• Journal of Microbiology and Biotechnology
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• v.27 no.9
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• pp.1628-1638
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• 2017

Viola tianshanica Maxim, belonging to the Violaceae plant family, is traditionally used in Uighur medicine for treating pneumonia, headache, and fever. There is, however, a lack of basic understanding of its pharmacological activities. This study was designed to observe the effects of the ethanol extract (TSM) from Viola tianshanica Maxim on the inflammation response in acute lung injury (ALI) induced by LPS and the possible underlying mechanisms. We found that TSM (200 and 500 mg/kg) significantly decreased inflammatory cytokine production and the number of inflammatory cells, including macrophages and neutrophils, in bronchoalveolar lavage fluid. TSM also markedly inhibited the lung wet-to-dry ratio and alleviated pathological changes in lung tissues. In vitro, after TSM ($12.5-100{\mu}g/ml$) treatment to RAW 264.7 cells for 1 h, LPS ($1{\mu}g/ml$) was added and the cells were further incubated for 24 h. TSM dose-dependently inhibited the levels of proinflammatory cytokines, such as NO, $PGE_2$, $TNF-{\alpha}$, IL-6, and $IL-1{\beta}$, and remarkably decreased the protein and mRNA expression of $TNF-{\alpha}$ and IL-6 in LPS-stimulated RAW 264.7 cells. TSM also suppressed protein expression of $p-I{\kappa}Ba$ and p-ERK1/2 and blocked nuclear translocation of $NF-{\kappa}B$ p65. The results indicate that TSM exerts anti-inflammatory effects related with inhibition on $NF-{\kappa}B$ and MAPK (p-ERK1/2) signaling pathways. In conclusion, our data demonstrate that TSM might be a potential agent for the treatment of ALI.

• International Journal of Internet, Broadcasting and Communication
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• v.13 no.2
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• pp.60-66
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• 2021

Blockchain is a technology that enables trust-based consensus and verification based on a decentralized network. Distributed ID (DID) is based on a decentralized structure, and users have the right to manage their own ID. Recently, interest in self-sovereign identity authentication is increasing. In this paper, as a method for transparent and safe sovereignty management of data, among data pseudonymization techniques for blockchain use, various methods for data encryption processing are examined. The public key technique (homomorphic encryption) has high flexibility and security because different algorithms are applied to the entire sentence for encryption and decryption. As a result, the computational efficiency decreases. The hash function method (MD5) can maintain flexibility and is higher than the security-related two-way encryption method, but there is a threat of collision. Zero-knowledge proof is based on public key encryption based on a mutual proof method, and complex formulas are applied to processes such as personal identification, key distribution, and digital signature. It requires consensus and verification process, so the operation efficiency is lowered to the level of O (log_eN) ~ O(N²). In this paper, data encryption processing for blockchain DID, based on zero-knowledge proof, was proposed and a one-way encryption method considering data use range and frequency of use was proposed. Based on the content presented in the thesis, it is possible to process corrected zero-knowledge proof and to process data efficiently.

• Molecules and Cells
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• v.44 no.9
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• pp.647-657
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• 2021

As a pancreatic inflammatory marker, regenerating islet-derived protein 3A (Reg3A) plays a key role in inflammation-associated pancreatic carcinogenesis by promoting cell proliferation, inhibiting apoptosis, and regulating cancer cell migration and invasion. This study aimed to reveal a novel immuno-regulatory mechanism by which Reg3A modulates tumour-promoting responses during pancreatic cancer (PC) progression. In an in vitro Transwell system that allowed the direct co-culture of human peripheral blood-derived dendritic cells (DCs) and Reg3A-overexpressing/ silenced human PC cells, PC cell-derived Reg3A was found to downregulate CD80, CD83 and CD86 expression on educated DCs, increase DC endocytic function, inhibit DC-induced T lymphocyte proliferation, reduce IL-12p70 production, and enhance IL-23 production by DCs. The positive effect of tumour-derived Reg3A-educated human DCs on PC progression was demonstrated in vivo by intraperitoneally transferring them into PC-implanted severe combined immunodeficiency (SCID) mice reconstituted with human T cells. A Reg3A-JAK2/STAT3 positive feedback loop was identified in DCs educated with Reg3A. In conclusion, as a tumour-derived factor, Reg3A acted to block the differentiation and maturation of the most important antigen-presenting cells, DCs, causing them to limit their potential anti-tumour responses, thus facilitating PC escape and progression.

