The Study of Crack Closure Phenomenon Following One Tensile Overload

During the load-controlled high-cycle fatigue test, when the overload was applied, it is shown that from the crack-growth rate (da/dN) versus stress-intensity-factor range (K) curve, the crack-growth rate decreased, following the overload, which indicated the crack-closure phenomenon. The crack-growth-retardation period was observed after the overload. The goal of this study is to investigate the deformation evolution during tensile loading and unloading cycles using neutron diffraction. Neutron diffraction is used to investigate the crack-closure phenomenon by measuring the changes in the elastic-lattice-strain profiles around the fatigue-crack tip in a compact-tension (CT) specimen during tensile loading and unloading cycles. Spatially-resolved-strain measurements were performed to determine the in-plane and through-thickness lattice-strain profiles ahead of the crack tip under a constant tensile load. The strain scanning was repeated under various applied loads ranging from 667 to 6,667 N. Subsequently, an overload at 8,889N was applied. The strain scans repeated. After the overload, large compressive strain fields were observed close to the crack tip, indicative of the crack-closure phenomena. Residual strain/stress mapping using neutron diffraction was also designed to investigate the mechanism of the retardation phenomenon by mapping the changes in the lattice-strain profiles around the fatigue-crack tip in a series of compact-tension (CT) specimens, which were fatigued to various stages through the retardation period after the overload. Following the overload, compressive-strain fields were observed along the loading direction close to the crack tip. As the crack grows out of the retardation period, the residual compressive strains decreased. The results provide a microscopic understanding of the overload effect during cyclic loading. The plastic deformation ahead of a fatigue-crack tip was measured from the diffraction-peak-width changes. The dislocation density was estimated from the fullwidth- half maximum (FWHM) of the diffraction peaks. High dislocation densities around the crack tip were observed after the overload. Furthermore, the plastic-zone size in front of the crack tip was estimated from the diffraction-peak broadening, which showed a good agreement with the calculated result. The plasticity-induced crack-closure phenomenon after an overload was observed. The measured elastic strains and dislocation densities will be compared to the finite-element simulations that are based on an irreversible, hysteretic-cohesive interface model. The experimental and numerical results will be compared and discussed. The deformation in the vicinity of the crack tip was not only studied with the neutron diffraction, but also the x-ray microbeam diffraction. The results help understand the overload effect, which induced a large plastic deformation causing dislocations inhomogeneously arranged around the crack tip. From neutron-diffraction measurements, the anisotropic line broadening was observed in front of the crack tip. Furthermore, Laue patterns, obtained from the microbeam diffraction at different locations near the crack, provide a better spatial resolution and show alternating regions with high and low dislocation densities. Overall, the dislocation density was found to decrease with the distance from the crack tip

Examining Cultural and Technological Change: A Study of Cultural Affordances on WeChat

This study presents qualitative research of the interaction among WeChat, users, and Chinese culture by applying a three-dimensional notion of cultural affordances. The data is collected by conducting 10 semi-structured in-depth interviews, follow-up discussions, and observations, and is analyzed via the grounded theory approach. The study provides preliminary findings that demonstrate the roles of WeChat, users, and Chinese culture in terms of cultural and technological changes. The study also discusses the interactive patterns among three dimensions of cultural affordances and offers possible direction for further study

Isoflavone Content of Soybean Cultivars from Maturity Group 0 to VI Grown in Northern and Southern China

