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As humans are influenced by their environment, this study explores how different construal levels of ambient scent temperature affect consumers’ food choices.

This study employed a series of experimental methods from three studies, totalling five experiments. The experiments involved both laboratory and field settings, as well as neuroscientific techniques, thus generating empirical evidence.

Three studies were conducted to investigate how construal levels of both ambient scent temperature and tasks influenced food choice. Study 1 found that the construal level of ambient scent temperature significantly affected the type of food consumed. Study 2 included the task’s construal level as another factor to examine whether it interacted with the ambient scent temperature construal level. Both factors were significant, but only when perceived by the participants simultaneously. If the task’s construal level was manipulated before exposure to the ambient scent temperature, the latter did not have a significant effect. Study 3 employed a neuroscientific method to explore the mechanism behind the match between ambient scent temperature and food choices based on construal levels. The congruence of ambient scent temperature and food choice based on construal level enhanced positive emotions.

The sample size, although in line with other neuroscientific studies, was not sufficiently large for robust generalizability. This limitation can encourage future research to increase the number of participants and thus enhance the accountability of the findings. Another limitation is the participants’ cultural background.

This study’s practical implications are twofold. First, odour intensity was perceived to be the strongest in hot samples (Kähkönen et al., 1995), and we confirmed how ambient scent temperature can influence one’s food choice. Thus, food business operators can use warm ambient scent temperatures to promote hedonic food or snacks. Second, participants’ positive emotions were enhanced by the congruence of ambient scent temperature and food choice.

The association between ambient scent temperature and food choice has been extensively researched. However, this study provides an empirical explanation for the application of CLT. Accordingly, we performed a series of laboratory and field experiments using behavioural and neuroscientific approaches. The results confirmed that the construal level of ambient scent temperature significantly affected food choice. Moreover, the FAA revealed that one’s positive emotions would be prompted if there was congruence in the construal levels of ambient scent temperature and food choice.

This study has theoretical and managerial value because people’s poor understanding of food selection is affected by ambient scent temperature. Moreover, its novelty lies in the application of a neuroscientific approach to one experiment.

The selection of sensitive temperature measurement points is the premise of thermal error modeling and compensation. However, most of the sensitive temperature measurement point selection methods do not consider the influence of the variability of thermal sensitive points on thermal error modeling and compensation. This paper considers the variability of thermal sensitive points, and aims to propose a sensitive temperature measurement point selection method and thermal error modeling method that can reduce the influence of thermal sensitive point variability.

Taking the truss robot as the experimental object, the finite element method is used to construct the simulation model of the truss robot, and the temperature measurement point layout scheme is designed based on the simulation model to collect the temperature and thermal error data. After the clustering of the temperature measurement point data is completed, the improved attention mechanism is used to extract the temperature data of the key time steps of the temperature measurement points in each category for thermal error modeling.

By comparing with the thermal error modeling method of the conventional fixed sensitive temperature measurement points, it is proved that the method proposed in this paper is more flexible in the processing of sensitive temperature measurement points and more stable in prediction accuracy.

The Grey Attention-Long Short Term Memory (GA-LSTM) thermal error prediction model proposed in this paper can reduce the influence of the variability of thermal sensitive points on the accuracy of thermal error modeling in long-term processing, and improve the accuracy of thermal error prediction model, which has certain application value. It has guiding significance for thermal error compensation prediction.

The paper aims to reveal the relationship among energy efficiency, thermal comfort and thermal regulation of electrically heated footwear and to investigate influencing factors on the energy efficiency and thermal comfort.

A finite volume model was proposed to simulate the two-dimensional heat transfer in electrically heated footwear (EHF) under an extremely cold condition. The model domain consists of three-layer footwear materials, a heating pad, a sock material, an air gap and skin tissues. Model predictions were verified by experimental data from cold-contact exposure. Then the influencing factors on the energy efficiency and thermal comfort were investigated through parametric analysis.

The paper demonstrated that the skin temperature control (STC) mode provided superior thermal comfort compared to the heating pad temperature control (HPTC) mode. However, the energy efficiency for the HPTC mode with a heating temperature of 38 °C was 18% higher than the STC mode. The energy efficiency of EHF while reaching the state of thermal comfort was strongly determined by the arrangement and connection of heating elements, heating temperature, thickness and thermal conductivity of footwear materials.

The findings obtained in this paper can be used to engineer the EHF that provides optimal thermal comfort and energy efficiency in cold environments.

