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The original meaning of city–industry integration should be understood as the coordination, balance, reasonable layout, and mutual support between urban production functional areas and service functional areas, which both have urban populations as their core element. The evaluation of city–industry integration in industrial parks can be carried out from two aspects: land–industry integration and residence–industry integration. The secondary indexes of the former mainly include industrial land efficiency and service sector land efficiency, while the secondary indicators of the latter mainly include supporting rail transit and the matching degree between residence and environment. The output value, land use structure, enterprise profile, employment rates, investments, air quality, rail transit system and other data points regarding sample industrial parks were collected by means of geofencing as well as through the creation of an enterprise credit information database and development area yearbook. The Analytic Hierarchy Process (AHP) combined with expert scoring was used to determine the index weights and implement the evaluation of city–industry integration. This study found that city–industry integration in Beijing and the Chengdu Economic and Technological Development Zones is at the forefront of sample industrial parks, and the entropy weight evaluation method verified this evaluation result. The analysis of the benchmark development zone of city–industry integration shows that the Chengdu model and the Beijing model are worthy of reference for growing and mature industrial parks when promoting city–industry integration. [ABSTRACT FROM AUTHOR]

Deepsea mining risers, which transport mineral resources from the seafloor to surface facilities, are critical components of deepsea mining systems. This article presents a novel cointegration-based method for localizing structural damage in risers subjected to random excitations from waves, currents, and moving floating facilities. Although the dynamic responses of a riser (usually consisting of multiple segments) are often nonstationary, those within an individual pipe segment often have synchronous fluctuations with a common trend, allowing the application of a multivariate time series analysis. Cointegration can thus be performed for a pipe segment by treating the internal responses as the endogenous variables and those of the other pipe segments as the exogenous variables. Consequently, a stationary cointegrating residual for the dynamic responses purged of the influence of nonstationary excitations can be obtained. The cointegrating residual in conjunction with a statistical hypothesis test scheme is used to create an output-only damage indicator. The effectiveness of the proposed damage localization method is demonstrated with a numerical and experimental multi-segment riser. The results indicate that the strain responses of both risers exhibit nonstationary fluctuations due to the changeable environmental excitations. As the proposed method is robust to the external loading, it can accurately identify the damage location. [ABSTRACT FROM AUTHOR]

Vibration-based damage identification methods are committed to detecting structural damage by examining changes in the vibration characteristics of structures. However, these characteristics are not only affected by the structural damage but also subject to the change of environmental condition. A new damage localisation method, termed as residual strain energy (RSE) method, which is capable of locating damage on 3D structures under environmental variations, is presented. This RSE method employs the residual mode shapes to construct the damage localisation indicator, in which the principal component analysis algorithm is introduced to eliminate the influence of environmental variations. Numerical simulations were conducted on a 3D offshore platform structure considering temperature variations. Results indicate that the RSE method can effectively eliminate environmental influences and identify structural damage sites correctly. [ABSTRACT FROM AUTHOR]

Thanks to its sensitive characteristics to damages, modal strain energy (MSE) has been widely utilized for structural damage identification. Various MSE-related techniques on structural damage identification are surveyed and classified as damage index (DI) method, modal strain energy change (MSEC) method, cross-modal strain energy (Cross-MSE) method, and other methods. Four typical MSE-related methods are selected and firstly overviewed. Then damage identification of 1-D beam and 3-D offshore platform structures, considering the issues of spatial incompleteness, noise contamination, etc., are examined systematically with numerical simulation and experimental data. The ability of these four methods to locate damage is compared. Finally, some generalized criteria on these methods for damage identification are concluded, and suggestions for future work are discussed. This brief review aims to help readers identify starting points for research in vibration-based damage identification and health monitoring, and guide researchers and practitioners in better implementing available MSE-based damage identification algorithms. [ABSTRACT FROM AUTHOR]

Summary: An iterative two‐stage structural damage identification approach that combines the modal strain energy decomposition (MSED) method with the multiobjective particle swarm optimization algorithm is presented. The proposed scheme is inspired by the general noniterative two‐stage approach, which attempts to locate damage in the first stage and estimate the severity of damage in the second stage; however, the present approach differs by constructing an iterative MSED indicator to perform damage localization and severity estimation in a cyclic manner. Consequently, false positive indications of damage are gradually suppressed, and the precision of the damage severity estimation is improved as the iteration continues. In addition, a new element activation operation is embedded into the iterative process; in this step, possible false negative indications of damage excluded in the first stage can be activated and subsequently retested to identify damage, thereby reducing the false negative rate. Furthermore, a comparative study is conducted between the iterative two‐stage approach and the general noniterative approach by contemplating a 3‐D structure, and the effects of measurement noise and spatial incompleteness are considered. [ABSTRACT FROM AUTHOR]

Copper ferrite (CuFe 2 O 4 ) magnetic hollow fibers were prepared by applying an organic sol-thermal decomposition method, and silver nanoparticles were subsequently loaded on the fibers by calcination. The Ag-CuFe 2 O 4 fibers exhibited excellent antibacterial efficacy against four different bacteria (E. coli, S. typhi, S. aureus and V. parahaemolyticus) with consistent results. Typical ferromagnetism behavior exhibited from the Ag-CuFe 2 O 4 fibers enables their feasible recyclability.