What can 35 years and over 700,000 measurements tell us about noise exposure in the mining industry?

PubMed Central

Roberts, Benjamin; Sun, Kan; Neitzel, Richard L.

2017-01-01

Objective To analyze over 700,000 cross-sectional measurements from the Mine Safety and Health Administration (MHSA) and develop statistical models to predict noise exposure for a worker. Design Descriptive statistics were used to summarize the data. Two linear regression models were used to predict noise exposure based on MSHA permissible exposure limit (PEL) and action level (AL) respectively. Two-fold cross validation was used to compare the exposure estimates from the models to actual measurements in the hold out data. The mean difference and t-statistic was calculated for each job title to determine if the model exposure predictions were significantly different from the actual data. Study Sample Measurements were acquired from MSHA through a Freedom of Information Act request. Results From 1979 to 2014 the average noise measurement has decreased. Measurements taken before the implementation of MSHA’s revised noise regulation in 2000 were on average 4.5 dBA higher than after the law came in to effect. Both models produced mean exposure predictions that were less than 1 dBA different compared to the holdout data. Conclusion Overall noise levels in mines have been decreasing. However, this decrease has not been uniform across all mining sectors. The exposure predictions from the model will be useful to help predict hearing loss in workers from the mining industry. PMID:27871188

Using Data Mining to Teach Applied Statistics and Correlation

ERIC Educational Resources Information Center

Hartnett, Jessica L.

2016-01-01

This article describes two class activities that introduce the concept of data mining and very basic data mining analyses. Assessment data suggest that students learned some of the conceptual basics of data mining, understood some of the ethical concerns related to the practice, and were able to perform correlations via the Statistical Package for…

Respiratory Disease Related Mortality and Morbidity on an Island of Greece Exposed to Perlite and Bentonite Mining Dust

PubMed Central

Sampatakakis, Stefanos; Linos, Athena; Papadimitriou, Eleni; Petralias, Athanasios; Dalma, Archontoula; Papasaranti, Eirini Saranti; Christoforidou, Eleni; Stoltidis, Melina

2013-01-01

A morbidity and mortality study took place, focused on Milos Island, where perlite and bentonite mining sites are located. Official data concerning number and cause of deaths, regarding specific respiratory diseases and the total of respiratory diseases, for both Milos Island and the Cyclades Prefecture were used. Standardized Mortality Ratios (SMRs) were computed, adjusted specifically for age, gender and calendar year. Tests of linear trend were performed. By means of a predefined questionnaire, the morbidity rates of specific respiratory diseases in Milos, were compared to those of the municipality of Oinofita, an industrial region. Chi-square analysis was used and the confounding factors of age, gender and smoking were taken into account, by estimating binary logistic regression models. The SMRs for Pneumonia and Chronic Obstructive Pulmonary Disease (COPD) were found elevated for both genders, although they did not reach statistical significance. For the total of respiratory diseases, a statistically significant SMR was identified regarding the decade 1989–1998. The morbidity study revealed elevated and statistically significant Odds Ratios (ORs), associated with allergic rhinitis, pneumonia, COPD and bronchiectasis. An elevated OR was also identified for asthma. After controlling for age, gender and smoking, the ORs were statistically significant and towards the same direction. PMID:24129114

Respiratory disease related mortality and morbidity on an island of Greece exposed to perlite and bentonite mining dust.

PubMed

Sampatakakis, Stefanos; Linos, Athena; Papadimitriou, Eleni; Petralias, Athanasios; Dalma, Archontoula; Papasaranti, Eirini Saranti; Christoforidou, Eleni; Stoltidis, Melina

2013-10-14

A morbidity and mortality study took place, focused on Milos Island, where perlite and bentonite mining sites are located. Official data concerning number and cause of deaths, regarding specific respiratory diseases and the total of respiratory diseases, for both Milos Island and the Cyclades Prefecture were used. Standardized Mortality Ratios (SMRs) were computed, adjusted specifically for age, gender and calendar year. Tests of linear trend were performed. By means of a predefined questionnaire, the morbidity rates of specific respiratory diseases in Milos, were compared to those of the municipality of Oinofita, an industrial region. Chi-square analysis was used and the confounding factors of age, gender and smoking were taken into account, by estimating binary logistic regression models. The SMRs for Pneumonia and Chronic Obstructive Pulmonary Disease (COPD) were found elevated for both genders, although they did not reach statistical significance. For the total of respiratory diseases, a statistically significant SMR was identified regarding the decade 1989-1998. The morbidity study revealed elevated and statistically significant Odds Ratios (ORs), associated with allergic rhinitis, pneumonia, COPD and bronchiectasis. An elevated OR was also identified for asthma. After controlling for age, gender and smoking, the ORs were statistically significant and towards the same direction.

Effect of heavy metals on soil enzyme activity at different field conditions in Middle Spis mining area (Slovakia).

PubMed

Angelovičová, Lenka; Lodenius, Martin; Tulisalo, Esa; Fazekašová, Danica

2014-12-01

Heavy metals concentrations were measured in the former mining area located in Hornad river valley (Slovakia). Soil samples were taken in 2012 from 20 sites at two field types (grasslands, heaps of waste material) and two different areas. Total content of heavy metals (Cu, Pb, Zn, Hg), urease (URE), acid phosphatase (ACP), alkaline phosphatase (ALP), soil reaction (pH) were changing depending on the field/area type. The tailing pond and processing plants have been found as the biggest sources of pollution. URE, ACP and ALP activities significantly decreased while the heavy metal contents increased. Significant differences were found among area types in the heavy metal contents and activity of URE. No statistical differences in the content of heavy metals but significant statistical differences for soil pH were found for field types (grassland and heaps). Significant negative correlation was found for URE-Pb, URE-Zn and also between soil reaction and ACP and ALP.

Exposure of insects and insectivorous birds to metals and other elements from abandoned mine tailings in three Summit County drainages, Colorado

USGS Publications Warehouse

Custer, Christine M.; Yang, C.; Crock, J.G.; Shearn-Bochsler, V.; Smith, K.S.; Hageman, P.L.

2009-01-01

Concentrations of 31 metals, metalloids, and other elements were measured in insects and insectivorous bird tissues from three drainages with different geochemistry and mining histories in Summit Co., Colorado, in 2003, 2004, and 2005. In insect samples, all 25 elements that were analyzed in all years increased in both Snake and Deer Creeks in the mining impacted areas compared to areas above and below the mining impacted areas. This distribution of elements was predicted from known or expected sediment contamination resulting from abandoned mine tailings in those drainages. Element concentrations in avian liver tissues were in concordance with levels in insects, that is with concentrations higher in mid-drainage areas where mine tailings were present compared to both upstream and downstream locations; these differences were not always statistically different, however. The lack of statistically significant differences in liver tissues, except for a few elements, was due to relatively small sample sizes and because many of these elements are essential and therefore well regulated by the bird's homeostatic processes. Most elements were at background concentrations in avian liver tissue except for Pb which was elevated at mid-drainage sites to levels where ??-aminolevulinic acid dehydratase activity was inhibited at other mining sites in Colorado. Lead exposure, however, was not at toxic levels. Fecal samples were not a good indication of what elements birds ingested and were potentially exposed to. ?? Springer Science+Business Media B.V. 2008.

Measuring mining safety with injury statistics: lost workdays as indicators of risk.

PubMed

Coleman, Patrick J; Kerkering, John C

2007-01-01

Mining in the United States remains one of the most hazardous industries, despite significant reductions in fatal injury rates over the last century. Coal mine fatality rates, for example, have dropped almost a thousand-fold since their peak in 1908. While incidence rates are very important indicators, lost worktime measures offer an alternative metric for evaluating job safety and health performance. The first objective of this study examined the distributions and summary statistics of all injuries reported to the Mine Safety and Health Administration from 1983 through 2004. Over the period studied (1983-2004), there were 31,515,368 lost workdays associated with mining injuries, for an equivalent of 5,700 person-years lost annually. The second objective addressed the problem of comparing safety program performance in mines for situations where denominator data were lacking. By examining the consequences of injuries, comparisons can be made between disparate operations without the need for denominators. Total risk in the form of lost workday sums can help to distinguish between lower- and higher-risk operations or time periods. Our method was to use a beta distribution to model the losses and to compare underground coal mining to underground metal/nonmetal mining from 2000 to 2004. Our results showed the probability of an injury having 10 or more lost workdays was 0.52 for coal mine cases versus 0.35 for metal/nonmetal mine cases. In addition, a comparison of injuries involving continuous mining machines over 2001-2002 versus 2003-2004 showed that the ratio of average losses in the later period to those in the earlier period was approximately 1.08, suggesting increasing risks for such operations. This denominator-free safety measure will help the mining industry more effectively identify higher-risk operations and more realistically evaluate their safety improvement programs. Attention to a variety of metrics concerning the performance of a job safety and health program will enhance industry's ability to manage these programs and reduce risk.

Comparsion analysis of data mining models applied to clinical research in traditional Chinese medicine.

PubMed

Zhao, Yufeng; Xie, Qi; He, Liyun; Liu, Baoyan; Li, Kun; Zhang, Xiang; Bai, Wenjing; Luo, Lin; Jing, Xianghong; Huo, Ruili

2014-10-01

To help researchers selecting appropriate data mining models to provide better evidence for the clinical practice of Traditional Chinese Medicine (TCM) diagnosis and therapy. Clinical issues based on data mining models were comprehensively summarized from four significant elements of the clinical studies: symptoms, symptom patterns, herbs, and efficacy. Existing problems were further generalized to determine the relevant factors of the performance of data mining models, e.g. data type, samples, parameters, variable labels. Combining these relevant factors, the TCM clinical data features were compared with regards to statistical characters and informatics properties. Data models were compared simultaneously from the view of applied conditions and suitable scopes. The main application problems were the inconsistent data type and the small samples for the used data mining models, which caused the inappropriate results, even the mistake results. These features, i.e. advantages, disadvantages, satisfied data types, tasks of data mining, and the TCM issues, were summarized and compared. By aiming at the special features of different data mining models, the clinical doctors could select the suitable data mining models to resolve the TCM problem.

Determinants of Interest Rates on Corporate Bonds of Mining Enterprises

NASA Astrophysics Data System (ADS)

Ranosz, Robert

2017-09-01

This article is devoted to the determinants of interest rates on corporate bonds of mining enterprises. The study includes a comparison between the cost of foreign capital as resulting from the issue of debt instruments in different sectors of the economy in relation to the mining industry. The article also depicts the correlation between the rating scores published by the three largest rating agencies: S&P, Moody's, and Fitch. The test was based on simple statistical methods. The analysis performed indicated that there is a dependency between the factors listed and the amount of interest rates on corporate bonds of global mining enterprises. Most significant factors include the rating level and the period for which the given series of bonds was issued. Additionally, it is not without significance whether the given bond has additional options. Pursuant to the obtained results, is should be recognized that in order to reduce the interest rate on bonds, mining enterprises should pay particular attention to the rating and attempt to include additional options in issued bonds. Such additional options may comprise, for example, an ability to exchange bonds to shares or raw materials.

Accumulation of metals in fish from lead-zinc mining areas of southeastern Missouri, USA

USGS Publications Warehouse

Schmitt, Christopher J.; Brumbaugh, William G.; May, Thomas W.

2007-01-01

The potential effects of proposed lead-zinc mining in an ecologically sensitive area were assessed by studying a nearby mining district that has been exploited for about 30 yr under contemporary environmental regulations and with modern technology. Blood and liver samples representing fish of three species (largescale stoneroller, Campostoma oligolepis, n=91; longear sunfish, Lepomis megalotis, n=105; and northern hog sucker, Hypentelium nigricans, n=20) were collected from 16 sites representing a range of conditions relative to lead-zinc mining and ore beneficiation in southeastern Missouri. Samples were analyzed for lead, zinc, and cadmium, and for a suite of biomarkers (reported in a companion paper). A subset of the hog sucker (n=9) representing three sites were also analyzed for nickel and cobalt. Blood and liver lead concentrations were highly correlated (r=0.84-0.85, P < 0.01) in all three species and were significantly (ANOVA, P < 0.01) greater at sites < 10 km downstream of active lead-zinc mines and mills and in a historical lead-zinc mining area than at reference sites, including a site in the area proposed for new mining. Correlations between blood and liver cadmium concentrations were less evident than for lead but were nevertheless statistically significant (r=0.26-0.69, P < 0.01-0.07). Although blood and liver cadmium concentrations were highest in all three species at sites near mines, within-site variability was greater and mining-related trends were less evident than for lead. Blood and liver zinc concentrations were significantly correlated only in stoneroller (r=0.46, P < 0.01) and mining-related trends were not evident. Concentrations of cobalt and nickel in blood and liver were significantly higher (ANOVA, P < 0.01) at a site near an active mine than at a reference site and a site in the historical lead-zinc mining area. These findings confirm previous studies indicating that lead and other metals are released to streams from active lead-zinc mines and are available for uptake by aquatic organisms. ?? 2006 Elsevier Inc. All rights reserved.

Accumulation of metals in fish from lead-zinc mining areas of southeastern Missouri, USA.

PubMed

Schmitt, Christopher J; Brumbaugh, William G; May, Thomas W

2007-05-01

The potential effects of proposed lead-zinc mining in an ecologically sensitive area were assessed by studying a nearby mining district that has been exploited for about 30 yr under contemporary environmental regulations and with modern technology. Blood and liver samples representing fish of three species (largescale stoneroller, Campostoma oligolepis, n=91; longear sunfish, Lepomis megalotis, n=105; and northern hog sucker, Hypentelium nigricans, n=20) were collected from 16 sites representing a range of conditions relative to lead-zinc mining and ore beneficiation in southeastern Missouri. Samples were analyzed for lead, zinc, and cadmium, and for a suite of biomarkers (reported in a companion paper). A subset of the hog sucker (n=9) representing three sites were also analyzed for nickel and cobalt. Blood and liver lead concentrations were highly correlated (r=0.84-0.85, P<0.01) in all three species and were significantly (ANOVA, P<0.01) greater at sites <10 km downstream of active lead-zinc mines and mills and in a historical lead-zinc mining area than at reference sites, including a site in the area proposed for new mining. Correlations between blood and liver cadmium concentrations were less evident than for lead but were nevertheless statistically significant (r=0.26-0.69, P <0.01-0.07). Although blood and liver cadmium concentrations were highest in all three species at sites near mines, within-site variability was greater and mining-related trends were less evident than for lead. Blood and liver zinc concentrations were significantly correlated only in stoneroller (r=0.46, P<0.01) and mining-related trends were not evident. Concentrations of cobalt and nickel in blood and liver were significantly higher (ANOVA, P<0.01) at a site near an active mine than at a reference site and a site in the historical lead-zinc mining area. These findings confirm previous studies indicating that lead and other metals are released to streams from active lead-zinc mines and are available for uptake by aquatic organisms.

Data Processing System (DPS) software with experimental design, statistical analysis and data mining developed for use in entomological research.

PubMed

Tang, Qi-Yi; Zhang, Chuan-Xi

2013-04-01

A comprehensive but simple-to-use software package called DPS (Data Processing System) has been developed to execute a range of standard numerical analyses and operations used in experimental design, statistics and data mining. This program runs on standard Windows computers. Many of the functions are specific to entomological and other biological research and are not found in standard statistical software. This paper presents applications of DPS to experimental design, statistical analysis and data mining in entomology. © 2012 The Authors Insect Science © 2012 Institute of Zoology, Chinese Academy of Sciences.

Comparison of Mortality Disparities in Central Appalachian Coal- and Non-Coal-Mining Counties.

PubMed

Woolley, Shannon M; Meacham, Susan L; Balmert, Lauren C; Talbott, Evelyn O; Buchanich, Jeanine M

2015-06-01

Determine whether select cause of death mortality disparities in four Appalachian regions is associated with coal mining or other factors. We calculated direct age-adjusted mortality rates and associated 95% confidence intervals by sex and study group for each cause of death over 5-year time periods from 1960 to 2009 and compared mean demographic and socioeconomic values between study groups via two-sample t tests. Compared with non-coal-mining areas, we found higher rates of poverty in West Virginia and Virginia (VA) coal counties. All-cause mortality rates for males and females were higher in coal counties across all time periods. Virginia coal counties had statistically significant excesses for many causes of death. We found elevated mortality and poverty rates in coal-mining compared with non-coal-mining areas of West Virginia and VA. Future research should examine these findings in more detail at the individual level.

Leukemia risk among U. S. white male coal miners. A case-control study

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

Gilman, P.A.; Ames, R.G.; McCawley, M.A.

The relevance of occupational exposure to electrical and magnetic fields (EMF) in the etiology of leukemia has been raised in several studies. Underground coal miners represent an occupational group with situationally determined EMF exposure, as high-voltage power distribution lines are strung overhead in the mines and converters and step-down transformers provide power to mining equipment. Risk in occupational exposure to EMF was examined in a case-control study of 40 leukemia decedents and 160 control subjects who died of causes other than cancer or accident and who were matched on age at death. Based on these data, 25 or more yearsmore » of underground mining, a surrogate of EMF exposure, was found to pose a statistically significant risk for leukemia (International Classification of Diseases (ICD) codes 204 through 207, eighth revision), myelogenous leukemia (ICD 205), and chronic lymphocytic leukemia (CLL) (ICD 204.1). Accumulative exposure to chemical agents probably poses a risk for acute myelogenous leukemia, although this relationship fell short of being statistically significant. Although CLL has not previously been attributed to environmental agents, these data suggest a possible CLL risk from prolonged exposure to EMF.« less

Mineral production and mining trends for selected non-fuel commodities in Idaho and Montana, 1905-2001

USGS Publications Warehouse

Larsen, Jeremy C.; Long, Keith R.; Assmus, Kenneth C.; Zientek, Michael L.

2004-01-01

Idaho and Montana state mining statistics were obtained from historical mineral production records and compiled into a continuous record from 1905 through 2001. To facilitate comparisons, the mineral production data were normalized by converting the units of measure to metric tons for all included commodities. These standardized statistical data include production rates for principal non-fuel mineral commodities from both Idaho and Montana, as well as the production rates of similar commodities for the U.S. and the world for contrast. Data are presented here in both tabular and bar chart format. Moreover, the tables of standardized mineral production data are also provided in digital format as, commodity_production.xls. Some significant historical events pertaining to the mining industry are described as well. When taken into account with the historical production data, this combined information may to help explain both specific fluctuations and general tendencies in the overall trends in the rates of mineral resource production over time.

Neural network analysis of electrodynamic activity of yeast cells around 1 kHz

NASA Astrophysics Data System (ADS)

Janca, R.

2011-12-01

This paper deals with data analysis of electrodynamic activity of two mutants of yeast cells, cell cycle of which is synchronized and non-synchronized, respectively. We used data already published by Jelinek et al. and treat them with data mining method based on the multilayer neural network. Intersection of data mining and statistical distribution of the noise shows significant difference between synchronized and non-synchronized yeasts not only in total power, but also discrete frequencies.

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.

Visualization of Differences in Data Measuring Mathematical Skills

ERIC Educational Resources Information Center

Zoubek, Lukas; Burda, Michal

2009-01-01

Identification of significant differences in sets of data is a common task of data mining. This paper describes a novel visualization technique that allows the user to interactively explore and analyze differences in mean values of analyzed attributes. Statistical tests of hypotheses are used to identify the significant differences and the results…

Pre-mining trace element and radiation exposure to biota from a breccia pipe uranium mine in the Grand Canyon (Arizona, USA) watershed

USGS Publications Warehouse

Hinck, Jo E.; Cleveland, Danielle; Brumbaugh, William G.; Linder, Greg; Lankton, Julia S.

2017-01-01

The risks to wildlife and humans from uranium (U) mining in the Grand Canyon watershed are largely unknown. In addition to U, other co-occurring ore constituents contribute to risks to biological receptors depending on their toxicological profiles. This study characterizes the pre-mining concentrations of total arsenic (As), cadmium (Cd), copper (Cu), lead (Pb), mercury (Hg), nickel (Ni), selenium (Se), thallium (Tl), U, and zinc (Zn); radiation levels; and histopathology in biota (vegetation, invertebrates, amphibians, birds, and mammals) at the Canyon Mine. Gross alpha levels were below the reporting limit (4 pCi/g) in all samples, and gross beta levels were indicative of background in vegetation (<10–17 pCi/g) and rodents (<10–43.5 pCi/g). Concentrations of U, Tl, Pb, Ni, Cu, and As in vegetation downwind from the mine were likely the result of aeolian transport. Chemical concentrations in rodents and terrestrial invertebrates indicate that surface disturbance during mine construction has not resulted in statistically significant spatial differences in fauna concentrations adjacent to the mine. Chemical concentrations in egg contents and nestlings of non-aquatic birds were less than method quantification limits or did not exceed toxicity thresholds. Bioaccumulation of As, Pb, Se, Tl, and U was evident in Western spadefoot (Spea multiplicata) tadpoles from the mine containment pond; concentrations of As (28.9–31.4 μg/g) and Se (5.81–7.20 μg/g) exceeded toxicity values and were significantly greater than in tadpoles from a nearby water source. Continued evaluation of As and Se in biota inhabiting and forging in the mine containment pond is warranted as mining progresses.

Pre-mining trace element and radiation exposure to biota from a breccia pipe uranium mine in the Grand Canyon (Arizona, USA) watershed.

PubMed

Hinck, Jo Ellen; Cleveland, Danielle; Brumbaugh, William G; Linder, Greg; Lankton, Julia

2017-02-01

The risks to wildlife and humans from uranium (U) mining in the Grand Canyon watershed are largely unknown. In addition to U, other co-occurring ore constituents contribute to risks to biological receptors depending on their toxicological profiles. This study characterizes the pre-mining concentrations of total arsenic (As), cadmium (Cd), copper (Cu), lead (Pb), mercury (Hg), nickel (Ni), selenium (Se), thallium (Tl), U, and zinc (Zn); radiation levels; and histopathology in biota (vegetation, invertebrates, amphibians, birds, and mammals) at the Canyon Mine. Gross alpha levels were below the reporting limit (4 pCi/g) in all samples, and gross beta levels were indicative of background in vegetation (<10-17 pCi/g) and rodents (<10-43.5 pCi/g). Concentrations of U, Tl, Pb, Ni, Cu, and As in vegetation downwind from the mine were likely the result of aeolian transport. Chemical concentrations in rodents and terrestrial invertebrates indicate that surface disturbance during mine construction has not resulted in statistically significant spatial differences in fauna concentrations adjacent to the mine. Chemical concentrations in egg contents and nestlings of non-aquatic birds were less than method quantification limits or did not exceed toxicity thresholds. Bioaccumulation of As, Pb, Se, Tl, and U was evident in Western spadefoot (Spea multiplicata) tadpoles from the mine containment pond; concentrations of As (28.9-31.4 μg/g) and Se (5.81-7.20 μg/g) exceeded toxicity values and were significantly greater than in tadpoles from a nearby water source. Continued evaluation of As and Se in biota inhabiting and forging in the mine containment pond is warranted as mining progresses.

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.

Biomarkers of metals exposure in fish from lead-zinc mining areas of Southeastern Missouri, USA

USGS Publications Warehouse

Schmitt, C.J.; Whyte, J.J.; Roberts, A.P.; Annis, M.L.; May, T.W.; Tillitt, D.E.

2007-01-01

The potential effects of proposed lead-zinc mining in an ecologically sensitive area were assessed by studying a nearby mining district that has been exploited for about 30 y under contemporary environmental regulations and with modern technology. Blood and liver samples representing fish of three species (largescale stoneroller, Campostoma oligolepis, n=91; longear sunfish, Lepomis megalotis, n=105; and northern hog sucker, Hypentelium nigricans, n=20) from 16 sites representing a range of conditions relative to mining activities were collected. Samples were analyzed for metals (also reported in a companion paper) and for biomarkers of metals exposure [erythrocyte ??-aminolevulinic acid dehydratase (ALA-D) activity; concentrations of zinc protoporphyrin (ZPP), iron, and hemoglobin (Hb) in blood; and hepatic metallothionein (MT) gene expression and lipid peroxidation]. Blood lead concentrations were significantly higher and ALA-D activity significantly lower in all species at sites nearest to active lead-zinc mines and in a stream contaminated by historical mining than at reference or downstream sites. ALA-D activity was also negatively correlated with blood lead concentrations in all three species but not with other metals. Iron and Hb concentrations were positively correlated in all three species, but were not correlated with any other metals in blood or liver in any species. MT gene expression was positively correlated with liver zinc concentrations, but neither MT nor lipid peroxidase differences among fish grouped according to lead concentrations were statistically significant. ZPP was not detected by hematofluorometry in most fish, but fish with detectable ZPP were from sites affected by mining. Collectively, these results confirm that metals are released to streams from active lead-zinc mining sites and are accumulated by fish. ?? 2007 Elsevier Inc. All rights reserved.

Heavy metal pollution of coal mine-affected agricultural soils in the northern part of Bangladesh.

PubMed

Bhuiyan, Mohammad A H; Parvez, Lutfar; Islam, M A; Dampare, Samuel B; Suzuki, Shigeyuki

2010-01-15

Total concentrations of heavy metals in the soils of mine drainage and surrounding agricultural fields in the northern part of Bangladesh were determined to evaluate the level of contamination. The average concentrations of Ti, Mn, Zn, Pb, As, Fe, Rb, Sr, Nb and Zr exceeded the world normal averages and, in some cases, Mn, Zn, As and Pb exceeded the toxic limit of the respective metals. Soil pollution assessment was carried out using enrichment factor (EF), geoaccumulation index (I(geo)) and pollution load index (PLI). The soils show significant enrichment with Ti, Mn, Zn, Pb, As, Fe, Sr and Nb, indicating inputs from mining activities. The I(geo) values have revealed that Mn (1.24+/-0.38), Zn (1.49+/-0.58) and Pb (1.63+/-0.38) are significantly accumulated in the study area. The PLIs derived from contamination factors indicate that the distal part of the coal mine-affected area is the most polluted (PLI of 4.02). Multivariate statistical analyses, principal component and cluster analyses, suggest that Mn, Zn, Pb and Ti are derived from anthropogenic sources, particularly coal mining activities, and the extreme proximal and distal parts are heavily contaminated with maximum heavy metals.

The birthweight toll of mining pollution: evidence from the most contaminated mine site in the Andean region.

PubMed

Arrieta, A; Guillen, J

2018-04-26

To assess the effect of mining pollution on birthweight. A retrospective before-and-after study with an untreated comparison group. La Oroya, a mining town in the Peruvian Andes, considered the most contaminated town in the Andean region. All pregnant women who delivered in the social security healthcare system in years 2005, 2006, 2008 and 2009. A total of 214 983 births records were used, 957 from La Oroya and 214 026 from the rest of the country. A difference-in-difference estimation is used to assess the effect of mining pollution on birthweight before and after two business policy changes: a partial environmental improvement and a subsequent closure of smelter operations in La Oroya. Birthweight was compared with a group not affected by the environmental changes in La Oroya. Birthweight in grams. A steep reduction in mining pollution due to the closure of smelter operations in La Oroya showed an increased birthweight of 71.6 g after controlling for socio-economic and medical characteristics. None of the environmental improvements prior to the closure had a statistically significant effect on birthweight. Mining pollution in La Oroya had a negative impact on birthweight. Partial environmental improvements were not enough to improve birthweight. Only after the closure of all mining and smelter operations in La Oroya was a significant gain in birthweight shown. The closure of the most contaminated mine site in the Andean region increased birthweight by 72 g. © 2018 Royal College of Obstetricians and Gynaecologists.

Data Mining and Complex Problems: Case Study in Composite Materials

NASA Technical Reports Server (NTRS)

Rabelo, Luis; Marin, Mario

2009-01-01

Data mining is defined as the discovery of useful, possibly unexpected, patterns and relationships in data using statistical and non-statistical techniques in order to develop schemes for decision and policy making. Data mining can be used to discover the sources and causes of problems in complex systems. In addition, data mining can support simulation strategies by finding the different constants and parameters to be used in the development of simulation models. This paper introduces a framework for data mining and its application to complex problems. To further explain some of the concepts outlined in this paper, the potential application to the NASA Shuttle Reinforced Carbon-Carbon structures and genetic programming is used as an illustration.

Mesothelioma in the Quebec chrysotile mining region

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

Case, B.W.; Armstrong, B.; McDonald, J.C.

Previous studies of incidence of mesothelioma and lung tissue burden in workers and nonworkers in the Quebec chrysotile mining region showed that mesothelioma incidence is very slightly increased in the mining area, and that tremolite, or even commercial amphiboles, are responsible (and chrysotile is not). Recently, one of us (BC) noted an increase in the numbers of cases of mesothelioma coming to autopsy in the mining region. There were 19 cases, all confirmed histologically, since 1982, vs. 6 that we know of in the previous 10 y. Eighteen were occupationally exposed; one was the wife of chrysotile miner/miller. We examinedmore » lung tissue from 9 cases matched to controls of the same sex and age, dying in the same years in the same hospitals, without evidence of malignant disease. We found an excess in cases of typical asbestos bodies; tremolite fibers; and total amphiboles. In univariate linear relative risk analysis, both longer (>8 {mu}m) and shorter fibers are significant. Multivariate analysis indicates that while adjustment of chrysotile lung content for tremolite content eliminates any statistical effect of chrysotile, the reverse comparison retains significance.« less

Effects of soil and topographic factors on vegetation restoration in opencast coal mine dumps located in a loess area

NASA Astrophysics Data System (ADS)

Wang, Jinman; Wang, Hongdan; Cao, Yingui; Bai, Zhongke; Qin, Qian

2016-02-01

Vegetation plays an important role in improving and restoring fragile ecological environments. In the Antaibao opencast coal mine, located in a loess area, the eco-environment has been substantially disturbed by mining activities, and the relationship between the vegetation and environmental factors is not very clear. Therefore, it is crucial to understand the effects of soil and topographic factors on vegetation restoration to improve the fragile ecosystems of damaged land. An investigation of the soil, topography and vegetation in 50 reclamation sample plots in Shanxi Pingshuo Antaibao opencast coal mine dumps was performed. Statistical analyses in this study included one-way ANOVA and significance testing using SPSS 20.0, and multivariate techniques of detrended correspondence analysis (DCA) and redundancy analysis (RDA) using CANOCO 4.5. The RDA revealed the environmental factors that affected vegetation restoration. Various vegetation and soil variables were significantly correlated. The available K and rock content were good explanatory variables, and they were positively correlated with tree volume. The effects of the soil factors on vegetation restoration were higher than those of the topographic factors.

Effects of soil and topographic factors on vegetation restoration in opencast coal mine dumps located in a loess area

PubMed Central

Wang, Jinman; Wang, Hongdan; Cao, Yingui; Bai, Zhongke; Qin, Qian

2016-01-01

Vegetation plays an important role in improving and restoring fragile ecological environments. In the Antaibao opencast coal mine, located in a loess area, the eco-environment has been substantially disturbed by mining activities, and the relationship between the vegetation and environmental factors is not very clear. Therefore, it is crucial to understand the effects of soil and topographic factors on vegetation restoration to improve the fragile ecosystems of damaged land. An investigation of the soil, topography and vegetation in 50 reclamation sample plots in Shanxi Pingshuo Antaibao opencast coal mine dumps was performed. Statistical analyses in this study included one-way ANOVA and significance testing using SPSS 20.0, and multivariate techniques of detrended correspondence analysis (DCA) and redundancy analysis (RDA) using CANOCO 4.5. The RDA revealed the environmental factors that affected vegetation restoration. Various vegetation and soil variables were significantly correlated. The available K and rock content were good explanatory variables, and they were positively correlated with tree volume. The effects of the soil factors on vegetation restoration were higher than those of the topographic factors. PMID:26916152

Effects of soil and topographic factors on vegetation restoration in opencast coal mine dumps located in a loess area.

PubMed

Wang, Jinman; Wang, Hongdan; Cao, Yingui; Bai, Zhongke; Qin, Qian

2016-02-26

Vegetation plays an important role in improving and restoring fragile ecological environments. In the Antaibao opencast coal mine, located in a loess area, the eco-environment has been substantially disturbed by mining activities, and the relationship between the vegetation and environmental factors is not very clear. Therefore, it is crucial to understand the effects of soil and topographic factors on vegetation restoration to improve the fragile ecosystems of damaged land. An investigation of the soil, topography and vegetation in 50 reclamation sample plots in Shanxi Pingshuo Antaibao opencast coal mine dumps was performed. Statistical analyses in this study included one-way ANOVA and significance testing using SPSS 20.0, and multivariate techniques of detrended correspondence analysis (DCA) and redundancy analysis (RDA) using CANOCO 4.5. The RDA revealed the environmental factors that affected vegetation restoration. Various vegetation and soil variables were significantly correlated. The available K and rock content were good explanatory variables, and they were positively correlated with tree volume. The effects of the soil factors on vegetation restoration were higher than those of the topographic factors.

Chemical data and statistical interpretations for rocks and ores from the Ranger uranium mine, Northern Territory, Australia

USGS Publications Warehouse

Nash, J. Thomas; Frishman, David

1983-01-01

Analytical results for 61 elements in 370 samples from the Ranger Mine area are reported. Most of the rocks come from drill core in the Ranger No. 1 and Ranger No. 3 deposits, but 20 samples are from unmineralized drill core more than 1 km from ore. Statistical tests show that the elements Mg, Fe, F, Be, Co, Li, Ni, Pb, Sc, Th, Ti, V, CI, As, Br, Au, Ce, Dy, La Sc, Eu, Tb, Yb, and Tb have positive association with uranium, and Si, Ca, Na, K, Sr, Ba, Ce, and Cs have negative association. For most lithologic subsets Mg, Fe, Li, Cr, Ni, Pb, V, Y, Sm, Sc, Eu, and Yb are significantly enriched in ore-bearing rocks, whereas Ca, Na, K, Sr, Ba, Mn, Ce, and Cs are significantly depleted. These results are consistent with petrographic observations on altered rocks. Lithogeochemistry can aid exploration, but for these rocks requires methods that are expensive and not amenable to routine use.

Respiratory effects of diesel exhaust in salt miners

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

Gamble, J.F.; Jones, W.G.

1983-09-01

The respiratory health of 259 white males working at 5 salt (NaCl) mines was assessed by questionnaire, chest radiographs, and air and He-O/sup 2/ spirometry. Response variables were symptoms, pneumoconiosis, and spirometry. Predictor variables included age, height, smoking, mine, and tenure in diesel-exposed jobs. The purpose was to assess the association of response measures of respiratory health with exposure to diesel exhaust. There were only 2 cases of Grade 1 pneumoconiosis, so no further analysis was done. Comparisons within the study population showed a statistically significant dose-related association of phlegm and diesel exposure. There was a nonsignificant trend for coughmore » and dyspnea, and no association with spirometry. Age- and smoking-adjusted rates of cough, phlegm, and dyspnea were 145, 159, and 93% of an external comparison population. Percent predicted flow rates showed statistically significant reductions, but the reductions were small and there were no dose-response relations. Percent predicted FEV1 and FVC were about 96% of predicted.« less

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

Comparison of thermal signatures of a mine buried in mineral and organic soils

NASA Astrophysics Data System (ADS)

Lamorski, K.; Pregowski, Piotr; Swiderski, Waldemar; Usowicz, B.; Walczak, R. T.

2001-10-01

Values of thermal signature of a mine buried in soils, which ave different properties, were compared using mathematical- statistical modeling. There was applied a model of transport phenomena in the soil, which takes into consideration water and energy transfer. The energy transport is described using Fourier's equation. Liquid phase transport of water is calculated using Richard's model of water flow in porous medium. For the comparison, there were selected two soils: mineral and organic, which differs significantly in thermal and hydrological properties. The heat capacity of soil was estimated using de Vries model. The thermal conductivity was calculated using a statistical model, which incorprates fundamental soil physical properties. The model of soil thermal conductivity was built on the base of heat resistance, two Kirchhoff's laws and polynomial distribution. Soil hydrological properties were described using Mualem-van Genuchten model. The impact of thermal properties of the medium in which a mien had been placed on its thermal signature in the conditions of heat input was presented. The dependence was stated between observed thermal signature of a mine and thermal parameters of the medium.

The Real World Significance of Performance Prediction

ERIC Educational Resources Information Center

Pardos, Zachary A.; Wang, Qing Yang; Trivedi, Shubhendu

2012-01-01

In recent years, the educational data mining and user modeling communities have been aggressively introducing models for predicting student performance on external measures such as standardized tests as well as within-tutor performance. While these models have brought statistically reliable improvement to performance prediction, the real world…

Statistical summaries of water-quality data for streams draining coal-mined areas, southeastern Kansas

USGS Publications Warehouse

Bevans, Hugh E.; Diaz, Arthur M.

1980-01-01

Summaries of descriptive statistics are compiled for 14 data-collection sites located on streams draining areas that have been shaft mined and strip mined for coal in Cherokee and Crawford Counties in southeastern Kansas. These summaries include water-quality data collected from October 1976 through April 1979. Regression equations relating specific conductance and instantaneous streamflow to concentrations of bicarbonate, sulfate, chloride, fluoride, calcium, magnesium, sodium, potassium, silica, and dissolved solids are presented.

Rule-based statistical data mining agents for an e-commerce application

NASA Astrophysics Data System (ADS)

Qin, Yi; Zhang, Yan-Qing; King, K. N.; Sunderraman, Rajshekhar

2003-03-01

Intelligent data mining techniques have useful e-Business applications. Because an e-Commerce application is related to multiple domains such as statistical analysis, market competition, price comparison, profit improvement and personal preferences, this paper presents a hybrid knowledge-based e-Commerce system fusing intelligent techniques, statistical data mining, and personal information to enhance QoS (Quality of Service) of e-Commerce. A Web-based e-Commerce application software system, eDVD Web Shopping Center, is successfully implemented uisng Java servlets and an Oracle81 database server. Simulation results have shown that the hybrid intelligent e-Commerce system is able to make smart decisions for different customers.

Environmental and human exposure assessment monitoring of communities near an abandoned mercury mine in the Philippines: a toxic legacy.

PubMed

Maramba, Nelia P C; Reyes, Jose Paciano; Francisco-Rivera, Ana Trinidad; Panganiban, Lynn Crisanta R; Dioquino, Carissa; Dando, Nerissa; Timbang, Rene; Akagi, Hirokatsu; Castillo, Ma Teresa; Quitoriano, Carmela; Afuang, Maredith; Matsuyama, Akito; Eguchi, Tomomi; Fuchigami, Youko

2006-10-01

Abandoned mines are an important global concern and continue to pose real or potential threats to human safety and health including environmental damage/s. Very few countries had government mine regulation and reclamation policies until the latter part of the century where legal, financial and technical procedures were required for existing mining operations. Major reasons for mine closure may be mainly due to poor economies of the commodity making mining unprofitable, technical difficulties and national security. If the mine is abandoned, more often than not it is the government that shoulders the burden of clean-up, monitoring and remediation. The topic of abandoned mines is complex because of the associated financial and legal liability implications. Abandoned mercury mines have been identified as one of the major concerns because of their significant long-term environmental problems. Primary mercury production is still ongoing in Spain, Kyrgzystan, China, Algeria, Russia and Slovakia while world production declined substantially in the late 1980s. In the Philippines, the mercury mine located southeast of Manila was in operation from 1955 to 1976, before ceasing operation because of the decline in world market price for the commodity. During this time, annual production of mercury was estimated to be about 140,000 kg of mercury yearly. Approximately 2,000,000 t of mine-waste calcines (retorted ore) were produced during mining and roughly 1,000,000 t of these calcines were dumped into nearby Honda Bay to construct a jetty to facilitate mine operations where about 2000 people reside in the nearby three barangays. In October, 1994 the Department of Health received a request from the Provincial Health Office for technical assistance relative to the investigation of increasing complaints of unusual symptoms (e.g. miscarriages, tooth loss, muscle weakness, paralysis, anemia, tremors, etc.) among residents of three barangays. Initial health reports revealed significant elevation of blood mercury levels exceeding the then recommended exposure level of 20ppb in 12 out of the 43 (27.9%) residents examined. The majority of the volunteers were former mine workers. In this study the abnormal findings included gingivitis, mercury lines, gum bleeding and pterydium. The most common neurologic complaints were numbness, weakness, tremors and incoordination. Anemia and elevated liver function tests were also seen in a majority of those examined. The assessment also revealed a probable association between blood mercury level and eosinophilia. The same association was also seen between high mercury levels and the presence of tremors and working in the mercury mine. To date, there are very limited environmental and health studies on the impact of both total and methylmercury that have been undertaken in the Philippines. Thus, this area of study was selected primarily because of its importance as an emerging issue in the country, especially regarding the combined effects of total and methylmercury low-dose and continuous uptake from environmental sources. At present the effects of total mercury exposure combined with MeHg consumption remain an important issue, especially those of low-dose and continuous uptake. Results of the study showed that four (4) species of fish, namely ibis, tabas, lapu-lapu and torsillo, had exceeded the recommended total mercury and methylmercury levels in fish (NV>0.5 microg/gf.w., NV>0.3 microg/gf.w., respectively). Saging and kanuping also exceeded the permissible levels for methylmercury. Total and methylmercury in canned fish, and total mercury in rice, ambient air and drinking water were within the recommended levels, however, additional mercury load from these sources may contribute to the over-all body burden of mercury among residents in the area. Surface water quality at the mining area, Honda Bay and during some monitoring periods at Palawan Bay exceeded total mercury standards (NV>0.002 ng/mL). Soil samples in two sites, namely Tagburos and Honda Bay, exceeded the EPA Region 9 Primary Remediation Goal recommended values for total mercury for residential purposes (NV>23 mg/kg). The hand to mouth activity among infants and children is another significant route for mercury exposure. Statistically significant results were obtained for infants when comparing the results after one year of monitoring for methylmercury levels in hair for both exposed and control sub-groups. Likewise, comparing the initial and final hair methylmercury levels among pregnant women/mothers in the exposed group showed statistically significant (p<0.05) results. Comparing the exposed and control sub-groups' mercury hair levels per sub-group showed statistically significant results among the following: (a) initial and final total mercury hair levels among children, (b) initial and final methylmercury hair levels among children, (c) final total mercury hair levels among pregnant women, (d) initial and final total mercury hair levels among mothers, and (e) initial and final methyl hair levels among mothers.

Littoral assessment of mine burial signatures (LAMBS): buried-landmine hyperspectral data collections

NASA Astrophysics Data System (ADS)

Kenton, Arthur C.; Geci, Duane M.; McDonald, James A.; Ray, Kristofer J.; Thomas, Clayton M.; Holloway, John H., Jr.; Petee, Danny A.; Witherspoon, Ned H.

2003-09-01

The objective of the Office of Naval Research (ONR) Rapid Overt Reconnaissance (ROR) program and the Airborne Littoral Reconnaissance Technologies project's Littoral Assessment of Mine Burial Signatures (LAMBS) contract is to determine if electro-optical spectral discriminants exist that are useful for the detection of land mines located in littoral regions. Statistically significant buried mine overburden and background signature data were collected over a wide spectral range (0.35 to 14 μm) to identify robust spectral features that might serve as discriminants for new airborne sensor concepts. The LAMBS program further expands the hyperspectral database previously collected and analyzed on the U.S. Army's Hyperspectral Mine Detection Phenomenology program [see "Detection of Land Mines with Hyperspectral Data," and "Hyperspectral Mine Detection Phenomenology Program," Proc. SPIE Vol. 3710, pp 917-928 and 819-829, AeroSense April 1999] to littoral areas where tidal, surf, and wind action can additionally modify spectral signatures. This work summarizes the LAMBS buried mine collections conducted at three beach sites - an inland bay beach site (Eglin AFB, FL, Site A-22), an Atlantic beach site (Duck, NC), and a Gulf beach site (Eglin AFB, FL, Site A-15). Characteristics of the spectral signatures of the various dry and damp beach sands are presented. These are then compared to buried land mine signatures observed for the tested background types, burial ages, and environmental conditions experienced.

The History of the Coal Mining Industry and Mining Accidents in the World and Turkey

PubMed Central

Atalay, Figen

2015-01-01

Three per thousand of the world’s coal reserves and 2% of lignite reserves exist in Turkey. Coal mining is the highest ranking industry for accidents and deaths per capita. For this reason, continuous monitoring and more attention should be gıven to the mining industry. In this review, the basic statistical data related to Turkey’s mining and mining disasters are summarized. PMID:29404107

Inferring Intra-Community Microbial Interaction Patterns from Metagenomic Datasets Using Associative Rule Mining Techniques

PubMed Central

Mande, Sharmila S.

2016-01-01

The nature of inter-microbial metabolic interactions defines the stability of microbial communities residing in any ecological niche. Deciphering these interaction patterns is crucial for understanding the mode/mechanism(s) through which an individual microbial community transitions from one state to another (e.g. from a healthy to a diseased state). Statistical correlation techniques have been traditionally employed for mining microbial interaction patterns from taxonomic abundance data corresponding to a given microbial community. In spite of their efficiency, these correlation techniques can capture only 'pair-wise interactions'. Moreover, their emphasis on statistical significance can potentially result in missing out on several interactions that are relevant from a biological standpoint. This study explores the applicability of one of the earliest association rule mining algorithm i.e. the 'Apriori algorithm' for deriving 'microbial association rules' from the taxonomic profile of given microbial community. The classical Apriori approach derives association rules by analysing patterns of co-occurrence/co-exclusion between various '(subsets of) features/items' across various samples. Using real-world microbiome data, the efficiency/utility of this rule mining approach in deciphering multiple (biologically meaningful) association patterns between 'subsets/subgroups' of microbes (constituting microbiome samples) is demonstrated. As an example, association rules derived from publicly available gut microbiome datasets indicate an association between a group of microbes (Faecalibacterium, Dorea, and Blautia) that are known to have mutualistic metabolic associations among themselves. Application of the rule mining approach on gut microbiomes (sourced from the Human Microbiome Project) further indicated similar microbial association patterns in gut microbiomes irrespective of the gender of the subjects. A Linux implementation of the Association Rule Mining (ARM) software (customised for deriving 'microbial association rules' from microbiome data) is freely available for download from the following link: http://metagenomics.atc.tcs.com/arm. PMID:27124399

Inferring Intra-Community Microbial Interaction Patterns from Metagenomic Datasets Using Associative Rule Mining Techniques.

PubMed

Tandon, Disha; Haque, Mohammed Monzoorul; Mande, Sharmila S

2016-01-01

The nature of inter-microbial metabolic interactions defines the stability of microbial communities residing in any ecological niche. Deciphering these interaction patterns is crucial for understanding the mode/mechanism(s) through which an individual microbial community transitions from one state to another (e.g. from a healthy to a diseased state). Statistical correlation techniques have been traditionally employed for mining microbial interaction patterns from taxonomic abundance data corresponding to a given microbial community. In spite of their efficiency, these correlation techniques can capture only 'pair-wise interactions'. Moreover, their emphasis on statistical significance can potentially result in missing out on several interactions that are relevant from a biological standpoint. This study explores the applicability of one of the earliest association rule mining algorithm i.e. the 'Apriori algorithm' for deriving 'microbial association rules' from the taxonomic profile of given microbial community. The classical Apriori approach derives association rules by analysing patterns of co-occurrence/co-exclusion between various '(subsets of) features/items' across various samples. Using real-world microbiome data, the efficiency/utility of this rule mining approach in deciphering multiple (biologically meaningful) association patterns between 'subsets/subgroups' of microbes (constituting microbiome samples) is demonstrated. As an example, association rules derived from publicly available gut microbiome datasets indicate an association between a group of microbes (Faecalibacterium, Dorea, and Blautia) that are known to have mutualistic metabolic associations among themselves. Application of the rule mining approach on gut microbiomes (sourced from the Human Microbiome Project) further indicated similar microbial association patterns in gut microbiomes irrespective of the gender of the subjects. A Linux implementation of the Association Rule Mining (ARM) software (customised for deriving 'microbial association rules' from microbiome data) is freely available for download from the following link: http://metagenomics.atc.tcs.com/arm.

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

Mining Claim Activity on Federal Land for the Period 1976 through 2003

USGS Publications Warehouse

Causey, J. Douglas

2005-01-01

Previous reports on mining claim records provided information and statistics (number of claims) using data from the U.S. Bureau of Land Management's (BLM) Mining Claim Recordation System. Since that time, BLM converted their mining claim data to the Legacy Repost 2000 system (LR2000). This report describes a process to extract similar statistical data about mining claims from LR2000 data using different software and procedures than were used in the earlier work. A major difference between this process and the previous work is that every section that has a mining claim record is assigned a value. This is done by proportioning a claim between each section in which it is recorded. Also, the mining claim data in this report includes all BLM records, not just the western states. LR2000 mining claim database tables for the United States were provided by BLM in text format and imported into a Microsoft? Access2000 database in January, 2004. Data from two tables in the BLM LR2000 database were summarized through a series of database queries to determine a number that represents active mining claims in each Public Land Survey (PLS) section for each of the years from 1976 to 2002. For most of the area, spatial databases are also provided. The spatial databases are only configured to work with the statistics provided in the non-spatial data files. They are suitable for geographic information system (GIS)-based regional assessments at a scale of 1:100,000 or smaller (for example, 1:250,000).

Microbial and geochemical assessment of bauxitic un-mined and post-mined chronosequence soils from Mocho Mountains, Jamaica.

PubMed

Lewis, Dawn E; Chauhan, Ashvini; White, John R; Overholt, Will; Green, Stefan J; Jasrotia, Puja; Wafula, Denis; Jagoe, Charles

2012-10-01

Microorganisms are very sensitive to environmental change and can be used to gauge anthropogenic impacts and even predict restoration success of degraded environments. Here, we report assessment of bauxite mining activities on soil biogeochemistry and microbial community structure using un-mined and three post-mined sites in Jamaica. The post-mined soils represent a chronosequence, undergoing restoration since 1987, 1997, and 2007. Soils were collected during dry and wet seasons and analyzed for pH, organic matter (OM), total carbon (TC), nitrogen (TN), and phosphorus. The microbial community structure was assessed through quantitative PCR and massively parallel bacterial ribosomal RNA (rRNA) gene sequencing. Edaphic factors and microbial community composition were analyzed using multivariate statistical approaches and revealed a significant, negative impact of mining on soil that persisted even after greater than 20 years of restoration. Seasonal fluctuations contributed to variation in measured soil properties and community composition, but they were minor in comparison to long-term effects of mining. In both seasons, post-mined soils were higher in pH but OM, TC, and TN decreased. Bacterial rRNA gene analyses demonstrated a general decrease in diversity in post-mined soils and up to a 3-log decrease in rRNA gene abundance. Community composition analyses demonstrated that bacteria from the Proteobacteria (α, β, γ, δ), Acidobacteria, and Firmicutes were abundant in all soils. The abundance of Firmicutes was elevated in newer post-mined soils relative to the un-mined soil, and this contrasted a decrease, relative to un-mined soils, in proteobacterial and acidobacterial rRNA gene abundances. Our study indicates long-lasting impacts of mining activities to soil biogeochemical and microbial properties with impending loss in soil productivity.

Geochemistry of mercury in tropical swamps impacted by gold mining.

PubMed

Marrugo-Negrete, José; Pinedo-Hernández, José; Díez, Sergi

2015-09-01

Artisanal and small-scale gold mining (ASGM) poses a serious threat to the local environment. Colombia has very active ASGM activities, where mercury (Hg) ends in piles of mining waste, soils, and waterways. In this study, we assessed Hg speciation and bioavailability in sediments of two tropical swamps, impacted by ASGM. In Ayapel swamp, total Hg (T-Hg) concentrations in sediments ranged between 145 and 313 ng g(-1) dry weight (dw) (mean: 235 ± 49 ng g(-1) dw), whereas Grande Achi swamp levels are 3-fold higher (range: 543-1021 ng g(-1) dw; mean: 722 ± 145 ng g(-1) dw). Even though lower levels of Hg were found in Ayapel, methylation was found to be significantly higher than in Grande Achi, and it is significantly higher in the dry than in the rainy season for both swamps. This increased methylation is linked to the statistically significant correlation between T-Hg, MeHg and organic matter in the Ayapel swamp. In fact, Hg content in both swamps is mainly associated to the organic fraction (Hg-o), with a higher statistically significant difference in Ayapel (43 ± 5%) compared to Grande Achi (33 ± 5%). On the other hand, a significant percentage (30 ± 6%) of elemental Hg fraction (Hg-e) was found in Grande Achi, directly related with Hg released during the gold recovery process from upstream ASGM sites. The percentage of the bioavailable fraction (Hg-w and Hg-h) is elevated (up to 15%), indicating a potential risk to the aquatic environment and human health because these labile Hg species could enter the water column and bioaccumulate in biota. Copyright © 2015 Elsevier Ltd. All rights reserved.

TOY SAFETY SURVEILLANCE FROM ONLINE REVIEWS

PubMed Central

Winkler, Matt; Abrahams, Alan S.; Gruss, Richard; Ehsani, Johnathan P.

2016-01-01

Toy-related injuries account for a significant number of childhood injuries and the prevention of these injuries remains a goal for regulatory agencies and manufacturers. Text-mining is an increasingly prevalent method for uncovering the significance of words using big data. This research sets out to determine the effectiveness of text-mining in uncovering potentially dangerous children’s toys. We develop a danger word list, also known as a ‘smoke word’ list, from injury and recall text narratives. We then use the smoke word lists to score over one million Amazon reviews, with the top scores denoting potential safety concerns. We compare the smoke word list to conventional sentiment analysis techniques, in terms of both word overlap and effectiveness. We find that smoke word lists are highly distinct from conventional sentiment dictionaries and provide a statistically significant method for identifying safety concerns in children’s toy reviews. Our findings indicate that text-mining is, in fact, an effective method for the surveillance of safety concerns in children’s toys and could be a gateway to effective prevention of toy-product-related injuries. PMID:27942092

Mining Claim Activity on Federal Land in the United States

USGS Publications Warehouse

Causey, J. Douglas

2007-01-01

Several statistical compilations of mining claim activity on Federal land derived from the Bureau of Land Management's LR2000 database have previously been published by the U.S Geological Survey (USGS). The work in the 1990s did not include Arkansas or Florida. None of the previous reports included Alaska because it is stored in a separate database (Alaska Land Information System) and is in a different format. This report includes data for all states for which there are Federal mining claim records, beginning in 1976 and continuing to the present. The intent is to update the spatial and statistical data associated with this report on an annual basis, beginning with 2005 data. The statistics compiled from the databases are counts of the number of active mining claims in a section of land each year from 1976 to the present for all states within the United States. Claim statistics are subset by lode and placer types, as well as a dataset summarizing all claims including mill site and tunnel site claims. One table presents data by case type, case status, and number of claims in a section. This report includes a spatial database for each state in which mining claims were recorded, except North Dakota, which only has had two claims. A field is present that allows the statistical data to be joined to the spatial databases so that spatial displays and analysis can be done by using appropriate geographic information system (GIS) software. The data show how mining claim activity has changed in intensity, space, and time. Variations can be examined on a state, as well as a national level. The data are tied to a section of land, approximately 640 acres, which allows it to be used at regional, as well as local scale. The data only pertain to Federal land and mineral estate that was open to mining claim location at the time the claims were staked.

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

A sentence sliding window approach to extract protein annotations from biomedical articles

PubMed Central

Krallinger, Martin; Padron, Maria; Valencia, Alfonso

2005-01-01

Background Within the emerging field of text mining and statistical natural language processing (NLP) applied to biomedical articles, a broad variety of techniques have been developed during the past years. Nevertheless, there is still a great ned of comparative assessment of the performance of the proposed methods and the development of common evaluation criteria. This issue was addressed by the Critical Assessment of Text Mining Methods in Molecular Biology (BioCreative) contest. The aim of this contest was to assess the performance of text mining systems applied to biomedical texts including tools which recognize named entities such as genes and proteins, and tools which automatically extract protein annotations. Results The "sentence sliding window" approach proposed here was found to efficiently extract text fragments from full text articles containing annotations on proteins, providing the highest number of correctly predicted annotations. Moreover, the number of correct extractions of individual entities (i.e. proteins and GO terms) involved in the relationships used for the annotations was significantly higher than the correct extractions of the complete annotations (protein-function relations). Conclusion We explored the use of averaging sentence sliding windows for information extraction, especially in a context where conventional training data is unavailable. The combination of our approach with more refined statistical estimators and machine learning techniques might be a way to improve annotation extraction for future biomedical text mining applications. PMID:15960831

Polymorphisms in genes encoding potential mercury transporters and urine mercury concentrations in populations exposed to mercury vapor from gold mining.

PubMed

Engström, Karin; Ameer, Shegufta; Bernaudat, Ludovic; Drasch, Gustav; Baeuml, Jennifer; Skerfving, Staffan; Bose-O'Reilly, Stephan; Broberg, Karin

2013-01-01

Elemental mercury (Hg0) is widely used in small-scale gold mining. Persons working or living in mining areas have high urinary concentrations of Hg (U-Hg). Differences in genes encoding potential Hg-transporters may affect uptake and elimination of Hg. We aimed to identify single nucleotide polymorphisms (SNPs) in Hg-transporter genes that modify U-Hg. Men and women (1,017) from Indonesia, the Philippines, Tanzania, and Zimbabwe were classified either as controls (no Hg exposure from gold mining) or as having low (living in a gold-mining area) or high exposure (working as gold miners). U-Hg was analyzed by cold-vapor atomic absorption spectrometry. Eighteen SNPs in eight Hg-transporter genes were analyzed. U-Hg concentrations were higher among ABCC2/MRP2 rs1885301 A-allele carriers than among GG homozygotes in all populations, though differences were not statistically significant in most cases. MRP2 SNPs showed particularly strong associations with U-Hg in the subgroup with highest exposure (miners in Zimbabwe), whereas rs1885301 A-allele carriers had higher U-Hg than GG homozygotes [geometric mean (GM): 36.4 µg/g creatinine vs. 21.9; p = 0.027], rs2273697 GG homozygotes had higher U-Hg than A-allele carriers (GM: 37.4 vs. 16.7; p = 0.001), and rs717620 A-allele carriers had higher U-Hg than GG homozygotes (GM: 83 vs. 28; p = 0.084). The SLC7A5/LAT1 rs33916661 GG genotype was associated with higher U-Hg in all populations (statistically significant for all Tanzanians combined). SNPs in SLC22A6/OAT1 (rs4149170) and SLC22A8/OAT3 (rs4149182) were associated with U-Hg mainly in the Tanzanian study groups. SNPs in putative Hg-transporter genes may influence U-Hg concentrations.

Polymorphisms in Genes Encoding Potential Mercury Transporters and Urine Mercury Concentrations in Populations Exposed to Mercury Vapor from Gold Mining

PubMed Central

Ameer, Shegufta; Bernaudat, Ludovic; Drasch, Gustav; Baeuml, Jennifer; Skerfving, Staffan; Bose-O’Reilly, Stephan; Broberg, Karin

2012-01-01

Background: Elemental mercury (Hg0) is widely used in small-scale gold mining. Persons working or living in mining areas have high urinary concentrations of Hg (U-Hg). Differences in genes encoding potential Hg-transporters may affect uptake and elimination of Hg. Objective: We aimed to identify single nucleotide polymorphisms (SNPs) in Hg-transporter genes that modify U-Hg. Methods: Men and women (1,017) from Indonesia, the Philippines, Tanzania, and Zimbabwe were classified either as controls (no Hg exposure from gold mining) or as having low (living in a gold-mining area) or high exposure (working as gold miners). U-Hg was analyzed by cold-vapor atomic absorption spectrometry. Eighteen SNPs in eight Hg-transporter genes were analyzed. Results: U-Hg concentrations were higher among ABCC2/MRP2 rs1885301 A–allele carriers than among GG homozygotes in all populations, though differences were not statistically significant in most cases. MRP2 SNPs showed particularly strong associations with U-Hg in the subgroup with highest exposure (miners in Zimbabwe), whereas rs1885301 A–allele carriers had higher U-Hg than GG homozygotes [geometric mean (GM): 36.4 µg/g creatinine vs. 21.9; p = 0.027], rs2273697 GG homozygotes had higher U-Hg than A–allele carriers (GM: 37.4 vs. 16.7; p = 0.001), and rs717620 A–allele carriers had higher U-Hg than GG homozygotes (GM: 83 vs. 28; p = 0.084). The SLC7A5/LAT1 rs33916661 GG genotype was associated with higher U-Hg in all populations (statistically significant for all Tanzanians combined). SNPs in SLC22A6/OAT1 (rs4149170) and SLC22A8/OAT3 (rs4149182) were associated with U-Hg mainly in the Tanzanian study groups. Conclusions: SNPs in putative Hg-transporter genes may influence U-Hg concentrations. PMID:23052037

Effects of human and organizational deficiencies on workers'safety behavior in a mining site in Iran.

PubMed

Mirzaei Aliabadi, Mostafa; Aghaei, Hamed; Kalatpour, Omid; Soltanian, Ali Reza; SeyedTabib, Maryam

2018-05-18

Mines are a dangerous workplace worldwide with a high accident rate. According to the Statistical Center of Iran, the number of occupational accidents in Iranian mines has increased in recent years. This study determined and explained human and organizational deficiencies influencing Iranian mining accidents. In this study, the data associated with 305 mining accidents were investigated. The data were analyzed based on a systems analysis approach to identify critical deficiencies in organizational influences, unsafe supervision, preconditions for unsafe acts, and workers' unsafe acts. Partial Least Square Structural Equation Modeling [PLS-SEM] was utilized for modeling the interactions between these deficiencies. It was demonstrated that organizational deficiencies had a direct positive effect on workers' violations (path coefficient=0.16) and workers' errors (path coefficient=0.23). The effect of unsafe supervision on workers' violations and workers' errors was also significant with the path coefficients of 0.14 and 0.20. Likewise, preconditions for unsafe acts also had a significant effect on both workers' violations (path coefficient=0.16) and workers' errors (path coefficient=0.21). Moreover, organizational deficiencies had an indirect positive effect on workers' unsafe acts mediated by unsafe supervision and preconditions for unsafe acts. Among the variables examined in the current study, organizational influences had the strongest impacts on workers' unsafe acts. Organizational deficiencies are the main causes of accidents in mining sectors that affects all other aspects of system safety. For preventing occupational accidents, organizational deficiencies should be modified first.

Assessment of the natural sources of particulate matter on the opencast mines air quality.

PubMed

Huertas, J I; Huertas, M E; Cervantes, G; Díaz, J

2014-09-15

Particulate matter is the main air pollutant in open pit mining areas. Preferred models that simulate the dispersion of the particles have been used to assess the environmental impact of the mining activities. Results obtained through simulation have been compared with the particle concentration measured in several sites and a coefficient of determination R(2)<0.78 has been reported. This result indicates that in the open pit mining areas there may be additional sources of particulate matter that have not been considered in the modeling process. This work proposes that the unconsidered sources of emissions are of regional scope such as the re-suspension particulate matter due to the wind action over uncovered surfaces. Furthermore, this work proposes to estimate the impact of such emissions on air quality as a function of the present and past meteorological conditions. A statistical multiple regression model was implemented in one of the world's largest open pit coal mining regions which is located in northern Colombia. Data from 9 particle-concentration monitoring stations and 3 meteorological stations obtained from 2009 to 2012 were statistically compared. Results confirmed the existence of a high linear relation (R(2)>0.95) between meteorological variables and particulate matter concentration being humidity, humidity of the previous day and temperature, the meteorological variables that contributed most significantly in the variance of the particulate matter concentration measured in the mining area while the contribution of the AERMOD estimations to the short term TSP (Total Suspended Particles) measured concentrations was negligible (<5%). The multiple regression model was used to identify the meteorological condition that leads to pollution episodes. It was found that conditions drier than 54% lead to pollution episodes while humidities greater than 70% maintain safe air quality conditions in the mining region in northern Colombia. Copyright © 2014 Elsevier B.V. All rights reserved.

Metal contamination in environmental media in residential ...

EPA Pesticide Factsheets

Hard-rock mining for metals, such as gold, silver, copper, zinc, iron and others, is recognized to have a significant impact on the environmental media, soil and water, in particular. Toxic contaminants released from mine waste to surface water and groundwater is the primary concern, but human exposure to soil contaminants either directly, via inhalation of airborne dust particles, or indirectly, via food chain (ingestion of animal products and/or vegetables grown in contaminated areas), is also, significant. In this research, we analyzed data collected in 2007, as part of a larger environmental study performed in the Rosia Montana area in Transylvania, to provide the Romanian governmental authorities with data on the levels of metal contamination in environmental media from this historical mining area. The data were also considered in policy decision to address mining-related environmental concerns in the area. We examined soil and water data collected from residential areas near the mining sites to determine relationships among metals analyzed in these different environmental media, using the correlation procedure in SAS statistical software. Results for residential soil and water analysis indicate that the average values for arsenic (As) (85 mg/kg), cadmium (Cd) (3.2 mg/kg), mercury (Hg) (2.3 mg/kg) and lead (Pb) (92 mg/kg) exceeded the Romanian regulatory exposure levels [the intervention thresholds for residential soil in case of As (25 mg/kg) and Hg

Data-driven modeling of background and mine-related acidity and metals in river basins

USGS Publications Warehouse

Friedel, Michael J

2013-01-01

A novel application of self-organizing map (SOM) and multivariate statistical techniques is used to model the nonlinear interaction among basin mineral-resources, mining activity, and surface-water quality. First, the SOM is trained using sparse measurements from 228 sample sites in the Animas River Basin, Colorado. The model performance is validated by comparing stochastic predictions of basin-alteration assemblages and mining activity at 104 independent sites. The SOM correctly predicts (>98%) the predominant type of basin hydrothermal alteration and presence (or absence) of mining activity. Second, application of the Davies–Bouldin criteria to k-means clustering of SOM neurons identified ten unique environmental groups. Median statistics of these groups define a nonlinear water-quality response along the spatiotemporal hydrothermal alteration-mining gradient. These results reveal that it is possible to differentiate among the continuum between inputs of background and mine-related acidity and metals, and it provides a basis for future research and empirical model development.

The extent and consequences of p-hacking in science.

PubMed

Head, Megan L; Holman, Luke; Lanfear, Rob; Kahn, Andrew T; Jennions, Michael D

2015-03-01

A focus on novel, confirmatory, and statistically significant results leads to substantial bias in the scientific literature. One type of bias, known as "p-hacking," occurs when researchers collect or select data or statistical analyses until nonsignificant results become significant. Here, we use text-mining to demonstrate that p-hacking is widespread throughout science. We then illustrate how one can test for p-hacking when performing a meta-analysis and show that, while p-hacking is probably common, its effect seems to be weak relative to the real effect sizes being measured. This result suggests that p-hacking probably does not drastically alter scientific consensuses drawn from meta-analyses.

