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To solve the problem that the traditional received signal strength indicator real-time location method does not test the attenuation characteristics of the electromagnetic wave transmission in the location area, which cannot guarantee the accuracy of the location, resulting in a large location error.

At present, the compressed sensing (CS) reconstruction algorithm can be roughly divided into the following two categories (Zhouzhou and Fubao, 2014; Lagunas et al., 2016): one is the greedy iterative algorithm proposed for combinatorial optimization problems, which includes matching pursuit algorithm (MP), positive cross matching tracking algorithm (OMP), greedy matching tracking algorithm, segmented orthogonal matching tracking algorithm (StOMP) and so on. The second kind is the convex optimization algorithm, which also called the optimization approximation method. The common method is the basic tracking algorithm, which uses the norm instead of the norm to solve the optimization problem. In this paper, based on the piecewise orthogonal MP algorithm, the improved StOMP reconstruction algorithm is obtained.

In this paper, the MP algorithm (OMP), the StOMP and the improved StOMP algorithm are used as simulation reconstruction algorithms to achieve the comparison of location performance. It can be seen that the estimated position of the target is very close to the original position of the target. It is concluded that the CS grid-based target stepwise location method in underground tunnel can accurately locate the target in such specific region.

In this paper, the offline fingerprint database in offline phase of location method is established and the measurement of the electromagnetic noise distribution in different localization areas is considered. Furthermore, the offline phase shares the work of the location process, which greatly reduces the algorithm complexity of the online phase location process and the power consumption of the reference node, meanwhile is easy to implement under the same conditions, as well as conforms to the location environment.

Environmental, social and governance (ESG) can enhance the sustainable value and profitability of assets by improving environmental responsibility, social benefits and governance quality. However, there is a lack of research on the ESG aspects of the asset sustainability of infrastructure Real Estate Investment Trusts (REITs), particularly in terms of how ESG affects asset sustainability and their intrinsic relationships. Therefore, this study aims to explore the ESG factors affecting the asset sustainability of infrastructure REITs and their intrinsic linkages, in order to enhance the long-term sustainability of the asset.

The study employed structural equation modeling (SEM) to analyze the relationship between ESG factors and the sustainability of infrastructure REITs, through a comprehensive literature review and questionnaire survey to collect data. This method aims to provide a quantitative analysis framework to assess the impact strength and interactions of these factors.

The 11 ESG factors positively influence the sustainability of infrastructure assets. Specifically, carbon emission management, information disclosure and infrastructure asset management have the most substantial impacts, with path coefficients of 0.830, 0.814 and 0.817, respectively. Measures such as optimizing resource use, enhancing transparency and improving operational efficiency contribute to increased asset sustainability. Also, interviews indicate that asset managers and corporate executives with overseas educational backgrounds play a crucial role in the ESG management of infrastructure assets. Sustainability can be enhanced by promoting sustainable technologies and enhancing cross-cultural communication.

The results offer guidance for infrastructure REIT managers and policymakers, emphasizing the importance of strengthening specific ESG practices to enhance sustainability. This provides an empirical basis for optimizing ESG policies and practices, helping to advance infrastructure REITs towards more sustainable development directions.

This study offers new insights into the field of ESG for infrastructure REITs in China by providing specific analysis of ESG factors and applying SEM. The originality of this study lies in its deep exploration of the specific impact factors within the ESG dimensions and quantifying their relationship with sustainability, offering strong scientific support for the sustainable development practices of infrastructure REIT.

Given the increasing importance of engineering insurance, it is still unclear which specific factors can enhance the role of engineering insurance as a risk transfer tool. This study aims to propose a hybrid approach to identify and analyze the key determinants influencing the consumption of engineering insurance in mainland China.

The empirical analysis utilizes provincial data from mainland China from 2008 to 2019. The research framework is a novel amalgamation of the generalized method of moments (GMM) model, the quantile regression (QR) technique and the random forest (RF) algorithm. This innovative hybrid approach provides a comprehensive exploration of the driving factors while also allowing for an examination across different quantiles of insurance consumption.

