Influence of Polycaprolactone/Collagen Ratio and Microstructure of FibrousMembranes on Mechanical Properties and Anti-Platelet Properties

Jia-Shuai Zhang,Hui-Lin Mo,Shun-Yang Shen,Du-Han Zhang,Wei Zhang,Yu Ren,Mei-Xian Li 한국고분자학회 2024 폴리머 Vol.48 No.1

In this paper, polycaprolactone (PCL)/collagen (COL) nanofibrous membranes were prepared by electrospinning to study their mechanical properties as well as biocompatibility. The surface morphology was characterized by scanning electron microscopy (SEM) to access the effect of microstructure on the mechanical properties, cytocompatibility, and enzymatic degradation behaviors. In addition, the effect of hydrophilicity of membranes on the antithrombotic properties was also investigated. The results show that tensile strength of PCL/COL10 is higher than that of other samples due to smaller fiber diameters and tight spatial interlacing of PCL/COL10 membranes. In addition, the hydrophobic surface of PCL becomes hydrophilic after the addition of collagen, which affect platelet adhesion and cytocompatibility of nanofibrous membrane samples. The addition of collagen could promote the cell proliferation as well as the enzymatic degradation rate. Overall, PCL/COL10 has good morphology, the best mechanical properties, appropriate degradation rate, and the best antithrombotic effect as well as biocompatibility.

Investigation on purification of α-Fe₂O₃ from zinc smelting iron slag by superconducting HGMS technology

Zhang, Peng,Li, Su-qin,Guo, Zi-jie,Zhang, Chang-quan,Yang, Chang-qiao,Han, Shuai-shuai The Korea Institute of Applied Superconductivity a 2018 한국초전도저온공학회논문지 Vol.20 No.2

Comprehensive utilization of zinc smelting iron slag not only solves environmental problems but also creates huge economic benefits. This study was conducted on the enrichment and recovery of ${\alpha}-Fe_2O_3$ from zinc smelting iron slag by superconducting HGMS technology. Several variables such as slurry flow velocity, slag concentration, magnetic field intensity and the amount of dispersing agent were tested in magnetic separation. In the experiments, obtained optimal magnetic separation parameters were 1.60 T of magnetic flux intensity, 600 mL/min of slurry flow velocity of, 15 g/L of slag concentration of, 0.10 g/L of dispersing agent. Under this condition, the content of ${\alpha}-Fe_2O_3$ was increased from 86.22% to 94.39% that can approach the Chinese national standard requirements (A level) of iron oxide red. It was concluded that using superconducting HGMS technology was an effective method for the purification of ${\alpha}-Fe_2O_3$ from zinc smelting iron slag.

Perceived Risks, Mitigating Factors and Travel Intentions of Potential Tourists in a High-Risk Environment: Case Studies on the 2021 Tokyo Olympics and 2022 Beijing Winter Olympics

( Shuai Zhang ),( Xinqi Zhang ),( Yu Cheng ),( Naiqiao Ning ),( Yinsheng Lin ),( Liang Chen ) 아시아스포츠융합과학회 2021 Asia Pacific Journal of Applied Sport Sciences Vol.2 No.3

PURPOSE This research establishes a reasonable research model to investigate the relationship between the perceived risks, mitigating factors, and travel intentions of potential visitors to the Olympic Games under the COVID-19 epidemic environment. And examine the mediating role of mitigating factors between perceived risk and travel intention. METHOD This study conducted two online surveys with Chinese athletes as the survey subject, divided into two samples for the Tokyo Olympics and the Beijing Olympics. The data analysis process is divided into two stages. In the first stage, confirmatory factor analysis (CFA) is used to test the reliability and validity of the scale. In the second stage, structural equation modeling (SEM) analysis is used to test the proposed hypothesis. Finally, the data test results of the two samples are compared. RESULT After the CFA test, the data fit well with the model, and the model had good combination reliability and convergence validity. On this basis, a structural equation model was established, and the mediation validity of the model was tested. CONCLUSION The results show that risk perception has a significant effect on mitigating factors, and mitigating factors have very significant positive effects on behavioral intentions. Mitigating factors mediate between risk perception and behavioral intentions.

