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A mesoscopic phase field (PF) model is proposed to simulate the meso-failure process of lightweight concrete.

The PF damage model is applied to the meso-failure process of lightweight concrete through the ABAQUS subroutine user-defined element (UEL). And the improved staggered iteration scheme with a one-pass procedure is used to alternately solve the coupling equations.

These examples clearly show that the crack initiation of the lightweight concrete specimens mainly occurs in the ceramsite aggregates with weak strength, especially in the larger aggregates. The crack propagation paths of the specimens with the same volume fraction of light aggregates are completely different, but the crack propagation paths all pass through the ceramsite aggregates near the cracks. The results also showed that with the increase in the volume fractions of the aggregates, the slope and the peak loads of the force-deflection (F-d) curves gradually decrease, the load-bearing capacity of the lightweight concrete specimens decreases, and crack branching and coalescence are less likely during crack propagation.

The mesostructures with a mortar matrix, aggregates and an interfacial transition zone (ITZ) are generated by an automatic generation and placement program, thus incorporating the typical three-phase characteristics of lightweight concrete into the PF model.

Intent detection and slot filling are two important tasks in question comprehension of a question answering system. This study aims to build a joint task model with some generalization ability and benchmark its performance over other neural network models mentioned in this paper.

This study used a deep-learning-based approach for the joint modeling of question intent detection and slot filling. Meanwhile, the internal cell structure of the long short-term memory (LSTM) network was improved. Furthermore, the dataset Computer Science Literature Question (CSLQ) was constructed based on the Science and Technology Knowledge Graph. The datasets Airline Travel Information Systems, Snips (a natural language processing dataset of the consumer intent engine collected by Snips) and CSLQ were used for the empirical analysis. The accuracy of intent detection and F1 score of slot filling, as well as the semantic accuracy of sentences, were compared for several models.

The results showed that the proposed model outperformed all other benchmark methods, especially for the CSLQ dataset. This proves that the design of this study improved the comprehensive performance and generalization ability of the model to some extent.

This study contributes to the understanding of question sentences in a specific domain. LSTM was improved, and a computer literature domain dataset was constructed herein. This will lay the data and model foundation for the future construction of a computer literature question answering system.

The purpose of this study is to present a highly stretchable and flexible strain sensor with simple and low cost of fabrication process and excellent dynamic characteristics, which make it suitable for human motion monitoring under large strain and high frequency.

The strain sensor was fabricated using the rubber/latex polymer as elastic carrier and single-walled carbon nanotubes (SWCNTs)/carbon black (CB) as a synergistic conductive network. The rubber/latex polymer was pre-treated in naphtha and then soaked in SWCNTs/CB/silicon rubber composite solution. The strain sensing and other performance of the sensor were measured and human motion tracking applications were tried.

These strain sensors based on aforementioned materials display high stretchability (500 per cent), excellent flexibility, fast response (approximately 45 ms), low creep (3.1 per cent at 100 per cent strain), temperature and humidity independence, superior stability and reproducibility during approximately 5,000 stretch/release cycles. Furthermore, the authors used these composites as human motion sensors, effectively monitoring joint motion, indicating that the stretchable strain sensor based on the rubber/latex polymer and the synergetic effects of mixed SWCNTs and CB could have promising applications in flexible and wearable devices for human motion tracking.

This paper presents a low-cost and a new type of strain sensor with excellent performance that can open up new fields of applications in flexible, stretchable and wearable electronics, especially in human motion tracking applications where very large strain should be accommodated by the strain sensor.

Employee engagement serves as a critical strategy for tourism and hospitality organizations to support their employees and fight adversity. This study aims to investigate the antecedents and effects of employee engagement and examine innovative behavior as a linchpin mechanism for the relationship between organizational engagement culture and organizational performance.

This study analyzed the antecedents and effects of employee engagement through a hierarchical linear model that considers both organizational- and individual-level factors. The data was collected through a questionnaire survey from employees of 39 hotels in Guangzhou, China.

