical effects of a bulkhead in the Dinero mine tunnel, Sugar Loaf mining district, near Leadville, Colorado

USGS Publications Warehouse

Walton-Day, Katherine; Mills, Taylor J.

2015-01-01

The Dinero mine drainage tunnel is an abandoned, draining mine adit near Leadville, Colorado, that has an adverse effect on downstream water quality and aquatic life. In 2009, a bulkhead was constructed (creating a mine pool and increasing water-table elevations behind the tunnel) to limit drainage from the tunnel and improve downstream water quality. The goal of this study was to document changes to hydrology and water quality resulting from bulkhead emplacement, and to understand post-bulkhead changes in source water and geochemical processes that control mine-tunnel discharge and water quality. Comparison of pre-and post-bulkhead hydrology and water quality indicated that tunnel discharge and zinc and manganese loads decreased by up to 97 percent at the portal of Dinero tunnel and at two downstream sites (LF-537 and LF-580). However, some water-quality problems persisted at LF-537 and LF-580 during high-flow events and years, indicating the effects of the remaining mine waste in the area. In contrast, post-bulkhead water quality degraded at three upstream stream sites and a draining mine tunnel (Nelson tunnel). Water-quality degradation in the streams likely occurred from increased contributions of mine-pool groundwater to the streams. In contrast, water-quality degradation in the Nelson tunnel was likely from flow of mine-pool water along a vein that connects the Nelson tunnel to mine workings behind the Dinero tunnel bulkhead. Principal components analysis, mixing analysis, and inverse geochemical modeling using PHREEQC indicated that mixing and geochemical reactions (carbonate dissolution during acid weathering, precipitation of goethite and birnessite, and sorption of zinc) between three end-member water types generally explain the pre-and post-bulkhead water composition at the Dinero and Nelson tunnels. The three end members were (1) a relatively dilute groundwater having low sulfate and trace element concentrations; (2) mine pool water, and (3) water that flowed from a structure in front of the bulkhead after bulkhead emplacement. Both (2) and (3) had high sulfate and trace element concentrations. These results indicate how analysis of monitoring information can be used to understand hydrogeochemical changes resulting from bulkhead emplacement. This understanding, in turn, can help inform future decisions on the disposition of the remaining mine waste and water-quality problems in the area.

Study on Reuse Strategy of Abandoned Industrial Square - in the case of Jingxi Wang Ping Coal Mine

NASA Astrophysics Data System (ADS)

Li, Xiaodan; Chen, Zhiting; Jia, Lijun; Wu, Wei; Zhang, Hailiang; Ma, Tianyi; Wang, Tao

2018-06-01

Wangping Coal Mine, whose industrial heritage is of great value, was one of the eight coal mines in Beijing. A large number of field surveys and analysis of the abandoned industrial facilities of Wangping Coal Mine were carried out in this paper. From the perspective of protecting industrial heritage culture and sustainable development, this paper studies the ideas and strategies for reusing the abandoned facilities of the Wangping Coal Mine. In order to protect its industrial heritage as much as possible, it is suggested to reuse the industrial square of Wangping Coal Mine as a community park.

Quantifying Associations between Environmental Stressors and Demographic Factors

EPA Science Inventory

Association rule mining (ARM) [1-3], also known as frequent item set mining [4] or market basket analysis [1], has been widely applied in many different areas, such as business product portfolio planning [5], intrusion detection infrastructure design [6], gene expression analysis...

Text mining and its potential applications in systems biology.

PubMed

Ananiadou, Sophia; Kell, Douglas B; Tsujii, Jun-ichi

2006-12-01

With biomedical literature increasing at a rate of several thousand papers per week, it is impossible to keep abreast of all developments; therefore, automated means to manage the information overload are required. Text mining techniques, which involve the processes of information retrieval, information extraction and data mining, provide a means of solving this. By adding meaning to text, these techniques produce a more structured analysis of textual knowledge than simple word searches, and can provide powerful tools for the production and analysis of systems biology models.

Clustering and Dimensionality Reduction to Discover Interesting Patterns in Binary Data

NASA Astrophysics Data System (ADS)

Palumbo, Francesco; D'Enza, Alfonso Iodice

The attention towards binary data coding increased consistently in the last decade due to several reasons. The analysis of binary data characterizes several fields of application, such as market basket analysis, DNA microarray data, image mining, text mining and web-clickstream mining. The paper illustrates two different approaches exploiting a profitable combination of clustering and dimensionality reduction for the identification of non-trivial association structures in binary data. An application in the Association Rules framework supports the theory with the empirical evidence.

Spatial and Temporal Analysis of the Microbial Community in the Tailings of a Pb-Zn Mine Generating Acidic Drainage ▿ †

PubMed Central

Huang, Li-Nan; Zhou, Wen-Hua; Hallberg, Kevin B.; Wan, Cai-Yun; Li, Jie; Shu, Wen-Sheng

2011-01-01

Analysis of spatial and temporal variations in the microbial community in the abandoned tailings impoundment of a Pb-Zn mine revealed distinct microbial populations associated with the different oxidation stages of the tailings. Although Acidithiobacillus ferrooxidans and Leptospirillum spp. were consistently present in the acidic tailings, acidophilic archaea, mostly Ferroplasma acidiphilum, were predominant in the oxidized zones and the oxidation front, indicating their importance to generation of acid mine drainage. PMID:21705549

Source Analysis of the Crandall Canyon, Utah, Mine Collapse

DOE PAGES

Dreger, D. S.; Ford, S. R.; Walter, W. R.

2008-07-11

Analysis of seismograms from a magnitude 3.9 seismic event on August 6, 2007 in central Utah reveals an anomalous radiation pattern that is contrary to that expected for a tectonic earthquake, and which is dominated by an implosive component. The results show the seismic event is best modeled as a shallow underground collapse. Interestingly, large transverse surface waves require a smaller additional non-collapse source component that represents either faulting in the rocks above the mine workings or deformation of the medium surrounding the mine.

Finite Element Analysis of M15 and M19 Mines Under Wheeled Vehicle Load

DTIC Science & Technology

2008-03-01

the plate statically. An implicit finite element option in a code called LSDYNA was used to model the pressure generated in the explosive by the...figure 4 for the M19 mines. Maximum pressure in the explosive for each mine calculated by LSDYNA code shown for a variety of plate sizes and weights...Director U.S. Army TRADOC Analysis Center-WSMR ATTN: ATRC-WSS-R White Sands Missile Range, NM 88002 Chemical Propulsion Information Agency ATTN

The Potential of Text Mining in Data Integration and Network Biology for Plant Research: A Case Study on Arabidopsis[C][W

PubMed Central

Van Landeghem, Sofie; De Bodt, Stefanie; Drebert, Zuzanna J.; Inzé, Dirk; Van de Peer, Yves

2013-01-01

Despite the availability of various data repositories for plant research, a wealth of information currently remains hidden within the biomolecular literature. Text mining provides the necessary means to retrieve these data through automated processing of texts. However, only recently has advanced text mining methodology been implemented with sufficient computational power to process texts at a large scale. In this study, we assess the potential of large-scale text mining for plant biology research in general and for network biology in particular using a state-of-the-art text mining system applied to all PubMed abstracts and PubMed Central full texts. We present extensive evaluation of the textual data for Arabidopsis thaliana, assessing the overall accuracy of this new resource for usage in plant network analyses. Furthermore, we combine text mining information with both protein–protein and regulatory interactions from experimental databases. Clusters of tightly connected genes are delineated from the resulting network, illustrating how such an integrative approach is essential to grasp the current knowledge available for Arabidopsis and to uncover gene information through guilt by association. All large-scale data sets, as well as the manually curated textual data, are made publicly available, hereby stimulating the application of text mining data in future plant biology studies. PMID:23532071

Detection of interaction articles and experimental methods in biomedical literature.

PubMed

Schneider, Gerold; Clematide, Simon; Rinaldi, Fabio

2011-10-03

This article describes the approaches taken by the OntoGene group at the University of Zurich in dealing with two tasks of the BioCreative III competition: classification of articles which contain curatable protein-protein interactions (PPI-ACT) and extraction of experimental methods (PPI-IMT). Two main achievements are described in this paper: (a) a system for document classification which crucially relies on the results of an advanced pipeline of natural language processing tools; (b) a system which is capable of detecting all experimental methods mentioned in scientific literature, and listing them with a competitive ranking (AUC iP/R > 0.5). The results of the BioCreative III shared evaluation clearly demonstrate that significant progress has been achieved in the domain of biomedical text mining in the past few years. Our own contribution, together with the results of other participants, provides evidence that natural language processing techniques have become by now an integral part of advanced text mining approaches.

Application of Quality Management Tools for Evaluating the Failure Frequency of Cutter-Loader and Plough Mining Systems

NASA Astrophysics Data System (ADS)

Biały, Witold

2017-06-01

Failure frequency in the mining process, with a focus on the mining machine, has been presented and illustrated by the example of two coal-mines. Two mining systems have been subjected to analysis: a cutter-loader and a plough system. In order to reduce costs generated by failures, maintenance teams should regularly make sure that the machines are used and operated in a rational and effective way. Such activities will allow downtimes to be reduced, and, in consequence, will increase the effectiveness of a mining plant. The evaluation of mining machines' failure frequency contained in this study has been based on one of the traditional quality management tools - the Pareto chart.

The systematic assessment of traditional evidence from the premodern Chinese medical literature: a text-mining approach.

PubMed

May, Brian H; Zhang, Anthony; Lu, Yubo; Lu, Chuanjian; Xue, Charlie C L

2014-12-01

This project aimed to develop an approach to evaluating information contained in the premodern Traditional Chinese Medicine (TCM) literature that was (1) comprehensive, systematic, and replicable and (2) able to produce quantifiable output that could be used to answer specific research questions in order to identify natural products for clinical and experimental research. The project involved two stages. In stage 1, 14 TCM collections and compendia were evaluated for suitability as sources for searching; 8 of these were compared in detail. The results were published in the Journal of Alternative and Complementary Medicine. Stage 2 developed a text-mining approach for two of these sources. The text-mining approach was developed for Zhong Hua Yi Dian; Encyclopaedia of Traditional Chinese Medicine, 4th edition) and Zhong Yi Fang Ji Da Ci Dian; Great Compendium of Chinese Medical Formulae). This approach developed procedures for search term selection; methods for screening, classifying, and scoring data; procedures for systematic searching and data extraction; data checking procedures; and approaches for analyzing results. Examples are provided for studies of memory impairment and diabetic nephropathy, and issues relating to data interpretation are discussed. This approach to the analysis of large collections of the premodern TCM literature uses widely available sources and provides a text-mining approach that is systematic, replicable, and adaptable to the requirements of the particular project. Researchers can use these methods to explore changes in the names and conceptions of a disease over time, to identify which therapeutic methods have been more or less frequently used in different eras for particular disorders, and to assist in the selection of natural products for research efforts.

Neopterin: A candidate biomarker for the early assessment of toxicity of aluminum among bauxite dust exposed mine workers

PubMed Central

Pingle, Shubhangi K.; Thakkar, Lucky R.; Jawade, Aruna A.; Tumane, Rajani G.; Jain, Ruchika K.; Soni, Pravin N.

2015-01-01

Introduction: Bauxite ore is a major source of aluminum (Al) which contains approximately 35–60% Al by weight. Occupational and environmental bauxite dust exposure may cause toxicity by interaction with human biological systems resulting in oxidative stress (OS) and cell death. A neopterin derivative as an antioxidant is able to modulate cytotoxicity by the induction of OS. Materials and Methods: A total of 273 subjects were selected for blood collection from three different major Al producing bauxite mines and were categorized into three groups as experimental (Exp) (n = 150), experimental controls (ExC) (n = 73) and control (Con) (n = 50). Whole blood and serum samples were used for measurement of Al, neopterin, urea and creatinine values. Statistical analysis was performed using R-2.15.1 programming language. Results and Discussion: The result showed that age, body mass index and the behavioral habits, that is, smoking, tobacco and alcohol consumption have possible effects on neopterin level. Serum neopterin levels were found to be significantly higher (P <0.0001) in the experimental group as compared to other groups. Significantly positive correlation (P < 0.0001) was observed between neopterin and creatinine. It was also observed that neopterin level increases as the duration of exposure increases. Conclusion: On the basis of findings it was concluded that exposure to bauxite dust (even at low levels of Al) changes biochemical profile leading to high levels of serum neopterin. Levels of serum neopterin in workers exposed to bauxite dust were probably examined for the 1st time in India. The outcome of this study suggested that serum neopterin may be used as potential biomarker for early detection of health risks associated with bauxite dust exposed population. PMID:26500413

Field test of electromagnetic geophysical techniques for locating simulated in situ mining leach solution. Report of investigations/1994

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tweeton, D.R.; Hanson, J.C.; Friedel, M.J.

1994-01-01

The U.S. Bureau of Mines, the University of Arizona, Sandia National Laboratory, and Zonge Engineering and Research, Inc., conducted cooperative field tests of six electromagnetic geophysical methods to compare their effectiveness in locating a brine solution simulating in situ leach solution or a high-conductivity plume of contamination. The brine was approximately 160 meters below the surface. The test site was the University's San Xavier experimental mine near Tucson, Arizona. Geophysical surveys using surface and surface-borehole time-domain electromagnetics (TEM), surface controlled source audio-frequency magnetotellurics (CSAMT), surface-borehole frequency-domain electromagnetics (FEM), crosshole FEM and surface magnetic field ellipticity were conducted before and duringmore » brine injection.« less

Randomization Based Privacy Preserving Categorical Data Analysis

ERIC Educational Resources Information Center

Guo, Ling

2010-01-01

The success of data mining relies on the availability of high quality data. To ensure quality data mining, effective information sharing between organizations becomes a vital requirement in today's society. Since data mining often involves sensitive information of individuals, the public has expressed a deep concern about their privacy.…

Mining influence on underground water resources in arid and semiarid regions

NASA Astrophysics Data System (ADS)

Luo, A. K.; Hou, Y.; Hu, X. Y.

2018-02-01

Coordinated mining of coal and water resources in arid and semiarid regions has traditionally become a focus issue. The research takes Energy and Chemical Base in Northern Shaanxi as an example, and conducts statistical analysis on coal yield and drainage volume from several large-scale mines in the mining area. Meanwhile, research determines average water volume per ton coal, and calculates four typical years’ drainage volume in different mining intensity. Then during mining drainage, with the combination of precipitation observation data in recent two decades and water level data from observation well, the calculation of groundwater table, precipitation infiltration recharge, and evaporation capacity are performed. Moreover, the research analyzes the transforming relationship between surface water, mine water, and groundwater. The result shows that the main reason for reduction of water resources quantity and transforming relationship between surface water, groundwater, and mine water is massive mine drainage, which is caused by large-scale coal mining in the research area.

Analysis of Occupational Accidents in Underground and Surface Mining in Spain Using Data-Mining Techniques.

PubMed

Sanmiquel, Lluís; Bascompta, Marc; Rossell, Josep M; Anticoi, Hernán Francisco; Guash, Eduard

2018-03-07

An analysis of occupational accidents in the mining sector was conducted using the data from the Spanish Ministry of Employment and Social Safety between 2005 and 2015, and data-mining techniques were applied. Data was processed with the software Weka. Two scenarios were chosen from the accidents database: surface and underground mining. The most important variables involved in occupational accidents and their association rules were determined. These rules are composed of several predictor variables that cause accidents, defining its characteristics and context. This study exposes the 20 most important association rules in the sector-either surface or underground mining-based on the statistical confidence levels of each rule as obtained by Weka. The outcomes display the most typical immediate causes, along with the percentage of accidents with a basis in each association rule. The most important immediate cause is body movement with physical effort or overexertion, and the type of accident is physical effort or overexertion. On the other hand, the second most important immediate cause and type of accident are different between the two scenarios. Data-mining techniques were chosen as a useful tool to find out the root cause of the accidents.

Application of ERTS-A imagery to fracture related mine safety hazards in the coal mining industry

NASA Technical Reports Server (NTRS)

Wier, C. E.; Wobber, F. J. (Principal Investigator)

1973-01-01

The author has identified the following significant results. The most important result to date is the demonstration of the special value of repetitive ERTS-1 multiband coverage for detecting previously unknown fracture lineaments despite the presence of a deep glacial overburden. The Illinois Basin is largely covered with glacial drift and few rock outcrops are present. A contribution to the geological understanding of Illinois and Indiana has been made. Analysis of ERTS-1 imagery has provided useful information to the State of Indiana concerning the surface mined lands. The contrast between healthy vegetation and bare ground as imaged by Band 7 is sharp and substantial detail can be obtained concerning the extent of disturbed lands, associated water bodies, large haul roads, and extent of mined lands revegetation. Preliminary results of analysis suggest a reasonable correlation between image-detected fractures and mine roof fall accidents for a few areas investigated. ERTS-1 applications to surface mining operations appear probable, but further investigations are required. The likelihood of applying ERTS-1 derived fracture data to improve coal mine safety in the entire Illinois Basin is suggested from studies conducted in Indiana.

Analysis of conditions and the concept of multidirectional revitalization of the dolomite quarry in Siewierz

NASA Astrophysics Data System (ADS)

Pawełczyk, Katarzyna

2018-01-01

The development of mining of rock raw materials in Poland has significantly contributed to economic growth and the quality of life of local communities. However, mining activity, besides a number of positive effects, also implies broadly understood changes in the environment and the formation of brownfields. Reclamation and redevelopment of post-industrial areas, and especially post-mining areas, is currently a huge environmental and socio-economic challenge. Revitalization of post-mining areas is particularly important for small towns and municipalities, where mining was one of the main pillars of development and prosperity. An example of such a municipality is Siewierz in Silesian Voivodship. In the paper analysis the conditions have been conducted and the concept of revitalization of dolomite quarry Górnicze Zakłady Dolomitowe S.A. has been proposed. The AHP method has been used to analyse and select the optimal method of revitalization. As a result of the analysis, the concept of multidirectional revitalization with socially, economically and environmentally beneficial functions has been created, maximizing the potential of the quarry.

Disaster risk management in prospect mining area Blitar district, East Java, using microtremor analysis and ANP (analytical network processing) approach

DOE Office of Scientific and Technical Information (OSTI.GOV)

Parwatiningtyas, Diyan, E-mail: diane.tyas@gmail.com, E-mail: erlinunindra@gmail.com; Ambarsari, Erlin Windia, E-mail: diane.tyas@gmail.com, E-mail: erlinunindra@gmail.com; Marlina, Dwi, E-mail: diane.tyas@gmail.com, E-mail: erlinunindra@gmail.com

Indonesia has a wealth of natural assets is so large to be managed and utilized, either from its own local government and local communities, especially in the mining sector. However, mining activities can change the state of the surface layer of the earth that have a high impact disaster risk. This could threaten the safety and disrupt human life, environmental damage, loss of property, and the psychological impact, sulking to the rule of law no 24 of 2007. That's why we strive to manage and minimize the risk of mine disasters in the region, how to use the method ofmore » calculation of Amplification Factor (AF) from the analysis based microtremor sulking Kanai and Nakamura, and decision systems were tested by analysis of ANP. Based on the amplification factor and Analytical Network Processing (ANP) obtained, some points showed instability in the surface layer of a mining area include the site of the TP-7, TP-8, TP-9, TP-10, (Birowo2). If in terms of structure, location indicated unstable due to have a sloping surface layer, resulting in the occurrence of landslides and earthquake risk is high. In the meantime, other areas of the mine site can be said to be a stable area.« less

Disaster risk management in prospect mining area Blitar district, East Java, using microtremor analysis and ANP (analytical network processing) approach

NASA Astrophysics Data System (ADS)

Parwatiningtyas, Diyan; Ambarsari, Erlin Windia; Marlina, Dwi; Wiratomo, Yogi

2014-03-01

Indonesia has a wealth of natural assets is so large to be managed and utilized, either from its own local government and local communities, especially in the mining sector. However, mining activities can change the state of the surface layer of the earth that have a high impact disaster risk. This could threaten the safety and disrupt human life, environmental damage, loss of property, and the psychological impact, sulking to the rule of law no 24 of 2007. That's why we strive to manage and minimize the risk of mine disasters in the region, how to use the method of calculation of Amplification Factor (AF) from the analysis based microtremor sulking Kanai and Nakamura, and decision systems were tested by analysis of ANP. Based on the amplification factor and Analytical Network Processing (ANP) obtained, some points showed instability in the surface layer of a mining area include the site of the TP-7, TP-8, TP-9, TP-10, (Birowo2). If in terms of structure, location indicated unstable due to have a sloping surface layer, resulting in the occurrence of landslides and earthquake risk is high. In the meantime, other areas of the mine site can be said to be a stable area.

Visual Analysis as a design and decision-making tool in the development of a quarry

Treesearch

Randall Boyd Fitzgerald

1979-01-01

In order to obtain local and state government approvals, an environmental impact analysis of the mining and reclamation of a proposed hard rock quarry was required. High visibility of the proposed mining area from the adjacent community required a visual impact analysis in the planning and design of the project. The Visual Analysis defined design criteria for the...

Cytogenetic instability in populations with residential proximity to open-pit coal mine in Northern Colombia in relation to PM10 and PM2.5 levels.

