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By investigating the thermal-mechanical interaction between the through silicon via (TSV) and the Cu pad, this study aimed to determine the effect of electroplating defects on the upper surface protrusion and internal stress distribution of the TSV at various temperatures and to provide guidelines for the positioning of TSVs and the optimization of the electroplating process.

A simplified model that consisted of a TSV (100 µm in diameter and 300 µm in height), a covering Cu pad (2 µm thick) and an internal drop-like electroplating defect (which had various dimensions and locations) was developed. The surface overall deformation and stress distribution of these models under various thermal conditions were analyzed and compared.

The Cu pad could barely suppress the upper surface protrusion of the TSV if the temperature was below 250 ?. Interfacial delamination started at the collar of the TSV at about 250 ? and became increasingly pronounced at higher temperatures. The electroplating defect constantly experienced the highest level of strain and stress during the temperature increase, despite its geometry or location. But as its radius expanded or its distance to the upper surface increased, the overall deformation of the upper surface and the stress concentration at the collar of the TSV showed a downward trend.

Previous studies have not examined the influence of the electroplating void on the thermal behavior of the TSV. However, with the proposed methodology, the strain and stress distribution of the TSV under different conditions in terms of temperature, dimension and location of the electroplating void were thoroughly investigated, which might be beneficial to the positioning of TSVs and the optimization of the electroplating process.

This study aims to investigate the service performances of a new full-section asphalt concrete waterproof sealing structure (FSACWSS) for the high-speed railway subgrade through on-site tracking, monitoring and post-construction investigation.

Based on the working state of the waterproof sealing structure, the main functional characteristics were analyzed, and a kind of roller-compacted high elastic modulus asphalt concrete (HEMAC) was designed and evaluated by several groups of laboratory tests. It is applied to an engineering test section, and the long-term performance monitoring and subgrade dynamic performance testing system were installed to track and monitor working performances of the test section and the adjacent contrast section with fiber-reinforced concrete.

Results show that both the dynamic performance of the track structure and the subgrade in the test section meet the requirements of the specification limits. The water content in the subgrade of the test section is maintained at 8–18%, which is less affected by the weather. However, the water content in the subgrade bed of the contrast section is 10–35%, which fluctuates significantly with the weather. The heat absorption effect of asphalt concrete in the test section makes the temperature of the subgrade at the shoulder larger than that in the contrastive section. The monitoring value of the subgrade vertical deformation in the test section is slightly larger than that in the contrastive section, but all of them meet the limit requirements. The asphalt concrete in the test section is in good contact with the base, and there are no diseases such as looseness or spalling. Only a number of cracks are found at the joints of the base plates. However, there are more longitudinal and lateral cracks in the contrastive section, which seriously affects the waterproof and sealing effects. Besides, the asphalt concrete is easier to repair, featuring good maintainability.

This research can provide a basis for popularization and application of the asphalt concrete waterproof sealing structure in high-speed railways.

Many FDI studies focus on the advantages that businesses can gain through internationalization and internalization. More recent research has indicated that such traditional theories or perspectives may not sufficiently explain the subsequent success or failure of a firm’s operation in a foreign country, because the advantages gained through FDIs could be greatly affected by their strategic management in the host country environment. This study focused on the issue of a firm’s resources on its subsidiary’s competitiveness in a foreign country. A survey was undertaken in China. All companies participating in the study were small and medium‐sized Singapore‐China joint ventures and Singaporean wholly owned enterprises in China. The findings indicated that the variance in a firm’s performance in a foreign country can be largely explained by the six dimensions of firm resources: (1) technological resources, (2) owner/top manager’s managerial skills and capabilities, (3) employee’s Guanxi skills, (4) employee’s professional/technical knowledge, (5) the firm’s internal relationships and, (6) the firm’s external relationships. Among these six dimensions, employees’ professional knowledge and Guanxi skills, as well as a firm’s internal and external relationships, are significant predictors of Singaporean SMEs’ success in China.

Dyadic interactions are significant for human life. Most body sensor networks-based research studies focus on daily actions, but few works have been done to recognize affective actions during interactions. The purpose of this paper is to analyze and recognize affective actions collected from dyadic interactions.

A framework that combines hidden Markov models (HMMs) and k-nearest neighbor (kNN) using Fisher kernel learning is presented in this paper. Furthermore, different features are considered according to the interaction situations (positive situation and negative situation).

Three experiments are conducted in this paper. Experimental results demonstrate that the proposed Fisher kernel learning-based framework outperforms methods using Fisher kernel-based approach, using only HMMs and kNN.

The research may help to facilitate nonverbal communication. Moreover, it is important to equip social robots and animated agents with affective communication abilities.

The presented framework may gain strengths from both generative and discriminative models. Further, different features are considered based on the interaction situations.

For mitigating biocorrosion induced by sulfate-reducing bacteria (SRB) in seawater, the zwitterionic molecule layer (ZML) of poly (sulfobetaine methacrylate) is grafted onto B10 surface by chemical vapor deposition and surface-initiated atom transfer radical polymerization.

Energy-dispersive spectroscopy-attenuated total reflectance Fourier transform infrared spectroscopy and static contact angle measurements are used to characterize the as-formed layer.

