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Majority of the existing direct slicing methods have generated precise slicing contours from different surface representations, they do not carry any interior information. Whereas, heterogeneous solids are highly preferable for designing and manufacturing sophisticated models. To directly slice heterogeneous solids for additive manufacturing (AM), this study aims to present an algorithm using octree-based subdivision and trivariate T-splines.

This paper presents a direct slicing algorithm for heterogeneous solids using T-splines, which can be applied to AM based on the fused deposition modeling (FDM) technology. First, trivariate T-splines are constructed using a harmonic field with the gradient direction aligning with the slicing direction. An octree-based subdivision algorithm is then used to directly generate the sliced layers with heterogeneous materials. For FDM-based AM applications, the heterogeneous materials of each sliced layer are discretized into a finite number of partitions. Finally, boundary contours of each separated partition are extracted and paired according to the rules of CuraEngine to generate the scan path for FDM machines equipped with multi-nozzles.

The experimental results demonstrate that the proposed algorithm is effective and reliable, especially for solid objects with multiple materials, which could maintain the model integrity throughout the process from the original representation to the final product in AM.

Directly slicing heterogeneous solid using trivariate T-splines will be a powerful supplement to current technologies in AM.

T-spline is the latest powerful modeling tool in the field of computer-aided design. It has all the merits of non-uniform rational B-spline (NURBS) whilst resolving some flaws in it. This work applies T-spline surfaces to additive manufacturing (AM). Most current AM products are based on Stereolithograph models. It is a kind of discrete polyhedron model with huge amounts of data and some inherent defects. T-spline offers a better choice for the design and manufacture of complex models.

In this paper, a direct slicing algorithm of T-spline surfaces for AM is proposed. Initially, a T-spline surface is designed in commercial software and saved as a T-spline mesh file. Then, a numerical method is used to directly calculate all the slicing points on the surface. To achieve higher manufacturing efficiency, an adaptive slicing algorithm is applied according to the geometrical properties of the T-spline surface.

Experimental results indicate that this algorithm is effective and reliable. The quality of AM can be enhanced at both the designing and slicing stages.

The T-spline and direct slicing algorithm discussed here will be a powerful supplement to current technologies in AM.

This paper aims to present a novel hybrid time integration approach for efficient numerical simulations of multiscale problems involving interactions of electromagnetic fields with fine structures.

The entire computational domain is discretized with a coarse grid and a locally refined subgrid containing the tiny objects. On the coarse grid, the time integration of Maxwell’s equations is realized by the conventional finite-difference technique, while on the subgrid, the unconditionally stable Krylov-subspace-exponential method is adopted to breakthrough the Courant–Friedrichs–Lewy stability condition.

It is shown that in contrast with the conventional finite-difference time-domain method, the proposed approach significantly reduces the memory costs and computation time while providing comparative results.

An efficient hybrid time integration approach for numerical simulations of multiscale electromagnetic problems is presented.

Compared with traditional industrial processing technologies of sulfurized isobutylene, the one-step synthesis method involving high pressure is more environment-friendly and leads to better product performance. However, products from various sources perform differently because of the difference in the contents of their components. Therefore, the purpose of this study was to investigate the relationships between sulfide components of high-pressure sulfurized isobutylene and load carrying capacities.

A typical high-pressure sulfurized isobutylene was chosen, and the structure and contents of its sulfide components were characterized using gas chromatography-mass spectrometry and gas chromatography (GC). Extreme-pressure properties of the sample at different concentrations were evaluated using a four-ball tribometer.

A multiple regression equation model was established, and tert-butyl trisulfide made the greatest contribution to the extreme-pressure properties according to the equation coefficient, while tert-butyl tetrasulfide had no effect. The results can be attributed to the fact that the structure of a sulfurized additive having an impact is application-specific.

A precise and fast way to predict weld load values of high-pressure sulfurized isobutylene by using GC and the established equation model were successfully developed. Moreover, the empirical equation shows the relationships between sulfide component concentrations and load carrying capacities.

The purpose of this study is to gather insights into digital consumer behaviour related to Chinese restaurents by examining visual contents on Tripadvisor platform.

Using the deep learning approach, this research assessed consumer-posted online content of dining experiences by implementing image analysis and clustering. Text mining using word cloud analysis revealed the most frequently repeated keywords.

First, 4,000 photos of nine Chinese restaurants posted on Tripadvisor’s website were analyzed using image recognition via Inception V3 and Google’s deep learning network; this revealed 12 hierarchical image clusters. Then, an open-questionnaire survey of 125 Chinese respondents investigated consumers’ information needs before visiting a restaurant and after purchasing behavior (motives to share).

