Geodynamic Development of the South China Block from Precambrian to Cretaceous: Constraints from Geology Geochemistry and Geochronology

The geo-tectonic evolution of the South China block is subject to debate. Most articles tend to subdivide the South China block into two sub-ordinate blocks (Yangtze and Cathaysia), with a central Sibao (Jiangnan) Orogen, although there are also suggestions for a separate eastern (Tolo) block. Debate primarily occurs around the timing of amalgamation of the Yangtze and Cathaysia blocks and the processes causing various episodes of magmatism. Some publications indicate that the South China block amalgamated between 800 and 900 Ma, but others propose amalgamation between 400 and 500 Ma. A recent paper suggests that the eastern portion of Cathaysia only collided with Cathaysia in the Jurassic. In this project, we bring together multiple data sets to develop a more constrained plate tectonic model for the South China block between ~1000 Ma and ~100 Ma. Compiled data include: zircon geochronology data, whole rock Lu-Hf isotope data, whole rock Sm-Nd and Rb-Sr isotopes data, rock major and trace element data. Geochronology data concentrate on U-Pb zircon and monazite data for the crystallisation ages of igneous rocks and near-peak metamorphism although lower-temperature closure ages have also been compiled where included in papers on crystallisation and metamorphism. Detrital zircon U-Pb data have also been compiled to aid in understanding changing sources of sediments through time to further constrain potential geodynamic processes. Lithochemistry data are used to infer geodynamic setting for igneous activity or for protolith formation. Together, these various data permit one to distinguish between upper and lower plate settings and to identify rifted environments. Precise location information is captured where available or approximated from published diagrams, correlated with available geological GIS maps. U-Pb and Sm-Nd isotope data for rocks formed between 900 and 800 Ma demonstrate primarily juvenile sources whereas the 400 to 500 Ma igneous activity reworked substantially older crust. Detrital zircon data show that the grains from South China block are primarily self-sourced. The combined data thus support models inferring collision of Cathaysia with Yangtze between 900 and 800 Ma and later SCB collide with potentially Australia at ~400 Ma

A Source-Initiated On-Demand Routing Algorithm Based on the Thorup-Zwick Theory for Mobile Wireless Sensor Networks

The unreliability and dynamics of mobile wireless sensor networks make it hard to perform end-to-end communications. This paper presents a novel source-initiated on-demand routing mechanism for efficient data transmission in mobile wireless sensor networks. It explores the Thorup-Zwick theory to achieve source-initiated on-demand routing with time efficiency. It is able to find out shortest routing path between source and target in a network and transfer data in linear time. The algorithm is easy to be implemented and performed in resource-constrained mobile wireless sensor networks. We also evaluate the approach by analyzing its cost in detail. It can be seen that the approach is efficient to support data transmission in mobile wireless sensor networks

Electronic Word-of-Mouth for E-Commerce Consumption in Mobile Social Network: a Case Study from WeChat

With the population of social networking services (SNS) like WeChat, they have emerged as an increasingly important media or platform that facilitates product-focused electronic word-of-mouth (eWOM) activities. Meanwhile, e-commerce has become an essential part of our daily life. The goal of the current research is to discover the key factors that affect consumers’ willingness to engage in eWOM behaviors on mobile social media like WeChat. We mainly investigate eight factors including personal factors, WeChat usage, social communication, e-commerce participation, consumer online perceptions, perceived risk, platform factors, and product factors, which may encourage or restrain consumers to spread eWOM on WeChat. We have constructed a theoretic model and proposed a series of hypotheses. In order to verify the model as well as the hypotheses, we have carried out a questionnaire survey. Moreover, we use SPSS 20 software to analyze the results of the survey. We try to find out the significant factors that affect eWOM most on WeChat. According to the result, social communications and consumer online perceptions have shown strong influence on eWOM. Finally we make a discussion on the results, which could be used to support the marketing or sales activities of potential enterprises

RPEFlow: Multimodal Fusion of RGB-PointCloud-Event for Joint Optical Flow and Scene Flow Estimation

