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The purpose of this paper is to define the “fast evolving industry” (FEI) and its supply chain management (SCM) challenges. The authors review and structure the literature regarding integration strategies and implementation methods to develop a strategic decision-making framework for SCM in the FEI.

The authors conduct a review of SCM literature, including supply chain strategy, supply chain integration (SCI), agile and responsive supply chain and SCM for innovative and fast-changing industries. The authors develop a conceptual model and a decision-making framework and use four mini cases to provide support for the model and framework.

The FEI, characterised by a high level of innovation and differentiation, short products/services lifecycle and high variety, is yet to be fully defined. Inherent uncertainty in FEI supply systems makes SCM in these industries a complex but strategic task for their managers. The framework and the model offered in this study, which employ a core competency concept and provide risk management strategies, offer a strategic tool for managers and scholars in the field to optimise their integration strategies and to operationalise integration decisions.

Little research has been published on transferable and cross-industrial SCM in FEIs. This paper defines the FEI and its resource-related concerns and then offers a conceptual model and a strategic decision-making framework for SCI in FEIs.

Cross-docking is a supply chain distribution and logistics strategy for which less-than-truckload shipments are consolidated into full-truckload shipments. Goods are stored up to a maximum of 24 hours in a cross-docking terminal. In this chapter, we build on the literature review by Ladier and Alpan (2016), who reviewed cross-docking research and conducted interviews with cross-docking managers to find research gaps and provide recommendations for future research. We conduct a systematic literature review, following the framework by Ladier and Alpan (2016), on cross-docking literature from 2015 up to 2020. We focus on papers that consider the intersection of research and industry, e.g., case studies or studies presenting real-world data. We investigate whether the research has changed according to the recommendations of Ladier and Alpan (2016). Additionally, we examine the adoption of Industry 4.0 practices in cross-docking research, e.g., related to features of the physical internet, the Internet of Things and cyber-physical systems in cross-docking methodologies or case studies. We conclude that only small adaptations have been done based on the recommendations of Ladier and Alpan (2016), but we see growing attention for Industry 4.0 concepts in cross-docking, especially for physical internet hubs.

This paper aims to study the effect of the establishment of bankruptcy courts on bond issuance market. This paper helps to predict that the introduction of bankruptcy courts in China can mitigate price distortions caused by the implicit government guarantees and promote the development of the high-risk bond market.

This paper exploits the staggered introduction of bankruptcy courts across cities to implement a differences-in-differences strategy on bond issuance data. Using bonds issued in China between 2018 and 2020, the impact of bankruptcy courts on the bond issuance market can be analyzed.

This paper reveals that bond issuance credit spreads increase and is more sensitive to firm size, profitability and downside risk of issuance entity after the introduction of bankruptcy courts. It also reveals a substantive increase in bond issuance quantity and a decrease in issuer credit ratings following the establishment of bankruptcy courts. In addition, the increase of credit spreads is more prominent for publicly traded bonds, those whose issuers located in provinces with lower judicial confidence, bonds issued by SOEs and bonds with stronger government guarantees. Finally, the role of bankruptcy courts is more pronounced in regions with higher marketization.

This paper relates to previous studies that investigate the impact of laws and institutions on external financing. It helps provide new evidence to this literature on how improvements of efficiency and quality in bankruptcy enforcements relate to the marketization of bond issuance. The results provide further evidence on legal institutions and bond financing.

Based on the survey data of 1,152 households in three provinces of Shaanxi, Gansu and Ningxia on the Loess Plateau, this paper aims to empirically analyze the impact of aging and off-farm employment on farmers’ adoption behavior of soil and water conservation technology. This paper analyzes the moderating effect of social network and the mediating effect of technological cognition in this impact relationship.

Based on the above analysis, the second part of this paper is based on relevant theories and constructs a theoretical model of the relationship of aging, off-farm employment, social network, technology cognition and farmers’ adoption behavior of soil and water conservation technology. The third part introduces research methods, variable selection and descriptive statistics analysis of variables. The fourth part, based on the data of Shaanxi, Gansu and Ningxia provinces in the Loess Plateau in 2016, empirically analyzes the impact of aging, off-farm employment and social network on the farmers’ adoption behavior of soil and water conservation technology. This paper further examines the moderating effect of social network and the mediating effect of technology cognition in this influence relationship. Finally, based on the findings of the empirical study, this paper puts forward countermeasures and suggestions.

First, aging and off-farm employment have a significant negative impact on farmers’ adoption behavior of soil and water conservation technology, while social network has a significant positive effect. Second, social network has alleviated the effect of aging and off-farm employment on restraining farmers’ adoption behavior of soil and water conservation technology. Third, aging and off-farm employment have restrained farmers’ cognition of soil and water conservation technology. Social network has promoted farmers’ cognition of soil and water conservation technology. Social network plays a moderating role in the impact of aging and off-farm employment on farmers’ cognition of soil and water conservation technology. Technology cognition plays a mediating role in the impact of social network on farmers’ adoption behavior of soil and water conservation technology.

