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The study aims to provide concrete service remediation and enhancement for LLM developers such as getting user forgiveness and breaking through perceived bottlenecks. It also aims to improve the efficiency of app users' usage decisions.

This paper takes the user reviews of the app stores in 21 countries and 10 languages as the research data, extracts the potential factors by LDA model, exploratively takes the misalignment between user ratings and textual emotions as user forgiveness and perceived bottleneck and uses the Word2vec-SVM model to analyze the sentiment. Finally, attributions are made based on empathy.

The results show that AI-based LLMs are more likely to cause bias in user ratings and textual content than regular APPs. Functional and economic remedies are effective in awakening empathy and forgiveness, while empathic remedies are effective in reducing perceived bottlenecks. Interestingly, empathetic users are “pickier”. Further social network analysis reveals that problem solving timeliness, software flexibility, model updating and special data (voice and image) analysis capabilities are beneficial in breaking perceived bottlenecks. Besides, heterogeneity analysis show that eastern users are more sensitive to the price factor and are more likely to generate forgiveness through economic remedy, and there is a dual interaction between basic attributes and extra boosts in the East and West.

The “gap” between negative (positive) user reviews and ratings, that is consumer forgiveness and perceived bottlenecks, is identified in unstructured text; the study finds that empathy helps to awaken user forgiveness and understanding, while it is limited to bottleneck breakthroughs; the dataset includes a wide range of countries and regions, findings are tested in a cross-language and cross-cultural perspective, which makes the study more robust, and the heterogeneity of users' cultural backgrounds is also analyzed.

This study aims to introduce a method for predicting the remaining useful life (RUL) of bearings based on parallel feature extraction. The proposed model provides prior knowledge and removes redundant handcrafted feature information, additionally, which focuses on the important features at different time scales.

Distinct from traditional parallel feature extraction methods, which can lead to information redundancy, a one-dimensional convolutional autoencoder is introduced to process selected indicators to remove redundancy and retain useful feature information. To fully capture the important degradation information within different stages in the feature sequences, a novel multi-scale attention feature fusion module is proposed to extract degradation features at different time scales. Considering the impact of degradation modes on RUL prediction, a dual-task prediction module based on no degradation mode labels is designed to obtain accurate RUL.

Comparative experiments and ablation studies on the PHM2012 bearing dataset verified the effectiveness of the proposed method. Furthermore, the rationality of the selected parameters is confirmed through model parameter analysis.

The novelty of the proposed method is that it not only provides prior knowledge but also further removes redundant information from prior knowledge. In addition, the distribution differences between the original features and their multi-scale convolution results are measured through Kullback–Leibler divergence as the attention scores, which allows the proposed method to focus on important information at different time scales.

This study focuses on the CFD numerical simulation and analysis of the vortex stacking problem at the top of the impeller of a high-speed fuel pump, mainly using LCS and entropy production theory to visualize the vortex at the top of the impeller as well as quantitatively analyzing the energy loss caused by the vortex at the top of the impeller. By combining the two methods, the two are well verified with each other that the stacking problem of the vortex at the top of the impeller and the location of the energy loss caused by the vortex are consistent with the vortex location. Such a method can reveal the problem of vortex buildup at the top of the lobe well, and provide a novel guidance idea for improving the performance of high-speed fuel pumps.

Based on CFD numerical simulation and analysis, this study mainly uses LCS and entropy production theory to visualize the top vortex of the impeller. Through the combination of the two methods, the accumulation problem of the top vortex of the impeller and the location of the energy loss caused by the vortex can be well revealed.

