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Construction robots, as a disruptive innovation in the construction industry, can effectively resolve industry pain points such as low construction efficiency, high safety risks, and high labor costs. For spraying robots of building exterior wall, the adoption of Human-Computer Interaction (HCI) control technology can effectively improve spraying quality, save raw materials, reduce construction costs, and enhance construction efficiency while ensuring personnel safety. The authors developed a prototype of a spraying robot based on HCI technology and proposed a real-time control method based on dynamic gesture recognition. This method focuses on the distance changes of 21 joints on the hand, combines the Support Vector Machine (SVM) classification algorithm, and constructs a real-time closed-loop control system including gesture acquisition, algorithm analysis, and robot execution. By capturing the movement trajectory of the right index finger and recognizing gestures of the left hand, the maximum error of turning head is only 0.89°, and the maximum error of the telescopic rod is only 0.21 mm. Through comparative experiments with automatic trajectory operation mode and HCI control mode at construction site, the HCI control mode can still maintain good spraying effects under different wind speed interference conditions, ensuring the continuity and accuracy of spraying quality.

Realizing the common wealth of all people is the essential requirement of socialism with Chinese characteristics. Measuring the process of realizing common wealth and the differences between groups is one of the important issues that need to be addressed urgently. In order to reasonably measure the process of realizing common wealth in China, on the premise of horizontal comparability and vertical consistency, the principles of comparability and consistency are introduced, and a comparative method of opportunity advantage based on income distribution is proposed from the perspective of opportunity equity. Using the 2012–2020 CFPS data to measure and test the opportunity advantages and their differences across regions and groups in China. The study found, firstly, that the opportunity advantage persists but tends to diminish across groups, with the more educated group having a more pronounced opportunity advantage, but that this advantage is diminishing over time. Secondly, the doctoral degree group has a greater probability of earning higher incomes, followed by the master’s and bachelor’s degree groups, but this opportunity advantage, i.e., the probability of earning higher incomes, is diminishing, i.e., the education dividend is diminishing. Third, the difference in opportunity advantage between urban and rural areas still exists, as evidenced by the greater probability of higher incomes in towns than in rural areas, but this advantage has narrowed further over time, with a clear process of urban-rural integration. Fourthly, in terms of gender, men have a certain opportunity advantage over women, but this difference is not significant. Fifthly, in the context of education levels, gender and urban/rural subgroups, under the framework proposed in this paper, China has achieved some success in the process of realizing the common wealth, and is showing a steady upward trend.

Skeletal muscle is essential for body physical activity, energy metabolism, and temperature maintenance. It has excellent capabilities to maintain homeostasis and to regenerate after injury, which indispensably relies on muscle stem cells, satellite cells (MuSCs). The quiescence, activation, and differentiation of MuSCs are tightly regulated in homeostatic and regenerating muscles. Among the important regulators are intramuscular macrophages, which are functionally heterogeneous with different subtypes present in a spatiotemporal manner to regulate the balance of different MuSC statuses. During chronic injury and aging, intramuscular macrophages often undergo aberrant activation, which in turn disrupts muscle homeostasis and regenerative repair. Growing evidence suggests that the aberrant activation is mainly triggered by altered muscle microenvironment. The trained immunity that affects myeloid progenitors during hematopoiesis may also contribute. Aged immune system may contribute, in part, to the aging-related sarcopenia and compromised skeletal muscle injury repair. As macrophages are actively involved in the progression of many muscle diseases, manipulating their functional activation has become a promising therapeutic approach, which requires comprehensive knowledge of the cellular and molecular mechanisms underlying the diverse activation. To this end, we discuss here the current knowledge of multifaceted role of macrophages in skeletal muscle homeostasis, injury, and repair.