PubMed

Espitia-Pérez, Lyda; da Silva, Juliana; Espitia-Pérez, Pedro; Brango, Hugo; Salcedo-Arteaga, Shirley; Hoyos-Giraldo, Luz Stella; de Souza, Claudia T; Dias, Johnny F; Agudelo-Castañeda, Dayana; Valdés Toscano, Ana; Gómez-Pérez, Miguel; Henriques, João A P

2018-02-01

Epidemiological studies indicate that living in proximity to coal mines is correlated with numerous diseases including cancer, and that exposure to PM 10 and PM 2.5 components could be associated with this phenomenon. However, the understanding of the mechanisms by which PM exerts its adverse effects is still incomplete and comes mainly from studies in occupationally exposed populations. The aims of this study were to: (1) evaluate DNA damage in lymphocytes assessing the cytokinesis-block micronucleus cytome assay (CBMN-cyt) parameters; (2) identify aneugenic or clastogenic effects in lymphocytes of exposed populations using CREST immunostaining for micronuclei; (3) evaluate multi-elemental composition of atmospheric particulate matter; and (4) verify relation between the DNA damage and PM 2.5 and PM 10 levels around the mining area. Analysis revealed a significant increase in micronuclei frequency in binucleated (MNBN) and mononucleated (MNMONO) cells of individuals with residential proximity to open-pit coal mines compared to residents from non-mining areas. Correlation analysis demonstrated a highly significant association between PM 2.5 levels, MNBN frequencies and CREST+ micronuclei induction in exposed residents. These results suggest that PM 2.5 fraction generated in coal mining activities may induce whole chromosome loss (aneuploidy) preferentially, although there are also chromosome breaks. Analysis of the chemical composition of PM 2.5 by PIXE demonstrated that Si, S, K and Cr concentrations varied significantly between coal mining and reference areas. Enrichment factor values (EF) showed that S, Cr and Cu were highly enriched in the coal mining areas. Compared to reference area, mining regions had also higher concentrations of extractable organic matter (EOM) related to nonpolar and polar compounds. Our results demonstrate that PM 2.5 fraction represents the most important health risk for residents living near open-pit mines, underscoring the need for incorporation of ambient air standards based on PM 2.5 measures in coal mining areas. Copyright © 2017. Published by Elsevier Inc.

A Proposed Data Fusion Architecture for Micro-Zone Analysis and Data Mining

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kevin McCarthy; Milos Manic

Data Fusion requires the ability to combine or “fuse” date from multiple data sources. Time Series Analysis is a data mining technique used to predict future values from a data set based upon past values. Unlike other data mining techniques, however, Time Series places special emphasis on periodicity and how seasonal and other time-based factors tend to affect trends over time. One of the difficulties encountered in developing generic time series techniques is the wide variability of the data sets available for analysis. This presents challenges all the way from the data gathering stage to results presentation. This paper presentsmore » an architecture designed and used to facilitate the collection of disparate data sets well suited to Time Series analysis as well as other predictive data mining techniques. Results show this architecture provides a flexible, dynamic framework for the capture and storage of a myriad of dissimilar data sets and can serve as a foundation from which to build a complete data fusion architecture.« less

Application of the Deformation Information System for automated analysis and mapping of mining terrain deformations - case study from SW Poland

NASA Astrophysics Data System (ADS)

Blachowski, Jan; Grzempowski, Piotr; Milczarek, Wojciech; Nowacka, Anna

2015-04-01

Monitoring, mapping and modelling of mining induced terrain deformations are important tasks for quantifying and minimising threats that arise from underground extraction of useful minerals and affect surface infrastructure, human safety, the environment and security of the mining operation itself. The number of methods and techniques used for monitoring and analysis of mining terrain deformations is wide and expanding with the progress in geographical information technologies. These include for example: terrestrial geodetic measurements, Global Navigation Satellite Systems, remote sensing, GIS based modelling and spatial statistics, finite element method modelling, geological modelling, empirical modelling using e.g. the Knothe theory, artificial neural networks, fuzzy logic calculations and other. The presentation shows the results of numerical modelling and mapping of mining terrain deformations for two cases of underground mining sites in SW Poland, hard coal one (abandoned) and copper ore (active) using the functionalities of the Deformation Information System (DIS) (Blachowski et al, 2014 @ http://meetingorganizer.copernicus.org/EGU2014/EGU2014-7949.pdf). The functionalities of the spatial data modelling module of DIS have been presented and its applications in modelling, mapping and visualising mining terrain deformations based on processing of measurement data (geodetic and GNSS) for these two cases have been characterised and compared. These include, self-developed and implemented in DIS, automation procedures for calculating mining terrain subsidence with different interpolation techniques, calculation of other mining deformation parameters (i.e. tilt, horizontal displacement, horizontal strain and curvature), as well as mapping mining terrain categories based on classification of the values of these parameters as used in Poland. Acknowledgments. This work has been financed from the National Science Centre Project "Development of a numerical method of mining ground deformation modelling in complex geological and mining conditions" UMO-2012/07/B/ST10/04297 executed at the Faculty of Geoengineering, Mining and Geology of the Wroclaw University of Technology (Poland).

Problems in using p-curve analysis and text-mining to detect rate of p-hacking and evidential value.

PubMed

Bishop, Dorothy V M; Thompson, Paul A

2016-01-01

Background. The p-curve is a plot of the distribution of p-values reported in a set of scientific studies. Comparisons between ranges of p-values have been used to evaluate fields of research in terms of the extent to which studies have genuine evidential value, and the extent to which they suffer from bias in the selection of variables and analyses for publication, p-hacking. Methods. p-hacking can take various forms. Here we used R code to simulate the use of ghost variables, where an experimenter gathers data on several dependent variables but reports only those with statistically significant effects. We also examined a text-mined dataset used by Head et al. (2015) and assessed its suitability for investigating p-hacking. Results. We show that when there is ghost p-hacking, the shape of the p-curve depends on whether dependent variables are intercorrelated. For uncorrelated variables, simulated p-hacked data do not give the "p-hacking bump" just below .05 that is regarded as evidence of p-hacking, though there is a negative skew when simulated variables are inter-correlated. The way p-curves vary according to features of underlying data poses problems when automated text mining is used to detect p-values in heterogeneous sets of published papers. Conclusions. The absence of a bump in the p-curve is not indicative of lack of p-hacking. Furthermore, while studies with evidential value will usually generate a right-skewed p-curve, we cannot treat a right-skewed p-curve as an indicator of the extent of evidential value, unless we have a model specific to the type of p-values entered into the analysis. We conclude that it is not feasible to use the p-curve to estimate the extent of p-hacking and evidential value unless there is considerable control over the type of data entered into the analysis. In particular, p-hacking with ghost variables is likely to be missed.

AHCODA-DB: a data repository with web-based mining tools for the analysis of automated high-content mouse phenomics data.

PubMed

Koopmans, Bastijn; Smit, August B; Verhage, Matthijs; Loos, Maarten

2017-04-04

Systematic, standardized and in-depth phenotyping and data analyses of rodent behaviour empowers gene-function studies, drug testing and therapy design. However, no data repositories are currently available for standardized quality control, data analysis and mining at the resolution of individual mice. Here, we present AHCODA-DB, a public data repository with standardized quality control and exclusion criteria aimed to enhance robustness of data, enabled with web-based mining tools for the analysis of individually and group-wise collected mouse phenotypic data. AHCODA-DB allows monitoring in vivo effects of compounds collected from conventional behavioural tests and from automated home-cage experiments assessing spontaneous behaviour, anxiety and cognition without human interference. AHCODA-DB includes such data from mutant mice (transgenics, knock-out, knock-in), (recombinant) inbred strains, and compound effects in wildtype mice and disease models. AHCODA-DB provides real time statistical analyses with single mouse resolution and versatile suite of data presentation tools. On March 9th, 2017 AHCODA-DB contained 650 k data points on 2419 parameters from 1563 mice. AHCODA-DB provides users with tools to systematically explore mouse behavioural data, both with positive and negative outcome, published and unpublished, across time and experiments with single mouse resolution. The standardized (automated) experimental settings and the large current dataset (1563 mice) in AHCODA-DB provide a unique framework for the interpretation of behavioural data and drug effects. The use of common ontologies allows data export to other databases such as the Mouse Phenome Database. Unbiased presentation of positive and negative data obtained under the highly standardized screening conditions increase cost efficiency of publicly funded mouse screening projects and help to reach consensus conclusions on drug responses and mouse behavioural phenotypes. The website is publicly accessible through https://public.sylics.com and can be viewed in every recent version of all commonly used browsers.

Stability analysis of rockmass using a hydrogeologic model of groundwater flow at an underground limestone mine in Korea

NASA Astrophysics Data System (ADS)

Baek, H.; Kim, D.; Kim, G.; Kim, D.; Cheong, S.

2017-12-01

The safety and environmental issues should be addressed for sustainable mining operations. One of the key factors is the groundwater flow into underground mine workings, which will affect the overall workability and efficiency of the mining operation. Prediction of the groundwater inflow requires a detailed knowledge of the geologic conditions, including the presence of major faults and other geologic structures at the mine site. The hydrologic boundaries and depth of the phreatic surface of the mine area, as well as other relevant properties of the rockmass, are also provided. The stability of underground structures, in terms of the maximum stresses and deformations within the rockmass, can be analyzed using either the total stress or the effective stress approaches. Both the dried and saturated conditions should be considered with appropriate safety factors, as the distribution of the water pressure within the rockmass resulted from the groundwater flow directly affects the stability. In some cases, the rockmass rating systems such as the RMR and Q-systems are also applied. Various numerical codes have been used to construct the hydrogeologic models of mine sites, and the MINEDW by Itasca is one of those groundwater flow model codes developed to simulate groundwater flow related to mining. In this study, with a 3D hydrogeologic model constructed using the MINEDW for an underground limestone mine, the rate of mine water inflow and the porewater pressure were estimated. The stability of mine pillars and adits was analyzed adopting the porewater pressure and effective stress developed in the rockmass. The results were also compared with those from other 2D stability analysis procedures.

Association mining of dependency between time series

NASA Astrophysics Data System (ADS)

Hafez, Alaaeldin

2001-03-01

Time series analysis is considered as a crucial component of strategic control over a broad variety of disciplines in business, science and engineering. Time series data is a sequence of observations collected over intervals of time. Each time series describes a phenomenon as a function of time. Analysis on time series data includes discovering trends (or patterns) in a time series sequence. In the last few years, data mining has emerged and been recognized as a new technology for data analysis. Data Mining is the process of discovering potentially valuable patterns, associations, trends, sequences and dependencies in data. Data mining techniques can discover information that many traditional business analysis and statistical techniques fail to deliver. In this paper, we adapt and innovate data mining techniques to analyze time series data. By using data mining techniques, maximal frequent patterns are discovered and used in predicting future sequences or trends, where trends describe the behavior of a sequence. In order to include different types of time series (e.g. irregular and non- systematic), we consider past frequent patterns of the same time sequences (local patterns) and of other dependent time sequences (global patterns). We use the word 'dependent' instead of the word 'similar' for emphasis on real life time series where two time series sequences could be completely different (in values, shapes, etc.), but they still react to the same conditions in a dependent way. In this paper, we propose the Dependence Mining Technique that could be used in predicting time series sequences. The proposed technique consists of three phases: (a) for all time series sequences, generate their trend sequences, (b) discover maximal frequent trend patterns, generate pattern vectors (to keep information of frequent trend patterns), use trend pattern vectors to predict future time series sequences.

Diverse Power Iteration Embeddings and Its Applications

DOE Office of Scientific and Technical Information (OSTI.GOV)

Huang H.; Yoo S.; Yu, D.

2014-12-14

Abstract—Spectral Embedding is one of the most effective dimension reduction algorithms in data mining. However, its computation complexity has to be mitigated in order to apply it for real-world large scale data analysis. Many researches have been focusing on developing approximate spectral embeddings which are more efficient, but meanwhile far less effective. This paper proposes Diverse Power Iteration Embeddings (DPIE), which not only retains the similar efficiency of power iteration methods but also produces a series of diverse and more effective embedding vectors. We test this novel method by applying it to various data mining applications (e.g. clustering, anomaly detectionmore » and feature selection) and evaluating their performance improvements. The experimental results show our proposed DPIE is more effective than popular spectral approximation methods, and obtains the similar quality of classic spectral embedding derived from eigen-decompositions. Moreover it is extremely fast on big data applications. For example in terms of clustering result, DPIE achieves as good as 95% of classic spectral clustering on the complex datasets but 4000+ times faster in limited memory environment.« less

Influence of gas compressibility on a burning accident in a mining passage

NASA Astrophysics Data System (ADS)

Demir, Sinan; Calavay, Anish Raman; Akkerman, V'yacheslav

2018-03-01

A recent predictive scenario of a methane/air/coal dust fire in a mining passage is extended by incorporating the effect of gas compressibility into the analysis. The compressible and incompressible formulations are compared, qualitatively and quantitatively, in both the two-dimensional planar and cylindrical-axisymmetric geometries, and a detailed parametric study accounting for coal-dust combustion is performed. It is shown that gas compression moderates flame acceleration, and its impact depends on the type of the fuel, its various thermal-chemical parameters as well as on the geometry of the problem. While the effect of gas compression is relatively minor for the lean and rich flames, providing 5-25% reduction in the burning velocity and thereby justifying the incompressible formulation in that case, such a reduction appears significant, up to 70% for near-stoichiometric methane-air combustion, and therefore it should be incorporated into a rigorous formulation. It is demonstrated that the flame tip velocity remains noticeably subsonic in all the cases considered, which is opposite to the prediction of the incompressible formulation, but qualitatively agrees with the experimental predictions from the literature.

Data Mining for 3D Organic Dirac Materials

NASA Astrophysics Data System (ADS)

Geilhufe, R. Matthias; Borysov, Stanislav S.; Bouhon, Adrien; Balatsky, Alexander V.

The study of Dirac materials, i.e. materials where the low-energy fermionic excitations behave as massless Dirac particles has been of ongoing interest for more than two decades. Such massless Dirac fermions are characterized by a linear dispersion relation with respect to the particle momentum. A combined study using group theory and data mining within the Organic Materials Database leads to the discovery of stable Dirac-point nodes and Dirac line-nodes within the electronic band structure in the class of 3-dimensional organic crystals. The nodes are protected by crystalline symmetry. As a result of this study, we present band structure calculations and symmetry analysis for previously synthesized organic materials. In all these materials, the Dirac nodes are well separated within the energy and located near the Fermi surface, which opens up a possibility for their direct experimental observation. The authors acknowledge support by the US Department of Energy, BES E3B7, the swedish Research Council Grant No. 638-2013-9243, the Knut and Alice Wallenberg Foundation, and the European Research Council (FP/2207-2013)/ERC Grant Agreement No. DM-321031.

Biclustering Learning of Trading Rules.

PubMed

Huang, Qinghua; Wang, Ting; Tao, Dacheng; Li, Xuelong

2015-10-01

Technical analysis with numerous indicators and patterns has been regarded as important evidence for making trading decisions in financial markets. However, it is extremely difficult for investors to find useful trading rules based on numerous technical indicators. This paper innovatively proposes the use of biclustering mining to discover effective technical trading patterns that contain a combination of indicators from historical financial data series. This is the first attempt to use biclustering algorithm on trading data. The mined patterns are regarded as trading rules and can be classified as three trading actions (i.e., the buy, the sell, and no-action signals) with respect to the maximum support. A modified K nearest neighborhood ( K -NN) method is applied to classification of trading days in the testing period. The proposed method [called biclustering algorithm and the K nearest neighbor (BIC- K -NN)] was implemented on four historical datasets and the average performance was compared with the conventional buy-and-hold strategy and three previously reported intelligent trading systems. Experimental results demonstrate that the proposed trading system outperforms its counterparts and will be useful for investment in various financial markets.

Contextualising the topographic signature of historic mining, a scaling analysis

NASA Astrophysics Data System (ADS)

Reinhardt, Liam

2017-04-01

Mining is globally one of the most significant means by which humans alter landscapes; we do so through erosion (mining), transport, and deposition of extracted sediments (waste). The iconic Dartmoor mountain landscape of SW England ( 700km2) has experienced over 1000 years of shallow (Cu & Sn) mining that has left a pervasive imprint on the landscape. The availability of high resolution digital elevation models (<=1m) and aerial photographs @12.5 cm resolution) combined with historic records of mining activity and output make this an ideal location to investigate the topographic signature of mining. Conceptually I ask the question: how much (digital elevation model) smoothing is required to remove the human imprint from this landscape ? While we may have entered the Anthropocene other gravity driven process have imparted distinct scale-dependant signatures. How might the human signature differ from these processes and how pervasive is it at the landscape scale? Spatial scaling analysis (curvature & semi-variance) was used to quantify the topographic signature of historic mining and to determine how it differs to a) natural landforms such as bedrock tors; and b) the morphology of biological activity (e.g. peat formation). Other forms of historic activity such as peat cutting and quarrying were also investigated. The existence of 400 years of mine activity archives also makes it possible to distinguish between the imprint of differing forms of mine technology and their spatio-temporal signature. Interestingly the higher technology 19th C mines have left a much smaller topographic legacy than Medieval miners; though the former had a much greater impact in terms of heavy metal contamination.

Analysis of Hospital Processes with Process Mining Techniques.

PubMed

Orellana García, Arturo; Pérez Alfonso, Damián; Larrea Armenteros, Osvaldo Ulises

2015-01-01

Process mining allows for discovery, monitoring, and improving processes identified in information systems from their event logs. In hospital environments, process analysis has been a crucial factor for cost reduction, control and proper use of resources, better patient care, and achieving service excellence. This paper presents a new component for event logs generation in the Hospital Information System or HIS, developed at University of Informatics Sciences. The event logs obtained are used for analysis of hospital processes with process mining techniques. The proposed solution intends to achieve the generation of event logs in the system with high quality. The performed analyses allowed for redefining functions in the system and proposed proper flow of information. The study exposed the need to incorporate process mining techniques in hospital systems to analyze the processes execution. Moreover, we illustrate its application for making clinical and administrative decisions for the management of hospital activities.

Analysis of Survey Results in Terms of Selection of Characteristics of the Mining Rescuer to the Ranks of Rapid Response

NASA Astrophysics Data System (ADS)

Grodzicka, Aneta; Szlązak, Jan

2016-06-01

The authors of the current study undertook the subject of the analysis features of the mining rescuer as a member of the ranks of the rescue, with particular emphasis on the following parameters: heart rate, body weight, height, BMI, age and seniority in the mining and rescue. This publication concerns the analysis of the test results of these characteristics rescuer as a potential member of the ranks of the rescue, taking into account its risk appetite, stress resistance, attitude towards life, the role of the team, teamwork, attitude to work, motivation to work and physical fitness.

Monitoring Metal Pollution Levels in Mine Wastes around a Coal Mine Site Using GIS

NASA Astrophysics Data System (ADS)

Sanliyuksel Yucel, D.; Yucel, M. A.; Ileri, B.

2017-11-01

In this case study, metal pollution levels in mine wastes at a coal mine site in Etili coal mine (Can coal basin, NW Turkey) are evaluated using geographical information system (GIS) tools. Etili coal mine was operated since the 1980s as an open pit. Acid mine drainage is the main environmental problem around the coal mine. The main environmental contamination source is mine wastes stored around the mine site. Mine wastes were dumped over an extensive area along the riverbeds, and are now abandoned. Mine waste samples were homogenously taken at 10 locations within the sampling area of 102.33 ha. The paste pH and electrical conductivity values of mine wastes ranged from 2.87 to 4.17 and 432 to 2430 μS/cm, respectively. Maximum Al, Fe, Mn, Pb, Zn and Ni concentrations of wastes were measured as 109300, 70600, 309.86, 115.2, 38 and 5.3 mg/kg, respectively. The Al, Fe and Pb concentrations of mine wastes are higher than world surface rock average values. The geochemical analysis results from the study area were presented in the form of maps. The GIS based environmental database will serve as a reference study for our future work.

Texas lignite mining: Groundwater and slope stability control in the nineties and beyond

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lawrence J.

As lignite mining in Texas approaches and exceeds depths of 200 feet below ground level, rising costs demand that innovative mining approaches be used in order to maintain the economic viability of lignite mining. Groundwater and slope stability problems multiply at these depths, resulting in increasing focus on how to control these costs. Dewatering costs are consistently rising for the lignite industry, as deeper mining encounters more and larger saturated sand bodies. These sands require dewatering in order to improve slope stability. Planning and analysis become more important as the number of wells grows beyond what can be managed withmore » a simple {open_quotes}cookie-cutter{close_quotes} approach. Slope stability plays an increasing role in mining concerns as deeper lignite is recovered. Slope stability causes several problems, including loss of lignite, increased rehandle, and hazards to personnel and equipment. Traditional lignite mine planning involved a fairly {open_quotes}generic{close_quotes} pit design with one design highwall angle, one design spoil angle, and little geotechnical evaluation of the deposit. This {open_quotes}one mine-one design{close_quotes} approach, while cost-effective in the past, is now being replaced by a more critical analysis of the design requirements of each area. Geotechnical evaluation plays an increasing role in the planning and operational aspects of lignite mining. Laboratory core sample test results can be used for slope stability modeling, in order to obtain more accurate design and operational information.« less

Release of Mercury Mine Tailings from Mine Impacted Watersheds by Extreme Events Resulting from Climate Change

NASA Astrophysics Data System (ADS)

Rytuba, J. J.

