117 research outputs found
Tectonic dynamics of the Zhongjiannan Basin in the western South China Sea since the late Miocene
The Zhongjiannan Basin is located west of the South China Sea (SCS) and was affected by the left-lateral strike-slip of the Red River Fault (RRF), the West Edge Fault of the South China Sea (WEFSCS) and the continental rifting of the South China Sea in the early Cenozoic. The Zhongjiannan Basin formed in a strike-pull basin with an S‒N distribution. During the middle Miocene, the sea spreading of the SCS stopped, but the dynamic mechanism of the Zhongjiannan Basin, which controlled the sedimentary and the structural evolution after the late Miocene, remains unclear. In this paper, through the segment interpretation of the latest seismic section in the Zhongjiannan Basin, we conduct a comparative study of the sedimentary structure in the southern and northern Zhongjiannan Basin since the late Miocene. Combined with the regional tectonic dynamics analysis, we propose that the sedimentary and structural evolution of the Zhongjiannan Basin since the late Miocene was mainly controlled by residual magmatic activity in the Southwest Subbasin (SWSB) after expansion stopped, and the compressional structure stress field weakened gradually from south to north. The compressional tectonic stress field from north to south was formed in the northern basin under the dextral strike-slip movement of the RRF. The sedimentary and structural environment was relatively stable in the middle basin. Therefore, the sedimentary-structure evolution of the Zhongjiannan Basin since the late Miocene was controlled by the two different structural stress fields. The above knowledge not only has guiding significance for oil and gas exploration in the Zhongjiannan Basin but also provides a reference for studying the initiation time of dextral strike-slip along the Red River Fault Zone, as well as the junction position between the RRF and the WEFSCS
Polyphyllin I Ameliorates Collagen-Induced Arthritis by Suppressing the Inflammation Response in Macrophages Through the NF-κB Pathway
Background: Rheumatoid arthritis (RA) is a chronic autoimmune disorder, characterized by an increased number of M1-like macrophages in the joints. Polyphyllin I (PPI), one of the main components in the Rhizoma of Paris polyphyllin, displays a selective inhibitory effect on various tumor cells. Here we sought to investigate the anti-rheumatoid arthritis effects and mechanisms of PPI on macrophages in vivo and in vitro.Materials and Methods:In vitro, primary bone marrow-derived macrophages (BMMs) and peritoneal elucidated macrophages (PEMs) were stimulated by lipopolysaccharide (LPS) and Interferon (IFN)-γ and then treated with PPI. We determined the degree of activation of IKKα/β and p65, two key mediators of the NF-κB-mediated inflammatory pathway, by measuring their phosphorylated forms by Western blot. The p65 nuclear localization was detected by immunofluorescent staining. Further, a NF-κB-linked luciferase reporter plasmid, as well as those expressing key mediators of the Toll-like receptor 4 pathway, such as myeloid differentiation primary response 88 (MYD88), interleukin-1 receptor (IL-1R) associated kinase (IRAK)-1, TNF receptor associated factors (TRAF)-6, Transforming growth factor-b–activated kinase 1 (TAK1) and p65, were used to identify the mechanism by which PPI achieves its inhibitory effects on macrophage-mediated inflammation. Moreover, a NF-κB inhibitor, p65-targeted siRNAs, and a p65 plasmid were further used to validate the anti-inflammatory mechanism of PPI. In vivo, PPI (1 mg/kg) was administered intragastrically one time a day for 7 weeks starting on the 42nd day after the first immunization with collagen in a collagen-induced arthritis (CIA) mouse model. Micro-computed Tomography scanning, histological examination, F4/80 and iNOS double immunofluorescent staining and CD4 immunohistochemical staining were performed to determine the effect of PPI treatment on joint structure and inflammation in this model.Results: PPI reduced the inflammatory cytokines production of PEMs stimulated by LPS/IFN-γ, inhibited the phosphorylation of IKKα/β and p65, and prevented p65 nuclear localization. The NF-κB luciferase assay showed that the target of PPI was closely related to the NF-κB pathway. Moreover, NF-κB inhibition, siRNA-mediated knockdown of p65, and p65 overexpression eliminated PPI's inhibitory effect. In addition, PPI attenuated the bone erosion and synovitis, as well as M1-like macrophage and T cell infiltration, in the ankle joint of the CIA model.Conclusion: PPI demonstrated effective amelioration of synovial inflammation in the ankle joint of CIA mice while suppressing NF-κB-mediated production of pro-inflammatory effectors in activated macrophages
Chaiqin chengqi decoction alleviates severity of acute pancreatitis via inhibition of TLR4 and NLRP3 inflammasome: Identification of bioactive ingredients via pharmacological sub-network analysis and experimental validation
