208 resultados para Underground Mine


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Video installation, Metrolpolis: Part I-III, using 1-channel HD video with surround sound. At the end of the first decade of the twenty–first century, contemporary culture appears increasingly seduced and absorbed by apocalyptic reveries. Scientists are racing to cryo-preserve genetic material from animals and plant matter in underground bunkers, while filmmakers use the spectacle of computer-generated imagery (CGI) to speculate on the outcomes from dramatic climate change, that we are not yet ready to confront in reality... Premier's new media art prize 2010: http://www.qagoma.qld.gov.au/exhibitions/past/2010/premier_of_queenslands_national_new_media_art_award_2010/chris_howlett

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Between 1984 and 1997, six cases of urothelial cancer and 14 cases of renal cell cancer occurred in a group of 500 underground mining workers in the copper-mining industry of the former German Democratic Republic, with high exposures to explosives containing technical dinitrotoluene. Exposure durations ranged from 7 to 37 years, and latency periods ranged from 21 to 46 years. The incidences of both urothelial and renal cell tumors in this group were much higher than anticipated on the basis of the cancer registers of the German Democratic Republic by factors of 4.5 and 14.3, respectively. The cancer cases and a representative group of 183 formerly dinitrotoluene- exposed miners of this local industry were interviewed for their working history and grouped into four exposure categories. This categorization of the 14 renal cell tumor cases revealed no dose-dependency concerning explosives in any of the four exposure categories and was similar to that of the representative group of employees, whereas the urothelial tumor cases were predominantly confined to the high-exposure categories. Furthermore, all identified tumor patients were genotyped by polymerase chain reaction, using lymphocyte DNA, regarding their genetic status of the polymorphic xenobiotic metabolizing enzymes, including the N-acetyltransferase 2 and the glutathione-S-transferases M1 and T1. This genotyping revealed remarkable distributions only for the urothelial tumor cases, who were exclusively identified as 'slow acetylators.' This points to the possibility of human carcinogenicity of dinitrotoluene, with regard to the urothelium as the target tissue.

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Technical dinitrotoluene (DNT) is a mixture of 2,4- and 2,6-DNT. In humans, industrial or environmental exposure can occur orally, by inhalation, or by skin contact. The classification of DNT as an 'animal carcinogen' is based on the formation of malignant tumors in kidneys, liver, and mammary glands of rats and mice. Clear signs of toxic nephropathy were found in rats dosed with DNT, and the concept was derived of an interrelation between renal toxicity and carcinogenicity. Recent data point to the carcinogenicity of DNT on the urinary tract of exposed humans. Between 1984 and 1997, 6 cases of urothelial cancer and 14 cases of renal cell cancer were diagnosed in a group of 500 underground mining workers in the copper mining industry of the former GDR and having high exposures to explosives containing technical DNT. The incidences of both urothelial and renal cell tumors in this group were 4.5 and 14.3 times higher, respectively, than anticipated on the basis of the cancer registers of the GDR. The genotyping of all identified tumor patients for the polymorphic enzymes NAT2, GSTM1, and GSTT1 identified the urothelial tumor cases as exclusively 'slow acetylates'. A group of 161 miners highly exposed to DNT was investigated for signs of subclinical renal damage. The exposures were categorized semi-quantitatively into 'low', 'medium', 'high', and 'very high'. A straight dose-dependence of the excretion of urinary biomarker proteins with the ranking of exposure was seen. Biomarker excretion (alpha1-microglobulin, glutathione S-transferases alpha and pi) indicated that DNT-induced damage was directed toward the tubular system. New data on DNT-exposed humans appear consistent with the concept of cancer initiation by DNT isomers and the subsequent promotion of renal carcinogenesis by selective damage to the proximal tubule. The differential pathways of metabolic activation of DNT appear to apply to the proximal tubule of the kidney and to the urothelium of the renal pelvis and lower urinary tract as target tissues of carcinogenicity.

