摘要 : Shoreline resources constitute one of the most critical terrestrial elements, as they play a pivotal role in fluvial-lacustrine monitoring and the sustainable utilization of spatial resources. As the longest and most economically significant river in China, the Yangtze River exhibits several unique geographical attributes, and as such, research on the spatiotemporal evolution and precise spatial delineation of its shoreline is important. Taking into account the complexity of the geographical environment, the study proposed a multi-stage strategy and geoscience knowledge-based method for shoreline extraction from Landsat time-series data. Longitudinal variations, spatial displacement, and interbank disparities between the northern and southern shores of the Yangtze River, China have been quantitatively assessed, supported by a shoreline change rate model was developed using the Digital Shoreline Analysis System. The results demonstrated a high level of accuracy in shoreline spatial positioning, with clearly demarcated land–water boundaries. From 1990 to 2020, the total shoreline length exhibited a net increase from 12, 645.02 km to 13, 637.42 km. Both the northern and southern shores displayed synchronous elongation trends, peaking in 2010 before subsequent retreat. Linear regression rate and end point rate analyses revealed overall stability in these migration trends but pronounced interbank heterogeneity. The southern shore exhibited significantly greater linear regression and end point rate variability than the northern shore ( P < 0.05), indicative of the stronger synergistic impacts from anthropogenic and natural drivers in that area. This study establishes a framework for high-resolution dynamic monitoring of shorelines along large river systems and elucidates the spatial differentiation mechanisms governing the fluvial evolution of shorelines. The findings provide empirical support for optimizing shoreline resource allocation, delineating environmental conservation boundaries, and implementing the "Yangtze River Conservation Strategy, " thereby advancing the capacity of regional sustainable development and spatial governance.

摘要 : Cf / SiC composites are characterized by high hardness, high brittleness, anisotropy, and heterogeneity, which induce machining defects such as matrix cracking and fiber pull-out during conventional mechanical processing, severely undermining the service performance and lifespan of components. To address this challenge, a novel single-excitation longitudinal-torsional ultrasonic elliptical vibration turning (LTUVT) device was designed and developed in this study. The primary objective was to achieve stable elliptical tool-tip motion through a simplified vibration system, thereby improving the machinability of the Cf / SiC composites. This study was conducted systematically, encompassing structural design, theoretical analysis, simulation verification, performance testing, and machining experiments. First, based on the principle of longitudinal-torsional vibration coupling, the core components of the device—the transducer and the horn—were structurally designed. Spiral grooves with the defined parameters were machined onto the horn surface. This design decomposes the longitudinal vibration generated by a single piezoelectric ceramic excitation into longitudinal and torsional vibration components with a specific phase difference. The three-dimensional elliptical trajectory of the tool tip, superimposed with the workpiece rotation, tool feed, and ultrasonic vibration, was analyzed through kinematic modeling. Motion equations were derived to elucidate the conditions for intermittent cutting and the friction reduction mechanism. Second, the dynamic characteristics of the designed transducer were investigated via finite element analysis using the COMSOL software. Modal analysis identifies an ideal longitudinal-torsional coupled vibration mode near 21 830 Hz, with the maximum amplitude concentrated at the output end and nearly zero amplitude at the flange, validating the structural rationality. Harmonic response analysis further shows that the longitudinal and torsional amplitudes at the output end at the target frequency are approximately 15 and 10.5 μm, respectively, with a ratio of about 0.7, falling within the preset range of 2-15 μm. Subsequently, the vibrational performance of the fabricated turning device was experimentally tested. The impedance analysis shows that the actual resonant frequency is 21 061 Hz, with a deviation of 5.3% from the preset frequency of 20 000 Hz. The admittance circle is well-formed, indicating good resonant characteristics. Amplitude testing using a laser Doppler vibrometer demonstrates that both longitudinal and torsional amplitudes increase synchronously with the ultrasonic power supply's output power, reaching maximum values of 12.84 and 11.2 μm, respectively, with an average ratio of about 0.9. These results are consistent with the simulation and design expectations, confirming the capability of the device to deliver stable and controllable elliptical vibrations. Finally, systematic comparative turning experiments were performed on the prepared Cf / SiC composite workpieces using polycrystalline diamond (PCD) tools. The influence of ultrasonic amplitude on the cutting forces, workpiece surface morphology, and tool wear was comprehensively investigated. The results indicate that the LTUVT significantly reduces the cutting forces. Compared with the CT, under the optimal parameters, the radial force, main cutting force, and feed force are reduced by an average of 25.8%, 23.9%, and 26.4%, respectively. Cutting forces decrease continuously with increasing ultrasonic amplitude, reaching minimum values (Fx=3.3 N, Fy=8.8 N, Fz=4.9 N) at a longitudinal amplitude of 9 μm. The LTUVT effectively suppresses the machining damage. Compared to the significant fiber pull-out, matrix cracking, and chip adhesion observed in CT, LTUVT promotes material removal modes dominated by fiber shear and brittle fractures. The fewest defects, such as fiber pull-out and pits, and maximum surface integrity are achieved at a longitudinal amplitude of 6 μm. LTUVT substantially mitigates tool wear. In contrast to the deep and continuous wear-land formed on the tool flank face in CT, LTUVT results in shallower wear grooves and a smaller wear-land area. The tool flank wear area first decreases and then increases with increasing amplitude, reaching a minimum average value of 50 150 μm2 at a longitudinal amplitude of 6 μm, representing a reduction of approximately 79.95% compared to CT. However, excessive amplitude (9 μm) leads to aggravated micro-chipping of the cutting edge. The optimal process parameter identified is a longitudinal amplitude of 6 μm (corresponding to a torsional amplitude of approximately 5.4 μm), which balances superior surface quality with minimal tool wear. This study provides an effective ultrasonic vibration-assisted machining solution for the precise and efficient processing of difficult-to-machine composites, such as Cf / SiC, with significant theoretical and practical engineering value.

