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.     

Structure-dependent activity and stability of Al2O3 supported Rh catalysts for the steam reforming of n-dodecane

Steam reforming of liquid hydrocarbon fuels is an appealing way for the production of hydrogen. In this work, the Rh/Al₂O₃ catalysts with nanorod (NR), nanofiber (NF) and sponge-shaped (SP) alumina supports were successfully designed for the steam reforming of n-dodecane as a surrogate compound for diesel/jet fuels. The catalysts before and after reaction were well characterized by using ICP, XRD, N₂ adsorption, TEM, HAADF-STEM, H₂-TPR, CO chemisorption, NH₃-TPD, CO₂-TPD, XPS, Al²⁷ NMR and TG. The results confirmed that the dispersion and surface structure of Rh species is quite dependent on the enclosed various morphologies. Rh/Al₂O₃-NR possesses highly dispersed, uniform and accessible Rh particles with the highest percentage of surface electron deficient Rh⁰ active species, which due to the unique properties of Al₂O₃ nanorod including high crystallinity, relatively large alumina particle size, thermal stability, and large pore volume and size. As a consequent, Rh/Al₂O₃-NR catalyst exhibited superior catalytic activity towards steam reforming reactions and hydrogen production rate over other two catalysts. Especially, Rh/Al₂O₃-NR catalyst showed the highest hydrogen production rate of 87,600 mmol g_fuel^?1 g_Rh^?1min^?1 among any Rh-based catalysts and other noble metal-based catalysts to date. After long-term reaction, a significant deactivation occurred on Rh/Al₂O₃–NF and Rh/Al₂O₃-SP catalysts, due to aggregation and sintering of Rh metal particles, coke deposition and poor hydrothermal stability of nanofibrous structure. In contrast, the Rh/Al₂O₃-NR catalyst shows excellent reforming stability with negligible coke formation. No significantly sintering and aggregation of the Rh particles is observed after long-term reaction. Such great catalyst stability can be explained by the role of hydrothermal stable nanorod alumina support, which not only provides a unique environment for the stabilization of uniform and small-size Rh particles but also affords strong surface basic sites.     

Digital twin-based analysis of volumetric error mapping procedures

The evaluation of the volumetric accuracy of a machine tool is an open challenge in the industry, and a wide variety of technical solutions are available in the market and at research level. All solutions have advantages and disadvantages concerning which errors can be measured, the achievable uncertainty, the ease of implementation, possibility of machine integration and automation, the equipment cost and the machine occupation time, and it is not always straightforward which option to choose for each application. The need to ensure accuracy during the whole lifetime of the machine and the availability of monitoring systems developed following the Industry 4.0 trend are pushing the development of measurement systems that can be integrated in the machine to perform semi-automatic verification procedures that can be performed frequently by the machine user to monitor the condition of the machine. Calibrated artefact based calibration and verification solutions have an advantage in this field over laser based solutions in terms of cost and feasibility of machine integration, but they need to be optimized for each machine and customer requirements to achieve the required calibration uncertainty and minimize machine occupation time.This paper introduces a digital twin-based methodology to simulate all relevant effects in an artefact-based machine tool calibration procedure, from the machine itself with its expected error ranges, to the artefact geometry and uncertainty, artefact positions in the workspace, probe uncertainty, compensation model, etc. By parameterizing all relevant variables in the design of the calibration procedure, this simulation methodology can be used to analyse the effect of each design variable on the error mapping uncertainty, which is of great help in adapting the procedure to each specific machine and user requirements. The simulation methodology and the analysis possibilities are illustrated by applying it on a 3-axis milling machine tool.     

Balancing control of a unicycle robot with double gyroscopes using adaptive fuzzy controller

This paper presents a unicycle robot which utilizes the precession effect of a double-gyroscope for lateral balancing and designs an adaptive fuzzy controller to realize the balance control according to its dynamic model. The double gyroscope structure of the unicycle robot can eliminate the pitch angle interference caused by the precession effect and improve the robot's lateral anti-interference ability. An adaptive fuzzy controller is designed based on the dynamic equations of the unicycle robot to improve its robustness. The adaptive controller part improves the anti-interference ability of the unicycle robot, and the fuzzy controller part is used as decoupling controller to reduce the interference of coupling. Simulation and experimental results to verify the anti-interference ability and decoupling effect of the designed controller.     

