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The sedimentary basin is a basic geological unit in the Earth system: its formation and evolution are controlled mainly by plate tectonics and geodynamics, which have produced a variety of basin types. The development and evolution of various basins depend not only on the tectonic effect of lithospheric plate but also on sublithospheric, and Earth surface actions. Basin classification schemes based on the theories of platform–geosyncline or plate tectonics could neither include all basin types nor reflect the complex processes of basin formation and evolution. From the viewpoint of Earth system, we proposed a new basin classification scheme based on geodynamic mechanism—that is, lithospheric plate, sublithospheric, and Earth surface actions. In our geodynamic classification, we employed a series of geodynamic settings of basin formation and evolution, including the lithospheric plate, sublithospheric, and Earth surface environments, the dynamic regimes of basin formation and evolution, such as tectonic setting (extension, compression and shearing), the thermal processes and gravity effects, the various natures of basin basement and crustal types (continental, oceanic, or transitional crust), and the history of basin sedimentary filling and tectonic paleogeography successively, as the controlling factors for basin classification. This new geodynamic classification scheme highlights both the role of the lithosphere and the effects of the sublithospheric and the Earth surface actions on controlling the basin formation and evolution. The basic dynamic types of basin classification include the prototype basin forming under a single tectonic, thermal, or gravity regime and the superimposed basin as well as residual basin forming under multistage thermal and/or tectonic regimes. Thus, this classification scheme could provide an evolving understanding of lithosphere, crust–mantle interaction, and geodynamic processes as well as of hydrocarbon accumulation and metallogenic mechanisms in sedimentary basins and would help in the synthetic exploration of various resources.

The outbreak of the COVID-19 pandemic affects lives and social-economic development around the world. The affecting of the pandemic has motivated researchers from different domains to find effective solutions to diagnose, prevent, and estimate the pandemic and relieve its adverse effects. Numerous COVID-19 datasets are built from these studies and are available to the public. These datasets can be used for disease diagnosis and case prediction, speeding up solving problems caused by the pandemic. To meet the needs of researchers to understand various COVID-19 datasets, we examine and provide an overview of them. We organise the majority of these datasets into three categories based on the category of applications, i.e., time-series, knowledge base, and media-based datasets. Organising COVID-19 datasets into appropriate categories can help researchers hold their focus on methodology rather than the datasets. In addition, applications and COVID-19 datasets suffer from a series of problems, such as privacy and quality. We discuss these issues as well as potentials of COVID-19 datasets.

In this paper we consider a fluid-fluid system coupled with a friction-type interface condition which is described by a jump of the velocities along the tangential interface. Based on domain decomposition, we propose a Schwarz type iterative method to decouple the different physical process in each subdomain occupied by a single fluid, which allows solving in each subdomain only the physical process described by a Stokes problem. Using energy estimate, we prove that the algorithm converges for any traction coefficient. A more detailed analysis based on Fourier analysis shows that the convergence rate depends on both the fluids' properties, the traction coefficient and the time stepsize, but is independent of the spatial mesh. We finally use numerical examples to illustrate the theoretical results.

Domain Adaptive Object Detection (DAOD) leverages a labeled domain to learn an object detector generalizing to a novel domain free of annotations. Recent advances align class-conditional distributions by narrowing down cross-domain prototypes (class centers). Though great success,they ignore the significant within-class variance and the domain-mismatched semantics within the training batch, leading to a sub-optimal adaptation. To overcome these challenges, we propose a novel SemantIc-complete Graph MAtching (SIGMA) framework for DAOD, which completes mismatched semantics and reformulates the adaptation with graph matching. Specifically, we design a Graph-embedded Semantic Completion module (GSC) that completes mismatched semantics through generating hallucination graph nodes in missing categories. Then, we establish cross-image graphs to model class-conditional distributions and learn a graph-guided memory bank for better semantic completion in turn. After representing the source and target data as graphs, we reformulate the adaptation as a graph matching problem, i.e., finding well-matched node pairs across graphs to reduce the domain gap, which is solved with a novel Bipartite Graph Matching adaptor (BGM). In a nutshell, we utilize graph nodes to establish semantic-aware node affinity and leverage graph edges as quadratic constraints in a structure-aware matching loss, achieving fine-grained adaptation with a node-to-node graph matching. Extensive experiments verify that SIGMA outperforms existing works significantly. Our code is available at https://github.com/CityU-AIM-Group/SIGMA., Comment: Accepted by CVPR2022 (ORAL presentation)

