A Data Middleware for Obtaining Trusted Price Data for Blockchain

As a trusted middleware connecting the blockchain and the real world, the blockchain oracle can obtain trusted real-time price information for financial applications such as payment and settlement, and asset valuation on the blockchain. However, the current oracle schemes face the dilemma of security and service quality in the process of node selection, and the implicit interest relationship in financial applications leads to a significant conflict of interest between the task publisher and the executor, which reduces the participation enthusiasm of both parties and system security. Therefore, this paper proposes an anonymous node selection scheme that anonymously selects nodes with high reputations to participate in tasks to ensure the security and service quality of nodes. Then, this paper also details the interest requirements and behavioral motives of all parties in the payment settlement and asset valuation scenarios. Under the assumption of rational participants, an incentive mechanism based on the Stackelberg game is proposed. It can achieve equilibrium under the pursuit of the interests of task publishers and executors, thereby ensuring the interests of all types of users and improving the enthusiasm of participation. Finally, we verify the security of the proposed scheme through security analysis. The experimental results show that the proposed scheme can reduce the variance of obtaining price data by about 55\% while ensuring security, and meeting the interests of all parties.Comment: 12 pages,8 figure

Spatiotemporal Evolution of Land Subsidence in the Beijing Plain 2003–2015 Using Persistent Scatterer Interferometry (PSI) with Multi-Source SAR Data

Land subsidence is one of the most important geological hazards in Beijing, China, and its scope and magnitude have been growing rapidly over the past few decades, mainly due to long-term groundwater withdrawal. Interferometric Synthetic Aperture Radar (InSAR) has been used to monitor the deformation in Beijing, but there is a lack of analysis of the long-term spatiotemporal evolution of land subsidence. This study focused on detecting and characterizing spatiotemporal changes in subsidence in the Beijing Plain by using Persistent Scatterer Interferometry (PSI) and geographic spatial analysis. Land subsidence during 2003–2015 was monitored by using ENVISAT ASAR (2003–2010), RADARSAT-2 (2011–2015) and TerraSAR-X (2010–2015) images, with results that are consistent with independent leveling measurements. The radar-based deformation velocity ranged from −136.9 to +15.2 mm/year during 2003–2010, and −149.4 to +8.9 mm/year during 2011–2015 relative to the reference point. The main subsidence areas include Chaoyang, Tongzhou, Shunyi and Changping districts, where seven subsidence bowls were observed between 2003 and 2015. Equal Fan Analysis Method (EFAM) shows that the maximum extensive direction was eastward, with a growing speed of 11.30 km2/year. Areas of differential subsidence were mostly located at the boundaries of the seven subsidence bowls, as indicated by the subsidence rate slope. Notably, the area of greatest subsidence was generally consistent with the patterns of groundwater decline in the Beijing Plain

Social spammer detection: A multi-relational embedding approach

© Springer International Publishing AG, part of Springer Nature 2018. Since the relation is the main data shape of social networks, social spammer detection desperately needs a relation-dependent but content-independent framework. Some recent detection method transforms the social relations into a set of topological features, such as degree, k-core, etc. However, the multiple heterogeneous relations and the direction within each relation have not been fully explored for identifying social spammers. In this paper, we make an attempt to adopt the Multi-Relational Embedding (MRE) approach for learning latent features of the social network. The MRE model is able to fuse multiple kinds of different relations and also learn two latent vectors for each relation indicating both sending role and receiving role of every user, respectively. Experimental results on a real-world multi-relational social network demonstrate the latent features extracted by our MRE model can improve the detection performance remarkably

Towards Label-free Scene Understanding by Vision Foundation Models

Vision foundation models such as Contrastive Vision-Language Pre-training (CLIP) and Segment Anything (SAM) have demonstrated impressive zero-shot performance on image classification and segmentation tasks. However, the incorporation of CLIP and SAM for label-free scene understanding has yet to be explored. In this paper, we investigate the potential of vision foundation models in enabling networks to comprehend 2D and 3D worlds without labelled data. The primary challenge lies in effectively supervising networks under extremely noisy pseudo labels, which are generated by CLIP and further exacerbated during the propagation from the 2D to the 3D domain. To tackle these challenges, we propose a novel Cross-modality Noisy Supervision (CNS) method that leverages the strengths of CLIP and SAM to supervise 2D and 3D networks simultaneously. In particular, we introduce a prediction consistency regularization to co-train 2D and 3D networks, then further impose the networks' latent space consistency using the SAM's robust feature representation. Experiments conducted on diverse indoor and outdoor datasets demonstrate the superior performance of our method in understanding 2D and 3D open environments. Our 2D and 3D network achieves label-free semantic segmentation with 28.4% and 33.5% mIoU on ScanNet, improving 4.7% and 7.9%, respectively. And for nuScenes dataset, our performance is 26.8% with an improvement of 6%. Code will be released (https://github.com/runnanchen/Label-Free-Scene-Understanding)