Evaluation of an exposure assessment used in epidemiological studies of diesel exhaust and lung cancer in underground mines

PubMed Central

Crump, Kenny; Van Landingham, Cynthia

2012-01-01

NIOSH/NCI (National Institute of Occupational Safety and Health and National Cancer Institute) developed exposure estimates for respirable elemental carbon (REC) as a surrogate for exposure to diesel exhaust (DE) for different jobs in eight underground mines by year beginning in the 1940s—1960s when diesel equipment was first introduced into these mines. These estimates played a key role in subsequent epidemiological analyses of the potential relationship between exposure to DE and lung cancer conducted in these mines. We report here on a reanalysis of some of the data from this exposure assessment. Because samples of REC were limited primarily to 1998–2001, NIOSH/NCI used carbon monoxide (CO) as a surrogate for REC. In addition, because CO samples were limited, particularly in the earlier years, they used the ratio of diesel horsepower (HP) to the mine air exhaust rate as a surrogate for CO. There are considerable uncertainties connected with each of these surrogate-based steps. The estimates of HP appear to involve considerable uncertainty, although we had no data upon which to evaluate the magnitude of this uncertainty. A sizable percentage (45%) of the CO samples used in the HP to CO model was below the detection limit which required NIOSH/NCI to assign CO values to these samples. In their preferred REC estimates, NIOSH/NCI assumed a linear relation between C0 and REC, although they provided no credible support for that assumption. Their assumption of a stable relationship between HP and CO also is questionable, and our reanalysis found a statistically significant relationship in only one-half of the mines. We re-estimated yearly REC exposures mainly using NIOSH/NCI methods but with some important differences: (i) rather than simply assuming a linear relationship, we used data from the mines to estimate the CO—REC relationship; (ii) we used a different method for assigning values to nondetect CO measurements; and (iii) we took account of statistical uncertainty to estimate bounds for REC exposures. This exercise yielded significantly different exposure estimates than estimated by NIOSH/NCI. However, this analysis did not incorporate the full range of uncertainty in REC exposures because of additional uncertainties in the assumptions underlying the modeling and in the underlying data (e.g. HP and mine exhaust rates). Estimating historical exposures in a cohort is generally a very difficult undertaking. However, this should not prevent one from recognizing the uncertainty in the resulting estimates in any use made of them. PMID:22594934

Quality-of-water data and statistical summary for selected coal-mined strip pits in Crawford and Cherokee counties, southeastern Kansas

USGS Publications Warehouse

Pope, Larry M.; Diaz, A.M.

1982-01-01

Quality-of-water data, collected October 21-23, 1980, and a statistical summary are presented for 42 coal-mined strip pits in Crawford and Cherokee Counties, Southeastern Kansas. The statistical summary includes minimum and maximum observed values , mean, and standard deviation. Simple linear regression equations relating specific conductance, dissolved solids, and acidity to concentrations of dissolved solids, sulfate, calcium, and magnesium, potassium, aluminum, and iron are also presented. (USGS)

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

Schuman, G.E.; Stahl, P.D.; Williams, S.E.

Reestablishment of Wyoming big sagebrush (Artemisia tridentata ssp. wyomingensis) on mined lands has been difficult in the past even though it is widespread in the western US. Its reestablishment on mined lands has recently become law where wildlife is one of the post-mining land uses and it represented the primary premining shrub species. One hypothesis thought to contribute to its difficult reestablishment is the reduce lack of mycorrhizae inoculum present in the disturbed topsoil and the resulting effect on the seedling`s ability to extract water from the soil under the arid/semiarid climate of this region. A greenhouse study was conductedmore » to evaluate the effect of mycorrhizae on sagebrush seedling water stress tolerance. Seedling ages evaluated ranged from 30 to 150 days. Seedling survival was greater for mycorrhizal seedlings compared to non-mycorrhizal seedlings when soil moisture tension was {minus}2.5 to {minus}3.8 MPa. At all ages, the degree of soil dryness necessary to cause sagebrush seedling mortality was significantly greater for mycorrhizal than non-mycorrhizal seedlings. Seedling age and mycorrhizal infection exhibited a significant statistical interaction; suggesting that as the sagebrush seedling aged, the benefits of arbuscular mycorrhizae (AM) increased the plants water stress tolerance. These findings lead the authors to conclude that topsoil management that prevents/reduces the loss of AM inoculum in the topsoil will significantly enhance the success of sagebrush establishment on mined lands.« less

Metal contamination in environmental media in residential areas around Romanian mining sites.

PubMed

Neamtiu, Iulia A; Al-Abed, Souhail R; McKernan, John L; Baciu, Calin L; Gurzau, Eugen S; Pogacean, Anca O; Bessler, Scott M

2017-03-01

Hard-rock mining for metals, such as gold, silver, copper, zinc, iron and others, is recognized to have a significant impact on the environmental media, soil and water, in particular. Toxic contaminants released from mine waste to surface water and groundwater is the primary concern, but human exposure to soil contaminants either directly, via inhalation of airborne dust particles, or indirectly, via food chain (ingestion of animal products and/or vegetables grown in contaminated areas), is also, significant. In this research, we analyzed data collected in 2007, as part of a larger environmental study performed in the Rosia Montana area in Transylvania, to provide the Romanian governmental authorities with data on the levels of metal contamination in environmental media from this historical mining area. The data were also considered in policy decision to address mining-related environmental concerns in the area. We examined soil and water data collected from residential areas near the mining sites to determine relationships among metals analyzed in these different environmental media, using the correlation procedure in the SAS statistical software. Results for residential soil and water analysis indicate that the average values for arsenic (As) (85 mg/kg), cadmium (Cd) (3.2 mg/kg), mercury (Hg) (2.3 mg/kg) and lead (Pb) (92 mg/kg) exceeded the Romanian regulatory exposure levels [the intervention thresholds for residential soil in case of As (25 mg/kg) and Hg (2 mg/kg), and the alert thresholds in case of Pb (50 mg/kg) and Cd (3 mg/kg)]. Average metal concentrations in drinking water did not exceed the maximum contaminant level (MCL) imposed by the Romanian legislation, but high metal concentrations were found in surface water from Rosia creek, downstream from the former mining area.

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.

Littoral Assessment of Mine Burial Signatures (LAMBS) buried land mine/background spectral signature analyses

USGS Publications Warehouse

Kenton, A.C.; Geci, D.M.; Ray, K.J.; Thomas, C.M.; Salisbury, J.W.; Mars, J.C.; Crowley, J.K.; Witherspoon, N.H.; Holloway, J.H.; Harmon R.S.Broach J.T.Holloway, Jr. J.H.

2004-01-01

The objective of the Office of Naval Research (ONR) Rapid Overt Reconnaissance (ROR) program and the Airborne Littoral Reconnaissance Technologies (ALRT) project's LAMBS effort is to determine if electro-optical spectral discriminants exist that are useful for the detection of land mines in littoral regions. Statistically significant buried mine overburden and background signature data were collected over a wide spectral range (0.35 to 14 ??m) to identify robust spectral features that might serve as discriminants for new airborne sensor concepts. LAMBS has expanded previously collected databases to littoral areas - primarily dry and wet sandy soils - where tidal, surf, and wind conditions can severely modify spectral signatures. At AeroSense 2003, we reported completion of three buried mine collections at an inland bay, Atlantic and Gulf of Mexico beach sites.1 We now report LAMBS spectral database analyses results using metrics which characterize the detection performance of general types of spectral detection algorithms. These metrics include mean contrast, spectral signal-to-clutter, covariance, information content, and spectral matched filter analyses. Detection performance of the buried land mines was analyzed with regard to burial age, background type, and environmental conditions. These analyses considered features observed due to particle size differences, surface roughness, surface moisture, and compositional differences.

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).

RADSS: an integration of GIS, spatial statistics, and network service for regional data mining

NASA Astrophysics Data System (ADS)

Hu, Haitang; Bao, Shuming; Lin, Hui; Zhu, Qing

2005-10-01

Regional data mining, which aims at the discovery of knowledge about spatial patterns, clusters or association between regions, has widely applications nowadays in social science, such as sociology, economics, epidemiology, crime, and so on. Many applications in the regional or other social sciences are more concerned with the spatial relationship, rather than the precise geographical location. Based on the spatial continuity rule derived from Tobler's first law of geography: observations at two sites tend to be more similar to each other if the sites are close together than if far apart, spatial statistics, as an important means for spatial data mining, allow the users to extract the interesting and useful information like spatial pattern, spatial structure, spatial association, spatial outlier and spatial interaction, from the vast amount of spatial data or non-spatial data. Therefore, by integrating with the spatial statistical methods, the geographical information systems will become more powerful in gaining further insights into the nature of spatial structure of regional system, and help the researchers to be more careful when selecting appropriate models. However, the lack of such tools holds back the application of spatial data analysis techniques and development of new methods and models (e.g., spatio-temporal models). Herein, we make an attempt to develop such an integrated software and apply it into the complex system analysis for the Poyang Lake Basin. This paper presents a framework for integrating GIS, spatial statistics and network service in regional data mining, as well as their implementation. After discussing the spatial statistics methods involved in regional complex system analysis, we introduce RADSS (Regional Analysis and Decision Support System), our new regional data mining tool, by integrating GIS, spatial statistics and network service. RADSS includes the functions of spatial data visualization, exploratory spatial data analysis, and spatial statistics. The tool also includes some fundamental spatial and non-spatial database in regional population and environment, which can be updated by external database via CD or network. Utilizing this data mining and exploratory analytical tool, the users can easily and quickly analyse the huge mount of the interrelated regional data, and better understand the spatial patterns and trends of the regional development, so as to make a credible and scientific decision. Moreover, it can be used as an educational tool for spatial data analysis and environmental studies. In this paper, we also present a case study on Poyang Lake Basin as an application of the tool and spatial data mining in complex environmental studies. At last, several concluding remarks are discussed.

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.

Advances in Machine Learning and Data Mining for Astronomy

NASA Astrophysics Data System (ADS)

Way, Michael J.; Scargle, Jeffrey D.; Ali, Kamal M.; Srivastava, Ashok N.

2012-03-01

Advances in Machine Learning and Data Mining for Astronomy documents numerous successful collaborations among computer scientists, statisticians, and astronomers who illustrate the application of state-of-the-art machine learning and data mining techniques in astronomy. Due to the massive amount and complexity of data in most scientific disciplines, the material discussed in this text transcends traditional boundaries between various areas in the sciences and computer science. The book's introductory part provides context to issues in the astronomical sciences that are also important to health, social, and physical sciences, particularly probabilistic and statistical aspects of classification and cluster analysis. The next part describes a number of astrophysics case studies that leverage a range of machine learning and data mining technologies. In the last part, developers of algorithms and practitioners of machine learning and data mining show how these tools and techniques are used in astronomical applications. With contributions from leading astronomers and computer scientists, this book is a practical guide to many of the most important developments in machine learning, data mining, and statistics. It explores how these advances can solve current and future problems in astronomy and looks at how they could lead to the creation of entirely new algorithms within the data mining community.

[Retrieval of Copper Pollution Information from Hyperspectral Satellite Data in a Vegetation Cover Mining Area].

PubMed

Qu, Yong-hua; Jiao, Si-hong; Liu, Su-hong; Zhu, Ye-qing

2015-11-01

Heavy metal mining activities have caused the complex influence on the ecological environment of the mining regions. For example, a large amount of acidic waste water containing heavy metal ions have be produced in the process of copper mining which can bring serious pollution to the ecological environment of the region. In the previous research work, bare soil is mainly taken as the research target when monitoring environmental pollution, and thus the effects of land surface vegetation have been ignored. It is well known that vegetation condition is one of the most important indictors to reflect the ecological change in a certain region and there is a significant linkage between the vegetation spectral characteristics and the heavy metal when the vegetation is effected by the heavy metal pollution. It means the vegetation is sensitive to heavy metal pollution by their physiological behaviors in response to the physiological ecology change of their growing environment. The conventional methods, which often rely on large amounts of field survey data and laboratorial chemical analysis, are time consuming and costing a lot of material resources. The spectrum analysis method using remote sensing technology can acquire the information of the heavy mental content in the vegetation without touching it. However, the retrieval of that information from the hyperspectral data is not an easy job due to the difficulty in figuring out the specific band, which is sensitive to the specific heavy metal, from a huge number of hyperspectral bands. Thus the selection of the sensitive band is the key of the spectrum analysis method. This paper proposed a statistical analysis method to find the feature band sensitive to heavy metal ion from the hyperspectral data and to then retrieve the metal content using the field survey data and the hyperspectral images from China Environment Satellite HJ-1. This method selected copper ion content in the leaves as the indicator of copper pollution level, using stepwise multiple linear regression and cross validation on the dataset which is consisting of 44 groups of copper ion content information in the polluted vegetation leaves from Dexing Copper Mine in Jiangxi Province to build up a statistical model by also incorporating the HJ-1 satellite images. This model was then used to estimate the copper content distribution over the whole research area at Dexing Copper Mine. The result has shown that there is strong statistical significance of the model which revealed the most sensitive waveband to copper ion is located at 516 nm. The distribution map illustrated that the copper ion content is generally in the range of 0-130 mg · kg⁻¹ in the vegetation covering area at Dexing Copper Mine and the most seriously polluted area is located at the South-east corner of Dexing City as well as the mining spots with a higher value between 80 and 100 mg · kg⁻¹. This result is consistent with the ground observation experiment data. The distribution map can certainly provide some important basic data on the copper pollution monitoring and treatment.

Data mining in child welfare.

PubMed

Schoech, D; Quinn, A; Rycraft, J R

2000-01-01

Data mining is the sifting through of voluminous data to extract knowledge for decision making. This article illustrates the context, concepts, processes, techniques, and tools of data mining, using statistical and neural network analyses on a dataset concerning employee turnover. The resulting models and their predictive capability, advantages and disadvantages, and implications for decision support are highlighted.

Applying robust design to study the effects of stratigraphic characteristics on brittle failure and bump potential in a coal mine

PubMed Central

Kim, Bo-Hyun; Larson, Mark K.; Lawson, Heather E.

2018-01-01

Bumps and other types of dynamic failure have been a persistent, worldwide problem in the underground coal mining industry, spanning decades. For example, in just five states in the U.S. from 1983 to 2014, there were 388 reportable bumps. Despite significant advances in mine design tools and mining practices, these events continue to occur. Many conditions have been associated with bump potential, such as the presence of stiff units in the local geology. The effect of a stiff sandstone unit on the potential for coal bumps depends on the location of the stiff unit in the stratigraphic column, the relative stiffness and strength of other structural members, and stress concentrations caused by mining. This study describes the results of a robust design to consider the impact of different lithologic risk factors impacting dynamic failure risk. Because the inherent variability of stratigraphic characteristics in sedimentary formations, such as thickness, engineering material properties, and location, is significant and the number of influential parameters in determining a parametric study is large, it is impractical to consider every simulation case by varying each parameter individually. Therefore, to save time and honor the statistical distributions of the parameters, it is necessary to develop a robust design to collect sufficient sample data and develop a statistical analysis method to draw accurate conclusions from the collected data. In this study, orthogonal arrays, which were developed using the robust design, are used to define the combination of the (a) thickness of a stiff sandstone inserted on the top and bottom of a coal seam in a massive shale mine roof and floor, (b) location of the stiff sandstone inserted on the top and bottom of the coal seam, and (c) material properties of the stiff sandstone and contacts as interfaces using the 3-dimensional numerical model, FLAC3D. After completion of the numerical experiments, statistical and multivariate analysis are performed using the calculated results from the orthogonal arrays to analyze the effect of these variables. As a consequence, the impact of each of the parameters on the potential for bumps is quantitatively classified in terms of a normalized intensity of plastic dissipated energy. By multiple regression, the intensity of plastic dissipated energy and migration of the risk from the roof to the floor via the pillars is predicted based on the value of the variables. The results demonstrate and suggest a possible capability to predict the bump potential in a given rock mass adjacent to the underground excavations and pillars. Assessing the risk of bumps is important to preventing fatalities and injuries resulting from bumps. PMID:29416902

Diesel engine exhaust and lung cancer mortality: time-related factors in exposure and risk.

PubMed

Moolgavkar, Suresh H; Chang, Ellen T; Luebeck, Georg; Lau, Edmund C; Watson, Heather N; Crump, Kenny S; Boffetta, Paolo; McClellan, Roger

2015-04-01

To develop a quantitative exposure-response relationship between concentrations and durations of inhaled diesel engine exhaust (DEE) and increases in lung cancer risks, we examined the role of temporal factors in modifying the estimated effects of exposure to DEE on lung cancer mortality and characterized risk by mine type in the Diesel Exhaust in Miners Study (DEMS) cohort, which followed 12,315 workers through December 1997. We analyzed the data using parametric functions based on concepts of multistage carcinogenesis to directly estimate the hazard functions associated with estimated exposure to a surrogate marker of DEE, respirable elemental carbon (REC). The REC-associated risk of lung cancer mortality in DEMS is driven by increased risk in only one of four mine types (limestone), with statistically significant heterogeneity by mine type and no significant exposure-response relationship after removal of the limestone mine workers. Temporal factors, such as duration of exposure, play an important role in determining the risk of lung cancer mortality following exposure to REC, and the relative risk declines after exposure to REC stops. There is evidence of effect modification of risk by attained age. The modifying impact of temporal factors and effect modification by age should be addressed in any quantitative risk assessment (QRA) of DEE. Until there is a better understanding of why the risk appears to be confined to a single mine type, data from DEMS cannot reliably be used for QRA. © 2015 Society for Risk Analysis.

Comparison of two wild rodent species as sentinels of environmental contamination by mine tailings.

PubMed

Tovar-Sánchez, E; Cervantes, L T; Martínez, C; Rojas, E; Valverde, M; Ortiz-Hernández, M L; Mussali-Galante, P

2012-06-01

Contamination with heavy metals is among the most hazardous environmental concerns caused by mining activity. A valuable tool for monitoring these effects is the use of sentinel organisms. Particularly, small mammals living inside mine tailings are an excellent study system because their analysis represents a realistic approach of mixtures and concentrations of metal exposure. We analyzed metal tissue concentrations and DNA damage levels for comparison between genders of a sentinel (Peromyscus melanophrys) and a nonsentinel (Baiomys musculus) species. Also, the relationship between DNA damage and the distance from the contamination source was evaluated. This study was conducted in an abandoned mine tailing at Morelos, Mexico. Thirty-six individuals from both species at the exposed and reference sites were sampled. Metal concentrations in bone and liver of both species were analyzed by atomic absorption spectrophotometry, and DNA damage levels were assayed using the alkaline comet assay. In general, concentrations of zinc, nickel, iron, and manganese were statistically higher in exposed individuals. A significant effect of the organ and the site on all metal tissue concentrations was detected. Significant DNA damage levels were registered in the exposed group, being higher in B. musculus. Females registered higher DNA damage levels than males. A negative relationship between distance from the mine tailing and DNA damage in B. musculus was observed. We consider that B. musculus is a suitable species to assess environmental quality, especially for bioaccumulable pollutants--such as metals--and recommend that it may be considered as a sentinel species.

COPS: Detecting Co-Occurrence and Spatial Arrangement of Transcription Factor Binding Motifs in Genome-Wide Datasets

PubMed Central

Lohmann, Ingrid

2012-01-01

In multi-cellular organisms, spatiotemporal activity of cis-regulatory DNA elements depends on their occupancy by different transcription factors (TFs). In recent years, genome-wide ChIP-on-Chip, ChIP-Seq and DamID assays have been extensively used to unravel the combinatorial interaction of TFs with cis-regulatory modules (CRMs) in the genome. Even though genome-wide binding profiles are increasingly becoming available for different TFs, single TF binding profiles are in most cases not sufficient for dissecting complex regulatory networks. Thus, potent computational tools detecting statistically significant and biologically relevant TF-motif co-occurrences in genome-wide datasets are essential for analyzing context-dependent transcriptional regulation. We have developed COPS (Co-Occurrence Pattern Search), a new bioinformatics tool based on a combination of association rules and Markov chain models, which detects co-occurring TF binding sites (BSs) on genomic regions of interest. COPS scans DNA sequences for frequent motif patterns using a Frequent-Pattern tree based data mining approach, which allows efficient performance of the software with respect to both data structure and implementation speed, in particular when mining large datasets. Since transcriptional gene regulation very often relies on the formation of regulatory protein complexes mediated by closely adjoining TF binding sites on CRMs, COPS additionally detects preferred short distance between co-occurring TF motifs. The performance of our software with respect to biological significance was evaluated using three published datasets containing genomic regions that are independently bound by several TFs involved in a defined biological process. In sum, COPS is a fast, efficient and user-friendly tool mining statistically and biologically significant TFBS co-occurrences and therefore allows the identification of TFs that combinatorially regulate gene expression. PMID:23272209

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

Band, P.; Feldstein, M.; Saccomanno, G.

To assess the effect of cigarette smoking and of exposure to radon daughters, a prospective survey consisting of periodic sputum cytology evaluation was initiated among 249 underground uranium miners and 123 male controls. Sputum cytology specimens showing moderate atypia, marked atypia, or cancer cells were classified as abnormal. As compared to control smokers, miners who smoke had a significantly higher incidence of abnormal cytology (P = 0.025). For miner smokers, the observed frequencies of abnormal cytology were linearly related to cumulative exposure to radon daughters and to the number of years of uranium mining. A statistical model relating the probabilitymore » of abnormal cytology to the risk factors was investigated using a binary logistic regression. The estimated frequency of abnormal cytology was significantly dependent, for controls, on the duration of cigarette smoking, and for miners, on the duration of cigarette smoking and of uranium mining.« less

The Extent and Consequences of P-Hacking in Science

PubMed Central

Head, Megan L.; Holman, Luke; Lanfear, Rob; Kahn, Andrew T.; Jennions, Michael D.

2015-01-01

A focus on novel, confirmatory, and statistically significant results leads to substantial bias in the scientific literature. One type of bias, known as “p-hacking,” occurs when researchers collect or select data or statistical analyses until nonsignificant results become significant. Here, we use text-mining to demonstrate that p-hacking is widespread throughout science. We then illustrate how one can test for p-hacking when performing a meta-analysis and show that, while p-hacking is probably common, its effect seems to be weak relative to the real effect sizes being measured. This result suggests that p-hacking probably does not drastically alter scientific consensuses drawn from meta-analyses. PMID:25768323

Statistical sensor fusion analysis of near-IR polarimetric and thermal imagery for the detection of minelike targets

NASA Astrophysics Data System (ADS)

Weisenseel, Robert A.; Karl, William C.; Castanon, David A.; DiMarzio, Charles A.

1999-02-01

We present an analysis of statistical model based data-level fusion for near-IR polarimetric and thermal data, particularly for the detection of mines and mine-like targets. Typical detection-level data fusion methods, approaches that fuse detections from individual sensors rather than fusing at the level of the raw data, do not account rationally for the relative reliability of different sensors, nor the redundancy often inherent in multiple sensors. Representative examples of such detection-level techniques include logical AND/OR operations on detections from individual sensors and majority vote methods. In this work, we exploit a statistical data model for the detection of mines and mine-like targets to compare and fuse multiple sensor channels. Our purpose is to quantify the amount of knowledge that each polarimetric or thermal channel supplies to the detection process. With this information, we can make reasonable decisions about the usefulness of each channel. We can use this information to improve the detection process, or we can use it to reduce the number of required channels.

Appraising the Corporate Sustainability Reports - Text Mining and Multi-Discriminatory Analysis

NASA Astrophysics Data System (ADS)

Modapothala, J. R.; Issac, B.; Jayamani, E.

The voluntary disclosure of the sustainability reports by the companies attracts wider stakeholder groups. Diversity in these reports poses challenge to the users of information and regulators. This study appraises the corporate sustainability reports as per GRI (Global Reporting Initiative) guidelines (the most widely accepted and used) across all industrial sectors. Text mining is adopted to carry out the initial analysis with a large sample size of 2650 reports. Statistical analyses were performed for further investigation. The results indicate that the disclosures made by the companies differ across the industrial sectors. Multivariate Discriminant Analysis (MDA) shows that the environmental variable is a greater significant contributing factor towards explanation of sustainability report.

Data mining: sophisticated forms of managed care modeling through artificial intelligence.

PubMed

Borok, L S

1997-01-01

Data mining is a recent development in computer science that combines artificial intelligence algorithms and relational databases to discover patterns automatically, without the use of traditional statistical methods. Work with data mining tools in health care is in a developmental stage that holds great promise, given the combination of demographic and diagnostic information.

Statistical learning and selective inference.

PubMed

Taylor, Jonathan; Tibshirani, Robert J

2015-06-23

We describe the problem of "selective inference." This addresses the following challenge: Having mined a set of data to find potential associations, how do we properly assess the strength of these associations? The fact that we have "cherry-picked"--searched for the strongest associations--means that we must set a higher bar for declaring significant the associations that we see. This challenge becomes more important in the era of big data and complex statistical modeling. The cherry tree (dataset) can be very large and the tools for cherry picking (statistical learning methods) are now very sophisticated. We describe some recent new developments in selective inference and illustrate their use in forward stepwise regression, the lasso, and principal components analysis.

[Lead exposure of people living in a lead high exposure area from local diet].

PubMed

Zhou, Yong; He, Liping; Huang, Xiao; He, Junshan

2011-11-01

To study the lead exposure of people living in a lead high exposure area from local diet, and to assess its health risks. Thirty five subjects were selected by random from a mining area and another 30 subjects were selected from a non-polluted area. The exposure of lead was estimated by the content of lead in drinking water and vegetables, and health risks was estimated by the levels of lead in blood and urine. The content of lead in drinking water and vegetables in the mining area was 20.6 microg/L and 1.61mg/kg (geometric mean) respectively, which were higher than that in the unpolluted area (6.0 microg/L and 0.56 mg/kg, geometric mean) (P < 0.01). The daily lead exposure of male and female inhabitants in the mining area from diet was 16.88 microg/kg and 16.09 microg/kg respectively, which was higher than that in the unpolluted area (P < 0.01), but the sex difference was not significant statistically (P > 0.05). Blood lead and urine lead of inhabitants in the mining-area were higher than those in the unpolluted area. The health risks for male and female inhabitants in the mining area were 4.73 and 4.51. The health risks of lead exposure caused by diet (drinking water and food) were relatively high in the mining area.

Stress shadows - a controversial topic

NASA Astrophysics Data System (ADS)

Lasocki, Stanislaw; Karakostas, Vassilis G.; Papadimitriou, Eletheria E.; Orlecka-Sikora, Beata

2010-05-01

The spatial correlation between the positive Coulomb stress changes and the subsequent seismic activity has been firmly confirmed in many recent studies. If, however, the static stress transfer is a consistent expression of interaction between earthquakes one should also observe a decrease of the activity in the zones of negative stress changes. Instead, the existence of stress shadows is poorly evidenced and may be questioned. We tested the influence of the static stress changes associated with the coseismic slip of the 1995 Mw6.5 Kozani-Grevena (Greece) earthquake on locations of its aftershocks. The study was based on a detailed slip model for the main shock and accurate locations and reliable fault plane solutions of an adequate number of the aftershocks. We developed a statistical testing method, which tested whether the proportions of aftershocks located inside areas determined by a selected criterion on the static stress change could be attained if there were no effect of the stress change due to the main shock on aftershock locations. The areas of stress change were determined at the focus of every aftershock. The distribution of test statistic was constructed with the use of a two-dimensional nonparametric, kernel density estimator of the reference epicenter distribution. The tests highly confidently indicated a rise in probability to locate aftershocks inside areas of positive static stress change, which supported the hypothesis on the triggering effect in these areas. Furthermore, it was evidenced that a larger stress increase caused a stronger triggering effect. The analysis, however, did not evidence the existence of stress shadows inside areas of negative stress change. Contrary to expectations, the tests indicated a significant increase of the probability of event location in the areas of a stress decrease of more than or equal to 5.0 and 10.0 bar. It turned out that for areas of larger absolute stress change this probability increased regardless of the sign of the change though distinctly more in areas of positive than of negative change. In the case of seismicity accompanying underground mining exploitation the coseismic stress changes expressed in terms of the Coulomb failure function are at least of one order smaller than those for earthquakes. Furthermore, they are only a small component of the total stress field variations in mining rockmass, which are mainly controlled by the mining process. Nevertheless, our studies of the induced seismicity in the Rudna mine in the Legnica-Głogow Copper District in Poland showed that the influence of the Coulomb stress changes on locations of subsequent events was statistically significant. We analyzed series of seismic events quantifying the triggering and inhibiting effect by the proportion of events in the series whose locations were consistent with the stress increased and stress decreased zones, respectively. It was found out that more than 60 per-cent of the analyzed seismic events occurred in areas where stress was enhanced due to the occurrence of previous events. The significance of this result was determined by comparing it with 2000 results of the same analysis carried out on the random permutations of the original series of events. The test indicated that the locations in positive stress changes areas were preferred statistically significantly when the stress changes exceeded 0.05 bar. However, no statistically significant inhibiting effect of negative static stress changes, within the considered range of these changes, was ascertained. Here we present details of these two studies and discuss possible reasons behind the negative conclusions on the existence of stress shadows.

Using ontology network structure in text mining.

PubMed

Berndt, Donald J; McCart, James A; Luther, Stephen L

2010-11-13

Statistical text mining treats documents as bags of words, with a focus on term frequencies within documents and across document collections. Unlike natural language processing (NLP) techniques that rely on an engineered vocabulary or a full-featured ontology, statistical approaches do not make use of domain-specific knowledge. The freedom from biases can be an advantage, but at the cost of ignoring potentially valuable knowledge. The approach proposed here investigates a hybrid strategy based on computing graph measures of term importance over an entire ontology and injecting the measures into the statistical text mining process. As a starting point, we adapt existing search engine algorithms such as PageRank and HITS to determine term importance within an ontology graph. The graph-theoretic approach is evaluated using a smoking data set from the i2b2 National Center for Biomedical Computing, cast as a simple binary classification task for categorizing smoking-related documents, demonstrating consistent improvements in accuracy.

Statistical evaluation of synchronous spike patterns extracted by frequent item set mining

PubMed Central

Torre, Emiliano; Picado-Muiño, David; Denker, Michael; Borgelt, Christian; Grün, Sonja

2013-01-01

We recently proposed frequent itemset mining (FIM) as a method to perform an optimized search for patterns of synchronous spikes (item sets) in massively parallel spike trains. This search outputs the occurrence count (support) of individual patterns that are not trivially explained by the counts of any superset (closed frequent item sets). The number of patterns found by FIM makes direct statistical tests infeasible due to severe multiple testing. To overcome this issue, we proposed to test the significance not of individual patterns, but instead of their signatures, defined as the pairs of pattern size z and support c. Here, we derive in detail a statistical test for the significance of the signatures under the null hypothesis of full independence (pattern spectrum filtering, PSF) by means of surrogate data. As a result, injected spike patterns that mimic assembly activity are well detected, yielding a low false negative rate. However, this approach is prone to additionally classify patterns resulting from chance overlap of real assembly activity and background spiking as significant. These patterns represent false positives with respect to the null hypothesis of having one assembly of given signature embedded in otherwise independent spiking activity. We propose the additional method of pattern set reduction (PSR) to remove these false positives by conditional filtering. By employing stochastic simulations of parallel spike trains with correlated activity in form of injected spike synchrony in subsets of the neurons, we demonstrate for a range of parameter settings that the analysis scheme composed of FIM, PSF and PSR allows to reliably detect active assemblies in massively parallel spike trains. PMID:24167487

Evaluation of metal mobility from copper mine tailings in northern Chile.

PubMed

Lam, Elizabeth J; Gálvez, M E; Cánovas, M; Montofré, I L; Rivero, D; Faz, A

2016-06-01

This work shows the results obtained on a copper mine tailing in the Antofagasta Region, Chile. The tailing was classified as saline-sodic with high concentrations of metals, especially Cu and Fe, with pH 8.4. Our objectives were to (1) compare the physicochemical properties of the tailing with surrounding soils of the mine under study, and (2) evaluate the effect of two amendments (CaCO3 and compost) and their mixtures on Cu(2+), Mn, Fe, Zn, Mg(2+), and K(+) and Ca(2+), SO4 (2-), NO3 (-), and PO4 (3-) leaching. The data obtained were submitted to variance and covariance analysis. The results from the comparison between both substrates showed that in general, the tailing presented greater content of metals. Regarding tailing leaching, pH, electrical conductivity (EC), and concentration of the elements of interest were measured. The statistical analysis showed that Cu(2+) leaching and immobilization of Fe occurred to the greatest extent with compost. The EC decreased throughout the experiment with irrigation and increased upon treatment with compost. The major interactions found among the chemical parameters were (1) tailings without treatment, Cu(2+)/Fe and NO3 (-)/SO4 (2-); (2) tailings treated with CaCO3, Cu(2+)/K(+); (3) tailings treated with compost, NO3 (-)/SO4 (-2) and EC/Cu(2+); and (4) tailings treated with both amendments, EC/Fe and Cu(2+)/Fe. The ANOVA showed that the number of irrigations and the amendments statistically significantly affected the copper mobility and the organic amendment significantly influenced the iron mobility.

Prediction model for peninsular Indian summer monsoon rainfall using data mining and statistical approaches

NASA Astrophysics Data System (ADS)

Vathsala, H.; Koolagudi, Shashidhar G.

2017-01-01

In this paper we discuss a data mining application for predicting peninsular Indian summer monsoon rainfall, and propose an algorithm that combine data mining and statistical techniques. We select likely predictors based on association rules that have the highest confidence levels. We then cluster the selected predictors to reduce their dimensions and use cluster membership values for classification. We derive the predictors from local conditions in southern India, including mean sea level pressure, wind speed, and maximum and minimum temperatures. The global condition variables include southern oscillation and Indian Ocean dipole conditions. The algorithm predicts rainfall in five categories: Flood, Excess, Normal, Deficit and Drought. We use closed itemset mining, cluster membership calculations and a multilayer perceptron function in the algorithm to predict monsoon rainfall in peninsular India. Using Indian Institute of Tropical Meteorology data, we found the prediction accuracy of our proposed approach to be exceptionally good.

An Impact Evaluation of a Federal Mine Safety Training Regulation on Injury Rates Among US Stone, Sand, and Gravel Mine Workers: An Interrupted Time-Series Analysis

PubMed Central

Windsor, Richard

2010-01-01

Objectives. We evaluated the impact of a safety training regulation, implemented by the US Department of Labor's Mine Safety and Health Administration (MSHA) in 1999, on injury rates at stone, sand, and gravel mining operations. Methods. We applied a time-series design and analyses with quarterly counts of nonfatal injuries and employment hours from 7998 surface aggregate mines from 1995 through 2006. Covariates included standard industrial classification codes, ownership, and injury severity. Results. Overall crude rates of injuries declined over the 12-year period. Reductions in incident rates for medical treatment only, restricted duty, and lost-time injuries were consistent with temporal trends and provided no evidence of an intervention effect attributable to the MSHA regulation. Rates of permanently disabling injuries (PDIs) declined markedly. Regression analyses documented a statistically significant reduction in the risk rate in the postintervention time period (risk rate = 0.591; 95% confidence interval = 0.529, 0.661). Conclusions. Although a causal relationship between the regulatory intervention and the decline in the rate of PDIs is plausible, inconsistency in the results with the other injury-severity categories preclude attributing the observed outcome to the MSHA regulation. Further analyses of these data are needed. PMID:20466960

An impact evaluation of a federal mine safety training regulation on injury rates among US stone, sand, and gravel mine workers: an interrupted time-series analysis.

PubMed

Monforton, Celeste; Windsor, Richard

2010-07-01

We evaluated the impact of a safety training regulation, implemented by the US Department of Labor's Mine Safety and Health Administration (MSHA) in 1999, on injury rates at stone, sand, and gravel mining operations. We applied a time-series design and analyses with quarterly counts of nonfatal injuries and employment hours from 7998 surface aggregate mines from 1995 through 2006. Covariates included standard industrial classification codes, ownership, and injury severity. Overall crude rates of injuries declined over the 12-year period. Reductions in incident rates for medical treatment only, restricted duty, and lost-time injuries were consistent with temporal trends and provided no evidence of an intervention effect attributable to the MSHA regulation. Rates of permanently disabling injuries (PDIs) declined markedly. Regression analyses documented a statistically significant reduction in the risk rate in the postintervention time period (risk rate = 0.591; 95% confidence interval = 0.529, 0.661). Although a causal relationship between the regulatory intervention and the decline in the rate of PDIs is plausible, inconsistency in the results with the other injury-severity categories preclude attributing the observed outcome to the MSHA regulation. Further analyses of these data are needed.

Littoral assessment of mine burial signatures (LAMBS): buried landmine/background spectral-signature analyses

NASA Astrophysics Data System (ADS)

Kenton, Arthur C.; Geci, Duane M.; Ray, Kristofer J.; Thomas, Clayton M.; Salisbury, John W.; Mars, John C.; Crowley, James K.; Witherspoon, Ned H.; Holloway, John H., Jr.

2004-09-01

The objective of the Office of Naval Research (ONR) Rapid Overt Reconnaissance (ROR) program and the Airborne Littoral Reconnaissance Technologies (ALRT) project's LAMBS effort is to determine if electro-optical spectral discriminants exist that are useful for the detection of land mines in littoral regions. Statistically significant buried mine overburden and background signature data were collected over a wide spectral range (0.35 to 14 μm) to identify robust spectral features that might serve as discriminants for new airborne sensor concepts. LAMBS has expanded previously collected databases to littoral areas - primarily dry and wet sandy soils - where tidal, surf, and wind conditions can severely modify spectral signatures. At AeroSense 2003, we reported completion of three buried mine collections at an inland bay, Atlantic and Gulf of Mexico beach sites. We now report LAMBS spectral database analyses results using metrics which characterize the detection performance of general types of spectral detection algorithms. These metrics include mean contrast, spectral signal-to-clutter, covariance, information content, and spectral matched filter analyses. Detection performance of the buried land mines was analyzed with regard to burial age, background type, and environmental conditions. These analyses considered features observed due to particle size differences, surface roughness, surface moisture, and compositional differences.

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

Environmental exposure as an independent risk factor of chronic bronchitis in northwest Russia

PubMed Central

Nieminen, Pentti; Panychev, Dmitry; Lyalyushkin, Sergei; Komarov, German; Nikanov, Alexander; Borisenko, Mark; Kinnula, Vuokko L.; Toljamo, Tuula

2013-01-01

Background In some parts of the northwest Russia, Murmansk region, high exposures to heavy mining and refining industrial air pollution, especially sulphur dioxide, have been documented. Objective Our aim was to evaluate whether living in the mining area would be an independent risk factor of the respiratory symptoms. Design A cross-sectional survey of 200 Murmansk region adult citizens was performed. The main outcome variable was prolonged cough with sputum production that fulfilled the criteria of chronic bronchitis. Results Of the 200 participants, 53 (26.5%) stated that they had experienced chronic cough with phlegm during the last 2 years. The prevalence was higher among those subjects living in the mining area with its high pollution compared to those living outside this region (35% vs. 18%). Multivariable regression model confirmed that the risk for the chronic cough with sputum production was elevated in a statistical significant manner in the mining and refining area (adjusted OR 2.16, 95% CI 1.07–4.35) after adjustment for smoking status, age and sex. Conclusions The increased level of sulphur dioxide emitted during nickel mining and refining may explain these adverse health effects. This information is important for medical authorities when they make recommendations and issue guidelines regarding the relationship between environmental pollution and health outcomes. PMID:23440671

Chimney subsidence development in the Colorado Springs coal field, Colorado

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

Matheson, G.M.; Pearson, M.L.

1985-01-01

Mining in the Colorodo Springs coal field took place from the 1880's to 1940's. The depth of mining in the coal field varied from about 10 meters to over 150 meters. Review of sequential historical aerial photographs from 1937 to 1960 indicated about 2400 chimney subsidence sinkholes had developed throughout the study area. Statistical analyses of the location and size of these sinkholes with respect to the time since mining, depth of mining, mined thickness and type of mining indicated definite trends in the time of occurrence, size, and location of these features. This data is valuable in the assessmentmore » of potential future subsidence in this and other areas of similar mining conditions.« less

Young addicted men hormone profile detection

NASA Astrophysics Data System (ADS)

Zieliński, Paweł; Wasiewicz, Piotr; Leszczyńska, Bożena; Gromadzka-Ostrowska, Joanna

2010-09-01

Hormone parameters were determined in the serum of young addicted men in order to compare them with those obtained from the group of healthy subjects. Three groups were investigated which were named opiates, mixed and control group. Statistical and data mining methods were applied to obtain significant differences. R package was used for all computation. The determination of hormones parameters provide important information relative to impact of addiction.

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

An aftermath analysis of the 2014 coal mine accident in Soma, Turkey: Use of risk performance indicators based on historical experience.

PubMed

Spada, Matteo; Burgherr, Peter

2016-02-01

On the 13th of May 2014 a fire related incident in the Soma coal mine in Turkey caused 301 fatalities and more than 80 injuries. This has been the largest coal mine accident in Turkey, and in the OECD country group, so far. This study investigated if such a disastrous event should be expected, in a statistical sense, based on historical observations. For this purpose, PSI's ENSAD database is used to extract accident data for the period 1970-2014. Four different cases are analyzed, i.e., OECD, OECD w/o Turkey, Turkey and USA. Analysis of temporal trends for annual numbers of accidents and fatalities indicated a non-significant decreasing tendency for OECD and OECD w/o Turkey and a significant one for USA, whereas for Turkey both measures showed an increase over time. The expectation analysis revealed clearly that an event with the consequences of the Soma accident is rather unlikely for OECD, OECD w/o Turkey and USA. In contrast, such a severe accident has a substantially higher expectation for Turkey, i.e. it cannot be considered an extremely rare event, based on historical experience. This indicates a need for improved safety measures and stricter regulations in the Turkish coal mining sector in order to get closer to the rest of OECD. Copyright © 2015 Elsevier Ltd. All rights reserved.

Manipulating measurement scales in medical statistical analysis and data mining: A review of methodologies

PubMed Central

Marateb, Hamid Reza; Mansourian, Marjan; Adibi, Peyman; Farina, Dario

2014-01-01

Background: selecting the correct statistical test and data mining method depends highly on the measurement scale of data, type of variables, and purpose of the analysis. Different measurement scales are studied in details and statistical comparison, modeling, and data mining methods are studied based upon using several medical examples. We have presented two ordinal–variables clustering examples, as more challenging variable in analysis, using Wisconsin Breast Cancer Data (WBCD). Ordinal-to-Interval scale conversion example: a breast cancer database of nine 10-level ordinal variables for 683 patients was analyzed by two ordinal-scale clustering methods. The performance of the clustering methods was assessed by comparison with the gold standard groups of malignant and benign cases that had been identified by clinical tests. Results: the sensitivity and accuracy of the two clustering methods were 98% and 96%, respectively. Their specificity was comparable. Conclusion: by using appropriate clustering algorithm based on the measurement scale of the variables in the study, high performance is granted. Moreover, descriptive and inferential statistics in addition to modeling approach must be selected based on the scale of the variables. PMID:24672565

An application of statistics to comparative metagenomics

PubMed Central

Rodriguez-Brito, Beltran; Rohwer, Forest; Edwards, Robert A

2006-01-01

Background Metagenomics, sequence analyses of genomic DNA isolated directly from the environments, can be used to identify organisms and model community dynamics of a particular ecosystem. Metagenomics also has the potential to identify significantly different metabolic potential in different environments. Results Here we use a statistical method to compare curated subsystems, to predict the physiology, metabolism, and ecology from metagenomes. This approach can be used to identify those subsystems that are significantly different between metagenome sequences. Subsystems that were overrepresented in the Sargasso Sea and Acid Mine Drainage metagenome when compared to non-redundant databases were identified. Conclusion The methodology described herein applies statistics to the comparisons of metabolic potential in metagenomes. This analysis reveals those subsystems that are more, or less, represented in the different environments that are compared. These differences in metabolic potential lead to several testable hypotheses about physiology and metabolism of microbes from these ecosystems. PMID:16549025

An application of statistics to comparative metagenomics.

PubMed

Rodriguez-Brito, Beltran; Rohwer, Forest; Edwards, Robert A

2006-03-20

Metagenomics, sequence analyses of genomic DNA isolated directly from the environments, can be used to identify organisms and model community dynamics of a particular ecosystem. Metagenomics also has the potential to identify significantly different metabolic potential in different environments. Here we use a statistical method to compare curated subsystems, to predict the physiology, metabolism, and ecology from metagenomes. This approach can be used to identify those subsystems that are significantly different between metagenome sequences. Subsystems that were overrepresented in the Sargasso Sea and Acid Mine Drainage metagenome when compared to non-redundant databases were identified. The methodology described herein applies statistics to the comparisons of metabolic potential in metagenomes. This analysis reveals those subsystems that are more, or less, represented in the different environments that are compared. These differences in metabolic potential lead to several testable hypotheses about physiology and metabolism of microbes from these ecosystems.

Mine Burial Expert System for Change of MIW Doctrine

DTIC Science & Technology

2011-09-01

allowed the mine to move vertically and horizontally, as well as rotate about the y axis. The first of these second generation impact models was...bearing strength and use multilayered sediments. Although they improve the knowledge of mine movement in two dimensions and rotation in one direction...conditional independence. Bayesian networks were originally developed 24 to handle uncertainty in a quantitative manner. They are statistical models

Redundancy in electronic health record corpora: analysis, impact on text mining performance and mitigation strategies.

PubMed

Cohen, Raphael; Elhadad, Michael; Elhadad, Noémie

2013-01-16

The increasing availability of Electronic Health Record (EHR) data and specifically free-text patient notes presents opportunities for phenotype extraction. Text-mining methods in particular can help disease modeling by mapping named-entities mentions to terminologies and clustering semantically related terms. EHR corpora, however, exhibit specific statistical and linguistic characteristics when compared with corpora in the biomedical literature domain. We focus on copy-and-paste redundancy: clinicians typically copy and paste information from previous notes when documenting a current patient encounter. Thus, within a longitudinal patient record, one expects to observe heavy redundancy. In this paper, we ask three research questions: (i) How can redundancy be quantified in large-scale text corpora? (ii) Conventional wisdom is that larger corpora yield better results in text mining. But how does the observed EHR redundancy affect text mining? Does such redundancy introduce a bias that distorts learned models? Or does the redundancy introduce benefits by highlighting stable and important subsets of the corpus? (iii) How can one mitigate the impact of redundancy on text mining? We analyze a large-scale EHR corpus and quantify redundancy both in terms of word and semantic concept repetition. We observe redundancy levels of about 30% and non-standard distribution of both words and concepts. We measure the impact of redundancy on two standard text-mining applications: collocation identification and topic modeling. We compare the results of these methods on synthetic data with controlled levels of redundancy and observe significant performance variation. Finally, we compare two mitigation strategies to avoid redundancy-induced bias: (i) a baseline strategy, keeping only the last note for each patient in the corpus; (ii) removing redundant notes with an efficient fingerprinting-based algorithm. (a)For text mining, preprocessing the EHR corpus with fingerprinting yields significantly better results. Before applying text-mining techniques, one must pay careful attention to the structure of the analyzed corpora. While the importance of data cleaning has been known for low-level text characteristics (e.g., encoding and spelling), high-level and difficult-to-quantify corpus characteristics, such as naturally occurring redundancy, can also hurt text mining. Fingerprinting enables text-mining techniques to leverage available data in the EHR corpus, while avoiding the bias introduced by redundancy.

Risk factors and prediction of very short term versus short/intermediate term post-stroke mortality: a data mining approach.

PubMed

Easton, Jonathan F; Stephens, Christopher R; Angelova, Maia

2014-11-01

Data mining and knowledge discovery as an approach to examining medical data can limit some of the inherent bias in the hypothesis assumptions that can be found in traditional clinical data analysis. In this paper we illustrate the benefits of a data mining inspired approach to statistically analysing a bespoke data set, the academic multicentre randomised control trial, U.K Glucose Insulin in Stroke Trial (GIST-UK), with a view to discovering new insights distinct from the original hypotheses of the trial. We consider post-stroke mortality prediction as a function of days since stroke onset, showing that the time scales that best characterise changes in mortality risk are most naturally defined by examination of the mortality curve. We show that certain risk factors differentiate between very short term and intermediate term mortality. In particular, we show that age is highly relevant for intermediate term risk but not for very short or short term mortality. We suggest that this is due to the concept of frailty. Other risk factors are highlighted across a range of variable types including socio-demographics, past medical histories and admission medication. Using the most statistically significant risk factors we build predictive classification models for very short term and short/intermediate term mortality. Crown Copyright © 2014. Published by Elsevier Ltd. All rights reserved.

An evolving computational platform for biological mass spectrometry: workflows, statistics and data mining with MASSyPup64.

PubMed

Winkler, Robert

2015-01-01

In biological mass spectrometry, crude instrumental data need to be converted into meaningful theoretical models. Several data processing and data evaluation steps are required to come to the final results. These operations are often difficult to reproduce, because of too specific computing platforms. This effect, known as 'workflow decay', can be diminished by using a standardized informatic infrastructure. Thus, we compiled an integrated platform, which contains ready-to-use tools and workflows for mass spectrometry data analysis. Apart from general unit operations, such as peak picking and identification of proteins and metabolites, we put a strong emphasis on the statistical validation of results and Data Mining. MASSyPup64 includes e.g., the OpenMS/TOPPAS framework, the Trans-Proteomic-Pipeline programs, the ProteoWizard tools, X!Tandem, Comet and SpiderMass. The statistical computing language R is installed with packages for MS data analyses, such as XCMS/metaXCMS and MetabR. The R package Rattle provides a user-friendly access to multiple Data Mining methods. Further, we added the non-conventional spreadsheet program teapot for editing large data sets and a command line tool for transposing large matrices. Individual programs, console commands and modules can be integrated using the Workflow Management System (WMS) taverna. We explain the useful combination of the tools by practical examples: (1) A workflow for protein identification and validation, with subsequent Association Analysis of peptides, (2) Cluster analysis and Data Mining in targeted Metabolomics, and (3) Raw data processing, Data Mining and identification of metabolites in untargeted Metabolomics. Association Analyses reveal relationships between variables across different sample sets. We present its application for finding co-occurring peptides, which can be used for target proteomics, the discovery of alternative biomarkers and protein-protein interactions. Data Mining derived models displayed a higher robustness and accuracy for classifying sample groups in targeted Metabolomics than cluster analyses. Random Forest models do not only provide predictive models, which can be deployed for new data sets, but also the variable importance. We demonstrate that the later is especially useful for tracking down significant signals and affected pathways in untargeted Metabolomics. Thus, Random Forest modeling supports the unbiased search for relevant biological features in Metabolomics. Our results clearly manifest the importance of Data Mining methods to disclose non-obvious information in biological mass spectrometry . The application of a Workflow Management System and the integration of all required programs and data in a consistent platform makes the presented data analyses strategies reproducible for non-expert users. The simple remastering process and the Open Source licenses of MASSyPup64 (http://www.bioprocess.org/massypup/) enable the continuous improvement of the system.

Software tool for data mining and its applications

NASA Astrophysics Data System (ADS)

Yang, Jie; Ye, Chenzhou; Chen, Nianyi

2002-03-01

A software tool for data mining is introduced, which integrates pattern recognition (PCA, Fisher, clustering, hyperenvelop, regression), artificial intelligence (knowledge representation, decision trees), statistical learning (rough set, support vector machine), computational intelligence (neural network, genetic algorithm, fuzzy systems). It consists of nine function models: pattern recognition, decision trees, association rule, fuzzy rule, neural network, genetic algorithm, Hyper Envelop, support vector machine, visualization. The principle and knowledge representation of some function models of data mining are described. The software tool of data mining is realized by Visual C++ under Windows 2000. Nonmonotony in data mining is dealt with by concept hierarchy and layered mining. The software tool of data mining has satisfactorily applied in the prediction of regularities of the formation of ternary intermetallic compounds in alloy systems, and diagnosis of brain glioma.

Compass: a hybrid method for clinical and biobank data mining.

PubMed

Krysiak-Baltyn, K; Nordahl Petersen, T; Audouze, K; Jørgensen, Niels; Angquist, L; Brunak, S

2014-02-01

We describe a new method for identification of confident associations within large clinical data sets. The method is a hybrid of two existing methods; Self-Organizing Maps and Association Mining. We utilize Self-Organizing Maps as the initial step to reduce the search space, and then apply Association Mining in order to find association rules. We demonstrate that this procedure has a number of advantages compared to traditional Association Mining; it allows for handling numerical variables without a priori binning and is able to generate variable groups which act as "hotspots" for statistically significant associations. We showcase the method on infertility-related data from Danish military conscripts. The clinical data we analyzed contained both categorical type questionnaire data and continuous variables generated from biological measurements, including missing values. From this data set, we successfully generated a number of interesting association rules, which relate an observation with a specific consequence and the p-value for that finding. Additionally, we demonstrate that the method can be used on non-clinical data containing chemical-disease associations in order to find associations between different phenotypes, such as prostate cancer and breast cancer. Copyright © 2013 Elsevier Inc. All rights reserved.

Heavy metal concentrations in redeveloping soil of mine spoil under plantations of certain native woody species in dry tropical environment, India.

PubMed

Singh, Anand N; Zeng, De-hui; Chen, Fu-sheng

2005-01-01

Total concentration of heavy metals (Cd, Cr, Cu, Fe, Pb, Ni, Mn and Zn) was estimated in the redeveloping soil of mine spoil under 5-yr old plantations of four woody species namely: Albizia lebbeck, Albizia procera, Tectona grandis and Dendrocalamus strictus. The data recorded in the present study were compared with other unplanted coal mine spoil colliery, which was around to the study site and adjoining area of dry tropical forest. Among all the heavy metals, the maximum concentration was found for Fe and minimum for Cd. However, among all four species, total concentrations of these heavy metals were recorded maximally in the plantation plots of T. grandis except for Fe, while minimally in A. lebbeck except for Zn, whereas, the maximum concentration of Fe and Zn was in the plantation plots of D. strictus and A. procera. Statistical analysis revealed significant differences due to species for all the heavy metals except Cu. Among four species, A. lebbeck, A. procera and D. strictus showed more efficient for reducing heavy metal concentrations whereas T. grandis was not more effective to reduce heavy metal concentrations in redeveloping soil of mine spoil.

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.

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.

Ask and Ye Shall Receive? Automated Text Mining of Michigan Capital Facility Finance Bond Election Proposals to Identify Which Topics Are Associated with Bond Passage and Voter Turnout

ERIC Educational Resources Information Center

Bowers, Alex J.; Chen, Jingjing

2015-01-01

The purpose of this study is to bring together recent innovations in the research literature around school district capital facility finance, municipal bond elections, statistical models of conditional time-varying outcomes, and data mining algorithms for automated text mining of election ballot proposals to examine the factors that influence the…

Data Stream Mining

NASA Astrophysics Data System (ADS)

Gaber, Mohamed Medhat; Zaslavsky, Arkady; Krishnaswamy, Shonali

Data mining is concerned with the process of computationally extracting hidden knowledge structures represented in models and patterns from large data repositories. It is an interdisciplinary field of study that has its roots in databases, statistics, machine learning, and data visualization. Data mining has emerged as a direct outcome of the data explosion that resulted from the success in database and data warehousing technologies over the past two decades (Fayyad, 1997,Fayyad, 1998,Kantardzic, 2003).

Examining microbial community response to a strong chemical gradient: the effects of surface coal mining on stream bacteria

NASA Astrophysics Data System (ADS)

Bier, R.; Lindberg, T. T.; Wang, S.; Ellis, J. C.; Di Giulio, R. T.; Bernhardt, E. S.

2012-12-01

Surface coal mining is the dominant form of land cover change in northern and central Appalachia. In this process, shallow coal seams are exposed by removing overlying rock with explosives. The resulting fragmented carbonate rock and coal residues are disposed of in stream valleys. These valley fills generate alkaline mine drainage (AlkMD), dramatically increasing alkalinity, ionic strength, substrate supply (esp. SO42-), and trace element (Mn, Li, Se, U) concentrations in downstream rivers as well as significant losses of sensitive fish and macroinvertebrate species. In prior work within the Mud River, which drains the largest surface mine complex in Appalachia, we found that concentrations of AlkMD increase proportionally with the extent of upstream mining. Here we ask "How do stream microbial communities change along this strong chemical gradient?" We collected surface water and benthic biofilms from 25 stream reaches throughout the Mud River spanning the full range of surface mining impacts, with 0-96% of the contributing watershed area converted to surface coal mines. Microbial communities were collected from biofilms grown on a common substrate (red maple veneers) that were incubated in each stream reach for four months prior to collection in April, 2011. 16S rRNA genes from microbial communities at each study site were examined using 454 sequencing and compared with a generalized UniFrac distance matrix (674 sequence eveness) that was used in statistical analyses. Water chemistry at the sites was sampled monthly from July 2010 to December 2010 and again in April 2011. In April, surface water concentrations of SO42-, Ca2+, Mg2+, and Se2- increased linearly with the extent of upstream mining (all regressions R2 >0.43; p<0.004), with the resulting gradient in ionic strength extending from low conductivity (average 83 μS cm-1 S.E. 27.4) in unmined streams (n=6) to as high as 899 μS cm-1 in the mainstem and 1889 μS cm-1 immediately below the Connelly Branch valley fill. Across this gradient, we found that microbial community composition varied significantly between sites receiving mine drainage and those that were unexposed (NMDS ordination R2 =0.86; PERMANOVA; p=0.029). Bacterial diversity (OTU richness defined at 3% sequence difference) peaked at intermediate conductivities (600 μS cm-1). Environmental data that correlated significantly with the ordination axes were a variety of surface water ions characteristic of AlkMD (SO42-, Mg2+, Sr2+, Se2-, and U) as well as stream DOC concentrations (p < 0.001).

Assessing the effects of oil sands related ozone precursor emissions on ambient ozone levels in the Alberta oil sands region, Canada

NASA Astrophysics Data System (ADS)

Cho, Sunny; Vijayaraghavan, Krish; Spink, David; Cosic, Biljana; Davies, Mervyn; Jung, Jaegun

2017-11-01

A study was undertaken to determine whether, and the extent to which, increased ground-level ozone (O3) precursor emissions from oil sands development have impacted ambient air quality in the north-eastern Alberta, Canada, over the period 1998 to 2012. Temporal trends in emissions of O3 precursors (NOx and VOC) and ambient air concentrations of O3 precursors, and O3 were examined using the Theil-Sen statistical analysis method. Statistically significant correlations between NOx emissions and ambient NOx concentrations were found mainly near surface (open-pit) mining areas where mine fleets are a large source of NOx emissions. No statistically significant trends in the 4th highest daily maximum 8-hr average O3 at any of the continuous and passive ambient air monitoring stations were found. A significant long-term decrease in monthly averaged O3 is observed at some ambient monitoring sites in summer. A visual examination of long-term variations in annual NOx and VOC emissions and annual 4th highest daily maximum 8-hr O3 concentrations does not reveal any indication of a correlation between O3 concentrations and O3 precursor emissions or ambient levels in the study area. Despite a significant increase in oil sands NOx emissions (8%/yr), there is no statistically significant increase in long-term O3 concentrations at any of monitoring stations considered. This suggests that there is surplus NOx available in the environment which results in a titration of ambient O3 in the areas that have ambient monitoring. The limited ambient O3 monitoring data distant from NOx emission sources makes it impossible to assess the impact of these increased O3 precursor levels on O3 levels on a regional scale. As a precautionary measure, the increasing oil sands development O3 precursor emissions would require that priority be given to the management of these emissions to prevent possible future O3 ambient air quality issues.

Prevalence of periodontal disease among mine workers of Zonguldak, Kozlu District, Turkey: a cross-sectional study.

PubMed

Cengiz, Murat İnanç; Zengin, Büşra; İçen, Murat; Köktürk, Firüzan

2018-03-16

Occupational injuries cause major health problems in all nations. Coal mining is one of the largest, oldest industries in the world. However, there is relatively little available literature concerning the health status of coal miners. The purpose of this work is to assess the prevalence of periodontal disease among coal miners and provide a basis for planning and evaluating the data from community oral health services. A cross-sectional study was conducted 106 men selected based on a stratified cluster sampling procedure. The study was performed among the mine workers of Zonguldak, Kozlu District, Turkey. The questionnaire prepared by the American Academy of Periodontology risk assessment test was used for the evaluation. The data were collected byWorld Health Organization (WHO) oral health assessment form, and clinical examination was conducted by the method recommended by the WHO oral health surveys. Statistical analysis was performed using SPSS software programme. The overall prevalence of periodontal disease was found to be 96.2% and was determined by considering subjects with Community Periodontal Index scores of 1-4 as diseased and the healthy subjects comprised of a mere 3.8%. Furthermore, various disturbing or embarrassing work conditions were reported. Statistically significant differences were observed among the workers who brush their teeth daily and visit dental attendance within the last two years have better periodontal status than those of the others (p < 0.05). The present level of periodontal disease in coal mine workers is severe. Moreover, its distribution and severity are strongly influenced by host susceptibility and risk factors. The priority should be based on population strategy and primary prevention programmes to benefit the periodontal health by promoting self-care and oral hygiene.

Mechanism-based Pharmacovigilance over the Life Sciences Linked Open Data Cloud.

PubMed

Kamdar, Maulik R; Musen, Mark A

2017-01-01

Adverse drug reactions (ADR) result in significant morbidity and mortality in patients, and a substantial proportion of these ADRs are caused by drug-drug interactions (DDIs). Pharmacovigilance methods are used to detect unanticipated DDIs and ADRs by mining Spontaneous Reporting Systems, such as the US FDA Adverse Event Reporting System (FAERS). However, these methods do not provide mechanistic explanations for the discovered drug-ADR associations in a systematic manner. In this paper, we present a systems pharmacology-based approach to perform mechanism-based pharmacovigilance. We integrate data and knowledge from four different sources using Semantic Web Technologies and Linked Data principles to generate a systems network. We present a network-based Apriori algorithm for association mining in FAERS reports. We evaluate our method against existing pharmacovigilance methods for three different validation sets. Our method has AUROC statistics of 0.7-0.8, similar to current methods, and event-specific thresholds generate AUROC statistics greater than 0.75 for certain ADRs. Finally, we discuss the benefits of using Semantic Web technologies to attain the objectives for mechanism-based pharmacovigilance.

Reclaimed surface mine terrestrial pools: Integrating remote sensing, spatial data and field work

NASA Astrophysics Data System (ADS)

Kazar, Sheila A.

This study investigated the remote sensing of aboveground biomass in reclaimed surface mine reclamation sites and the carbon (C) storage potential of these sites. The research is structured in three sections. In the first study, the potential for utilizing the tasseled cap (TC) spectral transformation to characterize multi-temporal changes of vegetation growth was investigated within nine reclaimed coal surface mines in Monongalia and Preston Counties, West Virginia. The spectral patterns of TC greenness, brightness and wetness values associated with the minesites were investigated for a multi-temporal series of Landsat Thematic Mapper (TM) images, from 1992 to 2007. In general, most of the minesites at the time of mining showed increased brightness, and decreased greenness and wetness, with a reverse of this pattern during reclamation. However, rainfall appears to be a confounding variable, at least for relatively recently reclaimed sites. Spectral change vector analysis (CVA) was found to be effective for summarizing the patterns of change in TC values before and after reclamation. In the second study, field samples were collected from reclaimed grassland minesites and used to estimate biomass and C accumulation. In general, biomass and C increased in the six years following reclamation, and then slowly declined. Three Landsat Thematic Mapper (TM) images, from April, May and September of 2007, were used to assess four vegetation indices (VIs), TC, and red and near infrared radiance for potential for mapping biomass. For the April 3 Landsat image, the vegetation indices were not statistically correlated with field-measured biomass, and nor were the regression models significant. For the May 13 image, TC greenness and EVI were most strongly correlated with biomass, with TC wetness, NDVI, TVI and SAVI all significant at the 0.05 level. A number of regression models that included age since reclamation and spectral indices for May 13 were statistically significant, with the strongest prediction obtained from EVI. For the September 18 image, the correlation of biomass and TC brightness, TM4 and TVI were all statistically significant at the 0.05 level, although regression models that included age since reclamation as a dummy variable were not significant. In the third and final study, the biophysical potential for terrestrial aboveground C storage in minelands reclaimed to grasslands was investigated at the regional and state scale. Although above-ground annual accumulation of C is low in grasslands, if the aboveground biomass were harvested annually, and stored permanently C storage over 20 years on the grasslands of reclaimed minelands in West Virginia could be 3.60-7.32 Tg C, compared to 1.60 -9.80 Tg C if those same sites were reclaimed to forests. Although there is currently only limited usage of harvested hay for purposes that would result in its long-term storage, this study points to the benefits that would accrue if such mechanisms could be developed.

STATISTICAL VALIDATION OF SULFATE QUANTIFICATION METHODS USED FOR ANALYSIS OF ACID MINE DRAINAGE

EPA Science Inventory

Turbidimetric method (TM), ion chromatography (IC) and inductively coupled plasma atomic emission spectrometry (ICP-AES) with and without acid digestion have been compared and validated for the determination of sulfate in mining wastewater. Analytical methods were chosen to compa...

Health risk assessment of rare earth elements in cereals from mining area in Shandong, China.

PubMed

Zhuang, Maoqiang; Wang, Liansen; Wu, Guangjian; Wang, Kebo; Jiang, Xiaofeng; Liu, Taibin; Xiao, Peirui; Yu, Lianlong; Jiang, Ying; Song, Jian; Zhang, Junli; Zhou, Jingyang; Zhao, Jinshan; Chu, Zunhua

2017-08-29

To investigate the concentrations of rare earth elements in cereals and assess human health risk through cereal consumption, a total of 327 cereal samples were collected from rare earth mining area and control area in Shandong, China. The contents of 14 rare earth elements were determined by Inductively Coupled Plasma-Mass Spectrometry (ICP-MS). The medians of total rare earth elements in cereals from mining and control areas were 74.22 μg/kg and 47.83 μg/kg, respectively, and the difference was statistically significant (P < 0.05). The wheat had the highest rare earth elements concentrations (109.39 μg/kg and 77.96 μg/kg for mining and control areas, respectively) and maize had the lowest rare earth elements concentrations (42.88 μg/kg and 30.25 μg/kg for mining and control areas, respectively). The rare earth elements distribution patterns for both areas were characterized by enrichment of light rare earth elements. The health risk assessment demonstrated that the estimated daily intakes of rare earth elements through cereal consumption were considerably lower than the acceptable daily intake (70 μg/kg bw). The damage to adults can be neglected, but more attention should be paid to the effects of continuous exposure to rare earth elements on children.

Statistical Mining of Predictability of Seasonal Precipitation over the United States

NASA Technical Reports Server (NTRS)

Lau, William K. M.; Kim, Kyu-Myong; Shen, S. P.

2001-01-01

Results from a new ensemble canonical correlation (ECC) prediction model yield a remarkable (10-20%) increases in baseline prediction skills for seasonal precipitation over the US for all seasons, compared to traditional statistical predictions. While the tropical Pacific, i.e., El Nino, contributes to the largest share of potential predictability in the southern tier States during boreal winter, the North Pacific and the North Atlantic are responsible for enhanced predictability in the northern Great Plains, Midwest and the southwest US during boreal summer. Most importantly, ECC significantly reduces the spring predictability barrier over the conterminous US, thereby raising the skill bar for dynamical predictions.

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).

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.

A geographical information system-based analysis of cancer mortality and population exposure to coal mining activities in West Virginia, United States of America.

PubMed

Hendryx, Michael; Fedorko, Evan; Anesetti-Rothermel, Andrew

2010-05-01

Cancer incidence and mortality rates are high in West Virginia compared to the rest of the United States of America. Previous research has suggested that exposure to activities of the coal mining industry may contribute to elevated cancer mortality, although exposure measures have been limited. This study tests alternative specifications of exposure to mining activity to determine whether a measure based on location of mines, processing plants, coal slurry impoundments and underground slurry injection sites relative to population levels is superior to a previously-reported measure of exposure based on tons mined at the county level, in the prediction of age-adjusted cancer mortality rates. To this end, we utilize two geographical information system (GIS) techniques--exploratory spatial data analysis and inverse distance mapping--to construct new statistical analyses. Total, respiratory and "other" age-adjusted cancer mortality rates in West Virginia were found to be more highly associated with the GIS-exposure measure than the tonnage measure, before and after statistical control for smoking rates. The superior performance of the GIS measure, based on where people in the state live relative to mining activity, suggests that activities of the industry contribute to cancer mortality. Further confirmation of observed phenomena is necessary with person-level studies, but the results add to the body of evidence that coal mining poses environmental risks to population health in West Virginia.