(1) The CFD numerical simulation analysis of the high-speed fuel pump is carried out, and the test is conducted to verify the numerical simulation results. The inlet and outlet pressure difference? P is used as the validation index, and the error analysis shows that the error between numerical simulation and test results is within 10%, which meets our requirements. Therefore, we carry out the next analysis with the help of CFD numerical simulation. By analyzing the full working condition simulation, its inlet and outlet differential pressure? P and efficiency? Are evaluated. It is found that its differential pressure decreases with the flow rate and its efficiency reaches its maximum at Qv = 9.87 L/s with a maximum efficiency of 78.32%. (2) We used the LCS in the analysis of vortices at the top of the impeller blades of a high-speed fuel pump. One of the metrics used to describe the LCS in fluid dynamics is the FTLE. The high FTLE region represents the region with the highest and fastest particle trajectory stretching velocity in the fluid flow. We performed a cross-sectional analysis of the FTLE field on the different height surfaces of the impeller on 25% Plane, 50% Plane, and 75% Plane, respectively. And a quarter turn of the rotor rotation was analyzed as a cycle divided into 8 moments. It is found that on 25% Plane, the vortex at the top of the lobe is not obvious, but there are high FTLE values on the shroud surface. On 50% Plane, the lobe top vortex is relatively obvious and the number of vortices is three. The vortex pattern remains stable with the rotating motion of the rotor. At 75% Plane, the lobe top vortex is more visible and its number of vortices increases to about 5 and the vortex morphology is relatively stable. The FTLE ridges visualize the vortex profile. This is a good guide for fluid dynamics analysis. (3) At the same time, we use the entropy production theory to quantitatively analyze the energy loss, and define the entropy production rate Ep. Through the entropy production analysis of the impeller shroud surface and the suction surface of the pressure surface of the blades at eight moments, we find that the areas of high energy loss are mainly concentrated in the leading and trailing edges of the blades as well as in the shroud surface close to the leading edge of the blades, and the value of the entropy production rate is up to 106 W/m3/K. The areas of high energy loss in the leading edge of the blades as well as the trailing edge show a curved arc, and the energy loss is decreasing as it moves away from the shroud surface and closer to the hub surface. The high energy loss areas at the leading and trailing edges of the blades are curved, and the energy loss decreases as they move away from the shroud surface and closer to the hub surface. The energy loss at the pressure surface of the blade is relatively small, about 5 × 105 W/m3/K, which is mainly concentrated near the leading edge of the blade near the shroud surface and the trailing edge of the blade near the hub surface. Such energy loss corresponds to the vortex LCS at the top of the impeller, and the two mirror each other.

This study focuses on the CFD numerical simulation and analysis of the vortex stacking problem at the top of the impeller of a high-speed fuel pump, mainly using LCS and entropy production theory to visualize the vortex at the top of the impeller as well as quantitatively analyzing the energy loss caused by the vortex at the top of the impeller. By combining the two methods, the two are well verified with each other that the stacking problem of the vortex at the top of the impeller and the location of the energy loss caused by the vortex are consistent with the vortex location. Such a method can reveal the problem of vortex buildup at the top of the lobe well, and provide a novel guidance idea for improving the performance of high-speed fuel pumps.

The aim of this study is to investigate the horizontal displacement effects of foundation pit excavation on adjacent metro stations and shield tunnel composite structures. It seeks to develop a theoretical calculation method capable of accurately assessing these engineering impacts, aiming to provide practical assistance for engineering applications.

This study introduces a model for shield tunnel segments incorporating rotation and misalignment, considering the constraints of metro stations. It establishes a displacement model for tunnel-station combinations during foundation pit excavation, deriving a formula for calculating station-proximal tunnel horizontal displacements. The method's accuracy is validated against field data from three engineering cases. The research also explores variations in tunnel displacement, inter-ring shear force, misalignment and rotation angle under different spatial relationships between pits, tunnels and stations.

This study models uneven deformation between stations and tunnels due to bending stiffness and shear constraints. It enhances the misalignment model with station-induced shear effects and introduces coefficients for their mutual interaction. Results show varied responses based on pit-station-tunnel positioning: minimal displacement near pit edges (coefficients around 0.1) and significant effects near pit centers (coefficients from 0.4 to 0.5). “Whip effect” from station constraints affects tunnel displacement, shear force, misalignment and rotation, with fluctuations decreasing with distance from excavation areas.