Observed changes of cryosphere in China over the second half of the 20th century: an overview
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Seismic stratigraphy of the central South China Sea basin and implications for neotectonics
Coring/logging data and physical property measurements from International Ocean Discovery Program Expedition 349 are integrated with, and correlated to, reflection seismic data to map seismic sequence boundaries and facies of the central basin and neighboring regions of the South China Sea. First-order sequence boundaries are interpreted, which are Oligocene/Miocene, middle Miocene/late Miocene, Miocene/Pliocene, and Pliocene/Pleistocene boundaries. A characteristic early Pleistocene strong reflector is also identified, which marks the top of extensive carbonate-rich deposition in the southern East and Southwest Subbasins. The fossil spreading ridge and the boundary between the East and Southwest Subbasins acted as major sedimentary barriers, across which seismic facies changes sharply and cannot be easily correlated. The sharp seismic facies change along the Miocene-Pliocene boundary indicates that a dramatic regional tectonostratigraphic event occurred at about 5 Ma, coeval with the onsets of uplift of Taiwan and accelerated subsidence and transgression in the northern margin. The depocenter or the area of the highest sedimentation rate switched from the northern East Subbasin during the Miocene to the Southwest Subbasin and the area close to the fossil ridge in the southern East Subbasin in the Pleistocene. The most active faulting and vertical uplifting now occur in the southern East Subbasin, caused most likely by the active and fastest subduction/obduction in the southern segment of the Manila Trench and the collision between the northeast Palawan and the Luzon arc. Timing of magmatic intrusions and seamounts constrained by seismic stratigraphy in the central basin varies and does not show temporal pulsing in their activities.Keywords: South China Sea, Neotectonism, Core-well-seismic integration, Seismic facies, Seismic stratigraphy, IODP Expedition 34
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Ages and magnetic structures of the South China Sea constrained by deep tow magnetic surveys and IODP Expedition 349
Combined analyses of deep tow magnetic anomalies and International Ocean Discovery Program Expedition 349 cores show that initial seafloor spreading started around 33 Ma in the northeastern South China Sea (SCS), but varied slightly by 1-2 Myr along the northern continent-ocean boundary (COB). A southward ridge jump of ∼20 km occurred around 23.6 Ma in the East Subbasin; this timing also slightly varied along the ridge and was coeval to the onset of seafloor spreading in the Southwest Subbasin, which propagated for about 400 km southwestward from ∼23.6 to ∼21.5 Ma. The terminal age of seafloor spreading is ∼15 Ma in the East Subbasin and ∼16 Ma in the Southwest Subbasin. The full spreading rate in the East Subbasin varied largely from ∼20 to ∼80 km/Myr, but mostly decreased with time except for the period between ∼26.0 Ma and the ridge jump (∼23.6 Ma), within which the rate was the fastest at ∼70 km/Myr on average. The spreading rates are not correlated, in most cases, to magnetic anomaly amplitudes that reflect basement magnetization contrasts. Shipboard magnetic measurements reveal at least one magnetic reversal in the top 100 m of basaltic layers, in addition to large vertical intensity variations. These complexities are caused by late-stage lava flows that are magnetized in a different polarity from the primary basaltic layer emplaced during the main phase of crustal accretion. Deep tow magnetic modeling also reveals this smearing in basement magnetizations by incorporating a contamination coefficient of 0.5, which partly alleviates the problem of assuming a magnetic blocking model of constant thickness and uniform magnetization. The primary contribution to magnetic anomalies of the SCS is not in the top 100 m of the igneous basement.Keywords: Crustal evolution, Deep tow magnetic survey, South China Sea tectonics, International Ocean Discovery Program Expedition 349, Magnetic anomaly, ModelingKeywords: Crustal evolution, Deep tow magnetic survey, South China Sea tectonics, International Ocean Discovery Program Expedition 349, Magnetic anomaly, Modelin
Encrypted traffic identification method based on deep residual capsule network with attention mechanism