The complex pore system in tight sandstone reservoirs controls the storage and transport of natural gas. Thus, quantitatively characterizing the micro-nanopore structure of tight sandstone reservoirs is of great significance to determining the accumulation and distribution of tight gas. The pore structure of reservoirs was determined through polarizing microscopy, scanning electron microscopy (SEM), and the combination of mercury injection capillary pressure (MICP) and nuclear magnetic resonance (NMR) experiments on Late Paleozoic conventional and tight sandstone samples from the Linxing Block, Ordos Basin. The results show that in contrast to conventional sandstone, dissolution pores, with diameters less than 8 μm, are the main contributors to the gas storage space of tight sandstone reservoirs. The pore size distribution derived from the MICP experiment demonstrates that the main peak of tight sandstones corresponds to a pore radius in the range of 247 nm to 371 nm, while the secondary peak usually corresponds to 18 nm. The results of the NMR test illustrate that the T2 spectra of tight sandstones are unimodal, bimodal and multimodal, and the main NMR peak is highly related to the MICP peak. Fractal theory was proposed to quantitatively characterize the complex pore structure and rough porous surface. The sandstones show fractal characteristics including nanopore fractal dimension DN obtained from the MICP and large pore fractal dimension DL obtained from the NMR experiment. Both DN and DL are positively correlated with porosity and negatively correlated with permeability, demonstrating that complex and heterogeneous pore structure could increase the gas storage space and reduce the connectivity.

Domain Adaptive Object Detection (DAOD) models a joint distribution of images and labels from an annotated source domain and learns a domain-invariant transformation to estimate the target labels with the given target domain images. Existing methods assume that the source domain labels are completely clean, yet large-scale datasets often contain error-prone annotations due to instance ambiguity, which may lead to a biased source distribution and severely degrade the performance of the domain adaptive detector de facto. In this paper, we represent the first effort to formulate noisy DAOD and propose a Noise Latent Transferability Exploration (NLTE) framework to address this issue. It is featured with 1) Potential Instance Mining (PIM), which leverages eligible proposals to recapture the miss-annotated instances from the background; 2) Morphable Graph Relation Module (MGRM), which models the adaptation feasibility and transition probability of noisy samples with relation matrices; 3) Entropy-Aware Gradient Reconcilement (EAGR), which incorporates the semantic information into the discrimination process and enforces the gradients provided by noisy and clean samples to be consistent towards learning domain-invariant representations. A thorough evaluation on benchmark DAOD datasets with noisy source annotations validates the effectiveness of NLTE. In particular, NLTE improves the mAP by 8.4\% under 60\% corrupted annotations and even approaches the ideal upper bound of training on a clean source dataset., CVPR-2022 Version

A series of organic-rich shale samples from various shale gas reservoirs that experienced complex structural change around the Sichuan Basin of the Upper Yangtze Block, South China, have been studied with respect to their microstructural and petrophysical variations, using mercury intrusion porosimetry (MIP) and scanning electron microscopy (SEM). Deformed samples were chosen as being representative of various degrees of deformation intensity, and undeformed samples (reference primary structure shales) were sampled outside the main deformed zones. In most of the examples explored, porosity, permeability, and fracture varied with the degree of structural deformation at the micrometer or even nanometer scale, changing and in most cases increasing the deformed shales's ability to store and transport hydrocarbon molecules. Quartz and carbonates are primarily responsible for petrophysical variations, but tectonism can strongly influence these existing relations. Porosity varies by up to one to two times in extreme cases, but the average porosity increase is about one time. Permeability increases by up to three to four orders of magnitude in extreme cases, but the average permeability increase is about two to three orders of magnitude. These ranges depend heavily on the development of abundant natural micro-fractures and micro-channels. Six major fracture types, including matrix micro-fracture, mineral-related micro-fracture, OM-related micro-fracture, fracture-edge micro-channel, pore-edge micro-channel, and intragranular micro-channel, have been identified and classified by size, location, and geometry. Furthermore, possible formation mechanisms for these fractures, such as grain crushing, grain cracking, grain folding, and grain spacing, have been proposed and discussed. This study highlights the tectonic processes for natural fracture formation and their changes in porosity and permeability. These results have significant implications for understanding methane storage and fluid migration in naturally deformed shale reservoirs, and they could prove important for evaluating and predicting producible resources.

