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A new expression of the philosophy framework of pansystems theory is stated. Some generalized quantification formulae are developed. Concrete contents include: new forms of panderivative and pansymmetry, meta‐equation, eight‐counter methodology, pansystems relativity, dialectical logic, panbox principle, complex systems, systems engineering, analytic hierarchy process, general living systems, economy‐sociology, clustering, topology, morphology, master equation, approximation‐transforming theory, equivalence theory of dynamics of electromagnetic media, etc.

The purpose of this study is to present the state of the art for fiber Bragg grating (FBG) acceleration sensing technologies from two aspects: the principle of the measurement dimension and the principle of the sensing configuration. Some commercial sensors have also been introduced and future work in this field has also been discussed. This paper could provide an important reference for the research community.

This review is to present the state of the art for FBG acceleration sensing technologies from two aspects: the principle of the measurement dimension (one-dimension and multi-dimension) and the principle of the sensing configuration (beam type, radial vibration type, axial vibration type and other composite structures).

The current research on developing FBG acceleration sensors is mainly focused on the sensing method, the construction and design of the elastic structure and the design of a new information detection method. This paper hypothesizes that in the future, the following research trends will be strengthened: common single-mode fiber grating of the low cost and high utilization rate; high sensitivity and strength special fiber grating; multi-core fiber grating for measuring single-parameter multi-dimensional information or multi-parameter information; demodulating equipment of low cost, small volume and high sampling frequency.

The principle of the measurement dimension and principle of the sensing configuration for FBG acceleration sensors have been introduced, which could provide an important reference for the research community.

The paper takes the air-ground integrated wireless ad hoc network-integrated system as the research object, this paper aims to propose a distributed robust H_∞ adaptive fault-tolerant control algorithm suitable for the system to distribute to solve the problem of control and communication failure at the same time.

In the paper, the authors propose a distributed robust H_∞ adaptive fault-tolerant control algorithm suitable for the air-ground integrated wireless ad hoc network-integrated system.

The results show that the integrated system has good robustness and fault tolerance performance indicators for flight control and wireless signal transmission when confronted with external disturbances, internal actuator failures and wireless network associated failures and the flight control curve of the quadrotor unmanned aerial vehicle (UAV) is generally smooth and stable, even if it encounters external disturbances and actuator failures, its fault tolerance performance is very good. Then in the range of 400–800 m wireless communication distance, the success rate of wireless signal loop transmission is stable at 80%–100% and the performance is at least relatively improved by 158.823%.

This paper takes the air-ground integrated wireless ad hoc network-integrated system as the research object, based on the robust fault-tolerant control algorithm, the authors propose a distributed robust H_∞ adaptive fault-tolerant control algorithm suitable for the system and through the Riccati equation and linear matrix inequation method, the designed distributed robust H_∞ adaptive fault-tolerant controller further optimizes the fault suppression factor γ, so as to break through the limitation of only one Lyapunov matrix for different fault modes to distribute to solve the problem of control and communication failure at the same time.

With the advent of the Digital 2.0 era, online doctor–patient (D–P) interaction has become increasingly popular. However, due to the fact that doctors use their fragmented time to serve patients, online D–P interaction inevitably has some problems, such as the lack of pertinence in the reply content and doctors' relative unfamiliarity with their individual patients. Therefore, the purpose of this study is to excavate whether potential D–P social ties and D–P knowledge ties accentuate or attenuate the influence of patient selection (online and offline selection).

The authors used the methods of text mining and empirical analysis on the structured and unstructured data of an online consultation platform in China to examine the research hypotheses.

The findings illustrate that the potential D–P social ties increase the influence on patient selection, as do the potential D–P knowledge ties. Specifically, the effect of social ties on patient selection is positively moderated by patient health literacy. Conversely, health literacy weakens the link between knowledge ties and patient selection. In addition, the doctor's title weakens the influence of social ties on patient selection, in contrast to knowledge ties (partially).

This study provides guidance for doctors and patients on how to communicate effectively and alleviate tension within D–P relationships. The study’s findings have both theoretical and practical implications for both doctors' and online platforms' decision-making.

Coal is a critical global energy source, and fluctuations in its price significantly impact related enterprises' profitability. This study aims to develop a robust model for predicting the coal price index to enhance coal purchase strategies for coal-consuming enterprises and provide crucial information for global carbon emission reduction.

The proposed coal price forecasting system combines data decomposition, semi-supervised feature engineering, ensemble learning and deep learning. It addresses the challenge of merging low-resolution and high-resolution data by adaptively combining both types of data and filling in missing gaps through interpolation for internal missing data and self-supervision for initiate/terminal missing data. The system employs self-supervised learning to complete the filling of complex missing data.

The ensemble model, which combines long short-term memory, XGBoost and support vector regression, demonstrated the best prediction performance among the tested models. It exhibited superior accuracy and stability across multiple indices in two datasets, namely the Bohai-Rim steam-coal price index and coal daily settlement price.

