Sonic food words influence the experience of beverage healthfulness

The consumption of healthful foods is relevant for the well-being of society. However, understanding healthfulness may be difficult because, in some cultures (i.e., the U.S.), individuals assume that unhealthy equals tasty, an association that does not hold in other contexts (i.e., France). Auditory cues could serve to inform consumers about the expected experience with food and thus could signal the sensory experience of a healthy product. This research contributes to the literature on the use of sound symbolism for analysis of the influence of onomatopoeias as packaging information that influences the expected healthfulness of a bottled drink. The study is a 4 × 4 mixed-model experiment. Grouping was done according to onomatopoeia variables as follows: “Fizz,” “Glup,” “Ahhh,” and control. Beverage color, a within-subject variable, was grouped as green, yellow, red, and control. Results show that the healthful concept is defined in two dimensions: fulfilling and light. Onomatopoeias motivated the experience of a less fulfilling beverage, which had the strongest effect on “Fizz” condition. For the light dimension, “Ahhh” diminishes the perception of light, thus creating the idea that the drink is high in calories. This study reaches out to food industries on the need to find the most consistent and pleasurable sound associated with their products. This will enable food industries to provide information to consumers as well as ascertain how much they enjoy the product.     

Digital twin-based assembly data management and process traceability for complex products

Complex products such as satellites, missiles, and aircraft typically have demanding requirements for dynamic data management and process traceability. The assembly process for these complex products involves high complexity, strong dynamics, many uncertainties, and frequent rework and repair, especially in the model development stage. Achieving assembly data management and process traceability for complex products has always been a challenge. A recently proposed solution involves one-to-one mapping of the corresponding physical entity, also known as the digital twin method. This paper proposes a digital twin-based assembly data management and process traceability approach for complex products. First, the dynamic evolutionary process of complex product assembly data was analyzed from three dimensions: granularity, period and version. Then, a framework of digital twin-based assembly data management and process traceability for complex products was constructed. Some core techniques are: 1) workflow-based product assembly data organization and version management; 2) synchronous modeling of the product assembly process based on digital twin; and 3) hierarchical management and traceability of product assembly data based on digital twin. On this basis, an algorithm flowchart for generating a product assembly data package was created, which includes product assembly data management, assembly process traceability, and generation of a product assembly data package. Furthermore, the Digital Twin-based Assembly Process Management and Control System (DT-APMCS) was designed to verify the efficiency of the proposed approach. Some aerospace-related assembly enterprises are currently using DT-APMCS and achieving satisfactory results. Finally, a summary of our work is given, and the future research work is also discussed.     

Research and development of liquid hydrogen (LH2) temperature monitoring system for marine applications

Monitoring the temperature in liquid hydrogen (LH₂) storage tanks on ships is important for the safety of maritime navigation. In addition, accurate temperature measurement is also required for commercial transactions. Temperature and pressure define the density of liquid hydrogen, which is directly linked to trading interests. In this study, we developed and tested a liquid hydrogen temperature monitoring system that uses platinum resistance sensors with a nominal electrical resistance of approximately 1000 Ω at room temperature, PT-1000, for marine applications. The temperature measurements were carried out using a newly developed temperature monitoring system under different pressure conditions. The measured values are compared with a calibrated reference PT-1000 resistance thermometer. We confirm a measurement accuracy of ±50 mK in a pressure range of 0.1 MPa–0.5 MPa.     

Rate equation theory for the hydrogenation kinetics of Mg-based materials

A uniform solid product layer normally assumed in the shrinking-core model cannot predict the kinetic transition behavior of the H₂ adsorption reactions. In this study, the concept of a uniform solid product layer has been replaced by that of the inward growth of solid products on the solid surface. A rate equation is established to calculate the inward growth of the solid product and was implemented into the shrinking-core model to calculate the H₂ adsorption kinetics for various shapes of Mg-based materials. The prediction accuracy of the developed model is verified from the detailed experimental data. To account for the external gas diffusion around the particle and the intraparticle gas diffusion, an analytical equation is derived using the Thiele modulus method. This model can be used to analyze various kinetic aspects and to analyze the effect of change in the particle microstructure on intraparticle diffusion.     

Intelligent Kano classification of product features based on customer reviews

Product features can be classified into different categories based on customer opinions. The rapid development of artificial intelligence and machine learning paves the way toward computational analysis of customer reviews for opinion mining. This paper presents an Intelligent Kano framework to extract, quantify, and classify different product features based on customer reviews. The framework is enabled by a novel integration of multiple artificial intelligence and machine learning techniques such as sentiment analysis and anomaly detection. A case study is conducted to validate the framework’s effectiveness. Over 12,000 customer reviews on two coffee machines are analyzed for the classification.     