This study demonstrates significant originality and value. It introduces a novel displacement model for tunnel-station combinations considering station constraints, addressing theoretical calculations of horizontal displacement effects from foundation pit excavation on metro stations and shield tunnel structures. Through validation with field data and parameter studies, the concept of influence coefficients is proposed, offering insights into variations in structural responses under different spatial relationships. This research provides crucial technical support and decision-making guidance for optimizing designs and facilitating practical construction in similar engineering projects.

Prefabricated building (PB) has high technical requirements and is susceptible to safety accidents, and its construction occupational health and safety (OHS) problems should not be ignored. To promote the better development of PB, this study aims to measure their construction safety management level and propose corresponding countermeasures.

By systematically combing the relevant literature, this study extracts the influencing factors that appear frequently in several studies and categorizes them according to six dimensions: people, materials and components, technology, mechanical equipment, environment and system. Combining expert opinions, the measurement index system, including 6 primary indexes and 24 secondary indexes, is constructed. The structural entropy weight (SEW) method is applied to calculate the index weights. The cloud matter element (CME) model based on the weights is constructed to determine the level of construction occupational health and safety management (COHSM). A project case of a training building is used to verify it. The results obtained from the model are compared with those from other measurement models to verify the feasibility of the model in measuring the level of COHSM for PB.

The calculated weights show that technology is the most important for the COHSM of PB. The management level of the project in terms of people, materials and components, technology, machinery and equipment, environment and system is Level II good. The overall safety management level is also Level II, which is good. The model of this study is consistent with other model measurements. The methodology of this study yields reasonable and realistic results.

This study is the first to include occupational health dimensions in the research on the construction safety management of PB, which not only covers the key elements in traditional construction safety management but also considers the impact of the construction process, material use and technology of PB on safety management, making the measurement index system more scientific. Meanwhile, the introduction of the CME model based on the SEW method effectively solves the deficiencies of the traditional method in dealing with ambiguity and uncertainty and provides practitioners with more accurate and comprehensive measurement results. It helps practitioners formulate a more scientific management plan in combination with the actual situation and provides a guiding idea and practical path for the COHSM of similar projects.

The brake pipe system was an essential braking component of the railway freight trains, but the existing E-type sealing rings had problems such as insufficient low-temperature resistance, poor heat stability and short service life. To address these issues, low-phenyl silicone rubber was prepared and tested, and the finite element analysis and experimental studies on the sealing performance of its sealing rings were carried out.

The low-temperature resistance and thermal stability of the prepared low-phenyl silicone rubber were studied using low-temperature tensile testing, differential scanning calorimetry, dynamic thermomechanical analysis and thermogravimetric analysis. The sealing performance of the low-phenyl silicone rubber sealing ring was studied by using finite element analysis software abaqus and experiments.

The prepared low-phenyl silicone rubber sealing ring possessed excellent low-temperature resistance and thermal stability. According to the finite element analysis results, the finish of the flange sealing surface and groove outer edge should be ensured, and extrusion damage should be avoided. The sealing rings were more susceptible to damage in high compression ratio and/or low-temperature environments. When the sealing effect was ensured, a small compression ratio should be selected, and rubbers with hardness and elasticity less affected by temperature should be selected. The prepared low-phenyl silicone rubber sealing ring had zero leakage at both room temperature (RT) and −50 °C.

The innovation of this study is that it provides valuable data and experience for the future development of the sealing rings used in the brake pipe flange joints of the railway freight cars in China.

Supply chain management (SCM) has evolved to fulfill the demands of the dynamic global business environment. The development of the Internet of Things (IoT), which offers unmatched connectivity and real-time data insights, has further transformed SCM. This chapter provides an overview of SCM development and its integration with IoTs. This integration led to improved inventory control, supply chain optimization (SCO), and visibility which further enhances the conventional SCM and provides benefits, such as more accurate real-time tracking and monitoring, improved data analytics, more efficient logistics and transportation management, and reduced costs and wastages. However, despite these benefits, there are various associated challenges and concerns, like privacy and data security, compatibility and interoperability, implementation costs, returns on investment, trained workforce, and training requirements, which are required to be addressed. Additionally, the outcomes of this study and managerial implications are provided along with the future research scope. Overall, this chapter provides valuable insight into the transformative potential of IoT in SCM and practical suggestions on how managers can successfully navigate difficulties and get benefits from the IoT-SCM integration. Organizations can enhance their supply chain operations, efficiency, and innovation by actively confronting challenges and taking advantage of the opportunities provided by IoT technologies. This will ultimately result in the delivery of greater value to both stakeholders and customers.

