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This study aims to test the possible correlation between the letter height-to-width ratio and consumers’ perception of cuteness.

Through the design of three groups of experimental questionnaires, this paper carried out experiments on subjects with different professional backgrounds.

The result shows that perceived cuteness is only beneficial for consumers who adopt communal relationship (rather than exchange relationship) with the brand. Compared to consumers who adopt communal relationship with brands, letters of lower height-to-width ratio are perceived as cuter and thus more preferable than thinner ones, whereas for consumers who adopt exchange relationship with brands, thinner letters are preferred.

To rule out interference, this study focuses only on the height-to-width ratio of the letters. In the future, researchers can pay more attention to the mobility of brand relationships, consumers’ reading strategy and logos’ visual elements that influence consumers’ brand perception (besides height-to-width ratio).

The research reminds scholars that the height-to-width ratio of letters/logos is not only of aesthetic value but also imposes a great impact on consumer perception. And the result of this research explains the contradiction in consumers’ preference for wide vs thin letter shapes and provides evidence for the interaction between brand relationship norms and letter preferences.

To the best of the authors’ knowledge, this research is the first to explore the influence of letter height-to-width ratio in marketing.

The purpose of this paper is to examine the contradictory effect of coldness in advertisement and brand logo design.

The authors conduct four experiments to test the influences of coldness on consumers’ attitude. In the first two experiments, the researchers use real/virtual brand names to test the moderating effect of brand status and customer power; in Study 3, the researchers test the moderating effect of autonomy; while in the last experiment, the findings in the previous experiments are extended to explain similar effect of cold/warm brand logo designs.

This research finds that coldness also brings benefit to brands under certain circumstances. More specifically, cold endorsers/brand logo designs are only beneficial for brands of high (vs low) status, and can only attract consumers who experience high power (vs low power). Such effects are mediated by consumers’ perceived brand autonomy.

This research urges the managers to analyze the characteristics of the brand and its target consumer. It also points out that the effectiveness of warm/cold representative derives from the customer perceived brand autonomy.

The authors’ contributions to the literature are as follows. First, this research examines the relationship between coldness and autonomy, which enables us to expand the findings to various contexts; second, this research expands the horizon of autonomy theory by identifying customer power and brand status as its moderators.

The purpose of this study is to identify the factors determining collaborative innovation effect of manufacturing firms in emerging economies.

Based on a survey of 1,206 Chinese manufacturing firms and using structural equation modelling, this study explores the factors determining the effect of collaborative innovation among manufacturing firms (namely, internal capabilities, government policies, collaboration mechanisms and social networks) and examines the relationship between collaborative innovation effect and innovation performance.

The study finds that there are significantly positive relationships between firms’ internal capabilities, government policies, collaboration mechanisms and social networks and collaborative innovation effect among firms.

These findings reveal that policymakers should create an effective institutional culture and market environment to facilitate firms’ collaborative innovation.

This paper draws on the resource-based view of firms and contributes to understanding of how the development of factors determining firms’ collaborative innovation effect can improve innovation performance. This study extends established frameworks on collaborative innovation in relation to four dimensions, namely, firms’ internal capabilities, government policies, collaboration mechanisms and social networks, uniquely identifying the limits of specific dimensions. Moreover, this study addresses government policies and “Guanxi culture” specific to China that provide new insights into how firms’ collaborative innovation is improved from the perspectives of business–governmental relations and social networks.

Compared with traditional methods relying on manual teaching or system modeling, data-driven learning methods, such as deep reinforcement learning and imitation learning, show more promising potential to cope with the challenges brought by increasingly complex tasks and environments, which have become the hot research topic in the field of robot skill learning. However, the contradiction between the difficulty of collecting robot–environment interaction data and the low data efficiency causes all these methods to face a serious data dilemma, which has become one of the key issues restricting their development. Therefore, this paper aims to comprehensively sort out and analyze the cause and solutions for the data dilemma in robot skill learning.

First, this review analyzes the causes of the data dilemma based on the classification and comparison of data-driven methods for robot skill learning; Then, the existing methods used to solve the data dilemma are introduced in detail. Finally, this review discusses the remaining open challenges and promising research topics for solving the data dilemma in the future.

This review shows that simulation–reality combination, state representation learning and knowledge sharing are crucial for overcoming the data dilemma of robot skill learning.

To the best of the authors’ knowledge, there are no surveys that systematically and comprehensively sort out and analyze the data dilemma in robot skill learning in the existing literature. It is hoped that this review can be helpful to better address the data dilemma in robot skill learning in the future.

To maintain the bottom line of food import risk in China, this paper proposes a novel risk state evaluation model based on bottom-line thinking after analyzing the decision-making ideas embedded in the bottom-line thinking method.

First, the order relation analysis method (G1 method) and Laplacian score (LS) are applied to calculate the constant weights of indexes. Then, the worst-case scenario of food import risk can be estimated to strive for the best result, so the penalty state variable weight function is introduced to obtain variable weights of indexes. Finally, the study measures the risk state of China's food import from the overall situation using the set pair analysis (SPA) method and identifies the key factors affecting food import risk.

The risk states of food supply in eight countries are in the state of average potential and partial back potential as a whole. The results indicate that China's food import risks are at medium and upper-medium risk levels in most years, fluctuating slightly from 2010 to 2020. In addition, some factors are diagnosed as the primary control objects for holding the bottom line of food import risk in China, including food output level, food export capacity, bilateral relationship and political risk.

This paper proposes a novel risk state evaluation model following bottom-line thinking for food import risk in China. Besides, SPA is first applied to the risk evaluation of food import, expanding the application field of the SPA method.

