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Nanotechnology has been able to bind to a wide range of functional textiles in recently. This paper aims to modify graphene oxide (GO) by grafting dimethyl phosphite and perfluorohexyl iodine. It was applied to cotton to obtain a flame-retardant, water-repellent and ultraviolet-resistant multifunctional fabric.

The GO-multi was synthesized by grafted dimethyl phosphite and perfluorohexyl chain and applied to cotton by the dipping-drying method. The surface chemistry of functionalized GO was characterized by Fourier transform infrared spectroscopy and X-ray photoelectron spectroscopy. The thermal stability of the fabric was characterized by thermogravimetric analysis (TGA). The combustion properties were evaluated using a microscale combustion calorimeter, match test and TGA. Hydrophobicity of film and fabric surface was characterized by static contact angle, and the UV resistance of the fabric was represented by the ultroviolet procetion factor (UPF) value.

Dimethyl phosphite and perfluorohexyl chains were grafted on the surface of GO successively. In the match test, the GO-multi/cotton kept the original outline of the fabric. According to the micro-scale combustion calorimetry (MCC) data, the value of PHRR and THR of GO-multi/cotton was about 45 per cent lower than that of untreated cotton fabric. It was found from the field-emission scanning electron microscopy (SEM) pictures that the residue of GO-multi/ cotton burned by the match method was more compact and the graphene lamellar structure remained more complete. The hydrophobic effect of GO-multi/cotton was improved compared to untreated cotton, but not better than the fabric treated by the perfluorohexyl chain-grafted GO. The UPF value of GO-multi/cotton reached 253, which indicated that the anti-ultraviolet performance of GO-multi was greatly improved after it was deposited on the cotton fabric.

Although the hydrophobic effect was much higher than that of untreated cotton fabric, its hydrophobic effect was not satisfied, which may be due to the fact that the content of F element content was low. So, it is still needed to explore the modifying method to increase the functional component amount on the GO nanosheet.

This modifying method can be used in any of multifunctional textile preparation process. The hydrophobic and flame-retardant cotton fabric revealed a sample for use in outdoor sports such as clothes and tents.

To meet the needs of multifunctional cotton fabrics, the modification of GO with dimethyl phosphite and perfluorohexyl iodine has not been reported. The modified fabric has flame-retardant, UV-resistant and hydrophobic properties.

The purpose of this paper is to develop a new vibration probe sensor for measurement of particle mass flow rate in gas–solid two phase flow.

A new vibration probe sensor based on polyvinylidene fluoride (PVDF) piezoelectric film is designed. The particle impact model according to Hertz contacting theory is presented. The average amplitude, standard deviation and spectral peak at the natural frequency of the probe (21.2 kHz) of the signals acquired through experiments are chosen as characteristic quantities for further analysis.

Through experimental study of relation between three characteristic quantities and the mass flow rate and air flow velocity, a good regularity is found in the average amplitude and the spectral peaks at natural frequency of the probe. According to the particle impact model, the structure of quantitative model is built and parameters of two models are calculated from experimental data. Additionally, tests are made to estimate mass flow rate. The average errors are 5.85 and 4.26 per cent, while the maximum errors are 10.81 and 8.65 per cent. The spectral peak at natural frequency of the probe is more applicable for mass flow rate measurement.

The sensor designed and the quantitative models established may be used in dilute phase pneumatic conveying lines of coal-fired power plants, cement manufacturing facilities and so on.

First, the new sensor is designed and the quantitative models are established. Second, the spectral peak at natural frequency of the probe is found that can be used for measurement of mass flow rate.

This study provides real-world evidence for the relationship between strategic communication from a global/multinational perspective and the effectiveness of corporate message strategies in the context of environment risk communication. Among sustainability issues, particulate matter (PM) air pollution has threatened the health and social wellbeing of citizens in many countries. The purpose of this paper is to apply the message framing and attribution theories in the context of sustainability communication to determine the effects of risk message characteristics on publics’ risk responses.

Using a 2 (message frame: gain vs loss) × 2 (attribution type: internal vs external) × 2 (country: China vs South Korea) between-subjects experimental design, the study examines the message framing strategies' on publics' risk responses (i.e. risk perception, risk responsibility attribution held toward another country and sustainable behavioral intention for risk prevention).

Findings include (1) main effects of message characteristics on participants’ risk responses; (2) the impact of country difference on participants’ differential risk responses and (3) three-way interactions on how risk message framing, risk threats type and country difference jointly affect not only participants’ risk perception and risk responsibility attribution but also their sustainable behavioral intention to prevent PM.

Although this study used young–adult samples in China and South Korea, the study advances the theory building in strategic environmental risk communication by emphasizing a global/multinational perspective in investigating differences among at-risk publics threatened by large-scale environmental risks.

The study's findings provide evidence-based implications such as how government agencies can enhance the environmental risk message strategy so that it induces more desired risk communication outcomes among at-risk publics. Insights from our study offer practical recommendations on which message feature is relatively more impactful in increasing intention for prosocial behavioral changes.

This study on all measured risk responses reveals important differences between at-risk young publics in China and South Korea and how they respond differently to a shared environmental risk such as PM. The study's findings provide new evidence that media coverage of global environmental issues needs to be studied at the national level, and cross-cultural comparisons are imperative to understand publics’ responses to different news strategies. Thus, this study offers implications for practitioners to understand and apply appropriate strategies to publics in a social way across different countries so as to tailor risk communication messaging.

This study offers new insights to help connect message framing effects with communication management practice at the multi-national level, providing recommendations for government communication practitioners regarding which PM message features are more likely to be effective in forming proper risk perception and motivate sustainable actions among at-risk publics in different countries.

This study explores how auditors' emotions, specifically negative moods triggered by flight delays, impact auditing quality.

