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Categorisations of social groups involve interpretations of reality that include social cognition, classification of relevant concepts, worldviews and ideologies. To reveal the factors that form the basis for the commonly used terms developed countries and developing countries, this study uses corpus-assisted critical discourse studies to examine how they are represented in United Nations climate change news reports. Results show these two categorisations are constructed through lexico-grammatical patterns that serve generally as Locations specifying the characteristics of various climate change scenarios. In addition, guided by UN mandates, Agents (developed countries) are expected to provide climate funds to Patients or Goals (developing countries) to effectively solve this global problem. The ways in which these patterns are represented in UN news reporting reflect the post-World War II world order and the core value of humanitarianism endorsed by the UN. To address the ongoing problem of insufficient financial support to developing countries, it is proposed that provisions of support be included in the Nationally Developed Contributions of developed countries. [ABSTRACT FROM AUTHOR]

In the degradation evaluation process of the crane girder structure under moving loads, the complex vibration response and low accuracy of health index standards are the main factors limiting the performance of the evaluation method. A method for identifying and evaluating damage to crane girder structures under moving loads has been proposed. In this method, optimized empirical wavelet transform (EWT) is used for decomposing the vibration signal of the crane girder structure to obtain sensitive components. A health indicator based on power spectrum maximum sequence is constructed by combining structural vibration simulation and response characteristics analysis under moving loads. A degradation index acquisition scheme based on an optimized sparse autoencoder is proposed, which utilizes a simulated annealing algorithm to optimize the model parameters of the sparse autoencoder. The effectiveness of the proposed method is verified through girder structure crack tests under moving loads. [ABSTRACT FROM AUTHOR]

To improve heat dissipation capability and enhance mechanical properties, a series of silica aerogel (SA) and modified glass fiber (GF)-filled SBR composites were prepared. It was found that the addition of SA successfully reduced the thermal conductivity of SBR by 35%, owing to the heat shield of the nanoscale porous structure of SA. Moreover, the addition of modified glass fiber (MGF) yielded a significant increase in the tensile and tear strength of SBR/SA composite rubber of 37% and 15%, respectively. This enhancement was more pronounced than the improvement observed with unmodified GF, and was attributed to the improved dispersion of fillers and crosslinking density of the SBR matrix. Rheological analysis revealed that the addition of SA and MGF weakened the ω dependence. This was due to the partial relaxation of immobilized rubber chains and limited relaxation of rubber chains adsorbed on the MGF. Furthermore, the strain amplification effect of MGF was stronger than that of GF, leading to a more pronounced reinforcing effect. [ABSTRACT FROM AUTHOR]

Silica-based mesoporous materials, such as SBA-15, are important supports in the field of catalysis due to their ordered pore channels. The traditional synthesis route of SBA-15 suffers from high autogenous pressure and explosion risks, limiting its industrial production. Herein, a reflux system under ambient pressure was used for the synthesis of SBA-15. Ni nanoparticles were incorporated into the obtained materials to evaluate the quality of the SBA-15 support. The comparative performance of Ni/SBA-15H and Ni/SBA-15R validated there was negligible difference between the SBA-15 prepared by the hydrothermal method (SBA-15H) and the reflux method (SBA-15R). This revolutionary synthesis methodology provides a novel and secure route for the large-scale preparation of SBA-15. [ABSTRACT FROM AUTHOR]

Viewing discourse as a social practice, one important task of critical discourse studies (CDS) is to unveil inequality, power, and ideologies through linguistic and discoursal analysis of social events, social identities, and social relations represented in oral or written texts. As such, it lends itself to social network analysis (SNA) which aims to discover relation patterns and structures among such social actors as people, organizations, and political entities. This article proposes an integration of SNA techniques into CDS and explores this possibility via an example in diachronic study on international relations represented in news reporting on China in The New York Times between 1980 and 2020 by examining subject – direct object pairs to approach the target relations between national actors. It is shown that the coupling of these two approaches effectively reveals international relation networks surrounding key national actors, based on which detailed linguistic and discoursal analysis further sheds light on the underlying ideological and socio-political factors in the news reports. Considering the fact that SNA consists of a great variety of network statistics, which can be broadly categorized into those related to the relative position of the actor in the network and those concerned with the structure of the network itself, there is vast space for the utility of SNA metrics in aiding CDS in further research. [ABSTRACT FROM AUTHOR]

In this study, to improve the speed tracking performance of the switched reluctance motor (SRM), a control scheme combining fast terminal sliding mode (FTSM) control and radial basis function (RBF) neural network is proposed. First, the convergence characteristic of the FTSM control is derived, and a basic control scheme is designed to ensure the fast convergence of SRM speed tracking errors. Second, the RBF neural network with adaptive parameters is introduced to replace the equivalent control law, which avoids the requirement for the precise mathematical model information of the system. At the same time, considering the network approximation error and unknown external disturbances, an adaptive control law with variables gain is designed. The chattering phenomenon is suppressed and the robustness of the system is enhanced. The updated law of the controller and the stability of the closed‐loop system are derived based on the Lyapunov stability theory. Finally, the simulation and experimental results of the SRM drive system show that the proposed control scheme has an excellent performance in terms of tracking accuracy, response speed, and robustness. © 2022 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

Tool wear status seriously affects the dimensional accuracy and surface quality of machined parts. Therefore, tool condition monitoring (TCM) is essential in the milling process of aerospace structural parts due to the utilization of difficult-to-cut materials and complex cutting trajectories. The higher order spectrum (HOS) was first employed to analyze the vibration signals. Then bispectral features extracted from denoised signals were used to characterize the tool wear status. The improved Pearson’s correlation coefficient was used for feature selection in order to reduce the influence of periodic components on the feature selection process. Furthermore, a novel objective function was proposed for the Bayesian optimization algorithm to guide the optimization process of hyperparameters for the support vector machine. This objective function takes into consideration the effect of imbalanced data on the recognition rates. To demonstrate the effectiveness of the proposed method, a milling experiment was conducted to machine a structural part, and vibration signals were collected during the process. Finally, an online TCM model was established based on this. The present study suggests that the proposed TCM system is accurate and robust. [ABSTRACT FROM AUTHOR]

