Comparative study on weathering durability property of phenol formaldehyde resin modified sweetgum and southern pine specimens

The effects of low molecular weight phenol formaldehyde resin on weathering durability property of sweetgum (Liquidambar styraciflua) and southern pine (Pinus taeda) specimens were studied using six wet-dry cycles with ultraviolet light accelerated weathering test following ASTM D2898-10 via evaluating the water repellent efficiency, dimensional stability, and crack formation of wood. The results showed that 1) the water repellent efficiency of treated quarter-sawn sweetgum specimens was higher than those of treated quarter-sawn and flat-sawn southern pine specimens; 2) the dimensional stabilities of sweetgum and southern pine specimens were all improved by impregnating low molecular weight phenol formaldehyde resin, especially for sweetgum; 3) there were clearly more cracks on exposed ends and surfaces of all treated sweetgum and southern pine specimens than those on control ones, indicating that the low molecular weight phenol formaldehyde resin modification used in this study were not able to improve the anti-cracking properties of sweetgum and southern pine specimens. Generally, the sweetgum was more suitable to be impregnated with low molecular weight phenol formaldehyde resin than southern pine with the procedure described according to dimensional stability and water repellent efficiency, in order to improve the weathering durability

Mechanical and acoustic characteristics of four wood species subjected to bending load

The mechanical and acoustic properties of four commonly used wood species, including poplar (Populus tomentosa), mahogany (Swietenia mahagoni), beech (Fagus orientalis), and Ash (Fraxinus excelsior) wood were investigated through using three-point bending and notched bending tests synchronizing with power spectrum analysis method and fractal dimension theory. The results showed that the bending modulus of elasticity and modulus of rapture changed in the same trend with the order ranging from high to low was ash, beech, poplar and mahogany, successively. The brittle fracture occurred in mahogany samples and ductile fracture raised in the other three wood species. Positive proportional correlation was observed between maximum acoustic pressure and fractal dimension of power spectrum regardless of seeing four wood species as independent or population samples. The failure modes can be identified by amplitude-frequency curve and fractal dimension of power spectrum with following laws: the peak value in amplitude-frequency curve and fractal dimension of power spectrum were relatively higher when a single crack developed at latewood; for crack developed at earlywood, only one peak was observed in power amplitude-frequency curves, and the corresponding fractal dimension of power spectrum was smaller than the that of latewood; in case of failure modes with two cracks developed at earlywood, there are two peaks in amplitude-frequency curve and the fractal dimension of power spectrum was between those of single crack developed at earlywood and latewood. The vibrational properties of the four wood species can be characterized through using power spectrum analysis method and notched bending test method can be used to distinguish the failure modes of samples

Exploiting Spatial-Temporal Context for Interacting Hand Reconstruction on Monocular RGB Video

Reconstructing interacting hands from monocular RGB data is a challenging task, as it involves many interfering factors, e.g. self- and mutual occlusion and similar textures. Previous works only leverage information from a single RGB image without modeling their physically plausible relation, which leads to inferior reconstruction results. In this work, we are dedicated to explicitly exploiting spatial-temporal information to achieve better interacting hand reconstruction. On one hand, we leverage temporal context to complement insufficient information provided by the single frame, and design a novel temporal framework with a temporal constraint for interacting hand motion smoothness. On the other hand, we further propose an interpenetration detection module to produce kinetically plausible interacting hands without physical collisions. Extensive experiments are performed to validate the effectiveness of our proposed framework, which achieves new state-of-the-art performance on public benchmarks.Comment: 16 page

BEST: BERT Pre-Training for Sign Language Recognition with Coupling Tokenization

In this work, we are dedicated to leveraging the BERT pre-training success and modeling the domain-specific statistics to fertilize the sign language recognition~(SLR) model. Considering the dominance of hand and body in sign language expression, we organize them as pose triplet units and feed them into the Transformer backbone in a frame-wise manner. Pre-training is performed via reconstructing the masked triplet unit from the corrupted input sequence, which learns the hierarchical correlation context cues among internal and external triplet units. Notably, different from the highly semantic word token in BERT, the pose unit is a low-level signal originally located in continuous space, which prevents the direct adoption of the BERT cross-entropy objective. To this end, we bridge this semantic gap via coupling tokenization of the triplet unit. It adaptively extracts the discrete pseudo label from the pose triplet unit, which represents the semantic gesture/body state. After pre-training, we fine-tune the pre-trained encoder on the downstream SLR task, jointly with the newly added task-specific layer. Extensive experiments are conducted to validate the effectiveness of our proposed method, achieving new state-of-the-art performance on all four benchmarks with a notable gain.Comment: Accepted by AAAI 2023 (Oral

