Search

Nature has evolved a myriad of dedicate‐designed structures that assist in prey capture. Spiders employ their web structures for vibrational sensing and prey capture, analogous to a component of a neurosensory system. Here, we propose a spider web‐inspired sensor with integrated energy‐absorption and force perception capabilities by 3D printing. The conductive carbon black/TPU composite made from TPU granules and carbon black particles are employed for 3D printing. We analyze the underlying sensing mechanism of conductive CB/TPU composites stemming from the enhanced dispersion of the CB particles. Through 3D printing method, we are allowed to regulate the structure's form, filling density, arrangement, and printing path to tailor the static mechanical properties, initial resistance, and force sensitivity of the spider‐web inspired structure. The static mechanical model for single silk of the spider‐web inspired structure is constructed. We explore the energy absorption capability of spider‐web inspired structures with different structural parameters, and demonstrate its impact perceiving characteristics at different falling height. Additionally, we assembled a circuit to visually reflect the falling height of the impacting ball through the brightness of the LED light. This study provides insights to endowing structural materials with intelligent characteristics, contributing to their practical applications in the fields of biomedical, soft robotics, and artificial skin, etc. Highlights: A spider web‐inspired sensor is 3D printed with CB/TPU composites.The sensor has integrated force perception and energy‐absorption capabilities.The sensitivity capabilities can be regulated by parameter design.The mechanical model of the bioinspired structure is constructed.Its impact perceiving characteristics are demonstrated by two applications. [ABSTRACT FROM AUTHOR]

The Internet of Things (IoT) has revolutionized the connectivity of physical devices, leading to an exponential increase in multimedia wireless traffic and creating substantial demand for radio spectrum. Given the inherent scarcity of available spectrum, Cognitive Radio (CR)-assisted IoT emerges as a promising solution to optimize spectrum utilization through cooperation between cognitive and IoT nodes. Unlicensed IoT nodes can opportunistically access licensed spectrum bands without causing interference to licensed users. However, energy constraints may lead to reduced cooperation from IoT nodes during the search for vacant channels, as they aim to conserve battery life. To address this issue, we propose a Punishment-reward-based Cooperative Sensing and Data Forwarding (PR-CSDF) approach for IoT data transmission. Our method involves two key steps: (1) distributing sensing tasks among IoT nodes and (2) enhancing cooperation through a reward and punishment strategy. Evaluation results demonstrate that both secondary users (SUs) and IoT nodes achieve significant utility gains with the proposed mechanism, providing strong incentives for cooperative behaviour. [ABSTRACT FROM AUTHOR]

The Advanced Geostationary Radiation Imager (AGRI) sensor on board the geostationary satellite Fengyun-4B (FY-4B) is capable of capturing particles in different phases in the atmospheric environment and acquiring aerosol observation data with high spatial and temporal resolution. To understand the quality of the Land Aerosol (LDA) product of AGRI and its application prospects, we conducted a comprehensive evaluation of the AGRI LDA AOD. Using the 550 nm AGRI LDA AOD (550 nm) of nearly 1 year (1 October 2022 to 30 September 2023) to compare with the Aerosol Robotic Network (AERONET), MODIS MAIAC, and Himawari-9/AHI AODs. Results show the erratic algorithmic performance of AGRI LDA AOD, the correlation coefficient (R), mean error (Bias), root mean square error (RMSE), and the percentage of data with errors falling within the expected error envelope of ± (0.05 + 0.15 × AOD A E R O N E T) (within EE15) of the LDA AOD dataset are 0.55, 0.328, 0.533, and 34%, respectively. The LDA AOD appears to be overestimated easily in the southern and western regions of China and performs poorly in the offshore areas, with an R of 0.43, a Bias of 0.334, a larger RMSE of 0.597, and a global climate observing system fraction (GCOSF) percentage of 15% compared to the inland areas (R = 0.60, Bias = 0.163, RMSE = 0.509, GCOSF = 17%). Future improvements should focus on surface reflectance calculation, water vapor attenuation, and more suitable aerosol model selection to improve the algorithm's accuracy. [ABSTRACT FROM AUTHOR]

Environmentally fueled sustainable autonomous locomotion is an advanced intelligent behavior analogous to unconscious actions in biological organisms, such as heartbeat and peristalsis. In this study, a self‐sustaining oscillating soft robot is introduced with eccentric hinge structures inspired by the crawling locomotion of mollusks. A parameter‐encoded 4D printing method is utilized to pre‐program local strain of the eccentric hinge structure, and thus endows the soft robot with sustainable crawling motions under constant thermal field. Through the coupling design of substrate friction, eccentric hinge constitution, and the substrate temperature, the soft robot can achieve tunable crawling, rolling, and oscillating. Two applications, namely an optical chopper and a power generator are presented as proof of concepts. This work offers a viable solution for soft robots for applications in constrained environments such as the aerospace and medical fields. [ABSTRACT FROM AUTHOR]