This paper reports on a novel unipolar current excited control scheme for the asymmetric bridge converter (ABC)‐based switched reluctance drive (SRD), where the 3D space vector modulation under three modes is developed to reduce the total harmonic distribution (THD) and torque ripple. Firstly, two different 3D vector distributions, namely, the small voltage amplitude mode and large mode are presented based on the asymmetric converter. For both distributions, the zero‐sequence voltages generated by the effective vectors are considered. Additionally, zero‐sequence vectors (1,1,1) and (−1,−1,−1) are no longer treated as null vectors and involved in the control of zero‐sequence current. Then, the duty cycles of both two modes are obtained by the combination of the zero‐sequence and two adjacent active vectors. Moreover, based on the large modulation mode, a novel method combined with the small mode is proposed to further optimise the switching costs and torque ripples. The effectiveness of the proposed modes is verified through the simulation in MATLAB and the experiment on a dSPACE‐1103‐based prototype. Compared with the conventional switched reluctance motor vector control, the proposed scheme delivers better performances of THD, efficiency and torque ripple reduction. [ABSTRACT FROM AUTHOR]

Chattering is one of the most important factors affecting productivity of robot machining. This paper investigates the pose-dependent cutting stability of a 5-DOF hybrid robot. By merging the complete robot structural dynamics with the cutting force at TCP, an effective approach for stability analysis of the robot milling process is proposed using the full-discretization technique. The proposed method enables the computational efficiency to be significantly improved because the system transition matrix can be simply generated using a sparse matrix multiplication. Both simulation and experimental results on a full size prototype machine show that the stability lobes are highly pose-dependent and primarily dominated by the lower-order structural modes. [ABSTRACT FROM AUTHOR]

Tool wear monitoring (TWM) system plays an important role since it ensures the accuracy of manufacturing and workpiece quality, especially in aerospace manufacturing. Due to the challenge of various paths from the milling process of large cavity-like structural parts and impact of tool wear on the surface quality, there remains an urgent need for a high-precision and robust TWM approach. This article addresses this issue by employing a stacked network in conjunction with a feature extraction method in which it combines vibration singularity analysis with correlation analysis. The singularity of the original vibration signal, estimated by the Holder exponent (HE), is analyzed to eliminate the influence of the milling path, and the sensitive features based on HEs are extracted and reduced via Pearson's correlation coefficient (PCC) analysis. Subsequently, a stacked long short-term memory neural network (LSTM) trained by these features has been applied to estimate tool wear, which is verified by a dataset obtained from the processing site. Experimental results indicate that the proposed method has improved the accuracy of tool wear prediction, which outperforms the developed methods such as LSTM, bi-direction LSTM (BiLSTM) and its stacked model, partial least squares regression (PLSR) model, and support vector regression (SVR) model optimized by the whale optimization algorithm (WOA). Meanwhile, this method lays the foundation for using vibration signal to monitor tool wear in cavity milling. [ABSTRACT FROM AUTHOR]

In contrast with the vital role China has played in global climate governance in recent years, it is rare to see the research on its foreign-language media representation of this issue. Drawing on critical discourse analysis and corpus linguistics, this study examines how China's flagship English-language newspaper China Daily communicates climate change (2010–2019) to international audiences and how it represents China and the US as well as China–US relations regarding climate issues. Results show that through the use of specific modalities and other collocates of China and the US, the newspaper constructs China as a responsible major country and the US as a capricious and self-centered nation while emphasizing the importance of their cooperation on climate actions. The ways it represents this issue can be interpreted with regard to pragmatism and the China Dream of national rejuvenation endorsed by the Chinese government. To have a stable environment for sustainable development of China and the whole world, China is willing to avoid confrontation and work together with the US and other countries in combating climate change though competition may remain in such related fields as green energy, as indicated by China Daily. [ABSTRACT FROM AUTHOR]

This paper is concerned with the path following control for an underactuated unmanned surface vehicle (USV) subject to modeling error and input saturation under time‐varying external disturbances. In this note, a novel trajectory linearization control (TLC) method is first introduced in the design of path following controller for an unmanned surface vessel. Adaptive line‐of‐sight (LOS) algorithm is used in the navigation strategy, which not only solves the sideslip angle problem caused by external disturbances but also optimizes the convergence speed. The neural network minimum learning parameter (MLP) method is used to compensate for modeling errors and external disturbances. Compared with multi‐layer neural networks, MLP solves the problem of 'dimension disaster'. Meanwhile, in order to increase the robustness of the system, adaptive technology is employed to compensate for the compensation error of MLP. In addition, an auxiliary dynamic system is introduced into the controller design to address potential input saturation issue. Considering the above practical conditions, it is more convenient for the engineering implementation of the proposed control path following the control system. Using Lyapunov stability analysis theory, it is proven that all error signals in the system are uniformly ultimately bounded. Finally, two simulation experiments are presented to demonstrate the feasibility of the proposed control strategy. © 2021 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

Objective. To investigate the effects of HOX transcript antisense RNA (HOTAIR) and miR-138 on inflammatory response and oxidative stress (OS) induced by IRI in rat cardiomyocytes. Methods. H9C2 cells were divided into the control group, H/R group, H/R+siRNA NC group, H/R+si-HOTAIR group, and H/R+si-HOTAIR+inhibitor group. Expression levels of HOTAIR, miR-138, and inflammatory factors were detected by quantitative reverse-transcription polymerase chain reaction (qRT-PCR). The double luciferase reporter gene assay was used to detect the targeting relationship between HOTAIR and miR-138. Results. Compared with the control group, the level of miR-138 and SOD in the H/R group was obviously reduced, while the expression levels of the HOTAIR, MDA, and NF-κB pathway were obviously increased. Compared with the H/R group, the level of miR-138 and SOD in the H/R+si-HOTAIR group was obviously increased, and the expression levels of the HOTAIR, MDA, and NF-κB pathway were obviously decreased. Compared with the H/R+si-HOTAIR group, the level of SOD in the H/R+si-HOTAIR+inhibitor group decreased; MDA content and the NF-κB pathway expression level increased. In the double luciferase reporter gene assay, compared with the HOTAIR wt+NC group, the luciferase activity of the HOTAIR wt+miR-138 mimic group was obviously decreased. Conclusions. Silent HOTAIR can promote the expression of miR-138 and inhibit H/R-induced inflammatory response and OS by regulating the NF-κB pathway, thus protecting cardiomyocytes. [ABSTRACT FROM AUTHOR]