Soybean isoflavone content has long been considered to be a desirable trait to target in selection programs for their contribution to human health and plant defense systems. The objective of this study was to determine isoflavone concentrations of various soybean cultivars from maturity groups 0 to VI grown in various environments and to analyze their relationship to other important seed characters. Forty soybean cultivars were grown in replicated trials at Wuhan and Beijing of China in 2009/2010 and their individual and total isoflavone concentrations were determined by HPLC. Their yield and quality traits were also concurrently analyzed. The isoflavone components had abundant genetic variation in soybean seed, with a range of coefficient variation from 45.01% to 69.61%. Moreover, individual and total isoflavone concentrations were significantly affected by cultivar, maturity group, site and year. Total isoflavone concentration ranged from 551.15 to 7584.07 μg g(−1), and averaged 2972.64 μg g(−1) across environments and cultivars. There was a similar trend regarding the isoflavone contents, in which a lower isoflavone concentration was generally presented in early rather than late maturing soybean cultivars. In spite of significant cultivar × year × site interactions, cultivars with consistently high or low isoflavone concentrations across environments were identified, indicating that a genetic factor plays the most important role for isoflavone accumulation. The total isoflavone concentration had significant positive correlations with plant height, effective branches, pods per plant, seeds per plant, linoleic acid and linolenic acid, while significant negative correlations with oleic acid and oil content, indicating that isoflavone concentration can be predicted as being associated with other desirable seed characteristics

Semi-Supervised Panoptic Narrative Grounding

Despite considerable progress, the advancement of Panoptic Narrative Grounding (PNG) remains hindered by costly annotations. In this paper, we introduce a novel Semi-Supervised Panoptic Narrative Grounding (SS-PNG) learning scheme, capitalizing on a smaller set of labeled image-text pairs and a larger set of unlabeled pairs to achieve competitive performance. Unlike visual segmentation tasks, PNG involves one pixel belonging to multiple open-ended nouns. As a result, existing multi-class based semi-supervised segmentation frameworks cannot be directly applied to this task. To address this challenge, we first develop a novel SS-PNG Network (SS-PNG-NW) tailored to the SS-PNG setting. We thoroughly investigate strategies such as Burn-In and data augmentation to determine the optimal generic configuration for the SS-PNG-NW. Additionally, to tackle the issue of imbalanced pseudo-label quality, we propose a Quality-Based Loss Adjustment (QLA) approach to adjust the semi-supervised objective, resulting in an enhanced SS-PNG-NW+. Employing our proposed QLA, we improve BCE Loss and Dice loss at pixel and mask levels, respectively. We conduct extensive experiments on PNG datasets, with our SS-PNG-NW+ demonstrating promising results comparable to fully-supervised models across all data ratios. Remarkably, our SS-PNG-NW+ outperforms fully-supervised models with only 30% and 50% supervision data, exceeding their performance by 0.8% and 1.1% respectively. This highlights the effectiveness of our proposed SS-PNG-NW+ in overcoming the challenges posed by limited annotations and enhancing the applicability of PNG tasks. The source code is available at https://github.com/nini0919/SSPNG.Comment: ACM MM 202

A quantum-inspired classical algorithm for separable Non-negative Matrix Factorization

Non-negative Matrix Factorization (NMF) asks to decompose a (entry-wise) non-negative matrix into the product of two smaller-sized nonnegative matrices, which has been shown intractable in general. In order to overcome this issue, separability assumption is introduced which assumes all data points are in a conical hull. This assumption makes NMF tractable and is widely used in text analysis and image processing, but still impractical for huge-scale datasets. In this paper, inspired by recent development on dequantizing techniques, we propose a new classical algorithm for separable NMF problem. Our new algorithm runs in polynomial time in the rank and logarithmic in the size of input matrices, which achieves an exponential speedup in the low-rank setting

Hierarchical Reinforcement Learning for Precise Soccer Shooting Skills using a Quadrupedal Robot

We address the problem of enabling quadrupedal robots to perform precise shooting skills in the real world using reinforcement learning. Developing algorithms to enable a legged robot to shoot a soccer ball to a given target is a challenging problem that combines robot motion control and planning into one task. To solve this problem, we need to consider the dynamics limitation and motion stability during the control of a dynamic legged robot. Moreover, we need to consider motion planning to shoot the hard-to-model deformable ball rolling on the ground with uncertain friction to a desired location. In this paper, we propose a hierarchical framework that leverages deep reinforcement learning to train (a) a robust motion control policy that can track arbitrary motions and (b) a planning policy to decide the desired kicking motion to shoot a soccer ball to a target. We deploy the proposed framework on an A1 quadrupedal robot and enable it to accurately shoot the ball to random targets in the real world.Comment: Accepted to 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2022