Search

Designing and synthesizing Si/C composites with a certain structure is an effective strategy to improve the performance of silicon anode materials for practical applications. Herein, we prepared Si/CNT composite microspheres with decent size uniformity and perfect spherical structure using droplet-microfluidics. The size and structure can be easily regulated by tuning the mass fraction of the precursor in the microfluidic device. The Si/CNT composite microspheres exhibited a narrow particle size distribution (coefficient of variation

Step into the 21st century, high strength materials have been increasingly used in engineering practice. However, current design codes for concrete-filled steel tube (CFST) columns have limitations when applied to high strength materials. At the meantime, few studies have investigated in such topic which leads to an inadequate validity of existing design formulae. In this paper, in order to develop a finite element model suitable for CFST columns using high strength materials, the stress-strain relations applicable for high strength materials was proposed by recalibrating the parameters of the models for normal strength materials. Then, a finite element model (FE) was established by incorporating the proposed stress-strain relations into the constitutive models. The validity and accuracy of established FE model were verified by comparing the collected experimental database. Full-range analyses of the behavior of HSCFST columns under axial loading were then carried out using the verified FE model to investigate the composite interactions of different material matching at the limit state. Numerical results presented show that normal strength steel filled with normal strength concrete have the strongest confinement effect, while the normal strength steel filled with high strength concrete exhibited almost no confinement effect. Moreover, to extend the applications of high strength materials, a new design formula was proposed based on the superposition theory with incorporating the effects of high strength materials. It was found that the proposed design formula yields satisfactory predictions when compared with current major code formulae.

Abstract Background The predictors of left ventricular thrombus (LVT) formation are not well defined in the contemporary era, especially in those patients at high risk. We aimed to evaluate whether the platelet/lymphocyte ratio (PLR) is valuable in the determination of LVT formation in patients with anterior ST-elevation myocardial infarction (STEMI) and left ventricular (LV) dysfunction. Methods The LVT group (n = 46) was identified from anterior STEMI patients with LV dysfunction who were treated with primary percutaneous coronary intervention (PCI) from January 2017 to December 2019 at the China-Japan Union Hospital of Jilin University. The no-LVT group (n = 92) were also selected from the same batch of patients and were age- and sex-matched to the patients with LVT. The PLR was determined at admission and was calculated as the ratio of the platelet count to the lymphocyte count using the complete blood count. The presence of LVT was determined by echocardiography. Results The PLR were significantly higher in patients with LVT than in no-LVT group (p = 0.001). In a receiver operator characteristic curve (ROC) analysis, using a cut-off value of 118.07 (AUC 0.673, 95% CI: 0.574–0.771, P = 0.001), the PLR could independently predict the occurrence of LVT. Multivariate analysis showed that an increased PLR (OR = 1.011, 95% CI: 1.004–1.018, P = 0.002), the presence of a left ventricular aneurysm (OR = 46.350, 95% CI: 5.659–379.615, P

Wuyi Mountain in Southeast China is the origin of black tea and oolong tea. It is also considered the ‘treasure trove of tea cultivars’ because of its rich tea germplasm resources. In the present study, the population structure and genetic diversity of 137 tea germplasms from Wuyi Mountain and its adjacent areas were analyzed by SNPs. The information index (I), observed heterozygosity (Ho), expected heterozygosity (He) and fixation index (F) polymorphisms of the selected SNPs were high, stable and reliable. Ho had an average of 0.389, while He had an average of 0.324, indicating that Wuyi Mountain tea germplasms had rich genetic diversity. The AMOVA results showed that genetic variation came mainly from intrapopulation variation, accounting for 66% of the total variation. The differences in the Fst and Nei values of tea germplasm between Wuyi Mountain and its adjacent areas are similar to the geographical differences. Multiple analyses based on high-quality SNPs found that the landraces of tea plants on Wuyi Mountain had different genetic backgrounds from the wild-type landraces and the landraces of Wuyi Mountain tea plants underwent population differentiation. This study provides a basis for the effective protection and utilization of tea germplasms on Wuyi Mountain and lays a foundation for identifying potential parents to optimize tea cultivation.