Parallel object-oriented data mining system

DOEpatents

Kamath, Chandrika; Cantu-Paz, Erick

2004-01-06

A data mining system uncovers patterns, associations, anomalies and other statistically significant structures in data. Data files are read and displayed. Objects in the data files are identified. Relevant features for the objects are extracted. Patterns among the objects are recognized based upon the features. Data from the Faint Images of the Radio Sky at Twenty Centimeters (FIRST) sky survey was used to search for bent doubles. This test was conducted on data from the Very Large Array in New Mexico which seeks to locate a special type of quasar (radio-emitting stellar object) called bent doubles. The FIRST survey has generated more than 32,000 images of the sky to date. Each image is 7.1 megabytes, yielding more than 100 gigabytes of image data in the entire data set.

Incorporating linguistic knowledge for learning distributed word representations.

PubMed

Wang, Yan; Liu, Zhiyuan; Sun, Maosong

2015-01-01

Combined with neural language models, distributed word representations achieve significant advantages in computational linguistics and text mining. Most existing models estimate distributed word vectors from large-scale data in an unsupervised fashion, which, however, do not take rich linguistic knowledge into consideration. Linguistic knowledge can be represented as either link-based knowledge or preference-based knowledge, and we propose knowledge regularized word representation models (KRWR) to incorporate these prior knowledge for learning distributed word representations. Experiment results demonstrate that our estimated word representation achieves better performance in task of semantic relatedness ranking. This indicates that our methods can efficiently encode both prior knowledge from knowledge bases and statistical knowledge from large-scale text corpora into a unified word representation model, which will benefit many tasks in text mining.

Incorporating Linguistic Knowledge for Learning Distributed Word Representations

PubMed Central

Wang, Yan; Liu, Zhiyuan; Sun, Maosong

2015-01-01

Combined with neural language models, distributed word representations achieve significant advantages in computational linguistics and text mining. Most existing models estimate distributed word vectors from large-scale data in an unsupervised fashion, which, however, do not take rich linguistic knowledge into consideration. Linguistic knowledge can be represented as either link-based knowledge or preference-based knowledge, and we propose knowledge regularized word representation models (KRWR) to incorporate these prior knowledge for learning distributed word representations. Experiment results demonstrate that our estimated word representation achieves better performance in task of semantic relatedness ranking. This indicates that our methods can efficiently encode both prior knowledge from knowledge bases and statistical knowledge from large-scale text corpora into a unified word representation model, which will benefit many tasks in text mining. PMID:25874581

Dynamic association rules for gene expression data analysis.

PubMed

Chen, Shu-Chuan; Tsai, Tsung-Hsien; Chung, Cheng-Han; Li, Wen-Hsiung

2015-10-14

The purpose of gene expression analysis is to look for the association between regulation of gene expression levels and phenotypic variations. This association based on gene expression profile has been used to determine whether the induction/repression of genes correspond to phenotypic variations including cell regulations, clinical diagnoses and drug development. Statistical analyses on microarray data have been developed to resolve gene selection issue. However, these methods do not inform us of causality between genes and phenotypes. In this paper, we propose the dynamic association rule algorithm (DAR algorithm) which helps ones to efficiently select a subset of significant genes for subsequent analysis. The DAR algorithm is based on association rules from market basket analysis in marketing. We first propose a statistical way, based on constructing a one-sided confidence interval and hypothesis testing, to determine if an association rule is meaningful. Based on the proposed statistical method, we then developed the DAR algorithm for gene expression data analysis. The method was applied to analyze four microarray datasets and one Next Generation Sequencing (NGS) dataset: the Mice Apo A1 dataset, the whole genome expression dataset of mouse embryonic stem cells, expression profiling of the bone marrow of Leukemia patients, Microarray Quality Control (MAQC) data set and the RNA-seq dataset of a mouse genomic imprinting study. A comparison of the proposed method with the t-test on the expression profiling of the bone marrow of Leukemia patients was conducted. We developed a statistical way, based on the concept of confidence interval, to determine the minimum support and minimum confidence for mining association relationships among items. With the minimum support and minimum confidence, one can find significant rules in one single step. The DAR algorithm was then developed for gene expression data analysis. Four gene expression datasets showed that the proposed DAR algorithm not only was able to identify a set of differentially expressed genes that largely agreed with that of other methods, but also provided an efficient and accurate way to find influential genes of a disease. In the paper, the well-established association rule mining technique from marketing has been successfully modified to determine the minimum support and minimum confidence based on the concept of confidence interval and hypothesis testing. It can be applied to gene expression data to mine significant association rules between gene regulation and phenotype. The proposed DAR algorithm provides an efficient way to find influential genes that underlie the phenotypic variance.

Parallel object-oriented decision tree system

DOEpatents

Kamath,; Chandrika, Cantu-Paz [Dublin, CA; Erick, [Oakland, CA

2006-02-28

A data mining decision tree system that uncovers patterns, associations, anomalies, and other statistically significant structures in data by reading and displaying data files, extracting relevant features for each of the objects, and using a method of recognizing patterns among the objects based upon object features through a decision tree that reads the data, sorts the data if necessary, determines the best manner to split the data into subsets according to some criterion, and splits the data.

Concentrations and health risk assessment of rare earth elements in vegetables from mining area in Shandong, China.

PubMed

Zhuang, Maoqiang; Zhao, Jinshan; Li, Suyun; Liu, Danru; Wang, Kebo; Xiao, Peirui; Yu, Lianlong; Jiang, Ying; Song, Jian; Zhou, Jingyang; Wang, Liansen; Chu, Zunhua

2017-02-01

To investigate the concentrations of rare earth elements in vegetables and assess human health risk through vegetable consumption, a total of 301 vegetable samples were collected from mining area and control area in Shandong, China. The contents of 14 rare earth elements were determined by Inductively Coupled Plasma-Mass Spectrometry (ICP-MS). The total rare earth elements in vegetables from mining and control areas were 94.08 μg kg -1 and 38.67 μg kg -1 , respectively, and the difference was statistically significant (p < 0.05). The leaf vegetable had the highest rare earth elements concentration (984.24 μg kg -1 and 81.24 μg kg -1 for mining and control areas, respectively) and gourd vegetable had the lowest rare earth elements concentration (37.34 μg kg -1 and 24.63 μg kg -1 for mining and control areas, respectively). For both areas, the rare earth elements concentration in vegetables declined in the order of leaf vegetable > taproot vegetable > alliaceous vegetable > gourd vegetable. The rare earth elements distribution patterns for both areas were characterized by enrichment of light rare earth elements. The health risk assessment demonstrated that the estimated daily intakes (0.69 μg kg -1 d -1 and 0.28 μg kg -1 d -1 for mining and control areas, respectively) of rare earth elements through vegetable consumption were significantly lower than the acceptable daily intake (70 μg kg -1 d -1 ). The damage to adults can be neglected, but more attention should be paid to the effects of continuous exposure to low levels of rare earth elements on children. Copyright © 2016 Elsevier Ltd. All rights reserved.

Data Mining in Health and Medical Information.

ERIC Educational Resources Information Center

Bath, Peter A.

2004-01-01

Presents a literature review that covers the following topics related to data mining (DM) in health and medical information: the potential of DM in health and medicine; statistical methods; evaluation of methods; DM tools for health and medicine; inductive learning of symbolic rules; application of DM tools in diagnosis and prognosis; and…

CrosstalkNet: A Visualization Tool for Differential Co-expression Networks and Communities.

PubMed

Manem, Venkata; Adam, George Alexandru; Gruosso, Tina; Gigoux, Mathieu; Bertos, Nicholas; Park, Morag; Haibe-Kains, Benjamin

2018-04-15

Variations in physiological conditions can rewire molecular interactions between biological compartments, which can yield novel insights into gain or loss of interactions specific to perturbations of interest. Networks are a promising tool to elucidate intercellular interactions, yet exploration of these large-scale networks remains a challenge due to their high dimensionality. To retrieve and mine interactions, we developed CrosstalkNet, a user friendly, web-based network visualization tool that provides a statistical framework to infer condition-specific interactions coupled with a community detection algorithm for bipartite graphs to identify significantly dense subnetworks. As a case study, we used CrosstalkNet to mine a set of 54 and 22 gene-expression profiles from breast tumor and normal samples, respectively, with epithelial and stromal compartments extracted via laser microdissection. We show how CrosstalkNet can be used to explore large-scale co-expression networks and to obtain insights into the biological processes that govern cross-talk between different tumor compartments. Significance: This web application enables researchers to mine complex networks and to decipher novel biological processes in tumor epithelial-stroma cross-talk as well as in other studies of intercompartmental interactions. Cancer Res; 78(8); 2140-3. ©2018 AACR . ©2018 American Association for Cancer Research.

Blood biomonitoring of metals in subjects living near abandoned mining and active industrial areas.

PubMed

Madeddu, Roberto; Tolu, Paola; Asara, Yolande; Farace, Cristiano; Forte, Giovanni; Bocca, Beatrice

2013-07-01

A human blood biomonitoring campaign to detect the environmental exposure to metals (Cd, Cu, Cr, Mn, Pb and Zn) in 265 subjects was performed in the South-Western part of Sardinia (an Italian island) that is a particular area with a great history of coal and metal mining (Pb/Zn mainly) activities and large industrial structures (as metallurgy). Subjects living near the industrial plant area had geometric means (GM) of blood Cd (0.79 μg/l), Cu (971 μg/l), Mn (12.2 μg/l), and Pb (55.7 μg/l) significantly higher than controls (Cd, 0.47 μg/l; Cu, 900 μg/l; Mn 9.98 μg/l; Pb, 26.5 μg/l) and than people living nearby the past mining sites. Subjects living next to one dismissed mine were statistically higher in blood Cu (GM, 1,022 μg/l) and Pb (GM, 41.4 μg/l) concentrations than controls. No differences were observed in people living in the different mining sites, and this might be related to the decennial disclosure of mines and the adoption of environmental remediation programmes. Some interindividual variables influenced blood biomonitoring data, as smoke and age for Cd, gender for Cu, age, sex and alcohol for Pb, and age for Zn. Moreover, blood metal levels of the whole population were similar to reference values representative of the Sardinian population and acceptably safe according to currently available health guidelines.

Respiratory parameters at varied altitudes in intermittent mining work.

PubMed

Bacaloni, Alessandro; Zamora Saà, Margarita Cecilia; Sinibaldi, Federica; Steffanina, Alessia; Insogna, Susanna

2018-01-07

Workers in the mining industry in altitude are subjected to several risk factors, e.g., airborne silica and low barometric pressure. The aim of this study has been to assess the risks for this work category, evaluating single risk factors as airborne silica, altitude and work shift, and relating them with cardiovascular and ventilatory parameters. Healthy miners employed in a mining company, Chile, working at varied altitudes, and subjected to unusual work shifts, were evaluated. Cardiovascular and respiratory parameters were investigated. Exposure to airborne silica was evaluated and compared to currently binding exposure limits. At varied altitudes and work shifts, alterations emerged in haemoglobin, ventilation and respiratory parameters, related to employment duration, due to compensatory mechanisms for hypoxia. Haemoglobin increased with altitude, saturation fell down under 90% in the highest mines. The multiple linear regression analysis showed a direct relationship, in the higher mine, between years of exposure to altitude and increased forced vital capacity percent (FVC%), and forced expiratory volume in 1 s (FEV1). An inverse relationship emerged between forced vital capacity (FVC) and years of exposure to airborne silica. In the workplace Mina Subterrànea (MT-3600), statistically significant inverse relationship emerged between the Tiffeneau index and body weight. The working conditions in the mining industry in altitude appeared to be potentially pathogenic; further investigations should be realized integrating risk assessment protocols even in consideration of their undeniable unconventionality. Int J Occup Med Environ Health 2018;31(2):129-138. This work is available in Open Access model and licensed under a CC BY-NC 3.0 PL license.

Characterization, distribution, and risk assessment of heavy metals in agricultural soil and products around mining and smelting areas of Hezhang, China.

PubMed

Briki, Meryem; Ji, Hongbing; Li, Cai; Ding, Huaijian; Gao, Yang

2015-12-01

Mining and smelting have been releasing huge amount of toxic substances into the environment. In the present study, agricultural soil and different agricultural products (potato, Chinese cabbage, garlic bolt, corn) were analyzed to examine the source, spatial distribution, and risk of 12 elements (As, Be, Bi, Cd, Co, Cr, Cu, Hg, Ni, Pb, Sb, and Zn) in agricultural soil near mine fields, smelting fields, and mountain field around Hezhang County, west of Guizhou Province, China. Multivariate statistical analysis indicated that in mining area, As, Bi, Cd, Cu, Hg, Pb, Sb, and Zn were generated from anthropogenic sources; in smelting area, As, Be, Cd, Co, Cu, Pb, Sb, and Zn were derived from anthropogenic sources through zinc smelting ceased in 2004. The enrichment factors (EFs) and ecological risk index (RI) of soil in mining area are the most harmful, showing extremely high enrichment and very high ecological risk of As, Bi, Cd, Cu, Hg, Pb, Sb, and Zn. Zinc is the most significant enriched in the smelting area; however, mountain area has a moderate enrichment and ecological risk and do not present any ecological risk. According to spatial distribution, the concentrations depend on the nearby mining and smelting activities. Transfer factors (TFs) in the smelting area and mountain are high, implying a threat for human consumption. Therefore, further studies should be carried out taking into account the harm of those heavy metals and potential negative health effects from the consumption of agricultural products in these circumstances.

Application of standard photogeologic techniques to LANDSAT imagery for mineral exploration in the basin and range province of Utah and Nevada

NASA Technical Reports Server (NTRS)

Lattman, L. H. (Principal Investigator)

1977-01-01

The author has identified the following significant results. Standard photogeologic techniques were applied to LANDSAT imagery of the basin and range province of Utah and Nevada to relate linear, tonal, textural, drainage, and geomorphic features to known mineralized areas in an attempt to develop criteria for the location of mineral deposits. No consistent correlation was found between lineaments, mapped according to specified criteria, and locations of mines, mining districts, or intrusive outcrops. Tonal and textural patterns were more closely related to geologic outcrop patterns than to mineralization. A statistical study of drainage azimuths of various length classes as measured on LANDSAT showed significant correlation with mineralized districts in the length class of 3-6 km. Alignments of outcrops of basalt, a rock type highly visible on LANDSAT imagery, appear to be colinear with acidic and intermediate intrusive centers in some areas and may assist on the recognition of regional fracture systems for mineral exploration.

Classification and statistical analysis of mine spoils chemical composition from Oliete basin (Teruel, NE Spain)

NASA Astrophysics Data System (ADS)

Meseguer, S.; Sanfeliu, T.; Jordán, M. M.

2009-02-01

The Oliete basin (Early Cretaceous, NE Teruel, Spain) is one of the most important areas for the supply of mine spoils used as ball clays for the production of white and red stoneware in the Spanish ceramic industry of wall and floor tiles. This study corresponds to the second part of the paper published recently by Meseguer et al. (Environ Geol 2008) about the use of mine spoils from Teruel coal mining district. The present study shows a statistical data analysis from chemical data (major, minor and trace elements). The performed statistical analysis of chemical data included descriptive statistics and cluster analysis (with ANOVA and Scheffé methods). The cluster analysis of chemical data provided three main groups: C3 with the highest mean SiO2 content (66%) and lowest mean Al2O3 content (20%); C2 with lower SiO2 content (48%) and higher mean Al2O3 content (28%); and C1 with medium values for the SiO2 and Al2O3 mean content. The main applications of these materials are refractory, white and red ceramics, stoneware, heavy ceramics (including red earthenware, bricks and roof tiles), and components of white Portland cement and aluminous cement. Clays from group 2 are used in refractories (with higher kaolinite content, and constrictions to CaO + MgO and K2O + Na2O contents). All materials can be used in fine ceramics (white or red, according to the Fe2O3 + TiO2 content).

Application of multispectral scanner data to the study of an abandoned surface coal mine

NASA Technical Reports Server (NTRS)

Spisz, E. W.

1978-01-01

The utility of aircraft multispectral scanner data for describing the land cover features of an abandoned contour-mined coal mine is considered. The data were obtained with an 11 band multispectral scanner at an altitude of 1.2 kilometers. Supervised, maximum-likelihood statistical classifications of the data were made to establish land-cover classes and also to describe in more detail the barren surface features as they may pertain to the reclamation or restoration of the area. The scanner data for the surface-water areas were studied to establish the variability and range of the spectral signatures. Both day and night thermal images of the area are presented. The results of the study show that a high degree of statistical separation can be obtained from the multispectral scanner data for the various land-cover features.

MineScan: non-image data monitoring and mining from imaging modalities

NASA Astrophysics Data System (ADS)

Zaidi, Shayan M.; Huff, Dov; Bhalodia, Pankit; Mongkolwat, Pattanasak; Channin, David S.

2003-05-01

This project is intended to capture and interactively display non-image information routinely generated by imaging modalities. This information relates to the device's performance of the individual procedures and is not necessarily available in other information streams such as DICOM headers. While originally intended for use in servicing the modalities, this information can also be presented to radiologists and administrators within the department for both micro- and macro-management purposes. This data can help hospital administrators and radiologists manage available resources and discover clues to indicate what modifications in hospital operations might significantly improve its ability to provide efficient patient care. Data is collected from a departmental CT scanner. The data consists of a running record of exams followed by a list of processing records logged over a 24-hour period. MineScan extracts information from these records and stores it into a database. A statistical program is run once a day to collect relevant metrics. MineScan can be accessed via a Web browser or through an advanced prototype PACS workstation. This information, if provided in real-time, can be used to manage operations in a busy department. Even when provided historically, the data can be used to assess current activity, analyze trends and plan future operations.

Predicting the graft survival for heart-lung transplantation patients: an integrated data mining methodology.

PubMed

Oztekin, Asil; Delen, Dursun; Kong, Zhenyu James

2009-12-01

Predicting the survival of heart-lung transplant patients has the potential to play a critical role in understanding and improving the matching procedure between the recipient and graft. Although voluminous data related to the transplantation procedures is being collected and stored, only a small subset of the predictive factors has been used in modeling heart-lung transplantation outcomes. The previous studies have mainly focused on applying statistical techniques to a small set of factors selected by the domain-experts in order to reveal the simple linear relationships between the factors and survival. The collection of methods known as 'data mining' offers significant advantages over conventional statistical techniques in dealing with the latter's limitations such as normality assumption of observations, independence of observations from each other, and linearity of the relationship between the observations and the output measure(s). There are statistical methods that overcome these limitations. Yet, they are computationally more expensive and do not provide fast and flexible solutions as do data mining techniques in large datasets. The main objective of this study is to improve the prediction of outcomes following combined heart-lung transplantation by proposing an integrated data-mining methodology. A large and feature-rich dataset (16,604 cases with 283 variables) is used to (1) develop machine learning based predictive models and (2) extract the most important predictive factors. Then, using three different variable selection methods, namely, (i) machine learning methods driven variables-using decision trees, neural networks, logistic regression, (ii) the literature review-based expert-defined variables, and (iii) common sense-based interaction variables, a consolidated set of factors is generated and used to develop Cox regression models for heart-lung graft survival. The predictive models' performance in terms of 10-fold cross-validation accuracy rates for two multi-imputed datasets ranged from 79% to 86% for neural networks, from 78% to 86% for logistic regression, and from 71% to 79% for decision trees. The results indicate that the proposed integrated data mining methodology using Cox hazard models better predicted the graft survival with different variables than the conventional approaches commonly used in the literature. This result is validated by the comparison of the corresponding Gains charts for our proposed methodology and the literature review based Cox results, and by the comparison of Akaike information criteria (AIC) values received from each. Data mining-based methodology proposed in this study reveals that there are undiscovered relationships (i.e. interactions of the existing variables) among the survival-related variables, which helps better predict the survival of the heart-lung transplants. It also brings a different set of variables into the scene to be evaluated by the domain-experts and be considered prior to the organ transplantation.

Mining level of control in medical organizations.

PubMed

Çalimli, Olgu; Türkeli, Serkan; Eken, Emir Gökberk; Gönen, Halil Emre

2014-01-01

In literature of strategic management, there are three layers of control defined in organizational structures. These layers are strategic, tactical and operational, in which resides senior, medium level and low level managers respectively. In strategic level, institutional strategies are determined according to senior managers' perceived state of organization. In tactical level, this strategy is processed into methods and activities of a business management plan. Operational level embodies actions and functions to sustain specified business management plan. An acknowledged lead organization in Turkish medical area is examined using case study and data mining method in the scope of this paper. The level of decisions regarded in managerial purposes evaluated through chosen organization's business intelligence event logs report. Hence specification of management level importance of medical organizations is made. Case study, data mining and descriptive statistical method of taken case's reports present that positions of "Chief Executive Officer", "Outpatient Center Manager", "General Manager", monitored and analyzed functions of operational level management more frequently than strategic and tactical level. Absence of strategic management decision level research in medical area distinguishes this paper and consequently substantiates its significant contribution.

Copper, cadmium, and zinc concentrations in aquatic food chains from the Upper Sacramento River (California) and selected tributaries

USGS Publications Warehouse

Saiki, M.K.; Castleberry, D. T.; May, T. W.; Martin, B.A.; Bullard, F. N.

1995-01-01

Metals enter the Upper Sacramento River above Redding, California, primarily through Spring Creek, a tributary that receives acid-mine drainage from a US EPA Superfund site known locally as Iron Mountain Mine. Waterweed (Elodea canadensis) and aquatic insects (midge larvae, Chironomidae; and mayfly nymphs, Ephemeroptera) from the Sacramento River downstream from Spring Creek contained much higher concentrations of copper (Cu), cadmium (Cd), and zinc (Zn) than did similar taxa from nearby reference tributaries not exposed to acid-mine drainage. Aquatic insects from the Sacramento River contained especially high maximum concentrations of Cu (200 mg/kg dry weight in midge larvae), Cd (23 mg/kg dry weight in mayfly nymphs), and Zn (1,700 mg/kg dry weight in mayfly nymphs). Although not always statistically significant, whole-body concentrations of Cu, Cd, and Zn in fishes (threespine stickleback, Gasterosteus aculeatus; Sacramento sucker, Catostomus occidentalis; Sacramento squawfish, Ptychocheilus grandis; and chinook salmon, Oncorhynchus tshawytasch) from the Sacramento River were generally higher than in fishes from the reference tributaries.

Statistically Modeling Individual Students' Learning over Successive Collaborative Practice Opportunities

ERIC Educational Resources Information Center

Olsen, Jennifer; Aleven, Vincent; Rummel, Nikol

2017-01-01

Within educational data mining, many statistical models capture the learning of students working individually. However, not much work has been done to extend these statistical models of individual learning to a collaborative setting, despite the effectiveness of collaborative learning activities. We extend a widely used model (the additive factors…

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

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.

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.

Data mining and statistical inference in selective laser melting

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

Kamath, Chandrika

Selective laser melting (SLM) is an additive manufacturing process that builds a complex three-dimensional part, layer-by-layer, using a laser beam to fuse fine metal powder together. The design freedom afforded by SLM comes associated with complexity. As the physical phenomena occur over a broad range of length and time scales, the computational cost of modeling the process is high. At the same time, the large number of parameters that control the quality of a part make experiments expensive. In this paper, we describe ways in which we can use data mining and statistical inference techniques to intelligently combine simulations andmore » experiments to build parts with desired properties. We start with a brief summary of prior work in finding process parameters for high-density parts. We then expand on this work to show how we can improve the approach by using feature selection techniques to identify important variables, data-driven surrogate models to reduce computational costs, improved sampling techniques to cover the design space adequately, and uncertainty analysis for statistical inference. Here, our results indicate that techniques from data mining and statistics can complement those from physical modeling to provide greater insight into complex processes such as selective laser melting.« less

Data mining and statistical inference in selective laser melting

DOE PAGES

Kamath, Chandrika

2016-01-11

Selective laser melting (SLM) is an additive manufacturing process that builds a complex three-dimensional part, layer-by-layer, using a laser beam to fuse fine metal powder together. The design freedom afforded by SLM comes associated with complexity. As the physical phenomena occur over a broad range of length and time scales, the computational cost of modeling the process is high. At the same time, the large number of parameters that control the quality of a part make experiments expensive. In this paper, we describe ways in which we can use data mining and statistical inference techniques to intelligently combine simulations andmore » experiments to build parts with desired properties. We start with a brief summary of prior work in finding process parameters for high-density parts. We then expand on this work to show how we can improve the approach by using feature selection techniques to identify important variables, data-driven surrogate models to reduce computational costs, improved sampling techniques to cover the design space adequately, and uncertainty analysis for statistical inference. Here, our results indicate that techniques from data mining and statistics can complement those from physical modeling to provide greater insight into complex processes such as selective laser melting.« less

Development and application of an interaction network ontology for literature mining of vaccine-associated gene-gene interactions.

PubMed

Hur, Junguk; Özgür, Arzucan; Xiang, Zuoshuang; He, Yongqun

2015-01-01

Literature mining of gene-gene interactions has been enhanced by ontology-based name classifications. However, in biomedical literature mining, interaction keywords have not been carefully studied and used beyond a collection of keywords. In this study, we report the development of a new Interaction Network Ontology (INO) that classifies >800 interaction keywords and incorporates interaction terms from the PSI Molecular Interactions (PSI-MI) and Gene Ontology (GO). Using INO-based literature mining results, a modified Fisher's exact test was established to analyze significantly over- and under-represented enriched gene-gene interaction types within a specific area. Such a strategy was applied to study the vaccine-mediated gene-gene interactions using all PubMed abstracts. The Vaccine Ontology (VO) and INO were used to support the retrieval of vaccine terms and interaction keywords from the literature. INO is aligned with the Basic Formal Ontology (BFO) and imports terms from 10 other existing ontologies. Current INO includes 540 terms. In terms of interaction-related terms, INO imports and aligns PSI-MI and GO interaction terms and includes over 100 newly generated ontology terms with 'INO_' prefix. A new annotation property, 'has literature mining keywords', was generated to allow the listing of different keywords mapping to the interaction types in INO. Using all PubMed documents published as of 12/31/2013, approximately 266,000 vaccine-associated documents were identified, and a total of 6,116 gene-pairs were associated with at least one INO term. Out of 78 INO interaction terms associated with at least five gene-pairs of the vaccine-associated sub-network, 14 terms were significantly over-represented (i.e., more frequently used) and 17 under-represented based on our modified Fisher's exact test. These over-represented and under-represented terms share some common top-level terms but are distinct at the bottom levels of the INO hierarchy. The analysis of these interaction types and their associated gene-gene pairs uncovered many scientific insights. INO provides a novel approach for defining hierarchical interaction types and related keywords for literature mining. The ontology-based literature mining, in combination with an INO-based statistical interaction enrichment test, provides a new platform for efficient mining and analysis of topic-specific gene interaction networks.

WGSSAT: A High-Throughput Computational Pipeline for Mining and Annotation of SSR Markers From Whole Genomes.

PubMed

Pandey, Manmohan; Kumar, Ravindra; Srivastava, Prachi; Agarwal, Suyash; Srivastava, Shreya; Nagpure, Naresh S; Jena, Joy K; Kushwaha, Basdeo

2018-03-16

Mining and characterization of Simple Sequence Repeat (SSR) markers from whole genomes provide valuable information about biological significance of SSR distribution and also facilitate development of markers for genetic analysis. Whole genome sequencing (WGS)-SSR Annotation Tool (WGSSAT) is a graphical user interface pipeline developed using Java Netbeans and Perl scripts which facilitates in simplifying the process of SSR mining and characterization. WGSSAT takes input in FASTA format and automates the prediction of genes, noncoding RNA (ncRNA), core genes, repeats and SSRs from whole genomes followed by mapping of the predicted SSRs onto a genome (classified according to genes, ncRNA, repeats, exonic, intronic, and core gene region) along with primer identification and mining of cross-species markers. The program also generates a detailed statistical report along with visualization of mapped SSRs, genes, core genes, and RNAs. The features of WGSSAT were demonstrated using Takifugu rubripes data. This yielded a total of 139 057 SSR, out of which 113 703 SSR primer pairs were uniquely amplified in silico onto a T. rubripes (fugu) genome. Out of 113 703 mined SSRs, 81 463 were from coding region (including 4286 exonic and 77 177 intronic), 7 from RNA, 267 from core genes of fugu, whereas 105 641 SSR and 601 SSR primer pairs were uniquely mapped onto the medaka genome. WGSSAT is tested under Ubuntu Linux. The source code, documentation, user manual, example dataset and scripts are available online at https://sourceforge.net/projects/wgssat-nbfgr.

Geochemical processes controlling selenium in ground water after mining, Powder River Basin, Wyoming, U.S.A.

USGS Publications Warehouse

Naftz, D.L.; Rice, J.A.

1989-01-01

Geochemical data for samples of overburden from three mines in the Powder River Basin indicate a statistically significant (0.01 confidence level) positive correlation (r = 0.74) between Se and organic C. Results of factor analysis with varimax rotation on the major and trace element data from the rock samples indicate large (>50) varimax loadings for Se in two of the three factors. In Factor 1, the association of Se with constituents common to detrital grains indicates that water transporting the detrital particles into the Powder River Basin also carried dissolved Se. The large (>50) varimax loadings of Se and organic C in Factor 2 probably are due to the organic affinities characteristic of Se. Dissolved Se concentrations in water samples collected at one coal mine are directly related to the dissolved organic C concentrations. Hydrophilic acid concentrations in the water samples from the mine ranged from 35 to 43% of the total dissolved organic C, and hydrophobic acid concentrations ranged from 40 to 49% of the total dissolved organic C. The largest dissolved organic C concentrations in water from the same mine (34-302 mg/l), coupled with the large proportion of acidic components, may saturate adsorption sites on geothite and similar minerals that comprise the aquifer material, thus decreasing the extent of selenite (SeO32-) adsorption as a sink for Se as the redox state of ground water decreases. ?? 1989.

Heavy metal pollution caused by small-scale metal ore mining activities: A case study from a polymetallic mine in South China.

PubMed

Sun, Zehang; Xie, Xiande; Wang, Ping; Hu, Yuanan; Cheng, Hefa

2018-10-15

Although metal ore mining activities are well known as an important source of heavy metals, soil pollution caused by small-scale mining activities has long been overlooked. This study investigated the pollution of surface soils in an area surrounding a recently abandoned small-scale polymetallic mining district in Guangdong province of south China. A total of 13 tailing samples, 145 surface soil samples, and 29 water samples were collected, and the concentrations of major heavy metals, including Cr, Mn, Co, Ni, Cu, Zn, As, Cd, Pb, and Se, were determined. The results show that the tailings contained high levels of heavy metals, with Cu, Zn, As, Cd, and Pb occurring in the ranges of 739-4.15 × 10 3 , 1.81 × 10 3 -5.00 × 10 3 , 118-1.26 × 10 3 , 8.14-57.7, and 1.23 × 10 3 -6.99 × 10 3  mg/kg, respectively. Heavy metals also occurred at high concentrations in the mine drainages (15.4-17.9 mg/L for Cu, 21.1-29.3 mg/L for Zn, 0.553-0.770 mg/L for Cd, and 1.17-2.57 mg/L for Pb), particularly those with pH below 3. The mean contents of Cu, Zn, As, Cd, and Pb in the surface soils of local farmlands were up to 7 times higher than the corresponding background values, and results of multivariate statistical analysis clearly indicate that Cu, Zn, Cd, and Pb were largely contributed by the mining activities. The surface soils from farmlands surrounding the mining district were moderately to seriously polluted, while the potential ecological risk of heavy metal pollution was extremely high. It was estimated that the input fluxes from the mining district to the surrounding farmlands were approximately 17.1, 59.2, 0.311, and 93.8 kg/ha/yr for Cu, Zn, Cd, and Pb, respectively, which probably occurred through transport of fine tailings by wind and runoff, and mine drainage as well. These findings indicate the significant need for proper containment of the mine tailings at small-scale metal ore mines. Copyright © 2018. Published by Elsevier B.V.

Fusion of Local Statistical Parameters for Buried Underwater Mine Detection in Sonar Imaging

NASA Astrophysics Data System (ADS)

Maussang, F.; Rombaut, M.; Chanussot, J.; Hétet, A.; Amate, M.

2008-12-01

Detection of buried underwater objects, and especially mines, is a current crucial strategic task. Images provided by sonar systems allowing to penetrate in the sea floor, such as the synthetic aperture sonars (SASs), are of great interest for the detection and classification of such objects. However, the signal-to-noise ratio is fairly low and advanced information processing is required for a correct and reliable detection of the echoes generated by the objects. The detection method proposed in this paper is based on a data-fusion architecture using the belief theory. The input data of this architecture are local statistical characteristics extracted from SAS data corresponding to the first-, second-, third-, and fourth-order statistical properties of the sonar images, respectively. The interest of these parameters is derived from a statistical model of the sonar data. Numerical criteria are also proposed to estimate the detection performances and to validate the method.

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.

Predicting Rotator Cuff Tears Using Data Mining and Bayesian Likelihood Ratios

PubMed Central

Lu, Hsueh-Yi; Huang, Chen-Yuan; Su, Chwen-Tzeng; Lin, Chen-Chiang

2014-01-01

Objectives Rotator cuff tear is a common cause of shoulder diseases. Correct diagnosis of rotator cuff tears can save patients from further invasive, costly and painful tests. This study used predictive data mining and Bayesian theory to improve the accuracy of diagnosing rotator cuff tears by clinical examination alone. Methods In this retrospective study, 169 patients who had a preliminary diagnosis of rotator cuff tear on the basis of clinical evaluation followed by confirmatory MRI between 2007 and 2011 were identified. MRI was used as a reference standard to classify rotator cuff tears. The predictor variable was the clinical assessment results, which consisted of 16 attributes. This study employed 2 data mining methods (ANN and the decision tree) and a statistical method (logistic regression) to classify the rotator cuff diagnosis into “tear” and “no tear” groups. Likelihood ratio and Bayesian theory were applied to estimate the probability of rotator cuff tears based on the results of the prediction models. Results Our proposed data mining procedures outperformed the classic statistical method. The correction rate, sensitivity, specificity and area under the ROC curve of predicting a rotator cuff tear were statistical better in the ANN and decision tree models compared to logistic regression. Based on likelihood ratios derived from our prediction models, Fagan's nomogram could be constructed to assess the probability of a patient who has a rotator cuff tear using a pretest probability and a prediction result (tear or no tear). Conclusions Our predictive data mining models, combined with likelihood ratios and Bayesian theory, appear to be good tools to classify rotator cuff tears as well as determine the probability of the presence of the disease to enhance diagnostic decision making for rotator cuff tears. PMID:24733553

Quantification of proportions of different water sources in a mining operation.

PubMed

Scheiber, Laura; Ayora, Carlos; Vázquez-Suñé, Enric

2018-04-01

The water drained in mining operations (galleries, shafts, open pits) usually comes from different sources. Evaluating the contribution of these sources is very often necessary for water management. To determine mixing ratios, a conventional mass balance is often used. However, the presence of more than two sources creates uncertainties in mass balance applications. Moreover, the composition of the end-members is not commonly known with certainty and/or can vary in space and time. In this paper, we propose a powerful tool for solving such problems and managing groundwater in mining sites based on multivariate statistical analysis. This approach was applied to the Cobre Las Cruces mining complex, the largest copper mine in Europe. There, the open pit water is a mixture of three end-members: runoff (RO), basal Miocene (Mb) and Paleozoic (PZ) groundwater. The volume of water drained from the Miocene base aquifer must be determined and compensated via artificial recharging to comply with current regulations. Through multivariate statistical analysis of samples from a regional field campaign, the compositions of PZ and Mb end-members were firstly estimated, and then used for mixing calculations at the open pit scale. The runoff end-member was directly determined from samples collected in interception trenches inside the open pit. The application of multivariate statistical methods allowed the estimation of mixing ratios for the hydrological years 2014-2015 and 2015-2016. Open pit water proportions have changed from 15% to 7%, 41% to 36%, and 44% to 57% for runoff, Mb and PZ end-members, respectively. An independent estimation of runoff based on the curve method yielded comparable results. Copyright © 2017 Elsevier B.V. All rights reserved.

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.

Accidents in Coal Mining from Perspective of Risk Theory

NASA Astrophysics Data System (ADS)

Khamidullina, E. A.; Timofeeva, S. S.; Smirnov, G. I.

2017-11-01

Introduction. The indicators of the safety system quality in the technosphere include risk indicators. The purpose of this work is to assess the social risk of coal mining since coal mining is associated with specific working conditions, and any emergency situation immediately jeopardizes thelives of many people at the same time. Methods. The work is based on the analysis of statistical information. Results and discussion. The F/N curve of coal mining for the 70-year period (1943-2012) was constructed, and the normative values of the social risk of Russia and other industrialized countries were discussed. Judging by the F/N diagram, only the frequency of accidents with a large number of deaths can correspond to the normative level indicating an exceptionally high level of coal mining risk.

Investigating spousal concordance of diabetes through statistical analysis and data mining.

PubMed

Wang, Jong-Yi; Liu, Chiu-Shong; Lung, Chi-Hsuan; Yang, Ya-Tun; Lin, Ming-Hung

2017-01-01

Spousal clustering of diabetes merits attention. Whether old-age vulnerability or a shared family environment determines the concordance of diabetes is also uncertain. This study investigated the spousal concordance of diabetes and compared the risk of diabetes concordance between couples and noncouples by using nationally representative data. A total of 22,572 individuals identified from the 2002-2013 National Health Insurance Research Database of Taiwan constituted 5,643 couples and 5,643 noncouples through 1:1 dual propensity score matching (PSM). Factors associated with concordance in both spouses with diabetes were analyzed at the individual level. The risk of diabetes concordance between couples and noncouples was compared at the couple level. Logistic regression was the main statistical method. Statistical data were analyzed using SAS 9.4. C&RT and Apriori of data mining conducted in IBM SPSS Modeler 13 served as a supplement to statistics. High odds of the spousal concordance of diabetes were associated with old age, middle levels of urbanization, and high comorbidities (all P < 0.05). The dual PSM analysis revealed that the risk of diabetes concordance was significantly higher in couples (5.19%) than in noncouples (0.09%; OR = 61.743, P < 0.0001). A high concordance rate of diabetes in couples may indicate the influences of assortative mating and shared environment. Diabetes in a spouse implicates its risk in the partner. Family-based diabetes care that emphasizes the screening of couples at risk of diabetes by using the identified risk factors is suggested in prospective clinical practice interventions.

Investigating spousal concordance of diabetes through statistical analysis and data mining

PubMed Central

Liu, Chiu-Shong; Lung, Chi-Hsuan; Yang, Ya-Tun; Lin, Ming-Hung

2017-01-01

Objective Spousal clustering of diabetes merits attention. Whether old-age vulnerability or a shared family environment determines the concordance of diabetes is also uncertain. This study investigated the spousal concordance of diabetes and compared the risk of diabetes concordance between couples and noncouples by using nationally representative data. Methods A total of 22,572 individuals identified from the 2002–2013 National Health Insurance Research Database of Taiwan constituted 5,643 couples and 5,643 noncouples through 1:1 dual propensity score matching (PSM). Factors associated with concordance in both spouses with diabetes were analyzed at the individual level. The risk of diabetes concordance between couples and noncouples was compared at the couple level. Logistic regression was the main statistical method. Statistical data were analyzed using SAS 9.4. C&RT and Apriori of data mining conducted in IBM SPSS Modeler 13 served as a supplement to statistics. Results High odds of the spousal concordance of diabetes were associated with old age, middle levels of urbanization, and high comorbidities (all P < 0.05). The dual PSM analysis revealed that the risk of diabetes concordance was significantly higher in couples (5.19%) than in noncouples (0.09%; OR = 61.743, P < 0.0001). Conclusions A high concordance rate of diabetes in couples may indicate the influences of assortative mating and shared environment. Diabetes in a spouse implicates its risk in the partner. Family-based diabetes care that emphasizes the screening of couples at risk of diabetes by using the identified risk factors is suggested in prospective clinical practice interventions. PMID:28817654

Proceedings of the International Conference on Educational Data Mining (EDM) (2nd, Cordoba, Spain, July 1-3, 2009)

ERIC Educational Resources Information Center

Barnes, Tiffany, Ed.; Desmarais, Michel, Ed.; Romero, Cristobal, Ed.; Ventura, Sebastian, Ed.

2009-01-01

The Second International Conference on Educational Data Mining (EDM2009) was held at the University of Cordoba, Spain, on July 1-3, 2009. EDM brings together researchers from computer science, education, psychology, psychometrics, and statistics to analyze large data sets to answer educational research questions. The increase in instrumented…

Data-Mining Techniques in Detecting Factors Linked to Academic Achievement

ERIC Educational Resources Information Center

Martínez Abad, Fernando; Chaparro Caso López, Alicia A.

2017-01-01

In light of the emergence of statistical analysis techniques based on data mining in education sciences, and the potential they offer to detect non-trivial information in large databases, this paper presents a procedure used to detect factors linked to academic achievement in large-scale assessments. The study is based on a non-experimental,…

Proceedings of the International Conference on Educational Data Mining (EDM) (4th, Eindhoven, the Netherlands, July 6-8, 2011)

ERIC Educational Resources Information Center

Pechenizkiy, Mykola; Calders, Toon; Conati, Cristina; Ventura, Sebastian; Romero, Cristobal; Stamper, John

2011-01-01

The 4th International Conference on Educational Data Mining (EDM 2011) brings together researchers from computer science, education, psychology, psychometrics, and statistics to analyze large datasets to answer educational research questions. The conference, held in Eindhoven, The Netherlands, July 6-9, 2011, follows the three previous editions…

Environmental performance and financial report integrity: challenges for the mining sector in Indonesia

NASA Astrophysics Data System (ADS)

Mayangsari, S.

2018-01-01

This study investigates the influence of environmental performance on the financial report integrity. The statistics used were primary data from interviews with senior members of the mining sector regarding environmental issues, as well as secondary data using Financial Report 2016. The samples were listed mining companies with semester data. Questionnaires were used to measure their perceptions of the challenges concerning climate change faced by the mining sector. The results of this research show that regulatory interventions will be critical to environmental issues. This study employed KLD as a proxy for environmental performance, correlated with other variables regarding the integrity of disclosure. The outcome indicates that environmental issues will increase the integrity of financial reports.

Chemical composition of samples collected from waste rock dumps and other mining-related features at selected phosphate mines in southeastern Idaho, western Wyoming, and northern Utah

USGS Publications Warehouse

Moyle, Phillip R.; Causey, J. Douglas

2001-01-01

This report provides chemical analyses for 31 samples collected from various phosphate mine sites in southeastern Idaho (25), northern Utah (2), and western Wyoming (4). The sampling effort was undertaken as a reconnaissance and does not constitute a characterization of mine wastes. Twenty-five samples were collected from waste rock dumps, 2 from stockpiles, and 1 each from slag, tailings, mill shale, and an outcrop. All samples were analyzed for a suite of major, minor, and trace elements. Although the analytical data set for the 31 samples is too small for detailed statistical analysis, a summary of general observations is made.

Impacts of mining on water and soil.

PubMed

Warhate, S R; Yenkie, M K N; Pokale, W K

2007-04-01

Out of seven coal mines situated in Wardha River Valley located at Wani (Dist. Yavatmal), five open caste coal mines are run by Western Coal Field Ltd, India. The results of 25 water and 19 soil samples (including one over burden) from Nilapur, Bramhani, Kolera, Gowari, Pimpari and Aheri for their pH, TDS, hardness, alkalinity, fluoride, chloride, nitrite, nitrate, phosphate, sulfate, cadmium, lead, zinc, copper, nickel, arsenic, manganese, sodium and potassium are studied in the present work. Statistical analysis and graphical presentation of the results are discussed in this paper.

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

Jaramillo, C.A.; Pardo-Trujillo, A.; Rueda, M.

A palynological study of the Cerrejon Formation was conducted in order to date the formation and understand the floristic composition and diversity of a Paleocene tropical site. The Cerrejon Formation outcrops in the Cerrejon Coal Mine, the largest open cast coal mine in the world. Two cores (725 m) were provided by Carbones del Cerrejon LLC for study. Two hundred samples were prepared for palynology, and at least 150 palynomorphs were counted per sample where possible. Several statistical techniques including rarefaction, species accumulation curves, detrended correspondence analysis, and Anosim were used to analyze the floristic composition and diversity of themore » palynofloras. Palynomorph assemblages indicate that the age of the Cerrejon Formation and the overlying Tabaco Formation is Middle to Late Paleocene (ca. 60-58 Ma). Major structural repetitions were not found in the Cerrejon Formation in the Cerrejon coal mine, and there is little floral variation throughout. The floral composition, diversity, and lithofacies do not change significantly. Lithofacies associations and floral composition indicate deposition fluctuating from an estuarine-influenced coastal plain at the base to a fluvial-influenced coastal plain at the top. There are, however, significant differences in the composition and diversity of coal and siliciclastic samples. Coal palynofloras have fewer morphospecies, and a distinct and more homogeneous floral assemblage compared to assemblages from the intervening sisliciclastic strata, suggesting that tropical swampy environments supported fewer plant species and had a distinct vegetation adapted to permanently wet environments.« less

Text mining by Tsallis entropy

NASA Astrophysics Data System (ADS)

Jamaati, Maryam; Mehri, Ali

2018-01-01

Long-range correlations between the elements of natural languages enable them to convey very complex information. Complex structure of human language, as a manifestation of natural languages, motivates us to apply nonextensive statistical mechanics in text mining. Tsallis entropy appropriately ranks the terms' relevance to document subject, taking advantage of their spatial correlation length. We apply this statistical concept as a new powerful word ranking metric in order to extract keywords of a single document. We carry out an experimental evaluation, which shows capability of the presented method in keyword extraction. We find that, Tsallis entropy has reliable word ranking performance, at the same level of the best previous ranking methods.

Prostate cancer mortality risk in relation to working underground in the Wismut cohort study of German uranium miners, 1970-2003.

PubMed

Walsh, Linda; Dufey, Florian; Tschense, Annemarie; Schnelzer, Maria; Sogl, Marion; Kreuzer, Michaela

2012-01-01

A recent study and comprehensive literature review has indicated that mining could be protective against prostate cancer. This indication has been explored further here by analysing prostate cancer mortality in the German 'Wismut' uranium miner cohort, which has detailed information on the number of days worked underground. An historical cohort study of 58 987 male mine workers with retrospective follow-up before 1999 and prospective follow-up since 1999. Uranium mine workers employed during the period 1970-1990 in the regions of Saxony and Thuringia, Germany, contributing 1.42 million person-years of follow-up ending in 2003. Simple standardised mortality ratio (SMR) analyses were applied to assess differences between the national and cohort prostate cancer mortality rates and complemented by refined analyses done entirely within the cohort. The internal comparisons applied Poisson regression excess relative prostate cancer mortality risk model with background stratification by age and calendar year and a whole range of possible explanatory covariables that included days worked underground and years worked at high physical activity with γ radiation treated as a confounder. The analysis is based on miner data for 263 prostate cancer deaths. The overall SMR was 0.85 (95% CI 0.75 to 0.95). A linear excess relative risk model with the number of years worked at high physical activity and the number of days worked underground as explanatory covariables provided a statistically significant fit when compared with the background model (p=0.039). Results (with 95% CIs) for the excess relative risk per day worked underground indicated a statistically significant (p=0.0096) small protective effect of -5.59 (-9.81 to -1.36) ×10(-5). Evidence is provided from the German Wismut cohort in support of a protective effect from working underground on prostate cancer mortality risk.

Antidepressants and testicular cancer: cause versus association.

PubMed

Andrade, Chittaranjan

2014-03-01

A data mining study that examined associations between 105 drugs and 55 cancer sites found significant associations between 2 selective serotonin reuptake inhibitors (fluoxetine and paroxetine) and testicular cancer. The study suggested several reasons why these associations merited further investigation. A later study tested specific relationships between 12 antidepressant drugs and testicular cancer and subtypes thereof; whereas significant relationships were again found, these disappeared after adjusting for confounding variables. These 2 studies are educative because they illustrate how false-positive results can easily arise in exploratory research and how confounding may be responsible for statistically significant relationships in study designs that are not randomized controlled trials. © Copyright 2014 Physicians Postgraduate Press, Inc.

Are Lithium Ion Cells Intrinsically Safe?

PubMed Central

Dubaniewicz, Thomas H.; DuCarme, Joseph P.

2015-01-01

National Institute for Occupational Safety and Health researchers are studying the potential for Li-ion-battery thermal runaway from an internal short circuit in equipment approved as permissible for use in underground coal mines. Researchers used a plastic wedge to induce internal short circuits for thermal runaway susceptibility evaluation purposes, which proved to be a more severe test than the flat plate method for selected Li-ion cells. Researchers conducted cell crush tests within a 20-L chamber filled with 6.5% CH4–air to simulate the mining hazard. Results indicate that LG Chem ICR18650S2 LiCoO2 cells pose a CH4 explosion hazard from a cell internal short circuit. Under specified test conditions, A123 Systems 26650 LiFePO4 cells were safer than the LG Chem ICR18650S2 LiCoO2 cells at a conservative statistical significance level. PMID:26166911

Mining Electronic Health Records Data: Domestic Violence and Adverse Health Effects.

PubMed

Karakurt, Gunnur; Patel, Vishal; Whiting, Kathleen; Koyutürk, Mehmet

2017-01-01

Intimate partner violence (IPV) often culminates in acute physical injury, sexual assault, and mental health issues. It is crucial to understand the healthcare habits of victims to develop interventions that can drastically improve a victim's quality of life and prevent future abuse. The objective of this study is to mine de-identified and aggregated Electronic Health Record data to identify women's health issues that are potentially associated with IPV. In this study we compared health issues of female domestic abuse victims to female non-domestic abuse victims. The Domestic abuse population contained 5870 patients, while the Non-Domestic Abuse population contained 14,315,140 patients. Explorys provides National Big Data from the entire USA. Statistical analysis identified 2429 terms as significantly more prevalent among victims of domestic abuse, compared to the general population. These terms were classified into broad categories, including acute injury, chronic conditions, substance abuse, mental health, disorders, gynecological and pregnancy related problems.

Multiple comparisons permutation test for image based data mining in radiotherapy.

PubMed

Chen, Chun; Witte, Marnix; Heemsbergen, Wilma; van Herk, Marcel

2013-12-23

: Comparing incidental dose distributions (i.e. images) of patients with different outcomes is a straightforward way to explore dose-response hypotheses in radiotherapy. In this paper, we introduced a permutation test that compares images, such as dose distributions from radiotherapy, while tackling the multiple comparisons problem. A test statistic Tmax was proposed that summarizes the differences between the images into a single value and a permutation procedure was employed to compute the adjusted p-value. We demonstrated the method in two retrospective studies: a prostate study that relates 3D dose distributions to failure, and an esophagus study that relates 2D surface dose distributions of the esophagus to acute esophagus toxicity. As a result, we were able to identify suspicious regions that are significantly associated with failure (prostate study) or toxicity (esophagus study). Permutation testing allows direct comparison of images from different patient categories and is a useful tool for data mining in radiotherapy.

Respiratory predictors of disability days: a five year prospective study of U. S. coal miners

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

Ames, R.G.; Trent, R.B.

1985-01-01

A 5-year prospective analysis tests the hypothesis that coal miners who have impaired respiratory health also experience greater numbers of disability days due to occupational injury. Occupational and respiratory health information collected for the period 1977 through 1981 by the National Institute for Occupational Safety and Health (NIOSH) on 1,118 U.S. underground coal miners was linked to coal miner injury records collected under a mandatory reporting system by the Mine Safety and Health Administration (MSHA). Respiratory impairment, based on spirometric measures, and a questionnaire measure of chronic bronchitis symptoms, after adjustment for cigarette smoking and total years of underground mining,more » did not provide statistically significant prediction of average disability days. In addition, respiratory impairment did not predict the number of episodes of occupational injuries resulting in days lost from work.« less

Use of data mining to predict significant factors and benefits of bilateral cochlear implantation.

PubMed

Ramos-Miguel, Angel; Perez-Zaballos, Teresa; Perez, Daniel; Falconb, Juan Carlos; Ramosb, Angel

2015-11-01

Data mining (DM) is a technique used to discover pattern and knowledge from a big amount of data. It uses artificial intelligence, automatic learning, statistics, databases, etc. In this study, DM was successfully used as a predictive tool to assess disyllabic speech test performance in bilateral implanted patients with a success rate above 90%. 60 bilateral sequentially implanted adult patients were included in the study. The DM algorithms developed found correlations between unilateral medical records and Audiological test results and bilateral performance by establishing relevant variables based on two DM techniques: the classifier and the estimation. The nearest neighbor algorithm was implemented in the first case, and the linear regression in the second. The results showed that patients with unilateral disyllabic test results below 70% benefited the most from a bilateral implantation. Finally, it was observed that its benefits decrease as the inter-implant time increases.

Developing image processing meta-algorithms with data mining of multiple metrics.

PubMed

Leung, Kelvin; Cunha, Alexandre; Toga, A W; Parker, D Stott

2014-01-01

People often use multiple metrics in image processing, but here we take a novel approach of mining the values of batteries of metrics on image processing results. We present a case for extending image processing methods to incorporate automated mining of multiple image metric values. Here by a metric we mean any image similarity or distance measure, and in this paper we consider intensity-based and statistical image measures and focus on registration as an image processing problem. We show how it is possible to develop meta-algorithms that evaluate different image processing results with a number of different metrics and mine the results in an automated fashion so as to select the best results. We show that the mining of multiple metrics offers a variety of potential benefits for many image processing problems, including improved robustness and validation.

Gaining Insights on Nasopharyngeal Carcinoma Treatment Outcome Using Clinical Data Mining Techniques.

PubMed

Ghaibeh, A Ammar; Kasem, Asem; Ng, Xun Jin; Nair, Hema Latha Krishna; Hirose, Jun; Thiruchelvam, Vinesh

2018-01-01

The analysis of Electronic Health Records (EHRs) is attracting a lot of research attention in the medical informatics domain. Hospitals and medical institutes started to use data mining techniques to gain new insights from the massive amounts of data that can be made available through EHRs. Researchers in the medical field have often used descriptive statistics and classical statistical methods to prove assumed medical hypotheses. However, discovering new insights from large amounts of data solely based on experts' observations is difficult. Using data mining techniques and visualizations, practitioners can find hidden knowledge, identify interesting patterns, or formulate new hypotheses to be further investigated. This paper describes a work in progress on using data mining methods to analyze clinical data of Nasopharyngeal Carcinoma (NPC) cancer patients. NPC is the fifth most common cancer among Malaysians, and the data analyzed in this study was collected from three states in Malaysia (Kuala Lumpur, Sabah and Sarawak), and is considered to be the largest up-to-date dataset of its kind. This research is addressing the issue of cancer recurrence after the completion of radiotherapy and chemotherapy treatment. We describe the procedure, problems, and insights gained during the process.

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.

Sources and fate of mercury pollution in Almadén mining district (Spain): Evidences from mercury isotopic compositions in sediments and lichens.

PubMed

Jiménez-Moreno, María; Barre, Julien P G; Perrot, Vincent; Bérail, Sylvain; Rodríguez Martín-Doimeadios, Rosa C; Amouroux, David

2016-03-01

Variations in mercury (Hg) isotopic compositions have been scarcely investigated until now in the Almadén mining district (Spain), which is one of the most impacted Hg areas worldwide. In this work, we explore and compare Hg isotopic signatures in sediments and lichens from Almadén mining district and its surroundings in order to identify and trace Hg aquatic and atmospheric contamination sources. No statistically significant mass independent fractionation was observed in sediments, while negative Δ(201)Hg values from -0.12 to -0.21‰ (2SD = 0.06‰) were found in lichens. A large range of δ(202)Hg values were reported in sediments, from -1.86 ± 0.21‰ in La Serena Reservoir sites far away from the pollution sources to δ(202)Hg values close to zero in sediments directly influenced by Almadén mining district, whereas lichens presented δ(202)Hg values from -1.95 to -0.40‰ (2SD = 0.15‰). A dilution or mixing trend in Hg isotope signatures versus the distance to the mine was found in sediments along the Valdeazogues River-La Serena Reservoir system and in lichens. This suggests that Hg isotope fingerprints in these samples are providing a direct assessment of Hg inputs and exposure from the mining district, and potential information on diffuse atmospheric contamination and/or geochemical alteration processes in less contaminated sites over the entire hydrosystem. This study confirms the applicability of Hg isotope signatures in lichens and sediments as an effective and complementary tool for tracing aquatic and atmospheric Hg contamination sources and a better constraint of the spatial and temporal fate of Hg released by recent or ancient mining activities. Copyright © 2015 Elsevier Ltd. All rights reserved.

Soil functional diversity analysis of a bauxite-mined restoration chronosequence.

PubMed

Lewis, Dawn E; White, John R; Wafula, Denis; Athar, Rana; Dickerson, Tamar; Williams, Henry N; Chauhan, Ashvini

2010-05-01

Soil microorganisms are sensitive to environmental perturbations such that changes in microbial community structure and function can provide early signs of anthropogenic disturbances and even predict restoration success. We evaluated the bacterial functional diversity of un-mined and three chronosequence sites at various stages of rehabilitation (0, 10, and 20 years old) located in the Mocho Mountains of Jamaica. Samples were collected during the dry and wet seasons and analyzed for metal concentrations, microbial biomass carbon, bacterial numbers, and functional responses of soil microbiota using community-level physiological profile (CLPP) assays. Regardless of the season, un-mined soils consisted of higher microbial biomass and numbers than any of the rehabilitated sites. Additionally, the number and rate of substrates utilized and substrate evenness (the distribution of color development between the substrates) were significantly greater in the un-mined soils with carbohydrates being preferentially utilized than amino acids, polymers, carboxylic acids, and esters. To some extent, functional responses varied with the seasons but the least physiological activity was shown by the site rehabilitated in 1987 indicating long-term perturbation to this ecosystem. Small subunit ribosomal DNA (SSUrDNA)-denaturing gradient-gel electrophoresis analyses on the microbiota collected from the most preferred CLPP substrates followed by taxonomic analyses showed Proteobacteria, specifically the gamma-proteobacteria, as the most functionally active phyla, indicating a propensity of this phyla to out-compete other groups under the prevailing conditions. Additionally, multivariate statistical analyses, Shannon's diversity, and evenness indices, principal component analysis, biplot and un-weighted-pair-group method with arithmetic averages dendrograms further confirmed that un-mined sites were distinctly different from the rehabilitated soils.

Application of data mining techniques and data analysis methods to measure cancer morbidity and mortality data in a regional cancer registry: The case of the island of Crete, Greece.

PubMed

Varlamis, Iraklis; Apostolakis, Ioannis; Sifaki-Pistolla, Dimitra; Dey, Nilanjan; Georgoulias, Vassilios; Lionis, Christos

2017-07-01

Micro or macro-level mapping of cancer statistics is a challenging task that requires long-term planning, prospective studies and continuous monitoring of all cancer cases. The objective of the current study is to present how cancer registry data could be processed using data mining techniques in order to improve the statistical analysis outcomes. Data were collected from the Cancer Registry of Crete in Greece (counties of Rethymno and Lasithi) for the period 1998-2004. Data collection was performed on paper forms and manually transcribed to a single data file, thus introducing errors and noise (e.g. missing and erroneous values, duplicate entries etc.). Data were pre-processed and prepared for analysis using data mining tools and algorithms. Feature selection was applied to evaluate the contribution of each collected feature in predicting patients' survival. Several classifiers were trained and evaluated for their ability to predict survival of patients. Finally, statistical analysis of cancer morbidity and mortality rates in the two regions was performed in order to validate the initial findings. Several critical points in the process of data collection, preprocessing and analysis of cancer data were derived from the results, while a road-map for future population data studies was developed. In addition, increased morbidity rates were observed in the counties of Crete (Age Standardized Morbidity/Incidence Rates ASIR= 396.45 ± 2.89 and 274.77 ±2.48 for men and women, respectively) compared to European and world averages (ASIR= 281.6 and 207.3 for men and women in Europe and 203.8 and 165.1 in world level). Significant variation in cancer types between sexes and age groups (the ratio between deaths and reported cases for young patients, less than 34 years old, is at 0.055 when the respective ratio for patients over 75 years old is 0.366) was also observed. This study introduced a methodology for preprocessing and analyzing cancer data, using a combination of data mining techniques that could be a useful tool for other researchers and further enhancement of the cancer registries. Copyright © 2017 Elsevier B.V. All rights reserved.

Chronic obstructive pulmonary disease in Welsh slate miners.

PubMed

Reynolds, C J; MacNeill, S J; Williams, J; Hodges, N G; Campbell, M J; Newman Taylor, A J; Cullinan, P

2017-01-01

Exposure to respirable crystalline silica (RCS) causes emphysema, airflow limitation and chronic obstructive pulmonary disease (COPD). Slate miners are exposed to slate dust containing RCS but their COPD risk has not previously been studied. To study the cumulative effect of mining on lung function and risk of COPD in a cohort of Welsh slate miners and whether these were independent of smoking and pneumoconiosis. The study was based on a secondary analysis of Medical Research Council (MRC) survey data. COPD was defined as forced expiratory volume in 1 s/forced vital capacity (FEV 1 /FVC) ratio <0.7. We created multivariable models to assess the association between mining and lung function after adjusting for age and smoking status. We used linear regression models for FEV 1 and FVC and logistic regression for COPD. In the original MRC study, 1255 men participated (726 slate miners, 529 unexposed non-miners). COPD was significantly more common in miners (n = 213, 33%) than non-miners (n = 120, 26%), P < 0.05. There was no statistically significant difference in risk of COPD between miners and non-miners when analysis was limited to non-smokers or those without radiographic evidence of pneumoconiosis. After adjustment for smoking, slate mining was associated with a reduction in %predicted FEV 1 [β coefficient = -3.97, 95% confidence interval (CI) -6.65, -1.29] and FVC (β coefficient = -2.32, 95% CI -4.31, -0.33) and increased risk of COPD (odds ratio: 1.38, 95% CI 1.06, 1.81). Slate mining may reduce lung function and increase the incidence of COPD independently of smoking and pneumoconiosis. © The Author 2016. Published by Oxford University Press on behalf of the Society of Occupational Medicine. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Wireless device for activation of an underground shock wave absorber

NASA Astrophysics Data System (ADS)

Chikhradze, M.; Akhvlediani, I.; Bochorishvili, N.; Mataradze, E.

2011-10-01

The paper describes the mechanism and design of the wireless device for activation of energy absorber for localization of blast energy in underground openings. The statistics shows that the greatest share of accidents with fatal results associate with explosions in coal mines due to aero-methane and/or air-coal media explosion. The other significant problem is terrorist or accidental explosions in underground structures. At present there are different protective systems to reduce the blast energy. One of the main parts of protective Systems is blast Identification and Registration Module. The works conducted at G. Tsulukidze Mining Institute of Georgia enabled to construct the wireless system of explosion detection and mitigation of shock waves. The system is based on the constant control on overpressure. The experimental research continues to fulfill the system based on both threats, on the constant control on overpressure and flame parameters, especially in underground structures and coal mines. Reaching the threshold value of any of those parameters, the system immediately starts the activation. The absorber contains a pyrotechnic device ensuring the discharge of dispersed water. The operational parameters of wireless device and activation mechanisms of pyrotechnic element of shock wave absorber are discussed in the paper.

U-Compare: share and compare text mining tools with UIMA.

PubMed

Kano, Yoshinobu; Baumgartner, William A; McCrohon, Luke; Ananiadou, Sophia; Cohen, K Bretonnel; Hunter, Lawrence; Tsujii, Jun'ichi

2009-08-01

Due to the increasing number of text mining resources (tools and corpora) available to biologists, interoperability issues between these resources are becoming significant obstacles to using them effectively. UIMA, the Unstructured Information Management Architecture, is an open framework designed to aid in the construction of more interoperable tools. U-Compare is built on top of the UIMA framework, and provides both a concrete framework for out-of-the-box text mining and a sophisticated evaluation platform allowing users to run specific tools on any target text, generating both detailed statistics and instance-based visualizations of outputs. U-Compare is a joint project, providing the world's largest, and still growing, collection of UIMA-compatible resources. These resources, originally developed by different groups for a variety of domains, include many famous tools and corpora. U-Compare can be launched straight from the web, without needing to be manually installed. All U-Compare components are provided ready-to-use and can be combined easily via a drag-and-drop interface without any programming. External UIMA components can also simply be mixed with U-Compare components, without distinguishing between locally and remotely deployed resources. http://u-compare.org/

Analyses of geological and hydrodynamic controls on methane emissions experienced in a Lower Kittanning coal mine

PubMed Central

Karacan, C. Özgen; Goodman, Gerrit V.R.

