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The performance of oil-filled pressure cores is very much affected by the corrugated diaphragm and the oil filling volume. The purpose of this paper is to show the effects of different corrugated diaphragms, different oil filling volumes and different treatments of the corrugated diaphragms on the performance of pressure sensors.

Pressure-sensitive cores with different diaphragm diameters, different diaphragm ripple numbers and different oil filling volumes are produced, and thermal cycling is introduced to improve the diaphragm performance, and finally the performance of each pressure-sensitive core is tested and the test data are analyzed and compared.

The experimental results show that the larger the diameter of the corrugated diaphragm used for encapsulation, the better the performance. For pressure-sensitive cores using smaller diameter corrugated diaphragms, the performance of one corrugation is better than that of two corrugations. When the number of corrugations and the diameter are the same size, the performance of the outer ring of the diaphragm with concave corrugations is better than that with convex corrugations. At the same time, the diaphragm after thermal cycling treatment and appropriate reduction of encapsulated oil filling can improve the performance of the pressure-sensitive core.

By exploring the effects of corrugated diaphragm and oil filling volume on the performance of oil-filled pressure cores, the design of oil-filled pressure sensors can be guided to improve sensor performance.

The purpose of this paper is to reduce the problem of temperature drift causing output errors in such sensors, three hardware compensation schemes are proposed in this paper, and three compensation schemes are designed and implemented.

In response to the problem of temperature drift causing output errors in this type of sensor, this paper proposes three hardware compensation schemes and carries out the design and implementation of the three compensation schemes. Finally, the advantages and disadvantages of the three compensation schemes are discussed through the analysis of the experimental results. The three hardware compensation methods are series-parallel resistance network compensation, digital signal processor (DSP) compensation and the joint compensation of resistance network and DSP. Series parallel resistance network compensation is to connect the low-temperature drift resistance and the sensor in series and parallel; DSP compensation is based on the combination of cubic spline interpolation and linear fitting algorithm, which uses DSP to process the data. Joint compensation is a new compensation method composed of the above two compensation methods.

The experimental results show that the relative error of the output is reduced to a certain extent after the three compensation methods, and the relative error of the output after the joint compensation is reduced to about 0.2%, which proves that the three compensation methods are feasible.

This paper presents three novel hardware compensation methods to reduce temperature drift in silicon on insulator (SOI) high-temperature pressure sensors. The joint compensation method, combining resistance network and DSP compensation, is particularly innovative and significantly improves output accuracy, reducing relative error to about 0.2%.

Due to its inexpensive production costs, low stress concentration and maintenance-friendliness, the adhesive bonded pipe joint is frequently utilized for pipe connection. However, further theoretical analysis is needed to understand the debonding failure mechanism of such bonded pipe joints under axial tension.

In this study, based on the bi-linear cohesive zone model, the integrated closed-form solutions were derived by considering the axial stiffness ratio and failure stage to determine the relative interfacial slip, interfacial shear stress and relationship of tension–displacement in the bonded pipe joint.

Additionally, solutions for the critical bonded length and the ultimate load capacity were put forth. Besides, the numerical study was conducted to verify the theoretical solutions regarding the load–displacement relationship. The interfacial shear stress distribution at different failure stages was presented to understand the interfacial shear stress transmission and debonding process. The effect of bonded length on the ultimate load and ductility of pipe joints was also discussed.

The findings in this study can give a reference for the design of bonded pipe joints in their actual engineering applications.

Business process models, while primarily intended for process documentation, communication, and improvement, are often also used as input for developing process-oriented software systems (Ouyang et al., 2009). Ensuring correctness, handling complexity, and improving reusability and maintainability of business process models are important for all these goals. The purpose of this paper is to propose an aspect-oriented business process modeling and correctness controlling method based on Petri nets to satisfy these goals.

The aspect-oriented paradigm provides a proper mechanism to modularization, and thus reduces the complexity of models, and also improves reusability and maintainability. However, weaving aspects into base processes may bring in mistakes or errors. To ensure correctness of modeling, this paper presents a formal approach to modeling aspect-oriented business processes and a method to ensure modeling correctness. Petri net is used as the process modeling language and its analysis techniques are applied to analyze the correctness of modeling. Two types of correctness, specifically, aspect-aspect correctness and base-aspect correctness are analyzed. A real banking process model is studied systematically in the case study to evaluate the approach and the performance assessments are conducted to show the cost and effect of the approach.