CLIP2Scene: Towards Label-efficient 3D Scene Understanding by CLIP

Contrastive Language-Image Pre-training (CLIP) achieves promising results in 2D zero-shot and few-shot learning. Despite the impressive performance in 2D, applying CLIP to help the learning in 3D scene understanding has yet to be explored. In this paper, we make the first attempt to investigate how CLIP knowledge benefits 3D scene understanding. We propose CLIP2Scene, a simple yet effective framework that transfers CLIP knowledge from 2D image-text pre-trained models to a 3D point cloud network. We show that the pre-trained 3D network yields impressive performance on various downstream tasks, i.e., annotation-free and fine-tuning with labelled data for semantic segmentation. Specifically, built upon CLIP, we design a Semantic-driven Cross-modal Contrastive Learning framework that pre-trains a 3D network via semantic and spatial-temporal consistency regularization. For the former, we first leverage CLIP's text semantics to select the positive and negative point samples and then employ the contrastive loss to train the 3D network. In terms of the latter, we force the consistency between the temporally coherent point cloud features and their corresponding image features. We conduct experiments on SemanticKITTI, nuScenes, and ScanNet. For the first time, our pre-trained network achieves annotation-free 3D semantic segmentation with 20.8% and 25.08% mIoU on nuScenes and ScanNet, respectively. When fine-tuned with 1% or 100% labelled data, our method significantly outperforms other self-supervised methods, with improvements of 8% and 1% mIoU, respectively. Furthermore, we demonstrate the generalizability for handling cross-domain datasets. Code is publicly available https://github.com/runnanchen/CLIP2Scene.Comment: CVPR 202

Posterior Circulation Mechanical Thrombectomy through Primitive Trigeminal Artery: A Case Report

Introduction: Primitive trigeminal artery (PTA) is a rare intracranial vascular malformation, and mechanical thrombectomy and revascularization via PTA are rarely reported. Case Presentation: We reported a case of mechanical thrombectomy through PTA in a patient who presented with sudden slurred speech and had a National Institutes of Health Stroke Scale score of 12. Digital subtraction angiography of the cerebral vasculature showed PTA formation in the right internal carotid artery cavernous segment, with acute occlusion of the distal basilar artery at the PTA junction, and bilateral vertebral arteries and proximal basilar artery were underdeveloped. Therefore, we chose mechanical thrombectomy via PTA, but unfortunately, the vessel failed to recanalize. Follow-up at 1-month post-procedure indicated that the patient had passed away. We present the endovascular process and analyze and summarize the reasons for the failure to provide a reference for subsequent mechanical thrombectomy via PTA. Conclusions: PTA increases the risk of ischemic stroke and adds to the complexity of mechanical thrombectomy post-stroke. However, in certain situations, PTA can be used as a thrombectomy channel to increase the first-line possibility of timely endovascular treatment to save ischemic brain tissue

Wafer-scale heterogeneous integration InP on trenched Si with a bubble-free interface

Heterogeneous integration of compound semiconductors on a Si platform leads to advanced device applications in the field of Si photonics and high frequency electronics. However, the unavoidable bubbles formed at the bonding interface are detrimental for achieving a high yield of dissimilar semiconductor integration by the direct wafer bonding technology. In this work, lateral outgassing surface trenches (LOTs) are introduced to efficiently inhibit the bubbles. It is found that the chemical reactions in InP-Si bonding are similar to those in Si-Si bonding, and the generated gas can escape via the LOTs. The outgassing efficiency is dominated by LOTs\u27 spacing, and moreover, the relationship between bubble formation and the LOT\u27s structure is well described by a thermodynamic model. With the method explored in this work, a 2-in. bubble-free crystalline InP thin film integrated on the Si substrate with LOTs is obtained by the ion-slicing and wafer bonding technology. The quantum well active region grown on this Si-based InP film shows a superior photoemission efficiency, and it is found to be 65% as compared to its bulk counterpart

