Structural Damage Detection Based on Improved Multi-Particle Swarm Co-Evolution Optimization Algorithm

This chapter presents an improved multi-particle swarm co-evolution optimization algorithm (IMPSCO) to detect structural damage. Firstly, IMPSCO is integrated with Newmark’s algorithm for damage detection and system identification, which just need few sensors. In addition, for reducing the searching parameters, a two-stage damage detection method based on modal strain energy and IMPSCO is presented. In order to validate the proposed method, a seven-story steel frame experiment in laboratory conditions is performed and a comparison is made between the proposed approach and genetic algorithm (GA). The results show that: (1) the proposed methods can not only effectively locate damage location but also accurately quantify the damage severity. Besides, it has excellent noise-tolerance and adaptability; (2) for integrating IMPSCO and Newmark’s algorithm, it implements only by using any kinds of structural time-series responses and the excitation force; (3) compared with genetic algorithm, IMPSCO is more efficient and robust for damage detection with a better noise-tolerance

Blockchain-based data privacy management with Nudge theory in open banking

Open banking brings both opportunities and challenges to banks all over the world especially in data management. A blockchain as a continuously growing list of records managed by a peer-to-peer network is widely used in various application scenarios; and it is commonly agreed that the blockchain technology can improve the protection of financial data privacy. However, current blockchain technology still poses some challenges in fully meeting the needs of financial data privacy protection. In order to address the existing problems, this paper proposes a new data privacy management framework based on the blockchain technology for the financial sector. The framework consists of three components: (1) a data privacy classification method according to the characteristics of financial data; (2) a new collaborative-filtering-based model; and (3) a data disclosure confirmation scheme for customer strategies based on the Nudge Theory. We implement a prototype and propose a set of algorithms for this framework. The framework is validated through field experiments and laboratory experiments. © 2019 Elsevier B.V

Alumni Network Centrality and Competitive Aggressiveness

This paper examines the role of external resources and information advantages embedded in a firm's alumni network in the adoption of aggressive competitive strategies. We extend the competitive dynamics literature and social network theory by analysing the effect that the acquisition of external resources and information advantage has on corporate competitive strategy. We hypothesize that more central firms in alumni networks are associated with more aggressive competitive actions and better performance. We introduce extensive data from China and find strong support for our central hypothesis. Further, the data indicate that the effect is stronger in firms with high product market competition, high input–output network centrality, and during periods of high economic policy uncertainty. The results are robust to several endogeneity tests

An Engineered DC-Targeting Lentivector Induces Robust T Cell Responses and Inhibits HBV Replication in HBV Transgenic Mice via Upregulating T Cell Autophagy

Background/Aims: Developing engineered dendritic cell (DC)-targeting lentivectors (LVs) have been the target of intense research for their potential to create antigen-directed immunotherapeutics which can be safely administered to patients. In this study, we constructed a DC-directed LV (LVDC-UbHBcAg-LIGHT) as a potential vaccine to induce anti-HBV immune responses. Methods: Specificity of LVDC-UbHBcAg-LIGHT for DCs in vivo was confirmed through live animal imaging studies. The levels of cytokine production in T cells were assessed by flow cytometry. The HBcAg-specific cytotoxic T lymphocyte (CTL) responses and antibody responses induced by direct administration of the LVs were detected by LDH release assay and ELISA respectively. The levels of serum HBsAg and HBV DNA were evaluated by Abbott kits and quantitative PCR respectively. The expression levels of HBsAg and HBcAg in liver tissues of HBV transgenic mice were examined by immunohistochemistry. In addition, molecular mechanism underlying the activation of CD8+ T cells was explored. Results: Live animal imaging studies showed that following subcutaneous administration of LVDC-UbHBcAg-LIGHT, no obvious luminescence signal was detected at the injection site. Immunization with LVDC-UbHBcAg-LIGHT elicited potent T cell responses in HBV transgenic mice evidenced by increased percentages of IFN-γ, TNF-α and GzmB producing CD8+ T cells as well as IFN-γ producing CD4+ T cells, improved HBcAg-specific CTL activities and antibody responses. Additionally, vaccination with LVDC-UbHBcAg-LIGHT efficiently reduced serum HBsAg, HBV DNA levels and the expression of HBsAg and HBcAg in liver tissues of HBV transgenic mice. More importantly, autophagy was induced in the activated CD8+ T cells, and the induced autophagy noticeably promoted the proliferation of T cells and decreased the frequencies of apoptotic CD8+ T cells by selectively degrading ubiquitinated apoptosis and cell cycle-associated protein aggregates. Futhermore, we confirmed the interaction between autophagosomes and ubiquitinated aggregates by confocal microscopy and immunoprecipitation analysis. Conclusions: These results demonstrated that LVDC-UbHBcAg-LIGHT provided a simple method of eliciting effective antiviral immune responses in HBV transgenic mice and might potentially be used as a therapeutic strategy to eradicate HBV with more safety and efficiency. Moreover, our results revealed a direct role of autophagy in promoting the survival and proliferation of activated CD8+ T cells

Differential expression and functions of Ehm2 transcript variants in lung adenocarcinoma

