Liquid metal (LM) is widely used in flexible electronic devices due to its excellent metallic conductivity and ductility. However, the fabrication of LM flexible strain sensors with high sensitivity and linearity is still a huge challenge, since the resistance of LM does not change much with strain. Here, a highly sensitive and linear fully flexible strain sensor with a resistive sensing function is proposed. The sensor comprises an Fe-doped liquid metal (Fe-LM) electrode for enhanced performance. The design and manufacturing of flexible strain sensors are based on the technology of controlling surface wettability by femtosecond laser micro/nano-processing. A supermetalphobic microstructure is constructed on a polydimethylsiloxane (PDMS) substrate to achieve the selection adhesion of Fe-LM on the PDMS substrate. The Fe-LM-based flexible strain sensor has high sensitivity and linearity, a gauge factor (GF) up to 1.18 in the strain range of 0–100%, excellent linearity with an R2 of 0.9978, a fast response time of 358 ms, and an excellent durability of more than 2400 load cycles. Additionally, the successful monitoring of human body signals demonstrates the potential of our developed flexible strain sensor in wearable monitoring applications.
Abstract The objective of this study was to evaluate the influence of inlet and outlet location and matrix particle size on the hydraulic efficiency of horizontal subsurface constructed wetlands. A quasi-two-dimensional model was set up to evaluate its hydraulic efficiency by salt tracer test, and the change of flow state in the system was observed by dye tracer test. Three inlet and outlet settings: top inlet-bottom outlet, middle inlet-middle outlet and bottom inlet-top outlet; three particle size distributions are 3 mm, 5 mm and 3/5 mm (one half part 3 mm, the other 5 mm). According to the tracer test, the position of inlet and outlet and the size distribution of matrix have an effect on the hydraulic characteristics of constructed wetlands. Larger substrate size with bottom inlet–top outlet configuration could improve hydraulic behaviour, improve water treatment efficiency.
To analyze the long-term effects of the quadratus femoris muscle pedicle bone graft with screw fixation for the treatment of femoral neck fractures in young adults.From 2002 to 2008, 38 patients with femoral neck fractures were operated. There were 22 males and 16 females, with an average age of 40 years (ranged 25 to 60 years). Twenty-six patients injured from high velocity road traffic accident, among which 14 patients injured in automobile accident, 8 in two wheeler accident and 4 in fall from height. Twelve patients had serious associated injuries. Femoral neck fractures were classified by Garden classification: 25 patients were Graden II and 13 patients were Graden III. Thirty-six patients underwent emergency operation and 2 had delayed operation. Clinical scores were evaluated based on Sanders scores and the radiological criteria which was judged by the diminution of density in the necrotic portion of the femoral head.All the patients were followed up for at least 2 years (ranged 2 to 5 years). There were significant differences between preoperation and postoperation in pain, function, muscle power and walk ability. All the patients with fractures were healed in an average of 5 months after operation and walked without aids and no complications occurred.This technique provides a high union rate with a low complication rate. In addition, the surgical procedure is relatively simple and has a nice long-term result.
Simulating the adsorption behavior of Sb(V) on goethite is of great significance for predicting the mobility of Sb(V) in soil. However, there is still a lack of charge distribution and multisite surface complexation (CD-MUSIC) models that conform to the actual adsorption mechanism. Therefore, our research combined the previous EXAFS results with the SCMs and established two CD-MUSIC models (Model I, which introduced bidentate binuclear and bidentate mononuclear complexes, and Model II, which introduced bidentate mononuclear and monodentate mononuclear complexes). It is also one of the rare cases that bidentate edge- and corner-sharing adsorption complexes have been distinguished by introducing different amounts of H + . The results showed that Model I was more suitable for predicting the adsorption behavior of Sb(V) on the goethite surface than Model II. However, at low pH and high Sb(V) loading, the presence of the monodentate complex ≡FeOSb(OH) 4 0.5- was possible due to the fast and slow two-step mechanism. Using the optimized CD-MUSIC model parameters, the contribution of surface species to the equilibrium adsorption under different conditions was determined. In the adsorption edge and adsorption isotherm simulation process, the edge-sharing bidentate mononuclear complex ≡FeO 2 H 2 Sb(OH) 4 0 was always the most important product, which was consistent with the results of EXAFS analysis. The applicability of the model parameters was verified by predicting the competitive adsorption between PO 4 3- and Sb(V). The CD-MUSIC model established in the present study could be a useful tool for evaluating the equilibrium distribution behavior and environmental risk of Sb(V) in different types of soils.
Key technology in design of embedded jacquard knitting control system was introduced in this paper, including technology requirements, real-time requirements, mechanical delays and embedded control system structure. The control system is of compact structure, reasonable design, high performance-price ratio, and can fully meet the jacquard knitting control requirements of the current computerized circular knitting machines. The research of this project provides some theory and practical effect for the product development of electronic jacquard control system.
In this paper, we propose a novel multi-user access in wireless optical communication based on the quantum detection of the coherent state. In this case, the coherent states are used as the signal carrier and a technique of quantum detection is applied to distinguish between signals from different users. To accomplish this task, two main quantum measurement methods are introduced; one is minimum error discrimination (MED), and the other is unambiguous state discrimination (USD). The theoretical derivation implies that the two methods can both distinguish between the signals from different users efficiently when the average photon number is large enough. Typically, the numerical result shows that in the two-user case, the channel capacity will approach the theoretical maximum limit when the average photon number is greater than 2.5 for MED and 5 for USD in the absence of noise. The MED gains more channel capacity than the USD at the same average photon number. However, the USD wins the error-correction scene with its free-error capability. Furthermore, the detection error probability and channel capacity for the USD with the thermal noise are examined. The result shows that increasing the signal average photon number can continue the USD's advantage of error-free detection even if in the presence of thermal noise. In addition, compared with non-orthogonal multiple access (NOMA), the bit error rate (BER) against signal-to-noise rate (SNR) performance of USD has been improved.
Our study focuses on mapless navigation in robotics, which involves navigating without an established obstacle map of the environment. Spiking Neural Networks (SNNs) have recently been applied to this task using Deep Reinforcement Learning (DRL), but face challenges in dynamic and partially observable environments, as well as inaccuracies in transmitted data. To overcome these issues, we propose a Multi-Critic DDPG with Spiking Memory (MC-DDPGSM) framework. Our approach introduces a spiking Gate Recurrent Unit layer (Spiking-GRU) to provide memory function and evaluates the state-action value with multi-critic networks. The experimental results demonstrate that our method achieves better performance (success rate, navigation distance, navigation time spent, and power consumption) in complex navigation tasks compared to the state-of-the-art approaches. Furthermore, our model can be transferred to unseen environments without the need for fine-tuning.
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