Designing aspect-oriented business process models help organizations reusing the model elements to reduce redundancy of their model repository, improving their maintainability, and supporting them to adapt to the changes of business requirements with flexible modeling. It is important to stress that the correctness of business process modeling is important in ensuring the quality of the models, especially in the safety-critical business domains, such as financial business domain.

In this paper, separation of concerns is used to separate the cross-cutting activities and core activities in accordance with the different functions of these activities, and an approach to modeling aspect-oriented business processes is proposed. First, the cross-cutting activities are encapsulated as aspects, while core business activities are modeled as base processes. Then, according to the correctness requirements of business process models, based on the weaving mechanisms of aspect-oriented approach, weaving correctness is defined. Weaving correctness controlling methods between multi-aspects and between aspects and base processes are designed. Errors or mistakes of aspect-oriented business process modeling are prevented during the procedure of modeling to ensure error-free business process modeling.

The purpose of this study is to provide a novel multi-fingered hand made of hyperelastic material. This kind of hand has the advantage of less mechanical parts, simpler control system. It can greatly cut down the complexity and cost of the hands under conditions of ensuring enough flexibility of grasping.

Based on the principle of virtual work, the equations of pulling force and grasping force are derived. To get the max grasping force, the optimal structural dimensions of the hand are obtained by finite element simulations. Hand’s grasping experiment is conducted.

The factors influencing grasping force and grasping stability are identified, and they are the length between short poles around the knuckles and the height of short poles. Experimental results show that the max strain of knuckles is less than the elastic limit of hyperelastic material, and the presented hand is practicable. The adaptive ability and grasping stability of the presented hand are demonstrated.

A novel multi-fingered hand made of hyperelastic material is presented in this paper. By designing the thickness of every section of a hyperelastic plate, the knuckle sections will bend and other sections of the plate will remain straight, and thus, the multi-fingered hand will grasp.

Online patient reviews are of considerable importance on online health platforms. However, there is limited understanding of how these reviews are generated and their impact on patients' choices of physicians. Therefore, this study aims to investigate the antecedents and consequences of online patient reviews on online health platforms.

This study introduced an online interaction model with multiple stages aimed at examining how physicians' service quality affects patients' review behavior and, consequently, influences patients' choices of physicians.

The results revealed that technical quality and emotional care significantly influenced the effort that patients exert and their use of positive emotional words when writing reviews, which, in turn, positively influenced patients' selection of physicians. Moreover, it was found that the voice channel had a significant moderating effect on the relationship between physician service quality and patient review behavior.

The study’s findings can help online health platform managers improve the platform system by optimizing the integrated text and voice interaction functions. The findings can also support physicians in improving service quality, managing online reviews and attracting patients’ choices.

This study enriches the literature on physician service quality, patient online reviews and choices in online health platforms. Furthermore, this study offers a novel perspective on the social exchange process in online healthcare settings by highlighting the role of media in shaping physician–patient interactions.

With burgeoning interest in the low-altitude economy, applications of long-endurance unmanned aerial vehicles (LE-UAVs) have increased in remote logistics distribution. Given LE-UAVs’ advantages of wide coverage, strong versatility and low cost, in addition to logistics distribution, they are widely used in military reconnaissance, communication relay, disaster monitoring and other activities. With limited autonomous intelligence, LE-UAVs require regular periodic and non-periodic control from ground control resources (GCRs) during flights and mission execution. However, the lack of GCRs significantly restricts the applications of LE-UAVs in parallel.

We consider the constraints of GCRs, investigating an integrated optimization problem of multi-LE-UAV mission planning and GCR allocation (Multi-U&G IOP). The problem integrates GCR allocation into traditional multi-UAV cooperative mission planning. The coupling decision of mission planning and GCR allocation enlarges the decision space and adds complexities to the problem’s structure. Through characterizing the problem, this study establishes a mixed integer linear programming (MILP) model for the integrated optimization problem. To solve the problem, we develop a three-stage iterative optimization algorithm combining a hybrid genetic algorithm with local search-variable neighborhood decent, heuristic conflict elimination and post-optimization of GCR allocation.