Measuring and quantifying the electromagnetic characteristics of switched reluctance motors (SRMs) are indispensable for advanced motor control and performance enhancement. This article reports on a novel method in obtaining the flux-linkage characteristics of an SRM without rotor clamping devices and position sensors. This approach combines measurement with data reconstruction. For the measuring step, flux-linkage samples at four torque-balanced positions were measured indirectly. Considering the magnetic coupling among phases, two different excitation forms were adopted to further increase accuracy. Then, for the reconstructing step, a fuzzy logic-based approach was applied to reconstruct the complete flux-linkage characteristics with measurement results. The construction results were compared to measurements results from the traditional rotor clamping method, and good agreements can be found, demonstrating the effectiveness of the proposed method. Furthermore, based on reconstructed electromagnetic characteristics, dynamic simulation of an SRM prototype under different control modes was carried out and analyzed in MATLAB. Comparison with dynamic experiments further verifies the accuracy and effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

In this paper, one concerns with the problem of trajectory tracking control for an underactuated unmanned surface vehicle subject to uncertain dynamics and input saturation. A first-order sliding surface and a second-order sliding surface are hired to design surge control law and yaw control law, respectively, which together form an underactuated trajectory tracking controller. Furthermore, the potential input saturation problem is solved through an auxiliary design system. Neural shunting model is introduced into the design of the controller to avoid the increase in calculation caused by variable derivation. The minimum learning parameter method of neural network replaces the traditional multilayer neural network to compensate uncertain dynamics and time-varying disturbances, which further reduces the computational burden of the controller. Besides, two adaptive robust terms are introduced to further enhance the robustness of the trajectory tracking system. Finally, comparative simulation experiments are carried out to verify the universality and superiority of the trajectory tracking control strategy. [ABSTRACT FROM AUTHOR]

In this study, a machine learning based computational approach has been developed to investigate the cation distribution in spinel crystals. The computational approach integrates the construction of datasets consisting of the energies calculated from density functional theory, the training of machine learning models to derive the relationship between system energy and structural features, and atomistic Monte Carlo simulations to sample the thermodynamic equilibrium structures of spinel crystals. It is found that the support vector machine model yields excellent performance in energy predictions based on spinel crystal structures. Furthermore, the developed computational approach has been applied to predict the cation distribution in single spinel MgAl2O4 and MgFe2O4 and double spinel MgAl2-aFeaO4. Agreeing with the available experimental data, the computational approach correctly predicts that the equilibrium degree of inversion of MgAl2O4 increases with temperature, whereas the degree of inversion of MgFe2O4 decreases with temperature. Additionally, it is predicted that the equilibrium occupancy of Mg cations at the tetrahedral and octahedral sites in MgAl2-aFeaO4 could be tuned as a function of chemical composition. Therefore, this study presents a reliable computational approach that can be extended to study the variation of cation distribution with processing temperature and chemical composition in a wide range of complex multi-cation spinel oxides with numerous applications. [ABSTRACT FROM AUTHOR]

The 2019–20 Hong Kong protests have attracted more attention from the international media than its previous mass movements. The Chinese government and the Trump administration have engaged tit-for-tat on this matter, but few studies have compared how the media in China and US have represented the issue. With the hypothesis that the dominant ideology in a given society interweaves with news framing and language use in news discourse, this paper uses the approach of corpus-assisted critical discourse studies to examine how China Daily and The New York Times have constructed the protests, with the findings that they framed it in different ways. As the leading official English-language newspaper of China, China Daily communicated to the world the Chinese government's baseline on this issue that the solution to this political movement, which finally turned into illegal riots, should be found under the "one country, two systems" framework. In contrast, The New York Times highlighted the pro-democracy aspect of the movement which was to fight against China's control over Hong Kong, which might indicate journalistic practice in US has gone astray from the professional norms it set up in the nineteenth century and is as politically-driven as that in China. [ABSTRACT FROM AUTHOR]

Due to ever increasing precision and automation demands in robotic grinding, the automatic and robust robotic grinding workstation has become a research hot-spot. This work proposes a grinding workstation constituting of machine vision and an industrial manipulator to solve the difficulty of positioning rough metal cast objects and automatic grinding. Faced with the complex characteristics of industrial environment, such as weak contrast, light nonuniformity and scarcity, a coarse-to-fine two-step localization strategy was used for obtaining the object position. The deep neural network and template matching method were employed for determining the object position precisely in the presence of ambient light. Subsequently, edge extraction and contour fitting techniques were used to measure the position of the contour of the object and to locate the main burr on its surface after eliminating the influence of burr. The grid method was employed for detecting the main burrs, and the offline grinding trajectory of the industrial manipulator was planned with the guidance of the coordinate transformation method. The system greatly improves the automaticity through the entire process of loading, grinding and unloading. It can determine the object position and target the robotic grinding trajectory by the shape of the burr on the surface of an object. The measurements indicate that this system can work stably and efficiently, and the experimental results demonstrate the high accuracy and high efficiency of the proposed method. Meanwhile, it could well overcome the influence of the materials of grinding work pieces, scratch and rust. [ABSTRACT FROM AUTHOR]

Aim: To explore the cross‐level relationships between group organisational citizenship behaviour, emotional intelligence, work engagement and nurse–patient relationship. Background: Group‐level factors influencing nurse–patient relationship are seldom studied. Method: A cross‐sectional questionnaire survey was conducted among 1,246 nurses from 55 nursing groups in a 3A hospital in China, and the data were analysed by multilevel analysis. Results: Group organisational citizenship behaviour is positively related to nurse–patient relationship with work engagement as a mediator. Emotional intelligence moderates the relationship between group organisational citizenship behaviour and nurse–patient relationship. Specifically, high emotional intelligence reduces the positive impact of group organisational citizenship behaviour on nurse–patient relationship. Conclusions: This study provides new insights into the influencing factors of nurse–patient relationship based on the social information processing theory. In groups with high group organisational citizenship, positive work engagement and emotional intelligence, nurses are more likely to deliver better performance in patient care, leading to better nurse–patient relationships. Implications for Nursing Management: This study suggests that influencing factors at both group and individual levels should be considered while establishing nurse–patient relationships. A positive group climate and personal ability development significantly improve patient care quality. [ABSTRACT FROM AUTHOR]

