نتایج جستجو برای: period deep crustal exploration
تعداد نتایج: 776957 فیلتر نتایج به سال:
Discrimination of the blind and dispersed mineralization deposits is a challenging problem in geochemical exploration. The frequency domain (FD) of the surface geochemical data can solve this important issue. This new exploratory information can be achieved using the interpretation of FD of geochemical data, which is impossible in spatial domain. In this research work, FD of the surface geochem...
It is generally accepted that continental subduction and crustal exhumation play an important role in the evolution of many orogenic belts. A variety of geological evidence suggests that continental crust is occasionally subducted to depths of tens to perhaps 150 km (e.g. Chopin, 1984; Dewey et al., 1993; Matte et al., 1997). Recently, a series of simulations (Chemenda, 1993; Chemenda et al., 1...
Abstract The deep seafloor covers two-thirds of Earth's surface area, but our understanding the ecosystems and resources found in ocean, as well ability deep-sea to withstand human perturbation, is limited. These habitats demand urgent study there are emergent uses form mining carbon sequestration that will fundamentally alter physical, chemical, biological conditions took millions years establ...
Eruptive activity at Turrialba Volcano (Costa Rica) has escalated significantly since 2014, causing airport and school closures in the capital city of San José. Whether or not new magma is involved in the current unrest seems probable but remains a matter of debate as ash deposits are dominated by hydrothermal material. Here we use high-frequency gas monitoring to track the behavior of the volc...
Abstract The Lu-Hf isotopic system, much like the Sm-Nd can be used to understand crustal evolution and growth. Crustal differentiation processes yield reservoirs with differing initial Lu/Hf values, radioactive decay of 176 Lu results in diverging Hf/ 177 Hf between over time. This chapter outlines fundamentals provides several case studies outlining utility this system mineral exploration und...
Building robust online content recommendation systems requires learning complex interactions between user preferences and content features. e eld has evolved rapidly in recent years from traditional multi-arm bandit and collaborative ltering techniques, with new methods employing Deep Learning models to capture non-linearities. Despite progress, the dynamic nature of online recommendations s...
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