3,573 research outputs found
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Direct and indirect impacts of ethnicity and communication factors on performance ratings
Equilibrium or Simple Rule at Wimbledon? An Empirical Study
We follow Walker and Wooders’(2001) empirical analysis to collect and study a broader data set in tennis, including male, female and junior matches. We find that there is mixed evidence in support of the minimax hypothesis. Granted, the plays in our data pass all the tests in Walker and Wooders (2001). However, we argue that not only the test on equal winning probabilities may lack power, but also the current serve choices may depend on past serve choices, the performance of past serve choices, or the time that the game has elapsed. We therefore examine the role that simple rules may play in determining the plays. For a significant number of top tennis players, some simple low-information rules outperform the minimax hypothesis. By comparing junior players with adult players, we find that the former tend to adopt simpler rules. The result of comparison between female and male players is inconclusiveminimax, learning, low-information
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Regulation of axon repulsion by MAX-1 SUMOylation and AP-3.
During neural development, growing axons express specific surface receptors in response to various environmental guidance cues. These axon guidance receptors are regulated through intracellular trafficking and degradation to enable navigating axons to reach their targets. In Caenorhabditis elegans, the UNC-5 receptor is necessary for dorsal migration of developing motor axons. We previously found that MAX-1 is required for UNC-5-mediated axon repulsion, but its mechanism of action remained unclear. Here, we demonstrate that UNC-5-mediated axon repulsion in C. elegans motor axons requires both max-1 SUMOylation and the AP-3 complex β subunit gene, apb-3 Genetic interaction studies show that max-1 is SUMOylated by gei-17/PIAS1 and acts upstream of apb-3 Biochemical analysis suggests that constitutive interaction of MAX-1 and UNC-5 receptor is weakened by MAX-1 SUMOylation and by the presence of APB-3, a competitive interactor with UNC-5. Overexpression of APB-3 reroutes the trafficking of UNC-5 receptor into the lysosome for protein degradation. In vivo fluorescence recovery after photobleaching experiments shows that MAX-1 SUMOylation and APB-3 are required for proper trafficking of UNC-5 receptor in the axon. Our results demonstrate that SUMOylation of MAX-1 plays an important role in regulating AP-3-mediated trafficking and degradation of UNC-5 receptors during axon guidance
Acute exposure to diesel particulate matter promotes collective cell migration in thyroid cancer cells
Several ecological studies suggest that ambient air pollution is associated with the occurrence of thyroid cancer. In this study, we used certified diesel particulate matter as a proxy for fine particulate matter. Human thyroid cancer cell lines 8505C and TPC-1 were incubated with different concentrations of NIST1650b for 5 days and subjected to functional assays. We found that NIST1650b treatment did not affect short-term cell growth but reduced colony formation at high concentrations. Notably, NIST1650b-treated cells showed altered morphology toward cluster coalescence following treatment. Wound healing assays revealed that leading-edge cells formed protruding tips while maintaining cell-cell adhesion, and a significantly higher ratio of wound closure following treatment at 10 μg/mL was seen in both cell lines. A weak stimulatory effect on transwell cell migration was observed in 8505C cells. Taken together, our results suggest that fine particulate matter induced a coherent phenotype accompanied by augmented collective cell migration in thyroid cancer cells
Measurement of the Near-Bed Turbulence in a Laboratory Surf Zone
Source: ICHE Conference Archive - https://mdi-de.baw.de/icheArchiv
Multi-almost periodicity and invariant basins of general neural networks under almost periodic stimuli
In this paper, we investigate convergence dynamics of almost periodic
encoded patterns of general neural networks (GNNs) subjected to external almost
periodic stimuli, including almost periodic delays. Invariant regions are
established for the existence of almost periodic encoded patterns under
two classes of activation functions. By employing the property of
-cone and inequality technique, attracting basins are estimated
and some criteria are derived for the networks to converge exponentially toward
almost periodic encoded patterns. The obtained results are new, they
extend and generalize the corresponding results existing in previous
literature.Comment: 28 pages, 4 figure
Efficient Quantization-aware Training with Adaptive Coreset Selection
The expanding model size and computation of deep neural networks (DNNs) have
increased the demand for efficient model deployment methods. Quantization-aware
training (QAT) is a representative model compression method to leverage
redundancy in weights and activations. However, most existing QAT methods
require end-to-end training on the entire dataset, which suffers from long
training time and high energy costs. Coreset selection, aiming to improve data
efficiency utilizing the redundancy of training data, has also been widely used
for efficient training. In this work, we propose a new angle through the
coreset selection to improve the training efficiency of quantization-aware
training. Based on the characteristics of QAT, we propose two metrics: error
vector score and disagreement score, to quantify the importance of each sample
during training. Guided by these two metrics of importance, we proposed a
quantization-aware adaptive coreset selection (ACS) method to select the data
for the current training epoch. We evaluate our method on various networks
(ResNet-18, MobileNetV2), datasets(CIFAR-100, ImageNet-1K), and under different
quantization settings. Compared with previous coreset selection methods, our
method significantly improves QAT performance with different dataset fractions.
Our method can achieve an accuracy of 68.39% of 4-bit quantized ResNet-18 on
the ImageNet-1K dataset with only a 10% subset, which has an absolute gain of
4.24% compared to the baseline.Comment: Code: https://github.com/HuangOwen/QAT-AC
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