Integrated rough VIKOR for customer-involved design concept evaluation combining with customers’ preferences and designers’ perceptions

Customer-involved design concept evaluation (DCE) allows customers to take part in evaluating the design alternatives to get more popular design concept. Traditional customer-involved DCE methods still focus on the collection of customer responses and only consider cost and benefit characteristics of design criteria in multi-criteria decision-making (MCDM) based evaluation process. Few studies have customized the decision-making algorithms specifically aimed at customers’ preferences. This paper further explores the customers’ influences in the early stages of the product design development, and proposes a new rough number based MCDM model (i.e., VIKOR) incorporating customers’ preferences for design specifications along with designers’ perceptions for the characteristics of design criteria (cost and benefit) to perform concept evaluation under subjective environment, and this proposed method is named as integrated rough VIKOR (IR-VIKOR). The objective of this study is to identify the best design concept which maximizes the satisfactions of expectations from most customers as well as conforms to the characteristics of design criteria. Firstly, Shannon entropy is used to obtain the weightings and relative importance ratings of design criteria from the customers’ preferences. Secondly, the customers’ preferences for design attribute values, the importance ratings of design criteria and the characteristics of design criteria are combined together to define the ideal solutions to calculate the rough evaluation index of each design alternative in IR-VIKOR, and finally the ranking result is provided by IR-VIKOR to determine the best design concept. A practical design example is introduced to illustrate the evaluation process of this proposed method, and the empirical comparisons are further carried out to validate its superiority for DCE. Through the sensitivity analysis experiments including i) inside IR-VIKOR, and ii) between IR-VIKOR and other classical MCDM methods, the proposed method is proved to be a reliable and feasible customer-involved DCE approach.     

How does external knowledge sourcing enhance product development? Evidence from drug commercialization

Like in many industries, knowledge management is the key to the successful developments of new drugs and other commercialized products in the pharmaceutical sector. Prior studies have shown that knowledge management requires effective external knowledge sourcing strategies. We argue that both the geographic distance to external knowledge sources and the diversity of such sources have strong influences on the success of the search process and the development of new drugs. We test these theoretical assumptions by applying several advanced estimation techniques on a combined broad set of data from the U.S. Patent and Trademarks Office (USPTO) and U.S. Food and Drug Administration (FDA). We find empirical evidence that the intensity of external knowledge sourcing activities has a positive effect on new drugs approval and commercialization. Specifically, our models predict that a higher number of references to prior patents increases the probability of a new patented drug to be approved and commercialized. Furthermore, the geographic distance covered in the search for external knowledge also positively contributes to drug commercialization. Important management implications derived from these findings are also discussed in the paper.     

A personal retrospect on three decades of high temperature fuel cell research; ideas and lessons learned

In1986 the Dutch national fuel cell program started. Fuel cells were developed under the paradigm of replacing conventional technology. Coal-fired power plants were to be replaced by large-scale MCFC power plants fuelled by hydrogen in a full-scale future hydrogen economy. With today's knowledge we will reflect on these and other ideas with respect to high temperature fuel cell development including the choice for the type of high temperature fuel cell. It is explained that based on thermodynamics proton conducting fuel cells would have been a better choice and the direct carbon fuel cell even more so, with electrochemical gasification of carbon as the ultimate step. The specific characteristics of fuel cells and multisource multiproduct systems were not considered, whereas we understand now that these can provide huge driving forces for the implementation of fuel cells compared to just replacing conventional combined heat and power production technology.     

Should emoji replace emotion words in questionnaire-based food-related consumer research?

Emotion word questionnaires remain dominant in food-related emotion research despite acknowledged limitations. Emoji questionnaires can overcome some of these limitations but are not yet regarded as a strong alternative to emotion word questionnaires. We believe they have the potential to earn this right and use this invited opinion piece to explain why. Following a brief introduction about emoji, advantages of emoji questionnaires are summarised: – enhanced ecological validity, familiarity and cross-culturally shared meanings. We then address concerns that hinder uptake of emoji questionnaires, including emoji meanings/interpretations, appropriateness for older consumers and ability to represent emotional arousal (activation to deactivation). Finally, we offer suggestions for how to accelerate the uptake of emoji questionnaires in sensory and consumer science, which include: i) more applied studies using emoji questionnaires, ii) establishing emoji meanings in the context of eating of drinking, iii) adopting open-ended question formats, iv) comparing emoji and emotion word questionnaires, and v) establishing guidelines for emoji questionnaires. An important spill-over benefit of research to develop emoji questionnaires is that it exposes the lack of similar research for emotion word questionnaires. We encourage colleagues in the field to engage in the task of conducting needed methodological research on emoji and emotion words alike.     

Experimental study of the pyrolysis of waste bitumen for oil production

This work focuses on bitumen slow pyrolysis. Mass and energy yields of oil, solid and gas were obtained from pyrolysis experiments using a semi-batch reactor in a nitrogen atmosphere, under three non-isothermal conditions (maximum temperature: 450 °C, 500 °C and 550 °C). The effect of temperature on the product yields was discussed. The gas compositions were analysed using gas chromatography (GC) and the heating value of oil and solid residue was also measured. Using a thermo-gravimetric analyser, kinetic parameters were evaluated through Ozawa-Flynn-Wall (OFW) method. Results showed that oil yield is maximum at 500 °C (50%). Moreover, gas yield increased with increasing pyrolysis temperature from 18% to 36%. On the other hand, solid yield showed an opposite trend: it decreased from 39% to 32%. As regard energy yields, they showed a similar trend with the mass ones. H_2, CH₄, C₂H₄, C₂H₆ and C₃H₈ are the main components of the produced gas phase. It has been noticed that the recovery of bitumen to liquid oil through pyrolysis process had a great potential since the oil produced had high calorific value comparable with commercial fuels.