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Vertebroplasty (VP) is a cost-efficient alternative to kyphoplasty. However, it is considered inferior when it comes to maintaining safety and in vertebral body (VB) height restoration. We assess the safety and efficacy of VP in alleviating pain, improving quality of life (QoL), and restoring alignment.

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The present data set provides contextual environmental data for samples from the Tara Oceans Expedition (2009-2013) that were selected for publication in a special issue of the SCIENCE journal (see related references below). The data set provides calculated averages of mesaurements made at the sampling location and depth, calculated averages from climatologies (AMODIS, VGPM) and satellite products.

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The present data set is a worldwide compilation from 11 oceanographic expeditions during which an underwater vision profiler (UVP) was deployed in situ to determine the vertical distribution (abundance) of 10 taxonomic/morphological groups of plankton larger than 600 µm, belonging to the Infrakingdom Rhizaria, including Phaeodaria, Radiolaria, Collodaria and Acantharia.

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The present data set provides environmental context to a worldwide compilation from 11 oceanographic expeditions during which an underwater vision profiler (UVP) was deployed in situ to determine the vertical distribution plankton larger than 600 µm, belonging to the Infrakingdom Rhizaria.

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The Tara Oceans Expedition (2009-2013) sampled the world oceans on board a 36 m long schooner, collecting environmental data and organisms from viruses to planktonic metazoans for later analyses using modern sequencing and state-of-the-art imaging technologies. Tara Oceans Data are particularly suited to study the genetic, morphological and functional diversity of plankton. The present data set provides biodiversity context to all samples from the Tara Oceans Expedition (2009-2013), including various diversity indexes calculated for the sampling location using satellite and model climatologies (Darwin project, Physat) and results from the sequencing of Tara Oceans samples.

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The Tara Oceans Expedition (2009-2013) sampled the world oceans on board a 36 m long schooner, collecting environmental data and organisms from viruses to planktonic metazoans for later analyses using modern sequencing and state-of-the-art imaging technologies. Tara Oceans Data are particularly suited to study the genetic, morphological and functional diversity of plankton. The present data set provides environmental context to all samples from the Tara Oceans Expedition (2009-2013), including calculated averages of mesaurements made concurrently at the sampling location and depth, and calculated averages from climatologies (AMODIS, VGPM) and satellite products.

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The Tara Oceans Expedition (2009-2013) sampled the world oceans on board a 36 m long schooner, collecting environmental data and organisms from viruses to planktonic metazoans for later analyses using modern sequencing and state-of-the-art imaging technologies. Tara Oceans Data are particularly suited to study the genetic, morphological and functional diversity of plankton. The present data set provides environmental context to all samples from the Tara Oceans Expedition (2009-2013), about mesoscale features related to the sampling date, time and location. Includes calculated averages of mesaurements made concurrently at the sampling location and depth, and calculated averages from climatologies (AMODIS, VGPM) and satellite products.

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This study analyzes the patterns of agglomeration of some modern manufacturing sectors in India, and in particular the Indian automobile sector. It also examines and contrasts the factors that have led to different patterns of cluster development in two leading auto clusters in India-Chennai and the National Capital Region (NCR). Moreover, the study analyzes whether firms in clusters perform better than those that are excluded and whether the relative importance of variables that determine the behavior of firms differs among clusters. Our analyses, which employ a combination of quantitative and qualitative methods, show that Indian industrial clusters are largely concentrated in the three clustered regions: NCR, Mumbai-Pune, and Chennai-Bangalore, across different manufacturing sectors. Our study of the auto clusters in Chennai and the NCR find considerable differences in the patterns of cluster formation, due partly to the historical and policy conditions under which firms, particularly, the lead firms must operate. Moreover, our econometric analyses confirmed that being part of a cluster positively influences the performance of the auto component firms and those belonging to a cluster perform better.