Bitcoin Network Measurement and a New Approach to Infer the Topology

Bitcoin has made an increasing impact on the world's economy and financial order,which attracted extensive attention of researchers and regulators from all over the world.Most previous studies had focused more on the transaction layer,but less on the network layer.In this paper,we developed BNS(Bitcoin Network Sniffer),which could find and connect nodes in the Bitcoin network,and made a measurement in detail.We collected nearly 4.1 million nodes in 1.5 hours and identified 9,515 reachable nodes.We counted the reachable nodes'properties such as:service type,port number,client version and geographic distribution.In addition,we analyzed the stability of the reachable nodes in depth and found nearly 60%kept stable during 15 days.Finally,we proposed a new approach to infer the Bitcoin network topology by analyzing the Neighbor Addresses of Adjacent Nodes and their timestamps,which had an accuracy over 80%.

Robotic single-incision left hemihepatectomy for intrahepatic bile duct stones by Da Vinci single-site surgical system: A case report with video

Minimally invasive surgery is a trend in hepatobiliary surgery.A 56-year-old female patient was admitted to our institution for intrahepatic lithiasis.The CT scan showed multiple calculi in the left liver,dilation of the left intrahepatic bile duct and liver atrophy of the left lobe.Robotic single-incision left hemihepatectomy by the single-site systemwas successfully applied.With the idea of enhanced recovery after surgery,the patient was discharged on the third day after the operation without any morbidity.Robotic single-incision surgery is more frequent in gynecologic and urological surgery.As far as we know,this is the first robotic single-incision left hemihepatectomy report in the world.

CO2 emission driving forces and corresponding mitigation strategies under low-carbon economy mode:evidence from China's Beijing-Tianjin-Hebei region

On account of the background of China's "new normal" characterized by slower economic growth, this paper analyses the low-carbon economy status quo in the Beijing-Tianjin-Hebei region and empirically investigates the relationship between carbon dioxide(CO_2) emissions and its various factors for China's Beijing-Tianjin-Hebei region using panel data econometric technique. We find evidence of existence of Environmental Kuznets Curve. Results also show that economic scale, industrial structure, and urbanization rate are crucial factors to promote CO_2emissions. However, technological progress, especially the domestic independent research and development, plays a key role in C0_2 emissions abatement. Next, we further analyze the correlation between each subregion and various factors according to Grey Relation Analysis. Thereby,our findings provide important implications for policymakers in air pollution control and C0_2 emissions reduction for this region.

BUES: A Blockchain-Based Upgraded Email System

This paper focuses on the improvement of traditional email system architecture with the help of blockchain technology in the existing network environment. The improved system architecture can better improve the security and stability of the system. The email content is extracted and stored in the blockchain network to achieve regulatory traceability between the email service provider and the higher-level organization. In turn, A Blockchain-based Upgraded Email System(BUES) is proposed. The defects of the existing traditional email system are addressed. Firstly, the threat model of the traditional email system is analyzed, and solutions are proposed for various threats. Then a system architecture consisting of the blockchain network, email servers, and users are constructed. The implementation of BUES is carried out, and the related experimental process and algorithm steps are given. After the experimental analysis, it is shown that BUES can ensure the security, reliability, efficiency, and traceability of email transmission.

Construction of multi-homojunction TiO_(2)nanotubes for boosting photocatalytic hydrogen evolution by steering photogenerated charge transfer

As an effective means to improve charge carrier separation efficiency and directional transport,the gradient doping of foreign elements to build multi-homojunction structures inside catalysts has received wide attentions.Herein,we reported a simple and robust method to construct multi-homojunctions in black TiO_(2) nanotubes by the gradient doping of Ni species through the diffusion of deposited Ni element on the top of black TiO2 nanotubes driven by a high temperature annealing process.The gradient Ni distribution created parts of different Fermi energy levels and energy band structures within the same black TiO_(2) nanotube,which subsequently formed two series of multi-homojunctions within it.This special multi-homojunction structure largely enhanced the charge carrier separation and transportation,while the low concentration of defect states near the surface layer further inhibited carrier recombination and facilitated the surface reaction.Thus,the B-TNT-2Ni sample with the optimized Ni doping concentration exhibited an enhanced hydrogen evolution rate of~1.84 mmol·g^(−1)·h^(−1)under visible light irradiation without the assistance of noble-metal cocatalysts,~four times higher than that of the pristine black TiO_(2)nanotube array.With the capability to create multi-homojunction structures,this approach could be readily applied to various dopant systems and catalyst materials for a broad range of technical applications.

Forget less,count better:a domain-incremental self-distillation learning benchmark for lifelong crowd counting

Crowd counting has important applications in public safety and pandemic control.A robust and practical crowd counting system has to be capable of continuously learning with the newly incoming domain data in real-world scenarios instead of fitting one domain only.Off-the-shelf methods have some drawbacks when handling multiple domains:(1)the models will achieve limited performance(even drop dramatically)among old domains after training images from new domains due to the discrepancies in intrinsic data distributions from various domains,which is called catastrophic forgetting;(2)the well-trained model in a specific domain achieves imperfect performance among other unseen domains because of domain shift;(3)it leads to linearly increasing storage overhead,either mixing all the data for training or simply training dozens of separate models for different domains when new ones are available.To overcome these issues,we investigate a new crowd counting task in incremental domain training setting called lifelong crowd counting.Its goal is to alleviate catastrophic forgetting and improve the generalization ability using a single model updated by the incremental domains.Specifically,we propose a self-distillation learning framework as a benchmark(forget less,count better,or FLCB)for lifelong crowd counting,which helps the model leverage previous meaningful knowledge in a sustainable manner for better crowd counting to mitigate the forgetting when new data arrive.A new quantitative metric,normalized Backward Transfer(nBwT),is developed to evaluate the forgetting degree of the model in the lifelong learning process.Extensive experimental results demonstrate the superiority of our proposed benchmark in achieving a low catastrophic forgetting degree and strong generalization ability.

