The Reliability Model of Artificial Monitoring on the Anomalous Event in Expressway Tunnels and Monte Carlo Simulation

Artificial monitoring remains to be a major way to detect anomalous events in expressway tunnels. To estimate the reliability of artificial monitoring on anomalous events in expressway tunnels, the video surveillance and mobile inspection based reliability models of artificial monitoring on the anomalous event in the expressway tunnel were built, and Monte Carlo method was applied to calculate the probability and mean time to detect the anomalous event at the specific time. The results showed that the Monte Carlo method could simulate video surveillance and mobile inspection, and obtain the probability distribution and mean time of detecting anomalous events. The mean time to spot the anomalous event was in reverse relation with the number of inspectors, the time of mobile inspection, and the reliability probability of the monitoring pre-warning system in tunnels and was in positive relationships with the departure interval. Combined with the actual operation cost, the model serves as a basis for the artificial monitoring package

3D Textile Reconstruction based on KinectFusion and Synthesized Texture

Purpose The purpose of this paper is to present a novel framework of reconstructing the 3D textile model with synthesized texture. Design/methodology/approach First, a pipeline of 3D textile reconstruction based on KinectFusion is proposed to obtain a better 3D model. Second, “DeepTextures” method is applied to generate new textures for various three-dimensional textile models. Findings Experimental results show that the proposed method can conveniently reconstruct a three-dimensional textile model with synthesized texture. Originality/value A novel pipeline is designed to obtain 3D high-quality textile models based on KinectFusion. The accuracy and robustness of KinectFusion are improved via a turntable. To the best of the authors’ knowledge, this is the first paper to explore the synthesized textile texture for the 3D textile model. This is not only simply mapping the texture onto the 3D model, but also exploring the application of artificial intelligence in the field of textile. </jats:sec

Personalized 3D mannequin reconstruction based on 3D scanning

Purpose Currently, a common method of reconstructing mannequin is based on the body measurements or body features, which only preserve the body size lacking of the accurate body geometric shape information. However, the same human body measurement does not equal to the same body shape. This may result in an unfit garment for the target human body. The purpose of this paper is to propose a novel scanning-based pipeline to reconstruct the personalized mannequin, which preserves both body size and body shape information. Design/methodology/approach The authors first capture the body of a subject via 3D scanning, and a statistical body model is fit to the scanned data. This results in a skinned articulated model of the subject. The scanned body is then adjusted to be pose-symmetric via linear blending skinning. The mannequin part is then extracted. Finally, a slice-based method is proposed to generate a shape-symmetric 3D mannequin. Findings A personalized 3D mannequin can be reconstructed from the scanned body. Compared to conventional methods, the method can preserve both the size and shape of the original scanned body. The reconstructed mannequin can be imported directly into the apparel CAD software. The proposed method provides a step for digitizing the apparel manufacturing. Originality/value Compared to the conventional methods, the main advantage of the authors’ system is that the authors can preserve both size and geometry of the original scanned body. The main contributions of this paper are as follows: decompose the process of the mannequin reconstruction into pose symmetry and shape symmetry; propose a novel scanning-based pipeline to reconstruct a 3D personalized mannequin; and present a slice-based method for the symmetrization of the 3D mesh. </jats:sec

Purification and comparison of enzymatic properties of endogenous transglutaminase between silver carp and black carp

Objective: This study aimed to investigate the differences in enzymatic properties of endogenous transglutaminase （TGase） in silver carp and black carp. Methods: STG and BTG were purified from the muscle of silver carp and black carp, respectively, by 80% ammonium sulfate precipitation, Q-Sepharose FF, and Sephacryl S-200 HR chromatographies. Two enzymes were analyzed for relative molecular weights, peptide sequences, secondary structures, optimal reaction conditions, and thermal inactivation kinetics. Results: The purified STG and BTG showed similar relative molecular weights, of which the enzyme activities were 14.34 U/mg and 12.67 U/mg, respectively. Both enzymes showed differences in peptide sequences. The secondary structures of them were mainly the β-fold, though the content of β-fold in STG was slightly higher than that of BTG. The optimal temperatures for STG and BTG were both 50 ℃, and the optimal pH values were 8.0 and 7.5, respectively. The enzymes required Ca2+ up to 1 mmol/L for full activation. The activities of STG and BTG were enhanced by DTT, whereas PMSF, NH4Cl, NEM, EDTA, Cu2+, Ba2+, Zn2+, and Mg2+ showed inhibitory effects. When the temperature was 37~50 ℃, the passivations of STG and BTG by thermal treatment conformed to the first-order exponential decay kinetics with similar values of Ea. Conclusion: The primary and secondary structures of STG and BTG exhibited obvious differences, yet they still exhibited similar properties in terms of optimal reaction conditions and thermal inactivation kinetics

