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Copyright of Journal of Zhejiang University: Science A is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In this study, a CuO modified the MnO2 nano-hollow spheres sorbent was prepared using the impregnation method. The effects of the CuO loading amount, reaction temperature, gas hourly space velocity, and flue gas component on the Hg0 removal performance of the sorbent were investigated. When loaded with 10% CuO, the sorbent's Hg0 removal efficiency was higher than 95% from 150 to 250 °C. The combination of plentiful acid sites and superior redox behavior ensured the efficient adsorption and oxidation of Hg0, which endowed the 10% CuO-doped sorbent with a satisfactory Hg0 removal performance over a wide temperature range. Throughout the Hg0 capture cycles, the Mars–Maessen mechanism well-depicted the Hg0 removal process over the 10% Cu/Mn adsorbent, the Mn4+, Cu2+, and chemisorbed oxygen acted as the active sites with HgO being the end product. However, the weak flue gas component adaptability demonstrated that further modification is needed to enhance the practicality of this system. [ABSTRACT FROM AUTHOR]

In this study, we synthesized a Ce-modified Mn/HZSM-5 adsorbent via the ultrasound-assisted impregnation for Hg0 capture. Given the addition of 15% CeO2, ~ 100% Hg0 efficiency was reached at 200 °C, suggesting its promotional effect on Hg0 removal. The doped Ce introduced additional chemisorbed oxygen species onto the adsorbent surfaces, which facilitated the oxidation of Hg0 to HgO. Even though adding CeO2 led to a weakened adsorbent acidity, yet it appeared that this negative affect could be completely overcome by the enhanced oxidative ability, which finally endowed Ce-modified Mn/HZSM-5 with a satisfactory Hg0 removal performance within the whole investigated temperature range. During the Hg0 capture process, chemisorption was predominant with Mn4+operating as the main active site for oxidizing Hg0 to Hg2+. Finally, the 15Ce-Mn/HZSM-5 adsorbent exhibited good recyclability and stability. However, its tolerance to H2O and SO2 appeared relatively weak, suggesting that some modification should be conducted to improve its practicality. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Zhejiang University: Science A is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Relation extraction in the threat intelligence domain plays an important role in mining the internal association between crucial threat elements and constructing a knowledge graph (KG). This study designed a novel document-level relation extraction model, FEDRE-KD, integrating additional features to take full advantage of the information in documents. The study also introduced a teacher–student model, realizing knowledge distillation, to further improve performance. Additionally, a threat intelligence ontology was constructed to standardize the entities and their relationships. To solve the problem of lack of publicly available datasets for threat intelligence, manual annotation was carried out on the documents collected from social blogs, vendor bulletins, and hacking forums. After training the model, we constructed a threat intelligence knowledge graph in Neo4j. Experimental results indicate the effectiveness of additional features and knowledge distillation. Compared to mainstream models SSAN, GAIN, and ATLOP, FEDRE-KD improved the F1score by 22.07, 20.06, and 22.38, respectively. [ABSTRACT FROM AUTHOR]

With the rapid development of Cooperative Intelligent Transportation System (C-ITS), it becomes an urgent problem to effectively evaluate the data transmission efficiency of code dissemination protocols with network coding in the Dedicated Transportation Sensor Network (DTSN). First, this paper builds the overall structure of DTSN to remotely monitor the railway infrastructure in the C-ITS. Second, we propose a time model of page dissemination to reduce the deviation between the predictive data of existing models and the real-world data of code dissemination. Third, a Firefly Algorithm is designed to further improve the data transmission efficiency. The algorithm makes the feasibility rules to handle constraints, and it searches the optimal page granularity to minimize the time of page dissemination through iteration. Experiments show that the simulation results are consistent with the prediction results of proposed model, and code images can be distributed quickly and efficiently in the DTSN. [ABSTRACT FROM AUTHOR]