2015-12-01

An increase in intensity and frequency of extreme events resulting from climate change is expected to result in extreme precipitation events on both regional and local scales. Extreme precipitation events have the potential to mobilize large volumes of mercury (Hg) mine tailings in watersheds where tailings reside in the floodplain downstream from historic Hg mines. The California Hg mineral belt produced one third of the worlds Hg from over 100 mines from the 1850's to 1972. In the absence of environmental regulations, tailings were disposed of into streams adjacent to the mines in order to have them transported from the mine site during storm events. Thus most of the tailings no longer reside at the mine site. Addition of tailings to the streams resulted in stream aggradation, increased over-bank flow, and deposition of tailings in the floodplain for up to 25 kms downstream from the mines. After cessation of mining, the decrease in tailings entering the streams resulted in degradation, incision of the streams into the floodplain, and inability of the streams to access the floodplain. Thus Hg tailings have remained stored in the floodplain since cessation of mining. Hg phases in these tailings consist of cinnabar, metacinnabar and montroydite based on EXAFS analysis. Size analysis indicates that Hg phases are fine grained, less than 1 um. The last regional scale extreme precipitation events to effect the entire area of the California Hg mineral belt were the ARkStorm events of 1861-1862 that occurred prior to large scale Hg mining. Extreme regional ARkStorm precipitation events as well as local summer storms, such as the July 2006 flood in the Clear Creek Hg mining district, are expected to increase in frequency and have the potential to remobilize the large volume of tailings stored in floodplain deposits. Although Hg mine remediation has decreased Hg release from mine sites in a period of benign climate, no remediation efforts have addressed the large source of Hg residing in floodplain deposits. This Hg source in a period of climate change poses a significant environmental risk to aquatic systems downstream from Hg mine-impacted watersheds. An extreme ARkStorm event is estimated to potentially remobilize an amount of Hg equivalent to that released in the past during the peak period of unregulated Hg mining in California.

Recording the LHCb data and software dependencies

NASA Astrophysics Data System (ADS)

Trisovic, Ana; Couturier, Ben; Gibson, Val; Jones, Chris

2017-10-01

In recent years awareness of the importance of preserving the experimental data and scientific software at CERN has been rising. To support this effort, we are presenting a novel approach to structure dependencies of the LHCb data and software to make it more accessible in the long-term future. In this paper, we detail the implementation of a graph database of these dependencies. We list the implications that can be deduced from the graph mining (such as a search for the legacy software), with emphasis on data preservation. Furthermore, we introduce a methodology of recreating the LHCb data, thus supporting reproducible research and data stewardship. Finally, we describe how this information is made available to the users on a web portal that promotes data and analysis preservation and good practise with analysis documentation.

Bioinformatics and molecular modeling in glycobiology

PubMed Central

Schloissnig, Siegfried

2010-01-01

The field of glycobiology is concerned with the study of the structure, properties, and biological functions of the family of biomolecules called carbohydrates. Bioinformatics for glycobiology is a particularly challenging field, because carbohydrates exhibit a high structural diversity and their chains are often branched. Significant improvements in experimental analytical methods over recent years have led to a tremendous increase in the amount of carbohydrate structure data generated. Consequently, the availability of databases and tools to store, retrieve and analyze these data in an efficient way is of fundamental importance to progress in glycobiology. In this review, the various graphical representations and sequence formats of carbohydrates are introduced, and an overview of newly developed databases, the latest developments in sequence alignment and data mining, and tools to support experimental glycan analysis are presented. Finally, the field of structural glycoinformatics and molecular modeling of carbohydrates, glycoproteins, and protein–carbohydrate interaction are reviewed. PMID:20364395

Molecular diversity of the ammonia-oxidizing bacteria community in disused tin-mining ponds located within Kampar, Perak, Malaysia.

PubMed

Sow, S L S; Khoo, G; Chong, L K; Smith, T J; Harrison, P L; Ong, H K A

2014-02-01

Disused tin-mining ponds make up a significant amount of water bodies in Malaysia particularly at the Kinta Valley in the state of Perak where tin-mining activities were the most extensive, and these abundantly available water sources are widely used in the field of aquaculture and agriculture. However, the natural ecology and physicochemical conditions of these ponds, many of which have been altered due to secondary post-mining activities, remains to be explored. As ammonia-oxidizing bacteria (AOB) are directly related to the nutrient cycles of aquatic environments and are useful bioindicators of environmental variations, the focus of this study was to identify AOBs associated with disused tin-mining ponds that have a history of different secondary activities in comparison to ponds which were left untouched and remained as part of the landscape. The 16S rDNA gene was used to detect AOBs in the sediment and water sampled from the three types of disused mining ponds, namely ponds without secondary activity, ponds that were used for lotus cultivation and post-aquaculture ponds. When the varying pond types were compared with the sequence and phylogenetic analysis of the AOB clone libraries, both Nitrosomonas and Nitrosospira-like AOB were detected though Nitrosospira spp. was seen to be the most ubiquitous AOB as it was present in all ponds types. However, AOBs were not detected in the sediments of idle ponds. Based on rarefaction analysis and diversity indices, the disused mining pond with lotus culture indicated the highest richness of AOBs. Canonical correspondence analysis indicated that among the physicochemical properties of the pond sites, TAN and nitrite were shown to be the main factors that influenced the community structure of AOBs in these disused tin-mining ponds.

Filter materials for metal removal from mine drainage--a review.

PubMed

Westholm, Lena Johansson; Repo, Eveliina; Sillanpää, Mika

2014-01-01

A large number of filter materials, organic and inorganic, for removal of heavy metals in mine drainage have been reviewed. Bark, chitin, chitosan, commercial ion exchangers, dairy manure compost, lignite, peat, rice husks, vegetal compost, and yeast are examples of organic materials, while bio-carbons, calcareous shale, dolomite, fly ash, limestone, olivine, steel slag materials and zeolites are examples of inorganic materials. The majority of these filter materials have been investigated in laboratory studies, based on various experimental set-ups (batch and/or column tests) and different conditions. A few materials, for instance steel slag materials, have also been subjects to field investigations under real-life conditions. The results from these investigations show that steel slag materials have the potential to remove heavy metals under different conditions. Ion exchange has been suggested as the major metal removal mechanisms not only for steel slag but also for lignite. Other suggested removal mechanisms have also been identified. Adsorption has been suggested important for activated carbon, precipitation for chitosan and sulphate reduction for olivine. General findings indicate that the results with regard to metal removal vary due to experimental set ups, composition of mine drainage and properties of filter materials and the discrepancies between studies renders normalisation of data difficult. However, the literature reveals that Fe, Zn, Pb, Hg and Al are removed to a large extent. Further investigations, especially under real-life conditions, are however necessary in order to find suitable filter materials for treatment of mine drainage.

Southeast corner with overhead crane in foreground Bureau of ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

Southeast corner with overhead crane in foreground - Bureau of Mines Boulder City Experimental Station, Titanium Development Plant, Date Street north of U.S. Highway 93, Boulder City, Clark County, NV

Introducing Text Analytics as a Graduate Business School Course

ERIC Educational Resources Information Center

Edgington, Theresa M.

2011-01-01

Text analytics refers to the process of analyzing unstructured data from documented sources, including open-ended surveys, blogs, and other types of web dialog. Text analytics has enveloped the concept of text mining, an analysis approach influenced heavily from data mining. While text mining has been covered extensively in various computer…

An economic analysis of mine-timber marketing in West Virginia

Treesearch

Henry H. Webster

1956-01-01

Coal mines have long provided a major outlet for the timber products of West Virginia. Although the structure and operation of mine-timber markets is little understood, the efficiency of the marketing system undoubtedly affects the decisions of most of the 130,000 farm and other private timber-growing enterprises in the state.

The use of data mining by private health insurance companies and customers' privacy.

PubMed

Al-Saggaf, Yeslam

2015-07-01

This article examines privacy threats arising from the use of data mining by private Australian health insurance companies. Qualitative interviews were conducted with key experts, and Australian governmental and nongovernmental websites relevant to private health insurance were searched. Using Rationale, a critical thinking tool, the themes and considerations elicited through this empirical approach were developed into an argument about the use of data mining by private health insurance companies. The argument is followed by an ethical analysis guided by classical philosophical theories-utilitarianism, Mill's harm principle, Kant's deontological theory, and Helen Nissenbaum's contextual integrity framework. Both the argument and the ethical analysis find the use of data mining by private health insurance companies in Australia to be unethical. Although private health insurance companies in Australia cannot use data mining for risk rating to cherry-pick customers and cannot use customers' personal information for unintended purposes, this article nonetheless concludes that the secondary use of customers' personal information and the absence of customers' consent still suggest that the use of data mining by private health insurance companies is wrong.

Development of ergonomics audits for bagging, haul truck and maintenance and repair operations in mining.

PubMed

Dempsey, Patrick G; Pollard, Jonisha; Porter, William L; Mayton, Alan; Heberger, John R; Gallagher, Sean; Reardon, Leanna; Drury, Colin G

2017-12-01

The development and testing of ergonomics and safety audits for small and bulk bag filling, haul truck and maintenance and repair operations in coal preparation and mineral processing plants found at surface mine sites is described. The content for the audits was derived from diverse sources of information on ergonomics and safety deficiencies including: analysis of injury, illness and fatality data and reports; task analysis; empirical laboratory studies of particular tasks; field studies and observations at mine sites; and maintenance records. These diverse sources of information were utilised to establish construct validity of the modular audits that were developed for use by mine safety personnel. User and interrater reliability testing was carried out prior to finalising the audits. The audits can be implemented using downloadable paper versions or with a free mobile NIOSH-developed Android application called ErgoMine. Practitioner Summary: The methodology used to develop ergonomics audits for three types of mining operations is described. Various sources of audit content are compared and contrasted to serve as a guide for developing ergonomics audits for other occupational contexts.

Rational Use of Land Resource During the Implementation of Transportless System of Coal Strata Surface Mining

NASA Astrophysics Data System (ADS)

Gvozdkova, T.; Tyulenev, M.; Zhironkin, S.; Trifonov, V. A.; Osipov, Yu M.

2017-01-01

Surface mining and open pits engineering affect the environment in a very negative way. Among other pollutions that open pits make during mineral deposits exploiting, particular problem is the landscape changing. Along with converting the land into pits, surface mining is connected with pilling dumps that occupy large ground. The article describes an analysis of transportless methods of several coal seams strata surface mining, applied for open pits of South Kuzbass coal enterprises (Western Siberia, Russia). To improve land-use management of open pit mining enterprises, the characteristics of transportless technological schemes for several coal seams strata surface mining are highlighted and observed. These characteristics help to systematize transportless open mining technologies using common criteria that characterize structure of the bottom part of a strata and internal dumping schemes. The schemes of transportless systems of coal strata surface mining implemented in South Kuzbass are given.

Data mining in radiology

PubMed Central

Kharat, Amit T; Singh, Amarjit; Kulkarni, Vilas M; Shah, Digish

2014-01-01

Data mining facilitates the study of radiology data in various dimensions. It converts large patient image and text datasets into useful information that helps in improving patient care and provides informative reports. Data mining technology analyzes data within the Radiology Information System and Hospital Information System using specialized software which assesses relationships and agreement in available information. By using similar data analysis tools, radiologists can make informed decisions and predict the future outcome of a particular imaging finding. Data, information and knowledge are the components of data mining. Classes, Clusters, Associations, Sequential patterns, Classification, Prediction and Decision tree are the various types of data mining. Data mining has the potential to make delivery of health care affordable and ensure that the best imaging practices are followed. It is a tool for academic research. Data mining is considered to be ethically neutral, however concerns regarding privacy and legality exists which need to be addressed to ensure success of data mining. PMID:25024513

Mining method selection by integrated AHP and PROMETHEE method.

PubMed

Bogdanovic, Dejan; Nikolic, Djordje; Ilic, Ivana

2012-03-01

Selecting the best mining method among many alternatives is a multicriteria decision making problem. The aim of this paper is to demonstrate the implementation of an integrated approach that employs AHP and PROMETHEE together for selecting the most suitable mining method for the "Coka Marin" underground mine in Serbia. The related problem includes five possible mining methods and eleven criteria to evaluate them. Criteria are accurately chosen in order to cover the most important parameters that impact on the mining method selection, such as geological and geotechnical properties, economic parameters and geographical factors. The AHP is used to analyze the structure of the mining method selection problem and to determine weights of the criteria, and PROMETHEE method is used to obtain the final ranking and to make a sensitivity analysis by changing the weights. The results have shown that the proposed integrated method can be successfully used in solving mining engineering problems.

A systematic mapping study of process mining

NASA Astrophysics Data System (ADS)

Maita, Ana Rocío Cárdenas; Martins, Lucas Corrêa; López Paz, Carlos Ramón; Rafferty, Laura; Hung, Patrick C. K.; Peres, Sarajane Marques; Fantinato, Marcelo

2018-05-01

This study systematically assesses the process mining scenario from 2005 to 2014. The analysis of 705 papers evidenced 'discovery' (71%) as the main type of process mining addressed and 'categorical prediction' (25%) as the main mining task solved. The most applied traditional technique is the 'graph structure-based' ones (38%). Specifically concerning computational intelligence and machine learning techniques, we concluded that little relevance has been given to them. The most applied are 'evolutionary computation' (9%) and 'decision tree' (6%), respectively. Process mining challenges, such as balancing among robustness, simplicity, accuracy and generalization, could benefit from a larger use of such techniques.

Research on mining truck vibration control based on particle damping

NASA Astrophysics Data System (ADS)

Liming, Song; Wangqiang, Xiao; Zeguang, Li; Haiquan, Guo; Zhe, Yang

2018-03-01

More and more attentions were got by people about the research on mining truck driving comfort. As the vibration transfer terminal, cab is one of the important part of mining truck vibration control. In this paper, based on particle damping technology and its application characteristics, through the discrete element modeling, DEM & FEM coupling simulation and analysis, lab test verification and actual test in the truck, particle damping technology was successfully used in driver’s seat base of mining truck, cab vibration was reduced obviously, meanwhile applied research and method of particle damping technology in mining truck vibration control were provided.

IEEE Conference Record of 1980 Fourteenth Pulse Power Modulator Symposium, 3-5 June 1980.

DTIC Science & Technology

1980-01-01

attachment and generation coefficients, usually given volume can control the velocity of the streamer phase as a function of E/P. Data on experimentally ...more foils could be used if desired. The mechanical design for the electron beau Experimental Program controlled switch has two competing requirenmts...deter- mine the effect of the plasma conditioning as compared to the control tests. 2W C C TABLE I: SUMMARY OF EXPERIMENTAL PROCEDURE • ur EIIEIT

Data warehousing as a basis for web-based documentation of data mining and analysis.

PubMed

Karlsson, J; Eklund, P; Hallgren, C G; Sjödin, J G

1999-01-01

In this paper we present a case study for data warehousing intended to support data mining and analysis. We also describe a prototype for data retrieval. Further we discuss some technical issues related to a particular choice of a patient record environment.

Mining a Web Citation Database for Author Co-Citation Analysis.

ERIC Educational Resources Information Center

He, Yulan; Hui, Siu Cheung

2002-01-01

Proposes a mining process to automate author co-citation analysis based on the Web Citation Database, a data warehouse for storing citation indices of Web publications. Describes the use of agglomerative hierarchical clustering for author clustering and multidimensional scaling for displaying author cluster maps, and explains PubSearch, a…

Fracture mapping and strip mine inventory in the Midwest by using ERTS-1 imagery

NASA Technical Reports Server (NTRS)

Wier, C. W.; Wobber, F. J.; Russell, O. R.; Amato, R. V.

1973-01-01

Analysis of the ERTS-1 imagery and high-altitude infrared photography indicates that useful fracture data can be obtained in Indiana and Illinois despite a glacial till cover. ERTS MSS bands 5 and 7 have proven most useful for fracture mapping in coal-bearing rocks in this region. Preliminary results suggest a reasonable correlation between image-detected fractures and mine roof-fall accidents. Information related to surface mined land, such as disturbed area, water bodies, and kind of reclamation, has been derived from the analysis of ERTS imagery.

Application and Exploration of Big Data Mining in Clinical Medicine.

PubMed

Zhang, Yue; Guo, Shu-Li; Han, Li-Na; Li, Tie-Ling

2016-03-20

To review theories and technologies of big data mining and their application in clinical medicine. Literatures published in English or Chinese regarding theories and technologies of big data mining and the concrete applications of data mining technology in clinical medicine were obtained from PubMed and Chinese Hospital Knowledge Database from 1975 to 2015. Original articles regarding big data mining theory/technology and big data mining's application in the medical field were selected. This review characterized the basic theories and technologies of big data mining including fuzzy theory, rough set theory, cloud theory, Dempster-Shafer theory, artificial neural network, genetic algorithm, inductive learning theory, Bayesian network, decision tree, pattern recognition, high-performance computing, and statistical analysis. The application of big data mining in clinical medicine was analyzed in the fields of disease risk assessment, clinical decision support, prediction of disease development, guidance of rational use of drugs, medical management, and evidence-based medicine. Big data mining has the potential to play an important role in clinical medicine.

Implications of Emerging Data Mining

NASA Astrophysics Data System (ADS)

Kulathuramaiyer, Narayanan; Maurer, Hermann

Data Mining describes a technology that discovers non-trivial hidden patterns in a large collection of data. Although this technology has a tremendous impact on our lives, the invaluable contributions of this invisible technology often go unnoticed. This paper discusses advances in data mining while focusing on the emerging data mining capability. Such data mining applications perform multidimensional mining on a wide variety of heterogeneous data sources, providing solutions to many unresolved problems. This paper also highlights the advantages and disadvantages arising from the ever-expanding scope of data mining. Data Mining augments human intelligence by equipping us with a wealth of knowledge and by empowering us to perform our daily tasks better. As the mining scope and capacity increases, users and organizations become more willing to compromise privacy. The huge data stores of the ‚master miners` allow them to gain deep insights into individual lifestyles and their social and behavioural patterns. Data integration and analysis capability of combining business and financial trends together with the ability to deterministically track market changes will drastically affect our lives.

South (side) and east (rear) elevations, view to northwest ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

South (side) and east (rear) elevations, view to northwest - Bureau of Mines Boulder City Experimental Station, Titanium Development Plant, Date Street north of U.S. Highway 93, Boulder City, Clark County, NV

6. Vacuum purification room and upper level offices Bureau ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

6. Vacuum purification room and upper level offices - Bureau of Mines Boulder City Experimental Station, Titanium Research Building, Date Street north of U.S. Highway 93, Boulder City, Clark County, NV

North (side) and west (front) elevations, view to southeast ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

North (side) and west (front) elevations, view to southeast - Bureau of Mines Boulder City Experimental Station, Titanium Development Plant, Date Street north of U.S. Highway 93, Boulder City, Clark County, NV

West (front) and south (side) elevations, view to north ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

West (front) and south (side) elevations, view to north - Bureau of Mines Boulder City Experimental Station, Titanium Development Plant, Date Street north of U.S. Highway 93, Boulder City, Clark County, NV

Protein-protein interaction predictions using text mining methods.

PubMed

Papanikolaou, Nikolas; Pavlopoulos, Georgios A; Theodosiou, Theodosios; Iliopoulos, Ioannis

2015-03-01

It is beyond any doubt that proteins and their interactions play an essential role in most complex biological processes. The understanding of their function individually, but also in the form of protein complexes is of a great importance. Nowadays, despite the plethora of various high-throughput experimental approaches for detecting protein-protein interactions, many computational methods aiming to predict new interactions have appeared and gained interest. In this review, we focus on text-mining based computational methodologies, aiming to extract information for proteins and their interactions from public repositories such as literature and various biological databases. We discuss their strengths, their weaknesses and how they complement existing experimental techniques by simultaneously commenting on the biological databases which hold such information and the benchmark datasets that can be used for evaluating new tools. Copyright © 2014 Elsevier Inc. All rights reserved.

Boise Basin Experimental Forest (Idaho)

Treesearch

Russell T. Graham; Theresa B. Jain

2004-01-01

The Boise Basin Experimental Forest was established in 1933 to study ponderosa pine. It consists of 3,537 ha with elevations ranging from 1,200 to 3,630 m. Boise Basin is divided into three units surrounding Idaho City in southern Idaho. Idaho City was a booming mining town in the 1870s and the surrounding forests supplied material to the community. Two units were...

The DynaMine webserver: predicting protein dynamics from sequence.

PubMed

Cilia, Elisa; Pancsa, Rita; Tompa, Peter; Lenaerts, Tom; Vranken, Wim F

2014-07-01

Protein dynamics are important for understanding protein function. Unfortunately, accurate protein dynamics information is difficult to obtain: here we present the DynaMine webserver, which provides predictions for the fast backbone movements of proteins directly from their amino-acid sequence. DynaMine rapidly produces a profile describing the statistical potential for such movements at residue-level resolution. The predicted values have meaning on an absolute scale and go beyond the traditional binary classification of residues as ordered or disordered, thus allowing for direct dynamics comparisons between protein regions. Through this webserver, we provide molecular biologists with an efficient and easy to use tool for predicting the dynamical characteristics of any protein of interest, even in the absence of experimental observations. The prediction results are visualized and can be directly downloaded. The DynaMine webserver, including instructive examples describing the meaning of the profiles, is available at http://dynamine.ibsquare.be. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.

A New Data Mining Scheme Using Artificial Neural Networks

PubMed Central

Kamruzzaman, S. M.; Jehad Sarkar, A. M.

