Search

Retaining talented salespeople is crucial for a company's survival. One effective strategy for retaining employees is to actively involve them in significant business decisions. Salespeople, however, differ significantly from their colleagues, for example, they are typically highly customer-oriented. Therefore, integrating them into new product development (NPD) may be a potentially valuable approach for firms to retain them. Nonetheless, salesforce integration (SI) into NPD is more intricate than initially thought. It may involve both psychological SI benefits (such as feeling valued or competent) and costs (including potential conflicts with NPD team members or role conflicts), thus differently affecting a salesperson's willingness to stay with the firm. To learn more about the intriguing link between SI into NPD and salesperson retention, we conducted a qualitative study and applied grounded theory to conceptualize this relationship. We identify key mediators (psychological SI benefits and costs) and moderators (such as company, NPD team, salesperson, procedural, relationship, or product characteristics) that can influence the SI-into-NPD-salesperson-retention connection and develop related, relevant propositions. All of these insights are integrated into a cohesive framework and we present a research agenda to guide future exploration of this critical subject. Furthermore, we derive and discuss implications for both academics and practitioners. [ABSTRACT FROM AUTHOR]

Marketers often assume that consumers comparing products (e.g., two TVs) will show a hedonic contrast. In other words, a product seems more appealing and consumers are willing to pay more for it when it is compared with an unappealing competitor than when it is compared with a highly appealing one. However, hedonic judgments (e.g., how appealing is this TV?) are confounded with underlying attribute judgments (e.g., how big is this TV?), and it is important to delineate their effects. This article presents six studies to disentangle them and shows evidence for two separate effects in opposite directions: while a product's attribute judgments contrast with those of a competitor, its hedonic judgments assimilate. Thus, marketing tactics based on the assumption of the hedonic contrast hypothesis can potentially backfire, reducing willingness to pay. More generally, this research reveals the hidden complexity underlying product comparisons. [ABSTRACT FROM AUTHOR]

As social media influencer endorsement gains significance in marketing communication, an increasing number of influencers have started to incorporate product information into their sponsored content. This study examines the effectiveness of product attribute description in the context of sponsored videos. Using a field dataset of 598 sponsored videos, we demonstrate that influencers' use of product attribute description as an endorsement strategy has a negative impact on video engagement, and this effect is stronger for trial versus awareness campaigns. However, the negative impact is reversed to a positive one when product attribute description is employed for utilitarian products but not for hedonic products. These results reveal that the effectiveness of product attribute description depends on the nature of the product and the campaign objectives. Overall, this study contributes to the understanding of influencer marketing effectiveness and sheds light on the nuances of endorsement strategies. Practical implications on how to optimise endorsement effectiveness and video performance are discussed. [ABSTRACT FROM AUTHOR]

Unlike previous research that suggests a predominant preference for older brands, this research takes a contingent perspective to examine how consumers' preference for older brands is affected by their expectations of category innovativeness. Results from the analysis of sales data from Amazon and seven experimental studies demonstrate that consumers' preference for older brands decreases with their expectations of category innovativeness. The rationale is that with expectations of category innovativeness, consumers place less importance on consistency-related brand traits (e.g., stability, reliability) and more on excitement-related brand traits (e.g., dynamic, adventurous). Because older brands are associated with consistency, preference for older brands diminishes with expectations of category innovativeness. Further, this research identifies two factors that moderate the effects of category innovativeness on preference for older (vs. younger) brands. First, familiarity with the older brand moderates the effect of category innovativeness on brand preferences such that category innovativeness increases preferences for younger brands only when consumers are choosing between unfamiliar brands. Second, consumers' need for uniqueness reduces the effect of category innovativeness on preferences for younger brands. Together, the findings suggest that the dominance of older brands reduces with expectations of category innovativeness. The findings are important from both theoretical and managerial perspectives. [ABSTRACT FROM AUTHOR]

It is common that marketers design and position pretty products more to female consumers than to male consumers, suggesting that they generally believe that females have a stronger preference than males for product form over function and apply this belief to their marketing practices. However, this research demonstrates that this belief is often inconsistent with actual preferences. Across seven studies and four follow-up studies, involving both hypothetical and field settings, we demonstrate that both marketers and consumers hold such a belief about gender difference and overpredict females' preference for form-superior (vs. function-superior) products relative to males. Specifically, people tend to choose form-superior (vs. function-superior) products for female (vs. male) others, but female consumers do not choose form-superior (vs. function-superior) products for themselves more than male consumers do. We further provide convergent evidence for the underlying mechanism and boundary conditions by showing that (1) people's choices for others and themselves are more in line with the lay belief about gender difference when they hold a stronger belief and (2) people's choices for distant (vs. close) others are more in line with this lay belief. We further assess the effectiveness of several debiasing interventions and show that this lay belief is quite robust. [ABSTRACT FROM AUTHOR]

Many US consumers wanting a healthy lifestyle are interested in cannabidiol (CBD) products, but these products remain somewhat controversial. This study investigates how product factors, consumer knowledge, and external cues to action influence the perceived benefits of, and barriers to, CBD, driving adoption intention. Study 1 explores important factors influencing CBD adoption. Study 2, which relies on experimental studies, reveals that certification labels, subjective knowledge, usage experience, and external cues to action influence the perceived benefits and barriers, further impacting adoption intention. The impact of the perceived benefits and barriers on adoption intention is stronger in consumers with greater concerns about their overall health. Insights into factors influencing consumer perceptions and adoption of CBD extend our knowledge of consumer responses to CBD and highlight valuable implications for marketers and policymakers. [ABSTRACT FROM AUTHOR]

Purchase decisions typically involve tradeoffs between attributes associated with desirability (e.g. quality) and feasibility (e.g. price). In this article, we examine how the decision context impacts consumers' preference between a high-desirability (HD) option and a high-feasibility (HF) alternative. Nineteen studies demonstrate a novel context effect, the "upscaling effect," whereby introducing a symmetrically dominated decoy option to a set (i.e. an option that is inferior compared to all alternatives in the set) leads to an increase in the choice share of the HD option. To account for the upscaling effect, we advance a two-stage model of consumer decision-making for decisions that involve tradeoffs between desirability and feasibility. According to our model, when the decision context provides a reason for choosing either option, such as when a decoy option is added to the set, consumers prioritize reasons that support choice of HD options over HF alternatives. Our model can explain the upscaling effect, as well as other findings reported in the literature, such as asymmetric attraction effects (Heath and Chatterjee 1995) and asymmetric sales promotion effects (Blattberg and Wisniewski 1989). Furthermore, the upscaling effect holds important managerial implications because it provides an effective way to increase sales of high-end products. [ABSTRACT FROM AUTHOR]