This paper integrates the aging, off-farm employment and social network into the same analytical framework and reveals their impact on farmers’ adoption behavior of soil and water conservation technology and its action mechanism, which enriches the impact of human capital and social network on farmers’ adoption behavior of soil and water conservation technology. Then taking the social network as a moderator variable, the paper verifies its moderating effect on the relationship of aging, off-farm employment and farmers’ adoption behavior of soil and water conservation technology. Farmers’ technology cognition should be included in the analysis framework to examine the impact of aging, off-farm employment and social network on farmers’ cognition of soil and water conservation technology. Taking the technology cognition as a mediator variable, the paper verifies its mediating effect on the relationship of aging, off-farm employment and farmers’ adoption behavior of soil and water conservation technology.

1. To improve the causality analysis performance, a novel causality detector based on time-delayed convergent cross mapping (TD-CCM) is proposed in this work. 2. Identify the root cause of plant-wide oscillations in process control system.

A novel causality analysis framework is proposed based on denoising and periodicity-removing TD-CCM (time-delayed convergent cross mapping). We first point out that noise and periodicity have adverse effects on causality detection. Then, the empirical mode decomposition (EMD) and detrended fluctuation analysis (FDA) are combined to achieve denoising. The periodicities are effectively removed through singular spectrum analysis (SSA). Following, the TD-CCM can accurately capture the causalities and locate the root cause by analyzing the filtered signals.

1. A novel causality detector based on denoising and periodicity-removing time-delayed convergent cross mapping (TD-CCM) is proposed. 2. Simulation studies show that the proposed method is able to improve the causality analysis performance. 3. Industrial case study shows the proposed method can be used to analyze the root cause of plant-wide oscillations in process control system.

1. A novel causality detector based on denoising and periodicity-removing time-delayed convergent cross mapping (TD-CCM) is proposed. 2. The influences of noise and periodicity on causality analysis are investigated. 3. Simulations and industrial case shows that the proposed method can improve the causality analysis performance and can be used to identify the root cause of plant-wide oscillations in process control system.

Based on DNase I and reduced graphene oxide (rGO)-magnetic silicon microspheres (MNPS), a highly sensitive and selective fluorescent probe for the detection of PD-L1 was developed.

Here °C we present a feasibility of biosensor to detection of PD-L1 in lung tumors plasma. In the absence of PD-L1°C the PD-L1 aptamer is absorbed on the surface of graphene oxide modified magnetic nanoparticles °8rGO-MNPS°9 and leading to effective fluorescence quenching. Upon adding PD-L1°C the aptamer sequences could be specifically recognized by PD-L1 and the aptamer/PD-L1 complex is formed°C resulting in the recovery of quenched fluorescence.

This sensor can detect PD-L1 with a linear range from 100 pg mL⁻¹ to 100 ng mL⁻¹, and a detection limit of 10 pg•m⁻¹ was achieved.

This method provides an easy and sensitive method for the detection of PD-L1 and will be beneficial to the early diagnosis and prognosis of tumors.

High-speed turnouts are more complex in structure and thus may cause abnormal vibration of high-speed train car body, affecting driving safety and passenger riding experience. Therefore, it is necessary to analyze the data characteristics of continuous hunting of high-speed trains passing through turnouts and propose a diagnostic method for engineering applications.

First, Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN) is performed to determine the first characteristic component of the car body’s lateral acceleration. Then, the Short-Time Fourier Transform (STFT) is performed to calculate the marginal spectra. Finally, the presence of a continuous hunting problem is determined based on the results of the comparison calculations and diagnostic thresholds. To improve computational efficiency, permutation entropy (PE) is used as a fast indicator to identify turnouts with potential problems.

Under continuous hunting conditions, the PE is less than 0.90; the ratio of the maximum peak value of the signal component to the original signal peak value exceeded 0.7, and there is an energy band in the STFT time-frequency map, which corresponds to a frequency distribution range of 1–2 Hz.

The research results have revealed the lateral vibration characteristics of the high-speed train’s car body during continuous hunting when passing through turnouts. On this basis, an effective diagnostic method has been proposed. With a focus on practical engineering applications, a rapid screening index for identifying potential issues has been proposed, significantly enhancing the efficiency of diagnostic processes.

This paper aims to build a theoretical model of the impact of farmers’ adoption behavior of soil and water conservation measures on the agricultural output to analyze the impact of farmers’ adoption behavior of soil and water conservation measures on agricultural output.

Based on the field survey data of 808 farmers households in three provinces (regions) of the Loess Plateau, this paper using the endogenous switching regression model to analyze the effect of farmers’ adoption behavior of soil and water conservation measures on agricultural output.