After surface modification, B10 can significantly reduce SRB adhesion, demonstrating the good antifouling property. Further, the biocorrosion inhibition is investigated by potentiodynamic polarization and electrochemical impedance spectroscopy, indicating that ZML exhibits high resistance to biocorrosion with inhibition efficiency of approximately 90 per cent.

ZML performs a dual feature, i.e. antifouling film and corrosion inhibitor, for the biocorrosion inhibition.

This paper aims to assess the impact of incorporating foxnut powder (FP) into bakery products to evaluate their effect on product quality and nutritional characteristics.

Samples of refined flour (control) and refined wheat flour with varying levels of FP were prepared for each bakery item. Sensory evaluations using a nine-point hedonic scale were conducted. Different concentrations of FP (20% for cakes, 12.5% for bread and 12.5% for doughnuts) were tested to achieve sensory acceptability.

The addition of FP at specified concentrations achieved sensory acceptability in the tested bakery items, significantly impacting overall acceptability. Incorporating FP led to textural attribute alterations, including increased hardness, gumminess and chewiness, alongside reduced cohesiveness and elasticity. Color properties were influenced, affecting lightness, redness and yellowness of the bakery items. Proximate composition analysis highlighted shifts in moisture, protein, fiber, fat and ash content between control and accepted samples. Mineral content analysis revealed notable differences in calcium, potassium, iron, magnesium and sodium between control and accepted samples.

These findings demonstrate the potential of FP to enhance bakery products, offering promising industrial applications in producing nutritionally enriched and visually appealing baked products.

This paper aims to understand whether the relationship between psychological empowerment, psychological well-being and higher person–job fit based on the self-determination theory could have mitigated the Great Resignation crisis.

A cross-sectional study was conducted by collecting data from 351 respondents working in Indian organizations (Nifty, 2020) using a standardized questionnaire by using the multifaceted psychological construct within the work context.

This study highlights that a moderated mediation relationship between psychological empowerment (specifically “impact” or “choice”) and psychological well-being (specifically “environmental mastery”) is impacted by the person–job “demand-abilities” fit and enhances the intention to stay in the current “great resignation” context.

The authors map the theoretical and empirical research of the “intention to stay” by developing the “demand-abilities” fit, which leads to higher levels of psychological empowerment and psychological well-being to build adaptability through effective learning practices.

The authors establish the underlying linkages and future research agenda to strengthen the “intention to stay” during the extraordinarily stressful context of the covid-19 pandemic.

Due to product diversity, traditional quality signals in the hotel industry such as star ratings and brand affiliation do not work well in the accommodation booking process on the sharing economy platform. From a suppliers’ perspective, this study aims to apply the signaling theory to the booking of Airbnb listings and explore the influence of quality signals on the odds of an Airbnb listing being booked.

A binomial logistic model is used to describe the influences of different attributes on the market demand. Because of the large sample size, sequential Bayesian updating method is utilized in hospitality and tourism field for the first attempt.

Results show that, in addition to host-specific information such as “Superhost” and identity verification, attributes including price, extra charges, region competitiveness and house rules are all effective signals in Airbnb. The signaling impact is more effective for the listings without any review comments.

This study contributes to the literature by incorporating the signaling theory in the analysis of booking probability of Airbnb accommodation. The research findings are valuable to hosts in improving their booking rates and revenue. In addition, government and industrial management organizations can have more efficient strategy and policy planning.

In a pandemic framework (COVID-19), this chapter explores the impact of the global economy and socio-cultures concerning three axes: recreational, tourism, and hospitality. Although we slowly see an economic revival, it is well known that this sector of study is very susceptible to being affected by the context of nations. Following restrictions and measures taken by governments around the world to reduce the number of cases of coronavirus infections, many nations closed their borders, affecting international travel and by 2020 tourism had been reduced to the near cessation of operations due to the imminent fear of this poorly studied disease, and the service sector was negatively affected. It should be added that, according to the World Tourism Organization's projections, a decrease of between 20 and 30% is forecast for 2020 compared to the previous year.

The purpose of this paper is to model a block-based inspection policy for a multi-component system with stochastic dependence. Some components may develop a hidden failure, an occurrence of which neither stops the system nor accelerates the other components’ deterioration. On the other hand, other components may experience three states: healthy, defective and revealed failures. Any revealed failure of each component not only stops the system but also generates a shock to all the other ones, which increases their occurrence rate of hidden, defect and revealed failures.

A block-based inspection policy is considered to take advantage of economic dependence as follows. In addition to the periodic inspections, the system is also inspected at revealed failures’ moments of each component to detect and fix both defects and hidden failures on all the other components. To calculate the expected total cost, the recursive equations for the required expected values is first mathematically derived. Then, due to computational complexity, an efficient Monte Carlo simulation algorithm is designed to calculate the expected values.

The proposed approach is illustrated through a numerical example, and the optimal periodic inspection interval over a finite time horizon is obtained via minimization of the expected total cost. Finally, the correctness of the results is validated by conducting sensitivity analysis.

Planning an appropriate inspection policy over a finite time horizon becomes more complicated when considering a multi-component system because different units may experience different failure modes with stochastic dependence.