Realizing the common wealth of all people is the essential requirement of socialism with Chinese characteristics. Measuring the process of realizing common wealth and the differences between groups is one of the important issues that need to be addressed urgently. In order to reasonably measure the process of realizing common wealth in China, on the premise of horizontal comparability and vertical consistency, the principles of comparability and consistency are introduced, and a comparative method of opportunity advantage based on income distribution is proposed from the perspective of opportunity equity. Using the 2012-2020 CFPS data to measure and test the opportunity advantages and their differences across regions and groups in China. The study found, firstly, that the opportunity advantage persists but tends to diminish across groups, with the more educated group having a more pronounced opportunity advantage, but that this advantage is diminishing over time. Secondly, the doctoral degree group has a greater probability of earning higher incomes, followed by the master's and bachelor's degree groups, but this opportunity advantage, i.e., the probability of earning higher incomes, is diminishing, i.e., the education dividend is diminishing. Third, the difference in opportunity advantage between urban and rural areas still exists, as evidenced by the greater probability of higher incomes in towns than in rural areas, but this advantage has narrowed further over time, with a clear process of urban-rural integration. Fourthly, in terms of gender, men have a certain opportunity advantage over women, but this difference is not significant. Fifthly, in the context of education levels, gender and urban/rural subgroups, under the framework proposed in this paper, China has achieved some success in the process of realizing the common wealth, and is showing a steady upward trend.

Lamb wave approaches have been accepted as efficiently non-destructive evaluations in structural health monitoring for identifying damage in different states. Despite significant efforts in signal process of Lamb waves, physics-based prediction is still a big challenge due to complexity nature of the Lamb wave when it propagates, scatters and disperses. Machine learning in recent years has created transformative opportunities for accelerating knowledge discovery and accurately disseminating information where conventional Lamb wave approaches cannot work. Therefore, the learning framework was proposed with a workflow from dataset generation, to sensitive feature extraction, to prediction model for lamb-wave-based damage detection. A total of 17 damage states in terms of different damage type, sizes and orientations were designed to train the feature extraction and sensitive feature selection. A machine learning method, support vector machine (SVM), was employed for the learning model. A grid searching (GS) technique was adopted to optimize the parameters of the SVM model. The results show that the machine learning-enriched Lamb wave-based damage detection method is an efficient and accuracy wave to identify the damage severity and orientation. Results demonstrated that different features generated from different domains had certain levels of sensitivity to damage, while the feature selection method revealed that time-frequency features and wavelet coefficients exhibited the highest damage-sensitivity. These features were also much more robust to noise. With increase of noise, the accuracy of the classification dramatically dropped.

China has entered the economic transition in the post-financial crisis era, with unprecedented new features that significantly lead to a decline in its carbon emissions. However, regional disparity implies different trajectories in regional decarbonisation. Here, we construct multi-regional input-output tables (MRIO) for 2012 and 2015 and quantitatively evaluate the regional disparity in decarbonisation and the driving forces during 2012-2015. We found China's consumption-based emissions peaked in 2013, largely driven by a peak in consumption-based emissions from developing regions. Declined intensity and industrial structures are determinants due to the economic transition. The rise of the Southwest and Central regions of China have become a new feature, driving up emissions embodied in trade and have reinforced the pattern of carbon flows in the post-financial crisis period. Export-related emissions have bounced up after years of decline, attributed to soaring export volume and export structure in the Southeast and North of the country. The disparity in developing regions has become the new feature in shaping China's economy and decarbonisation.

Skeletal muscle is essential to physical activity and energy metabolism. Maintaining intact functions of skeletal muscle is crucial to health and wellbeing. Evolutionarily, skeletal muscle has developed a remarkable capacity to maintain homeostasis and to regenerate after injury, which indispensably relies on the resident muscle stem cells, satellite cells. Satellite cells are largely quiescent in the homeostatic steady state. They are activated in response to muscle injury. Activated satellite cells proliferate and differentiate into myoblasts. Myoblasts fuse to form myotubes which further grow and differentiate into mature myofibers. This process is tightly regulated by muscle microenvironment that consists of multiple cellular and molecular components, including macrophages. Present in both homeostatic and injured muscles, macrophages contain heterogeneous functional subtypes that play diverse roles in maintaining homeostasis and promoting injury repair. The spatial-temporal presence of different functional subtypes of macrophages and their interactions with myogenic cells are vital to the proper regeneration of skeletal muscle after injury. However, this well-coordinated process is often disrupted in a chronic muscle disease, such as muscular dystrophy, leading to asynchronous activation and differentiation of satellite cells and aberrant muscle regeneration. Understanding the precise cellular and molecular processes regulating interactions between macrophages and myogenic cells is critical to the development of therapeutic manipulation of macrophages to promote injury repair. Here, we review the current knowledge of the many roles played by macrophages in the regulation of myogenic cells in homeostatic, regenerating, and dystrophic skeletal muscles.