2011-01-01

Classification is one of the data mining problems receiving enormous attention in the database community. Although artificial neural networks (ANNs) have been successfully applied in a wide range of machine learning applications, they are however often regarded as black boxes, i.e., their predictions cannot be explained. To enhance the explanation of ANNs, a novel algorithm to extract symbolic rules from ANNs has been proposed in this paper. ANN methods have not been effectively utilized for data mining tasks because how the classifications were made is not explicitly stated as symbolic rules that are suitable for verification or interpretation by human experts. With the proposed approach, concise symbolic rules with high accuracy, that are easily explainable, can be extracted from the trained ANNs. Extracted rules are comparable with other methods in terms of number of rules, average number of conditions for a rule, and the accuracy. The effectiveness of the proposed approach is clearly demonstrated by the experimental results on a set of benchmark data mining classification problems. PMID:22163866

An IPSO-SVM algorithm for security state prediction of mine production logistics system

NASA Astrophysics Data System (ADS)

Zhang, Yanliang; Lei, Junhui; Ma, Qiuli; Chen, Xin; Bi, Runfang

2017-06-01

A theoretical basis for the regulation of corporate security warning and resources was provided in order to reveal the laws behind the security state in mine production logistics. Considering complex mine production logistics system and the variable is difficult to acquire, a superior security status predicting model of mine production logistics system based on the improved particle swarm optimization and support vector machine (IPSO-SVM) is proposed in this paper. Firstly, through the linear adjustments of inertia weight and learning weights, the convergence speed and search accuracy are enhanced with the aim to deal with situations associated with the changeable complexity and the data acquisition difficulty. The improved particle swarm optimization (IPSO) is then introduced to resolve the problem of parameter settings in traditional support vector machines (SVM). At the same time, security status index system is built to determine the classification standards of safety status. The feasibility and effectiveness of this method is finally verified using the experimental results.

Integrating data from biological experiments into metabolic networks with the DBE information system.

PubMed

Borisjuk, Ljudmilla; Hajirezaei, Mohammad-Reza; Klukas, Christian; Rolletschek, Hardy; Schreiber, Falk

2005-01-01

Modern 'omics'-technologies result in huge amounts of data about life processes. For analysis and data mining purposes this data has to be considered in the context of the underlying biological networks. This work presents an approach for integrating data from biological experiments into metabolic networks by mapping the data onto network elements and visualising the data enriched networks automatically. This methodology is implemented in DBE, an information system that supports the analysis and visualisation of experimental data in the context of metabolic networks. It consists of five parts: (1) the DBE-Database for consistent data storage, (2) the Excel-Importer application for the data import, (3) the DBE-Website as the interface for the system, (4) the DBE-Pictures application for the up- and download of binary (e. g. image) files, and (5) DBE-Gravisto, a network analysis and graph visualisation system. The usability of this approach is demonstrated in two examples.

Land use-based landscape planning and restoration in mine closure areas.

PubMed

Zhang, Jianjun; Fu, Meichen; Hassani, Ferri P; Zeng, Hui; Geng, Yuhuan; Bai, Zhongke

2011-05-01

Landscape planning and restoration in mine closure areas is not only an inevitable choice to sustain mining areas but also an important path to maximize landscape resources and to improve ecological function in mine closure areas. The analysis of the present mine development shows that many mines are unavoidably facing closures in China. This paper analyzes the periodic impact of mining activities on landscapes and then proposes planning concepts and principles. According to the landscape characteristics in mine closure areas, this paper classifies available landscape resources in mine closure areas into the landscape for restoration, for limited restoration and for protection, and then summarizes directions for their uses. This paper establishes the framework of spatial control planning and design of landscape elements from "macro control, medium allocation and micro optimization" for the purpose of managing and using this kind of special landscape resources. Finally, this paper applies the theories and methods to a case study in Wu'an from two aspects: the construction of a sustainable land-use pattern on a large scale and the optimized allocation of typical mine landscape resources on a small scale.

Selected water-quality data for the Standard Mine, Gunnison County, Colorado, 2006-2007

USGS Publications Warehouse

Verplanck, Philip L.; Manning, Andrew H.; Mast, M. Alisa; Wanty, Richard B.; McCleskey, R. Blaine; Todorov, Todor I.; Adams, Monique

2007-01-01

Mine drainage and underground water samples were collected for analysis of inorganic solutes as part of a 1-year, hydrogeologic investigation of the Standard Mine and vicinity. The U.S. Environmental Protection Agency has listed the Standard Mine in the Elk Creek drainage near Crested Butte, Colorado, as a Superfund Site because discharge from the Standard Mine enters Elk Creek, contributing dissolved and suspended loads of zinc, cadmium, copper, and other metals to Coal Creek, which is the primary drinking-water supply for the town of Crested Butte. Water analyses are reported for mine-effluent samples from Levels 1 and 5 of the Standard Mine, underground samples from Levels 3 and 5 of the Standard Mine, mine effluent from an adit located on the Elk Lode, and two spring samples that emerged from waste-rock material below Level 5 of the Standard Mine and the adit located on the Elk Lode. Reported analyses include field parameters (pH, specific conductance, water temperature, dissolved oxygen, and redox potential) and major constituents and trace elements.

Reconstructing disturbance history for an intensively mined region by time-series analysis of Landsat imagery.

PubMed

Li, Jing; Zipper, Carl E; Donovan, Patricia F; Wynne, Randolph H; Oliphant, Adam J

2015-09-01

Surface mining disturbances have attracted attention globally due to extensive influence on topography, land use, ecosystems, and human populations in mineral-rich regions. We analyzed a time series of Landsat satellite imagery to produce a 28-year disturbance history for surface coal mining in a segment of eastern USA's central Appalachian coalfield, southwestern Virginia. The method was developed and applied as a three-step sequence: vegetation index selection, persistent vegetation identification, and mined-land delineation by year of disturbance. The overall classification accuracy and kappa coefficient were 0.9350 and 0.9252, respectively. Most surface coal mines were identified correctly by location and by time of initial disturbance. More than 8 % of southwestern Virginia's >4000-km(2) coalfield area was disturbed by surface coal mining over the 28-year period. Approximately 19.5 % of the Appalachian coalfield surface within the most intensively mined county (Wise County) has been disturbed by mining. Mining disturbances expanded steadily and progressively over the study period. Information generated can be applied to gain further insight concerning mining influences on ecosystems and other essential environmental features.

Soil microbial community successional patterns during forest ecosystem restoration.

PubMed

Banning, Natasha C; Gleeson, Deirdre B; Grigg, Andrew H; Grant, Carl D; Andersen, Gary L; Brodie, Eoin L; Murphy, D V

2011-09-01

Soil microbial community characterization is increasingly being used to determine the responses of soils to stress and disturbances and to assess ecosystem sustainability. However, there is little experimental evidence to indicate that predictable patterns in microbial community structure or composition occur during secondary succession or ecosystem restoration. This study utilized a chronosequence of developing jarrah (Eucalyptus marginata) forest ecosystems, rehabilitated after bauxite mining (up to 18 years old), to examine changes in soil bacterial and fungal community structures (by automated ribosomal intergenic spacer analysis [ARISA]) and changes in specific soil bacterial phyla by 16S rRNA gene microarray analysis. This study demonstrated that mining in these ecosystems significantly altered soil bacterial and fungal community structures. The hypothesis that the soil microbial community structures would become more similar to those of the surrounding nonmined forest with rehabilitation age was broadly supported by shifts in the bacterial but not the fungal community. Microarray analysis enabled the identification of clear successional trends in the bacterial community at the phylum level and supported the finding of an increase in similarity to nonmined forest soil with rehabilitation age. Changes in soil microbial community structure were significantly related to the size of the microbial biomass as well as numerous edaphic variables (including pH and C, N, and P nutrient concentrations). These findings suggest that soil bacterial community dynamics follow a pattern in developing ecosystems that may be predictable and can be conceptualized as providing an integrated assessment of numerous edaphic variables.

Soil Microbial Community Successional Patterns during Forest Ecosystem Restoration ▿†

PubMed Central

Banning, Natasha C.; Gleeson, Deirdre B.; Grigg, Andrew H.; Grant, Carl D.; Andersen, Gary L.; Brodie, Eoin L.; Murphy, D. V.

2011-01-01

Soil microbial community characterization is increasingly being used to determine the responses of soils to stress and disturbances and to assess ecosystem sustainability. However, there is little experimental evidence to indicate that predictable patterns in microbial community structure or composition occur during secondary succession or ecosystem restoration. This study utilized a chronosequence of developing jarrah (Eucalyptus marginata) forest ecosystems, rehabilitated after bauxite mining (up to 18 years old), to examine changes in soil bacterial and fungal community structures (by automated ribosomal intergenic spacer analysis [ARISA]) and changes in specific soil bacterial phyla by 16S rRNA gene microarray analysis. This study demonstrated that mining in these ecosystems significantly altered soil bacterial and fungal community structures. The hypothesis that the soil microbial community structures would become more similar to those of the surrounding nonmined forest with rehabilitation age was broadly supported by shifts in the bacterial but not the fungal community. Microarray analysis enabled the identification of clear successional trends in the bacterial community at the phylum level and supported the finding of an increase in similarity to nonmined forest soil with rehabilitation age. Changes in soil microbial community structure were significantly related to the size of the microbial biomass as well as numerous edaphic variables (including pH and C, N, and P nutrient concentrations). These findings suggest that soil bacterial community dynamics follow a pattern in developing ecosystems that may be predictable and can be conceptualized as providing an integrated assessment of numerous edaphic variables. PMID:21724890

Solutions for Mining Distributed Scientific Data

NASA Astrophysics Data System (ADS)

Lynnes, C.; Pham, L.; Graves, S.; Ramachandran, R.; Maskey, M.; Keiser, K.

2007-12-01

Researchers at the University of Alabama in Huntsville (UAH) and the Goddard Earth Sciences Data and Information Services Center (GES DISC) are working on approaches and methodologies facilitating the analysis of large amounts of distributed scientific data. Despite the existence of full-featured analysis tools, such as the Algorithm Development and Mining (ADaM) toolkit from UAH, and data repositories, such as the GES DISC, that provide online access to large amounts of data, there remain obstacles to getting the analysis tools and the data together in a workable environment. Does one bring the data to the tools or deploy the tools close to the data? The large size of many current Earth science datasets incurs significant overhead in network transfer for analysis workflows, even with the advanced networking capabilities that are available between many educational and government facilities. The UAH and GES DISC team are developing a capability to define analysis workflows using distributed services and online data resources. We are developing two solutions for this problem that address different analysis scenarios. The first is a Data Center Deployment of the analysis services for large data selections, orchestrated by a remotely defined analysis workflow. The second is a Data Mining Center approach of providing a cohesive analysis solution for smaller subsets of data. The two approaches can be complementary and thus provide flexibility for researchers to exploit the best solution for their data requirements. The Data Center Deployment of the analysis services has been implemented by deploying ADaM web services at the GES DISC so they can access the data directly, without the need of network transfers. Using the Mining Workflow Composer, a user can define an analysis workflow that is then submitted through a Web Services interface to the GES DISC for execution by a processing engine. The workflow definition is composed, maintained and executed at a distributed location, but most of the actual services comprising the workflow are available local to the GES DISC data repository. Additional refinements will ultimately provide a package that is easily implemented and configured at additional data centers for analysis of additional science data sets. Enhancements to the ADaM toolkit allow the staging of distributed data wherever the services are deployed, to support a Data Mining Center that can provide additional computational resources, large storage of output, easier addition and updates to available services, and access to data from multiple repositories. The Data Mining Center case provides researchers more flexibility to quickly try different workflow configurations and refine the process, using smaller amounts of data that may likely be transferred from distributed online repositories. This environment is sufficient for some analyses, but can also be used as an initial sandbox to test and refine a solution before staging the execution at a Data Center Deployment. Detection of airborne dust both over water and land in MODIS imagery using mining services for both solutions will be presented. The dust detection is just one possible example of the mining and analysis capabilities the proposed mining services solutions will provide to the science community. More information about the available services and the current status of this project is available at http://www.itsc.uah.edu/mws/

MINE: Module Identification in Networks

PubMed Central

2011-01-01

Background Graphical models of network associations are useful for both visualizing and integrating multiple types of association data. Identifying modules, or groups of functionally related gene products, is an important challenge in analyzing biological networks. However, existing tools to identify modules are insufficient when applied to dense networks of experimentally derived interaction data. To address this problem, we have developed an agglomerative clustering method that is able to identify highly modular sets of gene products within highly interconnected molecular interaction networks. Results MINE outperforms MCODE, CFinder, NEMO, SPICi, and MCL in identifying non-exclusive, high modularity clusters when applied to the C. elegans protein-protein interaction network. The algorithm generally achieves superior geometric accuracy and modularity for annotated functional categories. In comparison with the most closely related algorithm, MCODE, the top clusters identified by MINE are consistently of higher density and MINE is less likely to designate overlapping modules as a single unit. MINE offers a high level of granularity with a small number of adjustable parameters, enabling users to fine-tune cluster results for input networks with differing topological properties. Conclusions MINE was created in response to the challenge of discovering high quality modules of gene products within highly interconnected biological networks. The algorithm allows a high degree of flexibility and user-customisation of results with few adjustable parameters. MINE outperforms several popular clustering algorithms in identifying modules with high modularity and obtains good overall recall and precision of functional annotations in protein-protein interaction networks from both S. cerevisiae and C. elegans. PMID:21605434

Rare itemsets mining algorithm based on RP-Tree and spark framework

NASA Astrophysics Data System (ADS)

Liu, Sainan; Pan, Haoan

2018-05-01

For the issues of the rare itemsets mining in big data, this paper proposed a rare itemsets mining algorithm based on RP-Tree and Spark framework. Firstly, it arranged the data vertically according to the transaction identifier, in order to solve the defects of scan the entire data set, the vertical datasets are divided into frequent vertical datasets and rare vertical datasets. Then, it adopted the RP-Tree algorithm to construct the frequent pattern tree that contains rare items and generate rare 1-itemsets. After that, it calculated the support of the itemsets by scanning the two vertical data sets, finally, it used the iterative process to generate rare itemsets. The experimental show that the algorithm can effectively excavate rare itemsets and have great superiority in execution time.

The As removal from arsenopyrite-bearing mine waste by microwave

NASA Astrophysics Data System (ADS)

Kim, Hyun Soo; Myung, Eun Ji; Hack Lim, Dae; Kim, Bong Ju; Park, Cheon Young

2016-04-01

Penalties incurred by miners for arsenic in concentrates have increased significantly because the removal and disposal of arsenic is difficult and costly for smelters and because the environmental challenges are increasing worldwide. Typically miners incur penalties on arsenic in concentrates above 0.2% As with smelter rejection limits of 0.5%. Therefore, finding an effective solution for removing As during primary mining activities is necessary to avoid penalty. The aim of this study was to investigate the As removal from mine waste using microwave process. The mine waste samples were characterized by chemical and XRD analysis. To determine of As removal from the microwave experiments, aqua regia digestion was performed according to Korean environmental standard method(KESM) and the As removal effect were evaluated using the standard EPA toxicity characteristic leaching procedure(TCLP, EPA 1311 method). The result of mineralogical character for mine waste using XRD was detected arsenopyrite, pyrite, chalcopyrite, pyrrhotite and quartz. The chemical analysis of As, Pb, Zn contents in the mine waste measured 13,896.0, 896.1 and 1,054.6 mg/kg, respectively. The As removal of experiments was conducted to examine the effects of microwave exposure time(1~15min). The results showed that the As removal in mine waste (exposure time = 10min) was 92.90%, and the temperature of mine waste by microwave heating was 886℃. The TCLP leaching of treated mine waste by microwave measured values were below the EPA's current regulatory threshold(As, Pb, Zn : 5 mg/L). The optimum condition of microwave exposure for As removal from arsenopyrite-bearing mine waste was obtained at 800W, 2450MHz, 10min. Acknowledgment : This work was supported by the Energy and Resources Engineering Program Grant funded by the Ministry of Trade, Industry and Energy, Korea

Megabenthic Community Structure Within and Surrounding the DISCOL Experimental Area 26 Years After Simulated Manganese Nodule Mining Disturbance.

NASA Astrophysics Data System (ADS)

Purser, A.; Marcon, Y.; Boetius, A.

2016-02-01

The current supplies of many high technology elements from land-based sources are at capacity, such as copper, nickel and yttrium. Potential future sources of some of these elements include the deep sea manganese nodule fields of the Atlantic, Indian and Pacific oceans. Large swathes of deep-sea seafloor are covered with high densities of 5 - 25 cm diameter nodules - agglomerations of manganese, iron and trace metals. In the 1980's these manganese fields were first seriously considered as mining targets, and the ''DISturbance and reCOLonization (DISCOL) experiment was started in the South Pacific, to simulate the likely environmental impacts of mining. In September 1989, 'RV Sonne', deploying a custom-built plough device, removed manganese nodules from the seafloor surface by ploughing them down into the sediment. This removal of nodules (and therefore hard substrate) was considered to likely be the most significant environmental impact of any future mining efforts. 78 plough tracks of 8 - 16m width were made across a 10.8 km diameter circular area centered on 7°04.4´S 88°27.6´W. Megafauna abundances were assessed prior and post ploughing, both within the disturbed area and at reference stations 6 km from the disturbed area. Research cruises in the 1990s investigated the short-term temporal impact ploughing had on the faunal community in the DISCOL area. Cruises conducted 3 and 7 years after disturbance showed that megafaunal communities within ploughed areas remained quite distinct from those observed pre-disturbance or in the reference areas. In 2016 the 'RV Sonne' revisited the DISCOL site with two research cruises, as part of the 'JPI-Oceans' programme. Here we report the current megafaunal community structures observed by SO242-2 within the DISCOL area, and the slow recovery rates of many taxa 26 years after the initial experimental disturbance, and provide images of the long term impact of experimental disturbances at the seafloor.

Relationships between sources of acid mine drainage and the hydrochemistry of acid effluents during rainy season in the Iberian Pyrite Belt.

PubMed

Pérez-Ostalé, E; Grande, J A; Valente, T; de la Torre, M L; Santisteban, M; Fernández, P; Diaz-Curiel, J

2016-01-01

In the Iberian Pyrite Belt (IPB), southwest Spain, a prolonged and intense mining activity of more than 4,500 years has resulted in almost a hundred mines scattered through the region. After years of inactivity, these mines are still causing high levels of hydrochemical degradation in the fluvial network. This situation represents a unique scenario in the world, taking into consideration its magnitude and intensity of the contamination processes. In order to obtain a benchmark regarding the degree of acid mine drainage (AMD) pollution in the aquatic environment, the relationship between the areas occupied by the sulfide mines and the characteristics of the respective effluents after rainfall was analysed. The methodology developed, which includes the design of a sampling network, analytical treatment and cluster analysis, is a useful tool for diagnosing the contamination level by AMD in an entire metallogenic province, at the scale of each mining group. The results presented the relationship between sulfate, total dissolved solids and electrical conductivity, as well as other parameters that are typically associated with AMD and the major elements that compose the polymetallic sulfides of IPB. This analysis also indicates the low level of proximity between the affectation area and the other variables.

Quantitative Analysis of Critical Factors for the Climate Impact of Landfill Mining.

PubMed

Laner, David; Cencic, Oliver; Svensson, Niclas; Krook, Joakim

2016-07-05

Landfill mining has been proposed as an innovative strategy to mitigate environmental risks associated with landfills, to recover secondary raw materials and energy from the deposited waste, and to enable high-valued land uses at the site. The present study quantitatively assesses the importance of specific factors and conditions for the net contribution of landfill mining to global warming using a novel, set-based modeling approach and provides policy recommendations for facilitating the development of projects contributing to global warming mitigation. Building on life-cycle assessment, scenario modeling and sensitivity analysis methods are used to identify critical factors for the climate impact of landfill mining. The net contributions to global warming of the scenarios range from -1550 (saving) to 640 (burden) kg CO2e per Mg of excavated waste. Nearly 90% of the results' total variation can be explained by changes in four factors, namely the landfill gas management in the reference case (i.e., alternative to mining the landfill), the background energy system, the composition of the excavated waste, and the applied waste-to-energy technology. Based on the analyses, circumstances under which landfill mining should be prioritized or not are identified and sensitive parameters for the climate impact assessment of landfill mining are highlighted.

Mining of Business-Oriented Conversations at a Call Center

NASA Astrophysics Data System (ADS)

Takeuchi, Hironori; Nasukawa, Tetsuya; Watanabe, Hideo

Recently it has become feasible to transcribe textual records from telephone conversations at call centers by using automatic speech recognition. In this research, we extended a text mining system for call summary records and constructed a conversation mining system for the business-oriented conversations at the call center. To acquire useful business insights from the conversational data through the text mining system, it is critical to identify appropriate textual segments and expressions as the viewpoints to focus on. In the analysis of call summary data using a text mining system, some experts defined the viewpoints for the analysis by looking at some sample records and by preparing the dictionaries based on frequent keywords in the sample dataset. However with conversations it is difficult to identify such viewpoints manually and in advance because the target data consists of complete transcripts that are often lengthy and redundant. In this research, we defined a model of the business-oriented conversations and proposed a mining method to identify segments that have impacts on the outcomes of the conversations and can then extract useful expressions in each of these identified segments. In the experiment, we processed the real datasets from a car rental service center and constructed a mining system. With this system, we show the effectiveness of the method based on the defined conversation model.

North Korean Protective Mine Warfare: An Analysis of the Naval Minefields at Wonsan, Chinnampo and Hungnam during the Korean War

DTIC Science & Technology

2010-04-01

the United States Navy and the general military history community as well. As a result, studies involving mine warfare have been neglected. In...that particular campaign. The Navy, lulled into a sense of complacency, has neglected mine warfare studies . Naval Intelligence has made little attempt...Farragut famously ignored the mineline there to destroy the Confederate fleet nearby. While extensive mining also occurred during World War One , the United

Particle damping applied research on mining dump truck vibration control

NASA Astrophysics Data System (ADS)

Song, Liming; Xiao, Wangqiang; Guo, Haiquan; Yang, Zhe; Li, Zeguang

2018-05-01

Vehicle vibration characteristics has become an important evaluation indexes of mining dump truck. In this paper, based on particle damping technology, mining dump truck vibration control was studied by combining the theoretical simulation with actual testing, particle damping technology was successfully used in mining dump truck cab vibration control. Through testing results analysis, with a particle damper, cab vibration was reduced obviously, the methods and basis were provided for vehicle vibration control research and particle damping technology application.