Accelerating antiglobalization challenges previously undisputed assumptions about the importance of a product's globalness/localness in purchase decisions. Putting these assumptions to test, this article conceptualizes globalness/localness as a distinct product attribute and decomposes its utility into weight and preference components. Subsequently, it offers an equity-theory-based prediction of the attribute's declining relevance/trivialization and quantifies its trade-offs with other attributes by calculating global/local price premiums. Conjoint experiments in two countries (Austria and India) reveal that (1) emerging- (developed-) market consumers exhibit relative preference for global (local) products, (2) emerging-market consumers perceive higher preference inequity between global and local products than developed-market consumers, and (3) the corresponding inequity triggers consumers' cognitive inequity regulation (manifested through attribute trivialization in developed markets) and behavioral inequity regulation (manifested through asymmetrical willingness to pay for global/local products across developed/emerging markets). In addition, attribute trivialization and price premium tolerance are moderated by consumers' spatial identities and price segment. The findings contribute to the theoretical debate on the relevance of product globalness/localness in deglobalizing times and inform competitive strategies; segmentation, targeting, and positioning; and international pricing decisions. [ABSTRACT FROM AUTHOR]

Cultivations of Chinese Hamster Ovary (CHO) cells in a perfusion setup were conducted in the presence of super physiological concentrations of L-Arginine to investigate the impact on transmission through the perfusion filter for production of a recombinant domain antibody. Our study revealed that the presence of L-Arginine within the range of 30–50 mM had a positive impact on transmission. However, the higher concentrations were found to have a negative correlation with cell viability, and an optimal concentration of approximately 40 mM was identified. The supplementation of L-Arginine improved overall cultivation performance and enhanced product quality attributes. As a result, our findings demonstrate that the supplementation of L-Arginine to mammalian perfusion cultivations stands as an effective method to address transmission issues, exerting a broad impact on process and production of recombinant proteins. • Mammalian cell cultivations with high L-Arginine assessed impact on transmission for domain antibody production. • 30–50 mM L-Arginine positively affected transmission, while excessive concentrations impacted viability. • Optimal 40 mM improved transmission, positively influencing performance and product quality. • L-Arginine in perfusion cultivations offers a method for resolving transmission issues. • Findings suggest general applicability of L-Arginine in improving recombinant protein production. [ABSTRACT FROM AUTHOR]

Purpose: This study develops and validates an innovative approach for extracting knowledge from online user reviews by integrating textual content and emojis. Recognizing the pivotal role emojis play in enhancing the expressiveness and emotional depth of digital communication, this study aims to address the significant gap in existing sentiment analysis models, which have largely overlooked the contribution of emojis in interpreting user preferences and sentiments. By constructing a comprehensive model that synergizes emotional and semantic information conveyed through emojis and text, this study seeks to provide a more nuanced understanding of user preferences, thereby enhancing the accuracy and depth of knowledge extraction from online reviews. The goal is to offer a robust framework that enables more effective and empathetic engagement with user-generated content on digital platforms, paving the way for improved service delivery, product development and customer satisfaction through informed insights into consumer behavior and sentiments. Design/methodology/approach: This study uses a structured methodology to integrate and analyze text and emojis from online reviews for effective knowledge extraction, focusing on user preferences and sentiments. This methodology consists of four key stages. First, this study leverages high-frequency noun analysis to identify and extract product attributes mentioned in online user reviews. By focusing on nouns that appear frequently, the authors can systematically discern the primary features or aspects of products that users discuss, thereby providing a foundation for a more detailed sentiment and preference analysis. Second, a foundational sentiment dictionary is established that incorporates sentiment-bearing words, intensifiers and negation terms to analyze the textual part of the reviews. This dictionary is used to assign sentiment scores to phrases and sentences within reviews, allowing the quantification of textual sentiments based on the presence and combination of these predefined lexical items. Third, an emoticon sentiment dictionary is developed to address the emotional content conveyed through emojis. This dictionary categorizes emojis based on their associated sentiments, thus enabling the quantification of emotional expressions in reviews. The sentiment scores derived from the emojis are then integrated with those from the textual analysis. This integration considers the weights of text- and emoji-based emotions to compute a comprehensive attribute sentiment score that reflects a nuanced understanding of user sentiments and preferences. Finally, the authors conduct an empirical study to validate the effectiveness of the proposed methodology in mining user preferences from online reviews by applying the approach to a data set of online reviews and evaluating its ability to accurately identify product attributes and user sentiments. The validation process assessed the reliability and accuracy of the methodology in extracting meaningful insights from the complex interplay between text and emojis. This study offers a holistic and nuanced framework for knowledge extraction from online reviews, capturing both explicit and implicit sentiments expressed by users through text and emojis. By integrating these elements, this study seeks to provide a comprehensive understanding of user preferences, contributing to improved consumer insight and strategic decision-making for businesses and researchers. Findings: The application of the proposed methodology for integrating emojis with text in online reviews yields significant findings that underscore the feasibility and value of extracting realistic user knowledge to gain insights from user-generated content. The analysis successfully captured consumer preferences, which are instrumental in informing service decisions and driving innovation. This achievement is largely attributed to the development and utilization of a comprehensive emotion-sentiment dictionary tailored to interpret the complex interplay between textual and emoji-based expressions in online reviews. By implementing a sentiment calculation model that intricately combines textual sentiment analysis with emoji sentiment analysis, this study was able to accurately determine the final attribute emotion for various product features discussed in the reviews. This model effectively characterized the emotional knowledge of online users and provided a nuanced understanding of their sentiments and preferences. The emotional knowledge extracted is not only quantifiable but also rich in context, offering deeper insights into consumer behavior and attitudes. Furthermore, a case analysis is conducted to rigorously test the validity of the proposed model in a real-world scenario. This practical examination revealed that the model is not only capable of accurately extracting and analyzing user preferences but is also adaptable to different contexts and product categories. The case analysis highlights the robustness and flexibility of the model, demonstrating its potential to enhance the precision of knowledge extraction processes significantly. Overall, the results confirm the effectiveness of the proposed approach in integrating text and emojis for comprehensive knowledge extraction from online reviews. The findings validate the model's capability to offer actionable insights into consumer preferences, thereby supporting more informed and strategic decision-making by businesses. This study contributes to the broader field of sentiment analysis by showcasing the untapped potential of emojis as valuable indicators of user sentiments, opening new avenues for research and applications in digital marketing and consumer behavior analysis. Originality/value: This study introduces a pioneering approach to extract knowledge from Web user interactions, notably through the integration of online reviews that incorporate both textual content and emoticons. This innovative methodology stands out because it holistically considers the dual channels of communication, text and emojis, to comprehensively mine Web user preferences. The key contribution of this study lies in its novel insights into the extraction of consumer preferences, advancing beyond traditional text-based analysis to embrace nuanced expressions conveyed through emoticons. The originality of this study is underpinned by its acknowledgment of emoticons as a significant and untapped source of sentiment and preference indicators in online reviews. By effectively merging emoticon analysis and emoji emotion scoring with textual sentiment analysis, this study enriches the understanding of Web user preferences and enhances the accuracy and depth of consumer preference insights. This dual-analysis approach represents a significant leap forward in sentiment analysis, setting a new standard for how digital communication can be leveraged to derive meaningful insights into consumer behavior. Furthermore, the results have practical implications to businesses and marketers. The insights gained from this integrated analytical approach offer a more granular and emotionally nuanced view of customer feedback, which can inform more effective marketing strategies, product development and customer service practices. By pioneering this comprehensive method of knowledge extraction, this study paves the way for future research and practice to interpret and respond more accurately to the complex landscape of online consumer expressions. This study's originality and value lie in its innovative method of capturing and analyzing the rich tapestry of Web user communication, offering a ground-breaking perspective on consumer preference extraction that promises to enhance both academic research and practical applications in the digital era. [ABSTRACT FROM AUTHOR]