This study contributes to culinary marketing development by introducing a new analysis methodology and demonstrating its application by exploring a wide range of keywords and visual images published on the internet.

This research extends and contributes to the literature regarding visual user-generated content in culinary tourism.

Labor participation has always been a hot topic in academic circle and a vital label in the process of China's economic and social development. Therefore, the purpose this paper is to use CGSS 2015 data, starting from labor participation, and make a comparably comprehensive analysis of the influencing factors of subjective well-being of females.

By conducting probit regressions, the paper reveals the impact of labor participation and socio-demographic conditions on the subjective well-being of females in Mainland China.

First, the authors’ findings turn out that urban women do have a higher level of women's subjective well-being when compared to rural women. Second, educational attainment has a significantly positive effect on subjective well-being only in urban areas, while having teen children is only statistically significant for rural residents. Third, the overall impact of employment conditions on women's subjective well-being is reduced due to the transition of gender conceptions. In all, the evaluation of subjective well-being of females is reshaped by the overwhelming transition of society in Mainland China.

There remain some limitations of this study. First, because CGSS 2015 data are the only data analyzed here, it is hard and inaccurate to compare the differences between this result and previous outcomes conducted by other scholars using CGSS 2005, 2010 and 2013 data. Second, the categories of employment conditions are not detailed, and thus it adds burden to further analysis. For future studies, a wider range of data should be taken into account and provide data support to have a convincing comparison at different times. The social background of diverse employment conditions could be discussed in-depth as well.

Based on the early literature, this paper is intended to use Chinese data to study the major factors affecting Chinese female labor participation in Mainland China and also discuss the implications in practice.

The calculation of the crack width is necessary for the design of prestressed concrete (PC) members. The purpose of this paper is to develop a numerical model based on the bond-slip theory to calculate the crack width in PC beams.

Stress calculation method for common reinforcement after beam crack has occurred depends on the difference in the bonding performance between prestressed reinforcement and common reinforcement. A numerical calculation model for determining the crack width in PC beams is developed based on the bond-slip theory, and verified using experimental data. The calculation values obtained by the proposed numerical model and code formulas are compared, and the applicability of the numerical model is evaluated.

The theoretical analysis and experimental results verified that the crack width of PC members calculated based on the bond-slip theory in this study is reasonable. Furthermore, the stress calculation method for the common reinforcement is verified. Compared with the model calculation results obtained in this study, the results obtained from code formulas are more conservative.

The numerical calculation model for crack width proposed in this study can be used by engineers as a reference for calculating the crack width in PC beams to ensure the durability of the PC member.

This paper aims to report the influence of hexamethylenetetramine (HMTA) on phosphate coatings formed on AZ31 magnesium alloys.

These phosphate coatings were obtained by immersing magnesium alloys in phosphate baths with HMTA. The morphology and composition of the phosphate coatings were investigated via scanning electron microscopy, energy dispersive spectrometry and X-ray diffraction.

The phosphate coatings were mainly composed of CaHPO₄·2H₂O. The HMTA concentration in the phosphate bath influenced the crystallization and corrosion resistance of the phosphate coating.

The polarization curve shows that the anti-corrosion qualities of the phosphate coating were optimal when the HMTA concentration was 1.0 g/L in the phosphate bath. Electrochemical impedance spectroscopy (EIS) shows that the electrochemical impedances increased gradually when the HMTA concentration varied from 1.0 to 3.0 g/L.

The current popular image processing technologies based on convolutional neural network have the characteristics of large computation, high storage cost and low accuracy for tiny defect detection, which is contrary to the high real-time and accuracy, limited computing resources and storage required by industrial applications. Therefore, an improved YOLOv4 named as YOLOv4-Defect is proposed aim to solve the above problems.

On the one hand, this study performs multi-dimensional compression processing on the feature extraction network of YOLOv4 to simplify the model and improve the feature extraction ability of the model through knowledge distillation. On the other hand, a prediction scale with more detailed receptive field is added to optimize the model structure, which can improve the detection performance for tiny defects.

The effectiveness of the method is verified by public data sets NEU-CLS and DAGM 2007, and the steel ingot data set collected in the actual industrial field. The experimental results demonstrated that the proposed YOLOv4-Defect method can greatly improve the recognition efficiency and accuracy and reduce the size and computation consumption of the model.

This paper proposed an improved YOLOv4 named as YOLOv4-Defect for the detection of surface defect, which is conducive to application in various industrial scenarios with limited storage and computing resources, and meets the requirements of high real-time and precision.