Identity-Based Cryptography for Cloud Security

Cloud computing is a style of computing in which dynamically scalable and commonly virtualized resources are provided as a service over the Internet. This paper, first presents a novel Hierarchical Architecture for Cloud Computing (HACC). Then, Identity-Based Encryption (IBE) and Identity-Based Signature (IBS) for HACC are proposed. Finally, an Authentication Protocol for Cloud Computing (APCC) is presented. Performance analysis indicates that APCC is more efficient and lightweight than SSL Authentication Protocol (SAP), especially for the user side. This aligns well with the idea of cloud computing to allow the users with a platform of limited performance to outsource their computational tasks to more powerful servers

ActionPrompt: Action-Guided 3D Human Pose Estimation With Text and Pose Prompting

Recent 2D-to-3D human pose estimation (HPE) utilizes temporal consistency across sequences to alleviate the depth ambiguity problem but ignore the action related prior knowledge hidden in the pose sequence. In this paper, we propose a plug-and-play module named Action Prompt Module (APM) that effectively mines different kinds of action clues for 3D HPE. The highlight is that, the mining scheme of APM can be widely adapted to different frameworks and bring consistent benefits. Specifically, we first present a novel Action-related Text Prompt module (ATP) that directly embeds action labels and transfers the rich language information in the label to the pose sequence. Besides, we further introduce Action-specific Pose Prompt module (APP) to mine the position-aware pose pattern of each action, and exploit the correlation between the mined patterns and input pose sequence for further pose refinement. Experiments show that APM can improve the performance of most video-based 2D-to-3D HPE frameworks by a large margin.Comment: 6 pages, 4 figures, 2023ICM

FlowFormer: A Transformer Architecture and Its Masked Cost Volume Autoencoding for Optical Flow

This paper introduces a novel transformer-based network architecture, FlowFormer, along with the Masked Cost Volume AutoEncoding (MCVA) for pretraining it to tackle the problem of optical flow estimation. FlowFormer tokenizes the 4D cost-volume built from the source-target image pair and iteratively refines flow estimation with a cost-volume encoder-decoder architecture. The cost-volume encoder derives a cost memory with alternate-group transformer~(AGT) layers in a latent space and the decoder recurrently decodes flow from the cost memory with dynamic positional cost queries. On the Sintel benchmark, FlowFormer architecture achieves 1.16 and 2.09 average end-point-error~(AEPE) on the clean and final pass, a 16.5\% and 15.5\% error reduction from the GMA~(1.388 and 2.47). MCVA enhances FlowFormer by pretraining the cost-volume encoder with a masked autoencoding scheme, which further unleashes the capability of FlowFormer with unlabeled data. This is especially critical in optical flow estimation because ground truth flows are more expensive to acquire than labels in other vision tasks. MCVA improves FlowFormer all-sided and FlowFormer+MCVA ranks 1st among all published methods on both Sintel and KITTI-2015 benchmarks and achieves the best generalization performance. Specifically, FlowFormer+MCVA achieves 1.07 and 1.94 AEPE on the Sintel benchmark, leading to 7.76\% and 7.18\% error reductions from FlowFormer.Comment: arXiv admin note: substantial text overlap with arXiv:2203.16194, arXiv:2303.0123

Research on Assessment Methods for Urban Public Transport Development in China

In recent years, with the rapid increase in urban population, the urban travel demands in Chinese cities have been increasing dramatically. As a result, developing comprehensive urban transport systems becomes an inevitable choice to meet the growing urban travel demands. In urban transport systems, public transport plays the leading role to promote sustainable urban development. This paper aims to establish an assessment index system for the development level of urban public transport consisting of a target layer, a criterion layer, and an index layer. Review on existing literature shows that methods used in evaluating urban public transport structure are dominantly qualitative. To overcome this shortcoming, fuzzy mathematics method is used for describing qualitative issues quantitatively, and AHP (analytic hierarchy process) is used to quantify expert’s subjective judgment. The assessment model is established based on the fuzzy AHP. The weight of each index is determined through the AHP and the degree of membership of each index through the fuzzy assessment method to obtain the fuzzy synthetic assessment matrix. Finally, a case study is conducted to verify the rationality and practicability of the assessment system and the proposed assessment method