Aims Methods Results Conclusions Previous work has identified several limitations in “Summaries of Product Characteristics” (SmPCs), which are associated with risks for patients. The aim of this study was to evaluate pharmacists' and physicians' interpretation of contraindications in SmPCs and reasons for their nonadherence in clinical routine.For 20 commonly missed or ignored absolute contraindications, an anonymous online survey providing 24 clinical example cases (one or two per contraindication) for physicians and pharmacists was developed. Experts in medication safety were asked whether the respective case fulfilled the definition of the contraindication in the SmPC: (a) formally, irrespective of the clinical relevance of the contraindication (17 cases), and (b) whether the contraindication was deemed clinically relevant in each respective case (24 cases).Twenty‐seven pharmacists and 27 physicians completed the survey. For only one case (1/17; 5.8%) did all experts agree on the same answer option regarding the formal fulfilment of a given contraindication statement. Experts gave heterogeneous answers regarding the interpretation of a contraindication. For instance, among 10 predefined answer options for the contraindication “active liver disease” in the SmPC of simvastatin, every option was selected by at least six experts. In 17/24 (70.8%) clinical example cases a majority of experts agreed on the clinical relevance of a given contraindication. Key reasons for nonadherence to contraindications were “patient monitoring possible”, “lack of alternative treatment” and “acute/severe situations”.Experts' disagreement on the interpretation of contraindications in SmPCs using clinical example cases indicates that further efforts are needed to improve their usability in clinical routine. [ABSTRACT FROM AUTHOR]

Euryale ferox was chosen for this study to examine its mechanical properties during chewing. Experiments and the discrete element method were used to conduct the study. Initially, the intrinsic and contact parameters of E. ferox were established through physical tests. The maximum compressive force of breakage and chewing mechanical properties (hardness, springiness, and chewiness) were measured using a texture profile analyzer (TPA). A Hertz–Mindlin with bonding model of the E. ferox was constructed. Optimal values for significant factors, including the normal stiffness per unit area, shear stiffness per unit area, and bonding radius, were obtained through single‐factor, Plackett–Burman, steepest ascent, and Box–Behnken response surface tests, with the maximum compressive force as the index. Under optimal parameter combination conditions, the relative error between the simulated and experimental values of the maximum compressive force was 0.79%, and the relative errors between the simulated and TPA test values of all indicators were less than 5.65%. This study provides a valuable reference for simulating the textural characteristics of agricultural products. [ABSTRACT FROM AUTHOR]

Quality by design (QbD) is a systematic method for the development of product and process design to ensure quality and efficacy. In the fragrance and flavour industry, the design of delivery systems plays a crucial role in the overall product quality and consumer acceptance. This article analyses the current state‐of‐the‐art and future explorations from QbD perspective for designing appropriate delivery systems for flavour and fragrance applications. The QbD approach for delivery system design involves classifying critical quality attributes of the product and process, defining the critical process parameters and developing a design space to ensure product quality within the specified range. In addition, risk assessment and mitigation strategies are also a component of the QbD techniques, which ensure the robustness of the delivery system. Various delivery systems such as microencapsulation, nanoencapsulation, solid lipid nanoparticles and liposomes have been explored in the flavour and fragrance industry. These delivery systems provide controlled release, protection, and enhanced stability of the active ingredients. However, challenges such as scale‐up, reproducibility, and cost‐effectiveness need to be addressed to ensure their commercial viability. In conclusion, the QbD outlook provides a comprehensive framework for the design of carrier system for fragrance and flavour applications. The incorporation of risk assessment and mitigation strategies ensures the robustness of the delivery system, and the future exploration of advanced technologies may further enhance the efficiency and effectiveness of the QbD approach. [ABSTRACT FROM AUTHOR]

As the main energy consumption of aviation and aerospace, the study of combustion characteristics of aviation kerosene is of great significance. In this paper, through the self-built experimental system, the combustion flame characteristics of pure aviation kerosene, aviation kerosene mixed with n-amyl alcohol, aviation kerosene mixed with dimethylfuran were studied under different working conditions, and the physicochemical properties of soot particles generated in the flame, and the effects of mixing n-amyl alcohol and dimethylfuran on the formation of soot particles were analyzed from the microscopic perspective. The results show that: 1. The soot particles in the combustion of aviation kerosene mixed with n-amyl alcohol and dimethylfuran show some characteristics of amorphous structure, unclear outline and incomplete curing; 2. Under K-D20 condition, nitrates are included in particulate matter generated by soot; 3. After mixing n-amyl alcohol and dimethylfuran, the degree of graphitization continues to decrease. [ABSTRACT FROM AUTHOR]

This study explored the potential of two forms of sourdough—native and lyophilised—obtained through the spontaneous fermentation of whole grain flours from ancient wheat varieties, for cookie production. The research involved evaluated the dough's rheological properties through creep and recovery measurements and Mixolab analysis, assessing proximate composition, physical attributes, texture, colour, and sensory characteristics using the Rate-all-that-apply (RATA) method. The rheological analysis revealed that native sourdough significantly impacted dough behaviour, making it more challenging to process. Although differences were observed in the proximate composition, colour, and texture, these factors did not influence the samples as much as the rheological parameters. Sensory evaluation identified Khorasan lyophilised sourdough, along with its control sample, as the most promising, while modern wheat, spelt, and emmer exhibited potentially undesirable attributes. Based on these findings, it was concluded that lyophilised Khorasan sourdough was very favourable for cookie production and should be considered for further in-depth research and development. This suggests that the lyophilised forms of ancient wheats could offer valuable alternatives for cookie formulation, with implications for both the processing and sensory attributes of the final product. [ABSTRACT FROM AUTHOR]