Sanchuan ham, produced in Yunnan, China, is food with ethnic characteristics favored by consumers. However, it can contain biogenic amines such as tyramine that are harmful to health, and the synthesis mechanism of biogenic amines in Sanchuan ham is not clear. This study focuses on the regulation of biogenic amine synthesis by quorum sensing. We used high‐performance liquid chromatography to detect the content of biogenic amine in different kinds of ham and found that the content of biogenic amine in Sanchuan ham was higher than that in others. Tyramine‐producing strain isolated from Sanchuan ham was identified as Enterococcus faecium. By monitoring the growth and tyramine synthesis of Enterococcus faecium under cultured conditions, the results found that high temperature and low salt increased tyramine production by E. faecium. After seven exogenous amino acids were applied to E. faecium, only tyrosine could promote the production of tyramine in E. faecium, and tyramine could not be synthesized in E. faecium until a certain amount was reached, indicating the presence of microbial quorum sensing signal molecules in the synthesis of tyramine in E. faecium. Untargeted metabolomics analysis of the differential metabolites produced by E. faecium showed that the contents of some peptides, especially alanyl‐leucine, were significantly increased. Further experiments with synthetic alanyl‐leucine illustrated that alanyl‐leucine activated the expression of tyrosine decarboxylase (tyrDC), thereby regulating the synthesis of tyramine by E. faecium. Alanyl‐leucine acted as quorum sensing signal molecules for biogenic amine synthesis by E. faecium, which provided a theoretical basis for reducing biogenic amine accumulation in ham. It is beneficial to control the content of biogenic amines in ham in the future. [ABSTRACT FROM AUTHOR]

Aiming at the needs of edge computing for data privacy, the correctness of calculation results and the auditability of data processing, a privacy protection method for edge computing based on blockchain and federated learning was proposed, which can realize collaborative training with multiple devices at the edge of the network without a trusted environment and special hardware facilities. The blockchain was used to endow the edge computing with features such as tamper-proof and resistance to single-point-of-failure attacks, and the gradient verification and incentive mechanism were incorporated into the consensus protocol to encourage more local devices to honestly contribute computing power and data to the federated learning. For the potential privacy leakage problems caused by sharing model parameters, an adaptive differential privacy mechanism was designed to protect parameter privacy while reducing the impact of noise on the model accuracy, and moments accountant was used to accurately track the privacy loss during the training process. Experimental results show that the proposed method can resist 30% of poisoning attacks, and can achieve privacy protection with high model accuracy, and is suitable for edge computing scenarios that require high level of security and accuracy. [ABSTRACT FROM AUTHOR]

Network traffic classification technologies could be used by attackers to implement network monitoring and then launch traffic analysis attacks or website fingerprint attacks. In order to prevent such attacks, a novel way to generate adversarial samples of network traffic from the perspective of the defender is proposed. By adding perturbation to the normal network traffic, a kind of adversarial network traffic is formed, which will cause misclassification when the attackers are implementing network traffic classification with deep convolutional neural networks (CNN) as a classification model. The paper uses the concept of adversarial samples in image recognition for reference to the field of network traffic classification and chooses several different methods to generate adversarial samples of network traffic. The experiment, in which the LeNet-5 CNN is selected as a classification model used by attackers and Vgg16 CNN is selected as the model to test the transferability of the adversarial network traffic generated, shows the effect of the adversarial network traffic samples. [ABSTRACT FROM AUTHOR]

Cloud data, the ownership of which is separated from their administration, usually contain users' private information, especially in the fifth-generation mobile communication (5G) environment, because of collecting data from various smart mobile devices inevitably containing personal information. If it is not securely deleted in time or the result of data deletion cannot be verified after their expiration, this will lead to serious issues, such as unauthorized access and data privacy disclosure. Therefore, this affects the security of cloud data and hinders the development of cloud computing services seriously. In this paper, we propose a novel secure data deletion and verification (SDVC) scheme based on CP-ABE to achieve fine-grained secure data deletion and deletion verification for cloud data. Based on the idea of access policy in CP-ABE, we construct an attribute association tree to implement fast revoking attribute and reencrypting key to achieve fine-grained control of secure key deletion. Furthermore, we build a rule transposition algorithm to generate random data blocks and combine the overwriting technology with the Merkle hash tree to implement secure ciphertext deletion and generate a validator, which is then used to verify the result of data deletion. We prove the security of the SDVC scheme under the standard model and verify the correctness and effectiveness of the SDVC scheme through theoretical analysis and ample simulation experiment results. [ABSTRACT FROM AUTHOR]