The zero-velocity update (ZUPT) algorithm is a pivotal advancement in pedestrian navigation accuracy, utilizing foot-mounted inertial sensors. Its key issue hinges on accurately identifying periods of zero-velocity during human movement. This paper introduces an innovative adaptive sliding window technique, leveraging the Fourier Transform to precisely isolate the pedestrian’s gait frequency from spectral data. Building on this, the algorithm adaptively adjusts the zero-velocity detection threshold in accordance with the identified gait frequency. This adaptation significantly refines the accuracy in detecting zero-velocity intervals. Experimental evaluations reveal that this method outperforms traditional fixed-threshold approaches by enhancing precision and minimizing false positives. Experiments on single-step estimation show the adaptability of the algorithm to motion states such as slow, fast, and running. Additionally, the paper demonstrates pedestrian trajectory localization experiments under a variety of walking conditions. These tests confirm that the proposed method substantially improves the performance of the ZUPT algorithm, highlighting its potential for pedestrian navigation systems.

Welding is widely used in the connection of metallic structures, including welded joints in oil/gas metallic pipelines and other structures. The welding process is vulnerable to the inclusion of different types of welding defects, such as lack of penetration and undercut. These defects often initialize early-age cracking and induced corrosion. Moreover, welding-induced defects often accompany other types of mechanical damage, thereby leading to more challenges in damage detection. As such, identification of weldment defects and interaction with other mechanical damages at their early stage is crucial to ensure structural integrity and avoid potential premature failure. The current strategies of damage identification are achieved using ultrasonic guided wave approaches that rely on a change in physical parameters of propagating waves to discriminate as to whether there exist damaged states or not. However, the inherently complex nature of weldment, the complication of damages interactions, and large-scale/long span structural components integrated with structure uncertainties pose great challenges in data interpretation and making an informed decision. Artificial intelligence and machine learning have recently become emerging methods for data fusion, with great potential for structural signal processing through decoding ultrasonic guided waves. Therefore, this study aimed to employ the deep learning method, convolutional neural network (CNN), for better characterization of damage features in terms of welding defect type, severity, locations, and interaction with other damage types. The architecture of the CNN was set up to provide an effective classifier for data representation and data fusion. A total of 16 damage states were designed for training and calibrating the accuracy of the proposed method. The results revealed that the deep learning method enables effectively and automatically extracting features of ultrasonic guided waves and yielding high precise prediction for damage detection of structures with welding defects in complex situations. In addition, the effectiveness and robustness of the proposed methods for structure uncertainties using different embedding materials, and data under noise interference, was also validated and findings demonstrated that the proposed deep learning methods still exhibited a high accuracy at high noise levels.

Purpose This systematic review synthesizes the recent literature (2010–2020) on hospitality employees’ emotions, affect and moods. This study has three objectives: to clarify the definitions of emotions, affect and moods; to explain how theories are integrated into understanding hospitality employees’ emotions, affect and moods; and to assess how emotions, affect and moods are measured. Design/methodology/approach Using seven major databases, the authors selected 61 peer-reviewed academic journal articles published in hospitality outlets for review. We based our study on five stages of conducting a systematic review: scoping, planning, identification, screening and eligibility. Findings Affect is an umbrella term encompassing moods and emotions. Emotions are distinct from emotion-laden constructs, such as emotional labor and emotional intelligence. Theories on conservation of resources, emotional labor and social exchange have been most frequently used to understand hospitality employees’ emotions. However, they overlooked the dynamic nature of emotions when using these theories. Hospitality researchers often used a subset of the positive and negative affect scale and did not discuss back-translation. Practical implications Hospitality employees’ emotions lead to far-reaching consequences in attitudes, intentions and behaviors in work and non-work domains. Effective practices (e.g. creating a supportive climate) that help evoke positive employee emotions and reduce negative employee emotions are thus desirable. Originality/value Our findings crystallize the understanding of emotions, affect and moods of hospitality employees. We further provide a roadmap for future research on hospitality employees’ emotions. Data triangulation, cross-cultural research and mixed emotions are novel opportunities for future research.