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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.

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.

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.

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%.

The purpose of this paper is to improve the efficiency of on-orbit operations through the top-level task design based on DoDAF. Based on the existing upper stage rocket technology, orbit transfer vehicles (OTVs) have developed rapidly in recent years. However, the lack of decision guidance based on overall task analysis requires integrating top-level analysis and bottom-level execution to achieve the smooth development of full-process tasks.

Using the Department of Defense Architecture Framework (DoDAF) as a reference, this paper performs the top-level mission analysis modeling of the on-orbit rendezvous and capture of the OTV. Moreover, the typical operational view products are obtained, and the cooperative relations among the mission requirements, the system requirements, and the functional requirements are also analyzed.

The results show that the attitude of the OTV changes violently during the maneuver and rendezvous phases. In addition, the view products can be optimized based on the results.

The proposed DoDAF-based on-orbit task integration analysis method achieves the effective fusion of high-level analysis and bottom-level execution of OTV on-orbit rendezvous and capture task through the top-level task modeling, operation view generation and task relationship analysis. According to the requirements and constraints of the on-orbit rendezvous and capture task, the control instructions of the vehicle are efficiently generated under the DoDAF framework.

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.

The purpose of this paper is to explore the impact of peer-to-peer (P2P) supply chain financing on companies' innovation efficiency.

This study takes the core companies that invest in the P2P platform as the research background and uses data for Chinese companies and the systematic Generalised Method of Moments (the systematic GMM) to explore the relationship between the improvement of supply chain efficiency, research and development (R&D) investment, and innovation efficiency.

This study indicates that core enterprise investment in P2P can cause a significant improvement in the efficiency of the supply chain and that this improvement can significantly motivate enterprises to increase R&D investment. Although the improvement of supply chain efficiency has no significant effect on improving companies' innovation efficiency, it can have a positive impact on innovation efficiency through the regulating role of R&D investment.

This research shows several limitations such as single industry and few companies involved, but it analyses the impact of P2P supply chain financing on R&D investment, and companies' innovation efficiency and broadens the research field of P2P supply chain financing.

This article provides a theoretical direction for listed companies to invest in P2P platforms and achieve supply chain management. The research on the regulating role of this article provides a new way of thinking for the study of enterprise innovation.

This paper analyses the impact of the core enterprise investment in P2P on R&D investment and its subsequent impact on the companies' innovation efficiency, thus broadening the research field of P2P supply chain financing.

The purpose of this paper is to identify the determinants for currency internationalization and forecast the potential of RMB as an international reserve currency.

This paper performs linear or non-linear regressions of the shares of eight major international reserve currencies as the reserve assets in global central banks on the macro economic and financial variables of their corresponding countries to identify the determinants for their international positions, and conducts an “counter-factual simulation” for the potential of RMB as an international reserve currency.

This paper finds that the economic size and the “network externalities” are the most important determinants for the international status of a reserve currency; that exchange rate volatility has negative impacts; the conditions for the RMB internationalization are basically available. The simulation for the potential of RMB as an international reserve currency reveals that the international role of RMB could surpass that of the Japanese Yen and the British Pound, and get close to Euro in the coming 15 years. Based on the empirical evidence, this paper suggests a promoting strategy for RMB internationalization.

This paper has not taken the influence of economic systemic and political factors on the process of RMB internationalization into account.

RMB internationalization promotion should follow the strategy of “stably create RMB international demand in the initial period and dramatically release the RMB overseas supply in the latter period” in the coming 15 years.

The conclusions and policy implications are from the results of the empirical analysis on the 45-year historical experience on the eight main international currencies.