[Text mining, a method for computer-assisted analysis of scientific texts, demonstrated by an analysis of author networks].

PubMed

Hahn, P; Dullweber, F; Unglaub, F; Spies, C K

2014-06-01

Searching for relevant publications is becoming more difficult with the increasing number of scientific articles. Text mining as a specific form of computer-based data analysis may be helpful in this context. Highlighting relations between authors and finding relevant publications concerning a specific subject using text analysis programs are illustrated graphically by 2 performed examples. © Georg Thieme Verlag KG Stuttgart · New York.

TCGA4U: A Web-Based Genomic Analysis Platform To Explore And Mine TCGA Genomic Data For Translational Research.

PubMed

Huang, Zhenzhen; Duan, Huilong; Li, Haomin

2015-01-01

Large-scale human cancer genomics projects, such as TCGA, generated large genomics data for further study. Exploring and mining these data to obtain meaningful analysis results can help researchers find potential genomics alterations that intervene the development and metastasis of tumors. We developed a web-based gene analysis platform, named TCGA4U, which used statistics methods and models to help translational investigators explore, mine and visualize human cancer genomic characteristic information from the TCGA datasets. Furthermore, through Gene Ontology (GO) annotation and clinical data integration, the genomic data were transformed into biological process, molecular function, cellular component and survival curves to help researchers identify potential driver genes. Clinical researchers without expertise in data analysis will benefit from such a user-friendly genomic analysis platform.

COBRA ATD minefield detection model initial performance analysis

NASA Astrophysics Data System (ADS)

Holmes, V. Todd; Kenton, Arthur C.; Hilton, Russell J.; Witherspoon, Ned H.; Holloway, John H., Jr.

2000-08-01

A statistical performance analysis of the USMC Coastal Battlefield Reconnaissance and Analysis (COBRA) Minefield Detection (MFD) Model has been performed in support of the COBRA ATD Program under execution by the Naval Surface Warfare Center/Dahlgren Division/Coastal Systems Station . This analysis uses the Veridian ERIM International MFD model from the COBRA Sensor Performance Evaluation and Computational Tools for Research Analysis modeling toolbox and a collection of multispectral mine detection algorithm response distributions for mines and minelike clutter objects. These mine detection response distributions were generated form actual COBRA ATD test missions over littoral zone minefields. This analysis serves to validate both the utility and effectiveness of the COBRA MFD Model as a predictive MFD performance too. COBRA ATD minefield detection model algorithm performance results based on a simulate baseline minefield detection scenario are presented, as well as result of a MFD model algorithm parametric sensitivity study.

Thallium release from acid mine drainages: Speciation in river and tap water from Valdicastello mining district (northwest Tuscany).

PubMed

Campanella, Beatrice; Casiot, Corinne; Onor, Massimo; Perotti, Martina; Petrini, Riccardo; Bramanti, Emilia

2017-08-15

In this work we present an advantageous method for the simultaneous separation and detection of Tl(I) and Tl(III) species through ion chromatography coupled with on-line inductively coupled plasma - mass spectrometry. Chromatographic separation between Tl(III) and Tl(I) was achieved in less than two minutes. The method was validated by recovery experiments on real samples, and by comparing the sum of the concentrations of individual Tl species with total thallium values obtained from continuous flow ICP-MS. The experimental procedure offers an accurate, sensitive and interference-free method for Tl speciation at trace levels in environmental samples. This allowed us to investigate the Tl speciation in acid mine drainages (AMD), surface waters and springs in a mining catchment in Valdicastello Carducci (Tuscany, Italy), where severe Tl contamination ad been evidenced previously. This study shows for the first time that Tl(III), in addition to Tl(I), is present in considerable amounts in water samples affected by acid mining outflow, raising the question of the origin of this thermodynamically unstable species. Copyright © 2017 Elsevier B.V. All rights reserved.

Prediction of blast fragmentation of underground stopes for in situ leaching

DOE Office of Scientific and Technical Information (OSTI.GOV)

Stagg, M.S.; Otterness, R.E.; Djahanguiri, F.

1994-12-31

The US Bureau of Mines (USBM) evaluated empirical equations that predict fragmentation from underground stope rounds. Controlled blasting is necessary for creating leaching stopes that maximize the recovery and minimize backbreak of the perimeter wall. This paper presents the fragmentation results from one of the three drop-raise blasts used to develop a reduced-scale cylindrical stope, 1.8 m in diameter and 6 m in height. The stope is located in the Colorado School of Mines Experimental Mine (Edgar Mine) in Idaho Springs, Colorado. This stope is part of a USBM research effort to determine the feasibility of incorporating in situ leachingmore » of rubblized stopes into active underground metal and nonmetal mines. All the material from the first blast, 14 mtons was sieved. The resulting distribution was compared to the distribution predicted from empirical equations. The best fit was found with a USBM equation developed from over 50 sieved, reduced-scale (1- to 2-m) high wall blasts. Modifications to the equations were made to account for the observed differences due to breakout angle, shot geometry, initiation timing, decoupling, rock fracture toughness and explosive energy.« less

Evaluation of sulfidic mine tailings solidified/stabilized with cement kiln dust and fly ash to control acid mine drainage

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nehdi, M.; Tariq, A.

2008-11-15

In the present research, industrial byproducts, namely, cement kiln dust (CKD) and Class C fly ash (FAC) have been used as candidate materials along with the partial addition of sulfate-resistant cement (SRC) in the Stabilization/solidification of polymetallic sulfidic mine tailings (MT). The effectiveness of S/S was assessed by comparing laboratory experimental values obtained from unconfined compressive strength, hydraulic conductivity and leaching propensity tests of S/S samples with regulatory standards for safe surface disposal of such wastes. Despite general regulatory compliance of compressive strength and hydraulic conductivity, some solidified/stabilized-cured matrices were found unable to provide the required immobilization of pollutants. Solidified/stabilizedmore » and 90-day cured mine tailings specimens made with composite binders containing (10% CKD + 10% FAC), (5% SRC + 15% FAC) and (5% SRC + 5% CKD + 10% FAC) significantly impaired the solubility of all contaminants investigated and proved successful in fixing metals within the matrix, in addition to achieving adequate unconfined compressive strength and hydraulic conductivity values, thus satisfying USEPA regulations. Laboratory investigations revealed that, for polymetallic mining waste, leachate concentrations are the most critical factor in assessing the effectiveness of S/S technology.« less

Mining and Minerals Technical Advisory Committee on Curriculum Development. Job Clusters, Competencies and Task Analysis.

ERIC Educational Resources Information Center

Northern Montana Coll., Havre. Montana Center for Vocational Education, Research, Curriculum and Personnel Development.

This skills inventory for mining occupations was developed by a technical committee in Montana to assist in the development of model curricula and to address state labor market needs. The committee included employers from the mining industry, members of trade and professional associations, and educators. The validated task list and defined job…

A Quantitative Analysis of Organizational Factors That Relate to Data Mining Success

ERIC Educational Resources Information Center

Huebner, Richard A.

2017-01-01

The ubiquity of data in various forms has fueled the need for advanced data-mining techniques within organizations. The advent of data mining methods used to uncover hidden nuggets of information buried within large data sets has also fueled the need for determining how these unique projects can be successful. There are many challenges associated…

Numerical simulation study on the distribution law of smoke flow velocity in horizontal tunnel fire

NASA Astrophysics Data System (ADS)

Liu, Yejiao; Tian, Zhichao; Xue, Junhua; Wang, Wencai

2018-02-01

According to the fluid similarity theory, the simulation experiment system of mining tunnel fire is established. The grid division of experimental model roadway is carried on by GAMBIT software. By setting the boundary and initial conditions of smoke flow during fire period in FLUENT software, using RNG k-Ɛ two-equation turbulence model, energy equation and SIMPLE algorithm, the steady state numerical simulation of smoke flow velocity in mining tunnel is done to obtain the distribution law of smoke flow velocity in tunnel during fire period.

Hydraulic fracturing stress measurement in underground salt rock mines at Upper Kama Deposit

NASA Astrophysics Data System (ADS)

Rubtsova, EV; Skulkin, AA

2018-03-01

The paper reports the experimental results on hydraulic fracturing in-situ stress measurements in potash mines of Uralkali. The selected HF procedure, as well as locations and designs of measuring points are substantiated. From the evidence of 78 HF stress measurement tests at eight measuring points, it has been found that the in-situ stress field is nonequicomponent, with the vertical stresses having value close to the estimates obtained with respect to the overlying rock weight while the horizontal stresses exceed the gravity stresses by 2–3 times.

Mining Feature of Data Fusion in the Classification of Beer Flavor Information Using E-Tongue and E-Nose

PubMed Central

Men, Hong; Shi, Yan; Fu, Songlin; Jiao, Yanan; Qiao, Yu; Liu, Jingjing

2017-01-01

Multi-sensor data fusion can provide more comprehensive and more accurate analysis results. However, it also brings some redundant information, which is an important issue with respect to finding a feature-mining method for intuitive and efficient analysis. This paper demonstrates a feature-mining method based on variable accumulation to find the best expression form and variables’ behavior affecting beer flavor. First, e-tongue and e-nose were used to gather the taste and olfactory information of beer, respectively. Second, principal component analysis (PCA), genetic algorithm-partial least squares (GA-PLS), and variable importance of projection (VIP) scores were applied to select feature variables of the original fusion set. Finally, the classification models based on support vector machine (SVM), random forests (RF), and extreme learning machine (ELM) were established to evaluate the efficiency of the feature-mining method. The result shows that the feature-mining method based on variable accumulation obtains the main feature affecting beer flavor information, and the best classification performance for the SVM, RF, and ELM models with 96.67%, 94.44%, and 98.33% prediction accuracy, respectively. PMID:28753917

Influence of the Roof Movement Control Method on the Stability of Remnant

NASA Astrophysics Data System (ADS)

Adach-Pawelus, Karolina

2017-12-01

In the underground mines, there are geological and mining situations that necessitate leaving behind remnants in the mining field. Remnants, in the form of small, irregular parcels, are usually separated in the case of: significant problems with maintaining roof stability, high rockburst hazard, the occurrence of complex geological conditions and for random reasons (ore remnants), as well as for economic reasons (undisturbed rock remnants). Remnants left in the mining field become sites of high stress values concentration and may affect the rock in their vicinity. The values of stress inside the remnant and its vicinity, as well as the stability of the remnant, largely depend on the roof movement control method used in the mining field. The article presents the results of the numerical analysis of the influence of roof movement control method on remnant stability and the geomechanical situation in the mining field. The numerical analysis was conducted for the geological and mining conditions characteristic of Polish underground copper mines owned by KGHM Polska Miedz S.A. Numerical simulations were performed in a plane strain state by means of Phase 2 v. 8.0 software, based on the finite element method. The behaviour of remnant and rock mass in its vicinity was simulated in the subsequent steps of the room and pillar mining system for three types of roof movement control method: roof deflection, dry backfill and hydraulic backfill. The parameters of the rock mass accepted for numerical modelling were calculated by means of RocLab software on the basis of the Hoek-Brown classification. The Mohr-Coulomb strength criterion was applied.

Effects of anthropogenic heavy metal contamination on litter decomposition in streams - A meta-analysis.

PubMed

Ferreira, Verónica; Koricheva, Julia; Duarte, Sofia; Niyogi, Dev K; Guérold, François

2016-03-01

Many streams worldwide are affected by heavy metal contamination, mostly due to past and present mining activities. Here we present a meta-analysis of 38 studies (reporting 133 cases) published between 1978 and 2014 that reported the effects of heavy metal contamination on the decomposition of terrestrial litter in running waters. Overall, heavy metal contamination significantly inhibited litter decomposition. The effect was stronger for laboratory than for field studies, likely due to better control of confounding variables in the former, antagonistic interactions between metals and other environmental variables in the latter or differences in metal identity and concentration between studies. For laboratory studies, only copper + zinc mixtures significantly inhibited litter decomposition, while no significant effects were found for silver, aluminum, cadmium or zinc considered individually. For field studies, coal and metal mine drainage strongly inhibited litter decomposition, while drainage from motorways had no significant effects. The effect of coal mine drainage did not depend on drainage pH. Coal mine drainage negatively affected leaf litter decomposition independently of leaf litter identity; no significant effect was found for wood decomposition, but sample size was low. Considering metal mine drainage, arsenic mines had a stronger negative effect on leaf litter decomposition than gold or pyrite mines. Metal mine drainage significantly inhibited leaf litter decomposition driven by both microbes and invertebrates, independently of leaf litter identity; no significant effect was found for microbially driven decomposition, but sample size was low. Overall, mine drainage negatively affects leaf litter decomposition, likely through negative effects on invertebrates. Copyright © 2015 Elsevier Ltd. All rights reserved.

2. North (side) and west (front) elevations, view to south ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

2. North (side) and west (front) elevations, view to south - Bureau of Mines Boulder City Experimental Station, Titanium Research Building, Date Street north of U.S. Highway 93, Boulder City, Clark County, NV

3. South (side) and east (rear) elevations, view to northwest ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

3. South (side) and east (rear) elevations, view to northwest - Bureau of Mines Boulder City Experimental Station, Titanium Research Building, Date Street north of U.S. Highway 93, Boulder City, Clark County, NV

Evaluation of copper resistant bacteria from vineyard soils and mining waste for copper biosorption

PubMed Central

Andreazza, R.; Pieniz, S.; Okeke, B.C.; Camargo, F.A.O

2011-01-01

Vineyard soils are frequently polluted with high concentrations of copper due application of copper sulfate in order to control fungal diseases. Bioremediation is an efficient process for the treatment of contaminated sites. Efficient copper sorption bacteria can be used for bioremoval of copper from contaminated sites. In this study, a total of 106 copper resistant bacteria were examined for resistance to copper toxicity and biosorption of copper. Eighty isolates (45 from vineyard Mollisol, 35 from Inceptisol) were obtained from EMBRAPA (Empresa Brasileira de Pesquisa Agropecuária) experimental station, Bento Gonçalves, RS, Brazil (29°09′53.92″S and 51°31′39.40″W) and 26 were obtained from copper mining waste from Caçapava do Sul, RS, Brazil (30°29′43.48″S and 53′32′37.87W). Based on resistance to copper toxicity and biosorption, 15 isolates were identified by 16S rRNA gene sequencing. Maximal copper resistance and biosorption at high copper concentration were observed with isolate N2 which removed 80 mg L−1 in 24 h. Contrarily isolate N11 (Bacillus pumilus) displayed the highest specific copper biosorption (121.82 mg/L/OD unit in 24 h). GenBank MEGABLAST analysis revealed that isolate N2 is 99% similar to Staphylococcus pasteuri. Results indicate that several of our isolates have potential use for bioremediation treatment of vineyards soils and mining waste contaminated with high copper concentration. PMID:24031606

What Satisfies Students?: Mining Student-Opinion Data with Regression and Decision Tree Analysis

ERIC Educational Resources Information Center

Thomas, Emily H.; Galambos, Nora

2004-01-01

To investigate how students' characteristics and experiences affect satisfaction, this study uses regression and decision tree analysis with the CHAID algorithm to analyze student-opinion data. A data mining approach identifies the specific aspects of students' university experience that most influence three measures of general satisfaction. The…

An application of data mining in district heating substations for improving energy performance

NASA Astrophysics Data System (ADS)

Xue, Puning; Zhou, Zhigang; Chen, Xin; Liu, Jing

2017-11-01

Automatic meter reading system is capable of collecting and storing a huge number of district heating (DH) data. However, the data obtained are rarely fully utilized. Data mining is a promising technology to discover potential interesting knowledge from vast data. This paper applies data mining methods to analyse the massive data for improving energy performance of DH substation. The technical approach contains three steps: data selection, cluster analysis and association rule mining (ARM). Two-heating-season data of a substation are used for case study. Cluster analysis identifies six distinct heating patterns based on the primary heat of the substation. ARM reveals that secondary pressure difference and secondary flow rate have a strong correlation. Using the discovered rules, a fault occurring in remote flow meter installed at secondary network is detected accurately. The application demonstrates that data mining techniques can effectively extrapolate potential useful knowledge to better understand substation operation strategies and improve substation energy performance.

A concept for the modernization of underground mining master maps based on the enrichment of data definitions and spatial database technology

NASA Astrophysics Data System (ADS)

Krawczyk, Artur

2018-01-01

In this article, topics regarding the technical and legal aspects of creating digital underground mining maps are described. Currently used technologies and solutions for creating, storing and making digital maps accessible are described in the context of the Polish mining industry. Also, some problems with the use of these technologies are identified and described. One of the identified problems is the need to expand the range of mining map data provided by survey departments to other mining departments, such as ventilation maintenance or geological maintenance. Three solutions are proposed and analyzed, and one is chosen for further analysis. The analysis concerns data storage and making survey data accessible not only from paper documentation, but also directly from computer systems. Based on enrichment data, new processing procedures are proposed for a new way of presenting information that allows the preparation of new cartographic representations (symbols) of data with regard to users' needs.

Preliminary results of sequential extraction experiments for selenium on mine waste and stream sediments from Vermont, Maine, and New Zealand

USGS Publications Warehouse

Piatak, N.M.; Seal, R.R.; Sanzolone, R.F.; Lamothe, P.J.; Brown, Z.A.

2006-01-01

We report the preliminary results of sequential partial dissolutions used to characterize the geochemical distribution of selenium in stream sediments, mine wastes, and flotation-mill tailings. In general, extraction schemes are designed to extract metals associated with operationally defined solid phases. Total Se concentrations and the mineralogy of the samples are also presented. Samples were obtained from the Elizabeth, Ely, and Pike Hill mines in Vermont, the Callahan mine in Maine, and the Martha mine in New Zealand. These data are presented here with minimal interpretation or discussion. Further analysis of the data will be presented elsewhere.

LANDSAT inventory of surface-mined areas using extendible digital techniques

NASA Technical Reports Server (NTRS)

Anderson, A. T.; Schultz, D. T.; Buchman, N.

1975-01-01

Multispectral LANDSAT imagery was analyzed to provide a rapid and accurate means of identification, classification, and measurement of strip-mined surfaces in Western Maryland. Four band analysis allows distinction of a variety of strip-mine associated classes, but has limited extendibility. A method for surface area measurements of strip mines, which is both geographically and temporally extendible, has been developed using band-ratioed LANDSAT reflectance data. The accuracy of area measurement by this method, averaged over three LANDSAT scenes taken between September 1972 and July 1974, is greater than 93%. Total affected acreage of large (50 hectare/124 acre) mines can be measured to within 1.0%.

Open-source tools for data mining.

PubMed

Zupan, Blaz; Demsar, Janez

2008-03-01

With a growing volume of biomedical databases and repositories, the need to develop a set of tools to address their analysis and support knowledge discovery is becoming acute. The data mining community has developed a substantial set of techniques for computational treatment of these data. In this article, we discuss the evolution of open-source toolboxes that data mining researchers and enthusiasts have developed over the span of a few decades and review several currently available open-source data mining suites. The approaches we review are diverse in data mining methods and user interfaces and also demonstrate that the field and its tools are ready to be fully exploited in biomedical research.

Spatial Temporal Analysis Of Mine-induced Seismicity

NASA Astrophysics Data System (ADS)

Fedotova, I. V.; Yunga, S. L.

The results of analysis of influence mine-induced seismicity on state of stress of a rock mass are represented. The spatial-temporal analysis of influence of mass explosions on rock massif deformation is carried out in the territory of a mine field Yukspor of a wing of the Joined Kirovsk mine JSC "Apatite". Estimation of influence of mass explosions on a massif were determined based firstly on the parameters of natural seismicic regime, and secondly taking into consideration change of seismic energy release. After long series of explosions variations in average number of seismic events was fixed. Is proved, that with increase of a volume of rocks, involved in a deforma- tion the released energy of seismic events, and characteristic intervals of time of their preparation are also varied. At the same time, the mechanism of destruction changes also: from destruction's, of a type shift - separation before destruction's, in a quasi- solid heterogeneous massif (in oxidized zones and zones of actuated faults). Analysis of a database seismicity of a massif from 1993 to 1999 years has confirmed, that the response of a massif on explosions is connected to stress-deformations state a mas- sif and parameters of a mining working. The analysis of spatial-temporal distribution of hypocenters of seismic events has allowed to allocate migration of fissile regions of destruction after mass explosions. The researches are executed at support of the Russian foundation for basic research, - projects 00-05-64758, 01-05-65340.

Data Analysis and Data Mining: Current Issues in Biomedical Informatics

PubMed Central

Bellazzi, Riccardo; Diomidous, Marianna; Sarkar, Indra Neil; Takabayashi, Katsuhiko; Ziegler, Andreas; McCray, Alexa T.

2011-01-01

Summary Background Medicine and biomedical sciences have become data-intensive fields, which, at the same time, enable the application of data-driven approaches and require sophisticated data analysis and data mining methods. Biomedical informatics provides a proper interdisciplinary context to integrate data and knowledge when processing available information, with the aim of giving effective decision-making support in clinics and translational research. Objectives To reflect on different perspectives related to the role of data analysis and data mining in biomedical informatics. Methods On the occasion of the 50th year of Methods of Information in Medicine a symposium was organized, that reflected on opportunities, challenges and priorities of organizing, representing and analysing data, information and knowledge in biomedicine and health care. The contributions of experts with a variety of backgrounds in the area of biomedical data analysis have been collected as one outcome of this symposium, in order to provide a broad, though coherent, overview of some of the most interesting aspects of the field. Results The paper presents sections on data accumulation and data-driven approaches in medical informatics, data and knowledge integration, statistical issues for the evaluation of data mining models, translational bioinformatics and bioinformatics aspects of genetic epidemiology. Conclusions Biomedical informatics represents a natural framework to properly and effectively apply data analysis and data mining methods in a decision-making context. In the future, it will be necessary to preserve the inclusive nature of the field and to foster an increasing sharing of data and methods between researchers. PMID:22146916

Black Thunder Coal Mine and Los Alamos National Laboratory experimental study of seismic energy generated by large scale mine blasting

DOE Office of Scientific and Technical Information (OSTI.GOV)

Martin, R.L.; Gross, D.; Pearson, D.C.

