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The current rapid urbanization, industrialization, and expansion of urban construction patterns have resulted in a large number of residual plaques in the urban area, including both the original plaques that are extremely fragmented and the new plaques that are metabolized by urban production, especially natural habitat patches are more pronounced. Ecological restoration of residual plaques plays an important role in maintaining biodiversity, protecting native species, providing ecological services, revitalizing land resources, inheriting regional characteristics, shaping urban image, and improving the ecological environment. Therefore, research on the subject is necessary and urgent. The topic is based on the ecological survey of urban residual patches and the study of the characteristic attributes of current urbanization, defining the connotation, extension, type, characteristics, and influencing factors of urban residual patches, and analyzing the process of fragmentation of residual plaques in cities and their artificial interference relationship. From the macro, meso, and micro scales, from the top level of ecological planning, the whole process of life cycle management, and the moderately disturbed bottom layer of ecological engineering nodes, three levels are restored, theoretical integration guidance and technical restoration. Based on the three dimensions of the continuous symbiosis of nature, cost control of the economy, and public participation of the society, repair and activate the remaining plaques of the city to provide technical support for the construction and sustainable development of urban ecological civilization.

Neural networks are popular data-driven modeling tools that come with high data collection costs. This paper proposes a residual-based multipeaks adaptive sampling (RMAS) algorithm, which can reduce the demand for a large number of samples in the identification of stochastic dynamical systems. Compared to classical residual-based sampling algorithms, the RMAS algorithm achieves higher system identification accuracy without relying on any hyperparameters. Subsequently, combining the RMAS algorithm and neural network, a few-shot identification (FSI) method for stochastic dynamical systems is proposed, which is applied to the identification of a vegetation biomass change model and the Rayleigh–Van der Pol impact vibration model. We show that the RMAS algorithm modifies residual-based sampling algorithms and, in particular, reduces the system identification error by 76% with the same sample sizes. Moreover, the surrogate model accurately predicts the first escape probability density function and the P bifurcation behavior in the systems, with the error of less than 1.59 × 10 − 2 . Finally, the robustness of the FSI method is validated. [ABSTRACT FROM AUTHOR]

Human fingers possess stable high sensitivity and a wide range of tactile perception, attributed to the gradient microstructure and the interlocking collagen fiber on the skin's surface. However, challenges persist in achieving simultaneous enhancement of multiple functionalities in artificial skin. Inspired by the unique structure of the skin, a two‐step process involving ion diffusion‐induced and strong‐weak topological crosslinking is synergistically employed to fabricate a bilayer gradient hydrogel. Zn2+ initially diffuses to induce the formation of weak bonds, imparting elasticity. Subsequently, Fe3+/Zn2+ diffusion constructs a strong‐weak topologically crosslinked network, enhancing the toughness of the gel while reducing the brittleness associated with robust bonds. Due to its distinctive design, the gel employs an adaptive energy dissipation strategy subjected to large and small stress, ensuring high sensitivity (3.31 kPa−1, 0–2 kPa), wide sensing range (0.4–40.6 kPa), and exceptional stability (500 cycles). This flexible approach enables programmable design in three dimensions, including ion diffusion type, direction, and shape. This gel can detect the gentle brushing of feathers and human body movements. It utilizes significant differences generated by magnitudes of stress to perform binary information encryption. This study introduces a novel strategy for preparing skin‐like gels, offering promising potential for expanding their applications in complex scenarios. [ABSTRACT FROM AUTHOR]

Traditional artificial skin gels often only focuses on a single perspective and overlooks the necessity of multidimensional synergistic design for sensitivity enhancement. To address these problems, the innovative introduction of dual solvents on the surface of polyacrylamide/sodium alginate gel induces to the transformation of supramolecular interactions including ion coordination, crystalline alcohol, and phase separation, synergistically achieving adjustable wrinkle wavelengths (304.2 ± 19.9 to 2393.5 ± 95.9 µm) and modulated chemical compositions with tunable moduli (87.5 ± 3.3 to 157.6 ± 3.7 kPa). This flexible strategy allows the construction of long‐range ordered wrinkled microstructures of three‐dimensional surfaces and complex morphologies. Meanwhile, the bridge effect induced by crystalline alcohols directs the insertion of ethanol molecules into the polymer chains, effectively reducing intramolecular friction. Benefiting from the small wavelength and low modulus dominated by crystalline alcohol, the wrinkled gel exhibits extremely high sensitivity of 164 kPa−1 (<0.5 kPa) and wide detection range (44.3 kPa). The wrinkled gel remains stable high sensitive to detect micro‐ and large stress, tactile perception, and human motion behaviors. This work proposes a new strategy for constructing highly sensitive bioinspired skin from multiple dimensions, showing broad application prospects in the fields of bioengineering and behavioral cognition. [ABSTRACT FROM AUTHOR]

