Trans-Amazon Drilling Project (TADP): origins and evolution of the forests, climate, and hydrology of the South American tropics

This article presents the scientific rationale for an ambitious ICDP drilling project to continuously sample Late Cretaceous to modern sediment in four different sedimentary basins that transect the equatorial Amazon of Brazil, from the Andean foreland to the Atlantic Ocean. The goals of this project are to document the evolution of plant biodiversity in the Amazon forests and to relate biotic diversification to changes in the physical environment, including climate, tectonism, and the surface landscape. These goals require long sedimentary records from each of the major sedimentary basins across the heart of the Brazilian Amazon, which can only be obtained by drilling because of the scarcity of Cenozoic outcrops. The proposed drilling will provide the first long, nearly continuous regional records of the Cenozoic history of the forests, their plant diversity, and the associated changes in climate and environment. It also will address fundamental questions about landscape evolution, including the history of Andean uplift and erosion as recorded in Andean foreland basins and the development of west-to-east hydrologic continuity between the Andes, the Amazon lowlands, and the equatorial Atlantic. Because many modern rivers of the Amazon basin flow along the major axes of the old sedimentary basins, we plan to locate drill sites on the margin of large rivers and to access the targeted drill sites by navigation along these rivers

Detector Description and Performance for the First Coincidence Observations between LIGO and GEO

For 17 days in August and September 2002, the LIGO and GEO interferometer gravitational wave detectors were operated in coincidence to produce their first data for scientific analysis. Although the detectors were still far from their design sensitivity levels, the data can be used to place better upper limits on the flux of gravitational waves incident on the earth than previous direct measurements. This paper describes the instruments and the data in some detail, as a companion to analysis papers based on the first data.Comment: 41 pages, 9 figures 17 Sept 03: author list amended, minor editorial change

Soft Dynamics simulation: 2. Elastic spheres undergoing a T1 process in a viscous fluid

Robust empirical constitutive laws for granular materials in air or in a viscous fluid have been expressed in terms of timescales based on the dynamics of a single particle. However, some behaviours such as viscosity bifurcation or shear localization, observed also in foams, emulsions, and block copolymer cubic phases, seem to involve other micro-timescales which may be related to the dynamics of local particle reorganizations. In the present work, we consider a T1 process as an example of a rearrangement. Using the Soft dynamics simulation method introduced in the first paper of this series, we describe theoretically and numerically the motion of four elastic spheres in a viscous fluid. Hydrodynamic interactions are described at the level of lubrication (Poiseuille squeezing and Couette shear flow) and the elastic deflection of the particle surface is modeled as Hertzian. The duration of the simulated T1 process can vary substantially as a consequence of minute changes in the initial separations, consistently with predictions. For the first time, a collective behaviour is thus found to depend on another parameter than the typical volume fraction in particles.Comment: 11 pages - 5 figure

SciPy 1.0: fundamental algorithms for scientific computing in Python.

SciPy is an open-source scientific computing library for the Python programming language. Since its initial release in 2001, SciPy has become a de facto standard for leveraging scientific algorithms in Python, with over 600 unique code contributors, thousands of dependent packages, over 100,000 dependent repositories and millions of downloads per year. In this work, we provide an overview of the capabilities and development practices of SciPy 1.0 and highlight some recent technical developments