Soil erosion has a significant negative impact on agricultural output, and soil erosion has a significant positive impact on farmers’ adoption of soil and water conservation measures. Farmers adopt soil and water conservation measures such as engineering measures, biological measures and tillage measures to cope with soil erosion, which can increase agricultural output. Based on the counterfactual hypothesis, if farmers who adopt soil and water conservation measures do not adopt the corresponding soil and water conservation measures, their average output per ha output will decrease by 2.01%. Then, if farmers who do not adopt soil and water conservation measures adopt the corresponding soil and water conservation measures, their average output per ha output will increase by 12.12%. Government support and cultivated land area have a significant positive impact on farmers’ adoption behavior of soil and water conservation measures.

The research limitation is the lack of panel data.

Soil erosion has a significant negative impact on agricultural output, and soil erosion has a significant positive impact on farmers’ adoption of soil and water conservation measures. Farmers adopt soil and water conservation measures such as engineering measures, biological measures and tillage measures to cope with soil erosion, which can increase agricultural output.

The conclusion provides a reliable empirical basis for the government to formulate and implement relevant policies.

The contributions of this paper are as follows: the adoption behavior of soil and water conservation measures and agricultural output are included into the same analytical framework for empirical analysis, revealing the influencing factors of farmers’ adoption behavior of soil and water conservation measures and their output effects, enriching existing research. Using endogenous switching regression model and introducing instrumental variables to overcome the endogenous problem between the adoption behavior of soil and water conservation measures and agricultural output, and to analyze the influencing factors of farmers’ adoption behavior of soil and water conservation measures and its impact on agricultural output. Using the counter-factual idea to ensure that the two matched individuals have the same or similar attributes, to evaluate the average treatment effect of the behavior of soil and water conservation measures, to estimate the real impact of adaptation measures on agricultural output as accurately as possible and to avoid misleading policy recommendations.

This paper analyzes the application of digital twin technology in the field of intelligent operation and maintenance of high-speed railway infrastructure from the perspective of top-level design.

This paper provides a comprehensive overview of the definition, connotations, characteristics and key technologies of digital twin technology. It also conducts a thorough analysis of the current state of digital twin applications, with a particular focus on the overall requirements for intelligent operation and maintenance of high-speed railway infrastructure. Using the Jinan Yellow River Bridge on the Beijing–Shanghai high-speed railway as a case study, the paper details the construction process of the twin system from the perspectives of system architecture, theoretical definition, model construction and platform design.

Digital twin technology can play an important role in the whole life cycle management, fault prediction and condition monitoring in the field of high-speed rail operation and maintenance. Digital twin technology is of great significance to improve the intelligent level of high-speed railway operation and management.

This paper systematically summarizes the main components of digital twin railway. The general framework of the digital twin bridge is given, and its application in the field of intelligent operation and maintenance is prospected.

Through this research study, the authors found that digital thread has made significant progress in the life cycle management of the US Air Force. The authors hope that by reviewing similar studies in the aerospace field, the meaning of digital thread can be summarized and applied to a wider range of fields. In addition, theoretically, the definition of digital twin and digital thread are not unified. The authors hope that the comparison of digital thread and digital twin will better enable scholars to distinguish between the two concepts. Besides, the authors are also looking forward that more people will realize the significance of digital thread and carry out future research.

Complete research about digital thread and the relevant concept of the digital twin is conducted. First, by searching in Google Scholar with the keyword “digital thread”, the authors filter results and save literature with high relevance to digital thread. The authors also track these papers’ references for more paper of digital thread and digital twin. After removing the duplicate and low-relevance literature, 72 digital thread-related literature studies are saved and further analyzed from the perspective of time development, application field and research directions.

Digital thread application in industries other than the aviation manufacturing industry is still relatively few, and the research on the application of digital thread in real industrial scenarios is mainly at the stage of framework design and design-side decision optimization. In addition, the digital thread needs a new management mechanism and organizational structure to realize landing. The new management mechanism and the process can adapt to the whole life cycle management process based on the digital thread, manage the data security and data update, and promote the digital thread to play a better effect on the organizational management.

Based on a review of digital thread, future research directions and usage suggestions are given. The fault diagnosis of high-speed train bogie as an example shows the effectiveness of the method and also partially demonstrates the advantages and effects brought by the digital thread connecting the data models at various stages.

This paper first investigates and analyzes the theoretical connotation and research progress of digital thread and gives a complete definition of digital thread from the perspective of the combination of digital thread and digital twins. Next, the research process of digital thread is reviewed, and the application fields, research directions and achievements in recent years are summarized. Finally, taking the fault diagnosis of high-speed train bogie as an example partially demonstrates the advantages and effects brought by the digital thread connecting the data models at various stages.