Climate change presents great variations on different flanks and elevations in the same mountain range. Analysis of the spatial and temporal variations of climate on different flanks and elevations in the north-south transition zone--the Qinling-Daba Mountains (QDM) are of great significance for exploring the complexity of climate geography pattern and phenology in China. This paper collected 118 weather stations data on daily temperature and precipitation during 1969-2018 from the National Meteorological Information Center, and then explored the temporal and spatial distribution characteristics of climate on different flanks and elevations. The results showed that: 1) On the whole, there was a significant warming trend in the four seasons in the past 50 years. Precipitation did not show significant variation at most stations with an exception to 8 weather stations having significant changes in trend in different seasons. 2) The temperature showed an increasing trend in different seasons, but its increasing rate varied greatly on different flanks. Generally speaking, climate change was greater on the northern flanks than that on the southern flanks in the four seasons in the QDM. Temperature tendency is greater in spring and winter than in summer and autumn on different flanks in the QDM. 3) The increase rate of temperature varied greatly at different elevations in different seasons. The warming rate was greater in the higher altitude regions than that of the lower altitude regions in summer, autumn and winter, while, in spring, however, it is higher in the lower altitudes than in the higher altitudes.

Decoupling the sibling head has recently shown great potential in relieving the inherent task-misalignment problem in two-stage object detectors. However, existing works design similar structures for the classification and regression, ignoring task-specific characteristics and feature demands. Besides, the shared knowledge that may benefit the two branches is neglected, leading to potential excessive decoupling and semantic inconsistency. To address these two issues, we propose Heterogeneous task decoupling (HTD) framework for object detection, which utilizes a Progressive Graph (PGraph) module and a Border-aware Adaptation (BA) module for task-decoupling. Specifically, we first devise a Semantic Feature Aggregation (SFA) module to aggregate global semantics with image-level supervision, serving as the shared knowledge for the task-decoupled framework. Then, the PGraph module performs progressive graph reasoning, including local spatial aggregation and global semantic interaction, to enhance semantic representations of region proposals for classification. The proposed BA module integrates multi-level features adaptively, focusing on the low-level border activation to obtain representations with spatial and border perception for regression. Finally, we utilize the aggregated knowledge from SFA to keep the instance-level semantic consistency (ISC) of decoupled frameworks. Extensive experiments demonstrate that HTD outperforms existing detection works by a large margin, and achieves single-model 50.4%AP and 33.2% AP s on COCO test-dev set using ResNet-101-DCN backbone, which is the best entry among state-of-the-arts under the same configuration. Our code is available at https://github.com/CityU-AIM-Group/HTD .

Climate change exhibits great variation on different flanks and at different elevations in the same mountain range. To investigate the complexity of the geographic patterns of climate and phenology in the Qinling–Daba mountains (QDM), in the North–South transition zone of China, this study analyzed the spatiotemporal distribution characteristics of daily air temperature and precipitation data measured at 118 national weather stations (1969–2018). The principal findings were as follows. (1) Overall, a significant trend of warming was detected in all seasons over the past 50 years, with rates of increase of 0.347, 0.125, 0.200 and 0.302 °C/10a, in spring, summer, autumn and winter, respectively. Precipitation did not show significant variation at most stations in different seasons. (2) The rising rate of air temperature varied considerably between different flanks. Generally, air temperature change on northern flanks was greater than on southern flanks in all seasons. The tendency of air temperature change was greater in spring and winter than in summer and autumn on different flanks in the QDM. (3) The rate of increase in high-elevation regions was greater than in low-elevation regions in summer, autumn and winter, e.g., 0.440, 0.390 and 0.456 °C/10a at 3000–4000 m and 0.205, 0.218 and 0.303 °C/10a at 0–1000 m, respectively. However, in spring, the rate of increase in low-elevation regions were higher than in high-elevation regions, e.g., 0.369 °C/10a at 0–1000 m and 0.317 °C/10a at 3000–4000 m.