With the development of new concrete technology, high-strength concrete has been used worldwide. In particular, more economic benefits can be achieved by applying high-strength concrete-filled steel tube (HSCFST) columns in the concrete core walls of super high-rise buildings. A constitutive relation with high applicability for high-strength materials with different strength grades is proposed. Based on this constitutive model, a brick element model of 181 sets of axially compressed square HSCFST members is established and experimentally verified. The effects of the concrete strength, diameter-to-thickness ratio, and steel yield strength on the axial compressive capacities of these members were investigated based on finite element calculation results. The results showed that with an increase in the concrete strength, the ultimate bearing capacities of CS-CC, HS-HC, HS-CC, and CS-HC stub column members increased by 60%, 24%, 44%, and 21% at most, respectively. Additionally, as the steel yield strength increased, the ultimate bearing capacities of CS-CC, HS-HC, HS-CC, and CS-HC stub column members increased by 8.8%, 5.1%, 8.5%, and 5.2%, respectively, Hence, material strength has the greatest impact on CS-CC and HS-CC. The confinement effect of the square steel tube on the concrete weakens as the strength grade of steel or concrete increases. Notably, the confinement effect of steel tube on the concrete is strongest in CS-CC and weakest in the CS-HC. In addition, the confinement coefficients of square HSCFST stub columns with different combinations of concrete and steel strengths were analyzed. Based on the superposition principle in the ultimate state, a practical axial compressive capacity calculation formula for three types of square HSCFSTs is established. Compared with existing major design code formulas, the proposed formula is more accurate and concise and has a clear physical meaning.

A terahertz modulation structure based on hybrid metamaterial and graphene is proposed and demonstrated in this work. The metamaterial with a square slit ring array excites terahertz resonance in the slits and enhances the interaction between the terahertz wave and graphene. The graphene layer acting as the active material is tuned by the applied electrical field. With the separation by a dielectric layer between the graphene and the metallic structure, the resonant frequency and transmitted energy are both modulated by the graphene. Experimental result indicates that the modulation depth of the terahertz transmitted amplitude is 65.1% when the applied modulation voltage is tuned 5 V.

It is the refrigerator that is frequently used in homes. Freezing and refrigerating temperature sensors are significant temperature-sensing components in the refrigerator. However, it is simple to insert the temperature sensor wires erroneously during the manufacturing process. Currently, there is no effective method to detect the correctness of the wiring harnesses. We propose a novel detection method that combines machine vision and resistance analysis for the wiring harnesses of refrigerator temperature sensors. We utilized machine vision technology to determine the color and insertion position of each wire in the wiring harnesses. We distinguish the types of sensors by analyzing the resistance range of the temperature sensors. We combine two approaches to detect the wiring harnesses connecting the temperature sensors. The experimental results demonstrate that the proposed method can effectively detect the correctness of the wiring harnesses connecting the temperature sensors, and the accuracy reaches 99.19%. The proposed method has a good generalization in other electrical wiring harness detection problems. [ABSTRACT FROM AUTHOR]

Action recognition in real-world videos is difficult because of factors such as scenery muddle, scale alter, dynamic standpoint, and sharp motion. This paper proposes a novel two-stream architecture fusing static and dynamic features to recognize human actions in videos. Firstly, the original image (single frame and optical flow fields) is extracted by Convolutional Neural Network (CNN) to obtain feature maps. Secondly, we extract the obtained feature maps via a 3x3 convolution over all the neighbor features, leading to a static representations of features. Then we concatenate these static features with input feature maps to produce the dynamic attention matrix through two 1x1 convolutions. All of the generated feature maps are then aggregated using the learnt attention matrix, producing a dynamic representation. Thirdly, we take the interaction of the static and dynamic presentations as final outputs. Finally, we utilize Long Short-Term Memory (LSTM) to catch time sequence information among dense optical flow. The experimental results on the three hard datasets UCF101, HMDB51, and Kinetics400 have shown that the method works better than other state-of-the-art methods. [ABSTRACT FROM AUTHOR]