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A cohort of 161 underground miners who had been highly exposed to dinitrotoluene (DNT) in the copper-mining industry of the former German Democratic Republic was reinvestigated for signs of subclinical renal damage. The study included a screening of urinary proteins excreted by sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE), and quantitations of the specific urinary proteins α 1-microglobulin and glutathione-S-transferase α (GST α) as biomarkers for damage of the proximal tubule and glutathione-S-transferase π (GST π) for damage of the distal tubule. The exposures were categorized semiquantitatively (low, medium, high, and very high), according to the type and duration of professional contact with DNT. A straight dose-dependence of pathological protein excretion patterns with the semiquantitative ranking of DNT exposure was seen. Most of the previously reported cancer cases of the urinary tract, especially those in the higher exposed groups, were confined to pathological urinary protein excretion patterns. The damage from DNT was directed toward the tubular system. In many cases, the appearance of Tamm-Horsfall protein, a 105-kD protein marker, was noted. Data on the biomarkers α 1-microglobulin, GST α, and GST π consistently demonstrated a dose-dependent increase in tubular damage, which confirmed the results of screening by SDS-PAGE and clearly indicated a nephrotoxic effect of DNT under the given conditions of exposure. Within the cluster of cancer patients observed among the DNT-exposed workers, only in exceptional cases were normal biomarker excretions found.

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This research treated the response of underground transportation tunnels to surface blast loads using advanced computer simulation techniques. The influences of important parameters, such as tunnel material, geometrical configuration of segments and surrounding soil were investigated. The findings of this research offer significant new information on the blast performance of underground tunnels and will contribute towards future civil engineering applications.

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In 1996, Emma Baulch went to live in Bali to do research on youth culture. Her chats with young people led her to an enormously popular regular outdoor show dominated by local reggae, punk, and death metal bands. In this rich ethnography, she takes readers inside each scene: hanging out in the death metal scene among unemployed university graduates clad in black T-shirts and ragged jeans; in the punk scene among young men sporting mohawks, leather jackets, and hefty jackboots; and among the remnants of the local reggae scene in Kuta Beach, the island’s most renowned tourist area. Baulch tracks how each music scene arrived and grew in Bali, looking at such influences as the global extreme metal underground, MTV Asia, and the internationalization of Indonesia’s music industry. Making Scenes is an exploration of the subtle politics of identity that took place within and among these scenes throughout the course of the 1990s. Participants in the different scenes often explained their interest in death metal, punk, or reggae in relation to broader ideas about what it meant to be Balinese, which reflected views about Bali’s tourism industry and the cultural dominance of Jakarta, Indonesia’s capital and largest city. Through dance, dress, claims to public spaces, and onstage performances, participants and enthusiasts reworked “Balinese-ness” by synthesizing global media, ideas of national belonging, and local identity politics. Making Scenes chronicles the creation of subcultures at a historical moment when media globalization and the gradual demise of the authoritarian Suharto regime coincided with revitalized, essentialist formulations of the Balinese self.

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Transit passenger market segmentation enables transit operators to target different classes of transit users for targeted surveys and various operational and strategic planning improvements. However, the existing market segmentation studies in the literature have been generally done using passenger surveys, which have various limitations. The smart card (SC) data from an automated fare collection system facilitate the understanding of the multiday travel pattern of transit passengers and can be used to segment them into identifiable types of similar behaviors and needs. This paper proposes a comprehensive methodology for passenger segmentation solely using SC data. After reconstructing the travel itineraries from SC transactions, this paper adopts the density-based spatial clustering of application with noise (DBSCAN) algorithm to mine the travel pattern of each SC user. An a priori market segmentation approach then segments transit passengers into four identifiable types. The methodology proposed in this paper assists transit operators to understand their passengers and provides them oriented information and services.