Ehm2 [also known as erythrocyte membrane protein band 4.1‑like protein 4B (EPB41L4B)] is a member of the NF2/ERM/4.1 superfamily. The overexpression of Ehm2 has been observed in metastatic cancer cells. Through alternative splicing, the Ehm2 gene produces two transcript variants that encode the two different isoforms, Ehm2/1 and Ehm2/2. The biological functions of these different Ehm2 transcript variants remain unclear. The present study aimed to determine the expression of the Ehm2 variants in lung adenocarcinoma and their involvement in the disease progression of the patients. The expression of Ehm2 transcript variants in human lung adenocarcinoma tissues was analyzed using immunohistochemistry and western blot analysis. Ehm2 variants were overexpressed or knocked down in A549 human lung adenocarcinoma cells. The consequent effects of the genetic modifications on the cellular functions of lung cancer cells were then examined using in vitro cell viability, invasion and migration assays. The expression of epithelial‑mesenchymal transition (EMT)‑related markers was evaluated by western blot analysis in the cell models. The association of Ehm2 variant expression with patient survival was analyzed using Kaplan‑Meier survival analysis. The expression of Ehm2/1 was significantly decreased in lung cancers compared with the paired normal lung tissues (P<0.05), while the Ehm2/2 protein levels were higher in the tumors than in the paired normal lung tissues, although this was not statistically significant. The overexpression of Ehm2/1 exerted inhibitory effects, while the knockdown of Ehm2/1 promoted the growth, invasion and migration of A549 cells in vitro. Ehm2/2 was expressed at low levels in the A549 cells and the enforced expression of Ehm2/2 significantly increased the invasiveness and migration of the A549 cells. Immunofluorescence staining revealed that Ehm2/1 was confined to the plasma membrane, while Ehm2/2 was observed at both the plasma membrane and cytoplasm. The overexpression of Ehm2/1 resulted in the upregulation of the epithelial marker, E‑cadherin, and in the decreased expression of the mesenchymal markers, N‑cadherin and Snail1, while the knockdown of Ehm2/1 and the enforced expression of Ehm2/2 had the opposite effects on the protein levels of EMT‑related markers. Kaplan‑Meier survival analysis revealed that higher Ehm2/1 transcript levels were associated with the longer survival of patients with lung adenocarcinoma, while the lower expression of Ehm2/2 exhibited a similar association with patient survival. Taken together, the two Ehm2 variants appear to be differentially expressed in lung adenocarcinoma. Ehm2/1 may function as a putative tumor suppressor in the disease progression of lung adenocarcinoma, while Ehm2/2 may have an opposite function

Board affiliation and pay gap

This paper examines the effects of board affiliation on the corporate pay gap. Using a sample of Chinese listed firms from 2005 to 2011, we find that boards with a greater presence of directors appointed by block shareholders have lower pay gaps. Furthermore, the governance effects of board affiliation with and without pay are distinguished. The empirical results show that board affiliation without pay is negatively related to the pay gap, while board affiliation with pay is positively related to the pay gap. Overall, the results shed light on how block shareholders affect their companies’ pay gaps through board affiliation

A Rhombic Dodecahedron Topology for Human-Centric Banking Big Data

Banks are collecting an unprecedentedly large amount of data about their customers from difference sources, considering their cyber, physical, social activities. The focus of this paper is to study the problem of information sharing and lower the communication overhead among different nodes for a specific data mining approach in distributed big data architectures. This problem can be abstracted as how to efficiently search under a specific cluster node topology. This paper proposes a new design rule for topologies including: 1) low coordination number; 2) high packing density; and 3) having a 3-D structure. According to this rule, a rhombic dodecahedron topology is proposed. A distributed banking big data mining framework based on the proposed topology is implemented. The experiments based on multioptimization benchmark functions show the excellent searching ability of the proposed topology; and a banking customer feature reduction prototype has been implemented to showcase the practicality of the data mining framework

Stock market openness and analyst forecast bias

Biases in analysts’ forecasts can be reduced not only through regulation but also through market mechanisms. In 2014, China launched the Shanghai-Hong Kong Connect program, which opened part of its domestic equity market to foreign investors. The implementation of this program provides a quasi-natural experimental setting to explore whether stock market openness plays a governance role in brokerage firms and minimizes their affiliated analysts\u27 forecast biases. We find that the participation of foreign institutional investors mitigates the forecast biases of affiliated analysts. We also show that these analysts exert more significant effort by conducting more site visits. Our findings suggest that market liberalization can help improving the quality of analysts’ forecasts

Stress Monitoring of Concrete via Uniaxial Piezoelectric Sensor

The uniaxial piezoelectric sensor was developed to overcome the problem of reflecting the output charge of the piezoelectric element as a combination of vectors in the three stress directions. The work performance of the uniaxial piezoelectric sensor under varying load patterns and load rates was investigated. The sensor was embedded in concrete to monitor stress, and its elastic modulus was used as the intermediate bridge to establish the correlation between the embedded sensor and the external sensor. Furthermore, a correction factor for the charge transformation strain was suggested to overcome the mismatching of the sensor&rsquo;s medium and the concrete. Considering related circumstances, a new stress monitoring method based on a uniaxial piezoelectric sensor was proposed, which can achieve stress whole-process monitoring in concrete and confining stress monitoring in the reinforced concrete column. The results reveal that through the proposed method, the output charge curve of the sensor has a substantial overlap with the stress waveform and high fitting linearity. The work performance of the sensor was stable, and its sensitivity was not affected by loading rate and load pattern. The sensor was embedded in concrete and can coordinate with the concrete deformation. The correction factor of strain obtained by the sensor embedded in concrete was 1.07. The relationship between the charge produced by the embedded sensor and its external calibration sensitivity may be used to implement the whole process of stress monitoring in concrete