2015-01-01

This paper presents a study assessing potential factors and migration paths of methane emissions experienced in a room-and-pillar mine in Lower Kittanning coal, Indiana County, Pennsylvania. Methane emissions were not excessive at idle mining areas, but significant methane was measured during coal mining and loading. Although methane concentrations in the mine did not exceed 1% limit during operation due to the presence of adequate dilution airflow, the source of methane and its migration into the mine was still a concern. In the course of this study, structural and depositional properties of the area were evaluated to assess complexity and sealing capacity of roof rocks. Composition, gas content, and permeability of Lower Kittanning coal, results of flotation tests, and geochemistry of groundwater obtained from observation boreholes were studied to understand the properties of coal and potential effects of old abandoned mines within the same area. These data were combined with the data obtained from exploration boreholes, such as depths, elevations, thicknesses, ash content, and heat value of coal. Univariate statistical and principal component analyses (PCA), as well as geostatistical simulations and co-simulations, were performed on various spatial attributes to reveal interrelationships and to establish area-wide distributions. These studies helped in analyzing groundwater quality and determining gas-in-place (GIP) of the Lower Kittanning seam. Furthermore, groundwater level and head on the Lower Kittanning coal were modeled and flow gradients within the study area were examined. Modeling results were interpreted with the structural geology of the Allegheny Group of formations above the Lower Kittanning coal to understand the potential source of gas and its migration paths. Analyses suggested that the source of methane was likely the overlying seams such as the Middle and Upper Kittanning coals and Freeport seams of the Allegheny Group. Simulated ground-water water elevations, gradients of groundwater flow, and the presence of recharge and discharge locations at very close proximity to the mine indicated that methane likely was carried with groundwater towards the mine entries. Existing fractures within the overlying strata and their orientation due to the geologic conditions of the area, and activation of slickensides between shale and sandstones due to differential compaction during mining, were interpreted as the potential flow paths. PMID:26478644

Analysis of North Atlantic tropical cyclone intensify change using data mining

NASA Astrophysics Data System (ADS)

Tang, Jiang

Tropical cyclones (TC), especially when their intensity reaches hurricane scale, can become a costly natural hazard. Accurate prediction of tropical cyclone intensity is very difficult because of inadequate observations on TC structures, poor understanding of physical processes, coarse model resolution and inaccurate initial conditions, etc. This study aims to tackle two factors that account for the underperformance of current TC intensity forecasts: (1) inadequate observations of TC structures, and (2) deficient understanding of the underlying physical processes governing TC intensification. To tackle the problem of inadequate observations of TC structures, efforts have been made to extract vertical and horizontal structural parameters of latent heat release from Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR) data products. A case study of Hurricane Isabel (2003) was conducted first to explore the feasibility of using the 3D TC structure information in predicting TC intensification. Afterwards, several structural parameters were extracted from 53 TRMM PR 2A25 observations on 25 North Atlantic TCs during the period of 1998 to 2003. A new generation of multi-correlation data mining algorithm (Apriori and its variations) was applied to find roles of the latent heat release structure in TC intensification. The results showed that the buildup of TC energy is indicated by the height of the convective tower, and the relative low latent heat release at the core area and around the outer band. Adverse conditions which prevent TC intensification include the following: (1) TC entering a higher latitude area where the underlying sea is relative cold, (2) TC moving too fast to absorb the thermal energy from the underlying sea, or (3) strong energy loss at the outer band. When adverse conditions and amicable conditions reached equilibrium status, tropical cyclone intensity would remain stable. The dataset from Statistical Hurricane Intensity Prediction Scheme (SHIPS) covering the period of 1982-2003 and the Apriori-based association rule mining algorithm were used to study the associations of underlying geophysical characteristics with the intensity change of tropical cyclones. The data have been stratified into 6 TC categories from tropical depression to category 4 hurricanes based on their strength. The result showed that the persistence of intensity change in the past and the strength of vertical shear in the environment are the most prevalent factors for all of the 6 TC categories. Hyper-edge searching had found 3 sets of parameters which showed strong intramural binds. Most of the parameters used in SHIPS model have a consistent "I-W" relation over different TC categories, indicating a consistent function of those parameters in TC development. However, the "I-W" relations of the relative momentum flux and the meridional motion change from tropical storm stage to hurricane stage, indicating a change in the role of those two parameters in TC development. Because rapid intensification (RI) is a major source of errors when predicting hurricane intensity, the association rule mining algorithm was performed on RI versus non-RI tropical cyclone cases using the same SHIPS dataset. The results had been compared with those from the traditional statistical analysis conducted by Kaplan and DeMaria (2003). The rapid intensification rule with 5 RI conditions proposed by the traditional statistical analysis was found by the association rule mining in this study as well. However, further analysis showed that the 5 RI conditions can be replaced by another association rule using fewer conditions but with a higher RI probability (RIP). This means that the rule with all 5 constraints found by Kaplan and DeMaria is not optimal, and the association rule mining technique can find a rule with fewer constraints yet fits more RI cases. The further analysis with the highest RIPs over different numbers of conditions has demonstrated that the interactions among multiple factors are responsible for the RI process of TCs. However, the influence of factors saturates at certain numbers. This study has shown successful data mining examples in studying tropical cyclone intensification using association rules. The higher RI probability with fewer conditions found by association rule technique is significant. This work demonstrated that data mining techniques can be used as an efficient exploration method to generate hypotheses, and that statistical analysis should be performed to confirm the hypotheses, as is generally expected for data mining applications.

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.

Data Mining in Institutional Economics Tasks

NASA Astrophysics Data System (ADS)

Kirilyuk, Igor; Kuznetsova, Anna; Senko, Oleg

2018-02-01

The paper discusses problems associated with the use of data mining tools to study discrepancies between countries with different types of institutional matrices by variety of potential explanatory variables: climate, economic or infrastructure indicators. An approach is presented which is based on the search of statistically valid regularities describing the dependence of the institutional type on a single variable or a pair of variables. Examples of regularities are given.

Comparison analysis for classification algorithm in data mining and the study of model use

NASA Astrophysics Data System (ADS)

Chen, Junde; Zhang, Defu

2018-04-01

As a key technique in data mining, classification algorithm was received extensive attention. Through an experiment of classification algorithm in UCI data set, we gave a comparison analysis method for the different algorithms and the statistical test was used here. Than that, an adaptive diagnosis model for preventive electricity stealing and leakage was given as a specific case in the paper.

RUM JUNGLE PROJECT

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

Australia. Atomic Energy Commission

1963-01-01

A report is presented on the uranium mining and treatment industry established at Rum Jungle and its contribution to the development of the Northern Territory. The Combined Development Agency contract for uranium procurement (terminated in 1963) and some of its results are described. A description of Rum Jungle and its geology and mineralization is given. Mining and treatment of ore are discussed, and some production statistics are given. (D.L.C.)

SOME APPLICATIONS OF SEISMIC SOURCE MECHANISM STUDIES TO ASSESSING UNDERGROUND HAZARD.

USGS Publications Warehouse

McGarr, A.; ,

1984-01-01

Various measures of the seismic source mechanism of mine tremors, such as magnitude, moment, stress drop, apparent stress, and seismic efficiency, can be related directly to several aspects of the problem of determining the underground hazard arising from strong ground motion of large seismic events. First, the relation between the sum of seismic moments of tremors and the volume of stope closure caused by mining during a given period can be used in conjunction with magnitude-frequency statistics and an empirical relation between moment and magnitude to estimate the maximum possible sized tremor for a given mining situation. Second, it is shown that the 'energy release rate,' a commonly-used parameter for predicting underground seismic hazard, may be misleading in that the importance of overburden stress, or depth, is overstated. Third, results involving the relation between peak velocity and magnitude, magnitude-frequency statistics, and the maximum possible magnitude are applied to the problem of estimating the frequency at which design limits of certain underground support equipment are likely to be exceeded.

Statistical data mining of streaming motion data for fall detection in assistive environments.

PubMed

Tasoulis, S K; Doukas, C N; Maglogiannis, I; Plagianakos, V P

2011-01-01

The analysis of human motion data is interesting for the purpose of activity recognition or emergency event detection, especially in the case of elderly or disabled people living independently in their homes. Several techniques have been proposed for identifying such distress situations using either motion, audio or video sensors on the monitored subject (wearable sensors) or the surrounding environment. The output of such sensors is data streams that require real time recognition, especially in emergency situations, thus traditional classification approaches may not be applicable for immediate alarm triggering or fall prevention. This paper presents a statistical mining methodology that may be used for the specific problem of real time fall detection. Visual data captured from the user's environment, using overhead cameras along with motion data are collected from accelerometers on the subject's body and are fed to the fall detection system. The paper includes the details of the stream data mining methodology incorporated in the system along with an initial evaluation of the achieved accuracy in detecting falls.

The application of data mining techniques to oral cancer prognosis.

PubMed

Tseng, Wan-Ting; Chiang, Wei-Fan; Liu, Shyun-Yeu; Roan, Jinsheng; Lin, Chun-Nan

2015-05-01

This study adopted an integrated procedure that combines the clustering and classification features of data mining technology to determine the differences between the symptoms shown in past cases where patients died from or survived oral cancer. Two data mining tools, namely decision tree and artificial neural network, were used to analyze the historical cases of oral cancer, and their performance was compared with that of logistic regression, the popular statistical analysis tool. Both decision tree and artificial neural network models showed superiority to the traditional statistical model. However, as to clinician, the trees created by the decision tree models are relatively easier to interpret compared to that of the artificial neural network models. Cluster analysis also discovers that those stage 4 patients whose also possess the following four characteristics are having an extremely low survival rate: pN is N2b, level of RLNM is level I-III, AJCC-T is T4, and cells mutate situation (G) is moderate.

A Note on Interfacing Object Warehouses and Mass Storage Systems for Data Mining Applications

NASA Technical Reports Server (NTRS)

Grossman, Robert L.; Northcutt, Dave

1996-01-01

Data mining is the automatic discovery of patterns, associations, and anomalies in data sets. Data mining requires numerically and statistically intensive queries. Our assumption is that data mining requires a specialized data management infrastructure to support the aforementioned intensive queries, but because of the sizes of data involved, this infrastructure is layered over a hierarchical storage system. In this paper, we discuss the architecture of a system which is layered for modularity, but exploits specialized lightweight services to maintain efficiency. Rather than use a full functioned database for example, we use light weight object services specialized for data mining. We propose using information repositories between layers so that components on either side of the layer can access information in the repositories to assist in making decisions about data layout, the caching and migration of data, the scheduling of queries, and related matters.

Developing Image Processing Meta-Algorithms with Data Mining of Multiple Metrics

PubMed Central

Cunha, Alexandre; Toga, A. W.; Parker, D. Stott

2014-01-01

People often use multiple metrics in image processing, but here we take a novel approach of mining the values of batteries of metrics on image processing results. We present a case for extending image processing methods to incorporate automated mining of multiple image metric values. Here by a metric we mean any image similarity or distance measure, and in this paper we consider intensity-based and statistical image measures and focus on registration as an image processing problem. We show how it is possible to develop meta-algorithms that evaluate different image processing results with a number of different metrics and mine the results in an automated fashion so as to select the best results. We show that the mining of multiple metrics offers a variety of potential benefits for many image processing problems, including improved robustness and validation. PMID:24653748

Exploring patterns of epigenetic information with data mining techniques.

PubMed

Aguiar-Pulido, Vanessa; Seoane, José A; Gestal, Marcos; Dorado, Julián

2013-01-01

Data mining, a part of the Knowledge Discovery in Databases process (KDD), is the process of extracting patterns from large data sets by combining methods from statistics and artificial intelligence with database management. Analyses of epigenetic data have evolved towards genome-wide and high-throughput approaches, thus generating great amounts of data for which data mining is essential. Part of these data may contain patterns of epigenetic information which are mitotically and/or meiotically heritable determining gene expression and cellular differentiation, as well as cellular fate. Epigenetic lesions and genetic mutations are acquired by individuals during their life and accumulate with ageing. Both defects, either together or individually, can result in losing control over cell growth and, thus, causing cancer development. Data mining techniques could be then used to extract the previous patterns. This work reviews some of the most important applications of data mining to epigenetics.

Earth Conductivity Estimation from Through-the-Earth Measurements of 94 Coal Mines Using Different Electromagnetic Models

PubMed Central

Yan, Lincan; Waynert, Joseph; Sunderman, Carl

2015-01-01

Through-the-Earth (TTE) communication systems require minimal infrastructure to operate. Hence, they are assumed to be more survivable and more conventional than other underground mine communications systems. This survivability is a major advantage for TTE systems. In 2006, Congress passed the Mine Improvement and New Emergency Response Act (MINER Act), which requires all underground coal mines to install wireless communications systems. The intent behind this mandate is for trapped miners to be able to communicate with surface personnel after a major accident-hence, the interest in TTE communications. To determine the likelihood of establishing a TTE communication link, it would be ideal to be able to predict the apparent conductivity of the overburden above underground mines. In this paper, all 94 mine TTE measurement data collected by Bureau of Mines in the 1970s and early 1980s, are analyzed for the first time to determine the apparent conductivity of the overburden based on three different models: a homogenous half-space model, a thin sheet model, and an attenuation factor or Q-factor model. A statistical formula is proposed to estimate the apparent earth conductivity for a specific mine based on the TTE modeling results given the mine depth and signal frequency. PMID:26213457

Earth Conductivity Estimation from Through-the-Earth Measurements of 94 Coal Mines Using Different Electromagnetic Models.

PubMed

Yan, Lincan; Waynert, Joseph; Sunderman, Carl

2014-10-01

Through-the-Earth (TTE) communication systems require minimal infrastructure to operate. Hence, they are assumed to be more survivable and more conventional than other underground mine communications systems. This survivability is a major advantage for TTE systems. In 2006, Congress passed the Mine Improvement and New Emergency Response Act (MINER Act), which requires all underground coal mines to install wireless communications systems. The intent behind this mandate is for trapped miners to be able to communicate with surface personnel after a major accident-hence, the interest in TTE communications. To determine the likelihood of establishing a TTE communication link, it would be ideal to be able to predict the apparent conductivity of the overburden above underground mines. In this paper, all 94 mine TTE measurement data collected by Bureau of Mines in the 1970s and early 1980s, are analyzed for the first time to determine the apparent conductivity of the overburden based on three different models: a homogenous half-space model, a thin sheet model, and an attenuation factor or Q-factor model. A statistical formula is proposed to estimate the apparent earth conductivity for a specific mine based on the TTE modeling results given the mine depth and signal frequency.

Chronic cardiovascular disease mortality in mountaintop mining areas of central Appalachian states.

PubMed

Esch, Laura; Hendryx, Michael

2011-01-01

To determine if chronic cardiovascular disease (CVD) mortality rates are higher among residents of mountaintop mining (MTM) areas compared to mining and nonmining areas, and to examine the association between greater levels of MTM surface mining and CVD mortality. Age-adjusted chronic CVD mortality rates from 1999 to 2006 for counties in 4 Appalachian states where MTM occurs (N = 404) were linked with county coal mining data. Three groups of counties were compared: MTM, coal mining but not MTM, and nonmining. Covariates included smoking rate, rural-urban status, percent male population, primary care physician supply, obesity rate, diabetes rate, poverty rate, race/ethnicity rates, high school and college education rates, and Appalachian county. Linear regression analyses examined the association of mortality rates with mining in MTM areas and non-MTM areas and the association of mortality with quantity of surface coal mined in MTM areas. Prior to covariate adjustment, chronic CVD mortality rates were significantly higher in both mining areas compared to nonmining areas and significantly highest in MTM areas. After adjustment, mortality rates in MTM areas remained significantly higher and increased as a function of greater levels of surface mining. Higher obesity and poverty rates and lower college education rates also significantly predicted CVD mortality overall and in rural counties. MTM activity is significantly associated with elevated chronic CVD mortality rates. Future research is necessary to examine the socioeconomic and environmental impacts of MTM on health to reduce health disparities in rural coal mining areas. © 2011 National Rural Health Association.

Automated information and control complex of hydro-gas endogenous mine processes

NASA Astrophysics Data System (ADS)

Davkaev, K. S.; Lyakhovets, M. V.; Gulevich, T. M.; Zolin, K. A.

2017-09-01

The automated information and control complex designed to prevent accidents, related to aerological situation in the underground workings, accounting of the received and handed over individual devices, transmission and display of measurement data, and the formation of preemptive solutions is considered. Examples for the automated workplace of an airgas control operator by individual means are given. The statistical characteristics of field data characterizing the aerological situation in the mine are obtained. The conducted studies of statistical characteristics confirm the feasibility of creating a subsystem of controlled gas distribution with an adaptive arrangement of points for gas control. The adaptive (multivariant) algorithm for processing measuring information of continuous multidimensional quantities and influencing factors has been developed.

Detection and Evaluation of Spatio-Temporal Spike Patterns in Massively Parallel Spike Train Data with SPADE.

PubMed

Quaglio, Pietro; Yegenoglu, Alper; Torre, Emiliano; Endres, Dominik M; Grün, Sonja

2017-01-01

Repeated, precise sequences of spikes are largely considered a signature of activation of cell assemblies. These repeated sequences are commonly known under the name of spatio-temporal patterns (STPs). STPs are hypothesized to play a role in the communication of information in the computational process operated by the cerebral cortex. A variety of statistical methods for the detection of STPs have been developed and applied to electrophysiological recordings, but such methods scale poorly with the current size of available parallel spike train recordings (more than 100 neurons). In this work, we introduce a novel method capable of overcoming the computational and statistical limits of existing analysis techniques in detecting repeating STPs within massively parallel spike trains (MPST). We employ advanced data mining techniques to efficiently extract repeating sequences of spikes from the data. Then, we introduce and compare two alternative approaches to distinguish statistically significant patterns from chance sequences. The first approach uses a measure known as conceptual stability, of which we investigate a computationally cheap approximation for applications to such large data sets. The second approach is based on the evaluation of pattern statistical significance. In particular, we provide an extension to STPs of a method we recently introduced for the evaluation of statistical significance of synchronous spike patterns. The performance of the two approaches is evaluated in terms of computational load and statistical power on a variety of artificial data sets that replicate specific features of experimental data. Both methods provide an effective and robust procedure for detection of STPs in MPST data. The method based on significance evaluation shows the best overall performance, although at a higher computational cost. We name the novel procedure the spatio-temporal Spike PAttern Detection and Evaluation (SPADE) analysis.

Detection and Evaluation of Spatio-Temporal Spike Patterns in Massively Parallel Spike Train Data with SPADE

PubMed Central

Quaglio, Pietro; Yegenoglu, Alper; Torre, Emiliano; Endres, Dominik M.; Grün, Sonja

2017-01-01

Repeated, precise sequences of spikes are largely considered a signature of activation of cell assemblies. These repeated sequences are commonly known under the name of spatio-temporal patterns (STPs). STPs are hypothesized to play a role in the communication of information in the computational process operated by the cerebral cortex. A variety of statistical methods for the detection of STPs have been developed and applied to electrophysiological recordings, but such methods scale poorly with the current size of available parallel spike train recordings (more than 100 neurons). In this work, we introduce a novel method capable of overcoming the computational and statistical limits of existing analysis techniques in detecting repeating STPs within massively parallel spike trains (MPST). We employ advanced data mining techniques to efficiently extract repeating sequences of spikes from the data. Then, we introduce and compare two alternative approaches to distinguish statistically significant patterns from chance sequences. The first approach uses a measure known as conceptual stability, of which we investigate a computationally cheap approximation for applications to such large data sets. The second approach is based on the evaluation of pattern statistical significance. In particular, we provide an extension to STPs of a method we recently introduced for the evaluation of statistical significance of synchronous spike patterns. The performance of the two approaches is evaluated in terms of computational load and statistical power on a variety of artificial data sets that replicate specific features of experimental data. Both methods provide an effective and robust procedure for detection of STPs in MPST data. The method based on significance evaluation shows the best overall performance, although at a higher computational cost. We name the novel procedure the spatio-temporal Spike PAttern Detection and Evaluation (SPADE) analysis. PMID:28596729

An Analysis Pipeline with Statistical and Visualization-Guided Knowledge Discovery for Michigan-Style Learning Classifier Systems

PubMed Central

Urbanowicz, Ryan J.; Granizo-Mackenzie, Ambrose; Moore, Jason H.

2014-01-01

Michigan-style learning classifier systems (M-LCSs) represent an adaptive and powerful class of evolutionary algorithms which distribute the learned solution over a sizable population of rules. However their application to complex real world data mining problems, such as genetic association studies, has been limited. Traditional knowledge discovery strategies for M-LCS rule populations involve sorting and manual rule inspection. While this approach may be sufficient for simpler problems, the confounding influence of noise and the need to discriminate between predictive and non-predictive attributes calls for additional strategies. Additionally, tests of significance must be adapted to M-LCS analyses in order to make them a viable option within fields that require such analyses to assess confidence. In this work we introduce an M-LCS analysis pipeline that combines uniquely applied visualizations with objective statistical evaluation for the identification of predictive attributes, and reliable rule generalizations in noisy single-step data mining problems. This work considers an alternative paradigm for knowledge discovery in M-LCSs, shifting the focus from individual rules to a global, population-wide perspective. We demonstrate the efficacy of this pipeline applied to the identification of epistasis (i.e., attribute interaction) and heterogeneity in noisy simulated genetic association data. PMID:25431544

Odiel River, acid mine drainage and current characterisation by means of univariate analysis.

PubMed

Sainz, A; Grande, J A; de la Torre, M L

2003-04-01

Water pollution caused by sulfide oxidation responds to two geochemical processes: a natural one of temporal patterns, and the 'acid mine drainage', an accelerated process derived from the extractive activity. The Odiel River is located in Southwestern Spain; it flows to the south and into the Atlantic Ocean after joining the Tinto River near its mouth, forming a common estuary. There are three kinds of metallic mining in the Odiel River Basin: manganese, gold and silver, and pyrite mining, the latter being the most important in this basin, which is the object of this study. The main objective of the present study is centred in the characterisation of the sources responsible for the 'acid mine drainage' processes in the Odiel River Basin, through the sampling and subsequent chemical and statistical analyses of water samples collected in three types of sources: mine dumps, active mines and abandoned mines. The main conclusion is that mean pH values in the target area are remarkably lower than those in other active and abandoned mines outside of the study zone. On the contrary, mean values for heavy metal sulfates are much higher. Regarding mine dumps, mean values for pH, sulfates and heavy metals are within a similar range to those data known for areas outside the study zone. Copyright 2003 Elsevier Science Ltd.

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.

Subsurface microbial diversity in deep-granitic-fracture water in Colorado

USGS Publications Warehouse

Sahl, J.W.; Schmidt, R.; Swanner, E.D.; Mandernack, K.W.; Templeton, A.S.; Kieft, Thomas L.; Smith, R.L.; Sanford, W.E.; Callaghan, R.L.; Mitton, J.B.; Spear, J.R.

2008-01-01

A microbial community analysis using 16S rRNA gene sequencing was performed on borehole water and a granite rock core from Henderson Mine, a >1,000-meter-deep molybdenum mine near Empire, CO. Chemical analysis of borehole water at two separate depths (1,044 m and 1,004 m below the mine entrance) suggests that a sharp chemical gradient exists, likely from the mixing of two distinct subsurface fluids, one metal rich and one relatively dilute; this has created unique niches for microorganisms. The microbial community analyzed from filtered, oxic borehole water indicated an abundance of sequences from iron-oxidizing bacteria (Gallionella spp.) and was compared to the community from the same borehole after 2 weeks of being plugged with an expandable packer. Statistical analyses with UniFrac revealed a significant shift in community structure following the addition of the packer. Phospholipid fatty acid (PLFA) analysis suggested that Nitrosomonadales dominated the oxic borehole, while PLFAs indicative of anaerobic bacteria were most abundant in the samples from the plugged borehole. Microbial sequences were represented primarily by Firmicutes, Proteobacteria, and a lineage of sequences which did not group with any identified bacterial division; phylogenetic analyses confirmed the presence of a novel candidate division. This "Henderson candidate division" dominated the clone libraries from the dilute anoxic fluids. Sequences obtained from the granitic rock core (1,740 m below the surface) were represented by the divisions Proteobacteria (primarily the family Ralstoniaceae) and Firmicutes. Sequences grouping within Ralstoniaceae were also found in the clone libraries from metal-rich fluids yet were absent in more dilute fluids. Lineage-specific comparisons, combined with phylogenetic statistical analyses, show that geochemical variance has an important effect on microbial community structure in deep, subsurface systems. Copyright ?? 2008, American Society for Microbiology. All Rights Reserved.

Subsurface Microbial Diversity in Deep-Granitic-Fracture Water in Colorado▿

PubMed Central

Sahl, Jason W.; Schmidt, Raleigh; Swanner, Elizabeth D.; Mandernack, Kevin W.; Templeton, Alexis S.; Kieft, Thomas L.; Smith, Richard L.; Sanford, William E.; Callaghan, Robert L.; Mitton, Jeffry B.; Spear, John R.

2008-01-01

A microbial community analysis using 16S rRNA gene sequencing was performed on borehole water and a granite rock core from Henderson Mine, a >1,000-meter-deep molybdenum mine near Empire, CO. Chemical analysis of borehole water at two separate depths (1,044 m and 1,004 m below the mine entrance) suggests that a sharp chemical gradient exists, likely from the mixing of two distinct subsurface fluids, one metal rich and one relatively dilute; this has created unique niches for microorganisms. The microbial community analyzed from filtered, oxic borehole water indicated an abundance of sequences from iron-oxidizing bacteria (Gallionella spp.) and was compared to the community from the same borehole after 2 weeks of being plugged with an expandable packer. Statistical analyses with UniFrac revealed a significant shift in community structure following the addition of the packer. Phospholipid fatty acid (PLFA) analysis suggested that Nitrosomonadales dominated the oxic borehole, while PLFAs indicative of anaerobic bacteria were most abundant in the samples from the plugged borehole. Microbial sequences were represented primarily by Firmicutes, Proteobacteria, and a lineage of sequences which did not group with any identified bacterial division; phylogenetic analyses confirmed the presence of a novel candidate division. This “Henderson candidate division” dominated the clone libraries from the dilute anoxic fluids. Sequences obtained from the granitic rock core (1,740 m below the surface) were represented by the divisions Proteobacteria (primarily the family Ralstoniaceae) and Firmicutes. Sequences grouping within Ralstoniaceae were also found in the clone libraries from metal-rich fluids yet were absent in more dilute fluids. Lineage-specific comparisons, combined with phylogenetic statistical analyses, show that geochemical variance has an important effect on microbial community structure in deep, subsurface systems. PMID:17981950

PREVENTION OF ACID MINE DRAINAGE GENERATION FROM OPEN-PIT MINE HIGHWALLS

EPA Science Inventory

Exposed, open pit mine highwalls contribute significantly to the production of acid mine

drainage (AMD) thus causing environmental concerns upon closure of an operating mine. Available information on the generation of AMD from open-pit mine highwalls is very limit...

Trees for Ohio

Treesearch

Ernest J. Gebhart

1980-01-01

Other members of this panel are going to reveal the basic statistics about the coal strip mining industry in Ohio so I will confine my remarks to the revegetation of the spoil banks. So it doesn't appear that Ohio confined its tree planting efforts to spoil banks alone, I will rely on a few statistics.

The intriguing evolution of effect sizes in biomedical research over time: smaller but more often statistically significant.

PubMed

Monsarrat, Paul; Vergnes, Jean-Noel

2018-01-01

In medicine, effect sizes (ESs) allow the effects of independent variables (including risk/protective factors or treatment interventions) on dependent variables (e.g., health outcomes) to be quantified. Given that many public health decisions and health care policies are based on ES estimates, it is important to assess how ESs are used in the biomedical literature and to investigate potential trends in their reporting over time. Through a big data approach, the text mining process automatically extracted 814 120 ESs from 13 322 754 PubMed abstracts. Eligible ESs were risk ratio, odds ratio, and hazard ratio, along with their confidence intervals. Here we show a remarkable decrease of ES values in PubMed abstracts between 1990 and 2015 while, concomitantly, results become more often statistically significant. Medians of ES values have decreased over time for both "risk" and "protective" values. This trend was found in nearly all fields of biomedical research, with the most marked downward tendency in genetics. Over the same period, the proportion of statistically significant ESs increased regularly: among the abstracts with at least 1 ES, 74% were statistically significant in 1990-1995, vs 85% in 2010-2015. whereas decreasing ESs could be an intrinsic evolution in biomedical research, the concomitant increase of statistically significant results is more intriguing. Although it is likely that growing sample sizes in biomedical research could explain these results, another explanation may lie in the "publish or perish" context of scientific research, with the probability of a growing orientation toward sensationalism in research reports. Important provisions must be made to improve the credibility of biomedical research and limit waste of resources. © The Authors 2017. Published by Oxford University Press.

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.

Empirical evaluation of interest-level criteria

NASA Astrophysics Data System (ADS)

Sahar, Sigal; Mansour, Yishay

1999-02-01

Efficient association rule mining algorithms already exist, however, as the size of databases increases, the number of patterns mined by the algorithms increases to such an extent that their manual evaluation becomes impractical. Automatic evaluation methods are, therefore, required in order to sift through the initial list of rules, which the datamining algorithm outputs. These evaluation methods, or criteria, rank the association rules mined from the dataset. We empirically examined several such statistical criteria: new criteria, as well as previously known ones. The empirical evaluation was conducted using several databases, including a large real-life dataset, acquired from an order-by-phone grocery store, a dataset composed from www proxy logs, and several datasets from the UCI repository. We were interested in discovering whether the ranking performed by the various criteria is similar or easily distinguishable. Our evaluation detected, when significant differences exist, three patterns of behavior in the eight criteria we examined. There is an obvious dilemma in determining how many association rules to choose (in accordance with support and confidence parameters). The tradeoff is between having stringent parameters and, therefore, few rules, or lenient parameters and, thus, a multitude of rules. In many cases, our empirical evaluation revealed that most of the rules found by the comparably strict parameters ranked highly according to the interestingness criteria, when using lax parameters (producing significantly more association rules). Finally, we discuss the association rules that ranked highest, explain why these results are sound, and how they direct future research.

Mining drives extensive deforestation in the Brazilian Amazon.

PubMed

Sonter, Laura J; Herrera, Diego; Barrett, Damian J; Galford, Gillian L; Moran, Chris J; Soares-Filho, Britaldo S

2017-10-18

Mining poses significant and potentially underestimated risks to tropical forests worldwide. In Brazil's Amazon, mining drives deforestation far beyond operational lease boundaries, yet the full extent of these impacts is unknown and thus neglected in environmental licensing. Here we quantify mining-induced deforestation and investigate the aspects of mining operations, which most likely contribute. We find mining significantly increased Amazon forest loss up to 70 km beyond mining lease boundaries, causing 11,670 km 2 of deforestation between 2005 and 2015. This extent represents 9% of all Amazon forest loss during this time and 12 times more deforestation than occurred within mining leases alone. Pathways leading to such impacts include mining infrastructure establishment, urban expansion to support a growing workforce, and development of mineral commodity supply chains. Mining-induced deforestation is not unique to Brazil; to mitigate adverse impacts of mining and conserve tropical forests globally, environmental assessments and licensing must considered both on- and off-lease sources of deforestation.

Soil organic carbon and nitrogen accumulation on coal mine spoils reclaimed with maritime pine (Pinus pinaster Aiton) in Agacli-Istanbul.

PubMed

Sever, Hakan; Makineci, Ender

2009-08-01

Mining operations on open coal mines in Agacli-Istanbul have resulted in the destruction of vast amounts of land. To rehabilitate these degraded lands, plantations on this area began in 1988. Twelve tree species were planted, however, the most planted tree species was maritime pine (Pinus pinaster Aiton). This study performed on 14 sample plots randomly selected in maritime pine plantations on coal mine soil/spoils in 2005. Soil samples were taken from eight different soil layers (0-1, 1-3, 3-5, 5-10, 10-20, 20-30, 30-40 and 40-50 cm) into the soil profile. On soil samples; fine soil fraction (<2 mm), soil acidity (pH), organic carbon (C(org)) and total nitrogen (N(t)) contents were investigated, and results were compared statistically among soil layers. As a result, 17 years after plantations, total forest floor accumulation determined as 17,973.20 kg ha(-1). Total nitrogen and organic matter amounts of forest floor were 113.90 and 14,640.92 kg ha(-1) respectively. Among soil layers, the highest levels of organic carbon (1.77%) and total nitrogen (0.096%) and the lowest pH value (pH 5.38) were found in 0-1 cm soil layer, and the variation differs significantly among soil layers. Both organic carbon and total nitrogen content decreased, pH values increased from 0-1 to 5-10 cm layer. In conclusion, according to results obtained maritime pine plantations on coal mine spoils; slow accumulation and decomposition of forest floor undergo simultaneously. Depending on these changes organic carbon and total nitrogen contents increased in upper layer of soil/spoil.

Soil Quality of Bauxite Mining Areas

NASA Astrophysics Data System (ADS)

Terezinha Gonçalves Bizuti, Denise; Dinarowski, Marcela; Casagrande, José Carlos; Silva, Luiz Gabriel; Soares, Marcio Roberto; Henrique Santin Brancalion, Pedro

2015-04-01

The study on soil quality index (SQI) aims to assess the current state of the soil after use and estimating its recovery through sustainable management practices This type of study is being used in this work in order to check the efficiency of forest recovery techniques in areas that have been deeply degraded by bauxite mining process, and compare them with the area of native forest, through the determination of SQI. Treatments were newly mined areas, areas undergoing restoration (topsoil use with planting of native forest species), areas in rehabilitation (employment of the green carpet with topsoil and planting of native forest species) and areas of native forests, with six repetitions, in areas of ALCOA, in the municipality of Poços de Caldas/MG. To this end, we used the additive pondered model, establishing three functions: Fertility, water movement and root development, based on chemical parameters (organic matter, base saturation, aluminum saturation and calcium content); physical (macroporosity, soil density and clay content); and microbiological testing (basal respiration by the emission of CO2 ). The SQIs obtained for each treatment was 41%, 56%, 63% and 71% for newly mined areas, native forest, areas in restoration and rehabilitation, respectively. The recovering technique that most approximates the degraded soil to the soil of reference is the restoration, where there was no statistically significant difference of areas restored with native forest. It was found that for the comparison of the studied areas must take into account the nutrient cycling, that disappear with plant removal in mining areas, once the soil of native forest features low fertility and high saturation by aluminum, also taking in account recovering time.

Comparison of MERV 16 and HEPA filters for cab filtration of underground mining equipment.

PubMed

Cecala, A B; Organiscak, J A; Noll, J D; Zimmer, J A

2016-08-01

Significant strides have been made in optimizing the design of filtration and pressurization systems used on the enclosed cabs of mobile mining equipment to reduce respirable dust and provide the best air quality to the equipment operators. Considering all of the advances made in this area, one aspect that still needed to be evaluated was a comparison of the efficiencies of the different filters used in these systems. As high-efficiency particulate arrestance (HEPA) filters provide the highest filtering efficiency, the general assumption would be that they would also provide the greatest level of protection to workers. Researchers for the U.S. National Institute for Occupational Safety and Health (NIOSH) speculated, based upon a previous laboratory study, that filters with minimum efficiency reporting value, or MERV rating, of 16 may be a more appropriate choice than HEPA filters in most cases for the mining industry. A study was therefore performed comparing HEPA and MERV 16 filters on two kinds of underground limestone mining equipment, a roof bolter and a face drill, to evaluate this theory. Testing showed that, at the 95-percent confidence level, there was no statistical difference between the efficiencies of the two types of filters on the two kinds of mining equipment. As the MERV 16 filters were less restrictive, provided greater airflow and cab pressurization, cost less and required less-frequent replacement than the HEPA filters, the MERV 16 filters were concluded to be the optimal choice for both the roof bolter and the face drill in this comparative-analysis case study. Another key finding of this study is the substantial improvement in the effectiveness of filtration and pressurization systems when using a final filter design.

Comparison of MERV 16 and HEPA filters for cab filtration of underground mining equipment

PubMed Central

Cecala, A.B.; Organiscak, J.A.; Noll, J.D.; Zimmer, J.A.

2016-01-01

Significant strides have been made in optimizing the design of filtration and pressurization systems used on the enclosed cabs of mobile mining equipment to reduce respirable dust and provide the best air quality to the equipment operators. Considering all of the advances made in this area, one aspect that still needed to be evaluated was a comparison of the efficiencies of the different filters used in these systems. As high-efficiency particulate arrestance (HEPA) filters provide the highest filtering efficiency, the general assumption would be that they would also provide the greatest level of protection to workers. Researchers for the U.S. National Institute for Occupational Safety and Health (NIOSH) speculated, based upon a previous laboratory study, that filters with minimum efficiency reporting value, or MERV rating, of 16 may be a more appropriate choice than HEPA filters in most cases for the mining industry. A study was therefore performed comparing HEPA and MERV 16 filters on two kinds of underground limestone mining equipment, a roof bolter and a face drill, to evaluate this theory. Testing showed that, at the 95-percent confidence level, there was no statistical difference between the efficiencies of the two types of filters on the two kinds of mining equipment. As the MERV 16 filters were less restrictive, provided greater airflow and cab pressurization, cost less and required less-frequent replacement than the HEPA filters, the MERV 16 filters were concluded to be the optimal choice for both the roof bolter and the face drill in this comparative-analysis case study. Another key finding of this study is the substantial improvement in the effectiveness of filtration and pressurization systems when using a final filter design. PMID:27524838

Exploring the effects of acid mine drainage on diatom teratology using geometric morphometry.

PubMed

Olenici, Adriana; Blanco, Saúl; Borrego-Ramos, María; Momeu, Laura; Baciu, Călin

2017-10-01

Metal pollution of aquatic habitats is a major and persistent environmental problem. Acid mine drainage (AMD) affects lotic systems in numerous and interactive ways. In the present work, a mining area (Roșia Montană) was chosen as study site, and we focused on two aims: (i) to find the set of environmental predictors leading to the appearance of the abnormal diatom individuals in the study area and (ii) to assess the relationship between the degree of valve outline deformation and AMD-derived pollution. In this context, morphological differences between populations of Achnanthidium minutissimum and A. macrocephalum, including normal and abnormal individuals, were evidenced by means of valve shape analysis. Geometric morphometry managed to capture and discriminate normal and abnormal individuals. Multivariate analyses (NMDS, PLS) separated the four populations of the two species mentioned and revealed the main physico-chemical parameters that influenced valve deformation in this context, namely conductivity, Zn, and Cu. ANOSIM test evidenced the presence of statistically significant differences between normal and abnormal individuals within both chosen Achnanthidium taxa. In order to determine the relative contribution of each of the measured physico-chemical parameters in the observed valve outline deformations, a PLS was conducted, confirming the results of the NMDS. The presence of deformed individuals in the study area can be attributed to the fact that the diatom communities were strongly affected by AMD released from old mining works and waste rock deposits.

The exploration and prevention of mine water invasion in Feicheng area based on RS

NASA Astrophysics Data System (ADS)

Zheng, Yong-Guo; Wang, Ping; Ting, He

2004-10-01

Recently, when the ninth and tenth were mined in Feiching city mining area, several mine wells occurred on water invasion. Based on systematic interpretation of TMimages in Fei Cheng mining area, authors find that there are five zones of NS trending lineaments, which nearly distribute in radial in TM images. Image processing can be divided into three types, they are spectrum enhancement, spatial filtering and data fusion, the useful methods in this area are auto-adaptive enhancement, density slicing and K-L transform. With ninth and tenth seam coals mined, three mines of east area have broken out serious accidents of water. Statistical materials and the test of water quality drawing off five limestone indicates water-yielding zone near NS, NNE, and NW trending faults, or near intersection point of its and others. In order to solve the problem, using remote sensing and other techniques, we try to find some influential factors on mine flow. Further analyses, such as, the exploration of geology on earth, and microcosmic from rock slice, the authors find that there are some reasons which lead to water invasion such as geological structure, karsts, index and so on, in which the main reason might be north-south deep fracture which is the pathway of well water's distribution, migration and recharge of mine water. There being more complicate geologic structure in the west of mine area, at last, with RS authors point out important zone of mine water invasion which the prevention-control of hazards from mine water and some measures to avoid water blast in future.

Biomonitoring of lead, zinc, and cadmium in streams draining lead-mining and non-mining areas, Southeast Missouri, USA

USGS Publications Warehouse

Besser, John M.; Brumbaugh, William G.; May, Thomas W.; Schmitt, Christopher J.

2007-01-01

We evaluated exposure of aquatic biota to lead (Pb), zinc (Zn), and cadmium (Cd) in streams draining a Pb-mining district in southeast Missouri. Samples of plant biomass (detritus, periphyton, and filamentous algae), invertebrates (snails, crayfish, and riffle benthos), and two taxa of fish were collected from seven sites closest to mining areas (mining sites), four sites further downstream from mining (downstream sites), and eight reference sites in fall 2001. Samples of plant biomass from mining sites had highest metal concentrations, with means 10- to 60-times greater than those for reference sites. Mean metal concentrations in over 90% of samples of plant biomass from mining sites were significantly greater than those from reference sites. Mean concentrations of Pb, Zn, and Cd in most invertebrate samples from mining sites, and mean Pb concentrations in most fish samples from mining sites, were also significantly greater than those from reference sites. Concentrations of all three metals were lower in samples from downstream sites, but several samples of plant biomass from downstream sites had metal concentrations significantly greater than those from reference sites. Analysis of supplemental samples collected in the fall of 2002, a year of above-average stream discharge, had lower Pb concentrations and higher Cd concentrations than samples collected in 2001, near the end of a multi-year drought. Concentrations of Pb measured in fish and invertebrates collected from mining sites during 2001 and 2002 were similar to those measured at nearby sites in the 1970s, during the early years of mining in the Viburnum Trend. Results of this study demonstrate that long-term Pb mining activity in southeast Missouri has resulted in significantly elevated concentrations of Pb, Cd, and Zn in biota of receiving streams, compared to biota of similar streams without direct influence of mining. Our results also demonstrate that metal exposure in the study area differed significantly among sample types, habitats, and years, and that these factors should be carefully considered in the design of biomonitoring studies.

Biomonitoring of lead, zinc, and cadmium in streams draining lead-mining and non-mining areas, Southeast Missouri, USA

USGS Publications Warehouse

Besser, J.M.; Brumbaugh, W.G.; May, T.W.; Schmitt, C.J.

2007-01-01

We evaluated exposure of aquatic biota to lead (Pb), zinc (Zn), and cadmium (Cd) in streams draining a Pb-mining district in southeast Missouri. Samples of plant biomass (detritus, periphyton, and filamentous algae), invertebrates (snails, crayfish, and riffle benthos), and two taxa of fish were collected from seven sites closest to mining areas (mining sites), four sites further downstream from mining (downstream sites), and eight reference sites in fall 2001. Samples of plant biomass from mining sites had highest metal concentrations, with means 10- to 60-times greater than those for reference sites. Mean metal concentrations in over 90% of samples of plant biomass from mining sites were significantly greater than those from reference sites. Mean concentrations of Pb, Zn, and Cd in most invertebrate samples from mining sites, and mean Pb concentrations in most fish samples from mining sites, were also significantly greater than those from reference sites. Concentrations of all three metals were lower in samples from downstream sites, but several samples of plant biomass from downstream sites had metal concentrations significantly greater than those from reference sites. Analysis of supplemental samples collected in the fall of 2002, a year of above-average stream discharge, had lower Pb concentrations and higher Cd concentrations than samples collected in 2001, near the end of a multi-year drought. Concentrations of Pb measured in fish and invertebrates collected from mining sites during 2001 and 2002 were similar to those measured at nearby sites in the 1970s, during the early years of mining in the Viburnum Trend. Results of this study demonstrate that long-term Pb mining activity in southeast Missouri has resulted in significantly elevated concentrations of Pb, Cd, and Zn in biota of receiving streams, compared to biota of similar streams without direct influence of mining. Our results also demonstrate that metal exposure in the study area differed significantly among sample types, habitats, and years, and that these factors should be carefully considered in the design of biomonitoring studies. ?? Springer Science+Business Media B.V. 2006.

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.

Rockburst of parameters causing mining disasters in Mines of Upper Silesian Coal Basin

NASA Astrophysics Data System (ADS)

Patyńska, Renata; Mirek, Adam; Burtan, Zbigniew; Pilecka, Elżbieta

2018-04-01

In the years 2001-2015, 42 rockbursts were recorded in Polish coal mines. For the past 15 years the scale of the phenomena has been similar and ranges from 1 to 5 rockbursts per year. However, the number of recorded high energy seismic tremors of 108 and 109J (E) energy that has occurred in recent years, 2 to 5, is alarming. According to the data, 27 of tremors of E > 108 J energy that occurred between 2001 and 2015 caused 3 rockbursts. Confronting these data with seismic activity from 1989-2000, it should be noted that only 2 events out of 99 rockbursts caused tremors with energies of E>108 J. Against the background of the scale of seismic and rockburst hazards, the geological and mining conditions of the Upper Silesian Coal Basin (USCB) have been analysed, detailing the structural units in which the rockbursts occurred. On this basis, the author characterised factors that impacts on the mining excavations resulting in rockbursts that caused damage on a larger scale. These rockbursts had the characteristics of mining catastrophes and weak earthquakes not recorded in mining statistics of natural hazards of USCB so far.

Assessment of respirable dust exposures in an opencast coal mine.

PubMed

Onder, M; Yigit, E

2009-05-01

All major opencast mining activities produce dust. The major operations that produce dust are drilling, blasting, loading, unloading, and transporting. Dust not only deteriorates the environmental air quality in and around the mining site but also creates serious health hazards. Therefore, assessment of dust levels that arise from various opencast mining operations is required to prevent and minimize the health risks. To achieve this objective, an opencast coal mining area was selected to generate site-specific emission data and collect respirable dust measurement samples. The study covered various mining activities in different locations including overburden loading, stock yard, coal loading, drilling, and coal handling plant. The dust levels were examined to assess miners' exposure to respirable dust in each of the opencast mining areas from 1994 to 2005. The data obtained from the dust measurement studies were evaluated by using analysis of variance (ANOVA) and the Tukey-Kramer procedure. The analyses were performed by using Minitab 14 statistical software. It was concluded that, drilling operations produce higher dust concentration levels and thus, drill operators may have higher incidence of respiratory disorders related to exposure to dust in their work environment.

Using redescription mining to relate clinical and biological characteristics of cognitively impaired and Alzheimer's disease patients.

PubMed

Mihelčić, Matej; Šimić, Goran; Babić Leko, Mirjana; Lavrač, Nada; Džeroski, Sašo; Šmuc, Tomislav

2017-01-01

Based on a set of subjects and a collection of attributes obtained from the Alzheimer's Disease Neuroimaging Initiative database, we used redescription mining to find interpretable rules revealing associations between those determinants that provide insights about the Alzheimer's disease (AD). We extended the CLUS-RM redescription mining algorithm to a constraint-based redescription mining (CBRM) setting, which enables several modes of targeted exploration of specific, user-constrained associations. Redescription mining enabled finding specific constructs of clinical and biological attributes that describe many groups of subjects of different size, homogeneity and levels of cognitive impairment. We confirmed some previously known findings. However, in some instances, as with the attributes: testosterone, ciliary neurotrophic factor, brain natriuretic peptide, Fas ligand, the imaging attribute Spatial Pattern of Abnormalities for Recognition of Early AD, as well as the levels of leptin and angiopoietin-2 in plasma, we corroborated previously debatable findings or provided additional information about these variables and their association with AD pathogenesis. Moreover, applying redescription mining on ADNI data resulted with the discovery of one largely unknown attribute: the Pregnancy-Associated Protein-A (PAPP-A), which we found highly associated with cognitive impairment in AD. Statistically significant correlations (p ≤ 0.01) were found between PAPP-A and clinical tests: Alzheimer's Disease Assessment Scale, Clinical Dementia Rating Sum of Boxes, Mini Mental State Examination, etc. The high importance of this finding lies in the fact that PAPP-A is a metalloproteinase, known to cleave insulin-like growth factor binding proteins. Since it also shares similar substrates with A Disintegrin and the Metalloproteinase family of enzymes that act as α-secretase to physiologically cleave amyloid precursor protein (APP) in the non-amyloidogenic pathway, it could be directly involved in the metabolism of APP very early during the disease course. Therefore, further studies should investigate the role of PAPP-A in the development of AD more thoroughly.

Using redescription mining to relate clinical and biological characteristics of cognitively impaired and Alzheimer’s disease patients

PubMed Central

Mihelčić, Matej; Šimić, Goran; Babić Leko, Mirjana; Lavrač, Nada; Džeroski, Sašo; Šmuc, Tomislav

2017-01-01

Based on a set of subjects and a collection of attributes obtained from the Alzheimer’s Disease Neuroimaging Initiative database, we used redescription mining to find interpretable rules revealing associations between those determinants that provide insights about the Alzheimer’s disease (AD). We extended the CLUS-RM redescription mining algorithm to a constraint-based redescription mining (CBRM) setting, which enables several modes of targeted exploration of specific, user-constrained associations. Redescription mining enabled finding specific constructs of clinical and biological attributes that describe many groups of subjects of different size, homogeneity and levels of cognitive impairment. We confirmed some previously known findings. However, in some instances, as with the attributes: testosterone, ciliary neurotrophic factor, brain natriuretic peptide, Fas ligand, the imaging attribute Spatial Pattern of Abnormalities for Recognition of Early AD, as well as the levels of leptin and angiopoietin-2 in plasma, we corroborated previously debatable findings or provided additional information about these variables and their association with AD pathogenesis. Moreover, applying redescription mining on ADNI data resulted with the discovery of one largely unknown attribute: the Pregnancy-Associated Protein-A (PAPP-A), which we found highly associated with cognitive impairment in AD. Statistically significant correlations (p ≤ 0.01) were found between PAPP-A and clinical tests: Alzheimer’s Disease Assessment Scale, Clinical Dementia Rating Sum of Boxes, Mini Mental State Examination, etc. The high importance of this finding lies in the fact that PAPP-A is a metalloproteinase, known to cleave insulin-like growth factor binding proteins. Since it also shares similar substrates with A Disintegrin and the Metalloproteinase family of enzymes that act as α-secretase to physiologically cleave amyloid precursor protein (APP) in the non-amyloidogenic pathway, it could be directly involved in the metabolism of APP very early during the disease course. Therefore, further studies should investigate the role of PAPP-A in the development of AD more thoroughly. PMID:29088293

Respiratory symptoms and lung function in bauxite miners.

PubMed

Beach, J R; de Klerk, N H; Fritschi, L; Sim, M R; Musk, A W; Benke, G; Abramson, M J; McNeil, J J

2001-09-01

To determine whether cumulative bauxite exposure is associated with respiratory symptoms or changes in lung function in a group of bauxite miners. Current employees at three bauxite mines in Australia were invited to participate in a survey comprising: questionnaire on demographic details, respiratory symptoms, and work history; skin prick tests for four common aeroallergens; and spirometry. A task exposure matrix was constructed for bauxite exposure in all tasks in all jobs based on monitoring data. Data were examined for associations between cumulative bauxite exposure, and respiratory symptoms and lung function, by regression analyses. The participation rate was 86%. Self-reported work-related respiratory symptoms were reported by relatively few subjects (1.5%-11.8%). After adjustment for age and smoking no significant differences in the prevalence of respiratory symptoms were identified between subjects, in the quartiles of cumulative bauxite exposure distribution. The forced expiratory volume in I s (FEV1) of the exposed group was found to be significantly lower than that for the unexposed group. After adjustment for age, height, and smoking there were no statistically significant differences between quartiles in FEVI, forced vital capacity (FVC) and FEVl/FVC ratio. These data provide little evidence of a serious adverse effect on respiratory health associated with exposure to bauxite in an open-cut bauxite mine in present day conditions.

Biochemical effects of lead, zinc, and cadmium from mining on fish in the Tri-States district of northeastern Oklahoma, USA

USGS Publications Warehouse

Schmitt, Christopher J.; Whyte, Jeffrey J.; Brumbaugh, William G.; Tillitt, Donald E.

2005-01-01

We assessed the exposure of fish from the Spring and Neosho Rivers in northeast Oklahoma, USA, to lead, zinc, and cadmium from historical mining in the Tri-States Mining District (TSMD). Fish (n = 74) representing six species were collected in October 2001 from six sites on the Spring and Neosho Rivers influenced to differing degrees by mining. Additional samples were obtained from the Big River, a heavily contaminated stream in eastern Missouri, USA, and from reference sites. Blood from each fish was analyzed for Pb, Zn, Cd, Fe, and hemoglobin (Hb). Blood also was analyzed for ??-aminolevulinic acid dehydratase (ALA-D) activity. The activity of ALA-D, an enzyme involved in heme synthesis, is inhibited by Pb. Concentrations of Fe and Hb were highly correlated (r = 0.89, p < 0.01) across all species and locations and typically were greater in common carp (Cyprinus carpio) than in other taxa. Concentrations of Pb, Zn, and Cd typically were greatest in fish from sites most heavily affected by mining and lowest in reference samples. The activity of ALA-D, but not concentrations of Hb or Fe, also differed significantly (p < 0.01) among sites and species. Enzyme activity was lowest in fish from mining-contaminated sites and greatest in reference fish, and was correlated negatively with Pb in most species. Statistically significant (p < 0.01) linear regression models that included negative terms for blood Pb explained as much as 68% of the total variation in ALA-D activity, but differences among taxa were highly evident. Positive correlations with Zn were documented in the combined data for channel catfish (Ictalurus punctatus) and flathead catfish (Pylodictis olivaris), as has been reported for other taxa, but not in bass (Micropterus spp.) or carp. In channel catfish, ALA-D activity appeared to be more sensitive to blood Pb than in the other species investigated (i.e., threshold concentrations for inhibition were lower). Such among-species differences are consistent with previous studies. Enzyme activity was inhibited by more than 50% relative to reference sites in channel catfish from several TSMD sites. Collectively, our results indicate that Pb is both bioavailable and active biochemically in the Spring-Neosho River system. ?? 2005 SETAC.

RIBE at an inter-organismic level: A study on genotoxic effects in Daphnia magna exposed to waterborne uranium and a uranium mine effluent.

PubMed

Reis, P; Lourenço, J; Carvalho, F P; Oliveira, J; Malta, M; Mendo, S; Pereira, R

2018-05-01

The induction of RIBE (Radiation Induced Bystander Effect) is a non-target effect of low radiation doses that has already been verified at an inter-organismic level in fish and small mammals. Although the theoretical impact in the field of environmental risk assessment (ERA) is possible, there is a gap of knowledge regarding this phenomenon in invertebrate groups and following environmentally relevant exposures. To understand if RIBE should be considered for ERA of radionuclide-rich wastewaters, we exposed Daphnia magna (<24 h and 5d old) to a 2% diluted uranium mine effluent for 48 h, and to a matching dose of waterborne uranium (55.3 μg L -1 ). Then the exposed organisms were placed (24 and 48 h) in a clean medium together with non-exposed neonates. The DNA damage observed for the non-exposed organisms was statistically significant after the 24 h cohabitation for both uranium (neonates p = 0.002; 5 d-old daphnids p = <0.001) and uranium mine effluent exposure (only for neonates p = 0.042). After 48 h cohabitation significant results were obtained only for uranium exposure (neonates p = 0.017; 5 d-old daphnids p = 0.013). Although there may be some variability associated to age and exposure duration, the significant DNA damage detected in non-exposed organisms clearly reveals the occurrence of RIBE in D. magna. The data obtained and here presented are a valuable contribution for the discussion about the relevance of RIBE for environmental risk assessment. Copyright © 2018 Elsevier B.V. All rights reserved.

Establishing a pre-mining geochemical baseline at a uranium mine near Grand Canyon National Park, USA

USGS Publications Warehouse

Naftz, David L.; Walton-Day, Katherine

2016-01-01

During 2012, approximately 404,000 ha of Federal Land in northern Arizona was withdrawn from consideration of mineral extraction for a 20-year period to protect the Grand Canyon watershed from potentially adverse effects of U mineral exploration and development. The development, operation, and reclamation of the Canyon Mine during the withdrawal period provide an excellent field site to understand and document off-site migration of radionuclides within the withdrawal area. As part of the Department of Interior's (DOI's) study plan for the exclusion area, the objective of our study is to utilize pre-defined decision units (DUs) in areas within and surrounding the Canyon Mine to demonstrate how newly established incremental sampling methodologies (ISM) combined with multivariate statistical methods can be used to document a repeatable and statistically defensible measure of pre-mining baseline conditions in surface soils and stream sediment samples prior to ore extraction. During the survey in June 2013, the highest pre-mining 95% upper confidence level (UCL) concentrations with respect to As, Mo, U, and V were found in the triplicate samples collected from surface soils in the mine site DU designated as M1. Gamma activities were slightly elevated in soils within the M1 DU (up to 28 μR/h); however, off-site gamma activities in soil and stream-sediment samples were lower (< 6 to 12 μR/h). Hierarchical cluster analysis (HCA) was applied to 33 chemical constituents contained in the multivariate data generated from the analysis of triplicate samples collected in the soil and stream sediment DUs within and surrounding Canyon Mine. Most of the triplicate samples from individual DUs were grouped in the same dendrogram cluster when using a similarity value (SV) of 0.70 (unitless). Different group membership of triplicate samples from two of the four haul road DUs was likely the result of heterogeneity induced by non-native soil material introduced from the gravel road base or from vehicular traffic. Application of HCA and ISM will provide critical metrics to meet DOI's long-term goals for assessing off-site migration of radionuclides resulting from mining and reclamation in the current (2015) exclusion area associated within the Grand Canyon watershed and the associated national park.

Identifying Catchment-Scale Predictors of Coal Mining Impacts on New Zealand Stream Communities.

PubMed

Clapcott, Joanne E; Goodwin, Eric O; Harding, Jon S

2016-03-01

Coal mining activities can have severe and long-term impacts on freshwater ecosystems. At the individual stream scale, these impacts have been well studied; however, few attempts have been made to determine the predictors of mine impacts at a regional scale. We investigated whether catchment-scale measures of mining impacts could be used to predict biological responses. We collated data from multiple studies and analyzed algae, benthic invertebrate, and fish community data from 186 stream sites, including un-mined streams, and those associated with 620 mines on the West Coast of the South Island, New Zealand. Algal, invertebrate, and fish richness responded to mine impacts and were significantly higher in un-mined compared to mine-impacted streams. Changes in community composition toward more acid- and metal-tolerant species were evident for algae and invertebrates, whereas changes in fish communities were significant and driven by a loss of nonmigratory native species. Consistent catchment-scale predictors of mining activities affecting biota included the time post mining (years), mining density (the number of mines upstream per catchment area), and mining intensity (tons of coal production per catchment area). Mining was associated with a decline in stream biodiversity irrespective of catchment size, and recovery was not evident until at least 30 years after mining activities have ceased. These catchment-scale predictors can provide managers and regulators with practical metrics to focus on management and remediation decisions.

Identifying Catchment-Scale Predictors of Coal Mining Impacts on New Zealand Stream Communities

NASA Astrophysics Data System (ADS)

Clapcott, Joanne E.; Goodwin, Eric O.; Harding, Jon S.

2016-03-01

Coal mining activities can have severe and long-term impacts on freshwater ecosystems. At the individual stream scale, these impacts have been well studied; however, few attempts have been made to determine the predictors of mine impacts at a regional scale. We investigated whether catchment-scale measures of mining impacts could be used to predict biological responses. We collated data from multiple studies and analyzed algae, benthic invertebrate, and fish community data from 186 stream sites, including un-mined streams, and those associated with 620 mines on the West Coast of the South Island, New Zealand. Algal, invertebrate, and fish richness responded to mine impacts and were significantly higher in un-mined compared to mine-impacted streams. Changes in community composition toward more acid- and metal-tolerant species were evident for algae and invertebrates, whereas changes in fish communities were significant and driven by a loss of nonmigratory native species. Consistent catchment-scale predictors of mining activities affecting biota included the time post mining (years), mining density (the number of mines upstream per catchment area), and mining intensity (tons of coal production per catchment area). Mining was associated with a decline in stream biodiversity irrespective of catchment size, and recovery was not evident until at least 30 years after mining activities have ceased. These catchment-scale predictors can provide managers and regulators with practical metrics to focus on management and remediation decisions.

Data Mining Methods Applied to Flight Operations Quality Assurance Data: A Comparison to Standard Statistical Methods

NASA Technical Reports Server (NTRS)

Stolzer, Alan J.; Halford, Carl

2007-01-01

In a previous study, multiple regression techniques were applied to Flight Operations Quality Assurance-derived data to develop parsimonious model(s) for fuel consumption on the Boeing 757 airplane. The present study examined several data mining algorithms, including neural networks, on the fuel consumption problem and compared them to the multiple regression results obtained earlier. Using regression methods, parsimonious models were obtained that explained approximately 85% of the variation in fuel flow. In general data mining methods were more effective in predicting fuel consumption. Classification and Regression Tree methods reported correlation coefficients of .91 to .92, and General Linear Models and Multilayer Perceptron neural networks reported correlation coefficients of about .99. These data mining models show great promise for use in further examining large FOQA databases for operational and safety improvements.

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.

Urinary metabolic profiling of asymptomatic acute intermittent porphyria using a rule-mining-based algorithm.

PubMed

Luck, Margaux; Schmitt, Caroline; Talbi, Neila; Gouya, Laurent; Caradeuc, Cédric; Puy, Hervé; Bertho, Gildas; Pallet, Nicolas

2018-01-01

Metabolomic profiling combines Nuclear Magnetic Resonance spectroscopy with supervised statistical analysis that might allow to better understanding the mechanisms of a disease. In this study, the urinary metabolic profiling of individuals with porphyrias was performed to predict different types of disease, and to propose new pathophysiological hypotheses. Urine 1 H-NMR spectra of 73 patients with asymptomatic acute intermittent porphyria (aAIP) and familial or sporadic porphyria cutanea tarda (f/sPCT) were compared using a supervised rule-mining algorithm. NMR spectrum buckets bins, corresponding to rules, were extracted and a logistic regression was trained. Our rule-mining algorithm generated results were consistent with those obtained using partial least square discriminant analysis (PLS-DA) and the predictive performance of the model was significant. Buckets that were identified by the algorithm corresponded to metabolites involved in glycolysis and energy-conversion pathways, notably acetate, citrate, and pyruvate, which were found in higher concentrations in the urines of aAIP compared with PCT patients. Metabolic profiling did not discriminate sPCT from fPCT patients. These results suggest that metabolic reprogramming occurs in aAIP individuals, even in the absence of overt symptoms, and supports the relationship that occur between heme synthesis and mitochondrial energetic metabolism.

U-Compare: share and compare text mining tools with UIMA

PubMed Central

Kano, Yoshinobu; Baumgartner, William A.; McCrohon, Luke; Ananiadou, Sophia; Cohen, K. Bretonnel; Hunter, Lawrence; Tsujii, Jun'ichi

2009-01-01

Summary: Due to the increasing number of text mining resources (tools and corpora) available to biologists, interoperability issues between these resources are becoming significant obstacles to using them effectively. UIMA, the Unstructured Information Management Architecture, is an open framework designed to aid in the construction of more interoperable tools. U-Compare is built on top of the UIMA framework, and provides both a concrete framework for out-of-the-box text mining and a sophisticated evaluation platform allowing users to run specific tools on any target text, generating both detailed statistics and instance-based visualizations of outputs. U-Compare is a joint project, providing the world's largest, and still growing, collection of UIMA-compatible resources. These resources, originally developed by different groups for a variety of domains, include many famous tools and corpora. U-Compare can be launched straight from the web, without needing to be manually installed. All U-Compare components are provided ready-to-use and can be combined easily via a drag-and-drop interface without any programming. External UIMA components can also simply be mixed with U-Compare components, without distinguishing between locally and remotely deployed resources. Availability: http://u-compare.org/ Contact: kano@is.s.u-tokyo.ac.jp PMID:19414535

An extended data mining method for identifying differentially expressed assay-specific signatures in functional genomic studies.

PubMed

Rollins, Derrick K; Teh, Ailing

2010-12-17

Microarray data sets provide relative expression levels for thousands of genes for a small number, in comparison, of different experimental conditions called assays. Data mining techniques are used to extract specific information of genes as they relate to the assays. The multivariate statistical technique of principal component analysis (PCA) has proven useful in providing effective data mining methods. This article extends the PCA approach of Rollins et al. to the development of ranking genes of microarray data sets that express most differently between two biologically different grouping of assays. This method is evaluated on real and simulated data and compared to a current approach on the basis of false discovery rate (FDR) and statistical power (SP) which is the ability to correctly identify important genes. This work developed and evaluated two new test statistics based on PCA and compared them to a popular method that is not PCA based. Both test statistics were found to be effective as evaluated in three case studies: (i) exposing E. coli cells to two different ethanol levels; (ii) application of myostatin to two groups of mice; and (iii) a simulated data study derived from the properties of (ii). The proposed method (PM) effectively identified critical genes in these studies based on comparison with the current method (CM). The simulation study supports higher identification accuracy for PM over CM for both proposed test statistics when the gene variance is constant and for one of the test statistics when the gene variance is non-constant. PM compares quite favorably to CM in terms of lower FDR and much higher SP. Thus, PM can be quite effective in producing accurate signatures from large microarray data sets for differential expression between assays groups identified in a preliminary step of the PCA procedure and is, therefore, recommended for use in these applications.

Physiological strain in the Hungarian mining industry: The impact of physical and psychological factors.

PubMed

Varga, József; Nagy, Imre; Szirtes, László; Pórszász, János

2016-01-01

The objectives of these investigations completed on workplaces in the Hungarian mining industry were to characterize the physiological strain of workers by means of work pulse and to examine the effects of work-related psychological factors. Continuous heart rate (HR) recording was completed on 71 miners over a total of 794 shifts between 1987 and 1992 in mining plants of the Hungarian mining industry using a 6-channel recorder - Bioport (ZAK, Germany). The work processes were simultaneously documented by video recording along with drawing up the traditional ergonomic workday schedule. All workers passed health evaluation for fitness for work. The effects of different psychological factors (simulated danger, "instrument stress," presence of managers, and effect of prior involvement in accidents as well as different mining technologies and work place illumination) on the work pulse were evaluated. The statistical analysis was completed using SPSS software (version 13.0, SPSS Inc., USA). The work-related physiological strain differed between work places with different mining technologies in groups of 12-18 workers. The work pulse was lowest in bauxite mining (ΔHR = 22±8.9 bpm) and highest in drift drilling in dead rock with electric drilling machine (ΔHR = 30±6.9 bpm). During sham alarm situation the work pulse was significantly higher than during normal activities with the same physical task (ΔHR = 36.7±4.8 bpm vs. 25.8±1.6 bpm, p < 0.001). When work was performed under different psychological stress, the work pulse was consistently higher, while improving the work place illumination decreased the physiological strain appreciably (ΔHR (median, 25-75 percentiles) = 23, 20-26 bmp vs. 28, 25-31.3 bpm, p < 0.001). Recording the heart rate during whole-shift work along with the work conditions gives reliable results and helps isolating factors that contribute to increased strain. The results can be used to implement preventive and health promotion measures. This work is available in Open Access model and licensed under a CC BY-NC 3.0 PL license.

Multisensor fusion for the detection of mines and minelike targets

NASA Astrophysics Data System (ADS)

Hanshaw, Terilee

1995-06-01

The US Army's Communications and Electronics Command through the auspices of its Night Vision and Electronics Sensors Directorate (CECOM-NVESD) is actively applying multisensor techniques to the detection of mine targets. This multisensor research results from the 'detection activity' with its broad range of operational conditions and targets. Multisensor operation justifies significant attention by yielding high target detection and low false alarm statistics. Furthermore, recent advances in sensor and computing technologies make its practical application realistic and affordable. The mine detection field-of-endeavor has since its WWI baptismal investigated the known spectra for applicable mine observation phenomena. Countless sensors, algorithms, processors, networks, and other techniques have been investigated to determine candidacy for mine detection. CECOM-NVESD efforts have addressed a wide range of sensors spanning the spectrum from gravity field perturbations, magentic field disturbances, seismic sounding, electromagnetic fields, earth penetrating radar imagery, and infrared/visible/ultraviolet surface imaging technologies. Supplementary analysis has considered sensor candidate applicability by testing under field conditions (versus laboratory), in determination of fieldability. As these field conditions directly effect the probability of detection and false alarms, sensor employment and design must be considered. Consequently, as a given sensor's performance is influenced directly by the operational conditions, tradeoffs are necessary. At present, mass produced and fielded mine detection techniques are limited to those incorporating a single sensor/processor methodology such as, pulse induction and megnetometry, as found in hand held detectors. The most sensitive fielded systems can detect minute metal components in small mine targets but result in very high false alarm rates reducing velocity in operation environments. Furthermore, the actual speed of advance for the entire mission (convoy, movement to engagement, etc.) is determined by the level of difficulty presented in clearance or avoidance activities required in response to the potential 'targets' marked throughout a detection activity. Therefore the application of fielded hand held systems to convoy operations in clearly impractical. CECOM-NVESD efforts are presently seeking to overcome these operational limitations by substantially increasing speed of detection while reducing the false alarm rate through the application of multisensor techniques. The CECOM-NVESD application of multisensor techniques through integration/fusion methods will be defined in this paper.

Detecting Plastic PFM-1 Butterfly Mines Using Thermal Infrared Sensing

NASA Astrophysics Data System (ADS)

Baur, J.; de Smet, T.; Nikulin, A.

