1,402 research outputs found
Global deformation on the surface of Venus
Large-scale mapping of tectonic structures on Venus shows that there is an organized global distribution to deformation. The structures we emphasize are linear compressive mountain belts, extensional rafted zones, and the small-scale but widely distributed wrinkle ridges. Ninety percent of the area of the planet's compressive mountain belts are concentrated in the northern hemisphere whereas the southern hemisphere is dominated by extension and small-scale compression. We propose that this striking concentration of fold belts in the northern hemisphere, along with the globe-encircling equatorial rift system, represents a global organization to deformation on Venus
Surface effects of active folding, illustrated with examples from the TianShan intracontinental mountain belt (China)
Understanding the irregularity of seismic cycles: A case study in Turke
Investigating the kinematics of mountain building in Taiwan from the spatiotemporal evolution of the foreland basin and western foothills
The Taiwanese range has resulted from the collision between the Luzon volcanic arc and the Chinese continental margin, which started about 6.5 Myr ago in the north, and has since propagated southward. The building of the range has been recorded in the spatiotemporal evolution of the foreland basin. We analyze this sedimentary record to place some constraints on the kinematics of crustal deformation. The flexure of the foreland under the load of the growing wedge started with a 1.5 Myr long phase of rapid subsidence and sedimentation, which has migrated southward over the last 3.5 Myr at a rate of 31 +10/−5 mm/yr, reflecting the structural evolution of the range and the growth of the topography during the oblique collision. Isopachs from the Toukoshan (~0 to 1.1 Ma) and Cholan (~1.1 to 3.3 Ma) formations, as well as the sedimentation rates retrieved from a well on the Pakuashan anticline, indicate that the foreland basement has been moving toward the center of mass of the orogen by ~45–50 mm/yr during the development of the basin. From there, we estimate the long-term shortening rate across the range to 39.5–44.5 mm/yr. By considering available data on the thrust faults of the foothills of central Taiwan, we show that most (if not all) the shortening across the range is accommodated by the most frontal structures, with little if any internal shortening within the wedge. The range growth appears therefore to have been essentially sustained by underplating rather than by frontal accretion. In addition, only the upper ~7 to 9 km of the underthrusted crust participates to the growth of the orogen. This requires that a significant amount of the Chinese passive margin crust is subducted beneath the Philippine Sea plate
Does wrinkle ridge formation on Mars involve most of the lithosphere
Recent work on the origin of wrinkle ridges suggests that they are compressional tectonic features whose subsurface structure is not understood. Some characteristics of Martian wrinkle ridges are reviewed which suggest that they are the surface expression of thrust faults that extend through much of the lithosphere
DATA DRIVEN APPLICATION STORE LISTING OPTIMIZATION
A computing system (e.g., a cloud server that hosts an application store) may predict the effect of modifying marketing assets (e.g., text, an image, a screenshot, a description, a video, etc.) of an application (hereinafter referred to as an “app”) on acquisitions (e.g., installations) for the app. The computing system may generate these predictions based on historical performance data (e.g., data relating to modifications to one or more marketing assets of the app and to acquisitions for the app) of marketing assets for a variety of types (e.g., lifestyle apps, social media apps, utility apps, productivity apps, entertainment apps including games, etc.) of apps on the app store. In some examples, the historical performance data may include the origin country, language, device type, purchase history, acquisition history, and/or the like of potential customers (e.g., customers of the app) such that the predictions generated by the computing system may be based on one or more of those factors. The computing system may then provide these predictions to a user (e.g., an app developer) of the application store to help (e.g., by providing benchmarks and/or recommendations) the user modify the marketing assets of the user’s app in a manner predicted to increase acquisitions for the user’s app in the app store. For example, the computing system may cause the user’s computing device (e.g., a smartphone, a tablet, a laptop) to display a statistical model (e.g., a cat and whisker plot, a bar graph, etc.) indicating the relationship between modifying one or more marketing assets and acquisitions for any type of app. The computing system may also provide statistics such as the average acquisition, the range of acquisition, the distribution of acquisition, the standard deviation of acquisition, and/or the like. Such statistics may represent acquisition benchmarks for guiding the user in modifying the user’s marketing assets
DATA DRIVEN APPLICATION STORE LISTING OPTIMIZATION
A computing system (e.g., a cloud server that hosts an application store) may predict the effect of modifying marketing assets (e.g., text, an image, a screenshot, a description, a video, etc.) of an application (hereinafter referred to as an “app”) on acquisitions (e.g., installations) for the app. The computing system may generate these predictions based on historical performance data (e.g., data relating to modifications to one or more marketing assets of the app and to acquisitions for the app) of marketing assets for a variety of types (e.g., lifestyle apps, social media apps, utility apps, productivity apps, entertainment apps including games, etc.) of apps on the app store. In some examples, the historical performance data may include the origin country, language, device type, purchase history, acquisition history, and/or the like of potential customers (e.g., customers of the app) such that the predictions generated by the computing system may be based on one or more of those factors. The computing system may then provide these predictions to a user (e.g., an app developer) of the application store to help (e.g., by providing benchmarks and/or recommendations) the user modify the marketing assets of the user’s app in a manner predicted to increase acquisitions for the user’s app in the app store. For example, the computing system may cause the user’s computing device (e.g., a smartphone, a tablet, a laptop) to display a statistical model (e.g., a cat and whisker plot, a bar graph, etc.) indicating the relationship between modifying one or more marketing assets and acquisitions for any type of app. The computing system may also provide statistics such as the average acquisition, the range of acquisition, the distribution of acquisition, the standard deviation of acquisition, and/or the like. Such statistics may represent acquisition benchmarks for guiding the user in modifying the user’s marketing assets
Mechanisms of active folding of the landscape (Southern Tianshan, China)
We explore the kinematic mechanisms of active large-scale folding, based on analysis of two adjacent major anticlines in Tian Shan (central Asia) that share an acceleration of shortening rate leading to topographic emergence and folded geomorphic surfaces. Their folding mechanisms are fundamentally different. Yakeng anticline is a gentle
pure shear detachment fold with 1200 m of shortening and a well-constrained history of growth beginning at 5.5 Ma with an order-of-magnitude increase in shortening rate from 0.16 to 1.2–1.6 mm/yr at 0.16–0.21 Ma. The shape of the deformed topographic surface and of subsurface horizons deposited during deformation is a linearly proportional image at reduced amplitude of the deeper structure, which shows that instantaneous uplift rates have been pointwise linearly proportional to the current finite fold amplitude. In contrast, Quilitak anticline is a complex fault bend fold with uplift rates proportional to the sine of the fault dip, showing discontinuities in uplift rate across active axial surfaces. The 10- to 20-km-wide anticline is topographically emergent only in a central 5- to 7-km-wide mountainous uplift, the abrupt southern edge of which is marked by 600- to 700-m-high triangular facets that result from active folding of a pediment across an active axial surface. The giant facets are shown to form by kink band migration and record postemergence deformation since an order-of-magnitude acceleration in shortening rate from 0.6 t 4–5 mm/yr, apparently contemporaneous with Yakeng. Sections logged across the active 115-m-wide hinge zone show that recent strata provide a bed- by-bed record of fold scarp growth, which is quantitatively deciphered by fitting bed shapes to a finite width kink band migration model
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