Great progress has been made in the development of liquid-metal-based wearable devices. However, the sensitivities of the liquid-metal-based strain sensors are still limited in an inadequate range. Herein, a highly sensitive and stretchable strain sensor constructed with an aligned electrospun thermoplastic polyurethane (TPU) fibrous base and a patterned biphasic metal sensing layer was developed. The patterned biphasic metal sensing layer was composed of liquid metal (LM) Galinstan as “islands” and solid metal silver (Ag) as “sea”. Ag “sea” prevented the formation of a continuous LM conductive pathway. The sensitivity was enhanced significantly based on the crack propagation mechanism of the Ag conductive region. Additionally, the alignment of fibers ( horizontally or vertically aligned ) weakened fiber rearrangement, and enlarged the deformation of the sensing layer. Results showed that, the sensitivity of the sensors composed of a single LM layer or a pure Ag layer with a vertically aligned fibrous base increased by 1. 09 and 33. 19 times compared to that with the randomly oriented fibrous base, respectively. The final patterned biphasic metal strain sensor with a vertically aligned fibrous base could achieve an ultrahigh sensitivity (gauge factor up to 952. 20) and a wide sensing range (up to 59. 33%). This design shows a great potential for a wide variety of wearable devices.
To reduce slippage between the sensing module mounted on the tight-fitting clothing and the human skin during body movement, the clothing was optimized by numerical simulation. Firstly, solid models of the upper body and the sleeveless tight-fitting clothing were established using the reverse engineering software Geomagic Studio. Secondly, the sleeveless tight-fitting clothing was cut and segmented by the structural style of the tight-fitting clothing and the range of the skin deformation in each area. Finally, taking the running movement of the body as an example, the finite element analysis platform ANSYS Workbench was used to study the position change of sensing module mounting points relative to the human skin when different elastic fabrics were combined into the clothing. The results showed that when fabrics with higher elasticity were selected for front and back pieces and fabrics with lower elasticity were selected for shoulder and side pieces, the slippage between the sensing module and the human skin was smaller.
Monitoring muscle fatigue is a hot research topic in rehabilitation medicine and sports science. However, the previous research on monitoring muscle fatigue is limited by the size and price of equipment and is not applicable to the field of sports. In this study, a wearable smart band powered by a resistive fabric strain sensor was implemented to measure thickness changes and combined with a portable electromyography(EMG) sensor to monitor bicep fatigue. A dumbbell curl training scheme was designed, and based on muscle physiology, fatigue-related features of the muscle thickness were proposed. The Pearson correlation coefficient between the median frequency (MDF) of EMG and the MDF of resistance was 0. 781 5, the Pearson correlation coefficient between the zero crossing rate (ZCR) of EMG and the enclosed area of the resistance was 0. 874 7, and the significant level P-values were 0. 022 0 and 0. 004 5, respectively. The results indicated that the muscle thickness characteristic indices were significantly correlated with common EMG fatigue indices. This study proves the feasibility of muscle fatigue monitoring based on muscle thickness characteristic indices and flexible fabric strain sensors as a supplementary method in the study of muscle fatigue. The methodology of this study has broad development prospects in the field of muscle fatigue research.
In the task of sales forecasting of new clothing products, the lack of historical sales data often necessitates the full utilization of data from other modalities as a supplement. However, multi-modal clothing data are usually redundant and heterogeneous. To solve the problems, a hierarchical multi-modal attention based recurrent neural network ( HMA-RNN ) including three main elements is proposed. The hierarchical structure separates high-level semantic information from low-level semantic information to avoid information redundancy. The multi-modal attention (MMA) is introduced in the fusion stage to mitigate inherent data non-alignment. The shared attention mechanism is utilized to build the dependencies across the multi-modal data. Experimental results on the Visuelle 2. 0 dataset show that the proposed approach achieves promising results with 72. 07 on the weighted average percentage error (WAPE) and 0. 80 on the mean absolute error (MAE), outperforming existing works significantly, which indicates the effectiveness of the proposed approach.
Computer vision-based virtual try-on (VITON) technology refers to warping and composing the try-on clothing according to the model image features into the model image to replace the original clothing parts. Current VITON methods have two main challenges: insufficient preservation of original features such as the head, bottom, and background of the model image; poor matching of the warped try-on clothing to the model image. To solve these two problems, an original feature preserving virtual try-on network ( OFP-VTON ) is proposed, which consists of semantic segmentation map generation, try-on clothing warping, and try-on image synthesis. In the try-on clothing warping phase, the network learns the mapping of warping of the clothing worn in the model image to better constrain the try-on warping. In the try-on image synthesis phase, the original features of the model image are extracted and preserved, and a receptive field block (RFB) is introduced to preserve the features of try-on clothing as much as possible. Qualitative and quantitative experiments on the publicly available VITON dataset show that the proposed OFP-VTON better preserves the original features and that the warped try-on clothing matches the model images better than the baseline method.
This paper proposed a new structural design method for multi-layer honeycomb-filled woven fabrics, and the impact resistance of rope-like core supporting fabrics was studied on multi-layer honeycomb woven fabrics. The effects of the rope-like core filling yarn fineness, the rope-like core surface structure and the multi-layer fabric surface structure on the impact resistance of the filled fabric were analyzed. Nine samples were woven with different factors in accordance with the orthogonal test scheme. The effects of the above factors on the peak transmitted force of the filled fabric were discussed. The study demonstrates that all three factors are significant, and the primary order of influence with the optimal level in the parentheses is rope-like core filling yarn fineness (22. 22 tex) > multi-layer fabric surface structure ( interweave 2/2 ) > rope-like core surface structure (interweave 3/1).