2017-12-01

Remnant plastic-composite landmines, such as the mass-produced PFM-1, represent an ongoing humanitarian threat aggravated by high costs associated with traditional demining efforts. These particular unexploded ordnance (UXO) devices pose a challenge to conventional geophysical detection methods, due their plastic-body design and small size. Additionally, the PFM-1s represent a particularly heinous UXO, due to their low mass ( 25 lb) trigger limit and "butterfly" wing design, earning them the reputation of a "toy mine" - disproportionally impacting children across post-conflict areas. We developed a detection algorithm based on data acquired by a thermal infrared camera mounted to a commercial UAV to detect time-variable temperature difference between the PFM-1 and the surrounding environment. We present results of a field study focused on thermal detection and identification of the PFM-1 anti-personnel landmines from a remotely operated unmanned aerial vehicle (UAV). We conducted a series of field detection experiments meant to simulate the mountainous terrains where PFM-1 mines were historically deployed and remain in place. In our tests, 18 inert PFM-1 mines along with the aluminum KSF-1 casing were randomly dispersed to mimic an ellipsoidal minefield of 8-10 x 18-20 m dimensions in a de-vegetated rubble yard at Chenango Valley State Park (New York State). We collected multiple thermal infrared imagery datasets focused on these model minefields with the FLIR Vue Pro R attached to the 3DR Solo UAV flying at approximately at 2 m. We identified different environmental variables to constrain the optimal time of day and daily temperature variations to reveal presence of these plastic UXOs. We show that in the early-morning hours when thermal inertia is greatest, the PFM-1 mines can be detected based on their differential thermal inertia. Because the mines have statistically different temperatures than background and a characteristic shape, we were able to train a supervised learning algorithm to automate detection of the mines over large areas. We anticipate that following further development, this remote sensing method can aid in significantly reducing the cost and time associated with landmine remediation in post-conflict nations.

Study of Staphylococcus aureus N315 Pathogenic Genes by Text Mining and Enrichment Analysis of Pathways and Operons.

PubMed

Yang, Chun-Feng; Gou, Wei-Hui; Dai, Xin-Lun; Li, Yu-Mei

2018-06-01

Staphylococcus aureus (S. aureus) is a versatile pathogen found in many environments and can cause nosocomial infections in the community and hospitals. S. aureus infection is an increasingly serious threat to global public health that requires action across many government bodies, medical and health sectors, and scientific research institutions. In the present study, S. aureus N315 genes that have been shown in the literature to be pathogenic were extracted using a bibliometric method for functional enrichment analysis of pathways and operons to statistically discover novel pathogenic genes associated with S. aureus N315. A total of 383 pathogenic genes were mined from the literature using bibliometrics, and subsequently a few new pathogenic genes of S. aureus N315 were identified by functional enrichment analysis of pathways and operons. The discovery of these novel S. aureus N315 pathogenic genes is of great significance to treat S. aureus induced diseases and identify potential diagnostic markers, thus providing theoretical fundamentals for epidemiological prevention.

Mining Electronic Health Records Data: Domestic Violence and Adverse Health Effects

PubMed Central

Karakurt, Gunnur; Patel, Vishal; Whiting, Kathleen; Koyutürk, Mehmet

2016-01-01

Intimate partner violence (IPV) often culminates in acute physical injury, sexual assault, and mental health issues. It is crucial to understand the healthcare habits of victims to develop interventions that can drastically improve a victim's quality of life and prevent future abuse. The objective of this study is to mine de-identified and aggregated Electronic Health Record data to identify women's health issues that are potentially associated with IPV. In this study we compared health issues of female domestic abuse victims to female non-domestic abuse victims. The Domestic abuse population contained 5870 patients, while the Non-Domestic Abuse population contained 14,315,140 patients. Explorys provides National Big Data from the entire USA. Statistical analysis identified 2429 terms as significantly more prevalent among victims of domestic abuse, compared to the general population. These terms were classified into broad categories, including acute injury, chronic conditions, substance abuse, mental health, disorders, gynecological and pregnancy related problems. PMID:28435184

Multiple comparisons permutation test for image based data mining in radiotherapy

PubMed Central

2013-01-01

Comparing incidental dose distributions (i.e. images) of patients with different outcomes is a straightforward way to explore dose-response hypotheses in radiotherapy. In this paper, we introduced a permutation test that compares images, such as dose distributions from radiotherapy, while tackling the multiple comparisons problem. A test statistic Tmax was proposed that summarizes the differences between the images into a single value and a permutation procedure was employed to compute the adjusted p-value. We demonstrated the method in two retrospective studies: a prostate study that relates 3D dose distributions to failure, and an esophagus study that relates 2D surface dose distributions of the esophagus to acute esophagus toxicity. As a result, we were able to identify suspicious regions that are significantly associated with failure (prostate study) or toxicity (esophagus study). Permutation testing allows direct comparison of images from different patient categories and is a useful tool for data mining in radiotherapy. PMID:24365155

Mortality of workers in two Minnesota taconite mining and milling operations.

PubMed

Cooper, W C; Wong, O; Graebner, R

1988-06-01

Mortality during the years 1947 to 1983 was studied in 3,444 men employed for at least 3 months in Minnesota taconite mining operations during the years 1947 to 1958. During 86,307 person-years of observation, there were 801 deaths for a standardized mortality ratio (SMR) of 88 (US white male rates) or 98 (Minnesota rates). The 41 deaths from respiratory cancer were fewer than expected, the SMR being 61 (P less than or equal to .01) (US rates) and 85 (Minnesota rates). There were 25 respiratory cancers 20 or more years after first taconite employment, for an SMR of 57 (P less than or equal to .01) (US rates). SMRs for colon cancer, kidney cancer, and lymphopoietic cancer were elevated, but below the level of statistical significance. There was one death from pleural mesothelioma, 11 years after first taconite employment, in a man with long prior employment as a locomotive operator. The pattern of deaths did not suggest asbestos-related disease in taconite miners and millers.

An incremental knowledge assimilation system (IKAS) for mine detection

NASA Astrophysics Data System (ADS)

Porway, Jake; Raju, Chaitanya; Varadarajan, Karthik Mahesh; Nguyen, Hieu; Yadegar, Joseph

2010-04-01

In this paper we present an adaptive incremental learning system for underwater mine detection and classification that utilizes statistical models of seabed texture and an adaptive nearest-neighbor classifier to identify varied underwater targets in many different environments. The first stage of processing uses our Background Adaptive ANomaly detector (BAAN), which identifies statistically likely target regions using Gabor filter responses over the image. Using this information, BAAN classifies the background type and updates its detection using background-specific parameters. To perform classification, a Fully Adaptive Nearest Neighbor (FAAN) determines the best label for each detection. FAAN uses an extremely fast version of Nearest Neighbor to find the most likely label for the target. The classifier perpetually assimilates new and relevant information into its existing knowledge database in an incremental fashion, allowing improved classification accuracy and capturing concept drift in the target classes. Experiments show that the system achieves >90% classification accuracy on underwater mine detection tasks performed on synthesized datasets provided by the Office of Naval Research. We have also demonstrated that the system can incrementally improve its detection accuracy by constantly learning from new samples.

Privacy-Preserving Data Exploration in Genome-Wide Association Studies.

PubMed

Johnson, Aaron; Shmatikov, Vitaly

2013-08-01

Genome-wide association studies (GWAS) have become a popular method for analyzing sets of DNA sequences in order to discover the genetic basis of disease. Unfortunately, statistics published as the result of GWAS can be used to identify individuals participating in the study. To prevent privacy breaches, even previously published results have been removed from public databases, impeding researchers' access to the data and hindering collaborative research. Existing techniques for privacy-preserving GWAS focus on answering specific questions, such as correlations between a given pair of SNPs (DNA sequence variations). This does not fit the typical GWAS process, where the analyst may not know in advance which SNPs to consider and which statistical tests to use, how many SNPs are significant for a given dataset, etc. We present a set of practical, privacy-preserving data mining algorithms for GWAS datasets. Our framework supports exploratory data analysis, where the analyst does not know a priori how many and which SNPs to consider. We develop privacy-preserving algorithms for computing the number and location of SNPs that are significantly associated with the disease, the significance of any statistical test between a given SNP and the disease, any measure of correlation between SNPs, and the block structure of correlations. We evaluate our algorithms on real-world datasets and demonstrate that they produce significantly more accurate results than prior techniques while guaranteeing differential privacy.

Emphysema and pulmonary impairment in coal miners: Quantitative relationship with dust exposure and cigarette smoking

NASA Astrophysics Data System (ADS)

Kuempel, E. D.; Vallyathan, V.; Green, F. H. Y.

2009-02-01

Coal miners have been shown to be at increased risk of developing chronic obstructive pulmonary diseases including emphysema. The objective of this study was to determine whether lifetime cumulative exposure to respirable coal mine dust is a significant predictor of developing emphysema at a clinically-relevant level of severity by the end of life, after controlling for cigarette smoking and other covariates. Clinically-relevant emphysema severity was determined from the association between individuals' lung function during life (forced expiratory volume in one second, FEV1, as a percentage of predicted normal values) and emphysema severity at autopsy (as the proportion of lung tissue affected). In a logistic regression model, cumulative exposure to respirable coal mine dust was a statistically significant predictor of developing clinically-relevant emphysema severity, among both ever-smokers and never-smokers. The odds ratio for developing emphysema associated with FEV1 <80% at the cohort mean cumulative coal dust exposure (87 mg/m3 x yr) was 2.30 (1.46-3.64, 95% confidence limits), and at the cohort mean cigarette smoking (among smokers: 42 pack-years) was 1.95 (1.39-2.79).

The structural and content aspects of abstracts versus bodies of full text journal articles are different

PubMed Central

2010-01-01

Background An increase in work on the full text of journal articles and the growth of PubMedCentral have the opportunity to create a major paradigm shift in how biomedical text mining is done. However, until now there has been no comprehensive characterization of how the bodies of full text journal articles differ from the abstracts that until now have been the subject of most biomedical text mining research. Results We examined the structural and linguistic aspects of abstracts and bodies of full text articles, the performance of text mining tools on both, and the distribution of a variety of semantic classes of named entities between them. We found marked structural differences, with longer sentences in the article bodies and much heavier use of parenthesized material in the bodies than in the abstracts. We found content differences with respect to linguistic features. Three out of four of the linguistic features that we examined were statistically significantly differently distributed between the two genres. We also found content differences with respect to the distribution of semantic features. There were significantly different densities per thousand words for three out of four semantic classes, and clear differences in the extent to which they appeared in the two genres. With respect to the performance of text mining tools, we found that a mutation finder performed equally well in both genres, but that a wide variety of gene mention systems performed much worse on article bodies than they did on abstracts. POS tagging was also more accurate in abstracts than in article bodies. Conclusions Aspects of structure and content differ markedly between article abstracts and article bodies. A number of these differences may pose problems as the text mining field moves more into the area of processing full-text articles. However, these differences also present a number of opportunities for the extraction of data types, particularly that found in parenthesized text, that is present in article bodies but not in article abstracts. PMID:20920264

Estimation of respirable dust exposure among coal miners in South Africa.

PubMed

Naidoo, Rajen; Seixas, Noah; Robins, Thomas

2006-06-01

The use of retrospective occupational hygiene data for epidemiologic studies is useful in determining exposure-outcome relationships, but the potential for exposure misclassification is high. Although dust sampling in the South African coal industry has been a legal requirement for several decades, these historical data are not readily adequate for estimating past exposures. This study describes the respirable coal mine dust levels in three South African coal mines over time. Each of the participating mining operations had well-documented dust sampling information that was used to describe historical trends in dust exposure. Investigator-collected personal dust samples were taken using standardized techniques from the face, backbye (underground jobs not at the coal face), and surface from 50 miners at each mine, repeated over three sampling cycles. Job histories and exposure information was obtained from a sample of 684 current miners and 188 ex-miners. Linear models were developed to estimate the exposure levels associated with work in each mine, exposure zone, and over time using a combination of operator-collected historical data and investigator-collected samples. The estimated levels were then combined with work history information to calculate cumulative exposure metrics for the miner cohort. The mean historical and investigator-collected respirable dust levels were within international norms and South African standards. Silica content of the dust samples was also below the 5% regulatory action level. Mean respirable dust concentrations at the face, based on investigator-collected samples, were 0.9 mg/m(3), 1.3 mg/m(3), and 1.9 mg/m(3) at Mines 1, 2, and 3, respectively. The operator-collected samples showed considerable variability across exposure zones, mines, and time, with the annual means at the face ranging from 0.4 mg/m(3) to 2.9 mg/m(3). Statistically significant findings were found between operator- and investigator-collected dust samples. Model-based arithmetic mean dust estimates at the face were 1.2 mg/m(3), 2.0 mg/m(3), and 0.9 mg/m(3) for Mines 1, 2, and 3, respectively. Using these levels, the mean cumulative exposure for the cohort was 56.8 mg-years/m(3). Current miners had a mean cumulative exposure of 66.5 mg-years/m(3), compared with ex-miners of 26.8 mg-years/m(3). Improvements in dust management or the use of different sampling equipment could account for the significant differences seen between operator- and investigator-collected data. Regression modeling for estimating mean dust levels over time using combined historical and investigator-collected data seems a reasonable method and useful in constructing models to describe cumulative exposures in a cohort of current and ex-miners.

15 CFR 970.701 - Significant adverse environmental effects.

Code of Federal Regulations, 2014 CFR

2014-01-01

... REGULATIONS OF THE ENVIRONMENTAL DATA SERVICE DEEP SEABED MINING REGULATIONS FOR EXPLORATION LICENSES... effects of deep seabed mining which cumulatively during commercial recovery have the potential for significant effect. These three effects also occur during mining system tests that may be conducted under a...

15 CFR 970.701 - Significant adverse environmental effects.

Code of Federal Regulations, 2013 CFR

2013-01-01

... REGULATIONS OF THE ENVIRONMENTAL DATA SERVICE DEEP SEABED MINING REGULATIONS FOR EXPLORATION LICENSES... effects of deep seabed mining which cumulatively during commercial recovery have the potential for significant effect. These three effects also occur during mining system tests that may be conducted under a...

15 CFR 970.701 - Significant adverse environmental effects.

Code of Federal Regulations, 2012 CFR

2012-01-01

... REGULATIONS OF THE ENVIRONMENTAL DATA SERVICE DEEP SEABED MINING REGULATIONS FOR EXPLORATION LICENSES... effects of deep seabed mining which cumulatively during commercial recovery have the potential for significant effect. These three effects also occur during mining system tests that may be conducted under a...

15 CFR 970.701 - Significant adverse environmental effects.

Code of Federal Regulations, 2010 CFR

2010-01-01

... REGULATIONS OF THE ENVIRONMENTAL DATA SERVICE DEEP SEABED MINING REGULATIONS FOR EXPLORATION LICENSES... effects of deep seabed mining which cumulatively during commercial recovery have the potential for significant effect. These three effects also occur during mining system tests that may be conducted under a...

15 CFR 970.701 - Significant adverse environmental effects.

Code of Federal Regulations, 2011 CFR

2011-01-01

... REGULATIONS OF THE ENVIRONMENTAL DATA SERVICE DEEP SEABED MINING REGULATIONS FOR EXPLORATION LICENSES... effects of deep seabed mining which cumulatively during commercial recovery have the potential for significant effect. These three effects also occur during mining system tests that may be conducted under a...

Development of uncertainty-based work injury model using Bayesian structural equation modelling.

PubMed

Chatterjee, Snehamoy

2014-01-01

This paper proposed a Bayesian method-based structural equation model (SEM) of miners' work injury for an underground coal mine in India. The environmental and behavioural variables for work injury were identified and causal relationships were developed. For Bayesian modelling, prior distributions of SEM parameters are necessary to develop the model. In this paper, two approaches were adopted to obtain prior distribution for factor loading parameters and structural parameters of SEM. In the first approach, the prior distributions were considered as a fixed distribution function with specific parameter values, whereas, in the second approach, prior distributions of the parameters were generated from experts' opinions. The posterior distributions of these parameters were obtained by applying Bayesian rule. The Markov Chain Monte Carlo sampling in the form Gibbs sampling was applied for sampling from the posterior distribution. The results revealed that all coefficients of structural and measurement model parameters are statistically significant in experts' opinion-based priors, whereas, two coefficients are not statistically significant when fixed prior-based distributions are applied. The error statistics reveals that Bayesian structural model provides reasonably good fit of work injury with high coefficient of determination (0.91) and less mean squared error as compared to traditional SEM.

Numerical Study on 4-1 Coal Seam of Xiaoming Mine in Ascending Mining

PubMed Central

Tianwei, Lan; Hongwei, Zhang; Sheng, Li; Weihua, Song; Batugin, A. C.; Guoshui, Tang

2015-01-01

Coal seams ascending mining technology is very significant, since it influences the safety production and the liberation of dull coal, speeds up the construction of energy, improves the stability of stope, and reduces or avoids deep hard rock mining induced mine disaster. Combined with the Xiaoming ascending mining mine 4-1, by numerical calculation, the paper analyses ascending mining 4-1 factors, determines the feasibility of ascending mining 4-1 coalbed, and proposes roadway layout program about working face, which has broad economic and social benefits. PMID:25866840

A Combined Ecological and Epidemiologic Investigation of Metals Exposure amongst Indigenous Peoples Near the Marlin Mine in Western Guatemala

PubMed Central

Basu, Niladri; Abare, Marce; Buchanan, Susan; Cryderman, Diana; Nam, Dong-Ha; Sirkin, Susannah; Schmitt, Stefan; Hu, Howard

2016-01-01

In August 2009 a combined epidemiological and ecological pilot study was conducted to investigate allegations of human rights abuses in the form of exposures to toxic metals experienced by mine workers and Indigenous Mam Mayan near the Marlin Mine in Guatemala. In the human study there were no differences in blood and urine metals when comparing five mine workers with eighteen non-mine workers, and there were no discernible relationships between metals exposures and self-reported health measures in any study group. On the other hand, individuals residing closest to the mine had significantly higher levels of certain metals (urinary mercury, copper, arsenic, zinc) when compared to those living further away. Levels of blood aluminum, manganese, and cobalt were elevated in comparison to established normal ranges in many individuals; however, there was no apparent relationship to proximity to the mine or occupation, and thus are of unclear significance. In the ecological study, several metals (aluminum, manganese, cobalt) were found significantly elevated in the river water and sediment sites directly below the mine when compared to sites elsewhere. When the results of the human and ecological results are combined, they suggest that exposures to certain metals may be elevated in sites near the mine but it is not clear if the current magnitude of these elevations poses a significant threat to health. The authors conclude that more robust studies are needed while parallel efforts to minimize the ecological and human impacts of mining proceed. This is critical particularly as the impact of the exposures found could be greatly magnified by expected increases in mining activity over time, synergistic toxicity between metals, and susceptibility for the young and those with pre-existing disease. PMID:20952048

Ecological effects of lead mining on Ozark streams: In-situ toxicity to woodland crayfish (Orconectes hylas)

USGS Publications Warehouse

Allert, A.L.; Fairchild, J.F.; DiStefano, R.J.; Schmitt, C.J.; Brumbaugh, W.G.; Besser, J.M.

2009-01-01

The Viburnum Trend mining district in southeast Missouri, USA is one of the largest producers of lead-zinc ore in the world. Previous stream surveys found evidence of increased metal exposure and reduced population densities of crayfish immediately downstream of mining sites. We conducted an in-situ 28-d exposure to assess toxicity of mining-derived metals to the woodland crayfish (Orconectes hylas). Crayfish survival and biomass were significantly lower at mining sites than at reference and downstream sites. Metal concentrations in water, detritus, macroinvertebrates, fish, and crayfish were significantly higher at mining sites, and were negatively correlated with caged crayfish survival. These results support previous field and laboratory studies that showed mining-derived metals negatively affect O. hylas populations in streams draining the Viburnum Trend, and that in-situ toxicity testing was a valuable tool for assessing the impacts of mining on crayfish populations.

Expanding Coherent Array Processing to Larger Apertures Using Empirical Matched Field Processing

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

Ringdal, F; Harris, D B; Kvaerna, T

2009-07-23

We have adapted matched field processing, a method developed in underwater acoustics to detect and locate targets, to classify transient seismic signals arising from mining explosions. Matched field processing, as we apply it, is an empirical technique, using observations of historic events to calibrate the amplitude and phase structure of wavefields incident upon an array aperture for particular repeating sources. The objective of this project is to determine how broadly applicable the method is and to understand the phenomena that control its performance. We obtained our original results in distinguishing events from ten mines in the Khibiny and Olenegorsk miningmore » districts of the Kola Peninsula, for which we had exceptional ground truth information. In a cross-validation test, some 98.2% of 549 explosions were correctly classified by originating mine using just the Pn observations (2.5-12.5 Hz) on the ARCES array at ranges from 350-410 kilometers. These results were achieved despite the fact that the mines are as closely spaced as 3 kilometers. Such classification performance is significantly better than predicted by the Rayleigh limit. Scattering phenomena account for the increased resolution, as we make clear in an analysis of the information carrying capacity of Pn under two alternative propagation scenarios: free-space propagation and propagation with realistic (actually measured) spatial covariance structure. The increase in information capacity over a wide band is captured by the matched field calibrations and used to separate explosions from very closely-spaced sources. In part, the improvement occurs because the calibrations enable coherent processing at frequencies above those normally considered coherent. We are investigating whether similar results can be expected in different regions, with apertures of increasing scale and for diffuse seismicity. We verified similar performance with the closely-spaced Zapolyarni mines, though discovered that it may be necessary to divide event populations from a single mine into identifiable subpopulations. For this purpose, we perform cluster analysis using matched field statistics calculated on pairs of individual events as a distance metric. In our initial work, calibrations were derived from ensembles of events ranging in number to more than 100. We are considering the performance now of matched field calibrations derived with many fewer events (even, as mentioned, individual events). Since these are high-variance estimates, we are testing the use of cross-channel, multitaper, spectral estimation methods to reduce the variance of calibrations and detection statistics derived from single-event observations. To test the applicability of the technique in a different tectonic region, we have obtained four years of continuous data from 4 Kazakh arrays and are extracting large numbers of event segments. Our initial results using 132 mining explosions recorded by the Makanchi array are similar to those obtained in the European Arctic. Matched field processing clearly separates the explosions from three closely-spaced mines located approximately 400 kilometers from the array, again using waveforms in a band (6-10 Hz) normally considered incoherent for this array. Having reproduced ARCES-type performance with another small aperture array, we have two additional objectives for matched field processing. We will attempt to extend matched field processing to larger apertures: a 200 km aperture (the KNET) and, if data permit, to an aperture comprised of several Kazakh arrays. We also will investigate the potential of developing matched field processing to roughly locate and classify natural seismicity, which is more diffuse than the concentrated sources of mining explosions that we have investigated to date.« less

Cargo Throughput and Survivability Trade-Offs in Force Sustainment Operations

DTIC Science & Technology

2008-06-01

more correlation with direct human activity. Mines are able to simply ‘sit and wait,’ thus allowing for easier mathematical and statistical ...1.2) Since the ships will likely travel in groups along the same programmed GPS track, modeling several transitors to the identical path is assumed...setting of 1/2 was used for the actuation probability maximum. The ‘threat profile’ will give the probability that the nth transitor will hit a mine

Analytics for Cyber Network Defense

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

Plantenga, Todd.; Kolda, Tamara Gibson

2011-06-01

This report provides a brief survey of analytics tools considered relevant to cyber network defense (CND). Ideas and tools come from elds such as statistics, data mining, and knowledge discovery. Some analytics are considered standard mathematical or statistical techniques, while others re ect current research directions. In all cases the report attempts to explain the relevance to CND with brief examples.

Text grouping in patent analysis using adaptive K-means clustering algorithm

NASA Astrophysics Data System (ADS)

Shanie, Tiara; Suprijadi, Jadi; Zulhanif

2017-03-01

Patents are one of the Intellectual Property. Analyzing patent is one requirement in knowing well the development of technology in each country and in the world now. This study uses the patent document coming from the Espacenet server about Green Tea. Patent documents related to the technology in the field of tea is still widespread, so it will be difficult for users to information retrieval (IR). Therefore, it is necessary efforts to categorize documents in a specific group of related terms contained therein. This study uses titles patent text data with the proposed Green Tea in Statistical Text Mining methods consists of two phases: data preparation and data analysis stage. The data preparation phase uses Text Mining methods and data analysis stage is done by statistics. Statistical analysis in this study using a cluster analysis algorithm, the Adaptive K-Means Clustering Algorithm. Results from this study showed that based on the maximum value Silhouette, generate 87 clusters associated fifteen terms therein that can be utilized in the process of information retrieval needs.

Example Building Damage Caused by Mining Exploitation in Disturbed Rock Mass

NASA Astrophysics Data System (ADS)

Florkowska, Lucyna

2013-06-01

Issues concerning protection of buildings against the impact of underground coal mining pose significant scientific and engineering challenges. In Poland, where mining is a potent and prominent industry assuring domestic energy security, regions within reach of mining influences are plenty. Moreover, due to their industrial character they are also densely built-up areas. Because minerals have been extracted on an industrial scale in majority of those areas for many years, the rock mass structure has been significantly disturbed. Hence, exploitation of successive layers of multi-seam deposits might cause considerable damage - both in terms of surface and existing infrastructure networks. In the light of those facts, the means of mining and building prevention have to be improved on a regular basis. Moreover, they have to be underpinned by reliable analyses holistically capturing the comprehensive picture of the mining, geotechnical and constructional situation of structures. Scientific research conducted based on observations and measurements of mining-induced strain in buildings is deployed to do just that. Presented in this paper examples of damage sustained by buildings armed with protection against mining influences give an account of impact the mining exploitation in disturbed rock mass can have. This paper is based on analyses of mining damage to church and Nursing Home owned by Evangelical Augsburg Parish in Bytom-Miechowice. Neighbouring buildings differ in the date they were built, construction, building technology, geometry of the building body and fitted protection against mining damage. Both the buildings, however, have sustained lately significant deformation and damage caused by repeated mining exploitation. Selected damage has been discussed hereunder. The structures have been characterised, their current situation and mining history have been outlined, which have taken their toll on character and magnitude of damage. Description has been supplemented with photographic documentation.

BOUNDS ON SUBSURFACE MERCURY FLUX FROM THE SULPHUR BANK MERCURY MINE, LAKE COUNTY, CALIFORNIA

EPA Science Inventory

The Sulphur Bank Mercury Mine (SBMM) in Lake County, California has been identified as a significant source of mercury to Clear Lake. The mine was operated from the 1860s through the 1950's. Mining started with surface operations, progressed to shaft mining, and later to open p...

Definition of redox and pH influence in the AMD mine system using a fuzzy qualitative tool (Iberian Pyrite Belt, SW Spain).

PubMed

de la Torre, M L; Grande, J A; Valente, T; Perez-Ostalé, E; Santisteban, M; Aroba, J; Ramos, I

2016-03-01

Poderosa Mine is an abandoned pyrite mine, located in the Iberian Pyrite Belt which pours its acid mine drainage (AMD) waters into the Odiel river (South-West Spain). This work focuses on establishing possible reasons for interdependence between the potential redox and pH, with the load of metals and sulfates, as well as a set of variables that define the physical chemistry of the water-conductivity, temperature, TDS, and dissolved oxygen-transported by a channel from Poderosa mine affected by acid mine drainage, through the use of techniques of artificial intelligence: fuzzy logic and data mining. The sampling campaign was carried out in May of 2012. There were a total of 16 sites, the first inside the tunnel and the last at the mouth of the river Odiel, with a distance of approximately 10 m between each pair of measuring stations. While the tools of classical statistics, which are widely used in this context, prove useful for defining proximity ratios between variables based on Pearson's correlations, in addition to making it easier to handle large volumes of data and producing easier-to-understand graphs, the use of fuzzy logic tools and data mining results in better definition of the variations produced by external stimuli on the set of variables. This tool is adaptable and can be extrapolated to any system polluted by acid mine drainage using simple, intuitive reasoning.

Small mammal-heavy metal concentrations from mined and control sites

USGS Publications Warehouse

Smith, G.J.; Rongstad, O.J.

1982-01-01

Total body concentrations of zinc, copper, cadmium, lead, nickel, mercury and arsenic were determined for Peromyscus maniculatus and Microtus pennsylvanicus from an active zinc-copper mine near Timmins, Ontario, Canada, and a proposed zinc-copper mine near Crandon, Wisconsin, USA. Metal concentrations were evaluated with respect to area, species, sex and age groups. Metal concentrations in Peromyscus from the proposed mine site were not different from those collected in a third area where no mine or deposit exists. This is probably due to the 30 m of glacial material over the proposed mine site deposit. A statistical interaction between area, species, sex and age was observed for zinc and copper concentrations in small mammals we examined. Peromyscus from the mine site had consistently higher metal concentrations than Peromyscus from the control site. Greater total body cadmium and lead concentrations in adult?compared with juvenile?Peromyscus collected at the mine site suggests age-dependent accumulation of these toxic metals. Microtus did not exhibit this age-related response, and responded to other environmental metals more erratically and to a lesser degree. Differences in the response of these two species to environmental metal exposure may be due to differences in food habits. Nickel, mercury and arsenic concentrations in small mammals from the mine site were not different from controls. Heavy metal concentrations are also presented for Sorex cinereus, Blarina brevicauda and Zapus hudsonicus without respect to age and sex cohorts. Peromyscus may be a potentially important species for the monitoring of heavy metal pollution.

Changes in the Bacterial Community of Soil from a Neutral Mine Drainage Channel

PubMed Central

Pereira, Letícia Bianca; Vicentini, Renato; Ottoboni, Laura M. M.

2014-01-01

Mine drainage is an important environmental disturbance that affects the chemical and biological components in natural resources. However, little is known about the effects of neutral mine drainage on the soil bacteria community. Here, a high-throughput 16S rDNA pyrosequencing approach was used to evaluate differences in composition, structure, and diversity of bacteria communities in samples from a neutral drainage channel, and soil next to the channel, at the Sossego copper mine in Brazil. Advanced statistical analyses were used to explore the relationships between the biological and chemical data. The results showed that the neutral mine drainage caused changes in the composition and structure of the microbial community, but not in its diversity. The Deinococcus/Thermus phylum, especially the Meiothermus genus, was in large part responsible for the differences between the communities, and was positively associated with the presence of copper and other heavy metals in the environmental samples. Other important parameters that influenced the bacterial diversity and composition were the elements potassium, sodium, nickel, and zinc, as well as pH. The findings contribute to the understanding of bacterial diversity in soils impacted by neutral mine drainage, and demonstrate that heavy metals play an important role in shaping the microbial population in mine environments. PMID:24796430

Chapter 16: text mining for translational bioinformatics.

PubMed

Cohen, K Bretonnel; Hunter, Lawrence E

2013-04-01

Text mining for translational bioinformatics is a new field with tremendous research potential. It is a subfield of biomedical natural language processing that concerns itself directly with the problem of relating basic biomedical research to clinical practice, and vice versa. Applications of text mining fall both into the category of T1 translational research-translating basic science results into new interventions-and T2 translational research, or translational research for public health. Potential use cases include better phenotyping of research subjects, and pharmacogenomic research. A variety of methods for evaluating text mining applications exist, including corpora, structured test suites, and post hoc judging. Two basic principles of linguistic structure are relevant for building text mining applications. One is that linguistic structure consists of multiple levels. The other is that every level of linguistic structure is characterized by ambiguity. There are two basic approaches to text mining: rule-based, also known as knowledge-based; and machine-learning-based, also known as statistical. Many systems are hybrids of the two approaches. Shared tasks have had a strong effect on the direction of the field. Like all translational bioinformatics software, text mining software for translational bioinformatics can be considered health-critical and should be subject to the strictest standards of quality assurance and software testing.

Using Data Mining to Detect Health Care Fraud and Abuse: A Review of Literature

PubMed Central

Joudaki, Hossein; Rashidian, Arash; Minaei-Bidgoli, Behrouz; Mahmoodi, Mahmood; Geraili, Bijan; Nasiri, Mahdi; Arab, Mohammad

2015-01-01

Inappropriate payments by insurance organizations or third party payers occur because of errors, abuse and fraud. The scale of this problem is large enough to make it a priority issue for health systems. Traditional methods of detecting health care fraud and abuse are time-consuming and inefficient. Combining automated methods and statistical knowledge lead to the emergence of a new interdisciplinary branch of science that is named Knowledge Discovery from Databases (KDD). Data mining is a core of the KDD process. Data mining can help third-party payers such as health insurance organizations to extract useful information from thousands of claims and identify a smaller subset of the claims or claimants for further assessment. We reviewed studies that performed data mining techniques for detecting health care fraud and abuse, using supervised and unsupervised data mining approaches. Most available studies have focused on algorithmic data mining without an emphasis on or application to fraud detection efforts in the context of health service provision or health insurance policy. More studies are needed to connect sound and evidence-based diagnosis and treatment approaches toward fraudulent or abusive behaviors. Ultimately, based on available studies, we recommend seven general steps to data mining of health care claims. PMID:25560347

Flooded Underground Coal Mines: A Significant Source of Inexpensive Geothermal Energy

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

Watzlaf, G.R.; Ackman, T.E.

2007-04-01

Many mining regions in the United States contain extensive areas of flooded underground mines. The water within these mines represents a significant and widespread opportunity for extracting low-grade, geothermal energy. Based on current energy prices, geothermal heat pump systems using mine water could reduce the annual costs for heating to over 70 percent compared to conventional heating methods (natural gas or heating oil). These same systems could reduce annual cooling costs by up to 50 percent over standard air conditioning in many areas of the country. (Formatted full-text version is released by permission of publisher)

Evaluation of water resources around Barapukuria coal mine industrial area, Dinajpur, Bangladesh

NASA Astrophysics Data System (ADS)

Howladar, M. Farhad; Deb, Pulok Kanti; Muzemder, A. T. M. Shahidul Huqe; Ahmed, Mushfique

2014-09-01

Water is a very important natural resource which can be utilized in renewable or non-renewable forms but before utilizing, the evaluation of the quality of this resource is crucial for a particular use. However, the problems of water quality are more severe in areas where the mining and mineral processes' industries are present. In mining processes, several classes of wastes are produced which may turn into ultimately the sources of water quality and environmental degradation. In consequences, the evaluations of water quality for livestock, drinking, irrigation purposes and environmental implications have been carried out around the Barapukuria Coal Mining Industry under different methods and techniques such as primarily the field investigation; secondly the laboratory chemical analysis and thirdly justified the suitability of the laboratory analysis with statistical representation and correlation matrix, Schoeller plot, Piper's Trilinear diagram, Expanded Durov diagram, Wilcox diagram, US salinity diagram, Doneen's chart and others. The results of all surface and ground water samples analysis show that the characteristics and concentrations of all the major physical and chemical parameters such as pH, EC, TDS, Na+, K+, Ca2+, Mg2+, Fetotal, Cl-, HCO3 -, CO3 2- and SO4 2- are varied from one sample to other but well analogous with the WHO and EQS standard limit for all purposes in the area where the abundance of the major ions is as follows: Ca2+ > Na+ > Mg2+ > K+ > Fetotal = HCO3 - > SO4 2- > Cl- > CO3 2-. The graphical exposition of analytical data demonstrates two major hydrochemical facies for example: calcium-bicarbonate (Ca2+- HCO3 -) and magnesium-bicarbonate (Mg2+- HCO3 -) type facies which directly support the shallow recently recharged alkaline water around the industry. The calculated values for the evaluation classification of water based on TDS, Na%, EC, SAR, PI, RSC, MH, and TH replicate good to excellent use of water for livestock, drinking and irrigation activities except in some cases. For example, the high hardness in both water samples specifies the active hydraulic relation between surface and groundwater. Moreover, the statistical application and interpretation exhibit a good positive correlation among most of the water constituents which might be the indicator of having tightly grouped, precise homogeneous good-quality water resources around the mining industry. Finally from the environmental degradation point of view, it can be implied that there are no significant parameters or factors observed which are much badly effective on environment except very few cases. Thus, this research strongly recommends for monitoring the water quality in every 6 months or annually around this industry which might be positive for keeping the safe environment and healthy production of the coal mine.

The effect of crop protection strategy on pest and beneficials incidence in protected crops.

PubMed

Lourenço, I; Rodrigues, S; Figueiredo, E; Godinho, M C; Marques, C; Amaro, F; Mexia, A

2002-01-01

This study took place in the Oeste region from 1996-1999 and it intended to analyse if the crop protection strategy followed by the farmer influenced the arthropod incidence and the natural control in protected vegetable crops under Mediterranean conditions. The observations were made fortnightly (Autumn/Winter) or weekly (Spring/Summer) in 30-60 plants/parcel (1 plant/35 m2) in order to evaluate incidences. Samples of pests and natural enemies were collected for systematic identification in two greenhouses for each protection strategy (traditional chemical control (TCC), integrated pest management (IPM) and pest control allowed in organic farming (OF)) in lettuce, tomato, green beans and cucumber. Data on incidence of mites, aphids, caterpillars, leafminers, whiteflies, thrips and respective natural enemies were registered as well as phytosanitary treatments performed (farmers' information and/or in loco traces). The leafminers were the pest whose incidence more often presented significant statistical differences between the studied protection strategies. In relation to this pest, the main results obtained were: a higher feeding punctures incidence in TCC than in IPM; higher incidence of adults, mines and feeding punctures in TCC than in OF; and a higher mines' incidence in IPM than in OF. Both in TCC and IPM high percentages of plants with mines were found although without an adult proportional presence. In the first case this was due to the repeatedly phytosanitary treatments applied; in the second case it was due to the natural control, since in IPM and OF greenhouses the collected larvae were mostly parasitized or dead. In spite of the fact these two strategies have as final result a similar mines and adults incidence, their production and environmental costs are quite different. Significant differences at the beneficials' population level between TCC greenhouses and IPM or OF greenhouses were found. As the farmers did no biological treatments these differences are related to different levels of beneficial populations due to different secondary effects of the pesticides applied.

Systematic drug repositioning through mining adverse event data in ClinicalTrials.gov.

PubMed

Su, Eric Wen; Sanger, Todd M

2017-01-01

Drug repositioning (i.e., drug repurposing) is the process of discovering new uses for marketed drugs. Historically, such discoveries were serendipitous. However, the rapid growth in electronic clinical data and text mining tools makes it feasible to systematically identify drugs with the potential to be repurposed. Described here is a novel method of drug repositioning by mining ClinicalTrials.gov. The text mining tools I2E (Linguamatics) and PolyAnalyst (Megaputer) were utilized. An I2E query extracts "Serious Adverse Events" (SAE) data from randomized trials in ClinicalTrials.gov. Through a statistical algorithm, a PolyAnalyst workflow ranks the drugs where the treatment arm has fewer predefined SAEs than the control arm, indicating that potentially the drug is reducing the level of SAE. Hypotheses could then be generated for the new use of these drugs based on the predefined SAE that is indicative of disease (for example, cancer).

WORKSHOP ON: MINING-IMPACTED NATIVE AMERICAN LANDS

EPA Science Inventory

Mining waste which is generated from both active and inactive mining sites continues to be a problem for human health and ecosystems. Recent scoping studies show significant environmental impacts from mining activities primarily in the Western States. Approximately, 85% of this...

Antimicrobial Stewardship in a Community Hospital: Attacking the More Difficult Problems

PubMed Central

Philmon, Carla L.; Johnson, Gregory D.; Ward, William S.; Rivers, LaToya L.; Williamson, Sharon A.; Goodman, Edward L.

2014-01-01

Background: Antibiotic stewardship has been proposed as an important way to reduce or prevent antibiotic resistance. In 2001, a community hospital implemented an antimicrobial management program. It was successful in reducing antimicrobial utilization and expenditure. In 2011, with the implementation of a data-mining tool, the program was expanded and its focus transitioned from control of antimicrobial use to guiding judicious antimicrobial prescribing. Objective: To test the hypothesis that adding a data-mining tool to an existing antimicrobial stewardship program will further increase appropriate use of antimicrobials. Design: Interventional study with historical comparison. Methods: Rules and alerts were built into the data-mining tool to aid in identifying inappropriate antibiotic utilization. Decentralized pharmacists acted on alerts for intravenous (IV) to oral conversion, perioperative antibiotic duration, and restricted antimicrobials. An Infectious Diseases (ID) Pharmacist and ID Physician/Hospital Epidemiologist focused on all other identified alert types such as antibiotic de-escalation, bug-drug mismatch, and double coverage. Electronic chart notes and phone calls to physicians were utilized to make recommendations. Results: During 2012, 2,003 antimicrobial interventions were made with a 90% acceptance rate. Targeted broad-spectrum antimicrobial use decreased by 15% in 2012 compared to 2010, which represented cost savings of $1,621,730. There were no statistically significant changes in antimicrobial resistance, and no adverse patient outcomes were noted. Conclusions: The addition of a data-mining tool to an antimicrobial stewardship program can further decrease inappropriate use of antimicrobials, provide a greater reduction in overall antimicrobial use, and provide increased cost savings without negatively affecting patient outcomes. PMID:25477615

Integrative image segmentation optimization and machine learning approach for high quality land-use and land-cover mapping using multisource remote sensing data

NASA Astrophysics Data System (ADS)

Gibril, Mohamed Barakat A.; Idrees, Mohammed Oludare; Yao, Kouame; Shafri, Helmi Zulhaidi Mohd

2018-01-01

The growing use of optimization for geographic object-based image analysis and the possibility to derive a wide range of information about the image in textual form makes machine learning (data mining) a versatile tool for information extraction from multiple data sources. This paper presents application of data mining for land-cover classification by fusing SPOT-6, RADARSAT-2, and derived dataset. First, the images and other derived indices (normalized difference vegetation index, normalized difference water index, and soil adjusted vegetation index) were combined and subjected to segmentation process with optimal segmentation parameters obtained using combination of spatial and Taguchi statistical optimization. The image objects, which carry all the attributes of the input datasets, were extracted and related to the target land-cover classes through data mining algorithms (decision tree) for classification. To evaluate the performance, the result was compared with two nonparametric classifiers: support vector machine (SVM) and random forest (RF). Furthermore, the decision tree classification result was evaluated against six unoptimized trials segmented using arbitrary parameter combinations. The result shows that the optimized process produces better land-use land-cover classification with overall classification accuracy of 91.79%, 87.25%, and 88.69% for SVM and RF, respectively, while the results of the six unoptimized classifications yield overall accuracy between 84.44% and 88.08%. Higher accuracy of the optimized data mining classification approach compared to the unoptimized results indicates that the optimization process has significant impact on the classification quality.

Genomic research and data-mining technology: implications for personal privacy and informed consent.

PubMed

Tavani, Herman T

2004-01-01

This essay examines issues involving personal privacy and informed consent that arise at the intersection of information and communication technology (ICT) and population genomics research. I begin by briefly examining the ethical, legal, and social implications (ELSI) program requirements that were established to guide researchers working on the Human Genome Project (HGP). Next I consider a case illustration involving deCODE Genetics, a privately owned genetic company in Iceland, which raises some ethical concerns that are not clearly addressed in the current ELSI guidelines. The deCODE case also illustrates some ways in which an ICT technique known as data mining has both aided and posed special challenges for researchers working in the field of population genomics. On the one hand, data-mining tools have greatly assisted researchers in mapping the human genome and in identifying certain "disease genes" common in specific populations (which, in turn, has accelerated the process of finding cures for diseases tha affect those populations). On the other hand, this technology has significantly threatened the privacy of research subjects participating in population genomics studies, who may, unwittingly, contribute to the construction of new groups (based on arbitrary and non-obvious patterns and statistical correlations) that put those subjects at risk for discrimination and stigmatization. In the final section of this paper I examine some ways in which the use of data mining in the context of population genomics research poses a critical challenge for the principle of informed consent, which traditionally has played a central role in protecting the privacy interests of research subjects participating in epidemiological studies.

Reclamation Strategies and Geomorphic Outcomes in Coal Surface Mines of Eastern Ohio

NASA Astrophysics Data System (ADS)

Pollock, M.; Jaeger, K. L.

2014-12-01

Coal surface mining is a significant landscape disturbance in the United States. Since 1977, the reclamation of mined lands has been regulated by the Surface Mine Control and Reclamation Act (SMCRA). Prior to the act, many coalfields were left un-reclaimed or partially reclaimed, with highly irregular topology and drainage networks. Under the act, the reverse is often true; adherence to SMCRA often leads to the homogenization of surfaces and channel networks. While both pre and post-SMCRA landscapes are highly altered, they exhibit strongly dissimilar characteristics. We examine pre-SMCRA, post-SMCRA and unmined watersheds at 3 spatial scales in order to compare the geomorphic differences between reclamation strategies. In particular, we attempt to separate anthropogenic factors from pre-existing, natural factors via comparisons to unmined watersheds. Our study design incorporates a 3 scale top-down analysis of 21 independent watersheds (7 of each treatment type). Each watershed has an area of approximately 1km2. All watersheds share similar geography, climate and geology. At the landscape scale, characteristics are derived from 0.762m (2.5ft) resolution Digital Elevation Models (DEMs). At the channel network scale, DEMs, as well as remote sensing data (including the National Wetlands Inventory database) are used. Finally, the reach scale incorporates longitudinal and cross-section surveys (using a total station) as well as a particle size distribution. At each scale, attributes are parameterized for statistical comparison. Post-SMCRA sites are characterized by a general reduction of watershed surface slopes (11.9% median) compared to pre-SMCRA (19.3%) and unmined (19.8%) sites. Both pre and post-SMCRA channel networks are characterized by significant surface impoundments (in the form of remnant headwall trenches on pre-SMCRA sites and engineered retention basins on post-SMCRA sites). Pre-SMCRA outlet reaches have significantly steeper bed slopes (2.79% mean) than both post-SMCRA (1.72% mean) and unmined (1.67% mean) reaches (1-way ANOVA p=0.0488 n=19). Our results demonstrate the differential alterations resulting from these reclamation strategies, which may lead to alteration of long-term geomorphic processes. Further investigations of hydrology and sediment transport are needed.

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

Influence of occupational safety management on the incidence rate of occupational accidents in the Spanish industrial and ornamental stone mining.

PubMed

Sanmiquel, Lluís; Rossell, Josep M; Vintró, Carla; Freijo, Modesto

2014-01-01

Mines are hazardous and workers can suffer many types of accidents caused by fire, flood, explosion or collapse. Injury incidence rates in mining are considerably higher than those registered by other economic sectors. One of the main reasons for this high-level incidence rate is the existence of a large number of dangerous workplaces. This work analyzes the influence that occupational safety management had on the accidents that took place in Spanish mining of industrial and ornamental stone during the period 2007-2008. Primary data sources are: (a) Results from a statistical study of the occupational health and safety management practices of 71 quarries defined by a questionnaire of 41 items; and (b) Occupational accidents registered in the Spanish industrial and ornamental stone mining throughout the period 2007-2008. The obtained results indicate that workplaces with a low average score in the analysis of occupational safety management have a higher incidence rate of accidents. Studies on mining workplaces are very important to help detect occupational safety concerns. Results from this study help raise awareness and will encourage the adoption of appropriate measures to improve safety.

Revealing Significant Relations between Chemical/Biological Features and Activity: Associative Classification Mining for Drug Discovery

ERIC Educational Resources Information Center

Yu, Pulan

2012-01-01

Classification, clustering and association mining are major tasks of data mining and have been widely used for knowledge discovery. Associative classification mining, the combination of both association rule mining and classification, has emerged as an indispensable way to support decision making and scientific research. In particular, it offers a…

Interaction of mining activities and aquatic environment: A review from Greek mine sites.

NASA Astrophysics Data System (ADS)

Vasileiou, Eleni; Kallioras, Andreas

2016-04-01

In Greece a significant amount of mineral and ore deposits have been recorded accompanied by large industrial interest and a long mining history. Today many active and/or abandoned mine sites are scattered within the country; while mining activities take place in different sites for exploiting various deposits (clay, limestone, slate, gypsum, kaolin, mixed sulphide ores (lead, zinc, olivine, pozzolan, quartz lignite, nickel, magnesite, aluminum, bauxite, gold, marbles etc). The most prominent recent ones are: (i) the lignite exploitation that is extended in the area of Ptolemais (Western Macedonia) and Megalopolis (Central Peloponnese); and (ii) the major bauxite deposits located in central Greece within the Parnassos-Ghiona geotectonic zone and on Euboea Island. In the latter area, significant ores of magnesite were exploited and mixed sulphide ores. Centuries of intensive mining exploitation and metallurgical treatment of lead-silver deposits in Greece, have also resulted in significant abandoned sites, such as the one in Lavrion. Mining activities in Lavrio, were initiated in ancient times and continued until the 1980s, resulting in the production of significant waste stockpiles deposited in the area, crucial for the local water resources. Ιn many mining sites, environmental pressures are also recorded after the mine closure to the aquatic environment, as the surface waters flow through waste dump areas and contaminated soils. This paper aims to the geospatial visualization of the mining activities in Greece, in connection to their negative (surface- and/or ground-water pollution; overpumping due to extensive dewatering practices) or positive (enhanced groundwater recharge; pit lakes, improvement of water budget in the catchment scale) impacts on local water resources.

Long-term mortality in miners with coal workers' pneumoconiosis in The Netherlands: a pilot study.

PubMed

Meijers, J M; Swaen, G M; Slangen, J J; van Vliet, K; Sturmans, F

1991-01-01

In order to investigate whether the prolonged exposure to coal mine dust increases the cancer risk for coal miners, a pilot study in a selected cohort of 334 Dutch miners with coal workers' pneumoconiosis (CWP), followed from 1956 until 1983, was conducted. In total, 165 miners had died (49.4%); for 162 (98.2%) the cause of death was traced. In comparison to the general Dutch male population, total mortality in the cohort was statistically significantly increased (SMR: 153). This was in general due to the significantly higher than expected cancer mortality (SMR: 163), cancer of stomach and small intestine (SMR: 401) and nonmalignant respiratory disease (SMR: 426). The lung cancer mortality was within the expected range.

Effects of historical lead–zinc mining on riffle-dwelling benthic fish and crayfish in the Big River of southeastern Missouri, USA

USGS Publications Warehouse

Allert, A.L.; DiStefano, R.J.; Fairchild, J.F.; Schmitt, C.J.; McKee, M.J.; Girondo, J.A.; Brumbaugh, W.G.; May, T.W.

2013-01-01

The Big River (BGR) drains much of the Old Lead Belt mining district (OLB) in southeastern Missouri, USA, which was historically among the largest producers of lead–zinc (Pb–Zn) ore in the world. We sampled benthic fish and crayfish in riffle habitats at eight sites in the BGR and conducted 56-day in situ exposures to the woodland crayfish (Orconectes hylas) and golden crayfish (Orconectes luteus) in cages at four sites affected to differing degrees by mining. Densities of fish and crayfish, physical habitat and water quality, and the survival and growth of caged crayfish were examined at sites with no known upstream mining activities (i.e., reference sites) and at sites downstream of mining areas (i.e., mining and downstream sites). Lead, zinc, and cadmium were analyzed in surface and pore water, sediment, detritus, fish, crayfish, and other benthic macro-invertebrates. Metals concentrations in all materials analyzed were greater at mining and downstream sites than at reference sites. Ten species of fish and four species of crayfish were collected. Fish and crayfish densities were significantly greater at reference than mining or downstream sites, and densities were greater at downstream than mining sites. Survival of caged crayfish was significantly lower at mining sites than reference sites; downstream sites were not tested. Chronic toxic-unit scores and sediment probable effects quotients indicated significant risk of toxicity to fish and crayfish, and metals concentrations in crayfish were sufficiently high to represent a risk to wildlife at mining and downstream sites. Collectively, the results provided direct evidence that metals associated with historical mining activities in the OLB continue to affect aquatic life in the BGR.

Foundational Principles for Large-Scale Inference: Illustrations Through Correlation Mining.

PubMed

Hero, Alfred O; Rajaratnam, Bala

2016-01-01

When can reliable inference be drawn in fue "Big Data" context? This paper presents a framework for answering this fundamental question in the context of correlation mining, wifu implications for general large scale inference. In large scale data applications like genomics, connectomics, and eco-informatics fue dataset is often variable-rich but sample-starved: a regime where the number n of acquired samples (statistical replicates) is far fewer than fue number p of observed variables (genes, neurons, voxels, or chemical constituents). Much of recent work has focused on understanding the computational complexity of proposed methods for "Big Data". Sample complexity however has received relatively less attention, especially in the setting when the sample size n is fixed, and the dimension p grows without bound. To address fuis gap, we develop a unified statistical framework that explicitly quantifies the sample complexity of various inferential tasks. Sampling regimes can be divided into several categories: 1) the classical asymptotic regime where fue variable dimension is fixed and fue sample size goes to infinity; 2) the mixed asymptotic regime where both variable dimension and sample size go to infinity at comparable rates; 3) the purely high dimensional asymptotic regime where the variable dimension goes to infinity and the sample size is fixed. Each regime has its niche but only the latter regime applies to exa cale data dimension. We illustrate this high dimensional framework for the problem of correlation mining, where it is the matrix of pairwise and partial correlations among the variables fua t are of interest. Correlation mining arises in numerous applications and subsumes the regression context as a special case. we demonstrate various regimes of correlation mining based on the unifying perspective of high dimensional learning rates and sample complexity for different structured covariance models and different inference tasks.

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).

Relations of benthic macroinvertebrates to concentrations of trace elements in water, streambed sediments, and transplanted bryophytes and stream habitat conditions in nonmining and mining areas of the upper Colorado River basin, Colorado, 1995-98

USGS Publications Warehouse

Mize, Scott V.; Deacon, Jeffrey R.

2002-01-01

Intensive mining activity and highly mineralized rock formations have had significant impacts on surface-water and streambed-sediment quality and aquatic life within the upper reaches of the Uncompahgre River in western Colorado. A synoptic study by the U.S. Geological Survey National Water-Quality Assessment Program was completed in the upper Uncompahgre River Basin in 1998 to better understand the relations of trace elements (with emphasis on aluminum, arsenic, copper, iron, lead, and zinc concentrations) in water, streambed sediment, and aquatic life. Water-chemistry, streambed-sediment, and benthic macroinvertebrate samples were collected during low-flow conditions between October 1995 and July 1998 at five sites on the upper Uncompahgre River, all downstream from historical mining, and at three sites in drainage basins of the Upper Colorado River where mining has not occurred. Aquatic bryophytes were transplanted to all sites for 15 days of exposure to the water column during which time field parameters were measured and chemical water-quality and benthic macroinvertebrate samples were collected. Stream habitat characteristics also were documented at each site. Certain attributes of surface-water chemistry among streams were significantly different. Concentrations of total aluminum, copper, iron, lead, and zinc in the water column and concentrations of dissolved aluminum, copper, and zinc were significantly different between nonmining and mining sites. Some sites associated with mining exceeded Colorado acute aquatic-life standards for aluminum, copper, and zinc and exceeded Colorado chronic aquatic-life standards for aluminum, copper, iron, lead, and zinc. Concentrations of copper, lead, and zinc in streambed sediments were significantly different between nonmining and mining sites. Generally, concentrations of arsenic, copper, lead, and zinc in streambed sediments at mining sites exceeded the Canadian Sediment Quality Guidelines probable effect level (PEL), except at two mining sites where concentrations of copper and zinc were below the PEL. Concentrations of arsenic, copper, iron, and lead in transplanted bryophytes were significantly different between nonmining and mining sites. Bioconcentration factors calculated for 15-day exposure using one-half of the minimum reporting level were significantly different between nonmining and mining sites. In general, concentrations of trace elements in streambed sediment and transplanted bryophytes were more closely correlated than were the concentrations of trace elements in the water column with streambed sediments or concentrations in the water column with transplanted bryophytes. Stream habitat was rated as optimal to suboptimal using the U.S. Environmental Protection Agency Rapid Bioassessment Protocols for all sites in the study area. Generally, stream habitat conditions were similar at nonmining compared to mining sites and were suitable for diverse macroinvertebrate communities. All study sites had optimal instream habitat except two mining sites with suboptimal instream habitat because of disturbances in stream habitat. The benthic macroinvertebrate community composition at nonmining sites and mining sites differed. Mining sites had significantly lower total abundance of macroinvertebrates, fewer numbers of taxa, and lower dominance of Ephemeroptera (mayflies), Plecoptera (stoneflies), and Trichoptera (caddisflies), and a larger percentage of tolerant species than did nonmining sites. The predominance of Baetis sp. (mayflies), Hydropsychidae (caddisflies), and large percentage of Orthocladiinae chironomids (midges) at mining sites indicated that these species may be tolerant to elevated trace-element concentrations. The absence of Heptageniidae (mayflies), Chloroperlidae (stoneflies), and Rhyacophila sp. (caddisflies) at mining sites indicated that these species may be sensitive to elevated trace-element concentrations. Comparison of field parameters and

Statistical analysis of surface-water-quality data in and near the coal-mining region of southwestern Indiana, 1957-80

USGS Publications Warehouse

Martin, Jeffrey D.; Crawford, Charles G.

1987-01-01

The Surface Mining Control and Reclamation Act of 1977 requires that applications for coal-mining permits contain information about the water quality of streams at and near a proposed mine. To meet this need for information, streamflow, specific conductance, pH, and concentrations of total alkalinity, sulfate, dissolved solids, suspended solids, total iron, and total manganese at 37 stations were analyzed to determine the spatial and seasonal variations in water quality and to develop equations for predicting water quality. The season of lowest median streamflow was related to the size of the drainage area. Median streamflow was least during fall at 15 of 16 stations having drainage areas greater than 1,000 square miles but was least during summer at 17 of 21 stations having drainage areas less than 1,000 square miles. In general, the season of lowest median specific conductance occurred during the season of highest streamflow except at stations on the Wabash River. Median specific conductance was least during summer at 9 of 9 stations on the Wabash River, but was least during winter or spring (the seasons of highest streamflow) at 27 of the remaining 28 stations. Linear, inverse, semilog, log-log, and hyperbolic regression models were used to investigate the functional relations between water-quality characteristics and streamflow. Of 186 relations investigated, 143 were statistically significant. Specific conductance and concentrations of total alkalinity and sulfate were negatively related to streamflow at all stations except for a positive relation between total alkalinity concentration and streamflow at Patoka River near Princeton. Concentrations of total alkalinity and sulfate were positively related to specific conductance at all stations except for a negative relation at Patoka River near Princeton and for a positive and negative relation at Patoka River at Jasper. Most of these relations are good, have small confidence intervals, and will give reliable predictions of the water-quality variables listed above. The poorest relations are typically at stations in the Patoka River watershed. Suspended-solids concentration was positively related to streamflow at all but two stations on the Patoka River. These relations are poor, have large confidence intervals, and will give less reliable predictions of suspended-solids concentration. Predictive equations for the regional relations between dissolved-solids concentration and specific conductance and between sulfate concentration and specific conductance, and the seasonal patterns of water quality, are probably valid for the coal-mining regions of Illinois and western Kentucky.

Trace metal depositional patterns from an open pit mining activity as revealed by archived avian gizzard contents.

PubMed

Bendell, L I

2011-02-15

Archived samples of blue grouse (Dendragapus obscurus) gizzard contents, inclusive of grit, collected yearly between 1959 and 1970 were analyzed for cadmium, lead, zinc, and copper content. Approximately halfway through the 12-year sampling period, an open-pit copper mine began activities, then ceased operations 2 years later. Thus the archived samples provided a unique opportunity to determine if avian gizzard contents, inclusive of grit, could reveal patterns in the anthropogenic deposition of trace metals associated with mining activities. Gizzard concentrations of cadmium and copper strongly coincided with the onset of opening and the closing of the pit mining activity. Gizzard zinc and lead demonstrated significant among year variation; however, maximum concentrations did not correlate to mining activity. The archived gizzard contents did provide a useful tool for documenting trends in metal depositional patterns related to an anthropogenic activity. Further, blue grouse ingesting grit particles during the time of active mining activity would have been exposed to toxicologically significant levels of cadmium. Gizzard lead concentrations were also of toxicological significance but not related to mining activity. This type of "pulse" toxic metal exposure as a consequence of open-pit mining activity would not necessarily have been revealed through a "snap-shot" of soil, plant or avian tissue trace metal analysis post-mining activity. Copyright © 2010 Elsevier B.V. All rights reserved.

[Development of pneumoconiosis and outsourcing work in peruvian miners].

PubMed

Cáceres-Mejía, Brenda; Mayta-Tristán, Percy; Pereyra-Elías, Reneé; Collantes, Héctor; Cáceres-Leturia, Walter

2015-10-01

The aim of this study is to evaluate the association between the time of outsourced work and the development of pneumoconiosis in Peruvian miners who attended the "Centro Nacional de Salud Ocupacional y Protección al Ambiente para la Salud" between 2008 and 2011. Retrospective case-control study. Cases were defined as workers diagnosed of pneumoconiosis under standardized criteria. Outsourced work was defined as the time (in months) of work in a company that does not own the primary mining project. The project owner company was registered in the Mining Companies Directory (Ministerio de Energía y Minas). We used multiple logistic regression with crude and adjusted ORs. The study comprised 391 cases and 1519 controls. In both groups, most of the study subjects had a level of education lower than complete high school and were born and currently lived in the Peruvian highlands. There was statistically significant association between more frequency of pneumoconiosis and working 10 or more years in an outsourced company (OR: 1.50; 95%CI: 1.05-1.14; p=0.026). Miners with pneumoconiosis were more likely not to have education (OR: 3.07; 95%CI: 1.55-6.08; p=0.001), be currently living at the Peruvian highlands (OR: 1.40; 95%CI: 1.10-1.78; p=0.007) and to have more than 20 years of underground work history (OR: 8.92; 95%CI: 4.53-18.25; p<0.001). A statistically significant association was found between pneumoconiosis and the time of outsourced work. Not having education, residing in the Peruvian highlands and the time of underground work were associated risk factors.

Static versus dynamic sampling for data mining

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

John, G.H.; Langley, P.

1996-12-31

As data warehouses grow to the point where one hundred gigabytes is considered small, the computational efficiency of data-mining algorithms on large databases becomes increasingly important. Using a sample from the database can speed up the datamining process, but this is only acceptable if it does not reduce the quality of the mined knowledge. To this end, we introduce the {open_quotes}Probably Close Enough{close_quotes} criterion to describe the desired properties of a sample. Sampling usually refers to the use of static statistical tests to decide whether a sample is sufficiently similar to the large database, in the absence of any knowledgemore » of the tools the data miner intends to use. We discuss dynamic sampling methods, which take into account the mining tool being used and can thus give better samples. We describe dynamic schemes that observe a mining tool`s performance on training samples of increasing size and use these results to determine when a sample is sufficiently large. We evaluate these sampling methods on data from the UCI repository and conclude that dynamic sampling is preferable.« less

Long-Term Changes In The Shallow Water Table In A Mining Area: The Lubin-Glogow Copper Region, Southwestern Poland

NASA Astrophysics Data System (ADS)

Bochenska, T.; Limisiewicz, P.; Loprawski, L.

1995-03-01

In regions of intense mining, shortages of water are common. Increased water demand is normally associated with industry in mining areas, and mine unwatering has negative effects on the natural groundwater balance. The study area occupies 3,300 square kilometers within the copper mining region of Lubin-Glogow, southwestern Poland. Pumping of groundwater to drain mines has created a cone of depression that underlies 2,500 square kilometers. The lowering of potentiometric surfaces has occurred in deep aquifers, which are isolated from the surface by thick confining units (loams and clays). Changes of hydraulic head in the shallow aquifer have not previously been observed. In this study, the authors analyzed the water-table changes in the shallow aquifer. The statistical analysis of the water table was based on two sets of water-level measurements in about 1,200 farm wells during dry seasons. The first set was done in the fall of 1986, the second in the fall of 1991. In addition to these measurements, multi-seasonal observations were made by the mining survey in several tens of wells. During five years, the head declined an average of 0.4 meter. Locally, the lowering was as great as five meters. The regional decline of head resulted in a loss of water resources about 2×108 cubic meters. Regionally, this loss is not directly related to the dewatering of copper mines. Locally, however, mining activity strongly influences the water table. The general trend of the decline is probably an effect of decreasing precipitation.

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.

Dispersion and bioaccumulation of elements from an open-pit olivine mine in Southwest Greenland assessed using lichens, seaweeds, mussels and fish.

PubMed

Søndergaard, Jens

2013-08-01

This study investigated dispersion and bioaccumulation of mining-related elements from an open-pit olivine mine at Seqi in Southwest Greenland (64° N) using lichens (Flavocetraria nivalis), seaweeds (Fucus vesiculosus), mussels (Mytilus edulis) and fish (Myoxocephalus scorpius). The mine operated between 2005 and 2009, and samples were taken every year within a monitoring area 0-17 km from the mine during the period 2004-2011. A total of 46 elements were analysed in the samples. After mining began, highly elevated metal concentrations, especially nickel (Ni), chromium (Cr), iron (Fe) and cobalt (Co), were observed in lichens relative to pre-mining levels (up to a factor of 130) caused by dust dispersion from the mining activity. Elevated metal concentrations could be measured in lichens in distances up to ~5 km from the mine/ore treatment facility. Moderately elevated concentrations of Ni and Cr (up to a factor of 7) were also observed in seaweeds and mussels but only in close vicinity (<1 km) to the mine. Analyses of fish showed no significant changes in element composition. After mine closure, the elevated metal concentrations in lichens, seaweeds and mussels decreased markedly, and in 2011, significantly elevated metal concentrations could only be measured in lichens and only within a distance of 1 km from the mine.

Calypso: a user-friendly web-server for mining and visualizing microbiome-environment interactions.

PubMed

Zakrzewski, Martha; Proietti, Carla; Ellis, Jonathan J; Hasan, Shihab; Brion, Marie-Jo; Berger, Bernard; Krause, Lutz

2017-03-01

Calypso is an easy-to-use online software suite that allows non-expert users to mine, interpret and compare taxonomic information from metagenomic or 16S rDNA datasets. Calypso has a focus on multivariate statistical approaches that can identify complex environment-microbiome associations. The software enables quantitative visualizations, statistical testing, multivariate analysis, supervised learning, factor analysis, multivariable regression, network analysis and diversity estimates. Comprehensive help pages, tutorials and videos are provided via a wiki page. The web-interface is accessible via http://cgenome.net/calypso/ . The software is programmed in Java, PERL and R and the source code is available from Zenodo ( https://zenodo.org/record/50931 ). The software is freely available for non-commercial users. l.krause@uq.edu.au. Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press.

Standard reference water samples for rare earth element determinations

USGS Publications Warehouse

Verplanck, P.L.; Antweiler, Ronald C.; Nordstrom, D. Kirk; Taylor, Howard E.

2001-01-01

Standard reference water samples (SRWS) were collected from two mine sites, one near Ophir, CO, USA and the other near Redding, CA, USA. The samples were filtered, preserved, and analyzed for rare earth element (REE) concentrations (La, Ce, Pr, Nd, Sm, Eu, Gd, Tb, Dy, Ho, Er, Tm, Yb, and Lu) by inductively coupled plasma-mass spectrometry (ICP-MS). These two samples were acid mine waters with elevated concentrations of REEs (0.45-161 ??g/1). Seventeen international laboratories participated in a 'round-robin' chemical analysis program, which made it possible to evaluate the data by robust statistical procedures that are insensitive to outliers. The resulting most probable values are reported. Ten to 15 of the participants also reported values for Ba, Y, and Sc. Field parameters, major ion, and other trace element concentrations, not subject to statistical evaluation, are provided.