The results confirmed the significant positive effect of organizational empowerment, leadership and collaboration atmosphere on employment engagement. An individual’s perception of rewards and recognition, distributive justice and procedural justice significantly affected employee engagement. It was also confirmed that employee engagement ultimately improved performance outcomes at the individual and organizational levels. Additionally, the mediation effect of organizational innovation culture on the relationship between organizational employee engagement and organizational performance was confirmed.

Organizations can improve their performance by enhancing employee engagement, which in turn, can be encouraged by empowering leadership and organizational collaboration culture. Organizations can also improve their performance by providing rewards and recognition appreciated by employees and ensuring justice to them.

This research contributes to the literature on employee engagement in the hospitality industry by demonstrating how organizational performance can be improved through employee engagement using a multilevel model. The findings highlight that organizations with engaged employees are more likely to achieve an innovative culture, which in turn, leads to organizational success. This study also confirmed that empowerment, leadership and collaboration culture help improve organizational performance in the hospitality industry.

The purpose of this paper is to design a smart handheld device with force regulating function, which demonstrates the concept of patient-specialized tools.

This handheld device integrates an electrical bioimpedance (EBI) sensor for tissue measurement and a constant force regulation mechanism for ensuring stable tool–tissue contact. Particular focuses in this study are on the design of the constant force regulation mechanism whose design process is through genetic algorithm optimization and finite element simulation. In addition, the output force can be changed to the desired value by adjusting the cross-sectional area of the generated spring.

The following two specific applications based on ex vivo tissues are used for evaluating the designed device. One is in terms of safety of interaction with delicate tissue while the other is for compensating involuntary tissue motion. The results of both examples show that the handheld device is able to provide an output force with a small standard deviation.

In this paper, a handheld device with force regulation mechanism is designed for specific patients based on the genetic algorithm optimization and finite element simulation. The device can maintain a steady and safe interaction force during the EBI measurement on fragile tissues or moving tissues, to improve the sensing accuracy and to avoid tissue damage. Such functions of the proposed device are evaluated through a series of experiments and the device is demonstrated to be effective.

The study aims to pioneer an innovative approach for the evaluation of government portal websites (GPWs) by introducing an eye-tracking-based method. The research meticulously pinpoints and analyses the distinct usability issues and challenges that users encounter while navigating and interacting with GPWs.

This study devises an eye-tracking-based GPW usability evaluation approach, which focuses on the major functions (i.e. government information disclosure, government services and interactive responses) of GPWs. An Entropy Weighted Technique for Order Preference by Similarity to an Ideal Solution (EW-TOPSIS) method is employed to process eye-tracking indicator results for deriving GPW usability results.

The proposed approach is demonstrated to assess the usability of 12 GPWs in pilot smart cities in China, and it is found that most GPWs have lower-than-average usability. GPWs with low usability require more cognitive load that exhibit increased fixation and saccade. The comparisons among the GPW usability results from (1) the eye-tracking experiment, (2) questionnaire surveys and (3) the ready-made performance evaluation report validate the effectiveness of eye-tracking-based GPW usability evaluation.

The work contributes to shifting the GPW usability evaluation approach from a subjective judgment paradigm to an objective paradigm, as well as provides implications for enhancing GPW usability, including improving search function, reducing website complexity and prioritizing user needs.

Business model innovation (BMI) is an important channel of enterprise innovation, and BMI's antecedents have attracted extensive attention. The purpose of this paper is to address a substantial gap in the extant literature by developing a moderate model to explain the effects of boundary-spanning search on BMI as well as whether and how innovative cognitive imprinting (ICI) and environmental dynamics (ED) affect the above relationship.

A total of 239 usable questionnaires from different enterprises in China were collected to obtain firm-level data. Then multiple regression analyses were used by SPSS software to test hypotheses.

Boundary-spanning search extensity (BSE) and focus have inverted U-shaped impacts on BMI; ICI moderates the relationship between boundary-spanning search and BMI and steepens the curves; ED weakens the moderating role of ICI.

By identifying two antecedents of BMI, this paper contributes to the literature on the antecedents of BMI. Meanwhile, the joint moderating effect of ICI and ED is introduced into the emergent analysis framework of the relationship between boundary-spanning search and BMI and examined through empirical analysis for the first time.