Microalgae are a type of photosynthetic cellular factory capable of efficient CO2 capture, biofuel production and wastewater treatment. However, the large-scale harvesting of microalgae still faces technological bottlenecks, and microbial flocculation has distinct advantages. In this study, a highly efficient flocculating bacterium named EbZL-1 is screened from the sediment samples of Jingyue Lake at Donghua University. It is identified as Enterobacter through 16S rDNA sequencing and a strain identification kit. The flocculation ability of EbZL-1 is tested through singlefactor and multifactorial analysis experiments by using Kaolin suspension as standard flocculating liquid. The results show that the flocculation rate of EbZL-1 can reach 96. 6% within 10 min, which is superior to that of the commercial polyaluminum chloride ( 95. 0%, 120 min ). The optimal culture conditions for the bacterium to achieve the above flocculation rate are a carbon source of 11. 69 g/ L glucose, a nitrogen source of 1. 04 g/ L ammonium nitrate, a medium pH value of 7. 8, a shaker rotation speed of 160 r/ min, an inoculation amount of 45 μL (1. 2 × 105 CFU/ mL), and a culture time of 12 h to reach the logarithmic growth phase. The optimal flocculation conditions are Ca2+ as a flocculant aid with the pH value of the Kaolin suspension being 7. 0. In the flocculation and sedimentation experiment of chlorella, the flocculation rate of EbZL-1 is higher than 95%, and the chlorella cells after flocculation are found to be undamaged upon inspection, demonstrating the advantages of the microbial flocculation technology. Further investigation into the mechanism of flocculation reveals that EbZL-1 can complete the rapid sedimentation of large particles by tight adsorption. In summary, the flocculating bacterium EbZL-1 has application value in the large-scale harvesting of microalgae and wastewater treatment.
An efficient, redox-neutral and visible-lightinduced three-component tandem trifluoromethylation / gemdifluoroallylation reaction of electron-rich alkenes is described. Trifluoromethyl (—CF3) radical is generated from commercially available sodium trifluoromethanesulfinate (CF3SO2 Na), which is matched with the electron-rich alkene and α-trifluoromethyl alkene in turn, and finally, the polyfluoroolefin is obtained by β-F elimination. The advantages of this method are mild reaction conditions, excellent functional-group tolerance, broad substrate scope, and high reaction efficiency, which provides an opportunity for the late-stage modification of pharmaceuticals and natural product derivatives.
The short pulse laser is a research focus due to its high precision, non-contact and high controllability advantages. In this paper, nanosecond laser pulse ablation experiments on the titanium alloy surface were conducted to explore the interaction between nanosecond laser and titanium alloy. The formation mechanism of a volcano-like pit under the combined influence of surface tension, the Marangoni effect and recoil pressure was clarified and verified. Thereafter, a multi-pulse laser parameter experiment was carried out. Ablation morphology, quality and feature sizes of the volcano-like pit and micro-groove were studied under different laser parameters. Thus, the correlation between laser parameters and feature sizes was built. This study contributes to micromachining technology with nanosecond laser, which suggests that micro-pit and micro-groove with specific sizes and high processing quality can be obtained.
In order to further improve the bearing stiffness, the porous aerostatic bearings can obtain bidirectional stiffness without additional preload guideway by combining vacuum preloaded (VPL) technology with the bearings. To explore the influence of working conditions and structural parameters on VPL porous aerostatic bearing performance, a numerical analysis of static and dynamic characteristics was performed based on the computational fluid dynamics (CFD) method. The influences of the air supply pressure, the vacuum degree, the permeability, the vacuum suction port diameter, the perturbation amplitude and the perturbation frequency were thoroughly investigated. The analysis shows that the stiffness of VPL porous aerostatic bearings increases by 22. 34% compared with that of ordinary porous bearings, and working conditions and structural parameters have a significant influence on static and dynamic characteristics. It is expected that the results can guide performance research and optimization design for the high-stiffness aerostatic bearings.
Mobile crowd sensing ( MCS ) systems, which offer a great opportunity to take full advantage of the wisdom of the crowd, naturally benefit from low deployment cost and wide spatial coverage. Due to failure or risk caused by a central server, constructing an efficient MCS system with untrustworthy participants in a decentralized manner is investigated. An efficient and practical decentralized MCS system based on a distributed auction process and the blockchain system is proposed. The proposed method achieves the optimal social profit satisfying individual rationality and protecting their privacy, through a neutral, public and trustful platform. Both theoretical analysis and numerical experiments show the effectiveness of the proposed approach.
For the three-phase squirrel cage asynchronous motor sensorless fast Fourier transformation (FFT) speed measurement method, the number of rotor slots needs to be known in advance, and the test accuracy is easily affected by factors such as noise and acquisition time. Therefore, a sensorless high-precision speed detection method based on singular value decomposition ( SVD ) and the Prony algorithm is proposed. Based on the study of the mechanism of rotor slot harmonic speed measurement, the calculation method of integer multiple rotor slot number is given. The SVD method based on the singular value growth rate curve is used to filter the stator current and the Prony algorithm is used to identify the rotor slot harmonics to calculate the motor speed. By using finite element and numerical simulation methods, the adaptability of the proposed algorithm and analog-to-digital ( A / D ) acquisition is analyzed and studied under different operating conditions of the motor. The physical test platform is constructed and the YE90S-2 motor is measured. Simulation and experiment results show that under the same acquisition condition, the absolute error of the proposed method is only a fraction or even one tenth of the FFT speed measurement, and the test accuracy is greatly improved, which proves the correctness and accuracy of the proposed method.