In an attempt to better understand the impact that large mining shots will have on verifying compliance with the international, worldwide, Comprehensive Test Ban Treaty (CTBT, no nuclear explosion tests), a series of seismic and videographic experiments has been conducted during the past two years at the Black Thunder Coal Mine. Personnel from the mine and Los Alamos National Laboratory have cooperated closely to design and perform experiments to produce results with mutual benefit to both organizations. This paper summarizes the activities, highlighting the unique results of each. Topics which were covered in these experiments include: (1) synthesis of seismic,more » videographic, acoustic, and computer modeling data to improve understanding of shot performance and phenomenology; (2) development of computer generated visualizations of observed blasting techniques; (3) documentation of azimuthal variations in radiation of seismic energy from overburden casting shots; (4) identification of, as yet unexplained, out of sequence, simultaneous detonation in some shots using seismic and videographic techniques; (5) comparison of local (0.1 to 15 kilometer range) and regional (100 to 2,000 kilometer range) seismic measurements leading to determine of the relationship between local and regional seismic amplitude to explosive yield for overburden cast, coal bulking and single fired explosions; and (6) determination of the types of mining shots triggering the prototype International Monitoring System for the CTBT.« less

Coal supply and cost under technological and environmental uncertainty

NASA Astrophysics Data System (ADS)

Chan, Melissa

This thesis estimates available coal resources, recoverability, mining costs, environmental impacts, and environmental control costs for the United States under technological and environmental uncertainty. It argues for a comprehensive, well-planned research program that will resolve resource uncertainty, and innovate new technologies to improve recovery and environmental performance. A stochastic process and cost (constant 2005) model for longwall, continuous, and surface mines based on current technology and mining practice data was constructed. It estimates production and cost ranges within 5-11 percent of 2006 prices and production rates. The model was applied to the National Coal Resource Assessment. Assuming the cheapest mining method is chosen to extract coal, 250-320 billion tons are recoverable. Two-thirds to all coal resource can be mined at a cost less than 4/mmBTU. If U.S. coal demand substantially increases, as projected by alternate Energy Information Administration (EIA), resources might not last more than 100 years. By scheduling cost to meet EIA projected demand, estimated cost uncertainty increases over time. It costs less than 15/ton to mine in the first 10 years of a 100 year time period, 10-30/ton in the following 50 years, and 15-$90/ton thereafter. Environmental impacts assessed are subsidence from underground mines, surface mine pit area, erosion, acid mine drainage, air pollutant and methane emissions. The analysis reveals that environmental impacts are significant and increasing as coal demand increases. Control technologies recommended to reduce these impacts are backfilling underground mines, surface pit reclamation, substitution of robotic underground mining systems for surface pit mining, soil replacement for erosion, placing barriers between exposed coal and the elements to avoid acid formation, and coalbed methane development to avoid methane emissions during mining. The costs to apply these technologies to meet more stringent environmental regulation scenarios are estimated. The results show that the cost of meeting these regulatory scenarios could increase mining costs two to six times the business as usual cost, which could significantly affect the cost of coal-powered electricity generation. This thesis provides a first estimate of resource availability, mining cost, and environmental impact assessment and cost analysis. Available resource is not completely reported, so the available estimate is lower than actual resource. Mining costs are optimized, so provide a low estimate of potential costs. Environmental impact estimates are on the high end of potential impact that may be incurred because it is assumed that impact is unavoidable. Control costs vary. Estimated cost to control subsidence and surface mine pit impacts are suitable estimates of the cost to reduce land impacts. Erosion control and robotic mining system costs are lower, and methane and acid mine drainage control costs are higher, than they may be in the case that these impacts must be reduced.

Computational Analysis of Mine Blast on a Commercial Vehicle Structure

DTIC Science & Technology

2007-01-01

ANALYSIS OF MINE BLAST ON A COMMERCIAL VEHICLE STRUCTURE M. Grujicic 1∗ , B. Pandurangan 1 , I. Haque 1 , B. A. Cheeseman 2 , W. N. Roy 2 and R. R. Skaggs...buried in (either dry or saturated sand) underneath the vehicle’s front right wheel is analyzed computationally. The computational analysis included the...A frequency analysis of the pressure versus time signals and visual observation clearly show the differences in the blast loads resulting from the

Integrated Computational and Experimental Protocol for Understanding Rh(III) Speciation in Hydrochloric and Nitric Acid Solutions

DOE Office of Scientific and Technical Information (OSTI.GOV)

Samuels, Alex C.; Boele, Cherilynn A.; Bennett, Kevin T.

2014-12-01

A combined experimental and theoretical approach has investigated the complex speciation of Rh(III) in hydrochloric and nitric acid media, as a function of acid concentration. This has relevance to the separation and isolation of Rh(III) from dissolved spent nuclear fuel, which is an emergent and attractive alternative source of platinum group metals, relative to traditional mining efforts.

Who Says Your Frames Are Better than Mine? Making the Case for Strategic Framing by Using the Power of Experimental Research

ERIC Educational Resources Information Center

Manuel, Tiffany

2009-01-01

This article details the experimental research on frame effects that provides quantitative evidence that some types of frames have a greater ability to move and affect policy support than others. This method is particularly useful in showing the magnitude by which exposure to alternative ways of thinking about social issues alters the public's…

Online Analytical Processing (OLAP): A Fast and Effective Data Mining Tool for Gene Expression Databases

PubMed Central

2005-01-01

Gene expression databases contain a wealth of information, but current data mining tools are limited in their speed and effectiveness in extracting meaningful biological knowledge from them. Online analytical processing (OLAP) can be used as a supplement to cluster analysis for fast and effective data mining of gene expression databases. We used Analysis Services 2000, a product that ships with SQLServer2000, to construct an OLAP cube that was used to mine a time series experiment designed to identify genes associated with resistance of soybean to the soybean cyst nematode, a devastating pest of soybean. The data for these experiments is stored in the soybean genomics and microarray database (SGMD). A number of candidate resistance genes and pathways were found. Compared to traditional cluster analysis of gene expression data, OLAP was more effective and faster in finding biologically meaningful information. OLAP is available from a number of vendors and can work with any relational database management system through OLE DB. PMID:16046824

Applied Behavior Analysis Is Ideal for the Development of a Land Mine Detection Technology Using Animals

ERIC Educational Resources Information Center

Jones, B. M.

2011-01-01

The detection and subsequent removal of land mines and unexploded ordnance (UXO) from many developing countries are slow, expensive, and dangerous tasks, but have the potential to improve the well-being of millions of people. Consequently, those involved with humanitarian mine and UXO clearance are actively searching for new and more efficient…

Analysis of Occupational Accidents in Underground and Surface Mining in Spain Using Data-Mining Techniques

PubMed Central

Sanmiquel, Lluís; Bascompta, Marc; Rossell, Josep M.; Anticoi, Hernán Francisco; Guash, Eduard

2018-01-01

An analysis of occupational accidents in the mining sector was conducted using the data from the Spanish Ministry of Employment and Social Safety between 2005 and 2015, and data-mining techniques were applied. Data was processed with the software Weka. Two scenarios were chosen from the accidents database: surface and underground mining. The most important variables involved in occupational accidents and their association rules were determined. These rules are composed of several predictor variables that cause accidents, defining its characteristics and context. This study exposes the 20 most important association rules in the sector—either surface or underground mining—based on the statistical confidence levels of each rule as obtained by Weka. The outcomes display the most typical immediate causes, along with the percentage of accidents with a basis in each association rule. The most important immediate cause is body movement with physical effort or overexertion, and the type of accident is physical effort or overexertion. On the other hand, the second most important immediate cause and type of accident are different between the two scenarios. Data-mining techniques were chosen as a useful tool to find out the root cause of the accidents. PMID:29518921

Research of mine water source identification based on LIF technology

NASA Astrophysics Data System (ADS)

Zhou, Mengran; Yan, Pengcheng

2016-09-01

According to the problem that traditional chemical methods to the mine water source identification takes a long time, put forward a method for rapid source identification system of mine water inrush based on the technology of laser induced fluorescence (LIF). Emphatically analyzes the basic principle of LIF technology. The hardware composition of LIF system are analyzed and the related modules were selected. Through the fluorescence experiment with the water samples of coal mine in the LIF system, fluorescence spectra of water samples are got. Traditional water source identification mainly according to the ion concentration representative of the water, but it is hard to analysis the ion concentration of the water from the fluorescence spectra. This paper proposes a simple and practical method of rapid identification of water by fluorescence spectrum, which measure the space distance between unknown water samples and standard samples, and then based on the clustering analysis, the category of the unknown water sample can be get. Water source identification for unknown samples verified the reliability of the LIF system, and solve the problem that the current coal mine can't have a better real-time and online monitoring on water inrush, which is of great significance for coal mine safety in production.

Energy saving analysis on mine-water source heat pump in a residential district of Henan province, central China

NASA Astrophysics Data System (ADS)

Wang, Hong; Duan, Huanlin; Chen, Aidong

2018-02-01

In this paper, the mine-water source heat pump system is proposed in residential buildings of a mining community. The coefficient of performance (COP) and the efficiency of exergy are analyzed. The results show that the COP and exergy efficiency of the mine-water source heat pump are improved, the exergy efficiency of mine-water source heat pump is more than 10% higher than that of the air source heat pump.The electric power conservation measure of “peak load shifting” is also emphasized in this article. It shows that itis a very considerable cost in the electric saving by adopting the trough period electricity to produce hot water. Due to the proper temperature of mine water, the mine-watersource heat pump unit is more efficient and stable in performance, which further shows the advantage of mine-water source heat pump in energy saving and environmental protection. It provides reference to the design of similar heat pump system as well.

Monitoring of environmental effects of coal strip mining from satellite imagery

NASA Technical Reports Server (NTRS)

Brooks, R. L.; Parra, C. G.

1976-01-01

This paper evaluates satellite imagery as a means of monitoring coal strip mines and their environmental effects. The satellite imagery employed is Skylab EREP S-190A and S-190B from SL-2, SL-3 and SL-4 missions; a large variety of camera/film/filter combinations has been reviewed. The investigation includes determining the applicability of satellite imagery for detection of disturbed acreage in areas of coal surface mining as well as the much more detailed monitoring of specific surface-mining operations, including: active mines, inactive mines, highwalls, ramp roads, pits, water impoundments and their associated acidity, graded areas and types of grading, and reclamed areas. Techniques have been developed to enable mining personnel to utilize this imagery in a practical and economic manner, requiring no previous photo-interpretation background and no purchases of expensive viewing or data-analysis equipment. To corroborate the photo-interpretation results, on-site observations were made in the very active mining area near Madisonville, Kentucky.

The non-participation of organic sulphur in acid mine drainage generation

USGS Publications Warehouse

Casagrande, D.J.; Finkelman, R.B.; Caruccio, F.T.

1989-01-01

Acid mine drainage is commonly associated with land disturbances that encounter and expose iron sulphides to oxidising atmospheric conditions. The attendant acidic conditions solubilise a host of trace metals. Within this flow regime the potential exists to contaminate surface drinking water supplies with a variety of trace materials. Accordingly, in evaluating the applications for mines located in the headwaters of water sheds, the pre-mining prediction of the occurrence of acid mine drainage is of paramount importance. There is general agreement among investigators that coal organic sulphur is a nonparticipant in acid mine drainage generation; however, there is no scientific documentation to support this concensus. Using simulated weathering, kinetic, mass balance, petrographic analysis and a peroxide oxidation procedure, coal organic sulphur is shown to be a nonparticipant in acid mine drainage generation. Calculations for assessing the acid-generating potential of a sedimentary rock should not include organic sulphur content. ?? 1989 Sciences and Technology Letters.

A probabilistic approach for mine burial prediction

NASA Astrophysics Data System (ADS)

Barbu, Costin; Valent, Philip; Richardson, Michael; Abelev, Andrei; Plant, Nathaniel

2004-09-01

Predicting the degree of burial of mines in soft sediments is one of the main concerns of Naval Mine CounterMeasures (MCM) operations. This is a difficult problem to solve due to uncertainties and variability of the sediment parameters (i.e., density and shear strength) and of the mine state at contact with the seafloor (i.e., vertical and horizontal velocity, angular rotation rate, and pitch angle at the mudline). A stochastic approach is proposed in this paper to better incorporate the dynamic nature of free-falling cylindrical mines in the modeling of impact burial. The orientation, trajectory and velocity of cylindrical mines, after about 4 meters free-fall in the water column, are very strongly influenced by boundary layer effects causing quite chaotic behavior. The model's convolution of the uncertainty through its nonlinearity is addressed by employing Monte Carlo simulations. Finally a risk analysis based on the probability of encountering an undetectable mine is performed.

Determination of Abutment Pressure in Coal Mines with Extremely Thick Alluvium Stratum: A Typical Kind of Rockburst Mines in China

NASA Astrophysics Data System (ADS)

Zhu, Sitao; Feng, Yu; Jiang, Fuxing

2016-05-01

This paper investigates the abutment pressure distribution in coal mines with extremely thick alluvium stratum (ETAS), which is a typical kind of mines encountering frequent intense rockbursts in China. This occurs due to poor understanding to abutment pressure distribution pattern and the consequent inappropriate mine design. In this study, a theoretical computational model of abutment pressure for ETAS longwall panels is proposed based on the analysis of load transfer mechanisms of key stratum (KS) and ETAS. The model was applied to determine the abutment pressure distribution of LW2302S in Xinjulong Coal Mine; the results of stress and microseismic monitoring verified the rationality of this model. The calculated abutment pressure of LW2302S was also used in the terminal mining line design of LW2301N for rockburst prevention, successfully protecting the main roadway from the adverse influence of the abutment pressure.

Mining injuries in Serbian underground coal mines -- a 10-year study.

PubMed

Stojadinović, Saša; Svrkota, Igor; Petrović, Dejan; Denić, Miodrag; Pantović, Radoje; Milić, Vitomir

2012-12-01

Mining, especially underground coal mining, has always been a dangerous occupation. Injuries, unfortunately, even those resulting in death, are one of the major occupational risks that all miners live with. Despite the fact that all workers are aware of the risk, efforts must be and are being made to increase the safety of mines. Injury monitoring and data analysis can provide us with valuable data on the causes of accidents and enable us to establish a correlation between the conditions in the work environment and the number of injuries, which can further lead to proper preventive measures. This article presents the data on the injuries in Serbian coal mines during a 10-year period (2000-2009). The presented results are only part of an ongoing study whose aim is to assess the safety conditions in Serbian coal mines and classify them according to that assessment. Copyright © 2011 Elsevier Ltd. All rights reserved.

Application and Exploration of Big Data Mining in Clinical Medicine

PubMed Central

Zhang, Yue; Guo, Shu-Li; Han, Li-Na; Li, Tie-Ling

2016-01-01

Objective: To review theories and technologies of big data mining and their application in clinical medicine. Data Sources: Literatures published in English or Chinese regarding theories and technologies of big data mining and the concrete applications of data mining technology in clinical medicine were obtained from PubMed and Chinese Hospital Knowledge Database from 1975 to 2015. Study Selection: Original articles regarding big data mining theory/technology and big data mining's application in the medical field were selected. Results: This review characterized the basic theories and technologies of big data mining including fuzzy theory, rough set theory, cloud theory, Dempster–Shafer theory, artificial neural network, genetic algorithm, inductive learning theory, Bayesian network, decision tree, pattern recognition, high-performance computing, and statistical analysis. The application of big data mining in clinical medicine was analyzed in the fields of disease risk assessment, clinical decision support, prediction of disease development, guidance of rational use of drugs, medical management, and evidence-based medicine. Conclusion: Big data mining has the potential to play an important role in clinical medicine. PMID:26960378

Interstitial Lung Diseases in the U.S. Mining Industry: Using MSHA Data to Examine Trends and the Prevention Effects of Compliance with Health Regulations, 1996-2015.

PubMed

Yorio, Patrick L; Laney, A Scott; Halldin, Cara N; Blackley, David J; Moore, Susan M; Wizner, Kerri; Radonovich, Lewis J; Greenawald, Lee A

2018-04-12

Given the recent increase in dust-induced lung disease among U.S. coal miners and the respiratory hazards encountered across the U.S. mining industry, it is important to enhance an understanding of lung disease trends and the organizational contexts that precede these events. In addition to exploring overall trends reported to the Mine Safety and Health Administration (MSHA), the current study uses MSHA's enforcement database to examine whether or not compliance with health regulations resulted in fewer mine-level counts of these diseases over time. The findings suggest that interstitial lung diseases were more prevalent in coal mines compared to other mining commodities, in Appalachian coal mines compared to the rest of the United States, and in underground compared to surface coal mines. Mines that followed a relevant subset of MSHA's health regulations were less likely to report a lung disease over time. The findings are discussed from a lung disease prevention strategy perspective. © 2018 Society for Risk Analysis.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Goodman, P.S.

The report examines coal-miner absenteeism and its relationship to accidents and injuries at underground mines. A total of 19 mines participated in various phases of this 3-year project. Miners at the participating mines ranged in number from 185 to 776. The data consisted of the mines' daily attendance records and detailed interviews with approximately 50 miners from each mine. The interviews contained questions about the miners' satisfaction with various on-the-job and off-the-job factors, their perceptions of the mines' absenteeism policies, the reasons or causes for their own absences, and the miners' demographic characteristics. Accident and injury data from six minesmore » were used in parametric and multiple regression analysis of the absenteeism-accident relationship. The data represented activity during approximately 80,000 miner-days worked. Strategies for reducing absenteeism are discussed.« less

Trace elements biomonitoring in a historical mining district (les Malines, France).

PubMed

Saunier, Jean-Baptiste; Losfeld, Guillaume; Freydier, Rémi; Grison, Claude

2013-11-01

The aim of this study is to investigate the trace elements (TE) contents of potential biomonitors in a historical Zn-Pb mining district: apiary products (honey, royal-jelly and beeswax) lichen and moss were sampled and analysed. In spite of high TE concentrations in mining waste and soil, apiary products are free of TE contamination originating from historical mining. Lichen/moss show high TE levels, which suggest atmospheric input of local dust. Pb isotopes analysis proved the origin of TE found in lichen/moss to be mainly mining waste. These results help discuss the choice of relevant organisms for monitoring TE in the environment and bring additional data on the potential impacts of brownfields left after mining, especially on food products from apiaries. Copyright © 2013 Elsevier Ltd. All rights reserved.

RAIN: RNA–protein Association and Interaction Networks

PubMed Central

Junge, Alexander; Refsgaard, Jan C.; Garde, Christian; Pan, Xiaoyong; Santos, Alberto; Alkan, Ferhat; Anthon, Christian; von Mering, Christian; Workman, Christopher T.; Jensen, Lars Juhl; Gorodkin, Jan

2017-01-01

Protein association networks can be inferred from a range of resources including experimental data, literature mining and computational predictions. These types of evidence are emerging for non-coding RNAs (ncRNAs) as well. However, integration of ncRNAs into protein association networks is challenging due to data heterogeneity. Here, we present a database of ncRNA–RNA and ncRNA–protein interactions and its integration with the STRING database of protein–protein interactions. These ncRNA associations cover four organisms and have been established from curated examples, experimental data, interaction predictions and automatic literature mining. RAIN uses an integrative scoring scheme to assign a confidence score to each interaction. We demonstrate that RAIN outperforms the underlying microRNA-target predictions in inferring ncRNA interactions. RAIN can be operated through an easily accessible web interface and all interaction data can be downloaded. Database URL: http://rth.dk/resources/rain PMID:28077569

Survey of existing underground openings for in-situ experimental facilities

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wollenberg, H.; Graf, A.; Strisower, B.

1981-07-01

In an earlier project, a literature search identified 60 underground openings in crystalline rock capable of providing access for an in-situ experimental facility to develop geochemical and hydrological techniques for evaluating sites for radioactive waste isolation. As part of the current project, discussions with state geologists, owners, and operators narrowed the original group to 14. Three additional sites in volcanic rock and one site in granite were also identified. Site visits and application of technical criteria, including the geologic and hydrologic settings and depth, extent of the rock unit, condition, and accessibility of underground workings, determined four primary candidate sites:more » the Helms Pumped Storage Project in grandiodorite of the Sierra Nevada, California; the Tungsten Queen Mine in Precambrian granodiorite of the North Carolina Piedmont; the Mount Hope Mine in Precambrian granite and gneiss of northern New Jersey; and the Minnamax Project in the Duluth gabbro complex of northern Minnesota.« less

Determination of Destress Blasting Effectiveness Using Seismic Source Parameters

NASA Astrophysics Data System (ADS)

Wojtecki, Łukasz; Mendecki, Maciej J.; Zuberek, Wacaław M.