Utilizing flight delays during audit assignments as a mood indicator, weather conditions at departure airports serve as an instrumental variable to provide a robustness check between flight delays and audit outcomes, employing a two-stage least squares model.

The findings suggest that such negative moods improve auditing effort and quality, as evidenced by reduced future accounting restatements and increased audit fees. The positive effect of flight delays on auditing quality is consistent across different tests and measures.

This study highlights the significance of auditors' emotional states on their professional performance, indicating a unique angle on auditing quality research by focusing on the emotional well-being of auditors as influenced by external factors such as flight delays.

This paper aims to provide a series of new methods for projecting a three-dimensional (3D) object onto a free-form surface. The projection algorithms presented can be divided into three types, namely, orthogonal, perspective and parallel projection.

For parametric surfaces, the computing strategy of the algorithm is to obtain an approximate solution by using a geometric algorithm, then improve the accuracy of the approximate solution using the Newton–Raphson iteration. For perspective projection and parallel projection on an implicit surface, the strategy replaces Newton–Raphson iteration by multi-segment tracing. The implementation takes two mesh objects as an example of calculating an image projected onto parametric and implicit surfaces. Moreover, a comparison is made for orthogonal projections with Hu’s and Liu’s methods.

The results show that the new method can solve the 3D objects projection problem in an effective manner. For orthogonal projection, the time taken by the new method is substantially less than that required for Hu’s method. The new method is also more accurate and faster than Liu’s approach, particularly when the 3D object has a large number of points.

The algorithms presented in this paper can be applied in many industrial applications such as computer aided design, computer graphics and computer vision.

The construction industry has experienced an irreversible digital transformation to smart construction. Many countries have published supporting policies to encourage the development of smart construction. However, there is no universally valid approach. This paper thus aims to evaluate smart construction policies issued by 24 pilot cities in China and identify applicable policy tools and their impact.

This paper collected 33 governmental documents on smart construction through the official websites in China. Different policy tools were classified into supply-side, demand-side and environment-side categories. The supporting policies of smart construction development in pilot cities were quantitatively evaluated by using a policy modeling consistency index (PMC-index) model.

Supply-type and environment-type policy instruments were used more frequently than demand-type policies in 24 pilot cities. Most of the 24 pilot cities had an evaluation of PMC-index over 8, realizing the consistency of smart construction policies. Eight pilot cities had an evaluation of PMC-index of 6–7.99, realizing acceptable consistency. Only Foshan City has an evaluation of PMC-index below 4, which may reflect a poor consistency of policy implementation. The paper proposes consistencies of smart construction policies of 24 pilot cities and valid policy instruments, including the presale of commercial residential buildings, additional bonus points in the tendering process and cooperating with multiple departments when promoting smart construction.

This paper contributes to expanding policy evaluation studies in the smart construction field and provides concrete suggestions for policymakers to formulate more effective and specific policies and strategies for the development of smart construction.

Due to dynamic model is the basis of realizing various robot control functions, and it determines the robot control performance to a large extent, this paper aims to improve the accuracy of dynamic model for n-Degree of Freedom (DOF) serial robot.

This paper exploits a combination of the link dynamical system and the friction model to create robot dynamic behaviors. A practical approach to identify the nonlinear joint friction parameters including the slip properties in sliding phase and the stick characteristics in presliding phase is presented. Afterward, an adaptive variable-step moving average method is proposed to effectively reduce the noise impact on the collected data. Furthermore, a radial basis function neural network-based friction estimator for varying loads is trained to compensate the nonlinear effects of load on friction during robot joint moving.

Experiment validations are carried out on all the joints of a 6-DOF industrial robot. The experimental results of joint torque estimation demonstrate that the proposed strategy significantly improves the accuracy of the robot dynamic model, and the prediction effect of the proposed method is better than that of existing methods.

The proposed method extends the robot dynamic model with friction compensation, which includes the nonlinear effects of joint stick motion, joint sliding motion and load attached to the end-effector.

The purpose of this paper is to provide the extensive review on dynamic monitoring of forestry area in China.

Countermeasure and suggestions were proposed for three aspects including the establishment of data sets with unified standards, top-level design of monitoring and assessment and analysis models, and establishment of the decision support platform with multiple scenario simulation.

Finally, the authors proposed key research area in this field, i.e., improving the systematic and optimal forest management through integrating and improving the data, models and simulation platforms and coupling the data integration system, assessment system and decision support system.

The authors explored the limitation of dynamic monitoring and state of the art research on data accumulation, professional model development and the analytical platform.

Driven by the development of the global digital economy, knowledge management in industrial enterprises offers more possibilities for green innovation. Based on the perspective of external knowledge sources, this study aims to construct a panel regression model to explore the relationship between digital economy and industrial green innovation efficiency.

Panel data from 30 regions in China from 2011 to 2020 were selected as research samples. All data are obtained from national and provincial statistical yearbooks. Coupling coordination degree analysis, entropy method, panel regression analysis, robustness test and threshold effect test by Stata 16.0 were used to test the hypotheses.

The empirical results demonstrate the hypotheses and reveal the following findings: the digital economy is positively related to industrial green innovation efficiency and external knowledge sources, and external knowledge sources mediate the relationship between them. Moreover, based on the threshold test results, the digital economy has a double-threshold effect on industrial green innovation efficiency.

Based on the perspective of external knowledge sources, the proposed mediating mechanism between the digital economy and industrial green innovation efficiency has not been established previously, further enriching the research on the antecedents and outcomes of external knowledge sources. Moreover, this study estimated the direct influence mechanism and double-threshold effect of the digital economy on industrial green innovation efficiency from theoretical and empirical analysis, thus responding to the call of scholars and adding to existing research on how the digital economy affects the green transformation of industrial enterprises.