The metallic alloys and their components fabricated via laser powder bed fusion (LPBF) suffer from the microvoids formed inevitably due to the extreme solidification rate during fabrication, which are impossible to be removed by heat treatment. This paper aims to remove those microvoids in as-built AlSi10Mg alloys by hot forging and enhance their mechanical properties.

AlSi10Mg samples were built using prealloyed powder with a set of optimized LPBF parameters, viz. 350 W of laser power, 1,170 mm/s of scan speed, 50 µm of layer thickness and 0.24 mm of hatch spacing. As-built samples were preheated to 430°C followed by immediate pressing with two different thickness reductions of 10% and 35%. The effect of hot forging on the microstructure was analyzed by means of X-ray diffraction, scanning electron microscopy, electron backscattered diffraction and transmission electron microscopy. Tensile tests were performed to reveal the effect of hot forging on the mechanical properties.

By using hot forging, the large number of microvoids in both as-built and post heat-treated samples were mostly healed. Moreover, the Si particles were finer in forged condition (∼150 nm) compared with those in heat-treated condition (∼300 nm). Tensile tests showed that compared with heat treatment, the hot forging process could noticeably increase tensile strength at no expense of ductility. Consequently, the toughness (integration of tensile stress and strain) of forged alloy increased by ∼86% and ∼24% compared with as-built and heat-treated alloys, respectively.

Hot forging can effectively remove the inevitable microvoids in metals fabricated via LPBF, which is beneficial to the mechanical properties. These findings are inspiring for the evolution of the LPBF technique to eliminate the microvoids and boost the mechanical properties of metals fabricated via LPBF.

The chapter introduced stealth construction as a transformative concept emerging in the construction industry, emphasising resilience and efficiency through innovative technologies, cutting-edge materials, and advanced methodologies. Drawing parallels to stealth aircraft, stealth construction aims to create buildings and infrastructure that blend seamlessly into their environments, minimising environmental impact and enhancing sustainability. This approach integrates smart materials, strategic planning, and covert practices throughout all construction stages, ensuring robust, adaptive, and discreet structures. Stealth construction represents a significant paradigm shift by prioritising energy efficiency, environmental responsibility, and resilience against natural disasters and cyber threats. It combines modern aerospace engineering principles with diverse construction practices to achieve construction invincibility, setting new standards for the industry regarding sustainability, security, and aesthetics.

The purpose of this study is to solve the problem that existing researches ignore the long-term and staged nature of digital transformation, failing to conduct specific discussions for different stages. It responded the call by constructing a three-stage evolutionary model to analyze the impact of digital transformation at different stages on the sustainable performance of manufacturing enterprises. The moderating effect of core technology capabilities is also explored, guided by the theory of assimilation innovation.

Based on the panel data of Chinese listed manufacturing companies from 2012 to 2020, this study empirically investigate the impact of digital transformation (digital process, digital operation and digital ecology) on sustainability performance (economic performance and environmental performance).

The findings indicate that digital operations and digital ecology significantly improve economic performance and environmental performance. Furthermore, the core technological capacity of the enterprise serves to modify the positive correlation between digital transformation at each stage and sustainable performance to some extent. In other words, when an enterprise is equipped with the requisite technological capacity, the digital transformation at each stage accelerates both economic performance and environmental performance, which in turn is conducive to an improvement in the enterprise’s sustainable development performance.

The findings contribute to the theoretical framework of digital transformation and sustainable development in all stages of enterprises. Furthermore, they provide guidance for achieving sustainable development through the implementation of digital transformation and the enhancement of core technological capacity.