The flow duration curve (FDC) is the cumulative distribution function, which represents the relationship between the frequency and magnitude of streamflow, and the precipitation duration curves (PDC) follows the same principle. Nowadays, the correlation between the shape of PDC and FDCs, their respective physical control factors including human activities, and their fitting conditions in unmeasured catchments across China have not been fully understood. In this paper, daily precipitation and streamflow data with 30 years records from 224 hydrological stations in the middle and lower Yangtze River basin were chosen to fit PDC and FDCs through gamma distribution. Framework was proposed for modelling FDCs to analyse the relationship, similarity, regional patterns and response mechanism of fitting parameters between PDC and FDCs, dividing the streamflow time series into fast and base flow and stations into three categories in consideration of human activities to attribute the shapes of PDC and FDCs to catchment meteorological and geographical characteristics and physical processes under natural conditions. Results indicate that the parameters of PDC and certain FDCs (TFDC, FFDC, SFDC) share similar spatial patterns but vary for the different duration and interactions of the processes. The climate and catchment characteristics such as extreme properties of precipitation, base flow index (BFI), Pmax*αp and concentration ratio index (CIM) will influence the shape of PDC and FDCs. The relationship between BFI and SFDC/TFDC can be better reflected in "Regulated watersheds", while CIM/Pmax*αp and PDC/FFDC in "watersheds in the mainstream" are more related. This paper provides a deeper understanding and more accurate way of the application of these parameters in describing and predicting hydrological processes and estimation of PDC and FDCs in unmeasured catchments, and can be applied to more future research about processes based on catchment rainfall‐runoff responses and physical controls. [ABSTRACT FROM AUTHOR]

With the development of pre-fabricated composite structures, concrete filled steel tubular (CFST) columns have been widely used, and researches on T-shaped CFST slender columns have attracted much attention. Since ordinary T-shaped CFST columns have weak constraint on concrete at the sectional concave angle region and local buckling easily occurs in this region, a multi-cellular T-shaped concrete filled steel tubular (MCT-CFST) column was developed for improving the axial resistant performance. In this study, the global stability performance of MCT-CFST slender columns under uniaxial eccentric compression was investigated. Firstly, three pin-ended MCT-CFST slender columns were tested under eccentric compression with different eccentricities. Secondly, a refined finite-element (FE) model of MCT-CFST column was established, and the load–displacement curves, Mises stress and deformation diagrams from the FE analysis were compared with the experimental results to verify the validity of the FE model. Moreover, based on the validated FE model, a parametric analysis was carried out to study the effects of normalized slenderness ratio, thickness of steel plate and material strength on the global stability performance of MCT-CFST slender columns under combined axial and bending loads. Finally, N - M interaction curves were obtained from the numerical simulations, and these results were considered to provide valuable references for designing MCT-CFST slender columns in engineering practice. [ABSTRACT FROM AUTHOR]

In recent years, due to the support of our country, PV-storage microgrid develops rapidly. However, the flexible network operation modes of PV-storage microgrid change flexibly and the operating characteristics with a large amout of sources is highly complicated. Based on the existing microgrid coordinate control methods, this paper proposes multilayer PV-storage microgrid algorithm for fitting dispatch of distributed network, which achieves maximum output of renewable energy when meeting the scheduling requirements of network, by building PV-storage microgrid type dynamic simulation system in a variety of conditions in PSCAD. Simulation results show that the heuristic algorithm proposed can achieve microgrid stable operation and satisfy the demands of the dispatch in distributed network.