To evaluate the temperature-dependency of the Young’s and shear moduli of concrete after exposure to moderately elevated temperatures using the non-destructive impulse excitation technique (IET).

The study involved heating the concrete up to 225 °C and measuring the dynamic Young’s and shear moduli using the non-destructive technique of impulse excitation, which measures the natural vibration frequency from a mechanical impulse received by an acoustic sensor. The effects of temperature on the dynamic Young’s and shear moduli were analysed and the importance of the spatial variability of the measured values was also verified.

The study found that even moderately elevated temperatures (below 225 °C) resulted in a significant permanent reduction in the Young’s modulus of concrete (reduction in the range of 23%–36% for the maximum temperature considered in this research) as well as a modest and permanent reduction in the shear modulus of around 6%. It was also observed that spatial variability of the mechanical properties of concrete plays an important role in the measured values; higher dispersion of the results was found for the values of the Young’s and shear moduli of concrete measured along the height of the beam. The non-destructive test method used in this study was found to be extremely useful in the investigation of heat-related damage in concrete structures for its ease of use, low time consumption and accuracy. The results were consistent with the published literature.

This study provides important insights into the temperature-dependent behaviour of the dynamic Young’s and shear moduli of concrete and highlights the significance of proper consideration of the spatial variability of the measured values. The use of a non-destructive test method for continuous acoustic testing during heating and cooling proved to be effective, and the findings contribute to the fields of materials science and civil engineering in understanding the effects of elevated temperatures on concrete properties. The findings confirm that IET can be easily used to gather important information in the condition assessment and rehabilitation of concrete structures after a fire event. Further studies to foster the application of this technique to real structures are suggested.

The paper aims to study the effect of sintering temperature on the microstructure, shear strength and ratcheting fatigue life of nanosilver sintered lap shear joint. In addition, the Gerber model is used to predict the ratcheting fatigue lives of nanosilver sintered lap shear joints at different sintering temperatures.

In this paper, the nanosilver sintered lap shear joints were prepared at three sintering temperatures of 250 °C, 280 °C and 310 °C. The bonding quality was characterized by scanning electron microscopy, X-ray diffraction, transmission electron microscope and shear tests, and the long-term reliability was studied by conducting ratcheting fatigue tests. In addition, three modified models based on Basquin equation were used to predict the ratcheting fatigue life of nanosilver sintered lap shear joint and their accuracies were evaluated.

When the sintering temperature is 250°C, the nanosilver sintered lap shear joint shows the porosity of 22.9 ± 1.6 %, and the shear strength of 22.3 ± 2.4 MPa. Raising the sintering temperature enhances silver crystallite size, strengthens sintering necks, thus improves shear strength and ratcheting fatigue life in joints. In addition, the ratcheting fatigue lives of the joints sintered at different temperatures are effectively predicted by three equivalent force models, and the Gerber model shows the highest life prediction accuracy.

The sintered silver bondline is suffering a complex stress state. The study only takes the shear stress into consideration. The tensile stress and the combination of shear stress and tensile stress can to be considered in the future study.

The paper provides the experimental and theoretical support for robust bonding and long-term reliability of sintered silver structure.

The introduced model can predict the ratcheting fatigue lives of the joints sintered at different temperatures, which shows a potential in engineering applications.

The study revealed the relationship between the sintering temperature and the microstructure, the shear strength and the ratcheting fatigue life of the joint. In addition, the Gerber model can predict the ratcheting fatigue life accurately at different sintering temperatures.

At present, using the finite element method is difficult to efficiently and accurately construct the temperature field of mass concrete based on temperature measurement points. Thus, there is a need to propose a method for improvement.

This study developed an implicit finite element method that digitally constructs the temperature field of mass concrete based on temperature measurement data. That is, in the proposed method of this paper, the temperature of the measuring point is also one of the boundary conditions, which real-time corrects the calculation error.

In this method, during the digital construction of the temperature field, the computed temperature approaches the actual measured value at the point of measurement with increasing iteration steps. Using this method and sufficient temperature measurement data, the errors in calculation conditions (such as the boundary conditions, the initial casting temperature and material parameters) can be automatically corrected during the iterative computation process.

This new method can improve calculation accuracy and allows the digitally constructed temperature field to converge to its true value with sufficient measurement data.