• Proposed a pre-processing method to eliminate AM-FM harmonic components in signals. • Cutting excitation response generated during normal machining can be used for OMA. • Operational modal parameters of the milling robot are related to specific machining ways. The dynamics of a milling robot have a significant impact on machining efficiency and quality. Traditional experimental modal analysis (EMA) is used to study the dynamics of milling robots in the static state. However, the dynamic properties of milling robots change when they are in the operational state. To investigate the dynamics of milling robots during cutting, operational modal analysis (OMA) is used. During normal cutting, milling robots are primarily excited by cutting forces that are dominated by amplitude and frequency-modulated (AM-FM) harmonic components that are caused by the fluctuation of cutting loads and spindle speeds. Such cutting forces make the dynamic parameters identified by OMA inaccurate. To address this issue, the variational mode decomposition-OMA (VMD-OMA) method is proposed herein, which involves removing AM-FM harmonic components from the response signal using the VMD technology and subsequently using the stochastic subspace identification (SSI) algorithm to identify dynamic parameters. To verify the effectiveness of this method, simulations and experimental research have been conducted. The simulation results demonstrate that the dynamic parameters identified by VMD-OMA are generally closer to the theoretical values. Experimental research conducted on a milling robot named TriMule shows that VMD-OMA can effectively eliminate AM-FM harmonics in response signals and identify the dynamic parameters of TriMule during cutting. [ABSTRACT FROM AUTHOR]

For the three-dimensional (3D) pose estimation of metal blank casts estimate in industrial production process, a novel 6-degree-of-freedom (6DOF) positioning and grasping approach for industrial robots based on boundary features and combining structured light 3D vision and the point cloud matching method is proposed. The proposed approach first uses the Gray code plus grating phase-shift algorithm to reconstruct the 3D surface information of the object. Subsequently, an improved point pair feature (PPF) matching location method based on point cloud boundary extraction is proposed to realize the accurate 6DOF pose estimation of the object. In this method, the point cloud boundary feature is used to optimize the PPF algorithm. Finally, by combining with the point cloud preprocessing process and the improved PPF matching location method, the 6DOF pose positioning of metal blank casting by industrial robots is realized. The proposed approach can accurately complete pose measurement and positioning of objects placed randomly in an open environment. The experimental results demonstrate that the proposed PPF matching location method significantly improves both matching speed and accuracy compared to the traditional PPF algorithm. [ABSTRACT FROM AUTHOR]

For the three-dimensional (3D) pose estimation of metal blank casts estimate in industrial production process, a novel 6-degree-of-freedom (6DOF) positioning and grasping approach for industrial robots based on boundary features and combining structured light 3D vision and the point cloud matching method is proposed. The proposed approach first uses the Gray code plus grating phase-shift algorithm to reconstruct the 3D surface information of the object. Subsequently, an improved point pair feature (PPF) matching location method based on point cloud boundary extraction is proposed to realize the accurate 6DOF pose estimation of the object. In this method, the point cloud boundary feature is used to optimize the PPF algorithm. Finally, by combining with the point cloud preprocessing process and the improved PPF matching location method, the 6DOF pose positioning of metal blank casting by industrial robots is realized. The proposed approach can accurately complete pose measurement and positioning of objects placed randomly in an open environment. The experimental results demonstrate that the proposed PPF matching location method significantly improves both matching speed and accuracy compared to the traditional PPF algorithm. [ABSTRACT FROM AUTHOR]

Control of public discourse in China by official media has been the subject of several media-related studies. Few studies have been conducted, however, on the specific discourse strategies employed to exercise control. Based on Van Leeuwen's ([2007. "Legitimation in Discourse and Communication." Discourse and Communication 1 (1): 91–112]) and Reyes' ([2011. "Strategies of Legitimization in Political Discourse: From Words to Actions." Discourse and Society 22 (6): 781–807]) categories of legitimization, this study identifies five legitimization strategies of China's official media: legitimization through highlighting positive governmental actions, emotions, rationality, hypothetical futures, and quoting elites. This study uses reports of the 2018 vaccine scandal in China published by Xinhua News Agency as examples to show how a top-down perspective is adopted to legitimize the ruling party and sustain social stability in a crisis. This is done in the hope of contributing not only to a better understanding of how legitimization is realized in practice in the sociopolitical context of an authoritarian society, but also to a deeper insight into the nature of China's official media discourse. Of the five strategies, legitimization through emphasizing the government's positive actions sets the tone for official news discourse; the other four serve to provide information and solve problems in the interest of the ruling party. [ABSTRACT FROM AUTHOR]

Electrically assisted superplastic forming and diffusion bonding (EASPF/DB) is based on the electrically assisted technique in which the electric current is directly and simply introduced into metallic sheets during hot processing. Through the rapidly increasing heat by the Joule effect after several minutes, the advantages of the EASPF/DB process are further strengthened, and the limitations of commercial exploitation (e.g., long processing period) are partly overcome. In this study, an experimental setup of EASPF/DB was assembled for the experimental validation of this concept. The Ti2AlNb alloy sheet, which is regarded as a superior substitute for the nickel-based alloy, was diffusion-bonded and formed, and a double-layer structure was fabricated by means of the EASPF/DB process. The temperature distribution measured by an infrared imaging camera was apparently influenced by detour effects of the electric current. To examine the forming and bonding effects, the height and thickness were measured in different positions. The microstructures of the bonding interface were observed, and no microcavity and crack were found, which indicated the feasibility of the variant of the SPF/DB process. Meanwhile, the large-size grains of B2 phase compose the microstructure of forming zone with some fine needle–like precipitates. Finally, the hardness test showed higher values of Vickers hardness than that of the as-received sheet and the compression test showed three stages of the double-layer structure during continuous loading. The important values and significance for use of this variant are presented by markedly reducing the heating and cooling time and the targeted heating manner for metallic sheets. [ABSTRACT FROM AUTHOR]