Consumers typically have a higher preference and trust for traceability products, which makes many online platforms (e.g., JD.com, Tmall Global) and food manufacturers (e.g., BeingMate, Mengniu, Moutai) use blockchain‐enabled traceability to improve product transparency and trust. This paper systematically analyzes the effects of constructing blockchain‐based information traceability systems (BITS) on supply chains led by different members in a dual‐channel supply chain consisting of a manufacturer and an online platform. We studied the optimal operational strategy for dual‐channel members in two scenarios without blockchain technology and different members (i.e., manufacturer and online platform) as leaders in building BITS. We find that BITS adoption can effectively improve the performance of supply chain members, but the value added to blockchain depends on the level of consumer goodwill toward BITS, the level of competition, and the proportion of cost sharing. We show that either the manufacturer or the online platform can be more profitable as a leader in building BITS. Further, we showed that either the manufacturer or the online platform, as the leader of BITS construction, should bear more construction costs so that the nonleader builder can gain more profit to achieve a win‐win result. Interestingly, as the leader of BITS construction bearing more construction costs can achieve higher system total profit. [ABSTRACT FROM AUTHOR]

Web-based businesses create various product recommendation labels to facilitate online decision-making. Across three studies, this research demonstrates that relative to non-ranking-based recommendation labels, ranking-based recommendation labels increase e-shoppers' quality assessment belief and elicit a higher willingness to pay. Consistency among consensus attributes and perceived product differences moderate this effect. According to the findings, online retailers should use a multi-layer, diversified recommendation scheme and ranking-based recommendations for high profit-margin products to maximize their future revenues. [ABSTRACT FROM AUTHOR]

Modern consumers demand the replacement of synthetic colorants with natural alternatives. Microalgae can serve as an alternative source for these colorants since they hold significant amounts of pigments. This study aimed to evaluate the potential of using microalgae biomass and extracts as natural colorants for pastry and confectionary products. The application of different biomass and levels of Chlorella vulgaris (White, Honey, and a mixture of both) was evaluated in brioche‐type breads as egg substitute to confer the typical yellow coloration to the product. A mixture of 1% Chlorella vulgaris (White: Honey [1:1]) showed potential as egg substitute, having minimal impact on the physical–chemical, microbiological, nutritional, and sensory characteristics of the products. Hydroalcoholic Tetraselmis chuii extracts were applied in fondant at a concentration of 0.05%, providing a green coloration with minimal impact on the quality of the product. This study supported the potential of using microalgae, biomass, and extracts, as alternative natural colorants in pastry and confectionary products. [ABSTRACT FROM AUTHOR]

Recently, growing demand for products enriched with natural compounds that support human health has been observed. Black rice, its by-products, and residues are known to have in their composition a large amount of these compounds with biological potential, mainly anthocyanins. These compounds have reported effects on anti-obesity, antidiabetic, antimicrobial, anticancer, neuroprotective, and cardiovascular disease. Therefore, the extract from black rice or its by-products have great potential for application as ingredients in functional foods, supplements, or pharmacological formulations. This overview summarizes the methods employed for the extraction of anthocyanins from both black rice and its by-products. In addition, trends in applications of these extracts are also evaluated regarding their biological potential. Commonly, the extraction methods used to recover anthocyanins are conventional (maceration) and some emerging technologies (Ultrasound-Assisted Extraction - UAE, and Microwave-Assisted Extraction - MAE). Anthocyanin-rich extracts from black rice have presented a biological potential for human health. In vitro and in vivo assays (in mice) showed these compounds mainly with anti-cancer properties. However, more clinical trials are still needed to prove these potential biological effects. Extracts from black rice and its by-products have great potential in applying functional products with beneficial characteristics to humans and reducing agro-industrial residues. [ABSTRACT FROM AUTHOR]

In the traditional decision-making process for product form design, designers and experts often prioritize schemes based on their own knowledge and experience. This approach can lead to an oversight of user preferences, ultimately affecting decision outcomes. In contrast, crowd-intelligence-driven, multi-attribute decision-making for product form design in the cloud environment builds upon traditional approaches by leveraging the vast and diverse expertise of individuals on cloud platforms, engaging participants from various fields and roles in the decision-making process to enhance comprehensiveness and accuracy. To address the issue of a single decision-maker and limited user participation in the decision-making process for product form design schemes in the cloud environment, a multi-attribute decision-making method integrating expert knowledge and user preferences is proposed. This method aims to select a product form design scheme that optimally balances expert and user satisfaction. Initially, the Pythagorean Hesitant Fuzzy Set (PHFS) is used to quantify qualitative product attributes and to establish a comprehensive multi-attribute evaluation system. In the aspect of expert decision-making, a gray correlation coefficient decision matrix based on expert knowledge is established and the overall score of the base alternative is calculated by the ViseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) method and the Improved Osculating Value method. In terms of user decision-making, weights are determined by calculating the similarity between user evaluation matrices, and the Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) is used to calculate scores for product form designs based on user preferences. Ultimately, optimal selection is achieved by aggregating the aforementioned expert evaluation values and user preference values. The method's effectiveness and feasibility are confirmed through a case study of coffee machine product form design schemes. [ABSTRACT FROM AUTHOR]

The morphological characteristics of a product serve as essential carriers for conveying design intentions. These characteristics directly affect users' comprehension of the product's functions and proper usage, which are critical to the safety of product utilization and the overall comfort of the user experience. Incorporating prior experience to predict users' cognitive intentions regarding product form characteristics can provide valuable evaluation and decision-making references for design. This approach effectively reduces product development risks and contributes to enhancing user acceptance and experience. The study established intention discrimination indicators for form characteristics, covering six dimensions: functional orientation, behavioral intention, recognizability, cognitive load, attention distribution, and experiential feeling. Combining multidimensional scaling (MDS) and systematic clustering, samples were screened, and the morphological decomposition method was used to categorize and extract form characteristic categories and feature factors. The entropy weight method was applied to assign weights to the feature categories, and a feedforward neural network (FNN) was employed to construct a prediction model for cognitive intentions regarding product form characteristics. The model was tested using leave-one-out cross-validation, yielding a mean squared error (MSE) of 0.0089 and an R correlation coefficient of 0.9998, indicating high reliability. Finally, the feasibility and effectiveness of this method were validated through a case study on earthquake science experience facilities. [ABSTRACT FROM AUTHOR]

Drawing upon presence theory, this study seeks to unravel the critical determinants converting engagement into value cocreation in travel livestreaming. To configure an optimal path for real-time interaction, live room setting, and product attributes in livestreaming via viewers' sense of presence, we performed a scenario-based quasi-experiment with four alternative models. Model 1 elucidated the direct influence mechanism how real-time interaction, authenticity, and remuneration evoke value cocreation, while Model 2 reflected the moderation impact of the objective attributes between communication behaviours and value cocreation. Model 3 and Model 4 incorporated viewers' physical and social presence into assessments as mediators. The results reveal that communication behaviours psychologically drive viewers' sense of presence, thereby leading to value cocreation, while objective attributes moderate the subjective consciousness of presence. The research positions insightful theoretical implications to thrust value co-creation of tourism academia spotlight and practically contributes to promoting sales performance in the nascent tourism market. [ABSTRACT FROM AUTHOR]