AstroML: "better, faster, cheaper" towards state-of-the-art data mining and machine learning

NASA Astrophysics Data System (ADS)

Ivezic, Zeljko; Connolly, Andrew J.; Vanderplas, Jacob

2015-01-01

We present AstroML, a Python module for machine learning and data mining built on numpy, scipy, scikit-learn, matplotlib, and astropy, and distributed under an open license. AstroML contains a growing library of statistical and machine learning routines for analyzing astronomical data in Python, loaders for several open astronomical datasets (such as SDSS and other recent major surveys), and a large suite of examples of analyzing and visualizing astronomical datasets. AstroML is especially suitable for introducing undergraduate students to numerical research projects and for graduate students to rapidly undertake cutting-edge research. The long-term goal of astroML is to provide a community repository for fast Python implementations of common tools and routines used for statistical data analysis in astronomy and astrophysics (see http://www.astroml.org).

30 CFR 104.1 - Purpose and scope.

Code of Federal Regulations, 2010 CFR

2010-07-01

... Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR PATTERN OF VIOLATIONS PATTERN OF... whether a mine operator has established a pattern of significant and substantial (S&S) violations at a mine. It implements section 104(e) of the Federal Mine Safety and Health Act of 1977 (Act) by...

43 CFR 3420.1-4 - General requirements for land use planning.

Code of Federal Regulations, 2011 CFR

2011-10-01

... mining by other than underground mining techniques. (ii) For the purposes of this paragraph, any surface... techniques shall be deemed to have expressed a preference in favor of mining. Where a significant number of... underground mining techniques, that area shall be considered acceptable for further consideration only for...

43 CFR 3420.1-4 - General requirements for land use planning.

Code of Federal Regulations, 2013 CFR

2013-10-01

... mining by other than underground mining techniques. (ii) For the purposes of this paragraph, any surface... techniques shall be deemed to have expressed a preference in favor of mining. Where a significant number of... underground mining techniques, that area shall be considered acceptable for further consideration only for...

43 CFR 3420.1-4 - General requirements for land use planning.

Code of Federal Regulations, 2014 CFR

2014-10-01

... mining by other than underground mining techniques. (ii) For the purposes of this paragraph, any surface... techniques shall be deemed to have expressed a preference in favor of mining. Where a significant number of... underground mining techniques, that area shall be considered acceptable for further consideration only for...

43 CFR 3420.1-4 - General requirements for land use planning.

Code of Federal Regulations, 2012 CFR

2012-10-01

... mining by other than underground mining techniques. (ii) For the purposes of this paragraph, any surface... techniques shall be deemed to have expressed a preference in favor of mining. Where a significant number of... underground mining techniques, that area shall be considered acceptable for further consideration only for...

Deep data mining in a real space: Separation of intertwined electronic responses in a lightly doped BaFe 2As 2

DOE PAGES

Ziatdinov, Maxim; Maksov, Artem; Li, Li; ...

2016-10-25

Electronic interactions present in material compositions close to the superconducting dome play a key role in the manifestation of high-T c superconductivity. In many correlated electron systems, however, the parent or underdoped states exhibit strongly inhomogeneous electronic landscape at the nanoscale that may be associated with competing, coexisting, or intertwined chemical disorder, strain, magnetic, and structural order parameters. Here we demonstrate an approach based on a combination of scanning tunneling microscopy/spectroscopy and advanced statistical learning for an automatic separation and extraction of statistically significant electronic behaviors in the spin density wave regime of a lightly (~1%) gold-doped BaFe 2As 2.more » Lastly, we show that the decomposed STS spectral features have a direct relevance to fundamental physical properties of the system, such as SDW-induced gap, pseudogap-like state, and impurity resonance states.« less

Deep data mining in a real space: Separation of intertwined electronic responses in a lightly doped BaFe 2As 2

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

Ziatdinov, Maxim; Maksov, Artem; Li, Li

Electronic interactions present in material compositions close to the superconducting dome play a key role in the manifestation of high-T c superconductivity. In many correlated electron systems, however, the parent or underdoped states exhibit strongly inhomogeneous electronic landscape at the nanoscale that may be associated with competing, coexisting, or intertwined chemical disorder, strain, magnetic, and structural order parameters. Here we demonstrate an approach based on a combination of scanning tunneling microscopy/spectroscopy and advanced statistical learning for an automatic separation and extraction of statistically significant electronic behaviors in the spin density wave regime of a lightly (~1%) gold-doped BaFe 2As 2.more » Lastly, we show that the decomposed STS spectral features have a direct relevance to fundamental physical properties of the system, such as SDW-induced gap, pseudogap-like state, and impurity resonance states.« less

Seismic Parameters of Mining-Induced Aftershock Sequences for Re-entry Protocol Development

NASA Astrophysics Data System (ADS)

Vallejos, Javier A.; Estay, Rodrigo A.

2018-03-01

A common characteristic of deep mines in hard rock is induced seismicity. This results from stress changes and rock failure around mining excavations. Following large seismic events, there is an increase in the levels of seismicity, which gradually decay with time. Restricting access to areas of a mine for enough time to allow this decay of seismic events is the main approach in re-entry strategies. The statistical properties of aftershock sequences can be studied with three scaling relations: (1) Gutenberg-Richter frequency magnitude, (2) the modified Omori's law (MOL) for the temporal decay, and (3) Båth's law for the magnitude of the largest aftershock. In this paper, these three scaling relations, in addition to the stochastic Reasenberg-Jones model are applied to study the characteristic parameters of 11 large magnitude mining-induced aftershock sequences in four mines in Ontario, Canada. To provide guidelines for re-entry protocol development, the dependence of the scaling relation parameters on the magnitude of the main event are studied. Some relations between the parameters and the magnitude of the main event are found. Using these relationships and the scaling relations, a space-time-magnitude re-entry protocol is developed. These findings provide a first approximation to concise and well-justified guidelines for re-entry protocol development applicable to the range of mining conditions found in Ontario, Canada.

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.

PlanMine--a mineable resource of planarian biology and biodiversity.

PubMed

Brandl, Holger; Moon, HongKee; Vila-Farré, Miquel; Liu, Shang-Yun; Henry, Ian; Rink, Jochen C

2016-01-04

Planarian flatworms are in the midst of a renaissance as a model system for regeneration and stem cells. Besides two well-studied model species, hundreds of species exist worldwide that present a fascinating diversity of regenerative abilities, tissue turnover rates, reproductive strategies and other life history traits. PlanMine (http://planmine.mpi-cbg.de/) aims to accomplish two primary missions: First, to provide an easily accessible platform for sharing, comparing and value-added mining of planarian sequence data. Second, to catalyze the comparative analysis of the phenotypic diversity amongst planarian species. Currently, PlanMine houses transcriptomes independently assembled by our lab and community contributors. Detailed assembly/annotation statistics, a custom-developed BLAST viewer and easy export options enable comparisons at the contig and assembly level. Consistent annotation of all transcriptomes by an automated pipeline, the integration of published gene expression information and inter-relational query tools provide opportunities for mining planarian gene sequences and functions. For inter-species comparisons, we include transcriptomes of, so far, six planarian species, along with images, expert-curated information on their biology and pre-calculated cross-species sequence homologies. PlanMine is based on the popular InterMine system in order to make the rich biology of planarians accessible to the general life sciences research community. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

The synergic role of sociotechnical and personal characteristics on work injuries in mines.

PubMed

Paul, P S; Maiti, J

2008-05-01

Occupational injuries in mines are attributed to many factors. In this study, an attempt was made to identify the various factors related to work injuries in mines and to estimate their effects on work injuries to mine workers. An accident path model was developed to estimate the pattern and strength of relationships amongst the personal and sociotechnical variables in accident/injury occurrences. The input data for the model were the correlation matrix of 18 variables, which were collected from the case study mines. The case study results showed that there are sequential interactions amongst the sociotechnical and personal factors leading to accidents/injuries in mines. Amongst the latent endogenous constructs, job dissatisfaction and safe work behaviour show a significant positive and negative direct relationship with work injury, respectively. However, the construct safety environment has a significant negative indirect relationship with work injury. The safety environment is negatively affected by work hazards and positively affected by social support. The safety environment also shows a significant negative relationship with job stress and job dissatisfaction. However, negative personality has no significant direct or indirect effect on work injury, but it has a significant negative relationship with safe work behaviour. The endogenous construct negative personality is positively influenced by job stress and negatively influenced by social support.

Fusing Data Mining, Machine Learning and Traditional Statistics to Detect Biomarkers Associated with Depression

PubMed Central

Dipnall, Joanna F.

2016-01-01

Background Atheoretical large-scale data mining techniques using machine learning algorithms have promise in the analysis of large epidemiological datasets. This study illustrates the use of a hybrid methodology for variable selection that took account of missing data and complex survey design to identify key biomarkers associated with depression from a large epidemiological study. Methods The study used a three-step methodology amalgamating multiple imputation, a machine learning boosted regression algorithm and logistic regression, to identify key biomarkers associated with depression in the National Health and Nutrition Examination Study (2009–2010). Depression was measured using the Patient Health Questionnaire-9 and 67 biomarkers were analysed. Covariates in this study included gender, age, race, smoking, food security, Poverty Income Ratio, Body Mass Index, physical activity, alcohol use, medical conditions and medications. The final imputed weighted multiple logistic regression model included possible confounders and moderators. Results After the creation of 20 imputation data sets from multiple chained regression sequences, machine learning boosted regression initially identified 21 biomarkers associated with depression. Using traditional logistic regression methods, including controlling for possible confounders and moderators, a final set of three biomarkers were selected. The final three biomarkers from the novel hybrid variable selection methodology were red cell distribution width (OR 1.15; 95% CI 1.01, 1.30), serum glucose (OR 1.01; 95% CI 1.00, 1.01) and total bilirubin (OR 0.12; 95% CI 0.05, 0.28). Significant interactions were found between total bilirubin with Mexican American/Hispanic group (p = 0.016), and current smokers (p<0.001). Conclusion The systematic use of a hybrid methodology for variable selection, fusing data mining techniques using a machine learning algorithm with traditional statistical modelling, accounted for missing data and complex survey sampling methodology and was demonstrated to be a useful tool for detecting three biomarkers associated with depression for future hypothesis generation: red cell distribution width, serum glucose and total bilirubin. PMID:26848571

Fusing Data Mining, Machine Learning and Traditional Statistics to Detect Biomarkers Associated with Depression.

PubMed

Dipnall, Joanna F; Pasco, Julie A; Berk, Michael; Williams, Lana J; Dodd, Seetal; Jacka, Felice N; Meyer, Denny

2016-01-01

Atheoretical large-scale data mining techniques using machine learning algorithms have promise in the analysis of large epidemiological datasets. This study illustrates the use of a hybrid methodology for variable selection that took account of missing data and complex survey design to identify key biomarkers associated with depression from a large epidemiological study. The study used a three-step methodology amalgamating multiple imputation, a machine learning boosted regression algorithm and logistic regression, to identify key biomarkers associated with depression in the National Health and Nutrition Examination Study (2009-2010). Depression was measured using the Patient Health Questionnaire-9 and 67 biomarkers were analysed. Covariates in this study included gender, age, race, smoking, food security, Poverty Income Ratio, Body Mass Index, physical activity, alcohol use, medical conditions and medications. The final imputed weighted multiple logistic regression model included possible confounders and moderators. After the creation of 20 imputation data sets from multiple chained regression sequences, machine learning boosted regression initially identified 21 biomarkers associated with depression. Using traditional logistic regression methods, including controlling for possible confounders and moderators, a final set of three biomarkers were selected. The final three biomarkers from the novel hybrid variable selection methodology were red cell distribution width (OR 1.15; 95% CI 1.01, 1.30), serum glucose (OR 1.01; 95% CI 1.00, 1.01) and total bilirubin (OR 0.12; 95% CI 0.05, 0.28). Significant interactions were found between total bilirubin with Mexican American/Hispanic group (p = 0.016), and current smokers (p<0.001). The systematic use of a hybrid methodology for variable selection, fusing data mining techniques using a machine learning algorithm with traditional statistical modelling, accounted for missing data and complex survey sampling methodology and was demonstrated to be a useful tool for detecting three biomarkers associated with depression for future hypothesis generation: red cell distribution width, serum glucose and total bilirubin.

Search for Long Period Solar Normal Modes in Ambient Seismic Noise

NASA Astrophysics Data System (ADS)

Caton, R.; Pavlis, G. L.

2016-12-01

We search for evidence of solar free oscillations (normal modes) in long period seismic data through multitaper spectral analysis of array stacks. This analysis is similar to that of Thomson & Vernon (2015), who used data from the most quiet single stations of the global seismic network. Our approach is to use stacks of large arrays of noisier stations to reduce noise. Arrays have the added advantage of permitting the use of nonparametic statistics (jackknife errors) to provide objective error estimates. We used data from the Transportable Array, the broadband borehole array at Pinyon Flat, and the 3D broadband array in Homestake Mine in Lead, SD. The Homestake Mine array has 15 STS-2 sensors deployed in the mine that are extremely quiet at long periods due to stable temperatures and stable piers anchored to hard rock. The length of time series used ranged from 50 days to 85 days. We processed the data by low-pass filtering with a corner frequency of 10 mHz, followed by an autoregressive prewhitening filter and median stack. We elected to use the median instead of the mean in order to get a more robust stack. We then used G. Prieto's mtspec library to compute multitaper spectrum estimates on the data. We produce delete-one jackknife error estimates of the uncertainty at each frequency by computing median stacks of all data with one station removed. The results from the TA data show tentative evidence for several lines between 290 μHz and 400 μHz, including a recurring line near 379 μHz. This 379 μHz line is near the Earth mode 0T2 and the solar mode 5g5, suggesting that 5g5 could be coupling into the Earth mode. Current results suggest more statistically significant lines may be present in Pinyon Flat data, but additional processing of the data is underway to confirm this observation.

State summaries: Kentucky

USGS Publications Warehouse

Greb, S.F.; Anderson, W.H.

2006-01-01

Kentucky mines coal, limestone, clay, sand and gravel. Coal mining operations are carried out mainly in the Western Kentucky Coal Field and the Eastern Kentucky Coal field. As to nonfuel minerals, Mississippian limestones are mined in the Mississippian Plateaus Region and along Pine Mountain in southeastern Kentucky. Ordovician and Silurian limestones are mined from the central part of the state. Clay minerals that are mined in the state include common clay, ceramic and ball clays, refractory clay and shale. Just like in 2004, mining activities in the state remain significant.

Radiographic outcomes among South African coal miners.

PubMed

Naidoo, Rajen N; Robins, Thomas G; Solomon, A; White, Neil; Franzblau, Alfred

2004-10-01

This study, the first to document the prevalence of pneumoconiosis among a living South African coal mining cohort, describes dose-response relationships between coal workers' pneumoconiosis and respirable dust exposure, and relationships between pneumoconiosis and both lung function deterioration and respiratory symptoms. A total of 684 current miners and 188 ex-miners from three bituminous-coal mines in Mpumalanga, South Africa, was studied. Chest radiographs were read according to the International Labour Organization (ILO) classification by two experienced readers, one an accredited National Institute for Occupational Safety and Health (NIOSH) "B" reader. Interviews were conducted to assess symptoms, work histories (also obtained from company records), smoking, and other risk factors. Spirometry was performed by trained technicians. Cumulative respirable dust exposure (CDE) estimates were constructed from historical company-collected sampling and researcher-collected personal dust measurements. kappa-Statistics compared the radiographic outcomes predicted by the two readers. An average profusion score was used in the analysis for the outcomes of interest. Because of possible confounding by employment status, most analyses were stratified on current and ex-miner status. The overall prevalence of pneumoconiosis was low (2%-4%). The degree of agreement between the two readers for profusion was moderate to high (kappa=0.58). A significant association (P<0.001) and trend (P<0.001) was seen for pneumoconiosis with increasing categories of CDE among current miners only. A significant (P<0.0001) additional 58 mg-years/m3 CDE was seen among those with pneumoconiosis compared to those without. CDE contributed to a statistically significant 0.19% and 0.11% greater decline in the percent predicted 1-second forced expiration volume (FEV1) and forced vital capacity (FVC), respectively, among current miners with pneumoconiosis than among those without. Logistic regression models showed no significant relationships between pneumoconiosis and symptoms. The overall prevalence of pneumoconiosis, although significantly associated with CDE, was low. The presence of pneumoconiosis is associated with meaningful health effects, including deterioration in lung function. Intervention measures that control exposure are indicated, to reduce these functional effects.

DASS: efficient discovery and p-value calculation of substructures in unordered data.

PubMed

Hollunder, Jens; Friedel, Maik; Beyer, Andreas; Workman, Christopher T; Wilhelm, Thomas

2007-01-01

Pattern identification in biological sequence data is one of the main objectives of bioinformatics research. However, few methods are available for detecting patterns (substructures) in unordered datasets. Data mining algorithms mainly developed outside the realm of bioinformatics have been adapted for that purpose, but typically do not determine the statistical significance of the identified patterns. Moreover, these algorithms do not exploit the often modular structure of biological data. We present the algorithm DASS (Discovery of All Significant Substructures) that first identifies all substructures in unordered data (DASS(Sub)) in a manner that is especially efficient for modular data. In addition, DASS calculates the statistical significance of the identified substructures, for sets with at most one element of each type (DASS(P(set))), or for sets with multiple occurrence of elements (DASS(P(mset))). The power and versatility of DASS is demonstrated by four examples: combinations of protein domains in multi-domain proteins, combinations of proteins in protein complexes (protein subcomplexes), combinations of transcription factor target sites in promoter regions and evolutionarily conserved protein interaction subnetworks. The program code and additional data are available at http://www.fli-leibniz.de/tsb/DASS

Geochemical investigations and interim recommendations for priority abandoned mine sites on U.S.D.A. Forest Service lands, Mineral Creek watershed, San Juan County, Colorado

USGS Publications Warehouse

Nash, J.T.

1999-01-01

Field observations, sampling of mine dumps and mine drainage waters, and laboratory studies of dump materials have been made at mining areas deemed to be on public lands administered by the USDA Forest Service in the Mineral Creek watershed. Results of chemical analyses of dump materials, leachates of those materials, and of surface waters draining mines or dumps provide indications of where acid is generated or consumed, and what metals are mobilized below mines or dumps. Information on 25 sites is reviewed and reclamation priorities are ranked into four classes (high, medium, low priority, or no work required). The western side of the upper Animas watershed (the Mineral Creek watershed) has a history of mining and prospecting for about 130 years. The intensity of miningrelated disturbance is higher than in most parts of the San Juan Mountains region, but actually is much less than the eastern half of the watershed (US BLM lands) and none of the mines moved millions of tons of rock and ore as in some of the eastern mines. The majority of the roughly one thousand mining sites on the USFS lands are very small (less than 100 tons or 70 cubic yards of dump material), are more than 2 miles from a major stream, or are so inaccessible as to prohibit reclamation. Twenty five sites have been considered by others to have significant size and potential for significant environmental degradation. These most significant mining areas were evaluated by multiple criteria, including tendency to generate acid or liberate toxic metals, observed acidic pH or dead vegetation (?kill zones?) below dumps or adits, potential mobility of metals, and likelihood of transport into streams of the watershed. In the author?s opinion, no single measurable parameter, such as metal concentration, is reliable for ranking significance or feasibility of reclamation. Rather, subjective estimates are required to evaluate combinations of, or interactions among, several parameters. The most subjective estimate in ranking feasibility of reclamation is the amount of natural and mine-related contamination at each mining area. Mitigation of natural contributions at mines or unmined areas is beyond the scope of these Abandoned Mine Lands (AML) investigations, but must be considered when planning reclamation. Available information for the 25 problem sites is adequate for ranking, but at some sites additional information on groundwater conditions is needed for a more reliable ranking and evaluation of reclamation methods.

Spectral signature verification using statistical analysis and text mining

NASA Astrophysics Data System (ADS)

DeCoster, Mallory E.; Firpi, Alexe H.; Jacobs, Samantha K.; Cone, Shelli R.; Tzeng, Nigel H.; Rodriguez, Benjamin M.

2016-05-01

In the spectral science community, numerous spectral signatures are stored in databases representative of many sample materials collected from a variety of spectrometers and spectroscopists. Due to the variety and variability of the spectra that comprise many spectral databases, it is necessary to establish a metric for validating the quality of spectral signatures. This has been an area of great discussion and debate in the spectral science community. This paper discusses a method that independently validates two different aspects of a spectral signature to arrive at a final qualitative assessment; the textual meta-data and numerical spectral data. Results associated with the spectral data stored in the Signature Database1 (SigDB) are proposed. The numerical data comprising a sample material's spectrum is validated based on statistical properties derived from an ideal population set. The quality of the test spectrum is ranked based on a spectral angle mapper (SAM) comparison to the mean spectrum derived from the population set. Additionally, the contextual data of a test spectrum is qualitatively analyzed using lexical analysis text mining. This technique analyzes to understand the syntax of the meta-data to provide local learning patterns and trends within the spectral data, indicative of the test spectrum's quality. Text mining applications have successfully been implemented for security2 (text encryption/decryption), biomedical3 , and marketing4 applications. The text mining lexical analysis algorithm is trained on the meta-data patterns of a subset of high and low quality spectra, in order to have a model to apply to the entire SigDB data set. The statistical and textual methods combine to assess the quality of a test spectrum existing in a database without the need of an expert user. This method has been compared to other validation methods accepted by the spectral science community, and has provided promising results when a baseline spectral signature is present for comparison. The spectral validation method proposed is described from a practical application and analytical perspective.

[Statistical prediction methods in violence risk assessment and its application].

PubMed

Liu, Yuan-Yuan; Hu, Jun-Mei; Yang, Min; Li, Xiao-Song

2013-06-01

It is an urgent global problem how to improve the violence risk assessment. As a necessary part of risk assessment, statistical methods have remarkable impacts and effects. In this study, the predicted methods in violence risk assessment from the point of statistics are reviewed. The application of Logistic regression as the sample of multivariate statistical model, decision tree model as the sample of data mining technique, and neural networks model as the sample of artificial intelligence technology are all reviewed. This study provides data in order to contribute the further research of violence risk assessment.

[The effects of work in an air-conditioned cabin and stay in a resting chamber on blood pressure and heart rate of operators employed in deep copper mines].

PubMed

Borodulin-Nadzieja, L; Janocha, A; Pietraszkiewicz, T; Salomon, E; Stańda, M

2001-01-01

This paper is part of a wider comparative study of the heart rate, blood pressure, external and core temperature in operators of self-propelled mining machines with and without air-conditioning cabins. Two groups, each of ten operators, characterised by the similar age and duration of employment, stayed for 20 min a specially prepared resting chamber with much more advantageous microclimatic conditions. The results of our examinations (Holter heart rate and continuous blood pressure recordings, external and core temperature measurements) revealed that during the work (particularly during the increased work-load) all parameters recorded were significantly lower in air-conditioning cabins as compared with the group working without air-condition. In both groups, a complete restitution of the heart rate and blood pressure was observed after a 20-min stay in the resting chamber. During the work, a statistically significant increase in the external temperature was found in both groups of operators, whereas the increase in the core temperature was observed only in operators working without air-condition. After a 20-min stay in the resting chamber, a complete return to the normal temperature was noted only in operators working in air-conditioned cabins.

High lead exposure and auditory sensory-neural function in Andean children.

PubMed Central

Counter, S A; Vahter, M; Laurell, G; Buchanan, L H; Ortega, F; Skerfving, S

1997-01-01

We investigated blood lead (B-Pb) and mercury (B-Hg) levels and auditory sensory-neural function in 62 Andean school children living in a Pb-contaminated area of Ecuador and 14 children in a neighboring gold mining area with no known Pb exposure. The median B-Pb level for 62 children in the Pb-exposed group was 52.6 micrograms/dl (range 9.9-110.0 micrograms/dl) compared with 6.4 micrograms/dl (range 3.9-12.0 micrograms/dl) for the children in the non-Pb exposed group; the differences were statistically significant (p < 0.001). Auditory thresholds for the Pb-exposed group were normal at the pure tone frequencies of 0.25-8 kHz over the entire range of B-Pb levels, Auditory brain stem response tests in seven children with high B-Pb levels showed normal absolute peak and interpeak latencies. The median B-Hg levels were 0.16 micrograms/dl (range 0.04-0.58 micrograms/dl) for children in the Pb-exposed group and 0.22 micrograms/dl (range 0.1-0.44 micrograms/dl) for children in the non-Pb exposed gold mining area, and showed no significant relationship to auditory function. Images Figure 1. Figure 3. A Figure 3. B PMID:9222138

Estimating Morning Change in Land Surface Temperature from MODIS Day/Night Observations: Applications for Surface Energy Balance Modeling.

PubMed

Hain, Christopher R; Anderson, Martha C

2017-10-16

Observations of land surface temperature (LST) are crucial for the monitoring of surface energy fluxes from satellite. Methods that require high temporal resolution LST observations (e.g., from geostationary orbit) can be difficult to apply globally because several geostationary sensors are required to attain near-global coverage (60°N to 60°S). While these LST observations are available from polar-orbiting sensors, providing global coverage at higher spatial resolutions, the temporal sampling (twice daily observations) can pose significant limitations. For example, the Atmosphere Land Exchange Inverse (ALEXI) surface energy balance model, used for monitoring evapotranspiration and drought, requires an observation of the morning change in LST - a quantity not directly observable from polar-orbiting sensors. Therefore, we have developed and evaluated a data-mining approach to estimate the mid-morning rise in LST from a single sensor (2 observations per day) of LST from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor on the Aqua platform. In general, the data-mining approach produced estimates with low relative error (5 to 10%) and statistically significant correlations when compared against geostationary observations. This approach will facilitate global, near real-time applications of ALEXI at higher spatial and temporal coverage from a single sensor than currently achievable with current geostationary datasets.

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.

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. (Principal Investigator); Russell, O. R.; Amato, R. V.

1973-01-01

The author has identified the following significant results. The utility of ERTS-1/high altitude aircraft imagery to detect underground mine hazards is strongly suggested. A 1:250,000 scale mined lands map of the Vincennes Quadrangle, Indiana has been prepared. This map is a prototype for a national mined lands inventory and will be distributed to State and Federal offices.

Mining and Risk of Tuberculosis in Sub-Saharan Africa

PubMed Central

Basu, Sanjay; McKee, Martin; Lurie, Mark

2011-01-01

Objectives. We estimated the relationship between mining and tuberculosis (TB) among countries in sub-Saharan Africa. Methods. We used multivariate regression to estimate the contribution of mining activity to TB incidence, prevalence, and mortality, as well as rates of TB among people living with HIV, with control for economic, health system, and population confounders. Results. Mining production was associated with higher population TB incidence rates (adjusted b = 0.093; 95% confidence interval [CI] = 0.067, 0.120; with an increase of mining production of 1 SD corresponding to about 33% higher TB incidence or 760 000 more incident cases), after adjustment for economic and population controls. Similar results were observed for TB prevalence and mortality, as well as with alternative measures of mining activity. Independent of HIV, there were significant associations between mining production and TB incidence in countries with high HIV prevalence (≥ 4% antenatal HIV prevalence; HIV-adjusted B = 0.066; 95% CI = 0.050, 0.082) and between log gold mining production and TB incidence in all studied countries (HIV-adjusted B = 0.053; 95% CI = 0.032, 0.073). Conclusions. Mining is a significant determinant of countrywide variation in TB among sub-Saharan African nations. Comprehensive TB control strategies should explicitly address the role of mining activity and environments in the epidemic. PMID:20516372

Mining and risk of tuberculosis in sub-Saharan Africa.

PubMed

Stuckler, David; Basu, Sanjay; McKee, Martin; Lurie, Mark

2011-03-01

We estimated the relationship between mining and tuberculosis (TB) among countries in sub-Saharan Africa. We used multivariate regression to estimate the contribution of mining activity to TB incidence, prevalence, and mortality, as well as rates of TB among people living with HIV, with control for economic, health system, and population confounders. Mining production was associated with higher population TB incidence rates (adjusted b = 0.093; 95% confidence interval [CI] = 0.067, 0.120; with an increase of mining production of 1 SD corresponding to about 33% higher TB incidence or 760,000 more incident cases), after adjustment for economic and population controls. Similar results were observed for TB prevalence and mortality, as well as with alternative measures of mining activity. Independent of HIV, there were significant associations between mining production and TB incidence in countries with high HIV prevalence (≥ 4% antenatal HIV prevalence; HIV-adjusted B = 0.066; 95% CI = 0.050, 0.082) and between log gold mining production and TB incidence in all studied countries (HIV-adjusted B = 0.053; 95% CI = 0.032, 0.073). Mining is a significant determinant of countrywide variation in TB among sub-Saharan African nations. Comprehensive TB control strategies should explicitly address the role of mining activity and environments in the epidemic.

Possible health effects of living in proximity to mining sites near Potosí, Bolivia.

PubMed

Farag, Sara; Das, Riva; Strosnider, William H J; Wilson, Robin Taylor

2015-05-01

The goal of this study was to determine the health effects of living downstream from mines in the Potosí region of Bolivia. Histories, physical examinations, and urinalyses were completed on adults recruited from mining and nonmining villages in Bolivia. Blood concentrations of Cd, Hg, and Pb were determined in a subset of participants. Multiple logistic regression analyses were performed. Mining region participants had significantly higher frequencies of hypertension, hematuria, and ketonuria. Hematuria was significantly elevated among those watering livestock downstream from mines and eating grains from their own farm (odds ratio = 4.3; 95% confidence interval, 1.1 to 17.7). Significantly higher blood concentrations of Pb were observed in a subsample of participants with hematuria (4.80 μg/dL vs 10.91 μg/dL; P = 0.026). Efforts to abate environmental exposure to toxic metals seem warranted.

Unionism and Productivity in West Virginia Coal Mining.

ERIC Educational Resources Information Center

Boal, William M.

1990-01-01

This study presents econometric estimates of the effects of unionism on productivity in 83 West Virginia coal mines in the early 1920s. Results show that unionism significantly reduced productivity at small mines but not at large mines. The author ascribes this effect to systematic differences between small and large operations in the quality of…

Atmospheric particulate matter size distribution and concentration in West Virginia coal mining and non-mining areas.

PubMed

Kurth, Laura M; McCawley, Michael; Hendryx, Michael; Lusk, Stephanie

2014-07-01

People who live in Appalachian areas where coal mining is prominent have increased health problems compared with people in non-mining areas of Appalachia. Coal mines and related mining activities result in the production of atmospheric particulate matter (PM) that is associated with human health effects. There is a gap in research regarding particle size concentration and distribution to determine respiratory dose around coal mining and non-mining areas. Mass- and number-based size distributions were determined with an Aerodynamic Particle Size and Scanning Mobility Particle Sizer to calculate lung deposition around mining and non-mining areas of West Virginia. Particle number concentrations and deposited lung dose were significantly greater around mining areas compared with non-mining areas, demonstrating elevated risks to humans. The greater dose was correlated with elevated disease rates in the West Virginia mining areas. Number concentrations in the mining areas were comparable to a previously documented urban area where number concentration was associated with respiratory and cardiovascular disease.

Identification of common, unique and polymorphic microsatellites among 73 cyanobacterial genomes.

PubMed

Kabra, Ritika; Kapil, Aditi; Attarwala, Kherunnisa; Rai, Piyush Kant; Shanker, Asheesh

2016-04-01

Microsatellites also known as Simple Sequence Repeats are short tandem repeats of 1-6 nucleotides. These repeats are found in coding as well as non-coding regions of both prokaryotic and eukaryotic genomes and play a significant role in the study of gene regulation, genetic mapping, DNA fingerprinting and evolutionary studies. The availability of 73 complete genome sequences of cyanobacteria enabled us to mine and statistically analyze microsatellites in these genomes. The cyanobacterial microsatellites identified through bioinformatics analysis were stored in a user-friendly database named CyanoSat, which is an efficient data representation and query system designed using ASP.net. The information in CyanoSat comprises of perfect, imperfect and compound microsatellites found in coding, non-coding and coding-non-coding regions. Moreover, it contains PCR primers with 200 nucleotides long flanking region. The mined cyanobacterial microsatellites can be freely accessed at www.compubio.in/CyanoSat/home.aspx. In addition to this 82 polymorphic, 13,866 unique and 2390 common microsatellites were also detected. These microsatellites will be useful in strain identification and genetic diversity studies of cyanobacteria.

Discovering Knowledge from AIS Database for Application in VTS

NASA Astrophysics Data System (ADS)

Tsou, Ming-Cheng

The widespread use of the Automatic Identification System (AIS) has had a significant impact on maritime technology. AIS enables the Vessel Traffic Service (VTS) not only to offer commonly known functions such as identification, tracking and monitoring of vessels, but also to provide rich real-time information that is useful for marine traffic investigation, statistical analysis and theoretical research. However, due to the rapid accumulation of AIS observation data, the VTS platform is often unable quickly and effectively to absorb and analyze it. Traditional observation and analysis methods are becoming less suitable for the modern AIS generation of VTS. In view of this, we applied the same data mining technique used for business intelligence discovery (in Customer Relation Management (CRM) business marketing) to the analysis of AIS observation data. This recasts the marine traffic problem as a business-marketing problem and integrates technologies such as Geographic Information Systems (GIS), database management systems, data warehousing and data mining to facilitate the discovery of hidden and valuable information in a huge amount of observation data. Consequently, this provides the marine traffic managers with a useful strategic planning resource.

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.

Spatial characterization, risk assessment, and statistical source identification of the dissolved trace elements in the Ganjiang River-feeding tributary of the Poyang Lake, China.

PubMed

Zhang, Hua; Jiang, Yinghui; Wang, Min; Wang, Peng; Shi, Guangxun; Ding, Mingjun

2017-01-01

Surface water samples were collected from 20 sampling sites throughout the Ganjiang River during pre-monsoon, monsoon, and post-monsoon seasons, and the concentrations of dissolved trace elements were determined by inductively coupled plasma-mass spectrometry (ICP-MS) for the spatial and seasonal variations, risk assessment, source identification, and categorization for risk area. The result demonstrated that concentrations of the elements exhibited significant seasonality. The high total element concentrations were detected at sites close to the intensive mining and urban activities. The concentrations of the elements were under the permissible limits as prescribed by related standards with a few exceptions. The most of heavy metal pollution index (HPI) values were lower than the critical index limit, indicating the basically clean water used as habitat for aquatic life. As was identified as the priority pollutant of non-carcinogenic and carcinogenic concerns, and the inhabitants ingesting the surface water at particular site might be subjected to the integrated health risks for exposure to the mixed trace elements. Multivariate statistical analyses confirmed that Zn, As, Cd, and Tl were derived from mining and urban activities; V, Cd, and Pb exhibited mixed origin; and Co, Ni, and Cu mainly resulted from natural processes. Three categorized risk areas corresponded to high, moderate, and low risks, respectively. As a whole, the upstream of the Ganjiang River was identified as the high-risk area relatively.

Tobacco use, oral cancer screening, and oral disease burden in Indian women.

PubMed

Joseph, Immanuel; Rooban, Thavarajah; Ranganathan, Kannan

2017-01-01

India lacks data on national level adaptation of oral cancer screening measures and burden of oral diseases. We intend to address the issue through a secondary data analysis of existing data and reports. Data were acquired from the National Family Health Survey-4 (2015-2016). Of the 699,686 responses, representing 99% of India's women population living in all of India, the following data from the age group of 15-49 years were mined - any tobacco use, desire to quit tobacco use, and oral cavity screening for cancers. Data from Central Health Intelligence Bureau 2016 was used to identify population served by dentists in each state. The state-level data of the District Level Household and Facility Survey-4 (2012-2013) were mined for household population having symptoms of chronic illness including mouth/dental illness persisting for more than 1 month and had sought treatment. SPSS version 20; Descriptive statistics for values in proportions; Pearson's correlation test assessed between the various factors. Tobacco use in any form was highly prevalent among the North Eastern states, and there was also a lack of willingness to quit the habit. There was unequal distribution of dentists in different states. No significant statistical correlation was found between the proportions. There is disparity existing in treating seeking behavior of the general population as well as the need for dental treatment. The skewedness in dentists' distribution among the nation as compared with oral burden of diseases needs to be correlated before oral health policies are planned.

An Investigation of Organic and Inorganic Mercury Exposure and Blood Pressure in a Small-Scale Gold Mining Community in Ghana.

PubMed

Rajaee, Mozhgon; Sánchez, Brisa N; Renne, Elisha P; Basu, Niladri

2015-08-21

There is increasing concern about the cardiovascular effects of mercury (Hg) exposure, and that organic methylmercury and inorganic Hg(2+) may affect the cardiovascular system and blood pressure differentially. In small-scale gold mining communities where inorganic, elemental Hg exposures are high, little is known about the effects of Hg on blood pressure. In 2011, we assessed the relationship between Hg exposure and blood pressure (BP) in a cross-sectional study of adults from a small-scale gold mining community, Kejetia, and subsistence farming community, Gorogo, in Ghana's Upper East Region. Participants' resting heart rate and BP were measured, and hair and urine samples were provided to serve as biomarkers of organic and inorganic Hg exposure, respectively. Participants included 70 miners and 26 non-miners from Kejetia and 75 non-miners from Gorogo. Total specific gravity-adjusted urinary and hair Hg was higher among Kejetia miners than Kejetia non-miners and Gorogo participants (median urinary Hg: 5.17, 1.18, and 0.154 µg/L, respectively; hair Hg: 0.945, 0.419, and 0.181 µg/g, respectively). Hypertension was prevalent in 17.7% of Kejetia and 21.3% of Gorogo participants. Urinary and hair Hg were not significantly associated with systolic or diastolic BP for Kejetia or Gorogo participants while adjusting for sex, age, and smoking status. Although our results follow trends seen in other studies, the associations were not of statistical significance. Given the unique study population and high exposures to inorganic Hg, the work contained here will help increase our understanding of the cardiovascular effects of Hg.

An Investigation of Organic and Inorganic Mercury Exposure and Blood Pressure in a Small-Scale Gold Mining Community in Ghana

PubMed Central

Rajaee, Mozhgon; Sánchez, Brisa N.; Renne, Elisha P.; Basu, Niladri

2015-01-01

There is increasing concern about the cardiovascular effects of mercury (Hg) exposure, and that organic methylmercury and inorganic Hg2+ may affect the cardiovascular system and blood pressure differentially. In small-scale gold mining communities where inorganic, elemental Hg exposures are high, little is known about the effects of Hg on blood pressure. In 2011, we assessed the relationship between Hg exposure and blood pressure (BP) in a cross-sectional study of adults from a small-scale gold mining community, Kejetia, and subsistence farming community, Gorogo, in Ghana’s Upper East Region. Participants’ resting heart rate and BP were measured, and hair and urine samples were provided to serve as biomarkers of organic and inorganic Hg exposure, respectively. Participants included 70 miners and 26 non-miners from Kejetia and 75 non-miners from Gorogo. Total specific gravity-adjusted urinary and hair Hg was higher among Kejetia miners than Kejetia non-miners and Gorogo participants (median urinary Hg: 5.17, 1.18, and 0.154 µg/L, respectively; hair Hg: 0.945, 0.419, and 0.181 µg/g, respectively). Hypertension was prevalent in 17.7% of Kejetia and 21.3% of Gorogo participants. Urinary and hair Hg were not significantly associated with systolic or diastolic BP for Kejetia or Gorogo participants while adjusting for sex, age, and smoking status. Although our results follow trends seen in other studies, the associations were not of statistical significance. Given the unique study population and high exposures to inorganic Hg, the work contained here will help increase our understanding of the cardiovascular effects of Hg. PMID:26308023

Long-range prediction of Indian summer monsoon rainfall using data mining and statistical approaches

NASA Astrophysics Data System (ADS)

H, Vathsala; Koolagudi, Shashidhar G.

2017-10-01

This paper presents a hybrid model to better predict Indian summer monsoon rainfall. The algorithm considers suitable techniques for processing dense datasets. The proposed three-step algorithm comprises closed itemset generation-based association rule mining for feature selection, cluster membership for dimensionality reduction, and simple logistic function for prediction. The application of predicting rainfall into flood, excess, normal, deficit, and drought based on 36 predictors consisting of land and ocean variables is presented. Results show good accuracy in the considered study period of 37years (1969-2005).

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.

Automatic detection of adverse events to predict drug label changes using text and data mining techniques.

PubMed

Gurulingappa, Harsha; Toldo, Luca; Rajput, Abdul Mateen; Kors, Jan A; Taweel, Adel; Tayrouz, Yorki

2013-11-01

The aim of this study was to assess the impact of automatically detected adverse event signals from text and open-source data on the prediction of drug label changes. Open-source adverse effect data were collected from FAERS, Yellow Cards and SIDER databases. A shallow linguistic relation extraction system (JSRE) was applied for extraction of adverse effects from MEDLINE case reports. Statistical approach was applied on the extracted datasets for signal detection and subsequent prediction of label changes issued for 29 drugs by the UK Regulatory Authority in 2009. 76% of drug label changes were automatically predicted. Out of these, 6% of drug label changes were detected only by text mining. JSRE enabled precise identification of four adverse drug events from MEDLINE that were undetectable otherwise. Changes in drug labels can be predicted automatically using data and text mining techniques. Text mining technology is mature and well-placed to support the pharmacovigilance tasks. Copyright © 2013 John Wiley & Sons, Ltd.

Data mining: comparing the empiric CFS to the Canadian ME/CFS case definition.

PubMed

Jason, Leonard A; Skendrovic, Beth; Furst, Jacob; Brown, Abigail; Weng, Angela; Bronikowski, Christine

2012-01-01

This article contrasts two case definitions for myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS). We compared the empiric CFS case definition (Reeves et al., 2005) and the Canadian ME/CFS clinical case definition (Carruthers et al., 2003) with a sample of individuals with CFS versus those without. Data mining with decision trees was used to identify the best items to identify patients with CFS. Data mining is a statistical technique that was used to help determine which of the survey questions were most effective for accurately classifying cases. The empiric criteria identified about 79% of patients with CFS and the Canadian criteria identified 87% of patients. Items identified by the Canadian criteria had more construct validity. The implications of these findings are discussed. © 2011 Wiley Periodicals, Inc.

Agile Text Mining for the 2014 i2b2/UTHealth Cardiac Risk Factors Challenge

PubMed Central

Cormack, James; Nath, Chinmoy; Milward, David; Raja, Kalpana; Jonnalagadda, Siddhartha R

2016-01-01

This paper describes the use of an agile text mining platform (Linguamatics’ Interactive Information Extraction Platform, I2E) to extract document-level cardiac risk factors in patient records as defined in the i2b2/UTHealth 2014 Challenge. The approach uses a data-driven rule-based methodology with the addition of a simple supervised classifier. We demonstrate that agile text mining allows for rapid optimization of extraction strategies, while post-processing can leverage annotation guidelines, corpus statistics and logic inferred from the gold standard data. We also show how data imbalance in a training set affects performance. Evaluation of this approach on the test data gave an F-Score of 91.7%, one percent behind the top performing system. PMID:26209007

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.

Increased river alkalinization in the Eastern U.S.

PubMed

Kaushal, Sujay S; Likens, Gene E; Utz, Ryan M; Pace, Michael L; Grese, Melissa; Yepsen, Metthea

2013-09-17

The interaction between human activities and watershed geology is accelerating long-term changes in the carbon cycle of rivers. We evaluated changes in bicarbonate alkalinity, a product of chemical weathering, and tested for long-term trends at 97 sites in the eastern United States draining over 260,000 km(2). We observed statistically significant increasing trends in alkalinity at 62 of the 97 sites, while remaining sites exhibited no significant decreasing trends. Over 50% of study sites also had statistically significant increasing trends in concentrations of calcium (another product of chemical weathering) where data were available. River alkalinization rates were significantly related to watershed carbonate lithology, acid deposition, and topography. These three variables explained ~40% of variation in river alkalinization rates. The strongest predictor of river alkalinization rates was carbonate lithology. The most rapid rates of river alkalinization occurred at sites with highest inputs of acid deposition and highest elevation. The rise of alkalinity in many rivers throughout the Eastern U.S. suggests human-accelerated chemical weathering, in addition to previously documented impacts of mining and land use. Increased river alkalinization has major environmental implications including impacts on water hardness and salinization of drinking water, alterations of air-water exchange of CO2, coastal ocean acidification, and the influence of bicarbonate availability on primary production.

Coal Mining Machinery Development As An Ecological Factor Of Progressive Technologies Implementation

NASA Astrophysics Data System (ADS)

Efremenkov, A. B.; Khoreshok, A. A.; Zhironkin, S. A.; Myaskov, A. V.

2017-01-01

At present, a significant amount of energy spent for the work of mining machines and coal mining equipment on coal mines and open pits goes to the coal grinding in the process of its extraction in mining faces. Meanwhile, the increase of small fractions in mined coal does not only reduce the profitability of its production, but also causes a further negative impact on the environment and degrades labor conditions for miners. The countermeasure to the specified processes is possible with the help of coal mining equipment development. However, against the background of the technological decrease of coal mine equipment applied in Russia the negative impact on the environment is getting reinforced.

Modeling epidemics on adaptively evolving networks: A data-mining perspective.

PubMed

Kattis, Assimakis A; Holiday, Alexander; Stoica, Ana-Andreea; Kevrekidis, Ioannis G

2016-01-01

The exploration of epidemic dynamics on dynamically evolving ("adaptive") networks poses nontrivial challenges to the modeler, such as the determination of a small number of informative statistics of the detailed network state (that is, a few "good observables") that usefully summarize the overall (macroscopic, systems-level) behavior. Obtaining reduced, small size accurate models in terms of these few statistical observables--that is, trying to coarse-grain the full network epidemic model to a small but useful macroscopic one--is even more daunting. Here we describe a data-based approach to solving the first challenge: the detection of a few informative collective observables of the detailed epidemic dynamics. This is accomplished through Diffusion Maps (DMAPS), a recently developed data-mining technique. We illustrate the approach through simulations of a simple mathematical model of epidemics on a network: a model known to exhibit complex temporal dynamics. We discuss potential extensions of the approach, as well as possible shortcomings.

Algorithm of probabilistic assessment of fully-mechanized longwall downtime

NASA Astrophysics Data System (ADS)

Domrachev, A. N.; Rib, S. V.; Govorukhin, Yu M.; Krivopalov, V. G.

2017-09-01

The problem of increasing the load on a long fully-mechanized longwall has several aspects, one of which is the improvement of efficiency in using available stoping equipment due to the increase in coefficient of the machine operating time of a shearer and other mining machines that form an integral part of the longwall set of equipment. The task of predicting the reliability indicators of stoping equipment is solved by the statistical evaluation of parameters of downtime exponential distribution and failure recovery. It is more difficult to solve the problems of downtime accounting in case of accidents in the face workings and, despite the statistical data on accidents in mine workings, no solution has been found to date. The authors have proposed a variant of probability assessment of workings caving using Poisson distribution and the duration of their restoration using normal distribution. The above results confirm the possibility of implementing the approach proposed by the authors.

Combination of complementary data mining methods for geographical characterization of extra virgin olive oils based on mineral composition.

PubMed

Sayago, Ana; González-Domínguez, Raúl; Beltrán, Rafael; Fernández-Recamales, Ángeles

2018-09-30

This work explores the potential of multi-element fingerprinting in combination with advanced data mining strategies to assess the geographical origin of extra virgin olive oil samples. For this purpose, the concentrations of 55 elements were determined in 125 oil samples from multiple Spanish geographic areas. Several unsupervised and supervised multivariate statistical techniques were used to build classification models and investigate the relationship between mineral composition of olive oils and their provenance. Results showed that Spanish extra virgin olive oils exhibit characteristic element profiles, which can be differentiated on the basis of their origin in accordance with three geographical areas: Atlantic coast (Huelva province), Mediterranean coast and inland regions. Furthermore, statistical modelling yielded high sensitivity and specificity, principally when random forest and support vector machines were employed, thus demonstrating the utility of these techniques in food traceability and authenticity research. Copyright © 2018 Elsevier Ltd. All rights reserved.

GOLD ACRES BIOLOGICAL HEAP DETOXIFICATION

EPA Science Inventory

Many active mine sites, mines in closure stage and some abandoned mines are and have utilized cyanidation to remove and recover precious metals. Discharges from these sites normally contain significant amounts of metal cyanide complexes and concentrations of thiocyanate, soluble...

Is there an association of circulatory hospitalizations independent of mining employment in coal-mining and non-coal-mining counties in west virginia?

PubMed

Talbott, Evelyn O; Sharma, Ravi K; Buchanich, Jeanine; Stacy, Shaina L

2015-04-01

Exposures associated with coal mining activities, including diesel fuel exhaust, products used in coal processing, and heavy metals and other forms of particulate matter, may impact the health of nearby residents. We investigated the relationships between county-level circulatory hospitalization rates (CHRs) in coal and non-coal-mining communities of West Virginia, coal production, coal employment, and sociodemographic factors. Direct age-adjusted CHRs were calculated using West Virginia hospitalizations from 2005 to 2009. Spatial regressions were conducted to explore associations between CHR and total, underground, and surface coal production. After adjustment, neither total, nor surface, nor underground coal production was significantly related to rate of hospitalization for circulatory disease. Our findings underscore the significant role sociodemographic and behavioral factors play in the health and well-being of coal mining communities.

Remote Sensing based multi-temporal observation of North Korea mining activities : A case study of Rakyeon mine

NASA Astrophysics Data System (ADS)

Lim, J. H.; Yu, J.; Koh, S. M.; Lee, G.

2017-12-01

Mining is a major industrial business of North Korea accounting for significant portion of an export for North Korean economy. However, due to its veiled political system, details of mining activities of North Korea is rarely known. This study investigated mining activities of Rakyeon Au-Ag mine, North Korea based on remote sensing based multi-temporal observation. To monitor the mining activities, CORONA data acquired in 1960s and 1970s, SPOT and Landsat data acquired in 1980s and 1990s and KOMPSAT-2 data acquired in 2010s are utilized. The results show that mining activities of Rakyeon mine continuously carried out for the observation period expanding tailing areas of the mine. However, its expanding rate varies between the period related to North Korea's economic and political situations.

Statistical studies of selected trace elements with reference to geology and genesis of the Carlin gold deposit, Nevada

USGS Publications Warehouse

Harris, Michael; Radtke, Arthur S.

1976-01-01

Linear regression and discriminant analyses techniques were applied to gold, mercury, arsenic, antimony, barium, copper, molybdenum, lead, zinc, boron, tellurium, selenium, and tungsten analyses from drill holes into unoxidized gold ore at the Carlin gold mine near Carlin, Nev. The statistical treatments employed were used to judge proposed hypotheses on the origin and geochemical paragenesis of this disseminated gold deposit.

Text mining electronic hospital records to automatically classify admissions against disease: Measuring the impact of linking data sources.

PubMed

Kocbek, Simon; Cavedon, Lawrence; Martinez, David; Bain, Christopher; Manus, Chris Mac; Haffari, Gholamreza; Zukerman, Ingrid; Verspoor, Karin

2016-12-01

Text and data mining play an important role in obtaining insights from Health and Hospital Information Systems. This paper presents a text mining system for detecting admissions marked as positive for several diseases: Lung Cancer, Breast Cancer, Colon Cancer, Secondary Malignant Neoplasm of Respiratory and Digestive Organs, Multiple Myeloma and Malignant Plasma Cell Neoplasms, Pneumonia, and Pulmonary Embolism. We specifically examine the effect of linking multiple data sources on text classification performance. Support Vector Machine classifiers are built for eight data source combinations, and evaluated using the metrics of Precision, Recall and F-Score. Sub-sampling techniques are used to address unbalanced datasets of medical records. We use radiology reports as an initial data source and add other sources, such as pathology reports and patient and hospital admission data, in order to assess the research question regarding the impact of the value of multiple data sources. Statistical significance is measured using the Wilcoxon signed-rank test. A second set of experiments explores aspects of the system in greater depth, focusing on Lung Cancer. We explore the impact of feature selection; analyse the learning curve; examine the effect of restricting admissions to only those containing reports from all data sources; and examine the impact of reducing the sub-sampling. These experiments provide better understanding of how to best apply text classification in the context of imbalanced data of variable completeness. Radiology questions plus patient and hospital admission data contribute valuable information for detecting most of the diseases, significantly improving performance when added to radiology reports alone or to the combination of radiology and pathology reports. Overall, linking data sources significantly improved classification performance for all the diseases examined. However, there is no single approach that suits all scenarios; the choice of the most effective combination of data sources depends on the specific disease to be classified. Copyright © 2016 Elsevier Inc. All rights reserved.

Ecological impacts of lead mining on Ozark streams: toxicity of sediment and pore water.

PubMed

Besser, John M; Brumbaugh, William G; Allert, Ann L; Poulton, Barry C; Schmitt, Christopher J; Ingersoll, Christopher G

2009-02-01

We studied the toxicity of sediments downstream of lead-zinc mining areas in southeast Missouri, using chronic sediment toxicity tests with the amphipod, Hyalella azteca, and pore-water toxicity tests with the daphnid, Ceriodaphnia dubia. Tests conducted in 2002 documented reduced survival of amphipods in stream sediments collected near mining areas and reduced survival and reproduction of daphnids in most pore waters tested. Additional amphipod tests conducted in 2004 documented significant toxic effects of sediments from three streams downstream of mining areas: Strother Creek, West Fork Black River, and Bee Fork. Greatest toxicity occurred in sediments from a 6-km reach of upper Strother Creek, but significant toxic effects occurred in sediments collected at least 14 km downstream of mining in all three watersheds. Toxic effects were significantly correlated with metal concentrations (nickel, zinc, cadmium, and lead) in sediments and pore waters and were generally consistent with predictions of metal toxicity risks based on sediment quality guidelines, although ammonia and manganese may also have contributed to toxicity at a few sites. Responses of amphipods in sediment toxicity tests were significantly correlated with characteristics of benthic invertebrate communities in study streams. These results indicate that toxicity of metals associated with sediments contributes to adverse ecological effects in streams draining the Viburnum Trend mining district.

Ecological impacts of lead mining on Ozark streams: Toxicity of sediment and pore water

USGS Publications Warehouse

Besser, J.M.; Brumbaugh, W.G.; Allert, A.L.; Poulton, B.C.; Schmitt, C.J.; Ingersoll, C.G.

2009-01-01

We studied the toxicity of sediments downstream of lead-zinc mining areas in southeast Missouri, using chronic sediment toxicity tests with the amphipod, Hyalella azteca, and pore-water toxicity tests with the daphnid, Ceriodaphnia dubia. Tests conducted in 2002 documented reduced survival of amphipods in stream sediments collected near mining areas and reduced survival and reproduction of daphnids in most pore waters tested. Additional amphipod tests conducted in 2004 documented significant toxic effects of sediments from three streams downstream of mining areas: Strother Creek, West Fork Black River, and Bee Fork. Greatest toxicity occurred in sediments from a 6-km reach of upper Strother Creek, but significant toxic effects occurred in sediments collected at least 14 km downstream of mining in all three watersheds. Toxic effects were significantly correlated with metal concentrations (nickel, zinc, cadmium, and lead) in sediments and pore waters and were generally consistent with predictions of metal toxicity risks based on sediment quality guidelines, although ammonia and manganese may also have contributed to toxicity at a few sites. Responses of amphipods in sediment toxicity tests were significantly correlated with characteristics of benthic invertebrate communities in study streams. These results indicate that toxicity of metals associated with sediments contributes to adverse ecological effects in streams draining the Viburnum Trend mining district.

Fast elemental screening of soil and sediment profiles using small-spot energy-dispersive X-ray fluorescence: application to mining sediments geochemistry.

PubMed

Gonzalez-Fernandez, Oscar; Queralt, Ignacio

2010-09-01

Elemental analysis of different sediment cores originating from the Cartagena-La Union mining district in Spain was carried out by means of a programmable small-spot energy-dispersive X-ray fluorescence (EDXRF) spectrometer to study the distribution of heavy metals along soil profiles. Cores were obtained from upstream sediments of a mining creek, from the lowland sedimentation plain, and from a mining landfill dump (tailings pile). A programmable two-dimensional (2D) stage and a focal spot resolution of 600 μm allow us to obtain complete core mapping. Geochemical results were verified using a more powerful wavelength-dispersion X-ray fluorescence (WDXRF) technique. The data obtained was processed in order to study the statistical correlations within the elemental compositions. The results obtained allow us to observe the differential in-depth distribution of heavy metals among the sampled zones. Dump site cores exhibit a homogeneous distribution of heavy metals, whereas the alluvial plain core shows accumulation of heavy metals in the upper part. This approach can be useful for the fast screening of heavy metals in depositional environments around mining sites.

CYANIDE HEAP BILOGICAL DETOXIFICATION - PHASE II

EPA Science Inventory

Many active mine sites, mines in closure stage and some abandoned mines are and have utilized cyanidation to remove and recover precious metals. Discharges from these sites normally contain significant amounts of metal cyanide complexes and concentrations of thiocyanate, soluble...

CYANIDE HEAP BIOLOGICAL DETOXIFICATION - PHASE II

EPA Science Inventory

Many active mine sites, mines in the closure stage and some abandoned mines are and have utilized cyanidation to remove and recover precious metals. Discharges from these sites normally contain significant amounts of metal cyanide complexes and concentrations of thiocyanate, solu...

Longevity of acid discharges from underground mines located above the regional water table.

PubMed

Demchak, J; Skousen, J; McDonald, L M

2004-01-01

The duration of acid mine drainage flowing out of underground mines is important in the design of watershed restoration and abandoned mine land reclamation projects. Past studies have reported that acid water flows from underground mines for hundreds of years with little change, while others state that poor drainage quality may last only 20 to 40 years. More than 150 above-drainage (those not flooded after abandonment) underground mine discharges from Pittsburgh and Upper Freeport coal seams were located and sampled during 1968 in northern West Virginia, and we revisited 44 of those sites in 1999-2000 and measured water flow, pH, acidity, Fe, sulfate, and conductivity. We found no significant difference in flows between 1968 and 1999-2000. Therefore, we felt the water quality data could be compared and the data represented real changes in pollutant concentrations. There were significant water quality differences between year and coal seam, but no effect of disturbance. While pH was not significantly improved, average total acidity declined 79% between 1968 and 1999-2000 in Pittsburgh mines (from 66.8 to 14 mmol H+ L(-1)) and 56% in Upper Freeport mines (from 23.8 to 10.4 mmol H+ L(-1)). Iron decreased an average of about 80% across all sites (from an average of 400 to 72 mg L(-1)), while sulfate decreased between 50 and 75%. Pittsburgh seam discharge water was much worse in 1968 than Upper Freeport seam water. Twenty of our 44 sites had water quality information in 1980, which served as a midpoint to assess the slope of the decline in acidity and metal concentrations. Five of 20 sites (25%) showed an apparent exponential rate of decline in acidity and iron, while 10 of 20 sites (50%) showed a more linear decline. Drainage from five Upper Freeport sites increased in acidity and iron. While it is clear that surface mines and below-drainage underground mines improve in discharge quality relatively rapidly (20-40 years), above-drainage underground mines are not as easily predicted. In total, the drainage from 34 out of 44 (77%) above-drainage underground mines showed significant improvement in acidity over time, some exponentially and some linearly. Ten discharges showed no improvement and three of these got much worse.

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.

Educational Data Mining Application for Estimating Students Performance in Weka Environment

NASA Astrophysics Data System (ADS)

Gowri, G. Shiyamala; Thulasiram, Ramasamy; Amit Baburao, Mahindra

2017-11-01

Educational data mining (EDM) is a multi-disciplinary research area that examines artificial intelligence, statistical modeling and data mining with the data generated from an educational institution. EDM utilizes computational ways to deal with explicate educational information keeping in mind the end goal to examine educational inquiries. To make a country stand unique among the other nations of the world, the education system has to undergo a major transition by redesigning its framework. The concealed patterns and data from various information repositories can be extracted by adopting the techniques of data mining. In order to summarize the performance of students with their credentials, we scrutinize the exploitation of data mining in the field of academics. Apriori algorithmic procedure is extensively applied to the database of students for a wider classification based on various categorizes. K-means procedure is applied to the same set of databases in order to accumulate them into a specific category. Apriori algorithm deals with mining the rules in order to extract patterns that are similar along with their associations in relation to various set of records. The records can be extracted from academic information repositories. The parameters used in this study gives more importance to psychological traits than academic features. The undesirable student conduct can be clearly witnessed if we make use of information mining frameworks. Thus, the algorithms efficiently prove to profile the students in any educational environment. The ultimate objective of the study is to suspect if a student is prone to violence or not.

Mercury methylation in mine wastes collected from abandoned mercury mines in the USA

USGS Publications Warehouse

Gray, J.E.; Hines, M.E.; Biester, H.; Lasorsa, B.K.; ,

2003-01-01

Speciation and transformation of Hg was studied in mine wastes collected from abandoned Hg mines at McDermitt, Nevada, and Terlingua, Texas, to evaluate formation of methyl-Hg, which is highly toxic. In these mine wastes, we measured total Hg and methyl-Hg contents, identified various Hg compounds using a pyrolysis technique, and determined rates of Hg methylation and methyl-Hg demethylation using isotopic-tracer methods. Mine wastes contain total Hg contents as high as 14000 ??g/g and methyl-Hg concentrations as high as 88 ng/g. Mine wastes were found to contain variable amounts of cinnabar, metacinnabar, Hg salts, Hg0, and Hg0 and Hg2+ sorbed onto matrix particulates. Samples with Hg0 and matrix-sorbed Hg generally contained significant methyl-Hg contents. Similarly, samples containing Hg0 compounds generally produced significant Hg methylation rates, as much as 26%/day. Samples containing mostly cinnabar showed little or no Hg methylation. Mine wastes with high methyl-Hg contents generally showed low methyl-Hg demethylation, suggesting that Hg methylation was dominant. Methyl-Hg demethylation was by both oxidative and microbial pathways. The correspondence of mine wastes containing Hg0 compounds and measured Hg methylation suggests that Hg0 oxidizes to Hg2+, which is subsequently bioavailable for microbial Hg methylation.

Knowledge Discovery and Data Mining in Iran's Climatic Researches

NASA Astrophysics Data System (ADS)

Karimi, Mostafa

2013-04-01

Advances in measurement technology and data collection is the database gets larger. Large databases require powerful tools for analysis data. Iterative process of acquiring knowledge from information obtained from data processing is done in various forms in all scientific fields. However, when the data volume large, and many of the problems the Traditional methods cannot respond. in the recent years, use of databases in various scientific fields, especially atmospheric databases in climatology expanded. in addition, increases in the amount of data generated by the climate models is a challenge for analysis of it for extraction of hidden pattern and knowledge. The approach to this problem has been made in recent years uses the process of knowledge discovery and data mining techniques with the use of the concepts of machine learning, artificial intelligence and expert (professional) systems is overall performance. Data manning is analytically process for manning in massive volume data. The ultimate goal of data mining is access to information and finally knowledge. climatology is a part of science that uses variety and massive volume data. Goal of the climate data manning is Achieve to information from variety and massive atmospheric and non-atmospheric data. in fact, Knowledge Discovery performs these activities in a logical and predetermined and almost automatic process. The goal of this research is study of uses knowledge Discovery and data mining technique in Iranian climate research. For Achieve This goal, study content (descriptive) analysis and classify base method and issue. The result shown that in climatic research of Iran most clustering, k-means and wards applied and in terms of issues precipitation and atmospheric circulation patterns most introduced. Although several studies in geography and climate issues with statistical techniques such as clustering and pattern extraction is done, Due to the nature of statistics and data mining, but cannot say for internal climate studies in data mining and knowledge discovery techniques are used. However, it is necessary to use the KDD Approach and DM techniques in the climatic studies, specific interpreter of climate modeling result.

Application of Modern Tools and Techniques for Mine Safety & Disaster Management

NASA Astrophysics Data System (ADS)

Kumar, Dheeraj

2016-04-01

The implementation of novel systems and adoption of improvised equipment in mines help mining companies in two important ways: enhanced mine productivity and improved worker safety. There is a substantial need for adoption of state-of-the-art automation technologies in the mines to ensure the safety and to protect health of mine workers. With the advent of new autonomous equipment used in the mine, the inefficiencies are reduced by limiting human inconsistencies and error. The desired increase in productivity at a mine can sometimes be achieved by changing only a few simple variables. Significant developments have been made in the areas of surface and underground communication, robotics, smart sensors, tracking systems, mine gas monitoring systems and ground movements etc. Advancement in information technology in the form of internet, GIS, remote sensing, satellite communication, etc. have proved to be important tools for hazard reduction and disaster management. This paper is mainly focused on issues pertaining to mine safety and disaster management and some of the recent innovations in the mine automations that could be deployed in mines for safe mining operations and for avoiding any unforeseen mine disaster.

Determining the Solubility Product of Fe(OH)[subscript 3]: An Equilibrium Study with Environmental Significance

ERIC Educational Resources Information Center

Meighan, Michelle; MacNeil, Joseph; Falconer, Renee

2008-01-01

The relationship between pH and the aqueous solubility of heavy metals is explored by considering the environmental impact of acidic mine drainage. Acid mine drainage is an important environmental concern in many areas of the United States. Associated with coal mining in the East and hard rock mining in the West, the acidity originates primarily…

The mining sector of Liberia: current practices and environmental challenges.

PubMed

Wilson, Samuel T K; Wang, Hongtao; Kabenge, Martin; Qi, Xuejiao

2017-08-01

Liberia is endowed with an impressive stock of mineral reserves and has traditionally relied on mining, namely iron ore, gold, and diamonds, as a major source of income. The recent growth in the mining sector has the potential to contribute significantly to employment, income generation, and infrastructure development. However, the development of these mineral resources has significant environmental impacts that often go unnoticed. This paper presents an overview of the Liberian mining sector from historical, current development, and economic perspectives. The efforts made by government to address issues of environmental management and sustainable development expressed in national and international frameworks, as well as some of the environmental challenges in the mining sector are analyzed. A case study was conducted on one of the iron ore mines (China Union Bong Mines Investment) to analyze the effects of the water quality on the local water environment. The results show that the analyzed water sample concentrations were all above the WHO and Liberia water standard Class I guidelines for drinking water. Finally the paper examines the application of water footprint from a life cycle perspective in the Liberian mining sector and suggests some policy options for water resources management.

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.

Rethink potential risks of toxic emissions from natural gas and oil mining.

PubMed

Meng, Qingmin

2018-09-01

Studies have showed the increasing environmental and public health risks of toxic emissions from natural gas and oil mining, which have become even worse as fracking is becoming a dominant approach in current natural gas extraction. However, governments and communities often overlook the serious air pollutants from oil and gas mining, which are often quantified lower than the significant levels of adverse health effects. Therefore, we are facing a challenging dilemma: how could we clearly understand the potential risks of air toxics from natural gas and oil mining. This short study aims at the design and application of simple and robust methods to enhance and improve current understanding of the becoming worse toxic air emissions from natural gas and oil mining as fracking is becoming the major approach. Two simple ratios, the min-to-national-average and the max-to-national-average, are designed and applied to each type of air pollutants in a natural gas and oil mining region. The two ratios directly indicate how significantly high a type of air pollutant could be due to natural gas and oil mining by comparing it to the national average records, although it may not reach the significant risks of adverse health effects according to current risk screening methods. The min-to-national-average and the max-to-national-average ratios can be used as a direct and powerful method to describe the significance of air pollution by comparing it to the national average. The two ratios are easy to use for governments, stakeholders, and the public to pay enough attention on the air pollutants from natural gas and oil mining. The two ratios can also be thematically mapped at sampled sites for spatial monitoring, but spatial mitigation and analysis of environmental and health risks need other measurements of environmental and demographic characteristics across a natural gas and oil mining area. Copyright © 2018 Elsevier Ltd. All rights reserved.