Increasingly, more administrators (defenders) are using defense strategies with deception such as honeypots to improve the IoT network security in response to attacks. Using game theory, the signaling game is leveraged to describe the confrontation between attacks and defenses. However, the traditional approach focuses only on the defender; the analysis from the attacker side is ignored. Moreover, insufficient analysis has been conducted on the optimal defense strategy with deception when the model is established with the signaling game. In our work, the signaling game model is extended to a novel two-way signaling game model to describe the game from the perspectives of both the defender and the attacker. First, the improved model is formally defined, and an algorithm is proposed for identifying the refined Bayesian equilibrium. Then, according to the calculated benefits, optimal strategies choice for both the attacker and the defender in the game are analyzed. Last, a simulation is conducted to evaluate the performance of the proposed model and to demonstrate that the defense strategy with deception is optimal for the defender. [ABSTRACT FROM AUTHOR]

Mucor M/T was isolated from sufu pehtze. Using Mucor 40899 and Mucor M/T as mixed starters, the pre-fermentation process of Sufu was studied through single factors and response surface optimization method. Then, the changes of amino acid nitrogen, texture and chromaticity of Sufu fermented by mixed strains were studied under the optimal pre-fermentation conditions. The results showed that Mucor M/T was identified as the Actinomucor. The optimal pre-fermentation conditions were as follows: fermentation time was 60 h, strain quality ratio of Mucor 40899 and Mucor M/T was 1:1, pH value was 3.5. Under the optimal conditions, the protease activity reached 48.015 U/mL. After post-fermentation of 30 d, the content of amino acid nitrogen in Sufu was 0.53 g/(100 g), which met the mature standard in the industry standard of Sufu. The texture, adhesion and elasticity of Sufu were good. The color difference value was close to that of commercially mature fermented Sufu. [ABSTRACT FROM AUTHOR]

With Sanchuan ham made by traditional fermentation process as raw material, the mass concentration of 8 main biogenic amines in the curing, drying and fermentation stages of Sanchuan ham was determined by HPLC, and the change rule of biogenic amines in the processing of Sanchuan ham was studied. The results showed that: 1) a total of 7 kinds of biogenic amines were detected, which were phenethylamine, resinamine, saprolamine, histamine, tyramine, ispermine and spermine. Tryptamine was not detected out. Among them, sapromine and spermine existed in the whole process of Sanchuan ham. The cadaverine mass concentration was the highest in 7 species, followed by spermine. The cadaverine mass concentration continued to increase during the processing of Sanchuan ham, and reached the maximum value in the late stage of fermentation, which was (69.24 ±12.54) mg/kg, but began to decrease significantly in the late stage of fermentation. The mass concentration of spermidine and spermine were stable, and the mass concentration of spermidine was low. Phenethylamine was detected only in the middle of curing. The mass concentration of histamine was low, and the highest mass concentration was only (22.52 ±5. 25) mg/kg, which was relatively safe. 2) during the whole process of Sanchuan ham, the total biogenic amine mass concentration first increased, then stabilized and then decreased: the total biogenic amine mass concentration in fresh Sanchuan ham was the lowest, which was (5.84 ± 1.30) mg/kg, and the total biogenic amine mass concentration increased significantly in the middle and late stage of curing ( P < 0. 05 ) . During the drying period, the increase of total biogenic amine mass concentration was not significant ( P > 0. 05 ) . In the late stage of fermentation, the mass concentration of biogenic amine was the highest, which was (158.08 ±31.35) mg/kg. [ABSTRACT FROM AUTHOR]