Efficient User Identity Linkage Based on Aligned Multimodal Features and Temporal Correlation

User identity linkage(UIL)refers to identifying user accounts belonging to the same identity across different social media platforms.Most of the current research is based on text analysis,which fails to fully explore the rich image resources generated by users,and the existing attempts touch on the multimodal domain,but still face the challenge of semantic differences between text and images.Given this,we investigate the UIL task across different social media platforms based on multimodal user-generated contents(UGCs).We innovatively introduce the efficient user identity linkage via aligned multi-modal features and temporal correlation(EUIL)approach.The method first generates captions for user-posted images with the BLIP model,alleviating the problem of missing textual information.Subsequently,we extract aligned text and image features with the CLIP model,which closely aligns the two modalities and significantly reduces the semantic gap.Accordingly,we construct a set of adapter modules to integrate the multimodal features.Furthermore,we design a temporal weight assignment mechanism to incorporate the temporal dimension of user behavior.We evaluate the proposed scheme on the real-world social dataset TWIN,and the results show that our method reaches 86.39%accuracy,which demonstrates the excellence in handling multimodal data,and provides strong algorithmic support for UIL.

Oxygen vacancy-mediated WO_(3) phase junction to steering photogenerated charge separation for enhanced water splitting

Effective charge separation and transfer is deemed to be the contributing factor to achieve high photoelectrochemical(PEC)water splitting performance on photoelectrodes.Building a phase junction structure with controllable phase transition of WO_(3) can further improve the photocatalytic performance.In this work,we realized the transition from orthorhombic to monoclinic by regulating the annealing temperatures,and constructed an orthorhombic–monoclinic WO_(3)(o-WO_(3)/m-WO_(3))phase junction.The formation of oxygen vacancies causes an imbalance of the charge distribution in the crystal structure,which changes the W–O bond length and bond angle,accelerating the phase transition.As expected,an optimum PEC activity was achieved over the o-WO_(3)/m-WO_(3) phase junction in WO_(3)-450 photoelectrode,yielding the maximum O_(2) evolution rate roughly 32 times higher than that of pure WO_(3)-250 without any sacrificial agents under visible light irradiation.The enhancement of catalytic activity is attributed to the atomically smooth interface with a highly matched lattice and robust built-in electric field around the phase junction,which leads to a less-defective and abrupt interface and provides a smooth interfacial charge separation and transfer path,leading to improved charge separation and transfer efficiency and a great enhancement in photocatalytic activity.This work strikes out on new paths in the formation of an oxygen vacancy-induced phase transition and provides new ideas for the design of catalysts.

Effects of drying methods on the structure and emulsifying capacity of egg yolk lecithin

The purpose of this study was to investigate the effects of different drying methods,including ultrasonic vacuum drying,vacuum drying,vacuum freeze-drying,hot-air drying and spray drying,on the structure and emulsifying capacity of egg yolk lecithin based on Raman spectra.The results showed that ultrasonic vacuum drying and spray drying can induce the vibration of C-N bonds in the polar O-C-C-N^(+)head skeleton of egg yolk lecithin.The shift of the peak attributed to the C-N bond from 717 cm^(−1)to 774 and 772 cm^(−1)indicated that the vibration of some C-N bonds in the O-C-C-N^(+)skeleton had transformed from gauche to trans.Ultrasonic vacuum drying exerted the most intense effect on the C-C skeleton of egg yolk lecithin,with the greatest vibration peaks at 1062 cm^(−1),1128 cm^(−1),and 1097 cm^(−1)in the Raman spectra of egg yolks.Specifically,it relieved gauche vibration and strengthened trans vibration in the C-C skeleton.Hence,the I_(gauche)/I_(trans)ratio of the egg yolk lecithin processed through ultrasonic vacuum drying decreased.Ultrasonic vacuum drying and spray drying decreased the I_(2850)/I_(2878)ratio of the vibration peak of C-H bonds in the lipid chains of egg yolk lecithin.The weakening of the symmetric stretching vibration of the C-H bond and the strengthening of antisymmetric stretching vibration indicated that orderliness among the molecular chains of lipid bilayer membranes had increased,whereas liquidity had decreased.The emulsifying capacities were highly significantly different among various egg yolk lecithin samples,in which the highest emulsifying capacity(49.58 m^(2)/g)was shown for the egg yolk lecithin prepared through vacuum freeze-drying,and ultrasonic vacuum drying produced the lowest emulsifying capacity(14.77 m^(2)/g).This study demonstrated that ultrasonic vacuum drying and spray drying drastically affected the structure of egg yolk lecithin.The appropriate drying method can be selected based on sample volume and production situation.