Pose-Oriented Transformer with Uncertainty-Guided Refinement for 2D-to-3D Human Pose Estimation

There has been a recent surge of interest in introducing transformers to 3D human pose estimation (HPE) due to their powerful capabilities in modeling long-term dependencies. However, existing transformer-based methods treat body joints as equally important inputs and ignore the prior knowledge of human skeleton topology in the self-attention mechanism. To tackle this issue, in this paper, we propose a Pose-Oriented Transformer (POT) with uncertainty guided refinement for 3D HPE. Specifically, we first develop novel pose-oriented self-attention mechanism and distance-related position embedding for POT to explicitly exploit the human skeleton topology. The pose-oriented self-attention mechanism explicitly models the topological interactions between body joints, whereas the distance-related position embedding encodes the distance of joints to the root joint to distinguish groups of joints with different difficulties in regression. Furthermore, we present an Uncertainty-Guided Refinement Network (UGRN) to refine pose predictions from POT, especially for the difficult joints, by considering the estimated uncertainty of each joint with uncertainty-guided sampling strategy and self-attention mechanism. Extensive experiments demonstrate that our method significantly outperforms the state-of-the-art methods with reduced model parameters on 3D HPE benchmarks such as Human3.6M and MPI-INF-3DHPComment: accepted by AAAI202

VideoFlow: Exploiting Temporal Cues for Multi-frame Optical Flow Estimation

We introduce VideoFlow, a novel optical flow estimation framework for videos. In contrast to previous methods that learn to estimate optical flow from two frames, VideoFlow concurrently estimates bi-directional optical flows for multiple frames that are available in videos by sufficiently exploiting temporal cues. We first propose a TRi-frame Optical Flow (TROF) module that estimates bi-directional optical flows for the center frame in a three-frame manner. The information of the frame triplet is iteratively fused onto the center frame. To extend TROF for handling more frames, we further propose a MOtion Propagation (MOP) module that bridges multiple TROFs and propagates motion features between adjacent TROFs. With the iterative flow estimation refinement, the information fused in individual TROFs can be propagated into the whole sequence via MOP. By effectively exploiting video information, VideoFlow presents extraordinary performance, ranking 1st on all public benchmarks. On the Sintel benchmark, VideoFlow achieves 1.649 and 0.991 average end-point-error (AEPE) on the final and clean passes, a 15.1% and 7.6% error reduction from the best-published results (1.943 and 1.073 from FlowFormer++). On the KITTI-2015 benchmark, VideoFlow achieves an F1-all error of 3.65%, a 19.2% error reduction from the best-published result (4.52% from FlowFormer++). Code is released at \url{https://github.com/XiaoyuShi97/VideoFlow}

Exosomes from embryonic mesenchymal stem cells alleviate osteoarthritis through balancing synthesis and degradation of cartilage extracellular matrix