This study optimized the extraction process of Chlorella protein using response surface methodology and characterized its secondary structure. With the protein solubility rate of Chlorella as the indicator, the effects of ultrasonic power, ultrasonic time, NaOH mass fraction, and water bath time on the extraction rate were investigated. Based on the Plackett-Burman design, a four-factor three-level response surface analysis was conducted to determine the extraction process of Chlorella protein. The results showed that the optimal extraction conditions for Chlorella protein were ultrasonic power of 460.08 W, ultrasonic time of 16.05 min, NaOH mass fraction of 14.03%, and water bath time of 37.18 min, with a solubility rate of 87.64%. The extracted Chlorella protein was purified using isoelectric focusing under optimal conditions and then subjected to FTIR analysis, microscopic structure analysis, and amino acid analysis. The results indicated that the secondary structure of Chlorella protein mainly consisted of β-sheet, accounting for 30.00% of the total content. The microscopic structure revealed a smooth surface with pore structures, and it contained five essential amino acids, accounting for 42.71% of the total content. In conclusion, the ultrasonic-assisted alkaline method demonstrates significantly improved protein wall-breaking efficiency and high protein extraction rate for Chlorella, with simple operation and low cost. It has promising prospects for industrial applications and provides relevant references for the food application of Chlorella protein. [ABSTRACT FROM AUTHOR]

Plate-like structures, including composite material plates, are extensively employed in major engineering structures such as aerospace, high-speed rail, and civil engineering. The growing utilization of curved panel structures and the increasing complexity of these structures have emphasized the need for flexible sensors capable of efficient signal front-end reception. Addressing the limitations of conventional sensors made of brittle piezoelectric materials in adhering to the surface of structures for health monitoring, a self-developed flexible dielectric elastomer-interdigital transducer (DE-IDT) array is employed to achieve damage imaging in isotropic aluminum curved panel structures and orthotropic composite material plates using linear frequency modulation (chirp) signal excitation. In addition, a proposed fusion method is utilized to obtain weighted imaging results, and evaluation and analysis are performed using relevant indicators. Experimental findings highlight the improved imaging accuracy achieved through phased array data fusion using the linear chirp signal, attributed to its wideband characteristics and ability to capture more damage signals. Moreover, the effectiveness of the circular DE-IDT array for damage detection and imaging in curved panel structures and composite material plates is successfully verified. [ABSTRACT FROM AUTHOR]

This study addresses the issue of inaccurate single damage fingerprint recognition during the process of bridge damage identification. To improve accuracy, the proposed approach involves fusing displacement mode difference and curvature mode difference data for single damage identification, and curvature mode difference and displacement mode wavelet coefficient difference data for two damage identification. The methodology begins by establishing a finite element model of the cable-stayed bridge and obtaining the original damage fingerprints, displacement modes, curvature modes, and wavelet coefficient differences of displacement modes through modal analysis. A fusion program based on the D-S evidence theory criterion is then developed using Matlab to calculate the displacement mode difference (DMD), curvature mode difference (CMD), and wavelet coefficient difference of displacement mode (WCDM) for data fusion. The recognition effect of a single fingerprint is analyzed using modal data for both single and two damage conditions. Additionally, the fusion of multiple fingerprint initial data is performed, and the recognition effect of the data fusion method is quantitatively analyzed through sub peak to peak comparison. It is observed that when the fusion index is used as the recognition index, the sub peak to peak ratio is smaller compared to using the curvature mode as the damage index. Consequently, the reduction in single damage is more significant, ranging from 12% to 48%, while the reduction in multi damage is approximately 2%. This method demonstrates the ability to accurately identify the location of damage, yielding satisfactory recognition results and showing promising feasibility. [ABSTRACT FROM AUTHOR]

The use of composite plate structures has become increasingly prevalent in industries such as civil engineering, aerospace, high-speed rail, automotive, and wind power. However, the propagation of ultrasonic Lamb waves in these structures is subject to multi-modal and frequency dispersion effects, which, coupled with the complicated anisotropic propagation mechanism of composite materials, makes it challenging to extract damage scatter signals without a health signal as a reference. In this study, we apply the frequency-wavenumber (f - k) domain filter wavefront modal method to carbon fiber reinforced polymer (CFRP) materials and use a three-dimensional (3D) window function to achieve different modalities and their corresponding damage reflection signals in the absence of a reference dispersion curve. Single modal damage imaging is achieved using a common source method (CSM) by laser vibration scanning experiment. To effectively extract single modalities in laminate material damage detection, a 3D filter window function was constructed. Considering the skew angle correction, it can effectively remove the direct wave signal, so as to realize the imaging of the damage. [ABSTRACT FROM AUTHOR]