Recently, the RGB images and point clouds fusion methods have been proposed to jointly estimate 2D optical flow and 3D scene flow. However, as both conventional RGB cameras and LiDAR sensors adopt a frame-based data acquisition mechanism, their performance is limited by the fixed low sampling rates, especially in highly-dynamic scenes. By contrast, the event camera can asynchronously capture the intensity changes with a very high temporal resolution, providing complementary dynamic information of the observed scenes. In this paper, we incorporate RGB images, Point clouds and Events for joint optical flow and scene flow estimation with our proposed multi-stage multimodal fusion model, RPEFlow. First, we present an attention fusion module with a cross-attention mechanism to implicitly explore the internal cross-modal correlation for 2D and 3D branches, respectively. Second, we introduce a mutual information regularization term to explicitly model the complementary information of three modalities for effective multimodal feature learning. We also contribute a new synthetic dataset to advocate further research. Experiments on both synthetic and real datasets show that our model outperforms the existing state-of-the-art by a wide margin. Code and dataset is available at https://npucvr.github.io/RPEFlow.Comment: ICCV 2023. Project page: https://npucvr.github.io/RPEFlow Code: https://github.com/danqu130/RPEFlo

Mutual Information Regularization for Weakly-supervised RGB-D Salient Object Detection

In this paper, we present a weakly-supervised RGB-D salient object detection model via scribble supervision. Specifically, as a multimodal learning task, we focus on effective multimodal representation learning via inter-modal mutual information regularization. In particular, following the principle of disentangled representation learning, we introduce a mutual information upper bound with a mutual information minimization regularizer to encourage the disentangled representation of each modality for salient object detection. Based on our multimodal representation learning framework, we introduce an asymmetric feature extractor for our multimodal data, which is proven more effective than the conventional symmetric backbone setting. We also introduce multimodal variational auto-encoder as stochastic prediction refinement techniques, which takes pseudo labels from the first training stage as supervision and generates refined prediction. Experimental results on benchmark RGB-D salient object detection datasets verify both effectiveness of our explicit multimodal disentangled representation learning method and the stochastic prediction refinement strategy, achieving comparable performance with the state-of-the-art fully supervised models. Our code and data are available at: https://github.com/baneitixiaomai/MIRV.Comment: IEEE Transactions on Circuits and Systems for Video Technology 202

Decomposed Guided Dynamic Filters for Efficient RGB-Guided Depth Completion

RGB-guided depth completion aims at predicting dense depth maps from sparse depth measurements and corresponding RGB images, where how to effectively and efficiently exploit the multi-modal information is a key issue. Guided dynamic filters, which generate spatially-variant depth-wise separable convolutional filters from RGB features to guide depth features, have been proven to be effective in this task. However, the dynamically generated filters require massive model parameters, computational costs and memory footprints when the number of feature channels is large. In this paper, we propose to decompose the guided dynamic filters into a spatially-shared component multiplied by content-adaptive adaptors at each spatial location. Based on the proposed idea, we introduce two decomposition schemes A and B, which decompose the filters by splitting the filter structure and using spatial-wise attention, respectively. The decomposed filters not only maintain the favorable properties of guided dynamic filters as being content-dependent and spatially-variant, but also reduce model parameters and hardware costs, as the learned adaptors are decoupled with the number of feature channels. Extensive experimental results demonstrate that the methods using our schemes outperform state-of-the-art methods on the KITTI dataset, and rank 1st and 2nd on the KITTI benchmark at the time of submission. Meanwhile, they also achieve comparable performance on the NYUv2 dataset. In addition, our proposed methods are general and could be employed as plug-and-play feature fusion blocks in other multi-modal fusion tasks such as RGB-D salient object detection

Clinical Retrospective Study of Pterygomaxillary Implant Combined with Anterior Implant in the Repair of Atrophic Edentulous Maxilla

Objective: To retrospectively analyze the therapeutic effect of pterygomaxillary implant combined with anterior implant in the repair of atrophic maxillary edentulous jaw. Methods: The clinical data of 26 patients with atrophic edentulous maxilla who received pterygomaxillary implants combined with anterior implants from January 2019 to December 2020 were analyzed retrospectively. All patients were followed up for ≥ 1 year. The retention of anterior implants (105) and pterygomaxillary implants (45) were compared Patients' satisfaction with deep and middle periodontal examination (MBPD) and plaque (PLI). Results: The anterior implant retention rate was 97.14%, which was close to 93.33% in pterygomaxillary area (P > 0.05);The levels of PD, PLI, mesial MBL and distal MBL of anterior implants were similar to those of pterygomaxillary implants (P > 0.05); Patients' satisfaction with treatment was 92.31%. Conclusion: In the treatment of patients with posterior atrophic edentulous maxilla, the pterygomaxillary implant and the anterior implant supported complete arch fixed denture can bear the weight immediately, the short-term clinical effect is acceptable, and the patient satisfaction is high. It is a predictable and feasible repair method