Abstract Background Mesenchymal stem cell therapy for osteoarthritis (OA) has been widely investigated, but the mechanisms are still unclear. Exosomes that serve as carriers of genetic information have been implicated in many diseases and are known to participate in many physiological processes. Here, we investigate the therapeutic potential of exosomes from human embryonic stem cell-induced mesenchymal stem cells (ESC-MSCs) in alleviating osteoarthritis (OA). Methods Exosomes were harvested from conditioned culture media of ESC-MSCs by a sequential centrifugation process. Primary mouse chondrocytes treated with interleukin 1 beta (IL-1β) were used as an in vitro model to evaluate the effects of the conditioned medium with or without exosomes and titrated doses of isolated exosomes for 48 hours, prior to immunocytochemistry or western blot analysis. Destabilization of the medial meniscus (DMM) surgery was performed on the knee joints of C57BL/6 J mice as an OA model. This was followed by intra-articular injection of either ESC-MSCs or their exosomes. Cartilage destruction and matrix degradation were evaluated with histological staining and OARSI scores at the post-surgery 8 weeks. Results We found that intra-articular injection of ESC-MSCs alleviated cartilage destruction and matrix degradation in the DMM model. Further in vitro studies illustrated that this effect was exerted through ESC-MSC-derived exosomes. These exosomes maintained the chondrocyte phenotype by increasing collagen type II synthesis and decreasing ADAMTS5 expression in the presence of IL-1β. Immunocytochemistry revealed colocalization of the exosomes and collagen type II-positive chondrocytes. Subsequent intra-articular injection of exosomes derived from ESC-MSCs successfully impeded cartilage destruction in the DMM model. Conclusions The exosomes from ESC-MSCs exert a beneficial therapeutic effect on OA by balancing the synthesis and degradation of chondrocyte extracellular matrix (ECM), which in turn provides a new target for OA drug and drug-delivery system development

Network-Coded Relaying in Multiuser Multicast D2D Network

D2D communication trades short-range communication for achieving high communication rate and short communication latency. Relay aided D2D communication can further tackle the problem of intermediate obstacles blocking the communication. In this work, multidevice multicast communication via a layer of parallel relay nodes is considered. Two relaying strategies, respectively, called the conventional relaying (CR) and network-coded relaying (NCR), are proposed. The throughput of these two schemes is analytically derived and evaluated through numerical study. Theoretically, NCR shows advantage over CR in twofold: one is higher throughput and the other is requiring less relay nodes and, hence, consuming less aggregate power. Numerical studies verify the analysis and show that the throughput performance gap between the two schemes increases significantly, actually exponentially with the number of devices

Effect of Ermiao Fang with Xixin (Herba Asari Mandshurici) on bone marrow stem cell directional homing to a focal zone in an osteoarthritis rat model

AbstractObjectiveTo investigate the effects of Ermiao Fang (EM) with medical guide Xixin (Herba Asari Mandshurici) (HAM) on bone marrow stem cell migration to a focal zone in osteoarthritis (OA) rats.MethodsOA rats were induced by arthrectomy and assigned to sham-operated, model, EM, or EM plus HAM groups. All rats were injected with recombinant human granulocyte colony-stimulating factor 30 μg • kg−1 • d−1 for 7 days and treated with EM or EM plus HAM at 1.6 or 1.9 g • kg−1 • d−1 for 3 or 6 weeks, respectively. Chondrocyte apoptosis and cartilage matrix components were tested by transferase-mediated deoxyuridine triphosphate-biotin nick end labeling assay and special staining. Levels of interleukin-1 beta (IL-1β) tumor necrosis factor alpha (TNF-α) nitric oxide (NO), and inducible nitric oxide synthase (iNOS) in serum were detected by enzyme-linked immunosorbent assay or radioimmunoassay. Matrix metalloproteinases (MMPs)-13, tissue inhibitors of metalloproteinases (TIMPs)-1, Bromodeoxyuridine (BrdU), cluster of differentiation 34 (CD34), and stromal cell-derived factor 1 (SDF-1) were measured by immunohistochemical assay.ResultsThe EM and EM plus HAM groups had significantly less cartilage damage and synovium inflammation the model group. Moreover, the EM and EM plus HAM groups had less chondrocyte apoptosis and more proteoglycan and collagen content than the model group. The EM and EM plus HAM groups had obviously higher MMPs-13 and TIMPs-1 expression in the cartilage than the model group. Moreover, the two formula groups had less release of IL-1β, TNF-α, NO, and iNOS than model group. Importantly, the expressions of BrdU, CD34, and SDF-1 in cartilage were significantly higher in the EM and EM plus HAM-Medtreated rats than model group. Notably, the EM plus HAM treatment seemed to have the greatest effects.ConclusionsHAM improves the therapeutic effects of EM on OA rats by enhancing BMSC directional homing to the focal zone