The study identifies several driving factors that significantly impact engineering insurance consumption. Income, financial development, inflation, price, risk aversion, market structure and the social security system have a positive and significant influence on engineering insurance consumption. However, urbanization exhibits a negative and significant effect on the consumption of engineering insurance. QR techniques reveal variations in the effects of these driving factors across different levels of engineering insurance consumption.

This study extends the research on insurance consumption to the domain of the engineering business, making theoretical and practical contributions. The findings enrich the knowledge of insurance consumption by identifying the driving factors specific to engineering insurance for the first time. The research framework provides a novel and useful tool for examining the determinants of insurance consumption. Furthermore, the study offers insights into the engineering insurance market and its implications for policymakers and market participants.

The need for infrastructure is growing as urbanization picks up speed, and the infrastructure REITs financing model has been crucial in reviving the vast infrastructure stock, alleviating the pressure on government funds and diversifying investment entities. This study aims to propose a framework to better assess the risks of infrastructure REITs, which can serve for the researchers and the policy makers to propose risk mitigation strategies and policy recommendations more purposively to facilitate successful implementation and long-term development of infrastructure REITs.

The infrastructure REITs risk evaluation index system is established through literature review and factor analysis, and the optimal comprehensive weight of the index is calculated using the combination weight. Then, a risk evaluation cloud model of infrastructure REITs is constructed, and experts quantify the qualitative language of infrastructure REITs risks. This paper verifies the feasibility and effectiveness of the model by taking a basic REITs project in China as an example. This paper takes infrastructure REITs project in China as an example, to verify the feasibility and effectiveness of the cloud evaluation method.

The research outcome shows that infrastructure REITs risks manifest in the risk of policy and legal, underlying asset, market, operational and credit. The main influencing factors in terms of their weights are tax policy risk, operation and management risk, liquidity risk, termination risk and default risk. The financing project is at a higher risk, and the probability of risk is 64.2%.

This research contributes to the existing body of knowledge by supplementing a set of scientific and practical risk evaluation methods to assess the potential risks of infrastructure REITs project, which contributes the infrastructure financing risk management system. Identify key risk factors for infrastructure REITs with underlying assets, which contributes to infrastructure REITs project management. This research can help relevant stakeholders to control risks throughout the infrastructure investment and financing life cycle, provide them with reference for investment and financing decision-making and promote more sustainable and healthy development of infrastructure REITs in developing countries.

This study explores how factors arising from supply chain (SC) network and complexity work together in supply chain learning (SCL) behavior.

Fuzzy set qualitative comparative analysis, which is an emerging configurational analysis method, was adopted to examine the complex combination of five influencing factors. The data were collected using a two-stage survey. First, the authors selected seven typical firms with an awareness of SCL. Second, questionnaires were sent to the partners of the seven selected firms, and 156 valid questionnaires were obtained from 76 firms.

Drawing on emergent insights from the initiative, the authors find that multiple configurations of SC network and complexity lead to high SCL. Specifically, weak ties are necessary conditions of such learning, while strong ties are also conducive to this. Moreover, a moderate SC complexity is conducive to SCL.

This study enriches the understanding of SCL and provides new insights for SC management practitioners to take measures to improve it.

This study addresses the lack of in-depth understanding of the antecedent conditions of SCL in the literature. It establishes an integrated and comprehensive theoretical framework of such learning based on contingency theory. Additionally, this study incorporates ambidextrous SCL (i.e. creation capability and dispersion capacity). An overall prototype of SCL capability is proposed on SC network and complexity theory.

The purpose of this paper is to provide additive manufacturing-based solutions for preparation of elastomeric foam with broaden compressive stress plateau.

Mechanic models are developed for obtaining designs of foam cell units with enhanced elastic buckling. An experimental approach is taken to fabricate the foams based on direct ink writing technique. Experimental and simulation data are collected to assist understanding of our proposals and solutions.