Blockchain technique, with the novelties of decentralization, smart contract, security and cooperative autonomy, is expected to play great effects on promoting the development of energy local networks (ELNs). This paper presents an automated demand response (ADR) framework for decentralized scheduling and secure peer-to-peer (P2P) trading among energy storage systems in ELNs. Different from most existing works that trade electricity over long distances and through complex meshes, this proposed work performs decentralized and automated demand response through energy sharing of P2P executors. We explore for the first time the benefits of a promising blockchain to conduct the overall ADR framework and increase the P2P trading security. To achieve decentralized scheduling without relying on a central entity, a price-incentive noncooperative game theoretic model is introduced to produce equilibrium solutions for energy storage systems. Moreover, we develop a schedulable ability evaluation system to match trading pairs involving buying and selling nodes. On this basis, a state-machine-driven smart contract mechanism is built to realize P2P trading without reliance on a trusted third party. To illustrate the implementation details of the ADR method, a distributed algorithm is designed. Case studies are provided to verify the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

In this work, Bi 2 S 3 /MoS 2 /Bi 2 MoO 6 hetero-structured porous films were fabricated via a facile anion exchange process using the as-prepared Bi 2 MoO 6 nanoflake array film as substrate material. The formation of Bi 2 S 3 /MoS 2 /Bi 2 MoO 6 ternary hetero-structured porous film is both thermodynamically controllable and reaction time dependent. Systematic experiments were done to investigate the products at each reaction stage and disclose the relationships between the composite components and reaction temperature and time. The study showed that the energy barrier need to be overpassed when MoS 2 and Bi 2 S 3 were simultaneously produced. The optimized Bi 2 S 3 /MoS 2 /Bi 2 MoO 6 photoelectrode exhibited significantly higher photoelectrocatalytic efficiency than Bi 2 MoO 6 , binary Bi 2 S 3 /Bi 2 MoO 6 and Bi 2 S 3 /MoS 2 photoelectrodes. The remarkable degradation efficiency of the Bi 2 S 3 /MoS 2 /Bi 2 MoO 6 photoelectrode comes from the synergy of high quality assembly and heterostructure interfaces between the three components. The optimized film assembly and stepwise band alignment in the ternary heterostructure composite contribute to visible light utilization, transport and separation of charge carriers, mass transport, and accessibility of active sites. The generated active species such as superoxide anions (O 2 −) and holes were detected to promote the decomposition of organic pollutants. The reasonable photoeletrocatalytic degradation mechanism was also proposed. [ABSTRACT FROM AUTHOR]

This article develops a novel path‐following control strategy for underactuated unmanned surface vehicle (USV) subject to unmodeled dynamics and unknown multiple disturbance. A practical robust path‐following controller is proposed using trajectory linearization control (TLC) technology, neural network, and auxiliary design system. First, the greatest advantage of this article is that the TLC technology is first introduced into the field of USV motion control, which provides a new direction for TLC technology research. Second, the underactuated model based on a transformation of the USV kinematics to Serret‐Frenet frame is simplified by introducing a nonlinear coordinate transformation. Meanwhile, to improve the robustness and reduce the computational complexity, radial basis function neural network is replaced by neural network with minimum learning parameter method to compensate for unmodeled dynamics and unknown multiple disturbance. In addition, an auxiliary dynamic system is used to reduce the risk of actuator saturation. The stability of the whole system was proved based on the Lyapunov criteria. Finally, the comparison results demonstrate the superior performance of the proposed approach. © 2019 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc. [ABSTRACT FROM AUTHOR]

Effective tool remaining useful life (RUL) prediction can greatly improve the quality of workpiece and reduce the cost of production. An online tool RUL prediction framework is constructed based on Bayesian inference and sensory signals. In this method, Pairs model is adopted to depict the tool degradation process during cutting process and Gaussian importance resampling (GIR) method is proposed to update model parameters iteratively. Therefore, the future tool wear status can be predicted and RUL can be estimated correspondingly. To testify the effectiveness of the proposed method, milling experiment was carried out and relative waveform features are extracted to depict the relationship between sensory signal and tool wear value. The analysis and comparison show that Gaussian importance resampling method can avoid the problem of particle degradation and impoverishment effectively so as to realize accurate RUL prediction. [ABSTRACT FROM AUTHOR]

Objective: To investigate the role of miR‐424 in diabetic nephropathy (DN) and its relationship with Rictor in mammalian target of rapamycin (mTOR) C2/Akt signaling. Methods: The western blot analysis and real‐time polymerase chain reaction were used to determine the differential expression of Rictor, mTOR, and miR‐424 in DN rats. The upregulation of miR‐424 was achieved by caudal vein injection of miR‐424 mimics. The renal lesion was evaluated by hematoxylin‐eosin staining (H&E) and periodic acid schiff staining. The dual‐luciferase reporter assay was conducted to determine the binding target of miR‐424. The effect of miR‐424 upregulation on apoptosis was detected by the terminal deoxynucleotidyl transferase‐mediated 2‐Deoxyuridine‐5‐Triphosphate (dUTP) nick‐end labeling assay and western blot analysis. Results: A significantly lower expression of miR‐424 and a significantly higher expression of Rictor and mTOR were found in renal tissues of DN rats. The upregulation of miR‐424 improved renal lesion and DN symptoms of blood glucose level, urine protein level, body weight, creatinine level, blood urea nitrogen, and KW/BW ratio. The upregulation of miR‐424 could significantly reduce apoptosis rates of tissue cells by decreasing the expression levels of caspase‐3 and Bax as well as increasing the level of Bcl‐2. Furthermore, Rictor was the direct target for miR‐424, and upregulation of miR‐424 inhibited Rictor through Akt signaling in renal tissue of DN rats and high‐glucose‐treated human glomerular mesangial cells. Conclusion: miR‐424 contributes to alleviating the symptoms in DN rat models by targeting Rictor through mTORC2/Akt signaling. miR‐424 contributes to alleviating the symptoms in DN rat models by targeting Rictor through mTORC2/Akt signaling. [ABSTRACT FROM AUTHOR]

Using the concept of surface stress, we developed a model that is able to predict Young’s modulus of nanowires as a function of nanowire diameters from the calculated properties of their surface and bulk materials. We took both equilibrium strain effect and surface stress effect into consideration to account for the geometric size influence on the elastic properties of nanowires. In this work, we combined first-principles density functional theory calculations of material properties with linear elasticity theory of clamped-end three-point bending. Furthermore, we applied this computational approach to Ag, Au, and ZnO nanowires. For both Ag and Au nanowires, our theoretical predictions agree well with the experimental data in the literature. For ZnO nanowires, our predictions are qualitatively consistent with some of experimental data for ZnO nanostructures. Consequently, we found that surface stress plays a very important role in determining Young’s modulus of nanowires. Our finding suggests that the elastic properties of nanowires could be possibly engineered by altering the surface stress of their lateral surfaces. [ABSTRACT FROM AUTHOR]

