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People usually try to avoid uncertainty. Recently, however, uncertainty has become an emerging marketing tool in the hedonic product industry. In the case of blind box consumption, for example, the consumers become addicted to the uncertainty created by businesses, leading to repeat purchases and even indulgences. Previous research has, yet, to focus on the impact of uncertainty on indulgence and the role of emotions.

This paper constructs and validates a chain mediation model of uncertainty triggering indulgent consumption based on the information gap theory, positive emotion theory and uncertainty resolution theory and examines the difference between resolved and unresolved uncertainty. This study also explores differences in the impact of whether uncertainty is resolved on emotions. The uncertainty-resolved group elicited a more positive emotional response than the uncertainty-unresolved group, leading to a more indulgent consumption.

The results of three studies show that uncertainty influences indulgent consumption through curiosity and positive emotion, and that curiosity and positive emotion play separate and chain mediating roles between uncertainty and indulgent consumption, respectively. We validate our central hypothesis with questionnaires among blind box consumer groups, examining the moderating role of perceived luck and risk preferences.

The findings shed new light on firms' use of uncertainty to promote consumer purchases.

Laser cladding has been used in the field of repairing damaged parts of machine tools due to its advantages of less processing restrictions and easy formation of a good metallurgical bond with the base material. However, the mechanical properties of the coating sometimes cannot meet the process requirements. Therefore, the purpose of this paper is to prepare coatings with high microhardness and flexural strength.

The YCF102 alloy powder was mixed with different contents of Co and tested for laser cladding on AISI 1045 substrate under the same process parameters. The main phase composition of the coating was revealed by the XRD results. The main chemical composition of the coating was determined by the SEM and EDS results. In addition, the effect of Co content on the microstructure, microhardness and flexural strength of the coatings was investigated.

The results show that when the Co content is 2 wt% and 4 wt%, Co does not form compounds with other elements, but is uniformly distributed in the coating. And when the Co content is 6 wt% and 8 wt%, the Co reacts with Fe in the coating and generates Co₃Fe₇ in situ. The increase in Co did not result in a monotonic change in microhardness, but significantly improved the flexural strength and the flatness of the microstructure of the coating. When the Co content of the mixed powder is 8 wt%, the coating has high microhardness and flexural strength.

Co/YCF102 composite coating with high microhardness and flexural strength was prepared. This paper provides a theoretical and practical basis for research in the area of repairing damaged parts of machine tools by laser cladding.

This study aims to discuss the effect of carbon fiber on the electric-respone of shape memory epoxy property. Epoxy (EP) is a typical excellent thermosetting shape memory polymer (SMP). To enrich the shape memory epoxy (SMEP) responsive mode, the carbon fiber fabric-reinforced SMEP composites were prepared, and the mechanical properties and the electric- and light-responsive shape memory effect of the composites were investigated and confirmed.

The carbon fiber fabric/SMEP composites were prepared via a dipping method. The carbon fiber fabric was dipped into the waterborne epoxy emulsion and dried at room temperature and then post-cured in the oven at 120 °C for 2 h. The mechanical properties and the multi-responsive shape memory properties of the composites were tested and confirmed via tensile test instrument, DC electrical source and near-infrared (NIR) laser source control system.

The carbon fiber fabric/SMEP composites showed excellent electric- and light-responsive shape memory effect.

High performance and multi-responsive shape memory materials have always been the goal of the scientists. Carbon fiber fabric and SMEP both consist of a good reputation in the field of composites, and the combination of both would set a solid foundation for getting a high performance and multi-responsive shape memory effect materials, which will enrich the responsive mode and broaden the application of SMEP.

Multi-responsive SMEP composites were prepared from waterborne epoxy and carbon fiber fabric.

The purpose of this paper is to present a transition detector (TD)-based radiation hardened flip-flop (TDRH-FF) for single event upset (SEU).

With SEU recovery and single event transient (SET) detector mechanism, the TDRH-FF can tolerate SEU during hold mode and generate a warning signal for architecture-level recovery during transport mode when input signal contains SET. Evaluation results show that the TDRH-FF outperforms comparable comprehensive performance.

Simulation results show that 1) the mean pulse width of the correction glitches (at full width half maximum) of TDRH-FF is less than 10 ps; 2) the area overhead of TDRH-FF is similar to the EVFERST-FF, BISER-FF and DNURHL-FF; 3) TDRH-FF has the same average power consumption as SETTOF, and moderate PDP and Ps values among these compared FFs.