摘要 : This paper presents a distributed finite-time observer design approach for the problem of intelligent connected vehicles (ICVs) containing both attack signals and unknown disturbances. Firstly, an analysis is conducted on the two types of network attacks that ICVs may encounter, followed by the construction of a dynamic vehicle model and its transformation into a state space equation. Secondly, an intermediate variable is introduced to design a distributed attack estimation observer, which both ensures accurate estimation of the vehicle safety state and attack signal within a limited time and overcomes the constraints of traditional observers. Additionally, sufficient conditions for the finite-time boundedness of the observer error system with H∞ performance are provided in the form of linear matrix inequalities. Furthermore, an adaptive threshold attack detection method is designed. Finally, the simulation results validate the efficiency of the design methods.

摘要 : Communication among the stakeholders has critical influences on the knowledge sharing among them and overall performance of construction projects. However, a comprehensive review on communication in construction is absent, leading to a poor understanding on the research status and future research directions in this field. This research, therefore, aims to conduct a review on global communication research in construction from a bibliometric perspective. CiteSpace software was used to visualize and analyze the papers related to communication in construction in Web of Science Core Collection from 2015 to 2024. 189 English papers were screened and then analyzed. The results indicate that the number of construction communication papers has been generally increasing in recent years. Although researchers have shown significant interests in communication issues pertaining to management, performance, and model, the research hotspot areas have evolved over the past two five-year periods. Six important clusters were identified including building information modeling, construction industry, social network analysis, safety communication, and others. Research limitations within the topics and methods, along with future directions, were discussed in depth based on the analysis results. The insights obtained from this paper are valuable for researchers to embark on further research on communication in construction in the future.

摘要 : Introduction: With the rapid popularization of electric vehicles, their charging load influences the stable operation of the power grid. An accurate prediction of EV charging station load is crucial for optimal resource allocation in power systems. The objective of this study is to address the issue of insufficient accuracy in existing prediction methods, this paper proposes a hybrid prediction model based on Bidirectional Long Short-Term Memory and Adaptive Boosting, aiming to improve the accuracy and stability of medium and long-term EV charging station load forecasting. Methods: The study employs a three-step approach: (1) The pearson correlation analysis was utilized to evaluate multi-dimensional influencing factors and reduce dataset dimensionality' (2) implementation of a BiLSTM neural network for temporal feature extraction and preliminary prediction' and (3) application of the Adaboost algorithm to construct a weighted combination of strong classifiers. The model's effectiveness was validated through comprehensive simulation tests using real-world charging station data. Results: The proposed Pearson feature selection-based BiLSTM-Adaboost model outperforms traditional benchmark models (LSTM and SVM), effectively reduces data redundancy through feature selection, achieves better performance in key indicators (MSE, RMSE, and MAPE), and demonstrates strong generalization ability and robustness while maintaining high accuracy. Discussion: Experimental results demonstrate that the proposed method effectively extracts key features of charging loads, achieving superior prediction accuracy and generalization ability compared to traditional methods. This provides a reliable decision-making tool for power grid operation, effectively supporting the resilience planning needs of urban power grids under continuously increasing EV penetration rates. But further research is needed to address robustness under extreme weather conditions. Conclusion: This study provides an effective load forecasting methodology for power systems to address the challenges of large-scale electric vehicle integration. Future research will explore more robust feature engineering methods and deep learning architectures, such as combining other more advanced time series prediction models and improving optimization algorithms to enhance model adaptability and generalization capability for complex data patterns.

