4 resultados para Silver mines and mining

em Digital Commons at Florida International University


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The Peruvian economy depends for its growth on the export of natural resources and investment in the mining and hydrocarbon sectors. Peruvian governments and mining corporations have confronted anti-mining protests in different ways. While the current government has introduced policies of social inclusion to soften the negative effects of the operations of mining capital and policies of dialogue to engage social actors with the essence of governmental policies, mining companies use corporate social responsibility programs as a cover for the devastating effects of their operations on the environment and the livelihoods and habitats of the indigenous and peasant communities. Curiously, in the current context of the declining commodity prices and export volumes the Peruvian government strengthens its extractivist model of development. This article argues that whatever government that follows the rules of capital cannot but favor the corporations. It points out the main adversaries of the indigenous and peasant communities and the problems to transform the locally and/or regionally struggle into a nationwide battle for another development model.

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Hurricanes, earthquakes, floods, and other serious natural hazards have been attributed with causing changes in regional economic growth, income, employment, and wealth. Natural disasters are said to cause; (1) an acceleration of existing economic trends; (2) an expansion of employment and income, due to recovery operations (the so-called silver lining); and (3) an alteration in the structure of regional economic activity due to changes in "intra" and "inter" regional trading patterns, and technological change.^ Theoretical and stylized disaster simulations (Cochrane 1975; Haas, Cochrane, and Kates 1977; Petak et al. 1982; Ellson et al. 1983, 1984; Boisvert 1992; Brookshire and McKee 1992) point towards a wide scope of possible negative and long lasting impacts upon economic activity and structure. This work examines the consequences of Hurricane Andrew on Dade County's economy. Following the work of Ellson et al. (1984), Guimaraes et al. (1993), and West and Lenze (1993; 1994), a regional econometric forecasting model (DCEFM) using a framework of "with" and "without" the hurricane is constructed and utilized to assess Hurricane Andrew's impact on the structure and level of economic activity in Dade County, Florida.^ The results of the simulation exercises show that the direct economic impact associated with Hurricane Andrew on Dade County is of short duration, and of isolated sectoral impact, with impact generally limited to construction, TCP (transportation, communications, and public utilities), and agricultural sectors. Regional growth, and changes in income and employment reacted directly to, and within the range and direction set by national economic activity. The simulations also lead to the conclusion that areal extent, infrastructure, and sector specific damages or impacts, as opposed to monetary losses, are the primary determinants of a disaster's effects upon employment, income, growth, and economic structure. ^

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The matrices in which Multi Walled Carbon Nanotubes (MWCNTs) are incorporated to produce composites with improved electrical properties can be polymer, metal or metal oxide. Most composites containing CNTs are polymer based because of its flexibility in fabrication. Very few investigations have been focused on CNT-metal composites due to fabrication difficulties, such as achievement of homogeneous distribution of MWCNTs and poor interfacial bonding between MWCNTs and the metal matrix. In an effort to overcome poor interfacial bonding for the Cu - MWCNT composite, silver (Ag) and nickel (Ni) resinates have been incorporated in the ball milling stage. Composites of MWCNT (16, 12, and 8 Vol %) - Cu+Ag+Ni were pelleted at 20,000 psi (669.4 Mpa) and sintered at 950 °C. The electrical conductivity results measured by four probe meter showed that the conductivity decreases with increase in the porosity. Moreover from these results it can also be stated that an addition of optimum value of (12 Vol %) MWCNT leads to high electrical conductivity (9.26E+07 s-m"), which is 50% greater than the conductivity of Cu. It is anticipated that the conductivity can be increased substantially with hot isostatic pressing of the pellet.

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Thanks to the advanced technologies and social networks that allow the data to be widely shared among the Internet, there is an explosion of pervasive multimedia data, generating high demands of multimedia services and applications in various areas for people to easily access and manage multimedia data. Towards such demands, multimedia big data analysis has become an emerging hot topic in both industry and academia, which ranges from basic infrastructure, management, search, and mining to security, privacy, and applications. Within the scope of this dissertation, a multimedia big data analysis framework is proposed for semantic information management and retrieval with a focus on rare event detection in videos. The proposed framework is able to explore hidden semantic feature groups in multimedia data and incorporate temporal semantics, especially for video event detection. First, a hierarchical semantic data representation is presented to alleviate the semantic gap issue, and the Hidden Coherent Feature Group (HCFG) analysis method is proposed to capture the correlation between features and separate the original feature set into semantic groups, seamlessly integrating multimedia data in multiple modalities. Next, an Importance Factor based Temporal Multiple Correspondence Analysis (i.e., IF-TMCA) approach is presented for effective event detection. Specifically, the HCFG algorithm is integrated with the Hierarchical Information Gain Analysis (HIGA) method to generate the Importance Factor (IF) for producing the initial detection results. Then, the TMCA algorithm is proposed to efficiently incorporate temporal semantics for re-ranking and improving the final performance. At last, a sampling-based ensemble learning mechanism is applied to further accommodate the imbalanced datasets. In addition to the multimedia semantic representation and class imbalance problems, lack of organization is another critical issue for multimedia big data analysis. In this framework, an affinity propagation-based summarization method is also proposed to transform the unorganized data into a better structure with clean and well-organized information. The whole framework has been thoroughly evaluated across multiple domains, such as soccer goal event detection and disaster information management.