DynaMask: Dynamic Mask Selection for Instance Segmentation

The representative instance segmentation methods mostly segment different object instances with a mask of the fixed resolution, e.g., 28*28 grid. However, a low-resolution mask loses rich details, while a high-resolution mask incurs quadratic computation overhead. It is a challenging task to predict the optimal binary mask for each instance. In this paper, we propose to dynamically select suitable masks for different object proposals. First, a dual-level Feature Pyramid Network (FPN) with adaptive feature aggregation is developed to gradually increase the mask grid resolution, ensuring high-quality segmentation of objects. Specifically, an efficient region-level top-down path (r-FPN) is introduced to incorporate complementary contextual and detailed information from different stages of image-level FPN (i-FPN). Then, to alleviate the increase of computation and memory costs caused by using large masks, we develop a Mask Switch Module (MSM) with negligible computational cost to select the most suitable mask resolution for each instance, achieving high efficiency while maintaining high segmentation accuracy. Without bells and whistles, the proposed method, namely DynaMask, brings consistent and noticeable performance improvements over other state-of-the-arts at a moderate computation overhead. The source code: https://github.com/lslrh/DynaMask.Comment: Accepted by CVPR202

Challenges and Solutions for High-Speed Aviation Piston Pumps: A Review

As a core power component, aviation piston pumps are widely used in aircraft hydraulic systems. The piston pump’s power-to-weight ratio is extremely crucial in the aviation industry, and the “ceiling effect” of the PV value (product of compressive stress and linear velocity) limits the piston pump’s ability to increase working pressure. Therefore, increasing the piston pump’s speed has been a real breakthrough in terms of further enhancing the power-to-weight ratio. However, the piston pump’s design faces several challenges under the extreme operating conditions at high speeds. This study reviews several problems aviation axial piston pumps face under high-speed operating conditions, including friction loss, cavitation, cylinder overturning, flow pressure pulsation, and noise. It provides a detailed description of the research state of the art of these problems and potential solutions. The axial piston pump’s inherent sliding friction pair, according to the report, considerably restricts further increasing of its speed and power-to-weight ratio. With its mature technology and deep research base, the axial piston pump will continue to dominate the aviation pumps. Furthermore, breaking the limitation of the sliding friction pair on speed and power density, thus innovating a novel structure of the piston pump, is also crucial. Therefore, this study also elaborates on the working principle and development process of the two-dimensional (2D) piston pump, which is a representative of current high-speed pump structure innovation

Masked Surfel Prediction for Self-Supervised Point Cloud Learning

Masked auto-encoding is a popular and effective self-supervised learning approach to point cloud learning. However, most of the existing methods reconstruct only the masked points and overlook the local geometry information, which is also important to understand the point cloud data. In this work, we make the first attempt, to the best of our knowledge, to consider the local geometry information explicitly into the masked auto-encoding, and propose a novel Masked Surfel Prediction (MaskSurf) method. Specifically, given the input point cloud masked at a high ratio, we learn a transformer-based encoder-decoder network to estimate the underlying masked surfels by simultaneously predicting the surfel positions (i.e., points) and per-surfel orientations (i.e., normals). The predictions of points and normals are supervised by the Chamfer Distance and a newly introduced Position-Indexed Normal Distance in a set-to-set manner. Our MaskSurf is validated on six downstream tasks under three fine-tuning strategies. In particular, MaskSurf outperforms its closest competitor, Point-MAE, by 1.2\% on the real-world dataset of ScanObjectNN under the OBJ-BG setting, justifying the advantages of masked surfel prediction over masked point cloud reconstruction. Codes will be available at https://github.com/YBZh/MaskSurf.Comment: Codes will be available at https://github.com/YBZh/MaskSur

Precise in-situ infrared spectra and kinetic analysis of gasification under the H2O or CO2 atmospheres