Land use changes affect the surface radiative budget and energy balance by changing the surface albedo, which generates radiative forcing, impacting the regional and global climate. To estimate the effect of land use changes on the surface albedo and climate change in a mountainous area with complex terrain, we obtained MODIS data, identified the spatial–temporal characteristics of the surface albedo caused by land use changes, and then calculated the radiative forcing based on solar radiative data and the surface albedo in the Qinling-Daba mountains from 2000 to 2015. The correlation between the land use changes and the radiative forcing was analyzed to explore the climate effects caused by land use changes on a kilometer-grid scale in the Qinling-Daba mountains. Our results show that the primarily land use changes were a decrease in the cultivated land area and an increase in the construction land area, as well as other conversions between six land use types from 2000 to 2015. The land use changes led to significant changes in the surface albedo. Meanwhile, the radiative forcing caused by the land use had different magnitudes, strengths, and occurrence ranges, resulting in both warming and cooling climate change effects.

Pore types and pore size vary systematically across structural deformation in the shale gas reservoirs but lack a comprehensive study. Twelve Longmaxi Shale samples spanning a tectonism range from undeformed to deformed were formed in the structural deformation zone located in a field section of the Chuandong Thrust-Fold Belt, South China. Herein, pore structure investigations are performed using three types of organic-rich shale (undeformed shale, fault-related shale, and fold-related shale) with vitrinite reflectance (Ro value) ranging between 1.90 and 2.57% and total organic carbon (TOC) content ranging between 2.25 and 4.40%. Compared to the undeformed shales, deformed samples are quartz rich and carbonate poor. Total porosity from mercury intrusion porosimetry (MIP) ranges between 3.74 and 5.62% in undeformed shales, 2.66–6.83% in fold-related shales, and 2.55–13.92% in fault-related shales. Scanning electron microscopy (SEM) study of the pore type evolution reveals organic matter (OM) pores are dominant in undeformed shales whereas the interparticle (interP) pores, intraparticle (intraP) pores, micro-channels, and micro-fractures are more developed in both fold- and fault-related shales. A combination of low-pressure gas (N2 and CO2) adsorption and MIP techniques suggests that with increasing structural deformation, micropore volumes relatively increase in fold-related samples, while macropore volumes significantly increase in fault-related shales. These observations and experiments confirm that tectonism produces an open and interconnected pore network within organic-rich shale, which is not related to OM pores. The role of structural deformation during ductile folding and brittle sliding, both in changing the mineral composition and in the producing process of the new pore networks, may be critical to understanding tectonism on organic-rich shales. These data could provide important theoretical guidance and scientific basis for the exploration and development of shale gas and resources assessment in the complex tectonic area of South China.

The Fenton oxidation of nuclear grade cationic exchange resin was investigated in view of the effects of initial temperature, H2O2 dosage, catalyst type and concentration as well as initial pH. Initial temperature and H2O2 dosage exhibited a significant positive effect on the decomposition of cationic resins, whereas the initial pH showed a negative effect. Ferrous ions had higher catalytic ability than copper ions to the H2O2 activation for resin decomposition, and the best Fe2+ concentration was 0.3 M. Under the conditions of initial temperature of 75 °C, H2O2 dosage of 200 mL, Fe2+ concentration of 0.3 M and initial pH of 0.01, a weight reduction of 73% was achieved. The experimental results on Co-substituted mock samples indicated that the radionuclides loaded in the resins were concentrated in liquid residue. The decomposition of cationic resins followed the two-stage first-order kinetics that composed of a dissolution period of resin beads (first-stage) and a followed degradation stage of resin solution (second-stage). Combined with the UV–visible and infrared spectra and their corresponding density functional theory (DFT) calculations, the dissolution of resin beads was due to the desulfonation of the sulfonated aromatic rings and the oxidative fragmentation of the polymer backbone by hydroxyl radicals ( OH) formed in Fenton reactions. After the dissolution of resin beads, the oxidative degradation and mineralization process proceeded by the attack of OH mainly in aqueous medium.