This study addresses the challenge of deformation and failure on loess slopes, predominantly triggered by rainfall, by evaluating the efficacy of various slope protective measures. Recognizing the escalating preference for ecological protection techniques, this paper focuses on identifying optimal strategies that align with local rainfall patterns. A comprehensive analysis of loess slopes under diverse rainfall conditions was conducted, encompassing scenarios with prime soil, stabilized soil, and no protection. Utilizing the finite element software ABAQUS, a sophisticated rainfall infiltration slope model was developed and validated against experimental data. The investigation reveals that under low rainfall intensities, the choice of protective material—whether stabilized or prime soil—exerts limited influence on slope pore pressure. In contrast, at higher rainfall intensities, the impact of these protective materials on slope stability becomes significantly more pronounced. [ABSTRACT FROM AUTHOR]

The parts with integrated design technology are widely used in aerospace field because of their advantages such as high strength and high reliability compared with riveted structures, which often present multiple cavities and thin walls, and milling occupies a large amount of machining time, while it is very easy to cause rapid degradation of tool performance because their materials are mostly made of hard-to-machine metals. To address the failure of traditional methods in monitoring the tool trajectory of complex cavity milling process, this paper proposes a tool wear prediction method based on a short-time Fourier transform and an improved depth residual network. Firstly, the short-time Fourier transform is used to convert the signal into a time-frequency map. Then, to solve the problem that the depth residual network describes the machining state from a single perspective, the original model is improved by adding a feature fusion layer. Finally, the signal and the time-frequency map are simultaneously input into the improved deep residual network, and the tool wear sensitive features filtered by Pearson correlation coefficient are extracted from the time domain and frequency domain of the signal, and the deep features in the time-frequency domain are extracted from the residual block structure of the time-frequency map, and the tool wear sensitive features and the deep features in the time-frequency domain are fused in the feature fusion layer to complete the model training. The experimental results show that the average prediction deviation of tool wear by the regression model established in this paper is 0.76%, which is lower than that of the original deep residual network, shallow convolutional neural network, and artificial feature-based machine learning model. [ABSTRACT FROM AUTHOR]

We have investigated the segregation of Pt atoms in the surfaces of Pt-Ni nanoparticles, using modified embedded atom method potentials and the Monte Carlo method. The nanoparticles are constructed with disordered fcc configurations at two fixed overall concentrations (50 at. % Pt and 75 at. % Pt). We use octahedral and cubo-octahedral nanoparticles terminated by {111} and {100} facets to examine the extent of the Pt segregation to the nanoparticle surfaces at T=600 K. The model particles contain between 586 and 4033 atoms (particle size ranging from 2.5 to 5 nm). Our results imply that a complete {100}-facet reconstruction could make the cubo-octahendral Pt-Ni nanoparticles most energetically favorable. We predict that at 600 K due to segregation the equilibrium cubo-octahedral Pt50Ni50 nanoparticles with fewer than 1289 atoms and Pt75Ni25 nanoparticles with fewer than 4033 atoms would achieve a surface-sandwich structure, in which the Pt atoms are enriched in the outermost and third atomic shells while the Ni atoms are enriched in the second atomic shell. We also find that, due to an order-disorder transition, the Pt50Ni50 cubo-octahedral nanoparticles containing more than 2406 atoms would form a core-shell structure with a Pt-enriched surface and a Pt-deficient homogenous core.© 2005 American Institute of Physics. [ABSTRACT FROM AUTHOR]

Abstract Ultrafine-grained Ti–6Al–4V alloy with high mechanical properties in both strength and elongation was prepared by equal channel angular pressing and following pulsed electric current treatment. The mechanical properties of Ti–6Al–4V alloy were investigated by tensile tests at room temperature. Elongation of the samples treated by pulsed electric current and annealing was considerably increased by 66.5% and 20.8%, respectively. The plasticity of ECAP deformed Ti–6Al–4V alloy was significantly improved by pulsed electric current while the strength still remained relatively high. Comparing with conventional equal channel angular pressing and following annealing process, uniform fully recrystallization microstructure with fine grains, increasing proportion of beta phase and decreasing dislocation density was obtained at a relatively low temperature during a short time with the help of pulsed electric current. This study proves that the pulsed electric current provoked a fast recrystallization and phase transformation process of a titanium alloy produced by equal channel angular pressing. Highlights • Ti–6Al–4V alloy was treated by pulsed electric current and annealing. • Recrystallization and phase transformation were induced by pulsed electric current. • Plasticity of ECAP deformed Ti–6Al–4V alloy was improved. [ABSTRACT FROM AUTHOR]

In the work reported in this paper, high-pressure torsion (HPT) was conducted on Ti-22Al-25Nb alloy under the applied pressure of 6 GPa at ambient temperature in 1, 5, and 10 turns. Investigation of the microstructural characteristics and microhardness evolution of the HPT-processed Ti-22Al-25Nb alloy showed that the lamella B2-phase could be transformed to O-phase at ambient temperature. This was due to severe shear transformation of the B2 lattice caused by the high density of dislocations generated during HPT. Significant grain refinement was achieved, from grain size of ~67 μm in the initial annealed specimen to ~53 nm after 10 turns in the HPT process. In addition to dislocations, nanotwins played an important role in the grain refining process. With increasing accumulation of equivalent strain, the microhardness value of this alloy increased and reached a saturated value of about ~600 HV when the equivalent strain reached ~20. This is higher than that obtained by conventional processes. The hardening mechanisms were primarily attributed to pronounced grain refinement and the high density of dislocations induced by the HPT process. • The nanocrystalline Ti-22Al-25Nb alloy was first prepared by high-pressure torsion. • The phase transformation of B2→O at ambient temperature was observed during high-pressure torsion. • The hardening mechanism is attributed to grain refinement and the high density of dislocations induced by HPT process. [ABSTRACT FROM AUTHOR]