Optimizing Stem Cell Therapy after Ischemic Brain Injury

Shuai Zhang,Brittany Bolduc Lachance,Bilal Moiz,Xiaofeng Jia 대한뇌졸중학회 2020 Journal of stroke Vol.22 No.3

Stem cells have been used for regenerative and therapeutic purposes in a variety of diseases. In ischemic brain injury, preclinical studies have been promising, but have failed to translate results to clinical trials. We aimed to explore the application of stem cells after ischemic brain injury by focusing on topics such as delivery routes, regeneration efficacy, adverse effects, and in vivo potential optimization. PUBMED and Web of Science were searched for the latest studies examining stem cell therapy applications in ischemic brain injury, particularly after stroke or cardiac arrest, with a focus on studies addressing delivery optimization, stem cell type comparison, or translational aspects. Other studies providing further understanding or potential contributions to ischemic brain injury treatment were also included. Multiple stem cell types have been investigated in ischemic brain injury treatment, with a strong literature base in the treatment of stroke. Studies have suggested that stem cell administration after ischemic brain injury exerts paracrine effects via growth factor release, blood-brain barrier integrity protection, and allows for exosome release for ischemic injury mitigation. To date, limited studies have investigated these therapeutic mechanisms in the setting of cardiac arrest or therapeutic hypothermia. Several delivery modalities are available, each with limitations regarding invasiveness and safety outcomes. Intranasal delivery presents a potentially improved mechanism, and hypoxic conditioning offers a potential stem cell therapy optimization strategy for ischemic brain injury. The use of stem cells to treat ischemic brain injury in clinical trials is in its early phase; however, increasing preclinical evidence suggests that stem cells can contribute to the down-regulation of inflammatory phenotypes and regeneration following injury. The safety and the tolerability profile of stem cells have been confirmed, and their potent therapeutic effects make them powerful therapeutic agents for ischemic brain injury patients.

Scanning ion conductance microscopy studies of amyloid fibrils at nanoscale.

Zhang, Shuai,Cho, Sang-Joon,Busuttil, Katerina,Wang, Chen,Besenbacher, Flemming,Dong, Mingdong RSC Pub 2012 Nanoscale Vol.4 No.10

<P>Atomic force microscopy (AFM) has developed to become a very versatile nano-scale technique to reveal the three-dimensional (3D) morphology of amyloid aggregates under physiological conditions. However, the imaging principle of AFM is based on measuring the 'force' between a sharp tip and a given nanostructure, which may cause mechanical deformation of relatively soft objects. To avoid the deformation, scanning ion conductance microscopy (SICM) is an alternative scanning probe microscopy technique, operating with alternating current mode. Here we can indeed reveal the 3D morphology of amyloid fibrils and it is capable of exploring proteins with nanoscale resolution. Compared with conventional AFM, we show that SICM can provide precise height measurements of amyloid protein aggregates, a feature that enables us to obtain unique insight into the detailed nucleation and growth mechanisms behind amyloid self-assembly.</P>

Rolling element-bearing feature extraction based on combined wavelets and quantum-behaved particle swarm optimization

Shuai Zhang,Yongxiang Zhang,Jieping Zhu 대한기계학회 2015 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.29 No.2

A new approach is proposed to quickly determine the optimal band-pass filter for the resonant demodulation of rolling element bearings. The combined wavelet filter is joined with quantum-behaved particle swarm optimization for optimal filtering. The correlated kurtosisis used as an evaluation index to identify the optimal filtered signal. The proposed approach possesses good band-pass filteringproperties and improves optimal filtering speed and effect to converge rapidly to an optimal solution. Simulation and experiment resultsshow that this approach can generate fault features that are superior to those produced with the classic algorithm. It also shortens the timespent on the same filtering effect in comparison.

Bending actuation in a single-layer carbon-nanofiber/polypyrrole composite film and its fabrication

Shuai Zhang,김철 대한기계학회 2011 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.25 No.7

Thin CNF/PPy composite single-layer films were produced by the electrophoretic deposition and polymerization process which was developed for this study. It was demonstrated that the films could generate a bending motion subjected to an actuating electric voltage even though they consisted of only single-layer. Carbon nanofiber and polypyrrole composite films were obtained from only one side of a working electrode. Several different CNF/PPy films were synthesized, as varying the CNF weight ratios from 3%, 5%, and 7% to 10%. Conductivity of pure PPy and CNF/PPy composite films were measured. Conductivity of the films is improved linearly from 77.9S/cm (pure PPy film) to 124.3 S/cm (10% CNF/PPy) as the CNF weight ratio increases. Adding CNF was effective for improving the conductivity of PPy. As results of electromechanical actuation tests with the films, it was noticed that the strain of the films was reduced a little as the CNF weight ratio increased. Bending motions were observed for both PPy and CNF/PPy films subjected to a voltage. The tip bending deflections was in the range of 0.5 mm to 2 mm. CNF/PPy films showed a great potential to be a good candidate for small light actuators.