• Smart Structures and Systems
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• v.31 no.3
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• pp.229-245
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• 2023

The absence of excitation measurements may pose a big challenge in the application of structural damage identification owing to the fact that substantial effort is needed to reconstruct or identify unknown input force. To address this issue, in this paper, an iterative strategy, a synergy of Tikhonov regularization method for force identification and modified Jaya algorithm (M-Jaya) for stiffness parameter identification, is developed for damage identification with partial output-only responses. On the one hand, the probabilistic clustering learning technique and nonlinear updating equation are introduced to improve the performance of standard Jaya algorithm. On the other hand, to deal with the difficulty of selection the appropriate regularization parameters in traditional Tikhonov regularization, an improved L-curve method based on B-spline interpolation function is presented. The applicability and effectiveness of the iterative strategy for simultaneous identification of structural damages and unknown input excitation is validated by numerical simulation on a 21-bar truss structure subjected to ambient excitation under noise free and contaminated measurements cases, as well as a series of experimental tests on a five-floor steel frame structure excited by sinusoidal force. The results from these numerical and experimental studies demonstrate that the proposed identification strategy can accurately and effectively identify damage locations and extents without the requirement of force measurements. The proposed M-Jaya algorithm provides more satisfactory performance than genetic algorithm, Gaussian bare-bones artificial bee colony and Jaya algorithm.

• Structural Engineering and Mechanics
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• v.48 no.3
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• pp.291-308
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• 2013

Structural health monitoring is crucial to maintain the structural performance safely. Moreover, the Kullback-Leibler divergence (KLD) is applied usually to asset the similarity between different probability density functions in the pattern recognition. In this study, the KLD is employed to detect the damage. However the asymmetry of the KLD is a shortcoming for the damage detection, to overcoming this shortcoming, two other divergences and one statistic distribution are proposed. Then the damage identification by the KLD and its three descriptions from the symmetric point of view is investigated. In order to improve the reliability and accuracy of the four divergences, the gapped smoothing method (GSM) is adopted. On the basis of the damage index approach, the new damage index (DI) for detect damage more accurately based on the four divergences is developed. In the last, the grey relational coefficient and hypothesis test (GRCHT) is utilized to obtain the more precise damage identification results. Finally, a clear remarkable improvement can be observed. To demonstrate the feasibility and accuracy of the proposed method, examples of an isotropic beam with different damage scenarios are employed so as to check the present approaches numerically. The final results show that the developed approach successfully located the damaged region in all cases effect and accurately.

• Structural Engineering and Mechanics
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• v.91 no.2
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• pp.227-238
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• 2024

Sparse regularization methods have proven effective in addressing the ill-posed equations encountered in moving force identification (MFI). However, the complexity of vehicle loads is often ignored in existing studies aiming at enhancing MFI accuracy. To tackle this issue, a double 𝑙₁ regularization method is proposed for MFI based on a response spectrum-based weighted dictionary in this study. Firstly, the relationship between vehicle-induced responses and moving vehicle loads (MVL) is established. The structural responses are then expanded in the frequency domain to obtain the prior knowledge related to MVL and to further construct a response spectrum-based weighted dictionary for MFI with a higher accuracy. Secondly, with the utilization of this weighted dictionary, a double 𝑙₁ regularization framework is presented for identifying the static and dynamic components of MVL by the alternating direction method of multipliers (ADMM) method successively. To assess the performance of the proposed method, two different types of MVL, such as composed of trigonometric functions and driven from a 1/4 bridge-vehicle model, are adopted to conduct numerical simulations. Furthermore, a series of MFI experimental verifications are carried out in laboratory. The results shows that the proposed method's higher accuracy and strong robustness to noises compared with other traditional regularization methods.