To enhance the performance of hydrostatic bearings, graphene serves as a lubricant additive. Using the high thermal conductivity of graphene, the purpose of this study is to focus on the impact of graphene nano-lubricating oil hydrostatic bearing temperature rise at various speeds and eccentricities.

The thermal conductivity of graphene nano-lubricating oil was calculated by molecular dynamics method and based on the viscosity–temperature effect, the coupled heat transfer finite element model of hydrostatic bearing was established; temperature rise of pure lubricating oil and graphene nano-lubricating oil hydrostatic bearing were analysed at different speed and eccentricity based on computational fluid dynamics method.

With the increase of speed and eccentricity, the temperature rise of 0.2% graphene nano-lubricating oil bearings is lower than that of pure lubricating oil bearings; in addition with the increase of graphene mass fraction, the temperature rise of graphene nano-lubricating oil bearings is always higher than that of pure lubricating oil bearings, and the higher the speed, the more obvious the phenomenon.

The effects of graphene as a lubricant additive on the thermal conductivity of nano-lubricating oil and the variation of the temperature rise of graphene nano-lubricating oil bearings compared to pure lubricating oil bearings were analysed by combining micro and macro methods.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-12-2023-0388

The purpose of this study is to investigate the accumulation process of transfer film formation and dissipation and its effect on friction coefficients in non asbestos organic friction materials with various lubricant FeS₂ contents.

In total, 2.5%, 5% and 10% FeS₂ were added as lubricating components to the friction materials. Friction tests composed of two stages were conducted for these friction materials, and the friction surfaces of the counterpart discs were examined using scanning electron microscopy.

The transfer film formation reduced the friction coefficients, and the transfer film dissipation influenced the recovery of the friction coefficients. The effect of a high content of FeS₂ was to promote the transfer film formation at high temperatures and to hinder the transfer film dissipation at low temperatures, thus resulting in a decrease in the friction coefficients at high temperatures together with recovery retardation at low temperatures.

FeS₂ contributed to the transfer film formation at high temperatures in the fade test but hindered the transfer film removal in the recovery test, resulting in the retardation of friction coefficient recovery. The mechanism by which the FeS₂ lubricant component affected the transfer film formation and dissipation was analyzed and attributed to the different levels of FeS₂ pyrolysis at different temperature levels.

The purpose of this study is to investigate the thermoforming process of 3D-printed parts made from polylactic acid (PLA) and explore its application in producing wrist-hand orthoses. These orthoses were 3D printed flat, heated and molded to fit the patient’s hand. The advantages of such an approach include reduced production time and cost.

The study used both experimental and numerical methods to analyze the thermoforming process of PLA parts. Thermal and mechanical characteristics were determined at different temperatures and infill densities. An equivalent material model that considers infill within a print is proposed. Its practical use was proven using a coupled finite-element analysis model. The simulation strategy enabled a comparative analysis of the thermoforming behavior of orthoses with two designs by considering the combined impact of natural convection cooling and imposed structural loads.

The experimental results indicated that at 27°C and 35°C, the tensile specimens exhibited brittle failure irrespective of the infill density, whereas ductile behavior was observed at 45°C, 50°C and 55°C. The thermal conductivity of the material was found to be linearly related to the temperature of the specimen. Orthoses with circular open pockets required more time to complete the thermoforming process than those with hexagonal pockets. Hexagonal cutouts have a lower peak stress owing to the reduced reaction forces, resulting in a smoother thermoforming process.

This study contributes to the existing literature by specifically focusing on the thermoforming process of 3D-printed parts made from PLA. Experimental tests were conducted to gather thermal and mechanical data on specimens with two infill densities, and a finite-element model was developed to address the thermoforming process. These findings were applied to a comparative analysis of 3D-printed thermoformed wrist-hand orthoses that included open pockets with different designs, demonstrating the practical implications of this study’s outcomes.

The effect of humidity, temperature and temperature ramping rate on the dimensional changes of the photo‐cured stereolithography (SL) resin SL5195 was investigated. It was found that moisture absorption by the SL resin is a very slow process at ambient temperatures. Varying relative humidity (RH) between 20 and 90 per cent in the environment only produced slight changes in the sample dimensions during the time period investigated. Increasing the environment temperature caused a significant increase in the sample dimensions through thermal expansion along with accelerated moisture absorption at 50 per cent or higher RH. Increasing the temperature ramping rate reduces the moisture absorption during the thermal cycles.