In this paper, a TD-based TDRH-FF is proposed to solve the problems in the previous design. And the main contributions of the proposed TDRH-FF are summarized: Minimum size transistors are used in the proposed TD which leads to a considerable decrease in area overheads and propagation delay (resulting in an ignorable correction glitch); and compared with other radiation hardened flip-flop, TDRH-FF outperforms comparable comprehensive performance.

The purpose of this paper is to study the wire and arc additive manufacturing (WAAM) method and path planning algorithm of truss structure parts, to realize the collision-free rapid prototyping of truss structures with complex characteristics.

First, a point-by-point stacking strategy is proposed based on the spot-welding mode of cold metal transfer welding technology. A force analysis model of the droplet is established, which can be used to adjust the posture of the welding torch and solve the collapse problem in the WAAM process of the truss structure. The collision detection model is developed to calculate the interference size between the truss structure and the welding torch, which is used to control the offset of the welding torch. Finally, the ant colony algorithm has been used to optimize the moving path of welding torch between truss with considering the algorithm efficiency and collision avoiding and the efficiency of the algorithm is improved by discretizing the three-dimensional workspace.

A series of experiments were conducted to prove the validity of the proposed methods. The results show that the wire feeding speed, welding speed are the important parameters for controlling the WAAM process of truss parts. The inclination angle of the welding torch has an important influence on the forming quality of the truss.

The force analysis model of truss structure in the WAAM process is established to ensure the forming quality and a collision-free path planning algorithm is proposed to improve forming efficiency.

Achieving project objectives in constructionprojects such as time, cost and quality is a challenging task. Minimizing project cost often results in additional project duration and might jeopardize quality, and minimizing project duration often results in additional cost and might jeopardize quality. Also, increasing construction quality often results in additional cost and time. The purpose of this paper is to identify and analyze trade-offs among the project objectives of time, cost and quality.

The optimization model adopted a quantitative research method and is developed in two main steps formulation step that focuses on identifying model decision variables and formulating objective functions, and implementation step that executes the model computations using multi-objective optimization of Non-Dominated Sorting Genetic Algorithms to identify the aforementioned trade-offs, and codes the model using python. The model performance is verified and tested using a case study of construction project consisting of 20 activities.

The model was able to show practical and needed value for construction managers by identifying various trade-off solutions between the project objectives of time, cost and quality. For example, the model was able to identify the shortest project duration at 84 days while keeping cost under $440,000 and quality higher than 85 percent. However, with an additional budget of $20,000 (4.5 percent increase), the quality can be increased to 0.935 (8.5 percent improvement).

The present research work is limited to project objectives of time, cost and quality. Future expansion of the model will focus on additional project objectives such as safety and sustainability. Furthermore, new optimization models can be developed for construction projects with repetitive nature such as roads, tunnels and high rise buildings.

The present model advances existing research in planning construction projects efficiently and achieving important project objectives. On the practical side, the optimization model will support the construction industry by allowing construction managers to identify the highest quality to deliver a construction project within specified budget and duration, lowest cost for specified duration and quality or shortest duration for specified budget and quality.

The present model introduces new and innovative method of increasing working hours per day and number of working days per shift while analyzing labor working efficiency and overtime rate to identify optimal trade-offs among important project objectives of time, cost and quality.

For a better understanding of the preferences and differences of young consumers in emerging wine markets, this study aims to propose a clustering method to segment the super-new generation wine consumers based on their sensitivity to wine brand, origin and price and then conduct user profiles for segmented consumer groups from the perspectives of demographic attributes, eating habits and wine sensory attribute preferences.

We first proposed a consumer clustering perspective based on their sensitivity to wine brand, origin and price and then conducted an adaptive density peak and label propagation layer-by-layer (ADPLP) clustering algorithm to segment consumers, which improved the issues of wrong centers' selection and inaccurate classification of remaining sample points for traditional DPC (DPeak clustering algorithm). Then, we built a consumer profile system from the perspectives of demographic attributes, eating habits and wine sensory attribute preferences for segmented consumer groups.

In this study, 10 typical public datasets and 6 basic test algorithms are used to evaluate the proposed method, and the results showed that the ADPLP algorithm was optimal or suboptimal on 10 datasets with accuracy above 0.78. The average improvement in accuracy over the base DPC algorithm is 0.184. As an outcome of the wine consumer profiles, sensitive consumers prefer wines with medium prices of 100–400 CNY and more personalized brands and origins, while casual consumers are fond of popular brands, popular origins and low prices within 50 CNY. The wine sensory attributes preferred by super-new generation consumers are red, semi-dry, semi-sweet, still, fresh tasting, fruity, floral and low acid.