This paper aims to investigate the relationships between empowering leadership, basic psychological needs satisfaction, work-related well-being, and project citizenship behavior.

Drawing upon the self-determination theory (SDT), a conceptual model was developed and then empirically tested using a cross-sectional survey of 435 project members in Chinese construction projects.

The results fully support the research hypotheses proposed in the study, illustrating the positive impacts of empowering leadership on work-related well-being and project citizenship behavior, the mediating role of basic psychological needs satisfaction, and the positive association between work-related well-being and project citizenship behavior.

This research determines the utility of empowering leadership in the context of construction projects, especially in enhancing individual outcomes (i.e. work-related well-being and project citizenship behavior). Therefore, construction project managers can apply empowering leadership to meet the basic psychological needs of subordinates to increase project members' work-related well-being and project citizenship behavior.

To our knowledge, the present study first explores the micro-level impacts of empowering leadership in the construction context. Additionally, this study enriches the understanding of the mediating mechanism between empowering leadership and individual outcomes from a self-determination perspective.

This study conducts a comparative study on the performance of reliability assessment methods based on adaptive surrogate models to accurately assess the reliability of automobile components, which is critical to the safe operation of vehicles.

In this study, different adaptive learning strategies and surrogate models are combined to study their performance in reliability assessment of automobile components.

By comparing the reliability evaluation problems of four automobile components, the Kriging model and Polynomial Chaos-Kriging (PCK) have better robustness. Considering the trade-off between accuracy and efficiency, PCK is optimal. The Constrained Min-Max (CMM) learning function only depends on sample information, so it is suitable for most surrogate models. In the four calculation examples, the performance of the combination of CMM and PCK is relatively good. Thus, it is recommended for reliability evaluation problems of automobile components.

Although a lot of research has been conducted on adaptive surrogate-model-based reliability evaluation method, there are still relatively few studies on the comprehensive application of this method to the reliability evaluation of automobile component. In this study, different adaptive learning strategies and surrogate models are combined to study their performance in reliability assessment of automobile components. Specially, a superior surrogate-model-based reliability evaluation method combination is illustrated in this study, which is instructive for adaptive surrogate-model-based reliability analysis in the reliability evaluation problem of automobile components.

The purpose of this paper is to study the effect of micro-nano surface texture on the corrosion resistance of a titanium alloy and investigate the correlation between corrosion resistance and hydrophobicity.

The surface of the Ti₆Al₄V alloy was modified by laser processing and anodizing to fabricate micro-pits, nanotubes and micro-nano surface textures. Afterward, the surface morphology, hydrophobicity and polarization curve of the samples were analyzed by cold field scanning electron microscopy, contact angle measurement instruments and a multi-channel electrochemical workstation.

The micro-nano surface texture can enhance the hydrophobicity of the Ti₆Al₄V surface, which may lead to better drag reduction to ease the friction of implants in vivo. Nevertheless, no correlation existed between surface hydrophobicity and corrosion resistance; the corrosion resistance of samples with nanotubes and high-density samples with micro-nano surface texture was extremely enhanced, indicating the similar corrosion resistance of the two.

The mechanism of micro-dimples on the corrosion resistance of the micro-nano surface texture was not studied.

The density of micro-pits needs to be optimized to guarantee excellent corrosion resistance in the design of the micro-nano surface texture; otherwise, it will not fulfill the requirement of surface modification.

The influence of the micro-nano surface texture on the corrosion resistance, as well as the relationship between hydrophobicity and corrosion resistance of the titanium alloy surface, were systematically investigated for the first time. These conclusions offer new knowledge.

The purpose of this paper is to investigate the preparation and the flexural property of hollow glass microspheres (HGMs) filled resin-matrix composites, which have been widely applied in deep-sea fields.

The composites with different contents of HGMs from 47 to 57 Wt.% were studied. The voids in syntactic foams and their flexural properties were investigated.

The results showed that the voids quantity increased because of the increment of HGM content, whereas the exural strength and the exural modulus decreased. The fracture mechanism of the composites was also investigated by scanning electron microscope, which indicated that the composites failed by the crack extending through the microspheres.

The advantages of HGMs with similar hollow spheres will be further investigated in a future research.

Results demonstrated that the properties of the composite might be tailored for specific application conditions by changing the HGM volume fraction.

The HGM filled resin-matrix composite materials have their unique properties and significant application potential. In this work, the resin-HGM composites were synthesized by mechanically mixing defined quantities of HGMs into epoxy resin, by which a kind of syntactic foams with good flexural properties could be obtained.

The aim of the article was to focus on various peptides identified in the egg and their probable application as novel ingredients in the development of functional food products. Bioactive peptides of egg origin have attracted increasing interest as one of the prominent candidates for development of various health-promoting functional and designer foods.

Traditionally known as a source of highly valuable proteins in human nutrition, eggs are nowadays also considered as an important source of many bioactive peptides which may find wide application in medicine and food production. These specific protein fragments from egg proteins which, above and beyond their nutritional capabilities, have a positive impact on the body’s function or condition by affecting the digestive, endocrine, cardiovascular, immune and nervous systems, and may ultimately influence health.

Several peptides that are released in vitro or in vivo from egg proteins have been attributed to different health effects, including antihypertensive effects, antimicrobial properties, antioxidant activities, anticancer activity, immunomodulating activity, antiadhesive properties and enhancement of nutrient absorption and/or bioavailability. Extensive research has been undertaken to identify and characterize these biologically active peptides of egg origin which has changed the image of egg as a new source of biologically active ingredients for the development of functional foods with specific benefits for human health and treatment and prevention of diseases.

The paper mainly describes the above-stated properties of bioactive peptides derived from egg proteins.