Factors Affecting the Decision Process of Online Purchase of Sports Good under the background of COVID-19: Application of Goal Oriented Behavior Model

( Shuai Zhang ),( Xiao Ren ),( Yanzhang Wang ),( Yongdi Wang ) 아시아스포츠융합과학회 2022 Asia Pacific Journal of Applied Sport Sciences Vol.3 No.1

PURPOSE This study used a sporting goods goal-oriented behavior model (SG-MGB) to predict and test consumers' behavioral intentions for purchasing sporting goods online. Based on the original MGB, the study added three constructs related to online consumption, and examined the factors that influence the online consumer's consumption decision-making process. METHOD A conceptual model containing 13 hypotheses was empirically tested using data from 271 Shanghai residents who have purchased sports goods online in the past 12 months. RESULT The results showed that consumers' positive anticipated emotion, negative anticipated emotion, past behavior frequency, and brand image all positively affected desire. Desire had the most significant positive effect on behavioral intention. Desire played a positive mediating role. CONCLUSION The study found that brand image is an important variable that affects consumers' willingness to buy sports goods online. The SG-MGB is a strong predictive model for online consumers' behavioral intentions.

A dynamic human reliability assessment approach for manned submersibles using PMV-CREAM

Zhang, Shuai,He, Weiping,Chen, Dengkai,Chu, Jianjie,Fan, Hao The Society of Naval Architects of Korea 2019 International Journal of Naval Architecture and Oc Vol.11 No.2

Safety is always acritical focus of exploration of ocean resources, and it is well recognized that human factor is one of the major causes of accidents and breakdowns. Our research developed a dynamic human reliability assessment approach, Predicted Mean Vote-Cognitive Reliability and Error Analysis Method (PMV-CREAM), that is applicable to monitoring the cognitive reliability of oceanauts during deep-sea missions. Taking into account the difficult and variable operating environment of manned submersibles, this paper analyzed the cognitive actions of oceanauts during the various procedures required by deep-sea missions, and calculated the PMV index using human factors and dynamic environmental data. The Cognitive Failure Probabilities (CFP) were calculated using the extended CREAM approach. Finally, the CFP were corrected using the PMV index. This PMV-CREAM hybrid model can be utilized to avoid human error in deep-sea research, thereby preventing injury and loss of life during undersea work. This paper verified the method with "Jiaolong" manned submersible 7,000 m dive test. The"Jiaolong" oceanauts CR(Corrected CFP) is dynamic from 3.0615E-3 to 4.2948E-3, the CR caused by the environment is 1.2333E-3. The result shown the PMV-CREAM method could describe the dynamic human reliability of manned submersible caused by thermal environment.

A Real Time Traffic Flow Model Based on Deep Learning

Shuai Zhang,Cai Y. Pei,Wen Y. Liu 한국인터넷정보학회 2022 KSII Transactions on Internet and Information Syst Vol.16 No.8

Urban development has brought about the increasing saturation of urban traffic demand, and traffic congestion has become the primary problem in transportation. Roads are in a state of waiting in line or even congestion, which seriously affects people's enthusiasm and efficiency of travel. This paper mainly studies the discrete domain path planning method based on the flow data. Taking the traffic flow data based on the highway network structure as the research object, this paper uses the deep learning theory technology to complete the path weight determination process, optimizes the path planning algorithm, realizes the vehicle path planning application for the expressway, and carries on the deployment operation in the highway company. The path topology is constructed to transform the actual road information into abstract space that the machine can understand. An appropriate data structure is used for storage, and a path topology based on the modeling background of expressway is constructed to realize the mutual mapping between the two. Experiments show that the proposed method can further reduce the interpolation error, and the interpolation error in the case of random missing is smaller than that in the other two missing modes. In order to improve the real-time performance of vehicle path planning, the association features are selected, the path weights are calculated comprehensively, and the traditional path planning algorithm structure is optimized. It is of great significance for the sustainable development of cities.