YOLSO: You Only Look Small Object

Small object detection is challenging and far from satisfactory. Most general object detectors suffer from two critical issues with small objects: (1) Feature extractor based on classification network cannot express the characteristics of small objects reasonably due to insufficient appearance information of targets and a large amount of background interference around them. (2) The detector requires a much higher location accuracy for small objects than for general objects. This paper proposes an effective and efficient small object detector YOLSO to address the above problems. For feature representation, we analyze the drawbacks in previous backbones and present a Half-Space Shortcut(HSSC) module to build a background-aware backbone. Furthermore, a coarse-to-fine Feature Pyramid Enhancement(FPE) module is introduced for layer-wise aggregation at a granular level to enhance the semantic discriminability. For loss function, we propose an exponential L1 loss to promote the convergence of regression, and a focal IOU loss to focus on prime samples with high classification confidence and high IOU. Both of them significantly improves the location accuracy of small objects. The proposed YOLSO sets state-of-the-art results on two typical small object datasets, MOCOD and VeDAI, at a speed of over 200 FPS. In the meantime, it also outperforms the baseline YOLOv3 by a wide margin on the common COCO dataset.     

The effects of washing a collagen sample prior to TEM examination

Transmission electron microscopy (TEM) is an important analysis technique to visualize (bio)macromolecules and their assemblies, including collagen fibers. Many protocols for TEM sample preparation of collagen involve one or more washing steps to remove excess salts from the dispersion that could hamper analysis when dried on a TEM grid. Such protocols are not standardized and washing times as well as washing solvents vary from procedure to procedure, with each research group typically having their own protocol. Here, we investigate the influence of washing with water, ethanol, but also methanol and 2-propanol, for both mineralized and unmineralized collagen samples via a protocol based on centrifugation. Washing with water maintains the hydrated collagen structure and the characteristic banding pattern can be clearly observed. Conversely, washing with ethanol results in dehydration of the fibrils, often leading to aggregation of the fibers and a less obvious banding pattern, already within 1 min of ethanol exposure. As we show, this process is fully reversible. Similar observations were made for methanol and propanol. Based on these results, a standardized washing protocol for collagenous samples is proposed.     

基于误差估值累加开环校正的诱导式欺骗检测方法

诱导式卫星欺骗干扰可诱导航空器逐渐偏离预定航迹，难以被发现，因此及时有效地检测干扰是飞行安全的保障。在现有紧组合导航体制基础上，设计了一种基于误差估值累加开环校正的紧组合导航结构，并证明了其性能与传统闭环校正紧组合导航性能等效。在此结构中，将紧组合导航系统与自适应序贯概率比检测方法结合，提出了一种基于误差估值累加开环校正的诱导式欺骗检测方法，融合紧组合导航信息与其他不受欺骗影响的导航信息，构建欺骗检测统计量进行诱导式欺骗检测。仿真结果表明，开环校正结构可避免随时间累加的惯性导航系统误差所导致的组合导航滤波器发散问题，同时欺骗检测方法可进一步提高算法对“最坏”情形下微小诱导式欺骗的检测效果。     

Electrodeposition of the manganese-doped nickel-phosphorus catalyst with enhanced hydrogen evolution reaction activity and durability

Hydrogen technology is widely considered a novel clean energy source, and electrolysis is an effective method for hydrogen evolution. Therefore, efficient hydrogen evolution reaction (HER) catalysts are urgently needed to replace precious metal catalysts and meet ecological and environmental protection standards. Herein, Ni–Mn–P electrocatalysts are synthesized using facile electrodeposition technology. The influence of the Mn addition on the catalytic behavior is studied by the comprehensive analysis of catalytic performance and morphology of the catalysts. Among them, the Ni–Mn–P0.01 catalyst exhibits small coral-like structures, greatly improving the adsorption and desorption of hydrogen ions and reducing the overpotential hydrogen evolution. Consequently, overpotential at 10 mA cm^?2 electric current density is 113 mV, and the value of the Tafel slope achieves 74 mV/dec. Furthermore, the Ni–Mn–P catalyst shows long-time (20 h) stability at current densities of 10 and 60 mA/cm². The results confirm that the synergistic effect of Ni, Mn, and P accelerates the electrochemical reaction. Meanwhile, the addition of manganese element can change the micromorphology of the catalyst, thereby exposing more active sites to participate in the reaction, enhancing water ionization, improving the catalytic performance. This study opens a new way toward improving the activity of the catalyst by adjusting Mn concentration during the electrodeposition process.     

Experimental investigation on the invert stability of operating railway tunnels with different drainage systems using 3D printing technology

In recent years, the invert anomalies of operating railway tunnels in water-rich areas occur frequently, which greatly affect the transportation capacity of the railway lines. Tunnel drainage system is a crucial factor to ensure the invert stability by regulating the external water pressure (EWP). By means of a three-dimensional (3D) printing model, this paper experimentally investigates the deformation behavior of the invert for the tunnels with the traditional drainage system (TDS) widely used in China and its optimized drainage system (ODS) with bottom drainage function. Six test groups with a total of 110 test conditions were designed to consider the design factors and environmental factors in engineering practice, including layout of the drainage system, blockage of the drainage system and groundwater level fluctuation. It was found that there are significant differences in the water discharge, EWP and invert stability for the tunnels with the two drainage systems. Even with a dense arrangement of the external blind tubes, TDS was still difficult to eliminate the excessive EWP below the invert, which is the main cause for the invert instability. Blockage of drainage system further increased the invert uplift and aggravated the track irregularity, especially when the blockage degree is more than 50%. However, ODS can prevent these invert anomalies by reasonably controlling the EWP at tunnel bottom. Even when the groundwater level reached 60 m and the blind tubes were fully blocked, the invert stability can still be maintained and the railway track experienced a settlement of only 1.8 mm. Meanwhile, the on-site monitoring under several rainstorms further showed that the average EWP of the invert was controlled within 84 kPa, while the maximum settlement of the track slab was only 0.92 mm, which also was in good agreement with the results of model test.     