This article deals with the Raman spectroscopic research of aluminum–graphene (Al–Gr) composites obtained by aqueous suspension-based mixing to improve dispersion of graphene sheets in composite powders. Raman spectra of composite powders reflect encapsulated nanostructure of Al–Gr composite powders and chemical interaction of oxygen groups on graphene oxide (GO) with magnesium ions (Mg2+), depending on the added Mg2+ content. First, the enhanced Raman signal for our composite powders is an apparent evidence of that graphene sheets with uniform dispersion on Al matrix are in close contact with the spherical surface of Al powders. The polarization dependence of the Raman spectra, which are dependent on the incident laser spot, also confirms that the graphene sheets surrounded the spherical powder. SEM image, XPS and FT-IR spectra for the composite powders provide additional data to decipher the Raman analysis results. [ABSTRACT FROM AUTHOR]

Abstract This paper presents a novel course control strategy for unmanned surface vehicles (USV) subject to unmodeled dynamics and time-varying external disturbance. A practical adaptive course controller is proposed by trajectory linearization control (TLC) technology, neural network minimum learning parameter method (MLP), disturbance observer (DOB) and auxiliary design system. MLP and DOB are introduced to compensate for unmodeled dynamics and time-varying external disturbance, respectively. In addition, auxiliary design system is hired to deal with input saturation issue. By Lyapunov stability theory, it is proved that all the error signals in the course control system are uniform ultimate bounded. The advantages of the developed control strategy are that first, from the author's point of view, TLC technology is applied to the field of USV motion control for the first time, which opens a new research direction of this algorithm; second, MLP with a smaller computational burden is used to replace radial basis function (RBF) neural network, which is more convenient for engineering implementation; third, the proposed scheme has strong anti-interference ability, which can compensate for the inherent defect that the USV with a smaller volume is susceptible to external disturbance. Finally, numerical simulations prove the effectiveness and correctness of the proposed control strategy. [ABSTRACT FROM AUTHOR]

Abstract This study presents an electrically assisted diffusion bonding (EADB) process as a variation of solid-state diffusion bonding to obtain a wider dissemination of this technique. This concept is an experimental adaptation inspired by the rapidly increasing Joule heat during welding that has already been placed into practice. EADB was studied for a Ti 2 AlNb alloy sheet using a commercially pure titanium (CP-Ti) foil interlayer. An in-house built experimental setup was assembled to implement the EADB concept. The nonuniform temperature profiles of the Ti 2 AlNb alloy sheets under different electric current densities were imaged for reference in the subsequent discussion. Common characterization techniques were used to observe the interfacial microstructures, and the shear property and surface Vickers hardness were tested to assess the joint quality. The results showed that bonding interfaces consisted of the interlayer zone and the transition zone, and the Ti 2 AlNb alloy sheets were completely bonded under high electric current densities in the central zone of the sheet. When the density was increased to 4.58 A/mm2, the average room-temperature shear strength and Vickers hardness value reached the maximum values of 641 MPa and 493 HV, respectively. [ABSTRACT FROM AUTHOR]

Abstract Climate change, characterized with global warming, created severe potential threat to natural ecosystems and sustainable development of human society. Effective adaptation measures to mitigate the negative effects of climate change would affect both the ecological environment and the social economy. In this paper, we built a positive mathematical programming model to assess adaptation measures, which were divided into four aspects, to tackle climate change based on the survey data obtained from seven counties and 32 villages in the region of Hulun Buir. The results showed that, livestock breeding improvement had a positive impact on grass yield, livestock number and especially herder's household income (the most in Ewenki (11.7%) and the least in Xinzuo (2.3%)); artificial grassland project could lead to an average growth rate of 8.4% in household income among the four counties; current policies and going out for work could also increase household income, however, not a sustainable choice. To realize sustainable development in the context of global climate change, the vitality of sustainable development of animal husbandry under the premise of protecting ecological environment should be enhanced. For example, improving the safety and quality of livestock products through influencing livestock breeding, processing technology and high quality forage, and ensuring adequate forage supplement through artificial grassland project. Highlights • The pastoral regions in Hunlun Buir have a poor capability for resisting natural disasters. • We built a positive mathematical programming model to assess adaptation measures in a pastoral region. • Livestock breeding improvement and artificial grassland project had a positive impact on income. • Sustainable development of animal husbandry under the premise of protecting ecological environment should be enhanced. [ABSTRACT FROM AUTHOR]

In the milling process, chatter, which results in poor surface quality, dimensional errors, and reduced cutter and machine life, is one of the main limitations on performance. Consequently, a reliable, real-time detection method is desired to recognize chatter while it is developing. This study develops a novel method of online chatter identification for milling processes. In this method, optimized variational mode decomposition (OVMD) is used to decompose cutting force measurements, and the sub-components containing chatter information are extracted using a simulated annealing (SA) algorithm. The approximate entropy and the sample entropy are used to detect the onset of chatter. To evaluate the effectiveness of the proposed method, milling operations were performed and force measurements were collected for five types of operating conditions. The results show that the proposed method is suitable for detecting both continuous and intermittent chatter. Rather than establishing an absolute threshold for chatter detection, the onset of chatter is identified from relative changes in the entropy with time that occur under the various cutting conditions. The proposed method is shown to have greater sensitivity and stability than empirical mode decomposition (EMD). [ABSTRACT FROM AUTHOR]

Abstract This study calculated the CO 2 emissions due to fossil fuel consumption in China during 2000–2015 with consideration of the regional coal-, oil-, and gas-related variations. We used logarithmic mean Divisia index methods to establish the primary influencing factors of CO 2 emissions, and we extended the UK National Ecosystem Assessment Scenarios to forecast future CO 2 emissions related to fossil fuel use during 2020–2030. It was determined economic development is the main reason for increased CO 2 emissions, and that energy intensity and energy structure decreased CO 2 emissions. Finally, we considered six scenarios to predict the future development of coal, oil, and gas consumption in China. Six scenarios including Go with the Flow, Nature@work, Green and Pleasant Land, World Market, National Security and Local Stewardship, results show Green and Pleasant Land will induced coal and oil emission decrease and gas emission slightly increase. The results obtained based on analysis of CO 2 emissions and identification of regional influencing factors could provide useful information for decision makers regarding the allocation of fossil fuel use. [ABSTRACT FROM AUTHOR]