With the improvement of users’ security awareness and the development of encryption technology, encrypted traffic has become an important part of network traffic, and identifying encrypted traffic has become an important part of network traffic supervision.The encrypted traffic identification method based on the traditional deep learning model has problems such as poor effect and long model training time.To address these problems, the encrypted traffic identification method based on a deep residual capsule network (DRCN) was proposed.However, the original capsule network was stacked in the form of full connection, which lead to a small model coupling coefficient and it was impossible to build a deep network model.The DRCN model adopted the dynamic routing algorithm based on the three-dimensional convolutional algorithm (3DCNN) instead of the fully-connected dynamic routing algorithm, to reduce the parameters passed between each capsule layer, decrease the complexity of operations, and then build the deep capsule network to improve the accuracy and efficiency of recognition.The channel attention mechanism was introduced to assign different weights to different features, and then the influence of useless features on the recognition results was reduced.The introduction of the residual network into the capsule network layer and the construction of the residual capsule network module alleviated the gradient disappearance problem of the deep capsule network.In terms of data pre-processing, the first 784byte of the intercepted packets was converted into images as input of the DRCN model, to avoid manual feature extraction and reduce the labor cost of encrypted traffic recognition.The experimental results on the ISCXVPN2016 dataset show that the accuracy of the DRCN model is improved by 5.54% and the training time of the model is reduced by 232s compared with the BLSTM model with the best performance.In addition, the accuracy of the DRCN model reaches 94.3% on the small dataset.The above experimental results prove that the proposed recognition scheme has high recognition rate, good performance and applicability
Evaluation on new first-tier smart cities in China based on entropy method and TOPSIS
Overload of infrastructure, shortages in energy resources and environmental pollution constitute the main challenges facing current urban management and development. As the best solution to these challenges, smart cities enjoy increasing attention around the world. As China speeds up the urbanization process, the number of pilot smart cities in China continues to increase. Under such a context, it is of great significance to arrange effective and comprehensive evaluations on the construction level of these smart cities. Based on the development realities of cities in China, this study arranged an in-depth analysis of the current literature and policies and established an evaluation system with five dimensions and 30 indicators. The entropy method and TOPSIS (technique for order preference by similarity to an ideal solution) were comprehensively applied to evaluate 15 new first-tier cities in China. The study results demonstrated that these 15 new first-tier cities still had a relatively low smart level, and the gaps among different cities were significant. Because of the differences in the emphasis of the smart city construction of various cities, their performances under different dimensions were widely divergent. Among the five dimensions, smart infrastructure, economy and life had poor performance compared with smart governance and the environment. In addition, some recommendations were initiated to boost the construction of smart cities in China, including accelerated construction for new infrastructure, more emphasis on the digital economy, acceleration in the development of important mechanisms, etc
Towards a Global Schema for Web Entities
Popular entities often have thousands of instances on the Web. In this paper, we focus on the case where they are presented in table-like format, namely appearing with their attribute names. It is observed that, on one hand, for the same entity, different web pages often incorporate different attributes; on the other, for the same attribute, different web pages often use different attribute names (labels). Therefore, it is imaginably difficult to produce a global attribute schema for all the web entities of a given entity type based on their web instances, although the global attribute schema is usually highly desired in web entity instances integration and web object extraction. To this end, we propose a novel framework of automatically learning a global attribute schema for all web entities of one specific entity type. Under this framework, an iterative instances extraction procedure is first employed to extract sufficient web entity instances to discover enough attribute labels. Next, based on the labels, entity instances, and related web pages, a maximum entropy-based schema discovery approach is adopted to learn the global attribute schema for the target entity type. Experimental results on the Chinese Web achieve weighted average Fscores of 0.7122 and 0.7123 on two global attribute schemas for person-type and movie-type web entities, respectively. These results show that our framework is general, efficient and effective
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