Ultra) high-pressure (HP) rocks can be exhumed rapidly by subduction reversal or divergent plate motion. Recent studies show that subduction reversal can in particular occur in a divergent double subduction zone when the slab pull of one slab exceeds that of the other, shorter one, which then experiences a net upward pull. This recent hypothesis, first proposed for Triassic HP-rocks exposed in the central Qiangtang mélange belt in central Tibet, can explain the exhumation of (ultra) HP rocks through upward slab movement. However, this model lacks the support of kinematic evidence. In this study, based on the recognition of multiple deformational phases, we analyze the kinematics of the HP-bearing mélange in central Qiangtang. Based on new 40 Ar-39 Ar geochronology data and those collected from the literature, we present a temporal framework for the new observations. We recognize a switch in sense of shear between the prograde (D1) and exhumation (D2-3) paths. The change of shear sense reflects the reversal from downward to upward movement of the oceanic slab below. Early D2 represents the early exhumation stage that caused retrograde metamorphism from eclogite to blueschist facies. No magmatism occurred during this period. Continued exhumation from blueschist facies to greenschist facies resulted in D2-D3 structures. Voluminous igneous activity occurred during this stage. We suggest that subduction reversal in a divergent double subduction zone can best explain the kinematic evolution and temporal framework above. This exhumation model may provide a new perspective on the exhumation mechanism for other HP rocks around the world.

Low temperature radioluminescence and thermoluminescence spectra of ZnO track numerous changes produced by copper ion implantation into the surface layer. A significant, but unexpected, feature is that the bulk crystal becomes modified by the stress generated in the surface layer. This is reflected by the energy of intrinsic band gap emission. There are also differences in the spectra and peak temperatures of the thermoluminescence components, consistent with such a structural relaxation. The copper implant layer is both absorbing and reflective, so this introduces major distortions on the radioluminescence component from the bulk region, since the bulk luminescence signals are transmitted through, or reflected from, the implant layer. The temperature dependence of the spectra includes anomalies that are typical of changes driven by phase transitions of nanoparticle inclusions. Overall, the features of bulk relaxation, spectral distortion, and detection of nanoparticle inclusions are rarely considered for ion implanted luminescence studies, but the data suggest they are almost inevitable in a wide range of implanted materials.

ABSTRACT:Hyperspectral images (HSIs) denoising is a critical research area in image processing duo to its importance in improving the quality of HSIs, which has a negative impact on object detection and classification and so on. In this paper, we develop a noise reduction method based on principal component analysis (PCA) for hyperspectral imagery, which is dependent on the assumption that the noise can be removed by selecting the leading principal components. The main contribution of paper is to introduce the spectral spatial structure and nonlocal similarity of the HSIs into the PCA denoising model. PCA with spectral spatial structure can exploit spectral correlation and spatial correlation of HSI by using 3D blocks instead of 2D patches. Nonlocal similarity means the similarity between the referenced pixel and other pixels in nonlocal area, where Mahalanobis distance algorithm is used to estimate the spatial spectral similarity by calculating the distance in 3D blocks. The proposed method is tested on both simulated and real hyperspectral images, the results demonstrate that the proposed method is superior to several other popular methods in HSI denoising.