Assessment of mercury and methylmercury in water, sediment, and biota in Sulphur Creek in the vicinity of the Clyde Gold Mine and the Elgin Mercury Mine, Colusa County, California

USGS Publications Warehouse

Hothem, Roger L.; Rytuba, James J.; Brussee, Brianne E.; Goldstein, Daniel N.

2013-01-01

At the request of the U.S. Bureau of Land Management, we performed a study during April–July 2010 to characterize mercury (Hg), monomethyl mercury (MMeHg), and other geochemical constituents in sediment, water, and biota at the Clyde Gold Mine and the Elgin Mercury Mine, located in neighboring subwatersheds of Sulphur Creek, Colusa County, California. This study was in support of a Comprehensive Environmental Response, Compensation, and Liability Act - Removal Site Investigation. The investigation was in response to an abatement notification from the California Central Valley Regional Water Quality Control Board to evaluate the release of Hg from the Clyde and Elgin mines. Samples of water, sediment, and biota (aquatic macroinvertebrates) were collected from sites upstream and downstream from the two mine sites to evaluate the level of Hg contamination contributed by each mine to the aquatic ecosystem. Physical parameters, as well as dissolved organic carbon, total Hg (HgT), and MMeHg were analyzed in water and sediment. Other relevant geochemical constituents were analyzed in sediment, filtered water, and unfiltered water. Samples of aquatic macroinvertebrates from each mine were analyzed for HgT and MMeHg. The presence of low to moderate concentrations of HgT and MMeHg in water, sediment, and biota from the Freshwater Branch of Sulphur Creek, and the lack of significant increases in these concentrations downstream from the Clyde Mine indicated that this mine is not a significant source of Hg to the watershed during low flow conditions. Although concentrations of HgT and MMeHg were generally higher in samples of sediment and water from the Elgin Mine compared to the Clyde Mine, concentrations in comparable biota from the two mine areas were similar. It is likely that highly saline effluent from nearby hot springs contribute more Hg to the West Fork of Sulphur Creek than the mine waste material at the Elgin Mine.

Hydrogeochemical investigations of some historic mining areas in the western Humboldt River basin, Nevada

USGS Publications Warehouse

Nash, J.T.

2001-01-01

Productive historic mines in 13 mining districts, of many geochemical types, were investigated in May of 1998. Reconnaissance field observations were made and samples of mine dumps, mine drainage waters, and mill tailings have been collected to characterize the geochemical signature of these materials and to determine their actual or potential contamination of surface or ground waters. Field observations suggest that visible indicators of acidic mine drainage are rare, and field measurements of pH and chemical analyses of several kinds of materials indicate that only a few sites release acid or significant concentrations of metals.

Foundational Principles for Large-Scale Inference: Illustrations Through Correlation Mining

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

Hero, Alfred O.; Rajaratnam, Bala

When can reliable inference be drawn in the ‘‘Big Data’’ context? This article presents a framework for answering this fundamental question in the context of correlation mining, with implications for general large-scale inference. In large-scale data applications like genomics, connectomics, and eco-informatics, the data set is often variable rich but sample starved: a regime where the number n of acquired samples (statistical replicates) is far fewer than the number p of observed variables (genes, neurons, voxels, or chemical constituents). Much of recent work has focused on understanding the computational complexity of proposed methods for ‘‘Big Data.’’ Sample complexity, however, hasmore » received relatively less attention, especially in the setting when the sample size n is fixed, and the dimension p grows without bound. To address this gap, we develop a unified statistical framework that explicitly quantifies the sample complexity of various inferential tasks. Sampling regimes can be divided into several categories: 1) the classical asymptotic regime where the variable dimension is fixed and the sample size goes to infinity; 2) the mixed asymptotic regime where both variable dimension and sample size go to infinity at comparable rates; and 3) the purely high-dimensional asymptotic regime where the variable dimension goes to infinity and the sample size is fixed. Each regime has its niche but only the latter regime applies to exa-scale data dimension. We illustrate this high-dimensional framework for the problem of correlation mining, where it is the matrix of pairwise and partial correlations among the variables that are of interest. Correlation mining arises in numerous applications and subsumes the regression context as a special case. We demonstrate various regimes of correlation mining based on the unifying perspective of high-dimensional learning rates and sample complexity for different structured covariance models and different inference tasks.« less

Effects of natural factors on the spatial distribution of heavy metals in soils surrounding mining regions.

PubMed

Ding, Qian; Cheng, Gong; Wang, Yong; Zhuang, Dafang

2017-02-01

Various studies have shown that soils surrounding mining areas are seriously polluted with heavy metals. Determining the effects of natural factors on spatial distribution of heavy metals is important for determining the distribution characteristics of heavy metals in soils. In this study, an 8km buffer zone surrounding a typical non-ferrous metal mine in Suxian District of Hunan Province, China, was selected as the study area, and statistical, spatial autocorrelation and spatial interpolation analyses were used to obtain descriptive statistics and spatial autocorrelation characteristics of As, Pb, Cu, and Zn in soil. Additionally, the distributions of soil heavy metals under the influences of natural factors, including terrain (elevation and slope), wind direction and distance from a river, were determined. Layout of sampling sites, spatial changes of heavy metal contents at high elevations and concentration differences between upwind and downwind directions were then evaluated. The following results were obtained: (1) At low elevations, heavy metal concentrations decreased slightly, then increased considerably with increasing elevation. At high elevations, heavy metal concentrations first decreased, then increased, then decreased with increasing elevation. As the slope increased, heavy metal contents increased then decreased. (2) Heavy metal contents changed consistently in the upwind and downwind directions. Heavy metal contents were highest in 1km buffer zone and decreased with increasing distance from the mining area. The largest decrease in heavy metal concentrations was in 2km buffer zone. Perennial wind promotes the transport of heavy metals in downwind direction. (3) The spatial extent of the influence of the river on Pb, Zn and Cu in the soil was 800m. (4) The influence of the terrain on the heavy metal concentrations was greater than that of the wind. These results provide a scientific basis for preventing and mitigating heavy metal soil pollution in areas surrounding mines. Copyright © 2016 Elsevier B.V. All rights reserved.

Preliminaries on pollution risk factors related to mining and ore processing in the Cu-rich pollymetallic belt of Eastern Carpathians, Romania.

PubMed

Stumbea, Dan

2013-11-01

The present study focuses on the mineralogical and geochemical patterns of mining and ore-processing wastes from some occurrences in the Eastern Carpathians; its aim is to identify the main factors and processes that could lead to the pollution of the environment. In this respect, the following types of solid waste were investigated: efflorescent salts developed on the surface of rock blocks from a quarry, ore-processing waste from two tailings ponds, and salt crusts developed at the surface of a tailings pond. The potential risks emphasized by these preliminary investigations are the following: (1) the risk of wind-driven removal and transport of the waste from the surface of tailings ponds, given that fine grains prevail (up to 80%); (2) the risk of tailings removal through mechanical transport by water, during heavy rainfall; (3) the appearance of hydrated sulfates on the rock fragments from the mining waste, sulfates which are highly susceptible to the generation of acid mine drainage (pH<4); (4) the high amount of toxic elements (Pb, Cd, Cu, Zn, As, etc.) that acid mine drainage leachates contain; and (5) the development of a salt crust on the flat, horizontal surfaces of the waste deposit, due to this very shape. Statistical data regarding the amount of both major and minor elements in the tailings have revealed two statistical populations for nearly all the toxic metals. This suggests that, beyond the effect that the tailings have upon the environment through their mere presence in a given area, there are alleged additional factors and processes which intensify the pollution: the location of the waste deposit relative to the topography of the area; the shape of the waste deposit; the development of low areas on the surface of the deposit, areas which favor the appearance of salt crusts; and the mineralogy of efflorescent aggregates.

Foundational Principles for Large-Scale Inference: Illustrations Through Correlation Mining

PubMed Central

Hero, Alfred O.; Rajaratnam, Bala

2015-01-01

When can reliable inference be drawn in fue “Big Data” context? This paper presents a framework for answering this fundamental question in the context of correlation mining, wifu implications for general large scale inference. In large scale data applications like genomics, connectomics, and eco-informatics fue dataset is often variable-rich but sample-starved: a regime where the number n of acquired samples (statistical replicates) is far fewer than fue number p of observed variables (genes, neurons, voxels, or chemical constituents). Much of recent work has focused on understanding the computational complexity of proposed methods for “Big Data”. Sample complexity however has received relatively less attention, especially in the setting when the sample size n is fixed, and the dimension p grows without bound. To address fuis gap, we develop a unified statistical framework that explicitly quantifies the sample complexity of various inferential tasks. Sampling regimes can be divided into several categories: 1) the classical asymptotic regime where fue variable dimension is fixed and fue sample size goes to infinity; 2) the mixed asymptotic regime where both variable dimension and sample size go to infinity at comparable rates; 3) the purely high dimensional asymptotic regime where the variable dimension goes to infinity and the sample size is fixed. Each regime has its niche but only the latter regime applies to exa cale data dimension. We illustrate this high dimensional framework for the problem of correlation mining, where it is the matrix of pairwise and partial correlations among the variables fua t are of interest. Correlation mining arises in numerous applications and subsumes the regression context as a special case. we demonstrate various regimes of correlation mining based on the unifying perspective of high dimensional learning rates and sample complexity for different structured covariance models and different inference tasks. PMID:27087700

Foundational Principles for Large-Scale Inference: Illustrations Through Correlation Mining

DOE PAGES

Hero, Alfred O.; Rajaratnam, Bala

2015-12-09

When can reliable inference be drawn in the ‘‘Big Data’’ context? This article presents a framework for answering this fundamental question in the context of correlation mining, with implications for general large-scale inference. In large-scale data applications like genomics, connectomics, and eco-informatics, the data set is often variable rich but sample starved: a regime where the number n of acquired samples (statistical replicates) is far fewer than the number p of observed variables (genes, neurons, voxels, or chemical constituents). Much of recent work has focused on understanding the computational complexity of proposed methods for ‘‘Big Data.’’ Sample complexity, however, hasmore » received relatively less attention, especially in the setting when the sample size n is fixed, and the dimension p grows without bound. To address this gap, we develop a unified statistical framework that explicitly quantifies the sample complexity of various inferential tasks. Sampling regimes can be divided into several categories: 1) the classical asymptotic regime where the variable dimension is fixed and the sample size goes to infinity; 2) the mixed asymptotic regime where both variable dimension and sample size go to infinity at comparable rates; and 3) the purely high-dimensional asymptotic regime where the variable dimension goes to infinity and the sample size is fixed. Each regime has its niche but only the latter regime applies to exa-scale data dimension. We illustrate this high-dimensional framework for the problem of correlation mining, where it is the matrix of pairwise and partial correlations among the variables that are of interest. Correlation mining arises in numerous applications and subsumes the regression context as a special case. We demonstrate various regimes of correlation mining based on the unifying perspective of high-dimensional learning rates and sample complexity for different structured covariance models and different inference tasks.« less

Application of data mining in science and technology management information system based on WebGIS

NASA Astrophysics Data System (ADS)

Wu, Xiaofang; Xu, Zhiyong; Bao, Shitai; Chen, Feixiang

2009-10-01

With the rapid development of science and technology and the quick increase of information, a great deal of data is accumulated in the management department of science and technology. Usually, many knowledge and rules are contained and concealed in the data. Therefore, how to excavate and use the knowledge fully is very important in the management of science and technology. It will help to examine and approve the project of science and technology more scientifically and make the achievement transformed as the realistic productive forces easier. Therefore, the data mine technology will be researched and applied to the science and technology management information system to find and excavate the knowledge in the paper. According to analyzing the disadvantages of traditional science and technology management information system, the database technology, data mining and web geographic information systems (WebGIS) technology will be introduced to develop and construct the science and technology management information system based on WebGIS. The key problems are researched in detail such as data mining and statistical analysis. What's more, the prototype system is developed and validated based on the project data of National Natural Science Foundation Committee. The spatial data mining is done from the axis of time, space and other factors. Then the variety of knowledge and rules will be excavated by using data mining technology, which helps to provide an effective support for decisionmaking.

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

Relating landscape characteristics to non-point source pollution in mine waste-located watersheds using geospatial techniques.

PubMed

Xiao, Huaguo; Ji, Wei

2007-01-01

Landscape characteristics of a watershed are important variables that influence surface water quality. Understanding the relationship between these variables and surface water quality is critical in predicting pollution potential and developing watershed management practices to eliminate or reduce pollution risk. To understand the impacts of landscape characteristics on water quality in mine waste-located watersheds, we conducted a case study in the Tri-State Mining District which is located in the conjunction of three states (Missouri, Kansas and Oklahoma). Severe heavy metal pollution exists in that area resulting from historical mining activities. We characterized land use/land cover over the last three decades by classifying historical multi-temporal Landsat imagery. Landscape metrics such as proportion, edge density and contagion were calculated based on the classified imagery. In-stream water quality data over three decades were collected, including lead, zinc, iron, cadmium, aluminum and conductivity which were used as key water quality indicators. Statistical analyses were performed to quantify the relationship between landscape metrics and surface water quality. Results showed that landscape characteristics in mine waste-located watersheds could account for as much as 77% of the variation of water quality indicators. A single landscape metric alone, such as proportion of mine waste area, could be used to predict surface water quality; but its predicting power is limited, usually accounting for less than 60% of the variance of water quality indicators.

CASE STUDY OF AN INTEGRATED PASSIVE BIOLOGICAL ARD TREATMENT SYSTEM

EPA Science Inventory

Many active mine sites, mines in the closure stage and some abandoned mines are and have utilized cyanidation to remove and recover precious metals. Discharges from these sites normally contain significant amounts of metal cyanide complexes and concentrations of thiocyanate, solu...

Manganese and Mercury Levels in Water, Sediments, and Children Living Near Gold-Mining Areas of the Nangaritza River Basin, Ecuadorian Amazon.

PubMed

González-Merizalde, Max V; Menezes-Filho, José A; Cruz-Erazo, Claudia Teresa; Bermeo-Flores, Santos Amable; Sánchez-Castillo, María Obdulia; Hernández-Bonilla, David; Mora, Abrahan

2016-08-01

Artisanal and small-scale gold-mining activities performed in mountain areas of the Southern Ecuadorian Amazon have incorporated several heavy metals into the aquatic systems, thus increasing the risk of exposure in populations living in adjacent zones. Therefore, the objective of this study was to evaluate the contamination levels of mercury (Hg) and manganese (Mn) in several rivers of the Nangaritza River basin and assess the exposure in school-aged children residing near the gold-mining zones. River water and sediment samples were collected from a highly contaminated (HEx) and a moderately contaminated (MEx) zones. Hair Mn (MnH) and urinary Hg (HgU) levels were determined in school-aged children living in both zones. High concentrations of dissolved Mn were found in river waters of the HEx zone (between 2660 and 3990 µg l(-1)); however, Hg levels, in general, were lower than the detection limit (DL; <1.0 µg l(-1)). Similarly, Mn levels in sediments were also increased (3090 to 4086 µg g(-1)). Median values of MnH in children of the HEx and MEx zones were 5.5 and 3.4 µg g(-1), respectively, whereas the median values of HgU concentrations in children living in the HEx and MEx zones were 4.4 and 0.62 µg g-creat(-1), respectively. Statistically significant differences were observed between both biomarkers in children from the HEx and MEx zones. In addition, boys presented significantly greater MnH levels in both zones. The greater MnH values were found in children living in alluvial areas, whereas children living in the high mountain areas, where some ore-processing plants are located close to or inside houses and schools, had the greater HgU concentrations. In summary, the data reported in this paper highlights that artisanal and small-scale gold-mining activities can not only produce mercurial contamination, that can also release other heavy metals (such as Mn) that may pose a risk to human health.

Agile text mining for the 2014 i2b2/UTHealth Cardiac risk factors challenge.

PubMed

Cormack, James; Nath, Chinmoy; Milward, David; Raja, Kalpana; Jonnalagadda, Siddhartha R

2015-12-01

This paper describes the use of an agile text mining platform (Linguamatics' Interactive Information Extraction Platform, I2E) to extract document-level cardiac risk factors in patient records as defined in the i2b2/UTHealth 2014 challenge. The approach uses a data-driven rule-based methodology with the addition of a simple supervised classifier. We demonstrate that agile text mining allows for rapid optimization of extraction strategies, while post-processing can leverage annotation guidelines, corpus statistics and logic inferred from the gold standard data. We also show how data imbalance in a training set affects performance. Evaluation of this approach on the test data gave an F-Score of 91.7%, one percent behind the top performing system. Copyright © 2015 Elsevier Inc. All rights reserved.

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.

Lung cancer mortality and airways obstruction among metal miners exposed to silica and low levels of radon daughters.

PubMed

Carta, P; Cocco, P; Picchiri, G

1994-04-01

Starting from a cross-sectional survey in 1973, the mortality of two cohorts of Sardinian metal miners was followed through December 31, 1988. In mine A, the quartz concentration in respirable dust ranged between 0.2% and 2.0% and the exposure to radon daughters averaged 0.13 working level (WL), with the highest estimated cumulative exposure around 80-120 WLM. In mine B, the silica content was much higher (6.5-29%), but exposure to radon daughters was significantly lower than in mine A. More than 98% of the overall work force in 1973 (1,741 miners) entered the cohort, providing 25,842.5 person-years. Smoking, occupational history, chest radiographs, and lung function tests were available for the cohort members at admission. Mortality for all causes was slightly lower than expected. A significant excess for nonmalignant chronic respiratory diseases was noticed in both mines. Twenty-four subjects died of lung cancer, 17 from mine A (SMR: 128; 95% confidence interval [CI]: 75-205) and 7 from mine B (SMR: 85; 95% CI: 34-175). The SMR for lung cancer was highest among the underground workers from mine A (SMR: 148; 95% CI: 74-265), with a significant upward trend by duration of employment in underground jobs. Mine B underground miners showed lung cancer SMRs close to 100 without a significant trend by duration of employment. Among underground miners with spirometric airways obstruction in 1973, those from mine A showed the highest risk (SMR: 316; 95% CI: 116-687). The relationship did not change after adjusting for age and smoking. Based on the present findings, crystalline silica per se does not appear to affect lung cancer mortality. A slight association between lung cancer mortality and exposure to radon daughters, though within relatively low levels, may be considered for underground miners from mine A. Impaired pulmonary function may be an independent predictor of lung cancer and an important risk factor enhancing the residence time of inhaled carcinogens, i.e., alpha particles or PAHs, by impairing their bronchial and alveolar clearance.

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...

Optimising dewatering costs on a south african gold mine

NASA Astrophysics Data System (ADS)

Connelly, R. J.; Ward, A. D.

1987-06-01

Many South African Gold Mines are geologically in proximity to the Transvaal Dolomites. This geological unit, is karstic in many areas and is very extensive. Very large volumes of ground water can be found in the dolomites, and have given rise to major dewatering problems on the mines. Hitherto, the general philosophy on the mines has been to acept these large inflows into the mine, and then to pump out from underground at a suitably convenient level. The dolomites constitute a ground water control area which means that Goverment permission is required to do anything with ground water within the dolomite. When the first major inflows occurred, the mines started dewatering the dolomites, and in many areas induced sinkholes, with significant loss of life and buildings. The nett result is that mines have to pump large quantities of water out of the mine but recharge into the dolomite to maintain water levesl. During the past 2 years a number of investigations have been carried out to reduce the very high costs of dewatering. On one mine the cost of removing 130×103 m3/day is about 1×106 Rand/month. The hydrogeologic model for the dolomites is now reasonably well understood. It shows that surface wells to a depth of up to 150 m can withdraw significant quantities of water and reduce the amount that has to be pumped from considerable depth with significant saving in puming costs. Such a system has a number of additional advantages such as removing some of the large volume of water from the underground working environment and providing a system that can be used for controlled surface dewatering should it be required.

Hand-arm vibration syndrome in South African gold miners.

PubMed

Nyantumbu, Busi; Barber, Chris M; Ross, Mary; Curran, Andrew D; Fishwick, David; Dias, Belinda; Kgalamono, Spo; Phillips, James I

2007-01-01

Hand-arm vibration syndrome (HAVS) is associated with the use of hand-held vibrating tools. Affected workers may experience symptoms of tingling, numbness, loss of grip strength and pain. Loss of dexterity may impair everyday activities, and potentially increase the risk of occupational accidents. Although high vibration levels (up to 31 m/s(2)) have been measured in association with rock drills, HAVS has not been scientifically evaluated in the South African mining industry. The aim of this study was to determine the prevalence and severity of HAVS in South African gold miners, and to identify the tools responsible. A cross-sectional study was conducted in a single South African gold-mine. Participants were randomly selected from mineworkers returning from annual leave, comprising 156 subjects with occupational exposure to vibration, and 140 workers with no exposure. Miners who consented to participate underwent a clinical HAVS assessment following the UK Health and Safety Laboratory protocol. The prevalence of HAVS in vibration-exposed gold miners was 15%, with a mean latent period of 5.6 years. Among the non-exposed comparison group, 5% had signs and symptoms indistinguishable from HAVS. This difference was statistically significant (P < 0.05). All the cases of HAVS gave a history of exposure to rock drills. The study has diagnosed the first cases of HAVS in the South African mining industry. The prevalence of HAVS was lower than expected, and possible explanations for this may include a survivor population, and lack of vascular symptom reporting due to warm-ambient temperatures.

Using Fisher information to track stability in multivariate systems

EPA Science Inventory

With the current proliferation of data, the proficient use of statistical and mining techniques offer substantial benefits to capture useful information from any dataset. As numerous approaches make use of information theory concepts, here, we discuss how Fisher information (FI...

Mitochondrial DNA copy number in peripheral blood cell and hypertension risk among mining workers: a case-control study in Chinese coal miners.

PubMed

Lei, L; Guo, J; Shi, X; Zhang, G; Kang, H; Sun, C; Huang, J; Wang, T

2017-09-01

Alteration of mitochondrial DNA (mtDNA) copy number, which reflects oxidant-induced cell damage, has been observed in a wide range of human diseases. However, whether it correlates with hypertension has not been elucidated. We aimed to explore the association between mtDNA copy number and the risk of hypertension in Chinese coal miners. A case-control study was performed with 378 hypertension patients and 325 healthy controls in a large coal mining group located in North China. Face-to-face interviews were conducted by trained staffs with necessary medical knowledge. The mtDNA copy number was measured by a quantitative real-time PCR assay using DNA extracted from peripheral blood. No significant differences in mtDNA copy number were observed between hypertension patients and healthy controls. However, in both case and control groups, the mtDNA copy number was statistically significantly lower in the elder population (≥45 years old) compared with the younger subjects (<45 years old; 7.17 vs 6.64, P=0.005 and 7.21 vs 6.84, P=0.036). A significantly higher mtDNA copy number could be found in hypertension patients consuming alcohol regularly compared with no alcohol consumption patients (7.09 vs 6.69); mtDNA copy number was also positively correlated with age and alcohol consumption. Hypertension was found significantly correlated with factors such as age, work duration, monthly family income and drinking status. Our results suggest that the mtDNA copy number is not associated with hypertension in coal miners.

Outdoor (222)Rn-concentrations in Germany - part 2 - former mining areas.

PubMed

Kümmel, M; Dushe, C; Müller, S; Gehrcke, K

2014-06-01

In the German Federal States of Saxony, Saxony-Anhalt and Thuringia, centuries of mining and milling activities resulted in numerous residues with increased levels of natural radioactivity such as waste rock dumps and tailings ponds. These may have altered potential radiation exposures of the population significantly. Especially waste rock dumps from old mining activities as well as 20th century uranium mining may, due to their radon ((222)Rn) exhalation capacity, lead to significant radiation exposures. They often lie close to or within residential areas. In order to study the impact on the natural radon level, the Federal Office for Radiation Protection (BfS) has run networks of radon measurement points in 16 former mining areas, together with 2 networks in regions not influenced by mining for comparison purposes. Representative overviews of the long-term outdoor radon concentrations could be established including estimates of regional background concentrations. Former mining and milling activities did not result in large-area impacts on the outdoor radon level. However, significantly increased radon concentrations were observed in close vicinity of shafts and large waste rock dumps. They are partly located in residential areas and need to be considered under radiation protection aspects. Examples are given that illustrate the consequences of the Wismut Ltd. Company's reclamation activities on the radon situation. Copyright © 2014 Elsevier Ltd. All rights reserved.

Environmental geochemistry of a Kuroko-type massive sulfide deposit at the abandoned Valzinco mine, Virginia, USA

USGS Publications Warehouse

Seal, R.R.; Hammarstrom, J.M.; Johnson, A.N.; Piatak, N.M.; Wandless, G.A.

2008-01-01

The abandoned Valzinco mine, which worked a steeply dipping Kuroko-type massive sulfide deposit in the Virginia Au-pyrite belt, contributed significant metal-laden acid-mine drainage to the Knight's Branch watershed. The host rocks were dominated by metamorphosed felsic volcanic rocks, which offered limited acid-neutralizing potential. The ores were dominated by pyrite, sphalerite, galena, and chalcopyrite, which represented significant acid-generating potential. Acid-base accounting and leaching studies of flotation tailings - the dominant mine waste at the site - indicated that they were acid generating and therefore, should have liberated significant quantities of metals to solution. Field studies of mine drainage from the site confirmed that mine drainage and the impacted stream waters had pH values from 1.1 to 6.4 and exceeded aquatic ecosystem toxicity limits for Fe, Al, Cd, Cu, Pb and Zn. Stable isotope studies of water, dissolved SO42 -, and primary and secondary sulfate and sulfide minerals indicated that two distinct sulfide oxidation pathways were operative at the site: one dominated by Fe(III) as the oxidant, and another by molecular O2 as the oxidant. Reaction-path modeling suggested that geochemical interactions between tailings and waters approached a steady state within about a year. Both leaching studies and geochemical reaction-path modeling provided reasonable predictions of the mine-drainage chemistry.

Long-term effects of surface coal mining on ground-water levels and quality in two small watersheds in eastern Ohio

USGS Publications Warehouse

Cunningham, W.L.; Jones, R.L.

1990-01-01

Two small watersheds in eastern Ohio that were surface mined for coal and reclaimed were studied during 1986-89. Water-level and water-quality data were compared with similar data collected during previous investigations conducted during 1976-83 to determine long-term effects of surface mining on the hydrologic system. Before mining, the watersheds were characterized by sequences of flat-lying sedimentary rocks containing two major coal seams and underclays. An aquifer was present above each of the underclays. Surface mining removed the upper aquifer, stripped the coal seam, and replaced the sediment. This created a new upper aquifer with different hydraulic and chemical characteristics. Mining did not disturb the middle aquifer. A third, deeper aquifer in each watershed was not studied. Water levels were continuously recorded in one well in each aquifer. Other wells were measured every 2 months. Water levels in the upper aquifers reached hydraulic equilibrium from 2 to 5 years after mining ceased. Water levels in the middle aquifers increased more than 5 feet during mining and reached equilibrium almost immediately thereafter. Water samples were collected from three upper-aquifer well, a seep from the upper aquifer, and the stream in each watershed. Two samples were collected in 1986 and 1987, and one each in 1988 and 1989. In both watersheds, sulfate replaced bicarbonate as the dominant upper-aquifer and surface-water anion after mining. For the upper aquifer of a watershed located in Muskingum County, water-quality data were grouped into premining and late postmining time periods (1986-89). The premining median pH and concentration of dissolved solids and sulfate were 7.6, 378 mg/L (milligrams per liter), and 41 mg/L, respectively. The premining median concentrations of iron and manganese were 10? /L (micrograms per liter) and 25?, respectively. The postmining median values of pH, dissolved solids, and sulfate were 6.7, 1,150 mg/L, and 560 mg/L, respectively. The postmining median concentrations of iron and manganese were 3,900?g/L and 1,900? g/L, respectively. For the upper aquifer of a watershed located in Jefferson County, the water-quality data were grouped into three time periods of premining, early postmining, and late postmining. The premining median pH and concentrations of dissolved solids and sulfate were 7.0, 335 mg/L, and 85 mg/L, respectively. The premining median concentrations of iron and manganese were 30? g/L for each constituent. Late postmining median pH and concentrations of dissolved solids and sulfate were 6.7, 1,495 mg/L, and 825 mg/L, respectively. The postmining median concentrations of iron and manganese were 31? g/L and 1,015? g/L, respectively. Chemistry of water in the middle aquifer in each watershed underwent similar changes. In general, statistically significant increases in concentrations of dissolved constituents occurred because of surface mining. In some constituents, concentrations increased by more than an order of magnitude. The continued decrease in pH indicated that ground water had no reached geochemical equilibrium in either watershed more than 8 years after mining.

The future of European mining: What should our mining industry learn from the Skouries and Rosia Montana community gold conflicts

NASA Astrophysics Data System (ADS)

Hardy, Liam; Heller, Shaun; Faltyn, Rowan; Stefanaki, Anna; Economidou, Romina; Savin, Irina; Hood, Leo; Conway, Christopher

2017-04-01

The popular image of mining portrayed by media and by a majority of public opinion is a dominantly negative one. From worker's rights to environmental damages, disasters such as the Copiapó mine collapse (Chile), the acid mine drainage at Lousal (Portugal) and the Pb contamination of waters around the Tyndrum mines (Scotland) overshadow initiatives like the ICMM. Some companies receive little praise despite creating active community education and investment projects, while others simply build higher barbed wire fences and attempt to weather the protests, budgeting them into mine life assessments. This image problem, combined with the decentralised political segregation of Europe and the increased power of grass-roots protest initiatives (such as Antigold in Greece), has resulted in mining companies joining a long list of industries effected by the 'auto-protest' reaction in face of development, regardless of potential regional and national benefits, there is a pre-existing lack of trust in corporate and government powers to protect community interests. The poor management of existing licences is thus becoming a significant danger to future operations and the wider industry. Here we report on the Rosia Montana dispute (Romania) and the ongoing Skouries conflict (Greece). We then discuss how the European mining industry may need to significantly adapt its exploration and community engagement strategies to avoid future conflicts and, present a recent example of how effective suitably organised community engagement projects can be for local mining initiatives from Southern Portugal.

ORD Technical Outreach and Support Activities on Sustainable Mining Applications

EPA Science Inventory

Hardrock mining has played a significant role in the development of economies, consumer products and defense in the United States from the start of industrialization. Currently, the industry continues to lay a critical role in the development of our country. Mining waste which ...

30 CFR 282.21 - Plans, general.

Code of Federal Regulations, 2011 CFR

2011-07-01

... Resources BUREAU OF OCEAN ENERGY MANAGEMENT, REGULATION, AND ENFORCEMENT, DEPARTMENT OF THE INTERIOR... provide comments on proposed Delineation, Testing, and Mining Plans and any proposal for a significant... Mining Plan if the lessee has sufficient data and information on which to base a Testing or Mining Plan...

MERCURY CONTRIBUTIONS TO THE ENVIRONMENT FROM HISTORIC MINING PRACTICES

EPA Science Inventory

Significant quantities of mercury have been released to the environment as a result of historic precious metal mining. Many gold and silver deposits are enriched in mercury, which is released during mining and processing activities. Historically in the U.S., although a modern ...

Overview of bureau research directed towards surface powered haulage safety

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

May, J.P.; Aldinger, J.A.

1995-12-31

Surface mining operations, including mills and preparation plants, employ over 260,000 people. This represents a significant contribution to our nation`s economy and an important source of skilled and well-paying jobs. As mine production has shifted from underground to surface, and with continuing advances in underground mine safety, surface mining has unfortunately become the leader in mine fatalities. In 1994 surface mining accidents accounted for 49% of all mine fatalities, followed by underground mining with 37% and mills and preparation plants with 14%. The U.S. Bureau of Mines (USBM) has targeted surface mining as an important research priority to reduce themore » social and economic costs associated with fatalities and lost-work-time injuries. USBM safety research focuses on the development of technologies that can enhance productivity and reduce mining costs through a reduction in the number and severity of mining accidents. This report summarizes a number of completed and ongoing research programs directed towards surface powered haulage--the single largest category of fatalities in surface mining and a major cause of lost workdays. Research products designed for industry are highlighted and future USBM surface mining safety research is discussed.« less

Remote sensing application to regional activities

NASA Technical Reports Server (NTRS)

Shahrokhi, F.; Jones, N. L.; Sharber, L. A.

1976-01-01

Two agencies within the State of Tennessee were identified whereby the transfer of aerospace technology, namely remote sensing, could be applied to their stated problem areas. Their stated problem areas are wetland and land classification and strip mining studies. In both studies, LANDSAT data was analyzed with the UTSI video-input analog/digital automatic analysis and classification facility. In the West Tennessee area three land-use classifications could be distinguished; cropland, wetland, and forest. In the East Tennessee study area, measurements were submitted to statistical tests which verified the significant differences due to natural terrain, stripped areas, various stages of reclamation, water, etc. Classifications for both studies were output in the form of maps of symbols and varying shades of gray.

The Research of Spatial-Temporal Analysis and Decision-Making Assistant System for Disabled Person Affairs Based on Mapworld

NASA Astrophysics Data System (ADS)

Zhang, J. H.; Yang, J.; Sun, Y. S.

2015-06-01

This system combines the Mapworld platform and informationization of disabled person affairs, uses the basic information of disabled person as center frame. Based on the disabled person population database, the affairs management system and the statistical account system, the data were effectively integrated and the united information resource database was built. Though the data analysis and mining, the system provides powerful data support to the decision making, the affairs managing and the public serving. It finally realizes the rationalization, normalization and scientization of disabled person affairs management. It also makes significant contributions to the great-leap-forward development of the informationization of China Disabled Person's Federation.

78 FR 5055 - Pattern of Violations

Federal Register 2010, 2011, 2012, 2013, 2014

2013-01-23

...The Mine Safety and Health Administration (MSHA) is revising the Agency's existing regulation for pattern of violations (POV). MSHA has determined that the existing regulation does not adequately achieve the intent of the Federal Mine Safety and Health Act of 1977 (Mine Act) that the POV provision be used to address mine operators who have demonstrated a disregard for the health and safety of miners. Congress included the POV provision in the Mine Act so that mine operators would manage health and safety conditions at mines and find and fix the root causes of significant and substantial (S&S) violations, protecting the health and safety of miners. The final rule simplifies the existing POV criteria, improves consistency in applying the POV criteria, and more effectively achieves the Mine Act's statutory intent. It also encourages chronic safety violators to comply with the Mine Act and MSHA's health and safety standards.

Automatic mine detection based on multiple features

NASA Astrophysics Data System (ADS)

Yu, Ssu-Hsin; Gandhe, Avinash; Witten, Thomas R.; Mehra, Raman K.

2000-08-01

Recent research sponsored by the Army, Navy and DARPA has significantly advanced the sensor technologies for mine detection. Several innovative sensor systems have been developed and prototypes were built to investigate their performance in practice. Most of the research has been focused on hardware design. However, in order for the systems to be in wide use instead of in limited use by a small group of well-trained experts, an automatic process for mine detection is needed to make the final decision process on mine vs. no mine easier and more straightforward. In this paper, we describe an automatic mine detection process consisting of three stage, (1) signal enhancement, (2) pixel-level mine detection, and (3) object-level mine detection. The final output of the system is a confidence measure that quantifies the presence of a mine. The resulting system was applied to real data collected using radar and acoustic technologies.

A Need for Systems Architecture Approach for Next Generation Mine Warfare Capability

DTIC Science & Technology

2006-09-01

MRUUV Mission Reconfigurable Unmanned Undersea Vehicle MSC Mine Countermeasures Ship Coastal MSO Mine Countermeasures Ship Open-ocean P3I Preplanned...Helicopter, the Remote Mine Hunting System (RMS), the Mission Reconfigurable Unmanned Undersea Vehicle (MRUUV) and finally the Littoral Combat Ship (LCS...guarding against the sophisticated Soviet blue-water, air, and undersea threats. Yet since World War II, U.S. Naval Forces have suffered significantly

Malaria in gold-mining areas in Colombia

PubMed Central

Castellanos, Angélica; Chaparro-Narváez, Pablo; Morales-Plaza, Cristhian David; Alzate, Alberto; Padilla, Julio; Arévalo, Myriam; Herrera, Sócrates

2016-01-01

Gold-mining may play an important role in the maintenance of malaria worldwide. Gold-mining, mostly illegal, has significantly expanded in Colombia during the last decade in areas with limited health care and disease prevention. We report a descriptive study that was carried out to determine the malaria prevalence in gold-mining areas of Colombia, using data from the public health surveillance system (National Health Institute) during the period 2010-2013. Gold-mining was more prevalent in the departments of Antioquia, Córdoba, Bolívar, Chocó, Nariño, Cauca, and Valle, which contributed 89.3% (270,753 cases) of the national malaria incidence from 2010-2013 and 31.6% of malaria cases were from mining areas. Mining regions, such as El Bagre, Zaragoza, and Segovia, in Antioquia, Puerto Libertador and Montelíbano, in Córdoba, and Buenaventura, in Valle del Cauca, were the most endemic areas. The annual parasite index (API) correlated with gold production (R2 0.82, p < 0.0001); for every 100 kg of gold produced, the API increased by 0.54 cases per 1,000 inhabitants. Lack of malaria control activities, together with high migration and proliferation of mosquito breeding sites, contribute to malaria in gold-mining regions. Specific control activities must be introduced to control this significant source of malaria in Colombia. PMID:26814645

Malaria in gold-mining areas in Colombia.

PubMed

Castellanos, Angélica; Chaparro-Narváez, Pablo; Morales-Plaza, Cristhian David; Alzate, Alberto; Padilla, Julio; Arévalo, Myriam; Herrera, Sócrates

2016-01-01

Gold-mining may play an important role in the maintenance of malaria worldwide. Gold-mining, mostly illegal, has significantly expanded in Colombia during the last decade in areas with limited health care and disease prevention. We report a descriptive study that was carried out to determine the malaria prevalence in gold-mining areas of Colombia, using data from the public health surveillance system (National Health Institute) during the period 2010-2013. Gold-mining was more prevalent in the departments of Antioquia, Córdoba, Bolívar, Chocó, Nariño, Cauca, and Valle, which contributed 89.3% (270,753 cases) of the national malaria incidence from 2010-2013 and 31.6% of malaria cases were from mining areas. Mining regions, such as El Bagre, Zaragoza, and Segovia, in Antioquia, Puerto Libertador and Montelíbano, in Córdoba, and Buenaventura, in Valle del Cauca, were the most endemic areas. The annual parasite index (API) correlated with gold production (R2 0.82, p < 0.0001); for every 100 kg of gold produced, the API increased by 0.54 cases per 1,000 inhabitants. Lack of malaria control activities, together with high migration and proliferation of mosquito breeding sites, contribute to malaria in gold-mining regions. Specific control activities must be introduced to control this significant source of malaria in Colombia.

Data Mining CMMSs: How to Convert Data into Knowledge.

PubMed

Fennigkoh, Larry; Nanney, D Courtney

2018-01-01

Although the healthcare technology management (HTM) community has decades of accumulated medical device-related maintenance data, little knowledge has been gleaned from these data. Finding and extracting such knowledge requires the use of the well-established, but admittedly somewhat foreign to HTM, application of inferential statistics. This article sought to provide a basic background on inferential statistics and describe a case study of their application, limitations, and proper interpretation. The research question associated with this case study involved examining the effects of ventilator preventive maintenance (PM) labor hours, age, and manufacturer on needed unscheduled corrective maintenance (CM) labor hours. The study sample included more than 21,000 combined PM inspections and CM work orders on 2,045 ventilators from 26 manufacturers during a five-year period (2012-16). A multiple regression analysis revealed that device age, manufacturer, and accumulated PM inspection labor hours all influenced the amount of CM labor significantly (P < 0.001). In essence, CM labor hours increased with increasing PM labor. However, and despite the statistical significance of these predictors, the regression analysis also indicated that ventilator age, manufacturer, and PM labor hours only explained approximately 16% of all variability in CM labor, with the remainder (84%) caused by other factors that were not included in the study. As such, the regression model obtained here is not suitable for predicting ventilator CM labor hours.

Reconnaissance investigation of the rough diamond resource potential and production capacity of Côte d’Ivoire

USGS Publications Warehouse

Chirico, Peter G.; Malpeli, Katherine C.

2013-01-01

Ethnic and political conflict developed into open civil war in Côte d’Ivoire in 2002, leading to a de facto partitioning of the country into the government-controlled south and the rebel-controlled north. Côte d’Ivoire’s two main diamond mining areas, Séguéla and Tortiya, are located in the north, under what was, until recently, rebel-controlled territory. In an effort to prevent proceeds from diamond mining from funding the conflict, the United Nations (UN) placed an embargo on the export of rough diamonds from Côte d’Ivoire in 2005. That same year, the Kimberley Process (KP), the international initiative charged with stemming the flow of conflict diamonds, acted to enforce this ban by adopting the Moscow Resolution on Côte d’Ivoire, which contained measures to prevent the infiltration of Ivorian diamonds into the legitimate global rough diamond trade. Though under scrutiny by the international community, diamond mining activities continued in Côte d’Ivoire, with artisanal miners exploiting both alluvial deposits in fluvial systems and primary kimberlitic dike deposits. However, because of the embargo, there has been no official record of diamond production since the conflict began in 2002. This lack of production statistics represents a significant data gap and hinders efforts by the KP to understand how illicitly produced diamonds may be entering the legitimate trade. This study presents the results of a multiyear effort to monitor the diamond mining activities of Côte d’Ivoire’s two main diamond mining areas, Séguéla and Tortiya. An innovative approach was developed that integrates data acquired from archival reports and maps, high-resolution satellite imagery, and digital terrain modeling to assess the total diamond endowment of the Séguéla and Tortiya deposits and to calculate annual diamond production from 2006 to 2013. On the basis of currently available data, this study estimates that a total of 10,100,000 carats remain in Séguéla and a total of 1,100,000 carats remain in Tortiya. Production capacity was calculated for the two study areas for the years 2006–2010 and 2012–2013. Production capacity was found to range from between 38,000 carats and 375,000 carats in Séguéla and from 13,000 carats and 20,000 carats in Tortiya. Further, this study demonstrates that artisanal mining activities can be successfully monitored by using remote sensing and geologic modeling techniques. The production capacity estimates presented here fill a significant data gap and provide policy makers, the UN, and the KP with important information not otherwise available.

78 FR 75924 - Request for Nominations of Candidates To Serve on the Mine Safety and Health Research Advisory...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-12-13

... findings. This advice may take the form of reports or verbal communications to the NIOSH Director during..., statistics, and psychology. Federal employees will not be considered for membership. Members may be invited...

Cost estimation and analysis using the Sherpa Automated Mine Cost Engineering System

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

Stebbins, P.E.

1993-09-01

The Sherpa Automated Mine Cost Engineering System is a menu-driven software package designed to estimate capital and operating costs for proposed surface mining operations. The program is engineering (as opposed to statistically) based, meaning that all equipment, manpower, and supply requirements are determined from deposit geology, project design and mine production information using standard engineering techniques. These requirements are used in conjunction with equipment, supply, and labor cost databases internal to the program to estimate all associated costs. Because virtually all on-site cost parameters are interrelated within the program, Sherpa provides an efficient means of examining the impact of changesmore » in the equipment mix on total capital and operating costs. If any aspect of the operation is changed, Sherpa immediately adjusts all related aspects as necessary. For instance, if the user wishes to examine the cost ramifications of selecting larger trucks, the program not only considers truck purchase and operation costs, it also automatically and immediately adjusts excavator requirements, operator and mechanic needs, repair facility size, haul road construction and maintenance costs, and ancillary equipment specifications.« less

Transplantation of epiphytic bioaccumulators (Tillandsia capillaris) for high spatial resolution biomonitoring of trace elements and point sources deconvolution in a complex mining/smelting urban context

NASA Astrophysics Data System (ADS)

Goix, Sylvaine; Resongles, Eléonore; Point, David; Oliva, Priscia; Duprey, Jean Louis; de la Galvez, Erika; Ugarte, Lincy; Huayta, Carlos; Prunier, Jonathan; Zouiten, Cyril; Gardon, Jacques

2013-12-01

Monitoring atmospheric trace elements (TE) levels and tracing their source origin is essential for exposure assessment and human health studies. Epiphytic Tillandsia capillaris plants were used as bioaccumulator of TE in a complex polymetallic mining/smelting urban context (Oruro, Bolivia). Specimens collected from a pristine reference site were transplanted at a high spatial resolution (˜1 sample/km2) throughout the urban area. About twenty-seven elements were measured after a 4-month exposure, also providing new information values for reference material BCR482. Statistical power analysis for this biomonitoring mapping approach against classical aerosols surveys performed on the same site showed the better aptitude of T. Capillaris to detect geographical trend, and to deconvolute multiple contamination sources using geostatistical principal component analysis. Transplanted specimens in the vicinity of the mining and smelting areas were characterized by extreme TE accumulation (Sn > Ag > Sb > Pb > Cd > As > W > Cu > Zn). Three contamination sources were identified: mining (Ag, Pb, Sb), smelting (As, Sn) and road traffic (Zn) emissions, confirming results of previous aerosol survey.

The Mine Safety and Health Administration's criterion threshold value policy increases miners' risk of pneumoconiosis.

PubMed

Weeks, James L

2006-06-01

The Mine Safety and Health Administration (MSHA) proposes to issue citations for non-compliance with the exposure limit for respirable coal mine dust when measured exposure exceeds the exposure limit with a "high degree of confidence." This criterion threshold value (CTV) is derived from the sampling and analytical error of the measurement method. This policy is based on a combination of statistical and legal reasoning: the one-tailed 95% confidence limit of the sampling method, the apparent principle of due process and a standard of proof analogous to "beyond a reasonable doubt." This policy raises the effective exposure limit, it is contrary to the precautionary principle, it is not a fair sharing of the burden of uncertainty, and it employs an inappropriate standard of proof. Its own advisory committee and NIOSH have advised against this policy. For longwall mining sections, it results in a failure to issue citations for approximately 36% of the measured values that exceed the statutory exposure limit. Citations for non-compliance with the respirable dust standard should be issued for any measure exposure that exceeds the exposure limit.

A GIS and statistical approach to identify variables that control water quality in hydrothermally altered and mineralized watersheds, Silverton, Colorado, USA

USGS Publications Warehouse

Yager, Douglas B.; Johnson, Raymond H.; Rockwell, Barnaby W.; Caine, Jonathan S.; Smith, Kathleen S.

2013-01-01

Hydrothermally altered bedrock in the Silverton mining area, southwest Colorado, USA, contains sulfide minerals that weather to produce acidic and metal-rich leachate that is toxic to aquatic life. This study utilized a geographic information system (GIS) and statistical approach to identify watershed-scale geologic variables in the Silverton area that influence water quality. GIS analysis of mineral maps produced using remote sensing datasets including Landsat Thematic Mapper, advanced spaceborne thermal emission and reflection radiometer, and a hybrid airborne visible infrared imaging spectrometer and field-based product enabled areas of alteration to be quantified. Correlations between water quality signatures determined at watershed outlets, and alteration types intersecting both total watershed areas and GIS-buffered areas along streams were tested using linear regression analysis. Despite remote sensing datasets having varying watershed area coverage due to vegetation cover and differing mineral mapping capabilities, each dataset was useful for delineating acid-generating bedrock. Areas of quartz–sericite–pyrite mapped by AVIRIS have the highest correlations with acidic surface water and elevated iron and aluminum concentrations. Alkalinity was only correlated with area of acid neutralizing, propylitically altered bedrock containing calcite and chlorite mapped by AVIRIS. Total watershed area of acid-generating bedrock is more significantly correlated with acidic and metal-rich surface water when compared with acid-generating bedrock intersected by GIS-buffered areas along streams. This methodology could be useful in assessing the possible effects that alteration type area has in either generating or neutralizing acidity in unmined watersheds and in areas where new mining is planned.

Web mining in soft computing framework: relevance, state of the art and future directions.

PubMed

Pal, S K; Talwar, V; Mitra, P

2002-01-01

The paper summarizes the different characteristics of Web data, the basic components of Web mining and its different types, and the current state of the art. The reason for considering Web mining, a separate field from data mining, is explained. The limitations of some of the existing Web mining methods and tools are enunciated, and the significance of soft computing (comprising fuzzy logic (FL), artificial neural networks (ANNs), genetic algorithms (GAs), and rough sets (RSs) are highlighted. A survey of the existing literature on "soft Web mining" is provided along with the commercially available systems. The prospective areas of Web mining where the application of soft computing needs immediate attention are outlined with justification. Scope for future research in developing "soft Web mining" systems is explained. An extensive bibliography is also provided.

Mercury and methylmercury contamination related to artisanal gold mining, Suriname

USGS Publications Warehouse

Gray, J.E.; Labson, V.F.; Weaver, J.N.; Krabbenhoft, D.P.

2002-01-01

Elemental Hg-Au amalgamation mining practices are used widely in many developing countries resulting in significant Hg contamination of surrounding ecosystems. We have measured total Hg and methyl-Hg concentrations in sediment and water collected from artisanal Au mines and these are the first Hg speciation data from such mines in Suriname. Total Hg and methyl-Hg contents in mine-waste sediment and water are elevated over local uncontaminated baselines. Total Hg (10-930 ng/L) and methyl-Hg (0.02-3.8 ng/L) are highly elevated in mine waters. Increasing total Hg contents in discharged mine waters correlate with increasing water turbidity indicating that most Hg transport is on suspended particulates. Our Hg results are similar to those found in artisanal Au mines in the Amazon basin, where Hg contamination has led to adverse effects on tropical ecosystems.

Metal contamination in environmental media in residential areas around Romanian mining sites

EPA Science Inventory

Hard-rock mining for metals, such as gold, silver, copper, zinc, iron and others, is recognized to have a significant impact on the environmental media, soil and water, in particular. Toxic contaminants released from mine waste to surface water and groundwater is the primary co...

78 FR 40496 - Notice of availability of the Final Environmental Impact Statement for the Proposed Hollister...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-07-05

... silver mining operation. Most of the infrastructure to support a mining operation was authorized and.... The Proposed Action consists of underground mining, constructing a new production shaft, improving.... Public comments resulted in the addition of clarifying text, but did not significantly change the...

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

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.

Surface water monitoring in the mercury mining district of Asturias (Spain).

PubMed

Loredo, Jorge; Petit-Domínguez, María Dolores; Ordóñez, Almudena; Galán, María Pilar; Fernández-Martínez, Rodolfo; Alvarez, Rodrigo; Rucandio, María Isabel

2010-04-15

Systematic monitoring of surface waters in the area of abandoned mine sites constitutes an essential step in the characterisation of pollution from historic mine sites. The analytical data collected throughout a hydrologic period can be used for hydrological modelling and also to select appropriate preventive and/or corrective measures in order to avoid pollution of watercourses. Caudal River drains the main abandoned Hg mine sites (located in Mieres and Pola de Lena districts) in Central Asturias (NW Spain). This paper describes a systematic monitoring of physical and chemical parameters in eighteen selected sampling points within the Caudal River catchment. At each sampling station, water flow, pH, specific conductance, dissolved oxygen, salinity, temperature, redox potential and turbidity were controlled "in situ" and major and trace elements were analysed in the laboratory. In the Hg-mineralised areas, As is present in the form of As-rich pyrite, realgar and occasionally arsenopyrite. Mine drainage and leachates from spoil heaps exhibit in some cases acidic conditions and high As contents, and they are incorporated to Caudal River tributaries. Multivariate statistical analysis aids to the interpretation of the spatial and temporary variations found in the sampled areas, as part of a methodology applicable to different environmental and geological studies. 2009 Elsevier B.V. All rights reserved.

Censored data treatment using additional information in intelligent medical systems

NASA Astrophysics Data System (ADS)

Zenkova, Z. N.

2015-11-01

Statistical procedures are a very important and significant part of modern intelligent medical systems. They are used for proceeding, mining and analysis of different types of the data about patients and their diseases; help to make various decisions, regarding the diagnosis, treatment, medication or surgery, etc. In many cases the data can be censored or incomplete. It is a well-known fact that censorship considerably reduces the efficiency of statistical procedures. In this paper the author makes a brief review of the approaches which allow improvement of the procedures using additional information, and describes a modified estimation of an unknown cumulative distribution function involving additional information about a quantile which is known exactly. The additional information is used by applying a projection of a classical estimator to a set of estimators with certain properties. The Kaplan-Meier estimator is considered as an estimator of the unknown cumulative distribution function, the properties of the modified estimator are investigated for a case of a single right censorship by means of simulations.

On-line Machine Learning and Event Detection in Petascale Data Streams

NASA Astrophysics Data System (ADS)

Thompson, David R.; Wagstaff, K. L.

2012-01-01

Traditional statistical data mining involves off-line analysis in which all data are available and equally accessible. However, petascale datasets have challenged this premise since it is often impossible to store, let alone analyze, the relevant observations. This has led the machine learning community to investigate adaptive processing chains where data mining is a continuous process. Here pattern recognition permits triage and followup decisions at multiple stages of a processing pipeline. Such techniques can also benefit new astronomical instruments such as the Large Synoptic Survey Telescope (LSST) and Square Kilometre Array (SKA) that will generate petascale data volumes. We summarize some machine learning perspectives on real time data mining, with representative cases of astronomical applications and event detection in high volume datastreams. The first is a "supervised classification" approach currently used for transient event detection at the Very Long Baseline Array (VLBA). It injects known signals of interest - faint single-pulse anomalies - and tunes system parameters to recover these events. This permits meaningful event detection for diverse instrument configurations and observing conditions whose noise cannot be well-characterized in advance. Second, "semi-supervised novelty detection" finds novel events based on statistical deviations from previous patterns. It detects outlier signals of interest while considering known examples of false alarm interference. Applied to data from the Parkes pulsar survey, the approach identifies anomalous "peryton" phenomena that do not match previous event models. Finally, we consider online light curve classification that can trigger adaptive followup measurements of candidate events. Classifier performance analyses suggest optimal survey strategies, and permit principled followup decisions from incomplete data. These examples trace a broad range of algorithm possibilities available for online astronomical data mining. This talk describes research performed at the Jet Propulsion Laboratory, California Institute of Technology. Copyright 2012, All Rights Reserved. U.S. Government support acknowledged.

The siting of a prison complex above an abandoned underground coal mine

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

Marino, G.G.

1997-12-31

This paper discusses in detail the process undertaken to mitigate the effects of any future mine subsidence on prison structures proposed above old abandoned underground workings. The site for a proposed prison complex purchased by the State of Indiana was located in west-central Indiana and was undermined by an old abandoned room and pillar mine. The original plan for construction consisted of one phase. Based on a study of the mine map and subsurface verification of the extent of mining it was determined that all prison buildings and important structures could be placed above solid coal to the north. Onemore » masonry building, however, was located within the potential draw zone of mine works which still contained significant mine voids. Based on empirical data the subsidence potential was estimated and the building was accordingly designed to be mine subsidence resistant. It was decided that a phase two prison complex should be constructed adjacent to and just south of the Phase I complex. This complex would be directly above the underground workings. The first stage of design was to minimize subsidence potential by positioning the exposure of significant structures to the subjacent mining assuming the mine map was sufficiently accurate. Subsequently, an extensive subsurface investigation program was then undertaken to: (1) ascertain whether or not mine areas where buildings would be located were already collapsed and thus only nominal, if any, subsidence could occur in the future; and (2) verify the presence of solid coal areas within the mine as indicated on the mine map. Based on all the site information gathered subsidence profiles were developed from an empirical data base of subsidence events in the Illinois Coal Basin. As a result of this work many structures on the site required no or nominal subsidence considerations.« less

[Pollution Assessment and Spatial Distribution Characteristics of Heavy Metals in Soils of Coal Mining Area in Longkou City].

PubMed

Liu, Shuo; Wu, Quan-yuan; Cao, Xue-jiang; Wang, Ji-ning; Zhang, Long-long; Cai, Dong-quan; Zhou, Li-yuan; Liu, Na

2016-01-15

The present paper takes the coal mining area of Longkou City as the research area. Thirty-six topsoil (0-20 cm) samples were collected and the contents of 5 kinds of heavy metals were determined, including Cd, As, Ni, Ph, Cr. Geo-statistics analysis was used to analyze the spatial distribution of heavy metals. Principal component analysis (PCA) was used to explore the pollution sources of heavy metals and the degree of heavy metals pollution was evaluated by weighted average comprehensive pollution evaluation method. The results showed that enrichment phenomenon was significant for the 5 kinds of heavy metals. Taking secondary standard of National Environment Quality Standard for Soil as the background value, their exceed standard rates were 72.22%, 100%, 100%, 91.67%, 100%, respectively. Average contents of heavy metals in the soil samples were all over the national standard level two and were 1.53, 11.86, 2.40, 1.31, 4.09 times of the background value. In addition, the average contents were much higher than the background value of the topsoil in the eastern part of Shandong Province and were 9.85, 39.98, 8.85, 4.29, 12.71 times of the background value. According to the semivariogram model, we obtained the nugget-effects of 5 kinds of heavy metals and their values were in the order of As (0.644) > Cd (0.627) > Cr (0.538) > Ni (0.411) > Pb (0.294), all belonging to moderate spatial correlation. On the whole, the central part of the Sangyuan Coal Mine and its surrounding areas were the most seriously polluted, while the pollution of heavy metals in the east and west of the study area was relatively light. Principal component analysis suggested that the enrichment of Cd, As, Ni, Cr was due to irrigation of wastewater, the discharge of industry and enterprise, and the industrial activity. Automobile exhaust and coal combustion were the main pollution sources of Pb. The single-factor assessment of heavy metals pollution showed that the degree of different heavy metals pollution was in the order of As > Cr > Ni > Cd > Pb. Simultaneously, comprehensive pollution evaluation showed that the degree of heavy metals pollution in the study area was very serious, with comprehensive pollution index ranging from 2.17 to 4.66, among which, the numbers of moderate and heavy pollution samples were 10 and 26, respectively. Areas with heavy pollution were mainly distributed in the Sangyuan Coal Mine, Beizao Coal Mine, Liuhai Coal Mine; and the areas with moderate pollution covered Wali Coal Mine, Liangjia Coal Mine, and other regions. The results of this paper will provide data reference and theoretical support for the study of ecological risk assessment in the study area.

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.

Geochemistry and mineralogy of arsenic in mine wastes and stream sediments in a historic metal mining area in the UK.

PubMed

Rieuwerts, J S; Mighanetara, K; Braungardt, C B; Rollinson, G K; Pirrie, D; Azizi, F

2014-02-15

Mining generates large amounts of waste which may contain potentially toxic elements (PTE), which, if released into the wider environment, can cause air, water and soil pollution long after mining operations have ceased. The fate and toxicological impact of PTEs are determined by their partitioning and speciation and in this study, the concentrations and mineralogy of arsenic in mine wastes and stream sediments in a former metal mining area of the UK are investigated. Pseudo-total (aqua-regia extractable) arsenic concentrations in all samples from the mining area exceeded background and guideline values by 1-5 orders of magnitude, with a maximum concentration in mine wastes of 1.8×10(5)mgkg(-1) As and concentrations in stream sediments of up to 2.5×10(4)mgkg(-1) As, raising concerns over potential environmental impacts. Mineralogical analysis of the wastes and sediments was undertaken by scanning electron microscopy (SEM) and automated SEM-EDS based quantitative evaluation (QEMSCAN®). The main arsenic mineral in the mine waste was scorodite and this was significantly correlated with pseudo-total As concentrations and significantly inversely correlated with potentially mobile arsenic, as estimated from the sum of exchangeable, reducible and oxidisable arsenic fractions obtained from a sequential extraction procedure; these findings correspond with the low solubility of scorodite in acidic mine wastes. The work presented shows that the study area remains grossly polluted by historical mining and processing and illustrates the value of combining mineralogical data with acid and sequential extractions to increase our understanding of potential environmental threats. Copyright © 2013 Elsevier B.V. All rights reserved.

Using knowledge for indexing health web resources in a quality-controlled gateway.

PubMed

Joubert, Michel; Darmoni, Stefan J; Avillach, Paul; Dahamna, Badisse; Fieschi, Marius

2008-01-01

The aim of this study is to provide to indexers MeSH terms to be considered as major ones in a list of terms automatically extracted from a document. We propose a method combining symbolic knowledge - the UMLS Metathesaurus and Semantic Network - and statistical knowledge drawn from co-occurrences of terms in the CISMeF database (a French-language quality-controlled health gateway) using data mining measures. The method was tested on CISMeF corpus of 293 resources. There was a proportion of 0.37+/-0.26 major terms in the processed records. The method produced lists of terms with a proportion of terms initially pointed out as major of 0.54+/-0.31. The method we propose reduces the number of terms, which seem not useful for content description of resources, such as "check tags", but retains the most descriptive ones. Discarding these terms is accounted for by: 1) the removal by using semantic knowledge of associations of concepts bearing no real medical significance, 2) the removal by using statistical knowledge of nonstatistically significant associations of terms. This method can assist effectively indexers in their daily work and will be soon applied in the CISMeF system.

[Soil seed bank formation during early revegetation of areas affected by mining in a tropical rain forest of Chocó, Colombia].

PubMed

Valois-Cuesta, Hamleth; Martínez-Ruiz, Carolina; Urrutia-Rivas, Yorley

2017-03-01

Mining is one of the main economic activities in many tropical regions and is the cause of devastation of large areas of natural tropical forests. The knowledge of the regenerative potential of mining disturbed areas provides valuable information for their ecological restoration. The aim of this study was to evaluate the effect of age of abandonment of mines and their distance from the adjacent forest, on the formation of soil seed bank in abandoned mines in the San Juan, Chocó, Colombia. To do this, we determined the abundance and species composition of the soil seed bank, and the dynamics of seed rain in mines of different cessation period of mining activity (6 and 15 years), and at different distances from the adjacent forest matrix (50 and 100 m). Seed rain was composed by five species of plants with anemocorous dispersion, and was more abundant in the mine of 6 years than in the mine of 15 years. There were no significant differences in the number of seeds collected at 50 m and 100 m from the adjacent forest. The soil seed bank was represented by eight species: two with anemocorous dispersion (common among the seed rain species) and the rest with zoochorous dispersion. The abundance of seeds in the soil did not vary with the age of the mine, but was higher at close distances to the forest edge than far away. During the early revegetation, the formation of the soil seed bank in the mines seems to be related to their proximity to other disturbed areas, rather than their proximity to the adjacent forest or the cessation activity period of mines. Therefore, the establishment of artificial perches or the maintenance of isolated trees in the abandoned mines could favour the arrival of bird-dispersed seeds at mines. However, since the soil seed bank can be significantly affected by the high rainfall in the study area, more studies are needed to evaluate management actions to encourage soil seed bank formation in mines of high-rainfall environments in the Chocó region.

Impact of potential phosphate mining on the hydrology of Osceola National Forest, Florida

USGS Publications Warehouse

Miller, James A.; Hughes, G.H.; Hull, R.W.; Vecchioli, John; Seaber, P.R.

1978-01-01

Potentially exploitable phosphate deposits underlie part of Osceola National Forest, Fla. Hydrologic conditions in the forest are comparable with those in nearby Hamilton County, where phosphate mining and processing have been ongoing since 1965. Given similarity of operations, hydroloigc effects of mining in the forest are predicted. Flow of stream receiving phosphate industry effluent would increase somewhat during mining, but stream quality would not be greatly affected. Local changes in the configuration of the water table and the quality of water in the surficial aquifer will occur. Lowering of the potentiometric surface of the Floridan aquifer because of proposed pumpage would be less than five feet at nearby communities. Flordian aquifer water quality would be appreciably changed only if industrial effluent were discharged into streams which recharge the Flordian through sinkholes. The most significant hydrologic effects would occur at the time of active mining: long-term effects would be less significant. (Woodard-USGS)

The Evolution of Joint Operations during the Civil War

DTIC Science & Technology

2009-06-12

requested a large quantity of anti-personnel mines to enhance the minefield in front of the land face.64 Lamb‘s requests did not elicit a significant... mines the Confederates had buried. Several of the men realized what they were (buried anti-personnel torpedoes) and systematically disabled them by...devices which today would include booby traps, land mines , naval mines and others. 118 Traverse--A fortified gun emplacement in a fortified position

Impacts of manganese mining activity on the environment: interactions among soil, plants, and arbuscular mycorrhiza.

PubMed

Rivera-Becerril, Facundo; Juárez-Vázquez, Lucía V; Hernández-Cervantes, Saúl C; Acevedo-Sandoval, Otilio A; Vela-Correa, Gilberto; Cruz-Chávez, Enrique; Moreno-Espíndola, Iván P; Esquivel-Herrera, Alfonso; de León-González, Fernando

2013-02-01

The mining district of Molango in the Hidalgo State, Mexico, possesses one of the largest deposits of manganese (Mn) ore in the world. This research assessed the impacts of Mn mining activity on the environment, particularly the interactions among soil, plants, and arbuscular mycorrhiza (AM) at a location under the influence of an open Mn mine. Soils and plants from three sites (soil under maize, soil under native vegetation, and mine wastes with some vegetation) were analyzed. Available Mn in both soil types and mine wastes did not reach toxic levels. Samples of the two soil types were similar regarding physical, chemical, and biological properties; mine wastes were characterized by poor physical structure, nutrient deficiencies, and a decreased number of arbuscular mycorrhizal fungi (AMF) spores. Tissues of six plant species accumulated Mn at normal levels. AM was absent in the five plant species (Ambrosia psilostachya, Chenopodium ambrosoides, Cynodon dactylon, Polygonum hydropiperoides, and Wigandia urens) established in mine wastes, which was consistent with the significantly lower number of AMF spores compared with both soil types. A. psilostachya (native vegetation) and Zea mays showed mycorrhizal colonization in their root systems; in the former, AM significantly decreased Mn uptake. The following was concluded: (1) soils, mine wastes, and plant tissues did not accumulate Mn at toxic levels; (2) despite its poor physical structure and nutrient deficiencies, the mine waste site was colonized by at least five plant species; (3) plants growing in both soil types interacted with AMF; and (4) mycorrhizal colonization of A. psilostachya influenced low uptake of Mn by plant tissues.

Underwater target classification using wavelet packets and neural networks.

PubMed

Azimi-Sadjadi, M R; Yao, D; Huang, Q; Dobeck, G J

2000-01-01

In this paper, a new subband-based classification scheme is developed for classifying underwater mines and mine-like targets from the acoustic backscattered signals. The system consists of a feature extractor using wavelet packets in conjunction with linear predictive coding (LPC), a feature selection scheme, and a backpropagation neural-network classifier. The data set used for this study consists of the backscattered signals from six different objects: two mine-like targets and four nontargets for several aspect angles. Simulation results on ten different noisy realizations and for signal-to-noise ratio (SNR) of 12 dB are presented. The receiver operating characteristic (ROC) curve of the classifier generated based on these results demonstrated excellent classification performance of the system. The generalization ability of the trained network was demonstrated by computing the error and classification rate statistics on a large data set. A multiaspect fusion scheme was also adopted in order to further improve the classification performance.