2017-12-01

Underground mining of coal seams in the Upper Silesian Coal Basin is currently performed under difficult geological and mining conditions. The mining depth, dislocations (faults and folds) and mining remnants are responsible for rockburst hazard in the highest degree. This hazard can be minimized by using active rockburst prevention, where destress blastings play an important role. Destress blastings in coal seams aim to destress the local stress concentrations. These blastings are usually performed from the longwall face to decrease the stress level ahead of the longwall. An accurate estimation of active rockburst prevention effectiveness is important during mining under disadvantageous geological and mining conditions, which affect the risk of rockburst. Seismic source parameters characterize the focus of tremor, which may be useful in estimating the destress blasting effects. Investigated destress blastings were performed in coal seam no. 507 during its longwall mining in one of the coal mines in the Upper Silesian Coal Basin under difficult geological and mining conditions. The seismic source parameters of the provoked tremors were calculated. The presented preliminary investigations enable a rapid estimation of the destress blasting effectiveness using seismic source parameters, but further analysis in other geological and mining conditions with other blasting parameters is required.

Safety survey of Iran's mines and comparison to some other countries.

PubMed

Bagherpour, Raheb; Yarahmadi, Reza; Khademian, Amir; Almasi, Seied Najmedin

2017-03-01

The increasing development of mining activities in Iran makes it necessary to have a closer look at the safety issues. Analysis of different incidents and damages in mines can be helpful for the adoption of suitable approaches to prevent the incidents. In this study, safety statistics of Iran's mines in 2011 and 2012 were assessed and important incidents and injuries happening to employees for 12 different groups of minerals were evaluated and eventually compared to the situation of some other countries. According to the obtained results, the average incidence probability in Iran's mines was calculated to be 0.18 for 2011 and the incidence probability of coal, copper and iron ore mines was greater than others. The injury rate of Iran's mines was 106 and 164 out of 10,000 persons for 2011 and 2012, respectively, and the maximum values of injury rate belonged to coal, dimension stone and aggregate mines. Also, it turned out that the fatal rate per 100 tons of production had the highest values in chromite and coal mines. Besides, comparison of injury rate and the fatal rate in Iran and some countries showed that the safety situation in Iran's mines was in a fair condition.

Sinkhole-type subsidence over abandoned coal mines in St. David, Illinois. Mine subsidence report, St. David, Illinois. A field survey and analysis of mine subsidence of abandoned coal mines in St. David, Illinois

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wildanger, E.G.; Mahar, J.; Nieto, A.

1980-01-01

This study examined the geologic data, mining history, and subsidence trends of the St. David region. Mine subsidence has occurred due to collapse of the abandoned mine workings. The known subsidence areas have been mapped and described. Results of the study include: (1) St. David has been undermined by both large shipping mines and smaller local mines; (2) sinkholes will continue to develop in this area in response to rock failure and roof collapse above the abandoned mine workings; (3) some primary factors that contribute to the sinkhole problems are the undermining and roof rock composition; (4) sinkholes will bemore » smaller in the future; (5) ten of the 63 sinkholes occurred close enough to structures to cause damage, and only six sinkholes caused damage; (6) ways to minimize potential damage to future homes from sinkhole subsidence are manageable; (7) threats to residents lie in the collapse of heavy walls, brick chimneys, breaks in gas, water, or electrical lines; and (8) location of future subsidence is not predictable. (DP)« less

What Satisfies Students? Mining Student-Opinion Data with Regression and Decision-Tree Analysis. AIR 2002 Forum Paper.

ERIC Educational Resources Information Center

Thomas, Emily H.; Galambos, Nora

To investigate how students' characteristics and experiences affect satisfaction, this study used regression and decision-tree analysis with the CHAID algorithm to analyze student opinion data from a sample of 1,783 college students. A data-mining approach identifies the specific aspects of students' university experience that most influence three…

Identifying Engineering Students' English Sentence Reading Comprehension Errors: Applying a Data Mining Technique

ERIC Educational Resources Information Center

Tsai, Yea-Ru; Ouyang, Chen-Sen; Chang, Yukon

2016-01-01

The purpose of this study is to propose a diagnostic approach to identify engineering students' English reading comprehension errors. Student data were collected during the process of reading texts of English for science and technology on a web-based cumulative sentence analysis system. For the analysis, the association-rule, data mining technique…

The performance evaluation model of mining project founded on the weight optimization entropy value method

NASA Astrophysics Data System (ADS)

Mao, Chao; Chen, Shou

2017-01-01

According to the traditional entropy value method still have low evaluation accuracy when evaluating the performance of mining projects, a performance evaluation model of mineral project founded on improved entropy is proposed. First establish a new weight assignment model founded on compatible matrix analysis of analytic hierarchy process (AHP) and entropy value method, when the compatibility matrix analysis to achieve consistency requirements, if it has differences between subjective weights and objective weights, moderately adjust both proportions, then on this basis, the fuzzy evaluation matrix for performance evaluation. The simulation experiments show that, compared with traditional entropy and compatible matrix analysis method, the proposed performance evaluation model of mining project based on improved entropy value method has higher accuracy assessment.

Satellite radar interferometry for monitoring subsidence induced by longwall mining activity using Radarsat-2, Sentinel-1 and ALOS-2 data

NASA Astrophysics Data System (ADS)

Ng, Alex Hay-Man; Ge, Linlin; Du, Zheyuan; Wang, Shuren; Ma, Chao

2017-09-01

This paper describes the simulation and real data analysis results from the recently launched SAR satellites, ALOS-2, Sentinel-1 and Radarsat-2 for the purpose of monitoring subsidence induced by longwall mining activity using satellite synthetic aperture radar interferometry (InSAR). Because of the enhancement of orbit control (pairs with shorter perpendicular baseline) from the new satellite SAR systems, the mine subsidence detection is now mainly constrained by the phase discontinuities due to large deformation and temporal decorrelation noise. This paper investigates the performance of the three satellite missions with different imaging modes for mapping longwall mine subsidence. The results show that the three satellites perform better than their predecessors. The simulation results show that the Sentinel-1A/B constellation is capable of mapping rapid mine subsidence, especially the Sentinel-1A/B constellation with stripmap (SM) mode. Unfortunately, the Sentinel-1A/B SM data are not available in most cases and hence real data analysis cannot be conducted in this study. Despite the Sentinel-1A/B SM data, the simulation and real data analysis suggest that ALOS-2 is best suited for mapping mine subsidence amongst the three missions. Although not investigated in this study, the X-band satellites TerraSAR-X and COSMO-SkyMed with short temporal baseline and high spatial resolution can be comparable with the performance of the Radarsat-2 and Sentinel-1 C-band data over the dry surface with sparse vegetation. The potential of the recently launched satellites (e.g. ALOS-2 and Sentinel-1A/B) for mapping longwall mine subsidence is expected to be better than the results of this study, if the data acquired from the ideal acquisition modes are available.

Screening and prioritisation of chemical risks from metal mining operations, identifying exposure media of concern.

PubMed

Pan, Jilang; Oates, Christopher J; Ihlenfeld, Christian; Plant, Jane A; Voulvoulis, Nikolaos

2010-04-01

Metals have been central to the development of human civilisation from the Bronze Age to modern times, although in the past, metal mining and smelting have been the cause of serious environmental pollution with the potential to harm human health. Despite problems from artisanal mining in some developing countries, modern mining to Western standards now uses the best available mining technology combined with environmental monitoring, mitigation and remediation measures to limit emissions to the environment. This paper develops risk screening and prioritisation methods previously used for contaminated land on military and civilian sites and engineering systems for the analysis and prioritisation of chemical risks from modern metal mining operations. It uses hierarchical holographic modelling and multi-criteria decision making to analyse and prioritise the risks from potentially hazardous inorganic chemical substances released by mining operations. A case study of an active platinum group metals mine in South Africa is used to demonstrate the potential of the method. This risk-based methodology for identifying, filtering and ranking mining-related environmental and human health risks can be used to identify exposure media of greatest concern to inform risk management. It also provides a practical decision-making tool for mine acquisition and helps to communicate risk to all members of mining operation teams.

Roadway backfill method to prevent geohazards induced by room and pillar mining: a case study in Changxing coal mine, China

NASA Astrophysics Data System (ADS)

Zhou, Nan; Li, Meng; Zhang, Jixiong; Gao, Rui

2016-11-01

Coal mines in the western areas of China experience low mining rates and induce many geohazards when using the room and pillar mining method. In this research, we proposed a roadway backfill method during longwall mining to target these problems. We tested the mechanical properties of the backfill materials to determine a reasonable ratio of backfill materials for the driving roadway during longwall mining. We also introduced the roadway layout and the backfill mining technique required for this method. Based on the effects of the abutment stress from a single roadway driving task, we designed the distance between roadways and a driving and filling sequence for multiple-roadway driving. By doing so, we found the movement characteristics of the strata with quadratic stabilization for backfill mining during roadway driving. Based on this research, the driving and filling sequence of the 3101 working face in Changxing coal mine was optimized to avoid the superimposed influence of mining-induced stress. According to the analysis of the surface monitoring data, the accumulated maximum subsidence is 15 mm and the maximum horizontal deformation is 0.8 mm m-1, which indicated that the ground basically had no obvious deformation after the implementation of the roadway backfill method at 3101 working face.

A large area cosmic muon detector located at Ohya stone mine

NASA Technical Reports Server (NTRS)

Nii, N.; Mizutani, K.; Aoki, T.; Kitamura, T.; Mitsui, K.; Matsuno, S.; Muraki, Y.; Ohashi, Y.; Okada, A.; Kamiya, Y.

1985-01-01

The chemical composition of the primary cosmic rays between 10 to the 15th power eV and 10 to the 18th power eV were determined by a Large Area Cosmic Muon Detector located at Ohya stone mine. The experimental aims of Ohya project are; (1) search for the ultra high-energy gamma-rays; (2) search for the GUT monopole created by Big Bang; and (3) search for the muon bundle. A large number of muon chambers were installed at the shallow underground near Nikko (approx. 100 Km north of Tokyo, situated at Ohya-town, Utsunomiya-city). At the surface of the mine, very fast 100 channel scintillation counters were equipped in order to measure the direction of air showers. These air shower arrays were operated at the same time, together with the underground muon chamber.

Methane asphyxia. Coal mine accident investigation of distribution of gas

DOE Office of Scientific and Technical Information (OSTI.GOV)

Terazawa, K.; Takatori, T.; Tomii, S.

1985-09-01

Death from asphyxia due to substitution of air by methane gas may occur in coal mine by gas outburst. In such a case, it is required to determine methane gas contents from cadaveric blood and tissues for diagnosing cause of death and estimating conditions of the accident. The methane concentration in blood and tissue samples of 22 male victims by a gas outburst accident was measured by gas chromatography. The level of methane in the cardiac blood was in the range of 6.8-26.8 microliters/g. As a model of gas outburst in coal mine, rats were exposed experimentally to various concentrationsmore » of methane. Their course of death and methane distribution in the bodies were observed. From these findings, diagnostic criteria for asphyxia from substitution of air by methane are also discussed.« less

NDVI (Normalized Difference Vegetation Index) signatures of transient ecohydrological systems: The case of post-mining landscapes

NASA Astrophysics Data System (ADS)

Brück, Yasemine; Schulte Overberg, Philipp; Pohle, Ina; Hinz, Christoph

2017-04-01

Assessing ecohydrological systems that undergo state transitions due to environmental change is becoming increasingly important. One system that can be used to study severe disturbances are post-mining landscapes as they usually are associated with complete removal of vegetation and afterwards subsequent ecosystem restoration or spontaneous rehabilitation in line with natural succession. Within this context it is of interest, whether and how (fast) the land cover in these areas returns to conditions comparable to those in the undisturbed surrounding or those prior mining. Many aspects of mine site rehabilitation depend on climatic, geomorphic and ecological settings, which determine at which rate vegetation may be re-established. In order to identify general patterns of vegetation establishment, we propose to use NDVI (Normalized Difference Vegetation Index) time series for mine affected land to estimate rate of recovery across climate regions and ecoregions. In this study we analysed the MODIS Terra Satellite 8 day-composite NDVI for areas influenced by surface mining in different climates from 2001 to 2015. The locations have been chosen based on their extent and the data availability of mining and rehabilitation activities. We selected coal extraction as a case study as strip mining generates well-defined chronosequences of disturbance. The selected mining areas are located in equatorial, arid, warm temperate or snow climates with different precipitation and temperature conditions according to the Köppen-Geiger classification. We analysed the NDVI time series regarding significant characteristics of the re-vegetation phase. We applied hierarchical cluster analysis to capture the spatial heterogeneity between different pixels (ca. 250 * 250 m2 each) in and around each open cast mine. We disentangled seasonality, trend and residual components in the NDVI time series by Seasonal and Trend decomposition using LOESS. As expected the time of the removal of vegetation can be clearly identified from the NDVI time series and provides the starting point of disturbance. The cluster analysis allowed us to distinguish between the non-mining land, the mine and the restored land of different ages. Based on these clusters, the time series decomposition revealed the dominance of the trend of increasing NDVI in areas undergoing the restoration process as well as the prevailing seasonality of the oldest restored sites. The determined phase of a dominant trend component, lasting until the NDVI is in the range of the surrounding landscape or the pre-mining conditions, is in the scale of a decade. The impacts of different hydroclimatic regimes and different rehabilitation strategies on long term NDVI development are currently being investigated. Furthermore, coherence analysis will be applied to quantify short term influences of hydrometeorological variables on vegetation development.

Indicators for the use of robotic labs in basic biomedical research: a literature analysis

PubMed Central

2017-01-01

Robotic labs, in which experiments are carried out entirely by robots, have the potential to provide a reproducible and transparent foundation for performing basic biomedical laboratory experiments. In this article, we investigate whether these labs could be applicable in current experimental practice. We do this by text mining 1,628 papers for occurrences of methods that are supported by commercial robotic labs. Using two different concept recognition tools, we find that 86%–89% of the papers have at least one of these methods. This and our other results provide indications that robotic labs can serve as the foundation for performing many lab-based experiments. PMID:29134146

Assessing the Environmental and Socio-Economic Impacts of Artisanal Gold Mining on the Livelihoods of Communities in the Tarkwa Nsuaem Municipality in Ghana.

PubMed

Obiri, Samuel; Mattah, Precious A D; Mattah, Memuna M; Armah, Frederick A; Osae, Shiloh; Adu-kumi, Sam; Yeboah, Philip O

2016-01-26

Gold mining has played an important role in Ghana's economy, however the negative environmental and socio-economic effects on the host communities associated with gold mining have overshadowed these economic gains. It is within this context that this paper assessed in an integrated manner the environmental and socio-economic impacts of artisanal gold mining in the Tarkwa Nsuaem Municipality from a natural and social science perspective. The natural science group collected 200 random samples on bi-weekly basis between January to October 2013 from water bodies in the study area for analysis in line with methods outlined by the American Water Works Association, while the social science team interviewed 250 residents randomly selected for interviews on socio-economic issues associated with mining. Data from the socio-economic survey was analyzed using logistic regression with SPSS version 17. The results of the natural science investigation revealed that the levels of heavy metals in water samples from the study area in most cases exceeded GS 175-1/WHO permissible guideline values, which are in tandem with the results of inhabitants' perceptions of water quality survey (as 83% of the respondents are of the view that water bodies in the study area are polluted). This calls for cost-benefits analysis of mining before new mining leases are granted by the relevant authorities.

Assessing the Environmental and Socio-Economic Impacts of Artisanal Gold Mining on the Livelihoods of Communities in the Tarkwa Nsuaem Municipality in Ghana

PubMed Central

Obiri, Samuel; Mattah, Precious A. D.; Mattah, Memuna M.; Armah, Frederick A.; Osae, Shiloh; Adu-kumi, Sam; Yeboah, Philip O.

2016-01-01

Gold mining has played an important role in Ghana’s economy, however the negative environmental and socio-economic effects on the host communities associated with gold mining have overshadowed these economic gains. It is within this context that this paper assessed in an integrated manner the environmental and socio-economic impacts of artisanal gold mining in the Tarkwa Nsuaem Municipality from a natural and social science perspective. The natural science group collected 200 random samples on bi-weekly basis between January to October 2013 from water bodies in the study area for analysis in line with methods outlined by the American Water Works Association, while the social science team interviewed 250 residents randomly selected for interviews on socio-economic issues associated with mining. Data from the socio-economic survey was analyzed using logistic regression with SPSS version 17. The results of the natural science investigation revealed that the levels of heavy metals in water samples from the study area in most cases exceeded GS 175-1/WHO permissible guideline values, which are in tandem with the results of inhabitants’ perceptions of water quality survey (as 83% of the respondents are of the view that water bodies in the study area are polluted). This calls for cost-benefits analysis of mining before new mining leases are granted by the relevant authorities. PMID:26821039

Data mining applications in the context of casemix.

PubMed

Koh, H C; Leong, S K

2001-07-01

In October 1999, the Singapore Government introduced casemix-based funding to public hospitals. The casemix approach to health care funding is expected to yield significant benefits, including equity and rationality in financing health care, the use of comparative casemix data for quality improvement activities, and the provision of information that enables hospitals to understand their cost behaviour and reinforces the drive for more cost-efficient services. However, there is some concern about the "quicker and sicker" syndrome (that is, the rapid discharge of patients with little regard for the quality of outcome). As it is likely that consequences of premature discharges will be reflected in the readmission data, an analysis of possible systematic patterns in readmission data can provide useful insight into the "quicker and sicker" syndrome. This paper explores potential data mining applications in the context of casemix by using readmission data as an illustration. In particular, it illustrates how data mining can be used to better understand readmission data and to detect systematic patterns, if any. From a technical perspective, data mining (which is capable of analysing complex non-linear and interaction relationships) supplements and complements traditional statistical methods in data analysis. From an applications perspective, data mining provides the technology and methodology to analyse mass volume of data to detect hidden patterns in data. Using readmission data as an illustrative data mining application, this paper explores potential data mining applications in the general casemix context.

Source identification of uranium-containing materials at mine legacy sites in Portugal.

PubMed

Keatley, A C; Martin, P G; Hallam, K R; Payton, O D; Awbery, R; Carvalho, F P; Oliveira, J M; Silva, L; Malta, M; Scott, T B

2018-03-01

Whilst prior nuclear forensic studies have focused on identifying signatures to distinguish between different uranium deposit types, this paper focuses on providing a scientific basis for source identification of materials from different uranium mine sites within a single region, which can then be potentially used within nuclear forensics. A number of different tools, including gamma spectrometry, alpha spectrometry, mineralogy and major and minor elemental analysis, have been utilised to determine the provenance of uranium mineral samples collected at eight mine sites, located within three different uranium provinces, in Portugal. A radiation survey was initially conducted by foot and/or unmanned aerial vehicle at each site to assist sample collection. The results from each mine site were then compared to determine if individual mine sites could be distinguished based on characteristic elemental and isotopic signatures. Gamma and alpha spectrometry were used to differentiate between samples from different sites and also give an indication of past milling and mining activities. Ore samples from the different mine sites were found to be very similar in terms of gangue and uranium mineralogy. However, rarer minerals or specific impurity elements, such as calcium and copper, did permit some separation of the sites examined. In addition, classification rates using linear discriminant analysis were comparable to those in the literature. Crown Copyright © 2018. Published by Elsevier Ltd. All rights reserved.

A prototype system based on visual interactive SDM called VGC

NASA Astrophysics Data System (ADS)

Jia, Zelu; Liu, Yaolin; Liu, Yanfang

2009-10-01

In many application domains, data is collected and referenced by its geo-spatial location. Spatial data mining, or the discovery of interesting patterns in such databases, is an important capability in the development of database systems. Spatial data mining recently emerges from a number of real applications, such as real-estate marketing, urban planning, weather forecasting, medical image analysis, road traffic accident analysis, etc. It demands for efficient solutions for many new, expensive, and complicated problems. For spatial data mining of large data sets to be effective, it is also important to include humans in the data exploration process and combine their flexibility, creativity, and general knowledge with the enormous storage capacity and computational power of today's computers. Visual spatial data mining applies human visual perception to the exploration of large data sets. Presenting data in an interactive, graphical form often fosters new insights, encouraging the information and validation of new hypotheses to the end of better problem-solving and gaining deeper domain knowledge. In this paper a visual interactive spatial data mining prototype system (visual geo-classify) based on VC++6.0 and MapObject2.0 are designed and developed, the basic algorithms of the spatial data mining is used decision tree and Bayesian networks, and data classify are used training and learning and the integration of the two to realize. The result indicates it's a practical and extensible visual interactive spatial data mining tool.

Alkahest NuclearBLAST : a user-friendly BLAST management and analysis system

PubMed Central

Diener, Stephen E; Houfek, Thomas D; Kalat, Sam E; Windham, DE; Burke, Mark; Opperman, Charles; Dean, Ralph A

2005-01-01

Background - Sequencing of EST and BAC end datasets is no longer limited to large research groups. Drops in per-base pricing have made high throughput sequencing accessible to individual investigators. However, there are few options available which provide a free and user-friendly solution to the BLAST result storage and data mining needs of biologists. Results - Here we describe NuclearBLAST, a batch BLAST analysis, storage and management system designed for the biologist. It is a wrapper for NCBI BLAST which provides a user-friendly web interface which includes a request wizard and the ability to view and mine the results. All BLAST results are stored in a MySQL database which allows for more advanced data-mining through supplied command-line utilities or direct database access. NuclearBLAST can be installed on a single machine or clustered amongst a number of machines to improve analysis throughput. NuclearBLAST provides a platform which eases data-mining of multiple BLAST results. With the supplied scripts, the program can export data into a spreadsheet-friendly format, automatically assign Gene Ontology terms to sequences and provide bi-directional best hits between two datasets. Users with SQL experience can use the database to ask even more complex questions and extract any subset of data they require. Conclusion - This tool provides a user-friendly interface for requesting, viewing and mining of BLAST results which makes the management and data-mining of large sets of BLAST analyses tractable to biologists. PMID:15958161

Geochemistry and hydrology of perched groundwater springs: assessing elevated uranium concentrations at Pigeon Spring relative to nearby Pigeon Mine, Arizona (USA)

USGS Publications Warehouse

Beisner, Kimberly R.; Paretti, Nicholas; Tillman, Fred; Naftz, David L.; Bills, Donald; Walton-Day, Katie; Gallegos, Tanya J.

