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The purpose of this study is to assist brand and product managers in selecting appropriate ingredient names for environmentally friendly products. It investigates the effects of unfamiliar ingredients on consumers’ evaluations of environmental friendliness and their purchase intentions, based on the cue consistency theory.

Five experimental studies (n = 968) were conducted to achieve the research objectives. Study 1 found that consumers tended to avoid choosing unfamiliar ingredients. Study 2 examined the impact of ingredient familiarity on consumers’ perceived greenness. Study 3 investigated the mediating role of perceived naturalness. Studies 4 and 5, respectively, explored the moderating effects of emphasizing the importance of technology in environmental conservation and product category.

The findings indicate that when environmentally friendly products are labeled with unfamiliar ingredients (vs. familiar), consumers’ perceived greenness and purchase intentions decrease. This effect is mediated by perceived naturalness. Moreover, the negative impact of unfamiliar ingredients is mitigated by emphasizing the importance of technology and the high-tech product category.

This paper reveals the unique role of unfamiliar ingredients in shaping consumer attitudes toward environmentally friendly products. Based on cue consistency theory, it uncovers how unfamiliar ingredients influence the perceived greenness of environmentally friendly products through perceived naturalness. Furthermore, the paper demonstrates the impact of emphasizing the importance of technology (emphasis vs. control) and product category (high-tech vs. low-tech) on consumer attitudes and behaviors toward environmentally friendly products.

Polyaniline (PANI) has garnered attention for its potential applications in anticorrosion fields because of its unique properties. Satisfactory outcomes have been achieved when using PANI as a functional filler in organic coatings. More recently, research has extensively explored PANI-based organic coatings with self-healing properties. The purpose of this paper is to provide a summary of the active agents, methods and mechanisms involved in the self-healing of organic coatings.

This study uses specific doped acids and metal corrosion inhibitors as active and self-healing agents to modify PANI using the methods of oxidation polymerization, template synthesis, nanosheet carrier and nanocontainer loading methods. The anticorrosion performance of the coatings is evaluated using EIS, LEIS and salt spray tests.

Specific doped acids and metal corrosion inhibitors are used as active agents to modify PANI and confer self-healing properties to the coatings. The coatings’ active protection mechanism encompasses PANI’s own passivation ability, the adsorption of active agents and the creation of insoluble compounds or complexes.

This paper summarizes the active agents used to modify PANI, the procedures used for modification and the self-healing mechanism of the composite coatings. It also proposes future directions for developing PANI organic coatings with self-healing capabilities. The summaries and proposals presented may facilitate large-scale production of the PANI organic coatings, which exhibit outstanding anticorrosion competence and self-healing properties.

What’s the flow path of knowledge sharing among members in online health community (OHC)? Exploration of this issue could shed light on mechanisms behind user knowledge sharing and interaction on OHC, but few studies have focused on it. This study is going to address this research gap and to provide richer support for subsequent knowledge management related research.

Based on the core-periphery effect, this study combines content analysis and social network analysis to portray the paths of different types of social support for core and periphery users from social support perspective.

Results reveal that the core users follow a pattern of high-stage and low-stage users with distinct needs, while the path pattern of the edge user group mainly consists support from high-stage to low-stage users. Results show that there is apparent distinction between the paths of emotional and informational support between core and periphery users. For core users, emotional support flows from lower stage users to higher stage users, while informational support follows the opposite direction. For periphery users, the paths of emotional support and informational support are identical, with both flowing from higher stage users to lower stage users.

This study explores the flow paths of information support and emotional support for core and periphery users, and discovers the different patterns of these two types of users, providing theoretical guidance for platform administrators to manage users more efficiently and ensure the sustainable development of the platform.

Field-effect transistor (FET) has excellent electronic properties and inherent signal amplification, and with the development of nanomaterials technology, FET biosensors with nanomaterials as channels play an important role in the field of heavy metal ion detection. This paper aims to review the research progress of silicon nanowire, graphene and carbon nanotube field-effect tube biosensors for heavy metal ion detection, so as to provide technical support and practical experience for the application and promotion of FET.

The article introduces the structure and principle of three kinds of FET with three kinds of nanomaterials, namely, silicon nanowires, graphene and carbon nanotubes, as the channels, and lists examples of the detection of common heavy metal ions by the three kinds of FET sensors in recent years. The article focuses on the advantages and disadvantages of the three sensors, puts forward measures to improve the performance of the FET and looks forward to its future development direction.

Compared with conventional instrumental analytical methods, FETs prepared using nanomaterials as channels have the advantages of fast response speed, high sensitivity and good selectivity, among which the diversified processing methods of graphene, the multi-heavy metal ions detection of silicon nanowires and the very low detection limit and wider detection range of carbon nanotubes have made them one of the most promising detection tools in the field of heavy metal ions detection. Of course, through in-depth analysis, this type of sensor has certain limitations, such as high cost and strict process requirements, which are yet to be solved.

This paper elaborates on the detection principle and classification of field-effect tube, investigates and researches the application status of three kinds of FET biosensors in the detection of common heavy metal ions. By comparing the advantages and disadvantages of each of the three sensors in practical applications, the paper focuses on the feasibility of improvement measures, looks forward to the development trend in the field of heavy metal detection and ultimately promotes the application of field-effect tube development technology to continue to progress, so that its performance continues to improve and the application field is constantly expanding.