Copyright of Machine Tool & Hydraulics is the property of Guangzhou Mechanical Engineering Research Institute (GMERI) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Current routes to boronic acids and their corresponding esters to be used in subsequent Suzuki–Miyaura (SM) cross couplings impact the cost, waste, and safety concerns associated with generating these materials. A new method for installing the ethyl pinacol boronic ester, or B(Epin) derivative leads to stable borylated products under near-neat conditions using high concentrations of a green solvent and moderate reaction temperatures, catalyzed by relatively low palladium loadings. Alternatively, the newly fashioned Ar–B(Epin) can be generated in situ and used directly in the same pot for SM reactions leading to aromatic and heteroaromatic residues characteristic of the biaryl products being formed. An array of complex targets, including API-related products, can be generated via this green and environmentally responsible methodology. [ABSTRACT FROM AUTHOR]

Milk protein and pea protein were used as raw materials to produce milk-pea blended protein processed cheese. This study investigated the effect of three types of calcium sequestering salts (trisodium citrate (TSC), dibasic sodium phosphate (DSP), and sodium hexametaphosphate (SHMP)) at different mass fractions (0.5%, 1.0%, 1.5%, and 2.0%) on the quality of the blended protein processed cheese based on functional properties, texture properties, sensory evaluation, and microstructure. The results showed that milk protein and pea protein could substitute for natural cheese in processed cheese formulations. As the mass fraction of the calcium sequestering salts increased, the meltability of the blended protein processed cheese demonstrated a consistent upward trend, accompanied by a reduction in fat separation, and the TSC had shown good effects in improving product melting characteristics and inhibiting oil precipitation. When the mass fraction of TSC was 1.0%, the hardness of the blended protein processed cheese was lower, whereas its total sensory score, elasticity, cohesiveness, and adhesiveness were higher. Meanwhile, casein network micelles were arranged in a regular pattern, with fat globules and minerals uniformly distributed throughout the matrix. Consequently, the incorporation of TSC could improve the quality of milk-pea blended protein processed cheese by enhancing its emulsification,stability and other functional characteristics. [ABSTRACT FROM AUTHOR]

Although the market share of domestic children's furniture is increasing annually, some potential problems limit its long-term and stable development, and there is still a gap in China compared with foreign countries. This study focused on the demand preferences for growable children's beds and examined the design features that influence these preferences. This study introduces a combination of Hierarchical Analyses (AHP), Quality Function Development (QFD), and the Platts Conceptual Decision Matrix (PUGH) into the innovative design of a research model for children's furniture (AHP-QFD-PUGH). This study screened and classified the decision-making indicators obtained from the research, ranked their importance by quantitative calculation, and finally proposed an optimal design solution. Additionally, to further study the structural characteristics, the function-behavior-structure (FBS) model served as a supplementary analysis tool to effectively circumvent subjective factors in product design. This integrated model accurately explored user needs and product characteristics, providing substantial guidance and new ideas for optimizing the design of growable children's beds and enhancing growth of the children's furniture industry. [ABSTRACT FROM AUTHOR]

The safe disposal of large irradiated cation exchange resin waste in nuclear power plant has drawn worldwide attention. The kinetic characteristics and product characteristics of the simulated spent cation exchange resin in the pyrolysis and gasification were evaluated based on thermogravimetric analysis as well as TG-FTIR and TG-GC/MS. The temperature ranges at different decomposition stages of the resins were determined. In nitrogen atmosphere, the metal nuclides would hinder the reaction of waste resin in the first stage and promote the reaction in the second stage. The second-order reaction model was the best one to describe the kinetic mechanism in the first and second stages of the spent resins in different atmospheres, while Mample Power model (n = 1) and two-dimensional shrinking cylinder model were for the third gasification stage of the waste resins in 10 % oxygen atmosphere and 10 % steam atmosphere, respectively. The average mass loss ratio of the waste resin in 10 % oxygen atmosphere almost reached to 90 % that was higher than in 10 % steam atmosphere (80 %) and much higher than in nitrogen atmosphere (55 %). The initial reaction temperature in the third stage in 10 % oxygen was about 100 °C earlier than that in 10 % steam atmosphere, indicating that the sulfur bond would easily break due to the strong oxidization action of the oxygen. In the nitrogen atmosphere, the sulfur bond broke at 700 °C, which would lead to low mass loss ratio of the waste resin since the copolymer matrix is difficult to decompose. This work could supply basic data for the pyrolysis and gasification treatment of irradiated spent cation exchange resin in nuclear power plant. [ABSTRACT FROM AUTHOR]

Background/Objectives: Elexacaftor, tezacaftor, and ivacaftor (ETI) have significantly improved lung function in people with cystic fibrosis (pwCF). Despite exceptional improvements in most cases, treatment-related inter-subject variability and drug–drug interactions that complicate modulator therapy have been reported. Methods: This retrospective analysis presents data on the serum concentration of ETI in our pwCF with full or reduced dosage from August 2021 to December 2023 via routine therapeutic drug monitoring (TDM). The data were compared with the maximum drug concentrations (Cmax) from the pharmaceutical company's summary of product characteristics. Results: A total of 786 blood samples from 155 pwCF (41% female, 59% male) were analyzed. The examinations were divided into four groups: full dose within the given tmax (38.5% of all measurements), full dose outside the tmax (29%), reduced dose within the tmax (19.2%), and reduced dose outside the tmax (13.2%). In pwCF receiving the full dose and blood taken within the tmax, 45.3% of serum concentrations of elexacaftor, 51.1% of serum concentrations of ivacaftor, and 8.9% of serum concentrations of tezacaftor were found to be above the Cmax, respectively. For those on reduced doses within the tmax, 24.5% had a serum concentration of elexacaftor, 23.2% had a serum concentration of ivacaftor, and 2.5% had a serum concentration of tezacaftor above the Cmax, respectively. Conclusions: Many pwCF under ETI therapy have Cmax values for elexacaftor and ivacaftor above the recommended range, even on reduced doses or before the tmax was reached. This highlights the value of a TDM program. Further pharmacokinetic studies are necessary. [ABSTRACT FROM AUTHOR]

Three-level control charts have been developed for monitoring processes where the quality of products is characterized by classifying the product characteristic into three discrete levels. In this paper, a double sampling (DS) attribute control chart is developed for monitoring three-level products. The statistical performance of the proposed chart is evaluated using the statistical measures average run length (ARL) and average number of inspected items to signal (ANI). A Markov chain approach is applied to derive expressions for ARL and ANI. Using numerical examples, we illustrate the performance of the proposed control scheme and compare its efficiency with the other control schemes. The results approve the statistical efficiency of the proposed control scheme compared with the other control schemes. [ABSTRACT FROM AUTHOR]