Numerical experimental results show that our developed algorithm can solve the problem efficiently and exceeds the solution performance of the solver CPLEX. For small-scale instances, our algorithm can obtain optimal solutions in less time than CPLEX. For large-scale instances, our algorithm produces better results in one hour than CPLEX does. Implementing our approach allows efficient coordination of multiple UAVs, enabling faster mission completion with a minimal number of GCRs.

Drawing on the interplay between LE-UAVs and GCRs and considering the practical applications of LE-UAVs, we propose the Multi-U&G IOP problem. We formulate this problem as a MILP model aiming to minimize the maximum task completion time (makespan). Furthermore, we present a relaxation model for this problem. To efficiently address the MILP model, we develop a three-stage iterative optimization algorithm. Subsequently, we verify the efficacy of our algorithm through extensive experimentation across various scenarios.

The purpose of this paper is to analyze and forecast the Chinese term structure of interest rates using functional principal component analysis (FPCA).

The authors propose an FPCA-K model using FPCA. The forecasting of the yield curve is based on modeling functional principal component (FPC) scores as standard scalar time series models. The authors evaluate the out-of-sample forecast performance using the root mean square and mean absolute errors.

Monthly yield data from January 2002 to December 2016 are used in this paper. The authors find that in the full sample, the first two FPCs account for 98.68 percent of the total variation in the yield curve. The authors then construct an FPCA-K model using the leading principal components. The authors find that the FPCA-K model compares favorably with the functional signal plus noise model, the dynamic Nelson-Siegel models and the random walk model in the out-of-sample forecasting.

The authors propose a functional approach to analyzing and forecasting the yield curve, which effectively utilizes the smoothness assumption and conveniently addresses the missing-data issue.

To the best knowledge, the authors are the first to use FPCA in the modeling and forecasting of yield curves.

This study examined how marketer- and user-generated photographs jointly influence consumers' online hotel booking.

Viewing photographs as stimuli that influence consumers' online hotel booking, this study proposes a research model and validates that using one quasi-experiment.

The findings of this study provide some empirical insights. Marketers can release room- and scene-related photographs. Users can release product- and social-related photographs. The interaction between room-related photographs by marketers and product-related photographs by users can promote energetic arousal and dominance and then promote online booking intention. The interaction between scene-related photographs by marketers and social-related photographs by users can promote energetic arousal and dominance and then promote online booking intention. Pleasure, energetic arousal and dominance can positively influence the attitude toward photographs. Pleasure and energetic arousal can positively influence the attitude toward photographs and then positively influence booking intention. Dominance can positively influence booking intention.

The findings of this study reveal significant interaction effects between marketer- and user-generated photographs on consumers' online booking. The findings will help researchers and marketers better understand the impact of photographs on consumers' online hotel booking.

Field-effect transistor (FET) has excellent electronic properties and inherent signal amplification, and with the development of nanomaterials technology, FET biosensors with nanomaterials as channels play an important role in the field of heavy metal ion detection. This paper aims to review the research progress of silicon nanowire, graphene and carbon nanotube field-effect tube biosensors for heavy metal ion detection, so as to provide technical support and practical experience for the application and promotion of FET.

The article introduces the structure and principle of three kinds of FET with three kinds of nanomaterials, namely, silicon nanowires, graphene and carbon nanotubes, as the channels, and lists examples of the detection of common heavy metal ions by the three kinds of FET sensors in recent years. The article focuses on the advantages and disadvantages of the three sensors, puts forward measures to improve the performance of the FET and looks forward to its future development direction.

Compared with conventional instrumental analytical methods, FETs prepared using nanomaterials as channels have the advantages of fast response speed, high sensitivity and good selectivity, among which the diversified processing methods of graphene, the multi-heavy metal ions detection of silicon nanowires and the very low detection limit and wider detection range of carbon nanotubes have made them one of the most promising detection tools in the field of heavy metal ions detection. Of course, through in-depth analysis, this type of sensor has certain limitations, such as high cost and strict process requirements, which are yet to be solved.

This paper elaborates on the detection principle and classification of field-effect tube, investigates and researches the application status of three kinds of FET biosensors in the detection of common heavy metal ions. By comparing the advantages and disadvantages of each of the three sensors in practical applications, the paper focuses on the feasibility of improvement measures, looks forward to the development trend in the field of heavy metal detection and ultimately promotes the application of field-effect tube development technology to continue to progress, so that its performance continues to improve and the application field is constantly expanding.