摘要 : Accurate quantification of iron is essential in biological, chemical, and nanomaterial research, yet commonly used ferrozine-based assays suffer from safety hazards, inconsistent reduction efficiency, and unstable absorbance readings. To address these issues, we systematically optimized the classical protocol and validated improvements that enhance both operational safety and analytical reproducibility. In this work, samples were digested using perchloric acid and hydrogen peroxide, reduced with hydroxylamine, and complexed with ferrozine, with all steps quantitatively evaluated to identify conditions that minimize variability. The optimized assay introduces three key refinements: combining the two traditional hydroxylamine additions into a single reduction step, extending the post-complexation incubation to 2 h to ensure complete formation of the Fe2+–ferrozine complex, and performing digestion exclusively in 5 mL screw-cap polypropylene tubes to eliminate tube-bursting events frequently observed with flip-cap formats. Kinetic analysis confirmed that absorbance at 562 nm reaches a stable plateau after 2 h, and the resulting standard curve exhibited excellent linearity (R2 = 0.9999). These improvements significantly enhance precision, safety, and ease of implementation. The refined method is broadly applicable and enables reliable quantification of iron in tissues, cultured cells, aqueous solutions, and iron-containing nanomaterials.

摘要 : Shear walls are essential for enhancing a building's seismic resilience. Controlled cracking boosts ductility and energy dissipation, while excessive cracking weakens strength and stability. Optical Frequency Domain Reflectometry (OFDR) has enabled the acquisition of strain measurements with an unparalleled level of detail, providing an accurate and ubiquitous description of cracking throughout reinforced concrete structures. In this paper, a method for the deployment of optical fibers (OFs) in the cast-in-place shear wall and assembled prefabricated shear wall (APSW) connected with Ultra-High Performance Concrete (UHPC) is presented, and the OFDR technology is utilized to capture the strain field evolution associated with crack initiation and propagate of the shear walls under low-cyclic loading. The results indicate that the cracking positions of the shear walls appear as the occurrence of peak tensile strains in the sensing OFs, and the locations of micro-crack initiation within the shear cracks can be well identified via peak positioning. Two-dimensional strain field analysis shows the morphology and development of shear cracks, which also proved the seismic performance of the APSW has been improved compared with that of the cast-in-place shear wall. Embedding OFs as sensing elements empowers intelligent shear wall monitoring and paves the way for advanced smart construction.

摘要 : Due to the wide range of application prospects, the high-performance optoelectronic sensing system are crucial for supporting rapid societal progress. In this work, we propose and demonstrate an optoelectronic sensing system based on the on-board integration of a photodetector (PD) based on (In,Ga)N nanowires and an aqueous zinc-ion battery (AZIB) employing a polyaniline cathode successfully. The PD demonstrates distinct on-off switching characteristic under ultraviolet illumination and operates effectively in zero-bias (self-powered) mode. It can perform different logic gate operations, and its responsivity exhibits bias-dependent tunability. Furthermore, the AZIB demonstrates a coulombic efficiency of 99.55% at 1 mA cm−2. Notably, by integrating the voltage supplied by the AZIB to the external circuit with the bias voltage regulation of the PD, the responsivity of the PD can be enhanced by 264%, demonstrating the beneficial role of the AZIB integration in optimizing detection performance. This study provides a novel approach to construct the safe, low-cost and portable photoelectric sensing systems, which is conducive to broadening application scenarios in the field of photoelectric technology.