In this work, the airborne Synthetic Aperture Radar (SAR) infrastructure developed at the Institute for Electromagnetic Sensing of the Environment (IREA) of the National Research Council of Italy (CNR) is described. This infrastructure allows IREA-CNR to plan and execute airborne SAR campaigns and to process the acquired data with a twofold aim. On one hand, the aim is to develop research activities; on the other hand, the aim is to support the emergency prevention and management activities of the Department of Civil Protection of the Italian Presidency of the Council of Ministers, for which IREA-CNR serves as National Centre of Competence. Such infrastructure consists of a flight segment and a ground segment that include a multi-frequency airborne SAR sensor based on the Frequency-Modulated Continuous Wave (FMCW) technology and operating in the X- and L-bands, an Information Technology (IT) platform for data storage and processing and an airborne SAR data processing chain. In this work, the technical aspects related to the flight and ground segments of the infrastructure are presented. Moreover, a discussion on the response times and characteristics of the final products that can be achieved with the infrastructure is provided with the aim of showing its capabilities to support the monitoring activities required in a possible emergency scenario. In particular, as a case study, the acquisition and subsequent interferometric processing of airborne SAR data relevant to the Stromboli volcanic area in the Sicily region, southern Italy, are presented [ABSTRACT FROM AUTHOR]

Summary: Three freeze–thaw (FT) pre‐treatments using different freezing methods that freezing at −80 °C (FT‐80), freezing at −25 °C (FT‐25) and vacuum freezing (VFT) were used for carrot slices, the effects and mechanisms of FT pre‐treatment on the drying characteristics and product quality of carrots during microwave freeze drying (MFD) were studied. The results showed that FT pre‐treatment under different freezing methods affected the water state of carrots, resulting in varying degrees of moisture loss and shortening drying time by 14.3% to 42.8%. VFT treatment caused the greatest water loss (35.33%) during FT and significantly increased the effective moisture diffusivity in the MFD process. FT treatments did not cause any significant degradation in the colour of the carrots. The VFT and FT‐80 treatments resulted in an elevated rehydration ratio, increased crispiness of MFD carrots and products with a porous microstructure and higher porosity. In contrast, the FT‐25 treatment led to a decrease in porosity due to destructive damage to the carrot cell structure. However, this damage favoured the extractability of carotenoids, resulting in a higher carotenoid content than the other treatments. This study provides a theoretical foundation for the practical implementation of FT pre‐treatment using various freezing methods on fresh foods prior to drying. It is recommended to employ VFT pre‐treatment before MFD due to its efficiency and effectiveness. [ABSTRACT FROM AUTHOR]

Three-level control charts have been developed for monitoring processes where the quality of products is characterized by classifying the product characteristic into three discrete levels. In this article, a combined double sampling and variable sampling interval (DSVSI) attribute control chart is developed for monitoring three-level products. This research is motivated by recent studies done on combining the DSVSI scheme with traditional attribute charts and their results recommend the application of the DSVSI attribute charts. The proposed DSVSI three-level chart is compared with the existing standard, adaptive, and EWMA three-level charts. The results approve the superiority of the proposed scheme and recommend it as an efficient three-level control chart in application. An example is also provided to illustrate the application of the proposed chart. [ABSTRACT FROM AUTHOR]

E-commerce platforms are recognizing the value of customer experience and are dedicating sections for customers to share reviews of the product purchased. Therefore, this study aimed to analyze Online Customer Review (OCR) to identify hidden emotion expressed about the purchasing experience and further identify factors relating to the product. Text-based emotion classification is a prominent and growing field to better understand human emotions. An integrated Information Gain-Recursive Feature Elimination (IG-RFE) and stacking ensemble learning were implemented to develop a predictive emotion classification model to identify the hidden emotions of the customers. Additionally, the Latent Dirichlet Allocation (LDA) model was used to extract the influencing factors, providing further insight in OCR. The study extracted eight emotions from OCR and seven influencing factors from product's attributes. The emotions included anger, anticipation, disgust, fear, happiness, sadness, surprise, and trust while the identified factors were quality, brand credibility, product functionality, usability, appearance, price, and functional effect. The extracted emotions and factors from the OCR provided valuable knowledge on the study. The findings showed knowledge gaps in emotion classification and customer behavior fields, suggesting further investigation for future study. [ABSTRACT FROM AUTHOR]

With the continuous growth of e-commerce sales, a robust product selection model is essential to maintain competitiveness and meet consumer demand. Current research primarily focuses on single models for sales prediction and lacks an integrated approach to sales forecasting and product selection. This paper proposes a comprehensive framework (VN-CPC) that combines sales forecasting with product selection to address these issues. We integrate a series of classical machine learning models, including Tree Models (XGBoost, LightGBM, CatBoost), Support Vector Machine (SVM), Bayesian Ridge, and Artificial Neural Networks (ANN), using a voting mechanism to determine the optimal weighting scheme. Our method demonstrates a lower Root Mean Square Error (RMSE) on collected Amazon data than individual models and other ensemble models. Furthermore, we employ a three-tiered clustering model: Initial Clustering, Refinement Clustering, and Final Clustering, based on our predictive model to refine product selection to specific categories. This integrated forecasting and selection framework can be more effectively applied in the dynamic e-commerce environment. It provides a robust tool for businesses to optimize their product offerings and stay ahead in a competitive market. [ABSTRACT FROM AUTHOR]

Copyright of Revista Fatec Zona Sul (REFAS) is the property of Revista Fatec Zona Sul (REFAS) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The aim of this paper is to investigate the relevance of sustainable product attributes as compared to ongoing costs and risk–return profiles when individuals choose funds underlying unit-linked life insurances. Regarding sustainability attributes, we focus on the product classification according to the Sustainable Finance Disclosure Regulation as a European regulatory transparency standard, and on sustainable investment strategies. We conduct two choice-based conjoint analyses using a German panel for unit-linked life insurances as well as fund savings plans as a financial product comparison. We estimate the relative importance, part-worth utilities, and the marginal willingness to pay for changes in product attributes. Our results suggest that private investors of unit-linked life insurances value sustainable product attributes and that they result in a slightly higher marginal willingness to pay, but risk–return indicators and especially ongoing costs are currently more relevant. We find further indications that sustainability attributes are less relevant in the setting of a unit-linked life insurance as compared to a fund savings plans setting. [ABSTRACT FROM AUTHOR]