Investigation of stress fields for non-standard sized glass plates loaded by ring-on-ring

A ring-on-ring (ROR) test is a prevailing test method for evaluating the equi-biaxial strength of glass materials. However, current ROR test standards limit the strength and size of glass to prevent a nonlinear behavior. In this study, the feasibility of ROR testing for non-standard, high-strength glass, such as tempered or ion-exchanged rectangular glass is investigated. To this end, ROR simulation based on theory and experiment is conducted for thirty non-standard glasses with widths of 100–300 mm and aspect ratios of 1.0–2.0. As a result, the maximum measurable stress was about 215.6 MPa for 100 × 200 mm glass and 481.3 MPa for 300 × 600 mm glass with a 3% deviation, which is well above the strength of regular tempered glass. The main purpose of this work is to understand the range of aspect ratio of horizontal and vertical widths of a glass plate that can be evaluated by the standard ROR test.     

Machine fault diagnosis with small sample based on variational information constrained generative adversarial network

In actual engineering scenarios, limited fault data leads to insufficient model training and over-fitting, which negatively affects the diagnostic performance of intelligent diagnostic models. To solve the problem, this paper proposes a variational information constrained generative adversarial network (VICGAN) for effective machine fault diagnosis. Firstly, by incorporating the encoder into the discriminator to map the deep features, an improved generative adversarial network with stronger data synthesis capability is established. Secondly, to promote the stable training of the model and guarantee better convergence, a variational information constraint technique is utilized, which constrains the input signals and deep features of the discriminator using the information bottleneck method. In addition, a representation matching module is added to impose restrictions on the generator, avoiding the mode collapse problem and boosting the sample diversity. Two rolling bearing datasets are utilized to verify the effectiveness and stability of the presented network, which demonstrates that the presented network has an admirable ability in processing fault diagnosis with few samples, and performs better than state-of-the-art approaches.     

Structural silicone sealants after exposure to laboratory test for durability assessment

During the service life of structural sealant glazing (SSG) facades, the load-bearing capacity of the silicone bonds needs to be guaranteed. Laboratory tests can assess the durability of SSG-systems based on mechanical characteristics of the bond after simultaneous exposure to both climatic and mechanical loads. This article studies how the material characteristics of two common structural sealants are affected by laboratory and field exposure. Dynamic mechanical analysis (DMA) confirms a reduction in the dynamic modulus of exposed silicone samples. Results from thermogravimetric analysis, Fourier-transform infrared spectroscopy, differential scanning calorimetry, and small-angle X-ray scattering/wide-angle X-ray scattering show differences between the two sealants and indicate no/minor changes in the composition and morphology of the laboratory and field exposed sealants. Mechanical characterization methods, such as DMA, and tensile and shear testing of the structural bond, are shown to be sensitive toward the combined climatic and mechanical loadings, and are hence suitable for studying degradation mechanisms of structural sealants.     

基准平面垂直断面法在爆破漏斗试验中的应用

系统阐述了基准平面垂直断面法在爆破漏斗试验中测量爆破漏斗体积的基本原理,并将隧道激光断面仪应用于金厂河矿1 750 m水平15^#采场底部切割巷道爆破漏斗试验爆破漏斗体积测量中。通过与传统体重法等计算法所得漏斗体积分析比较,结果表明基于隧道激光断面仪与3D Mine软件分析的基准平面垂直断面法实用性强、操作方便、结果直观可靠,达到试验预期目的。     

Preparation and electrochemical characterization of Ti-based amorphous metallic glass with high strength

Ti-based amorphous metallic glasses have excellent mechanical, physical, and chemical properties, which is an important development direction and research hotspot of metal composite reinforcement. As a stable, simple, efficient, and large-scale preparation technology of metallic powders, the gas atomization process provides an effective way of preparing amorphous metallic glasses. In this study, the controllable fabrication of a Ti-based amorphous powder, with high efficiency, has been realized by using gas atomization. The scanning electron microscope, energy-dispersive spectrometer, and X-ray diffraction are used to analyze surface morphology, element distribution, and phase structure, respectively. A microhardness tester is used to measure the mechanical property. An electrochemical workstation is used to characterize corrosion behavior. The results show that as-prepared microparticles are more uniform and exhibit good amorphous characteristics. The mechanical test shows that the hardness of amorphous powder is significantly increased as compared with that before preparation, which has the prospect of being an important part of engineering reinforced materials. Further electrochemical measurement shows that the corrosion resistance of the as-prepared sample is also significantly improved. This study has laid a solid foundation for expanding applications of Ti-based metallic glasses, especially in heavy-duty and corrosive domains.