EXPERIMENTAL CHARACTERIZATION AND MULTISCALE MODELING OF THE DEFORMATION AND FRACTURE BEHAVIOR OF CARBON NANOFILLER REINFORCED POLYMER NANOCOMPOSITES

Carbon based nanofillers such as carbon nanotube (CNT), carbon nanofiber (CNF), and graphite nanoplatelet (GNP), which possess superior strength and stiffness, have emerged as new potential reinforcement materials for developing advanced composites. Despite the many research efforts that have been devoted to the area of nanocomposites, a comprehensive understating of this new material system is still lacking as nearly all of them have been focused on a specific type of composite or material property. The overall objective of this research is to gain a comprehensive and coherent understanding of the mechanical characteristics and reinforcement mechanisms of CNT, CNF, and GNP and their correlation with the performance of the resultant composites.To achieve the research objective, the mechanical behavior of a High Density Polyethylene (HDPE)-based composite reinforced with CNT, CNF, and GNP is processedand characterized first. The load spectrum spreads over both tension and compression for a wide range of strain rates, 10-2-104/s. This part of the work establishes a data base for this research. Following the experiment work, molecular dynamics simulations are used to gain insights on the mechanical characteristics and reinforcement mechanisms of different types of carbon nanofillers. Finally, a mesoscale finite element study is performed to understand the correlation between the reinforcement mechanism and the overall performance of the resultant composites.It is found that the properties of the nanofillers that make the most significant differences are their interfacial properties and the shapes. For perfect bonding, CNT and CNF perform better than GNP due to their larger aspect ratio and longer critical length which lead to better load transfer capability. However, for poor bonding, the differences between the reinforcements by fillers diminish. For pristine fillers, CNT and GNP have very poor interfacial strength due to their smooth exterior surface. The interfacial strength of CNF is much stronger due to its serrated surface which leads to better mechanical interlocking between filler and matrix. Thus, without any surface treatment, CNF-composites perform better than others due to its better stress transfer capability. The better surface treatments, the closer the performance of the composites to that predicted by the perfect bonding

Mechanical characterization of carbon nano-fiber reinforced high density polyethylene

The superior mechanical properties and relatively low price have made carbon nanofibers (CNFs) an excellent candidate for the reinforcement material in polymeric nanocomposites. As in all the composite materials, the strength of the interface between the matrix and reinforcement material plays an important role on the overall performance of the composites. The objective of this study is to characterize the compressive mechanical properties of polymer nanocomposites with high density polyethylene (HDPE) as the matrix and carbon nanofiber as the reinforcement material. Three different types of nanofibers were used, one was pristine CNFs and the other two were silanized CNFs with different interfacial treatments. For each type, three different concentrations were used, namely, 0.5 wt%, 1 wt% and 3 wt%. The compressive mechanical behaviors under quasi-static and dynamic loadings at strain rates of 0.01/sec and 5000/sec respectively were characterized. The former was done on a screw-driven Instron test machine and the latter was tested on a modified Split-Hopkinson Pressure Bar (SHPB) system which was originally designed for testing hard materials. The modified system was demonstrated to be capable of testing soft materials such as polymers. The experimental results indicated that the addition of CNFs in polymers did not seem to show appreciable improvement of the compressive properties of the composites. This could be due to the low concentration of the reinforcement material used and/or the inability of the fibers to support compression load