Studying the mechanisms of bagasse conversion into syngas is essential to sustain the growing use of biomass in energy economy production. In this work, the precise kinetics of bagasse gasification with various gasification agents was firstly investigated employing insitu infrared spectra with Coats-Redfern integration, combining qualitative infrared spectroscopy allowed for kinetic analysis, so as to explore how the intermediate species vary in each basic reaction. The results demonstrate that the CO2 agent reduces the activation energy of nitryl after amino oxidation, making the lignin involved in gasification more easily as well as causing higher gasification efficiency. On the one hand, steam serving as a gasification agent enhances the concentration of hydroxyl groups and produces H2-rich syngas. On the other hand, the strong oxidizing hydroxyl group reduces the energy barrier of carbonyl and carboxyl groups in cellulose, which facilitates the gasification process. Furthermore, this study compared the effects of gasification agent (H2O or CO2) on syngas composition, reactor temperature distribution, carbon conversion rate, gasification efficiency, as well as low calorific value, providing essential information for understanding the micro-reaction pathways and pathway regulation during bagasse gasification. (c) 2023 Hydrogen Energy Publications LLC. Published by Elsevier Ltd. All rights reserved

An effective nonlinear dynamic formulation to analyze grasping capability of soft pneumatic robotic gripper

Soft pneumatic robotic grippers have found extensive applications across various engineering domains, which prompts active research due to their splendid compliance, high flexibility, and safe human-robot interaction over conventional stiff counterparts. Previously simplified rod-based models principally focused on clarifying overall large deformation and bending postures of soft grippers from static or quasi-static perspectives, whereas it is challenging to elaborate grasping characteristics of soft grippers without considering contact interaction and nonlinear large deformation behaviors. To address this, based on absolute nodal coordinate formulation (ANCF), comprehensively allowing for structural complexity, geometric, material and boundary nonlinearities, and incorporating Coulomb’ friction law with a multiple-point contact method, we put forward an effective nonlinear dynamic modeling approach for exploring grasping capability of soft gripper. Moreover, we solved the established dynamic equations using Generalized-α scheme, and conducted thorough numerical simulation analysis on a three-jaw soft pneumatic gripper (SPG) in terms of grasping configurations, displacements and contact forces. The proposed dynamic approach can accurately both describe complicated deformed configurations along with stress distribution and provide a feasible solution to simulate grasping targets, whose effectiveness and precision were analyzed theoretically and verified experimentally, which may shed new light on devising and optimizing other multifunctional SPGs

Analytical modeling and experimental verification of churning torque for cam guide rails of 2D piston pump

For 2D piston pump the churning torque of its cam guide rails at high speed is one of the main sources of mechanical efficiency loss. To conveniently calculate the churning torque and also provide guidance for future optimization of churning torque reduction, an accurate analytical model of constant acceleration and constant deceleration cam guide rail assembly of the stacked-rollers 2D piston pump is established, where the whole churning torque is divided into the peripheral churning torque, the pushing flow churning torque, and the end face churning torque. Then the analytical model is verified by CFD simulation preliminarily. Analytical modeling shows that at 16,000 rpm, the churning torque reaches about 0.826 N m, where the peripheral churning torque, the pushing flow churning torque, and the end face churning torque account for about 55.4%, 37.3%, and 7.3% of the total torque respectively, indicating that the structural parameters related to the pushing flow torque should be optimized with first priority at high rotational speed. Finally, the churning torque at 1000–16,000 rpm was experimentally measured and the influence of oil temperature was considered. The experimental results are in good agreement with the results of analytical modeling and CFD simulation, thus verifying the correctness of the proposed analytical model

Defect-Rich Regulatory Activity Strategy: Disordered Structure for Enhanced Catalytic Interfacial Reaction of Chlorobenzene

In contrast to previous defect engineering methods, the preparation of amorphous materials can obtain abundant defect sites through a simple way, which is expected to effectively degrade Volatile Organic Compounds (VOCs) under milder conditions. However, in-depth and systematic studies in this area are still lacking. Novel types of amorphous CeMn x catalysts with abundant defects were prepared through simple hydrothermal synthesis and used for Cl-VOCs catalysis for the first time. Experimental characterizations and DFT calculations proved that Ce doping induced MnO2 lattice distortion, which led to the transformation of CeMn x into an amorphous structure and the formation of abundant defect sites. It was observed that CeMn0.16 was able to eliminate chlorobenzene (CB) at 200 degrees C, and the CO(2 )yields and the selectivity of inorganic chlorine was significantly higher than that of MnO2. The O-18 isotope kinetic experiments revealed that the interfacial reaction process followed the MVK mechanism. The large number of oxygen vacancies accelerated the migration of lattice oxygen from the interior to the exterior, enhancing the ability to trap gas-phase oxygen. Mn4+ acted as the main active center to participate in CB catalysis, and the resulting reactive oxygen species (ROS) and Mn3+-[O2-]-Ce4+ further accelerated the entire oxidation cycle