Pet‐food industry growth and demand for specialized product offerings have generated new opportunities for companies to enhance their competitiveness and profitability through effective product differentiation. Recent rise in e‐commerce and technological advancements for capturing and analyzing online customer review data provide new opportunities for large‐scale assessment of customer perceptions of product attributes. This paper presents an integrated qualitative and quantitative approach for utilizing online customer review data to generate insights for informing pet‐food industry product and marketing decisions. The results from the analysis of 5632 online reviews of two pet‐food products highlight (i) product attributes that effectively differentiate (or put on par) two competing pet‐food products, (ii) identify product attributes that are most important for customer postpurchase experience, and (iii) estimate the effect of specific attributes on customers' positive (or negative) postpurchase experience. Specific pet‐food attributes examined include packaging, health/benefit, ingredient, taste, smell, appearance/form, natural/organic, processing, sourcing, small/large breed, price, and service. The advantages of this approach include its ability to leverage large amounts of easily accessible data and its generalizability to the analysis of other consumer goods that have significant online sales and customer review data [EconLit Citations: Q13, M31]. [ABSTRACT FROM AUTHOR]

This research explores consumer reactions following green product failures, identifying a novel benefit for companies selling environmentally friendly products. Across an empirical field analysis and eight controlled experiments, the authors show that consumers react less negatively to the failure of green products than conventional ones, which is referred to as the greenguard effect. The findings suggest that by not reacting negatively to green product failures, consumers believe they are being more prosocial, as their negative reaction may harm the success of a product that otherwise benefits the environment and society. This research contributes to the literature on green products by highlighting a novel benefit of green product attributes and demonstrating how prosocial motives influence consumer reactions to green product failures, and offers valuable insights for marketers on green product marketing. [ABSTRACT FROM AUTHOR]

The article presents the possibilities of using by-products from the agri-food industry in the form of fruit and vegetable pomace as a supplementary ingredient to extruded food products in the form of snack pellets. In the recipe based on potato starch, pomace from apples, chokeberries, pumpkin, nigella seed and flaxseed were added in amounts of 10%, 20% and 30%. The prepared raw material blends were processed using a single-screw extruder-cooker with a plastification system L/D = 20 and variable screw speed. The aim of the research was to determine the effect of pomace addition on the extrusion-cooking process, i.e., efficiency and energy consumption, as well as on selected physical properties of the obtained food pellets, such as expansion index, bulk density and durability. The addition of selected pomace influenced the extrusion-cooking process and the physical properties of the extrudates. A percentage contribution ranging from 10 to 20% can optimize the extrusion-cooking process and improve the quality characteristics of the final product, while simultaneously utilizing by-products from the agri-food industry and reducing their negative environmental impact. [ABSTRACT FROM AUTHOR]

The performance of the final part of the turning process, a topic of practical importance, heavily depends on the cutting parameters. Surface quality, a crucial product attribute in manufacturing, often tops consumer demands during machining due to its significant influence on product functionality. This paper assesses the correlation between the detected vibration signal, statistical parameters (Crest, Kurtosis and I-kaz3D coefficient) and surface roughness and provides valuable insights for practical applications. When the tool experiences vibrations during material removal, these oscillations leave a ripple effect on the surface of the workpiece. We aim to determine the impact of cutting parameters on surface roughness while turning 42CrMo4 steel using a carbide tool insert. Cutting parameters, such as spindle speed, feed, and depth of cut, were used. Signal processing is carried out using different techniques to identify the effect of the cutting parameters on vibration signals. Finally, we delve into the interaction effects between the cutting parameters, vibration signals and surface roughness, offering a comprehensive understanding of real-world manufacturing scenarios. Higher I-kaz3D coefficients correspond to higher surface roughness values. The I-kaz3D coefficient decreases as the surface roughness measurements decrease, indicating that the I-kaz3D technique can accurately indicate an increase or decrease in surface roughness. On the other hand, the cutting force Fc was the component most strongly correlated with surface roughness (Ra), yielding the best results across all indices (adjusted R²adj = 95.1%, er=.8 ± 2.3%). [ABSTRACT FROM AUTHOR]

Shotcrete is one of the most important types of concrete used in engineering construction, and its properties are significantly influenced by accelerators. This study investigates the effects of aluminum sulfate series alkali-free accelerator (AKF) and alkali accelerator (ALK) on the strength, hydration process, characteristic hydration products, and microstructure properties of shotcrete. Techniques such as setting time measurement, isothermal calorimetry, simultaneous thermal analysis, scanning electron microscopy with energy-dispersive X-ray spectroscopy (SEM–EDS), and mercury intrusion porosimetry (MIP) were utilized. The results indicate that both ALK and AKF significantly accelerate and increase the early hydration heat release rate and cumulative hydration heat of Portland cement, producing the characteristic hydration products hexagonal plate AFm and rod AFt, respectively. This acceleration notably speeds up the setting process of Portland cement. ALK negatively impacts the later-stage microstructural development and pore structure filling of hardened cement paste, leading to average reductions of 15.3% and 19.9% in flexural and compressive strengths at 28 days, respectively. Specifically, compared to ALK, AKF shows a faster hydration heat release rate during the induction period and a more significant increase in cumulative hydration heat during the hydration process; the cumulative hydration heat is on average 18.2% higher than AKF. Furthermore, AKF does not hinder the subsequent C3S hydration and C-S-H gel densification process. After 28 days of curing, EDS analysis indicates an average Ca/Si ratio of 1.171 for the AKF-treated shotcrete; the average Ca/Si ratio shows minimal variation from the reference group and is classified as the same type of C-S-H gel as the reference group. Therefore, the strength of hardened cement paste with AKF continues to increase steadily in the later stages. At 28 days, the average flexural strength increased by 10.2%, while the compressive strength decreased by only 3.0%. These findings suggest that AKF enhances the microstructural development and strength of shotcrete, making it a more effective accelerator for engineering applications. [ABSTRACT FROM AUTHOR]

Purpose: This paper aims to explore consumer perceptions of product design awards (PDAs) and their impact on consumer product evaluation and attitude formation about the award-winning product, the award-winning organization and the award-granting organization. Design/methodology/approach: Based on the grounded theory approach, an exploratory qualitative study is conducted, using 16 semi-structured in-depth interviews with Turkish consumers through discussions on real-world examples. Findings: Results show that consumers develop emotional responses to PDAs (e.g. interest, curiosity and confusion), hypothesize reasons for products receiving awards and cite rewards as confirmation of their existing judgments about products. PDAs are perceived as extrinsic cues signaling quality and price, and their impact is increased when consumers feel that the award is based on functional feature superiority. Consumer responses to PDAs are also influenced by the perceived expertise of the award-granting organization and beliefs about the award-granting process. Finally, PDAs can lead to positive brand-perception outcomes, influencing consumer perceptions of the product company as resourceful, competent and prominent. Practical implications: This study shows that it is critical for companies to inform consumers about the specific features that resulted in a given product receiving a design award, as well as to provide information about the PDA itself. Originality/value: To the best of the authors' knowledge, this study is the first attempt to explore consumer perceptions of and reactions to PDAs, with significant implications for both the marketing managers of PDA-winning products and award-granting organizations. [ABSTRACT FROM AUTHOR]