Identification of Urban Functional Areas Based on POI Data: A Case Study of the Guangzhou Economic and Technological Development Zone

Functional areas are the basic spatial units in which cities or development zones implement urban plans and provide functions. Internet map big data technology provides a new method for the identification and spatial analysis of functional areas. Based on the POI (point of interest) data from AMap (a map application of AutoNavi) from 2017, this paper proposes an urban functional areas recognition and analysis method based on the frequency density and the ratio of POI function types. It takes the Guangzhou Economic and Technological Development Zone as a case study to analyze the main function and spatial distribution characteristics of the detailed functional areas. The research shows the following: (1) The POI frequency density index and the function type ratio can effectively distinguish the functions of the grid units and analyze the spatial distribution characteristics of a complex functional area. (2) The single functional area is the most common area type in the Guangzhou Economic and Technological Development Zone. The largest proportion of all areas is allocated to traditional manufacturing industry functional areas, followed by high-tech enterprises, catering and entertainment, real estate, and education and health care, in descending order. The smallest proportion is allocated to finance and insurance functional areas. (3) The current layout of the functional areas in the Guangzhou Economic and Technological Development Zone conforms to the overall requirements and planning objectives of the central and local government. The layout and agglomeration of different blocks within the economic development zone are consistent with local industry&rsquo;s target orientation and development history

Internationalization and Organizational Resilience to COVID-19 Crisis: The Moderating Effect of Digitalization

Organizational resilience is a company’s ability to quickly recover and adapt when it encounters sudden and unexpected challenges. Our study looks at how a company’s level of international involvement before such challenges can influence its resilience, particularly when faced with the global disruptions caused by the COVID-19 pandemic. We also examine whether a company’s prior investment in digital technologies can help soften any negative impacts. From January 20 to June 10, 2020, we analyzed data from 2,363 Chinese companies that are traded on stock exchanges. We assessed their organizational resilience based on how their stock prices fluctuated and how quickly they returned to their pre-shock performance levels. Our findings indicate that companies with more international activities before the pandemic were generally slower to recover. However, companies with advanced digital capabilities before the pandemic demonstrated greater resilience, overcoming the negative repercussions more effectively. This research contributes new insights to the understanding of how international business activities affect a company’s ability to withstand and bounce back from global crises. Additionally, it underscores the importance of digitalization in enhancing organizational resilience

Information Extraction and Spatial Distribution of Research Hot Regions on Rocky Desertification in China

Rocky desertification is an important type of ecological degradation in southwest of China. The author uses the web crawler technology and obtained 9345 journal papers related to rocky desertification from 1950s to 2016 in China. The authors also constructed a technological process to extract research hot regions on rocky desertification and then a spatial distribution map of research hot regions on rocky desertification was formed. Finally, the authors compared the spatial distribution using the sensitivity map of rocky desertification to find the differences between two maps. The study shows that: (1) rocky desertification research hot regions in China are mainly distributed in Guizhou, Yunnan and Guangxi, especially in Bijie, Liupanshui, Guiyang, Anshun, Qianxinan Autonomous Prefecture, QianNan Autonomous Prefecture, Qiandongnan Autonomous Prefecture in Guizhou Province, Hechi, Baise, Nanning, Guilin in Guangxi Zhuang Autonomous Region and Zhaotong in Yunnan Province. (2) The research hot regions on rocky desertification have good spatial consistency with the sensitivity regions of rocky desertification. At the prefecture level, the overlap rate of the two regions reached 85%. Because of the influence of topography, vegetation coverage, population distribution, traffic accessibility and other factors, there were regions that consisted of combinations of high sensitivity but low research popularity regarding rocky desertification; these sites included Qionglai Mountain-Liangshan Area of Sichuan, Wushan-Shennongjia Area of Hubei, Hengduan Mountain Area of western Yunnan and Dupangling Area of southern Hunan. (3) The research hot regions and sensitive regions cannot be matched completely in time, space and concept. Therefore, we can use their spatial distribution differences to improve the pertinence of planning, governance and study of rocky desertification