2017-01-01

The processes that affect water chemistry as the water flows from recharge areas through breccia-pipe uranium deposits in the Grand Canyon region of the southwestern United States are not well understood. Pigeon Spring had elevated uranium in 1982 (44 μg/L), compared to other perched springs (2.7–18 μg/L), prior to mining operations at the nearby Pigeon Mine. Perched groundwater springs in an area around the Pigeon Mine were sampled between 2009 and 2015 and compared with material from the Pigeon Mine to better understand the geochemistry and hydrology of the area. Two general groups of perched groundwater springs were identified from this study; one group is characterized by calcium sulfate type water, low uranium activity ratio 234U/238U (UAR) values, and a mixture of water with some component of modern water, and the other group by calcium-magnesium sulfate type water, higher UAR values, and radiocarbon ages indicating recharge on the order of several thousand years ago. Multivariate statistical principal components analysis of Pigeon Mine and spring samples indicate Cu, Pb, As, Mn, and Cd concentrations distinguished mining-related leachates from perched groundwater springs. The groundwater potentiometric surface indicates that perched groundwater at Pigeon Mine would likely flow toward the northwest away from Pigeon Spring. The geochemical analysis of the water, sediment and rock samples collected from the Snake Gulch area indicate that the elevated uranium at Pigeon Spring is likely related to a natural source of uranium upgradient from the spring and not likely related to the Pigeon Mine.

An novel frequent probability pattern mining algorithm based on circuit simulation method in uncertain biological networks.

PubMed

He, Jieyue; Wang, Chunyan; Qiu, Kunpu; Zhong, Wei

2014-01-01

Motif mining has always been a hot research topic in bioinformatics. Most of current research on biological networks focuses on exact motif mining. However, due to the inevitable experimental error and noisy data, biological network data represented as the probability model could better reflect the authenticity and biological significance, therefore, it is more biological meaningful to discover probability motif in uncertain biological networks. One of the key steps in probability motif mining is frequent pattern discovery which is usually based on the possible world model having a relatively high computational complexity. In this paper, we present a novel method for detecting frequent probability patterns based on circuit simulation in the uncertain biological networks. First, the partition based efficient search is applied to the non-tree like subgraph mining where the probability of occurrence in random networks is small. Then, an algorithm of probability isomorphic based on circuit simulation is proposed. The probability isomorphic combines the analysis of circuit topology structure with related physical properties of voltage in order to evaluate the probability isomorphism between probability subgraphs. The circuit simulation based probability isomorphic can avoid using traditional possible world model. Finally, based on the algorithm of probability subgraph isomorphism, two-step hierarchical clustering method is used to cluster subgraphs, and discover frequent probability patterns from the clusters. The experiment results on data sets of the Protein-Protein Interaction (PPI) networks and the transcriptional regulatory networks of E. coli and S. cerevisiae show that the proposed method can efficiently discover the frequent probability subgraphs. The discovered subgraphs in our study contain all probability motifs reported in the experiments published in other related papers. The algorithm of probability graph isomorphism evaluation based on circuit simulation method excludes most of subgraphs which are not probability isomorphism and reduces the search space of the probability isomorphism subgraphs using the mismatch values in the node voltage set. It is an innovative way to find the frequent probability patterns, which can be efficiently applied to probability motif discovery problems in the further studies.

An novel frequent probability pattern mining algorithm based on circuit simulation method in uncertain biological networks

PubMed Central

2014-01-01

Background Motif mining has always been a hot research topic in bioinformatics. Most of current research on biological networks focuses on exact motif mining. However, due to the inevitable experimental error and noisy data, biological network data represented as the probability model could better reflect the authenticity and biological significance, therefore, it is more biological meaningful to discover probability motif in uncertain biological networks. One of the key steps in probability motif mining is frequent pattern discovery which is usually based on the possible world model having a relatively high computational complexity. Methods In this paper, we present a novel method for detecting frequent probability patterns based on circuit simulation in the uncertain biological networks. First, the partition based efficient search is applied to the non-tree like subgraph mining where the probability of occurrence in random networks is small. Then, an algorithm of probability isomorphic based on circuit simulation is proposed. The probability isomorphic combines the analysis of circuit topology structure with related physical properties of voltage in order to evaluate the probability isomorphism between probability subgraphs. The circuit simulation based probability isomorphic can avoid using traditional possible world model. Finally, based on the algorithm of probability subgraph isomorphism, two-step hierarchical clustering method is used to cluster subgraphs, and discover frequent probability patterns from the clusters. Results The experiment results on data sets of the Protein-Protein Interaction (PPI) networks and the transcriptional regulatory networks of E. coli and S. cerevisiae show that the proposed method can efficiently discover the frequent probability subgraphs. The discovered subgraphs in our study contain all probability motifs reported in the experiments published in other related papers. Conclusions The algorithm of probability graph isomorphism evaluation based on circuit simulation method excludes most of subgraphs which are not probability isomorphism and reduces the search space of the probability isomorphism subgraphs using the mismatch values in the node voltage set. It is an innovative way to find the frequent probability patterns, which can be efficiently applied to probability motif discovery problems in the further studies. PMID:25350277

Mercury speciation on three European mining districts by XANES techniques

NASA Astrophysics Data System (ADS)

Esbri, J. M.; Garcia-Noguero, E. M.; Guerrero, B.; Kocman, D.; Bernaus, A.; Gaona, X.; Higueras, P.; Alvarez, R.; Loredo, J.; Horvat, M.; Ávila, M.

2009-04-01

The mobility, bioavailability and toxicity of mercury in the environment depend on the chemical species in which is present in soil, sediments, water or air. In this work we used synchrotron radiation to determine mercury species in geological samples of three mercury mining districts: Almadén (Spain), Idria (Slovenia) and Asturias (Spain). The aim of this study was to find differences on mobility and bioavailability of mercury on three mining districts with different type of mineralization. For this porpoises we selected samples of ore, calcines, soils and stream sediments from the three sites, completely characterized by the Almadén School of Mines, Josef Stefan Institute of Ljubljana and Oviedo School of Mines. Speciation of mercury was carried out on Synchrotron Laboratories of Hamburg (HASYLAB) by XANES techniques. Spectra of pure compounds [HgCl2, HgSO4, HgO, CH3HgCl, Hg2Cl2 (calomel), HgSred (cinnabar), HgSblack (metacinnabar), Hg2NCl0.5(SO4)0.3(MoO4)0.1(CO3)0.1(H2O) (mosesite), Hg3S2Cl2 (corderoite), Hg3(SO4)O2 (schuetteite) y Hg2ClO (terlinguaite)] were obtained on transmittance mode. The number and type of the compounds required to reconstruct experimental spectra for each sample was obtained by PCA analysis and linear fitting of minimum quadratics of the pure compounds spectra. This offers a semiquantitative approach to the mineralogical constitution of each analyzed sample. The results put forward differences on the efficiency of roasting furnaces from the three studied sites, evidenced by the presence of metacinnabar on the less efficient (Almadén and Asturias) and absence on the most efficient (Idria). For the three studied sites, sulfide species (cinnabar and metacinnabar) were largely more abundant than soluble species (chlorides and sulfates). On the other hand, recent results on the mobility of both Hg and As on the target sites will be presented. These results correlate with the related chemical species found by XANES techniques.

Using NASA Earth Observing Satellites and Statistical Model Analysis to Monitor Vegetation and Habitat Rehabilitation in Southwest Virginia's Reclaimed Mine Lands

NASA Astrophysics Data System (ADS)

Tate, Z.; Dusenge, D.; Elliot, T. S.; Hafashimana, P.; Medley, S.; Porter, R. P.; Rajappan, R.; Rodriguez, P.; Spangler, J.; Swaminathan, R. S.; VanGundy, R. D.

2014-12-01

The majority of the population in southwest Virginia depends economically on coal mining. In 2011, coal mining generated $2,000,000 in tax revenue to Wise County alone. However, surface mining completely removes land cover and leaves the land exposed to erosion. The destruction of the forest cover directly impacts local species, as some are displaced and others perish in the mining process. Even though surface mining has a negative impact on the environment, land reclamation efforts are in place to either restore mined areas to their natural vegetated state or to transform these areas for economic purposes. This project aimed to monitor the progress of land reclamation and the effect on the return of local species. By incorporating NASA Earth observations, such as Landsat 8 Operational Land Imager (OLI) and Landsat 5 Thematic Mapper (TM), re-vegetation process in reclamation sites was estimated through a Time series analysis using the Normalized Difference Vegetation Index (NDVI). A continuous source of cloud free images was accomplished by utilizing the Spatial and Temporal Adaptive Reflectance Fusion Model (STAR-FM). This model developed synthetic Landsat imagery by integrating the high-frequency temporal information from Terra/Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) and high-resolution spatial information from Landsat sensors In addition, the Maximum Entropy Modeling (MaxENT), an eco-niche model was used to estimate the adaptation of animal species to the newly formed habitats. By combining factors such as land type, precipitation from Tropical Rainfall Measuring Mission (TRMM), and slope from Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), the MaxENT model produced a statistical analysis on the probability of species habitat. Altogether, the project compiled the ecological information which can be used to identify suitable habitats for local species in reclaimed mined areas.

Applications of Geomatics in Surface Mining

NASA Astrophysics Data System (ADS)

Blachowski, Jan; Górniak-Zimroz, Justyna; Milczarek, Wojciech; Pactwa, Katarzyna

2017-12-01

In terms of method of extracting mineral from deposit, mining can be classified into: surface, underground, and borehole mining. Surface mining is a form of mining, in which the soil and the rock covering the mineral deposits are removed. Types of surface mining include mainly strip and open-cast methods, as well as quarrying. Tasks associated with surface mining of minerals include: resource estimation and deposit documentation, mine planning and deposit access, mine plant development, extraction of minerals from deposits, mineral and waste processing, reclamation and reclamation of former mining grounds. At each stage of mining, geodata describing changes occurring in space during the entire life cycle of surface mining project should be taken into consideration, i.e. collected, analysed, processed, examined, distributed. These data result from direct (e.g. geodetic) and indirect (i.e. remote or relative) measurements and observations including airborne and satellite methods, geotechnical, geological and hydrogeological data, and data from other types of sensors, e.g. located on mining equipment and infrastructure, mine plans and maps. Management of such vast sources and sets of geodata, as well as information resulting from processing, integrated analysis and examining such data can be facilitated with geomatic solutions. Geomatics is a discipline of gathering, processing, interpreting, storing and delivering spatially referenced information. Thus, geomatics integrates methods and technologies used for collecting, management, processing, visualizing and distributing spatial data. In other words, its meaning covers practically every method and tool from spatial data acquisition to distribution. In this work examples of application of geomatic solutions in surface mining on representative case studies in various stages of mine operation have been presented. These applications include: prospecting and documenting mineral deposits, assessment of land accessibility for a potential large-scale surface mining project, modelling mineral deposit (granite) management, concept of a system for management of conveyor belt network technical condition, project of a geoinformation system of former mining terrains and objects, and monitoring and control of impact of surface mining on mine surroundings with satellite radar interferometry.

Determination of the Zone Endangered by Methane Explosion in Goaf with Caving of Longwalls Ventilated on "Y" System

NASA Astrophysics Data System (ADS)

Brodny, Jarosław; Tutak, Magdalena

2016-12-01

One of the most dangerous and most commonly present risks in hard coal mines is methane hazard. During exploitation by longwall system with caving, methane is emitted to mine heading from the mined coal and coal left in a pile. A large amount of methane also flows from neighboring seams through cracks and fissures formed in rock mass. In a case of accumulation of explosive methane concentration in goaf zone and with appropriate oxygen concentration and occurrence of initials (e.g. spark or endogenous fire), it may come to the explosion of this gas. In the paper there are presented results of numerical analysis of mixture of air and methane streams flow through the real heading system of a mine, characterized by high methane hazard. The aim of the studies was to analyze the ventilation system of considered heading system and determination of braking zones in goaf zone, in which dangerous and explosive concertation of methane can occur with sufficient oxygen concentration equal to at least 12%. Determination of position of these zones is necessary for the selection of appropriate parameters of the ventilation system to ensure safety of the crew. Analysis of the scale of methane hazard allows to select such a ventilation system of exploitation and neighboring headings that ensures chemical composition of mining atmosphere required by regulation, and required efficiency of methane drainage. The obtained results clearly show that numerical methods, combined with the results of tests in real conditions can be successfully used for the analysis of variants of processes related to ventilation of underground mining, and also in the analysis of emergency states.

Passive neutralization of acid mine drainage using basic oxygen furnace slag as neutralization material: experimental and modelling.

PubMed

Zvimba, John N; Siyakatshana, Njabulo; Mathye, Matlhodi

2017-03-01

This study investigated passive neutralization of acid mine drainage using basic oxygen furnace slag as neutralization material over 90 days, with monitoring of the parameters' quality and assessment of their removal kinetics. The quality was observed to significantly improve over time with most parameters removed from the influent during the first 10 days. In this regard, removal of acidity, Fe(II), Mn, Co, Ni and Zn was characterized by fast kinetics while removal kinetics for Mg and SO 4 2- were observed to proceed slowly. The fast removal kinetics of acidity was attributed to fast release of alkalinity from slag minerals under mildly acidic conditions of the influent water. The removal of acidity through generation of alkalinity from the passive treatment system was also observed to generally govern the removal of metallic parameters through hydroxide formation, with overall percentage removals of 88-100% achieved. The removal kinetics for SO 4 2- was modelled using two approaches, yielding rate constant values of 1.56 and 1.53 L/(day mol) respectively, thereby confirming authenticity of SO 4 2- removal kinetics experimental data. The study findings provide insights into better understanding of the potential use of slags and their limitations, particularly in mine closure, as part of addressing this challenge in South Africa.

Evaluation of the Kloswall longwall mining system

NASA Astrophysics Data System (ADS)

Guay, P. J.

1982-04-01

A new longwal mining system specifically designed to extract a very deep web (48 inches or deeper) from a longwall panel was studied. Productivity and cost analysis comparing the new mining system with a conventional longwall operation taking a 30 inch wide web is presented. It is shown that the new system will increase annual production and return on investment in most cases. Conceptual drawings and specifications for a high capacity three drum shearer and a unique shield type of roof support specifically designed for very wide web operation are reported. The advantages and problems associated with wide web mining in general and as they relate specifically to the equipment selected for the new mining system are discussed.

Application of EREP imagery to fracture-related mine safety hazards in coal mining and mining-environmental problems in Indiana. [Indiana and Illinois

NASA Technical Reports Server (NTRS)

Wier, C. E. (Principal Investigator); Powell, R. L.; Amato, R. V.; Russell, O. R.; Martin, K. R.

1975-01-01

The author has identified the following significant results. This investigation evaluated the applicability of a variety of sensor types, formats, and resolution capabilities to the study of both fuel and nonfuel mined lands. The image reinforcement provided by stereo viewing of the EREP images proved useful for identifying lineaments and for mined lands mapping. Skylab S190B color and color infrared transparencies were the most useful EREP imagery. New information on lineament and fracture patterns in the bedrock of Indiana and Illinois extracted from analysis of the Skylab imagery has contributed to furthering the geological understanding of this portion of the Illinois basin.

Decision support methods for the environmental assessment of contamination at mining sites.

PubMed

Jordan, Gyozo; Abdaal, Ahmed

2013-09-01

Polluting mine accidents and widespread environmental contamination associated with historic mining in Europe and elsewhere has triggered the improvement of related environmental legislation and of the environmental assessment and management methods for the mining industry. Mining has some unique features such as natural background pollution associated with natural mineral deposits, industrial activities and contamination located in the three-dimensional sub-surface space, the problem of long-term remediation after mine closure, problem of secondary contaminated areas around mine sites and abandoned mines in historic regions like Europe. These mining-specific problems require special tools to address the complexity of the environmental problems of mining-related contamination. The objective of this paper is to review and evaluate some of the decision support methods that have been developed and applied to mining contamination. In this paper, only those methods that are both efficient decision support tools and provide a 'holistic' approach to the complex problem as well are considered. These tools are (1) landscape ecology, (2) industrial ecology, (3) landscape geochemistry, (4) geo-environmental models, (5) environmental impact assessment, (6) environmental risk assessment, (7) material flow analysis and (8) life cycle assessment. This unique inter-disciplinary study should enable both the researcher and the practitioner to obtain broad view on the state-of-the-art of decision support methods for the environmental assessment of contamination at mine sites. Documented examples and abundant references are also provided.

Mine Clearance Industry: Background, Geography, Funding, Analysis and Future Projections

DTIC Science & Technology

2007-12-01

the targeting of food supplies to such an extreme (through widespread mining of agricultural areas and destruction of irrigation systems) that...UNOPS), Food and Agriculture Organization (FAO), Office for the Coordination of Humanitarian Affairs (OCHA), Office of the Special Adviser to the...U.N. High Commissioner for Refugees (UNHCR), World Food Program (WFP), World Health Organization (WHO), World Bank) on Mine Action before being

Analysis by the Residual Method for Estimate Market Value of Land on the Areas with Mining Exploitation in Subsoil under Future New Building

NASA Astrophysics Data System (ADS)

Gwozdz-Lason, Monika

2017-12-01

This paper attempts to answer some of the following questions: what is the main selling advantage of a plot of land on the areas with mining exploitation? which attributes influence on market value the most? and how calculate the mining influence in subsoil under future new building as market value of plot with commercial use? This focus is not accidental, as the paper sets out to prove that the subsoil load bearing capacity, as directly inferred from the local geotechnical properties with mining exploitation, considerably influences the market value of this type of real estate. Presented in this elaborate analysis and calculations, are part of the ongoing development works which aimed at suggesting a new technology and procedures for estimating the value of the land belonging to the third category geotechnical. Analysed the question was examined both in terms of the theoretical and empirical. On the basis of the analysed code calculations in residual method, numerical, statistical and econometric defined results and final conclusions. A market analysis yielded a group of subsoil stabilization costs which depend on the mining operations interaction, subsoil parameters, type of the contemplated structure, its foundations, selected stabilization method, its overall area and shape.

Trace Metal Content of Sediments Close to Mine Sites in the Andean Region

PubMed Central

Yacoub, Cristina; Pérez-Foguet, Agustí; Miralles, Nuria

2012-01-01

This study is a preliminary examination of heavy metal pollution in sediments close to two mine sites in the upper part of the Jequetepeque River Basin, Peru. Sediment concentrations of Al, As, Cd, Cu, Cr, Fe, Hg, Ni, Pb, Sb, Sn, and Zn were analyzed. A comparative study of the trace metal content of sediments shows that the highest concentrations are found at the closest points to the mine sites in both cases. The sediment quality analysis was performed using the threshold effect level of the Canadian guidelines (TEL). The sediment samples analyzed show that potential ecological risk is caused frequently at both sites by As, Cd, Cu, Hg, Pb, and Zn. The long-term influence of sediment metals in the environment is also assessed by sequential extraction scheme analysis (SES). The availability of metals in sediments is assessed, and it is considered a significant threat to the environment for As, Cd, and Sb close to one mine site and Cr and Hg close to the other mine site. Statistical analysis of sediment samples provides a characterization of both subbasins, showing low concentrations of a specific set of metals and identifies the main characteristics of the different pollution sources. A tentative relationship between pollution sources and possible ecological risk is established. PMID:22606058

Selenium and mining in the Powder River Basin, Wyoming: Phase III - a preliminary survey of selenium concentrations in deer mice (Peromyscus maniculatus) livers

DOE Office of Scientific and Technical Information (OSTI.GOV)

Raisbeck, M.L.; Vance, G.F.; Steward, D.G.

1995-09-01

Samples of liver tissue from deer mice trapped on not-yet-mined areas and reclaimed areas at five surface coal mines in the Powder River Basin of northeastern Wyoming were analyzed for selenium. The overall mean concentration of selenium in wet weight liver tissue was 1.685 ppm. The mean value from not-yet-mined areas was 1.437 ppm; the mean value from reclaimed areas was 1.910 ppm (significant at p<0.1016). When one not-yet-mined outlier was removed, significance rose to p<0.0004. Mine-to-mine comparison of samples stratified by type (that is, by not-yet-mined or reclaimed), showed average tissue concentrations from the reclaimed area of Mine 1more » were also higher (p<0.0143) then not-yet-mined area samples at Mine 1. No statistically significant differences were found between mines for samples from not-yet-mined areas, and no statistically significant differences were found between Mines 2, 3, 4, and 5 for samples from reclaimed areas. Multiple analysis of variance using the factors: site (mine) and type (not-yet-mined or reclaimed) was not significantly significant (p<0.2115). Simple linear regression showed that selenium concentrations in dry tissue could easily be predicted from wet tissue selenium (r2=0.9775), demonstrating that percent water in the samples was relatively constant. Animal body weight in general was not a predictor for either wet or dry tissue selenium concentrations, but was related to body weight at the higher tissue concentrations of selenium encountered in samples from the reclaimed area at Mine 1. Mouse body weights at Mine 1 were higher on the reclaimed area than mouse body weights from the not-yet-mined area.« less

The Pollution Detectives: Part II. Lead and Zinc Mining.

ERIC Educational Resources Information Center

Sanderson, P. L.

1988-01-01

Describes a field trip taken to an old mining area to study water pollution. Discussed are methods for silt analysis, reagent preparation, color charts, techniques, fieldwork, field results, and a laboratory study. (CW)