Synthesis of Cu2O micro/nanocrystals for catalytic combustion of high-concentration CO: The crucial role of glucose

Cubic Cu2O micro/nanocrystals were successfully synthesized by liquid-phase reduction using copper salt of CuSO4 or CuCl2.2H2O, and glucose or ascorbic acid as reducing agent, respectively. The activity of the catalysts was evaluated by light-off curves of CO self-sustained catalytic combustion via temperature-programmed oxidation of CO (CO-TPO), with the results showing the activity of catalysts following the order of Cu2O-ClGLU > Cu2O-S-GLU > Cu2O-S-AA > Cu2O-Cl-AA, (Cl denotes CuCl2.2H2O, GLU denotes glucose, S denotes CuSO4 and AA denotes ascorbic acid, respectively), corresponding to the ignition temperature of 109 degrees C, 122 degrees C, 137 degrees C and 186 degrees C, respectively. The crystal structure, elemental valence, morphology and redox property of the prepared catalysts were analyzed by using various characterization techniques. Combined with in situ infrared spectrum, the CO self-sustained catalytic combustion over Cu2O catalysts mainly follows the Mars-van-Krevelen (M-v-K) mechanism: the adsorbed and activated CO reacts with lattice oxygen to yield CO2 and oxygen vacancy, and then the oxygen vacancy can be replenished by gaseous oxygen. Combined with catalytic performance of high-concentration CO, it is found that the catalysts prepared using glucose as reducing agent are more angular compared with ascorbic acid. The Cu2O-Cl-GLU synthesized with glucose and CuCl2.2H2O exhibits the best catalytic activity among all the catalysts tested, attributing to its more obvious edge and rough crystal surface. The unique structure of Cu2O-Cl-GLU leads to the high exposure rate and coordination unsaturation of atoms on the cubic Cu2O micro/nanocrystals that can improve the ability of activating gaseous O2 and low temperature reducibility, and consequently facilitating the catalytic activity

Synthesis of Cu2O micro/nanocrystals for catalytic combustion of high-concentration CO: The crucial role of glucose

Cubic Cu2O micro/nanocrystals were successfully synthesized by liquid-phase reduction using copper salt of CuSO4 or CuCl2.2H2O, and glucose or ascorbic acid as reducing agent, respectively. The activity of the catalysts was evaluated by light-off curves of CO self-sustained catalytic combustion via temperature-programmed oxidation of CO (CO-TPO), with the results showing the activity of catalysts following the order of Cu2O-ClGLU > Cu2O-S-GLU > Cu2O-S-AA > Cu2O-Cl-AA, (Cl denotes CuCl2.2H2O, GLU denotes glucose, S denotes CuSO4 and AA denotes ascorbic acid, respectively), corresponding to the ignition temperature of 109 degrees C, 122 degrees C, 137 degrees C and 186 degrees C, respectively. The crystal structure, elemental valence, morphology and redox property of the prepared catalysts were analyzed by using various characterization techniques. Combined with in situ infrared spectrum, the CO self-sustained catalytic combustion over Cu2O catalysts mainly follows the Mars-van-Krevelen (M-v-K) mechanism: the adsorbed and activated CO reacts with lattice oxygen to yield CO2 and oxygen vacancy, and then the oxygen vacancy can be replenished by gaseous oxygen. Combined with catalytic performance of high-concentration CO, it is found that the catalysts prepared using glucose as reducing agent are more angular compared with ascorbic acid. The Cu2O-Cl-GLU synthesized with glucose and CuCl2.2H2O exhibits the best catalytic activity among all the catalysts tested, attributing to its more obvious edge and rough crystal surface. The unique structure of Cu2O-Cl-GLU leads to the high exposure rate and coordination unsaturation of atoms on the cubic Cu2O micro/nanocrystals that can improve the ability of activating gaseous O2 and low temperature reducibility, and consequently facilitating the catalytic activity