A simple tetragonal structured elastomeric foam is proposed and fabricated by direct ink writing, in which its cell unit is theoretically designed by repeating every four filament layers. The foam exhibits a broader stress plateau, because of the pronounced elastic buckling under compressive loading as predicted by the authors’ mechanic modeling. A two-stage stress plateaus as observed in the foam, being attributed to the dual elastic buckling of the cell units along two lateral directions of the XY plane during compression.

Future work should incorporate more microscopic parameters to tune the elastomeric foam for mechanic performance testing on linear elastic deformation and densification of polymer matrix.

Additive manufacturing offers an alternative to fabricate elastomeric foam with controlled cell unit design and therefore mechanics. Our results comment on its broad space for development such superior cushioning or damping material in the fields of vibration and energy absorption.

This work has contributed to new knowledge on preparation of high performance elastomeric foam by providing a better understanding on its cell structure, being printed using direct ink writing machines.

This paper aims to systematically review the literature on quality management in agri-food supply chains (SCs) and propose an integrated conceptual framework.

A systematic literature review that analyses 93 papers in peer-reviewed academic journals published from 1996 to November 2021 is conducted. A conceptual model is advanced.

Based on a hierarchy of capabilities perspective, the authors develop an integrated conceptual framework in which SC quality (SCQ) management practices promote three levels of SC dynamic capabilities, which in turn lead to agri-food SCQ performance.

The authors propose a hierarchy of capabilities perspective of quality management in agri-food SCs and develop a conceptual framework. Furthermore, a number of propositions based on dynamic capabilities and the review findings are provided. Four future research directions are presented.

This paper aims to develop an ideal technique for the preparation of print circuit boards (PCBs) with ladder conductive lines on practical industrial process lines.

First, the raw materials of ladder copper-clad laminates were prepared by plating double-sided copper-clad laminates with vertical plating line. Second, etching compensation experiments were designed and conducted to set up the relationships between etching compensation and width of conductive lines on ladder line print circuit boards (LLPCBs). Third, to evaluate the process technique for the preparation of LLPCBs through etching compensation, verification experiments were designed and conducted on a practical industrial process line, and the quality of lines on LLPCBs was observed and evaluated.

Under the judgment of the quality of conductive lines on LLPCBs as well as the feasibility with a practical industrial process line, the process technique for the preparation of LLPCBs with etching compensation is a simple and reliable method which has the potential to be applied in the industry.

It is the first successful report of a new method that produces LLPCBs with etching compensation and has the potential to be applied in the industry.

The purpose of this paper is to prepare, characterise and evaluate nano-emulsions of copolymers of various compositions as eco-friendly binders for flexographic ink industry.

Various nano-emulsions of copolymers were prepared using styrene (St), butyl acrylate (BuAc), acrylic acid (AA) and acrylamide (AAm) monomers by means of a conventional seeded emulsion polymerisation technique, using K2S2O8 as the initiator. The characterisation of the prepared emulsions was performed using Fourier transform infrared (FT-IR), thermogravimetric analysis (TGA), gel permeation chromatography (GPC) and transmission electron microscopy (TEM). A selection of copolymers was formulated with pigments and additional ingredients, as water-based flexographic inks. The inks were characterised for their viscosity, pH, degree of dispersion, water resistance and colour density.

It was found that the low viscosity of the prepared copolymers may reduce the film thickness of the flexographic inks and may also increase the spreading of the ink on the surface. As a result, stable modified polyacrylate-based latex with improved physico-mechanical properties were obtained. The prepared latexes were showed improving and enhancing in water resistance; gloss values, and the print density that ranged from 2.06 to 2.51 and the maximum gloss values (39 and 48) were also obtained. Also, these binders provide excellent adhesion properties for both the pigment particles and the base paper.

This study focuses on the preparation of new water-based copolymer nanoparticles and their use as eco-friendly binders for flexographic ink industry.

The ink formulations developed could find use in industrial-scale printing.

Eco-friendly environment ink formulations for printing on paper substrates are novel.