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Successful prediction of groundwater flow and solute transport through highly heterogeneous aquifers has remained elusive due to the limitations of methods to characterize hydraulic conductivity (K) and generate realistic stochastic fields from such data. As a result, many studies have suggested that the classical advective-dispersive equation (ADE) cannot reproduce such transport behavior. Here we demonstrate that when high-resolution K data are used with a fractal stochastic method that produces K fields with adequate connectivity, the classical ADE can accurately predict solute transport at the macrodispersion experiment site in Mississippi. This development provides great promise to accurately predict contaminant plume migration, design more effective remediation schemes, and reduce environmental risks. Key Points Non-Gaussian transport behavior at the MADE site is unraveledADE can reproduce tracer transport in heterogeneous aquifers with no calibrationNew fractal method generates heterogeneous K fields with adequate connectivity

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Large concentrations of magnetite in sedimentary deposits and soils with igneous parent material have been reported to affect geophysical sensor performance. We have undertaken the first systematic experimental effort to understand the effects of magnetite for ground-penetrating radar (GPR) characterization of the shallow subsurface. Laboratory experiments were conducted to study how homogeneous magnetite-sand mixtures and magnetite concentrated in layers affect the propagation behavior (velocity, attenuation) of high-frequency GPR waves and the reflection characteristics of a buried target. Important observations were that magnetite had a strong effect on signal velocity and reflection, at magnitudes comparable to what has been observed in small-scale laboratory experiments that measured electromagnetic properties of magnetite-silica mixtures. Magnetite also altered signal attenuation and affected the reflection characteristics of buried targets. Our results indicated important implications for several fields, including land mine detection, Martian exploration, engineering, and moisture mapping using satellite remote sensing and radiometers.

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Hydraulic conductivity (K) fields are used to parameterize groundwater flow and transport models. Numerical simulations require a detailed representation of the K field, synthesized to interpolate between available data. Several recent studies introduced high-resolution K data (HRK) at the Macro Dispersion Experiment (MADE) site, and used ground-penetrating radar (GPR) to delineate the main structural features of the aquifer. This paper describes a statistical analysis of these data, and the implications for K field modeling in alluvial aquifers. Two striking observations have emerged from this analysis. The first is that a simple fractional difference filter can have a profound effect on data histograms, organizing non-Gaussian ln K data into a coherent distribution. The second is that using GPR facies allows us to reproduce the significantly non-Gaussian shape seen in real HRK data profiles, using a simulated Gaussian ln K field in each facies. This illuminates a current controversy in the literature, between those who favor Gaussian ln K models, and those who observe non-Gaussian ln K fields. Both camps are correct, but at different scales.

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Full-resolution 3D Ground-Penetrating Radar (GPR) data were combined with high-resolution hydraulic conductivity (K) data from vertical Direct-Push (DP) profiles to characterize a portion of the highly heterogeneous MAcro Dispersion Experiment (MADE) site. This is an important first step to better understand the influence of aquifer heterogeneities on observed anomalous transport. Statistical evaluation of DP data indicates non-normal distributions that have much higher similarity within each GPR facies than between facies. The analysis of GPR and DP data provides high-resolution estimates of the 3D geometry of hydrostratigraphic zones, which can then be populated with stochastic K fields. The lack of such estimates has been a significant limitation for testing and parameterizing a range of novel transport theories at sites where the traditional advection-dispersion model has proven inadequate.

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Magnetic properties of soils have been highlighted as a primary detrimental environmental effect on the performance of geophysical systems for detection of unexploded ordnance (UXO) and mine targets. A recent workshop at Cranfield University, U.K., aimed to identify knowledge gaps related to soil magnetism. Eight invited speakers from multidisciplinary areas provided briefings on state‐of‐the‐art research linked to soil magnetism and geophysical sensing. Contributions from other participants provided additional insights from a range of disciplines through case studies and applications. The workshop included break‐out sessions to identify current gaps in knowledge and to determine priority areas for investment in research to further developments in UXO and mine detection in magnetic soil environments. Key recommendations for future research investments have been grouped in categories including soils, theory and modeling, instrumentation, and communication.