Cardiac data mining (CDM); organization and predictive analytics on biomedical (cardiac) data

NASA Astrophysics Data System (ADS)

Bilal, M. Musa; Hussain, Masood; Basharat, Iqra; Fatima, Mamuna

2013-10-01

Data mining and data analytics has been of immense importance to many different fields as we witness the evolution of data sciences over recent years. Biostatistics and Medical Informatics has proved to be the foundation of many modern biological theories and analysis techniques. These are the fields which applies data mining practices along with statistical models to discover hidden trends from data that comprises of biological experiments or procedures on different entities. The objective of this research study is to develop a system for the efficient extraction, transformation and loading of such data from cardiologic procedure reports given by Armed Forces Institute of Cardiology. It also aims to devise a model for the predictive analysis and classification of this data to some important classes as required by cardiologists all around the world. This includes predicting patient impressions and other important features.

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.

Interpreter of maladies: redescription mining applied to biomedical data analysis.

PubMed

Waltman, Peter; Pearlman, Alex; Mishra, Bud

2006-04-01

Comprehensive, systematic and integrated data-centric statistical approaches to disease modeling can provide powerful frameworks for understanding disease etiology. Here, one such computational framework based on redescription mining in both its incarnations, static and dynamic, is discussed. The static framework provides bioinformatic tools applicable to multifaceted datasets, containing genetic, transcriptomic, proteomic, and clinical data for diseased patients and normal subjects. The dynamic redescription framework provides systems biology tools to model complex sets of regulatory, metabolic and signaling pathways in the initiation and progression of a disease. As an example, the case of chronic fatigue syndrome (CFS) is considered, which has so far remained intractable and unpredictable in its etiology and nosology. The redescription mining approaches can be applied to the Centers for Disease Control and Prevention's Wichita (KS, USA) dataset, integrating transcriptomic, epidemiological and clinical data, and can also be used to study how pathways in the hypothalamic-pituitary-adrenal axis affect CFS patients.

Modelling the sensory space of varietal wines: Mining of large, unstructured text data and visualisation of style patterns.

PubMed

Valente, Carlo C; Bauer, Florian F; Venter, Fritz; Watson, Bruce; Nieuwoudt, Hélène H

2018-03-21

The increasingly large volumes of publicly available sensory descriptions of wine raises the question whether this source of data can be mined to extract meaningful domain-specific information about the sensory properties of wine. We introduce a novel application of formal concept lattices, in combination with traditional statistical tests, to visualise the sensory attributes of a big data set of some 7,000 Chenin blanc and Sauvignon blanc wines. Complexity was identified as an important driver of style in hereto uncharacterised Chenin blanc, and the sensory cues for specific styles were identified. This is the first study to apply these methods for the purpose of identifying styles within varietal wines. More generally, our interactive data visualisation and mining driven approach opens up new investigations towards better understanding of the complex field of sensory science.

Cluster analysis as a prediction tool for pregnancy outcomes.

PubMed

Banjari, Ines; Kenjerić, Daniela; Šolić, Krešimir; Mandić, Milena L

2015-03-01

Considering specific physiology changes during gestation and thinking of pregnancy as a "critical window", classification of pregnant women at early pregnancy can be considered as crucial. The paper demonstrates the use of a method based on an approach from intelligent data mining, cluster analysis. Cluster analysis method is a statistical method which makes possible to group individuals based on sets of identifying variables. The method was chosen in order to determine possibility for classification of pregnant women at early pregnancy to analyze unknown correlations between different variables so that the certain outcomes could be predicted. 222 pregnant women from two general obstetric offices' were recruited. The main orient was set on characteristics of these pregnant women: their age, pre-pregnancy body mass index (BMI) and haemoglobin value. Cluster analysis gained a 94.1% classification accuracy rate with three branch- es or groups of pregnant women showing statistically significant correlations with pregnancy outcomes. The results are showing that pregnant women both of older age and higher pre-pregnancy BMI have a significantly higher incidence of delivering baby of higher birth weight but they gain significantly less weight during pregnancy. Their babies are also longer, and these women have significantly higher probability for complications during pregnancy (gestosis) and higher probability of induced or caesarean delivery. We can conclude that the cluster analysis method can appropriately classify pregnant women at early pregnancy to predict certain outcomes.

Prior to the Oral Therapy, What Do We Know About HCV-4 in Egypt: A Randomized Survey of Prevalence and Risks Using Data Mining Computed Analysis

PubMed Central

Abd Elrazek, Abd Elrazek; Bilasy, Shymaa E.; Elbanna, Abduh E. M.; Elsherif, Abd Elhalim A.

2014-01-01

Abstract Hepatitis C virus (HCV) affects over 180 million people worldwide and it's the leading cause of chronic liver diseases and hepatocellular carcinoma. HCV is classified into seven major genotypes and a series of subtypes. In general, HCV genotype 4 (HCV-4) is common in the Middle East and Africa, where it is responsible for more than 80% of HCV infections. Although HCV-4 is the cause of approximately 20% of the 180 million cases of chronic hepatitis C worldwide, it has not been a major subject of research yet. The aim of the current study is to survey the morbidities and disease complications among Egyptian population infected with HCV-4 using data mining advanced computing methods mainly and other complementary statistical analysis. Six thousand six hundred sixty subjects, aged between 17 and 58 years old, from different Egyptian Governorates were screened for HCV infection by ELISA and qualitative PCR. HCV-positive patients were further investigated for the incidence of liver cirrhosis and esophageal varices. Obtained data were analyzed by data mining approach. Among 6660 subjects enrolled in this survey, 1018 patients (15.28%) were HCV-positive. Proportion of infected-males was significantly higher than females; 61.6% versus 38.4% (P = 0.0052). Around two-third of infected-patients (635/1018; 62.4%) were presented with liver cirrhosis. Additionally, approximately half of the cirrhotic patients (301/635; 47.4%) showed degrees of large esophageal varices (LEVs), with higher variceal grade observed in males. Age for esophageal variceal development was 47 ± 1. Data mining analysis yielded esophageal wall thickness (>6.5 mm), determined by conventional U/S, as the only independent predictor for esophageal varices. This study emphasizes the high prevalence of HCV infection among Egyptian population, in particular among males. Egyptians with HCV-4 infection are at a higher risk to develop cirrhotic liver and esophageal varices. Data mining, a new analytic technique in medical field, shed light in this study on the clinical importance of esophageal wall thickness as a useful predictor for risky esophageal varices using decision tree algorithm. PMID:25526438

Mercury distribution in the soil-plant-air system at the Wanshan mercury mining district in Guizhou, Southwest China.

PubMed

Wang, Jianxu; Feng, Xinbin; Anderson, Christopher W N; Zhu, Wei; Yin, Runsheng; Wang, Heng

2011-12-01

The level of mercury bioaccumulation in wild plants; the distribution of bioavailable Hg, elemental Hg, and total Hg in soil; and the concentration of total gaseous Hg (TGM) in ambient air was studied at three different mining sites (SiKeng [SK], WuKeng [WK], and GouXi [GX]) in the Wanshan mercury mining district of China. Results of the present study showed that the distribution of soil total Hg, elemental Hg, bioavailable Hg, and TGM varies across the three mining sites. Higher soil total Hg (29.4-1,972.3 mg/kg) and elemental Hg (19.03-443.8 mg/kg) concentrations were recorded for plots SK and WK than for plot GX. Bioavailable Hg was lower at plot SK and GX (SK, 3-12 ng/g; GX, 9-14 ng/g) than at plot WK (11-1,063 ng/g), although the TGM concentration in the ambient air was significantly higher for plot GX (52,723 ng/m(3) ) relative to WK (106 ng/m(3) ) and SK (43 ng/m(3)). Mercury in sampled herbage was elevated and ranged from 0.8 to 4.75 mg/kg (SK), from 2.17 to 34.38 mg/kg (WK), and from 47.45 to 136.5 mg/kg (GX). Many of the sampled plants are used as fodder or for medicinal purposes. High shoot Hg concentrations may therefore pose an unacceptable human health risk. Statistical analysis of the recorded data showed that the Hg concentration in plant shoots was positively correlated with TGM and that the Hg concentration in roots was positively correlated with the bioavailable Hg concentration in the soil. The bioaccumulation factor (BAF) in the present study was defined with reference to the concentration of bioavailable Hg in the soil (Hg([root]) /Hg([bioavail])). Three plant species, Macleaya cordata L., Achillea millefolium L., and Pteris vittata L., showed enhanced accumulation of Hg and therefore may have potential for use in the phytoremediation of soils of the Wanshan mining area. Copyright © 2011 SETAC.

Using Fisher information to track stability in multivariate ...

EPA Pesticide Factsheets

With the current proliferation of data, the proficient use of statistical and mining techniques offer substantial benefits to capture useful information from any dataset. As numerous approaches make use of information theory concepts, here, we discuss how Fisher information (FI) can be applied to sustainability science problems and used in data mining applications by analyzing patterns in data. FI was developed as a measure of information content in data, and it has been adapted to assess order in complex system behaviors. The main advantage of the approach is the ability to collapse multiple variables into an index that can be used to assess stability and track overall trends in a system, including its regimes and regime shifts. Here, we provide a brief overview of FI theory, followed by a simple step-by-step numerical example on how to compute FI. Furthermore, we introduce an open source Python library that can be freely downloaded from GitHub and we use it in a simple case study to evaluate the evolution of FI for the global-mean temperature from 1880 to 2015. Results indicate significant declines in FI starting in 1978, suggesting a possible regime shift. Demonstrate Fisher information as a useful method for assessing patterns in big data.

Repeated climate-linked host shifts have promoted diversification in a temperate clade of leaf-mining flies

PubMed Central

Winkler, Isaac S.; Mitter, Charles; Scheffer, Sonja J.

2009-01-01

A central but little-tested prediction of “escape and radiation” coevolution is that colonization of novel, chemically defended host plant clades accelerates insect herbivore diversification. That theory, in turn, exemplifies one side of a broader debate about the relative influence on clade dynamics of intrinsic (biotic) vs. extrinsic (physical-environmental) forces. Here, we use a fossil-calibrated molecular chronogram to compare the effects of a major biotic factor (repeated shift to a chemically divergent host plant clade) and a major abiotic factor (global climate change) on the macroevolutionary dynamics of a large Cenozoic radiation of phytophagous insects, the leaf-mining fly genus Phytomyza (Diptera: Agromyzidae). We find one of the first statistically supported examples of consistently elevated net diversification accompanying shift to new plant clades. In contrast, we detect no significant direct effect on diversification of major global climate events in the early and late Oligocene. The broader paleoclimatic context strongly suggests, however, that climate change has at times had a strong indirect influence through its effect on the biotic environment. Repeated rapid Miocene radiation of these flies on temperate herbaceous asterids closely corresponds to the dramatic, climate-driven expansion of seasonal, open habitats. PMID:19805134

Spatiotemporal distribution of airborne particulate metals and metalloids in a populated arid region

NASA Astrophysics Data System (ADS)

Prabhakar, Gouri; Sorooshian, Armin; Toffol, Emily; Arellano, Avelino F.; Betterton, Eric A.

2014-08-01

A statistical analysis of data from the Interagency Monitoring of Protected Visual Environments (IMPROVE) network of aerosol samplers has been used to study the spatial and temporal concentration trends in airborne particulate metals and metalloids for southern Arizona. The study region is a rapidly growing area in southwestern North America characterized by high fine soil concentrations (among the highest in the United States), anthropogenic emissions from an area within the fastest growing region in the United States, and a high density of active and abandoned mining sites. Crustal tracers in the region are most abundant in the summer (April-June) followed by fall (October-November) as a result of dry meteorological conditions which favor dust emissions from natural and anthropogenic activity. A distinct day-of-week cycle is evident for crustal tracer mass concentrations, with the greatest amplitude evident in urban areas. There have been significant reductions since 1988 in the concentrations of toxic species that are typically associated with smelting and mining. Periods with high fine soil concentrations coincide with higher concentrations of metals and metalloids in the atmosphere, with the enhancement being higher at urban sites.

Fire Risk Assessment of Some Indian Coals Using Radial Basis Function (RBF) Technique

NASA Astrophysics Data System (ADS)

Nimaje, Devidas; Tripathy, Debi Prasad

2017-04-01

Fires, whether surface or underground, pose serious and environmental problems in the global coal mining industry. It is causing huge loss of coal due to burning and loss of lives, sterilization of coal reserves and environmental pollution. Most of the instances of coal mine fires happening worldwide are mainly due to the spontaneous combustion. Hence, attention must be paid to take appropriate measures to prevent occurrence and spread of fire. In this paper, to evaluate the different properties of coals for fire risk assessment, forty-nine in situ coal samples were collected from major coalfields of India. Intrinsic properties viz. proximate and ultimate analysis; and susceptibility indices like crossing point temperature, flammability temperature, Olpinski index and wet oxidation potential method of Indian coals were carried out to ascertain the liability of coal to spontaneous combustion. Statistical regression analysis showed that the parameters of ultimate analysis provide significant correlation with all investigated susceptibility indices as compared to the parameters of proximate analysis. Best correlated parameters (ultimate analysis) were used as inputs to the radial basis function network model. The model revealed that Olpinski index can be used as a reliable method to assess the liability of Indian coals to spontaneous combustion.

A data mining approach to dinoflagellate clustering according to sterol composition: Correlations with evolutionary history.

USDA-ARS?s Scientific Manuscript database

This study examined the sterol compositions of 102 dinoflagellates (including several previously unexamined species) using clustering techniques as a means of determining the relatedness of the organisms. In addition, dinoflagellate sterol-based relationships were compared statistically to dinoflag...

DATAFERRETT AND DATAWEB

EPA Science Inventory

DataFerrett is a data extraction software and a data mining tool that accesses data stored in TheDataWeb through the Internet. It can be installed as an application on your desktop or use a java applet with an Internet browser. Census Bureau and Bureau of Labor Statistics release...

Application of ERTS-1 imagery to fracture related mine safety hazards in the coal mining industry. [Indiana

NASA Technical Reports Server (NTRS)

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

1974-01-01

The author has identified the following significant results. New fracture detail of Indiana has been observed and mapped from ERTS-1 imagery. Studies so far indicate a close relationship between the directions of fracture traces mapped from the imagery, fractures measured on bedrock outcrops, and fractures measured in the underground mines. First hand observations and discussions with underground mine operators indicate good correlation of mine hazard maps prepared from ERTS-1/aircraft imagery and actual roof falls. The inventory of refuse piles/slurry ponds of the coal field of Indiana has identified over 225 such sites from past mining operations. These data will serve the State Legislature in making tax decisions on coal mining which take on increased importance because of the energy crisis.

Knowledge modeling of coal mining equipments based on ontology

NASA Astrophysics Data System (ADS)

Zhang, Baolong; Wang, Xiangqian; Li, Huizong; Jiang, Miaomiao

2017-06-01

The problems of information redundancy and sharing are universe in coal mining equipment management. In order to improve the using efficiency of knowledge of coal mining equipments, this paper proposed a new method of knowledge modeling based on ontology. On the basis of analyzing the structures and internal relations of coal mining equipment knowledge, taking OWL as ontology construct language, the ontology model of coal mining equipment knowledge is built with the help of Protégé 4.3 software tools. The knowledge description method will lay the foundation for the high effective knowledge management and sharing, which is very significant for improving the production management level of coal mining enterprises.

Ecotoxicity of Mine Tailings: Unrehabilitated Versus Rehabilitated.

PubMed

Maboeta, M S; Oladipo, O G; Botha, S M

2018-05-01

Earthworms are bioindicators of soil pollution. The ecotoxicity of tailings from selected gold mines in South Africa was investigated utilizing Eisenia andrei bioassays and biomarkers. Samples were obtained from unrehabilitated, rehabilitated and naturally vegetated sites. Biomass, neutral red retention time (NRRT), survival and reproduction were assessed using standardized protocols. Earthworm biomass, NRRT and reproductive success in rehabilitated tailings (comparable to naturally vegetated site) were significantly higher (p < 0.05) than in unrehabilitated tailings. In addition, significantly lower (p < 0.05) body tissue concentrations of As, Cd, Co, Cu and Ni contents were found in the rehabilitated tailings compared to the unrehabilitated. Further, significantly lower (p < 0.05) soil Mn and Zn concentrations were obtained in unrehabilitated tailings than the rehabilitated and naturally vegetated sites. Overall, reduced ecotoxicity effects were confirmed in rehabilitated compared to unrehabilitated tailings. This suggests that rehabilitation as a post-mining restorative strategy has strong positive influence on mine tailings.

The environmental pollution perception of residents in coal mining areas: a case study in the Hancheng mine area, Shaanxi Province, China.

PubMed

Shi, Xingmin; He, Fei

2012-10-01

The environmental behavior of the residents depends on their perception of environmental pollution. Hence, it is important for scientific and policy experts to research on the impact of the environmental pollution perception of local residents. Owing to the richness of natural resources, Hancheng coal mine areas are abound in heavy industries, and environmental pollution is serious and typical in this area, thus, the residents are anxious about their health. Using questionnaires, this paper surveys the perception of residents living in the coal mine area. The influential factors of environmental perception were analyzed by the Rank Sum Test. The results were: (1) the majority of the residents in the coal mine area are not satisfied with their living environment. The perception order of pollution severity is: air pollution > noise pollution > sanitation > water pollution. The residents think that pollution is mainly caused by coal processing. Hence, coal mining is not the main reason of the pollution in the coal mine area. (2) Age and length of residence have significant positive effects on perceptions of air, water, and noise pollutions; whereas education has a significant negative effect on perceptions of water and noise pollutions, as well as sanitation. This phenomenon can be explained by the various cultural groups having varied perceptions on the environmental pollution. In addition, proximity to mine has significant negative effect on perceptions of water and noise pollution. In conclusion, the paper discusses the effects of demographical and social factors on the perception of environmental pollution and gives suggestions on the planning and management of the environment.

Problems with the application of hydrogeological science to regulation of Australian mining projects: Carmichael Mine and Doongmabulla Springs

NASA Astrophysics Data System (ADS)

Currell, Matthew J.; Werner, Adrian D.; McGrath, Chris; Webb, John A.; Berkman, Michael

2017-05-01

Understanding and managing impacts from mining on groundwater-dependent ecosystems (GDEs) and other groundwater users requires development of defensible science supported by adequate field data. This usually leads to the creation of predictive models and analysis of the likely impacts of mining and their accompanying uncertainties. The identification, monitoring and management of impacts on GDEs are often a key component of mine approvals, which need to consider and attempt to minimise the risks that negative impacts may arise. Here we examine a case study where approval for a large mining project in Australia (Carmichael Coal Mine) was challenged in court on the basis that it may result in more extensive impacts on a GDE (Doongmabulla Springs) of high ecological and cultural significance than predicted by the proponent. We show that throughout the environmental assessment and approval process, significant data gaps and scientific uncertainties remained unresolved. Evidence shows that the assumed conceptual hydrogeological model for the springs could be incorrect, and that at least one alternative conceptualisation (that the springs are dependent on a deep fault) is consistent with the available field data. Assumptions made about changes to spring flow as a consequence of mine-induced drawdown also appear problematic, with significant implications for the spring-fed wetlands. Despite the large scale of the project, it appears that critical scientific data required to resolve uncertainties and construct robust models of the springs' relationship to the groundwater system were lacking at the time of approval, contributing to uncertainty and conflict. For this reason, we recommend changes to the approval process that would require a higher standard of scientific information to be collected and reviewed, particularly in relation to key environmental assets during the environmental impact assessment process in future projects.

Understanding the mobilisation of metal pollution associated with historical mining in a carboniferous upland catchment.

PubMed

Valencia-Avellan, Magaly; Slack, Rebecca; Stockdale, Anthony; Mortimer, Robert John George

2017-08-16

Point and diffuse pollution from metal mining has led to severe environmental damage worldwide. Mine drainage is a significant problem for riverine ecosystems, it is commonly acidic (AMD), but neutral mine drainage (NMD) can also occur. A representative environment for studying metal pollution from NMD is provided by carboniferous catchments characterised by a circumneutral pH and high concentrations of carbonates, supporting the formation of secondary metal-minerals as potential sinks of metals. The present study focuses on understanding the mobility of metal pollution associated with historical mining in a carboniferous upland catchment. In the uplands of the UK, river water, sediments and spoil wastes were collected over a period of fourteen months, samples were chemically analysed to identify the main metal sources and their relationships with geological and hydrological factors. Correlation tests and principal component analysis suggest that the underlying limestone bedrock controls pH and weathering reactions. Significant metal concentrations from mining activities were measured for zinc (4.3 mg l -1 ), and lead (0.3 mg l -1 ), attributed to processes such as oxidation of mined ores (e.g. sphalerite, galena) or dissolution of precipitated secondary metal-minerals (e.g. cerussite, smithsonite). Zinc and lead mobility indicated strong dependence on biogeochemistry and hydrological conditions (e.g. pH and flow) at specific locations in the catchment. Annual loads of zinc and lead (2.9 and 0.2 tonnes per year) demonstrate a significant source of both metals to downstream river reaches. Metal pollution results in a large area of catchment having a depleted chemical status with likely effects on the aquatic ecology. This study provides an improved understanding of geological and hydrological processes controlling water chemistry, which is critical to assessing metal sources and mobilization, especially in neutral mine drainage areas.

Data Mine and Forget It?: A Cautionary Tale

NASA Technical Reports Server (NTRS)

Tada, Yuri; Kraft, Norbert Otto; Orasanu, Judith M.

2011-01-01

With the development of new technologies, data mining has become increasingly popular. However, caution should be exercised in choosing the variables to include in data mining. A series of regression trees was created to demonstrate the change in the selection by the program of significant predictors based on the nature of variables.

Study of application of ERTS-1 imagery to fracture-related mine safety hazards in the coal mining industry

NASA Technical Reports Server (NTRS)

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

1972-01-01

The author has identified the following significant results. Numerous fractures are identifiable on the 1:120,000 color infrared photography. Some of these fractures are in the proximity of operating open pit mines and should provide opportunities for field checking and confirmation.

RECENT GEOCHEMICAL SAMPLING AND MERCURY SOURCES AT SULPHUR BANK MERCURY MINE, LAKE COUNTY, CA

EPA Science Inventory

The Sulphur Bank Mercury Mine (SBMM), located on the shore of Clear Lake in Lake County, California, has been identified as a significant source of mercury to the lake. Sulphur Bank was actively minded from the 1880's to the 1950's. Mining and processing operations at the Sulph...

Increasing the Reliability of the Work of Artificial Filtering Arrays for the Purification of Quarry Waste Water

NASA Astrophysics Data System (ADS)

Tyulenev, Maxim; Lesin, Yury; Litvin, Oleg; Maliukhina, Elena; Abay, Asmelash

2017-11-01

Features of geological structure of the Kuznetsk coal basin stipulate the application of a low-cost open technique of coal mining, which is more advantageous both from the economic standpoint, and by safety criteria of mining. However, open mining affects significantly the water resources of region. Intensive pollution of reservoirs and water courses, exhaustion of the underground water-bearing layers, violation of a hydrographic network, etc. be-long to the main disadvantages of an open technique of coal mining. Besides, the volume of the water coming into the mining producers exceeds signi-ficantly the needed quantity. According to the data of annual reports of ecology and natural resources department, 348.277 million m3 of water were ta-ken away during production of soft coal, brown coal and lignum fossil from waters of Kemerovo region in 2013 (mostly from underground water objects (96,5%) when draining of mine openings). At the same time, only 87.018 million m3 of water (25%) has been used within a year.

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.

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

NASA Technical Reports Server (NTRS)

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

1973-01-01

The author has identified the following significant results. The Mined Land Inventory map of Pike, Gibson, and Warrick Counties, Indiana, prepared from ERTS-1 imagery, was included in the 1973 Annual Report of the President's Council on Environmental Quality as an example of ERTS applications to mined lands. Increasing numbers of inquiries have been received from coal producing states and coal companies interested in the Indiana Program.

Economic significance of revised age relations of rocks in the Cornucopia mining district, Elko County, Nevada

USGS Publications Warehouse

Coats, Robert Roy

1967-01-01

Recent geologic work in the Cornucopia mining district, a small silver-gold mining district in northwestern Elko County, Nev., has resulted in significant revision of the geological interpretation. Rocks formerly thought to be premineralization in age, but unmineralized, are now known to be postmineral extrusives, resting unconformably on the altered andesite in which the ore bodies are found. Extensions of the known productive veins may be expected at shallow depth beneath the younger volcanic rocks, and are separated from the mined part of the veins by postmineral high-angle faults that have brought the younger volcanic rocks into fault contact with the mineralized andesite. Some veins are apparently terminated against premineral faults.

Application of a Novel Liquid Nitrogen Control Technique for Heat Stress and Fire Prevention in Underground Mines.

PubMed

Shi, Bobo; Ma, Lingjun; Dong, Wei; Zhou, Fubao

2015-01-01

With the continually increasing mining depths, heat stress and spontaneous combustion hazards in high-temperature mines are becoming increasingly severe. Mining production risks from natural hazards and exposures to hot and humid environments can cause occupational diseases and other work-related injuries. Liquid nitrogen injection, an engineering control developed to reduce heat stress and spontaneous combustion hazards in mines, was successfully utilized for environmental cooling and combustion prevention in an underground mining site named "Y120205 Working Face" (Y120205 mine) of Yangchangwan colliery. Both localized humidities and temperatures within the Y120205 mine decreased significantly with liquid nitrogen injection. The maximum percentage drop in temperature and humidity of the Y120205 mine were 21.9% and 10.8%, respectively. The liquid nitrogen injection system has the advantages of economical price, process simplicity, energy savings and emission reduction. The optimized heat exchanger used in the liquid nitrogen injection process achieved superior air-cooling results, resulting in considerable economic benefits.

Reuse and Securing of Mining Waste : Need of the hour

NASA Astrophysics Data System (ADS)

Mehta, Neha; Dino, Giovanna; Ajmone-Marsan, Franco; De Luca, Domenico Antonio

2016-04-01

With recent advancements in technology and rising standards of living the demand for minerals has increased drastically. Increased reliance on mining industry has led to unmanageable challenges of Mining waste generated out of Mining and Quarrying activities. According to Statistics from EuroStat Mining and Quarrying generated 734 million Tons in Europe in 2012 which accounted for 29.19 % of the total waste, becoming second most important sector in terms of waste generation after Construction Industry. Mining waste can be voluminous and/ or chemically active and can cause environmental threats like groundwater pollution due to leaching of pollutants, surface water pollution due to runoffs during rainy season, river and ocean pollution due to intentional dumping of tailings by mining companies. Most of the big mining companies have not adopted policies against dumping of tailings in rivers and oceans. Deep Sea Tailings Placement (DSTP) is creating havoc in remote and pristine environment of deep-sea beds e.g. Bismarck Sea. Furthermore, mining waste is contaminating soil in nearby areas by disturbing soil microbial activity and other physio-chemical and biological properties of soil (e.g. Barruecopardo village - Spain). Mining waste stored in heaps and dams has led to many accidents and on an average, worldwide, there is one major accident in a year involving tailings dams (e.g. Myanmar, Brazil, 2015). Pollution due to tailings is causing local residents to relocate and become 'ecological migrants'. The above issues linked to mining waste makes reuse and securing of mining waste one of the urgent challenge to deal with. The studies done previously on mining show that most of the researches linked with mining waste reuse and securing are very site specific. For instance, the type of recovery method should not only provide environmental clean-up but also economic benefits to promise sustainability of the method. Environmental risk assessment of using mining waste as agricultural soils can depend on Bio-accumulation factor, Translocation factor of heavy metals, species of plant grown and type of the natural biota of the surroundings and effect of different exposure routes. This also leads to the fact that more research is required in this area. Accordingly the same problem statement was chosen as part of a PhD research Project. The PhD research is part of REMEDIATE project (A Marie Sklodowska-Curie Action Initial Training Network for Improved decision making in contaminated land site investigation and risk assessment, Grant Agreement No. 643087). In this project the researcher will select a mining site in Italy to find possible solutions to the environmental impact of mining waste collected there. The project will focus on 1) physical and chemical characterization of waste 2)environmental risk assessment study of the mining waste 3) impact of mining waste on water bodies and soil 4) to discover possible routes of reuse and recovery of minerals from the waste. Thus project focuses on environmental sustainability of mining waste reuse and clean up. Keywords : Mining waste ; environmental risk assessment ;reuse and recovery.

Mortality of Sardinian lead and zinc miners: 1960-88.

PubMed Central

Cocco, P L; Carta, P; Belli, S; Picchiri, G F; Flore, M V

1994-01-01

The mortality of 4740 male workers of two lead and zinc mines was followed up from 1960 to 1988. Exposure to respirable dust was comparable in the two mines, but the median concentration of silica in respirable dust was 10-fold higher in mine B (12.8%) than in mine A (1.2%), but the mean annual exposure to radon daughters in underground workplaces differed in the opposite direction (mine A: 0.13 working levels (WL), mine B: 0.011 WL). Total observed deaths (1205) were similar to expected figures (1156.3) over a total of 119 390.5 person-years at risk. Underground workers of mine B had significant increases in risk of pulmonary tuberculosis (SMR 706, 95% confidence interval (95% CI) 473-1014) and non-malignant respiratory diseases (SMR 518; 95% CI 440-1606), whereas the only significant excess at mine A was for non-malignant respiratory diseases (SMR 246; 95% CI 191-312). Total cancer and lung cancer mortality did not exceed the expectation in the two mines combined. A 15% excess mortality for lung cancer, increased up to an SMR 204 (95% CI 89-470) for subjects employed > or = 26 years, was, however, found among underground workers in mine A who on the average experienced an exposure to radon daughters 10-fold higher than those of mine B. By contrast, despite their higher exposure to silica, mine B underground workers experienced a lower than expected lung cancer mortality. A ninefold increase in risk of peritoneal and retroperitoneal cancer combined was also found among underground workers of mine A (SMR 917; 95% CI 250-2347; based on four deaths). A causal association with workplace exposures is unlikely, however, as the SMR showed an inverse trend by duration of employment. These findings are consistent with low level exposure to radon daughters as a risk factor for lung cancer among metal miners. Exposure to silica at the levels estimated for the mine B underground environment did not increase the risk of lung cancer. PMID:8000492

Working Performance Analysis of Rolling Bearings Used in Mining Electric Excavator Crowd Reducer

NASA Astrophysics Data System (ADS)

Zhang, Y. H.; Hou, G.; Chen, G.; Liang, J. F.; Zheng, Y. M.

2017-12-01

Refer to the statistical load data of digging process, on the basis of simulation analysis of crowd reducer system dynamics, the working performance simulation analysis of rolling bearings used in crowd reducer of large mining electric excavator is completed. The contents of simulation analysis include analysis of internal load distribution, rolling elements contact stresses and rolling bearing fatigue life. The internal load characteristics of rolling elements in cylindrical roller bearings are obtained. The results of this study identified that all rolling bearings satisfy the requirements of contact strength and fatigue life. The rationality of bearings selection and arrangement is also verified.

Environmental exposures to metals in Native communities and implications for child development: basis for the Navajo birth cohort study.

PubMed

Lewis, Johnnye; Gonzales, Melissa; Burnette, Courtney; Benally, Malcolm; Seanez, Paula; Shuey, Christopher; Nez, Helen; Nez, Christopher; Nez, Seraphina

2015-01-01

Two disparate statistics often cited for the Western United States raise concern about risks for developmental disabilities in Native American children. First, 13 of the states with the highest percentage of Native American population are located in the Western United States (U.S. Census Bureau, 2012 ). Second, more than 161,000 abandoned hard-rock mines are located in 12 Western states (General Accounting Office, 2014 ). Moreover, numerous studies have linked low-level metals exposure with birth defects and developmental delays. Concern has emerged among tribal populations that metals exposure from abandoned mines might threaten development of future generations.

CSPMS supported by information technology

NASA Astrophysics Data System (ADS)

Zhang, Hudan; Wu, Heng

This paper will propose a whole new viewpoint about building a CSPMS(Coal-mine Safety Production Management System) by means of information technology. This system whose core part is a four-grade automatic triggered warning system achieves the goal that information transmission will be smooth, nondestructive and in time. At the same time, the system provides a comprehensive and collective technology platform for various Public Management Organizations and coal-mine production units to deal with safety management, advance warning, unexpected incidents, preplan implementation, and resource deployment at different levels. The database of this system will support national related industry's resource control, plan, statistics, tax and the construction of laws and regulations effectively.

Data mining approach identifies research priorities and data requirements for resolving the red algal tree of life.

PubMed

Verbruggen, Heroen; Maggs, Christine A; Saunders, Gary W; Le Gall, Line; Yoon, Hwan Su; De Clerck, Olivier

2010-01-20

The assembly of the tree of life has seen significant progress in recent years but algae and protists have been largely overlooked in this effort. Many groups of algae and protists have ancient roots and it is unclear how much data will be required to resolve their phylogenetic relationships for incorporation in the tree of life. The red algae, a group of primary photosynthetic eukaryotes of more than a billion years old, provide the earliest fossil evidence for eukaryotic multicellularity and sexual reproduction. Despite this evolutionary significance, their phylogenetic relationships are understudied. This study aims to infer a comprehensive red algal tree of life at the family level from a supermatrix containing data mined from GenBank. We aim to locate remaining regions of low support in the topology, evaluate their causes and estimate the amount of data required to resolve them. Phylogenetic analysis of a supermatrix of 14 loci and 98 red algal families yielded the most complete red algal tree of life to date. Visualization of statistical support showed the presence of five poorly supported regions. Causes for low support were identified with statistics about the age of the region, data availability and node density, showing that poor support has different origins in different parts of the tree. Parametric simulation experiments yielded optimistic estimates of how much data will be needed to resolve the poorly supported regions (ca. 103 to ca. 104 nucleotides for the different regions). Nonparametric simulations gave a markedly more pessimistic image, some regions requiring more than 2.8 105 nucleotides or not achieving the desired level of support at all. The discrepancies between parametric and nonparametric simulations are discussed in light of our dataset and known attributes of both approaches. Our study takes the red algae one step closer to meaningful inclusion in the tree of life. In addition to the recovery of stable relationships, the recognition of five regions in need of further study is a significant outcome of this work. Based on our analyses of current availability and future requirements of data, we make clear recommendations for forthcoming research.

Evidence-based rules from family practice to inform family practice; the learning healthcare system case study on urinary tract infections.

PubMed

Soler, Jean K; Corrigan, Derek; Kazienko, Przemyslaw; Kajdanowicz, Tomasz; Danger, Roxana; Kulisiewicz, Marcin; Delaney, Brendan

2015-05-16

Analysis of encounter data relevant to the diagnostic process sourced from routine electronic medical record (EMR) databases represents a classic example of the concept of a learning healthcare system (LHS). By collecting International Classification of Primary Care (ICPC) coded EMR data as part of the Transition Project from Dutch and Maltese databases (using the EMR TransHIS), data mining algorithms can empirically quantify the relationships of all presenting reasons for encounter (RfEs) and recorded diagnostic outcomes. We have specifically looked at new episodes of care (EoC) for two urinary system infections: simple urinary tract infection (UTI, ICPC code: U71) and pyelonephritis (ICPC code: U70). Participating family doctors (FDs) recorded details of all their patient contacts in an EoC structure using the ICPC, including RfEs presented by the patient, and the FDs' diagnostic labels. The relationships between RfEs and episode titles were studied using probabilistic and data mining methods as part of the TRANSFoRm project. The Dutch data indicated that the presence of RfE's "Cystitis/Urinary Tract Infection", "Dysuria", "Fear of UTI", "Urinary frequency/urgency", "Haematuria", "Urine symptom/complaint, other" are all strong, reliable, predictors for the diagnosis "Cystitis/Urinary Tract Infection" . The Maltese data indicated that the presence of RfE's "Dysuria", "Urinary frequency/urgency", "Haematuria" are all strong, reliable, predictors for the diagnosis "Cystitis/Urinary Tract Infection". The Dutch data indicated that the presence of RfE's "Flank/axilla symptom/complaint", "Dysuria", "Fever", "Cystitis/Urinary Tract Infection", "Abdominal pain/cramps general" are all strong, reliable, predictors for the diagnosis "Pyelonephritis" . The Maltese data set did not present any clinically and statistically significant predictors for pyelonephritis. We describe clinically and statistically significant diagnostic associations observed between UTIs and pyelonephritis presenting as a new problem in family practice, and all associated RfEs, and demonstrate that the significant diagnostic cues obtained are consistent with the literature. We conclude that it is possible to generate clinically meaningful diagnostic evidence from electronic sources of patient data.

Consumptive Water-Use Coefficients for the Great Lakes Basin and Climatically Similar Areas

USGS Publications Warehouse

Shaffer, Kimberly H.; Runkle, Donna L.

2007-01-01

Consumptive water use is the portion of water withdrawn (for a particular use) that is evaporated, transpired, incorporated into products or crops, consumed by humans or livestock, or otherwise removed from the immediate water environment. This report, which is organized by water?use categories, includes consumptive?use coefficients for the Great Lakes Basin (including Canada) and for areas climatically similar to the Great Lakes Basin. This report also contains an annotated bibliography of consumptive water?use coefficients. Selected references are listed for consumptive?use data from elsewhere in the world. For the industrial water?use category, the median consumptive?use coefficients were 10 percent for the Great Lakes Basin, climatically similar areas, and the world; the 25th and 75th percentiles for these geographic areas were comparable within 6 percent. The combined domestic and public?supply consumptive?use statistics (median, 25th and 75th percentiles) were between 10 to 20 percent for the various geographic areas. Although summary statistics were similar for coefficients in the livestock and irrigation water?use categories for the Great Lakes Basin and climatically similar areas, statistic values for the world on a whole were substantially lower (15 to 28 percent lower). Commercial and thermoelectric power consumptive?use coefficient statistics (median, 25th, and 75th percentile) also were comparable for the Great Lakes Basin and climatically similar areas, within 2 percent. References for other countries were not found for commercial and thermoelectric power water?use categories. The summary statistics for the mining consumptive?use coefficients varied, likely because of differences in types of mining, processes, or equipment.

Effectiveness of a mining simulation cooperative learning activity on the cognitive and affective achievement of students in a lower division physical geology course: A confluent approach

NASA Astrophysics Data System (ADS)

Tolhurst, Jeffrey Wayne

Most students enrolled in lower division physical geology courses are non-majors and tend to finish the course with little appreciation of what it is geologists really do. They may also be expected to analyze, synthesize, and apply knowledge from previous laboratory experiences with little or no instruction and/or practice in utilizing the critical thinking skills necessary to do so. This study sought to answer two research questions: (1) do physical geology students enrolled in a course designed around a mining simulation activity perform better cognitively than students who are taught the same curriculum in the traditional fashion; and (2) do students enrolled in the course gain a greater appreciation of physical geology and the work that geologists do. Eighty students enrolled in the course at Columbia College, Sonora, California over a two year period. During the first year, thirty-one students were taught the traditional physical geology curriculum. During the second year, forty-nine students were taught the traditional curriculum up until week nine, then they were taught a cooperative learning mining simulation activity for three weeks. A static group, split plot, repeated measures design was used. Pre- and post-tests were administered to students in both the control and treatment groups. The cognitive assessment instrument was validated by content area experts in the University of South Carolina Geological Sciences Department. Students were given raw lithologic, gravimetric, topographic, and environmental data with which to construct maps and perform an overlay analysis. They were tested on the cognitive reasoning and spatial analysis they used to make decisions about where to test drill for valuable metallic ores. The affective instrument used a six point Likert scale to assess students' perceived enjoyment, interest, and importance of the material. Gains scores analysis of cognitive achievement data showed a mean of 2.43 for the control group and 4.47 for the treatment group, statistically significantly different at the alpha = 0.05 level (p = 0.0038). Gains scores for the affective data indicated no statistically significant differences between the treatment and control groups. The simulation seems to make a difference in terms of students' intellectual performance, but not in terms of their attitudinal perceptions of the course. Results support the hypothesis that cognitive achievement is improved by a cooperative learning mining simulation activity. One implication might include adapting and implementing the model in lower division physical geology courses. Another would be to develop similar activities for other lower division, non-majors earth science courses (i.e. environmental geology, astronomy, meteorology, oceanography, etc.) that could improve students' subject matter knowledge. Additionally, the research supports shifting the locus of control from the instructor to students as well as the use of the principles of active learning, cooperative learning, and confluent education in the science classroom.

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.

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.

Contamination of water and soil by the Erdenet copper-molybdenum mine in Mongolia

NASA Astrophysics Data System (ADS)

Battogtokh, B.; Lee, J.; Woo, N. C.; Nyamjav, A.

2013-12-01

As one of the largest copper-molybdenum (Cu-Mo) mines in the world, the Erdenet Mine in Mongolia has been active since 1978, and is expected to continue operations for at least another 30 years. In this study, the potential impacts of mining activities on the soil and water environments have been evaluated. Water samples showed high concentrations of sulfate, calcium, magnesium, Mo, and arsenic, and high pH values in the order of high to low as follows: tailing water > Khangal River > groundwater. Statistical analysis and the δ2H and δ18O values of water samples indicate that the tailing water directly affects the stream water and indirectly affects groundwater through recharge processes. Soil and stream sediments are highly contaminated with Cu and Mo, which are major elements of ore minerals. Based on the contamination factor (CF), the pollution load index (PLI), and the degree of contamination (Cd), soil appears to be less contaminated than stream sediments. The soil particle size is similar to that of tailing materials, but stream sediments have much coarser particles, implying that the materials have different origins. Contamination levels in stream sediments display a tendency to decrease with distance from the mine, but no such changes are found in soil. Consequently, soil contamination by metals is attributable to wind-blown dusts from the tailing materials, and stream sediment contamination is caused by discharges from uncontained subgrade ore stock materials. Considering the evident impact on the soil and water environment, and the human health risk from the Erdenet Mine, measures to mitigate its environmental impact should be taken immediately including source control, the establishment of a systematic and continuous monitoring system, and a comprehensive risk assessment. Sampling locations around the Erdenet Mine

Mine Land Reclamation and Eco-Reconstruction in Shanxi Province I: Mine Land Reclamation Model

PubMed Central

Bing-yuan, Hao; Li-xun, Kang

2014-01-01

Coal resource is the main primary energy in our country, while Shanxi Province is the most important province in resource. Therefore Shanxi is an energy base for our country and has a great significance in energy strategy. However because of the heavy development of the coal resource, the ecological environment is worsening and the farmland is reducing continuously in Shanxi Province. How to resolve the contradiction between coal resource exploitation and environmental protection has become the imperative. Thus the concept of “green mining industry” is arousing more and more attention. In this assay, we will talk about the basic mode of land reclamation in mine area, the engineering study of mine land reclamation, the comprehensive model study of mine land reclamation, and the design and model of ecological agricultural reclamation in mining subsidence. PMID:25050398

Effects of coal mine drainage on the water quality of small receiving streams in Washington, 1975-77

USGS Publications Warehouse

Packard, F.A.; Skinner, E.L.; Fuste, L.A.

1988-01-01

Drainage from abandoned coal mines in western and central Washington has minimal environmental impact. Water quality characteristics that have the most significant environmental impact are suspended sediment and turbidity. Water quality data from 51 abandoned coal mines representing 11 major coal bearing areas indicate that less than 1% of the mine drainage has a pH of 4.5 or less. Fifty percent of the drainage is alkaline and has pH 7.0 and greater, and about 95% of the drainage has pH 6.0 and greater. Less than 2% is acidified to a pH of 5.6, a point where water and free (atmospheric) carbon dioxide are in equilibrium. The area where pH 5.6 or less is most likely to occur is in the Centralia/Chehalis mine district. No significant difference in diversity of benthic organisms was found between stations above and below the mine drainage. However, within the 50-ft downstream reach ostracods were more abundant than above the mine drainage and mayflies, stoneflies, and caddisflies were less abundant than at the control site. Correlations to water quality measurements show that these faunal changes are closely associated with iron and sulfate concentrations. (USGS)

Linear data mining the Wichita clinical matrix suggests sleep and allostatic load involvement in chronic fatigue syndrome.

PubMed

Gurbaxani, Brian M; Jones, James F; Goertzel, Benjamin N; Maloney, Elizabeth M

2006-04-01

To provide a mathematical introduction to the Wichita (KS, USA) clinical dataset, which is all of the nongenetic data (no microarray or single nucleotide polymorphism data) from the 2-day clinical evaluation, and show the preliminary findings and limitations, of popular, matrix algebra-based data mining techniques. An initial matrix of 440 variables by 227 human subjects was reduced to 183 variables by 164 subjects. Variables were excluded that strongly correlated with chronic fatigue syndrome (CFS) case classification by design (for example, the multidimensional fatigue inventory [MFI] data), that were otherwise self reporting in nature and also tended to correlate strongly with CFS classification, or were sparse or nonvarying between case and control. Subjects were excluded if they did not clearly fall into well-defined CFS classifications, had comorbid depression with melancholic features, or other medical or psychiatric exclusions. The popular data mining techniques, principle components analysis (PCA) and linear discriminant analysis (LDA), were used to determine how well the data separated into groups. Two different feature selection methods helped identify the most discriminating parameters. Although purely biological features (variables) were found to separate CFS cases from controls, including many allostatic load and sleep-related variables, most parameters were not statistically significant individually. However, biological correlates of CFS, such as heart rate and heart rate variability, require further investigation. Feature selection of a limited number of variables from the purely biological dataset produced better separation between groups than a PCA of the entire dataset. Feature selection highlighted the importance of many of the allostatic load variables studied in more detail by Maloney and colleagues in this issue [1] , as well as some sleep-related variables. Nonetheless, matrix linear algebra-based data mining approaches appeared to be of limited utility when compared with more sophisticated nonlinear analyses on richer data types, such as those found in Maloney and colleagues [1] and Goertzel and colleagues [2] in this issue.

Biogeochemical variability of plants at native and altered sites, San Juan Basin, New Mexico

USGS Publications Warehouse

Gough, L.P.; Severson, R.C.

1981-01-01

The San Juan Basin is becoming a major energy resource region. The anticipated increase in strip mining for coal can be expected to alter the geochemical and biogeochemical environment. because such activities destroy the native vegetation communities, rearrange the rock strata, and disrupt natural soil development. This study investigated the variability in the biogeochemistry of native plant species at both undisturbed and altered sites and assessed the importance of the observed differences. Three studies are involved in this investigation: Study 1, the biogeochemical variability of native species found at sites throughout that part of the basin underlain by economically recoverable coal; Study 2, the biogeochemical variability of native species growing on soils considered favorable for use in the topsoiling of spoil areas; and Study 3, the biogeochemical variability of native species on rehabilitated sites at the San Juan coal mine. Summary statistics for concentrations of 35 elements (and ash yield) are reported in Study 1 for galleta grass, broom snakeweed, and fourwing saltbush. The concentrations of manganese, molybdenum, nickel, and uranium (and possibly iron and selenium) in galleta show regional patterns, with the highest values generally found in the south-central region and western edge of the study area. Differences in the concentration of elements between species was generally subtle (less than a factor of two) except for the following: ash yield of saltbush was two times that of the other plants; boron in snakeweed and saltbush was four times greater than in galleta; iron in galleta was two times greater than in saltbush; and, calcium, magnesium, potassium, phosphorus, and sulfur were generally highest in saltbush. Summary statistics (including the 95-percent expected range) for concentrations of 35 elements (and ash yield) are reported from Study 2 for galleta and broom snakeweed growing on the Sheppard, Shiprock, and Doak soil association. Significant regional (greater than 10 km) variation for aluminum, iron, sulfur, vanadium, and zirconium in galleta are reported; however, for most elements, a significant proportion of the variation in the data was measured locally (less than 0.1 km). This variation indicates that samples of galleta and snakeweed taken more than 10 km apart vary, in their element composition, little more than plants sampled as close together as 0.1 km. The concentrations of 35 elements (and ash yield) in alkali sacaton and fourwing saltbush, which were collected on a rehabilitation plot at the San Juan mine (Study 3), are compared with those of control samples of similar material from native sites from throughout the ,an Juan Basin. Concentrations of aluminum, arsenic, boron, cobalt, copper, fluorine, iron, lead, manganese, sodium, and uranium in samples of saltbush growing over spoil generally exceed the levels of these elements in control samples. For many elements, concentrations in mine samples are from two to five times higher 1 han concentrations in the control samples. Sodium concentrations i saltbush, however, were 100 times higher in mine samples than in control samples. This high concentration reflects a corresponding : OO-fold increase in the extractable sodium levels in spoil material s compared to C-horizon control samples. Sampled plants from the l1ine area, spaced relatively close together (5 m (meters) or less), vary greatly in their element compositions, apparently in response 1 J the heterogenous composition and element availability of the l1ine soils. Topsoiling to a depth of 20 cm (centimeters) does little to meliorate the uptake of elements from spoil by saltbush.

A Closed Network Queue Model of Underground Coal Mining Production, Failure, and Repair

NASA Technical Reports Server (NTRS)

Lohman, G. M.

1978-01-01

Underground coal mining system production, failures, and repair cycles were mathematically modeled as a closed network of two queues in series. The model was designed to better understand the technological constraints on availability of current underground mining systems, and to develop guidelines for estimating the availability of advanced mining systems and their associated needs for spares as well as production and maintenance personnel. It was found that: mine performance is theoretically limited by the maintainability ratio, significant gains in availability appear possible by means of small improvements in the time between failures the number of crews and sections should be properly balanced for any given maintainability ratio, and main haulage systems closest to the mine mouth require the most attention to reliability.

ILDgenDB: integrated genetic knowledge resource for interstitial lung diseases (ILDs).

PubMed

Mishra, Smriti; Shah, Mohammad I; Sarkar, Malay; Asati, Nimisha; Rout, Chittaranjan

2018-01-01

Interstitial lung diseases (ILDs) are a diverse group of ∼200 acute and chronic pulmonary disorders that are characterized by variable amounts of inflammation, fibrosis and architectural distortion with substantial morbidity and mortality. Inaccurate and delayed diagnoses increase the risk, especially in developing countries. Studies have indicated the significant roles of genetic elements in ILDs pathogenesis. Therefore, the first genetic knowledge resource, ILDgenDB, has been developed with an objective to provide ILDs genetic data and their integrated analyses for the better understanding of disease pathogenesis and identification of diagnostics-based biomarkers. This resource contains literature-curated disease candidate genes (DCGs) enriched with various regulatory elements that have been generated using an integrated bioinformatics workflow of databases searches, literature-mining and DCGs-microRNA (miRNAs)-single nucleotide polymorphisms (SNPs) association analyses. To provide statistical significance to disease-gene association, ILD-specificity index and hypergeomatric test scores were also incorporated. Association analyses of miRNAs, SNPs and pathways responsible for the pathogenesis of different sub-classes of ILDs were also incorporated. Manually verified 299 DCGs and their significant associations with 1932 SNPs, 2966 miRNAs and 9170 miR-polymorphisms were also provided. Furthermore, 216 literature-mined and proposed biomarkers were identified. The ILDgenDB resource provides user-friendly browsing and extensive query-based information retrieval systems. Additionally, this resource also facilitates graphical view of predicted DCGs-SNPs/miRNAs and literature associated DCGs-ILDs interactions for each ILD to facilitate efficient data interpretation. Outcomes of analyses suggested the significant involvement of immune system and defense mechanisms in ILDs pathogenesis. This resource may potentially facilitate genetic-based disease monitoring and diagnosis.Database URL: http://14.139.240.55/ildgendb/index.php.

Bioavailability of Pb and Zn from mine tailings as indicated by erythrocyte aminolevulinic acid dehydratase (ALA-D) activity in suckers (Pisces: catostomidae)

USGS Publications Warehouse

Schmitt, Christopher J.; Dwyer, F. James; Finger, Susan E.

1984-01-01

The activity of the erythrocyte enzyme δ-aminolevulinic acid dehydratase (ALA-D) was measured in 35 catostomids (black redhorse, Moxostoma duquesnei; golden redhorse, M. erythrurum; northern hogsucker, Hypentelium nigricans) collected from three sites on a stream contaminated with Pb-, Cd-, and Zn-rich mine tailings and from an uncontaminated site upstream. Enzyme activity was expressed in terms of hemoglobin (Hb), DNA, and protein concentrations; these variables can be determined in the laboratory on once-frozen blood samples. Concentrations of Pb and Zn in blood and of Pb in edible tissues were significantly higher, and ALA-D activity was significantly lower, at all three contaminated sites than upstream. At the most contaminated site, ALA-D activity was 62–67% lower than upstream. Lead concentrations in the edible tissues and in blood were positively correlated (r = 0.80), whereas ALA-D activity was negatively correlated with Pb in blood (r = −0.70) and in edible tissues (r = −0.59). Five statistically significant relations between Pb and Zn in blood and ALA-D activity were determined. The two models that explained the highest percentage (> 74%) of the total variance also included factors related to Hb concentration. All five significant models included negative coefficients for variables that represented Pb in blood and positive coefficients for Zn in blood. The ALA-D assay with results standardized to Hb concentration represents an expedient alternative to the more traditional hematocrit standardization, and the measurement of ALA-D activity by this method can be used to document exposure of fish to environmental Pb.

SiBIC: a web server for generating gene set networks based on biclusters obtained by maximal frequent itemset mining.

PubMed

Takahashi, Kei-ichiro; Takigawa, Ichigaku; Mamitsuka, Hiroshi

2013-01-01

Detecting biclusters from expression data is useful, since biclusters are coexpressed genes under only part of all given experimental conditions. We present a software called SiBIC, which from a given expression dataset, first exhaustively enumerates biclusters, which are then merged into rather independent biclusters, which finally are used to generate gene set networks, in which a gene set assigned to one node has coexpressed genes. We evaluated each step of this procedure: 1) significance of the generated biclusters biologically and statistically, 2) biological quality of merged biclusters, and 3) biological significance of gene set networks. We emphasize that gene set networks, in which nodes are not genes but gene sets, can be more compact than usual gene networks, meaning that gene set networks are more comprehensible. SiBIC is available at http://utrecht.kuicr.kyoto-u.ac.jp:8080/miami/faces/index.jsp.

Assessment of factors limiting algal growth in acidic pit lakes--a case study from Western Australia, Australia.

PubMed

Kumar, R Naresh; McCullough, Clint D; Lund, Mark A; Larranaga, Santiago A

2016-03-01

Open-cut mining operations can form pit lakes on mine closure. These new water bodies typically have low nutrient concentrations and may have acidic and metal-contaminated waters from acid mine drainage (AMD) causing low algal biomass and algal biodiversity. A preliminary study was carried out on an acidic coal pit lake, Lake Kepwari, in Western Australia to determine which factors limited algal biomass. Water quality was monitored to obtain baseline data. pH ranged between 3.7 and 4.1, and solute concentrations were slightly elevated to levels of brackish water. Concentrations of N were highly relative to natural lakes, although concentrations of FRP (<0.01 mg/L) and C (total C 0.7-3.7 and DOC 0.7-3.5 mg/L) were very low, and as a result, algal growth was also extremely low. Microcosm experiment was conducted to test the hypothesis that nutrient enrichment will be able to stimulate algal growth regardless of water quality. Microcosms of Lake Kepwari water were amended with N, P and C nutrients with and without sediment. Nutrient amendments under microcosm conditions could not show any significant phytoplankton growth but was able to promote benthic algal growth. P amendments without sediment showed a statistically higher mean algal biomass concentration than controls or microcosms amended with phosphorus but with sediment did. Results indicated that algal biomass in acidic pit lake (Lake Kepwari) may be limited primarily by low nutrient concentrations (especially phosphorus) and not by low pH or elevated metal concentrations. Furthermore, sediment processes may also reduce the nutrient availability.

Levels and composition of atmospheric particulates (PM10) in a mining-industrial site in the city of Lavrion, Greece.

PubMed

Protonotarios, V; Petsas, N; Moutsatsou, A

2002-11-01

The present work focuses on the characterization of air quality and the identification of pollutant origin at a former mining site in the city of Lavrion, Greece. A historical metallurgy complex is reused for establishing the Lavrion Technology and Cultural Park (LTCP). A serious problem with this is the severe soil contamination that resulted from intensive mining and metallurgical activities that has taken place in the greater area for the past 3,000 years. Among other consequences, surface-polluted depositions, rich in heavy and toxic metals, are loose and easily wind-eroded, resulting in transportation of particulate matter (PM) in the surrounding atmosphere. On the other hand, there are a number of industries relatively close to the site that are potential sources of PM air pollution. The current study deals with the collection and analysis of PM10 samples with respect to their concentration in heavy metals, such as Pb, Cd, Cu, Fe, Zn, Mn, Cr, and Ni. Though not a heavy metal, As also is included. Furthermore, the source of these elements is verified using statistical correlation and by calculating enrichment factors (EFs), considering that some substances are certainly of contaminated soil origin. Results show that PM10 and element concentrations are relatively low during winter but significantly increase during summer. Fe, Pb, Zn, Mn, and Cu may be considered of contaminated soil origin, while As, Ni, Cd, and Cr are very much enriched with respect to contaminated soil, indicating another possible source attributed to the adjacent industrial plants.

40 CFR 721.3100 - Oligomeric silicic acid ester compound with a hy-droxyl-al-kyla-mine.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 40 Protection of Environment 32 2012-07-01 2012-07-01 false Oligomeric silicic acid ester compound with a hy-droxyl-al-kyla-mine. 721.3100 Section 721.3100 Protection of Environment ENVIRONMENTAL... hy-droxyl-al-kyla-mine. (a) Chemical substance and significant new uses subject to reporting. (1) The...

40 CFR 721.3100 - Oligomeric silicic acid ester compound with a hy-droxyl-al-kyla-mine.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 40 Protection of Environment 30 2010-07-01 2010-07-01 false Oligomeric silicic acid ester compound with a hy-droxyl-al-kyla-mine. 721.3100 Section 721.3100 Protection of Environment ENVIRONMENTAL... hy-droxyl-al-kyla-mine. (a) Chemical substance and significant new uses subject to reporting. (1) The...

40 CFR 721.3100 - Oligomeric silicic acid ester compound with a hy-droxyl-al-kyla-mine.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 40 Protection of Environment 31 2011-07-01 2011-07-01 false Oligomeric silicic acid ester compound with a hy-droxyl-al-kyla-mine. 721.3100 Section 721.3100 Protection of Environment ENVIRONMENTAL... hy-droxyl-al-kyla-mine. (a) Chemical substance and significant new uses subject to reporting. (1) The...

40 CFR 721.3100 - Oligomeric silicic acid ester compound with a hy-droxyl-al-kyla-mine.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 40 Protection of Environment 32 2013-07-01 2013-07-01 false Oligomeric silicic acid ester compound with a hy-droxyl-al-kyla-mine. 721.3100 Section 721.3100 Protection of Environment ENVIRONMENTAL... hy-droxyl-al-kyla-mine. (a) Chemical substance and significant new uses subject to reporting. (1) The...

40 CFR 721.3100 - Oligomeric silicic acid ester compound with a hy-droxyl-al-kyla-mine.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 40 Protection of Environment 31 2014-07-01 2014-07-01 false Oligomeric silicic acid ester compound with a hy-droxyl-al-kyla-mine. 721.3100 Section 721.3100 Protection of Environment ENVIRONMENTAL... hy-droxyl-al-kyla-mine. (a) Chemical substance and significant new uses subject to reporting. (1) The...

Abandoned metal mines and their impact on receiving waters: A case study from Southwest England.

PubMed

Beane, Steven J; Comber, Sean D W; Rieuwerts, John; Long, Peter

2016-06-01

Historic mine sites are a major source of contamination to terrestrial and river environments. To demonstrate the importance of determining the significance of point and diffuse metal contamination and the related bioavailability of the metals present from abandoned mines a case study has been carried out. The study provides a quantitative assessment of a historic mine site, Wheal Betsy, southwest England, and its contribution to non-compliance with Water Framework Directive (WFD) Environmental Quality Standards (EQS) for Cd, Cu, Pb and Zn. Surface water and sediment samples showed significant negative environmental impacts even taking account of the bioavailability of the metal present, with lead concentration in the stream sediment up to 76 times higher than the Canadian sediment guidelines 'Probable Effect Level'. Benthic invertebrates showed a decline in species richness adjacent to the mine site with lead and cadmium the main cause. The main mine drainage adit was the single most significant source of metal (typically 50% of metal load from the area, but 88% for Ni) but the mine spoil tips north and south of the adit input added together discharged roughly an equivalent loading of metal with the exception of Ni. The bioavailability of metal in the spoil tips exhibited differing spatial patterns owing to varying ambient soil physico-chemistry. The data collected is essential to provide a clear understanding of the contamination present as well as its mobility and bioavailability, in order to direct the decision making process regarding remediation options and their likely effectiveness. Copyright © 2016 Elsevier Ltd. All rights reserved.

An exploration into study design for biomarker identification: issues and recommendations.

PubMed

Hall, Jacqueline A; Brown, Robert; Paul, Jim

2007-01-01

Genomic profiling produces large amounts of data and a challenge remains in identifying relevant biological processes associated with clinical outcome. Many candidate biomarkers have been identified but few have been successfully validated and make an impact clinically. This review focuses on some of the study design issues encountered in data mining for biomarker identification with illustrations of how study design may influence the final results. This includes issues of clinical endpoint use and selection, power, statistical, biological and clinical significance. We give particular attention to study design for the application of supervised clustering methods for identification of gene networks associated with clinical outcome and provide recommendations for future work to increase the success of identification of clinically relevant biomarkers.

Estimating procedure times for surgeries by determining location parameters for the lognormal model.

PubMed

Spangler, William E; Strum, David P; Vargas, Luis G; May, Jerrold H

2004-05-01

We present an empirical study of methods for estimating the location parameter of the lognormal distribution. Our results identify the best order statistic to use, and indicate that using the best order statistic instead of the median may lead to less frequent incorrect rejection of the lognormal model, more accurate critical value estimates, and higher goodness-of-fit. Using simulation data, we constructed and compared two models for identifying the best order statistic, one based on conventional nonlinear regression and the other using a data mining/machine learning technique. Better surgical procedure time estimates may lead to improved surgical operations.

The Diesel Exhaust in Miners Study: A Nested Case–Control Study of Lung Cancer and Diesel Exhaust

PubMed Central

Samanic, Claudine M.; Lubin, Jay H.; Blair, Aaron E.; Stewart, Patricia A.; Vermeulen, Roel; Coble, Joseph B.; Rothman, Nathaniel; Schleiff, Patricia L.; Travis, William D.; Ziegler, Regina G.; Wacholder, Sholom; Attfield, Michael D.

2012-01-01

Background Most studies of the association between diesel exhaust exposure and lung cancer suggest a modest, but consistent, increased risk. However, to our knowledge, no study to date has had quantitative data on historical diesel exposure coupled with adequate sample size to evaluate the exposure–response relationship between diesel exhaust and lung cancer. Our purpose was to evaluate the relationship between quantitative estimates of exposure to diesel exhaust and lung cancer mortality after adjustment for smoking and other potential confounders. Methods We conducted a nested case–control study in a cohort of 12 315 workers in eight non-metal mining facilities, which included 198 lung cancer deaths and 562 incidence density–sampled control subjects. For each case subject, we selected up to four control subjects, individually matched on mining facility, sex, race/ethnicity, and birth year (within 5 years), from all workers who were alive before the day the case subject died. We estimated diesel exhaust exposure, represented by respirable elemental carbon (REC), by job and year, for each subject, based on an extensive retrospective exposure assessment at each mining facility. We conducted both categorical and continuous regression analyses adjusted for cigarette smoking and other potential confounding variables (eg, history of employment in high-risk occupations for lung cancer and a history of respiratory disease) to estimate odds ratios (ORs) and 95% confidence intervals (CIs). Analyses were both unlagged and lagged to exclude recent exposure such as that occurring in the 15 years directly before the date of death (case subjects)/reference date (control subjects). All statistical tests were two-sided. Results We observed statistically significant increasing trends in lung cancer risk with increasing cumulative REC and average REC intensity. Cumulative REC, lagged 15 years, yielded a statistically significant positive gradient in lung cancer risk overall (P trend = .001); among heavily exposed workers (ie, above the median of the top quartile [REC ≥ 1005 μg/m3-y]), risk was approximately three times greater (OR = 3.20, 95% CI = 1.33 to 7.69) than that among workers in the lowest quartile of exposure. Among never smokers, odd ratios were 1.0, 1.47 (95% CI = 0.29 to 7.50), and 7.30 (95% CI = 1.46 to 36.57) for workers with 15-year lagged cumulative REC tertiles of less than 8, 8 to less than 304, and 304 μg/m3-y or more, respectively. We also observed an interaction between smoking and 15-year lagged cumulative REC (P interaction = .086) such that the effect of each of these exposures was attenuated in the presence of high levels of the other. Conclusion Our findings provide further evidence that diesel exhaust exposure may cause lung cancer in humans and may represent a potential public health burden. PMID:22393209

The Diesel Exhaust in Miners study: a nested case-control study of lung cancer and diesel exhaust.

PubMed

Silverman, Debra T; Samanic, Claudine M; Lubin, Jay H; Blair, Aaron E; Stewart, Patricia A; Vermeulen, Roel; Coble, Joseph B; Rothman, Nathaniel; Schleiff, Patricia L; Travis, William D; Ziegler, Regina G; Wacholder, Sholom; Attfield, Michael D

2012-06-06

Most studies of the association between diesel exhaust exposure and lung cancer suggest a modest, but consistent, increased risk. However, to our knowledge, no study to date has had quantitative data on historical diesel exposure coupled with adequate sample size to evaluate the exposure-response relationship between diesel exhaust and lung cancer. Our purpose was to evaluate the relationship between quantitative estimates of exposure to diesel exhaust and lung cancer mortality after adjustment for smoking and other potential confounders. We conducted a nested case-control study in a cohort of 12 315 workers in eight non-metal mining facilities, which included 198 lung cancer deaths and 562 incidence density-sampled control subjects. For each case subject, we selected up to four control subjects, individually matched on mining facility, sex, race/ethnicity, and birth year (within 5 years), from all workers who were alive before the day the case subject died. We estimated diesel exhaust exposure, represented by respirable elemental carbon (REC), by job and year, for each subject, based on an extensive retrospective exposure assessment at each mining facility. We conducted both categorical and continuous regression analyses adjusted for cigarette smoking and other potential confounding variables (eg, history of employment in high-risk occupations for lung cancer and a history of respiratory disease) to estimate odds ratios (ORs) and 95% confidence intervals (CIs). Analyses were both unlagged and lagged to exclude recent exposure such as that occurring in the 15 years directly before the date of death (case subjects)/reference date (control subjects). All statistical tests were two-sided. We observed statistically significant increasing trends in lung cancer risk with increasing cumulative REC and average REC intensity. Cumulative REC, lagged 15 years, yielded a statistically significant positive gradient in lung cancer risk overall (P (trend) = .001); among heavily exposed workers (ie, above the median of the top quartile [REC ≥ 1005 μg/m(3)-y]), risk was approximately three times greater (OR = 3.20, 95% CI = 1.33 to 7.69) than that among workers in the lowest quartile of exposure. Among never smokers, odd ratios were 1.0, 1.47 (95% CI = 0.29 to 7.50), and 7.30 (95% CI = 1.46 to 36.57) for workers with 15-year lagged cumulative REC tertiles of less than 8, 8 to less than 304, and 304 μg/m(3)-y or more, respectively. We also observed an interaction between smoking and 15-year lagged cumulative REC (P (interaction) = .086) such that the effect of each of these exposures was attenuated in the presence of high levels of the other. Our findings provide further evidence that diesel exhaust exposure may cause lung cancer in humans and may represent a potential public health burden.

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.