With the development of the fifth generation (5G) wireless networks, the dense, heterogeneous and irregular network architecture puts forward higher requirements for inter-cell interference coordination (ICIC) technology. How to combine the existing technology to suppress inter-cell interference has become a focus worthy of research. This paper proposes a novel ICIC scheme that combines three-dimensional (3D) multi-level soft frequency reuse (ML-SFR) and coordinated multi-point (CoMP) transmission technology. Based on the scheme, a model of ML-SFR and CoMP is built for different scenarios. Finally, the information rates of users at the cell edge and the entire cell are analyzed through simulation, respectively. The results show that the proposed scheme is superior to the traditional anti-interference technology in suppressing inter-cell interference. The proposed scheme can effectively improve the transmission performance of the 5G wireless networks. [ABSTRACT FROM AUTHOR]

the infrared human recognition is challengeable due to the factors including poor imaging quality, disturbance objects in surroundings, large variations of human poses and casual movements. In this paper, a novel human recognition method is proposed. Its critical components include a feature descriptor that is referred to as a histogram of oriented monogenic energy (HOME), and a deep learning network that is referred to as a deep brief network (DBN). The feature descriptor, which is formulated from the multi-scale monogenic signal representation (MMSR), provides discriminative representation of lines/edges of the human subjects of interest. The DBN learns multiple layers of abstraction of the feature and conducts accurate human and/or non-human classification. Experimental results validate the advantages of the proposed method in recognition accuracy and robustness to scenic changes as well, due to such factors including the discriminative representation of human cues, high-level understanding of the cues, and tightly architectural coupling between the feature and the classifier. [ABSTRACT FROM AUTHOR]

The deformation of thin-wall stacked structures with low stiffness has been a common problem in the aircraft assembly process, making it difficult to achieve tight tolerance of the countersink depth in one-shot stack drilling. This difficulty is attributed to the complex tool position relative to the workpiece during the machining process. In this paper, an approach to countersink depth control composed of real measurement of the workpiece deformation and compensation of the tool position is presented. The deformation of the workpiece is divided into the following two categories: the rotation angle perpendicular to the feed direction and the deformation along the feed direction. These types of deformation are analysed regarding their influence on the countersink depth error. Effective measures are taken to ensure the countersink depth accuracy; such measures include the adjustment of the normal vector of the drilling position after the clamping process, the error monitoring of the normal vector during machining, and the multi-level compensation during machining. Theoretical analysis and validation of the proposed solution via comparative experiments showed a clear understanding of the coupled interaction of the thrust force with the workpiece deformation and corresponding reduction in the countersink depth error. The compensation solution requires simple computation and is straightforward to implement in industrial automatic drilling applications. [ABSTRACT FROM AUTHOR]

A novel activity feature for thermal infrared human activity recognition, which suffers from poor quality infrared imaging and a great variation in human subjects, is proposed in this paper. Extraction of this feature consists of three major stages. First, a coarse-to-fine localization procedure extracts the regions of interest (ROIs) that may contain human subjects from a raw infrared sequence. Second, it generates a motion deviation image (MDI), which is a novel spatio-temporal template, from the available ROIs to represent the infrared activity sequence efficiently. Third, from such MDI, it generates a directional phase congruency-based feature that codes the significant activity information via the steps including calculating phase maps, estimating intrinsic dimensions and reducing vector dimensionality. The proposed feature is validated on the IADB infrared human activity database, and the experimental results show its advantages in recognition accuracy when used for multi-class activity recognition due to its robustness to poor quality thermal infrared imagery, good representation of activity information and effective removal of noise. [ABSTRACT FROM AUTHOR]