This paper presents a novel direct adaptive neural network controller for switched reluctance motor (SRM) speed control, which takes into account parameter variations, external load disturbances, and input saturation constraint. The radial basis function (RBF) neural network based on the technology of minimal learning parameters (MLP) is employed to approximate an ideal control law that includes parameter variations and external disturbances. An auxiliary dynamic system is constructed to handle the input saturation constraint. Furthermore, uniform ultimate boundedness of all signals in the SRM drive closed‐loop control system is guaranteed through rigorous Lyapunov analysis. Comparative studies are carried out between the proposed control scheme and conventional proportional‐integral (PI) control, and the simulation and experimental results show that the proposed control scheme has better performance for parameter variations and external load disturbances. © 2018 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc. [ABSTRACT FROM AUTHOR]

Abstract The process of diffusion bonding involves long time heating and needs bulky heating furnace. A long production cycle severely limits the commercial application on a large scale due to capital and energy costs. In an attempt to shorten the heating time in a cost-feasible manner, a novel electrically-assisted diffusion bonding (EADB) was proposed in this study. EADB is a result of applying electrically assisted concept to the conventional diffusion bonding process. Firstly, an EADB set-up was assembled to study the joining of Ti 2 AlNb alloy sheet that is recently studied as an excellent high-temperature structural material. The temperature distributions under different electric current densities were experimentally studied and the Ti 2 AlNb alloy sheets were successfully bonded without micro-cavity under 4.58 A/mm2. The microstructural evolution of EADB samples was discussed. Detour effect of electric current was found around the micro-cavity, which was determined by finite element analysis. Moreover, the mechanical tests of EADB samples showed that the highest shear strength was 587.24 MPa and the maximum hardness was 472.88 ± 6.36 HV/0.5/10. After that, heat treatment was used to homogenize the microstructures of EADB samples and the final samples showed basket-weave microstructures. Finally, comparisons with conventional processes were discussed in detail. Graphical abstract Unlabelled Image Highlights • A novel diffusion bonding process assisted by electric current was presented and validated. • Ti 2 AlNb ally sheets were successfully bonded by a self-built experimental set-up. • The maximum shear strength of bonding sample was 587.24 MPa and the highest hardness value was 472.88 ± 6.36 HV/0.5/10. [ABSTRACT FROM AUTHOR]

The electrically assisted forming has been a potential technique in the field of metallic sheet processing. Due to the demand of aerospace industry, Ti2AlNb alloy sheet combined with electrically assisted bulging method is studied. The results indicate that the superplasticity characterized by height/diameter ratio of the electrically assisted sample is 0.64 whereas that of the furnace-heating sample is 0.18. Because of the decrease in temperature during electrically assisted bulging and uneven temperature distribution, the lamellar O-phase precipitates from the matrix B2-phase with different sizes at typical positions of bulging sample, which is considered to simultaneously give rise to the transformation induced superplasticity. Subject to the high heating rate and short elevated-temperature exposure time compared with furnace-heating bulging, the O-phase is not coarse attributed to the deficient diffusion, while the O-phase has markedly grown up in the furnace-heating bulging sample. Moreover, no cavity has been found in the electrically assisted bulging sample. The impacts of temperature, strain, and electric current during electrically assisted bulging on precipitation and growth of O-phase were individually discussed in this work. [ABSTRACT FROM AUTHOR]

Recently the hotel industry has been facing immense pressure from several stakeholders, including the government, society, and consumers, to reduce the adverse impact of their activities on the environment. To respond to this pressure, hotels have started implementing various strategies to mitigate their detrimental environmental impact, and one of the strategies is to boost consumers' green behavior. However, there is limited knowledge about the decision-making process behind consumers' green behavior in hotels. Hence, this study aims to provide new insights and fill this critical research gap by exploring why and how hotels' perceived Corporate Social Responsibility (CSR) initiatives influence consumers' green behavior. To achieve this objective, the study investigates the mediating role of consumer engagement and positive emotions and the moderating role of altruistic values on the relationship between CSR and consumer engagement and positive emotions. Data is collected through a structured survey of hotel consumers in Pakistan. The results show that consumers' positive emotions and engagement mediate the effect of hotels' perceived CSR initiatives on consumers' green behavior. Moreover, the study confirms that altruistic values moderate the relationship between CSR, positive emotions, and consumer engagement. Theoretical and managerial implications are also discussed at the end of the paper. [ABSTRACT FROM AUTHOR]

This paper addresses three interrelated problems concerning the path following of a podded propulsion unmanned surface vessel (USV), namely, the modeling of podded propulsion USV, the model parameter identification and the guidance law design. Based on hypotheses and simplification, three degree of freedom (DOF) manipulating mathematical model group (MMG) models of podded propulsion USV are reduced to the response model, and then, a series of field experiments (turning experiment and zig‐zag experiment) is carried out to collect corresponding data. On this basis, the parameters of the model are obtained through the method of system identification. Meanwhile, the simulation data are compared with the actual data to verify the accuracy of the identification results. The conventional line‐of‐sight guidance is modified by adaptive sideslip angle and a time‐varying lookahead distance, where the lookahead distance is adjusted by fuzzy algorithm. Lyapunov function is used to prove that all error signals in the system are uniformly ultimately bounded. Three numerical examples and the real ship field experiment have been described to illustrate the performance and effectiveness of the proposed scheme. © 2018 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc. [ABSTRACT FROM AUTHOR]

Parallel kinematic machines exhibit strong pose-dependent static and dynamic behaviors, which makes accurate and rapid compliance analysis over the entire workspace an important issue in the design optimization. This paper presents a general approach for elastodynamic modeling of parallel kinematic machines using substructure synthesis technique. Firstly, the whole system is decomposed into two groups of substructures, i.e. component substructures and joint substructures. Then, the degrees of freedom of component substructures are reduced using modal reduction technique, and joint substructures are modeled by virtual springs with contact stiffness between adjacent component substructures. Finally, two threads are merged at junction surfaces to offer the equations of motion of the system as a whole, allowing the static and dynamic performances to be rapidly predicted with sufficient accuracy. The dynamic model of a 5-DOF hybrid robot is developed using the proposed method and the computational results show that rigidity and lower mode natural frequencies over the workspace match well with those obtained by the full finite element analysis. [ABSTRACT FROM AUTHOR]