Polymer particle size constitutes a crucial characteristic of product quality in polymerization. Raman spectroscopy is an established and reliable process analytical technology for in‐line concentration monitoring. Recent approaches and some theoretical considerations show a correlation between Raman signals and particle sizes but do not determine polymer size from Raman spectroscopic measurements accurately and reliably. With this in mind, we propose three alternative machine learning workflows to perform this task, all involving diffusion maps, a nonlinear manifold learning technique for dimensionality reduction: (i) directly from diffusion maps, (ii) alternating diffusion maps, and (iii) conformal autoencoder neural networks. We apply the workflows to a data set of Raman spectra with associated size measured via dynamic light scattering of 47 microgel (cross‐linked polymer) samples in a diameter range of 208–483 nm. The conformal autoencoders substantially outperform state‐of‐the‐art methods and results for the first time in a promising prediction of polymer size from Raman spectra. [ABSTRACT FROM AUTHOR]

A critical issue in laser powder bed fusion (LPBF) additive manufacturing is the selective vaporization of alloying elements resulting in poor mechanical properties and corrosion resistance of parts. The process also alters the part's chemical composition compared to the feedstock. Here we present a novel multi-physics modeling framework, integrating heat and fluid flow simulations, thermodynamic calculations, and evaporation modeling to estimate and control the composition change during LPBF of nickel-based superalloys. Experimental validation confirms the accuracy of our model. Moreover, we quantify the relative vulnerabilities of different nickel-based superalloys to composition change quantitatively and we examine the effect of remelting due to the layer-by-layer deposition during the LPBF process. Spatial variations in evaporative flux and compositions for each element were determined, providing valuable insights into the LPBF process and product attributes. The results of this study can be used to optimize the LPBF process parameters such as laser power, scanning speed, and powder layer thickness to ensure the production of high-quality components with desired chemical compositions. [ABSTRACT FROM AUTHOR]

In this paper, a two‐step process is described for the chemoselective synthesis of highly fluorescent polycyclic chromeno[4,3,2‐ij]isoquinoline‐3‐carbonitriles using a sequential nucleophilic addition reaction involving 4‐chloro‐3‐vinyl coumarins, α,α‐dicyanoolefins and ammonium acetate as a source of nitrogen. In this process, it is believed that ammonium acetate is converted into ammonia and acetic acid during the reaction. Ammonia is the source of nitrogen, and the acid produced can catalyze the progress of the reaction. Single‐crystal X‐ray analysis was performed to confirm the structure of one of the typical products. In addition, the photophysical characteristics of the product 3 a were investigated through absorption and emission spectroscopy. This analysis reveals that the new heterocyclic system has impressive fluorescence characteristics. Several advantages of the presented synthetic strategy can be found in its simplicity, readily available starting materials, high‐efficiency products, highly chemoselective route, metal‐free catalyst, and ability to purify products by washing them with EtOH (96 %), a technique called GAP (Group‐Assisted‐Purification) chemistry. [ABSTRACT FROM AUTHOR]

This study deeply integrates multimodal data analysis and big data technology, proposing a multimodal learning framework that consolidates various information sources, such as user geographic location, behavior data, and product attributes, to achieve a more comprehensive understanding and prediction of consumer behavior. By comparing the performance of unimodal and multimodal approaches in handling complex cross-border e-commerce data, it was found that multimodal learning models using the Adam optimizer significantly outperformed traditional unimodal learning models in terms of prediction accuracy and loss rate. The improvements were particularly notable in training loss and testing accuracy. This demonstrates the efficiency and superiority of multimodal methods in capturing and analyzing heterogeneous data. Furthermore, the study explores and validates the potential of big data and multimodal learning methods to enhance customer satisfaction in the cross-border e-commerce environment. Based on the core findings, specific applications of big data technology in cross-border e-commerce operations were further explored. A series of innovative strategies aimed at improving operational efficiency, enhancing consumer satisfaction, and increasing global market competitiveness were proposed. [ABSTRACT FROM AUTHOR]

Copyright of Food Research & Development is the property of Food Research & Development Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In recent years, powerful new forms of influence have been discovered that the internet has made possible. In the present paper, we introduce another new form of influence which we call the "opinion matching effect" (OME). Many websites now promise to help people form opinions about products, political candidates, and political parties by first administering a short quiz and then informing people how closely their answers match product characteristics or the views of a candidate or party. But what if the matching algorithm is biased? We first present data from real opinion matching websites, showing that responding at random to their online quizzes can produce significantly higher proportions of recommendations for one political party or ideology than one would expect by chance. We then describe a randomized, controlled, counterbalanced, double-blind experiment that measured the possible impact of this type of matching on the voting preferences of real, undecided voters. With data obtained from a politically diverse sample of 773 eligible US voters, we observed substantial shifts in voting preferences toward our quiz's favored candidate–between 51% and 95% of the number of people who had supported that candidate before we administered and scored the quiz. These shifts occurred without any participants showing any awareness of having been manipulated. In summary, in the present study we show not only that OME is a large effect; we also show that biased online questionnaires exist that might be shifting people's opinions without their knowledge. [ABSTRACT FROM AUTHOR]

Sebum is a complex mixture of skin lipids responsible for lubrication, moisture retention and skin protection from external factors such as bacteria and fungi. The physicochemical properties of natural sebum are not well understood and are not easily accessible. Artificial sebum is widely used for sebum‐related research such as dermal bioaccessibility, fingerprint production, dermatology, removal and sebum studies. It was found that the composition of artificial sebum affects the bioaccessibility of metals and drugs as well as the growth of some strains of bacteria. Squalene present in sebum was also found to be responsible for creating yellow stains on fabrics, whereas an increased concentration of fatty acids and triglycerides can lead to higher malodour of fabrics. Moreover, sebum and artificial sebum are poorly characterized with only 20 of 81 formulations characterized by certain techniques such as differential scanning calorimetry, nuclear magnetic resonance and thin‐layer chromatography. This article reviews the artificial sebum formulations reported in the open literature between 1965 and 2023. We have discussed the compositions, uses and characterization techniques of artificial sebum used in the previous work and compared their properties to those of human sebum. A total of 81 artificial sebum formulations were found across the literature with 17 new formulations identified. The artificial sebum composition varies greatly between publications and there is no consistent formulation. There is a wide range of chemicals that are used as the main components of artificial sebum. We have highlighted the effect of chemical composition and individual compounds on the overall properties of the artificial sebum reported, and recommend that there is a great potential for creating personalized cosmetics and home care products once the characteristics of sebum are better understood. [ABSTRACT FROM AUTHOR]