Young Chinese consumers are the main driver of wine consumption in the future. This paper provides a tool for decision-makers and marketers to identify the preferences of young consumers quickly which is meaningful and helpful for wine marketing.

In this study, the ADPLP algorithm was introduced for the first time. Subsequently, the user profile label system was constructed for segmented consumers to highlight their characteristics and demand partiality from three aspects: demographic characteristics, consumers' eating habits and consumers' preferences for wine attributes. Moreover, the ADPLP algorithm can be considered for user profiles on other alcoholic products.

The precise segmentation of brain tumors is the most important and crucial step in their diagnosis and treatment. Due to the presence of noise, uneven gray levels, blurred boundaries and edema around the brain tumor region, the brain tumor image has indistinct features in the tumor region, which pose a problem for diagnostics. The paper aims to discuss these issues.

In this paper, the authors propose an original solution for segmentation using Tamura Texture and ensemble Support Vector Machine (SVM) structure. In the proposed technique, 124 features of each voxel are extracted, including Tamura texture features and grayscale features. Then, these features are ranked using the SVM-Recursive Feature Elimination method, which is also adopted to optimize the parameters of the Radial Basis Function kernel of SVMs. Finally, the bagging random sampling method is utilized to construct the ensemble SVM classifier based on a weighted voting mechanism to classify the types of voxel.

The experiments are conducted over a sample data set to be called BraTS2015. The experiments demonstrate that Tamura texture is very useful in the segmentation of brain tumors, especially the feature of line-likeness. The superior performance of the proposed ensemble SVM classifier is demonstrated by comparison with single SVM classifiers as well as other methods.

The authors propose an original solution for segmentation using Tamura Texture and ensemble SVM structure.

The purpose of this paper is to design and develop a rotary three-dimensional (3D) printer for curved layer fused deposition modeling (CLFDM), and discuss some technical challenges in the development.

Some technical challenges include, but are not limited to, the machine design and control system, motion analysis and simulation, workspace and printing process analysis, curved layer slicing and tool path planning. Moreover, preliminary experiments are carried out to prove the feasibility of the design.

A rotary 3D printer for CLFDM has been designed and developed. Moreover, this printer can function as a polar 3D printer for flat layer additive manufacturing (AM). Compared with flat layer AM, CLFDM weakens the staircase effect and improves geometrical accuracy and mechanical properties. Hence, CLFDM is more suitable for parts with curved surfaces.

Double extruders have brought improved build speed. However, this paper is restricted to complex process planning and mechanical structures, which may lead to collisions during printing. Meanwhile, the rotation range of the nozzle is limited by mechanical structures, affecting the manufacturing capability of complex curved surfaces.

A novel rotary 3D printer, which has four degrees of freedom and double extruders, has been designed and manufactured. The investigation on the prototype has proved its capability of CLFDM. Besides, this rotary 3D printer has two working modes, which brings the possibility of flat layer AM and CLFDM.

The purpose of this paper is to analyze the reasons that plagiarism in online literature is so hard to control in China, and it will conclude with a clear solution for the future.

This paper begins its research with the statistics and analysis of plagiarism data and a review of expert interviews regarding online literature publishing. All of these data materials were collected from anti-plagiarism platforms, online literature websites, news report websites and judiciary office websites.

The paper provides empirical insights into why the plagiarism is so rampant in the publishing of online literature in China. It suggests that the current task of controlling network literature plagiarism is arguably created by the literary production platform, which leads to the problem of the validity of the “self-monitoring model.” In fact, controlling plagiarism must be emphasized by means of external monitoring, because strict supervision and various external punitive measurements for committing plagiarism can force literature-generating platforms to strengthen their own internal monitoring.

Online plagiarism occurs almost constantly, but it rarely results in court cases over copyright because of the lack of a robust copyright ecology in China. This paper considers large amounts of data and cases from self-publishing media platforms.

The paper includes implications for the development of plagiarism management in online literature publishing from the publishing Association, media and government.

This paper suggests to online literature users that plagiarism will be controlled when certain active measures against it are taken. The authors hope that this view will promote the development of original online literature.

This paper points out that China must strengthen supervision that comes from outside the online literature generate platforms to control the current rampant plagiarism that occurs on these platforms.