LDSA: Learning Dynamic Subtask Assignment in Cooperative Multi-Agent Reinforcement Learning

Cooperative multi-agent reinforcement learning (MARL) has made prominent progress in recent years. For training efficiency and scalability, most of the MARL algorithms make all agents share the same policy or value network. However, in many complex multi-agent tasks, different agents are expected to possess specific abilities to handle different subtasks. In those scenarios, sharing parameters indiscriminately may lead to similar behavior across all agents, which will limit the exploration efficiency and degrade the final performance. To balance the training complexity and the diversity of agent behavior, we propose a novel framework to learn dynamic subtask assignment (LDSA) in cooperative MARL. Specifically, we first introduce a subtask encoder to construct a vector representation for each subtask according to its identity. To reasonably assign agents to different subtasks, we propose an ability-based subtask selection strategy, which can dynamically group agents with similar abilities into the same subtask. In this way, agents dealing with the same subtask share their learning of specific abilities and different subtasks correspond to different specific abilities. We further introduce two regularizers to increase the representation difference between subtasks and stabilize the training by discouraging agents from frequently changing subtasks, respectively. Empirical results show that LDSA learns reasonable and effective subtask assignment for better collaboration and significantly improves the learning performance on the challenging StarCraft II micromanagement benchmark and Google Research Football

A Study to Assess the Effect of Asphalt Mixture on the Photocatalytic Performance: A Simulation

This study reports the simulation of a photocatalytic system process and the photocatalytic property of self-cleaning asphalt concrete (SCAC) with four typical asphalt mixtures. A photocatalytic system was simulated based on the pollutant concentration data, which were collected on three types of city roads. Two photocatalytic indexes were proposed to evaluate the photocatalytic property of self-cleaning asphalt concrete: relative decomposition rate and degradation capacity. Four typical asphalt mixtures were prepared with SBS/TiO2 modified bitumen: AC-13a asphalt mixture (AC-13a), AC-13b asphalt mixture (AC-13b), open-graded fraction courses (OGFC), and porous asphalt concrete (PAC). The performance of the SCAC samples was investigated using the cracking resistance, rutting resistance, and moisture susceptibility. The results show that the degradation capacity of CO is approximately 20 times more than that of HC and CO . The air voids of SCAC, which is exposed to ultraviolet rays, contribute to the photocatalytic indexes in the simulated system in this study. In addition, the SBS /TiO2 modified bitumen does not improve the high- or low-temperature property and water stability of SCAC

Strong enhancement of photoresponsivity with shrinking the electrodes spacing in few layer GaSe photodetectors

A critical challenge for the integration of the optoelectronics is that photodetectors have relatively poor sensitivities at the nanometer scale. It is generally believed that a large electrodes spacing in photodetectors is required to absorb sufficient light to maintain high photoresponsivity and reduce the dark current. However, this will limit the optoelectronic integration density. Through spatially resolved photocurrent investigation, we find that the photocurrent in metal-semiconductor-metal (MSM) photodetectors based on layered GaSe is mainly generated from the photoexcited carriers close to the metal-GaSe interface and the photocurrent active region is always close to the Schottky barrier with higher electrical potential. The photoresponsivity monotonically increases with shrinking the spacing distance before the direct tunneling happen, which was significantly enhanced up to 5,000 AW-1 for the bottom contacted device at bias voltage 8 V and wavelength of 410 nm. It is more than 1,700-fold improvement over the previously reported results. Besides the systematically experimental investigation of the dependence of the photoresponsivity on the spacing distance for both the bottom and top contacted MSM photodetectors, a theoretical model has also been developed to well explain the photoresponsivity for these two types of device configurations. Our findings realize shrinking the spacing distance and improving the performance of 2D semiconductor based MSM photodetectors simultaneously, which could pave the way for future high density integration of 2D semiconductor optoelectronics with high performances.Comment: 25 pages, 4 figure