Susceptibilities of Yersinia pestis to Twelve Antimicrobial Agents in China

Streptomycin is the preferred choice for therapy of plague in China and other countries. However, Yersinia pestis exhibiting plasmid-mediated antimicrobial agent–resistant traits had been reported in Madagascar. In this study, we evaluated the susceptibility of traditional or newer antimicrobial agents used for treatment and/or prophylaxis of plague. Following Clinical and Laboratory Standards Institute (CLSI) recommendations, the susceptibility of 12 antimicrobial agents was evaluated by the agar microdilution method in 1,012 strains of Y. pestis isolated from 1943 to 2017 in 12 natural plague foci in China. One clinical Y. pestis isolate (S19960127) was found to be highly resistant to streptomycin, while the strain was still sensitive to other 11 antibiotics, that is, ciprofloxacin, ofloxacin, kanamycin, chloramphenicol, ampicillin, ceftriaxone, cefuroxime, trimethoprim-sulfamethoxazole, tetracycline, spectinomycin and moxifloxacin. The remaining 1,011 Y. pestis strains in this study demonstrated susceptibility to the above-mentioned 12 antimicrobial agents. Antimicrobial sensitivity surveillance of Y. pestis isolates, including dynamic monitoring of streptomycin resistance during various clinical plague treatments, should be carried out routinely

Histopathological Observation of Immunized Rhesus Macaques with Plague Vaccines after Subcutaneous Infection of Yersinia pestis

In our previous study, complete protection was observed in Chinese-origin rhesus macaques immunized with SV1 (20 µg F1 and 10 µg rV270) and SV2 (200 µg F1 and 100 µg rV270) subunit vaccines and with EV76 live attenuated vaccine against subcutaneous challenge with 6×106 CFU of Y. pestis. In the present study, we investigated whether the vaccines can effectively protect immunized animals from any pathologic changes using histological and immunohistochemical techniques. In addition, the glomerular basement membranes (GBMs) of the immunized animals and control animals were checked by electron microscopy. The results show no signs of histopathological lesions in the lungs, livers, kidneys, lymph nodes, spleens and hearts of the immunized animals at Day 14 after the challenge, whereas pathological alterations were seen in the corresponding tissues of the control animals. Giemsa staining, ultrastructural examination, and immunohistochemical staining revealed bacteria in some of the organs of the control animals, whereas no bacterium was observed among the immunized animals. Ultrastructural observation revealed that no glomerular immune deposits on the GBM. These observations suggest that the vaccines can effectively protect animals from any pathologic changes and eliminate Y. pestis from the immunized animals. The control animals died from multi-organ lesions specifically caused by the Y. pestis infection. We also found that subcutaneous infection of animals with Y. pestis results in bubonic plague, followed by pneumonic and septicemic plagues. The histopathologic features of plague in rhesus macaques closely resemble those of rodent and human plagues. Thus, Chinese-origin rhesus macaques serve as useful models in studying Y. pestis pathogenesis, host response and the efficacy of new medical countermeasures against plague

Molecular Evidence of Bartonella melophagi in Ticks in Border Areas of Xinjiang, China

Bartonella are gram-negative intracellular bacteria; certain species of Bartonella can cause diseases in mammals and humans. Ticks play a major role in the transmission of Bartonella. Xinjiang is the largest province in China according to land area and has one-third of the tick species in China; the infection rate of Bartonella in ticks in the Xinjiang border areas has not been studied in detail. Therefore, this study investigated tick infections by Bartonella in Xinjiang border areas, and the purpose of the study was to fill in gaps in information regarding the genetic diversity of tick infections by Bartonella in Xinjiang. We tested 1,549 tick samples from domestic animals (sheep and cattle) for Bartonella using ribC-PCR. Positive samples from the ribC-PCR assay for Bartonella spp. were further subjected to PCR assays targeting the ITS, rpoB and gltA genes followed by phylogenetic analyses. Bartonella DNA was detected in 2.19% (34/1,549) of tick samples, and the ITS, rpoB and gltA genes of ribC gene-positive samples were amplified to identify nine samples of Bartonella melophagi. In this study, molecular analysis was used to assess the presence and genetic diversity of B. melophagi in ticks collected from sheep and cattle from Xinjiang, China. This study provides new information on the presence and identity of B. melophagi in ticks from sheep and cattle