The proposed coal price forecasting system stands out as it integrates data decomposition, semi-supervised feature engineering, ensemble learning and deep learning. Moreover, the system pioneers the use of self-supervised learning for filling in complex missing data, contributing to its originality and effectiveness.

The purpose of this paper is to explore a new approach to solve the problem of positive and negative offset in the calculation process of integral elements, then propose a series of new grey relational degree model for cross sequences.

The definitions of cross sequences and area elements have been proposed at first. Then the concept of difference degree between sequences has been put forward. Based on the definition of difference degree between sequences, various modified grey relational degree models for cross sequences have been proposed to solve the measurement problem of cross sequence correlation relationships.

(1) The new definition of cross sequences; (2) The area element; (3) Various modified grey relational degree models for cross sequences based on the definition of difference degree between sequences.

The grey relational analysis model of cross sequences is a difficult problem in grey relational analysis. The new model proposed in this article can effectively avoid the calculation deviation of grey relational analysis model for cross sequences, and reasonably measure the correlation between cross sequences. The new model was used to analyse the food consumer price index in Shaanxi Province, clarifying the relationship between different types of food consumer price indices, some interesting results that are not completely consistent with general economic theory were obtained.

The new definition of cross sequences, the area element and various modified grey relational degree models for cross sequences were proposed.

A new expression of the panorama of pansystems relativity is stated. Some modes and related principles or applications are developed. Concrete contents include: new forms of the framework 784e of pansystems theory and its connections with relativity. The paper introduces eight classes of relativity topics, and further research presents many new models of pansystems relativity such as: 23456R, super‐23456R, SSOS, SOMERQ, pansystems dialectics, clustering quotient, field‐net, meta‐topology, image‐boundary, cognition and practice, thinking experiment, etc. These modes present some new understanding to systems, society, methodology, epistemology, wisdom, psychology, hi‐tech, paradox, anthropology, ego, literature, arts, poetics and aesthetics, etc. There are 60 or more related references listed in the paper.

This chapter explores a descriptive theory of multidimensional travel behaviour, estimation of quantitative models and demonstration in an agent-based microsimulation.

A descriptive theory on multidimensional travel behaviour is conceptualised. It theorizes multidimensional knowledge updating, search start/stopping criteria and search/decision heuristics. These components are formulated or empirically modelled and integrated in a unified and coherent approach.

The theory is supported by empirical observations and the derived quantitative models are tested by an agent-based simulation on a demonstration network.

Based on artificially intelligent agents, learning and search theory and bounded rationality, this chapter makes an effort to embed a sound theoretical foundation for the computational process approach and agent-based micro-simulations. A pertinent new theory is proposed with experimental observations and estimations to demonstrate agents with systematic deviations from the rationality paradigm. Procedural and multidimensional decision-making are modelled. The numerical experiment highlights the capabilities of the proposed theory in estimating rich behavioural dynamics.

The high-quality development of the real estate industry is crucial to the transformation of China's economy. However, few studies apply the productivity to explore the development path of the real estate industry in China. To fill this gap, this study mainly investigates the total factor productivity (TFP) of the real estate industry of 30 sample provinces in mainland China from 2007 to 2016.

The Malmquist index is applied to estimate the productivity (i.e. TFP) of the real estate industry, based on the data envelopment analysis (DEA). Then, the truncated tobit regression analysis explores the external influencing factors on the TFP of the real estate industry.

Through empirical analysis, it is found that the high-quality development of the real estate industry depends on the technological innovation by the real estate enterprises and the targeted policies by the provincial government. Moreover, the development of the real estate industry has a positive correlation with the growth of China's economy but a negative correlation with the development of other industries.

TFP mainly reveals the development status of the provincial real estate industry and identifies the driving force for exploring the high-quality development mode of the real estate sector. Furthermore, the fluctuation rule of TFP can be applied to predict the development trend of the real estate industry in the future.

As an application, this study measures the TFP of the Chinese real estate industry in different provinces and periods. The results have meaningful policy implications for policymakers regulating the real estate industry.

This paper aims to focus on the high-speed rotary lip seal in aircraft engines, combining its service parameters, its own structure and application conditions, to study the influence of different eccentric forms, eccentricity, rotational speed and other factors on the performance of the rotary lip seal.

A numerical simulation model for high-speed eccentric rotary lip seals has been developed based on the theory of elastic hydrodynamic lubrication. This model comprehensively considers the coupling of multiple physical fields, including interface hydrodynamics, macroscopic solid mechanics and surface microscopic contact mechanics, under the operating conditions of rotary lip seals. The model takes into account eccentricity and uses the hazardous cross-sectional method to quantitatively predict sealing performance parameters, such as leakage rate and friction force.

Eccentricity has a large impact on lip seal performance; lips are more susceptible to wear failure under static eccentricity and to leakage failure under dynamic eccentricity.

This study provides a new idea for the design of rotary lip seal considering eccentricity, which is of guiding significance for the engineering application of rotary lip seal.