Projecting the population distribution in geographical regions is important for many applications such as launching marketing campaigns or enhancing the public safety in certain densely populated areas. Conventional studies require the collection of people’s trajectory data through offline means, which is limited in terms of cost and data availability. The wide use of online social network (OSN) apps over smartphones has provided the opportunities of devising a lightweight approach of conducting the study using the online data of smartphone apps. This paper aims to reveal the relationship between the online social networks and the offline communities, as well as to project the population distribution by modeling geo-homophily in the online social networks.

In this paper, the authors propose the concept of geo-homophily in OSNs to determine how much the data of an OSN can help project the population distribution in a given division of geographical regions. Specifically, the authors establish a three-layered theoretic framework that first maps the online message diffusion among friends in the OSN to the offline population distribution over a given division of regions via a Dirichlet process and then projects the floating population across the regions.

By experiments over large-scale OSN data sets, the authors show that the proposed prediction models have a high prediction accuracy in characterizing the process of how the population distribution forms and how the floating population changes over time.

This paper tries to project population distribution by modeling geo-homophily in OSNs.

The role of inventors' creativity is crucial for technological innovation within enterprises. The mobility of inventors among different enterprises is a primary source for companies to acquire external knowledge. The mechanism of “learning-by-hiring” is widely recognized by companies. Therefore, it is important to determine how to allocate network resources to enhance the creativity of inventors when companies hire mobile inventors.

The study suggests an analytical framework that analyzes alterations in tie strength and structural holes resulting from the network embeddedness of mobile inventors as well as the effect of the interaction between these two variables on changes in inventor’s creativity after the mobility. In addition, this paper examines the moderating impact of cognitive richness of mobile inventors and cognitive distance between mobile inventors and new employers on the correlation between network embeddedness and creativity.

This study found that: (1) The increase of tie strength has a significant boost in creativity. (2) Increasing structural holes can significantly improve the creativity of mobile inventors. (3) When both the tie strength and the structural holes increase, the creativity of the mobile inventors significantly increases. (4) It is important to note that when there is a greater cognitive distance, stronger tie strength promotes the creativity of mobile inventors. Additionally, cognitive richness plays a significant role in moderating the relationship between changes in structural holes and the creativity of mobile inventors.

These findings provide theoretical guidance for firms to effectively manage mobile inventors and optimize collaborative networks within organizations.

In spite of the vehicle, magnetic field interference can be reduced by some measures and techniques in ammunition design and manufacturing stage, the corruption of the vehicle magnetic field can still reach hundreds to thousands of nanoteslas. Besides, the magnetic field that the ferromagnetic materials generate in response to the strong magnetic field in the vicinity of the body. So, a real-time and accurate vehicle magnetic field calibration method is needed to improve the real-time measurement accuracy of the geomagnetic field for spinning projectiles.

Unlike the past two-step calibration method, the algorithm uses a linear model to calibrate the magnetic measurement error in real-time. In the method, the elliptical model of magnetometer measurement is established to convert the coefficients of hard and soft iron errors into the parameters of the elliptic equation. Then, the parameters are estimated by recursive least square estimator in real-time. Finally, the initial conditions for the estimator are established using prior knowledge method or static calibration method.

Studies show the proposed algorithm has remarkable estimation accuracy and robustness and it realizes calibration the magnetic measurement error in real-time. A turntable experiments indicate that the post-calibration residuals approximate the measurement noise of the magnetometer and the roll accuracy is better than 1°. The algorithm is restricted to biaxial magnetometers’ calibration in real-time as expressed in this paper. It, however, should be possible to broaden this method’s applicability to triaxial magnetometers' calibration in real-time.

Unlike the past two-step calibration method, the algorithm uses a linear model to calibrate the magnetic measurement error in real-time and the calculation is small. Besides, it does not take up storage space. The proposed algorithm has remarkable estimation accuracy and robustness and it realizes calibration the magnetic measurement error in real time. The algorithm is restricted to biaxial magnetometers’ calibration in real-time as expressed in this paper. It, however, should be possible to broaden this method’s applicability to triaxial magnetometers’ calibration in real-time.