Regulation of the NADH supply by nuoE deletion and pncB overexpression to enhance hydrogen production in Enterobacter aerogenes

In this study, seven mutants from E. aerogenes IAM1183 wildtype were constructed via different strategies including deletion of lactate dehydrogenase, disruption of NADH dehydrogenase gene nuoE, overexpression of pncB and a combination of both to regulate of the NADH supply to enhance hydrogen production. Compared with the parental strain, the hydrogen yields of the strains IAM1183-E, IAM1183-L and IAM1183-EL increased by 23.3, 81.7 and 97.9%, respectively. When the pncB gene was overexpressed, the hydrogen yield of IAM1183/P, IAM1183-E/P, IAM1183-L/P and IAM1183-EL/P increased by 39.0, 6.5, 5.9, and 5.1% compared with the respective original knockout strains. Among them, the total hydrogen yield of strain IAM1183-EL/P with highest production efficiency was 58% higher than IAM1183. Further metabolite analysis indicated that the knockout of nuoE and ldhA, combined with the overexpression of pncB, resulted in a redistribution of the metabolic fluxes in E. aerogenes, which led to an improvement of the hydrogen yield.     

三维石墨烯-碳纳米管/水泥净浆的压敏性能

为了探索三维石墨烯-碳纳米管(G-CNTs)/水泥净浆的压敏性能,采用四电极法研究了荷载作用下GCNTs/水泥净浆的电阻率变化,并分析不同G-CNTs掺量、加载幅度、加载速度以及恒定荷载对电阻率变化的影响。研究表明:随着G-CNTs掺量的增加,电阻率呈先减小后稳定的变化趋势,在G-CNTs掺量由0.2wt%增加至1.6wt%时,电阻率下降51.8%;电阻率与温度呈负相关;G-CNTs掺量高于0.8wt%时可以显著提高水泥净浆的压敏性能,且电阻率变化率与应力应变有明显的对应关系,1.2wt%G-CNTs掺量下试件的应力灵敏系数和应变灵敏系数分别为2.3%/MPa和291;G-CNTs/水泥净浆电阻率变化率幅值随着加载幅度增大而相应增加,其电阻率变化率曲线在不同加载速度以及恒定荷载作用下均与应力-应变曲线一一对应,具有良好的压敏特性。     

Effect of wind condition on unintended hydrogen release in a hydrogen refueling station

Ambient condition, especially the wind condition, is an important factor to determine the behavior of hydrogen diffusion during hydrogen release. However, only few studies aim at the quantitative study of the hydrogen diffusion in a wind-exist condition. And very little researches aiming at the variable wind condition have been done. In this paper, the hydrogen diffusion in different wind condition which including the constant wind velocity and the variable wind velocity is investigated numerically. When considering the variable wind velocity, the UDF (user defined function) is compiled. Characteristics of the FGC (flammable gas cloud) and the HMF (hydrogen mass fraction) are analyzed in different wind condition and comparisons are made with the no-wind condition. Results indicate that the constant wind velocity and the variable wind velocity have totally different effect for the determination of hydrogen diffusion. Comparisons between the constant wind velocity and the variable wind velocity indicate that the variable wind velocity may cause a more dangerous situation since there has a larger FGC volume. More importantly, the wind condition has a non-negligible effect when considering the HMF along the radial direction. As the wind velocity increases, the distribution of the HMF along the radial direction is not Gaussian anymore when the distance between the release hole and the observation line exceeds to a critical value. This work can be a supplement of the research on the hydrogen release and diffusion and a valuable reference for the researchers.     

Effect of cooking temperature on texture and flavour binding of braised sauce porcine skin

To investigate the effect of cooking temperature (55, 65, 75, 85 and 95 °C) on texture and flavour binding of braised sauce porcine skin (BSPS), sensory acceptance, microstructure and flavour-binding capacity were investigated during the processing of BSPS. Samples cooked at 85 and 95 °C showed better texture and aroma scores. Hardness and chewiness of BSPS were obviously improved at 85 and 95 °C than control group. Collagen structure was significantly destroyed over 85 °C. The porcine skin collagen heated at 85 and 95 °C showed relatively higher flavour-binding capacity than other samples. The improvement of texture of BSPS was mainly attributed to the degradation of collagen. Higher aroma scores of BSPS were related to intense binding abilities with aroma compounds at 85 and 95 °C. Cooking at 85 or 95 °C could be an optimal cooking temperature for BSPS.