• Structural Engineering and Mechanics
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• v.46 no.3
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• pp.433-445
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• 2013

Vibration-based structural identification has become an important tool for structural health monitoring and safety evaluation. However, various kinds of uncertainties (e.g., observation noise) involved in the field test data obstruct automation system identification for accurate and fast structural safety evaluation. A practical way including a data preprocessing procedure and a vector backward auto-regressive (VBAR) method has been investigated for practical bridge identification. The data preprocessing procedure serves to improve the data quality, which consists of multi-level uncertainty mitigation techniques. The VBAR method provides a determinative way to automatically distinguish structural modes from extraneous modes arising from uncertainty. Ambient test data of a cantilever beam is investigated to demonstrate how the proposed method automatically interprets vibration data for structural modal estimation. Especially, structural identification of a truss bridge using field test data is also performed to study the effectiveness of the proposed method for real bridge identification.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.7
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• pp.2532-2553
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• 2014

In Asiacrypt 2003, Al-Riyami and Paterson proposed the notion of certificateless cryptography, a technique to remove key escrow from traditional identity-based cryptography as well as circumvent the certificate management problem of traditional public key cryptography. Subsequently much research has been done in the realm of certificateless encryption and signature schemes, but little to no work has been done for the identification primitive until 2013 when Chin et al. rigorously defined certificateless identification and proposed a concrete scheme. However Chin et al.'s scheme was proven in the random oracle model and Canetti et al. has shown that certain schemes provable secure in the random oracle model can be insecure when random oracles are replaced with actual hash functions. Therefore while having a proof in the random oracle model is better than having no proof at all, a scheme to be proven in the standard model would provide stronger security guarantees. In this paper, we propose the first certificateless identification scheme that is both efficient and show our proof of security in the standard model, that is without having to assume random oracles exist.

• Structural Engineering and Mechanics
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• v.29 no.2
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• pp.155-169
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• 2008

A MOM-based algorithm (MOMA) has been developed for moving force identification from dynamic responses of bridge in the companion paper. This paper further evaluates and investigates the properties of the developed MOMA by experiment in laboratory. A simply supported bridge model and a few vehicle models were designed and constructed in laboratory. A series of experiments have then been conducted for moving force identification. The bending moment and acceleration responses at several measurement stations of the bridge model are simultaneously measured when the model vehicle moves across the bridge deck at different speeds. In order to compare with the existing time domain method (TDM), the best method for moving force identification to date, a carefully comparative study scheme was planned and conducted, which includes considering the effect of a few main parameters, such as basis function terms, mode number involved in the identification calculation, measurement stations, executive CPU time, Nyquist fraction of digital filter, and two different solutions to the ill-posed system equation of moving force identification. It was observed that the MOMA has many good properties same as the TDM, but its CPU execution time is just less than one tenth of the TDM, which indicates an achievement in which the MOMA can be used directly for real-time analysis of moving force identification in field.

• Journal of Microbiology and Biotechnology
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• v.28 no.12
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• pp.1999-2008
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• 2018

The compound 2,5-furandicarboxylic acid (FDCA), an important bio-based monomer for the production of various polymers, can be obtained from 5-hydroxymethylfurfural (HMF). However, efficient production of FDCA from HMF via biocatalysis has not been well studied. In this study, we report the identification of key genes that are involved in FDCA synthesis and then the engineering of Raoultella ornithinolytica BF60 for biocatalytic oxidation of HMF to FDCA using its resting cells. Specifically, previously unknown candidate genes, adhP3 and alkR, which were responsible for the reduction of HMF to the undesired product 2,5-bis(hydroxymethyl)furan (HMF alcohol), were identified by transcriptomic analysis. Combinatorial deletion of these two genes resulted in 85.7% reduction in HMF alcohol formation and 23.7% improvement in FDCA production (242.0 mM). Subsequently, an aldehyde dehydrogenase, AldH, which was responsible for the oxidation of the intermediate 5-formyl-2-furoic acid (FFA) to FDCA, was identified and characterized. Finally, FDCA production was further improved by overexpressing AldH, resulting in a 96.2% yield of 264.7 mM FDCA. Importantly, the identification of these key genes not only contributes to our understanding of the FDCA synthesis pathway in R. ornithinolytica BF60 but also allows for improved FDCA production efficiency. Moreover, this work is likely to provide a valuable reference for producing other furanic chemicals.